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Day-ahead scheduling of virtual power plant in joint energy and regulation reserve markets under uncertainties

机译:不确定性下联合能源和监管储备市场中虚拟电厂的提前调度

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This paper presents a day-ahead scheduling framework for virtual power plant (VPP) in a joint energy and regulation reserve (RR) markets. The proposed VPP clusters a mix of generation units in term of synchronous distributed generation (SDG) and wind power plant (WPP) as well as storage facilities such as electrical vehicles (EVs) and small pumped storage plant (PSP). It is assumed that VPP provides required RR through its SDG and small PSP based on the delivery request probability of day-ahead market. In order to aggregate EVs, the VPP establishes bilateral incentive contracts with vehicle owners. Moreover, impact of carbon dioxide (CO2)emission of SDG is included by means of penalty cost function. Different uncertain parameters with regard to wind generation, EV owner behaviors, energy and RR market prices and regulation up and down probabilities are considered using a point estimate method (PEM). The case studies are applied to demonstrate the effectiveness of the scheduling model. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文提出了在联合能源与监管储备(RR)市场中虚拟电厂(VPP)的提前调度框架。拟议的VPP将同步分布式发电(SDG)和风力发电厂(WPP)以及诸如电动汽车(EV)和小型抽水蓄能电站(PSP)等存储设施组合在一起。假定VPP根据日前市场的交付请求概率通过其SDG和小型PSP提供所需的RR。为了汇总电动汽车,VPP与车主建立了双边激励合同。此外,SDG排放的二氧化碳(CO2)的影响还包括惩罚成本函数。使用点估计法(PEM)考虑有关风力发电,电动车拥有者行为,能源和RR市场价格以及调节上下概率的不同不确定参数。通过案例研究来证明调度模型的有效性。 (C)2017 Elsevier Ltd.保留所有权利。

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