Energy optimization and digitization of the PV energy balance between production and consumption

• Published in: e-Prime Vol. 11; p. 100883
• Main Authors: Hraich, Abdellatif, Haddi, Ali
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2025; Elsevier
• Subjects: Artificial intelligence; Astronomic position; Data base; Energy balance; Energy internet; Photovoltaic; Solar tracking system; Stochastic algorithm; ADC; DAST; GRT; SAST; GPS; NTR; IoT; Photovoltaic; STS; Solar tracking system; SAPA; DOF; LDR; SCADA; AA; COSE; AI; Stochastic algorithm; IT; PVs; Data base; GPIO; Energy balance; Astronomic position; Energy internet; Artificial intelligence; DB
• ISSN: 2772-6711; 2772-6711
• DOI: 10.1016/j.prime.2024.100883

·Smart grids integrate information technologies to enhance the management of renewable energy sources as well as managing the energy balance between production and consumption.·The energy data from the photovoltaic panels is stored in real-time, in local database and in external IoT database (NoSQL→ GoogleFirebase) using the concept of connected objects or energy internet.·Photovoltaic, energy balance, solar tracking system, artificial intelligence, astronomic position, stochastic algorithm, energy internet, data base. Smart grids integrate information technologies to enhance the management of renewable energy sources as well as managing the energy balance between production and consumption. Their design relies on efficiently controlling intermittent energy production through two-way communication between energy generation and consumption, across the entire power grid value chain. Our primary objective is to demonstrate that the Sun Path Tracker, either with two or one degree of freedom, is more energy-efficient than fixed solar panels. This study offers solutions to optimize photovoltaic energy production by passing from experimentation using a solar tracking system and a Sun Astronomic Position Algorithm, that incorporates three different degrees of freedom photovoltaic panels mounted in mobile bracket and artificial intelligence optimization using stochastic algorithms. The energy data from the photovoltaic panels is stored in real-time, in local database and in external database (NoSQL→ GoogleFirebase) using the concept of connected objects or energy internet. This work had permitted to enhance the conversion efficiency of the photovoltaic panels by using the tracking technique and the Sun Algorithm Position via Astronomic calculation in the same line, we had built a database permitting to store the details about the different positions of tracking system with their equivalent energy values in their real actual reading times. Based on the average calculations, it is clear that our solution provides between 8,43 % and 14,56 % of energy yields significantly higher than fixed solar panels.