Skip to main content

The Optimum Research and Case Study of Wind Power Heating Based on Supply and Demand Load Forecasting

  • Conference paper
  • First Online:
  • 1826 Accesses

Part of the book series: Environmental Science and Engineering ((ENVENG))

Abstract

Wind power heating is one of the most important methods for reducing the discard wind power. However, one of the key problems is reasonably matching electric power between the output power in a wind farm and building demand heat load, which can improve the economic benefits of the overall project. In this paper, an optimization model includes the wind power prediction model, and demand load model was established, and by which the ratio of discarded wind power was calculated. And under different boundary conditions and optimization objective, the optimal heating area and heat storage tank capacity were obtained. Using this method, a practical project of wind power heating was analyzed in Inner Mongolia Autonomous Region. The analysis result is the ratio of discarded wind reduced to 4.96 % when heating supply using wind power from 14.96% under not heating supply. The annual average of wind farm is raised to 18.47% from 12.51%. This model can improve the efficiency of renewable energy and bring down the ratio of discarded wind, and it can obtain a considerable economic and society benefit.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Li, G., Shi, J., Zhou, J.: Bayesian adaptive combination of short-term wind speed forecasts from neural network models. Renew. Energy 36(1), 352–359 (2011)

    Article  Google Scholar 

  2. Cadenas, E., Rivera, W., Campos-Amezcua, R., et al.: Wind speed prediction using a univariate ARIMA model and a multivariate NARX model. Energies 9(2), 109–113 (2016)

    Article  Google Scholar 

  3. Lei, X.: Investigations on short-term reliability prediction models of wind turbines and active power control strategies of wind farms. Dissertation for the doctoral degree in engineering in Chongqing University, Chongqing (2014) (in Chinese)

    Google Scholar 

  4. Chitsaz, H., Amjady, N., Zareipour, H.: Wind power forecast using wavelet neural network trained by improved Clonal selection algorithm. Energy Convers. Manage. 89, 588–598 (2015)

    Article  Google Scholar 

  5. Hu, Q., Zhang, R., Zhou, Y.: Transfer learning for short-term wind speed prediction with deep neural networks. Renew. Energy 85(14), 83–95 (2016)

    Article  Google Scholar 

  6. Pei, Z., Wang, C., He, Q., et al.: Analysis and suggestions on renewable energy integration problems in China. Electr. Power 49(11), 1–7 (2016). (in Chinese)

    MathSciNet  Google Scholar 

  7. Xu, X.: Research on accommodating wind power using heating. Dissertation for the master degree in North China Electric Power University, Beijing (2016) (in Chinese)

    Google Scholar 

  8. Li, S., Dong, H., Zhang, R., et al.: Multi-source coordination and optimization operation of combined heat and power system considering wind power consumption. Acta Energiae Solaris Sin. 39(8), 2217–2225 (2018). (in Chinese)

    Google Scholar 

  9. Yang, X., Lei, X., Ren, J., et al.: Operation model and economic analysis of using curtailed wind power for heat. Distrib. Energy 1(1), 28–32 (2016). (in Chinese)

    Google Scholar 

  10. Xu, M., Jiang, D.: Energy efficiency and economic analysis in wind power heating system. Energy China 37(8), 42–47 (2015). (in Chinese)

    Google Scholar 

Download references

Acknowledgements

The project is supported by the National Key Research and Development Program of China (Project Number 2017YFC0702900).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chuankai Niu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Niu, C., Li, Z., Cao, R. (2020). The Optimum Research and Case Study of Wind Power Heating Based on Supply and Demand Load Forecasting. In: Wang, Z., Zhu, Y., Wang, F., Wang, P., Shen, C., Liu, J. (eds) Proceedings of the 11th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC 2019). ISHVAC 2019. Environmental Science and Engineering(). Springer, Singapore. https://doi.org/10.1007/978-981-13-9528-4_121

Download citation

Publish with us

Policies and ethics