ANALIZA OPTIMALNE STRUKTURE I PROSTORNE DISPERZIVNOSTI OBNOVLJIVIH IZVORA ENERGIJE U PROCESU DEKARBONIZACIJE ELEKTROENERGETSKOG SISTEMA SRBIJE

Флексибилност електроенергетског система / Зборник CIGRE (2023).  (стр 1074-1089)

АУТОР(И) / AUTHOR(S): Bojana Škrbić, Željko Đurišić

Е-АДРЕСА / E-MAIL: bskrbic@etf.bg.ac.rs

Download Full Pdf   

DOI:  10.46793/CIGRE36.1074S

САЖЕТАК / ABSTRACT:

Proces dekarbonizacije proizvodnje električne energije u Srbiji je uslovljen pre svega iscrpljenošću resursa uglja i ekološkim problemima njihovog sagorevanja u termoelektranama, što zahteva planiranje zamenskih kapaciteta koji bi mogli u budućnosti nadomestiti postojeću proizvodnju iz termoelektrana na ugalj. Osnovna strateška pretpostavka koja je usvojena u ovom radu je maksimizacija stepena energetske nezavisnosti, a to znači da elektroenergetski proizvodni sistem Srbije treba planirati iz nacionalnih primarnih resursa na način da razmena energije sa okolnim sistemima bude minimizovana. Pod tom pretpostavkom razvijen je matematički model i sprovedena analiza optimalne instalisane snage fotonaponskih (PV) elektrana i vetroelektrana i njihove prostorne disperzivnosti pri kojoj bi se postigao najveći stepen pokrivenosti potrošnje u elektroenergetskom sistemu Srbije za zadati stepen smanjenja proizvodnje iz termoelektrana. Na osnovu definisanog profila proizvodnje agregiranih proizvodnih jedinica i profila potrošnje u elektroenergetskom sistemu Srbije definisani su potrebni balansni kapaciteti u elektroenergetskom sistemu Srbije za zadate stepene dekarbonizacije proizvodnje električne energije.

КЉУЧНЕ РЕЧИ / KEYWORDS:

dekarbonizacija, obnovljivi izvori energije, termoelektrana, fleksibilnost, planiranje, optimizacija

ЛИТЕРАТУРА / REFERENCES:

  • International Energy Agency, Net Zero by 2050 – A roadmap for the Global Energy Sector, 2021.

  • D. Tong et al. Committed emissions from existing energy infrastructure jeopardize 1.5 °C climate target. Nature, 572, p. 373–377, 2019.

  • G. Luderer et al. The role of renewable energy in climate stabilization: results from the EMF27 scenarios. Clim. Change, 123, p. 427–441, 2014.

  • M. Delgado-Téllez, M. Ferdinandusse, C. Nerlich, Fiscal policies to mitigate climate change in the euro area ECB Economic Bulletin, Issue 6 / 2022.

  • https://climate.ec.europa.eu/eu-action/eu-emissions-trading-system-eu-ets_en

  • Ministartstvo zaštite životne sredine, Agencija za zaštitu životne sredine, Godišnji izveštaj o stanju kvaliteta vazduha u Srbiji za 2021. godinu, Beogad, 2022. 

  • htps://taxation-customs.ec.europa.eu/green-taxation-0/carbon-border-adjustment-mechanism_en 

  • F. Verástegui, Á. Lorca, D. Olivares, Negrete-Pincetic, M. Optimization-based analysis of decarbonization pathways and flexibility requirements in highly renewable power systems. Energy, 234, p. 121242. 2021. https://doi.org/10.1016/j.energy.2021.121242

  • N.A. Sepulveda, J.D. Jenkins, F.J. de Sisternes, R.K. Lester, The role of firm low-carbon electricity resources in deep de-carbonization of power generation. Joule, 2(11), p. 2403-2420, 2018. https://doi.org/10.1016/j.joule.2018.08.006
  • I.J. Scott, P.M. Carvalho, A. Botterud, C.A. Silva, Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage. Applied Energy, 253, p. 113603, 2019. https://doi.org/10.1016/j.apenergy.2019.113603
  • F. Feijoo et al. A long-term capacity investment and operational energy planning model with power-to-X and flexibility technologies. Renewable and Sustainable Energy Reviews, 167, p. 112781, 2022. https://doi.org/10.1016/j.rser.2022.112781
  • E. Zozmann et al. 100% Renewable Energy Scenarios for North America—Spatial Distribution and Network Constraints. Energies, 14, p. 658, 2021.
    https://doi.org/10.3390/en14030658
  • S. Simon, T. Naegler, H.C. Gils, Transformation towards a Renewable Energy System in Brazil and Mexico—Technological and Structural Options for Latin America. Energies, 11, p. 907, 2018. https://doi.org/10.3390/en11040907
  • P. Das et al. Intra-regional renewable energy resource variability in long-term energy system planning. Energy, 245, p. 123302, 2022. https://doi.org/10.1016/j.energy.2022.123302
  • C. Cheng et al. 100% renewable energy in Japan. Energy Conversion and Management, 255, p.115299, 2022. https://doi.org/10.1016/j.enconman.2022.115299
  • B. Lu. et al. A zero-carbon, reliable and affordable energy future in Australia. Energy, 220, p.119678, 2021. https://doi.org/10.1016/j.energy.2020.119678
  • T. Luz, P. Moura, 100% Renewable energy planning with complementarity and flexibility based on a multi-objective assessment. Applied Energy, 255, p. 113819, 2019. https://doi.org/10.1016/j.apenergy.2019.113819
  • H.C. Gils, S. Simon, R. Soria, 100% Renewable Energy Supply for Brazil—The Role of Sector Coupling and Regional Development. Energies, 10, p. 1859, 2017. https://doi.org/10.3390/en10111859
  • O. Lugovoy et al. Towards a Zero-Carbon Electricity System for India in 2050: IDEEA Model-Based Scenarios Integrating Wind and Solar Complementarity and Geospatial Endowments. Energies, 14, p. 7063, 2021. https://doi.org/10.3390/en14217063
  • A. Aghahosseini, D. Bogdanov, C.A. Breyer, Techno-Economic Study of an Entirely Renewable Energy-Based Power Supply for North America for 2030 Conditions. Energies, 10, p. 1171, 2017. https://doi.org/10.3390/en10081171
  • M. Drechsler, J. Egerer, M. Lange et al. Efficient and equitable spatial allocation of renewable power plants at the country scale. Nature Energy, 2 , p.17124, 2017. https://doi.org/10.1038/nenergy.2017.124
  • B. Škrbić, Ž. Đurišić, Novel Planning Methodology for Spatially Optimized RES Development Which Minimizes Flexibility Requirements for Their Integration into the Power System. Energies, 16, p. 3251, 2023. https://doi.org/10.3390/en16073251
  • Ž. Đurišić, B. Škrbić, Potencijal energije sunca i vetra za strateško planiranјe dekarbonizacije proizvodnјe električne energije u Srbiji, ENERGIJA, EKONOMIJA, EKOLOGIJA, No. 4, pp. 1 – 11, 2022. doi: 10.46793/EEE22-4.01D 
  • Å. Björck, Numerical Methods for Least Squares Problems, SIAM: Philadelphia, USA, 1995.