Cost mitigation strategy for microgrid using an advanced energy management system with an intelligent controller

• Published in: Electric power systems research Vol. 210; p. 108116
• Main Authors: Vaikund, Harini, S․G․, Srivani
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2022
• Subjects: Electricity cost; Energy management system; Intelligent controller; Microgrid; Power demand; Electricity cost; Power demand; Microgrid; Energy management system; Intelligent controller
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2022.108116

•A standard power system with source and load is designed. PV, battery and utility grid integrated microgrid is designed on the source side, and linear and nonlinear loads of single-person home appliances are designed on the load side.•A dataset is then created based on a person's behaviour and the functions of the loads associated with that behaviour. It is also analysed based on the overall required power of the respective behaviour and the unit price of a source.•An intelligent controller is designed based on the created database, the trained net for the controller is integrated into the EMS.•Based on the trained net, the EMS can effectively operate supply power to fulfil the required load demand on the consumer side. The proposed intelligent EMS provides low power cost and effective power management, and the outcome is compared to other previous methods. A microgrid is a power distribution system that mixes distributed energy resources with controlled loads, and it has the capability to operate both grid-connected mode and islanding mode. However, increasing electricity demand and electricity cost remains a major problem worldwide. To mitigate these cost issues, several organizations have developed innovative techniques for power control, monitoring and security. The Energy Management System (EMS) focuses more on managing power between load and source sides. To overcome the aforementioned issues, an intelligent EMS controller is proposed in this paper. The proposed intelligent controlling system manages power flows as well as reduce electricity cost very effectively. The proposed method contains four steps of the operation such as system design, data gathering, design of intelligent controller and EMS. Dataset is created based on the behaviour of a single person and corresponding load activation for that period, which is used for implementation and performance validation of the proposed method. The proposed method is validated for two modes of operations, namely, grid-connected mode and islanding modes. In both modes, the proposed method offers cost-effective control of energy flow. MATLAB/Simulink software has been used to design the proposed method and test its performance. The proposed method provides better accuracy of 95%. Furthermore, the outcome of the proposed method is compared with other existing methods such as k-nearest neighbours (KNN) and Naive Bayes (NB). The result demonstrates that the ANN-based EMS can interface with various power sources and offer well performance for the task of energy management.