Performance Enhancement of Radial Distribution System via Network Reconfiguration: A Case Study of Urban City in Nepal

Govinda Prashad Pandey, Ashish Shrestha, Bijen Mali, Ajay Singh, Ajay Kumar Jha


Increasing unplanned energy demand increase has led to network congestion, increases power losses and poor voltage profile. To decrease these effects of an unmanaged power system, distribution network reconfiguration provides an effective solution. This paper deals with improving the power losses and poor voltage profile of the Phulchowk Distribution and Consumer Services (DCS) via the implementation of an optimum reconfiguration approach. A Genetic Algorithm (GA) is developed for the optimization. Further, it tries to answer to what extent can we improve the distribution system without overhauling the entire network. The developed simulation algorithm is firstly put into work on the IEEE 33 bus system to better its voltage profile and the poor power losses. The effectiveness of the developed system is validated as it reduced the voltage drop by 5.66% and the power loss by 25.96%. With the solution validated, the algorithm is further implemented in the case of Pulchowk DCS. After reconfiguring the system in different individual cases, optimum network reconfiguration is selected that improved the voltage profile by 3.85%, and the active and reactive power losses by 44.29% and 45.54% respectively from the base case scenario.


Radial Distribution System; Grid Reconfiguration Power; System Performance Enhancement; Genetic Algorithm

Full Text:



Al-Abri, R. (2012). Voltage stability analysis with high distributed generation (DG) Penetration.

Badran, O., Mekhilef, S., Mokhlis, H., & Dahalan, W. (2017). Optimal reconfiguration of distribution system connected with distributed generations: A review of different methodologies. Renewable and Sustainable Energy Reviews, 73, 854-867.

Basiago, A. D. (1998). Economic, social, and environmental sustainability in development theory and urban planning practice. Environmentalist, 19(2), 145-161.

Flaih, F. M., Lin, X., Abd, M. K., Dawoud, S. M., Li, Z., & Adio, O. S. (2017). A new method for distribution network reconfiguration analysis under different load demands. Energies, 10(4), 455.

Georgilakis, P. S., & Hatziargyriou, N. D. (2015). A review of power distribution planning in the modern power systems era: Models, methods and future research. Electric Power Systems Research, 121, 89-100.

Monthly loss report of Pulchowk Distribution and Consumer Services. (2019). Retrieved from Kathmandu

Napis, N. F., Khatib, T., Hassan, E. E., & Sulaima, M. F. (2018). An improved method for reconfiguring and optimizing electrical active distribution network using evolutionary particle swarm optimization. Applied Sciences, 8(5), 804.

NEA. (2019). NEA Annual Report 2018/2019. Retrieved from Kathmandu:

Prakash, K., Lallu, A., Islam, F., & Mamun, K. (2016). Review of power system distribution network architecture. Paper presented at the 2016 3rd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE).

Rao, R. S., Ravindra, K., Satish, K., & Narasimham, S. (2012). Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE transactions on power systems, 28(1), 317-325.

Shrestha, A. (2017). Planning, Design and Optimization of Distribution System for Affected Area of Upper Karnali Hydropower Project: GRIN Verlag.

Shrestha, A., Jha, S. K., Shah, B., & Gautam, B. R. (2016). Optimal grid network for rural electrification of Upper Karnali hydro project affected area. Paper presented at the 2016 IEEE Region 10 Humanitarian Technology Conference (R10-HTC).

Shrestha, A., Kattel, R., Dachhepatic, M., Mali, B., Thapa, R., Singh, A., . . . Maskey, R. K. (2019). Comparative study of different approaches for islanding detection of distributed generation systems. Applied System Innovation, 2(3), 25.

Shrestha, A., Shah, B. B., Gautam, B. R., & Jha, S. K. (2017). Framework development to analyze the distribution system for upper karnali hydropower project affected area. International Journal of Modern Engineering Research, 7(4), 82-91.


Article Metrics

 Abstract Views : 454 times
 PDF Downloaded : 113 times


  • There are currently no refbacks.

Copyright (c) 2021 Govinda Prashad Pandey, Ashish Shrestha, Bijen Mali, Ajay Singh, Ajay Kumar Jha

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.