Coordinated Optimal Placement of Energy Storage System and Capacitor Bank Considering Optimal Energy Storage Scheduling for Distribution System Using Mixed-Integer Particle Swarm Optimization

Abstract

This paper proposes a mixed-integer particle swarm optimization (MIPSO) for coordinated optimal placement of energy storage system (ESS) and capacitor bank (CB). In the propose method, optimal ESS scheduling (OESSS) is solved by particle swarm optimization (PSO), as a subproblem, the optimal coordinated placement (COP) for ESS and CB, simultaneously. The distribution system annual loss minimization (DSALM) is used as the objectives of COP problem. The proposed method was tested with the IEEE 33-bus radial distribution test system. The results demonstrated that the proposed method is successful and robust in minimizing system losses, which loss saving of 35.12% when compare to the based case, which is the best solution among other existing methods.

Self-Adaptive Dragonfly Algorithm for Optimal Allocation of Multiple Energy Storage Systems with VAr Support for Islanded Microgrid Operation

“…On the other hand, network reconfiguration along with DGs and CBs can further improve the network performance. [35], mixed-integer particle swarm optimization (MIPSO) [36], genetic algorithm [37], self-adaptive butterfly algorithm (SABOA) [38], and honey badger algorithm [HBA] [39], and many other algorithms as seen in [40], have been used for simultaneous DGs/CBs allocation and network reconfiguration. In this connection, the current work can be further extended for reconfiguration.…”

Simultaneous Optimal Network Reconfiguration and Allocation of Four Different Distributed Generation Types in Radial Distribution Networks Using a Graph Theory-Based MPSO Algorithm

“…Using random weighted inverse vector (RWIV) and dual-phase parasitism (DPP) made NeSOS faster, more accurate and better performance than SOS. In addition, there are other technologies that are used to reduce losses and improve the voltage profile such as optimal integration of energy storage systems and capacitor bank as in [20], a coordinated optimal placement problem (COPP) of energy storage system (ESS) and capacitor bank was proposed and solved simultaneously using mixed-integer particle swarm optimization (MIPSO). Optimal ESS scheduling (OESSS) was considered as a sub problem and was solved by PSO, the goals of the COPP are to reduce distribution system annual losses.…”