Battery energy storage with renewable energy sources integration in unbalanced distribution network considering time of use pricing

• Proposed optimal PV and BESS allocation in unbalanced distribution system (URDS) • Voltage unbalanced factor (VUF) of URDS as a metric for performance evaluation. • Impact of varying PV and BESS in each phase of URDS. • Load-dependent sensitivity analysis for power loss, voltage profile and VUF. • Multi-objective Pelican optimization considering NPC and VPEI factors. • Charging-discharging strategy of BESS for peak and off-peak hours and TOU pricing. The increasing demand for sustainable energy solutions and the escalating energy demand have facilitated the emergence of renewable energy sources (RES), such as photovoltaic (PV) sources. Combining RES with battery energy storage system (BESS) technology reduces peak hour demand and allows for economical charging and discharging for time-based energy pricing. Integrating PV and BESS in an unbalanced system with multiple RES sources is a challenging task. It requires a robust algorithm to minimise power loss in the distribution system and decrease the voltage unbalance factor (VUF). This paper presents a new multi-objective Pelican optimisation algorithm (MOPOA) for the optimal allocation of PV and BESS. The MOPOA helps find the best placement of PV and BESS in an IEEE-33 bus unbalanced radial distribution system (URDS). The proposed algorithm combines multiple benefits from a lower net present cost (NPC) and a higher voltage profile enhancement index (VPEI). The case studies and simulation results show that the proposed method places PV and BESS in IEEE 33-bus URDS optimally, satisfying all of the system’s requirements. The results indicate an improvement in the minimum VUF factor of 4.4% in a winter day and 4.3% in a summer day; a reduction in active power loss of 16% in a winter day and 7.1% in a summer day; and a reduction in reactive power loss of 7.5% in a winter day and 7.2% in a summer day. Thus, the recommended strategy effortlessly accelerates to a suboptimal solution.