Optimization of wind farm layout considering wake effect and multiple parameters

Abstract

The output power of wind farms in real world applications is lower than the theoretical output which is largely due to wake effect. So as to maximize the output power, the wake effect of upstream wind turbines on downstream ones should be attenuated. Thus, arrangement of wind turbines in a wind farm is an essential issue that needs to be tackled. This study pursues the aim of finding an optimal layout. Initially, Jensen wake model is applied to simulate the wake effect. Then, genetic algorithm is employed to optimize the wind farm layout considering multiple factors that include different hub heights, rotor diameters, variable induction factors, power and capacity factor curves. Three cases including constant wind–constant direction, constant wind–variable direction and variable wind–variable direction are studied and compared with previous studies. The results indicate that the efficiency of the wind farm for case 1 is 96.71% which is a high record comparing to the previous literature. For Case 2 and 3, the annual wind farm capacity factor (CF) is found to be 97.96 and 97.51%. The power output of Case 1, 2, and 3 are 5.6855 × 108 kWh, 5.6694 × 108 kWh, and 4.5572 × 108 kWh, respectively. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13146, 2019

Enhanced Chaotic Manta Ray Foraging Algorithm for Function Optimization and Optimal Wind Farm Layout Problem

“…This approach is called a genetic algorithm; it extracts a maximum output power at a minimum cost per unit value. For the same algorithm applied by Mosetti, several works employed GA and its variants [4] - [12]. Referring to [13], the authors attempted to solve the power produced by a wind farm using the particle swarm optimization approach (PSO).…”

Wind power resources assessment at 10 different locations using wind measurements at five heights

“…10 The African and Middle East wind power markets are expected to grow by 10.9 GW capacity over next 5 years with particular contributions of 3.5, 1.8, 1.2, and 1.2 GW from South Africa, Egypt, Morocco, and Saudi Arabia. 10 Keeping in view the necessity of safeguarding our environment and hence the planet, wind power related research and development, [11][12][13][14][15] resource assessment and potential site selection, [16][17][18][19][20] wind speed and power characteristics, [21][22][23][24][25][26] technoeconomic feasibilities, 27,28 wind farm layout and energy output optimization studies, 29,30 grid connectivity and storage issues, 31,32 wind power economics, 22,33,34 renewable energy policy development, [35][36][37] and various other important aspects are being addressed and reported in the literature. Accurate wind power resource assessment is the key for selecting a potential and profitable site for wind farm development.…”

Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization

“…However, there are still some challenges facing these applications. The main issue associated with wind energy is that the actual power generated by wind farms is less than its theoretical power capacity due to the wake effect, wind velocity variations, angle variations, wind turbine inefficiencies, and transmission line problems [14][15][16]. The wake effect can be characterized as wind speed reduction and turbulent flow creation downstream of wind turbines [17][18][19][20].…”

“…As a result, this impact can reduce power generation by 10-20%. An enhanced layout of wind turbines can significantly improve power output and reduce its associated charges [14,21]. The power generated in a wind turbine is related to the perfect square of the receiving wind speed.…”