Viability of Micro Wind Turbines in the Urban Environment

Transcription

1 Viability of Micro Wind Turbines in the Urban Environment World Renewable Energy Forum WREF/WREN May 13-17, 2012, Denver, Colorado Ghanim Putrus Reader in Electrical Power Engineering Power and Wind Energy Research (PaWER) group School of Computing, Engineering and Information Sciences Northumbria University Newcastle upon Tyne NE16 5RD, UK Mahinsasa Narayana Keith Sunderland Michael Conlon Dublin Institute of Technology, Ireland Dublin Institute of Technology, Ireland

2 Viability of Micro Wind Turbines in the Urban Environment Presentation Outline Introduction and Background Energy Conversion in Micro Wind Turbines Siting of Wind Turbines Sensitivity Analysis Results Optimal System Configuration Conclusions

3 Introduction A growing economy means a growing demand for electrical energy. The Kyoto Protocol Targets Developed countries to reduce greenhouse gas emissions by ~ 5% of 1990 levels in the period The 20/20/20 energy targets for European countries; By 2020: 20% reduced CO2 emission 20% lowered energy consumption 20% more renewable energy in the system The UK Energy Policy 80% reduction of greenhouse gas emissions below 1990 levels by % UK Electricity from renewables by 2020 (currently, this is ~6%) This will require: ~ 10 GW of Renewables 10 GW e of Combined Heat and Power (CHP) capacity by 2010! This will require hundreds of large CHP and numerous CHP installations.

4 The UK Electricity Generation Mix and Challenges Main Challenges to Renewable Energy: Ambitious targets Cost 2009 Reliability and safety Technical problems Connection to the grid Voltage and frequency control Public acceptance 2020

5 Wind Energy Conversion Systems Wind energy conversion systems (WECS) are currently the most fast growing commercial resources of renewable energy. Factors that largely affect the economic viability of WECS (including micro wind turbines) include: Initial cost per kw generated Maintenance costs Potential energy generated Average wind speed Turbine type, size, mechanical design, etc. Maximum power point tracker (MPPT) The actual value of 1 kwh of electricity produced, which depends on the fuel price, load profile and electricity tariff.

6 Generation as a percentage of sales Source: Ofgem Sustainable Development Report, November 2007 Growth of Renewable Generation Capacity in the UK RO : Renewables Obligation Micro generation can help meeting the targets for renewable energy. Micro generation (including micro wind generation) is still at early stages of market penetration.

7 Micro Wind Turbines Current trends show a growing market for micro wind systems. In the rural environment, the average wind speed is relatively high and the wind speed/direction is reasonably stable. In the urban environment, the average wind speed tends to be low and wind direction is constantly changing (turbulent wind). Performance of the wind turbines in the urban environment is very sensitive to the location and is generally poor. Most micro WTs do not perform as expected and operate without adequate MPP tracking. Micro wind systems are generally expensive (over 2,500 per kw installed) and payback time (particularly for the urban environment) currently is unrealistically long.

8 Micro Wind Turbines Available studies on the performance of micro wind turbines in the urban environment are generic, e.g. that technology can work if installed correctly and in appropriate locations! There is a need to establish the various factors that affect performance of small scale wind turbines, particularly in the urban environment, and find out minimum requirements to make such installations commercially viable.

9 Main Components of Micro Wind Turbine Micro wind turbines can be: Horizontal axis (HAWT) Vertical axis (VAWT). Wind Power P Wind Aerodynamic power extracted by the wind rotor A.C. power generated PMG Rectifier MPPT Inverter P wind P Losses Aerodynamic losses P loss = I G 2 + Friction losses Power Electronic converter losses

10 Power Wind Energy Conversion The captured power by the wind rotor depends on the wind speed and wind turbine aerodynamic characteristics. According to Betz s law, the aerodynamic power extracted by the wind rotor is: Maximum aerodynamic power points of the wind rotor P Where a 1 2 C p is the air density. ρ. A. v A is the turbine swept area = R 2 v (R is the radius of the rotor) is the wind speed 3 C p is the power coefficient which depends on the pitch angle of the wind rotor blades and on the tip speed ratio ( ) defined as: V 1 V 2 Rotational speed V 3 V 4 Wind rotor curves at different wind speeds.r v is the rotational speed of the rotor

11 Power Operating Points of Wind Turbine Rotor At steady state, wind turbine generator systems are operated at the points where the wind rotor curve and the electrical generator curve coincide. These points may not represent the optimal condition of the system. When the wind speed varies, the rotor speed should be adjusted to follow the optimum operating point for maximum power generation. However, changing the rotor speed to follow the variation of wind speed is particularly difficult in turbulent wind conditions. Maximum aerodynamic power points of the wind rotor Operating points Restoring power curve of the generator Wind rotor PMG V 1 V 2 V 3 V 4 Wind speeds Rotational speed Wind rotor curve (Fixed pitched wind turbine)

12 Wind Energy Conversion The coefficient C p has a maximum value at a certain value of which results in a maximum possible (theoretical) power extraction of ~60%. MPP tracking in turbulent wind conditions is very difficult (not effective) due to the inertia of the wind turbine. This, in addition to losses due to blade roughness, hub, tip, generator and inverter losses result in a reduction of the overall energy conversion to around 30%. Wind power (100%) Mechanical Power Electrical Power Electrical Power output ( 30%) Aerodynamic losses ( 55%) Electric generator losses ( 10%) Converter losses ( 5%)

13 Siting of Small Wind Turbine In most of the places in the UK, the wind speed is more than 5 m/s at 25 m height. Siting of wind turbines is very important to achieve accepted performance. Location; Location; Location! The BERR developed Numerical Objective Analysis of Boundary Layer (NOABL) Wind Speed Database ultilises an air flow model that estimates the effect of topography on wind speed. This model is limited by the fact that there is no allowance for the effect of local thermally driven winds and also by virtue that it has a 1 km 2 resolution (at either 10 m, 25 m or 45 m above ground level) in which there is no consideration of small scale topography. In more constricted (urban) areas, wind speeds will be lower and wind resource estimation, particularly at lower elevations, is very challenging. Annual mean wind speed

14 Sensitivity Analysis Cost of energy and initial cost of the system are the most important parameters to evaluate economic viability of small wind power systems. Cost Of Energy (COE) is the average cost per 1 kwh ( /kwh) of useful electrical energy produced by the system and may be described as: COE E prim C E anntot, def grid, sales Where; C ann,tot = Total average annual cost of the system ( /Year), E prim = Primary load served (kwh/year), E def = Deferrable load served (kwh/year), E grid,sales = Total grid sales (kwh/year) E Estimated cost of a typical small system is 2,500-5,000 per kw capacity installed, though this may go down to less than 1,000 with mass production. The maintenance costs are between 1.5% and 3% of the turbine cost but increase with time as the turbines get older.

15 Sensitivity Analysis The average annual capital cost (C ann,cap ) of the system may be represented as: Where C ann, cap Ccap. CRF ( i, N) C cap = Initial capital cost ( ) CRF(i, N) = Capital recovery factor defined as: N i(1 i) CRF ( i, N) N (1 i) 1 i = Annual interest rate N = Project lifetime measured in number of years System considered: 2.4 kw micro wind turbine system (Skystream 3.7). Initial cost of the system = 9500 Annual operation and maintenance cost = 250. Life time of the system = 25 years Replacement cost is considered equal to initial cost of the system (salvage cost is neglected). The annual interest rate = 6%. Annual energy production is determined based on power curves provided by the manufacturer.

16 Power demand (kw) Power Flow and Load Profiles 2.4 kw micro wind turbine system (Skystream 3.7) Grid Main Distribution Board Generation Grid sales and purchases Electricity demand Household consumer 1.4 Summer Autumn and spring 1.2 Winter Time (hr) Typical daily load profile for a domestic load Based on ADMD referenced to a nominal 100 consumers and measured at a distribution substation on an outgoing feeder

17 Energy (kwh) Wind speed (m/s) Typical Energy Production A typical wind pattern in UK was considered (hourly wind data based on 5 m/s annual mean wind speed). Grid sales and purchases were calculated by considering hourly based energy generation of the wind turbine and typical domestic demand throughout the year Energy production by the wind turbine(kwh) Grid sales (kwh) Monthly mean wind speed (m/s) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Monthly mean wind speed, energy production and grid sales for 5 m/s annual mean wind speed 0

18 Results of Sensitivity Analysis HOMER micro power optimisation model (developed by National Renewable Energy Laboratory, USA) was used to calculate cost of energy for various initial cost values and different annual mean speeds. Annual energy productions by the wind turbine (SW- Skysream3.7) and cost of energy production based on different initial cost values for different annual mean speeds were determined.

19 Initial cost per 1kW installation Annual Energy Productions and Cost of Energy Production by the Wind Turbine per kwh 2.4 kw micro wind turbine system (SW-Skystream3.7) Annual mean wind speed 3m/s 4m/s 5m/s 6m/s 7m/s 8m/s 9m/s 7, , , , , , , , , AEP (kwh) Assuming current electricity buying price of ~0.15 /kwh, a minimum average wind speed of 5 m/s is needed to make the wind turbine a cost effective source of electricity based on current prices and technology used. This agrees with the recommendation of the Energy saving Trust, UK.

20 Optimal System Configuration Optimal system configuration to supply domestic demand is analysed by considering energy cost for grid supply only or grid in addition to an integrated wind turbine. Energy cost of grid supply integrated with wind turbine depends on time based energy demand, energy generation by wind turbine, electricity Feed In Tariff and buying price. HOMER was used to determine optimal system configuration for different initial cost and various annual mean speeds. A grid-connected wind turbine would be cost effective within the area shaded in green. The cost of electricity generation per kwh for a micro grid-connected wind turbine

21 Viable Initial Cost of Micro Wind Turbines Annual mean wind speed Viable maximum initial cost per 1 kw capacity installed 3 m/s < 950 / kw 4m/s 5m/s 6m/s 7m/s < 2280 / kw < 3800 / kw < 5700 / kw < 7410 / kw

22 Conclusions For micro wind turbines to be viable in the urban environment, need to: Reduce the initial cost of the system (to less than 1000/kW capacity installed). Operation cost is comparatively low. Improve the wind turbine aerodynamics and energy capture at low wind speed Reduce power losses in the generator and power electronic converter. Have generous Feed In Tariffs (FIT) for the foreseeable future.

23 Conclusions An important component which affects the performance of the wind turbine system is the maximum power point tracker (MPPT). The turbulent nature of wind in the urban environment and the inertia of the wind turbine make it practically impossible to track the wind speed/direction and operate close to the maximum power point, particularly for HAWTs. It is important to consider the use of advanced dynamic maximum power point tracking control techniques, e.g. wind speed forecasting, predictive control, active yaw control, etc. to maximize energy capture when operating in turbulent wind conditions.

24 Wind speed (m/s) Predictive Control by Considering Wind Speed Forecasting Techniques Wind speed-time series data typically exhibit autocorrelation, which can be defined as the degree of dependence on preceding values. Time series prediction takes an existing series of data and forecasts future values measured Prediction_NN Time (sec)

25 Rotational speed (rad/s) MPPT Performance with and without Wind Prediction Performance of the predictive MPPT control was compared with conventional MPPT control system, which operates without prediction. The results obtained show that predictive control system improves the response time of the MPPT controller and performs well in turbulent wind condition Optimum Actual with prediction Actual without prediction Time (s) Wind rotor Radius of wind rotor : 1.105m Blade profile : NACA4415 Number of blades : 2 Moment of inertia (J) : 9.77kg.m 2

26 Energy Extraction in 1350 Sec With prediction Without prediction Available energy kJ kJ Extracted energy kJ kJ Actual energy extraction % 79.43% 74.73%

27 Viability of Micro Wind Turbines in the Urban Environment Thank You Ghanim Putrus School of Computing, Engineering and Information Sciences Northumbria University Newcastle upon Tyne NE16 5RD, UK