Functional Smart Grid Prototype using NI LabVIEW, NI DAQ Hardware and NI FPGA CompactRIO Country: Singapore Author(s): P. H. Cheah, B. Sivaneasan, K. V. Ravi Kishore, G. Anima, M. K. Foo, H. B. Gooi Organization: Nanyang Technological University Products Used: NI LabVIEW 2009 NI crio 9082 (FPGA module) NI USB 6215 NI 9227 NI 9225 The Challenge: The integration of distributed energy resources (DERs) such as solar photovoltaic (PV) and battery energy storage system (BESS) and demand response management (DRM) into the microgrid, building and home has been a great challenge in developing a reliable, cost effective, secure and resilient smart grid infrastructure for Singapore. The Solution: The project utilizes NI LabVIEW, USB 6215, 9227, 9225 and crio to develop the maximum power point tracking (MPPT) module of the PV system and control scheme of BESS for the integration of home and building energy management systems (HEMS, BEMS), solar PV and energy storage into the microgrid. Abstract The project utilizes LabVIEW 2009, NI DAQ and NI FPGA CompactRIO to develop and test a smart grid laboratory prototype. NI crio 9082 is used to implement voltage balancing mechanism during battery charging and discharging and NI 9401 is used to drive the digital IO signal for controlling the on/off switching of discharging resistors and battery chargers. The MPPT module uses NI 9225 and NI 9227 to acquire voltage and current measurement data from the PV modules. NI 6215 is used to issue gating signals for use by the boost converter and to generate analog output signals to control the speed of the fan motor in HVAC System.
Smart Grid Development The Laboratory for Clean Energy Research (LaCER) at School of EEE, NTU houses the award winning 1 Microgrid Energy Management System (MG-EMS) prototype which incorporates software applications that manage sensing data and perform load and generation management. In order to extend the microgrid to a full fledge smart grid prototype, further works need to be done to integrate the HEMS, BEMS, renewable energy resources typically PV and BESS into the microgrid as shown in Figure 1. Through the integration of the consumer loads and their DERs in the supervisory control and data acquisition (SCADA) of LabVIEW, smart grid applications such as DRM, TOU electricity pricing scheme, power quality monitoring, power system optimization, DER scheduling, load forecasting and electricity billing can be performed easily. Figure 1: Smart Grid Architecture Figure 2 shows the block diagram on how the application works. 1 Best Innovation in Green Engineering Award, ASEAN Virtual Instrumentation Applications Contest Singapore, 20 October 2010.
Figure 2: Block Diagram of PV and BESS System Battery Energy Storage System with NI FPGA-Based CompactRIO-9082 NI CompactRIO module, NI Voltage Sensing module and NI Digital IO driver are used to implement the BESS to increase the reliability, life span of the battery pack as shown in Figure 3. Figure 3: Passive Balancing of BESS
NI PS-15 supplies power to the NI crio 9082 module. NI 9225 and NI 9401 are used to measure the voltage and control the parallel switch of each battery respectively every second. NI crio 9082 module is a vital part of the whole system. The voltage sensing module and DIO channel are integrated into crio module. The balancing logic is implemented on FPGA hardware with the help of Xilinx interface with LabVIEW. To control the balancing of the BESS, a LabVIEW VI was developed. In passive balancing, the parallel switch is ON until its voltage becomes equal to minimum voltage. In auto mode, passive balancing is active when the voltage difference between maximum and minimum is greater than the threshold preset through LabVIEW GUI. In manual mode, passive balancing is active independent of voltage difference which is a case of 0V threshold in auto mode. The BESS hardware setup is shown in Figure 4. Figure 4: BESS Hardware Setup in LaCER LabVIEW VI diagram for the balancing algorithm is shown in Figure 5. Figure 5: BESS Balancing Algorithm in LabVIEW: (a) VI Diagram and (b) GUI
Photovoltaic System based on MPPT A MPPT system is implemented with NI DAQ modules such as NI 9227 and NI 9227. The PV voltage and current can be directly measured with the help of NI 9225 and NI 9227 respectively. The acquired instantaneous voltage and current can be used for the implementation of MPPT. The operating point of PV panels usually depend on the load connected to it. So to ensure the operation occurs at maximum point, a MPPT controller is required to be implemented at the boost converter stage. The MPPT hardware setup is shown in Figure 6. Figure 6: Hardware Setup for PV System The MPPT is implemented by Perturb and Observe algorithm. The present and previous real time values of voltage and power are compared by perturbing the duty cycle of the boost converter. The duty cycle is incremented or decremented instantaneously The PWM gating signals required for the boost converter are issued through NI USB 6215. The operating point reaches maximum power point in 3s. The GUI of MPPT is shown in Figure 7.
Figure 7: MPPT in LabVIEW: (a) VI Diagram and (b) GUI BEMS A real-time BEMS that can monitor, manage and control every load and energy source installed in a commercial building has been developed. The GUI of the BEMS developed using LabVIEW is shown in Figure 8. The BEMS is integrated with the communication and control hardware components in order to perform DRM. NI-VISA is used to interface between the BEMS and ZigBee end devices through ZigBee USB Dongle (coordinator). NI USB 6215 is used to read data from temperature and water level sensors and generate analog output signals to control the speed of the fan motor in Air Handling Unit (AHU) through a VSD. The three DRM functions implemented are: 1. Load Shedding: Each load holds a pre-assigned priority as shown in Figure 9. When the main supply is about to exceed the contracted capacity, the system will automatically shed lower priority loads. 2. VSD control: The BEMS has the ability to reduce the AHU s energy consumption based on the temperature data collected from the temperature sensors. Figure 10 shows the VI diagram for the implementation of the VSD based DRM algorithm and the laboratory setup. 3. Sump Pump Scheduling: The BEMS performs pump scheduling to take advantage of the lower electricity price by shifting load to off-peak period and reduces the overall energy cost.
Figure 8: BEMS in LabVIEW Figure 9: Load Shedding in LabVIEW: (a) VI Diagram and (b) GUI showing DRM s algorithms
Figure 10: VSD DRM in LabVIEW: (a) VI Diagram and (b) Laboratory Setup HEMS A ZigBee-based HEMS which consists of three main components: the smart meter, Ethernet-ZigBee Gateway and SCADA has been developed. The software modules such as DRM, scheduling function and database are developed based on NI LabVIEW. HEMS enable home users to centrally manage and monitor the energy usage of their electrical devices through load control modules (LCMs). NI-VISA is used to interface between LCMs, smart meter and SCADA through ZigBee-based USB Dongle. Data such as energy consumption and status of each individual home appliance will be captured from LCMs to do intelligent automatic window blinds control, room temperature control and smart lighting control which are developed using NI LabVIEW. Figure 11 shows the VI diagram and front panel of GUI. Figure 11: HEMS in LabVIEW: (a) VI Diagram and (b) GUI showing intelligent control systems In order to fulfill the key function of the smart grid applications, DRM algorithms were designed using LabVIEW as shown in Figure 12. The DRM algorithm developed will interrupt the home appliances (HAs)
based on maximum demand or TOU electricity pricing. Home users can set or schedule the sequence of HA interruption via the developed GUI. Figure 12: DRM in LabVIEW: (a) VI Diagram and (b) Front Panel showing the DRM s GUI and algorithms Conclusion With the help of NI LabVIEW, NI CompactRIO FPGA and NI DAQ modules, we can integrate the developed BESS, PV System, BEMS and HEMS into the microgrid prototype easily. The FPGA technology module provides a direct interface for sensing, Xilinx interface to import the logic to hardware and LabVIEW GUI for debugging and validation. It has saved us time to select micro controller, programming tool, debugging tool, and sensors for operating range. This work is part of the fundamental blocks of the Intelligent Energy System (IES) project initiated by Energy Market Authority to explore if small non-contestable loads of buildings and homes in a district can be aggregated in a sizable capacity so that it is big enough to participate in the frequency regulation and demand response markets of National Electricity Market of Singapore. For more information, please contact: Cheah Peng Huat Nanyang Technological University School of EEE 50 Nanyang Ave Singapore 639798 Email: cheahph@ntu.edu.sg