Faculty of Computing, Health and Science
School of Engineering
Efficient utilisation of Storage Devices (SD) among multiple sources of dispatch within a typical microgrid have a substantial impact on reducing the economic and environmental generation costs in that particular microgrid. Eventually, managing the multiple sources that supply energy simultaneously is a big engineering challenge. The complexity rises due the uncertainty of demand, generation cost, availability of renewable energy sources and (charging/discharging) time and price for the installed SD. This paper introduces a utilisation method that makes the SD more efficient in supplying the electricity within a typical medium size enterprise microgrid. The method is simply targeting the dynamic charging price for the SD to achieve a profitable charging, and also to maximise the opportunity of participation during the SD lifetime. A fuzzy logic based adaptive charging price is set for charging the SD based on the microgrid's local generation price at the time of charging, and the amount of the daily SD participation in the microgrid dispatch. By considering the economic and environmental generation costs in 30-minute operation intervals, a multi-objective Particle Swarm Optimisation (PSO) method is applied to optimise the energy dispatch for the managed microgrid. In addition, a switching mechanism based on the SD status is integrated with the proposed PSO to deal with the variable operation scenarios in the managed microgrid. The proposed optimisation technique has been tested on the realistic operation scenarios of the power grid of the Joondalup Campus of Edith Cowan University in Western Australia. The simulation results showed a reasonable amount of efficiency improvement with a range of benefits in cutting the generation cost for the targeted case study.