Application of Controller Area Networks to Direct Load Control in Residential Areas

Transcription

1 Application of Controller Area Networks to Direct Load Control in Residential Areas A. Molina-Garcia, R. Torres, J.L. Munoz and N. Encinas Abstract The objective of this paper is to describe and assess the application of Controller Area Networks to Direct Load Control programs, extending the CAN applications from industrial sector to residential automation. The proposed system allows the customers to monitor and control automatically their heating and cooling individual loads, maintaining minimum comfort levels and offering a flexible, low-cost and friendly tool through a graphical user interface environment in order to active the demand-side participation in the current deregulated electricity markets. Finally, an application example to real residential loads is also presented. Index Terms Demand-Side Bidding, Direct Load Control, Controller Area Networks (CAN) I. INTRODUCTION Competition has acquired a major role in electricity industry due to power markets restructuring. A desired market performance requires the demand to be flexible, [], [2]. Active demand-side participation can decrease the market power of supply side agents, [3], and help these markets to obtain a better operation. Additionally, new energy policies reinforce the idea of the need of additional electricity resources, including demand-side resources. In this way, two different goals exist when referring to demand resources: Long term demand efficiency improvements Customer short-term responsiveness to market signal The achievement of the first of these two goals relies mainly on technology developments, while the second one requires a change in customers, in order to react to the received market signals. The demand response has not appeared naturally in the electricity industry and, therefore, new tools and products are required to overcome the barriers which are preventing the customer reaction. The objectives of these tools and products should be twofold: Acting as interface between the complexity of the market and the simplicity required by the user. The products in development are to act as interface, in order to maintain the market efficiency, ensuring that the customer response is financed though market mechanisms and not through subsidies. Additionally the products should also provide trading agents structures to use in the market the response obtained form the customer. A. Molina-Garcia is with the Dept. of Electrical Eng, Technical University of Cartagena (UPCT), 3.22, Cartagena (Spain); angel.molina@upct.es R. Torres and J.L. Munoz are with the Dept. of Systems and Control Eng, Technical University of Cartagena (UPCT), 3.22, Cartagena (Spain); roque.torres@upct.es, joselu.mlozano@upct.es N. Encinas is with the Institute of Energy Engineering, Polytechnic University of Valencia,.22, Valencia (Spain); nuenre@aaa.upv.es To ease customers managing their loads for reacting to the market signals received: Decision of when to react, at what price, what loads to use for the reaction, how to control the loads,... In case of large consumers, the products that are being developed focus on direct participation in markets or partial participation bilateral contracts jointly with compensations for demand reductions based on market prices [], [], [5]. And the tools in progress deal with the continuous decision process of the customer for identifying the loads that should be used for reacting and the price they should be paid for. This approach is not suitable for small customers. First of all the consumption volumes make individual direct participation in the market unfeasible and participation only possible with aggregation. On the other hand, importance of electricity costs is usually much lower for the residential customer and therefore they are not willing to dedicate as much effort as the industrial customers do. Additionally, residential and small commercial customers perception of electricity supply is different from large customers one. Industries are used to deal with electricity supply as they do with other resources: a product they buy and they negotiate, if they can, the price. But residential customers still consider electricity supply a service. This fact complicates direct reaction to prices. On the other hand, large customers usually include dedicated staff in charge of facilities maintenance that are more or less aware of their loads and needs and may manage the tools developed. But, in the case of residential customers, there is clearly no dedicated staff and the knowledge of their loads is minimum. All this specific characteristics of the residential and small commercial customers suggests that the demand response should include long term changes on consumer behaviour to compensate normal prices fluctuation during the day complemented with Automatic Load Control, which would provide response to market signals. In this way, the objective of this paper is to present and assess the application of a Controller Area Network (CAN) protocol, known as CANopen, in order to monitor and control by the own residential customers their heating and cooling loads. CAN Bus has long been used in the automotive industry or textile machinery, and it has also found a good way as a fieldbus system within the industrial control sector, since it provides mechanisms that make it possible for devices of different types and makings to be integrated together and to communicate with each other, [], [7]. II. CAN BUS APPLICATIONS. REVIEW CAN bus was born with the aim of be used in the on-road vehicles, mainly in cars, being extended to superstructures

2 2 Power Line Node #n Node #n+ PC Temperature Power Temperature Power CAN Bus Switching Switching Residential Customer Heating and Cooling Load Heating and Cooling Load Fig.. General system architecture such as cranes or fire-fighting. Besides, its use was soon generalized to other fields: marine and aerospace electronics, factory automation, machine control,... ; most of them belong to the industrial sector. Nowadays, this extension also includes applications in mining, agriculture, civil construction and army. Some Swiss, German and Czech manufacturers have included CANopen in different kind of trains, such us undergrounds, streetcars and light railways; with the aim of controlling and monitoring doors, lighting and motors. Recently, in the public transport, CAN bus is being used in urban buses, []. In the residential sector, CANOpen has been used in lift and escalators control, sprinklers, lighting doors control, security systems and video and radio systems, [9], and an approach to home automation can be found in []. Nevertheless, in this sector, LongWorks bus created by Echelon Corp. has a relevant presence. This bus has been used in control appliances, cooling and heating, humidity control, lighting, external and internal security, pool and SPA monitoring and control, sprinklers, electrical loads and energy measures, []. Other non-industrial sectors have also used CANOpen, such as supermarkets control systems, office building, hospital mainly in operating rooms monitoring or X-Ray Machines control, laboratories and high-energy physical experiments. CAN is increasingly used in climate control engineering, where temperature and humidity need to be measured at more than one spot in order to monitor and control the overall climate. Application examples are libraries, museums or factories, which require a very narrowly defined air-conditioning tolerance. Further application areas are the cross linkage of climate sensors in green houses, motor coaches, local transportation, harvesters as well as in printing units. CAN sensors are also in use in warehouses, cooling chambers and grocery shops with centralized monitoring and control of the air-conditioning. Furthermore CAN is used for climate monitoring and control in aquariums and zoos, where inter-connectable temperature and humidity sensors play an important role. Finally, some machines such as telescopes, coffee machines, sport cameras or underwater autonomous vehicles (UAV) have incorporated CAN-bus to their control structure, [2], [3]. Therefore, the extension of CAN applications to residential sectors, offering a flexible, low cost and friendly tool for the customer would be desired, moreover taking into account the deregulated process suffered by the electricity market, where the Demand-Side has to be an active agent in this pool. III. LOAD CONTROL SYSTEM DESCRIPTION A detailed description about the developed load control system is presented in this section. In this way, subsection III- A provides a system equipment description, and subsection III- B, the developed interface software and its main characteristics are described. III-A. Hardware description According to Fig., the hardware architecture can be divided into three subsystems physically differentiated : III-A.. Subsystem of interaction: It is the PC interface module, which establishes the communication between the CAN bus and the action required by the user. A F 7 microcontroller of Microchip has been used for the CAN RS232 interface, and a M CP 255 controller of Microchip through two ports following the SPI protocol for the interface CAN bus. Since it is necessary to turn the signal levels of the controller up to CAN bus compatible levels, a PCA2C25 of Philips has also been used for this purpose. III-A.2. Subsystem of measurements: This subsystem is formed by the power and temperature modules, which measure the active power demanded by the load and the indoor temperature respectively, sending this data through the CAN bus to the PC. In case of monitoring fridge freezers and/or refrigerators, it is also possible to monitor the internal temperature, since each temperature module admit to connect up to temperature sensors, multiplexed by 3 control inputs, Fig. 2. Both modules are directly fed from the power line and, therefore, they do not need any additional DC source. Fig 3 shows the power module structure, where a serial interface has been included in order to set up the measured power value. III-A.3. Subsystem of drive: This subsystem is formed by the switching module, see Fig., which provides the forced switching off periods according to the interruptible load

3 3 F7 Microcontroller MCP255 Positive voltage regulator L75 Transceiver CAN High CAN Low F7 Microcontroller Voltage DC V CAN Low CAN High MCP255 Voltage DC V Positive voltage regulator L75 Commutation Circuit Fig. 2. Temperature module structure Serial Sensor of current Fig.. Switching module structure Transformer Manage Data File - CAN Power module - Forced swithing off-on periods - Microcontroller Amplifiers Telegram traffic - Fig. 3. Power module structure Fig. 5. Graphical interface. General description policies previously fixed by the user. The module consists of a commutation circuit, a microcontroller and a CAN interface. A Ralux relay DN 5 A rms provides the forced switching off and on cycles. For the control signal, two Darlignton are used through a port of the microcontroller. A F7 microcontroller of Microchip is again used for the signal calculation stage and the communication task with the CAN bus. An interface composed by a MCP255 controller and a PCA2C25 transceiver of Philips are also needed and implemented. Two types of telegrams, through the CAN bus, can be received by the subsystem drive: asking about the load state, or switching on(off) the power line. If a request telegram about the load state is transmitted, the microcontroller will answer with another telegram, indicating the On/Off relay state. However, if a switch On/Off telegram is received, the microcontroller will perform physically this operation. module and, consequently, to calibrate the zero power setpoint when the load is switched off. On the other hand, the last and cumulative measurements of active power are also available, Fig.. III-B.2. Measuring and storing data: According to the previous hardware description, the power and temperature data corresponding to each node are viewed in real-time and stored in columns in an ASCII file. This file also contains the date and hour for each one of the measured data. Afterwards, these data can be analyzed by the user and exported to spreadsheet programs. The demanded active power is determined from the voltage and current signal data. These signals are measured with khz sampling frequency, obtaining the instantaneous power and, subsequently, the active power as an average value per cycle 5 Hz, nominal AC frequency. III-B. Software description In order to make easier the load control and monitor tasks, a friendly graphical interface has been designed using LabView software package, see Fig. 5. This developed software package allows the customer to make the following tasks: III-B.. Setting up the power module: It is possible to view and store the current and voltage measured by any power Power Viewer Active Power - Cumulative Measurements Active Power Last Measurement Amplification Factor Fig.. Active power interface Active Power (W) Active Power (W)

4 Fig. 7. Forced Switching off-on periods. Manual mode Temperature Control Sensor Temperature Sensor Temperature 2 Metric (ºC) Metric (ºC) Fig.. interface III-B.3. Applying forced switching off-on periods: The customer can use two different ways in order to introduce forced switching off-on periods in a specific node: manual mode and automatic mode. The first one is based on modifying manually the state of the power line for a specific node, providing an off or on signal when it is desired, see Fig. 7. The second one automatic mode allows the customer to define an ASCII file which contains a zero and one matrix, where each column corresponds to a specific node and each row to a period of one minute. Obviously, zero and one means the forced switching off and on periods respectively, sending these signals through the CAN bus each minute. Since the controlled load are mainly heating and cooling loads, an additional constraint related to the temperature values has been implemented. This consists of a threshold temperature, which can be selected for each node, in order to ensure a minimum comfort level for the customer and avoid high temperatures in refrigerators and fridge freezers. If this threshold is exceeded, the corresponding node will be automatically switching on, Fig.. III-B.. Monitoring the telegram traffic: A secondary window has been implemented in order to monitor and check the data packages and the telegram traffic which flow through the CAN bus. It also allows the advanced customers to send manually a set of telegrams previously defined by the authors, see Fig. 9. IV. EXAMPLE AND RESULTS Different residential loads have been monitored and controlled through the proposed systems. In all cases, an additional CAN bus Debug Telegram list Real Switching Behaviour Refrigerator - Internal Temperature (ºC) Refrigerator Demanded Active Power (W) Time Interval (min) Fig.. Refrigerator control example (I) wiring has been used for the CAN bus, in a similar way to the industrial sector applications. Fig. shows an example about the proposed system performance. As seen, when the threshold temperature is exceeded, the switching module is automatically turned on, spite of the forced duty-cycles are in off-mode. Power demand and temperature evolution are also presented. In the same way, Fig. shows another example for the collected data during a day, where the refrigerator contents are changing along the day. The differences between the desired switching on/off pattern and the real duty-cycles according to the limit of maximum internal temperature are also showed. Air conditioner devices has also been controlled and monitored by means of the developed CAN system. Fig. 2 shows the active power and indoor temperature data when a forced switching-off pattern is applied on the power line during several hours. In this case, the threshold temperature has not been fixed and, therefore, the forced connections and disconnections produce indoor temperature values slightly higher than the normal target temperature, and the customers will suffer internal thermal conditions more and more distant to their desired comfort levels. Hex Send telegram Erase Fig. 9. CAN Bus telegram traffic V. CONCLUSIONS An application of Controller Area Networks to Direct Load Control programs have been described and assessed. The proposed system has been focused on residential customers,

5 5 Real Switching Behaviour External Temperature (ºC) Refrigerator - Internal Temperature (ºC) Refrigerator Active Power (W) Time (hour) Fig.. Refrigerator control example (II) with around 3% share of the global electricity consumption, offering these customers a flexible, low-cost and friendly tool through a graphical user interface environment in order to active their participation in the current deregulated electricity markets. The proposed system has been successfully applied to different real residential environments, mainly heating and cooling loads, which accounts for around 5% of the residential electricity consumption. Some of these results are also presented in this paper. Finally, the dissemination of the proposed system is also an objective and, in this way, all schematic circuits, source files and miscellaneous technical information will be provided on request to the authors. ACKNOWLEDGMENT The work described in this paper is financially supported by the Regional Seneca Foundation of Spain through a research project (Ref. 32/PI/5). 2 Indoor temperature evolution (ºC) Air conditioner Active Power (kw) Time (min) Fig. 2. Air conditioner. Control example REFERENCES Thermostat target temperature [] G. Heffner, Configuring load as a resource for competitive electricity, markets. Review of demand response programs in the U.S. and around the world, Environmental Energy Technologies Division, Ernest Orlando Lawrence Berkeley National Laboratory, November 22. [2] D. Kirschen, Demand-side view of electricity markets, IEEE Trans. Power Systems, vol., no. 2, pp , May 23. [3] S. Rassanti, V. Smith, and B. Wilson, Controlling market power and price spikes in electricity networks: Demand-Side Bidding, Interdisciplinary Center for Economic Science, George Mason University, July 2. [] C. Alvarez, A. Gabaldon, and A. Molina, Assessment and simulation of the responsive demand potential in end-user facilities: Application to a university customer, IEEE Trans. Power Systems, vol. 9, no. 2, pp , 2. [5] L. Associates, A vision of demand response 25, California Energy Commission PIER interim report, January 2. [] M. Farsi and K. Ratcliff, Controlling with CANopen, IEE Review Journal, vol., no. 5, pp , September 99. [7] M. Farsi, K. Ratcliff, and M. Barbosa, An introduction to CANopen, Computing and Control Engineering Journal, vol., no., pp., August 999. [] J. Hu and G. Li, Design of city bus intelligent control system framework, IEEE - International Conference on Mechatronics and Automation, vol., pp , 2. [9] CANopen application fields, CAN in automation, Tech. Rep. [] H. Othman, Y. Aji, F. Fakhreddin, and A. Al-Ali, Controller area networks: Evolution and applications, Information and Communication Technologies ICTTA, vol. 2, pp , April 2. [] The digital home powered by Echelon, Echelon Corporation, Tech. Rep. [2] H. Yoshida, T. Aoki, S. Tsukioka, T. Hyakudome, S. Ishibashi, R. Sasamoto, and Y.Ñasuno, A working AUV using CAN bus interface, th International Offshore and Polar Engineering Conference, vol., pp , 2. [3] W. Liu, L. Gao, Y. Ding, and J. Xu, Communication scheduling for CAN bus autonomous underwater vehicles, IEEE - International conference on mechatronics and automation, vol., pp , 2.