One-level optimization methods have been proposed to optimize the load profile of a single user or a cluster of users in the smart grids. In this work, two two-level optimization methods are studied, one considering technical requirements and other 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 methods. In this sense, an indirect control is established in which users react to a price signal. Simulations results illustrate that both cases improve the demand profile and increase the retailer profit. However, when the supplier tries to maximize the profit, some users receive benefits in detriment of others, concluding that the technical approach is preferable than the economical one.

中文翻译：

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多级优化模型需求侧管理技术经济指标比较


已经提出了一级优化方法来优化智能电网中单个用户或一组用户的负载曲线。在这项工作中，研究了两种两级优化方法，一种考虑技术要求，另一种考虑经济标准。在上层，供应商优化其目标函数。同时，在较低层面上，用户优化了他们的电力成本。所提出的方法基于遗传算法方法。从这个意义上说，建立了一种间接控制，用户对价格信号做出反应。模拟结果表明，这两种情况都改善了需求状况并增加了零售商的利润。然而，当供应商试图实现利润最大化时，一些用户会在损害其他用户的情况下获得利益，从而得出技术方法比经济方法更可取的结论。