基于建筑质量和电蓄热系统的分布式住宅需求响应

Farshad Etedadi Aliabadi, K. Agbossou, N. Henao, S. Kelouwani, F. Laurencelle
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引用次数: 2

摘要

居民电网能源需求的增加增加了电网的能源成本,降低了电网的运行可靠性。这种行为在寒冷的气候地区更为突出,那里的大多数消费者都使用电供暖系统。在这种情况下,蓄热系统可以作为柔性源来缓解电网应力。然而,有必要设计一种有效的需求响应技术,以充分利用蓄热系统的最大潜力。本研究旨在提出并评估一种分布式需求响应方法来控制综合被动式建筑蓄热和电蓄热系统(利用砖作为存储手段)。该方法是基于博弈论概念的基于动态价格的日前调度优化问题。该公式表达了消费者对需求响应计划的参与意愿及其相关的财务激励。进行了模拟以检查系统的电/热行为,并揭示了所提出的方法在平坦总需求剖面,降低成本和确保家庭舒适度方面的有效性。数值计算结果表明,该算法可将峰值平均比提高57.36%,峰值需求降低57.3%,总电力成本降低24.19%,分布式能源份额增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Residential Demand Response Using Building Mass and Electric Thermal Storage System
The increment of energy demand in residential electric networks increases the energy cost and reduces the operating reliability. This behavior is accentuated in cold climate regions where most of the consumers use electric space heating systems. In this context, thermal energy storage systems can be used as flexibility sources to relieve power grid stress. However, it is necessary to design an effective demand response technique to take advantage of the maximum potential of thermal storage systems. This research aims to propose and evaluate a distributed demand response approach to control integrated passive building thermal storage and electric thermal storage systems (utilizing bricks as storage means). The proposed approach is implemented as a dynamic price-based and day-ahead scheduling optimization problem based on the game theory concept. The formulation expresses the consumer’s participation willingness in the demand response program and their associated financial incentives. A simulation is carried out to examine the electrical/thermal behavior of the system and reveal the effectiveness of the proposed method in flattening the aggregated demand profile, reducing costs, and ensuring the households’ comfort. The numerical results show the capability of the proposed algorithm to improve the peak-to-average ratio by 57.36% and decrease the peak demand by 57.3%, while reducing the total electricity cost by 24.19% and increasing the share of distributed energy resources.
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