摘要
微网中可再生能源和负荷功率等具有不确定性,传统的经济调度模型已不再适用。针对微网运行中各种随机性因素的影响,建立了基于机会约束规划并计及制热收益的热电联产型微网动态经济调度模型,以一个包含风、光、储、微型燃气轮机、燃料电池以及热电负荷的微网为例,运用结合蒙特卡罗模拟的改进遗传算法优化了并网下各微源和外网的功率,并对比分析了微源和外网分别承担微网内部波动时一天内的综合成本和蓄电池充放电次数。通过算例验证了所提模型和算法的有效性。
Due to the uncertainties of renewable energy generation and load power, the traditional economic dispatch models are not applicable to microgrid. In order to deal with various stochastic factors in the operation of CHP micro- grid, the dynamic economic dispatch model is established based on chance constrained programming and heating in- come. A microgrid consisting of a wind turbine, photovohaic cells, a storage battery, a micro turbine, a fuel cell, heating and electric loads is selected as the research object. The improved genetic algorithm based on Monte Carlo sim- ulation is chosen to optimize the power of microsources and external network in grid-connected mode. The comprehen- sive costs and storage battery charge and discharge times in one day are comparatively analyzed when microsource and external network undertake internal fluctuation of microgrid respectively. The validity of the proposed model and algo- rithm is proved by the examples.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2013年第4期22-28,共7页
Proceedings of the CSU-EPSA
基金
国家863高技术基金项目(2011AA05A106)
上海市科委重点科技攻关计划(11dz1210405)
曙光计划(10SG51)
上海高等教育"085"工程建设项目
上海市教育委员会重点学科建设项目(J51301)
关键词
分布式电源
微网
动态经济调度
机会约束规划
蒙特卡罗模拟
改进遗传算法
distributed generation
microgrid
dynamic economic dispatch
chance constrained programming
MonteCarlo simulation
improved genetic algorithm
