Bi-level optimization for demand response integration with solar pv and battery energy storage systems: Enhancing distribution network efficiency and sustainability

The integration of distributed energy resources (DERs) offers significant potential to enhance the efficiency and resilience of distribution networks (DNs). Yet, high penetration of distributed generation (DG), particularly solar photovoltaic (PV), can introduce voltage instability, higher losses, and reverse power flows. Addressing these challenges, this study presents a novel bi-level optimization framework that jointly coordinates DG placement, battery energy storage systems (BESS), and price-based demand response (DR). In the upper level, a Grey Wolf Optimizer (GWO) determines the optimal siting and sizing of DG and BESS; the lower level schedules real-time BESS dispatch with DR participation. Metaheuristic GWO is adopted for its strong exploration–exploitation balance in the nonlinear, mixed-integer search space of AC power-flow constraints. Using the IEEE-33 bus test system, six integration scenarios were evaluated. The best configuration—Case 6 (DG + BESS + DR)—reduced annual energy losses by 46.8 %, improved the average voltage profile to 1.01 p.u., shaved the peak demand by ∼50 %, and achieved a payback period of 4.4 years with the lowest levelized cost of energy (LCOE). These findings demonstrate that coordinated DER planning and real-time control can significantly improve technical and economic performance, providing actionable guidance for utilities seeking smarter and more sustainable power-distribution systems.