摘要
园区综合能源系统通过多能耦合互补和协同优化调度,可以显著提高能源利用率和促进可再生能源消纳,已成为用户侧满足多能供需的一种新的能源利用实现方式。以河北雄安新区某园区作为研究对象,设计了一种计及负荷供给可靠性的园区综合能源系统两阶段优化方法:第一阶段基于带有精英保留策略的二代非支配排序遗传算法(NSGA-Ⅱ),对园区能源站设备类型及容量进行优化,是一个多目标规划优化问题,其目的是实现经济成本和环境成本的协调优化;第二阶段是一个运行优化问题,针对上一阶段规划得到的多组帕累托前沿解,利用混合整数线性规划(mixed integer linear programming,MILP)分别优化求解各规划方案对应运行成本及负荷供给可靠性指标,结果作为确定系统最佳规划方案的重要参考。算例表明,所设计规划方法可以有效降低系统运行成本和保障负荷供给可靠性,对指导园区综合能源系统规划更具实用性。
The community integrated energy system(CIES)can significantly improve energy utilization and promote the consumption of renewable energy through multienergy coupling complementary and collaborative optimization scheduling.It has become a new energy utilization realization approach for users to meet multi-energy supply and demand.Taking a community in Xiong’an New District,Hebei province as the research object,this paper designed a two-stage optimization approach for the CIES that takes into account the reliability of load supply.The first stage is based on the non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)with elite preservation strategy to optimize the equipment type and capacity of the community energy station.It is a multi-objective planning optimization problem,and its purpose is to achieve the coordinated optimization of economic costs and environmental costs.The second stage is an operation optimization problem.As for the multiple Pareto frontier solutions obtained in the previous planning stage,the mixed integer linear programming(MILP)was used to separately optimize the operation cost and load supply reliability indicators of each planning scheme,and the result is used as an important reference for determining the best planning scheme.Case studies show that the designed planning approach can effectively reduce the system operating cost and guarantee the reliability of load supply,and it is more practical for instructing the CIES planning.
作者
亢猛
钟祎勍
石鑫
温港成
房方
KANG Meng;ZHONG Yiqing;SHI Xin;WEN Gangcheng;FANG Fang(Hebei Xiong’an Branch of China Huaneng Group Co.,Ltd.,Baoding 071799,Hebei Province,China;School of Control and Computer Engineering,North China Electric Power University,Changping District,Beijing 102206,China)
出处
《发电技术》
CSCD
2023年第1期25-35,共11页
Power Generation Technology
基金
国家自然科学基金项目(52176005)
中央高校基本科研业务费专项资金项目(2021MS018)。
