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

• Published in: Applied soft computing 2017-11, Vol.60, p.268-280
• Main Authors: Biswas, Partha P., Mallipeddi, R., Suganthan, P.N., Amaratunga, Gehan A.J.
• Format: Article
• Language: English
• Subjects: Distributed generator (DG); MOEA/D algorithm; Multiobjective optimization; Power loss; Radial distribution network; Shunt capacitor (SC)
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2017.07.004

[Display omitted] •Distribution network real power loss and reactive power loss are minimized.•Rating and location of both distributed generator and shunt capacitor are optimized.•Multiobjective evolutionary algorithm based on decomposition (MOEA/D) is applied.•Several case studies with various radial bus systems are performed.•Results are compared with most recent studies and improvement is observed. 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 capacity can 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.