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相对于传统大电网,新能源高渗透率下微网中的不确定因素是限制微网发展的关键.为克服传统优化运行中仅考虑单一不确定性导致的调度结果保守性问题,该文深入研究微网中的不确定因素,从不确定理论出发,将风电出力和光伏出力分别处理为模糊随机变量和模糊变量,构造双重不确定环境下的机会约束模糊随机规划模型.为更为灵活直观地描述该环境下的复杂双重不确定性,利用机会测度衡量模糊随机事件的机会,并提出一种模糊随机模拟技术与遗传算法相结合的混合智能算法对机会约束模糊随机规划模型进行求解.针对不同置信水平下的最优解,进一步将传统优化问题中单一的经济分析扩展为风险分析,分析结果表明,随着置信水平的减小,微网运行成本降低,而对新能源发电的管控也随之降低,导致风险增大.以一个包含风、光、储以及燃料电池和微型燃气轮机的微网系统为实例进行计算分析,验证该模型及求解算法的可行性及有效性.“,”Compared with the traditional power grid,the uncertain factors of microgrid with high permeability of new energies are the keys of limiting microgrid development.To overcome the conservative problem of traditional optimal operation scheduling results considering single uncertainty,this paper deeply studied the uncertain factors of microgrid and started from the uncertainty theory.A chance constrained fuzzy random programming model under double uncertainty environment was constructed while processing the wind power output as fuzzy random variable and the photovoltaic power output as fuzzy variable.To describe the complex double uncertainty under this environment in a more flexible and intuitive way,a chance measure function was used to measure the chance of fuzzy random events and a hybrid intelligent algorithm combining fuzzy random simulation technology and genetic algorithm was used on the solution of chance constrained fuzzy random programming model.Aiming at the optimal solution under different confidence level,the single economic analysis in the conventional optimization problem was further extended to a risk analysis.The analysis results show that along with the lower confidence level and the less operation costs,the control on new energy power generation decreases which leads to an increasing risk.A typical microgrid consisting of wind turbine,photovoltaic,storage battery,fuel cell and micro turbine was selected as a calculation and analysis example.The results verify the feasibility and effectiveness of the proposed model and algorithm.