Methodology

Solargis PV simulation

Photovoltaic power production is simulated using numerical models developed and implemented by Solargis. Data and model quality is checked according to recommendation of IEA SHC Task 36 and EU FP6 project MESoR standards.

By simulating different situations using historic, recent or forecasted weather data, the results may be used respectively for:

  • Planning phase. Using the available data period long-term expected values can be calculated, as well as minimum-achievable values in case a full study on uncertainty is done.
  • Operational phase. Recent data can be used for performance assessment analysis. Production forecast can be also calculated for energy management optimization.

Factors affecting plant performance

There are a number of factors affecting PV module performance, which in Solargis are implemented in the computation process in various steps.  The simulation of the production is based on the provided technical details and assumptions. In PV simulation, the energy losses can be classified in two groups:

  • Static: module surface pollution, losses in cables, and mismatch between PV modules
  • Dynamic: these losses depend on the irradiance/temperature conditions, which change over the day and over the seasons.

 

Global irradiation on the tilted surface of PV modules

Global irradiation impinging on a tilted plane of PV modules is calculated from Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), terrain albedo, and instantaneous sun position within subhourly time interval.

GTI = fDIFF (GHI, DNI, SE, SA, Albedo)

 

Losses due to terrain shading

Shading by terrain features is calculated by disaggregation using SRTM-3 DEM and horizon height. For open space systems the uncertainty of this estimate is very low due to high resolution of DEM (~80 m). For urban areas, where shading is mainly influenced by buildings, an additional analysis must be undertaken.

GTISHADED = fSHAD (GTI,SE, SA, Horizon)

 

Losses due to angular reflectivity

The magnitude of effects depends on relative position of the sun and plane of the module. The accuracy of calculations of angular reflectivity losses depends on cleanness and specific properties of the module surface (antireflection coating, texture, etc.).

GTIANGULAR = fANGULAR (GTISHADED, SE, SA)

 

Losses due to snow

Losses of solar radiation during winter months are increased by snow on the modules. Typically snow remains on the modules surface from the morning hours to the noon. The highest negative impact on the production has snowfall during cold, cloudy days, when the temperature of the modules is not high enough to melt the snow.

 

Losses due to dirt and soiling

Depends mainly on the environmental factors and cleaning of the PV modules surface during the power plant lifetime. The longterm effects are not satisfactorily known. This is especially valid for dry seasons of the year.

 

Losses due to performance of PV modules outside of STC conditions

Global irradiation reaching modules of the given type along with the air temperature are the input parameters to the PV performance model. The conversion efficiency is non-linear and depends on the distribution of both the values of irradiance and temperature. Additional analysis on other meteo parameters can be also relevant for certain situations.

Relative change of produced energy from this stage of conversion depends on module technology and mounting type. Typically the losses at this step are higher for crystalline silicon modules than thin films due to higher negative thermal power coefficient of crystalline silicon and better behaviour of thin film at low light levels (different spectral sensitivity).

PVOUTDC = fPV (GTIANGULAR, TEMP, Module type)

 

Losses by inter-row shading

Relative spacing of leads to electricity losses due to short distance shading. Crystalline silicon modules are sensitive to partial shading, and losses depend on the topology of module interconnections.

 

Power tolerance of modules

 From the module power tolerance result bigger or smaller mismatch losses of the modules connected in strings. If modules with higher power tolerance are connected in series, the losses are higher. The power tolerance of modules increases uncertainty of power output estimation.

 

Mismatch and DC cabling losses

Mismatch due to different MPP operating point of modules connected into an inverter and heat losses in the interconnections and cables depend on the design and components of the PV power plant. If classification of modules is considered according to the measurements of the nominal conversion efficiency performed by the manufacturer, grouping the modules from the same class is an effective measure to minimize the mismatch losses of the modules connected within one string.

 

Inverter losses from conversion of DC to AC

Although power efficiency of inverter is high, each type of inverter has its own efficiency function (dependence of the inverter efficiency on the inverter load and inverter input voltage). Losses due to performance of inverters can be estimated using inverter power curve with subhourly pairs of DC data or using the less accurate pre-calculated value given by the manufacturer and representing the average efficiency (Euro efficiency).

PVOUTAC = fINVERTER (PVOUTDC, VDC)

 

AC and transformer losses

The inverter output is connected to the grid through the transformer. The additional AC side losses reduce the final system output by a combination of cabling and transformer losses.

PVOUT = fAC (PVOUTAC, ACLOSS, TRLOSS)

 

Availability

This empirical parameter quantifies electricity losses incurred by shutdown of a PV power plant due to maintenance or failures.

 

Long term degradation

 Many years of operation of PV power plants is the ultimate test for all components, placing the module encapsulants, cell interconnections, junction boxes, cabling, and inverters under stress during the weather cycles. Currently produced modules and system components represent a mature technology, and low degradation can be assumed. Although it has been observed in different studies that performance degradation rate of PV modules is higher at the beginning of the exposure (initial degradation).