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<p>The increasing integration of distributed energy resources (DERs) into power systems introduces significant uncertainties in renewable generation, demand, and market prices. These uncertainties complicate decision-making for microgrid (MG) operators, affecting their participation in energy and reserve markets. This research paper discusses the role of MG operators in Day-Ahead (DA), Intraday, Real-Time (RT) energy, and reserve markets. The primary objectives of the MG operator include maximizing revenue and minimizing total costs while considering demand, renewable generation, and market price uncertainty. A three-stage stochastic model is developed to optimize the energy market bidding strategy, factoring in active and reactive power balance as well as power loss constraints. The first stage involves “here-and-now” decisions before uncertainty revelation, the second involves “adjustment” decisions in an intraday market where partial uncertainty is revealed, and the third stage involves “wait-and-see” decisions after uncertainty resolution. Information gap decision theory (IGDT) is also applied to evaluate variations in RT market prices and reserve probabilities that influence MG operator’s expected total cost (ETC), renewable energy allocations, and reserve capacities. The results of IGDT reveal that, in the risk-seeking scenario, the MG operator’s ETC decreases from $75.74 to $63.27, resulting in a 28.21% improvement in revenue maximization. Conversely, the ETC substantially increases to $225.19 in the risk-averse scenario. The findings provide valuable insights into optimizing MG participation in energy markets, improving financial performance, and enhancing system reliability under uncertainty.</p>

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Enhanced Risk-Based Strategy for Microgrid Market Participation using Three-Stage Stochastic Optimization

  • 期刊论文

  • 发表日期：

    2025年9月29日

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  • Priyanka Hooda,
  • Prem Prakash

摘要

The increasing integration of distributed energy resources (DERs) into power systems introduces significant uncertainties in renewable generation, demand, and market prices. These uncertainties complicate decision-making for microgrid (MG) operators, affecting their participation in energy and reserve markets. This research paper discusses the role of MG operators in Day-Ahead (DA), Intraday, Real-Time (RT) energy, and reserve markets. The primary objectives of the MG operator include maximizing revenue and minimizing total costs while considering demand, renewable generation, and market price uncertainty. A three-stage stochastic model is developed to optimize the energy market bidding strategy, factoring in active and reactive power balance as well as power loss constraints. The first stage involves “here-and-now” decisions before uncertainty revelation, the second involves “adjustment” decisions in an intraday market where partial uncertainty is revealed, and the third stage involves “wait-and-see” decisions after uncertainty resolution. Information gap decision theory (IGDT) is also applied to evaluate variations in RT market prices and reserve probabilities that influence MG operator’s expected total cost (ETC), renewable energy allocations, and reserve capacities. The results of IGDT reveal that, in the risk-seeking scenario, the MG operator’s ETC decreases from $75.74 to $63.27, resulting in a 28.21% improvement in revenue maximization. Conversely, the ETC substantially increases to $225.19 in the risk-averse scenario. The findings provide valuable insights into optimizing MG participation in energy markets, improving financial performance, and enhancing system reliability under uncertainty.