Program 1: Integrated Building Systems
Owners of commercial buildings with a PV system installed need to be able to answer two key questions:
- “Is my PV system generating as much energy as it should?”.
- “How can I reduce my electricity consumption?”
This project will develop intelligent algorithms using real time on-site weather, building and system inputs to automate the analysis of the electricity production and consumption. The monitoring solution developed in this project will monitor the energy generation of PV systems using energy modelling algorithms, and investigate integration into building management systems to provide a tool that monitors both energy generation and utilisation.
Program
Project leader
A/Prof Alistair Sproul, UNSW
Project status
Complete
Project period
02/2013 to 02/2014
- Publications
- Partners
- Posters
Peer Reviewed Research Publications
RP1007: Journal Article: Photovoltaic (PV) performance modelling in the absence of onsite measured plane of array irradiance (POA) and module temperature
In this study, the outputs from a simple PV performance model were compared to measurements of AC power for three PV systems located across Sydney, Australia. The study aimed to investigate the level of uncertainty and bias of the model when onsite measurements of plane of array (POA) irradiance and module temperature were not available. The results demonstrated that the simple PV performance model estimated the AC performance with a low level of model bias (NBME = ±3.2%) and uncertainty (NRMSE < 6%) when onsite measurements of POA irradiance and module temperatures were available.
For POA irradiance, the results indicated that modelling uncertainty increased significantly (NRMSE < 13%) when alternative methods to estimate POA irradiance were utilised. For module temperature, the results indicated that the choice of model coefficients had a significant impact on the performance of the module temperature models. In particular, for the three parallel roof mounted PV systems studied, the results suggested that the open rack/free standing or well ventilated module temperature coefficients should be used within the module temperature models investigated. This selection of coefficients was not directly evident given the PV systems investigated were parallel roof mounted PV systems, not free standing rack mounted arrays.
Read the full article here: https://doi.org/10.1016/j.renene.2015.09.005
RP1007: Project Report: Intelligent automated monitoring of commercial photovoltaic (PV) systems
Rapid growth of distributed small scale Photovolatic (PV) systems has increased the need for tools that can undertake reliable real time monitoring of system performance with the capability to detect and diagnose underperformance at the earliest possible stage.
This project refined the system performance algorithms within Solar Analytics, a PV systems monitoring tool offered by Suntech, to improve their accuracy and to test their ability to predict the performance of residential and commercial PV systems. It also developed an initial set of algorithms to detect and diagnose underperformance. The project also investigated the feasibility of (1) including forecasts of PV system performance within Solar Analytics and (2) the integration of commercial building energy management systems with Solar Analytics to provide a holistic energy management platform for the small to medium sized commercial office buildings market.
rp1007 pv monitoring crc final report (861575 PDF)
Partners on this project
- University of Wollongong Australia
- UNSW Sydney
- NSW Government Office of Environment & Heritage
CRCLCL Project Posters
Research Snapshot Poster - RP1007
Research Snapshot A3 size poster from Participants Annual Forum 2014
Research Snapshot Poster - RP1007 (1014422 PDF)