A Technical and Economic Approach to Multi-Level Optimization Models for Electricity Demand Considering User-Supplier Interaction

S. Bragagnolo, J. Vaschetti, F. Magnago
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引用次数: 3

Abstract

One-level optimization methods have been proposed to optimize a single user’s load profile or a cluster of users. In this work, two two-level optimization methods are studied, one case considering technical requirements and another considering economic criteria. In the upper level, the supplier optimizes it objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on Genetic Algorithm (GA) methods. In this sense, an indirect control is established in which users react to a price signal. Simulation results illustrate that both cases improve the demand profile and increase the retailer profit with respect to an unscheduled case. However, when the supplier tries to maximize the profit, some users receive benefits in detriment of others, concluding that the technical approach is preferable to the economic one.
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考虑用户-供应商交互的电力需求多层次优化模型的技术与经济方法
一级优化方法已被提出用于优化单个用户或用户集群的负载概况。本文研究了两种两级优化方法,一种是考虑技术要求,另一种是考虑经济标准。在上层,供应商对目标函数进行优化。同时,在较低的层次上,用户优化他们的电力成本。该方法基于遗传算法(GA)方法。从这个意义上说,建立了一种间接控制,用户对价格信号作出反应。仿真结果表明,这两种情况都改善了需求曲线,并增加了零售商的利润。然而,当供应商试图最大化利润时,一些用户获得利益而损害了其他用户,从而得出结论,技术方法比经济方法更可取。
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