DocumentCode :
647721
Title :
A comparison study of demand response using optimal and heuristic algorithms
Author :
Shuhui Li ; Dong Zhang
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Alabama, Tuscaloosa, AL, USA
fYear :
2013
fDate :
21-25 July 2013
Firstpage :
1
Lastpage :
5
Abstract :
The development of the smart grid is driving an explosion of interest in demand response programs in the power and energy industry. The term “demand response” is usually used to describe programs that result in changes in electricity usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time. To do so, smart usage of major home appliances is necessary. This paper compares optimal and heuristic demand response (DR) algorithms through a computational experiment strategy. The optimal DR algorithm is obtained based on the objective of minimizing the cost for household electricity consumption. The heuristic DR algorithm is based on the dynamic price information during a day. The computational experiment approach combines building energy consumption simulation and dynamic electricity price together for different DR algorithm evaluation. The paper examines the characteristics of the two different DR strategies and how they are affected by dynamic price tariffs, seasons, and weathers.
Keywords :
cost reduction; demand side management; energy consumption; DR algorithm evaluation; building energy consumption simulation; demand response; dynamic price information; electricity usage; end-use customers; energy industry; heuristic algorithms; household electricity consumption; normal consumption patterns; optimal algorithms; power industry; smart grid; Buildings; Electricity; Energy consumption; Heuristic algorithms; Home appliances; Load management; Thermostats; building energy consumption; demand response; dynamic electricity price; heuristic algorithm; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location :
Vancouver, BC
ISSN :
1944-9925
Type :
conf
DOI :
10.1109/PESMG.2013.6672246
Filename :
6672246
Link To Document :
بازگشت