Abstract
Renewable energy shapes have been broadly utilized in the previous decades, featuring a Green move in energy production. A genuine explanation for this swing to Renewable energy generation is internationals directives, which set the worldwide objectives for energy production from inexhaustible sources, greenhouse gas emissions and increase in energy efficiency. The ability expansion-planning problem of the renewable energy industry implies some important decisions concerning the optimal mix of different plant types, locations where each plant should be built, and capacity extension decisions over the planning horizon for each plant.
The aim of this paper is to analyse the relationship between the type of renewable energy by combining the geographical, climatic and ecological criteria, in the Algerian framework, using a multi criteria analysis, precisely Fuzzy Goal Programming model, based on a multi-source, multi-sink network, in order to determine the optimal number of renewable energy plants for electric generation in the Algerian territory.
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References
Ali, E.S., Elazim, S.M.A., Abdelaziz, A.Y.: Ant Lion Optimization Algorithm for optimal location and sizing of renewable distributed generations. Renew. Energy 101, 1311–1324 (2017). https://doi.org/10.1016/j.renene.2016.09.023
Atmania, H.: La Strategie D’implantation Des Energies Renouvelables En Algérie: Cas De La Photovoltaïque. Memory of Magister, University of Oran 2 -Mohamed Ben Ahmed (2015)
Bal, J.-L., Chabot, B.: Comptes Rendus de l’Académie des Sciences, Series IIA - Earth and Planetary Science, pp. 333, 827 (2001)
Chang, C.T.: Multi-choice goal programming model for the optimal location of renewable energy facilities. Renew. Sustain. Energy Rev. 41, 379–389 (2015). https://doi.org/10.1016/j.rser.2014.08.055
Hocine, A., Kouaissah, N., Bettahar, S., Benbouziane, M.: Optimizing renewable energy portfolios under uncertainty: a multi-segment fuzzy goal programming approach. Renew. Energy (2018). https://doi.org/10.1016/j.renene.2018.06.013
Jayaraman, R., Colapinto, C., La Torre, D., Malik, T.: A weighted goal programming model for planning sustainable development applied to gulf cooperation council countries. Appl. Energy 185, 1931–1939 (2017). https://doi.org/10.1016/j.apenergy.2016.04.065
Jayaraman, R., La Torre, D., Malik, T., Pearson, Y.E.: A polynomial goal programming model with application to energy consumption and emissions in United Arab Emirates. In: 2015 International Conference on Industrial Engineering and Operations Management (IEOM) (2015). https://doi.org/10.1109/ieom.2015.7093869
Kim, K.H., Song, K.B., Joo, S.K., Lee, Y.J., Kim, J.O.: Multiobjective distributed generation placement using fuzzy goal programming with genetic algorithm. Eur. Trans. Electr. Power 18(3), 217–230 (2008). https://doi.org/10.1002/etep.226
Mezher, T., Chedid, R., Zahabi, W.: Energy resource allocation using multi-objective goal programming: the case of Lebanon. Appl. Energy 61(4), 175–192 (1998)
San Cristóbal, J.R.: A goal programming model for the optimal mix and location of renewable energy plants in the north of Spain. Renew. Sustain. Energy Rev. 16(7), 4461–4464 (2012). https://doi.org/10.1016/j.rser.2012.04.039
Scala, A., Allmann, S., Mirabella, R., Haring, M.A., Schuurink, R.C.: Green leaf volatiles: a plant’s multifunctional weapon against herbivores and pathogens. Int. J. Mol. Sci. 14, 17781–17811 (2013)
Yaghoobi, M.A., Jones, D.F., Tamiz, M.: Weighted additive models for solving fuzzy goal programming problems. Asia Pac. J. Ope. Res. 25(5), 715–733 (2008). https://doi.org/10.1142/s0217595908001973
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Ghouali, S., Guellil, M.S., Belmokaddem, M. (2020). Looking over the Horizon 2030: Efficiency of Renewable Energy Base Plants in Algeria Using Fuzzy Goal Programming. In: Hatti, M. (eds) Smart Energy Empowerment in Smart and Resilient Cities. ICAIRES 2019. Lecture Notes in Networks and Systems, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-030-37207-1_34
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