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Optimization method for a hybrid microgrid energy management system with reserve margins
Author(s)
Mquqwana, Manduleli Alfred
Date Issued
2024
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
The research study aims to provide an optimization technique for a hybrid microgrid energy
management system with reserve margins. The load for the hybrid microgrid under
consideration consists of grid-connected photovoltaic, wind, and battery energy storage devices
and electric vehicles that may provide grid support.
The recommended solution considers both an isolated mode of operation and a grid-connected
operating situation. Isolated microgrids improve system resilience by distributing electricity to
nearby loads from locally accessible resources. Furthermore, it is still challenging to govern,
run, and protect these systems in grid-connected and islanded modes, cope with dispatch
difficulties that decide the DRES's priority, and provide grid support, among other challenges.
Furthermore, the BESS charging and discharging strategy should follow the Risk Mitigation
Independent Power Producer Procurement Programme (RMIPPP) guidelines, charging
predominantly from local renewable energy sources rather than the grid. This ensures that local
South African legislation and requirements are observed throughout the investigation.
The study focuses on optimizing and modeling a hybrid microgrid system incorporating different
green energy sources, such as grid-tied solar photovoltaic, wind energy, and battery energy
storage devices. The study uses sophisticated optimization techniques to increase the
microgrid's efficiency and reliability. Specifically, particle swarm optimization and the genetic
algorithm are used to solve the system model and address the difficulties of optimal energy
generation, storage management, and hybrid integration. The findings illustrate the efficiency of
these optimization approaches in improving overall performance, lowering costs, and assuring
the microgrid's dispatch strategy under different operational situations.
management system with reserve margins. The load for the hybrid microgrid under
consideration consists of grid-connected photovoltaic, wind, and battery energy storage devices
and electric vehicles that may provide grid support.
The recommended solution considers both an isolated mode of operation and a grid-connected
operating situation. Isolated microgrids improve system resilience by distributing electricity to
nearby loads from locally accessible resources. Furthermore, it is still challenging to govern,
run, and protect these systems in grid-connected and islanded modes, cope with dispatch
difficulties that decide the DRES's priority, and provide grid support, among other challenges.
Furthermore, the BESS charging and discharging strategy should follow the Risk Mitigation
Independent Power Producer Procurement Programme (RMIPPP) guidelines, charging
predominantly from local renewable energy sources rather than the grid. This ensures that local
South African legislation and requirements are observed throughout the investigation.
The study focuses on optimizing and modeling a hybrid microgrid system incorporating different
green energy sources, such as grid-tied solar photovoltaic, wind energy, and battery energy
storage devices. The study uses sophisticated optimization techniques to increase the
microgrid's efficiency and reliability. Specifically, particle swarm optimization and the genetic
algorithm are used to solve the system model and address the difficulties of optimal energy
generation, storage management, and hybrid integration. The findings illustrate the efficiency of
these optimization approaches in improving overall performance, lowering costs, and assuring
the microgrid's dispatch strategy under different operational situations.
Additional information
Thesis (DEng (Electrical Engineering))--Cape Peninsula University of Technology, 2024
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