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Enspi Technologies

The introduction of a power energy system bring new opportunities for fully exploiting its power system efficiency and reliability, such as demand response at a large scale for household, commercial and industrial users.
Enspi-03

The introduction of a power energy system bring new opportunities for fully exploiting its power system efficiency and reliability, such as demand response at a large scale for household, commercial and industrial users. This information is provided from different balancing authority electric utilities companies. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, making an appropriate forecasting model for a specific electricity network is not an easy task. This model will finally include energy demand usage data prediction and forecasting with newly technologies using deep learning models.

In recent years, countries worldwide have actively researched the power sector. Deep learning technologies have brought new opportunities and challenges to power load forecasting. The power system’s main task is to provide a safe and reliable power supply for the consumers. Therefore, energy forecasting is of considerable significance to the power sector. Accurate power load forecasting is of great importance for saving energy, reducing power generation costs, and improving social and economic benefits. With the development of power reform and the deepening of power market, energy load forecasting has become more critical in the power system. It is also essential to increase power demand forecasting accuracy for the power system’s stable and efficient operation.

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