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An innovative multi-objective optimization approach for long-term energy planning

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  • Mahbub, Md Shahriar
  • Viesi, Diego
  • Cattani, Sara
  • Crema, Luigi

Abstract

Designing future energy scenarios is an important topic to energy planners. As designing future optimized scenarios is a multi-objective optimization problem; therefore, it is required to identify trade-off scenarios (Pareto-front) in order to optimize conflicting objectives. In this study, three Pareto-fronts are identified for designing future scenarios for Val di Non (VdN) for three different time horizons. As the community has to reach different emission targets in different time horizons, it is require to select the optimized scenarios that fulfill the targets. In this regards, we propose a new approach for selecting scenarios based on maximizing decision space diversity in order to provide a diverse set of scenarios to the decision makers. The technique is tested on optimized scenarios of VdN and three sets containing 10 diverse scenarios for different time horizons are selected. Moreover, a smooth transition (in terms of decision variables) is desirable when having a transition from a scenario from one time horizon to a consecutive time horizon. A novel method is proposed to choose scenarios from the sets for a smooth transition based on minimizing distances among the scenarios. The approach is applied on VdN where transient scenarios are identified among different possible optimized scenarios.

Suggested Citation

  • Mahbub, Md Shahriar & Viesi, Diego & Cattani, Sara & Crema, Luigi, 2017. "An innovative multi-objective optimization approach for long-term energy planning," Applied Energy, Elsevier, vol. 208(C), pages 1487-1504.
  • Handle: RePEc:eee:appene:v:208:y:2017:i:c:p:1487-1504
    DOI: 10.1016/j.apenergy.2017.08.245
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    References listed on IDEAS

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    1. Hao, Han & Liu, Zongwei & Zhao, Fuquan & Li, Weiqi & Hang, Wen, 2015. "Scenario analysis of energy consumption and greenhouse gas emissions from China's passenger vehicles," Energy, Elsevier, vol. 91(C), pages 151-159.
    2. Mahbub, Md Shahriar & Viesi, Diego & Crema, Luigi, 2016. "Designing optimized energy scenarios for an Italian Alpine valley: the case of Giudicarie Esteriori," Energy, Elsevier, vol. 116(P1), pages 236-249.
    3. Sharafi, Masoud & ELMekkawy, Tarek Y., 2014. "Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach," Renewable Energy, Elsevier, vol. 68(C), pages 67-79.
    4. Zhang, Qi & Mclellan, Benjamin C. & Tezuka, Tetsuo & Ishihara, Keiichi N., 2013. "An integrated model for long-term power generation planning toward future smart electricity systems," Applied Energy, Elsevier, vol. 112(C), pages 1424-1437.
    5. Prebeg, Pero & Gasparovic, Goran & Krajacic, Goran & Duic, Neven, 2016. "Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles," Applied Energy, Elsevier, vol. 184(C), pages 1493-1507.
    6. Kim, Kyoung-Kuk & Lee, Chi-Guhn, 2012. "Evaluation and optimization of feed-in tariffs," Energy Policy, Elsevier, vol. 49(C), pages 192-203.
    7. Oree, Vishwamitra & Sayed Hassen, Sayed Z. & Fleming, Peter J., 2017. "Generation expansion planning optimisation with renewable energy integration: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 790-803.
    8. Mahbub, Md Shahriar & Cozzini, Marco & Østergaard, Poul Alberg & Alberti, Fabrizio, 2016. "Combining multi-objective evolutionary algorithms and descriptive analytical modelling in energy scenario design," Applied Energy, Elsevier, vol. 164(C), pages 140-151.
    9. Koroneos, C. & Michailidis, M. & Moussiopoulos, N., 2004. "Multi-objective optimization in energy systems: the case study of Lesvos Island, Greece," Renewable and Sustainable Energy Reviews, Elsevier, vol. 8(1), pages 91-100, February.
    10. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    11. Mourmouris, J.C. & Potolias, C., 2013. "A multi-criteria methodology for energy planning and developing renewable energy sources at a regional level: A case study Thassos, Greece," Energy Policy, Elsevier, vol. 52(C), pages 522-530.
    12. Wierzbowski, Michal & Lyzwa, Wojciech & Musial, Izabela, 2016. "MILP model for long-term energy mix planning with consideration of power system reserves," Applied Energy, Elsevier, vol. 169(C), pages 93-111.
    13. Sithole, H. & Cockerill, T.T. & Hughes, K.J. & Ingham, D.B. & Ma, L. & Porter, R.T.J. & Pourkashanian, M., 2016. "Developing an optimal electricity generation mix for the UK 2050 future," Energy, Elsevier, vol. 100(C), pages 363-373.
    14. Brand, Bernhard & Missaoui, Rafik, 2014. "Multi-criteria analysis of electricity generation mix scenarios in Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 251-261.
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