Advanced Building Energy Data Visualization

Advanced Building Energy Data Visualization is a way to detect performance problems in commercialbuildings. By placing sensors in a building that collects data from example, air temperature and electricalpower, then makes it possible to calculate the data in Data Visualization software. This softwaregenerates visual diagrams so the building manager or building operator can see if for example thepower consumption is to high.A first step (before sensors are installed in a building) to see how the energy consumption is in abuilding can be to use a Benchmarking Tool. There is a number of Benchmarking Tools that is availablefor free on the Internet. Each tool have a bit different approach, but they all show how much energyconsumption there is in a building compared to other similar buildings.In this study a new web design for the benchmarking tool CalARCH has been developed. CalARCHis developed at the Berkeley Lab in Berkeley, California, USA. CalARCH uses data collected only frombuildings in California, and is only for comparing buildings in California with other similar buildingsin the state.Five different versions of the web site were made. Then a web survey was done to determine whichversion would be the best for CalARCH. The results showed that Version 5 and Version 3 was the best.Then a new version was made, based on these two versions. This study was made at the LawrenceBerkeley Laboratory.

COMPARISON OF PARTIAL SHADING LOSSES IN FREE FIELD PV-PLANTS WITH DIFFERENT ARRAY CONFIGURATIONS

A common problem when planning large free field PV-plants is optimizing the ground occupation ratio while maintaining low shading losses. Due to the complexity of this task, several PV-plants have been built using various configurations. In order to compare the shading losses of different PV technologies and array designs, empirical performance data of five free field PV-plants operating in Germany was analyzed. The data collected comprised 140 winter days from October 2011 until March 2012. The relative shading losses were estimated by comparing the energy output of selected arrays in the front rows (shading-free) against that of shaded arrays in the back rows of the same plant. The results showed that landscape mounting with mc-Si PV-modules yielded significantly better results than portrait one. With CIGS modules, making cross-table strings using the lower modules was not beneficial as expected and had more losses than a one-string-per-table layout. Parallel substrings with CdTe showed relatively low losses. Among the two CdTe products analyzed, none showed a significantly better performance.