Multi-Objective Market Clearing Model with an Autonomous Demand Response Scheme

Neda Hajibandeh, Miadreza Shafie-khah, Sobhan Badakhshan, Jamshid Aghaei, Sílvio J. P. S. Mariano and João P. S. Catalão
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Neda Hajibandeh: C-MAST, University of Beira Interior, 6201-001 Covilhã, Portugal
Miadreza Shafie-khah: School of Technology and Innovations, University of Vaasa, 65200 Vaasa, Finland
Sobhan Badakhshan: Department of Electrical Engineering, Sharif University of Technology, Tehran 11365-11155, Iran
Jamshid Aghaei: Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 71557-13876, Iran
Sílvio J. P. S. Mariano: Instituto de Telecomunicações, 6201-001 Covilhã, Portugal
João P. S. Catalão: Faculty of Engineering of the University of Porto and INESC TEC, 4200-465 Porto, Portugal

Energies, 2019, vol. 12, issue 7, 1-16

Abstract: Demand response (DR) is known as a key solution in modern power systems and electricity markets for mitigating wind power uncertainties. However, effective incorporation of DR into power system operation scheduling needs knowledge of the price–elastic demand curve that relies on several factors such as estimation of a customer’s elasticity as well as their participation level in DR programs. To overcome this challenge, this paper proposes a novel autonomous DR scheme without prediction of the price–elastic demand curve so that the DR providers apply their selected load profiles ranked in the high priority to the independent system operator (ISO). The energy and reserve markets clearing procedures have been run by using a multi-objective decision-making framework. In fact, its objective function includes the operation cost and the customer’s disutility based on the final individual load profile for each DR provider. A two-stage stochastic model is implemented to solve this scheduling problem, which is a mixed-integer linear programming approach. The presented approach is tested on a modified IEEE 24-bus system. The performance of the proposed model is successfully evaluated from economic, technical and wind power integration aspects from the ISO viewpoint.

Keywords: customer’s disutility; day-ahead market; demand response; multi-objective model; wind integration (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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