An unsupervised method for identifying local PV shading based on AC power and regional irradiance data

\u3cp\u3eMonitored power output data of photovoltaic (PV) installations is increasingly used for purposes such as fault detection and performance studies of distributed PV systems. The value of such datasets can increase significantly when they are paired with information about local irradiance and shading conditions, especially in urban environments. However, on-site irradiance measurements are seldom performed for small or medium-sized rooftop PV installations. This paper proposes a novel method to identify locally shaded periods of PV installations, using only measured AC power, regional irradiance data and basic information about the sites (i.e. module tilt, orientation and nominal power) as inputs. The proposed three-step method uses machine learning techniques and a grey-box PV performance prediction model to classify the visible sky hemisphere of a PV installation to obstructed and unobstructed areas. Detailed results of a moderately-shaded residential PV site in the Netherlands are shown to illustrate the working principles of the method. Finally, a successful comparison with on-site shade measurements is carried out and the ability of the method to detect shade from nearby objects is illustrated.\u3c/p\u3

Characterization of BIPV(T) applications in research facility ‘SOLARBEAT’

The SolarBEAT facility is an outdoor Research & Development infrastructure for innovation on BIPV(T). The facility is a cooperation between SEAC and the Technical University Eindhoven and is located in the Netherlands. It has been founded early 2014 and has grown rapidly to its full capacity at the moment: a total of 6 projects are testing 8 different BIPV prototypes on one full year performance in realistic outdoor conditions. Performance (Ratio) is measured according to the norms and best practices. The secondary standard Solar Measurement Station is checked continuosly with the measurements of the nearby official Dutch meteorological institute (KNMI). Data is coming in flawless from more than 500 sensors. The daily data stream sums up to more than one million data points which are imported by a central relational (SQL-based) server. Much care is taken that every data point is synchronized with atomic time within 5 seconds, which makes a comparison between different projects possible. Moreover, at SolarBEAT, reliability issues can be checked by using professional equipment a.o. Infrared Thermography (IRT), and in-house developed outdoor Electroluminescence (EL)

Identifying local PV shading in urban areas based on AC power and regional irradiance measurement

As the price of photovoltaic applications is decreasing, more and more PV is installed in an urban environment. Driven by the need for aesthetics and integration in building constructions, new BIPV products are developed, which opens the possibility to extend the usable area to almost any built surface. As a consequence of this, in the new era of BIPV applications, it is only natural that PV is installed on a surface that is regularly shaded. Furthermore, because of the increased capacity, it is expected, that the dependency of future buildings on on-site electricity generation will increase. These factors drive the need for accurate performance monitoring and fault detection methods, of which shade detection of PV applications is an essential element.\u3cbr/\u3eA new method is developed, that relies on locally measured AC power and regionally measured irradiance data. By calculating the apparent Performance Ratio (aPR) and applying machine-learning algorithms on the measured AC power time series, locally shaded time periods can be identified, without local irradiance measurement. The method consists of 5 steps: Step1. Creating analemma graph of aPR Step2. Eliminate data points, with cloud-shading. Step3. Binarizing the remaining measurement points with an aPR-treshold. Step4. Train Support Vector Machine (SVM) with the previously binarized dataset. Step5. Use trained SVM to perform a soft-margin nonlinear classification of all data points recorded in the first step. \u3cbr/\u3eWith this method it is possible to distinguish between local and cloud-shading and - in case of a mono-pane installation - to plot the shading contour of the nearby objects, which is useful input for fault detection and monitoring of PV installations in an urban area. The next step is the validation of the method by on-site shading measurements.\u3cbr/\u3

Modeling reflected irradiance in urban environments – a case study for simulation-based measurement quality control for an outdoor PV test site

The increased application of PV in urban environments goes together with a growing awareness of the need to consider the influence of partial shading and reflected irradiance on PV performance. Most of the conventional PV simulation tools do not have the capabilities to account for the possible additional PV yield due to reflected sunlight. On the other end of the spectrum are complex ray-tracing tools that can accurately model reflected irradiance, but require a large amount of input data, are computationally intensive and have limited or no PV modeling algorithms. In this work, as a step towards quantifying uncertainties due to reflected irradiance in urban settings, the potential of a modeling strategy using building energy simulation software, with intermediate complexity is investigated using a case study of an outdoor PV test site

Towards simulation-assisted performance monitoring of BIPV systems considering shading effects

Nowadays, the application of BIPV systems is growing very fast and among this type of technology, application of BIPV façade systems is becoming more common. A main question in this field is how we can ensure the intended performance of such systems considering different involved parameters over the system’s life-time. To do so, we need to be able to predict normal behavior of BIPV systems in urban environments, considering the effect of shading from neighboring obstructions. This research investigates a combination of real-time shading simulation using Rhino and Grasshopper with BIPV performance monitoring to detect abnormal system operation. The application of this approach is demonstrated for a 12 m2 vertical BIPV system in the SolarBEAT test facility in Eindhoven, the Netherlands. We have conducted an experiment to better understand the impact of different partial shading scenarios on the I-V curve of a vertical CIGS BIPV panel. The results show that the simulation-assisted approach, coupled with data visualization and a decision tree can be a powerful tool for guaranteeing robust BIPV system outpu

Outdoor characterization of colored and textured prototype PV facade elements

The aim of this study is to assess the performance of prototype PV façade elements of various PV technologies, colors and textures. Within this context, a prototype PV façade demonstrator was constructed and monitored at SolarBEAT, Eindhoven. This prototype demonstrator consists of 9 façade PV panels of c-Si and CIGS technologies with flat and textured solar glasses and black, grey and red colors. The field-testing results indicate a limited performance drop of less than 20% for all colors and textures

Really building with BIPV - putting the foundation in place for a successful Dutch BIPV sector (The ‘werkelijk bouwen aan BIPV’ project)

The main result of this project is the organisation of a strong BIPV market and supply chain, to encourage knowledge sharing, and successful business development by collaboration of (SMEs) businesses, R&D knowledge institutions and the solar- and building associations. This should result in a significant increase in the use of BIPV in building projects in Netherlands, and as a result in economic growth. The project runs from 2017 until the end of 2020, and is a follow-up to the national BIPV Roadmap issued in early 2016