Grey Wolf Algorithm-Based source size and location determination method for capacity expansion planning in power systems

Expansion of power generation capacity within power systems is crucial for improving system reliability and efficiency. The main objective of the process is to optimize the power generation capacity to appropriately meet current and future load demands. In this study, the stability issues that arise in power systems due to the increment in load power, overloads on transmission lines, changes in bus voltages and the effects of available generation resources on these dynamics are investigated. In particular, the issues such as overloads on transmission lines, increases in the loading rates of generation resources and decreases or increases in bus voltages are examined. The size and location of new sources to be added to the system have great importance in order to overcome these issues. IEEE 39 bus test system is used, and the power system is modeled in the DIgSILENT platform. Integrated simulations were performed by integrating the DIgSILENT and Python programming. The simulation scenarios are created by increasing the load power located at various buses. The scenarios and system configurations were automatically tested through Python scripts, allowing a broader perspective of the effects of line loading, bus voltages and generation resources on system performance. The possible solutions without optimization are obtained in the first stage with the standard IEEE 39 bus test system. Considering the source size and location, line loading limits, generator capacity, and bus parameters, the Grey Wolf optimization algorithm determines the optimum solution for the capacity expansion. Thus, an effective method is proposed for power system planning. According to the optimization results the IEEE 39 bus test system is modified by increasing capacity of current sources or adding new sources. The obtained solutions with the proposed method are simulated, and the system performance in terms of line loading, generator loading, and bus voltage is tested. The results reveal that the proposed method provides the optimum capacity expansion solutions to eliminate the adverse effects of increment in load power.

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Publication Details

Journal
Engineering Science and Technology an International Journal
Published
2024-12-20
DOI
https://doi.org/10.1016/j.jestch.2024.101934
Citations
2
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
0.42

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article

Grey Wolf Algorithm-Based source size and location determination method for capacity expansion planning in power systems

Murat Akın, Mustafa Bahadır Özdemir, Ugur Feslı
2 citations
Engineering Science and Technology an International Journal
Power System Optimization and Stability
0.42
article

Grey Wolf Algorithm-Based source size and location determination method for capacity expansion planning in power systems

Murat Akın, Mustafa Bahadır Özdemir, Ugur Feslı
article en
2 citations

Abstract

Expansion of power generation capacity within power systems is crucial for improving system reliability and efficiency. The main objective of the process is to optimize the power generation capacity to appropriately meet current and future load demands. In this study, the stability issues that arise in power systems due to the increment in load power, overloads on transmission lines, changes in bus voltages and the effects of available generation resources on these dynamics are investigated. In particular, the issues such as overloads on transmission lines, increases in the loading rates of generation resources and decreases or increases in bus voltages are examined. The size and location of new sources to be added to the system have great importance in order to overcome these issues. IEEE 39 bus test system is used, and the power system is modeled in the DIgSILENT platform. Integrated simulations were performed by integrating the DIgSILENT and Python programming. The simulation scenarios are created by increasing the load power located at various buses. The scenarios and system configurations were automatically tested through Python scripts, allowing a broader perspective of the effects of line loading, bus voltages and generation resources on system performance. The possible solutions without optimization are obtained in the first stage with the standard IEEE 39 bus test system. Considering the source size and location, line loading limits, generator capacity, and bus parameters, the Grey Wolf optimization algorithm determines the optimum solution for the capacity expansion. Thus, an effective method is proposed for power system planning. According to the optimization results the IEEE 39 bus test system is modified by increasing capacity of current sources or adding new sources. The obtained solutions with the proposed method are simulated, and the system performance in terms of line loading, generator loading, and bus voltage is tested. The results reveal that the proposed method provides the optimum capacity expansion solutions to eliminate the adverse effects of increment in load power.

Engineering Science and Technology an International JournalVol. 61
Gazi University (TR)
Qatar Foundation, Qatar National Research Fund
Openalex Percentile: Top 36%
Power System Optimization and Stability
0.42
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