Published July 22, 2017 | Version v1
Journal article Open

A Novel Stochastic Reserve Cost Allocation Approach of Electricity Market Agents in the Restructured Power Systems

Creators

  • 1. Department of Computer Science and Automation, School of Science University of Salamanca, Plaza de la Merced s/n, 37008, Salamanca, Spain
  • 2. C-MAST, University of Beira Interior, Covilhã 6201-001, Portugal
  • 3. Electrical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, 15914, Tehran, Iran.
  • 4. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798 Singapore, Singapore.
  • 5. Electrical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), No. 424, Hafez Avenue, 15914 Tehran, Iran
  • 6. MediaLab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  • 7. Department of Computer Science and Automation, School of Science University of Salamanca, Plaza de la Merced s/n, 37008 Salamanca, Spain
  • 8. INESC-ID, Instituto Superior Técnico, University of Lisbon, Lisbon 1049-001, Portugal

Description

In this paper, a new mechanism is proposed to apportion expected reserve costs between
electricity market agents in the power system. The uncertainties of generation units, transmission lines, wind
power generation and electrical loads are considered in this model. Hence, a Stochastic Unit Commitment

(SUC) is used to apply the uncertainty of stochastic variables in the simultaneous energy and reserve market-
clearing problem. Moreover, electrical customers can participate in the electricity market based on their

desired strategies. In this paper, a novel method is proposed to allocate reserve costs between GenCos,
TransCos, electrical customers and wind farm owners. Consequently, market agents are responsible for
paying a portion of the allocated expected reserve costs based on the economic metrics that are defined for
the first time in this paper. Finally, two cases including a 3-bus test system and IEEE-RTS are utilized to
illustrate the performance of the proposed mechanism to share the expected reserve costs.

Notes

Amin Shokri Gazafroudi, Francisco Prieto-Castrillo, and Juan Manuel Corchado acknowledge the support by the European Commission H2020 MSCA-RISE-2014: Marie Sklodowska-Curie project DREAM-GO Enabling Demand Response for short and real-time Efficient And Market Based Smart Grid Operation - An intelligent and real-time simulation approach ref. 641794. Moreover, Miadreza Shafie-khah and João P. S. Catalão acknowledge the support by FEDER funds through COMPETE 2020 and by Portuguese funds through FCT, under Projects SAICT-PAC/0004/2015 - POCI-01-0145-FEDER-016434, POCI-01-0145-FEDER-006961, UID/EEA/50014/2013, UID/CEC/50021/2013, and UID/EMS/00151/2013, and funding from the EU 7th Framework Programme FP7/2007-2013 under GA no. 309048.

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Additional details

Funding

UID/EMS/00151/2013 – Centre for Mechanical and Aerospace Science and Technologies 147350
Fundação para a Ciência e Tecnologia
UID/EEA/50014/2013 – INESC TEC - INESC Technology and Science 147326
Fundação para a Ciência e Tecnologia
UID/CEC/50021/2013 – Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa 147282
Fundação para a Ciência e Tecnologia
DREAM-GO – Enabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach 641794
European Commission
SINGULAR – Smart and Sustainable Insular Electricity Grids Under Large-Scale Renewable Integration 309048
European Commission