Abstract
We consider the Photovoltaic Installation Design Problem (PIDP) were photovoltaic modules must be organized in strings and wired to a set of electronic devices. The aim is to minimize installation costs and maximize power production considering “mismatch losses” caused by non-uniform irradiation (shading) and directly related to design decisions. We relate the problem to the known class of location routing problems and thanks to the existing knowledge on the problem, we design a route-first cluster-second heuristic. We propose an efficient machine learning approach to evaluate the installation performances accounting for mismatch losses. We prove that our approach is effective on real-world instances provided by our industrial partner.
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References
Ahn, J., de Weck, O., Geng, Y., Klabjan, D.: Column generation based heuristics for a generalized location routing problem with profits arising in space exploration. Eur. J. Oper. Res. 223(1), 47–59 (2012)
Beasley, J.: Route first cluster second methods for vehicle routing. Omega 11(4), 403–408 (1983)
Di Dio, V., La Cascia, D., Miceli, R., Rando, C.: A mathematical model to determine the electrical energy production in photovoltaic fields under mismatch effect. In: 2009 International Conference on Clean Electrical Power, pp. 46–51. IEEE (2009)
Drexl, M., Schneider, M.: A survey of variants and extensions of the location-routing problem. Eur. J. Oper. Res. 241(2), 283–308 (2015)
Fernández-Delgado, M., Cernadas, E., Barro, S., Amorim, D.: Do we need hundreds of classifiers to solve real world classification problems. J. Mach. Learn. Res. 15(1), 3133–3181 (2014)
Friedman, J., Hastie, T., Tibshirani, R.: The Elements of Statistical Learning, vol. 1. Springer (2001)
Green, M.A.: Commercial progress and challenges for photovoltaics. Nat. Energy 1, 15015 (2016)
Kang, M.H., Rohatgi, A.: Quantitative analysis of the levelized cost of electricity of commercial scale photovoltaics systems in the us. Solar Energy Mater. Solar Cells 154, 71–77 (2016)
Laporte, G., Nobert, Y., Arpin, D.: An exact algorithm for solving a capacitated location-routing problem. Ann. Oper. Res. 6(9), 291–310 (1986)
Nagy, G., Salhi, S.: Location-routing: issues, models and methods. Eur. J. Oper. Res. 177(2), 649–672 (2007)
Peled, A., Appelbaum, J.: Enhancing the power output of pv modules by considering the view factor to sky effect and rearranging the interconnections of solar cells. Prog. Photovolt. Res. Appl. 25(9), 810–818 (2017)
Prins, C., Lacomme, P., Prodhon, C.: Order-first split-second methods for vehicle routing problems: a review. Transp. Res. Part C Emerg. Technol. 40(Supplement C), 179–200 (2014)
Prodhon, C., Prins, C.: A survey of recent research on location-routing problems. Eur. J. Oper. Res. 238(1), 1–17 (2014)
Toro, E.M., Franco, J.F., Echeverri, M.G., Guimares, F.G.: A multi-objective model for the green capacitated location-routing problem considering environmental impact. Comput. Ind. Eng. 110(Supplement C), 114–125 (2017)
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Salani, M., Corbellini, G., Corani, G. (2018). A Hybrid Metaheuristic for the Optimal Design of Photovoltaic Installations. In: Daniele, P., Scrimali, L. (eds) New Trends in Emerging Complex Real Life Problems. AIRO Springer Series, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-00473-6_47
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DOI: https://doi.org/10.1007/978-3-030-00473-6_47
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