Application of multi-objective grey wolf algorithm on energy management of microgrids with techno-economic and environmental considerations

A review of constraints and adjustable parameters in microgrids for cost and carbon dioxide emission reduction

“… [ [ 2 , 5 , 6 , [48] , [49] , [50] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] ], [ [28] , [29] , [30] , [31] , 33 , 35 ]] Dynamic power rate dynamic charging/discharging ratio, measured by the energy stored in the final stage or state of charge (SOC) [ 51 , 20 , 30 , 31 ] Apparent power limitations on the apparent power of power flow, MG lines, or generators. [ 19 , [35] , [36] , [37] ] Unbalance Maximum neutral current for converters connecting MG and CDERs [ 2 ] Voltage level limitations on the power buses and/or terminal voltage of DERs [ 2 , 6 , 19 , 36 , [38] , [39] , [52] ] Power ramping Maximum power ramping up/down suggestions from the manufacturer [ [ 2 , 50 , 19 ...…”

Black Widow Optimization for Power System Load Frequency Control: A Comparative Study

“…Figure 1 displays the notional specifications and configurations of conventional and renewable power generation systems, which are drawn from existing research [18,19] papers and are provided in the Appendix.…”

Energy management system optimization in islanded microgrids: An overview and future trends

“…The results show the superiority of GWO with a very narrow standard deviation. Besides, the multi-objective grey wolf optimization (MOGWO), which is carried out in a similar way to the MOPSO with an external archive to save dominant solutions, is applied in [83] for the optimization of a 70-bus grid-connected MG. Furthermore, the GWO algorithm is tested in a generic IEEE 33-bus system while considering uncertainty [156].…”