Development of Mae Sa Nga Dam Hydro Power Plant Model for Application of Nonlinear Model Predictive Control to Energy Management System in Mae Hong Son
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Abstract
This paper aims to improve the hydro power plant model for the control of energy management systems (EMS) with optimal power flow. In addition, it aims to apply nonlinear model predictive control to the EMS of Mae Hong Son (MHS). Improving the hydro power plant model employs the prediction of the water level in the Mae Sa Nga Dam based on a time series model and a long-short term memory model. We compare the water level model with the dataset of Mae Sa Nga Dam for predicting water levels of 1 day ahead and 30 days ahead. When applying the improved hydroelectric power plant model to the EMS of MHS, it is found that more electricity is generated in the rainy and winter seasons, which results in a reduction of total operating costs (TOC) and total CO2 emissions (TCOE) without relying on diesel power sources. However, in the summer there is a decrease in hydro power generation which results in an increase of TOE and TCOE. It requires diesel power generation and the import of electricity from the electrical power grid.
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