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A Stochastic Adaptive Robust Optimization Approach for the Offering Strategy of a Virtual Power Plant

机译:虚拟电厂提供策略的随机自适应鲁棒优化方法

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摘要

This paper proposes a novel approach for the offering strategy of a virtual power plant that participates in the day-ahead and the real-time energy markets. The virtual power plant comprises a conventional power plant, a wind-power unit, a storage facility, and flexible demands, which participate in the day-ahead and the real-time markets as a single entity in order to optimize their energy resources. We model the uncertainty in the wind-power production and in the market prices using confidence bounds and scenarios, respectively, which allows us to formul-ate the strategic offering problem as a stochastic adaptive robust optimization model. Results of a case study are provided to show the applicability of the proposed approach.
机译:本文为参与日前和实时能源市场的虚拟电厂的报价策略提出了一种新颖的方法。虚拟电厂包括常规电厂,风力发电机组,存储设施和灵活的需求,它们作为一个整体参与日间和实时市场,以优化其能源。我们分别使用置信区间和情景对风电生产和市场价格中的不确定性进行建模,这使我们能够将战略产品问题公式化为随机自适应鲁棒优化模型。提供了一个案例研究的结果,以显示该方法的适用性。

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