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Consumer Energy Management System: Contract Optimization using Forecasted Demand

Authors:
Chi-Cheng Chuang
Jimi Y. C. Wen
Ray-I Chang

Keywords: Energy Management System, Load Forecasting, Contract Optimization, Particle Swarm Optimization.

Abstract:
Smart grid initiative is gaining traction around the world, enabling more complexity in the utility contracts designed to revolutionize our society towards more energy efficient and effective. Consumer energy management system (EMS) is important in assisting how consumers participate in the smart grid with the increasing complexity of utility contracts. A web-based EMS was presented in this paper with two novel design features: i) a maximum demand load forecasting ii) maximum contracted demand (MCD) contract optimization. A maximum demand load forecasting based on space-specific regression models of simple latent variables, temperature, number of workdays and employees, was proposed. These regression models were accurate with a mean average percentage error of 4$sim$8% and robust to different space size of similar nature. The use of simple latent variables enables consumers to input parameters easily through the proposed EMS web-based interface. The Particle Swarm Optimization (PSO) algorithm is especially suitable in dealing with utility contract's interdependent and discontinuous structure. A MCD contract optimization based on the PSO algorithm was then proposed and showed significant savings in the studied cases of 10$sim$30% improvement over the current MCD contracts and a 5$sim$12.5% improvement over using the average maximum demand load. The results showed promising potential of the two proposed features in future consumer EMS.

Pages: 58 to 63

Copyright: Copyright (c) IARIA, 2011

Publication date: May 22, 2011

Published in: conference

ISSN: 2308-412X

ISBN: 978-1-61208-136-6

Location: Venice/Mestre, Italy

Dates: from May 22, 2011 to May 27, 2011