IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i17p6157-d1224085.html
   My bibliography  Save this article

Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System

Author

Listed:
  • Chandu Valuva

    (Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur 603203, India)

  • Subramani Chinnamuthu

    (Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur 603203, India)

Abstract

Transmission line losses are a crucial and essential issue in stable power system operation. Numerous methodologies and techniques prevail for minimizing losses. Subsequently, Flexible Alternating Current Transmission Systems (FACTSs) efficiently reduce transmission losses, and the Unified Power Flow Controller (UPFC) is a reactive power compensation controller. The parameter strength of the proportional–integral (PI) controller was calibrated with the Marine Predator Algorithm (MPA), a recent metaheuristic algorithm. An MPA-based optimum PI controller with a UPFC evaluates the optimal location of the UPFC and PI controller parameters to accomplish the desired research objective. The power rating of the UPFC was determined depending on the voltage collapse rating and power loss and an evaluated performance analysis of the MPA–PI-controlled UPFC on a modified IEEE-30 bus transmission network in MATLAB Simulink code. The Newton–Raphson method was used to perform the load flow analysis. Hence, the proposed MPA–PI controller was examined in contrast to preferred heuristic algorithms, the Artificial Bee Colony (ABC) and Moth Flame Optimization algorithms (MFO); the results showed that the MPA–PI controller exhibited better performance with an improved voltage profile and surpasses active power losses with the optimal placement of the UPFC device under different loading conditions. The active power loss, considering a UPFC with the proposed algorithm, reduced from 0.0622 p.u to 0.0301 p.u; consequently, the voltage profile was improved in the respective buses, and the loss percentage reduction during a 100% base load was 68.39%, which was comparatively better than the ABC and MFO algorithms.

Suggested Citation

  • Chandu Valuva & Subramani Chinnamuthu, 2023. "Performance Analysis of Marine-Predator-Algorithm-Based Optimum PI Controller with Unified Power Flow Controller for Loss Reduction in Wind–Solar Integrated System," Energies, MDPI, vol. 16(17), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6157-:d:1224085
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/17/6157/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/17/6157/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Reddy, S. Surender, 2017. "Optimal scheduling of thermal-wind-solar power system with storage," Renewable Energy, Elsevier, vol. 101(C), pages 1357-1368.
    2. Martin Ćalasan & Tatjana Konjić & Katarina Kecojević & Lazar Nikitović, 2020. "Optimal Allocation of Static Var Compensators in Electric Power Systems," Energies, MDPI, vol. 13(12), pages 1-24, June.
    3. Sharif, Arshian & Raza, Syed Ali & Ozturk, Ilhan & Afshan, Sahar, 2019. "The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: A global study with the application of heterogeneous panel estimations," Renewable Energy, Elsevier, vol. 133(C), pages 685-691.
    4. Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh & Entezariharsini, Azam, 2018. "Power fluctuation smoothing and loss reduction in grid integrated with thermal-wind-solar-storage units," Energy, Elsevier, vol. 152(C), pages 759-769.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hossain, Mohammad Razib & Singh, Sanjeet & Sharma, Gagan Deep & Apostu, Simona-Andreea & Bansal, Pooja, 2023. "Overcoming the shock of energy depletion for energy policy? Tracing the missing link between energy depletion, renewable energy development and decarbonization in the USA," Energy Policy, Elsevier, vol. 174(C).
    2. Namahoro, J.P. & Wu, Q. & Su, H., 2023. "Wind energy, industrial-economic development and CO2 emissions nexus: Do droughts matter?," Energy, Elsevier, vol. 278(PA).
    3. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    4. Łukasz Nazarko & Eigirdas Žemaitis & Łukasz Krzysztof Wróblewski & Karel Šuhajda & Magdalena Zajączkowska, 2022. "The Impact of Energy Development of the European Union Euro Area Countries on CO 2 Emissions Level," Energies, MDPI, vol. 15(4), pages 1-12, February.
    5. Aruna Kanagaraj & Kumudini Devi Raguru Pandu, 2020. "Investigations of Various Market Models in a Deregulated Power Environment Using ACOPF," Energies, MDPI, vol. 13(9), pages 1-17, May.
    6. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization," Renewable Energy, Elsevier, vol. 191(C), pages 459-492.
    7. Monteiro, Raul V.A. & Guimarães, Geraldo C. & Silva, Fernando Bento & da Silva Teixeira, Raoni F. & Carvalho, Bismarck C. & Finazzi, Antônio de P. & de Vasconcellos, Arnulfo B., 2018. "A medium-term analysis of the reduction in technical losses on distribution systems with variable demand using artificial neural networks: An Electrical Energy Storage approach," Energy, Elsevier, vol. 164(C), pages 1216-1228.
    8. Stylianos A. Papazis, 2022. "Integrated Economic Optimization of Hybrid Thermosolar Concentrating System Based on Exact Mathematical Method," Energies, MDPI, vol. 15(19), pages 1-22, September.
    9. Peng, Benhong & Zhao, Yinyin & Elahi, Ehsan & Wan, Anxia, 2023. "Can third-party market cooperation solve the dilemma of emissions reduction? A case study of energy investment project conflict analysis in the context of carbon neutrality," Energy, Elsevier, vol. 264(C).
    10. Yi, Yuxin & Zhang, Liming & Du, Lei & Sun, Helin, 2024. "Cross-regional integration of renewable energy and corporate carbon emissions: Evidence from China's cross-regional surplus renewable energy spot trading pilot," Energy Economics, Elsevier, vol. 135(C).
    11. Héctor F. Salazar-Núñez & Francisco Venegas-Martínez & José Antonio Lozano-Díez, 2022. "Assessing the interdependence among renewable and non-renewable energies, economic growth, and CO2 emissions in Mexico," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(11), pages 12850-12866, November.
    12. Xu, Jiuping & Wang, Fengjuan & Lv, Chengwei & Huang, Qian & Xie, Heping, 2018. "Economic-environmental equilibrium based optimal scheduling strategy towards wind-solar-thermal power generation system under limited resources," Applied Energy, Elsevier, vol. 231(C), pages 355-371.
    13. Rashid Khan, Haroon Ur & Islam, Talat & Yousaf, Sheikh Usman & Zaman, Khalid & Shoukry, Alaa Mohamd & Sharkawy, Mohamed A. & Gani, Showkat & Aamir, Alamzeb & Hishan, Sanil S., 2019. "The impact of financial development indicators on natural resource markets: Evidence from two-step GMM estimator," Resources Policy, Elsevier, vol. 62(C), pages 240-255.
    14. Shiyu Wu & Xinyi Li & Xiaosen Du & Zexin Li, 2022. "The Impact of ESG Performance on Firm Value: The Moderating Role of Ownership Structure," Sustainability, MDPI, vol. 14(21), pages 1-22, November.
    15. Sukono Sukono & Wahyuddin Albra & T. Zulham & Iskandarsyah Majid & Jumadil Saputra & Betty Subartini & Friscila Thalia, 2019. "The Effect of Gross Domestic Product and Population Growth on CO2 Emissions in Indonesia: An Application of the Ant Colony Optimisation Algorithm and Cobb-Douglas Model," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 313-319.
    16. Abdul Rehman & Hengyun Ma & Magdalena Radulescu & Crenguta Ileana Sinisi & Loredana Maria Paunescu & MD Shabbir Alam & Rafael Alvarado, 2021. "The Energy Mix Dilemma and Environmental Sustainability: Interaction among Greenhouse Gas Emissions, Nuclear Energy, Urban Agglomeration, and Economic Growth," Energies, MDPI, vol. 14(22), pages 1-21, November.
    17. Erfan Mohagheghi & Mansour Alramlawi & Aouss Gabash & Pu Li, 2018. "A Survey of Real-Time Optimal Power Flow," Energies, MDPI, vol. 11(11), pages 1-20, November.
    18. Karaaslan, Abdulkerim & Çamkaya, Serhat, 2022. "The relationship between CO2 emissions, economic growth, health expenditure, and renewable and non-renewable energy consumption: Empirical evidence from Turkey," Renewable Energy, Elsevier, vol. 190(C), pages 457-466.
    19. Ehigiamusoe, Kizito Uyi & Dogan, Eyup, 2022. "The role of interaction effect between renewable energy consumption and real income in carbon emissions: Evidence from low-income countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    20. Sultan Salem & Noman Arshed & Ahsan Anwar & Mubasher Iqbal & Nyla Sattar, 2021. "Renewable Energy Consumption and Carbon Emissions—Testing Nonlinearity for Highly Carbon Emitting Countries," Sustainability, MDPI, vol. 13(21), pages 1-17, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6157-:d:1224085. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.