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Long-term optimal energy mix planning towards high energy security and low GHG emission

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  • Thangavelu, Sundar Raj
  • Khambadkone, Ashwin M.
  • Karimi, Iftekhar A.

Abstract

Conventional energy planning focused on energy cost, GHG emission and renewable contribution based on future energy demand, fuel price, etc. Uncertainty in the projected variables such as energy demand, volatile fuel price and evolution of renewable technologies will influence the cost of energy when projected over a period of 15–30years. Inaccurate projected variables could affect energy security and lead to the risk of high energy cost, high emission and low energy security. The energy security is an ability of generation capacity to meet the future energy demand. In order to minimize the risks, a generic methodology is presented to determine an optimal energy mix for a period of around 15years. The proposed optimal energy mix is a right combination of energy sources that minimize the risk caused due to future uncertainties related to the energy sources. The proposed methodology uses stochastic optimization to address future uncertainties over a planning horizon and minimize the variations in the desired performance criteria such as energy security and costs. The developed methodology is validated using a case study for a South East Asian region with diverse fuel sources consists of wind, solar, geothermal, coal, biomass and natural gas, etc. The derived optimal energy mix decision outperformed the conventional energy planning by remaining stable and feasible against 79% of future energy demand scenarios at the expense of 0–10% increase in the energy cost. Including the nuclear option in the energy mix resulted 26.7% reduction in the total energy cost, 53.2% reduction in the GHG emission and guarantees feasibility against 79% of future energy demand scenarios over a 15year planning horizon.

Suggested Citation

  • Thangavelu, Sundar Raj & Khambadkone, Ashwin M. & Karimi, Iftekhar A., 2015. "Long-term optimal energy mix planning towards high energy security and low GHG emission," Applied Energy, Elsevier, vol. 154(C), pages 959-969.
  • Handle: RePEc:eee:appene:v:154:y:2015:i:c:p:959-969
    DOI: 10.1016/j.apenergy.2015.05.087
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    References listed on IDEAS

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    1. Chalvatzis, Konstantinos J. & Hooper, Elizabeth, 2009. "Energy security vs. climate change: Theoretical framework development and experience in selected EU electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2703-2709, December.
    2. Iniyan, S & Sumathy, K, 2000. "An optimal renewable energy model for various end-uses," Energy, Elsevier, vol. 25(6), pages 563-575.
    3. Iniyan, S & Suganthi, L & Jagadeesan, T.R & Samuel, Anand A, 2000. "Reliability based socio economic optimal renewable energy model for India," Renewable Energy, Elsevier, vol. 19(1), pages 291-297.
    4. Koroneos, C. & Zairis, N. & Charaklias, P. & Moussiopoulos, N., 2005. "Optimization of energy production system in the Dodecanese Islands," Renewable Energy, Elsevier, vol. 30(2), pages 195-210.
    5. Mujiyanto, Sugeng & Tiess, Günter, 2013. "Secure energy supply in 2025: Indonesia's need for an energy policy strategy," Energy Policy, Elsevier, vol. 61(C), pages 31-41.
    6. Bishop, Justin D.K. & Amaratunga, Gehan A.J. & Rodriguez, Cuauhtemoc, 2008. "Using strong sustainability to optimize electricity generation fuel mixes," Energy Policy, Elsevier, vol. 36(3), pages 971-980, March.
    7. Kjetil Høyland & Stein W. Wallace, 2001. "Generating Scenario Trees for Multistage Decision Problems," Management Science, INFORMS, vol. 47(2), pages 295-307, February.
    8. Koo, Jamin & Han, Kyusang & Yoon, En Sup, 2011. "Integration of CCS, emissions trading and volatilities of fuel prices into sustainable energy planning, and its robust optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 665-672, January.
    9. Stram, Bruce Nels, 2014. "A new strategic plan for a carbon tax," Energy Policy, Elsevier, vol. 73(C), pages 519-523.
    10. Hong, Sanghyun & Bradshaw, Corey J.A. & Brook, Barry W., 2013. "Evaluating options for sustainable energy mixes in South Korea using scenario analysis," Energy, Elsevier, vol. 52(C), pages 237-244.
    11. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    12. Rubin, Edward S. & Chen, Chao & Rao, Anand B., 2007. "Cost and performance of fossil fuel power plants with CO2 capture and storage," Energy Policy, Elsevier, vol. 35(9), pages 4444-4454, September.
    13. Hong, Sanghyun & Bradshaw, Corey J.A. & Brook, Barry W., 2014. "South Korean energy scenarios show how nuclear power can reduce future energy and environmental costs," Energy Policy, Elsevier, vol. 74(C), pages 569-578.
    14. Zerriffi, Hisham & Dowlatabadi, Hadi & Farrell, Alex, 2007. "Incorporating stress in electric power systems reliability models," Energy Policy, Elsevier, vol. 35(1), pages 61-75, January.
    15. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Kopanos, Georgios M. & Pistikopoulos, Efstratios N. & Georgiadis, Michael C., 2014. "A spatial multi-period long-term energy planning model: A case study of the Greek power system," Applied Energy, Elsevier, vol. 115(C), pages 456-482.
    16. Hong, Sanghyun & Bradshaw, Corey J.A. & Brook, Barry W., 2014. "Nuclear power can reduce emissions and maintain a strong economy: Rating Australia’s optimal future electricity-generation mix by technologies and policies," Applied Energy, Elsevier, vol. 136(C), pages 712-725.
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