IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i10p1536-d114005.html
   My bibliography  Save this article

Probabilistic Load-Flow Analysis of Biomass-Fuelled Gas Engines with Electrical Vehicles in Distribution Systems

Author

Listed:
  • Francisco J. Ruiz-Rodríguez

    (Electrical and Thermal Engineering Department, University of Huelva, 21004 Huelva, Spain)

  • Jesús C. Hernández

    (Department of Electrical Engineering, University of Jaén, 23071 Jaén, Spain)

  • Francisco Jurado

    (Department of Electrical Engineering, University of Jaén, 23071 Jaén, Spain)

Abstract

Feeding biomass-fueled gas engines (BFGEs) with olive tree pruning residues offers new opportunities to decrease fossil fuel use in road vehicles and electricity generation. BFGEs, coupled to radial distribution systems (RDSs), provide renewable energy and power that can feed electric vehicle (EV) charging stations. However, the combined impact of BFGEs and EVs on RDSs must be assessed to assure the technical constraint fulfilment. Because of the stochastic nature of source/load, it was decided that a probabilistic approach was the most viable option for this assessment. Consequently, this research developed an analytical technique to evaluate the technical constraint fulfilment in RDSs with this combined interaction. The proposed analytical technique (PAT) involved the calculation of cumulants and the linearization of load-flow equations, along with the application of the cumulant method, and Cornish-Fisher expansion. The uncertainties related to biomass stock and its heating value (HV) were important factors that were assessed for the first time. Application of the PAT in a Spanish RDS with BFGEs and EVs confirmed the feasibility of the proposal and its additional benefits. Specifically, BFGEs were found to clearly contribute to the voltage constraint fulfilment. The computational cost of the PAT was lower than that associated with Monte-Carlo simulations (MCSs).

Suggested Citation

  • Francisco J. Ruiz-Rodríguez & Jesús C. Hernández & Francisco Jurado, 2017. "Probabilistic Load-Flow Analysis of Biomass-Fuelled Gas Engines with Electrical Vehicles in Distribution Systems," Energies, MDPI, vol. 10(10), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:10:p:1536-:d:114005
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/10/1536/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/10/1536/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ruiz-Arias, J.A. & Terrados, J. & Pérez-Higueras, P. & Pozo-Vázquez, D. & Almonacid, G., 2012. "Assessment of the renewable energies potential for intensive electricity production in the province of Jaén, southern Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2994-3001.
    2. Ahmadian, Ali & Sedghi, Mahdi & Aliakbar-Golkar, Masoud & Elkamel, Ali & Fowler, Michael, 2016. "Optimal probabilistic based storage planning in tap-changer equipped distribution network including PEVs, capacitor banks and WDGs: A case study for Iran," Energy, Elsevier, vol. 112(C), pages 984-997.
    3. Vera, David & Carabias, Julio & Jurado, Francisco & Ruiz-Reyes, Nicolás, 2010. "A Honey Bee Foraging approach for optimal location of a biomass power plant," Applied Energy, Elsevier, vol. 87(7), pages 2119-2127, July.
    4. Zhou, Bowen & Littler, Tim & Meegahapola, Lasantha & Zhang, Huaguang, 2016. "Power system steady-state analysis with large-scale electric vehicle integration," Energy, Elsevier, vol. 115(P1), pages 289-302.
    5. Shabani, Nazanin & Akhtari, Shaghaygh & Sowlati, Taraneh, 2013. "Value chain optimization of forest biomass for bioenergy production: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 299-311.
    6. Eduardo Valsera-Naranjo & Andreas Sumper & Roberto Villafafila-Robles & David Martínez-Vicente, 2012. "Probabilistic Method to Assess the Impact of Charging of Electric Vehicles on Distribution Grids," Energies, MDPI, vol. 5(5), pages 1-29, May.
    7. Sajdak, M. & Velázquez-Martí, B. & López-Cortés, I., 2014. "Quantitative and qualitative characteristics of biomass derived from pruning Phoenix canariensis hort. ex Chabaud. and Phoenix dactilifera L," Renewable Energy, Elsevier, vol. 71(C), pages 545-552.
    8. Velázquez-Martí, B. & Fernández-González, E. & López-Cortés, I. & Salazar-Hernández, D.M., 2011. "Quantification of the residual biomass obtained from pruning of trees in Mediterranean almond groves," Renewable Energy, Elsevier, vol. 36(2), pages 621-626.
    9. Ilaria Zambon & Fabrizio Colosimo & Danilo Monarca & Massimo Cecchini & Francesco Gallucci & Andrea Rosario Proto & Richard Lord & Andrea Colantoni, 2016. "An Innovative Agro-Forestry Supply Chain for Residual Biomass: Physicochemical Characterisation of Biochar from Olive and Hazelnut Pellets," Energies, MDPI, vol. 9(7), pages 1-11, July.
    10. Vargas-Moreno, J.M. & Callejón-Ferre, A.J. & Pérez-Alonso, J. & Velázquez-Martí, B., 2012. "A review of the mathematical models for predicting the heating value of biomass materials," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3065-3083.
    11. Svensson, Elin & Strömberg, Ann-Brith & Patriksson, Michael, 2011. "A model for optimization of process integration investments under uncertainty," Energy, Elsevier, vol. 36(5), pages 2733-2746.
    12. Pol Olivella-Rosell & Roberto Villafafila-Robles & Andreas Sumper & Joan Bergas-Jané, 2015. "Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks," Energies, MDPI, vol. 8(5), pages 1-28, May.
    13. Svensson, Elin & Berntsson, Thore, 2011. "Planning future investments in emerging energy technologies for pulp mills considering different scenarios for their investment cost development," Energy, Elsevier, vol. 36(11), pages 6508-6519.
    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. Smarajit Ghosh & Vinod Karar, 2018. "Assimilation of Optimal Sized Hybrid Photovoltaic-Biomass System by Dragonfly Algorithm with Grid," Energies, MDPI, vol. 11(7), pages 1-19, July.
    2. Yi, Tao & Cheng, Xiaobin & Chen, Yaxuan & Liu, Jinpeng, 2020. "Joint optimization of charging station and energy storage economic capacity based on the effect of alternative energy storage of electric vehicle," Energy, Elsevier, vol. 208(C).
    3. Ali M. Hakami & Kazi N. Hasan & Mohammed Alzubaidi & Manoj Datta, 2022. "A Review of Uncertainty Modelling Techniques for Probabilistic Stability Analysis of Renewable-Rich Power Systems," Energies, MDPI, vol. 16(1), pages 1-26, December.
    4. Benjamin Böckl & Matthias Greiml & Lukas Leitner & Patrick Pichler & Lukas Kriechbaum & Thomas Kienberger, 2019. "HyFlow—A Hybrid Load Flow-Modelling Framework to Evaluate the Effects of Energy Storage and Sector Coupling on the Electrical Load Flows," Energies, MDPI, vol. 12(5), pages 1-25, March.
    5. Jin-Xin Ou-Yang & Xiao-Xuan Long & Xue Du & Yan-Bo Diao & Meng-Yang Li, 2019. "Voltage Control Method for Active Distribution Networks Based on Regional Power Coordination," Energies, MDPI, vol. 12(22), pages 1-23, November.
    6. Yongchun Yang & Xiaodan Wang & Jingjing Luo & Jie Duan & Yajing Gao & Hong Li & Xiangning Xiao, 2017. "Multi-Objective Coordinated Planning of Distributed Generation and AC/DC Hybrid Distribution Networks Based on a Multi-Scenario Technique Considering Timing Characteristics," Energies, MDPI, vol. 10(12), pages 1-29, December.
    7. Paulo M. De Oliveira-De Jesus & Mario A. Rios & Gustavo A. Ramos, 2018. "Energy Loss Allocation in Smart Distribution Systems with Electric Vehicle Integration," Energies, MDPI, vol. 11(8), pages 1-19, July.
    8. Christian Thiel & Andreea Julea & Beatriz Acosta Iborra & Nerea De Miguel Echevarria & Emanuela Peduzzi & Enrico Pisoni & Jonatan J. Gómez Vilchez & Jette Krause, 2019. "Assessing the Impacts of Electric Vehicle Recharging Infrastructure Deployment Efforts in the European Union," Energies, MDPI, vol. 12(12), pages 1-23, June.
    9. Ziqiang Zhou & Fei Tang & Dichen Liu & Chenxu Wang & Xin Gao, 2020. "Probabilistic Assessment of Distribution Network with High Penetration of Distributed Generators," Sustainability, MDPI, vol. 12(5), pages 1-20, February.
    10. Arman Oshnoei & Rahmat Khezri & Mehrdad Tarafdar Hagh & Kuaanan Techato & SM Muyeen & Omid Sadeghian, 2018. "Direct Probabilistic Load Flow in Radial Distribution Systems Including Wind Farms: An Approach Based on Data Clustering," Energies, MDPI, vol. 11(2), pages 1-19, February.
    11. Kegang Zhao & Jinghao Bei & Yanwei Liu & Zhihao Liang, 2019. "Development of Global Optimization Algorithm for Series-Parallel PHEV Energy Management Strategy Based on Radau Pseudospectral Knotting Method," Energies, MDPI, vol. 12(17), pages 1-23, August.

    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. Shabani, Nazanin & Akhtari, Shaghaygh & Sowlati, Taraneh, 2013. "Value chain optimization of forest biomass for bioenergy production: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 299-311.
    2. Hernández, J.C. & Ruiz-Rodriguez, F.J. & Jurado, F., 2017. "Modelling and assessment of the combined technical impact of electric vehicles and photovoltaic generation in radial distribution systems," Energy, Elsevier, vol. 141(C), pages 316-332.
    3. Abasian, Foroogh & Rönnqvist, Mikael & Ouhimmou, Mustapha, 2019. "Forest bioenergy network design under market uncertainty," Energy, Elsevier, vol. 188(C).
    4. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.
    5. Buzna, Luboš & De Falco, Pasquale & Ferruzzi, Gabriella & Khormali, Shahab & Proto, Daniela & Refa, Nazir & Straka, Milan & van der Poel, Gijs, 2021. "An ensemble methodology for hierarchical probabilistic electric vehicle load forecasting at regular charging stations," Applied Energy, Elsevier, vol. 283(C).
    6. Arias, Mariz B. & Kim, Myungchin & Bae, Sungwoo, 2017. "Prediction of electric vehicle charging-power demand in realistic urban traffic networks," Applied Energy, Elsevier, vol. 195(C), pages 738-753.
    7. Nunes, L.J.R. & Matias, J.C.O. & Catalão, J.P.S., 2017. "Biomass in the generation of electricity in Portugal: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 373-378.
    8. Durusut, Emrah & Tahir, Foaad & Foster, Sam & Dineen, Denis & Clancy, Matthew, 2018. "BioHEAT: A policy decision support tool in Ireland’s bioenergy and heat sectors," Applied Energy, Elsevier, vol. 213(C), pages 306-321.
    9. Arias, Mariz B. & Bae, Sungwoo, 2016. "Electric vehicle charging demand forecasting model based on big data technologies," Applied Energy, Elsevier, vol. 183(C), pages 327-339.
    10. Svensson, Elin & Berntsson, Thore, 2014. "The effect of long lead times for planning of energy efficiency and biorefinery technologies at a pulp mill," Renewable Energy, Elsevier, vol. 61(C), pages 12-16.
    11. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
    12. Yvenn Amara-Ouali & Yannig Goude & Pascal Massart & Jean-Michel Poggi & Hui Yan, 2021. "A Review of Electric Vehicle Load Open Data and Models," Energies, MDPI, vol. 14(8), pages 1-35, April.
    13. Bergthorson, Jeffrey M. & Thomson, Murray J., 2015. "A review of the combustion and emissions properties of advanced transportation biofuels and their impact on existing and future engines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1393-1417.
    14. Mobini, Mahdi & Sowlati, Taraneh & Sokhansanj, Shahab, 2011. "Forest biomass supply logistics for a power plant using the discrete-event simulation approach," Applied Energy, Elsevier, vol. 88(4), pages 1241-1250, April.
    15. Gao, Evelyn & Sowlati, Taraneh & Akhtari, Shaghaygh, 2019. "Profit allocation in collaborative bioenergy and biofuel supply chains," Energy, Elsevier, vol. 188(C).
    16. Xuejun Qian & Jingwen Xue & Yulai Yang & Seong W. Lee, 2021. "Thermal Properties and Combustion-Related Problems Prediction of Agricultural Crop Residues," Energies, MDPI, vol. 14(15), pages 1-18, July.
    17. Julia Vopava & Christian Koczwara & Anna Traupmann & Thomas Kienberger, 2019. "Investigating the Impact of E-Mobility on the Electrical Power Grid Using a Simplified Grid Modelling Approach," Energies, MDPI, vol. 13(1), pages 1-23, December.
    18. Aina Maimó-Far & Alexis Tantet & Víctor Homar & Philippe Drobinski, 2020. "Predictable and Unpredictable Climate Variability Impacts on Optimal Renewable Energy Mixes: The Example of Spain," Energies, MDPI, vol. 13(19), pages 1-25, October.
    19. María Pilar González-Vázquez & Roberto García & Covadonga Pevida & Fernando Rubiera, 2017. "Optimization of a Bubbling Fluidized Bed Plant for Low-Temperature Gasification of Biomass," Energies, MDPI, vol. 10(3), pages 1-16, March.
    20. Deboni, Tamires Liza & Simioni, Flávio José & Brand, Martha Andreia & Costa, Valdeci José, 2019. "Models for estimating the price of forest biomass used as an energy source: A Brazilian case," Energy Policy, Elsevier, vol. 127(C), pages 382-391.

    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:10:y:2017:i:10:p:1536-:d:114005. 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.