Optimal Energy Management System of Isolated Multi-Microgrids with Local Energy Transactive Market with Indigenous PV-, Wind-, and Biomass-Based Resources

Abstract

The availability of sustainable, efficient electricity access is critical for rural communities as it can facilitate economic development and improve the quality of life for residents. Isolated microgrids can provide a solution for rural electrification, as they can generate electricity from local renewable energy sources and can operate independently from the central grid. Residential load scheduling is also an important aspect of energy management in isolated microgrids. However, effective management of the microgrid’s energy resources and load scheduling is essential for ensuring the reliability and cost-effectiveness of the system. To cope with the stochastic nature of RERs, the idea of an optimal energy management system (EMS) with a local energy transactive market (LETM) in an isolated multi-microgrid system is proposed in this work. Nature-inspired algorithms such as JAYA (Sanskrit word meaning victory) and teaching–learning based optimization algorithm (TLBO) can get stuck in local optima, thus reducing the effectiveness of EMS. For this purpose, a modified hybrid version of the JAYA and TLBO algorithm, namely, the modified JAYA learning-based optimization (MJLBO), is proposed in this work. The prosumers can sell their surplus power or buy power to meet their load demand from LETM enabling a higher load serving as compared to a single isolated microgrid with multi-objectives, resulting in a reduced electricity bill, increased revenue, peak-average ratio, and user discomfort. The proposed system is evaluated against three other algorithms TLBO, JAYA, and JAYA learning-based optimization (JLBO). The result of this work shows that MJLBO outperforms other algorithms in achieving the best numerical value for all objectives. The simulation results validate that MJLBO achieves a peak-to-average ratio (PAR) reduction of 65.38% while there is a PAR reduction of 51.4%, 52.53%, and 51.2% for TLBO, JLBO, and JAYA as compared to the unscheduled load.

State-of-the-art review on energy sharing and trading of resilient multi microgrids

“…Several game equilibrium methods have been widely adopted in recent literature to satisfy the market-related constraints in the presence of intermittent sources and electric vehicles. The authors in 62 formulated the MMG energy management problem in the real-time pricing market using sequential game theory. To this end, the sequential non-cooperative games model is designed to optimize the operation routines of each individual microgrid.…”

An intelligent multi-layer, multi-agent MMG framework with amelioration of energy efficiency and future investment outlook, under the deregulated day-ahead and real-time market regime

“…The authors have not discussed the energy transaction among grids and the details of the MG load nature and its scheduling. Ali et al (2023) proposed the energy management system for the residential load only but have neglected the priorities to be assigned to the appliances during low Frontiers in Energy Research frontiersin.org generation power. Furthermore, the economic viability of the MG for power transactions in the energy market is not highlighted.…”

Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity

“…Energy Management Systems: Energy management systems (EMSs) are software programs that manage and control the operation of a microgrid [92,100,101]. They optimize the use of energy resources, including storage, generation, and load, to meet demand and minimize energy costs.…”

“…By optimizing the use of RESs, MEMSs can help to reduce greenhouse gas emissions and contribute to a more sustainable energy future. MEMSs can also help to reduce energy costs for consumers by optimizing energy use and reducing waste [101].…”