Advertisement

The Influence of New Energy Access on Load Peaks and Troughs Based on Optimization Techniques

  • Weibao ZhangEmail author
  • Hong Gang
  • Baozhong Gan
  • Qianhui Gang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 921)

Abstract

Power is the basis of the continuous development of modern science and technology, the important guarantee of improving human life quality and the lifeblood of the national economy and security. Traditional power system generates electricity with the method of centralized power generation and then transmits electricity to the users with the network of electricity transmission. Developed countries and developing countries have the increased demand on energy. Therefore, how to solve the contradiction between increased demands for the energy and the traditional energy depleted by people increasingly will be the competitive field between countries. Meanwhile, it will be an important guarantee of the governments to maintain or improve the world influence and one of the keys to the continuous development of human civilization. In order to solve the contradiction between the distributed new energy power generation and the security of power system, we should maximize the utility of distributed new energy power generation to bring the technical, economic and social benefits, such as we can improve the flexibility and reliability of power system operation to meet people about the growing demand for electricity consumption and sustainable development in the future.

Keywords

Power system Distributed new energy Sustainable development 

References

  1. 1.
    Anindita, R., Kedare, B., Santanu, B.: Optimum sizing of wind-battery systems incorporating resource uncertainty. Appl. Energy 87(8), 2712–2727 (2010)CrossRefGoogle Scholar
  2. 2.
    Yuan, Y., Li, Q., Wang, W.: Optimal operation strategy of energy storage unit in wind power integration based on stochastic programming. IET Renew. Power Gener. 5(2), 194–201 (2011)CrossRefGoogle Scholar
  3. 3.
    Chen, Z., Ding, M., Su, J.: Modeling and control for large capacity battery energy storage system. In: 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), vol. 62(6), pp. 1429–1436. IEEE (2011)Google Scholar
  4. 4.
    Hu, X., Tseng, K., Srinivasan, M.: Optimization of battery energy storage system with super-capacitor for renewable energy (2008)Google Scholar
  5. 5.
    Li, J.: Lanar cardinal spline curves with minimum strain energy, vol. 4(3), pp. 2–4 (2018)Google Scholar
  6. 6.
    Tomura, Y., Nakagawa, T.: Adjust the energy supply and demand system for using renewable energy effectively. In: Proceedings of the Annual Conference of the Japan Institute of Energy, vol. 26(10), pp. 859–862 (2003)Google Scholar
  7. 7.
    Mandal, J., Sinha, A.: Artificial neural network based hourly load forecasting for decentralized load management. In: Proceedings of the 1995 International Conference on Energy Management and Power Delivery (EMPD 1995), vol. 21(1), pp. 61–66. IEEE (1995)Google Scholar
  8. 8.
    Junmeng, C., Ronghou, L.: Biomass Energy Engineering Research Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 201101, People’s Republic of China. New distributed activation energy model and its application to pyrolysis kinetics of some types of biomass (2010)Google Scholar
  9. 9.
    Hu, Y.: Distributed energy transaction pattern and block chain based architecture design. In: Proceedings of the 2017 2nd International Conference on Energy, Power and Electrical Engineering (EPEE 2017), vol. 5(25), pp. 31–40. Science and Engineering Research Center (2017)Google Scholar
  10. 10.
    Li, M.-J., Zhao, W., Chen, X., Tao, W.-Q.: Economic analysis of a new class of vanadium redox-flow battery for medium and large-scale energy storage in commercial applications with renewable energy. Appl. Therm. Eng. 9(22), 114–128 (2017)Google Scholar
  11. 11.
    Dantzig, G.B.: General convex objective forms. In: Arrow, K.J., Karlin, S., Suppes, P. (eds.) Mathematical Models in the Social Sciences, 1959. Proceedings of the First Stanford Symposium. Stanford Mathematical Studies in the Social Sciences, vol. IV, pp. 151–158. Stanford University Press, Stanford (1960)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Weibao Zhang
    • 1
    Email author
  • Hong Gang
    • 1
  • Baozhong Gan
    • 1
  • Qianhui Gang
    • 1
  1. 1.Jinzhou Power Supply Branch, State Grid Liaoning Electric Power Supply Co. Ltd.JinzhouChina

Personalised recommendations