在主动配电网中分布式资源(distributed energy resources,DERs)渗透率不断上升及电力市场改革不断推进的背景下,高比例DERs引起的线路过载和节点电压越限等网络阻塞现象不容忽视。针对主动配电网的阻塞问题,该文提出基于配电网节点电价...在主动配电网中分布式资源(distributed energy resources,DERs)渗透率不断上升及电力市场改革不断推进的背景下,高比例DERs引起的线路过载和节点电压越限等网络阻塞现象不容忽视。针对主动配电网的阻塞问题,该文提出基于配电网节点电价(distribution location marginal price,DLMP)的日前-实时阻塞管理模型。在日前阶段,各负荷聚合商(aggregator,Agg)首先预测日前市场电价并收集相关DERs信息,然后配电网管理员在保证用户用电需求的同时使其用电支出最小,并兼顾网络约束制定DLMP发布给Agg,Agg得到日前交易计划;在实时阶段,各Agg更新DERs信息,并根据配电网管理员更新的DLMP重新调整日前交易产生的偏差。最后,通过IEEE33节点算例进行仿真验证,结果表明提出的阻塞管理模型可以有效解决主动配电网在日前和实时两阶段的阻塞问题,保证线路容量及节点电压在允许的安全范围内。展开更多
This paper proposes a distribution locational marginal pricing(DLMP) based bi-level Stackelberg game framework between the internet service company(ISC) and distribution system operator(DSO) in the data center park. T...This paper proposes a distribution locational marginal pricing(DLMP) based bi-level Stackelberg game framework between the internet service company(ISC) and distribution system operator(DSO) in the data center park. To minimize electricity costs, the ISC at the upper level dispatches the interactive workloads(IWs) across different data center buildings spatially and schedules the battery energy storage system temporally in response to DLMP. Photovoltaic generation and static var generation provide extra active and reactive power. At the lower level, DSO calculates the DLMP by minimizing the total electricity cost under the two-part tariff policy and ensures that the distribution network is uncongested and bus voltage is within the limit. The equilibrium solution is obtained by converting the bi-level optimization into a single-level mixed-integer second-order cone programming optimization using the strong duality theorem and the binary expansion method. Case studies verify that the proposed method benefits both the DSO and ISC while preserving the privacy of the ISC. By taking into account the uncertainties in IWs and photovoltaic generation, the flexibility of distribution networks is enhanced, which further facilitates the accommodation of more demand-side resources.展开更多
基金supported in part by the 2021 Graduate Research and Innovation Program of Jiangsu,China (No.KYCX21_0473)the China Scholarship Council (CSC) Program (No.202106710110)。
文摘This paper proposes a distribution locational marginal pricing(DLMP) based bi-level Stackelberg game framework between the internet service company(ISC) and distribution system operator(DSO) in the data center park. To minimize electricity costs, the ISC at the upper level dispatches the interactive workloads(IWs) across different data center buildings spatially and schedules the battery energy storage system temporally in response to DLMP. Photovoltaic generation and static var generation provide extra active and reactive power. At the lower level, DSO calculates the DLMP by minimizing the total electricity cost under the two-part tariff policy and ensures that the distribution network is uncongested and bus voltage is within the limit. The equilibrium solution is obtained by converting the bi-level optimization into a single-level mixed-integer second-order cone programming optimization using the strong duality theorem and the binary expansion method. Case studies verify that the proposed method benefits both the DSO and ISC while preserving the privacy of the ISC. By taking into account the uncertainties in IWs and photovoltaic generation, the flexibility of distribution networks is enhanced, which further facilitates the accommodation of more demand-side resources.
