СОВРЕМЕННЫЕ МЕТОДЫ ОТСЛЕЖИВАНИЯ ТОЧКИ МАКСИМАЛЬНОЙ МОЩНОСТИ (ТММ) С ИСПОЛЬЗОВАНИЯ ИСКУССТВЕННОЙ НЕЙРОННОЙ СЕТИ
Keywords:
Искусственная нейронная сеть (ИНС), фотоэлектрическая станция (ФЭС), точка максимальной мощности, солнечный модуль, солнечная батарея (СБ) , фотоэлемент, MPPT контроллеры, Matlab.Abstract
В статье анализируются современные методы нахождения точки максимальной мощности солнечного элемента с помощью искусственной нейронной сети.
References
E. Kabir, P.Kumar,A.A.Adelodun, and K.-H.Kim, “Solar energy: Potential and future prospects,” Renew. Sustain. Energy Rev., vol.82,pp, 894-900,2018.
Колтун М.М., Солнечные элементы/ М.М.Колтун.-Москва: Наука, 1987.-191 с.
J.A.Gow and C.D.Manning, “Development of a photovoltaic array model for use in power-electronics simulation studies,” IEE Proc. – Electr.Power Appl., vol.146, no.2, 193-200, Mar.199.
R.Faranda and S.Leva, “Energy comparison of MPPT techniques fo PV Systems,” J Electromagn Anal Appl, vol.3, Jan.2008.
T. Esram and P.L.Chapman, “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques,” Energy Convers. IEEE Trans. On, vol.22, pp. 439-449, Jul.2007.
F.Sedaghati, A.Nahavandi, M.A.Badamchizadeh, S.Ghaemi, and M.Abedinpour Fallah, “PV Maximum Power-Point Tracking by Using Artifical Neural Network”, Matematical Problem in Engineering, 2012/
R. Rajesh and M.C.Mabel, “Efficency analysis of a multi-fuzzy logic controller for the determination of operating points in a PV system,” Sol. Energy, vol.99, pp.77-87, 2014.
A. E. Khateb, N.A. Rahim, J.Selvaraj, and M.N.Uddin, “Fuzzy-Logic-Controller-Based SEPIC Converter for Maximum Power Point Tracking,” IEEE Trans. Ind. Appl., vol.50, no 4, pp. 2349-2358, Jul.2014.
R.Khanaki.M.A.Mohd Radzi, and M.H.Marhaban, “Artifical Neural Network Based Maximum Power Point Tracking Controller for Photovoltaic Standalone Sytem,” Int. J.Green Energy, vol.13,p. 140516111758009, May 2014.
I.A.Belova, M.V.Martinovich, and V. A. Skolota, “Application of photovoltaic cells with in intelligent control system for railways transport,” in 2016 13th International Scientific – Technical Conference on Actual Problems of Electronics Istrument Engineering (APEIE), Oct. 2016, vol.03,pp. 64-68.
K.Putinha, D.Devaraj, and S.Sakthivel, “Artificial neural network based modified incremental conductance algorithm for maximum power point tracking in photovoltaic system under partial shading conditions,” Energy, vol.62, no. Supplement C, pp. 330-340, Dec.2013.
M.A.A.M.Zainuri, M.A.Radzi, A.C.Soh, and N.A.Rahim, “Development of adaptive perturb and oseve-fuzzy control maximum power point tracking for photovoltaic boost dc-dc converter,” IET Renew. Power Gener., vol.8, no. 2, pp. 183-194, Mart.
A.Chaouachi, R.M.Kamel, and K.Nagasaka, “A novel multi-model neuro-fuzzy-based MPPT for three-phase grid-connected photovoltaic system,” Sol. Energy, vol.84, no.12, pp. 2219-2229, Dec 2010.
