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Reasoning about Control Situations in Power Systems

机译:电力系统控制局势的推理

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摘要

Introduction of distributed generation, deregulation and distribution of control has brought new challenges for electric power system operation, control and automation. Traditional power system models used in reasoning tasks such as intelligent control are highly dependent on the task purpose. Thus, a model for intelligent control must represent system features, so that information from measurements can be related to possible system states and to control actions. These general modeling requirements are well understood, but it is, in general, difficult to translate them into a model because of the lack of explicit principles for model construction. Available modeling concepts for intelligent control do not assist the model builder in the selection of model content i.e. in deciding what is relevant to represent for a particular reasoning task and thereby faced with a difficult interpretation problem. In this paper, we present our work on using explicit means-ends model based reasoning about complex control situations which results in maintaining consistent perspectives and selecting appropriate control action for goal driven agents.
机译:引入分布式发电,放松管制和控制的分配为电力系统运行,控制和自动化带来了新的挑战。用于推理任务(如智能控制)的传统电力系统模型高度依赖于任务目的。因此,智能控制模型必须表示系统特征,从而可以与可能的系统状态和控制动作有关的信息。这些一般建模要求很好地理解,但通常,由于模型建设缺乏明确原则,这是一般的,难以将它们转化为模型。智能控制的可用建模概念不帮助模型构建器在模型内容中选择,即决定与特定推理任务表示相关的内容,从而面临困难的解释问题。在本文中,我们在使用基于显式的方法模型的基于复杂控制局势的原因介绍了我们的工作,这导致保持一致的观点并为目标驱动剂选择适当的控制作用。

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