4.6 Article

Demand response integrated day-ahead energy management strategy for remote off-grid hybrid renewable energy systems

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2020.106731

关键词

Hybrid renewable energy systems; Day-ahead energy management; Demand response; Probabilistic fuzzy inference systems; Particle swarm optimization

资金

  1. University of Manitoba
  2. Solar Solutions Inc., Canada
  3. NSERC Engage program

向作者/读者索取更多资源

With the expected price reductions in renewable technologies, hybrid renewable energy systems have emerged as feasible retrofit solutions for primarily diesel-based remote off-grid power systems; effective energy management is crucial for stable and reliable power system operation; integrating demand response strategies with energy management framework can maximize benefits.
With the anticipated future price reductions in renewable technologies, hybrid renewable energy systems have emerged as a feasible retrofit to the primarily diesel-based remote off-grid power systems. However, in the presence of many supply/storage systems along with high penetration of intermittent renewable energy, energy management becomes a decisive step to achieve a stable and reliable power system operation. The intended benefits can be further maximized when the energy management framework is unified with demand response strategies. This paper presents a novel demand response integrated day-ahead energy management framework subjecting remote off-grid power systems. Several measures are taken to enhance the consumer acceptance and practical implementation of the demand response platform. Responsiveness of the customers to price-based incentives is estimated using a probabilistic fuzzy inference system to accurately model the stochastic human nature. Results are demonstrated for an isolated remote community in Northern Canada for both summer and winter seasons. The results confirm the applicability of the proposed method in achieving the intended objectives of day-ahead energy management.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据