The optimal design of grid-connected Hybrid Renewable Energy Systems (HRESs) is studied by using multi-objective evolutionary algorithm in this paper. With the total system cost and fuel emissions to be minimized, a two-objective optimization model of the hybrid system is established. Then, a modifi ed preference-inspired co-evolutionary algorithm is, for the first time, applied to fi nd the optimal con guration of a grid-connected hybrid system. As an example, a grid-connected hybrid system, including PV panels, wind turbines, and diesel generators, has been designed and good results are obtained which show that the proposed method is effective.
Shi, Z., Wang, R., Zhang, X., Zhang, Y., & Zhang, T. (2017). Optimal design of grid-connected hybrid renewable energy systems using multi-objective evolutionary algorithm. Scientia Iranica, 24(6), 3148-3156. https://doi.org/10.24200/sci.2017.4405
MLA
Shi, Z., Wang, R., Zhang, X., Zhang, Y., & Zhang, T. "Optimal design of grid-connected hybrid renewable energy systems using multi-objective evolutionary algorithm", Scientia Iranica, 24, 6, 2017, 3148-3156. doi: 10.24200/sci.2017.4405
HARVARD
Shi Z., Wang R., Zhang X., Zhang Y., Zhang T. (2017). 'Optimal design of grid-connected hybrid renewable energy systems using multi-objective evolutionary algorithm', Scientia Iranica, 24(6), pp. 3148-3156. doi: 10.24200/sci.2017.4405
CHICAGO
Z. Shi, R. Wang, X. Zhang, Y. Zhang & T. Zhang, "Optimal design of grid-connected hybrid renewable energy systems using multi-objective evolutionary algorithm," Scientia Iranica, 24 6 (2017): 3148-3156, doi: 10.24200/sci.2017.4405
VANCOUVER
Shi Z., Wang R., Zhang X., Zhang Y., Zhang T. Optimal design of grid-connected hybrid renewable energy systems using multi-objective evolutionary algorithm. Scientia Iranica. 2017;24(6):3148-3156. doi: 10.24200/sci.2017.4405
