Two-stage intelligent planning with improved artificial bee colony algorithm for a microgrid by considering the uncertainty of renewable sources

A two-stage planning form of multi-energy supply optimization such as power, cooling, and heating is presented in this paper a micro energy grid (MEG) To cover the effect uncertainty renewable sources (RES), scheduling cycle considered paper. Next, results day-ahead prediction are random variables for upper-layer model. realize at lower layer, revised model storage demand response (DR) considered. Finally, modified version artificial bee colony (ABC) algorithm utilized to find optimal solution. The improved ABC shape-memory method based on collective intelligence behavior bees finding best nutrition source. In algorithm, with information exchange between bees, Newton’s law universal gravitation, full potential used solution given constraints applied system. proposed real system show that intelligent obtained simultaneous different forms. numerical analysis test cases prove following points: (1) synergistic multiple forms has been provided approach. (2) surplus can be converted natural gas by power-to-gas converter (P2G) power cascade conversion multi-directional mode. (3) get some revenue, MEG flexible enough cooperate upper-grade network. (4) DR-based price smooth load shape increase operation revenue using supplementary features. Also, P2G sequentially develop multidirectional - cooling cascade. When evaluated rises 450 kW, total GST output raises 1244 kWh. For more economic benefits, connected upstream grid. Load management also increases net