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Optimal Demand Response Scheduling with Real Time Thermal Ratings of Overhead Lines for Improved Network Reliability

机译:基于实时热额定值的架空线最优需求响应调度提高网络可靠性

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摘要

Abstract— This paper proposes a probabilistic framework for optimal demand response scheduling in the day-ahead planning of transmission networks. Optimal load reduction plans are determined from network security requirements, physical characteristics of various customer types and by recognising two types of reductions, voluntary and involuntary. Ranking of both load reduction categories is based on their values and expected outage durations, whilst sizing takes into account the inherent probabilistic components. The optimal schedule of load recovery is then found by optimizing the customers’ position in the joint energy and reserve market, whilst considering several operational and demand response constraints. The developed methodology is incorporated in the sequential Monte Carlo simulation procedure and tested on several IEEE networks. Here, the overhead lines are modelled with the aid of either seasonal or real-time thermal ratings. Wind generating units are also connected to the network in order to model wind uncertainty. The results show that the proposed demand response scheduling improves both reliability and economic indices, particularly when emergency energy prices drive the load recovery.
机译:摘要—本文提出了一种概率框架,用于在输电网络的日前计划中优化需求响应调度。最佳的负载减少计划是根据网络安全要求,各种客户类型的物理特征以及通过识别两种减少类型(自愿的和非自愿的)来确定的。两种负载减少类别的排名均基于它们的值和预期的停机时间,而规模调整则考虑了固有的概率因素。然后,在考虑几个运营和需求响应约束的同时,通过优化客户在联合能源和储备市场中的位置,找到最佳的负载恢复计划。所开发的方法被并入顺序蒙特卡洛仿真程序中,并在多个IEEE网络上进行了测试。在这里,架空线是根据季节性或实时热额定值建模的。风力发电机组也连接到网络,以便对风力不确定性进行建模。结果表明,提出的需求响应调度可以提高可靠性和经济指标,特别是在紧急能源价格推动负荷恢复的情况下。

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