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Stochastic multi-objective economic-environmental energy and reserve scheduling of microgrids considering battery energy storage system

机译:考虑电池储能系统的随机多目标经济环境能量与微网储备调度

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摘要

Due to environmental concerns and ever-increasing fuel costs, governments offer incentives for clean and sustainable energy production from Distributed Generations (DGs) such as Wind Turbine (WT) and Photovoltaic (PV) generators. Optimal operation of Microgrids (MGs) and management of demand side are necessary to increase the efficiency and reliability of distribution networks. In this paper, the stochastic operation scheduling of a MG consisting of non-dispatchable resources including WT and PV and dispatchable resources including Phosphoric Acid Fuel Cell (PAFC), Micro-gas Turbine (MT), and electrical storage as Battery Energy Storage System (BESS) is investigated to minimize operation cost and emissions. The problem is solved by combination of Differential Evolutionary (DE) and Modified PSO (MPSO) algorithms considering Incentive-based (IB) Demand Response (DR) program and generation reserve scheduling. A stochastic model is also proposed for energy management in MGs in the grid-connected operating mode by taking into account the uncertainty of WT and PV generations and forecasted electric demands. A scenario tree is used to generate scenarios and then, representative scenarios are selected by a scenario reduction technique based on DE. The proposed method is applied on a typical MG and simulation results illustrate its efficiency in comparison to other techniques.
机译:由于对环境的关注和不断增长的燃料成本,政府为使用风力涡轮机(WT)和光伏(PV)发电机等分布式发电(DG)提供清洁和可持续能源生产的激励措施。微电网(MG)的最佳运行和需求方的管理对于提高配电网的效率和可靠性是必不可少的。在本文中,由WT和PV等不可分配资源以及磷酸燃料电池(PAFC),微型燃气轮机(MT)和电力存储等可分配资源组成的MG的随机运行调度(作为电池储能系统(对BESS进行了研究,以最大程度地降低运营成本和排放。考虑到基于激励的(IB)需求响应(DR)程序和发电储备计划,通过结合差分进化(DE)和改进的PSO(MPSO)算法解决了该问题。考虑到发电量和光伏发电量的不确定性以及预测的电力需求,还提出了一种随机模型,用于并网运行模式下的中型企业的能源管理。场景树用于生成场景,然后通过基于DE的场景约简技术选择代表性场景。将该方法应用于典型的MG上,仿真结果表明了与其他技术相比的效率。

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