在低碳发展和能源转型的背景下，探索综合能源系统，有助于减少对传统化石能源的依赖，有益于能源结构的调整和能源可持续发展的进程。基于传统混合储能系统的出力特性，构建了结合用户侧需求响应模型的三级混合储能系统模型，利用"源—网—储—荷"的互补关系，提出了 4 种方案。通过采用带精英策略的快速非支配排序遗传算法(Nondominated Sorting Genetic Algorithm-Ⅱ，NSGA-Ⅱ)进行优化，帕累托前沿解集利用优劣解距离法(Technique for Order Preference by Similarity to Ideal Solution，TOPSIS)找出每种方案的最优解，并得到了电网和热网各设备的最佳运行情况。结果表明:相较于独立运行模式，电和热需求响应模型优化加入后，在各指标相同偏好下系统每日可以节省成本 463。5 元，减少碳排放 4。36 kg，但同时会影响系统的独立性。
Research on the integrated energy system supply and demand optimization operation based on NSGA-Ⅱ
In the context of low-carbon development and energy transition,the exploration of integrated energy systems has been conducted to reduce reliance on traditional fossil fuels and support the adjustment of energy structure and sustainable energy development.Based on the output characteristics of conventional hybrid energy storage systems,a three-level hybrid energy storage system model incorporating user-side demand response models has been constructed.By utilizing the complementary relationship of"source-grid-storage-load",four alternative schemes have been proposed.Optimization is conducted using a fast Nondominated Sorting Genetic Algorithm-Ⅱ(NSGA-Ⅱ)with an elite strategy.The Pareto front solution set is obtained using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)to identify the optimal solutions for each scheme,and the optimal operation conditions of each device in the electricity grid and heating network are determined.The results show that,compared with the independent operation mode,incorporating electrical and thermal demand response models can save 463.5 CNY per day and reduce carbon emissions by 4.36 kg,under the same preference for each index.However,this integration impacts the system's independence.
integrated energy systemsNondominated Sorting Genetic Algorithm Ⅱdemand responseTOPSIS
万方数据
维普
