Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 9, Issue 1, Pages 252-260Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2016.2550031
Keywords
Smart scheduling; home energy management system; heuristic algorithm; dynamic environment; intelligent automation
Categories
Funding
- National Natural Science Foundation of China [61075064, 61034004, 61005090]
Ask authors/readers for more resources
This paper details a proposed demand response (DR) application to optimize the operation of appliances in an indeterminate environment in a home energy management system. An indeterminate environment results from forecasted errors of electricity prices and system loads, so a probabilistic analysis of the system performance is of significant interest. Herein, a chance constrained optimization-based model is formulated to accommodate these uncertainties. The resulting DR application can be easily embedded in resource limited electric devices. To reduce the computational cost, both improved particle swarm optimization (PSO) and a two-point estimate method are presented to solve the chance constrained problem. The improved PSO is used to provide the optimum solution, while the probabilistic assessment of uncertainties is estimated using a two-point estimate method. Numerical comparisons were made to justify the effectiveness of the method. The simulated results obtained using the models indicate that the proposed method can significantly reduce the computational burden while maintaining a high level of accuracy.
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