An Evaluation of the Power System Stability for a Hybrid Power Plant Using Wind Speed and Cloud Distribution Forecasts

Théodore Desiré Tchokomani Moukam (), Akira Sugawara, Yuancheng Li and Yakubu Bello
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Théodore Desiré Tchokomani Moukam: Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
Akira Sugawara: Department of Electrical and Electronic Engineering, Faculty of Engineering, Niigata University, 8050 Ikarashi-2, Niigata 950-2181, Japan
Yuancheng Li: Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
Yakubu Bello: Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan

Energies, 2025, vol. 18, issue 6, 1-21

Abstract: Power system stability (PSS) refers to the capacity of an electrical system to maintain a consistent equilibrium between the generation and consumption of electric power. In this paper, the PSS is evaluated for a “hybrid power plant” (HPP) which combines thermal, wind, solar photovoltaic (PV), and hydropower generation in Niigata City. A new method for estimating its PV power generation is also introduced based on NHK (the Japan Broadcasting Corporation)’s cloud distribution forecasts (CDFs) and land ratio settings. Our objective is to achieve frequency stability (FS) while reducing CO 2 emissions in the power generation sector. So, the PSS is evaluated according to the results in terms of the FS variable. Six-minute autoregressive wind speed prediction (6ARW) support is used for wind power (WP). One-hour GPV wind farm (1HWF) power is computed from the Grid Point Value (GPV) wind speed prediction data. The PV power is predicted using autoregressive modelling and the CDFs. In accordance with the daily power curve and the prediction time, we can support thermal power generation planning. Actual data on wind and solar are measured every 10 min and 1 min, respectively, and the hydropower is controlled. The simulation results for the electricity frequency fluctuations are within ±0.2 Hz of the requirements of Tohoku Electric Power Network Co,. Inc. for testing and evaluation days. Therefore, the proposed system supplies electricity optimally and stably while contributing to reductions in CO 2 emissions.

Keywords: wind speed; autoregressive model; power system stability; NHK cloud distribution forecasts; photovoltaic (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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