Operational Research

, Volume 17, Issue 3, pp 885–900 | Cite as

Evaluation and comparison of power network plans including distributed photovoltaic generations

Original Paper
  • 112 Downloads

Abstract

Distributed power generation reduces the network loss and investment of transmission line when close to the load power. At the same time, distributed photovoltaic generation is intermittent and impacted by environmental factors. To compare different power network plans including distributed photovoltaic generations, a comprehensive evaluation model is developed at the perspective of grid company based on improved entropy-matter-element extension model. This study builds a set of index system referring to the reliability, safety, efficiency and environmental protection. Improved entropy model combines with objective and subjective weight factors. Meanwhile, the improved matter-element extension model can perform observations beyond range. The study also tests the model by evaluating and giving the corresponding rating for two groups of distributed power supply plans. The results of sensitivity analysis process shows that the main factors effectively influencing the distribution network plans include: “N-1” check, capacity-load ratio, system component failure rate, system component repair time.

Keywords

Distributed photovoltaic generation Power network plans Evaluation Entropy-matter-element extension model 

Notes

Acknowledgements

The authors thank the anonymous referees and the editor of this journal. The authors gratefully acknowledge the financial support of the Social Science Foundation of Ministry of Education of China (Grant No. 15YJA630011).

References

  1. Ceballos C, Pilaud V (2015) Denominator vectors and compatibility degrees in cluster algebras of finite type[J]. Trans Am Math Soc 367(2):1421–1439CrossRefGoogle Scholar
  2. Costianu DR, Iliescu SS, Arghira N et al (2013) Distributed generation influence on smart distribution grids[J]. IFAC Proc Vol 46(6):54–57CrossRefGoogle Scholar
  3. Dulău LI, Abrudean M, Bică D (2016) Optimal location of a distributed generator for power losses improvement[J]. Proced Technol 22:734–739CrossRefGoogle Scholar
  4. El-Abbasy MS, El Chanati H, Mosleh F et al (2016) Integrated performance assessment model for water distribution networks[J]. Struct Infrastruct Eng 12(11):1505–1524Google Scholar
  5. Evangelopoulos VA, Georgilakis PS, Hatziargyriou ND (2016) Optimal operation of smart distribution networks: a review of models, methods and future research[J]. Electr Power Syst Res 140:95–106CrossRefGoogle Scholar
  6. Jamil M, Anees AS (2016) Optimal sizing and location of SPV (solar photovoltaic) based MLDG (multiple location distributed generator) in distribution system for loss reduction, voltage profile improvement with economical benefits[J]. Energy 103:231–239CrossRefGoogle Scholar
  7. Kaddah SS, El-Saadawi MM, El-Hassanin DM (2015) Influence of distributed generation on distribution networks during faults[J]. Electric Power Compon Syst 43(16):1781–1792CrossRefGoogle Scholar
  8. Kintisch E (2007) A career CO2 hunter goes after big game[J]. Science 317(5835):186CrossRefGoogle Scholar
  9. Lenssen N (2000) A critical technology: interconnecting distributed generation to the grid[J]. Cogener Compet Power J 15(3):18–25Google Scholar
  10. Mahmud MA, Hossain MJ, Pota HR (2011) Analysis of voltage rise effect on distribution network with distributed generation[J]. IFAC Proc Vol 44(1):14796–14801CrossRefGoogle Scholar
  11. Mohammadi M, Rozbahani AM, Montazeri M (2016) Multi criteria simultaneous planning of passive filters and distributed generation simultaneously in distribution system considering nonlinear loads with adaptive bacterial foraging optimization approach[J]. Int J Electr Power Energy Syst 79:253–262CrossRefGoogle Scholar
  12. Mohanty B, Tripathy S (2016) A teaching learning based optimization technique for optimal location and size of DG in distribution network[J]. J Electr Syst Inf Technol 3(1):33–44Google Scholar
  13. Resener M, Haffner S, Pereira LA et al (2016) Mixed-integer LP model for volt/var control and energy losses minimization in distribution systems[J]. Electr Power Syst Res 140:895–905CrossRefGoogle Scholar
  14. Sik Pak P (2004) Comprehensive evaluation of a CO2-capturing NOx-free repowering system with utilization of middle-pressure steam in a thermal power plant[J]. Electr Eng Jpn 148(4):34–40CrossRefGoogle Scholar
  15. Silva ENM, Rodrigues AB, da Silva MG (2016) Stochastic assessment of the impact of photovoltaic distributed generation on the power quality indices of distribution networks[J]. Electr Power Syst Res 135:59–67CrossRefGoogle Scholar
  16. Sitharthan R, Geethanjali M, Pandy TKS (2016) Adaptive protection scheme for smart microgrid with electronically coupled distributed generations[J]. Alex Eng J 55(3):2539–2550CrossRefGoogle Scholar
  17. Zhang L, Ye T, Xin Y, Fan G (2010) Problems and measures of power grid accommodating large scale wind power. In: Proceedings of the CSEE, vol 30, no 25, pp 1–9Google Scholar
  18. Zhou XY, Wang LY, Liang WY et al (2014) Research on the voltage influence of active distribution network with distributed generation access[C]. Appl Mech Mater 668:749–752CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.School of Economics and ManagementNorth China Electric Power UniversityBeijingChina

Personalised recommendations