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Probabilistic planning for participation of virtual power plants in the presence of the thermal power plants in energy and reserve markets

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Abstract

Renewable energy-based on virtual power plants (VPPs) has recently attracted considerable attention for participating in energy and reserve markets due to the disadvantages of thermal power plants (TPPs). The present paper aims to maximize the VPP profitability in distribution networks including thermal power plants, at minimum load cost, using a mathematical model for implementing the VPP and evaluating its role in the energy and reserve markets. The proposed model includes a series of probabilistic scenarios used to consider the uncertainty of wind/solar generation. Therefore in the first step, the lower bound of the problem, i.e., minimizing demand cost for all the units, should be calculated. It determines the status of VPP units based on the best-case scenarios. Afterward, the problem is cut to calculate the upper bound of the problem which is maximizing the profit of the VPP. The problem is evaluated in two cases: one is the presence of VPP only in the energy market and the other is the simultaneous presence of the VPP in the reserve and energy markets. The computation ends with the convergence of lower and upper bounds of the problem. Since the proposed method uses a piece-wise model of thermal units and the problem has nonlinear equations, Mixed Integer Programming (MIP) used to calculate the contribution of units by utilizing GAMS software. Finally, the VPP profitability calculated for the day-ahead energy and reserve market after determining the method for the participation of power plants in supply at the minimum cost. The proposed method was then applied to a sample system consisting of three thermal plants, three wind farms, two solar farms, and two energy storage systems, considering several situations to examine the impact of the resources and also the resulting profitability in the energy and reserve market. The final step was the analysis of the results.

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Authors and Affiliations

  1. Electrical Engineering Department, Bushehr Branch, Islamic Azad University, Bushehr, Iran

    Masoud Dashtdar, Mojtaba Najafi & Mostafa Esmaeilbeig

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  1. Masoud Dashtdar
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  2. Mojtaba Najafi
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  3. Mostafa Esmaeilbeig
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Correspondence to Mojtaba Najafi.

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Dashtdar, M., Najafi, M. & Esmaeilbeig, M. Probabilistic planning for participation of virtual power plants in the presence of the thermal power plants in energy and reserve markets. Sādhanā 45, 93 (2020). https://doi.org/10.1007/s12046-020-01335-z

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  • DOI: https://doi.org/10.1007/s12046-020-01335-z

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