A clearing mechanism for joint energy and ancillary services in non-convex markets considering high penetration of renewable energy sources

Goudarzi, H ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1016/j.ijepes.2021.106817
  3. Publisher: Elsevier Ltd , 2021
  4. Abstract:
  5. This paper introduces a day-ahead clearing model for the simultaneous energy and ancillary services market in high penetration of renewable energy sources (RESs) considering fast-start generators’ behaviors as non-spinning reserve providers. For managing the uncertainties of RESs, the system operator takes the advantages of the stochastic model of security-constrained unit commitment (SCUC) problem considering plausible scenarios. The non-convexities due to the startup costs, minimum power outputs, and commitment variables make the stochastic SCUC problem and market-clearing non-convex. Meanwhile, with traditional market-clearing methods for energy and ancillary services based on marginal costs or dual variables, the net profit of some generators may become negative. In this situation, more financial losses will be imposed on fast-start generators since they are marginal/intermittent units for managing the uncertainties of RESs. Using a duality gap minimization and profit insurance, this paper presents a pricing model to solve these issues. The proposed market-clearing model leads to uniform prices for ancillary services and nodal prices for energy guaranteeing the non-negative net profit of all generators. The results of the 3-buses system and IEEE 118-buses system are analyzed to illustrate the applications of the proposed pricing approach. © 2021 Elsevier Ltd
  6. Keywords:
  7. Commerce ; Costs ; Electromagnetic wave emission ; Losses ; Natural resources ; Profitability ; Renewable energy resources ; Stochastic systems ; Ancillary service ; Ancillary services markets ; Market clearing ; Renewable energy source ; Security-constrained unit commitment ; Spinning reserves ; System operator ; Traditional markets ; Stochastic models
  8. Source: International Journal of Electrical Power and Energy Systems ; Volume 129 , July , 2021 ; 01420615 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S0142061521000570?via%3Dihub