PARTICLE SWARM OPTIMIZATION OF A HEAT PUMP PHOTOVOLTAIC ENERGY SYSTEM
Abstract
This paper presents cost optimization of a heat pump photovoltaic-thermal energy supply system designed to meet heating, cooling and electricity loads of an energy efficient detached family house. Particle Swarm Optimization algorithm (PSO) was applied and discussed in the paper, where geometrical and mathematical algorithm explanation was given. Convergence analysis is done via eigenvaluess in order to avoid cyclical and quasi-cyclic or divergent behavior of the presented. The performance of described optimization method was numerically tested for optimization of an efficient house model with decentralized energy production and compared to the results obtained by generic algorithm optimization. The model assumes bivalent heat pump operation with a gas boiler, and application of roof integrated and façade integrated photovoltaic thermal collectors. Nominal heat pump power and photovoltaic array surface area are set as optimization variables, optimized according to the value of net present value fitness function. The optimal solution showed that 35% of the design load should be covered by the heat pump, and total available south roof area and east façade area should include photovoltaic integration.
This article has been corrected. Link to the correction - DOI: 10.22190/FUWLEP1701101E
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Schneider et all. “Mapping the potential for decentralized energyGeneration based on res in Western Balkans,”Thermal Science11, 037 (2007).
Hiremath, S. Shikha and N. Ravindranath, “Decentralized energy planning; modeling andapplication—a review, ”Renewable and Sustainable Reviews11, 729 (2007).
Goran Jovanovic, Dragoljub Zivkovic, Marko Mancic, Vladana Stankovic, Danica Stankovic, Velimir Stefanović and Petar Mitkovic, A model of a Serbian energy efficient house for decentralized electricity production, J. Renewable Sustainable Energy 5, 041810 (2013);
Ruben Ruiz-Femenia and Jose A. Caballero, A particle swarm optimization for solving NLP/MINLP process synthesis problems,20th European Symposium on Computer Aided Process Engineering – ESCAPE20.
Erdinc, O.; Uzunoglu, M. Optimum design of hybrid renewable energy systems: Overview of different approaches. Renew. Sustain. Energy Rev. 2012, 16, 1412–1425.
R. Bornatico, M. Pfeiffer A.Witzig and L. Guzzella ,Particle Swarm Optimization for the Optimal Sizing of a Solar Thermal Building Installation, Proceedings of the “23rd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems” (ECOS 2010), Lausanne, Switzerland, June 14-17, 2010.
M. Clerc, J. Kennedy, The particle swarm−explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. on Evolutionary Computation, (2002), (1):58-73.
Structure optimization of energy supply systems in tertiary sector buildings. Miguel A. Lozano, Jose´ C. Ramos, Monica Carvalho, Luis M. Serra. 2009, Energy and Buildings, T. 41, str. 1063–1075.
Official Gazette of Rebublic Serbia84, 04 (Ministry of Minings and Energy, Government of the Republic of Serbia, Belgrade, 2004)].
Vladan Karamarkovic, Maja Matejic, Ljiljana Brdarevic, Mirjana Stamenic, Biljana Ramic, Handbook for preparing energy efficiency projects in municipalities, Belgrade, 2008, Ministry for mining and energy of Republic of Serbia
Woodward, M.: Epidemiology: Study Design and Data Analysis. 2nd Ed. Chapman & Hall/CRC; London: pp. 1-849, 2005.
Yu, Y., Su, F-C., Callaghan, B.C., Goutman, S.A., Batterman, S.A. and Feldman, E.L.: Environmental Risk Factors and Amyotrophic Lateral Sclerosis (ALS): A Case-Control Study of ALS in Michigan. 2014. PLoS ONE 9(6): e101186. doi:10.1371/journal.pone.0101186
Zhang Q.G., Zhang, J., Yu, P. and Shen, H.: Environmental and genetic factors associated with congenital microtia: A case-control study in Jiangsu, China, 2004 to 2007. Plast. Reconstr. Surg., Vol. 124, pp.1157–1164, 2009.
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