引用本文: | 赵晋泉,胡佳,王珂,等.一种日前发电调度与日前分时电价联合优化模型[J].电力系统保护与控制,2019,47(9):56-63.[点击复制] |
ZHAO Jinquan,HU Jia,WANG Ke,et al.A joint optimization model of day-ahead generation scheduling and day-ahead time-of-use price[J].Power System Protection and Control,2019,47(9):56-63[点击复制] |
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摘要: |
为充分发挥电价对市场需求的调节作用,有效引导需求侧资源参与电网调度,提出一种日前发电调度与日前分时电价(Time-of-Use, TOU)联合优化模型。考虑分时电价对用户收益的影响,以最大化社会福利和最小化峰谷差为目标函数,通过源荷两侧的协调调度来增强分时电价的实施效果。考虑负荷响应的差异性,对各类负荷实施不同的分时电价。计及电网公司让利约束,在保障用户和电网公司利益的前提下,电网公司以让利的形式将因分时电价带来的电网缓建获益适当转嫁给用户,以实现经济效益的共享。结合NSGA-II算法和优先顺序法求解该多目标优化问题,根据最大满意度法从Pareto解集中选取最优解。通过对修改的IEEE 39节点系统算例的仿真,验证了所提模型的有效性。 |
关键词: 分时电价 日前调度 社会福利 利益共享 需求响应 |
DOI:10.7667/PSPC181405 |
投稿时间:2018-11-11修订日期:2019-03-15 |
基金项目:国家重点研发计划项目资助(2017YFB0902600) |
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A joint optimization model of day-ahead generation scheduling and day-ahead time-of-use price |
ZHAO Jinquan,HU Jia,WANG Ke,YAO Jianguo,YANG Shengchun,SU Dawei,XU Chunlei |
(Research Center for Renewable Energy Generation Engineering of Ministry of Education, Hohai University, Nanjing 210098, China;State Grid Electric Power Research Institute, Nanjing 210003, China;Jiangsu Electric Power Dispatching and Control Center, Nanjing 210024, China) |
Abstract: |
In order to give full play to the regulatory role of electricity price on demand, and effectively guide demand side resources to participate in scheduling, a joint optimization model of day-ahead generation scheduling and day-ahead time-of-use (TOU) price is proposed. Considering the impact of TOU on user benefits, the objective functions are the maximum social welfare and the minimum peak-valley difference, so as to enhance the effect of TOU by the coordinated scheduling of supply side and demand side. For the load response difference to the electricity price, different TOU schemes for different loads are designed. On the premise of protecting the interests of users and the utility companies, the utility companies transfer the benefits of delayed grid expansion to users to realize benefit sharing in the form of ceding profits, so the constraint of utility company ceding profits is considered in the model. The NSGA-II algorithm and priority list are used to solve this multi-objective optimization problem. The optimal solution is selected from the Pareto solutions by using the maximum satisfaction method. The simulation results of the modified IEEE 39-buses system show that the proposed method is effective. This work is supported by National Key Research and Development Program of China (No. 2017YFB0902600). |
Key words: time-of-use price day-ahead scheduling social welfare benefit sharing demand response |