Environment Impact Assessment (Draft) SRI: Wind Power Generation Project

Transcription

1 Environment Impact Assessment Draft) May 2017 SRI: Wind Power Generation Project Appendices 5 6 Prepared by Ceylon Electricity Board, Ministry of Power and Renewable Energy, Democratic Socialist Republic of Sri Lanka for the Asian Development Bank.

2 This environmental impact assessment is a document of the borrower. The views expressed herein do not necessarily represent those of ADB's Board of Directors, Management, or staff, and may be preliminary in nature. Your attention is directed to the terms of use section on ADB s website. In preparing any country program or strategy, financing any project, or by making any designation of or reference to a particular territory or geographic area in this document, the Asian Development Bank does not intend to make any judgments as to the legal or other status of any territory or area.

3 APPENDIX 5 Noise Modelling Report SRI: Wind Power Generation Project

4 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Executive summary A noise assessment of the proposed 100 MW Mannar Wind Farm has been completed, as a component of the feasibility study, and as an input to the Asian Development Bank ADB) and Ceylon Electricity Board CEB) Environmental Impact Assessment. The wind turbine model will be selected through a tender process, so the noise characteristics and number of wind turbine locations are not decided. As such, the noise impact has been assessed by modelling a selection of illustrative scenarios, with the maximum impact defined by noise limits that are prescribed at sensitive locations in the vicinity of the wind farm. In consultation with ADB and CEB, sensitive locations, or receptors, have been classified as follows: Residential: permanent dwellings and community facilities in surrounding villages, Shell Coast Resort and two new tourist hotels Cabanas) currently under construction, and sleeping quarters where migrant workers are living and are not provided alternative accomodation) Institutional sleeping): Naval camps Institutional: Naval outpost and churches Industrial: Industrial facilities including the fish meal processing factory, and the proposed cucumber hatchery Commercial: Fisher camps Noise limits have been defined in accordance with ADB requirements, referencing IFC World Bank Environmental Health and Safety Guidelines. Based on this guideline and in consultation with ADB, the proposed maximum allowable total noise levels at the identified receptors : At residential locations: LA eq 1 hour) during day-time hours of , and 45 LA eq 1 hour) during night-time hours of At institutional locations where people are sleeping): 55 LA eq 1 hour) during day-time hours of , and 45 LA eq 1 hour) during night-time hours of At institutional locations: 55 LA eq 1 hour) during day-time and night-time hours At industrial and commercial locations: 70 LA eq 1 hour) during day-time hours of , and 60 LA eq 1 hour) during night-time hours of Wind farm noise level is typically modelled at receptors without consideration of any potential additive effects of ambient background noise. As such, a 1 allowance for the additive effect of wind farm noise plus background noise has been assumed in this assessment, to estimate the total noise level, in the absence of reliable measured background noise data. These noise limits will potentially be revised after background noise measurements are completed in June 2017, depending on if background noise levels exceed these limits Scenarios A1, A2 and A3 outline the potential noise impact of all 39 wind turbine locations for a range of wind turbine noise power curves. During unconstrained operation of the wind farm under these scenarios, predicted noise levels exceed the night-time limits and in some cases day-time limits) at receptors in close proximity to wind turbines, including the Shell Coast Resort, two Investment Cabanas, and naval camps grouped along the coastline. v

5 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Scenarios B and C have been developed as better scenarios that illustrate a wind turbine layout of 31 x 3.3 MW wind turbines that is compliant with specified noise limits, through use of operational constraints on wind turbine noise output settings, which can be varied based on time of day and season and potentially wind speed and direction). There is an estimated 8.5% and 4.3% reduction respectively in annual energy output based on the constrained operation modelled under these scenarios. Scenario C assumes migrant labourers residing near WT31 can be relocated 1 and thus fewer wind turbines operate in a noise constrained mode. As a consequence of this assessment, Entura provides the following recommendations: 1. Wind turbines supplied for the project must be able to operate in a noise constrained mode, in order to meet the seasonal day/night noise limit requirements defined by this report. The noise constrained operation will be implemented automatically as wind speed increases, with the specific noise mode selected to ensure the project is in compliance with the relevant seasonal day/night noise limits, based on outputs from noise modelling. 2. Wind turbine noise should have no tonal component unless incorporated into the assessment as a penalty. 3. During the tender process, the wind turbine supplier must propose a wind turbine model and wind farm layout subset of 39 locations) that complies with the prescribed limits at relevant receptors. Any requirements for reduced noise output and hence reduced power output) must be quantified, and a specific operational regime will be determine from the outputs of noise modelling. 4. Background noise measurements to be completed in June 2017 may facilitate noise limits to be updated. However bidders are likely to have finalised wind turbine model and location selection by that time, and any changes to noise limits will primarily be useful for lifting noise constraints at the selected locations. 5. CEB should obtain further information on the use of naval camps and migrant labour quarters used for sleeping, and investigate the possibility of relocating facilities and/or compensating to facilitate the lifting of some of the noise constraints at these locations. 6. Compliance with noise limits defined in the Environmental Impact Assessment will require CEB to commit to implementing operational constraints on the wind farm, which will reduce noise and energy output of the wind farm. 1 CEB is working on the relocation option and having consultations with parties that could be potentially affected. vi

6 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Contents 1. Introduction Objectives Noise assessment methodology Background noise measurements Compliance requirements Sri Lankan regulations Compliance requirements Asian Development Bank Wind turbine noise constrained operation 5 2. Noise model inputs Wind turbine layout Wind turbine noise output Receptor locations Model parameters Predicted noise levels Scenario A1: 39 x generic wind turbines at Scenario A2: 39 x generic wind turbines at Scenario A3: 39 x generic wind turbines at Scenario B: 31x wind turbines in noise constrained mode Summary and recommendations References 17 Appendices A Locations and results A.1 Wind turbine locations A.2 Wind turbine noise curve A.3 Receptors B Noise contour maps List of figures Figure 2.1: Wind turbine layout all locations, and Scenario B) 8 List of tables Table 1.1: March 2017 background noise measurement results ) 2 vii

7 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Table 2.1: Reference octave band spectrum 9 Table 2.2: Example noise output curves 9 Table 2.3: Noise model parameters 10 Table 3.1: Annual energy loss as a percentage of annual energy output for Scenario B from draft energy report) 13 viii

8 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Introduction 1.1 Objectives Entura has been engaged by the Asian Development Bank ADB) to model the noise output of the Mannar Wind Farm. Modelling of the following scenarios is required to achieve the objectives of the project proponent Ceylon Electricity Board - CEB) and ADB: 1. For the Environmental Impact Assessment EIA) 2. For the feasibility study and energy production estimates 3. After background measurements have been obtained approximately June 2017) This report describes the noise limits, based on relevant standards and guidelines, that constitute the maximum permissible noise impact from the project, consisting of up to 39 wind turbine locations. Because of the nature of the tender process, the final wind turbine model and final wind turbine layout are not decided. As such, this report also provides a typical 100 MW project design using only 31 wind turbine locations, that is provided to demonstrate compliance with the maximum permissible noise impact. 1.2 Noise assessment methodology The wind farm noise assessment consists of the following key stages: Identification of noise sensitive locations within the vicinity of the wind farm, typically by first considering where noise levels exceed 35 LA 90. 4] Identification of a limited number of selected locations where background noise monitoring should be undertaken, that are deemed to be representative of noise receptor locations around the wind farm. Derive noise limits at noise receptor locations, based on fixed limits Predict wind farm noise output and assess wind farm compliance this report) Aquire background noise monitoring and update the assessment approximately June 2017). 1.3 Background noise measurements Background noise measurements have been obtained at locations in the vicinity of the wind farm during two separate measurement programs: 1. As an input to the project s Initial Environmental Examination IEE) report. The Industrial Technology Institute of Sri Lanka was engaged by CEB to acquire background noise measurements at the following 8 locations, for a period of 24 hours at each location, from 5-8 October 2015: a. Thoddaveli Water Board Office b. Mr Mariyadas c. Shell Coast Resort 1

9 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 d. Julian Dias, Pesale e. House, Nadukudda f. Bishop house, Mannar g. Old pier Navy camp), Thalimannar h. House, Tahlimannar 2. The National Engineering Research Development Centre of Sri Lanka was engaged by ADB to acquire background noise measurements at 6 locations, for a period of 48 hours at each location, from 6-12 March 2017: a. Sea cucumber drying compound near WT1 b. Kalutota Cabanas between WT7&8 c. Fishing camp near WT7&8, sea cucumber hatchery is 135 m east from this point d. Shell Coast Resort between WT10&11 e. Kalutota Cabanas between WT17&18 f. Fishing camp near WT30&31 The duration of each of these measurement programs is relatively short in comparison to the minimum 2-3 week duration required by international standards for wind farm background noise monitoring. A longer duration of measurements is necessary because measurements are heavily influence by factors such as wind speed and direction and the specific social and environmental conditions found outside during the measurement period. Further, quality documentation for the second program of measurements has not been made available, and the uncertainty associated with these measurements cannot be determined. Given the above factors, these measurements provide a preliminary indication of ambient background noise at measurement locations, but are insufficient for setting noise limits based on background noise. High quality measurement for a duration of 2-3 weeks will be obtained in June 2017 at these same locations, and can be used to update results. These measurements will be acquired by a specialised acoustic consultant, experienced in the application of international guidelines on wind farm noise measurements. Results from the 6-12 March 2017 measurement program are presented in Table 1.1. Table 1.1: March 2017 background noise measurement results ) L Aeq L 90 Ave Min Max Ave Min Max Sea cucumber drying compound near WT1 Kalutota Cabanas between WT7&8 Fishing camp near WT7&8 Shell Coast Resort between WT10&11 Kalutota Cabanas between WT17&18 Fishing camp near WT30&

10 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Compliance requirements Sri Lankan regulations The Sri Lankan Urban Development Authority has confirmed in a letter 1] to the Sri Lankan Sustainable Energy Authority that the project site is to be classified an Industrial Area for application of the National Environmental Noise Control) Regulations 1]. These regulations require the noise output from the wind farm to be within the greater of the following, at the of the land in which any source of noise is located : 70 LA eq ) during the day defined as between 0600 and 1800, 60 LA eq ) during the night defined as between 1800 and 0600 Measured Background Noise Level +5 Noise limits are expressed as LA eq over an unspecified time period. Background noise level is defined as LA 90, and measurement time intervals are not specifically defined. CEB is seeking clarification on the definition of the at which these noise limits should be applied, the overall site or the of each individual parcel of land on which a wind turbine is located. 1.5 Compliance requirements Asian Development Bank ADB has indicated the following guidelines are to be followed for noise assessment: 1. Local regulatory requirements to be adhered to where they are more stringent) 2] 2. IFC General EHS Guidelines 3] 3. World Bank Group, Environmental, Health and Safety Guidelines for Wind Energy, August 7, ] and reference documents below for some aspects of the assessment) a) The Assessment and Rating of Noise from Wind Farms, ETSU-R-97, September ] b) A Good Practice Guide to the Application of ETSU-R-07 for the Assessment and Rating of Wind Turbine Noise, IAO, May 2013 and supplementary guidance) 6] With the site classified as an industrial area, compliance with local regulatory requirements is achievable for even a relatively small around each individual wind turbine, such as the 150 m x 150 m land parcels CEB are acquiring. In addition to local regulatory requirements, fixed noise limits defined by the IFC General EHS Guidelines 3] are applicable to the project, with limits at receptors as follows, with day defined as between 0700 and 2200, and night defined as between 2200 and 0700: for residential, institutional and educational facilities, 55 LA eq 1 hour) during the day, 45 LA eq 1hour) during the night or for industrial and commercial facilities, 70 LA eq 1 hour) day and night or measured background noise +3 LA eq 1hour) 3

11 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 The following clarifications are offered on how these limits will be applied to the Mannar wind project: Background noise suitable for deriving noise limits at sensitive locations has not yet been acquired. As such, the noise predictions presented in this report are compared with the IFC General EHS Guideline fixed limits as defined above. Higher daytime limits shall apply between the hours of 0600 and 1800, consistent with Sri Lankan regulations, and more stringent than IFC General EHS guidelines 3]. The IFC General EHS Guideline noise limits refer to the total noise level at sensitive locations, considering the combined ambient background noise and wind farm noise. For the purpose of modelling wind farm noise output, the typical assumption is that wind farm noise is the dominant noise source, and that ambient background noise at a similar or lower level than wind farm noise output does not materially add to the total noise level. That said, there is a potential increase due to the summation of the sound pressure levels, which in theory is a maximum of 3 for similar sound pressure levels, but in practice typically adds very little to the total noise level when wind farm noise output is high. For this assessment, Entura will assume that ambient background noise adds 1 to the modelled wind farm noise level. CEB will ultimately need to confirm total noise level at receptors through post-construction measurements. Fisher camps and tea kiosks along the coast are only occupied from October through to March, and will only be considered receptors for that period. Naval outposts are locations where it is assumed that naval personnel are stationed but are not sleeping. Therefore, it can be considered an Institutional location, but with day-time limits applicable at night-time. ADB s social safeguard consultant has noted the church at Nadukudda is a small church, which is used by fishermen to conduct their prayers for a few minutes before they set out for fishing. Except for occasional masses conducted by a priest coming from outside which would last for 1-2 hours, the church is rarely used for any mass gatherings or regular religious activities. Therefore, it can be considered an Institutional location, but with day-time limits applicable at night-time. Receptors will be classified as follows: o o o o o Residential: permanent dwellings and community facilities in surrounding villages, Shell Coast Resort and two new tourist hotels Cabanas) currently under construction, and sleeping quarters where migrant workers are living and are not provided alternative accomodation) Institutional sleeping): Naval camps Institutional: Naval outpost and churches Industrial: Industrial facilities including the fish meal processing factory, and the proposed cucumber hatchery Commercial: Fisher camps ADB has further specified that for reasons of daytime amenity, the day-time limit shall be adjusted to for the local villages, homes, churches, tourist facilities and sleeping quarters where migrant workers are living. 4

12 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Consequently, the proposed allowable total noise levels for the Mannar wind project at receptors, for this assessment are as follows with the maximum allowable wind farm noise level 1 lower): At residential locations: LA eq 1 hour) during day-time hours of , and 45 LA eq 1 hour) during night-time hours of At institutional locations sleeping): 55 LA eq 1 hour) during day-time hours of , and 45 LA eq 1 hour) during night-time hours of At institutional locations: 55 LA eq 1 hour) during day-time and night-time hours At industrial and commercial locations: 70 LA eq 1 hour) during day-time hours of , and 60 LA eq 1 hour) during night-time hours of These noise limits will potentially be revised after background noise measurements have been acquired during the high wind season, during May to September, depending on if background noise levels exceed or are close to these limits. ADB has indicated that wind turbine noise should have no tonal component unless incorporated into the assessment as a penalty. It is unusual for wind turbines noise output to have a tonal component, and it is not typically considered during modelling. Compliance with limits will be verified through: Pre-construction modelling of wind farm noise output this report Post-construction measurement of ambient noise with the wind farm operating 1.6 Wind turbine noise constrained operation The noise output of a wind farm can be controlled by several means: Design features: The wind turbines supplied for the project may contain design features, such as aerodynamic modifications to the blade to permanently reduce the noise output of a wind turbine model. There may be an associated cost to include such additional features, and there may or may not be an impact on the power curve / energy output. Operational modes: Modern wind turbines are equipped with programmable operational modes that can reduce the noise output of the wind turbine on-demand. There is typically an associated reduction in power output, which increases as the noise output decreases. These operational modes of reduced noise ouput are triggered automatically as wind speed, power output and consequently noise output) increase. The operational modes are programmed for each wind turbine based on time of day and season. Shut down: In extreme cases, wind turbines might be shut down turned off) under certain conditions to eliminate noise output. This can also be programmed, based on wind speed and time of day/season. 5

13 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Noise model inputs 2.1 Wind turbine layout The following scenarios are considered in this report: A. The 39 wind turbine 2 layout developed by CEB and provided to Entura on 30 November 2016, with the following wind turbine characteristics: 1. Wind turbine noise level of a typical 3MW wind turbine) 2. Wind turbine noise level of a typical 3 MW wind turbine) 3. Wind turbine noise level of a typical noise constrained 3 MW wind turbine) B. A subset of 31 wind turbines for a MW wind farm consisting of 3.3 MW wind turbines with a 117 m rotor diameter, as per the energy production report 12]. o o o For this layout, WT 27 and WT 28 have been removed, as instructed by CEB. The following five 5) locations have been removed due to their potential to generate relatively high noise levels at nearby receptors: WTs 4, 7, 8, 17, 22, 31. The remaining 31 locations are operating in noise modes ranging from the standard unconstrained version, to the noise constrained version of the wind turbine. C. An example alternate subset of 31 wind turbines, assuming that migrant worker sleeping quarters located between WT30 and WT31 can be relocated. Relative to Scenario B, WT31 is reinstated, WT5 disregarded, and noise constraints on WT29, 30, 32 and 33 can be lifted. Wind turbine location coordinates are listed in Appendix A.1, and displayed in Figure 2.1. Due to ongoing land acquisition and micro-siting, there are likely to be changes to these wind turbine locations. The impact of such changes may require an update of this noise assessment. 2 For this layout, locations of WT 27 and WT 28 are still included, although they will not be used due to potential disturbance on a communication facility as instructed by CEB. 7

14 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Scenario C includes WT31) Scenario C excludes WT5) Figure 2.1: Wind turbine layout 2.2 Wind turbine noise output The noise model based on ISO requires the wind turbine noise output to be represented by Octave Band data. For the generic wind turbine examples, Entura has used octave band data from a reputed manufacturer s 11] wind turbine, scaled to achieve the maximum broadband sound power levels detailed in Table

15 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Table 2.1: Reference octave band spectrum Octave band centre frequency Hz) Generic wind turbine Sound power level at hub height A) Generic wind turbine Generic wind turbine Generic wind turbine Broadband Noise Noise output vs. wind speed data for a selection of typical wind turbines that might be employed for this project are shown in Table 2.2. Different manufacturers have different methods for specifying noise constrained modes, but typically it is presented as a reduced noise output and hence reduced power output) as wind speed increases, such as shown in Table A.3 for the generic wind turbine. Table 2.2: Example noise output curves Hub height wind speed m/s) Vestas V MW Vestas V MW blades with serrated training edge) Siemens SWT GE Senvion 3.2M122NES

16 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Receptor locations The study area can be defined as the area around the wind farm where preliminary modelling suggests LA90 noise level will exceed 35 A) at up to 10 m/s wind speed from the proposed wind turbines 4]6]. For the Mannar Wind Power Project, this is equivalent to a distance of approximately 2 km from the wind turbines. Within this area a list of 115 receptor locations has been prepared, and is provided in Appendix A.3. This list has been prepared by ADB s environmental and social safeguard consultants, with some additional building locations that Entura has identified through observations of Google Earth aerial imagery. 2.4 Model parameters Wind farm noise predictions have been derived using the software package DNG-GL Windfarmer , which is based on the ISO standard, with input parameters set as required by relevant guidelines 5]6] for this assessment. Model parameters are listed in Table 2.3. Table 2.3: Noise model parameters Parameter Noise model Ground effect Atmospheric attenuation Calculation grid spacing Height above ground level for noise mapping Atmosphere Topographic corrections Air absorption parameters Setting Complex ISO9613) General Ground factor of G=0.5 Octave spreading 10 m 4 m 10 C temperature, 70% humidity, kpa atmospheric pressure None Octave band mid frequency Hz) k 2k 4k 8k Ground effect factor of G=0.5 is selected as a conservative model input. The IOA guideline 6] notes that a soft ground factor G=1.0) should not be used, and a ground factor of G=0.0 is commonly used, and provides robust predictions in most situations, however can overpredict noise levels. Therefore, G=0.5 is recommended. A receiver height of 4 m is recommended, as it has the effect of reducing the potential oversensitivity of the calculation to ground factor compared to lower receiver heights, and the selected atmospheric conditions represent a reasonably low level of air absorption. International studies show this prediction model with the selected input parameters provides a reliable representation of the upper noise levels expected in practice. 10

17 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Predicted noise levels The predicted maximum noise levels for the different scenarios are presented in Appendix A.3. A discussion of the results is presented below. Scenarios A and B are compared against noise limits that include residential classification for fisher camps where migrant workers are living. Scenario C 3 assumes these workers are to be provided with accommodation elsewhere. 3.1 Scenario A1: 39 x generic wind turbines at Scenario A1 is for illustrative purposes, showing the predicted noise levels from a wind turbine model, using all 39 wind turbine locations. Noise limits are exceeded at many receptor locations, and significant operational controls would be required to reduce noise levels at receptors below the limits specified in Table A Scenario A2: 39 x generic wind turbines at Scenario A2 is similar to Scenario A1, but with predicted noise levels at receptor locations reduced by slightly less than 2 relative to Scenario A1. As with Scenario A1, significant operational controls would be required to reduce noise levels at all receptors below the limits specified in Table A.1. This scenario complies with noise limits at nearby villages without operational constraints. In Entura s opinion, is an appropriate maximum noise level for the wind turbines, and this specification permits a good range of wind turbine models with noise control 4 ) that can be considered for the project. 3.3 Scenario A3: 39 x generic wind turbines at Scenario A3 is representative of a wind turbine operating in a highly constrained mode at low noise level. Scenario A3 is significantly closer to achieving full compliance with the specified noise limits than either Scenarios A1 or A2. However maximum noise level exceeds noise limits at the following locations: 3 CEB is working on the relocation option and having consultations with parties that could be potentially affected. 4 As additional 2 turbines will be removed due to potential disturbance on a communication facility, and 37 numbers of turbine could be potentially operated in compliance with speficied noise limits if the wind farm operated with a highly constrained mode. 11

18 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 The naval camp between WT4 and WT5. It is recommended that CEB investigate the use of these buildings at the naval camp, to confirm whether or not the 45 night-time limit is appropriate. The migrant labour quarters between WT7 and WT8. It is recommended that CEB confirm when these buildings will be occupied and when the occupants will be sleeping, to confirm whether or not the 45 night-time limit is appropriate. CEB should investigate possible alternative accommodation arrangements. The Kaluthota Finance Hotel under construction), adjacent WT8. The Kaluthota Finance Hotel under construction) St Jude Road, adjacent WT17 Vadi between WT30 and 31. It is recommended that CEB investigates the use of these buildings by migrant labourers, and possible alternative accommodation arrangements as assumed for Scenario C). 3.4 Scenarios B and C: 31x wind turbines in noise constrained mode Scenario B is a layout of 31 wind turbines, with some wind turbines operating in a constrained mode which differs from day to night) as listed in Table A.2, in order to meet the prescribed noise limits. The results are within the prescribed day-time and night-time limits at all locations. It is noted that to comply with night-time limits in Scenario B, the following locations are only compliant when wind turbine shut-down at night is assumed: The naval camp between WT4 and WT5. It is recommended that CEB investigates the use of these buildings at the naval camp, to confirm whether or not the 45 night-time limit is appropriate. Vadi and naval observation unit between WT30 and 31. It is recommended that CEB investigates that use of these buildings by migrant labourers, and possible alternative accommodation arrangements. Scenario C assumes such relocation of migrant labourers is achievable 5, and therefore location WT31 is used instead of WT5. Background measurements to be completed in June 2017 may result in increased noise limits that facilitate compliance. Scenarios B and C demonstrate that a 100 MW wind farm is feasible using a likely wind turbine model and a subset of 31 of the 39 available locations provided the impacts on receptors are managed by CEB through appropriate operational constraints. Entura has modelled the impact on energy output of the constrained operation that generates the maximum noise levels listed in Table A.1, and the results are displayed in Table 3.1. A 2% loss is included for night-time shutdown of WT5 and WT 30 during October to April) to make Scenario B fully compliant with noise limits.) 5 CEB is working on the relocation option and having consultations with parties that could be potentially affected. 12

19 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Table 3.1: Annual energy loss as a percentage of annual energy output for Scenarios B and C from draft energy report) Scenario May to September October to April Day Night Day Night Total B 0.3% 6.4% 0.1% 1.7% 8.5%* C 0.1% 3.2% 0.0% 1.0% 4.3% * Including night-time shutdown of WT5 and WT30 equal to 2% on annual energy output 13

20 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Summary and recommendations The number of wind turbine locations and specific wind turbine model for the proposed 100 MW project will only be known after the conclusion of the tender process. As such, the noise impact of the proposed wind farm can only be modelled using likely scenarios, and is ultimately defined by the maximum noise limits defined in this report. Scenarios A1, A2 and A3 presented in this report are illustrative, but do not represent likely wind farm configurations as they exceed 100 MW installed capacity. Scenarios B and C consisting of 31 x 3.3 MW wind turbines and including constrained operation, are better options of a 100 MW wind farm. During unconstrained operation of the wind farm with all wind turbine locations represented by Scenarios A1 and A2), predicted noise levels exceed the night-time limits and in some cases day-time limits) at receptors in close proximity to wind turbines, including the Shell Coast Resort, two Investment Cabanas, sea cucumber hatchery, and many of the naval observations units and naval camps) and Vadi fisher camps, and fishermen s restrooms) grouped along the coastline. For Scenarios B and C, constrained output results in compliance with noise limits, and estimated losses in annual energy output of 8.5% and 4.3% respectively, compared to operating unconstrained by noise limits. The significantly reduced loss of Scenario C results from assuming migrant labourers residing near WT31 can be relocated 6. As a consequence of this assessment, Entura provides the following recommendations: Wind turbines supplied for the project must be able to operate in a noise constrained mode, in order to meet the seasonal day/night noise limit requirements defined by this report. The noise constrained operation will be implemented automatically as wind speed increases, with the specific noise mode selected to ensure the project is in compliance with the relevant seasonal day/night noise limits, based on outputs from noise modelling. Wind turbine noise should have no tonal component unless incorporated into the assessment as a penalty. During the tender process, the wind turbine supplier must propose a wind turbine model and wind farm layout subset of 39 locations) that complies with the prescribed limits at relevant receptors. Any requirements for reduced noise output and hence reduced power output) must be quantified, and a specific operational regime will be determine from the outputs of noise modelling. Background noise measurements to be completed in June 2017 may facilitate noise limits to be updated. However bidders are likely to have finalised wind turbine model and location selection by that time, and any changes to noise limits will primarily be useful for lifting noise constraints at the selected locations. 6 CEB is working on the relocation option and having consultations with parties that could be potentially affected. 15

21 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 CEB should obtain further information on the use of naval camps and migrant labour quarters used for sleeping, and investigate the possibility of relocating facilities and/or compensating to facilitate the lifting of some of the noise constraints at these locations. Compliance with noise limits defined in the Environmental Impact Assessment will require CEB to commit to implementing operational constraints on the wind farm, which will reduce noise and energy output of the wind farm. 16

22 Mannar Wind Power Project - Noise assessment Revision No: 3 E May References 1] Letter from Urban Development Authority to Sustainable Enercon Authority, 2/5/2017, Request to Declare the Energy Development Area of Mannar Wind Power Project as an Industrial Zone, File No: J/PR/SED/60 2] National Environmental Noise Control) Regulations No ,The National Environment Act, No. 47 of 1980, 3] IFC General EHS Guidelines 4] World Bank Group, Environmental, Health and Safety Guidelines for Wind Energy, August 7, and reference documents below for some aspects of the assessment) 5] The Assessment and Rating of Noise from Wind Farms, ETSU-R-97, September ] A Good Practice Guide to the Application of ETSU-R-07 for the Assessment and Rating of Wind Turbine Noise, IAO, May 2013 and supplementary guidance) 7] Proposed 100 MW Mannar Wind Power Project Initial Environmental Examination Report, CEB, April ] Report on Feasibility Study on 100 MW Semi-Dispatchable Wind Farm in Mannar Island, Sri Lanka, CEB, May ] Monitoring of Background Noise Levels and Existing Noise Levels, Existing Vibration levels Report No:CP , ITI, October ] General Specification, V /3.45 MW 50/60 Hz, V10, 10/7/ ] V /3.45MW Third Octaves according to General Specification, _V03 12] Mannar wind power project, wind resource, wind turbine suitability and energy production report, Entura, E TR-01 13] Guidelines for Community Noise, World Health Organisation,

23 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Appendices 19

24 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 A Locations and results A.1 Wind turbine locations Table A.1: WTG layout Turbine number X coordinate Y coordinate Scenario B noise mode ) Scenario C noise mode ) Day Night Day Night WT 1 373, , WT 2 373, , WT 3 373, , WT 4 372, , WT 5 372, , WT 6 372, , WT 7 371, , WT 8 371, , WT 9 371, , WT , , WT , , WT , , WT , , WT , , WT , , WT , , WT , , WT , , WT ,979 1,000, WT ,649 1,000, WT ,309 1,000, WT ,006 1,000, WT ,476 1,000, WT ,211 1,001, WT ,953 1,001, WT ,684 1,001, WT ,415 1,001, WT ,144 1,001, WT ,873 1,001, WT ,605 1,001, WT ,343 1,001, WT ,043 1,002, WT ,772 1,002,

25 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Turbine number X coordinate Y coordinate Scenario B noise mode ) Scenario C noise mode ) WT , , WT , , WT , , WT , , WT , , WT ,503 1,000, Note: Scenarios A1, A2, A3 are fixed at 108.5, and Coordinate reference: WGS84 / UTM zone 44P A.2 Wind turbine noise curve Table A.2: Wind turbine annual energy loss as a percentage of wind turbine annual energy output for the different operational modes wind turbine noise mode Annual Energy Loss % % % % Table A.3: Example wind turbine noise curve, wind turbine Wind speed at hub height m/s) Frequency Energy generation distribution Sound power level at hub height A) % 0.0% % 0.4% % 1.5% % 3.5% % 6.5% % 8.9% % 9.8% % 9.7% % 11.8% % 14.1% % 12.4% % 9.4% % 11.8%

26 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 A.3 Receptors Table A.4: Receptor list and noise predictions, Scenarios A and B Nearby WT ID Receptor name Easting m) Northing m) Distance to nearest wind turbine m) Limit Receptor noise night), including +1 assumed background contribution LA eq ) Scenario Day Night A1 A2 A3 B 1 Thalvupadu Thottavelly-Thalvupadu Rd 3 N1 Thoddaveli Water Board Office N2 Mr Mariyadas Konniankuduiruppu village and church Konniankuduiruppu Konniankuduiruppu Konniankuduiruppu Konniankuduiruppu WT 1 10 Naval observation unit WT 1 11 Vadi Vadi Vadi Vadi Vadi Vadi Vadi Vadi WT 1 and 2 19 Industrial unit fish meal manufacturing company) 20 Industrial unit fish meal manufacturing company) 21 Industrial unit fish meal manufacturing company) 22 Industrial unit fish meal manufacturing company) 23 Industrial unit fish meal manufacturing company) estimated location

27 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 WT 4 and 5 24 Naval Camp Naval Camp Naval Camp Naval Camp Naval Camp building) Naval Camp building) WT 7 and 8 30 Vadi Vadi Vadi Vadi Vadi Naval observation unit Vadi Vadi Sea cucumber hatchery Vadi Vadi Vadi Vadi Fishermen s rest room Tea kiosk Vadi Vadi Residential unit - Konniankuduiruppu 48 Residential unit - Konniankuduiruppu 49 Residential unit - Konniankuduiruppu 50 Residential unit - Konniankuduiruppu WT 8 and 9 51 Kaluthota Finance Hotel under construction) - 52 Kaluthota Finance Hotel under construction) - 53 Kaluthota Finance Hotel under construction) - 54 Kaluthota Finance Hotel under construction) WT 9 and Vadi WT 10 and Vadi Vadi

28 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Vadi WT 10 and Shell Coast Hotel Shell Coast Hotel Shell Coast Hotel Shell Coast Hotel Shell coast resort B WT Naval observation unit WT Vadi WT Naval observation unit Olaiththoduvai Olaiththoduvai Church Olaiththoduvai School Residential unit - Uvary village and church 71 Residential unit - Uvary village and church 72 Residential unit - Uvary village and church WT Kaluthota Finance Hotel under construction) St Jude Road - 74 Kaluthota Finance Hotel under construction) St Jude Road - 75 Kaluthota Finance Hotel under construction) St Jude Road - 76 Kaluthota Finance Hotel under construction) St Jude Road - 77 Kaluthota Finance Hotel under construction) St Jude Road WT 22 and Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda WT 22 and Tea kiosk Tea kiosk

29 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Fishermen s rest room Church WT Naval observation unit Nadukudda N5 House, Naddukkuda Residential unit - Nadukuda WT 30 and Vadi Vadi Vadi Vadi Naval observation unit WT 32 and Vadi Vadi Vadi Vadi Vadi WT Vadi Vadi Vadi Vadi Residential unit - KeelaiyanKuduiruppu 107 Residential unit - KeelaiyanKuduiruppu 108 Residential unit - KeelaiyanKuduiruppu 109 Residential unit - KeelaiyanKuduiruppu Navy Camp - Selvary WT Vadi N4 Julian Dias, Pesale N6 Bishop House N7 Old pier Navy camp)thalimannar N8 House Thalimannar Coordinate reference: WGS84 / UTM zone 44P Yellow shading: > lower night limit, red shading: > upper day/night limit 26

30 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 Table A.5: Noise predictions, Scenario C Nearby WT ID Receptor name Easting m) Northing m) Distance to nearest wind turbine m) Limit Receptor noise, including +1 assumed background contribution LA eq ) Scenario Day Night Day Night 1 Thalvupadu Thottavelly-Thalvupadu Rd 3 N1 Thoddaveli Water Board Office N2 Mr Mariyadas Konniankuduiruppu village and church Konniankuduiruppu Konniankuduiruppu Konniankuduiruppu Konniankuduiruppu WT 1 10 Naval observation unit WT 1 11 Vadi Vadi Vadi Vadi Vadi Vadi Vadi Vadi WT 1 and 2 19 Industrial unit fish meal manufacturing company) 20 Industrial unit fish meal manufacturing company) 21 Industrial unit fish meal manufacturing company) 22 Industrial unit fish meal manufacturing company) 23 Industrial unit fish meal manufacturing company) estimated location WT 4 and 5 24 Naval Camp Naval Camp Naval Camp Naval Camp

31 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Naval Camp building) Naval Camp building) WT 7 and 8 30 Vadi Vadi Vadi Vadi Vadi Naval observation unit Vadi Vadi Sea cucumber hatchery Vadi Vadi Vadi Vadi Fishermen s rest room Tea kiosk Vadi Vadi Residential unit - Konniankuduiruppu 48 Residential unit - Konniankuduiruppu 49 Residential unit - Konniankuduiruppu 50 Residential unit - Konniankuduiruppu WT 8 and 9 51 Kaluthota Finance Hotel under construction) - 52 Kaluthota Finance Hotel under construction) - 53 Kaluthota Finance Hotel under construction) - 54 Kaluthota Finance Hotel under construction) WT 9 and Vadi WT 10 and Vadi Vadi Vadi WT 10 and Shell Coast Hotel Shell Coast Hotel

32 Mannar Wind Power Project - Noise assessment Revision No: 3 E May Shell Coast Hotel - 62 Shell Coast Hotel Shell coast resort B WT Naval observation unit WT Vadi WT Naval observation unit Olaiththoduvai Olaiththoduvai Church Olaiththoduvai School Residential unit - Uvary village and church 71 Residential unit - Uvary village and church 72 Residential unit - Uvary village and church WT Kaluthota Finance Hotel under construction) St Jude Road - 74 Kaluthota Finance Hotel under construction) St Jude Road - 75 Kaluthota Finance Hotel under construction) St Jude Road - 76 Kaluthota Finance Hotel under construction) St Jude Road - 77 Kaluthota Finance Hotel under construction) St Jude Road WT 22 and Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda WT 22 and Tea kiosk Tea kiosk Fishermen s rest room Church WT Naval observation unit Nadukudda

33 Mannar Wind Power Project - Noise assessment Revision No: 3 E May N5 House, Naddukkuda Residential unit - Nadukuda WT 30 and Vadi Vadi Vadi Vadi Naval observation unit WT 32 and Vadi Vadi Vadi Vadi Vadi WT Vadi Vadi Vadi Vadi Residential unit - KeelaiyanKuduiruppu 107 Residential unit - KeelaiyanKuduiruppu 108 Residential unit - KeelaiyanKuduiruppu 109 Residential unit - KeelaiyanKuduiruppu Navy Camp - Selvary WT Vadi N4 Julian Dias, Pesale N6 Bishop House N7 Old pier Navy camp)thalimannar N8 House Thalimannar

34 Mannar Wind Power Project - Noise assessment Revision No: 3 E May 2017 B Noise contour maps Attached: E P GIS Scenario B - 31 WTGs - 1 of 2 Rev 1 E P GIS Scenario B - 31 WTGs - 2 of 2 Rev 1 E P GIS Scenario A1-39 WTGs - 1 of 2 E P GIS Scenario A1-39 WTGs - 2 of 2 E P GIS Scenario A2-39 WTGs - 1 of 2 E P GIS Scenario A2-39 WTGs - 2 of 2 E P GIS Scenario A3-39 WTGs - 1 of 2 E P GIS Scenario A3-39 WTGs - 2 of 2 31

35 Title Client Mannar Wind Power Project Noise Assessment Scenario A1-39 WTGs Asian Development Bank Client Map no. E P GIS of 2) Date 12/04/2017 Drawn Toby Dove Reviewed Brendon Bateman Approved Andrew Wright Legend! WTG Receivers # Single Cluster Noise assessment Noise contours 5 ) Map: "\\hydrotasm ania\consult$\project\consultdm \E305xxx\E3056xx\E305674\P511697\GIS\P511697_GIS04 Noise Contours\E P GIS Scenario A1-39 WTGs.mxd" exported on 12/04/2017 3:22:45 PM by uziallog Data sources): Esri, HERE, DeLorme, Mapm yindia, OpenStreetMap contributors Esri, H ER E, D elorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CN ES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User C om munity ! Enlargement 1!! 88! Enlargement 2! 89!! Enlargement 3 66!!!!! !! ! 64 73! 74 75! ! 5 Enlargement 4! ! Enlargement ! ! Enlargement Notes Scale ,000 2,000 3,000 m Locality map 54+ A3 INDIA Receiver IDs shown refer to Mannar Wind Power Project, Noise assessment, E TR03, Appendix A 2. Noise modelling underteken in GLGH Windfarmer V , using Complex ISO9613) General noise model. Modelled scenario: 39x Generic WTG, m/s hub height), ground factor of G= For enlargements see sheet 2 MANNAR ISLAND WGS 1984 UTM Zone 44N All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from e rrors or omissions in this information or its use in any way Hydro Tasmania

36 101 60! WT 32 Enlargement 1 54! 0 6 WT Enlargement 4 Title Client Client Map no. Date Mannar Wind Power Project Noise Assessment Scenario A1-39 WTGs Asian Development Bank E P GIS of 2) 12/04/ ! WT Drawn Reviewed Approved Legend Toby Dove Brendon Bateman Andrew Wright Map: "\\hydrotasm ania\consult$\project\consultdm \E305xxx\E3056xx\E305674\P511697\GIS\P511697_GIS04 N oise Contours\E P GIS Scenario A1-39 WTGs - Enlargements.m xd" exported on 12/04/2017 5:12:02 PM by uziallog Data sources): Esri, HERE, DeLorme, Mapm yindia, OpenStreetMap contributors Esri, H ER E, D elorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CN ES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User C om munity 6 0! d B m WT ! m 49! 60 WT m WT ! 60 WT ! WT ! WT ! WT 30 Enlargement ! 60 Enlargement m! 6 0 WT WT m m! 60! 60 WT 5 WT 8 55! ! WT 4 55 WT 10! Enlargement 5 WT 3 Enlargement 6 Notes Locality map INDIA! WTG Receiver Noise assessment MANNAR ISLAND Noise contours 1 ) Receiver IDs shown refer to Mannar Wind Power Project, Noise assessment, E TR03, Appendix A 2. Noise modelling underteken in GLGH Windfarmer V , using Complex ISO9613) General noise model. Modelled scenario: 39x Generic WTG, m/s hub height), ground factor of G=0.5. All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from e rrors or omissions in this information or its use in any way Hydro Tasmania.

37 Title Client Mannar Wind Power Project Noise Assessment Scenario A2-39 WTGs Asian Development Bank Client Map no. E P GIS of 2) Date 12/04/2017 Drawn Toby Dove Reviewed Brendon Bateman Approved Andrew Wright Legend! WTG Receivers # Single Cluster Noise assessment Noise contours 5 ) Map: "\\hydrotasm ania\consult$\project\consultdm \E305xxx\E3056xx\E305674\P511697\GIS\P511697_GIS04 Noise Contours\E P GIS Scenario A2-39 WTGs.mxd" exported on 12/04/2017 3:31:05 PM by uziallog Data sources): Esri, HERE, DeLorme, Mapm yindia, OpenStreetMap contributors Esri, H ER E, D elorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CN ES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User C om munity Enlargement 1!!! 88! Enlargement 2! Enlargement 3!!!!! 66!! !!!!!! ! 64 73! !! 5 Enlargement 4! 8! Enlargement d B Enlargement ! Notes Scale ,000 2,000 3,000 m Locality map 54+ A3 INDIA Receiver IDs shown refer to Mannar Wind Power Project, Noise assessment, E TR03, Appendix A 2. Noise modelling underteken in GLGH Windfarmer V , using Complex ISO9613) General noise model. Modelled scenario: 39x Generic WTG, m/s hub height), ground factor of G= For enlargements see sheet 2 MANNAR ISLAND WGS 1984 UTM Zone 44N All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from e rrors or omissions in this information or its use in any way Hydro Tasmania

38 55 101! WT 32 Enlargement ! 54 WT Enlargement 4 Title Client Client Map no. Date Mannar Wind Power Project Noise Assessment Scenario A2-39 WTGs Asian Development Bank E P GIS of 2) 12/04/ Drawn Toby Dove ! WT Reviewed Approved Legend Brendon Bateman Andrew Wright Map: "\\hydrotasm ania\consult$\project\consultdm \E305xxx\E3056xx\E305674\P511697\GIS\P511697_GIS04 N oise Contours\E P GIS Scenario A2-39 WTGs - Enlargements.m xd" exported on 12/04/2017 5:29:33 PM by uziallog Data sources): Esri, HERE, DeLorme, Mapm yindia, OpenStreetMap contributors Esri, H ER E, D elorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CN ES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User C om munity! m WT ! m 55! WT WT m ! WT ! WT ! WT 16! WT 30 Enlargement ! WT 21 Enlargement m 54 55! WT m WT 5 27! m 55! WT ! 54! 55 WT 4 55 WT ! 25 WT ! WT Enlargement 5 Enlargement 6 Notes Locality map INDIA! WTG Receiver Noise assessment MANNAR ISLAND Noise contours 1 ) Receiver IDs shown refer to Mannar Wind Power Project, Noise assessment, E TR03, Appendix A 2. Noise modelling underteken in GLGH Windfarmer V , using Complex ISO9613) General noise model. Modelled scenario: 39x Generic WTG, m/s hub height), ground factor of G=0.5. All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from e rrors or omissions in this information or its use in any way Hydro Tasmania.

39 Title Client Mannar Wind Power Project Noise Assessment Scenario A3-39 WTGs Asian Development Bank Client Map no. E P GIS of 2) Date 12/04/2017 Drawn Toby Dove Reviewed Brendon Bateman Approved Andrew Wright Legend! WTG Receivers # Single Cluster Noise assessment Noise contours 5 ) Map: "\\hydrotasm ania\consult$\project\consultdm \E305xxx\E3056xx\E305674\P511697\GIS\P511697_GIS04 Noise Contours\E P GIS Scenario A3-39 WTGs.mxd" exported on 12/04/2017 3:38:12 PM by uziallog Data sources): Esri, HERE, DeLorme, Mapm yindia, OpenStreetMap contributors Esri, H ER E, D elorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CN ES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User C om munity ! Enlargement 1!! 88! Enlargement 2! 89!! Enlargement 3!!!! !! ! 64 73! 74 75! ! 5 Enlargement 4! ! Enlargement ! 66! ! Enlargement Notes Scale ,000 2,000 3,000 m A3 Locality map INDIA Receiver IDs shown refer to Mannar Wind Power Project, Noise assessment, E TR03, Appendix A 2. Noise modelling underteken in GLGH Windfarmer V , using Complex ISO9613) General noise model. Modelled scenario: 39x Generic WTG, m/s hub height), ground factor of G= For enlargements see sheet 2 MANNAR ISLAND WGS 1984 UTM Zone 44N All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from e rrors or omissions in this information or its use in any way Hydro Tasmania

40 49 101! WT 32 Enlargement 1 49! WT Enlargement 4 Title Client Client Map no. Date Mannar Wind Power Project Noise Assessment Scenario A3-39 WTGs Asian Development Bank E P GIS of 2) 12/04/ ! WT Drawn Reviewed Approved Legend Toby Dove Brendon Bateman Andrew Wright Map: "\\hydrotasm ania\consult$\project\consultdm \E305xxx\E3056xx\E305674\P511697\GIS\P511697_GIS04 N oise Contours\E P GIS Scenario A3-39 WTGs - Enlargements.m xd" exported on 12/04/2017 5:46:45 PM by uziallog Data sources): Esri, HERE, DeLorme, Mapm yindia, OpenStreetMap contributors Esri, H ER E, D elorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CN ES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User C om munity! m WT ! m! 49 WT m WT ! WT ! 49 WT ! 45 WT 16! WT 30 Enlargement ! 44 WT 21 Enlargement m 49! 50 WT 9 46! WT m WT 5 27! m ! 49! WT 4 49 WT ! 25 WT 10 49! WT Enlargement 5 Enlargement 6 Notes Locality map INDIA! WTG Receiver Noise assessment MANNAR ISLAND Noise contours 1 ) Receiver IDs shown refer to Mannar Wind Power Project, Noise assessment, E TR03, Appendix A 2. Noise modelling underteken in GLGH Windfarmer V , using Complex ISO9613) General noise model. Modelled scenario: 39x Generic WTG, m/s hub height), ground factor of G=0.5. All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from e rrors or omissions in this information or its use in any way Hydro Tasmania.

41 Title Client Mannar Wind Power Project Noise Assessment Scenario B - 31 WTGs Asian Development Bank Client Map no. E P GIS of 2) Date 13/04/2017 Drawn Toby Dove Reviewed Brendon Bateman Approved Andrew Wright 115 Legend! WTG Receivers # Single Cluster Noise assessment Map: "\\hydrotasm ania\consult$\project\consultdm \E305xxx\E3056xx\E305674\P511697\GIS\P511697_GIS04 Noise Contours\E P GIS Scenario B - 31 WTGs - 1 of 2.mxd" exported on 13/04/2017 4:01:37 PM by uziallog Data sources): Esri, HERE, DeLorme, Mapm yindia, OpenStreetMap contributors Esri, H ER E, D elorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CN ES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User C om munity Enlargement 1 45! ! !!!! Enlargement 2 89!!! Enlargement 3!!!!!!!! 65! 64! ! Enlargement ! 55! 40 Enlargement !! 45! Enlargement Notes 1. Receiver IDs shown refer to Mannar Wind Power Project, Noise assessment, E TR03, Appendix A 2. Noise modelling underteken in GLGH Windfarmer V , using Complex ISO9613) General noise model. Modelled scenario: 31x Vestas V MW, m/s hub height) employing reduced noise modes at some locations, ground factor of G= For enlargements see sheet 2 Scale ,000 2,000 3,000 m Locality map Noise contours 5 ) A3 INDIA MANNAR ISLAND WGS 1984 UTM Zone 44N All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from e rrors or omissions in this information or its use in any way Hydro Tasmania

42 101! WT Enlargement ! WT Enlargement 4 Title Client Client Map no. Date Mannar Wind Power Project Noise Assessment Scenario B - 31 WTGs Asian Development Bank E P GIS of 2) 13/04/2017 Map: "\\hydrotasm ania\consult$\project\consultdm \E305xxx\E3056xx\E305674\P511697\GIS\P511697_GIS04 Noise Contours\E P GIS Scenario B - 31 WTGs - 2 of 2.mxd" exported on 13/04/2017 4:14:34 PM by uziallog Data sources): Esri, HERE, DeLorme, Mapm yindia, OpenStreetMap contributors Esri, H ER E, D elorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CN ES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User C om munity 98 45! m WT 24 B 4 d ! m! 49 WT m WT WT WT WT ! 49 WT ! WT 30 Enlargement ! 40 WT 21 Enlargement m 4 9! 50 WT ! m WT 5 27! WT m WT 4 WT 7 49! WT ! WT Enlargement 5 Enlargement Drawn Reviewed Approved Legend Notes Locality map INDIA Toby Dove Brendon Bateman Andrew Wright WTG WTG excluded from Scenario B Layout) Receiver Noise assessment MANNAR ISLAND Noise contours 1 ) Receiver IDs shown refer to Mannar Wind Power Project, Noise assessment, E TR03, Appendix A 2. Noise modelling underteken in GLGH Windfarmer V , using Complex ISO9613) General noise model. Modelled scenario: 39x Generic WTG, m/s hub height) employing reduced noise modes at some locations, ground factor of G=0.5. All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from e rrors or omissions in this information or its use in any way Hydro Tasmania.

43 APPENDIX 6 Shadow Flicker Assessment Report SRI: Wind Power Generation Project

44 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 E ecutive su ar Shadow flicker modelling was carried out for the proposed 100 MW Mannar Wind Power Project, using a method corresponding to the World Bank Environmental, Health, and Safety Guidelines for Wind Energy 1], and the German Shadow Flicker guidelines 2] which are the basis of the World Bank requirements, adopted in this case by the Asian Development Bank. These guidelines e o e d a p o ess fo odelli g a o st- ase s e a io a d o pa i g ith li its of hou s per year and 30 minutes per day on the worst affected day. The proposed wind farm configuration of 39 wind turbines Scenario A) with a rotor diameter of 130 m and hub height of 90 m has been defined as the worst case and hence likely maximum impact for assessing shadow flicker impacts on receptors. It is noted that wind turbine models offered for the project will probably include wind turbines with an individual capacity of around 3.3 MW, so that 31 wind turbine locations is a likely configuration for the 100 MW project this has been modelled as Scenario B. The modelled shadow flicker significantly exceeds the recommended limits at locations along the coastline which are 300 m or less from wind turbine locations. These include considering either Scenario A and B): The Shell Coast resort. Annual shadow flicker hours are calculated as up to 164 hours. Kaluthota Investment Cabanas and St Jude Rd, Kaluthota Investment Cabana. Annual shadow flicker hours are calculated as between 77 and 267 hours, depending on the exact location considered, and whether Scenario A or Scenario B is considered. Vaadi, naval outpost and camps, the fish meal factory and sea cucumber hatchery, and other assorted structures located along the coast, where the potential for shadow flicker exists on many days each year from 100 days up to almost every day). The Scenario B layout significantly mitigates shadow flicker at some specific receptors such as the sea cucumber hatchery) lo ated adja e t to the e o ed i d tu i e lo atio s WTs,,,, 22, 27, 28, 31), however shadow flicker remains significant at other locations. Shadow flicker can be mitigated by turning off wind turbines during time periods when there is potential for shadow flicker at receptors typically around sunrise and sunset). Shadow flicker could be completely mitigated with an estimated energy loss equivalent to approximately 1.5% of the annual energy output of the wind farm for Scenario A, or 1.0% for Scenario B. The precise shutdown regime for shadow flicker mitigation will be determined after the wind turbine model is sele ted CEB s te de p o ess, and further investigation of the sensitivity of each potential receptor, to shadow flicker. An automatic shutdown regime will be implemented on the individual wind turbines that exceed limits to reduce the hours of modelled shadow flicker to within the required 30 hours annually. Based on the final wind turbine configuration, the precise time of day when shadow flicker is present will be modelled for each day of wind farm operational life. Postconstructon monitoring and consultation should be undertaken to determine whether the automated shutdown shadow flicker mitigation has been effectively implemented. Blade glint is not expected to cause any issue, provided the wind turbine supplier ensures that blades supplied are coated with a low reflectivity treatment. i

45 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Co te ts 1. Introduction Reference guidelines Mitigations 2 2. Method 5 3. Results Shadow flicker modelling Mitigations Rotor azimuth Cloud cover, rainfall and periods of calm Rotor size Wind turbine shutdown 9 4. Blade glint Conclusions References 15 Appendices A B Locations and results A.1 Wind turbines A.2 Receptors A.3 Modelling results Map List of figures Figure 3.1: Monthly shadow flicker hours, average rainfall, and low wind speeds 8 List of tables Table 2.1: Shadow Flicker modelling parameters 6 iii

46 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May I troductio The rotating blades of wind turbines can cast intermittent shadows to a person located in the shadow of the wind turbine termed shadow flicker. Because wind turbines are tall structures, shadow flicker can be observed at considerable distances but usually only for a brief time at any given location. In some circumstances for some people shadow flicker may cause annoyance, however it is not generally associated with adverse health impacts 4]. A detailed consideration of the phenomenon of shadow flicker is presented in the referenced UK report 4], which reviews the results of numerous studies, including the evidence for shadow flicker impacts on health and residential amenity. A primary concern of planning authorities has been whether wind turbine shadow flicker can lead to photosensitive epileptic seizures in individuals there is little or no evidence of any such incidents ever occurring. Statistically in the UK), approximately 0.5% of the population suffers from epilepsy, of these between 3.5% to 5% are photosensitive, and of these less than 5% are sensitive to the low freqeuencies in the range Hz, with the remainder sensitive to higher frequencies up to 30 Hz. Modern large wind turbines rotate more slowly than previous generations of wind turbines, and produce shadow flicker at a frequency of between 0.3 to 1.0 Hz. As such, the rotational frequency of wind turbine shadow flicker is much lower than the flickering light conditions that are associated with photosensitive epileptic seizures in an extremely small percentage of the population. As such, and based on their own surveys, organisations such as the UK epilepsy society have concluded the risk is minimal 7]. The extent to which shadow flicker is a nuisance to individuals is more difficult to gauge. However for the short durations mandated by the guidelines below, the nuisance impact of shadow flicker is minimal. 1.1 Reference guidelines Sri Lanka does not have any specific guidelines for wind farm shadow flicker. The World Bank Environmental, Health, and Safety Guidelines for Wind Energy 1] refers to international sources of good practice, and Asian Development Bank has confirmed the German guidelines 2] for shadow flicker should be applied to this project. These guidelines include detailed limits: 30 hr/yr and 30 min/day modelled shadow flicker at ecepto s 8 hr/yr actual shadow flicker in a realistic scenario considering meteorological parameters The guidelines include a detailed method and assumptions to be used in calculations including: continual sunshine in cloudless skies from sunrise to sunset 1

47 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 sufficient wind for continually rotating wind turbine blades minimum angle of the sun above the horizon of three 3) degrees model the Sun as a point include effects of topography do not adjust for atmospheric refraction receptor height 2 m above ground or window height) Receptor locations are all dwelling entry points windows and balconies) distance between rotor place and tower axis is negligible rotor is perpendicular to the incident direction of the sunlight document assessment for at least a one year period 365 days, 24 h/day) Possible mitigating circumstances and supporting evidence for limits and approaches is also included, and exceptions may typically occur by agreement with a landowner. The German guideline does not provide a specific distance beyond which shadow flicker will not occur. For this assessment, Entura will adopt the assumption that shadow flicker is not experienced beyond 10 rotor diameters, as per standards used in the United Kingdom 4]. Modelling for comparison against the 30 hour limit applies the most conservative assumption at each step, to p odu e a o st- ase esti ate of total hou s of e posu e. Modelling is used as it provides a benchmark however it is widely recognised as considerably overestimating actual exposure and the exposure limit has been set to account for this. 1.2 Mitigations The actual observed shadow flicker at receptors is less than the modelled results, because of the following items: If the sun is blocked by cloudy skies, wind turbines do not cast pronounced shadows. When the wind turbine rotor is not oriented perpendicular to the line between the sun and the receptor, the region of shadow flicker is thinner than modelled, and may not therefore be cast over the receptor. When the wind turbine is not rotating due to low wind, no moving shadows will be cast and no shadow flicker would occur. If the wind turbine is screened by vegetation or other structures the amount of shadow flicker at the receptor will be reduced. Shadow flicker impact is generally most noticeable when experienced in a confined indoor space, where sunlight through a narrow window opening is the predominant light source 4]. As such, the hours of shadow flicker calculated in this report are more than the hours of shadow flicker that will be experienced in practice. As noted in the previous section, the 30 hour limit for modelled shadow flicker takes into account that mitigations related to meteorological factors including some of the above) will typically reduce actual exposure considerably. 2

48 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 However, individual cases may differ, and additional mitigations such as physical screening or scheduling of wind turbine operation may be introduced. For this reason, the German guidelines provide an alternate limit for assessments that take into account these mitigations. As stated earlier, if mitigation measures are to be relied upon then this limit is 8 hr/yr actual shadow flicker in a realistic scenario considering meteorological parameters. 3

49 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May Method Entura has used the DNV-GL WindFarmer software package to model the occurrence of shadow flicker at the wind farm site. In completing this analysis, Entura has used the following inputs Wind turbine coordinates consisting of 39 locations provided by Ceylon Electricity Board on 30/11/2017, shown in Appendix A. This la out of lo atio s is efe ed to as S e a io A i this report. A subset of 31 locations, representing a typical layout that satisfies the 100 MW installed capacity limit with 31x 3.3 MW wind turbines. WTs 4, 7, 8, 17, 22, 27, 28, 31 have been removed from the 39 locations. This la out is efe ed to as S e a io B i this epo t. Residence coordinates for all residences, public facilities, fisher camps and navel outposts within 2 km of any turbine e epto s. A list of e epto lo atio s has ee de eloped a d is p o ided i Appe di A. This list has ee de eloped the Asia De elop e t Ba k s environmental and social safeguard consultants, with some additional building locations that Entura has identified through observations of Google Earth aerial imagery.. A generic wind turbine model of 130 rotor diameter and 90 m hub height. Contour map file of site extending a minimum of 2 km in all directions from the wind turbine locations and residences of interest. The modelling parameters and settings in Table 2.1 show the recommendations of the German guideline 2], the values used in this analysis. 5

50 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Table 2.1: Shadow Flicker modelling parameters Model parameter Zone of influence of shadows Minimum angle to the Sun Shape of the Sun Time and duration of modelling Orientation of the rotor Offset between rotor and tower Time step Effects of topography Receptor height Grid size for mapping Value required by guideline 10 x rotor diameter, 1300 m 3 degrees Point source 2018 one full non-leap year) Disk facing the sun None 10 min Include 2 m 25 m 6

51 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May Results 3.1 Shadow flicker modelling The full results of the modelling are presented in Appendix A, and the distribution of shadow flicker annual totals is shown across the site in the map in Appendix B. We note the following key observations from the results: Shadow flicker hours at the Shell Coast resort are up to 164 hours or less depending on the exact location modelled). Shadow fli ke hou s at the Kaluthota I est e t Ca a as a d St Jude d, Kaluthota I est e t Ca a as a e between 77 and 267 hours, depending on the exact location considered, and whether Scenario A 39 WTG) or Scenario B 31 WTG) is considered. The majority of Vaadi and naval outposts and camps, the fish meal and sea cucumber factories, and other assorted structures located along the coast and between wind turbine locations are calculated to receive shadow flicker well in excess of 30 hours. The Scenario B layout significantly mitigates shadow flicker at some specific receptors located adja e t to the e o ed i d tu i e lo atio s WTs,,,,,,, Where shadow flicker hours exceed 30 hours per year, there are a large number of days typically > 100) where the 30 min per day limit is exceeded. Other sensitive locations surrounding the wind farm are have less than 30 hours of shadow flicker per year and less than 30 minutes per day. 3.2 Mitigations The high number of hours of modelled shadow flicker at many locations close to wind turbines far exceeds the 30 hour limit of the guidelines. Partially mitigating the amenity concern, is research that suggests when wind turbines are rotating at below 2.5 Hz as they will be for this project), they will hardly cause any nuisance 4]. The impact on amenity is perhaps most critical for patrons of the Shell Coast resort, and in future at the two Cabanas under construction. For these locations, with shadow flicker unmitigated e.g. by shutdown as discussed in Section 3.3), the average daily duration is roughly 30 minutes but probably less in most cases), which could conceivably cause some annoyance. It is common practice to consider eteo ologi al mitigations in the event that some locations exceed 30 hours of shadow flicker. Some potential mitigations are discussed in the Sections below. However because shadow flicker hours greatly exceed 30 hours, meteorological mitigations do not alter the conclusion that shadow flicker at many locations along the coastline exceeds the guidelines. 7

52 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May Rotor azimuth A relatively simple first step for further analysis is to test the assumption that the rotor is always orientated perpendicular to the sun. In practice, the wind turbines at Mannar will be oriented along a 40 / 220 axis for most of the year, and when shadow flicker hours are modelled with the rotor fixed in this orientation, the number of shadow flicker hours at many locations reduces significantly see Table A Cloud cover, rainfall and periods of calm Figure 3.1 displays monthly shadow flicker hours across the receptors, monthly rainfall at Mannar Island 5], and the number of hours where wind speed is below the typical 3 m/s cut-in wind speed of wind turbines. The following observations are noted: High monthly shadow flicker totals generally coincide with months of relatively high rainfall January, November, December). This implies that cloud cover may obscure a larger proportion of shadow flicker hours than typically expected although a firm link between rainfall and consistent cloud cover has not been confirmed for this site). As a consequence of this analysis, we note the potential for some mitigation due to significant cloud cover from November through January. This does not alter the basic conclusion that the 30 hour per year limit will be greatly exceeded at receptors close to wind turbines. Additionally, periods of calm may occur when shadow flicker is modelled. Taking November as an example, the wind turbines may be stationary for approximately 14% of the time due to low wind speeds, however across the year there is not a strong correlation between months with low wind speeds and months with high shadow flicker. As such, consideration of periods of calm does not alter the basic conclusions about the high level of shadow flicker at some locations. Figure 3.1: Monthly shadow flicker hours, average rainfall, and low wind speeds 8

53 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May Rotor size The wind turbine has been modelled with a 130 m rotor and 90 m hub height based on the maximum likely size of wind turbine. The actual wind turbine size may be smaller than 130 m e.g. 110 m), and in such a case, the number of shadow flicker hours will be reduced. 3.3 Wind turbine shutdown For locations where shadow flicker exceeds guidelines, shadow flicker may be mitigated by implementing control algorithms to shut down the wind turbines responsible for shadow flicker during the specific times when shadow flicker would impact receptors. It may not be feasible to completely mitigate shadow flicker at all locations, however due to the clustering of many of these locations, operational constraints on selected wind turbines will significantly reduce the impact of shadow flicker. Entura estimates that operational constraints implemented at selected wind turbine locations could completely mitigate the shadow flicker at affected receptors, with a resulting shutdown period equivalent to 1.5% of the annual time period for Scenario A 39 wind turbines) or 1.0% of the annual time period for Scenarion B 31 wind turbines). Assuming a 1:1 relationship between time and energy loss, this represents the annual energy loss due to shadow flicker for each scenario. The precise shutdown regime and associated energy loss is highly dependent on the number of wind turbine locations likely less than 39), the wind turbine model and size, and whether the affected receptors are occupied and sensitive to shadow flicker during the relevant time periods generally morning and evening). The estimated 1.5% energy loss or 1.0% for Scenario B) is likely to overstate the loss, given these factors. The precise shutdown regime for shadow flicker mitigation will be determined after the wind turbine model is sele ted CEB s te de p o ess, and further investigation of the sensitivity of each potential receptor, to shadow flicker. An automatic shutdown regime will be implemented on the individual wind turbines that exceed limits to reduce the hours of modelled shadow flicker to within the required 30 hours annually. Based on the final wind turbine configuration, the precise time of day when shadow flicker is present will be modelled for each day of wind farm operational life. Postconstructon monitoring and consultation should be undertaken to determine whether the automated shutdown shadow flicker mitigation has been effectively implemented. Entura is not aware of a proven and commercial viable system to assess meteorological conditions in real time and determine when to implement shutdown to prevent shadow flicker, however adaption of cloud cover detection systems used in forecasting for solar arrays is a potential solution for investigation, if shadow flicker losses have a significant financial impact. 9

54 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May Blade gli t Blade glint can potentially e p odu ed he the su s light is efle ted f o the su fa e of i d turbine blades. All major wind turbine blade manufacturers currently finish their blades with a low reflectivity treatment. This prevents a potentially annoying reflective glint from the surface of the blades and the possibility of a strobing reflection when the turbine blades are spinning. Therefore the risk of blade glint from a new development is considered to be very low. Provided the wind turbine specifications require that blades supplied are coated with a low reflectivity treatment, no issue is foreseen. 11

55 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May Co clusio s The shadow flicker impacts on receptors in the vicinity of Mannar Wind Power Project have been assessed. Shadow flicker impacts are dependent on proximity to wind turbines, hence the impacts on receptors in the vicinity of the wind farm can be grouped as follows Locations 800 m or further from the wind turbines, which are unaffected or experience impacts that are within shadow flicker guidelines requirements of 30 hours per year and a maximum 30 minutes per day. Local villages and permanent residences fall within this category. Locations along the coastline 300 m or less from wind turbine locations, which exceed the guideline requirements by a large number of hours and for a large number of days. These include: o o o o The Shell Coast resort. Annual shadow flicker hours are calculated as up to 164 hours. Kaluthota I est e t Ca a as a d St Jude d, Kaluthota I est e t Ca a a. A ual shadow flicker hours are calculated as between 77 and 267 hours, depending on the exact location considered, and whether Scenario A 39 wind turbines) or Scenario B 31 wind turbines) is considered. Vaadi, naval outpost and camps, the fish meal and sea cucumber factories, and other assorted structures located along the coast, where the potential for shadow flicker exists on many days each year from 100 days up to almost every day) The Scenario B layout significantly mitigates shadow flicker at some specific receptors lo ated adja e t to the e o ed i d tu i e lo atio s WTs,,,,,,, 31) Shadow flicker can be mitigated by stopping wind turbines during time periods when there is potential for shadow flicker at receptors. It is estimated that shadow flicker at receptors could be completely mitigated, with a resulting loss of energy equivalent to approximately 1.5% of the annual energy output of the wind farm if 39 wind turbines are considered, or a 1.0% loss if 31 wind turbines are considered. The precise shutdown regime and associated energy loss is highly dependent on the number of wind turbine locations likely less than 39), the wind turbine model and size, and whether the affected receptors are occupied and sensitive to shadow flicker during the relevant time periods generally morning and evening). The estimated 1.5% / 1.0% 39 / 31 wind turbine) energy loss is likely to overstate the loss, given these factors, but is a reasonable estimate for the purpose of assessing the energy output of the project at this point in time 13

56 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May Refere ces 1] World Bank IFC Environmental, Health, and Safety Guidelines for Wind Energy, August 7, ] Federal States Committee for Pollution Control, Hinweise zur Ermittlung und Beurteilung der optischen Immissionen von Windenergieanlagen Information on Identifying and Assessing the Optical Emissions from Wind Turbines], 2002). 3] Planning for Renewable Energy: A Companion Guide to PPS22 Office of the Deputy Prime Minister 2004) 4] Update of UK Shadow Flicker Evidence Base, PB Power, Prepared for the UK Department of Energy and Climate Change. 5] Proposed 100 MW Mannar Wind Power Project, Initial Environmental Examination IEE) Report, April ] Mannar wind power project, wind resource, wind turbine suitability and energy production report, Entura report E305674, April 2016 draft. 7] 15

57 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Appe dices 17

58 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 A Locations and results A.1 Wind turbines Table A.1: WTG layout Turbine number X coordinate Y coordinate WT 1 373, ,733 WT 2 373, ,973 WT 3 373, ,277 WT 4 372, ,524 WT 5 372, ,767 WT 6 372, ,017 WT 7 371, ,250 WT 8 371, ,487 WT 9 371, ,717 WT , ,950 WT , ,397 WT , ,612 WT , ,832 WT , ,033 WT , ,257 WT , ,462 WT , ,667 WT , ,867 WT ,979 1,000,059 WT ,649 1,000,250 WT ,309 1,000,444 WT ,006 1,000,609 WT ,476 1,000,904 WT ,211 1,001,046 WT ,953 1,001,183 WT ,684 1,001,324 WT ,415 1,001,463 19

59 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Turbine number X coordinate Y coordinate WT ,144 1,001,588 WT ,873 1,001,714 WT ,605 1,001,843 WT ,343 1,001,963 WT ,043 1,002,092 WT ,772 1,002,196 WT , ,958 WT , ,215 WT , ,434 WT , ,641 WT , ,852 WT ,503 1,000,099 Coordinate reference: WGS84 / UTM zone 44P. Shaded locations are removed from Scenario B A.2 Receptors Table A.2: Receptor list Nearby WT ID Receptor name Easting m) Northing m) Distance to nearest wind turbine m) 1 Thalvupadu Thottavelly-Thalvupadu Rd N1 Thoddaveli Water Board Office N2 Mr Mariyadas Konniankuduiruppu village and church Konniankuduiruppu Konniankuduiruppu Konniankuduiruppu Konniankuduiruppu WT 1 10 Naval observation unit WT 1 11 Vadi Vadi Vadi Vadi Vadi Vadi

60 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Nearby WT ID Receptor name Easting m) Northing m) Distance to nearest wind turbine m) WT 1 and 2 19 WT 4 and 5 WT 7 and 8 17 Vadi Vadi Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) estimated location Naval Camp Naval Camp Naval Camp Naval Camp Naval Camp building) Naval Camp building) Vadi Vadi Vadi Vadi Vadi Naval observation unit Vadi Vadi Sea cucumber hatchery and accommodation Vadi Vadi Vadi Vadi Fishe e s est oo Tea kiosk Vadi Vadi Residential unit - Konniankuduiruppu Residential unit - Konniankuduiruppu Residential unit - Konniankuduiruppu

61 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Nearby WT ID Receptor name Easting m) Northing m) Distance to nearest wind turbine m) 50 Residential unit - Konniankuduiruppu WT 8 and Kalthota Finance Hotel under construction) - Kalthota Finance Hotel under construction) - Kalthota Finance Hotel under construction) - Kalthota Finance Hotel under construction) WT 9 and Vadi WT 10 and Vadi Vadi Vadi WT 10 and Shell Coast Hotel Shell Coast Hotel Shell Coast Hotel Shell Coast Hotel Shell coast resort B WT Naval observation unit WT Vadi WT 17 WT Naval observation unit Olaiththoduvai Olaiththoduvai Church Olaiththoduvai School Residential unit - Uvary village and church Residential unit - Uvary village and church Residential unit - Uvary village and church Kalthota Finance Hotel under construction) St Jude Road - Kalthota Finance Hotel under construction) St Jude Road - Kalthota Finance Hotel under construction) St Jude Road - Kalthota Finance Hotel under construction) St Jude Road - Kalthota Finance Hotel under construction) St Jude Road WT 22 and 78 Naval Camp - Nadukuda

62 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Nearby WT ID Receptor name 23 WT 22 and 23 Easting m) Northing m) Distance to nearest wind turbine m) 79 Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Tea kiosk Tea kiosk Fishe e s est oo Church WT Naval observation unit WT 30 and 31 WT 32 and Nadukudda N5 House, Naddukkuda Residential unit - Nadukuda Vadi Vadi Vadi Vadi Naval observation unit Vadi Vadi Vadi Vadi Vadi WT Vadi Vadi Vadi Vadi Residential unit - KeelaiyanKuduiruppu Residential unit - KeelaiyanKuduiruppu Residential unit - KeelaiyanKuduiruppu Residential unit - KeelaiyanKuduiruppu Navy Camp - Selvary WT Vadi N4 Julian Dias, Pesale N6 Bishop House N7 Old peir Navy camp)thalimannar

63 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Nearby WT ID Receptor name Easting m) Northing m) Distance to nearest wind turbine m) 115 N8 Housae Thalimannar Coordinate reference: WGS84 / UTM zone 44P A.3 Modelling results Table A.3: Receptor modelling results Scenario A - 39 WTG Scenario B - 31 WTG Nearby WT ID Receptor name annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded 1 Thalvupadu none none 2 Thottavelly-Thalvupadu Rd 19: : N1 Thoddaveli Water Board Office none none 4 N2 Mr Mariyadas 9: none 5 Konniankuduiruppu village and church none none 6 Konniankuduiruppu 16: : Konniankuduiruppu none none 8 Konniankuduiruppu none none 9 Konniankuduiruppu 25: none WT 1 10 Naval observation unit none none WT 1 11 Vadi none none 12 Vadi none none 13 Vadi none none 14 Vadi none none 15 Vadi none none 16 Vadi none none 17 Vadi none none 18 Vadi none none WT 1 and 2 19 Industrial unit fish meal manufacturing company) 195: : Industrial unit fish meal manufacturing company) 502: : Industrial unit fish meal manufacturing company) 220: :

64 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Scenario A - 39 WTG Scenario B - 31 WTG Nearby WT ID Receptor name annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) estimated location 617: : : : WT 4 and 5 24 Naval Camp - 251: : Naval Camp - 446: : Naval Camp - 183: : Naval Camp - 833: : Naval Camp building) 189: : Naval Camp building) 727: : WT 7 and 8 30 Vadi 465: : Vadi 602: : Vadi 404: : Vadi 599: : Vadi 298: : Naval observation unit 285: : Vadi 312: : Vadi 215: : Sea cucumber hatchery and accommodation 356: : Vadi 301: : Vadi 255: : Vadi 296: : Vadi 301: : Fishe e s est oo 284: : Tea kiosk 291: : Vadi 157: : Vadi 168: : WT 8 and Residential unit - Konniankuduiruppu Residential unit - Konniankuduiruppu Residential unit - Konniankuduiruppu Residential unit - Konniankuduiruppu Kalthota Finance Hotel under construction) - Kalthota Finance Hotel under construction) - 26: none 31: none 35: none 8: none 248: : : :

65 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Scenario A - 39 WTG Scenario B - 31 WTG Nearby WT ID Receptor name annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded Kalthota Finance Hotel under construction) - Kalthota Finance Hotel under construction) - 128: : : : WT 9 and Vadi 258: : WT 10 and Vadi 372: : Vadi 343: : Vadi 309: : WT 10 and Shell Coast Hotel - 87: : Shell Coast Hotel - 61: : Shell Coast Hotel - 122: : Shell Coast Hotel - 149: : Shell coast resort B 164: : WT Naval observation unit 173: : WT Vadi 235: : WT Naval observation unit 460: : Olaiththoduvai none none 68 Olaiththoduvai Church none none 69 Olaiththoduvai School none none 70 Residential unit - Uvary village and church 12: : Residential unit - Uvary village and church 11: : Residential unit - Uvary village and church 14: : WT Kalthota Finance Hotel under construction) St Jude Road - 267: : Kalthota Finance Hotel under construction) St Jude Road - 252: : Kalthota Finance Hotel under construction) St Jude Road - 178: : Kalthota Finance Hotel under construction) St Jude Road - 151: : Kalthota Finance Hotel under construction) St Jude Road - 149: : WT 22 and Naval Camp - Nadukuda - 204: :

66 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Scenario A - 39 WTG Scenario B - 31 WTG Nearby WT ID Receptor name annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded Naval Camp - Nadukuda - Naval Camp - Nadukuda - Naval Camp - Nadukuda - Naval Camp - Nadukuda - Naval Camp - Nadukuda - 416: : : : : : : : : : WT 22 and Tea kiosk 165: : Tea kiosk 191: : Fishe e s est oo 229: : Church 232: : WT Naval observation unit 257: : Nadukudda none none 90 N5 House, Naddukkuda none none 91 Residential unit - Nadukuda 15: : WT 30 and Vadi 350: : Vadi 421: : Vadi 354: : Vadi 345: : Naval observation unit 207: : WT 32 and Vadi 114: : Vadi 246: : Vadi 242: : Vadi 293: : Vadi 350: : WT Vadi 152: : Vadi 145: : Vadi 144: : Vadi 135: : Residential unit - KeelaiyanKuduiruppu Residential unit - KeelaiyanKuduiruppu Residential unit - KeelaiyanKuduiruppu Residential unit - KeelaiyanKuduiruppu 13: : : none 11: none 12: none 110 Navy Camp - Selvary none none 27

67 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Scenario A - 39 WTG Scenario B - 31 WTG Nearby WT ID Receptor name annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded annual shadow flicker hh:mm] number of days with flicker number of days for which the limit is exceeded WT Vadi 43: : N4 Julian Dias, Pesale none none 113 N6 Bishop House none none 114 N7 Old peir Navy camp)thalimannar none none 115 N8 Housae Thalimannar none none Table A.4: Receptor modelled shadow flicker with rotor azimuth of 40 /220 Scenario A) Rotor perpendicular to sunlight Fixed rotor azimuth of 40 /220 ID Receptor name hours) hours) 19 Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) Industrial unit fish meal manufacturing company) estimated location Naval Camp Naval Camp Naval Camp Naval Camp Naval Camp building) Naval Camp building) Vadi Vadi Vadi Vadi Vadi Naval observation unit Vadi Vadi Sea cucumber hatchery and accommodation Vadi Vadi

68 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Rotor perpendicular to sunlight Fixed rotor azimuth of 40 /220 ID Receptor name hours) hours) 41 Vadi Vadi Fishe e s est oo Tea kiosk Vadi Vadi Residential unit - Konniankuduiruppu Residential unit - Konniankuduiruppu Kalthota Finance Hotel under construction) Kalthota Finance Hotel under construction) Kalthota Finance Hotel under construction) Kalthota Finance Hotel under construction) Vadi Vadi Vadi Vadi Shell Coast Hotel Shell Coast Hotel Shell Coast Hotel Shell Coast Hotel Shell coast resort B Naval observation unit Vadi Naval observation unit Kalthota Finance Hotel under construction) St Jude Road Kalthota Finance Hotel under construction) St Jude Road Kalthota Finance Hotel under construction) St Jude Road Kalthota Finance Hotel under construction) St Jude Road Kalthota Finance Hotel under construction) St Jude Road Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda Naval Camp - Nadukuda

69 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 Rotor perpendicular to sunlight Fixed rotor azimuth of 40 /220 ID Receptor name hours) hours) 84 Tea kiosk Tea kiosk Fishe e s est oo Church Naval observation unit Vadi 350: Vadi Vadi Vadi Naval observation unit Vadi Vadi Vadi Vadi Vadi Vadi Vadi Vadi Vadi Vadi

70 Mannar Wind Power Project - Shadow flicker assessment Revision No: 2 E May 2017 B Map 31

71 Title Mannar Wind Power Project Shadow Flicker Assessment Scenario A Client Asian Development Bank Client Map no. E P GIS03-1 Date 3/05/2017 Drawn Toby Dove Reviewed Brendon Bateman Approved Andrew Wright Legend 115 WTG Shadow flicker hrs/y) Receivers # Single Map: "\\hydrotasmania\consult$\project\consultdm\e305xxx\e3056xx\e305674\p511697\gis\p511697_gis03 Shadow Flicker\E P GIS Scenario A - Shadow flicker.mxd" exported on 3/05/ :43:52 PM by dovet Data sources): Esri, HERE, DeLorme, MapmyIndia, OpenStreetMap contributors Esri, HERE, DeLorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User Community ! ! 90 91! !!!!! 65! 64! ! !! Notes 1. Receiver IDs shown refer to Mannar Wind Power Project, Shadow flicker assessment, E TR02, Appendix A Scale ,000 2,000 3,000 m Locality map Cluster A3 INDIA MANNAR ISLAND WGS 1984 UTM Zone 44N All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from errors or omissions in this information or its use in any way Hydro Tasmania

72 Title Mannar Wind Power Project Shadow Flicker Assessment Scenario B Client Asian Development Bank Client Map no. E P GIS03-2 Date 3/05/2017 Drawn Toby Dove Reviewed Brendon Bateman Approved Andrew Wright Legend 115 WTG Shadow flicker hrs/y) Receivers # Single Map: "\\hydrotasmania\consult$\project\consultdm\e305xxx\e3056xx\e305674\p511697\gis\p511697_gis03 Shadow Flicker\E P GIS Scenario B - Shadow flicker.mxd" exported on 3/05/ :33:27 PM by dovet Data sources): Esri, HERE, DeLorme, MapmyIndia, OpenStreetMap contributors Esri, HERE, DeLorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS User Community !! ! 88! 89! 90 91! !!!!!!! 65! 64! ! ! ! Notes 1. Receiver IDs shown refer to Mannar Wind Power Project, Shadow flicker assessment, E TR02, Appendix A Scale ,000 2,000 3,000 m Locality map Cluster A3 INDIA MANNAR ISLAND WGS 1984 UTM Zone 44N All reasonable care has been taken in collecting and recording the information shown on this map. Entura assumes no liability resulting from errors or omissions in this information or its use in any way Hydro Tasmania