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Two-Stage Optimal Sizing of Standalone Hybrid Electricity Systems with Time-of-Use Incentive Demand Response

机译:具有使用时间激励需求响应的独立混合电力系统的两阶段最优规模

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This paper presents a two-stage optimization technique in sizing various components of standalone hybrid electricity systems with time-of-use (ToU) incentive demand response program. In the first stage of optimization, the minimum levelized cost of electricity (LCOE) is determined without using demand response. The result of the first stage (LCOE) is used as a base rate to develop a ToU demand response for incentive payment in the second stage of optimization. In developing the incentive payment, three periods of a day (off-peak, shoulder, and peak) with different payment rates of electricity are considered. Five different standalone system configurations are developed using various combinations of diesel generators, wind generators, solar photovoltaics, battery energy storages, and flywheels. The proposed two-stage optimization technique is then applied to all five configurations of a remote area South Australian community. Real yearly data of electricity consumption, solar radiation, wind speed, and air temperature, as well as real market price of the components are used in the optimization. It has been found that the hybrid standalone system consisting of diesel, solar, wind, and battery has the minimum overall cost of electricity.
机译:本文提出了一种采用阶段性(ToU)激励需求响应程序确定独立混合电力系统各个组件大小的两阶段优化技术。在优化的第一阶段,无需使用需求响应即可确定最小的平准化电力成本(LCOE)。第一阶段的结果(LCOE)被用作基本费率,以在优化的第二阶段中开发出用于奖励支付的ToU需求响应。在制定奖励金时,要考虑一天中的三个时段(非高峰时段,高峰时段和高峰时段),这些时段具有不同的电费支付率。使用柴油发电机,风力发电机,太阳能光伏电池,电池储能器和飞轮的各种组合,开发了五种不同的独立系统配置。然后,将拟议的两阶段优化技术应用于偏远地区南澳大利亚社区的所有五种配置。优化中使用了实际的年度用电量,太阳辐射,风速和气温以及组件的实际市场价格数据。已经发现,由柴油,太阳能,风能和电池组成的混合式独立系统的总电力成本最低。

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