An Arduino Based On-Site Monitoring and Gravitational Search Algorithm Based Parameter Estimation for PV Module
Tóm tắt
Performance monitoring and parameter estimation of a PV module are challenging because of nonlinear module characteristics and variations of environmental factors. In the existing literatures, parameter estimation is mostly done on the standard test condition or in controlled experimental environment. Unlike that, the PV module is exposed to the natural weather conditions in the Himalayan city of Ravangla, India in this work. An on-site data acquisition system using Arduino™ and various sensors is developed for remote monitoring. A gravitational search algorithm based estimation of the PV parameters is proposed and is validated on a 74 W and a 20 W PV modules through extensive results. The proposed method is compared with the existing literatures considering data sets of RTC France cell, Solarland SLP080-12M, PhotoWatt-PWP 201 and different algorithms [e.g., farmland fertility optimization (FFO), enhanced harris hawks optimization (EHHO), artificial bee colony (ABC), variants of particle swarm optimization (PSO), whale optimization (WO), cuckoo search (CS)]. These results show the suitability and improvements by the proposed method.
Tài liệu tham khảo
Agwa AM, El-Fergany AA, Maksoud HA (2020) Electrical characterization of photovoltaic modules using farmland fertility optimizer. Energy Convers Manage 217:112990
Alam D, Yousri D, Eteiba M (2015) Flower pollination algorithm based solar PV parameter estimation. Energy Convers Manage 101:410–422
Bastidas-Rodriguez JD, Franco E, Petrone G, Ramos-Paja CA, Spagnuolo G (2015) Model-based degradation analysis of photovoltaic modules through series resistance estimation. IEEE Trans Ind Electron 62(11):7256–7265
Brano VL, Orioli A, Ciulla G, Di Gangi A (2010) An improved five-parameter model for photovoltaic modules. Sol Energy Mater Sol Cells 94(8):1358–1370
Ćalasan M, Aleem SHA, Zobaa AF (2020) On the root mean square error (RMSE) calculation for parameter estimation of photovoltaic models: a novel exact analytical solution based on Lambert W function. Energy Convers Manage 210:112716
Celik AN, Acikgoz N (2007) Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four-and five-parameter models. Appl Energy 84(1):1–15
Chen X, Yu K, Du W, Zhao W, Liu G (2016a) Parameters identification of solar cell models using generalized oppositional teaching learning based optimization. Energy 99:170–180
Chen Z, Wu L, Lin P, Wu Y, Cheng S (2016b) Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy. Appl Energy 182:47–57
Chen X, Tianfield H, Mei C, Du W, Liu G (2017) Biogeography-based learning particle swarm optimization. Soft Comput 21(24):7519–7541
Chen X, Xu B, Mei C, Ding Y, Li K (2018) Teaching-learning-based artificial bee colony for solar photovoltaic parameter estimation. Appl Energy 212:1578–1588
Chen H, Jiao S, Heidari AA, Wang M, Chen X, Zhao X (2019a) An opposition-based sine cosine approach with local search for parameter estimation of photovoltaic models. Energy Convers Manage 195:927–942
Chen X, Yue H, Yu K (2019b) Perturbed stochastic fractal search for solar PV parameter estimation. Energy 189:116247
Chen Y, Chen Z, Wu L, Long C, Lin P, Cheng S (2019c) Parameter extraction of PV models using an enhanced shuffled complex evolution algorithm improved by opposition-based learning. Energy Procedia 158:991–997
Chen H, Jiao S, Wang M, Heidari AA, Zhao X (2020) Parameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic drifts. J Clean Prod 244:118778
Chenouard R, El-Sehiemy RA (2020) An interval branch and bound global optimization algorithm for parameter estimation of three photovoltaic models. Energy Convers Manage 205:112400
De Blas M, Torres J, Prieto E, Garcıa A (2002) Selecting a suitable model for characterizing photovoltaic devices. Renewable Energy 25(3):371–380
Elazab OS, Hasanien HM, Alsaidan I, Abdelaziz AY, Muyeen S (2020) Parameter estimation of three diode photovoltaic model using grasshopper optimization algorithm. Energies 13(2):497
Ghosh A, Singh O, Ray AK, Nurujjaman M (2018) Gravitational search algorithm optimized state feedback load frequency controller. In: 15th India Council International Conference (INDICON), IEEE, pp 1–6
Gupta V, Sharma M, Pachauri RK, Babu KD (2020) A low-cost real-time IOT enabled data acquisition system for monitoring of PV system. Recovery, Utilization, and Environmental Effects, Energy Sources, Part A, pp 1–16
Jian X, Weng Z (2020) A logistic chaotic JAYA algorithm for parameters identification of photovoltaic cell and module models. Optik 203:164041
Jordehi AR (2018) Enhanced leader particle swarm optimisation (ELPSO): an efficient algorithm for parameter estimation of photovoltaic (PV) cells and modules. Sol Energy 159:78–87
Kang T, Yao J, Jin M, Yang S, Duong T (2018) A novel improved cuckoo search algorithm for parameter estimation of photovoltaic (PV) models. Energies 11(5):1060
Kaplani E, Kaplanis S (2020) PV module temperature prediction at any environmental conditions and mounting configurations. In: Renewable Energy and Sustainable Buildings, Springer, pp 921–933
Liang JJ, Qin AK, Suganthan PN, Baskar S (2006) Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans Evol Comput 10(3):281–295
Messaoud RB (2020) Extraction of uncertain parameters of single and double diode model of a photovoltaic panel using salp swarm algorithm. Measurement 154:107446
Mittal H, Tripathi A, Pandey AC, Pal R (2020) Gravitational search algorithm: a comprehensive analysis of recent variants. Multimedia Tools and Applications pp 1–28
Oladimeji I, Adediji Y, Akintola J, Afolayan M, Ogunbiyi O, Ibrahim S, Olayinka S (2020) Design and construction of an arduino-based solar power parameter-measuring system with data logger. Arid Zone J Eng, Technol Environ 16(2):255–268
Pradhan SS, Pradhan R (2020) An AIA-based parameter extraction method for PV system. In: Advances in Electrical Control and Signal Systems, Springer, pp 997–1008
Premkumar M, Babu TS, Umashankar S, Sowmya R (2020) A new metaphor-less algorithms for the photovoltaic cell parameter estimation. Optik p 164559
Rashedi E, Nezamabadi-Pour H, Saryazdi S (2009) GSA: a gravitational search algorithm. Inf Sci 179(13):2232–2248
Ridha HM, Gomes C, Hizam H (2020) Estimation of photovoltaic module model’s parameters using an improved electromagnetic–like algorithm. Neural Computing and Applications pp 1–16
Sanchez-Pacheco FJ, Sotorrío-Ruiz PJ, Heredia-Larrubia JR, Pérez-Hidalgo F, de Cardona MS (2014) PLC-based PV plants smart monitoring system: field measurements and uncertainty estimation. IEEE Trans Instrum Meas 63(9):2215–2222
Sanchez-Sutil F, Cano-Ortega A, Hernandez J, Rus-Casas C (2019) Development and calibration of an open source, low-cost power smart meter prototype for PV household-prosumers. Electronics 8(8):878
Shen L, Li Z, Ma T (2020) Analysis of the power loss and quantification of the energy distribution in PV module. Appl Energy 260:114333
Shongwe S, Hanif M (2015) Comparative analysis of different single-diode PV modeling methods. IEEE J Photovoltaics 5(3):938–946
Sun R, Wu Q, Guo J, Wang T, Wu Y, Qiu B, Luo Z, Yang W, Hu Z, Guo J, et al. (2020) A layer-by-layer architecture for printable organic solar cells overcoming the scaling lag of module efficiency. Joule
Villalva MG, Gazoli JR, Ruppert Filho E (2009) Comprehensive approach to modeling and simulation of photovoltaic arrays. IEEE Trans Power Electron 24(5):1198–1208
Xiao W, Dunford WG, Capel A (2004) A novel modeling method for photovoltaic cells. In: 35th Annual Power Electronics Specialists Conference, IEEE, vol 3, pp 1950–1956
Xiong G, Zhang J, Shi D, He Y (2018) Parameter extraction of solar photovoltaic models using an improved whale optimization algorithm. Energy Convers Manage 174:388–405
Yu K, Liang J, Qu B, Chen X, Wang H (2017) Parameters identification of photovoltaic models using an improved JAYA optimization algorithm. Energy Convers Manage 150:742–753
Yu K, Qu B, Yue C, Ge S, Chen X, Liang J (2019) A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module. Appl Energy 237:241–257