Stochastic Optimal Reconfiguration and Placement of Photovoltaic Systems in Distribution Networks: A Real Case Study

In this paper, a stochastic multi-objective (MO) modeling for the optimal reconfiguration and placement of photovoltaic (PV) systems in distribution networks (DNs) is presented. The main objectives are to jointly maximize the profit of generating companies (GenCos) as well as to minimize the distribution company's (DisCo) costs and the expected interruption cost (ECOST). This approach can provide numerous economic and technical advantages for all players in the restructured power system, including GenCos, DisCos, and customers. To attain more practical and accurate results in the simultaneous placement of PVs and reconfiguration, uncertainties are considered in the problem formulation. To cope with the stochastic behavior of PV systems, electricity prices, and demands in the DN, the scenario approach is used. The proposed optimization problem is solved by the dragonfly algorithm (DA) and the best compromise solution is chosen using a fuzzy satisfying criterion. The results are also compared with the particle swarm optimization (PSO) algorithm. To confirm the effectiveness of the proposed MO model, it is implemented on the IEEE 33-bus DN and simulated in various case studies. The model is also applied to a real DN. The results confirm that the proposed model gives a more desired schedule than previous approaches, as all players in the DN including the PV owners, DisCo, and customers are satisfied at the same time.