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Probabilistic pricing of ramp service in power systems with wind and solar generation

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  • Sarfati, Mahir
  • Hesamzadeh, Mohammad Reza
  • Biggar, Darryl R.
  • Baldick, Ross

Abstract

This paper proposes a probabilistic pricing which achieves efficient operation of and investment in ramp-service providers in power systems with a large amount of wind or solar generation. The proposed pricing differs from the existing literature in that it focuses exclusively on the efficient dispatch of electrical energy with no exogenous consideration of the need for reserves or balancing services. The proposed optimal dispatch task determines both the efficient level of any preventive actions taken before a contingency event occurs and the efficient response of the power system - i.e., corrective actions - once an event occurs. We show analytically that the efficient dispatch outcome can be achieved in a decentralized market mechanism provided the market participants are profit-maximizers and price-takers. We show how the total economic benefit of an investment can be decomposed into two components (a) the normal dispatch cost benefit and (b) the economic value of the investment in contributing ramp service to the power system. In order to study different aspects of the probabilistic pricing, the IEEE 30-node example system is deliberately modified. The results show the efficiency of the proposed pricing and the use of the investment model to assess the economic value of ramp-service providers.

Suggested Citation

  • Sarfati, Mahir & Hesamzadeh, Mohammad Reza & Biggar, Darryl R. & Baldick, Ross, 2018. "Probabilistic pricing of ramp service in power systems with wind and solar generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 851-862.
    • Handle: RePEc:eee:rensus:v:90:y:2018:i:c:p:851-862
    DOI: 10.1016/j.rser.2018.03.037
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    References listed on IDEAS

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    1. Geoffrey Pritchard & Golbon Zakeri & Andrew Philpott, 2010. "A Single-Settlement, Energy-Only Electric Power Market for Unpredictable and Intermittent Participants," Operations Research, INFORMS, vol. 58(4-part-2), pages 1210-1219, August.
    2. Hirth, Lion, 2013. "The market value of variable renewables," Energy Economics, Elsevier, vol. 38(C), pages 218-236.
    3. Katzenstein, Warren & Apt, Jay, 2012. "The cost of wind power variability," Energy Policy, Elsevier, vol. 51(C), pages 233-243.
    4. Lamont, Alan D., 2008. "Assessing the long-term system value of intermittent electric generation technologies," Energy Economics, Elsevier, vol. 30(3), pages 1208-1231, May.
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    Cited by:

    1. T. M. I. Mahlia & H. Syaheed & A. E. Pg Abas & F. Kusumo & A. H. Shamsuddin & Hwai Chyuan Ong & M. R. Bilad, 2019. "Organic Rankine Cycle (ORC) System Applications for Solar Energy: Recent Technological Advances," Energies, MDPI, vol. 12(15), pages 1-19, July.
    2. Fugui Dong & Xiaohui Ding & Lei Shi, 2019. "Wind Power Pricing Game Strategy under the China’s Market Trading Mechanism," Energies, MDPI, vol. 12(18), pages 1-17, September.

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