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Optimal Stochastic Operation of a Power System Incorporated with Compressed Air Energy Storage and Wind Turbine

机译:带有压缩空气储能和风力涡轮机的电力系统的随机优化运行

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This paper proposes the two-stage stochastic operation model for optimal scheduling of the power system integrated with the conventional power plants as the backup systems, renewable energy resources (RERs) for clean energy production, and compressed air energy storage (CAES) systems to facilitate the presence of the RERs. In the DA market (first stage problem), the system is targeted to minimize the operational cost of the conventional units while the second stage problem is focused to model the system considering the variations of the RERs in the RT balancing market. In this study, the coordinated operation of both the reserve and energy markets are carried out to provide a reliable condition for energy supply to the consumers in the presence of the uncontrollable energy generation units. The solar radiation and wind speed are considered as the uncertain parameters, which the Monte Carlo simulation (MCS) and fast forward selection (FFS) techniques are exerted for scenario generation and reduction. In this study, the effective role of the CAES system is investigated by analyzing the three cases. The modified IEEE 24-bus test system is considered for evaluating the extracted results during a day. The results indicate the presence of the CAES units is necessary for optimal operation of the power grid with a high share of RERs not only for minimizing energy costs but also for more clean energy production in the electricity network.
机译:本文提出了一种两阶段随机操作模型,用于优化与常规电厂(作为备用系统),用于清洁能源生产的可再生能源(RER)和压缩空气能量存储(CAES)系统相集成的电力系统的调度。 RER的存在。在DA市场(第一阶段问题)中,该系统的目标是使常规装置的运营成本降至最低,而第二阶段问题则是在考虑RT平衡市场中RER的变化的情况下对系统进行建模。在这项研究中,进行了储备市场和能源市场的协调运作,以在存在无法控制的能源生产单元的情况下为消费者的能源供应提供可靠的条件。太阳辐射和风速被认为是不确定参数,蒙特卡罗模拟(MCS)和快进选择(FFS)技术被用于场景的生成和减少。在本研究中,通过分析这三种情况来研究CAES系统的有效作用。修改后的IEEE 24总线测试系统被认为可以在一天内评估提取的结果。结果表明,CAES单元的存在对于具有较高RER份额的电网的最佳运行是必要的,这不仅是为了最大程度地降低能源成本,而且是电网中更多清洁能源的产生。

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