DocumentCode :
1635918
Title :
Supporting wind generation deployment with demand response
Author :
Kowli, Anupama S. ; Meyn, Sean P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois, Urbana, IL, USA
fYear :
2011
Firstpage :
1
Lastpage :
8
Abstract :
In this paper, we investigate how the demand-side of the electricity industry can provide a potential solution for the reliable integration of wind generation resources into power system operations. More specifically, we investigate how the consumers enrolled in demand response (DR) programs mechanisms which induce changes in load consumption through incentives or prices can provide a valuable demand-side reserve capacity which can help manage the unexpected deviations of actual wind generation from its forecast value. We also study how a levelized load profile can help accommodate wind generation on the system. Our analysis is based on a stochastic unit commitment model that explicitly represents the uncertainty in the day-ahead scheduling decisions using a two-stage stochastic program with recourse actions. We extend the standard formulation of this program to accommodate the outcomes the DR programs. Simulation results provide a proof of concept that DR-based reserve capacity is an effective mechanism to counter the volatility and uncertainty of wind resources. Also, studies indicate that load leveling can prove beneficial for systems with wind generation. Finally, our analysis raises some policy-related questions on the best possible ways to integrate wind generation into system operations and the risks that lie in wind integration without adequate backup from the demand-side.
Keywords :
power generation dispatch; power generation reliability; power generation scheduling; stochastic processes; wind power plants; DR programs; day-ahead scheduling decisions; demand response; demand side reserve capacity; electricity industry; integration reliability; load consumption; policy-related questions; power system operations; stochastic unit commitment model; two-stage stochastic program; wind generation deployment; wind generation resources; Availability; Generators; Real time systems; Stochastic processes; Uncertainty; Wind forecasting; demand response; demand-side reserves; electricity markets; load leveling; load shifting; operational planning; reserves; scheduling; uncertainty; unit commitment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PES.2011.6039780
Filename :
6039780
Link To Document :
بازگشت