Optimal reactive power resources sizing for power system operations enhancement based on improved grey wolf optimiser

被引:35
|
作者
Taha, Ibrahim B. M. [1 ,2 ]
Elattar, Ehab E. [1 ,3 ]
机构
[1] Taif Univ, Dept Elect Engn, Coll Engn, At Taif, Saudi Arabia
[2] Tanta Univ, Fac Engn, Dept Elect Engn, Tanta 31521, Egypt
[3] Menoufia Univ, Dept Elect Engn, Fac Engn, Shibin Al Kawm 32511, Egypt
关键词
RADIAL-DISTRIBUTION NETWORKS; GRAVITATIONAL SEARCH ALGORITHM; PARTICLE SWARM OPTIMIZATION; LEARNING-BASED OPTIMIZATION; OPTIMAL CAPACITOR PLACEMENT; BEE COLONY ALGORITHM; DISTRIBUTED GENERATORS; GENETIC ALGORITHM; FLOW PROBLEM; ALLOCATION;
D O I
10.1049/iet-gtd.2018.0053
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In recent years, optimal sizing and location of reactive power resources are drawing much attention to help the operators of the utilities to enhance the power system operations. Therefore, this work presents a new version of grey wolf optimiser (GWO) to solve the problem of optimal reactive power resources sizing for power system operation enhancement. The proposed method which called improved grey wolf optimiser (IGWO) can be derived by modifying the exploration-exploitation balance in the conventional GWO to enhance its rate of convergence. Also, the weighted distance strategy is employed in the proposed IGWO to overcome the drawback of the conventional GWO. Optimal reactive power resources sizing problem is nonlinear and non-convex optimisation problem. To solve this problem, different objective functions are used. These objective functions are minimisation of generating cost, minimisation of transmission power loss and voltage profile improvement. The validity and superiority of the proposed IGWO method are tested using three standard IEEE systems for normal and contingency conditions. Then the results are compared with those obtained from other recently published algorithms. The simulation results show that the proposed IGWO method is more accurate and efficient than other recently published algorithms.
引用
收藏
页码:3421 / 3434
页数:14
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