水电站库区翻坝能源-物流耦合调度优化OA
Energy-logistics coupled scheduling optimization for cross-dam in hydropower reservoir areas
为解决水电站大坝阻断造成的翻坝运输成本高昂与碳排放严重问题,提出了一种结合电-氢-油多能互补的翻坝能源-物流耦合调度优化方法.针对翻坝货物在水路和陆路间的分流特点,分析了涵盖多类型重卡及水路转运设施的翻坝物流运行特性,建立了物流设施能耗模型;基于制充储氢一体站等设施的运行功率特征,构建了能源设施产能模型.结合能源供需耦合机理刻画,建立翻坝能源-物流耦合调度优化模型.以运行成本最低为目标,兼顾碳排放与负荷响应能力,对翻坝能源与物流进行耦合优化,得到货流分配及物流和能源设施的调度方案.以西南某6 400 MW水电站库区为例,仿真结果表明,所提方法能够有效降低翻坝运行成本和碳排放.
To address the high transportation costs and severe carbon emissions caused by dam blockages at hydropower stations,a cross-dam energy-logistics coupled dispatching optimization method that integrates electricity-hydrogen-oil multi-energy complementarity is pro-posed.According to the flow diversion characteristics of cross-dam cargo between waterway and land routes,the operational characteristics of cross-dam logistics covering heterogeneous heavy-duty trucks and waterway handling facilities are analyzed,and energy consumption models for transportation equipment are established.Based on the operational power characteristics of facilities such as integrated hydrogen production-charging-storage stations,energy facility production models are constructed.Combined with the characterization of energy sup-ply-demand coupling mechanisms,a cross-dam energy-logistics coupled dispatching optimization model is established.With the objective of minimizing operational costs while considering carbon emissions and load response capability,coupled optimization is performed on cross-dam energy and logistics systems to obtain cargo flow distribution and dispatching strategies for transportation and energy equipment.Taking a 6 400 MW hydropower station in Southwest China as a case study,simulation results demonstrate that the proposed method can ef-fectively reduce cross-dam operational costs and carbon emissions.
贾清茹;刘皓明;普月;王健
河海大学 电气与动力工程学院,南京 211100河海大学 电气与动力工程学院,南京 211100河海大学 电气与动力工程学院,南京 211100河海大学 电气与动力工程学院,南京 211100
交通工程
水电站翻坝物流能源-物流耦合耦合优化节能减排
hydropower stationcross-dam logisticsenergy-logistics couplingcoupled optimizationenergy saving and emission reduction
《电力需求侧管理》 2026 (3)
7-13,7
国家自然科学基金资助项目(52207091)
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