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Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network

Author

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  • Ebrahim Farjah

    (Department of Power and Control Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran)

  • Mosayeb Bornapour

    (Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran)

  • Taher Niknam

    (Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran)

  • Bahman Bahmanifirouzi

    (Department of Power and Control Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran)

Abstract

This paper presents a new Fuzzy Adaptive Modified Particle Swarm Optimization algorithm (FAMPSO) for the placement of Fuel Cell Power Plants (FCPPs) in distribution systems. FCPPs, as Distributed Generation (DG) units, can be considered as Combined sources of Heat, Power, and Hydrogen (CHPH). CHPH operation of FCPPs can improve overall system efficiency, as well as produce hydrogen which can be stored for the future use of FCPPs or can be sold for profit. The objective functions investigated are minimizing the operating costs of electrical energy generation of distribution substations and FCPPs, minimizing the voltage deviation and minimizing the total emission. In this regard, this paper just considers the placement of CHPH FCPPs while investment cost of devices is not considered. Considering the fact that the objectives are different, non-commensurable and nonlinear, it is difficult to solve the problem using conventional approaches that may optimize a single objective. Moreover, the placement of FCPPs in distribution systems is a mixed integer problem. Therefore, this paper uses the FAMPSO algorithm to overcome these problems. For solving the proposed multi-objective problem, this paper utilizes the Pareto Optimality idea to obtain a set of solution in the multi-objective problem instead of only one. Also, a fuzzy system is used to tune parameters of FAMPSO algorithm such as inertia weight. The efficacy of the proposed approach is validated on a 69-bus distribution system.

Suggested Citation

  • Ebrahim Farjah & Mosayeb Bornapour & Taher Niknam & Bahman Bahmanifirouzi, 2012. "Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network," Energies, MDPI, vol. 5(3), pages 1-25, March.
  • Handle: RePEc:gam:jeners:v:5:y:2012:i:3:p:790-814:d:16740
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    References listed on IDEAS

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    1. Alfredo Iranzo & Felipe Rosa & Javier Pino, 2009. "A Simulation Tool for Geometrical Analysis and Optimization of Fuel Cell Bipolar Plates: Development, Validation and Results," Energies, MDPI, vol. 2(3), pages 1-13, July.
    2. Niknam, Taher & Mojarrad, Hassan Doagou & Nayeripour, Majid, 2010. "A new fuzzy adaptive particle swarm optimization for non-smooth economic dispatch," Energy, Elsevier, vol. 35(4), pages 1764-1778.
    3. Niknam, Taher & Meymand, Hamed Zeinoddini & Mojarrad, Hasan Doagou, 2011. "An efficient algorithm for multi-objective optimal operation management of distribution network considering fuel cell power plants," Energy, Elsevier, vol. 36(1), pages 119-132.
    4. Niknam, Taher, 2010. "A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem," Applied Energy, Elsevier, vol. 87(1), pages 327-339, January.
    5. Niknam, Taher & Taheri, Seyed Iman & Aghaei, Jamshid & Tabatabaei, Sajad & Nayeripour, Majid, 2011. "A modified honey bee mating optimization algorithm for multiobjective placement of renewable energy resources," Applied Energy, Elsevier, vol. 88(12), pages 4817-4830.
    6. Martin Geske & Maik Heuer & Günter Heideck & Zbigniew A. Styczynski, 2010. "Current Density Distribution Mapping in PEM Fuel Cells as An Instrument for Operational Measurements," Energies, MDPI, vol. 3(4), pages 1-14, April.
    7. Shixue Liu & Wei Kong & Zijing Lin, 2009. "A Microscale Modeling Tool for the Design and Optimization of Solid Oxide Fuel Cells," Energies, MDPI, vol. 2(2), pages 1-18, June.
    8. Niknam, Taher & Meymand, Hamed Zeinoddini & Mojarrad, Hasan Doagou, 2011. "A practical multi-objective PSO algorithm for optimal operation management of distribution network with regard to fuel cell power plants," Renewable Energy, Elsevier, vol. 36(5), pages 1529-1544.
    9. Pan Duan & Kaigui Xie & Tingting Guo & Xiaogang Huang, 2011. "Short-Term Load Forecasting for Electric Power Systems Using the PSO-SVR and FCM Clustering Techniques," Energies, MDPI, vol. 4(1), pages 1-12, January.
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    Cited by:

    1. Kumar Mahesh & Perumal Nallagownden & Irraivan Elamvazuthi, 2016. "Advanced Pareto Front Non-Dominated Sorting Multi-Objective Particle Swarm Optimization for Optimal Placement and Sizing of Distributed Generation," Energies, MDPI, vol. 9(12), pages 1-23, November.
    2. Stojiljković, Mirko M., 2017. "Bi-level multi-objective fuzzy design optimization of energy supply systems aided by problem-specific heuristics," Energy, Elsevier, vol. 137(C), pages 1231-1251.
    3. Ran Li & Huizhuo Ma & Feifei Wang & Yihe Wang & Yang Liu & Zenghui Li, 2013. "Game Optimization Theory and Application in Distribution System Expansion Planning, Including Distributed Generation," Energies, MDPI, vol. 6(2), pages 1-24, February.
    4. Arandian, B. & Ardehali, M.M., 2017. "Effects of environmental emissions on optimal combination and allocation of renewable and non-renewable CHP technologies in heat and electricity distribution networks based on improved particle swarm ," Energy, Elsevier, vol. 140(P1), pages 466-480.
    5. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah, 2015. "An efficient scenario-based stochastic programming for optimal planning of combined heat, power, and hydrogen production of molten carbonate fuel cell power plants," Energy, Elsevier, vol. 83(C), pages 734-748.

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