Application of artificial intelligence for prediction, optimization, and control of thermal energy storage systems

• Published in: Thermal science and engineering progress Vol. 39; p. 101730
• Main Authors: Olabi, A.G., Abdelghafar, Aasim Ahmed, Maghrabie, Hussein M., Sayed, Enas Taha, Rezk, Hegazy, Radi, Muaz Al, Obaideen, Khaled, Abdelkareem, Mohammad Ali
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2023
• Subjects: Artificial intelligence; Artificial neural networks; Energy efficiency; Energy storage; Optimization; MPC; FFC; FLFFC; GHI; CHP; DP; PVT; HVAC; RNN; ANFIS; SNEG; NARX; R2; FFNN; AC; Artificial neural networks; AI; MAPE; PSO; ES; MAE; RH; TESS; Energy efficiency; HTF; PCM; SAH; PTC; Qcool; Energy storage; CFD; 5GDHC; ANN; MRE; GEHP; GMDH; SVM; BP; Optimization; RDC; DHW; ANNi; VDF; GA; SP; MSE; CSP; LSTM; ESS; COP; SOC; Nu; CL; RMSE; CCHP; Artificial intelligence

•Different types of Artificial Intelligence Techniques are presented.•Artificial Intelligence Techniques for ESS are presented.•Analysis, design, operation, optimization, and control of ESS are studied.•Multiple independent parameters affecting the performance of ESS are reviewed. Energy storage is...