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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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
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