IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v148y2018icp1116-1139.html
   My bibliography  Save this article

Probabilistic operation cost minimization of Micro-Grid

Author

Listed:
  • Sharma, Sharmistha
  • Bhattacharjee, Subhadeep
  • Bhattacharya, Aniruddha

Abstract

In recent years due to the increasing integration of Renewable Energy Sources (RES) into the Micro-Grid (MG), necessity of Battery Energy Storage (BES) has increased quickly and size of BES plays vital role in this regard. Present paper aims to minimize total operation cost of MG in presence of BES of optimal size, by considering uncertainties present in the MG. Here, 2 m point estimate method (PEM) has been applied to model the uncertainties in load demand, market prices and available power from RES in the MG, as it is computationally efficient and reliable probabilistic method. Moreover, Gram-Charlier expansion is used to provide more accurate probability distribution of MG operation cost. Classical techniques may be applied here to solve the problem, but these techniques may increase complexity of the problem and hence may affect the accuracy. As evolvement of soft computing techniques are not restricted by the complexity of system model, therefore Swine Influenza Model Based Optimization with Quarantine (SIMBO-Q) and Whale Optimization Algorithm (WOA) have been applied here to minimize operation cost of MG. Simulation results obtained by SIMBO-Q and WOA prove the effectiveness of the algorithms. Here incorporation of BES of optimum size reduces operation cost of MG effectively.

Suggested Citation

  • Sharma, Sharmistha & Bhattacharjee, Subhadeep & Bhattacharya, Aniruddha, 2018. "Probabilistic operation cost minimization of Micro-Grid," Energy, Elsevier, vol. 148(C), pages 1116-1139.
    • Handle: RePEc:eee:energy:v:148:y:2018:i:c:p:1116-1139
    DOI: 10.1016/j.energy.2018.01.164
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218301920
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2018.01.164?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation," Applied Energy, Elsevier, vol. 99(C), pages 455-470.
    2. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher & Alizadeh Pahlavani, Mohammad Reza, 2011. "Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source," Energy, Elsevier, vol. 36(11), pages 6490-6507.
    3. Ekren, Orhan & Ekren, Banu Y., 2010. "Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing," Applied Energy, Elsevier, vol. 87(2), pages 592-598, February.
    4. Mohammadi, Sirus & Mozafari, Babak & Solimani, Soodabeh & Niknam, Taher, 2013. "An Adaptive Modified Firefly Optimisation Algorithm based on Hong's Point Estimate Method to optimal operation management in a microgrid with consideration of uncertainties," Energy, Elsevier, vol. 51(C), pages 339-348.
    5. Carta, José A. & Velázquez, Sergio, 2011. "A new probabilistic method to estimate the long-term wind speed characteristics at a potential wind energy conversion site," Energy, Elsevier, vol. 36(5), pages 2671-2685.
    6. Pantoš, Miloš, 2011. "Stochastic optimal charging of electric-drive vehicles with renewable energy," Energy, Elsevier, vol. 36(11), pages 6567-6576.
    7. Fossati, Juan P. & Galarza, Ainhoa & Martín-Villate, Ander & Fontán, Luis, 2015. "A method for optimal sizing energy storage systems for microgrids," Renewable Energy, Elsevier, vol. 77(C), pages 539-549.
    8. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher, 2012. "Multi-operation management of a typical micro-grids using Particle Swarm Optimization: A comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1268-1281.
    9. Niknam, Taher & Golestaneh, Faranak & Malekpour, Ahmadreza, 2012. "Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational," Energy, Elsevier, vol. 43(1), pages 427-437.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chakraborty, Amit & Ray, Saheli, 2023. "Operational cost minimization of a microgrid with optimum battery energy storage system and plug-in-hybrid electric vehicle charging impact using slime mould algorithm," Energy, Elsevier, vol. 278(PA).
    2. Roy, Kallol & Mandal, Kamal Krishna & Mandal, Atis Chandra, 2019. "Ant-Lion Optimizer algorithm and recurrent neural network for energy management of micro grid connected system," Energy, Elsevier, vol. 167(C), pages 402-416.
    3. Ho-Sung Ryu & Mun-Kyeom Kim, 2020. "Two-Stage Optimal Microgrid Operation with a Risk-Based Hybrid Demand Response Program Considering Uncertainty," Energies, MDPI, vol. 13(22), pages 1-25, November.
    4. Mansour-lakouraj, Mohammad & Shahabi, Majid, 2019. "Comprehensive analysis of risk-based energy management for dependent micro-grid under normal and emergency operations," Energy, Elsevier, vol. 171(C), pages 928-943.
    5. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    6. Huiru Zhao & Hao Lu & Bingkang Li & Xuejie Wang & Shiying Zhang & Yuwei Wang, 2020. "Stochastic Optimization of Microgrid Participating Day-Ahead Market Operation Strategy with Consideration of Energy Storage System and Demand Response," Energies, MDPI, vol. 13(5), pages 1-16, March.
    7. Chakraborty, Amit & Ray, Saheli, 2024. "Economic and environmental factors based multi-objective approach for optimizing energy management in a microgrid," Renewable Energy, Elsevier, vol. 222(C).
    8. Ceran, Bartosz, 2019. "The concept of use of PV/WT/FC hybrid power generation system for smoothing the energy profile of the consumer," Energy, Elsevier, vol. 167(C), pages 853-865.
    9. Bishwajit Dey & Fausto Pedro García Márquez & Sourav Kr. Basak, 2020. "Smart Energy Management of Residential Microgrid System by a Novel Hybrid MGWOSCACSA Algorithm," Energies, MDPI, vol. 13(13), pages 1-23, July.
    10. Mo, Qiu & Liu, Fang, 2020. "Modeling and optimization for distributed microgrid based on Modelica language," Applied Energy, Elsevier, vol. 279(C).
    11. Incheol Shin, 2020. "Approximation Algorithm-Based Prosumer Scheduling for Microgrids," Energies, MDPI, vol. 13(21), pages 1-16, November.

    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. Elsied, Moataz & Oukaour, Amrane & Gualous, Hamid & Hassan, Radwan, 2015. "Energy management and optimization in microgrid system based on green energy," Energy, Elsevier, vol. 84(C), pages 139-151.
    2. Firouzmakan, Pouya & Hooshmand, Rahmat-Allah & Bornapour, Mosayeb & Khodabakhshian, Amin, 2019. "A comprehensive stochastic energy management system of micro-CHP units, renewable energy sources and storage systems in microgrids considering demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 355-368.
    3. Izadbakhsh, Maziar & Gandomkar, Majid & Rezvani, Alireza & Ahmadi, Abdollah, 2015. "Short-term resource scheduling of a renewable energy based micro grid," Renewable Energy, Elsevier, vol. 75(C), pages 598-606.
    4. Deihimi, Ali & Keshavarz Zahed, Babak & Iravani, Reza, 2016. "An interactive operation management of a micro-grid with multiple distributed generations using multi-objective uniform water cycle algorithm," Energy, Elsevier, vol. 106(C), pages 482-509.
    5. Rabiee, Abdorreza & Sadeghi, Mohammad & Aghaeic, Jamshid & Heidari, Alireza, 2016. "Optimal operation of microgrids through simultaneous scheduling of electrical vehicles and responsive loads considering wind and PV units uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 721-739.
    6. Ahmad Khan, Aftab & Naeem, Muhammad & Iqbal, Muhammad & Qaisar, Saad & Anpalagan, Alagan, 2016. "A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1664-1683.
    7. Pawan Singh & Baseem Khan, 2017. "Smart Microgrid Energy Management Using a Novel Artificial Shark Optimization," Complexity, Hindawi, vol. 2017, pages 1-22, October.
    8. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    9. Ho-Sung Ryu & Mun-Kyeom Kim, 2020. "Two-Stage Optimal Microgrid Operation with a Risk-Based Hybrid Demand Response Program Considering Uncertainty," Energies, MDPI, vol. 13(22), pages 1-25, November.
    10. Yehia Gad & Hatem Diab & Mahmoud Abdelsalam & Yasser Galal, 2020. "Smart Energy Management System of Environmentally Friendly Microgrid Based on Grasshopper Optimization Technique," Energies, MDPI, vol. 13(19), pages 1-22, September.
    11. Whei-Min Lin & Chia-Sheng Tu & Ming-Tang Tsai, 2015. "Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization," Energies, MDPI, vol. 9(1), pages 1-16, December.
    12. Elattar, Ehab E. & ElSayed, Salah K., 2020. "Probabilistic energy management with emission of renewable micro-grids including storage devices based on efficient salp swarm algorithm," Renewable Energy, Elsevier, vol. 153(C), pages 23-35.
    13. Salah K. ElSayed & Sattam Al Otaibi & Yasser Ahmed & Essam Hendawi & Nagy I. Elkalashy & Ayman Hoballah, 2021. "Probabilistic Modeling and Equilibrium Optimizer Solving for Energy Management of Renewable Micro-Grids Incorporating Storage Devices," Energies, MDPI, vol. 14(5), pages 1-24, March.
    14. Kavousi-Fard, Abdollah & Abunasri, Alireza & Zare, Alireza & Hoseinzadeh, Rasool, 2014. "Impact of plug-in hybrid electric vehicles charging demand on the optimal energy management of renewable micro-grids," Energy, Elsevier, vol. 78(C), pages 904-915.
    15. Danny Espín-Sarzosa & Rodrigo Palma-Behnke & Oscar Núñez-Mata, 2020. "Energy Management Systems for Microgrids: Main Existing Trends in Centralized Control Architectures," Energies, MDPI, vol. 13(3), pages 1-32, January.
    16. Niknam, Taher & Golestaneh, Faranak & Malekpour, Ahmadreza, 2012. "Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational," Energy, Elsevier, vol. 43(1), pages 427-437.
    17. Najibi, Fatemeh & Niknam, Taher & Kavousi-Fard, Abdollah, 2016. "Optimal stochastic management of renewable MG (micro-grids) considering electro-thermal model of PV (photovoltaic)," Energy, Elsevier, vol. 97(C), pages 444-459.
    18. Ben Christopher, S.J. & Carolin Mabel, M., 2020. "A bio-inspired approach for probabilistic energy management of micro-grid incorporating uncertainty in statistical cost estimation," Energy, Elsevier, vol. 203(C).
    19. Azizipanah-Abarghooee, Rasoul & Niknam, Taher & Roosta, Alireza & Malekpour, Ahmad Reza & Zare, Mohsen, 2012. "Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method," Energy, Elsevier, vol. 37(1), pages 322-335.
    20. Syed Ali Abbas Kazmi & Muhammad Khuram Shahzad & Akif Zia Khan & Dong Ryeol Shin, 2017. "Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective," Energies, MDPI, vol. 10(4), pages 1-47, April.

    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:eee:energy:v:148:y:2018:i:c:p:1116-1139. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.