For the economic and environmental protection multi-objective optimization scheduling of the Micro-grid ,and traditional intelligent algorithms are easy to fall into local optimization and premature convergence, with the dualistic factor contrast method, the economy and environmental protection multi objective optimization model is transformed into a single objective optimization model, and a Micro-grid scheduling strategy in time-of-use price mechanism with charging and discharging of battery and a new adaptive bird swarm optimization algorithm based on Levy flight strategy (LSABSA) are proposed, the bird swarm optimization algorithm is based on bird foraging, vigilance and flight behavior. Meanwhile, 5 typical test functions are used to compare LSABSA, bird swarm algorithm (BSA), particle swarm optimization (PSO) and improved particle swarm optimization (GPSO) algorithm to verify the superiority of LSABSA algorithm. Finally, the typical day in summer Micro-grid system including cold and electric loads is taken as an example, and the LSABSA algorithm is used to simulate the economic, environmental and multiobjective models. The results show the feasibility of the improved algorithm and the effectiveness of multiobjective optimization.%针对微电网经济环保多目标优化调度以及传统智能算法易陷入局部最优和早熟收敛的问题,利用二元对比定权法将经济环保多目标转化为单目标优化模型,提出了在分时电价机制下含蓄电池充放电的微电网优化调度策略,并采用一种新型的以鸟类觅食、警惕和飞行行为为依据的基于Levy飞行策略的自适应改进鸟群算法(LSABSA),同时利用5个典型测试函数对LSABSA、鸟群算法(BSA)、粒子群(PSO)和改进粒子群算法(GPSO)进行仿真对比分析,验证了LSABSA算法的优越性.最后,以包含冷、电负荷的夏季典型日微电网系统作为算例,采用LSABSA算法对经济、环保和多目标模型进行仿真,结果表明了改进算法的可行性以及多目标优化的有效性.
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