Optimal Scheduling of Energy Storage Systems with Private Ownership Based on a Stochastic-Robust Hybrid Optimization Model in Energy and Ancillary Services Markets

Document Type : Power Article

Authors

1 MSc, Department of Electrical Engineering, Arak University of Technology, Arak, Iran

2 Assistant Professor, Department of Electrical Engineering, Arak University of Technology, Arak, Iran

Abstract

In this paper, the problem of participation of a Battery Energy Storage (BES) in the Day-Ahead Market (DAM) and Real-Time Market (RTM) in three cases including Joint Energy and Reactive Power Market (JERPM), Energy Market (EM) and Energy and Reserve Market (ERM) is modeled based on a hybrid Stochastic Robust Optimization (SRO) model and it tries to maximize the profit of the BES owner in the face of uncertainty pertaining to the market prices. In the proposed model, in the first step, the decision maker or BES owner predicts energy, reserve and reactive power prices in each market according to historical network information. In the second step, by determining the uncertainty interval of prices for DAM and RTM, robust optimization is implemented aiming at maximizing the profit of the BES owner using a model of forming a robust counterpart of the objective function and dual theory. In the next step, by defining some different scenarios for the robust budget, Stochastic Programming (SP) assigns a probability to each scenario. Then, the final profit of each market is calculated through probabilistic weighting, and finally the market with more profit is opted as considered participation market. The proposed formulation based on the Mixed Integer Nonlinear Programming (MINLP) model is implemented in the GAMS software environment and the results demonstrate the maximum profitability of BES in EM (21% more) and also show participation in providing ancillary services, such as reserve to provide security in incidents and reactive power to maintain stability and reduce cost and losses, despite the decrease in profit, leads to neutralizing the negative impact of uncertainties in the BES profit.
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Keywords

Main Subjects

References

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Journal of Modeling in Engineering
Volume 22, Issue 76
May 2024
Pages 1-12

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History

  • Receive Date: 21 February 2022
  • Revise Date: 22 July 2023
  • Accept Date: 20 August 2023

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