EV-Based reconfigurable smart grid management using support vector regression learning technique machine learning

Intelligent fault tolerant energy management system using first-price sealed-bid algorithm for microgrids

“…As shown in figure 3, tenderer gets power and offer price, then picks the lowest bid as a winning price. Thereafter, tenderer subtracts requested power from power presented by winning, and checks balance between supply and demand is achieved or not 13 This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4172983 P r e p r i n t n o t p e e r r e v i e w e d (Eq.…”

“…The authors, in [12] presented a nondominated sorting genetic algorithm to optimize cost and schedule for residential buildings. Moreover the study [13] presents a machine learning based approach to manage energy in the system by displacement loads.…”

Data-Driven Methods of Machine Learning in modeling the Smart Grids

“…An ML-based energy optimization algorithm enables to tracking of realtime energy use, irreversible transaction records of electricity trading, managing electricity trading, and model reward [2]. The Gray-Wolf algorithm helps to manage the optimum programming of agents, loads, storage, and switches in the SG [3]. The AMI network's communication methods are largely similar to those of the most recently developed Internet of Things (IoT) communication models.…”

Application of Machine Learning to Predict Thermal Performances of Heat Sinks

“…Accurate ML-based models overcome the challenges of expensive experimental and computational techniques for developing physics-based models [3]. Different mathematics-based algorithms in ML such as artificial neural network (ANN) [4], support vector regression (SVR) [5], and kernel ridge regression (KRR) [6] have been widely used for regression and classification analysis. However, selecting appropriate ML techniques to predict hydrothermal performances of engineering systems highly depends on understanding the capabilities of the individual ML methods and algorithms.…”