pp. 379-391
S&M2461 Research Paper of Special Issue https://doi.org/10.18494/SAM.2021.3021 Published: January 31, 2021 Power Dispatch Combining Meteorological Forecast and Dynamic Game Model in Multivariate Distributed Power Generation Systems [PDF] Long-Yi Chang and Shiu-Fu Lin (Received June 22, 2020; Accepted December 10, 2020) Keywords: distributed energy, demand bidding, demand response, power dispatching, DGM
We propose a system of distributed energy that combines a dynamic game model (DGM) with the Central Weather Bureau’s weather data, and apply it to the power dispatch of a distributed grid. A programmable logic controller (PLC) and human–machine interface (HMI) are used to build the distributed grid for dispatching renewable energy. Moreover, the weather overview for 3 days is downloaded by using MATLAB/Simulink and the Python programming language to link to the weather forecast data, and the power generation on the next day is estimated on the basis of the weather data to dispatch the distributed energy according to the time-of-use power price and management plan announced by the power company. In addition, the weather data may change owing to the changeability of the weather. Therefore, this system can, at any time, obtain the latest weather data, apply the DGM, and dispatch the stored distributed energy in accordance with the power company’s demand bidding measures, so that the power system can achieve the most economic power when there is high demand. It was found that the managed dispatch of all the power supplies and loads had optimal efficiencies, and the power company’s reserve capacity was increased to achieve optimal power dispatch.
Corresponding author: Long-Yi ChangThis work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Long-Yi Chang and Shiu-Fu Lin, Power Dispatch Combining Meteorological Forecast and Dynamic Game Model in Multivariate Distributed Power Generation Systems, Sens. Mater., Vol. 33, No. 1, 2021, p. 379-391. |