Analysis of Power Network Stabilities Considering the Uncertainty of Large Renewable Power Generations

• Published in: 2023 23rd International Conference on Control, Automation and Systems (ICCAS) pp. 1797 - 1801
• Main Authors: Cho, Haesong, Yi, Sung-Wook, Kwon, Do-Hoon
• Format: Conference Proceeding
• Language: English
• Published: ICROS 17.10.2023
• Subjects: large renewable power; power network stability; Power system stability; Power transmission lines; Predictive models; probabilistic forecast; Probabilistic logic; Renewable energy sources; Stability analysis; Uncertainty
• ISSN: 2642-3901
• DOI: 10.23919/ICCAS59377.2023.10316905

The South Korea's government declared that it will increase renewable power's share of the energy mix from its current level of 7 % to 20 % by 2030. An increase of the renewable power means that fluctuations and uncertainties of power generation are increased, which brings new challenges of power network stability analysis to the system operators. This paper presents a one of the methods for power network stability analyses considering the uncertainty of large renewable power generations in the Korea Electrotechnology Research Institute (KERI). The proposed method forecasts the renewable power generations with probabilistic ranges instead of a point prediction for next time step. A power network modelling is then conducted automatically several times using forecasted loads and the renewable power generations having probabilistic ranges. Finally, the power network stability analyses are conducted automatically for every forecasted power network models. The results are obtained by number of violations related to transmission line overloads and under- or over-voltage buses as well as fault currents of several buses. Simulation case studies are performed using a PSS/E and the case study results confirm that the proposed method successfully conducts the power network stability analyses considering the uncertainty of large renewable power generations.