Research on Grid Planning of Dual Power Distribution Network Based on Parallel Ant Colony Optimization Algorithm
Download PDF


Parallel ant colony optimization algorithm
Dual power sources
Distribution network
Grid planning



Submitted : 2023-04-17
Accepted : 2023-05-02
Published : 2023-05-17


A distribution network plays an extremely important role in the safe and efficient operation of a power grid. As the core part of a power grid’s operation, a distribution network will have a significant impact on the safety and reliability of residential electricity consumption. it is necessary to actively plan and modify the distribution network’s structure in the power grid, improve the quality of the distribution network, and optimize the planning of the distribution network, so that the network can be fully utilized to meet the needs of electricity consumption. In this paper, a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm. For the distribution network structure planning of dual power sources, the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies, and the dual power distribution network structure model is established based on the principle of the lowest cost. The artificial ants in the algorithm were compared with real ants in nature, and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem (TSP). Then, the limitations of the ant colony algorithm were analyzed, and an improvement strategy was proposed by using python for digital simulation. The results demonstrated the reliability of model-building and algorithm improvement.


Asrari A, Ansari M, Khazaei J, et al., 2021, The Impacts of a Decision Making Framework on Distribution Network Reconfiguration. IEEE Transactions on Sustainable Energy, 16(11): 821–824.

Masoumi-Amiri SM, Shahabi M, Barforoushi T, 2021, Interactive Framework Development for Microgrid Expansion Strategy and Distribution Network Expansion Planning. Sustainable Energy Grids and Networks, 29(11): 1005-1008.

Dash SK, Mishra S, Abdelaziz A Y, et al. 2022, Optimal Planning of Multitype DGs and D-STATCOMs in Power Distribution Network Using an Efficient Parameter Free Metaheuristic Algorithm. Energies, 15(4): 216–218.

Liu X, 2021, Automatic Routing of Medium Voltage Distribution Network Based on Load Complementary Characteristics and Power Supply Unit Division. International Journal of Electrical Power & Energy Systems, 33(2): 106–109.

Ketjoy N, 2021, The Analysis Framework for High Penetration PV Rooftop in LV Distribution Network: Case Study Provincial Electricity Authority. 32(1): 473–476.

Aygun NK, Bulut O, Byk E, 2021, A Framework for Capacity Expansion Planning in Failure-Prone Flow-Networks via Systemic Risk Analysis. IEEE Systems Journal, 21(09): 9–12.

Nasri A, Abdollahi A, Rashidinejad M, 2022, Multi-Stage and Resilience-Based Distribution Network Expansion Planning Against Hurricanes Based on Vulnerability and Resiliency Metrics. International Journal of Electrical Power & Energy Systems, 136(12): 1076–1079.

Alobaidi AH, Khodayar M, Vafamehr A, et al., 2021, Stochastic Expansion Planning of Battery Energy Storage for the Interconnected Distribution and Data Networks. International Journal of Electrical Power & Energy Systems, 13(2): 1072–1078.

Ali ZM, Diaaeldin IM, El-Rafei A, et al., 2021, A Novel Distributed Generation Planning Algorithm Via Graphically-Based Network Reconfiguration and Soft Open Points Placement Using Archimedes Optimization Algorithm. Ain Shams Engineering Journal, 31(2): 175–178.

Sabzehgar R, Amirhosseini DZ, Manshadi SD, et al., 2021, Stochastic Expansion Planning of Various Energy Storage Technologies in Active Power Distribution Networks. Sustainability, 13(2): 87–93.

Ashoornezhad A, Asadi Q, Falaghi H, et al., 2021, Private Investors Participation in Long-Term Distribution Network Planning. Proceedings of Power Electronics, Drive Systems, and Technologies Conference, 154–159.

Shahbazi A, Aghaei J, Pirouzi S, et al., 2021, Holistic Approach to Resilient Electrical Energy Distribution Network Planning. International Journal of Electrical Power & Energy Systems, 132(5): 1072–1075.

Wu Z, Xu Z, Gu W, et al., 2021, Decentralized Game-Based Robustly Planning Scheme for Distribution Network and Microgrids Considering Bilateral Energy Trading. IEEE Transactions on Sustainable Energy, 25(9): 628–635.

Zhang Y, Tao Y, Zhang S, et al. 2021, Optimal Sensing Task Distribution Algorithm for Mobile Sensor Networks with Agent Cooperation Relationship. IEEE Internet of Things Journal, 25(10): 275–279.

Paul S, Sharma A, Padhy NP, 2021, Risk Constrained Energy Efficient Optimal Operation of a Converter Governed AC/DC Hybrid Distribution Network with Distributed Energy Resources and Volt-VAR Controlling Devices. IEEE Transactions on Industry Applications, 24(08): 318–324.

Zhang Y, Qian T, Tang W, 2022, Buildings-to-Distribution-Network Integration Considering Power Transformer Loading Capability and Distribution Network Reconfiguration. Energy, 24(6): 176–179.

Li P, Zhang Z, Grosu R, et al., 2022, An End-to-End Neural Network Framework for State-of-Health Estimation and Remaining Useful Life Prediction of Electric Vehicle Lithium Batteries. Renewable and Sustainable Energy Reviews, 15(4): 1184–1187.

Zhao H, Jin J, Liu Y, et al., 2022, AdaBoost-MICNN: A New Network Framework for Pulsar Candidate Selection. Monthly Notices of the Royal Astronomical Society, 24(2): 264–268.

Mohamed A, Morrow DJ, Best RJ, et al., 2021, Distributed Battery Energy Storage Systems Operation Framework for Grid Power Levelling in the Distribution Networks. IET Smart Grid, 19(6): 75–79.

Che TC, Wang X, Ghidaoui MS, 2022, Leak Localization in Looped Pipe Networks Based on a Factorized Transient Wave Model: Theoretical Framework. Water Resources Research, 26(4): 258-264.