DocumentCode :
104596
Title :
Dynamic Demand Response : A Solution for Improved Energy Efficiency for Industrial Customers
Author :
Mohagheghi, Salman ; Raji, Neda
Author_Institution :
Electr. Eng. & Comput. Sci., Colorado Sch. of Mines, Golden, CO, USA
Volume :
21
Issue :
2
fYear :
2015
fDate :
March-April 2015
Firstpage :
54
Lastpage :
62
Abstract :
Electric demand-side management (DSM) focuses on changing the electricity consumption patterns of end-use customers through improving energy efficiency and the optimal 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 to comply with a DR event. Whereas the noncriticality of loads at the residential and commercial levels allows for demand reduction with relative ease, reducing the demand of industrial processes requires a more sophisticated solution. Production constraints, inventory constraints, maintenance schedules, and crew management constraints are some of the many factors that have to be taken into account before one or more processes can be temporarily shut down. Some of these constraints can be viewed along the overall performance of the system, while others need to be analyzed and evaluated in real time. In this article, a system that dynamically ranks loads and workstations of an industrial site as candidates for demand reduction is proposed. A fuzzy/expert-based system combined with an optimization module verifies whether and, if applicable, by how much the plant can participate in a utility-initiated DR event while satisfying its local operational constraints.
Keywords :
demand side management; expert systems; fuzzy systems; maintenance engineering; DSM; crew management constraints; demand reduction; demand shifting; dynamic demand response; electric demand-side management; electricity consumption patterns; energy efficiency; fuzzy-expert-based system; industrial customers; inventory constraints; maintenance schedules; on-site generation; optimization module; production constraints; utility-initiated DR event; Electricity supply industry; Energy consumption; Job shop scheduling; Maintenance engineering; Management; Power system management; Real-time systems; Schedules; Workstations;
fLanguage :
English
Journal_Title :
Industry Applications Magazine, IEEE
Publisher :
ieee
ISSN :
1077-2618
Type :
jour
DOI :
10.1109/MIAS.2014.2345799
Filename :
6994443
Link To Document :
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