DocumentCode
136003
Title
Impact of demand response on thermal generation investment with high wind penetration
Author
Shan Jin ; Botterud, Audun ; Ryan, Sarah
Author_Institution
Decision & Inf. Sci. Div., Argonne Nat. Lab., Argonne, IL, USA
fYear
2014
fDate
27-31 July 2014
Firstpage
1
Lastpage
1
Abstract
Summary form only given. We present a stochastic programming model for investments in thermal generation capacity to study the impact of demand response (DR) at high wind penetration levels. The investment model combines continuous operational constraints and wind scenarios to represent the implications of wind variability and uncertainty at the operational level. DR is represented in terms of linear price-responsive demand functions. A numerical case study based on load and wind profiles of Illinois is constructed with 20 candidate generating units of various types. Numerical results show the impact of DR on both investment and operational decisions. We also propose a model in which DR provides operating reserves and discuss its impact on lowering the total capacity needed in the system. We observe that a relatively small amount of DR capacity is sufficient to enhance the system reliability. When compared to the case with no DR, a modest level of DR results in less wind curtailment and better satisfaction of reserve requirements, as well as improvements in both the social surplus and generator utilization, as measured by capacity factors.
Keywords
demand side management; investment; power generation economics; stochastic programming; thermal power stations; wind power plants; demand response; generator utilization; high wind penetration level; investment model; linear price responsive demand function; operational constraints; social surplus; stochastic programming; thermal generation capacity; thermal generation investment; Investment; Laboratories; Load management; Load modeling; Numerical models; Programming; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location
National Harbor, MD
Type
conf
DOI
10.1109/PESGM.2014.6939881
Filename
6939881
Link To Document