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Stochastic Optimization Scheme to Schedule Energy Supply and Demands in an Islanded Microgrid

机译:调度孤岛微电网能源供需的随机优化方案

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With the increasing awareness of climate change and the declining prices of renewable energy sources (RESs), societies are transforming themselves to access cheap and clean energy. Solar and Wind are the two most abundantly available energy resources that can be accessed in remote areas where it is infeasible for a national grid to supply electricity. However, the RESs are intermittent in nature show high variability in output power, and become more volatile without the integration of the national grid. In this paper, we address such a problem of RESs uncertainty in an islanded microgrid, incorporating both supply-side and demand-side energy management techniques. We propose a model predictive time-ahead rolling horizon based optimization approach, that generates cost-optimal scheduling signals for various energy supply entities and flexible load demands. The objective of this work is to; 1) minimize the operating cost of the power generators, 2) minimize electricity cost for the energy consumers, and 3) maximize the consumers’ satisfaction level. The numerical results show that our optimization strategy ensures the supply and demand balance applying cost-efficient decisions under any uncertain circumstances using error-correcting rolling time horizon based strategy.
机译:随着人们对气候变化意识的增强和可再生能源价格的下降,社会正在转变自己,以获取廉价和清洁的能源。太阳能和风能是最丰富的两种能源,可以在偏远地区获得,国家电网无法提供电力。但是,RES本质上是间歇性的,在输出功率方面表现出很大的可变性,并且在不整合国家电网的情况下变得更加不稳定。在本文中,我们结合了供应方和需求方能源管理技术,解决了孤岛微电网中RES不确定性的问题。我们提出了一种基于模型预测性的提前滚动水平的优化方法,该方法针对各种能源供应实体和灵活的负荷需求生成成本最优的调度信号。这项工作的目的是: 1)最小化发电机的运行成本,2)最小化能源消费者的电力成本,以及3)最大化消费者的满意度。数值结果表明,我们的优化策略可使用基于纠错滚动时间范围的策略在任何不确定情况下应用具有成本效益的决策来确保供需平衡。

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