Improved grey wolf optimizer for optimal reactive power dispatch with integration of wind and solar energy
DOI:
https://doi.org/10.20998/2074-272X.2025.1.04Keywords:
optimal reactive power dispatch, renewable energy resources, wind energy, solar energy, improved grey wolf optimizerAbstract
The aim of this paper is to present a new improved grey wolf optimizer (IGWO) to solve the optimal reactive power dispatch (ORPD) problem with and without penetration of renewable energy resources (RERs). It is a nonlinear multivariable problem of optimization, with multiconstraints. The purpose is to minimize real power losses and improve the voltage profile of a given electric system by adjusting control variables, such as generator voltages, tap ratios of a transformer, switching VAr sources, without violating technical constraints that are presented as equalities and inequalities. Methodology. Metaheuristics are stochastic algorithms that can be applied to solve a wide variety of optimization problems without needing specific problem structure information. The penetration of RERs into electric power networks has been increased considerably to reduce the dependence of conventional energy resources, reducing the generation cost and greenhouse emissions. It is essential to include these sources in power flow studies. The wind and photovoltaic based systems are the most applied technologies in electrical systems compared to other technologies of RERs. Moreover, grey wolf optimizer (GWO) is a powerful metaheuristic algorithm that can be used to solve optimization problems. It is inspired from the social hierarchy and hunting behavior of grey wolves in the wild. The novelty. This paper presents an IGWO to solve the ORPD problem in presence of RERs. Methods. The IGWO based on enhancing the exploitation phase of the conventional GWO. The robustness of the method is tested on the IEEE 30 bus test system. For the control variables, a mixed representation (continuous/discrete), is proposed. The obtained results demonstrate the effectiveness of the introduced improvement and ability of the proposed algorithm for finding better solutions compared to other presented methods. References 40, tables 3, figures 9.
References
Kirchmayer L.K. Economic operation of power systems. New York, John Wiley & Sons Inc., 1958. 260 p.
Carpentier J. Contribution á l’étude du dispatching économique. Bulletin de la Société Francaise des électriciens, 1962, vol. 3, ser. 8, pp. 431-447. (Fra).
Dommel H., Tinney W. Optimal Power Flow Solutions. IEEE Transactions on Power Apparatus and Systems, 1968, vol. PAS-87, no. 10, pp. 1866-1876. doi: https://doi.org/10.1109/TPAS.1968.292150.
Shaheen M.A.M., Ullah Z., Hasanien H.M., Tostado-Véliz M., Ji H., Qais M.H., Alghuwainem S., Jurado F. Enhanced transient search optimization algorithm-based optimal reactive power dispatch including electric vehicles. Energy, 2023, vol. 277, art. no. 127711. doi: https://doi.org/10.1016/j.energy.2023.127711.
Jamal R., Zhang J., Men B., Khan N.H., Ebeed M., Kamel S. Solution to the deterministic and stochastic Optimal Reactive Power Dispatch by integration of solar, wind-hydro powers using Modified Artificial Hummingbird Algorithm. Energy Reports, 2023, vol. 9, pp. 4157-4173. doi: https://doi.org/10.1016/j.egyr.2023.03.036.
Chamba A., Barrera-Singaña C., Arcos H. Optimal Reactive Power Dispatch in Electric Transmission Systems Using the Multi-Agent Model with Volt-VAR Control. Energies, 2023, vol. 16, no. 13, art. no. 5004. doi: https://doi.org/10.3390/en16135004.
Shaik M., Gaonkar D.N., Nuvvula R.S.S., Kumar P.P., Khan B. Probabilistic Optimal Active and Reactive Power Dispatch including Load and Wind Uncertainties considering Correlation. International Transactions on Electrical Energy Systems, 2023, vol. 2023, art. no. 2759073. doi: https://doi.org/10.1155/2023/2759073.
Ali A., Abbas G., Keerio M.U., Touti E., Ahmed Z., Alsalman O., Kim Y.-S. A Bi-Level Techno-Economic Optimal Reactive Power Dispatch Considering Wind and Solar Power Integration. IEEE Access, 2023, vol. 11, pp. 62799-62819. doi: https://doi.org/10.1109/ACCESS.2023.3286930.
Granados J.F.L., Uturbey W., Valadão R.L., Vasconcelos J.A. Many-objective optimization of real and reactive power dispatch problems. International Journal of Electrical Power & Energy Systems, 2023, vol. 146, art. no. 108725. doi: https://doi.org/10.1016/j.ijepes.2022.108725.
Pattanaik J.K., Basu M., Dash D.P. Improved Real-Coded Genetic Algorithm for Reactive Power Dispatch. IETE Journal of Research, 2022, vol. 68, no. 2, pp. 1462-1474. doi: https://doi.org/10.1080/03772063.2019.1654933.
Bhurt F., Ali A., Keerio M.U., Abbas G., Ahmed Z., Mugheri N.H., Kim Y.-S. Stochastic Multi-Objective Optimal Reactive Power Dispatch with the Integration of Wind and Solar Generation. Energies, 2023, vol. 16, no. 13, art. no. 4896. doi: https://doi.org/10.3390/en16134896.
Zhang M., Li Y. Multi-Objective Optimal Reactive Power Dispatch of Power Systems by Combining Classification-Based Multi-Objective Evolutionary Algorithm and Integrated Decision Making. IEEE Access, 2020, vol. 8, pp. 38198-38209. doi: https://doi.org/10.1109/ACCESS.2020.2974961.
Candra O., Alghamdi M.I., Hammid A.T., Alvarez J.R.N., Staroverova O.V., Hussien Alawadi A., Marhoon H.A., Shafieezadeh M.M. Optimal distribution grid allocation of reactive power with a focus on the particle swarm optimization technique and voltage stability. Scientific Reports, 2024, vol. 14, no. 1, art. no. 10889. doi: https://doi.org/10.1038/s41598-024-61412-9.
Biswas P.P., Suganthan P.N., Mallipeddi R., Amaratunga G.A.J. Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach. Applied Soft Computing, 2019, vol. 75, pp. 616-632. doi: https://doi.org/10.1016/j.asoc.2018.11.042.
Kumar P.G.A, Jeyanthy P.A., Devaraj D. Hybrid CAC-DE in optimal reactive power dispatch (ORPD) for renewable energy cost reduction. Sustainable Computing: Informatics and Systems, 2022, vol. 35, art. no. 100688. doi: https://doi.org/10.1016/j.suscom.2022.100688.
Kar M.K., Kumar S., Singh A.K., Panigrahi S. Reactive power management by using a modified differential evolution algorithm. Optimal Control Applications and Methods, 2023, vol. 44, no. 2, pp. 967-986. doi: https://doi.org/10.1002/oca.2815.
Abou El Ela A.A., Abido M.A., Spea S.R. Differential evolution algorithm for optimal reactive power dispatch. Electric Power Systems Research, 2011, vol. 81, no. 2, pp. 458-464. doi: https://doi.org/10.1016/j.epsr.2010.10.005.
Naderi E., Mirzaei L., Pourakbari-Kasmaei M., Cerna F.V., Lehtonen M. Optimization of active power dispatch considering unified power flow controller: application of evolutionary algorithms in a fuzzy framework. Evolutionary Intelligence, 2024, vol. 17, no. 3, pp. 1357-1387. doi: https://doi.org/10.1007/s12065-023-00826-2.
Saddique M.S., Bhatti A.R., Haroon S.S., Sattar M.K., Amin S., Sajjad I.A., Ul Haq S.S., Awan A.B., Rasheed N. Solution to optimal reactive power dispatch in transmission system using meta-heuristic techniques – Status and technological review. Electric Power Systems Research, 2020, vol. 178, art. no. 106031. doi: https://doi.org/10.1016/j.epsr.2019.106031.
Li C., Lu Q., He H., Zhao J., Jiang Y., Xu B., Yan Y., Bian J., Du W. Reactive Power Optimization of Active Distribution Networks Based on Simulated Annealing Algorithm. 2023 IEEE 7th Information Technology and Mechatronics Engineering Conference (ITOEC), 2023, pp. 1022-1026. doi: https://doi.org/10.1109/ITOEC57671.2023.10291951.
Srinivasan G., Mahesh Kumar Reddy V., Venkatesh P., Parimalasundar E. Reactive power optimization in distribution systems considering load levels for economic benefit maximization. Electrical Engineering & Electromechanics, 2023, no. 3, pp. 83-89. doi: https://doi.org/10.20998/2074-272X.2023.3.12.
Wu X., Yan J., Zhao J. Comparative Research on Reactive Power Optimization of Distribution Network Based on Ant Colony and Bee Colony Algorithm. 2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC), 2022, pp. 247-251. doi: https://doi.org/10.1109/ITOEC53115.2022.9734469.
Vishnu M., Sunil Kumar T.K. An Improved Solution for Reactive Power Dispatch Problem Using Diversity-Enhanced Particle Swarm Optimization. Energies, 2020, vol. 13, no. 11, art. no. 2862. doi: https://doi.org/10.3390/en13112862.
Jimenez-Nunez J.J., Cedeno-Maldonado J.R. A particle swarm optimization approach for reactive power dispatch. Proceedings of the 37th Annual North American Power Symposium, 2005, pp. 198-205. doi: https://doi.org/10.1109/NAPS.2005.1560524.
Ghasemi A., Valipour K., Tohidi A. Multi objective optimal reactive power dispatch using a new multi objective strategy. International Journal of Electrical Power & Energy Systems, 2014, vol. 57, pp. 318-334. doi: https://doi.org/10.1016/j.ijepes.2013.11.049.
Jaisiva S., Prabaakaran K., Kumar C., Lakshmanan M., Alwabli A., Jaffar A., Alharbi A., Miyajan A. A novel solution for the optimal reactive power dispatch problem using an artificial neural network integrated with the firefly optimization algorithm. Frontiers in Energy Research, 2023, vol. 11, art. no. 1310010. doi: https://doi.org/10.3389/fenrg.2023.1310010.
Mirjalili S., Mirjalili S.M., Lewis A. Grey Wolf Optimizer. Advances in Engineering Software, 2014, vol. 69, pp. 46-61. doi: https://doi.org/10.1016/j.advengsoft.2013.12.007.
Varan M., Erduman A., Menevşeoğlu F. A Grey Wolf Optimization Algorithm-Based Optimal Reactive Power Dispatch with Wind-Integrated Power Systems. Energies, 2023, vol. 16, no. 13, art. no. 5021. doi: https://doi.org/10.3390/en16135021.
Jamal R., Men B., Khan N.H. A Novel Nature Inspired Meta-Heuristic Optimization Approach of GWO Optimizer for Optimal Reactive Power Dispatch Problems. IEEE Access, 2020, vol. 8, pp. 202596-202610. doi: https://doi.org/10.1109/ACCESS.2020.3031640.
Hosseini-Hemati S., Sheisi G.H., Karimi S. Allocation-Based Optimal Reactive Power Dispatch Considering Polynomial Load Model Using Improved Grey Wolf Optimizer. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 2021, vol. 45, no. 3, pp. 921-944. doi: https://doi.org/10.1007/s40998-021-00419-8.
Hasanien H.M., Alsaleh I., Tostado-Véliz M., Zhang M., Alateeq A., Jurado F., Alassaf A. Hybrid particle swarm and sea horse optimization algorithm-based optimal reactive power dispatch of power systems comprising electric vehicles. Energy, 2024, vol. 286, art. no. 129583. doi: https://doi.org/10.1016/j.energy.2023.129583.
Abd-El Wahab A.M., Kamel S., Hassan H.M., Domínguez-García J.L., Nasrat L. Jaya-AEO: An Innovative Hybrid Optimizer for Reactive Power Dispatch Optimization in Power Systems. Electric Power Components and Systems, 2024, vol. 52, no. 4, pp. 509-531. doi: https://doi.org/10.1080/15325008.2023.2227176.
Abd-El Wahab A.M., Kamel S., Sultan H.M., Hassan M.H., Ruiz-Rodríguez F.J. Optimizing reactive power dispatch in electrical networks using a hybrid artificial rabbits and gradient-based optimization. Electrical Engineering, 2024, vol. 106, no. 4, pp. 3823-3851. doi: https://doi.org/10.1007/s00202-023-02188-5.
Shaheen M.A.M., Hasanien H.M., Alkuhayli A. A novel hybrid GWO-PSO optimization technique for optimal reactive power dispatch problem solution. Ain Shams Engineering Journal, 2021, vol. 12, no. 1, pp. 621-630. doi: https://doi.org/10.1016/j.asej.2020.07.011.
Ahmed M.K., Osman M.H., Korovkin N.V. Optimal reactive power dispatch in power system comprising renewable energy sources by means of a multi-objective particle swarm algorithm. Materials Science. Power Engineering, 2021, vol. 27, no. 1, pp. 5-20. doi: https://doi.org/10.18721/JEST.27101.
Hassan M.H., Kamel S., El-Dabah M.A., Khurshaid T., Dominguez-Garcia J.L. Optimal Reactive Power Dispatch With Time-Varying Demand and Renewable Energy Uncertainty Using Rao-3 Algorithm. IEEE Access, 2021, vol. 9, pp. 23264-23283. doi: https://doi.org/10.1109/ACCESS.2021.3056423.
Khan N.H., Wang Y., Tian D., Jamal R., Ebeed M., Deng Q. Fractional PSOGSA Algorithm Approach to Solve Optimal Reactive Power Dispatch Problems With Uncertainty of Renewable Energy Resources. IEEE Access, 2020, vol. 8, pp. 215399-215413. doi: https://doi.org/10.1109/ACCESS.2020.3039571.
Manikandan K., Sasikumar S., Arulraj R. A novelty approach to solve an economic dispatch problem for a renewable integrated micro-grid using optimization techniques. Electrical Engineering & Electromechanics, 2023, no. 4, pp. 83-89. doi: https://doi.org/10.20998/2074-272X.2023.4.12.
Nid A., Sayah S., Zebar A. Power fluctuation suppression for grid connected permanent magnet synchronous generator type wind power generation system. Electrical Engineering & Electromechanics, 2024, no. 5, pp. 70-76. doi: https://doi.org/10.20998/2074-272X.2024.5.10.
Bounechba H., Boussaid A., Bouzid A. Experimental validation of fuzzy logic controller based on voltage perturbation algorithm in battery storage photovoltaic system. Electrical Engineering & Electromechanics, 2024, no. 5, pp. 20-27. doi: https://doi.org/10.20998/2074-272X.2024.5.03.
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