【摘要】 针对农村及偏远地区可利用的生物质能以及我国扶贫攻坚进入最后阶段,建立了含风、柴、储,生物质能的微电网,综合考虑燃料、电能交互、投资折旧、维护及环境成本等变动成本,使系统在一个调度周期内的总运行成本最低,建立了微电网多目标经济优化模型。在计及国家对可再生能源补贴价格的基础上,采用改进遗传算法进行求解。当基本遗传算法陷入某个局部最优解时,从临时Parcto解集中保留拥挤距离最大的个体,使个体密度小的Parcto解占优,从而使算法迅速跃出局部最优。24 h内优化的结果对比表明,所提的优化调度方案具有很好的实用性和应用前景。更多还原

【Abstract】 In view of the biomass energy available in rural and remote areas and China’s poverty alleviation program entering the final stage, the micro-grid containing wind, diesel,storage and biomass energy can be built with comprehensive considerations given to variable costs of fuel, electrical energy interaction, investment depreciation, maintenance and environmental costs, so that the system is operated at the lowest total operating cost within a scheduling period. A multiobjective economical optimization model of the micro-grid is established, and on the basis of taking into account the state’s subsidy price for renewable energy, an improved genetic algorithm is used to solve the problem. When the basic genetic algorithm is trapped in a local optimal solution, the individual with the largest crowded distance is preserved from the temporary Parcto solution set, so that the Parcto solution with small individual density is dominant, and the algorithm quickly jumps out of the local optimum. The comparison of the results within 24 hours of optimization shows that the proposed optimal scheduling scheme has good practicality and application prospects.更多还原