Microgrid Dispatching Optimization Based on Improved Multi‐Objective Firefly Algorithm

Aiming at the problems of slow convergence speed, susceptibility to local optima, and insufficient diversity when the multi‐objective firefly algorithm (MOFA) is leveraged to solve the microgrid dispatching optimization problem, the research proposes an improved multi‐objective firefly algorithm (IMOFA) and applies it to microgrid dispatching. An enhanced attraction factor is designed and incorporated into the movement formula of dominant fireflies to strengthen attractiveness and accelerate convergence. For non‐dominant fireflies, an external archive guidance term is introduced into their movement formula, which optimizes their movement pattern, enhances global exploration capability, and avoids local optima. A hierarchical penalty function is proposed. By dynamically adjusting the penalty factor and designing different indicator function differences of equality constraints and inequality constraints to penalize terms, the constraint handling effect is improved. An environmental selection mechanism based on adjacent distance is constructed. The adjacent distance is leveraged to measure the crowding degree of solutions to maintain the diversity and uniform distribution of offspring solutions. Based on IMOFA, a microgrid dispatching optimization model (IMOFA‐MG) with operation cost and pollutant gas treatment cost as objective functions is established. To verify the optimization performance of IMOFA and the dispatching efficiency of IMOFA‐MG, comparison tests involving IMOFA and 5 other algorithms are carried out, and dispatching simulation experiments are conducted for the IMOFA‐MG model. The results show that on benchmark test problems, IMOFA has better convergence performance and can solve optimization problems; in dispatching simulation experiments, the IMOFA‐MG model can obtain a set of dispatching scheme Pareto frontiers with better convergence and distribution. The effectiveness of IMOFA‐MG in dispatching optimization is verified.