# Management of Distributed Renewable Energy Resources with the Help of a Wireless Sensor Network
## 1 Introduction  
The world is becoming increasingly reliant on energy as the social economy develops, and the energy problem has become a bottleneck in human society's progress [1]. According to contemporary scientific literacy works [2], the primary sources of energy linked with the petroleum family, contributing to about 78-80% of energy, are expected to be exhausted by 2050. Referring to some studies, gas, oil, and their products are expected to deplete in the next two decades, implying that these sources may not be able to meet energy requirements [3]. As the energy emergency intensifies, sustainable power sources such as wind and solar energy have gained the limelight. Global wind power generation reached 733 GW in 2020, an increase of 17.8% over 2019 [4]. Solar power generation reached 714 GW in 2020, an approximate increase of 21.6% from the previous year [5, 6]. The boundless and unpolluted nature of eco-friendly energy sources such as photovoltaic (PV) and wind energy makes them the most suitable and fastest growing green energies. As a significant means of developing and utilizing renewable energy, PV and wind powergeneration have an exceptionally wide application prospect with the upsides of no fuel utilization, no contamination outflow, and adaptable application structure. PV and wind power generation, on the other hand, are sensitive to fluctuating solar radiation intensity and environmental conditions. The output is unpredictable and intermittent, which will certainly have a negative impact on the stability and reliability of the power system once it is connected to the grid. As a result, a PV system's dependable power generation projection can help to mitigate the negative consequences of the utility grid. Microgrids (MGs) with limited-scale low-voltage energy frameworks are becoming an inexorably significant part of today's electricity grids [7]. These independent frameworks consist of modular and distributed generation units, energy storage systems (ESSs), and utility loads; additionally, these MGs can work on- or off-grid. A point of common coupling allows for bidirectional power exchange in a grid-connected mode operation, authorizing the trading of energy with the grid [8]. Modern MGs are complex energy systems that incorporate renewable energy sources (RESs), dispatchable generating units, various types of consumers and prosumers, electric vehicles (EVs), and ESSs [9]. Consequently, the development of an energy management system is a captivating option that takes on a crucial job in the long-term MG arrangement to improve system performance. The goals of power management are to lower operating costs, increase living comfort, and redistribute peak load demand [10]. Optimal scheduling of the electric apparatus is frequently required for redistribution of peak load demand, and scheduling is the same as adjusting the power usage of particular appliances [11]. Time-series forecasting is an important field that encourages researchers to keep looking into new areas of interest for various applications. The volume and speed with which time-series data is updated continue to grow as sensors and storage devices improve. As the conventional forecasting techniques cannot utilize continuous information data to progressively refresh the model, online prediction algorithms have received broad attention [12]. The online projection algorithms can obtain the dynamic factual attributes of the information progressively, create timely and accurate forecasts, and give significant reference data for logical exploration [13]. The recurring tasks determined by an artificial neural network (ANN) include pattern recognition, prediction, picture classification, clustering, signal processing, social networking, and machine learning (ML) techniques. ML, deep learning (DL), neural network (NN), cloud computing, big data, wireless communication, and information security are just a few of the hot subjects in information and communications technology [14].