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A multi-agent intelligent decision making support system for home energy management in smart grid: A fuzzy TOPSIS approach

机译:智能电网中家庭能源管理的多智能体智能决策支持系统:一种模糊的TOPSIS方法

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In the context of intelligent home energy management in smart grid, the occupants' consumption behavior has a direct effect on the demand and supply of the electrical energy market. Correspondingly, the policies of the utility providers affect consumption behavior so techniques and tools are required to analyse the occupants' preferences, habits and lifestyles in order to support and facilitate their decision-making regarding the curtailing of their energy consumption and costs. The uncertainty about householders' preferences increases the uncertainty of appliance prioritization and makes it difficult to determine the consistency of preferences in terms of energy consumption. In this complex system, the preferences and judgments of householders are represented by linguistic and vague patterns. This paper proposes a much better representation of this linguistics that can be developed and refined by using the evaluation methods of fuzzy set theory. The proposed approach will apply the fuzzy Technique for Order Preference by Similarity to Ideal Solution (fuzzy TOPSIS) for achieving preferences. Based on our detailed literature review of the multi-agent system approach in this field, it is expected that the proposal model will offer a robust tool for communication and decision-making between occupant agents and dynamic environmental variables. It is shown that the proposed fuzzy TOPSIS approach will enable and assist householders to maximize their participation in demand response programs.
机译:在智能电网中进行智能家庭能源管理的情况下,居住者的消费行为直接影响着电能市场的供求关系。相应地,公用事业提供商的政策会影响消费行为,因此需要技术和工具来分析居住者的喜好,习惯和生活方式,以支持和促进他们在减少能源消耗和成本方面的决策。有关住户偏好的不确定性增加了设备优先级的不确定性,并使其难以确定能耗方面的偏好的一致性。在这个复杂的系统中,住户的偏好和判断以语言和模糊的模式表示。本文提出了一种更好的语言学表现形式,可以通过使用模糊集理论的评估方法来发展和完善这种语言学。所提出的方法将把基于相似性的订单偏好的模糊技术应用于理想解决方案(模糊TOPSIS)以实现偏好。根据我们对该领域多智能体系统方法的详细文献综述,预计该提议模型将提供一个强大的工具,用于在占用智能体与动态环境变量之间进行沟通和决策。结果表明,所提出的模糊TOPSIS方法将使并帮助住户最大限度地参与需求响应计划。

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