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首页> 外文期刊>Industrial Electronics, IEEE Transactions on >Market-Oriented Energy Management of a Hybrid Wind-Battery Energy Storage System Via Model Predictive Control With Constraint Optimizer
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Market-Oriented Energy Management of a Hybrid Wind-Battery Energy Storage System Via Model Predictive Control With Constraint Optimizer

机译:基于约束优化器的模型预测控制的混合风能储能系统面向市场的能源管理

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摘要

This paper presents a market-oriented energy management system (EMS) for a hybrid power system composed of a wind energy conversion system and a battery energy storage system (BESS). The EMS is designed as a real-time model predictive control (MPC) system. The EMS dispatches the BESS to achieve the maximum net profit from the deregulated electricity market. Furthermore, the EMS aims at expanding the BESS lifetime by applying typical and practical constraints in the MPC problem on both the daily number of cycles (DNC) and depth of discharge (DOD). The MPC constraint optimizer is designed to tune the lifetime constraints optimally. It guarantees the optimal economic profit by finding the optimal DNC and DOD to achieve the maximum market revenue from energy arbitrage with the minimal expended-life cost. The effectiveness of this work is verified by comparison with a conventional MPC used in previous works. Simulation is conducted using real wind power and market data in Alberta, Canada.
机译:本文提出了一种由风能转换系统和电池储能系统(BESS)组成的混合动力系统的面向市场的能源管理系统(EMS)。 EMS被设计为实时模型预测控制(MPC)系统。 EMS调度BESS以从放松管制的电力市场中获得最大的净利润。此外,EMS的目的是通过在MPC问题中对每日循环次数(DNC)和放电深度(DOD)应用典型的和实际的限制来延长BESS寿命。 MPC约束优化器旨在优化寿命约束。它通过找到最佳的DNC和DOD来确保最佳的经济利润,从而以最小的使用寿命成本从能源套利中获得最大的市场收益。通过与先前工作中使用的常规MPC进行比较,验证了这项工作的有效性。使用加拿大艾伯塔省的实际风力发电和市场数据进行了仿真。

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