Please use this identifier to cite or link to this item: http://hdl.handle.net/11328/4433
Title: Optimal stochastic conditional value at risk-based management of a demand response aggregator considering load uncertainty
Authors: Vahid-Ghavidel, Morteza
Javadi, Mohammad Sadegh
Santos, Sérgio F.
Gough, Matthew
Shafie-khah, Miadreza
Catalão, João P. S.
Keywords: Conditional value at risk (CVaR)
Demand response
DR aggregator
Stochastic programming
Risk management
Time-of-use (TOU)
Issue Date: 3-Nov-2021
Publisher: IEEE
Citation: Vahid-Ghavidel, M., Javadi, M. S., Santos, S. F., Gough, M., Shafie-khah, M., & Catalão, J. P. S. (2021). Optimal stochastic conditional value at risk-based management of a demand response aggregator considering load uncertainty. In 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Bari, Italy, 7th-10th September 2021 (pp. 1-5). 10.1109/EEEIC/ICPSEurope51590.2021.9584827. Repositório Institucional UPT. http://hdl.handle.net/11328/4433
Abstract: This paper models a novel demand response (DR) trading strategy. In this model, the DR aggregator obtains the DR from the end-users via two types of DR programs, i.e. a time-of-use (TOU) program and an incentive-based DR program. Then, it offers this DR to the wholesale market. Three consumer sectors, namely residential, commercial and industrial, are included in this problem. The DR program is dependent on their corresponding load profiles during the studied time horizon. This paper uses a mixed-integer linear programming (MILP) problem and it is solved using the CPLEX solver through a stochastic programming approach in GAMS. The risk measure chosen to represent the load uncertainty of the users who are participating in the DR program is Conditional Value-at-Risk (CVaR). The proposed problem is simulated and assessed through a case study of a test system. The results indicate that the industrial loads play a major role in the power system and this directly affects the DR program. Moreover, the risk-averse decision-maker in this model favors a reduced participation in the DR programs when compared to a decision-maker who is risk-neutral, since the risk-averse decision maker prefers to be more secure against uncertainties. In other words, an increase in risk factor results in a decrease in the participation rate of the consumers in DR programs.
URI: http://hdl.handle.net/11328/4433
ISBN: 978-1-6654-3613-7 (Electronic)
Appears in Collections:REMIT - Publicações em Livros de Atas Internacionais / Papers in International Proceedings



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