Modelling of the Electric Energy Storage Process in a PCM Battery

被引:2
作者
Karbowniczak, Anna [1 ]
Latala, Hubert [1 ]
Necka, Krzysztof [1 ]
Kurpaska, Slawomir [1 ]
Bergel, Tomasz [2 ]
机构
[1] Agr Univ Krakow, Fac Prod & Power Engn, PL-30149 Krakow, Poland
[2] Agr Univ Krakow, Fac Environm Engn & Land Surveying, PL-30059 Krakow, Poland
关键词
energy storage system; photovoltaic conversion modeling; phase-change battery; PHASE CHANGE SYSTEMS; HEAT-TRANSFER; FORECASTING METHODS; SPECIES TRANSPORT; CONTINUUM MODEL; NEURAL-NETWORK; PERFORMANCE; GENERATION; OPTIMIZATION; METHODOLOGY;
D O I
10.3390/en15030735
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The essence of the research was the modeling of a real electric energy storage system in a phase change battery operating in a foil tunnel. The scope of the work covered the construction of two partial models, i.e., energy storage in the PCM accumulator and heat losses in the PCM accumulator. Their construction was based on modeling methods selected on the basis of a literature review and previous analyses, i.e., artificial neural networks, random forest, enhanced regression trees, MARS plines, standard multiple regression, standard regression trees, exhaustive for regression trees. Based on the analysis of the error values, the models of the best quality were selected. The final result of this study was the construction of such a model of the process of storing electricity in a PCM battery, characterized by the mean absolute percentage error forecast error of 1-2%. The achievement of this goal was possible thanks to the use of the artificial neural networks model for which the input variables were the amount of energy supplied to the accumulator and the temperature of the heat storage medium.
引用
收藏
页数:17
相关论文
共 82 条
[1]   LOW-TEMPERATURE LATENT-HEAT THERMAL-ENERGY STORAGE - HEAT-STORAGE MATERIALS [J].
ABHAT, A .
SOLAR ENERGY, 1983, 30 (04) :313-332
[2]   A review of materials, heat transfer and phase change problem formulation for latent heat thermal energy storage systems (LHTESS) [J].
Agyenim, Francis ;
Hewitt, Neil ;
Eames, Philip ;
Smyth, Mervyn .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2010, 14 (02) :615-628
[3]   Methods of heat transfer intensification in PCM thermal storage systems: Review paper [J].
Al-Maghalseh, Maher ;
Mahkamov, Khamid .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 92 :62-94
[4]   Modeling phase change materials embedded in building enclosure: A review [J].
AL-Saadi, Saleh Nasser ;
Zhai, Zhiqiang .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2013, 21 :659-673
[5]   PV power forecast using a nonparametric PV model [J].
Almeida, Marcelo Pinho ;
Perpinan, Oscar ;
Narvarte, Luis .
SOLAR ENERGY, 2015, 115 :354-368
[6]   A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator [J].
Almonacid, F. ;
Perez-Higueras, P. J. ;
Fernandez, Eduardo F. ;
Hontoria, L. .
ENERGY CONVERSION AND MANAGEMENT, 2014, 85 :389-398
[7]   A method for detailed, short-term energy yield forecasting of photovoltaic installations [J].
Anagnostos, D. ;
Schmidt, T. ;
Cavadias, S. ;
Soudris, D. ;
Poortmans, J. ;
Catthoor, F. .
RENEWABLE ENERGY, 2019, 130 :122-129
[8]  
[Anonymous], PERKINELMER DSC 7
[9]  
[Anonymous], DSC 60 PLUS ADDRESSE
[10]   Review of photovoltaic power forecasting [J].
Antonanzas, J. ;
Osorio, N. ;
Escobar, R. ;
Urraca, R. ;
Martinez-de-Pison, F. J. ;
Antonanzas-Torres, F. .
SOLAR ENERGY, 2016, 136 :78-111