Forecast modeling and performance assessment of solar PV systems

被引:46
|
作者
Ameur, Arechkik [1 ,2 ]
Berrada, Asmae [3 ]
Loudiyi, Khalid [2 ]
Aggour, Mohamed [1 ]
机构
[1] Ibn Tofail Univ, Fac Sci, Kenitra, Morocco
[2] Al Akhawayn Univ, Sch Sci & Engn, Ifrane, Morocco
[3] Int Univ Rabat, Coll Engn, LERMA Lab, Sala El Jadida 11100, Morocco
关键词
Solar radiation; PV; Prediction; Comparison; Performance; LCOE; TECHNOLOGIES;
D O I
10.1016/j.jclepro.2020.122167
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Electricity is converted directly from incident solar energy through photovoltaic systems. This latter is considered an elegant mean of exploiting renewable energy. It contributes significantly to the energy transition by reducing fossil fuel usage. Several studies about photovoltaic (PV) technology have focused on the design of photovoltaic systems or the theory behind them. On the contrary, this paper presents an evaluation of PV systems performance; it investigates the impact of diverse factors on the performance of these PV technologies. The aim of this work is to assess and compare the performance of different PV types including monocrystalline, polycrystalline, and amorphous silicon (Si) systems. Various indices are utilized in this evaluation such as system efficiency, performance ratio, energy output, and capacity factor. The performance analysis was evaluated using real measured data for a period of 5 years. It has shown that polycrystalline-Si technologies have higher performance compared to both monocrystalline-Si and amorphous-Si. This latter has lower conversion efficiency and capacity factor as compared to its counterparts. The performed economic analysis indicates that the most cost-effective system in the investigated Case study is polycrystalline-Si as it has the lowest levelized cost of energy (LCOE) of 0.10 USD/kWh. In addition, a dynamic simulator based on physical resources has been developed using Python to predict the power production of PV systems over one week. The forecast model is based on cloud cover predictions obtained from Dark Sky API. The simulation results are compared to the measured ones. The obtained results demonstrate that the proposed prediction model has high accuracy. The root mean square errors of polycrystalline-Si, monocrystalline-Si, and amorphous-Si are 17.9%, 17%, and 20.4%, respectively. In addition, the mean absolute percentage errors of the aforementioned systems are 5.05%, 4.57%, and 4.35%, respectively. Finally, a detailed analysis comparing the performance of PV systems installed in various regions of Morocco is presented in this paper. The compared systems have the same brand and power capacity.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] Performance of solar PV micro-grid systems: A comparison study
    Wang, Fu
    Zhu, Yingming
    Yan, Jinyue
    RENEWABLE ENERGY INTEGRATION WITH MINI/MICROGRID, 2018, 145 : 570 - 575
  • [42] Performance assessment of a trifunctional system integrating solar PV, solar thermal, and radiative sky cooling
    Hu, Mingke
    Zhao, Bin
    Ao, Xianze
    Ren, Xiao
    Cao, Jingyu
    Wang, Qiliang
    Su, Yuehong
    Pei, Gang
    APPLIED ENERGY, 2020, 260
  • [43] System for performance assessment of solar home systems
    Munoz Maldonado, Yecid Alfonso
    Pinto Calderon, Maria De los Angeles
    Vera Suarez, Carlos Eduardo
    INGENIERIA SOLIDARIA, 2021, 17 (02):
  • [44] Diffuse and direct light solar spectra modeling in PV module performance rating
    Kirn, Blaz
    Topic, Marko
    SOLAR ENERGY, 2017, 150 : 310 - 316
  • [45] Design and Modeling for the Performance Enhancement of Solar Photovoltaic/Thermal (PV/T) Collectors
    Sahlaoui, K.
    Oueslati, H.
    Belkhiria, F.
    Gammoudi, H.
    Ben Mabrouk, S.
    INTERNATIONAL JOURNAL OF AIR-CONDITIONING AND REFRIGERATION, 2020, 28 (02)
  • [46] Modeling and Evaluating the Capacity Credit of PV Solar Systems Using An Analytical Method
    Sulaeman, Samer
    Benidris, Mohammed
    Tian, Yuting
    Mitra, Joydeep
    2016 IEEE/PES TRANSMISSION AND DISTRIBUTION CONFERENCE AND EXPOSITION (T&D), 2016,
  • [47] Perturb and Observe MPPT Algorithm for Solar PV Systems-Modeling and Simulation
    Nedumgatt, Jacob James
    Jayakrishnan, K. B.
    Umashankar, S.
    Vijayakumar, D.
    Kothari, D. P.
    2011 ANNUAL IEEE INDIA CONFERENCE (INDICON-2011): ENGINEERING SUSTAINABLE SOLUTIONS, 2011,
  • [48] Dwarf Mongoose Optimizer for Optimal Modeling of Solar PV Systems and Parameter Extraction
    Moustafa, Ghareeb
    Smaili, Idris H.
    Almalawi, Dhaifallah R.
    Ginidi, Ahmed R.
    Shaheen, Abdullah M.
    Elshahed, Mostafa
    Mansour, Hany S. E.
    ELECTRONICS, 2023, 12 (24)
  • [49] Performance Assessment and Modeling Techniques for Domestic Solar Dryers
    Mahesh Shimpy
    Anil Kumar
    Food Engineering Reviews, 2023, 15 : 525 - 547
  • [50] Performance Assessment and Modeling Techniques for Domestic Solar Dryers
    Shimpy
    Kumar, Mahesh
    Kumar, Anil
    FOOD ENGINEERING REVIEWS, 2023, 15 (03) : 525 - 547