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The new investing effectiveness evaluation multi-criteria method in modern energy supply systems

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PL
Nowa wielokryterialna metoda oceny efektywności inwestowania w nowoczesnych systemach energetycznych
Języki publikacji
EN
Abstrakty
EN
The important problem in the processes of modelling and programming the development of sustainable energy sector is the multi-criteria manner of assessing the effectiveness of investments. The goal of this paper is to show how to take into account the impact of investments in multidimensional modeling decision-making processes. This goal can be achieved through the development, presentation, and use of a new multi-criteria method of evaluating the effectiveness of investing towards to modern renewable energy sector. This innovative method was developed and tested in research for the energy sector carried out by the author. Method consist of a relatively simple way of taking into account the qualitative features of the criteria in the process of evaluating investments in the energy sector. Using the real data of the energy invested in the city of X in Poland, the effectiveness of the project was examined applying the multi-criteria method proposed by the author, and for the same purpose, the well-known ELECTRE method was used. The comparison of the results of the investment effectiveness studies by both methods confirmed the high convergence of the effects obtained in both methods. The achieved results of research very high effectiveness of the analyzed renewable energy technologies.
PL
Istotnym problemem w procesach modelowania i programowania rozwoju sektora energii zrównoważonej jest wielokryterialny sposób oceny efektywności inwestycji. Celem artykułu jest pokazanie, jak uwzględnić wpływ inwestycji w wielowymiarowym modelowaniu procesów decyzyjnych. Cel ten można osiągnąć poprzez opracowanie, prezentacje i zastosowanie nowej, wielokryterialnej metody oceny efektywności inwestycji w nowoczesnym sektorze energetyki odnawialnej. Ta innowacyjna metoda została opracowana i sprawdzona w badaniach dla sektora energetycznego prowadzonych przez autora. Metoda polega na stosunkowo prostym sposobie uwzględnienia cech jakościowych kryteriów w procesie oceny inwestycji w energetyce. Wykorzystując rzeczywiste dane dotyczące energii zainwestowanej w mieście X w Polsce, zbadano efektywność projektu, stosując zaproponowana przez autora metoda wielokryterialna i w tym samym celu wykorzystano znana metoda ELECTRE. Porównanie wyników badań efektywności inwestycji obiema metodami potwierdziło wysoką zbieżność efektów uzyskanych obiema metodami. Uzyskane wyniki badan bardzo wysokiej efektywności analizowanych technologii energetyki odnawialnej.
Rocznik
Tom
Strony
10--17
Opis fizyczny
Bibliogr. 32 poz., rys., tab.
Twórcy
  • Gdansk University of Technology
Bibliografia
  • [1] Baas M. S., H. Kwakemaak,1997. "Rating and Ranking of Multiple-aspect Alternatives Using Fuzzy Sets", Automatica 13.
  • [2] Beccali M., et al 1997. "Decision Making in Energy Planning: the Electre Multicriteria Analysis Approach Compared to a Fuzzy-Sets Methodology", Proc. FLORA '97, Florence.
  • [3] Boie I., et al. 2016. "Opportunities and challenges of high renewable energy development and electricity exchange for North Africa and Europe-scenarios for power sector and transmission infrastructure in 2030 and 2050," Renewable Energy Vol. 87, pp. 130-144, 2016. https://doi.org/10.1016/j.renene.2015.10.008.
  • [4] Cannemi M., et al. 2014, "Modelling decision making as a support tool tier policy making on renewable energy development", Energy Policy (67): 127-137. https://doi.org/10.1016/j.enpol.2013.12.011.
  • [5] Central Statistical Office Poland, Statistical Year Book 2022.
  • [6] Charnes A., et al. 1995, "Data Envelopment Analysis - Theory, Methodology and Applications". Kluwer Academic Publishers, Dordrecht.
  • [7] Demirtas O., 2013. "Evaluating the best renewable energy technology for sustainable energy planning". International Journal of Energy Economics and Policy (3): 23-33.
  • [8] Grabisch M., et al. 1995. "Fundamentals of Uncertainty Calculi with Application to Fuzzy Inference." Kluwer Academic Publishers, Dordrecht.
  • [9] Greco S., et al. 2005, "Multiple criteria decision analysis. ", Springer's International Series.
  • [10] Haddad B., et al. 2017. "A multi-criteria approach to rank renewable for Algerian electricity system", Renewable Energy (107): 462-472. https://doi.org/10.1016/j.renene.2017.01.035.
  • [11] Kamrat W. 1999. "Methodology of investment evaluation in the local energy market". Energy Department Report, EN-D-65, Lappeenranta University of Technology, Finland.
  • [12] Kamrat W., 2004. "Investing effectiveness evaluation methods in electric power engineering". Gdansk University of Technology Publishing, Gdansk, Poland (in Polish).
  • [13] Kamrat W. 2021. "Selected problems of decision making modelling in power engineering". SETA_101054.
  • [14] Karst W. 2018. "Power Engineering Department Report" Gdansk, University of Technology, Gdansk, Poland (in Polish).
  • [15] Kolenda M. 2006. "Numerical taxonomy", Wroclaw University of Economics Publishing, Wroclaw, Poland, (in Polish).
  • [16] Kumar A., et al. 2017. "A review of multi criteria decision making (MCDM) towards sustainable renewable energy development", Renewable and Sustainable Energy Reviews (69): 596-609, 2017. https://doi.org/10.1016/jrser.2016.11.191.
  • [17] Lopez J. C. E. Fernandez-Gonzales 2003, "A new methods for group decision support based on ELECTRE 10 Methodology", European Journal of Operational Research (148). https://doi.org/10.1016/S0377-2217(02)00273-4.
  • [18] Löthgren M., W. Tambour. 1996. "Alternative Approaches to Estimate Returns to Scale in DEA - Models", Stockholm School of Economics, Working Paper Series in Economics and Finance, Vol. 90.
  • [19] Mirofushi T., M. Sugeno. 1991, "A theory of fuzzy measures. Representation, the Choquet integral and null sets", Journal Math. Anal. Appl., 159.
  • [20] Ribeiro F., et al. 2003. "Evaluating future scenarios for power generation sector using a Multi-Criteria Decision Analysis tools the Portuguese case", Energy (52): 126-136.
  • [21] Ribeiro F., et al. 2013. "Evaluating future scenarios for power generation sector using a Multi-Criteria Decision Analysis tools the Portuguese case", Energy (52): 126-136. https://doi.org/10.1016/j.energy.2012.12.036.
  • [22] Ringkjøb H. K., et.al. 2018. "A review of modeling tools for energy and electricity systems with large shares of variable renewable" Renewable and Sustainable Energy Reviews (96): 440-459, 2018. https://doi.org/10.1016/j.rser.2018.08.002.
  • [23] Saaty T. 1994. "Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process", Pittsburg, PA, RWS Publications.
  • [24] Sánchez-Lozano J. M., et al. 2013. "Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain", Renew. Sustain. Energy Rev(24): 544-556. https://doi.org/10.1016/j.rser.2013.03.019.
  • [25] Seiford L. M. 1992. "A Bibliography of Data Envelopment Analysis", Technical Report, The University of Massachussets.
  • [26] Stoltmann A. 2020. "Hybrid Multi-Criteria Method of Analyzing the Location of Distributed Renewable Energy Sources", Energies, 13(16): 1-22.
  • [27] Strantzali E., K. Aravossis, 2016. "Decision making in renewable energy investments: a review" Renewable and Sustainable Energy Reviews (55): 885-898. haps://doi.org/10.1016/j.rser.2015.11.021.
  • [28] Tegou L., et al. 2010. "Environmental management framework for wind farm sitting: Methodology and case study" J. Environ. Manag (91): 2134-2147. https://doi.org/I0.1016/j.jenvman.2010.05.010.
  • [29] Tietze I., et al., LAEND:2020. "A Model for Multi-Objective Investment Optimisation of Residential Quarters Considering Costs and Environmental Impacts", Energies (13): 6-14. https://doi.org/10.3390/en13030614.
  • [30] Wyrwa, et al. A. 2014. "Modelling the long-term development of energy systems with the use of a technology explicit partial equilibrium model", Lecture Notes in Computer Science. Springer International Publishing.
  • [31] Voropai N. I. I., E. Y. Ivanova. 2002. "Multi-criteria decision analysis techniques in electric power system expansion Planning", Int. J. Electr. Power Energy Syst, (24): 71-78, https://doi.org/10.1016/S0142-0615(01)00005-9.
  • [32] Zurada J., et al. 2011. "A Compare of Regression and Artificial Intelligence Methods in a Mass Appraisal Context" Journal of Real Estate Research (33:3): 349-388.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-702273bf-b6e0-430c-8457-a415c2b95914
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