DocumentCode :
32885
Title :
Managing Industrial Energy Intelligently: Demand Response Scheme
Author :
Mohagheghi, Salman ; Raji, Neda
Author_Institution :
Electr. Eng. & Comput. Sci. Dept., Colorado Sch. of Mines, Golden, CO, USA
Volume :
20
Issue :
2
fYear :
2014
fDate :
March-April 2014
Firstpage :
53
Lastpage :
62
Abstract :
Electric demand-side management (DSM) focuses on changing the electricity consumption patterns of end-use customers through improving energy efficiency and optimizing the allocation of power. Demand response (DR ) is a DSM solution that targets residential, commercial, and industrial customers and is developed for demand reduction or demand shifting at a specific time for a specific duration. In the absence of on-site generation or the possibility of demand shifting, the consumption level needs to be lowered. While the noncriticality of loads at the residential and commercial levels allows for demand reduction with relative ease, demand reduction of industrial processes requires a more sophisticated solution. Production constraints, inventory constraints, maintenance schedules, and crew management are some of the many factors that have to be considered before one or more processes can be temporarily shut down. An intelligent system is designed in this article for implementation of DR at an industrial site. Based on the various operational constraints of the industrial process, it determines the loads that could be potentially curtailed. Fuzzy/expert systems are used to derive a priority factor for different candidate loads. This information can then be used by the plant operator/DR client to make a comply/opt out decision during a utility-initiated DR event.
Keywords :
demand side management; energy conservation; expert systems; fuzzy systems; maintenance engineering; DSM; crew management; demand reduction; demand response scheme; demand shifting; electric demand side management; electricity consumption patterns; energy efficiency; fuzzy-expert systems; intelligent system; inventory constraints; maintenance schedules; operational constraints; power allocation; production constraints; Energy consumption; Energy efficiency; Energy management; Industrial plants; Maintenance engineering; Optimized production technology; Workstations;
fLanguage :
English
Journal_Title :
Industry Applications Magazine, IEEE
Publisher :
ieee
ISSN :
1077-2618
Type :
jour
DOI :
10.1109/MIAS.2013.2288387
Filename :
6689333
Link To Document :
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