IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v337y2023ics0306261923002520.html
   My bibliography  Save this article

Development of an integrated BLSVM-MFA method for analyzing renewable power-generation potential under climate change: A case study of Xiamen

Author

Listed:
  • Wang, Bingqing
  • Li, Yongping
  • Huang, Guohe
  • Gao, Pangpang
  • Liu, Jing
  • Wen, Yizhuo

Abstract

In order to reduce fossil-energy carbon emission and mitigate its climate change impact, developing integrated mathematical methods that are capable of predicting renewable power-generation (e.g., wind and photovoltaic power) potential are desired. This study advances an integrated Bayesian least-squares-support-vector-machine based multilevel-factorial-analysis (BLSVM-MFA) method to find out the main factors affecting wind- and photovoltaic-power generations (WPG and PPG), as well as predict WPG and PPG potentials. The BLSVM-MFA method is then applied to a case study of Xiamen (China), where various factors including climate, economic, technological and capacity are investigated and 216 scenarios are analyzed. Results disclose that the main factors affecting WPG are wind power index (contributing 54.04%) > installed capacity (41.45%) > technology (2.60%), and the main factors affecting PPG are installed capacity (60.36%) > solar radiation (19.27%) > technology (9.24%). Results also reveal that WPG and PPG potentials (in 2020–2035) decrease under most scenarios and WPG and PPG show seasonal complementarity. Ensemble predictions under 216 scenarios indicate that WPG and PPG would be 130.21 WMh and 436.51 MWh by 2035. The promotion of high-conversion and high-profit technologies can improve the competitiveness of WPG and PPG in the regional power system. Results are valuable for revealing the impacts of climate change, economic development, and technological improvement on renewable power potentials and providing support for regional energy-structure transformation and carbon-emission abatement.

Suggested Citation

  • Wang, Bingqing & Li, Yongping & Huang, Guohe & Gao, Pangpang & Liu, Jing & Wen, Yizhuo, 2023. "Development of an integrated BLSVM-MFA method for analyzing renewable power-generation potential under climate change: A case study of Xiamen," Applied Energy, Elsevier, vol. 337(C).
    • Handle: RePEc:eee:appene:v:337:y:2023:i:c:s0306261923002520
    DOI: 10.1016/j.apenergy.2023.120888
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923002520
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.120888?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Weipeng Zhang & Bo Zhao & Liming Zhou & Jizhong Wang & Kang Niu & Fengzhu Wang & Ruixue Wang, 2022. "Research on Comprehensive Operation and Maintenance Based on the Fault Diagnosis System of Combine Harvester," Agriculture, MDPI, vol. 12(6), pages 1-17, June.
    2. Zhu, Bangzhu & Ye, Shunxin & Jiang, Minxing & Wang, Ping & Wu, Zhanchi & Xie, Rui & Chevallier, Julien & Wei, Yi-Ming, 2019. "Achieving the carbon intensity target of China: A least squares support vector machine with mixture kernel function approach," Applied Energy, Elsevier, vol. 233, pages 196-207.
    3. Shi, Jing & Guo, Jinmei & Zheng, Songtao, 2012. "Evaluation of hybrid forecasting approaches for wind speed and power generation time series," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3471-3480.
    4. Nhuchhen, Daya R. & Sit, Song P. & Layzell, David B., 2022. "Towards net-zero emission cement and power production using Molten Carbonate Fuel Cells," Applied Energy, Elsevier, vol. 306(PB).
    5. Mills, Andrew D. & Rodriguez, Pía, 2020. "A simple and fast algorithm for estimating the capacity credit of solar and storage," Energy, Elsevier, vol. 210(C).
    6. Qunli Wu & Huaxing Lin, 2019. "Short-Term Wind Speed Forecasting Based on Hybrid Variational Mode Decomposition and Least Squares Support Vector Machine Optimized by Bat Algorithm Model," Sustainability, MDPI, vol. 11(3), pages 1-18, January.
    7. He, Gang & Kammen, Daniel M., 2016. "Where, when and how much solar is available? A provincial-scale solar resource assessment for China," Renewable Energy, Elsevier, vol. 85(C), pages 74-82.
    8. Liu, Da & Liu, Yumeng & Sun, Kun, 2021. "Policy impact of cancellation of wind and photovoltaic subsidy on power generation companies in China," Renewable Energy, Elsevier, vol. 177(C), pages 134-147.
    9. Yao, Huizong & Zang, Chuanfu, 2021. "The spatiotemporal characteristics of electrical energy supply-demand and the green economy outlook of Guangdong Province, China," Energy, Elsevier, vol. 214(C).
    10. Verdolini, Elena & Galeotti, Marzio, 2011. "At home and abroad: An empirical analysis of innovation and diffusion in energy technologies," Journal of Environmental Economics and Management, Elsevier, vol. 61(2), pages 119-134, March.
    11. Yuan, Xiaohui & Tan, Qingxiong & Lei, Xiaohui & Yuan, Yanbin & Wu, Xiaotao, 2017. "Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine," Energy, Elsevier, vol. 129(C), pages 122-137.
    12. Wang, Heming & Wang, Guoqiang & Qi, Jianchuan & Schandl, Heinz & Li, Yumeng & Feng, Cuiyang & Yang, Xuechun & Wang, Yao & Wang, Xinzhe & Liang, Sai, 2020. "Scarcity-weighted fossil fuel footprint of China at the provincial level," Applied Energy, Elsevier, vol. 258(C).
    13. Gorjian, Shiva & Zadeh, Babak Nemat & Eltrop, Ludger & Shamshiri, Redmond R. & Amanlou, Yasaman, 2019. "Solar photovoltaic power generation in Iran: Development, policies, and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 110-123.
    14. Wen-Chi Liu, 2020. "The Relationship between Primary Energy Consumption and Real Gross Domestic Product: Evidence from Major Asian Countries," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    15. Lin, Zhenjia & Chen, Haoyong & Wu, Qiuwei & Li, Weiwei & Li, Mengshi & Ji, Tianyao, 2020. "Mean-tracking model based stochastic economic dispatch for power systems with high penetration of wind power," Energy, Elsevier, vol. 193(C).
    16. Wang, Juan & Li, Ziming & Wu, Tong & Wu, Siyu & Yin, Tingwei, 2022. "The decoupling analysis of CO2 emissions from power generation in Chinese provincial power sector," Energy, Elsevier, vol. 255(C).
    17. Chandel, Rahul & Chandel, Shyam Singh & Malik, Prashant, 2022. "Perspective of new distributed grid connected roof top solar photovoltaic power generation policy interventions in India," Energy Policy, Elsevier, vol. 168(C).
    18. Li, M.S. & Lin, Z.J. & Ji, T.Y. & Wu, Q.H., 2018. "Risk constrained stochastic economic dispatch considering dependence of multiple wind farms using pair-copula," Applied Energy, Elsevier, vol. 226(C), pages 967-978.
    19. Martins, F.R. & Pereira, E.B. & Silva, S.A.B. & Abreu, S.L. & Colle, Sergio, 2008. "Solar energy scenarios in Brazil, Part one: Resource assessment," Energy Policy, Elsevier, vol. 36(8), pages 2843-2854, August.
    20. Liu, J. & Nie, S. & Shan, B.G. & Li, Y.P. & Huang, G.H. & Liu, Z.P., 2019. "Development of an interval-credibility-chance constrained energy-water nexus system planning model—a case study of Xiamen, China," Energy, Elsevier, vol. 181(C), pages 677-693.
    21. Mutschler, Robin & Rüdisüli, Martin & Heer, Philipp & Eggimann, Sven, 2021. "Benchmarking cooling and heating energy demands considering climate change, population growth and cooling device uptake," Applied Energy, Elsevier, vol. 288(C).
    22. Jia, Zhijie & Lin, Boqiang, 2021. "How to achieve the first step of the carbon-neutrality 2060 target in China: The coal substitution perspective," Energy, Elsevier, vol. 233(C).
    23. Gao, Yang & Ma, Shaoxiu & Wang, Tao, 2019. "The impact of climate change on wind power abundance and variability in China," Energy, Elsevier, vol. 189(C).
    24. Makowski, David & Naud, Cédric & Jeuffroy, Marie-Hélène & Barbottin, Aude & Monod, Hervé, 2006. "Global sensitivity analysis for calculating the contribution of genetic parameters to the variance of crop model prediction," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1142-1147.
    25. Zhao, Xiaohu & Huang, Guohe & Lu, Chen & Zhou, Xiong & Li, Yongping, 2020. "Impacts of climate change on photovoltaic energy potential: A case study of China," Applied Energy, Elsevier, vol. 280(C).
    26. Martins, F.R. & Rüther, R. & Pereira, E.B. & Abreu, S.L., 2008. "Solar energy scenarios in Brazil. Part two: Photovoltaics applications," Energy Policy, Elsevier, vol. 36(8), pages 2855-2867, August.
    27. Franke, Katja & Sensfuß, Frank & Deac, Gerda & Kleinschmitt, Christoph & Ragwitz, Mario, 2021. "Factors affecting the calculation of wind power potentials: A case study of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    28. Popp, David & Hascic, Ivan & Medhi, Neelakshi, 2011. "Technology and the diffusion of renewable energy," Energy Economics, Elsevier, vol. 33(4), pages 648-662, July.
    29. Narayan, Paresh Kumar & Narayan, Seema & Prasad, Arti, 2008. "A structural VAR analysis of electricity consumption and real GDP: Evidence from the G7 countries," Energy Policy, Elsevier, vol. 36(7), pages 2765-2769, July.
    30. Jin, L. & Huang, G.H. & Fan, Y.R. & Wang, L. & Wu, T., 2015. "A pseudo-optimal inexact stochastic interval T2 fuzzy sets approach for energy and environmental systems planning under uncertainty: A case study for Xiamen City of China," Applied Energy, Elsevier, vol. 138(C), pages 71-90.
    31. Yan, Zheming & Du, Keru & Yang, Zhiming & Deng, Min, 2017. "Convergence or divergence? Understanding the global development trend of low-carbon technologies," Energy Policy, Elsevier, vol. 109(C), pages 499-509.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Weijie Zhou & Huimin Jiang & Jiaxin Chang, 2023. "Forecasting Renewable Energy Generation Based on a Novel Dynamic Accumulation Grey Seasonal Model," Sustainability, MDPI, vol. 15(16), pages 1-26, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hille, Erik & Althammer, Wilhelm & Diederich, Henning, 2020. "Environmental regulation and innovation in renewable energy technologies: Does the policy instrument matter?," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    2. Francesco Nicolli & Francesco Vona & Lionel Nesta, 2012. "Determinants of Renewable Energy Innovation: Environmental Policies vs. Market Regulation," Working Papers 201204, University of Ferrara, Department of Economics.
    3. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2023. "Sustainable development pathways of China's wind power industry under uncertainties: Perspective from economic benefits and technical potential," Energy Policy, Elsevier, vol. 182(C).
    4. repec:hal:spmain:info:hdl:2441/eu4vqp9ompqllr09j0h0ji242 is not listed on IDEAS
    5. Verdolini, Elena & Vona, Francesco & Popp, David, 2018. "Bridging the gap: Do fast-reacting fossil technologies facilitate renewable energy diffusion?," Energy Policy, Elsevier, vol. 116(C), pages 242-256.
    6. Shahrouz Abolhosseini & Almas Heshmati & Jorn Altmann, 2014. "The Effect of Renewable Energy Development on Carbon Emission Reduction: An Empirical Analysis for the EU-15 Countries," TEMEP Discussion Papers 2014109, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Mar 2014.
    7. repec:hal:wpspec:info:hdl:2441/eu4vqp9ompqllr09j0h0ji242 is not listed on IDEAS
    8. Patricia Laurens & Christian Le Bas & Stéphane Lhuillery & Antoine Schoen, 2017. "The determinants of cleaner energy innovations of the world’s largest firms: the impact of firm learning and knowledge capital," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(4), pages 311-333, May.
    9. repec:hal:spmain:info:hdl:2441/f6h8764enu2lskk9p4oq2cqb0 is not listed on IDEAS
    10. Wang, Jujie & Li, Yaning, 2018. "Multi-step ahead wind speed prediction based on optimal feature extraction, long short term memory neural network and error correction strategy," Applied Energy, Elsevier, vol. 230(C), pages 429-443.
    11. Jin, Wei & Zhang, ZhongXiang, 2016. "On the mechanism of international technology diffusion for energy technological progress," Resource and Energy Economics, Elsevier, vol. 46(C), pages 39-61.
    12. Portolan dos Santos, Ísis & Rüther, Ricardo, 2014. "Limitations in solar module azimuth and tilt angles in building integrated photovoltaics at low latitude tropical sites in Brazil," Renewable Energy, Elsevier, vol. 63(C), pages 116-124.
    13. Martins, F.R. & Abreu, S.L. & Pereira, E.B., 2012. "Scenarios for solar thermal energy applications in Brazil," Energy Policy, Elsevier, vol. 48(C), pages 640-649.
    14. Bai, Yulong & Liu, Ming-De & Ding, Lin & Ma, Yong-Jie, 2021. "Double-layer staged training echo-state networks for wind speed prediction using variational mode decomposition," Applied Energy, Elsevier, vol. 301(C).
    15. Nesta, Lionel & Vona, Francesco & Nicolli, Francesco, 2014. "Environmental policies, competition and innovation in renewable energy," Journal of Environmental Economics and Management, Elsevier, vol. 67(3), pages 396-411.
    16. Chen, Jiandong & Xu, Chong & Wang, Yuzhi & Li, Ding & Song, Malin, 2021. "Carbon neutrality based on vegetation carbon sequestration for China's cities and counties: Trend, inequality and driver," Resources Policy, Elsevier, vol. 74(C).
    17. Zheming Yan & Rui Shi & Zhiming Yang, 2018. "ICT Development and Sustainable Energy Consumption: A Perspective of Energy Productivity," Sustainability, MDPI, vol. 10(7), pages 1-15, July.
    18. Silva, Tatiane C. & Pinto, Gabriel M. & de Souza, Túlio A.Z. & Valerio, Victor & Silvério, Naidion M. & Coronado, Christian J.R. & Guardia, Eduardo Crestana, 2020. "Technical and economical evaluation of the photovoltaic system in Brazilian public buildings: A case study for peak and off-peak hours," Energy, Elsevier, vol. 190(C).
    19. Gosens, Jorrit, 2017. "Natural resource endowment is not a strong driver of wind or PV development," Renewable Energy, Elsevier, vol. 113(C), pages 1007-1018.
    20. Lee, Chien-Chiang & He, Zhi-Wen & Xiao, Fu, 2022. "How does information and communication technology affect renewable energy technology innovation? International evidence," Renewable Energy, Elsevier, vol. 200(C), pages 546-557.
    21. Malagueta, Diego & Szklo, Alexandre & Borba, Bruno Soares Moreira Cesar & Soria, Rafael & Aragão, Raymundo & Schaeffer, Roberto & Dutra, Ricardo, 2013. "Assessing incentive policies for integrating centralized solar power generation in the Brazilian electric power system," Energy Policy, Elsevier, vol. 59(C), pages 198-212.
    22. Liang, M.S. & Huang, G.H. & Chen, J.P. & Li, Y.P., 2022. "Development of non-deterministic energy-water-carbon nexus planning model: A case study of Shanghai, China," Energy, Elsevier, vol. 246(C).
    23. Popp, David, 2012. "The role of technological change in green growth," Policy Research Working Paper Series 6239, The World Bank.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:337:y:2023:i:c:s0306261923002520. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.