Intelligent Energy Management System for Microgrids with Energy Storage Integration
The items are a software solution, it is designed for micro grids with energy storage integration to monitor, control, and best utilize available grid resources. Also called a mini-grid, the micro grid is a distributed energy system consisting of local small-scale generation and storage facilities that could operate independently from the main grid in an emergency. Micro grids are frequently paired with solar panels and wind turbines, making them more sustainable. The capacity of energy storage systems in micro grids has been playing an important role, as renewable energy in devices with temporal availability generates the need for their more efficient use. Based on real-time data, the items apply energy transmission and distribution management algorithms to control where the power is used in a micro grid. The items continuously monitor the demand and supply of energy to investigate the ideal combination of renewable generation and stored energy for peak shaving. In doing so, the micro grid can run optimally and minimize energy waste without running up bills. The items can also predict how and when individuals use energy, thus allowing better scheduling of the available resources. This enables the items to conduct predictive maintenance on those micro grid components to long and function as efficiently as possible.
Authors
- Monoo John (ORCID: https://orcid.org/0000-0002-6136-1833)
- Paramjit Baxi
- R Manaswini
- Mukesh Kumar (ORCID: https://orcid.org/0000-0003-4539-9732)
- Dhananjay Kumar Yadav (ORCID: https://orcid.org/0000-0002-8487-8165)
- Simranjeet Nanda
Institutions
- Jain University (IN)
- Presidency University (IN)
- Siksha O Anusandhan University (IN)
- Maharishi University of Management and Technology (IN)
- Chitkara University (IN)
Publication Details
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1109/autocom64127.2025.10957276
- Citations
- 2
- Primary Topic
- Microgrid Control and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 2.43