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Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract

机译:需求响应承诺合同下住宅楼中分布式能源的优化调度

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摘要

This study proposes optimal day-ahead demand response (DR) participation strategies and distributed energy resource (DER) management in a residential building under an individual DR contract with a grid-system operator. First, this study introduces a DER management system in the residential building for participation to the day-ahead DR market. The distributed photovoltaic generation system (PV) and energy-storage system (ESS) are applied to reduce the electricity demand in the building and sell surplus energy on the grid. Among loads in the building, lighting (LTG) and heating, ventilation, and air conditioning (HVAC) loads are included in the DR program. In addition, it is assumed that a power management system of an electric vehicle (EV) charging station is integrated the DER management system. In order to describe stochastic behavior of EV owners, the uncertainty of EV is formulated based on their arrival and departure scenarios. For measuring the economic efficiency of the proposed model, we compare it with the DER self-consuming operation model without DR participation. The problem is solved using mixed integer linear programming to minimize the operating cost. The results in summer and winter are analyzed to evaluate the proposed algorithm’s validity. From these results, the proposed model can be confirmed as reducing operation cost compared to the reference model through optimal day-ahead DR capacity bidding and implementation.
机译:本研究提出了在与网格系统运营商的个人DR合同下的住宅建筑中最佳的日前需求响应(DR)参与策略和分布式能源资源(DER)管理。首先,本研究介绍了住宅建筑中的DER管理系统,以参与前面的博士市场。应用分布式光伏发电系统(PV)和储能系统(ESS)以降低建筑物中的电力需求并销售网格上的剩余能量。在建筑物中的载荷中,DR程序中包括照明(LTG)和加热,通风和空调(HVAC)负载。另外,假设电动车辆(EV)充电站的电源管理系统集成了DER管理系统。为了描述EV所有者的随机行为,EV的不确定性基于其到达和出发场景制定。为了测量拟议模型的经济效率,我们将其与DER自耗操作模型进行比较,无需参与。使用混合整数线性编程来解决问题,以最小化运营成本。分析了夏季和冬季的结果,评估了所提出的算法的有效性。通过这些结果,通过最佳的一天DR容量竞标和实现,可以确认所提出的模型与参考模型相比降低运营成本。

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