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HYRES: A Multi-Objective Optimization Tool for Proper Configuration of Renewable Hybrid Energy Systems

Author

Listed:
  • Katheryn Donado

    (Dept. of Electrical and Electronics Engineering, Universidad del Norte, Barranquilla 081007, Colombia)

  • Loraine Navarro

    (Dept. of Electrical and Electronics Engineering, Universidad del Norte, Barranquilla 081007, Colombia)

  • Christian G. Quintero M.

    (Dept. of Electrical and Electronics Engineering, Universidad del Norte, Barranquilla 081007, Colombia)

  • Mauricio Pardo

    (Dept. of Electrical and Electronics Engineering, Universidad del Norte, Barranquilla 081007, Colombia)

Abstract

This paper presents the Hybrid Renewable Energy System (HYRES), a powerful tool to contribute to the viability analysis of energy systems involving renewable generators. HYRES considers various input parameters related to climatic conditions, statistical reliability, and economic views; in addition to offering multi-objective optimizations using Genetic Algorithms (GAs) that have a better cost-benefit ratio than mono-objective optimization, which is the technique used in several commercial systems like HOMER, a worldwide leader in microgrid modeling. The use of intelligent techniques in HYRES allows optimal sizing of hybrid renewable systems with wind and solar energy generators adapted to different conditions and case studies. The elements that affect the system design like buying and selling energy from/to the grid and the use of storage units can be included in system configuration according to the need. Optimization approaches are selectable and include Initial Cost, Life Cycle Cost, Loss of Power Probability, and Loss of Power Supply Probability.

Suggested Citation

  • Katheryn Donado & Loraine Navarro & Christian G. Quintero M. & Mauricio Pardo, 2019. "HYRES: A Multi-Objective Optimization Tool for Proper Configuration of Renewable Hybrid Energy Systems," Energies, MDPI, vol. 13(1), pages 1-20, December.
    • Handle: RePEc:gam:jeners:v:13:y:2019:i:1:p:26-:d:299728
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    References listed on IDEAS

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    2. Kumar Shivam & Jong-Chyuan Tzou & Shang-Chen Wu, 2020. "Multi-Objective Sizing Optimization of a Grid-Connected Solar–Wind Hybrid System Using Climate Classification: A Case Study of Four Locations in Southern Taiwan," Energies, MDPI, vol. 13(10), pages 1-30, May.
    3. Bame, Aaron T. & Furner, Joseph & Hoag, Ian & Mohammadi, Kasra & Powell, Kody & Iverson, Brian D., 2022. "Optimization of solar-coal hybridization for low solar augmentation," Applied Energy, Elsevier, vol. 319(C).
    4. Jean-Michel Clairand & Carlos Álvarez-Bel & Javier Rodríguez-García & Guillermo Escrivá-Escrivá, 2020. "Impact of Electric Vehicle Charging Strategy on the Long-Term Planning of an Isolated Microgrid," Energies, MDPI, vol. 13(13), pages 1-18, July.
    5. Mahmoud M. Gamil & Soichirou Ueda & Akito Nakadomari & Keifa Vamba Konneh & Tomonobu Senjyu & Ashraf M. Hemeida & Mohammed Elsayed Lotfy, 2022. "Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    6. Mariam Gómez Sánchez & Yunesky Masip Macia & Alejandro Fernández Gil & Carlos Castro & Suleivys M. Nuñez González & Jacqueline Pedrera Yanes, 2020. "A Mathematical Model for the Optimization of Renewable Energy Systems," Mathematics, MDPI, vol. 9(1), pages 1-16, December.

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