Day‐ahead scheduling of a hybrid renewable energy system based on generation forecasting using a deep‐learning approach

Abstract

A significant amount of electricity in numerous regions worldwide is used for lighting roads, squares, and other public spaces. Renewable energy can contribute notably to electricity usage for public lighting. This paper focuses on the day-ahead scheduling of a hybrid renewable energy system (HRES) exploiting solar-wind energy potential to meet the electrical energy needs of public lighting. The studied HRES provides electricity for a Wi-Fi hotspot and a charging hotspot for the end users and has an energy storage system that ensures a reliable electricity supply without interruptions. The day-ahead scheduling of the studied HRES is based on electricity generation forecasting by using a deep-learning approach. Particularly, the long short-term memory model is utilized, considering the fact that it is able to perceive long-term dependencies among the time series. Moreover, the model's performance is investigated through the determination of diverse inputs: (a) historical data, (b) weather predictions, and (c) historical data with weather predictions. Multiple scenarios of energy consumption are assumed and applied to optimize the day-ahead scheduling. A new recommendation method is proposed and applied for day-ahead scheduling, utilizing the power forecasts to achieve optimum operation and energy savings. The results point out that the utilization of the proposed recommendation method controls loads when a shortage in power generation and battery capacity is forecasted for the day ahead, leading to significant energy savings and minimizing the power demand from the grid.

Smart Street Light Control: A Review on Methods, Innovations, and Extended Applications

“…Zamanidou et al [137], used a multivariate LSTM model for day-ahead power generation forecasting from a PV panel and wind turbine in a hybrid renewable energy system. They optimized energy management by incorporating weather variables and historical data.…”

“…This transformation aligns with the shift towards smart city development, where Wi-Fi-enabled SLs can serve as integral components of a city's digital infrastructure. Various studies in the literature highlight the potential of SLs as Wi-Fi hotspots [137,171]. -5G or Beyond5G/6G: SLs play a key role in integrating 5G and 6G networks within smart cities, aiding the high-density base station requirements of these technologies [13].…”