Abstract

Accurate knowledge of solar radiation data or its estimation is crucial to maximize the benefits derived from the Sun. In this context, many sectors are re-evaluating their investments and plans to increase profit margins in line with sustainable development based on knowledge and estimation of solar radiation. This scenario has drawn the attention of researchers to the estimation and measurement of solar radiation with a low level of error. Various types of models, such as empirical models, time series, artificial intelligence algorithms and hybrid models, for estimating and measuring solar radiation have been continuously developed in the literature. In general, these models require atmospheric, geographical, climatic and historical solar radiation data from a specific region for accurate estimation. Each analysis model has its advantages and disadvantages when it comes to estimating solar radiation and, depending on the model, the results for one region may be better or worse than for another. Furthermore, it has been observed that an input parameter that significantly improves the model’s performance in one region can make it difficult to succeed in another. The research gaps, challenges and future directions in terms of solar radiation estimation have substantial impacts, but regardless of the model, in situ measurements and commercially available equipment consistently influence solar radiation calculations and, subsequently, simulations or estimates. This article aims to exemplify, through a case study in a multi-family residential building located in Viana do Castelo, a city in the north of Portugal, the difficulties of capturing the spectrum of radiations that make up the total radiation that reaches the measuring equipment or site. Three pieces of equipment are used—a silicon pyranometer, a thermopile pyranometer and a solar meter—on the same day, in the same place, under the same meteorological conditions and with the same measurement method. It is found that the thermopile pyranometer has superior behavior, as it does not oscillate as much with external factors such as the ambient temperature, which influence the other two pieces of equipment. However, due to the different assumptions of the measurement models, the various components of the measurement site make it difficult to obtain the most accurate and reliable results in most studies. Despite the advantages of each model, measurement models have gained prominence in terms of the ease of use and low operating costs rather than the rigor of their results.

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