A Robust Participation in the Load Following Ancillary Service and Energy Markets for a Virtual Power Plant in Western Australia

Behnaz Behi, Philip Jennings, Ali Arefi (), Ali Azizivahed, Almantas Pivrikas, S. M. Muyeen and Arian Gorjy
Additional contact information
Behnaz Behi: School of Engineering and Energy, Murdoch University, Murdoch, WA 6150, Australia
Philip Jennings: School of Engineering and Energy, Murdoch University, Murdoch, WA 6150, Australia
Ali Arefi: School of Engineering and Energy, Murdoch University, Murdoch, WA 6150, Australia
Ali Azizivahed: School of Electrical and Data Engineering, University of Technology Sydney, Broadway, NSW 2007, Australia
Almantas Pivrikas: School of Engineering and Energy, Murdoch University, Murdoch, WA 6150, Australia
S. M. Muyeen: Department of Electrical Engineering, Qatar University, Doha P.O. Box 2713, Qatar
Arian Gorjy: Innogreen Technologies Pty Ltd., Perth, WA 6000, Australia

Energies, 2023, vol. 16, issue 7, 1-20

Abstract: Virtual power plants (VPPs) are an effective platform for attracting private investment and customer engagement to speed up the integration of green renewable resources. In this paper, a robust bidding strategy to participate in both energy and ancillary service markets in the wholesale electricity market is proposed for a realistic VPP in Western Australia. The strategy is accurate and fast, so the VPP can bid in a very short time period. To engage customers in the demand management schemes of the VPP, the gamified approach is utilized to make the exercise enjoyable while not compromising their comfort levels. The modelling of revenue, expenses, and profit for the load-following ancillary service (LFAS) is provided, and the effective bidding strategy is developed. The simulation results show a significant improvement in the financial indicators of the VPP when participating in both the LFAS and energy markets. The payback period can be improved by 3 years to the payback period of 6 years and the internal rate of return (IRR) by 7.5% to the IRR of 18% by participating in both markets. The accuracy and speed of the proposed bidding strategy method is evident when compared with a mathematical method.

Keywords: ancillary service; bidding strategy; customer engagement; energy market; internal rate of return; load-following ancillary service; gamification; payback period; virtual power plants; wholesale electricity market (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: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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