Optimal allocation of distributed energy storage systems to improve performance and power quality of distribution networks
School of Engineering
The placement of grid-scale energy storage systems (ESSs) can have a significant impact on the level of performance improvements of distribution networks. This paper proposes a strategy for optimal allocation of distributed ESSs in distribution networks to simultaneously minimize voltage deviation, flickers, power losses, and line loading. The optimal ESS allocation is investigated through the PQ injection (considering a variable power factor on the dispatch of ESSs) and the results are compared in terms of performance and power quality improvements. An IEEE-33 bus distribution system (medium voltage), having a high influence of renewable (wind and solar) distributed generation, is used as the test network. The overall investigation is conducted for two distinct scenarios: (1) applying a uniform ESS size and (2) applying non-uniform ESS sizes. DIgSILENT PowerFactory is used for developing, analyzing, and testing the system models. The fitness-scaled chaotic artificial bee colony optimization algorithm (a hybrid meta-heuristic technique) is applied to optimize parameters of the objective function. A Python script is used to automate simulation events in PowerFactory. The optimization results are verified through the application of the conventional artificial bee colony algorithm. Detailed simulation results imply that the proposed ESS allocation technique can successfully minimize voltage deviation, flicker disturbance, line loading, and power losses, and thereby significantly improve performance and power quality of a distribution network.