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A novel cost-aware multi-objective energy management method for microgrids

机译:一种用于微电网的新型成本感知多目标能量管理方法

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This paper proposes a multi-objective energy management method for microgrids which include local generation sources, grid connection, energy storage units and various loads. Minimization of the energy cost and maximization of batterys lifetime in a microgrid are considered as two main objectives which are optimized simultaneously. To achieve these objectives, microgrids central controller must find the best pattern for charging and discharging the battery. To this purpose, there is a need to have information about time-of-use (TOU) grid electricity rates, forecasted load profile and renewable generation levels. Model predictive control (MPC) policy is then utilized for solving the optimization problem and real-time implementation in a closed-loop framework. The performance and effectiveness of the proposed method is verified by simulating a microgrid model with real yearly data for the demand and renewable generation profiles and TOU rates. It is shown that the saving in energy cost can be increased considerably by applying the proposed MPC algorithm instead of a static energy management approach. Furthermore, the proposed algorithm is capable of regulating the battery usage based on the expected lifetime by considering the battery life span maximization objective.
机译:本文提出了一种用于微电网的多目标能量管理方法,包括局部产生源,网格连接,能量存储单元和各种负载。在微电网中最小化电池寿命的能量成本和最大化被认为是同时优化的两个主要目标。为实现这些目的,微电网中央控制器必须找到最佳模式,用于充电和放电电池。为此目的,需要了解有关使用时间(TOU)电网电费,预测负载概况和可再生生成级别的信息。然后利用模型预测控制(MPC)策略来解决闭环框架中的优化问题和实时实现。通过模拟具有实时数据的微电网模型来验证所提出的方法的性能和有效性,以实现需求和可再生的生成简介和TOU汇率。结果表明,通过应用所提出的MPC算法而不是静态能量管理方法,可以显着提高能量成本。此外,所提出的算法能够通过考虑电池寿命跨度最大化目标来根据预期的寿命来调节电池使用。

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