Abstract
Optimal scheduling of distributed energy resources (DERs) of a low-voltage utility-connected microgrid system is studied in this paper. DERs include both dispatchable fossil-fueled generators and non-dispatchable renewable energy resources. Various real constraints associated with adjustable loads, charging/discharging limitations of battery, and the start-up/shut-down time of the dispatchable DERs are considered during the scheduling process. Adjustable loads are assumed to the residential loads which either operates throughout the day or for a particular period during the day. The impact of these loads on the generation cost of the microgrid system is studied. A novel hybrid approach considers the grey wolf optimizer (GWO), sine cosine algorithm (SCA), and crow search algorithm (CSA) to minimize the overall generation cost of the microgrid system. It has been found that the generation costs rise 50% when the residential loads were included along with the fixed loads. Active participation of the utility incurred 9–17% savings in the system generation cost compared to the cases when the microgrid was operating in islanded mode. Finally, statistical analysis has been employed to validate the proposed hybrid Modified Grey Wolf Optimization-Sine Cosine Algorithm-Crow Search Algorithm (MGWOSCACSA) over other algorithms used.
Highlights
Maximum output with minimum capital spent has always been a significant objective for all production processes including power generation
The hybridization will be done with modified GWO (MGWO) because of the results were better than the results found by grey wolf optimizer (GWO)
A low voltage (LV) utility connected microgrid system has been considered in this paper, both dispatchable and non-dispatchable distributed generators supply power to the system
Summary
Maximum output with minimum capital spent has always been a significant objective for all production processes including power generation. Trivedi et al [17] implemented an interior search algorithm (ISA) to perform the penalty-factor based combined economic emission dispatch (CEED) on a 3 unit microgrid system supported by wind turbine and PV. Artificial Fish Swarm Algorithm (AFSA) has been used by Kumar Saravanan [27] to minimize the operation cost of power generation with microgrid for 24 h considering two scenarios to estimate the uncertainty in power availability of renewable sources and load demand. Wen et al [34] established an optimal load dispatch model under three different scheduling scenarios for grid-connected community microgrid considering residential load, PV arrays, electric vehicles (EVs) and ESS.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
