Simple procedure for generating sequences of daily radiation values using a library of Markov transition matrices

Aguiar, R.; Collares-Pereira, Manuel; Conde, J.P.

doi:10.1016/0038-092x(88)90049-7

Cited by 230 publications

(145 citation statements)

References 11 publications

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“…Uniformly distributed random sampling of a transition from a current state to the next state is proposed in [2][3][4][5]. This study applies this random sampling to the proposed MCMC simulation that synthesizes rapid variations in the generation output of geographically distributed PV systems in minute intervals.…”

Section: Markov Chain Monte Carlomentioning

confidence: 99%

“…Since the supports of the two densities to be compared are approximately equal, the difference among them depends only on their shape. Figure 12: Wavelet-based correlation between units (1,2) in black, (1,3) in green, and (1,4) in red. The distances between the pairs are distance 1.14, 2.4, and 3.7 deg, respectively.…”

Section: Assessment Of Dissimilarities In Daily Short Term Productionmentioning

confidence: 99%

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Impact of Short-Term Variations in the Generation Output of Geographically Dispersed PV Systems

Begović

Kim

Vidakovic³

et al. 2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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Section: Markov Chain Monte Carlomentioning

confidence: 99%

Section: Assessment Of Dissimilarities In Daily Short Term Productionmentioning

confidence: 99%

Impact of Short-Term Variations in the Generation Output of Geographically Dispersed PV Systems

Begović

Kim

Vidakovic³

et al. 2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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“…Collares-Pereira and Rabl 9,10 Horizontal to tilted irradiation Whillier, Liu and Jordan 11,12 Hourly irradiance from daily values Pérez 13,14 Diffuse irradiance Lorenzo 15 Hourly ambient temperatures from daily min and max values Single-exponential [16][17] Current and cell voltage Copetti 8 Battery's charge and discharge voltages Jantsch and Schmid 18 Inverter's efficiency Some particular features of this application deserve further comment. On the one hand, the PV generator model, 16 valid only for crystalline Si technology, assumes the effect of parallel resistance to be negligible, while the series resistance R SG is related to the rated fill factor, FF * , by:…”

Section: Modelling the Battery Voltage Distributionmentioning

confidence: 99%

The battery voltage distribution: a possible tool for surveying the state of health of stand-alone PV systems

Lorenzo

Labed

2005

Prog. Photovolt: Res. Appl.

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Degradation phenomena can remain unnoticed over long periods in stand-alone PV systems, before eventually causing service interruption. Problems include battery capacity reduction because of ageing, PV array capacity reduction because of wiring corrosion or excessive dirtiness, and mis-adjustment of controller set-points. This underlines the practical interest of an easily applicable method of early detection, so that preventive measures can be taken in good time.This paper proposes the use of the battery voltage distribution, as a tool for surveying the state of health of stand-alone PV systems. Expected distributions can be derived by judicious modelling; while observed distributions can easily be obtained from systematic voltage measurements which are already made in many PV systems worldwide. Comparison between expected and observed distributions allows relatively simple diagnosis rules to be derived.

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“…To simulate a PV system one needs at least 10 years of daily data, to take account of the probability distribution of solar irradiation. Then, a sequence of daily clarity indices is generated from a library of Markov transition matrices, as proposed by Aguiar et al 19 The split of total daily irradiation on a horizontal surface into its beam and diffuse component is carried out, according to the correlation proposed by Collares-Pereira and Rabl. 20 It is convenient to deal with hourly values, because the behaviour of static concentrators varies during the day.…”

Section: Estimation Of Hourly Irradiationmentioning

confidence: 99%

“…Equation (19) relates the cell area and entry aperture area to front and rear efficiency, respectively.…”

Section: Estimation Of Hourly Irradiationmentioning

confidence: 99%

Optimisation of an asymmetric static concentrator: the PEC‐44D

Zanesco

Lorenzo

2002

Progress in Photovoltaics

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In this paper, the optimisation of the PV static concentrator module PEC-44D for constant demand during the year is presented. The method used is based on simulation of the system performance during 10 years and the set of concentrator parameters that produces the lowest cost of the PV array is determined. We find that the optimised PEC-44D module can be 38% cheaper than a standard module. Experimental results were obtained for a prototype of the optimised PEC-44D to validate the theoretical analysis of the behaviour of the concentrator. We conclude that the daily irradiation measured on the cells correlates well with calculated values, and that the operating temperature of the bifacial cells in this static concentrator is slightly lower than that of the monofacial cells in a standard module.

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Simple procedure for generating sequences of daily radiation values using a library of Markov transition matrices

Cited by 230 publications

References 11 publications

Impact of Short-Term Variations in the Generation Output of Geographically Dispersed PV Systems

Impact of Short-Term Variations in the Generation Output of Geographically Dispersed PV Systems

The battery voltage distribution: a possible tool for surveying the state of health of stand-alone PV systems

Optimisation of an asymmetric static concentrator: the PEC‐44D

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