Journal
ENERGY
Volume 171, Issue -, Pages 944-955Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2019.01.025
Keywords
Demand response; Smart grid; Load scheduling; Smart home; Virtual energy storage system; Cooperative particle swarm optimization
Categories
Funding
- funds for key research and development plan project of the Shaanxi Province, China [2018GY-022]
- China Postdoctoral Science Foundation [2017M623331XB]
- Scientific Research Program - Shaanxi Provincial Education Department [18JK0511]
- Xi'an Science and Technology Project [XDXD004]
- XUST Research Program [2015QDJ052, 201749]
Ask authors/readers for more resources
It will easily make peak loads happen with the increasing usage of residential high-power appliances, which may damage the power grid, cause unforeseen disasters, and reduce the global profit. Towards the optimization of energy consumption, this paper aims to provide an attempt to schedule the operations of household appliances considering their characteristics as well as customer convenience. Bottom-up engineering models that can obtain better understanding of residential electricity demand patterns are developed. Since the formulations are nonlinear complex combinatorial problems, the scheduling of household appliances within multiple smart homes is a challenging optimization problem. In order to solve this challenging optimization problem efficiently, an improved cooperative heuristic approach is proposed to achieve a near optimal solution with better performance. Experimental results confirm the effectiveness of the proposed algorithm. Moreover, a case study is conducted to show that by employing this proposed approach, user comfort is guaranteed, electricity cost is reduced and total loads on the main grid are flattened so that the global energy efficiency is improved. (C) 2019 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available