Photovoltaic array performance model.

Kratochvil, J.A.; Boyson, W.E.; King, David L.

doi:10.2172/919131

Cited by 559 publications

(224 citation statements)

References 17 publications

Supporting

Mentioning

190

Contrasting

Unclassified

Order By: Relevance

“…where Isc h (h) is the mean hourly short-circuit current measured per each cell or module, POA is the mean hourly plane of array irradiance, h is the hour, j and k are the hours when the first and last current measurements are taken, and n is the number of hours used for the daily average. Where not available, the POA has been calculated using the hourly values of global horizontal irradiance and angle of incidence, by estimating the direct, the ground-reflected diffuse, and the sky-diffuse components of global horizontal irradiance [15][16][17][18]. The same filtering criteria applied in the previous work [12] have been used in the present study.…”

Section: Soiling Metricsmentioning

confidence: 99%

An investigation of the key parameters for predicting PV soiling losses

Micheli

Muller

2017

Progress in Photovoltaics

128

View full text Add to dashboard Cite

One hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination (R 2 ) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of dry periods had the best correlation with the soiling ratio. A preliminary investigation of two-variable regressions was attempted and resulted in an adjusted R 2 of 0.90 when a combination of PM 2.5 and a binary classification for the average length of the dry period was introduced.

show abstract

Section: Soiling Metricsmentioning

confidence: 99%

An investigation of the key parameters for predicting PV soiling losses

Micheli

Muller

2017

Progress in Photovoltaics

128

View full text Add to dashboard Cite

show abstract

“…The power generated by the PV array is not only dependent on the solar irradiation but also dependent on the ambient temperature of the site. A maximum power point tracker (MPPT) is often used in the PV array to reach the maximum output power at any radiation level [16,17]. The maximum output power at different radiation and temperature is calculated by the following equation:…”

Section: Estimating the Output Power Of Pv Arraymentioning

confidence: 99%

A Simple Sizing Algorithm for Stand-Alone PV/Wind/Battery Hybrid Microgrids

2012

View full text Add to dashboard Cite

In this paper, we develop a simple algorithm to determine the required number of generating units of wind-turbine generator and photovoltaic array, and the associated storage capacity for stand-alone hybrid microgrid. The algorithm is based on the observation that the state of charge of battery should be periodically invariant. The optimal sizing of hybrid microgrid is given in the sense that the life cycle cost of system is minimized while the given load power demand can be satisfied without load rejection. We also report a case study to show the efficacy of the developed algorithm.

show abstract

“…Many studies have showed that the active output of photovoltaic generators could be described as [30]:…”

Section: Output Uncertainty Of Photovoltaic Generatorsmentioning

confidence: 99%

Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Gong¹,

Lei²,

Qiao³

et al. 2017

Sustainability

View full text Add to dashboard Cite

Abstract:The intermittency and variability of permeated distributed generators (DGs) could cause many critical security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. Then, four risk indices-EENS (expected energy not supplied), PLC (probability of load curtailment), EFLC (expected frequency of load curtailment), and SI (severity index)-were established to reflect the system risk level of the distribution system. For the certain mathematical distribution of the DGs' output power, an improved PEM (point estimate method)-based method was proposed to calculate these four system risk indices. In this improved PEM-based method, an enumeration method was used to list the states of distribution systems, and an improved PEM was developed to deal with the uncertainties of DGs, and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by testing a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.

show abstract

Photovoltaic array performance model.

Cited by 559 publications

References 17 publications

An investigation of the key parameters for predicting PV soiling losses

An investigation of the key parameters for predicting PV soiling losses

A Simple Sizing Algorithm for Stand-Alone PV/Wind/Battery Hybrid Microgrids

Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Contact Info

Product

Resources

About