摘要
针对园区综合能源系统中可再生能源消纳和冷热电负荷波动的问题,本文引入了电转气技术。同时,结合可平移的电负荷、灵活的热负荷和冷负荷,本文建立了一个考虑综合需求响应和电转气技术的园区综合能源系统优化调度方法。为了解决海量数据和约束条件对求解复杂度的影响,研究组将非凸数据模型处理转换为混合整数线性规划(MILP)模型,并通过MATLAB结合YALMIP调用CPLEX求解器进行算法求解。通过对比算例分析,本文考虑了综合需求响应对于削峰填谷、可再生能源消纳以及园区综合能源系统整体经济性的影响,以验证所搭建模型的有效性和合理性。
In solving the problems of renewable energy integration and fluctuating combined cooling,heating,and power(CCHP)loads in the integrated energy system of an industrial estate,this paper introduces the power-to-gas(P2G)technology.Simultaneously,considering the dispatchability of electrical loads as well as the flexibility of thermal and cooling loads,an integrated energy system optimization scheduling method for the industrial estate is established,taking into account integrated demand response and P2G technology.To mitigate the impact of extensive data and constraints on computational complexity,the research team transforms the non-convex data model into a mixed integer linear programming(MILP)model.Algorithmic solutions are obtained by utilizing MATLAB in conjunction with YALMIP and invoking the CPLEX solver.Through comparative case studies,this paper investigates the influence of integrated demand response on peak shaving,renewable energy accommodation,and the overall economic viability of the industrial estate's estate energy system.This serves to validate the effectiveness and rationality of the proposed model.
作者
韩钰
徐婷婷
吴迪凡
HAN Yu;XU Tingting;WU Difan(Shibei Power Supply Company,State Grid Shanghai Municipal Electric Power Company,Shanghai 201900,China)
出处
《电力大数据》
2023年第8期23-31,共9页
Power Systems and Big Data
