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Quantification of variable effects of demand response resources on power systems with integrated energy storage and renewable resources

机译:量化需求响应资源对具有集成储能和可再生资源的电力系统的各种影响

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This paper reports on the quantification of the variable effects of the integration of demand response resources (DRRs) in a power system with integrated renewable energy sources (RESs) and utility-scale energy storage systems (ESSs) with the various sources of uncertainty explicitly represented. We deploy a stochastic simulation approach based on Monte Carlo techniques to emulate the transmission-constrained hourly day ahead markets (DAMs) over longer term periods. Salient characteristics of the approach are the ability to represent the spatial and temporal correlation of the loads and the renewable resources, the ability to explicitly represent the payback characteristics of DRRs and the deployment of effective strategies to provide computational tractability for large-scale grids. We illustrate the application of the approach to a modified version of the WECC 240 bus-system to perform various study cases to evaluate the economics, emissions and reliability metrics. The studies illustrate the strong capabilities of the approach and provide insights into the impacts of deepening penetration of DRRs under different intensity levels.
机译:本文报告了对具有集成可再生能源(RES)和公用事业规模储能系统(ESS)的电力系统中需求响应资源(DRR)集成的变量影响的量化,其中明确表示了各种不确定性来源。我们部署基于蒙特卡洛技术的随机模拟方法,以模拟较长时期内受传输限制的每小时提前一天市场(DAM)。该方法的显着特征是表示负载和可再生资源的时空相关性的能力,明确表示DRR的投资回收率的能力以及部署有效策略以为大型网格提供计算可处理性的能力。我们举例说明了该方法在WECC 240总线系统的修改版本中的应用,以执行各种研究案例来评估经济性,排放和可靠性指标。这些研究说明了该方法的强大功能,并提供了深入了解在不同强度级别下DRR渗透深度的影响。

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