Energy Optimization Strategy for Reconfigurable Distribution Network with High Renewable Penetration Based on Bald Eagle Search Algorithm

This paper proposes a cost-optimal energy management strategy for reconfigurable distribution networks with high penetration of renewable generation. The proposed strategy accounts for renewable generation costs, maintenance and operating expenses of energy storage systems, diesel generator operational costs, typical daily load profiles, and power balance constraints. A penalty term for power backflow is incorporated into the objective function to discourage undesirable reverse flows. The Bald Eagle Search (BES) meta-heuristic is adopted to solve the resulting constrained optimization problem. Numerical simulations under multiple load scenarios demonstrate that the proposed method effectively reduces operating cost while preventing power backflow and maintaining secure operation of the distribution network.