A multiobjective approach for optimal placement and sizing of distributed generators and capacitors in distribution network

被引:85
|
作者
Biswas, Partha P. [1 ]
Mallipeddi, R. [2 ]
Suganthan, P. N. [1 ]
Amaratunga, Gehan A. J. [3 ]
机构
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore
[2] Kyungpook Natl Univ, Daegu, South Korea
[3] Univ Cambridge, Dept Engn, Cambridge, England
基金
新加坡国家研究基金会;
关键词
Radial distribution network; Distributed generator (DG); Shunt capacitor (SC); Power loss; Multiobjective optimization; MOEA/D algorithma; POWER LOSS MINIMIZATION; RADIAL-DISTRIBUTION NETWORKS; OPTIMAL ALLOCATION; DISTRIBUTION-SYSTEMS; DG; OPTIMIZATION; ALGORITHM; HYBRID; MAXIMIZATION; UNITS;
D O I
10.1016/j.asoc.2017.07.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Both active and reactive power play important roles in power system transmission and distribution networks. While active power does the useful work, reactive power supports the voltage that necessitates control from system reliability aspect as deviation of voltage from nominal range may lead to inadvertent operation and premature failure of system components. Reactive power flow must also be controlled in the system to maximize the amount of real power that can be transferred across the power transmitting media. This paper proposes an approach to simultaneously minimize the real power loss and the net reactive power flow in the system when reinforced with distributed generators (DGs) and shunt capacitors (SCs). With the suggested method, the system performance, reliability and loading capacitycan be increased by reduction of losses. A multiobjective evolutionary algorithm based on decomposition (MOEA/D) is adopted to select optimal sizes and locations of DGs and SCs in large scale distribution networks with objectives being minimizing system real and reactive power losses. MOEA/D is the process of decomposition of a multiobjective optimization problem into a number of scalar optimization subproblems and optimizing those concurrently. Case studies with standard IEEE 33-bus, 69-bus, 119-bus distribution networks and a practical 83-bus distribution network are performed. Output results of MOEA/D method are compared with similar past studies and notable improvement is observed. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:268 / 280
页数:13
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