上海交通大学学报

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能源-交通融合下电-气-热多能系统协同优化调度方法(网络首发)

  

  1. 1.上海电力大学电气工程学院;2.清华大学智能与网络化系统研究中心
  • 基金资助:
    国家重点研发计划项目(2022YFA1004600)

Collaborative Optimization Scheduling Method for Electric-Gas-Thermal MultiEnergy System Under Energy-Transportation Integration

  1. (1. College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090,China; 2. Center for Intelligent and Networked Systems, Tsinghua University, Beijing 100084, China)

摘要: 双碳目标下,能源系统与交通系统的交互程度将不断加深,存在多元能源-交通系统的协同优化调度问题,为此提出了能源-交通融合下电-气-热多能系统协同优化调度方法。首先,基于融合DBSCAN的K-means聚类算法与Dijkstra算法,对待调度交通车辆聚类,并对道路网架结构及车辆运行与车到网(V2G)技术参与的能量传递模式进行建模,交通对象为电动车、天然气车;在此基础上以系统总成本最小与总用电负荷波动最小为目标构建双层优化调度模型;最后,通过算例分析,验证了该模型在降低系统成本、减小碳排放、提高风光消纳能力的有效性与多能系统调度的优越性。

关键词: 能源-交通融合系统, 双层优化, 电-气-热多能系统

Abstract: Under the dual carbon target, the interaction between energy systems and transportation systems will continue to deepen, and there is a collaborative optimization scheduling problem of multiple energy-transportation systems. Therefore, a collaborative optimization scheduling method of electric-gas-thermal multi-energy systems under energy-transportation integration is proposed. Firstly, based on the K-means clustering algorithm fused with DBSCAN and Dijkstra algorithm, the clustering analysis of the scheduled traffic vehicles was carried out, and the road network structure and the energy transfer mode of vehicle operation and Vehicle to Network (V2G) technology were modeled. The traffic objects were electric vehicles and natural gas vehicles. On this basis, a twolevel optimization scheduling model was constructed with the goal of minimizing the total system cost and the total power load fluctuation. Finally, through the numerical example analysis, the effectiveness of the model in reducing system cost, reducing carbon emissions, improving scenery absorption capacity and the superiority of multi-energy system scheduling are verified.

Key words: energy-transportation integration system, bilevel optimization, electric-gas-thermal multi-energy system

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