Data-driven inference of unknown tilt and azimuth of distributed PV systems

Meng, Bin; Loonen, Roel C.G.M.; Hensen, Jlm Jan

doi:10.1016/j.solener.2020.09.077

Cited by 27 publications

(11 citation statements)

References 37 publications

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“…Initially, the orientation assessment method by Nespoli and Medici [32] was tested for the reference sites but found to be unsatisfactory. A second method, by Meng et al [33], was tested for both the reference and survey sites, implementing some adjustments for convenience or improved performance. The original method uses one year of PV production data and off-site solar irradiation data.…”

Section: Inference Of Tilt and Azimuthmentioning

confidence: 99%

Snow-Induced PV Loss Modeling Using Production-Data Inferred PV System Models

2021

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Snow-induced photovoltaic (PV)-energy losses (snow losses) in snowy and cold locations vary up to 100% monthly and 34% annually, according to literature. Levels that illustrate the need for snow loss estimation using validated models. However, to our knowledge, all these models build on limited numbers of sites and winter seasons, and with limited climate diversity. To overcome this limitation in underlying statistics, we investigate the estimation of snow losses using a PV system’s yield data together with freely available gridded weather datasets. To develop and illustrate this approach, 263 sites in northern Sweden are studied over multiple winters. Firstly, snow-free production is approximated by identifying snow-free days and using corresponding data to infer tilt and azimuth angles and a snow-free performance model incorporating shading effects, etc. This performance model approximates snow-free monthly yields with an average hourly standard deviation of 6.9%, indicating decent agreement. Secondly, snow losses are calculated as the difference between measured and modeled yield, showing annual snow losses up to 20% and means of 1.5–6.2% for winters with data for at least 89 sites. Thirdly, two existing snow loss estimation models are compared to our calculated snow losses, with the best match showing a correlation of 0.73 and less than 1% bias for annual snow losses. Based on these results, we argue that our approach enables studying snow losses for high numbers of PV systems and winter seasons using existing datasets.

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Section: Inference Of Tilt and Azimuthmentioning

confidence: 99%

Snow-Induced PV Loss Modeling Using Production-Data Inferred PV System Models

2021

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“…Meng et al 33 have introduced curve-matching procedure for obtaining the tilt and azimuth angles of distributed PV systems by the use of available data. The tilt and azimuth angles were very difficult to achievement.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

“…Twice of the year the sunlight falls at as teep angle to the equator is known as equinox. 33 The declination angle is expressed as.…”

Section: Latitude Declination Hour Anglesmentioning

confidence: 99%

Hybrid TSA‐RBFNN based approach for MPPT of the solar PV panel under the effects of tilt angles variations and environmental effects

2021

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This paper proposes a hybrid approach to improve the performance of photovoltaic (PV) system and track the maximum system power. The proposed hybrid approach is the combination of Tunicate Swarm algorithm (TSA) and Radial Basis Function Neural Network (RBFNN), hence it is called TSA-RBFNN. The main contribution of this paper is to "achieve the best output from solar system by tilt angles variations and environmental effects, like dust accumulation, water drops, partial shading, and maximum power point tracking (MPPT) of the solar PV panel. Here, tilt angle and orientation angles are important factor for obtaining the maximal power of the photovoltaic system with consequently the power fed to load in the PV system. The voltage, current, and PV system power are used to analyze the effect of any particle size and any weight of coal for the performance of PV modules. TSA is used to measure the PV module voltage, current, and power, then it generates a possible dataset in the offline way. The dataset has electrical parameters that are used to create a model by using RBFNN in the online way. In addition, the determination of cleaning frequency is also developed for dirty PV modules depending upon the dust deposition velocity, then the correlation among deposited dust density including power performance of photovoltaic module. The proposed method is activated in MATLAB/Simulink site under four different test cases and the efficiency is compared with other existing methods. Furthermore, optimum solutions for proposed technique, the current, voltage, power are also analyzed. In 100 iterations, the first order statistic evaluation for all the cases is obtained using proposed and existing techniques such as ANN, GBDT, SSA, and SSA-GBDT technique. In addition, the dependability, sensitivity, and accuracy of the proposed technique are also obtained. Computation time using various number of trails of proposed and existing techniques is analyzed for 100, 150, 200, 250, and 500 trails. The proposed technique achieves the trail number of 100, 150, 200, 250, and 500 trails is 48.1740 seconds, 51.2133 seconds, 71.0483 seconds, 60.00126 seconds, and 57.80132 seconds.

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“…The orientation of azimuth and tilt angles of PV panels is an essential input for PV performance studies [15]. The orientation of azimuth and tilt angles plays a significant role in promoting the generation efficiency of the PV panels.…”

Section: Azimuth and Tilt Anglesmentioning

confidence: 99%

Orientation-Optimization Simulation for Solar Photovoltaic Plant of Cairo International Airport

Abagy

Emeara

AbdelGawad

2021

The Egyptian International Journal of Engineering Sciences and

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Solar energy is a prompt creating source of energy worldwide. Airports are typically large, shade-free structures and have great areas, which offer the idealistic platform for installing large surfaces of photovoltaic panels generating more than 20 GW/yr. Optimization of the photovoltaic system is a main factor to promote the power conversion efficiency. Solar-radiation amount depends on an essential factor, which is the orientation of the photovoltaic modules. The azimuth and tilt angles for the photovoltaic panels are important factors that impact the receiving of the solar radiation, accordingly have a major influence on the photovoltaic system performance. PVsyst software is an important simulation software for the design of the photovoltaic system. Also, PVsyst enables the calculation of the amount of energy generated. This study provides a proposal for installing a photovoltaic plant in Cairo International Airport. Moreover, the study gives several orientation cases to get the optimal yearly tilt and azimuth angles. The optimal tilt and azimuth angles should be obtained to enhance the annual energy yield. The study also improves the energy generation by carrying out optimization to obtain the dualseasonal optimal tilt angles for summer and winter. The simulation for the energy generation and the orientation-optimization analysis was done by the PVsyst software. The optimization results indicated that the optimal azimuth angle is 0°, the optimal yearly tilt angle is 30°, and the generated energy is around 35 GWh/yr. The optimal dual-seasonal tilt angles are 10° in summer and 50° in winter that maximized the generated energy to be about 36.5 GWh/yr. This optimization study contributes effectively to increase the energy production by installing a photovoltaic plant and using an optimal photovoltaic panel-orientation, as well as being able to save about 50% of Cairo-International-Airport Terminal-Building 3 yearly electrical consumption.

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Data-driven inference of unknown tilt and azimuth of distributed PV systems

Cited by 27 publications

References 37 publications

Snow-Induced PV Loss Modeling Using Production-Data Inferred PV System Models

Snow-Induced PV Loss Modeling Using Production-Data Inferred PV System Models

Hybrid TSA‐RBFNN based approach for MPPT of the solar PV panel under the effects of tilt angles variations and environmental effects

Orientation-Optimization Simulation for Solar Photovoltaic Plant of Cairo International Airport

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