TY - JOUR
TI - Optimal Placement and Sizing of Renewable Distributed Generation Using Hybrid Metaheuristic Algorithm
AU - Radosavljevic, J.
AU - Arsic, N.
AU - Milovanovic, M.
AU - Ktena, A.
JO - Journal of Modern Power Systems and Clean Energy
PY - 2020
VL - 8
TODO - 3
SP - 499-510
PB - State Grid Electric Power Research Institute
SN - 2196-5625, 2196-5420
TODO - 10.35833/MPCE.2019.000259
TODO - Energy dissipation;  Particle swarm optimization (PSO);  Stochastic models;  Stochastic systems, Gravitational search algorithms;  High-quality solutions;  Hybrid metaheuristic algorithms;  Optimal placement and sizings;  Photovoltaic generation;  Probabilistic models;  Renewable distributed generations;  Total energy loss, Distributed power generation
TODO - The problem of optimal placement and sizing (OPS) of renewable distributed generation (RDG) is followed by numerous technical, economical, geographical, and ecological constraints. In this paper, it is investigated from two viewpoints, namely the simultaneous minimization of total energy loss of a distribution network and the maximization of profit for RDG owner. The stochastic nature of RDG such as the wind turbine and photovoltaic generation is accounted using suitable probabilistic models. To solve this problem, a hybrid metaheuristic algorithm is proposed, which is a combination of the phasor particle swarm optimization and the gravitational search algorithm. The proposed algorithm is tested on an IEEE 69-bus system for several cases in two scenarios. The results obtained by the hybrid algorithm shows that it provides high-quality solution for all cases considered and has better performances for solving the OPS problem compared to other metaheuristic population-based techniques. © 2013 State Grid Electric Power Research Institute.
ER -