Determination of optimal layout of wind turbines inside a wind farm in presence of practical constraints

被引:0
作者
Mittal, Prateek [1 ]
Mitra, Kishalay [1 ]
机构
[1] Indian Inst Technol Hyderabad, Dept Chem Engn, Medak 502285, Telangana, India
来源
2019 FIFTH INDIAN CONTROL CONFERENCE (ICC) | 2019年
关键词
Wind farm; turbine; noise; habitat; forbidden zone; multi-objective optimization; evolutionary algorithm; OPTIMIZATION; DESIGN; NUMBER;
D O I
10.1109/indiancc.2019.8715616
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Wind energy, one of the most promising alternative sources of energy to cater energy needs at the current time, is generally harvested placing wind turbines optimally inside a wind farm. However, limited availability of land has resulted in the construction of wind farms nearby human dwellings, restricted zones and natural habitats (rivers, forests) causing a negative impact on the human health, wildlife, and the environment. Using a widely used wake model and ISO-9613-2 noise calculation method, a multi-objective optimization among three important conflicting objectives such as noise propagation, investment cost, and energy generation has been performed in this study to determine the optimal layout (numbers and positions) of wind turbines inside a wind farm. Along with this, the effects of practical constraints such as the presence of human habitats and forbidden zone inside a wind farm is also studied. A novel space decomposition based approach with repair (SDwR) strategy implemented on the basic platform of non-dominated sorting genetic algorithm (NSGA II) has been proposed to solve this problem. Pareto optimal (PO) solutions are generated that allow the decision maker to choose among various layouts by considering the permissible noise standards, cost obligations, and land availability.
引用
收藏
页码:353 / 358
页数:6
相关论文
共 13 条
[1]   Performance assessment of a wind power plant using standard exergy and extended exergy accounting (EEA) approaches [J].
Aghbashlo, Mortaza ;
Tabatabaei, Meisam ;
Hosseini, Seyed Sina ;
Dashti, Behrouz B. ;
Soufiyan, Mohamad Mojarab .
JOURNAL OF CLEANER PRODUCTION, 2018, 171 :127-136
[2]  
Deb K., 2001, Multi-objective Optimization Using [Deb, 2001] Evolutionary Algorithms
[3]   Multi-Objective Random Search Algorithm for Simultaneously Optimizing Wind Farm Layout and Number of Turbines [J].
Feng, Ju ;
Shen, Wen Zhong ;
Xu, Chang .
SCIENCE OF MAKING TORQUE FROM WIND (TORQUE 2016), 2016, 753
[4]   Solving the wind farm layout optimization problem using random search algorithm [J].
Feng, Ju ;
Shen, Wen Zhong .
RENEWABLE ENERGY, 2015, 78 :182-192
[5]   Irregular-shape wind farm micro-siting optimization [J].
Gu, Huajie ;
Wang, Jun .
ENERGY, 2013, 57 :535-544
[6]   A Review of Methodological Approaches for the Design and Optimization of Wind Farms [J].
Herbert-Acero, Jose F. ;
Probst, Oliver ;
Rethore, Pierre-Elouan ;
Larsen, Gunner Chr. ;
Castillo-Villar, Krystel K. .
ENERGIES, 2014, 7 (11) :6930-7016
[7]   Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach [J].
Mittal, Prateek ;
Mitra, Kishalay ;
Kulkarni, Kedar .
ENERGY CONVERSION AND MANAGEMENT, 2017, 132 :147-160
[8]   A novel hybrid optimization methodology to optimize the total number and placement of wind turbines [J].
Mittal, Prateek ;
Kulkarni, Kedar ;
Mitra, Kishalay .
RENEWABLE ENERGY, 2016, 86 :133-147
[9]   OPTIMIZATION OF WIND TURBINE POSITIONING IN LARGE WINDFARMS BY MEANS OF A GENETIC ALGORITHM [J].
MOSETTI, G ;
POLONI, C ;
DIVIACCO, B .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 1994, 51 (01) :105-116
[10]   Design of optimal wind farm configuration using a binary particle swarm optimization at Huasai district, Southern Thailand [J].
Pookpunt, Sittichoke ;
Ongsakul, Weerakorn .
ENERGY CONVERSION AND MANAGEMENT, 2016, 108 :160-180