PL EN
Power Quality Enhancement of Smart Home Energy Management System in Smart Grid Using MAORDF-CapSA Technique
 
Więcej
Ukryj
1
Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra Pradesh 522502, India
2
Department of Electrical and Electronics Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Bachupally, Survey No. 288, Nizampet Rd, Kukatpally, Hyderabad, Telangana 500090, India
3
Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh 522502, India
AUTOR DO KORESPONDENCJI
Vinjamuri Usha Rani   

Department of Electrical and Electronics Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Bachupally, Survey No. 288, Nizampet Rd, Kukatpally, Hyderabad, Telangana 500090, India
 
Ecol. Eng. Environ. Technol. 2022; 5:1–19
 
SŁOWA KLUCZOWE
DZIEDZINY
STRESZCZENIE
An IoT-based Smart Home Energy Management System (SHEMS) with Power Quality Control (PQC) in Smart Grid using MAORDF-CapSA system is proposed in this paper. The proposed hybrid system is the combined execution of the Mexican Axolotl Optimization (MAO)-Random Decision Forest (RDF) and the capuchin search algorithm (CapSA) therefore it is known as MAORDF-CapSA system. The main contribution of this paper is divided into two phases namely, Smart Home Energy Management System (SHEMS) and Power Quality Enhancement (PQE). In the first phase, the main objective of the proposed work is pointed out as it pursues: (1) to propose an EMS for the distribution system that uses the IoT framework; (2) to deal with the power and resources of the distribution system; (3) promote the advancement of the DR energy management system; (4) expand the adaptability of networks and optimize the use of accessible resources. The second phase permits to improve the shared use of the grid to maintain the power quality. The proposed CapSA controller detects the event of power quality issue and voltage rise. Additionally, the proposed system is responsible for meeting the general supply and energy demand. The performance of the proposed system is executed on the MATLAB platform and compared with various existing systems.