模型预测控制在需求响应中的应用现状

IF 2.1 Q3 ENVIRONMENTAL SCIENCES
Amru Alqurashi
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引用次数: 2

摘要

需求响应方案已被用于优化需求方的参与。利用需求响应程序可以最大限度地提高社会福利并减少能源使用。模型预测控制是一种适用于能源网络管理的控制策略,具有其他预测控制器无法比拟的优越性。在需求侧实施该控制器的目标是最小化能耗、碳足迹和能源成本,最大化热舒适和社会福利。本文旨在突出该控制策略在处理需求响应优化问题方面的优越性。对控制器的优化方法进行了比较。总结了最近发表的用于解决模型预测控制优化问题的技术,包括需求响应程序、可再生能源和热舒适。阐述了基于模型的控制技术应用于需求响应优化问题的研究现状、面临的挑战和未来的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The State of the Art in Model Predictive Control Application for Demand Response
Demand response programs have been used to optimize the participation of the demand side. Utilizing the demand response programs maximizes social welfare and reduces energy usage. Model Predictive Control is a suitable control strategy that manages the energy network, and it shows superiority over other predictive controllers. The goal of implementing this controller on the demand side is to minimize energy consumption, carbon footprint, and energy cost and maximize thermal comfort and social welfare. This review paper aims to highlight this control strategy's excellence in handling the demand response optimization problem. The optimization methods of the controller are compared. Summarization of techniques used in recent publications to solve the Model Predictive Control optimization problem is presented, including demand response programs, renewable energy resources, and thermal comfort. This paper sheds light on the current research challenges and future research directions for applying model-based control techniques to the demand response optimization problem.
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来源期刊
CiteScore
5.40
自引率
9.50%
发文量
59
审稿时长
20 weeks
期刊介绍: The Journal of Sustainable Development of Energy, Water and Environment Systems – JSDEWES is an international journal dedicated to the improvement and dissemination of knowledge on methods, policies and technologies for increasing the sustainability of development by de-coupling growth from natural resources and replacing them with knowledge based economy, taking into account its economic, environmental and social pillars, as well as methods for assessing and measuring sustainability of development, regarding energy, transport, water, environment and food production systems and their many combinations.
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