Retail Electricity Pricing Strategy via an Artificial Neural Network-Based Demand Response Model of an Energy Storage System

A comprehensive state‐of‐the‐art review of power conditioning systems for energy storage systems: Topology and control applications in power systems

“…The ESS ensures the voltage/current regulation to maintain the grid frequency and voltage amplitude for the grid‐supporting converters. Among various ESS applications, this section addresses the PCS control of the ESS for power backup smoothing [73–82], frequency regulation [83–95] and voltage regulation and power quality applications [96–110], ESS multi‐functional stacking [111–119], artificial intelligence (AI) [120–130] and security of control for ESS [131–139].…”

“…The decision‐making process considers the preferences of both the distribution company and ESS owners in the single‐level structure of optimal pricing strategy. The data of the electricity price and optimal demand from the building EMS is used to train the ANN‐based DR model for day‐ahead optimal retail price while considering the peak reduction [121]. Different modifications of NN are used to estimate the BESS health for multiple channels multiple profiles based BMS and the charging profiles are modified according to the age of the BESS [122].…”

“…In the distribution network, an artificial neural network (ANN)‐based demand response (DR) model is formulated for the electricity retail pricing strategy and optimal operation of ESS [121]. The decision‐making process considers the preferences of both the distribution company and ESS owners in the single‐level structure of optimal pricing strategy.…”

“…The control design of the PCS is also responsible for facilitating the usage of ESS for different power applications such as power backup smoothing [73–82], frequency regulation [84–95], voltage regulation and power quality improvement [96–110]. ESS multi‐functional stacking [111–119], artificial intelligence [120–130] and security of control for ESS [131–139] are the popular and relatively new applications for the PCS of ESS.…”

IoT Technology Enabled Heuristic Model With Morlet Wavelet Neural Network for Numerical Treatment of Heterogeneous Mosquito Release Ecosystem

“…The Internet of Things (IoT) is an innovation embedded with software, sensors, actuators, electronics, and network connectivity through which data can be collected and exchanged over the Internet. Artificial neural network (ANN) [1][2][3][4], software-defined networks (SDN) [5][6][7], and internet of things (IoT) [8][9][10][11][12][13][14] technologies find useful in different applications from the smart healthcare sector [15][16][17][18][19][20] to the satellite [21]. The exponential utilization of the Internet of Things (IoT) is expanding and is of ongoing interest as it is broadly utilized in numerous applications and devices like remote sensors, clinical devices, delicate home sensors, and other related IoT devices as shown in Fig.…”