Renewable Energy Working Paper Series No Residential Solar PV Policy FEED-IN TARIFF vs NET METERING Options for Brunei DRAFT

Transcription

1 Renewable Energy Working Paper Series No. 001 Residential Solar PV Policy FEED-IN TARIFF vs NET METERING Options for Brunei DRAFT Dr Romeo Pacudan Chief Researcher Brunei National Energy Research Institute

2 Author Dr Romeo Pacudan Chief Researcher and Director Renewable and Alternative Energy Department Brunei National Energy Institute Science and Technology Research Building University of Brunei Darussalam Tungku Link BE 1410 Brunei Darussalam RE WPS 1 FIT vs NM page ii

3 Table of Contents 1 BACKGROUND AND STUDY OBJECTIVE KWP SOLAR PV SYSTEM Plant components Irradiation Yield Analysis Simulation Software Shading Analysis Modelling of Losses Degradation and Availability Final Energy Yield Estimation 7 3 TARIFF REQUIREMENT UNDER THE FEED-IN TARIFF POLICY OPTION Feed-in Tariff Policy Framework kwp Solar PV Monthly Production Required Tariff to Incentivize Investors Financial Cash Flow under Feed-in Tariff Scheme 12 4 TARIFF REQUIREMENT UNDER THE NET METERING POLICY OPTION Net Metering Policy Framework Consumption and Export of Electricity from 10 kwp PV System Opportunity Cost of Consumed Electricity Required Tariff for Exported Electricity Financial Cash Flow under Net Metering Scheme 18 5 POLICY RECOMMENDATION 19 6 APPENDIX 20 RE WPS 1 FIT vs NM page iii

4 List of Tables Table 2-1: Input parameters 2 Table 2-2: METEONORM S Irradiation Data on Horizontal and Inclined Plane 3 Table 2-3: Losses considered in plant yield analysis 5 Table 2-4: Other losses considered in the analysis 7 Table 2-5: Key results 10 kwp Rimba solar PV 8 Table 3-1. Technical, Financial and Economic Parameters 11 Table 4-1. Typical household information and electricity consumption 14 Table 4-2. Share of 10 kwp solar PV plant daily production consumed by each typical house 15 Table 4-3. Opportunity cost of consumed electricity 17 Table 6-1. Appliance ownership and power rating for typical houses 20 Table 6-2. Appliance usage for typical houses 20 List of Figures Figure 2-1: Pattern of irradiation distribution in Rimba 3 Figure 2-2: Loss diagram (excluding module degradation and plant availability) 6 Figure 3-1. Electricity generation under feed-in tariff policy 9 Figure 3-2. Monthly average production of 10 kwp system 10 Figure 3-3. Levelized cost of electricity generation for 10 kwp System 11 Figure 3-4. Financial cash flow and payback period 12 Figure 4-1. Electricity generation under net metering policy 13 Figure 4-2. Daily consumption profile for typical households 14 Figure 4-3. Household consumption patterns and 10 kwp PV production profile 15 Figure 4-4. Roof area required for 10 kwp solar PV plant 16 Figure 4-5. Consumed and exported energy for typical house D using 10 kwp solar PV plant 17 Figure 4-6. Financial cash flow under net metering scheme 18 RE WPS 1 FIT vs NM page iv

5 1 Background and Study Objective Brunei has recently launched the country s Energy White Paper which outlines the Government s strategy to steer the country towards sustainable energy future. One of the EWP s strategic goals is to diversify the power supply mix and increase the share of renewable energies to 10 percent of the total electricity production by Based on various resource assessment studies carried out in the past years, solar and municipal solid waste are the 2 main resources that have proven potential and could be commercially developed given the right policy framework and investment incentives. At present, the Government is preparing for a competitive bidding for waste-to-energy project. Solar PV is one of the technological options that could partly meet the long-term renewable energy target of the country. Deployment options for solar PV technologies include building-mounted distributed generation systems (residential, commercial and industrial buildings) and ground-mounted utility scale systems. This study focuses on policy framework that stimulates households to invest in gridconnected distributed solar PV systems. A residential solar PV program, as opposed to large-scale projects, promotes wider participation in electricity production, and channels benefits directly to residential consumers rather than large-scale producers, and could be designed to target low income households as the main project participants and beneficiaries. The residential sector represents more than one-third of the total electricity consumption in the country in The power system s peak demand in 2011 amounted to 523 MW. Adopting the US Federal Energy Regulatory Commission s 15 percent rule for distributed generation, around 78 MW of solar PV capacity could be immediately integrated into the system without affecting system voltage, power flow and protection. This corresponds to 7,800 households if the average solar PV system size is 10 kwp. One of the challenges for the Government is to introduce an appropriate policy framework that would incentivize residential households to invest in roof-mounted or residential building integrated systems. Among the options are the feed-in tariff and net metering policy frameworks that have been successfully demonstrated in many developed and developing countries. In a recent survey undertaken by the International Energy Agency, feed-in tariff is found to be the main driver for solar PV investments globally. Net metering has limited success in the US, Denmark and Netherlands where retail electricity prices are higher than the costs of producing electricity from solar PV. In addition, net metering is not the main investment driver for solar PV in these countries. The main objective of this study is to assess and compare the level of incentive (tariff rate) that should be provided to residential households under the feed-in tariff and net metering policy frameworks. It is expected that the study results will provide guidance in determining which policy option would be suitable for Brunei Darussalam. To simplify the analysis, the study uses a 10 kwp solar PV system as the reference technology for residential households. RE WPS 1 FIT vs NM page 1

6 2 10 kwp Solar PV System 2.1 Plant components The study used polycrystalline silicon modules in simulating energy yield of a 10 kwp PV power plant. Table 2-1 shows the main input parameters for energy yield analysis. DC electricity will be generated from polycrystalline modules and converted into AC electricity through the string inverters. For this specific analysis, the study randomly select a specific house in Kg Rimba with site coordinates N5.0, E114.9 with elevation of around 36 meters above mean sea level. Table 2-1: Input parameters Meteorological Data Input Data Data Set Interpolated with Meteonorm 6.1 Module Orientation Module Inclination: 5 Module Orientation: 0 Module-Inverter configuration Installed Module Capacity: 10 kwp Module Type: Polycrystalline Number of Modules: 40 Nominal Capacity of the Module: 250 Wp Number of Modules per String: 10 Number of Strings in Parallel 4 Inverter Capacity: 2.3 kw AC Number of Inverters: 4 Installed inverter capacity: 9.2 kw AC 2.2 Irradiation The study used the climatological database and program METEONORM to derive the radiation data. The program uses long time data sets to calculate hourly values, monthly average values and yearly sums for various climate parameters such as radiation, temperature, precipitation and sunshine duration. For locations where there was no data available from measurement stations, the data were calculated by means of an interpolation of the available stations. For locations where there were not enough stations available for interpolation (maximum distance is 300km), satellite data were used to fill in the data gap. 1 RE WPS 1 FIT vs NM page 2

7 Table 2-2 presents METEONORM s solar irradiation for both horizontal and inclined plane. The 5 tilted angle is selected based on the PV plant s specified array inclination to optimize electricity generation. Table 2-2: METEONORM S Irradiation Data on Horizontal and Inclined Plane Solar Radiation per m² (0 ) Solar Radiation per m² (5 ) Difference 1,782.0 kwh/year 1,786.2 kwh/year % The global horizontal irradiation consists of direct and diffuse radiation while the irradiation on the tilted surface, in addition includes ground reflected radiation (albedo). Several methodologies exist in transposing the radiation from horizontal to inclined plane. The most accurate and often used in solar energy projects is the Perez et al. model. METEONORM used the Perez et al. model as the default model for calculating irradiation for tilted surfaces. In calculating the inclined surface irradiation from hourly values of global horizontal radiation, the model first resolve the global values into direct and diffuse components and, second calculate the radiation on an inclined plane with these components including the albedo. kwh/m horizontal inclined (5 ) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 2-1: Pattern of irradiation distribution in Rimba The annual sum for global horizontal irradiation (GHI) in Rimba is 1,782 kwh/m². The seasonal pattern for irradiation shown in Figure 2-1 indicates highest GHI values in spring and low during summer though this is the period with longest solar days. But summer is also the monsoon season with high degree of cloud cover, affecting negatively the direct irradiation. The GHI also appears to be stable from autumn to winter. RE WPS 1 FIT vs NM page 3

8 The same pattern can be observed for inclined irradiation. While the annual sum of inclined irradiation is higher than horizontal, the inclined values from middle of spring (April) until early autumn (August) are however lower than the horizontal values. 2.3 Yield Analysis The energy yield of the 10 kwp solar PV power plant was estimated taking into account the regional climatic data and plant configuration Simulation Software The software used in simulating plant energy yield is PVSYST. PVSYST stands among the most powerful software tools for the simulation of grid-connected and stand-alone PV systems. It has been developed by the Center of Energy of the University of Geneva, Switzerland 2. In the engineering (project design) mode, PVSYST allows a very detailed definition of the PV plant, including special geometries, as near shading objects or tracking systems. PVSYST contains a huge database of technical and electrical properties of the most common PV components (modules, inverters) available on the market Shading Analysis The study carried out a no shading analysis Modelling of Losses Losses considered in the study including their descriptions and the corresponding model simulation results are summarized in Table 2-3. To illustrate the nature of the above-mentioned losses, a detailed energy loss diagram for the Rimba PV plant is presented below (Figure 2-2). The diagram generated by the simulation model provides a quick insight on the quality of a PV system design, by identifying and illustrating the main sources of losses. The array losses start from the rough evaluation of the nominal energy, using the global effective irradiance and the array MPP nominal efficiency at STC. Then it gives the detail of the PV model behavior according to the environmental variables. Each loss is defined as percentage of the previous energy quantity. Therefore the percent values are not additive: when grouping the losses, the overall percentage is not the sum of the detailed values. 2 RE WPS 1 FIT vs NM page 4

9 Table 2-3: Losses considered in plant yield analysis Type Description Model Simulation Results Near shading losses (discussed in the previous section) IAM factor on global irradiation Loss due to irradiance level Loss due to temperature Soiling losses Mismatch losses at MPP DC cabling losses Inverter losses Near shading losses caused by rows placing and also in this specific case in Indorama shadings due building infrastructure at the vicinity of the plant site. The additional reflection losses that occur when the sun is not vertical to the collector surface, and expressed by the incident angle modifier. Deviation of actual irradiation to STC irradiation, i.e. decrease of the model efficiency with decreasing irradiance (modules are less efficient with low irradiance) Loss of voltage due to high temperatures Losses due to dusty and dirty modules, monthly cleaning is considered in the yield calculation (the study specified soiling loss of 0.0%) Losses due to "mismatch" are related to the fact that the real modules in the array do not rigorously present the same I/V characteristics (not all modules will operate at maximum power, depending on configuration) Cabling losses of DC cabling (the study specified a loss fraction of 1.0% at STC) Inverter losses occurring in the DC to AC conversion 0% [no shading analysis was carried out in the study] -3.5% [IAM = 1-bo(1/cosine i - 1)] with bo=0.05 as recommended by ASHRAE The incidence effect (Incidence Angle Modifier, short IAM) corresponds to the weakening of the irradiation really reaching the PV cell s surface, with respect to irradiation under normal incidence. In principle, this loss obeys Fresnel s Laws concerning transmission and reflections on the protective layer (the glass), and on the cell s surface. -4.3% [results are based on module characteristics and deviation from 1000 W/m 2 a] % [results are based on module characteristics] -0.0% [typical values are 1% for Germany, 2% for South Italy/South Spain]. A lower soiling loss could be achieved through regular cleaning. -2.2% [typical value for inverters is -2%] -1.0% -6.4% [results are based on inverter technical parameters] RE WPS 1 FIT vs NM page 5

10 Figure 2-2: Loss diagram (excluding module degradation and plant availability) Degradation and Availability The losses discussed above are endogenously generated by the model based on specific input parameters. Other factors that reduce the energy yield such as module degradation and plant availability are calculated exogenously. Details of these factors are discussed below and a summary is shown in Table 2-4. Module Degradation PV module performance degrades over time of operation. The degradation depends on many factors such as the following: Deterioration of the cells Penetration of dirt and humidity into the surface Change of module surface structure, which affects the entry of light Hazing/ browning of laminate Affection on other parts of the module such as contacts Delaminating of the materials and mechanical damages Warranties given by the module manufacturers with respect to degradation tend to be rather conservative. The standard figures for the warranties offered by most of the manufacturers are the following: 90% of nominal performance after 10 years, 80% of nominal performance after 20 years (25 years in some cases). RE WPS 1 FIT vs NM page 6

11 Assuming a linear degradation this would be equivalent to a degradation factor about 1% per year relative to the original nominal power. Various studies have been conducted in order to assess the effect of degradation on PV modules. The published figures of degradation differ within a considerable range of about 0%, meaning no degradation at all, to over 1% per year. Also for the development of degradation with time there are different results available. Most studies report a stronger start degradation, followed by a quasi linear degradation. For this project, the study used 0.5% degradation per year. Plant Availability Plant availability was also considered in estimating the annual energy yield and other performance indicators. This refers mainly to the availability of the PV power plant in generating electricity. PV plant availability ranges from 95-99% but most inverter manufacturers often guarantee 97% inverter availability, thus many PV plant operators assure this level of availability. Higher plant availability could be guaranteed but this would entail additional costs to service PV plant inverters. A conservative value of 99% availability based on the global trends for solar PV plants with string inverters was considered in the study. Table 2-4: Other losses considered in the analysis Type Module degradation Plant availability Methodology 0.5% per year (most warranties specify an equivalent 1% degradation per year) 99.0% (availability ranges from 95-99% but inverter manufacturers often guarantee 97% availability) Results (First year of Operation) 65 kwh 130 kwh 2.4 Final Energy Yield Estimation Based on the climatic, physical and technical characteristics and assumptions presented earlier, the model estimates the following: annual energy yield yield factor (YF) performance ratio (PR) Yield factor (YF) refers to the plant s specific performance in net kwh delivered to the grid per kw of installed nominal PV module power. This is also equivalent to the number of full load hours for the plant. Performance ratio (PR) is defined as the actual amount of PV energy delivered to the grid in a given period, divided by the theoretical amount according to STC data of the RE WPS 1 FIT vs NM page 7

12 modules. Grid-connected PV plants at present have performance ratio ranging from 75-85%. Key results for the Rimba 10 kwp PV power plant are summarized in Table 2-5. Detailed results are shown in Annex. The expected long term (20 years) average annual energy yield is 12,292 kwh, the overall yield factor is 1229 kwh/kwp/year and the performance ratio is 68.8%. Table 2-5: Key results 10 kwp Rimba solar PV Output Unit Total Peak power [kwp] 10 Irradiation on horizontal plane [kwh/m²] 1,782.0 Irradiation on inclined plane [kwh/m²] 1,786.2 Plant availability % 99.0 First Year Performance Energy Yield (after inverter) [kwh/year] 12,886 Overall YF [kwh/kwp/year] 1,289 Overall PR [%] Average Performance (20 years) Energy yield per year (average 20 years) [kwh/year] 12,292 Total yield for 20 years [kwh] 245,846 Overall YF [kwh/kwp] 1,229 Overall PR [%] 68.8 RE WPS 1 FIT vs NM page 8

13 3 Tariff Requirement under the Feed-in Tariff Policy Option 3.1 Feed-in Tariff Policy Framework Feed-in tariff policy is a policy framework that offers long-term contracts to solar PV generators based on electricity generation costs and reasonable investment returns. Key policy design elements include the following: Guaranteed grid access and priority dispatch; Long-term contracts; and Cost-based prices The policy incentivizes potential investors to invest in solar PV power generation while addressing market barriers and reducing transaction costs. Under a feed-in tariff policy, residential households installing solar PV on their rooftops operate like a small power generation plant. From sun rays, DC electricity is generated by solar PV modules then converted into AC electricity by an inverter. The AC current is measured through a meter before it is being exported to the distribution grid (Figure 3-1). For a residential household that participate under this scheme, there will be two meters installed in the household. One is the revenue meter which registers the electricity generation and the other one is the consumption meter which records electricity consumption. The feed-in tariff is normally higher than the retail tariff. Figure 3-1. Electricity generation under feed-in tariff policy Source: kwp Solar PV Monthly Production All electricity generated from the solar PV power plant under the feed-in tariff framework is exported to the grid. From the previous section, using Meteonorm meteorological datasets and PVSYST simulation model, the average annual power production of the 10 kwp system amounts to 12.3 MWh. RE WPS 1 FIT vs NM page 9

14 The PVSYST model also generates daily production profile of power generation. The monthly generation average amounts to 1,025 kwh. This is shown in Figure 3-2. The monthly production pattern follows the solar irradiation pattern. Highest production is observed in the months of March and April when the solar irradiation are highest :00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 Watts 21:00 22:00 23:00 average daily production profiles JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Hours Figure 3-2. Monthly average production of 10 kwp system 3.3 Required Tariff to Incentivize Investors There are at least 4 main categories of price setting methodologies under feed-in tariff policies 3. The most common practice is the levelized cost of renewable energy generation plus a targeted return often set by policy makers. The other 3 approaches are the following: value of the renewable energy generation either to the society or to the utility; fixed price incentive based neither on cost of generation nor on the notion of value; auction-based mechanisms. The study estimated the required tariff for 10 kwp system using the levelized cost methodology. Levelized cost of electricity is defined by the equation below:, where: C stands for total costs, Q stands for energy generation n stands for year N stands for the project life. 3 Couture, T., Cory, K., Kreycik, C., and Williams, E., A Policy Maker s Guide to Feed-in Tariff Policy Design, National Renewable Energy Laboratory, July RE WPS 1 FIT vs NM page 10

15 The levelized cost of electricity for the 10 kwp solar PV plant, based on financial parameters given in Table 3-1 is shown in Figure 3-3. The required tariff for the 10 kwp solar PV system therefore, depending on the price scenarios for Brunei, ranges from USD 0.25 per kwh to as high as USD 0.35 per kwh with most likely range around USD 0.30 per kwh. Table 3-1. Technical, Financial and Economic Parameters Parameter Value Turnkey cost (benchmarked on Malaysian quoted prices) Scenario 1 High Scenario 2 Average Scenario 3 Low US 3,500/Wp US 3,000/Wp US 2,500/Wp O&M cost 0.5% of turnkey cost Discount rate 12% Project lifespan 20 years Natural gas price USD 15/MMBTU (constant price for the whole project duration) Heat rate 8760 BTU/kWh Average electricity retail rate 0.08 Brunei Dollar/kWh Transmission and distribution losses 10% 40 Levelized (US cents/kwh US cents/kwh gas savings electricity sales Scenario 1 Turnkey USD 3.5/Wp Scenario 2 Turnkey USD 3.0/Wp Scenario 3 Turnkey USD 2.5/Wp 10 kw system USD 35,000 USD 30,000 USD 25,000 Figure 3-3. Levelized cost of electricity generation for 10 kwp System The study also estimated the benefits that could be generated from the 10 kwp PV system using the levelized cost methodology and based on the technical parameters given in Table 3-1. The analysis considers only for one system of 10 kwp solar PV, thus RE WPS 1 FIT vs NM page 11

16 the calculation of benefits excludes the potential capacity cost that could be replaced by a number of solar PV systems under a feed-in tariff scheme. The system benefit amounts to more than USD 0.21 per kwh which is slightly lower than the low scenario of the required tariff analysis shown above. Both the required tariff and benefits results are however indicative figures since the costing assumptions are mainly based on benchmark cross-border prices. A survey will be undertaken later on realistic prices and costs that could be applied for Brunei. 3.4 Financial Cash Flow under Feed-in Tariff Scheme One of the goals of the policy framework is to incentivize the private sector to invest in renewable energy technologies. The financial cash flow of the project from investor s perspective is shown in Figure 3-4. The total benefit that the investor would receive over 20 years would amount to USD 73,435. The study also estimated the project s payback period. At tariff of USD 0.30 per kwh, capital investment of USD 30,000 and O&M costs of USD 150 per year, the simple payback period of the project would be around 8 years. FIT rate of USD 0.30 per kwh USD 3,849 USD 3,500 Revenue from FIT USD Payback Period OPEX USD 150/year CAPEX USD 30,000 Figure 3-4. Financial cash flow and payback period RE WPS 1 FIT vs NM page 12

17 4 Tariff Requirement under the Net Metering Policy Option 4.1 Net Metering Policy Framework Net metering policy is a policy framework that allows electric consumers to generate electricity on site and export excess generation to the distribution network. Export tariff policies under the net metering scheme varies from country to country. In the case of Ontario, Canada, no payment has been provided for the excess electricity exported to the grid but banking is allowed. In the case of Australia, premium price is provided for excess electricity. In other developing countries, e.g. the Philippines, the export price is indexed to the bulk electricity tariff which is lower than the retail tariff. Under net metering, the DC electricity that is produced by the solar panels is converted into AC electricity through an inverter. The generated AC electricity is being consumed directly by the residential households. If the production of electricity is higher than the consumption, excess energy is exported into the distribution grid. Conversely, when the consumption is higher than the renewable electricity generation, electricity is imported from the grid. Unlike in feed-in tariff scheme discussed in the previous section where two meters are installed in a residential household, the net metering scheme has only one bi-directional meter which spins backwards when there is a net export of electricity (Figure 4-1). Figure 4-1. Electricity generation under net metering policy Source: Consumption and Export of Electricity from 10 kwp PV System Typical Household Electricity Consumption Profile To analyse the consumption pattern of individual households, the study, in partnership with the University of Brunei Darussalam (UBD), carried out an electricity consumption RE WPS 1 FIT vs NM page 13

18 analysis for typical households in Brunei Darussalam. Four typical residential houses were identified in the study and these are the following: Type A: terrace house Type B: detached house Type C: single average house Type D: single big house Key typical household information and electricity consumption are given in Table 4-1. Other assumptions used in the analysis such as appliance ownership and usage are shown in the Appendix. Table 4-1. Typical household information and electricity consumption Typical House Building Area (m 2 ) Number of bedrooms Occupancy level Occupants A kids school, 2 adults working B ,7 3 kids, 2 adults working, 1 not working C ,7 4 kids, 2 working adults, 1 not working D ,8 5 kids, 2 working adults, 1 not working Electricity Consumption (kwh) Daily Monthly Watts Type A (1500 kwh/month) Type B (2100 kwh/month) Type C (2550 kwh/month) Type D (3000 kwh/month) :00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 Figure 4-2. Daily consumption profile for typical households RE WPS 1 FIT vs NM page 14

19 Based on the above household information, appliance ownership and behavioural patterns in Brunei, the daily load consumption profile of typical households were constructed. Household electricity demand peaks in the morning at around 6 o clock, at noontime and at around 5 o clock in the evening. This is shown in Figure 4-2. Consumed and Exported Production To determine the amount of electricity that will be consumed and exported to the grid by typical households, these daily consumption patterns were superimposed by the production profile of the 10 kwp PV system derived in section 2 of this report. This is shown in Figure 4-3. The figure shows that household electricity consumption between 7:30 in the morning and 3:30 in the afternoon could be covered by the 10 kwp solar PV plant. The area bounded by this time range and under the load profile curve represents the electricity consumption that would be covered by the solar PV plant while the area above the load profile but under the solar production curve represents the amount of electricity that could be exported to the grid. This is shown in columns 7 and 8 of Table Watts :00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Type A (1500 kwh/month) Type B (2100 kwh/month) Type C (2550 kwh/month) Type D (3000 kwh/month) Figure 4-3. Household consumption patterns and 10 kwp PV production profile Table 4-2. Share of 10 kwp solar PV plant daily production consumed by each typical house Typical House Building Area (m 2 ) Number of bedrooms Occupancy level Electricity Consumption (kwh) Share of 10 kwp PV production daily monthly consumed exported A B , C , D , RE WPS 1 FIT vs NM page 15

20 Roof Area Limitation The 10 kwp solar PV system if installed in a typical house A could export 70 percent of daily electricity generation while if installed in typical house D could only export 51 percent of the total daily production. Electricity generation (and PV plant capacity installation) is however constrained by the available roof area. The 10 kwp solar PV plant used in the analysis requires a total roof area of 65 m 2 (Figure 4-4). This implies that typical houses A and B may be able to provide a roof area for smaller systems and that only typical houses C and D may have sufficient roof spaces for a 10 kwp PV system. For the rest of the study, the analysis will focus on typical house D. 6.5 meters 10 meters Figure 4-4. Roof area required for 10 kwp solar PV plant 4.3 Opportunity Cost of Consumed Electricity The solar PV power plant will displace grid generation hence the opportunity cost of consuming power from PV installation is represented by the price of the grid power. For a typical house D, the average price of electricity is B$ cents 7.6 per kwh (USD cents per kwh) (Table 4-3). The consumed electricity for typical house D is 6,470 kwh per year, and in money terms, this amounts to USD 397 per year. RE WPS 1 FIT vs NM page 16

21 Table 4-3. Opportunity cost of consumed electricity Units (kwh) Tariff Rate (BND/kWh) Electricity consumption of typical house D (kwh per month) Opportunity Cost (B$) 1 to to to and above 0.12 TOTAL average B$ cents 7.6/kWh 4.4 Required Tariff for Exported Electricity The consumed and exported electricity for typical house D using 10 kwp solar PV plant is shown in Figure 4-5. The consumed amount remained constant over 20 years at 6,470 kwh. The exported energy on the first year amounts to 6,427 kwh and would slightly decline over the years due to module degradation reaching 5,246 kwh in year kwh exported consumed Year Figure 4-5. Consumed and exported energy for typical house D using 10 kwp solar PV plant To incentivize residential households to invest on rooftop solar PV plant under the net metering scheme, the tariff rate for exported energy should be high enough to recoup the household s investments. Using the same financial and technical parameters for 10 kwp solar PV system as in the feed-in tariff scheme, and subtracting the benefits derived from self-consuming 49% of total generation, the levelized cost of exported energy is USD cents per kwh. RE WPS 1 FIT vs NM page 17

22 4.5 Financial Cash Flow under Net Metering Scheme Under the net metering scheme, the benefits that could be derived from consuming power generation would be relatively small since the current tariff rates in the country are highly subsidized. To incentivize households to invest on an expensive solar PV system under this scheme, the export tariff rate must be raised sufficiently high to allow recovery of investments. Figure 4-6 shows the investor s financial cash flow under the net metering scheme. Though almost half of the total production is consumed, the equivalent benefit is relatively small. With this the required export tariff to meet the target investment returns is USD cents per kwh which is close to double the required tariff under the feedin tariff scheme. With this tariff rate, the simple payback period under net metering policy would be the same as those in feed-in tariff scheme which is 8 years. 49% of electricity generated is consumed on site (benefit is based on DES tariff rate) 51% of electricity generated is exported to the grid (required tariff is very high at USD per kwh) USD 3,549 USD 397 Revenue from exports (red) USD 2,902 USD 397 Benefit from displaced DES Power (blue) USD Payback Period OPEX USD 150/year CAPEX USD 30,000 Figure 4-6. Financial cash flow under net metering scheme RE WPS 1 FIT vs NM page 18

23 5 Policy Recommendation Feed-in tariff and net metering policies are two of the regulatory instruments that have been successfully introduced in many developed and developing countries to stimulate private investments and accelerate deployment of solar PV technologies, though globally there are more countries that introduced feed-in tariff schemes than net metering schemes. Both policy frameworks would be applicable in Brunei Darussalam but would require disparate policy design, tariff rates, connection and metering requirements. Either of these policies should however provide sufficient incentives to households to invest on solar PV systems. Given the unique electricity supply market structure, institutional arrangement and other conditions in the country, the study analyses the tariff requirements of these policy measures that provide necessary incentives to households. The feed-in tariff policy framework is a straightforward approach that provides direct incentives to households. Households are incentivized to become distributed power generators and sell their generated electricity to the grid. The tariff rate of locally produced electricity is based on levelized production costs with reasonable but competitive rate of return. The required tariff for a 10 kwp PV system with total investment cost of USD 30,000 per system, discount rate of 12 percent and tariff duration of 20 years, is USD cents 30 per kwh. The payback period for this tariff rate is more than 8 years. Net metering policy allows residential households to produce their own electricity and sell excess generation to the grid. This policy measure would be attractive to households in countries where electricity tariffs are not subsidized and are expensive such as in Singapore or the Philippines. In Brunei, net metering could however be made attractive if the export tariff for excess electricity be set at a certain level to ensure attractive returns of investment. The study shows that for 10 kwp solar PV system to be installed in a typical household with monthly consumption of 3000 kwh, around 49 percent of power generation would be consumed and the remaining 51% would be exported to the grid. From households point of view, the opportunity cost of consumed power is equal to the subsidized rates of the Department of Electrical Services. Exported power under the net metering scheme therefore requires a very high tariff rate. For the 10 kwp system, the required export tariff is USD cents per kwh which is almost twice as the tariff rate under the feed-in tariff scheme. A very high tariff rate could have several implications. One of which is to stimulate households to maximize their investment benefits by investing in oversized capacities and perhaps engaging in other schemes that could have positive or negative implications. The study therefore recommends to start with the feed-in tariff scheme as the key policy framework to stimulate private investments and to scale-up deployment of renewable energy technologies. In the future, once tariff reforms are introduced and coupled with declining technology costs, and once solar PV power generation would achieve or approach close to grid parity, net metering could be introduced. RE WPS 1 FIT vs NM page 19

24 6 Appendix Table 6-1. Appliance ownership and power rating for typical houses Equipment Typical House Power A B C D rating (W) AC Fan Chiller/Freezer to Water heater Light x36 Appliances (PC, TV, etc) Table 6-2. Appliance usage for typical houses Equipment Typical House A B C D # usage hours # usage hours # usage hours # usage hours AC x10 Fan x10, Chiller/Freezer Water heater Light Appliances (PC, TV, etc) x2 RE WPS 1 FIT vs NM page 20