Introduction of Configurational Indicators for Distribution Network Optimality Based on a Zoning Methodology

Document Type : Research Article

Authors

1 Electrical Distribution Research Center, Niroo Research Institute

2 Transmission and Substaion Dept., Niroo Research Institute

Abstract

The configuration of electrical distribution network may alter upon the changes in the load density and the load distribution in the region. Regional climatic conditions affect the rating of the components in the distribution network. Therefore, they have some influences on the network configuration as well. These two affecting factors (electrical load and climate) are not directed by the system operator or designer. Hence, it is pleasurable to find an appropriate network plan to satisfy the load requirements as well as the climate undesirable influences in real operating conditions. This paper is aimed to find some quantitative relevancies between the network configuration and the affecting parameters (i.e. climatic conditions, load density, load profile and loss factor) to achieve this goal. It has tried to define some factors to quantify the network configuration in order to simplify judgement about the design quality of the network. This means that these factors can be used as quantitative benchmarks that help network planner to understand which parts of the existing network are not in accordance with the optimal configuration. This study is conducted through statistical analysis on real data attained from several networks in different climatic conditions and different load situations. The idea is examined via performing the network design optimizations on 35 scenarios for the networks located in 5 different areas. Results are presented in tables and figures that are informative and practical for the network engineers to design and operate the distribution system in different loading conditions and climatic situations.

Keywords

Main Subjects

References

[1] Samrat Ganguly, N.C. Sahoo, Debabrata Das, “Multi-objective planning of electrical distribution systems using dynamic programming”, International journal of electrical power & energy systems, Vol. 46, pp. 65-78, 2013.
[2]. Mostafa Esmaeeli, Ahad Kazemi, Heidarali Shayanfar, Gianfranco Chicco, and Pierluigi Siano, “Risk-based planning of the distribution network structure considering uncertainties in demand and cost of energy”, Inter. journal of Energy, Vol. 119, pp. 578-587, 2017.
[3]. Jun Shu, Lei Wu, Bing Han, Lizi Zhang, “Enhanced multi-dimensional power network planning based on ant colony optimization”, International Transactions on Electrical Energy Systems, Vol. 25, No. 7, pp. 1204-1222, 2015.
[4]. Seyed Mahdi Mazhari, Hassan Monsef, Hamid Falaghi, “A hybrid heuristic and learning automata-based algorithm for distribution substations siting, sizing and defining the associated service areas”, International Transactions on Electrical Energy Systems, Vol. 24, No. 3, pp. 433-456, 2014.
[5] Pavlos S. Georgilakis and Nikos D. Hatziargyriou, “A   review of power distribution planning in the modern power systems era: Models, methods and future research”, Electric power system research, Vol. 121, pp. 89-100, 2015.
[6] Gregorio Munoz-Delgado, Javier Contreras, Jose M. Arroyo, “Distribution System Expansion Planning Considering Non-Utility-Owned DG and an Independent Distribution System Operator”, IEEE Transactions on Power Systems, Vol. 34, pp. 2588-2597, 2019.
[7] Shunbo Lei, Yunhe Hou, Feng Qiu, Jie Yan, “Identification of Critical Switches for Integrating Renewable Distributed Generation by Dynamic Network Reconfiguration”, IEEE Transactions on Sustainable Energy, Vol. 9, No. 1, pp. 420-432, 2018.
[8] Sultan S. Al Kaabi, Hatem H. Zeineldin, and Vinod Khadkikar “Planning Active Distribution Networks Considering Multi-DG Configurations”, IEEE transactions on power systems, Vol. 29, No. 2, pp. 785-793, 2014.
[9] Akihisa Kaneko, Yasuhiro Hayashi, Takaya Anegawa, Hideyasu Hokazono, Yukiyasu Kuwashita, “Evaluation of an Optimal Radial-Loop Configuration for a Distribution Network With PV Systems to Minimize Power Loss”, IEEE Access, Vol. 8, pp. 220408 – 220421, 2020.
[10] F. R. Alonso, Denisson Q. Oliveira, Antonio Carlos Zambroni de Souza, “Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration”, IEEE transactions on power systems, Vol. 30, No. 2, pp. 840-847, 2014.
[11] Changhyeok Lee, Cong Liu, Sanjay Mehrotra, and Zhaohong Bie “Robust Distribution Network Reconfiguration”, IEEE transactions on smart grid, Vol. 6, No. 2, pp. 836-842, 2015.
[12] Dong-Li Duan, Xiao-Dong Ling, Xiao-Yue Wu, and Bin Zhong,  “Reconfiguration of distribution network for loss reduction and reliability improvement based on an enhanced genetic algorithm”, International journal of electrical power & energy systems, Vol. 64, pp. 88-95, 2015.
[13] A. Mohamed Imran and muniswamy kowsalya, “A new power system reconfiguration scheme for power loss minimization and voltage profile enhancement using Fireworks Algorithm”, International electrical power and energy systems, Vol. 62, pp. 312-322, 2014.
[14] Mohammad Rasoul Narimani, Ali Azizi Vahed, Rasoul Azizipanah-Abarghooee, and Mahshid Javidsharifi, “Enhanced gravitational search algorithm for multi-objective distribution feeder reconfiguration considering reliability, loss and operational cost”, IET generation, transmission & distribution, Vol. 8, No. 1, pp. 55-69, 2014.
[15] Huayi Wu, Ping Dong, Mingbo Liu, “Distribution Network Reconfiguration for Loss Reduction and Voltage Stability with Random Fuzzy Uncertainties of Renewable Energy Generation and Load”, IEEE Transactions on Industrial Informatics, Vol. 16, No. 9, pp. 5655-5666, 2020.
[16] Mohammad Jafar Hadidian Moghaddam;Akhtar Kalam;Juan Shi;Saber Arabi Nowdeh;Foad Haidari Gandoman;Abdollah Ahmadi, “A New Model for Reconfiguration and Distributed Generation Allocation in Distribution Network Considering Power Quality Indices and Network Losses”, IEEE Systems Journal, Vol. 14, No. 3, pp. 3530-3538, 2020.
[17]. Iraj Ahmadi, Masoud Ahmadigorji, Ehsan Tohidifar, “A novel approach for power loss reduction in distribution networks considering budget constraint”, International Transactions on Electrical Energy Systems, Vol. 28, No. 12, 2018.
[18] Florin Cappitanescu, Luis F. Ochoa, Hagop Margossian, Nikos D. Hatziargyriou, “Assessing the Potential of Network Reconfiguration to Improve Distributed Generation Hosting Capacity in Active Distribution Systems”, IEEE transaction on power systems, Vol. 30, No. 1, pp. 346-356, 2015.
[19] Mojtaba Gilvanejad, Sara Khayyamim, Hamideh Ghadiri, Mohammad Reza Shariati, “Analyzing the Effect of Transformer Utilization Factor in Distribution Networks as an Investment Management Index by using DisPlan Software”, 22nd International Conference and Exhibition on Electricity Distribution (CIRED), 2013.
[20] Hamideh Ghadiri, Mohammad Reza Shariati, Sara Khayyamim, Iraj Kheirizad, Mojtaba Gilvanejad, “Industrial strategic network planning optimization, applying DisPlan software”, CIRED 2012 Workshop: Integration of Renewables into the Distribution Grid, 2012.
[21] Mojtaba Gilvanejad, Hamideh Ghadiri, Mohammad Reza Shariati, Sara Khayyamim, Akbar Yavartalab, Babak Nikfam, “Optimum Planning of Primary-Secondary Distribution Networks According to Real Municipal Maps”, 21st International Conference on Electricity Distribution (CIRED), 2011.
[22] Mojtaba Gilvanejad, Hamideh Ghadiri, Mohammad Reza Shariati, Safar Farzalizadeh, Ali Arefi, “Novel Algorithm for Distribution Network Planning Using Loss Reduction Approach”, Australasian Universities Power Engineering Conference, 2007.
[23] Mojtaba Gilvanejad, Mohammad Reza Shariati, Hamideh Ghadiri, Sara Khayyamim, Akbar Yavartalab, “A New Approach to System Planning: Iran Upgrades Planning Framework of its Distribution Networks”, Transmission & Distribution World Magazine, pp. 30-34, 2013.
[24] Mojtaba Gilvanejad, Mohammad Reza Shariati, Hamideh Ghadiri, Sara Khayyamim, Safar Farzalizadeh, “A software for determining the optimum configuration and technical specification of electrical distribution network based on the geographical data entered by the user”, State Organization for Registration of Deeds and Properties- Intellectual Property Center, Reg. No. 87968, 2012.
[25] H. Heydari, B. Alijani, “climatic classification of Iran map using multi-variable statistic techniques”, Journal of Geographical Studies, Vol. 37, pp. 57-74, March 2000.
AUT Journal of Electrical Engineering
Volume 53, Issue 2
December 2021
Pages 143-158

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