摘要
针对风电与规模化电动汽车入网给电力调度带来的挑战,建立了基于动态约束处理的风电与电动汽车协同作用的环境经济模糊决策调度优化模型。该模型包含风电机组和入网的电动汽车(vehicle to grid,V2G),以同时降低燃料成本和减少污染排放量为优化目标,在满足系统功率平衡和车主日常出行需求等约束条件下,通过动态调节电动汽车充放电功率和时间来最大限度地消纳过剩风电,平抑风能出力波动对电力系统的冲击;接着对常规机组进行负荷经济分配,以达到协同优化调度的经济性;同时采用多目标纵横交叉优化算法(multi-objective crisscross optimization algorithm,MOSCO)优化算法求解模型,利用模糊决策机制获得最优折中解;最后以10台机组测试系统为算例,仿真结果验证了模型及方法的有效性与合理性。
In viewof challenges in electric power dispatching brought by wind power and scaled electric vehc ing to the power grid, an environmental economic fuzzy decision-making dispatching optimizationmodel considering syner-gistic effect of wind power and EVbased on dynamic constraint was buiU. Thismodel includedwind power generators and vehicle to grid （V2G） and took reduction of fuel costs and pollution emission as optimized objects. On the premise of satisfy-ing constraint conditions including system power balance and daily trip demand of owners , this model could absorb excessive wind power farthett by dynamically adjutt charging and discharging power and time of EV as well power output fluctuation on the power system. According to economic distribution for load of conventional units , it could re-alize economy of synergistic optimized dispatching. Meanwhile , it adopted MOCSO optimized algorithm for solution andused fuzzy decision-making mechanism to obtain optimal compromise solution. Finally , ten-unit testing system was taken as an example for simulation , which proved effectiveness and reasonability of this model and method.
出处
《广东电力》
2017年第10期35-42,共8页
Guangdong Electric Power
基金
广东电网有限责任公司科技项目(GDKJQQ20152066)
关键词
模糊决策
环境经济调度
风电
电动汽车
V2G
fuzzy decision-making
environmental economic dispatching
wind power
electric vehicle
vehicle to grid（V2G）
