Electricity load level detail in computational general equilibrium – part II – welfare impacts of a demand response program

Renato Rodrigues and Pedro Linares ()

Energy Economics, 2015, vol. 47, issue C, 52-67

Abstract: Demand Response (DR) programs send time-based signals to electricity consumers so that they may shift or reduce their loads to better adjust to the system requirements, thus creating interesting benefits for power systems. However, the assessment of these benefits is quite challenging, since it requires combining features from bottom-up and computable general equilibrium (CGE) models. This paper assesses the impacts of a DR program in Spain using a CGE model which includes both technological and temporal disaggregation. The model is able to account for the indirect effects characteristic of CGE models while also mimicking the detailed behavior of the electricity operation and investment available before only in bottom-up detailed models. Our results show clearly the advantages of using this approach for this type of policies.

Keywords: Computable general equilibrium (CGE); Electricity demand response (search for similar items in EconPapers)
JEL-codes: C68 D58 L60 Q4 Q51 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988314002606
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:47:y:2015:i:c:p:52-67

DOI: 10.1016/j.eneco.2014.10.015

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().