Reducing Electricity Consumption Peaks with Parametrised Dynamic Pricing Strategies Given Maximal Unit Prices

N. Höning, H. L. Poutré
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引用次数: 3

Abstract

Demand response is a crucial mechanism for flattening of peak loads. For its implementation, we not only require consumers who react to price changes, but also intelligent strategies to select prices. We propose a parametrised meta-strategy for dynamic pricing and identify suitable strategies for given scenarios through offline optimisation using a population model. We also model an important and novel constraint: a price cap (a maximal unit price) for consumer protection. We show in computational simulations that the maximal unit price influences the peak reduction potential of dynamic pricing. We compare our dynamic pricing approach with a constant pricing approach and show that our approach, used by a profit-optimising seller, is both peak-reducing and equally profitable.
在最大电价条件下,参数化动态定价策略降低用电峰值
需求响应是峰值负荷扁平化的重要机制。为了实现它,我们不仅需要消费者对价格变化做出反应,还需要智能的价格选择策略。我们提出了一个动态定价的参数化元策略,并通过使用人口模型进行离线优化,确定给定场景的合适策略。我们还建立了一个重要而新颖的约束模型:保护消费者的价格上限(最大单价)。我们在计算模拟中表明,最大单价影响动态定价的峰值削减潜力。我们将动态定价方法与恒定定价方法进行比较,结果表明,利润优化卖家使用的动态定价方法既能降低峰值,又能带来同样的利润。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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