摘要
未来配电系统可再生能源渗透率日益提高。针对配网中风电消纳问题,考虑在系统中引入具有负荷转移特性的冰蓄冷空调进行需求响应控制,将夜间产生的风能转化为冷能并以冰形式存储,在日间用电峰段融冰释冷削减空调的用电峰值。具体来说,考虑系统内供电公司和风电生产商的综合运行成本以及空调用户的用电成本,建立基于能源效率和经济效益的多目标优化模型。以供电公司、风电生产商和空调用户的利益最大化为目标,采用非支配排序遗传算法-Ⅱ(NSGA-Ⅱ)对Pareto非支配解集进行求解,生成的Pareto解集,通过模糊隶属度法过滤选取最优解。最终根据最优解内参数变量的数值,对空调制冷机功率和蓄冰设备的融冰量进行调控。提出的算例验证了所提方法的有效性和可行性。
In the future,the distribution rate of renewable energy in distribution systems is increasing.For the problem of wind power consumption in distribution networks,it is considered to introduce the ice storage air conditioning with load transfer characteristics in the system to control the demand response,and convert the wind energy generated at night into cold energy and ice storage,reducing the peak electricity consumption of air conditioners during the daytime peaking of ice melting.Specifically,considering the comprehensive operating costs of power supply companies and wind power producers in the system as well as the cost of electricity for air-conditioning users,it establishes the multi-objective optimization model based on energy efficiency and economic benefit which aims at maximizing the interests of power supply companies,wind power producers and air-conditioning users.The non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)is used to solve the Pareto non-dominated solution set.The optimal solution of the generated Pareto solution set is filtered and selected by the fuzzy membership method.Finally,according to the value of the parameter variables in the optimal solution,the power of the air conditioner and the ice melting capacity of the ice storage device are regulated.The effectiveness and feasibility of the proposed method is verified by the example.
作者
何后裕
郭健翔
王永利
HE Houyu;GUO Jianxiang;WANG Yongli(Quanzhou Power Supply Company,State Grid Fujian Electric Power Company,Quanzhou 362000,China;North China Electric Power University,Beijing 102206,China)
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2019年第23期180-187,共8页
Power System Protection and Control
基金
北京社科基金项目资助(18GLB034)~~
关键词
风电消纳
冰蓄冷空调
多目标优化
非支配排序遗传算法
wind power consumption
ice storage air conditioning
multi-objective optimization
non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)
