Multi-Objective Framework of Energy Efficiency for Configuration Management with Battery Energy Storage in Distribution Networks Using Harmony Search Algorithm Amidst Probabilistic Loading Patterns

Energy efficiency performance (EEP) in power supply continuously changes depending on the load demand type and operation period. Integrating electric vehicles and battery energy storage (BES) has made it imperative. Therefore, in practice, it might be quite difficult for distribution system operators to concurrently meet the load demands of as many customers as possible at peak loading conditions. In the literature, distributed generation integration for loss minimization is a predominant approach, whereas BES can work as a source or load that can directly or indirectly affect the EEP. This work uses a heuristic technique to create multiple probabilistic loading patterns for EEP of small, medium and extra-large radial networks. The performance indicators such as node voltage profile, loadability, reliability, power losses, and computational efficacy are used. The multi-objective problem is solved using a harmony search algorithm (HSA). For robustness, the performance of the proposed approach is compared with the existing approach available in the literature. Moreover, the EEP is evaluated for 33-, 69-, 85-, 119-, 137- and 417-node radial networks while configuration management with enhanced EEP in the interest of utilities and customers with BES as a load and source exclusively.