absorber material where, unlike in real systems, each photon contributes to the photovoltaic current [16, 17]. Indirect band gap semiconductors, such as silicon (Si), have other dominating loss mechanisms than direct band-gap materials such as GaAs, and all of those effects are temperature and intensity dependent. Optimization methods include doping and change of layer thicknesses of the n- and p-layer, respectively. A great introduction into semiconductor modeling in general has been given by Sze and Lee and by Hovel for solar cells in particular [18, 19]. For amorphous Si, these models have to be adjusted according to the material properties and effects [20, 21]. In organic materials, exciton processes have to be modeled [22]. In order to overcome this challenge for IPV, Freunek has recently published a handbook that shows material-dependent and application-specific models for photovoltaic efficiencies [23].
Gemmer, who investigated realistic indoor cell efficiencies for c-Si, a-Si and CIGS with analytical and numerical models, presented the first modeling study for photovoltaic performance under indoor conditions [20, 24]. A current limit to the use of available photovoltaic simulation programs in IPV is their optimization for outdoor applications in their efficiency models and spectra. In addition, in most programs the numerical models have been developed for silicon only and neglect low irradiance or diffuse illumination effects.
For Si, GaAs, and CdTe, Bahrami-Yekta and Tiedje investigated the indoor efficiency limits and the optimization of real devices in indoor conditions in detail [25]. With an absorption layer thickness about two orders of magnitude below the ones of standard outdoor cells, Si devices can achieve or even outperform their outdoor performance under artificial light. Table 3.1 summarizes their results for three materials. It is important to note that spectra for fluorescent tubes can vary significantly with manufacturer and lamp type.
Table 3.1 Indoor efficiencies modeled by Bahrami-Yekta and Tiedje for different photovoltaic materials (adapted from [25]).
| Material | Efficiency FL250 Lux [%] | Efficiency LED [%] |
| Si | 27.0 | 29.0 |
| GaAs | 37.1 | 40.3 |
| CdTe | 40.3 | 43.3 |
As Chapter 6 shows similar results to that, the optimization goals for indoor organic photovoltaics (OPV) are contradictory to outdoor applications. For IPV, the influence of the serial resistance in organic devices can be neglected whereas the parallel resistance needs to be maximized.
Customers, product engineers, and researchers require reproducible and retraceable characterization methods in order to compare research results and products. The efforts to establish a standard characterization process has just begun and is outlined in Chapter 5 of this book. Methods to overcome the current gaps in standards are described in Chapters 4 and 5.
The following sections outline general operating conditions, efficiencies and product aspects for the state-of-the-art at the time of writing.
3.2 Indoor Spectra and Efficiencies
Outdoor spectra are broadband spectra resulting from the thermal radiation of the sun. The human eye is sensitive only to a small fraction of it, which has also been characterized as the human visibility function V(λ) (see Chapter 4 and 5 for detailed introductions). The users of artificial light in indoor environments are humans, plants, and animals, so their radiation is optimized for their optical range of sensitivity, such as V(λ). Broadband radiation sources in indoor environments are halogen lamps and incandescent bulbs, as well as solar radiation filtered through a window. Depending on the place of installation, windows are manufactured with functional coatings of a spectral transmittance T(λ), such as heat or sun protection coatings. In general, the filtering function of these windows is optimized to V(λ). Thus, the indoor solar spectrum is different to the outdoor spectrum not only in its intensity, but also in its spectral distribution. Figure 3.1 depicts typical indoor spectra. The window spectra result is from the spectral irradiance of the so-called AM 1.5 solar spectrum [26] that is transmitted through a heat and sun protection coating of a window, respectively (see Chapter 4 for a detailed introduction).
As windows in most applications do not face the sky horizontally, the actual irradiance E will result from the incident power P received on an area A in an incident angle α following Eq. (3.1).
In some applications, a sensor might be directly installed on a window facing the outdoors. However, most devices will be installed within a certain distance to the window. As the intensity is inverse to the square of the distance from the emitter, the incident irradiance is additionally lowered following Eq. (3.2)
Figure 3.1 Spectra for sunlight through heat and sun protection windows, LED, and warm white fluorescent lamps. The emissions after 1800 nm are negligible for this visualization purpose.
Note that the discussion so far has only included direct radiation. Indirect radiation resulting from reflection or transmission indoors has been neglected. Its effects and modeling are discussed in detail in Chapter 4.
The photovoltaic efficiency limit for a conversion from optical radiation to photoelectric power depends on many parameters. Some of these parameters are spectrally dependent, such as the energy gap or the photon flow, that is the intensity of the radiation. The number of photons N(λ) per area A and time t yields the spectral photon flux ϕpλ
(3.3)
The thermodynamic limit to photovoltaic efficiencies presented by Shockley and Queisser was calculated for black body radiation following Planck’s law [16]. It assumes that an ideal single absorber material, where every incident photon is absorbed, yields the so-called external quantum efficiency EQE = 1. Then the short circuit current density jsc ≈ jph, where the photocurrent density jph is
(3.4)
with the elementary charge q = 1.602 10-19 As. The Shockley-Queisser limit can be applied numerically to spectral distributions [17, 27]. Figure 3.2 shows the resulting maximum photovoltaic efficiencies for different indoor spectra in comparison to the solar AM 1.5 spectrum.