考虑需求侧响应及V2G的综合能源系统随机优化
Stochastic optimization of integrated energy system considering demand-side response and vehicle-to-grid situation
卢健航 1张淼 1肖国威 1许方圆 1董越2
作者信息
- 1. 广东工业大学 自动化学院,广州 510006
- 2. 国网宁夏电力有限公司中卫供电公司,宁夏 中卫 751700
- 折叠
摘要
为解决高比例新能源综合能源系统中风力、光伏等不确定因素,以及电动汽车无序充电对综合能源系统稳定运行带来的问题,提出一种包含需求侧响应以及电动汽车入网的随机优化调度方法,以优化综合能源系统的运行.根据负荷特性将用户负荷分类,建立用户负荷的需求侧响应模型.基于不确定因素的历史数据,使用场景法生成典型场景.以综合能源系统的经济运行为目标,建立综合能源系统随机优化模型,并通过算例分析该优化模型效果.研究结果表明,该优化模型可以有效减少负荷峰谷差,提高系统运行稳定性,降低系统运行成本.
Abstract
To address the uncertainties arising from high proportions of renewable sources such as wind and photovoltaics in intergrated energy systems,along with the challenges posed by the uncoordinated charging of electric vehicles on the stable operation of the system,proposes a stochastic optimization scheduling method that incorporates demand-side response and the integration of electric vehicles into the grid.The goal of this method is to optimize the operation of the integrated energy system.Loads are categorized based on their load characteristics,and a demand-side response model for user loads is established.Utilizing historical data characterized by uncertain factors,the scenario-based method is employed to generate representative scenarios.With the economic operation of the integrated energy system as the objective,a stochastic optimization model for the integrated energy system is established.The effectiveness of this optimization model is assessed through numerical analysis.Research outcomes indicate that the proposed optimization model significantly reduces the fluctuations in load peaks and valleys,enhances the stability of system operation,and reduces overall operational costs.
关键词
综合能源系统/场景分析/需求侧响应/随机优化/电动汽车/削峰填谷Key words
integrated energy system/scenario analysis/demand-side response/stochastic optimization/electric vehicles/peak shaving and valley filling引用本文复制引用
基金项目
广东省基础与应用基础研究项目(2021A1515010742)
出版年
2024
NETL
NSTL
万方数据