Journal article
Peer‐to‐peer load allocation using potential field concept for optimal operation of standalone microgrids
IET Generation, Transmission & Distribution, Vol.14(25), pp.6061-6070
2020
Abstract
The operation of a standalone microgrid is often optimised by the central controller that decides the set‐points of the local controllers of the distributed generators. However, the optimised set‐points may not remain optimal for a longer period due to the variability of loads and renewable generations. This study proposes a technique for readjusting the dispatch of the suitable generation units, between the optimisations carried out by the central controller, to support load changes. To this end, the potential field concept has been suggested to be adopted by the loads to select the appropriate generation units. The decision is made based on different criteria, such as their cost, reliability, emission, and power loss. This process requires low computational efforts, and thus, can act and make decisions immediately. This is valid as far as the change in the loads is not substantial. For a change above a predetermined level, the microgrid's central controller steps in to optimise the system. The central controller also performs the regular optimisation periodically to retune the whole system and reconfirm the optimal operation. The performance of the proposal has been evaluated by numerical analysis and validates the success and efficacy of the proposal.
Details
- Title
- Peer‐to‐peer load allocation using potential field concept for optimal operation of standalone microgrids
- Authors/Creators
- M.A. Shoeb (Author/Creator)F. Shahnia (Author/Creator)GM. Shafiullah (Author/Creator)
- Publication Details
- IET Generation, Transmission & Distribution, Vol.14(25), pp.6061-6070
- Publisher
- John Wiley & Sons, Ltd. on behalf of The Institution of Engineering and Technology
- Identifiers
- 991005544310707891
- Copyright
- © 2020 The Authors.
- Murdoch Affiliation
- School of Engineering and Energy
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.18 Power Systems & Electric Vehicles
- 4.18.204 Smart Grid Optimization
- Web Of Science research areas
- Engineering, Electrical & Electronic
- ESI research areas
- Engineering