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Analysis and Optimization of Power Supply Structure Based on Markov Chain and Error Optimization for Renewable Energy from the Perspective of Sustainability

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  • Xiaomin Xu

    (Research Institute of Technology Economics Forecasting and Assessment, School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Dongxiao Niu

    (Research Institute of Technology Economics Forecasting and Assessment, School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Jinpeng Qiu

    (Research Institute of Technology Economics Forecasting and Assessment, School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Peng Wang

    (Economic Research Office, Shaanxi Electric Power Design Institute Co., Ltd., China Energy Construction Group, Xi’an 710054, China)

  • Yanchao Chen

    (Nanning Power Supply Company, Guangxi Power Grid, Nanning 530000, China)

Abstract

With the rapid development of renewable energy, power supply structure is changing. However, thermal power is still dominant. With the background in low carbon economy, reasonable adjustment and optimization of the power supply structure is the trend of future development in the power industry. It is also a reliable guarantee of a fast, healthy and stable development of national economy. In this paper, the sustainable development of renewable energy sources is analyzed from the perspective of power supply. Through the research on the development of power supply structure, we find that regional power supply structure development mode conforms to dynamic characteristics and there must exist a Markov chain in the final equilibrium state. Combined with the characteristics of no aftereffect and small samples, this paper applies a Markov model to the power supply structure prediction. The optimization model is established to ensure that the model can fit the historical data as much as possible. Taking actual data of a certain area of Ningxia Province as an example, the models proposed in this paper are applied to the practice and results verify the validity and robustness of the model, which can provide decision basis for enterprise managers.

Suggested Citation

  • Xiaomin Xu & Dongxiao Niu & Jinpeng Qiu & Peng Wang & Yanchao Chen, 2016. "Analysis and Optimization of Power Supply Structure Based on Markov Chain and Error Optimization for Renewable Energy from the Perspective of Sustainability," Sustainability, MDPI, vol. 8(7), pages 1-14, July.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:7:p:634-:d:73463
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    References listed on IDEAS

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    1. 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.
    2. Munoz, F.D. & Hobbs, B.F. & Watson, J.-P., 2016. "New bounding and decomposition approaches for MILP investment problems: Multi-area transmission and generation planning under policy constraints," European Journal of Operational Research, Elsevier, vol. 248(3), pages 888-898.
    3. Parpas, Panos & Webster, Mort, 2014. "A stochastic multiscale model for electricity generation capacity expansion," European Journal of Operational Research, Elsevier, vol. 232(2), pages 359-374.
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    2. Haijun Zhao & Weichun Ma & Hongjia Dong & Ping Jiang, 2017. "Analysis of Co-Effects on Air Pollutants and CO 2 Emissions Generated by End-of-Pipe Measures of Pollution Control in China’s Coal-Fired Power Plants," Sustainability, MDPI, vol. 9(4), pages 1-19, March.

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