Вероятностная оценка краткосрочной гибкости энергосистемы с учетом ошибок прогнозов генерации и потребления
DOI:
https://doi.org/10.24160/0013-5380-2026-8-17-28Keywords:
power system flexibility, probabilistic analysis, forecast errors, renewable energy sources, wind power plants, solar power plants, net load forecasting, regulating reservesAbstract
The article addresses the problem of assessing electric power system (EPS) flexibility subject to uncertainty caused by forecast errors in renewable energy sources (RES) generation and EPS active power demand. The effect the forecast errors in wind power plants (WPP), solar power plants (SPP) generation, and in EPS electricity demand have on the power balance is analyzed. A methodology for determining the total uncertainty of operating conditions based on the statistical aggregation of forecast errors considering their correlation has been developed. An approach for evaluating the required level of power system flexibility and the amount of regulating reserves is proposed. A methodology for probabilistic assessment of power system flexibility has been developed that takes into account the combined effect of forecast errors in RES generation and electricity demand based on their statistical characteristics and mutual correlation. Relationships for determining the total uncertainty of operating conditions are obtained, and EPS flexibility requirements are evaluated at different levels of generation and demand variability. The impact of forecast errors on the required regulating reserves and the EPS ability to maintain power balance is demonstrated. The obtained results can be applied in planning the EPS operation modes, determining the requirements for generation flexibility and reserve amounts, and in analyzing the conditions for integrating wind and solar power plants into the EPS.
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2. IRENA. Power System Flexibility for the Energy Transition. Part 1: Overview for policy makers. Abu Dhabi: International Renewable Energy Agency, 2018, 48 p.
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6. Holttinen H. et al. Methodologies to Determine Operating Reserves Due to Increased Wind Power. – IEEE Transactions on Sustainable Energy, 2012, vol. 3. No. 4, pp. 713–723, DOI: 10.1109/TSTE.2012.2208207.
7. Wang Y. et al. Methods for Assessing Available Wind Primary Power Reserve. – IEEE Transactions on Sustainable Energy, 2015, vol. 6. No. 1, pp. 272–280, DOI: 10.1109/TSTE.2014.2369235.
8. Status of Power System Transformation: Advanced Power Plant Flexibility. Paris: International Energy Agency, 2018, 115 p.
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10. Response to CEER Consultation. Technical Report. Brussels: European Network of Transmission System Operators for Electricity (ENTSO-E), 2017, 34 p.
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13. Lyon J. et al. Market Implications and Pricing of Dynamic Reserve Policies for Systems with Renewables. – IEEE Power & Energy Society General Meeting, 2015, DOI: 10.1109/PESGM.2015.7285837.
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19. Heggarty T. et al. Quantifying Power System Flexibility Provision. – Applied Energy, 2020, vol. 279, DOI: 10.1016/j.apenergy.2020.115852
