The Bialystok University of Technology is the biggest school of technical higher education in northeast Poland. It consists of seven areas of study, 600 teachers and professors, and almost 12,000 students. On the campus of the university, we developed a hybrid system of small wind and photovoltaic energy (Figure 1). Our main goal was to work out a system to test the installed power of 20 kW with the wind turbine of 10 kW and the photovoltaic system of 10 kW.
We adjusted the designed system to work in two modes. One mode works independently, and energy produced during this period goes to the power system of the campus. During the other working mode, the all produced energy or just the surplus is transferred to the commercial power grid. This system is unique in Poland and is the only hybrid electrical power supply in the region model system. It consists of various configurations of photovoltaic panels placed on vertical walls of a building at the southeast and southwest sides on a tracker following the movement of the sun in two axes. The tracker is attached beneath the panels for all-year work at about 38° to the ground level.
We also equipped the system with two wind turbines of various constructions. One of them is a vertical three-bladed H-Darrieus turbine, and the other one is a horizontal turbine. We constantly monitor the technical parameters of the installation and display selected data on the website (Figure 2).
The measurement system controlling the work of the hybrid power system is an important element. Employees of the Electrical Engineering Faculty of the Bialystok University of Technology in cooperation with SARW s.c. company, which is an NI Alliance Partner, created the measurement system.
We used LabVIEW software and PXI hardware to develop the system of measurement data acquisition, storing, processing, and visualization. The PXI hardware collects the measurement data from local data centers. We attached various sensors, including accelerometers, microphones, thermometers, pyranometers, a weather station, and an anemometer to these modules (Figure 3).
An additional element of the measurement system is a system that monitors the temperature distribution in the cross section of the building wall (Figure 4). Due to a group of sensors being attached to the measurement system, we could research and analyze the temperature distribution inside the wall in a year cycle. At this stage of the research, we have worked out a measurement system for two rooms in the Research-Didactic Centre of the Electrical Engineering Faculty so far. We inserted nine temperature sensors in one wall of both rooms. We placed them at 50 cm, 150 cm, and 220 cm above the floor, and 20 cm, 40 cm, and 60 cm deep into the wall from its inner surface.
Measuring the noise intensity distribution within the wind turbine neighborhood and the analyzing the vibration level of the turbines compared with the wind velocity is the next activity in this stage of the experiment. This stage required collecting a great amount of measurement data recorded with a great frequency. The processes connected with acoustics and vibrations are fast, changeable processes, which meant we needed to introduce additional mechanisms to the DAQ system and distribute the sensors very carefully for their configuration and the appropriate rescaling of the measured parameters (Figure 5).
We based the measurement system architecture on real-time devices and software. We used: a PXIe-1082 8-slot 3U chassis, a PXIe-6363 X Series DAQ module, a PXI-8231 Gigabit Ethernet interface, the LabVIEW Real-Time Module, a PXI-8433/4 2000 V isolated RS422/485, 4-port serial interface, and cRIO-9024 modules. We also used a real-time PowerPC controller for CompactRIO 800 MHz equipped with an NI 9203 8-channel ±20 mA, 200 kS/s, 16-bit AI module; NI 9219 4 ch-ch isolated, 24-bit, ±60 V,100 S/s universal AI module; NI 9871 4-port RS422/RS485 serial module with four 10P10C-DE9 cables; NI 9215 4-channel, 100 kS/s/ch, 16-bit, ±10 V AI module; NI 9201 8-channel, ±10 V, 500 kS/s, 12-bit AI module; and C Series local data concentrators. These make up the main element of the system. Accelerometers, microphones, thermocouples, pyranometers, a weather station, and an anemometer are attached to those modules.
We used a SQL database to store measurement values collected from various points of the system as another component. The final layer are remote working stations (PCs) equipped with applications that make analysis of the measurement data possible. In this system, the measurement data is connected, stored, and made available to the client applications (Figure 6). Storing data in the SQL base directly from the real-time system is an important and innovative element of the system implemented for the sake of the project. Client applications communicate directly with the PXI system and the database. In case of system failure, they can communicate directly with the CompactRIO concentrators.
Communication among the local data concentrators, the PXI computer, the database, and the working stations occurs through Ethernet. The local data concentrators collect information from the attached measurement devices and then share the data in the real-time PXI.
Data Acquisition and Visualization
Visualizing the measured quantities or energetic yields in connection with the weather condition measurement is a significant element of such a system. For this reason, a measurement DAQ system implemented with LabVIEW works well (Figure 7). The software powers simultaneous attachment of numerous working units situated in a selected place in Poland or the world.
Creating an appropriate measurement data structure and a storage method was an inevitable element of this stage of research. We could use the collected measurement data optimally and conduct further analysis. Our application includes an interesting function that enables access to various functional modules depending on the access level of the user. That is, logging into the system enables access to the basic mode of data view, an engineer has the lowest access level and can view data and generate reports, an administrator has the engineer’s entitlements and can configure selected local settings of the program, at the service level they have special usage and full entitlement to modify the program.
Due to the use of the worked out environment, we can share the acquired data through the Internet. This means system users can conduct further data analysis. This is important because of the fact that the measurements of electric parameters, especially of the amount of energy acquired from renewable sources, which are stored in month cycles, make it possible to assess the effectiveness of the applied technological solutions. In further research, the analysis of such phenomena as energy loss in photovoltaic modules, where some amount of energy is consumed on temperature processes (Figure 8), and in the case of turbines, where non-electric quantities measure vibrations of the turbine construction or noise generated by them, are also possible.
In the case of both energy sources, power and efficiency depend on the weather conditions. This is essential to examining their influence on the amount of energy gained in those sources. The test considers the following quantities: wind velocity and direction, air temperature and humidity, air pressure and the level of sun radiation. The tests are continuous and stored, which makes it possible to analyze the acquired data in year cycles.
Using modern solutions offered by NI, we realized a return on our investment quickly and reliably. Using PXI and CompactRIO components simplified the process of installing measurement devices in selected points of the hybrid power system. LabVIEW software with the PXI hardware streamlined the implementation process of the measurement data processing algorithms and situated them on a dedicated server. Now, we can analyze the data and assess the use of the applied components of the hybrid power system as renewable energy sources in the northeast region of Poland. In the future, we can also use stored data as a benchmark to point out an optimal way of installing photovoltaic modules or to best construct wind turbines installed in our region.
Bialystok University of Technology, Faculty of Electrical Engineering