Reducing demand charges and onsite generation variability using behind-the-meter energy storage

B. Bhattarai, Kurt S. Myers, Jason Bush
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引用次数: 19

Abstract

Electric utilities in the United States are increasingly employing demand charges and/or real-time pricing. Such directive is bringing potential opportunities in deploying behind-the-meter energy storage (BMES) systems for various grid applications. This study quantifies the techno-economic benefits of BMES in reducing demand charge and smoothing load/generation intermittencies, and determines how those benefits vary with different penetration of onsite photovoltaic. We proposed a two-stage control algorithm, whereby the first stage proactively determines the cost-optimal BMES configuration for reducing peak demands and demand charges and the second stage adaptively compensates intermittent generations and short load spikes that may otherwise increase the demand charges. The performance of the proposed algorithm is evaluated through a 24-hours time sweep simulation performed using data from a smart microgrid testbed at Idaho National Laboratory. The simulation results demonstrated that this research provides a simple and effective solution for peak shaving, demand charge reductions, and onsite photovoltaic variability smoothing.
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使用表后储能降低了需求费用和现场发电的可变性
美国的电力公司越来越多地采用按需收费和/或实时定价。这一指令为各种电网应用部署电表后储能(BMES)系统带来了潜在的机会。本研究量化了BMES在降低需求费用和平滑负荷/发电间歇性方面的技术经济效益,并确定了这些效益如何随现场光伏的不同渗透率而变化。我们提出了一种两阶段控制算法,其中第一阶段主动确定成本最优的BMES配置以降低峰值需求和需求费用,第二阶段自适应补偿间歇性发电和短负荷峰值,否则可能会增加需求费用。通过使用爱达荷国家实验室智能微电网试验台的数据进行24小时时间扫描模拟,评估了所提出算法的性能。仿真结果表明,本研究提供了一种简单有效的解决方案,可用于调峰、降低需求费用和现场光伏变异性平滑。
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