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Day-ahead optimal bidding of microgrids considering uncertainties of price and renewable energy resources

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  • Nikpour, Ahmad
  • Nateghi, Abolfazl
  • Shafie-khah, Miadreza
  • Catalão, João P.S.

Abstract

Unpredictable faults always reduce the stability and reliability of the electrical system. The increasing use of renewable energy sources (RES) in recent decades has exacerbated power system problems. Microgrids (MG) participation in Ancillary Services (AS) market is a suitable solution for the optimal performance of power systems in these conditions. MGs can also maximize their profits by participating in the AS market. In this paper, the optimal stochastic bidding strategy in joint energy and AS (regulation up and regulation down, spinning reserve and non-spinning reserve) market is modeled. Uncertainties of wind speed and solar radiation are modeled using Weibull and Beta probability distribution functions (PDFs) and probability of call AS is computed for all available AS. Therefore, the risk of the bidding strategy is controlled using conditional value at risk (CVaR). ERCOT market simulation has been carried out in order to determine the participation of each generator in all of the mentioned markets for different prices of energy and also to present the bidding curve, based on real-world data.

Suggested Citation

  • Nikpour, Ahmad & Nateghi, Abolfazl & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Day-ahead optimal bidding of microgrids considering uncertainties of price and renewable energy resources," Energy, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:energy:v:227:y:2021:i:c:s0360544221007258
    DOI: 10.1016/j.energy.2021.120476
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