Tuyển tập công trình Hội nghị Cơ điện tử toàn quốc lần thứ 6 739 Mã bài: 160 Development of an adaptive temperature control for HVAC to intelligent energy management system in buildings at DaNang city Đề xuất bộ điều khiển thích nghi nhiệt độ cho thiết bị HVAC để quản lý thông minh hệ thống năng lượng trong các tòa nhà tại TP Đà Nẵng N. M. Tri 1 , N. H. Anh 2 , T. Q. Tuan 3 , H.D. Hoan 2 , N.D.H.Phuong 4 1 Vietnam Electricity-EVN nminhtri@cdmt.vn 2 QuyNhon University, Vietnam nhanh@qnu.edu.vn; huynhduchoan@qnu.edu 3 IDEA, Grenoble-INPG, France Senior Member, IEEE Abstract: In order to use loads in an active and intelligent way to resolve technical problems in the networks or contribute to ancillary services (smart grid), this paper presents a new method of air-conditioning control that allows to reduce the peak consumption by maintaining thermal comforts. This control is based on the variable set-point temperature of air conditioning adapted to the permissible power. This power can be fixed by outdoor signal from DNO (Distribution Network Operators). In addition, this method relies support on a wireless sensor network (WNS) which allows to measure in realtime simultaneously the internal temperatures and the power consumption. The protocol Zigbee is used for the communication between wireless temperature sensors. The proposed air-conditioning control is tested by simulation under EMTP-RV with satisfied results for a distribution network containing air-conditioners at DaNang. These results show that the proposed solution can be efficiently applied for a group of loads, buildings (such as a virtual consumer) in distribution networks in order to reduce the peak consumption in the distribution network. Keywords— Air conditioning, direct load control, adaptive control, peak load reduction, distribution network, Zigbee, wireless sensor network, WNS. Toám tắt: Để giải quyết các vấn đề về kỹ thuật, dịch vụ trên lưới điện cần có phương pháp điều chỉnh nhu cầu sử dụng tải một cách chủ động và linh hoạt, bài viết này trình bày một phương pháp mới để điều khiển thiết bị điều hòa không khí; cho phép giảm tiêu thụ cao điểm mà vẫn duy trì các tiện nghi về nhiệt. Điều khiển này dựa trên việc thiết lập nhiệt độ của điều hòa không khí thích ứng với công suất làm việc cho phép. Công suất này có thể được cố định bởi tín hiệu bên ngoài(Nhà cung cấp và phân phối điện). Ngoài ra, phương pháp này có sự hỗ trợ của một mạng cảm biến không dây (WNS) cho phép đo trong thời gian thực đồng thời nhiệt độ và công suất tiêu thụ điện. Giao thức Zigbee cho phép giao tiếp giữa các cảm biến nhiệt độ không dây. Việc kiểm soát bằng phương pháp đề xuất được thử nghiệm trên phần mêm EMTP-RV trên một mạng lưới phân phối có điều hòa nhiệt độ tại Đà Nẵng. Những kết quả này cho thấy rằng các giải pháp được đề xuất có thể được áp dụng quản lý hiệu quả cho một nhóm tải, các tòa nhà… để giảm công suất tiêu thụ trong giờ cao điểm hoặc khi điều độ yêu cầu của lưới điện phân phối. 1. Introduction: oad management is defined as sets of objectives designed to control and modify the patterns of demands of various consumers of a power utility. Load management permits to limit or shift peak load from on-peak to off-peak time periods. Load management is dedicated to control systems which monitor and plan the energy demand of a building or larger zone. They can be programmed to control lighting, thermal comfort equipment, HVAC, refrigeration equipment, pumps, valves and motors (Fig. 1). The sector of the building presents one of the greatest potentials of energy efficiency and reduction of the gas emissions. The use of the loads in an active and intelligent way and optimal load management is one of the major L 740 N. M. Tri , N. H. Anh, T. Q. Tuan , H.D. Hoan , N.D.H.Phuong VCM2012 concerns of the managers, the providers and the consumers of energy. The peak consumption reduction is one of the most effective solutions of energy management systems. This reduction presents many interests:  For the customers: reduce the bill for the subscription and consumption in peak hours,  For the DNO (Distribution Network Operator): avoid the congestion and the problems caused by overloads,  For the energy provider: limit the purchase of an expensive energy. In order to develop the intelligent electric distribution networks in the future (Smart Grid), direct load control for controllable loads plays an important role. Loads become active and intelligent. The loads participate to resolve technical problems in the networks or contribute to ancillary services such as voltage control, congestion management… The air-conditioning is a controllable load. For tropical countries in summer, it takes an important part in the tertiary and residential buildings. Demand Side Management (DSM) considers air-conditioning load as one of the most suitable loads to implement direct customer load control in order to exercise peak demand control as well as energy consumption control in supply systems [1-8]. In DSM, the air- conditioning units located at customer premises are directed to enter energy/demand saving control modes by means of control signals issued by DNO from sub stations either via remote radio link or via power line carrier communication link at distribution level when the utility wants to exercise demand control during periods of power shortage. Therefore the management of air conditioners has an important potential to reduce the peaks of consumption and permits to contribute to ancillary services in distribution. Figure 1. Energy and load management system In Vietnam, the electric power consumption is always superior to the electric power production. The load sheddings in on-peak periods in order to avoid over load or blackouts are inevitable. The air-conditioning takes an important part in the tertiary and residential buildings. This is why the direct load control of air conditioning presents one of the best solutions to reduce peak consumption. In this paper, an adaptive control of air- conditioning units is proposed. Then the proposed solution is applied for a distribution network in order to reduce the peak load consumption and to avoid congestion. 2. Load control 2.1 Techniques of load control Techniques of load control can be presented in the following: Time- Of- Use-Tariff, Interruptible Load Tariffs, Distribution System Loss Reduction (ex: reactive compensation). 2.2 Measurement for load management Load control can be realised for lighting load and HVAC. Load control strategies can be presented as following:  Fixed Priority Strategy Priority strategy sheds the least important loads first and the most important last. The last load shed is the first to be restored.  Fixed Priority Strategy Priority strategy sheds the least important loads first and the most important last. The last load shed is the first to be restored.  Rotate Strategy The rotating sequence provides for an equal distribution of power to all controlled loads.  Combination Fixed/Rotate Strategy This is the most versatile and powerful strategy because so many combinations are possible.  Adaptive Control Strategy This is an intelligent strategy by using an adaptive control for variable set-point values. 3. Principle of the adaptive control of air-conditioner 3.1. Model of air conditioner The operation of an air conditioner is based on the phase change of a fluid refrigerant: evaporation occurs with heat absorption, condensation with heat production. Therefore, in any air conditioner there is: Tuyển tập công trình Hội nghị Cơ điện tử toàn quốc lần thứ 6 741 Mã bài: 160 - An exchanger evaporator where cooling associated with the evaporation of refrigerant is transmitted to the ambient air; - A compressor compressing the gaseous fluids, increasing pressure and temperature; - An exchanger condenser where gas transfers its heat by condensing; - A relief valve decreasing the pressure of the liquid refrigerant before its evaporation in the heat exchanger. In this paper, the electrical analogue model for an air conditioned house proposed in [7] is used Fig. 2 shows the model of an air conditioning developed with EMTP-RV. From this model, we propose a new method based on the adaptive control of air-conditioner for load management system. Iac S(t) Is Rw Rw C w Ci To R c To Tw Ti Iinst Figure 2. Electrical analogue model for an air conditioned house Where:  Rw, Cw: the equivalent thermal conduction resistance and thermal storage capacity of the house (wall, base, roof)  Rc, Ci: the equivalent thermal conduction resistance of the average air infiltration and thermal capacity of the air inside the house  To, Tw, Ti: the exterior temperature, the wall temperature and interior temperature  Is : the current source of two components (solar irradiation and the portion of internal heat sources involved in this indirect heating of air)  Iinst: the current source of heat source produced by lamp, computer, the body…  Iac: The heat removed by the air conditioner  S(t): The switching function (= 1 when the compressor motor is ON and = 0 when the compressor motor is OFF). In Fig. 2, the equivalent thermal conduction resistance of inside-wall and outside-wall (Rw) are assumed to be equal. The differential equation system is obtained by applying Kirchoff’law at the nodes: Where Tw and Ti are the unknown variables. RwCw Tw RwCw To RwCw Ti Cw Is dt dTw 2  (1)   RcRwCi Ti RwCi Tw RcCi To Ci tIacS Ci Iinst dt dTi 11 )(  (2) Where Tw and Ti are the unknown variables. The Fig. 3 shows the EMTP-RV model of the air conditioner that is built from this differential equation system. In order to connect to distribution network, the air conditioner is modeled with EMTP-RV by a current injection. f(u)1 Fm1 f(u)1 Fm12 f(u)1 Fm13 f(u)1 Fm14 + + + + + sum6 f(u)1 Fm15 f(u)1 Fm16 f(u)1 Fm17 f(u)1 Fm18 f(u)1 Fm20 + + + + + + sum7 !h Int3 !h Int4 f(u) 1 2 3 Fm2 2 c #P_AC# C1 + + + + sum8 c #T_Set# C4 scope T_int c C10 1 Ftb3 f(u) Fm2 3 Ftb4 c C11 0 scope T_ext scope Sola r f(u)1 Fm2 4 -1 Gain 1 scope Q_AC -1 Gain 2 scope scp6 f(s) fs1 f(u)1 Fm2 5 scope P_AC P_Depas f(u)=0 1 2 Relay Iinst scope F _ A C Figure 3. Air conditioner modelized using EMTP-RV 3.2. Proposed adaptive control In general, a modern air conditioner is equipped with a temperature regulator (called classical control). This regulator is used to maintain the temperature in a specified value and carried out by a thermostat (a bimetal or an electronic thermostat). The classical controls can ensure the thermal comfort, but this method is not able to vary the power consumption and can also cause an excess from a permissible power fixed by outdoor signal from DNO (Distribution Network Operators). In order to reduce the peak consumption for a network in presence of air conditioners, this part presents a development of an adaptive temperature control for air conditioning. In the normal operation (without excess of contractual demand or without outdoor signal from DNO or energy provider), the regulator operates like a normal temperature regulator to ensure thermal comfort (Ex: Tset-point ±1 where Tset-point is constant and fixed). 742 N. M. Tri , N. H. Anh, T. Q. Tuan , H.D. Hoan , N.D.H.Phuong VCM2012 Classical regulator Air conditioning M eteorologies Conditions P_permissible Temperature regulator PID and Fuzzy - T_room P_total Temperature Set-point Thermal model of building ( surfaces, walls, windows ) + Adaptive module + - Adaptive conversion ΔP  ΔT Figure 4. Principle of the proposed air conditioning control In case of excess of contractual demand or with outdoor signal (ex: congestion signal generated by DNO), the regulator switches to the adaptive regulator mode with a variable set- point value of temperature in order to limit the peak of consumption to a predefined level. The principle of the proposed air conditioning regulator is represented in Fig.4. In case of excess of contractual demand or with outdoor signal, this signal converts it into a temperature variation corresponding to required reduction power. This value is transmitted to each air conditioning in order to modify the set- point temperature. In a distribution network with different houses, the permissible power signal of DNO is generated from sub stations. 4. Real-time control using Zigbee sensor network for energy management system in buildings In the light of developments in microelectro- mechanical systems (MEMS), along with progress made in communication and embedded smart sensors, the residential sector has a huge potential for mitigating demand. The possibilities of creating networks between home appliances, sensors and wireless media, enable the control of domestic equipment locally or remotely via the Internet. The development of WNS, with the Zigbee technology allows us to establish more sophisticated control based on the combination of measured information and intelligent control in order to improve the use of electrical equipments. The advantages of this type of technology ZigBee include:  Elimination of all costs related to the physical connection of devices.  Possibility of establishing a single communication interface between several devices, using a communication protocol supported by numerous manufacturers.  Ability to automatically reconfigure the communication network each time a new element is added. This application relies on a wireless sensor network (WNS) which allows simultaneous, real-time measurement of indoor temperature and power consumption. The ZigBee communication protocol is used between wireless temperature sensors and equipment. Table 1. Electrical appliances of the apartement Name Description air conditioning Traditional air conditioning Actuator Implements control actions from the control unit ZigBee layers ZigBee layers for communication This system comprises an array of wireless temperature sensors, a wireless electrical power sensor, radiators equipped adaptive controls, and a central control unit (Fig.5). Figure 5. Architecture of system The Wireless Electrical Power Sensor comprises two components: a power sensor and a communication unit. The first component is used to measure power consumption instantaneously. The communication unit transmits this information to the central cont rol unit. The wireless electrical power sensor receives the consum ption information and detects excessive power (beyond the authorized power limit). air conditioning air conditioning Tuyển tập công trình Hội nghị Cơ điện tử toàn quốc lần thứ 6 743 Mã bài: 160 The central control unit : in our system, the control unit is a computer equipped with a wireless communication module and control software. The central control unit analyzes the information received. The central control unit processes the temperature and power measurements and makes decisions to control the air conditionings in an intelligent manner, maintaining comfort and keeping power consumption below the authorized power limit. The array of Wireless Temperature Sensors is programmed to measure temperature within the building at all times. After collection, this information is transmitted to the central control unit via a ZigBee communication link. 5. Application for a distribution network at DaNang city The proposed temperature control is used for air conditioner load in a LV rural distribution network at DaNang city as shown in Fig. 7. This network is connected with a MV network via a 100 kVA, 22/0.4 kV transformer. This network contains 12 air conditioners with 5kW for individual houses. Other loads (lightning, freezer, refrigerator, cooker, washing- machine…) are considered as an equivalent load in each house. Fig. 6 shows the daily variation of these loads (active and reactive power). The maximal active power is 5 kW. The power factor of equivalent load is 0.93. The total consumption of each house includes two parts: consumption by air-conditioner and consumption by this equivalent load. The exterior temperature variation is presented in Fig. 8. Total equivalent power obtained from solar irradiation (Is) for each house is showed by (Fig. 9). We suppose that the load variation, the exterior temperature variation and the solar irradiation are identical for all houses in this network. Figure 6. Daily variation of residential loads in each house without air conditioners + 1 R3 + 1 R1 LF LF1 Slack: 20.5kVRMSLL/_0 Phase:0 + 5nF C1 p1 p2 N1 N2 ALM 70_1 30m PI p1 p2 N1 N2 ALM 70_ 185m PI p1 p2 N1 N2 ALM 70_ 1000m PI p1 p2 N1 N2 ALM 70 _346m PI p1 p2 N1 N2 ALM 70_416 PI p1 p2 N1 N2 ALM7 0_130m PI p1 p2 N1 N2 ALM7 0_251m PI p1 p2 N1 N2 ALM3 5_145m PI p1 p2 N1 N2 ALM 35 _157m PI p1 p2 N1 N2 ALM 35 _121m PI p1 p2 N1 N2 ALM 35_ 130m PI p1 p2 N1 N2 ALM 35_ 127m PI p1 p2 N1 N2 AL9 5_50S_470m PI 1 2 DY_1 20/0.42 + S_HTA 20.5kVRMSLL /_0 Slack:LF1 p V_pu V4 p V_pu V5 p V_pu V3 p V_pu V2 P ic p1 50Hz Qic p2 50Hz L_AC N Load_AirConditi oning L_AC_5 L_AC N Load_AirConditioning L_AC_4 L_AC N Load_AirConditi oning L_AC_3 L_AC N Load_AirConditi oning L_AC_6 L_AC N Load_AirConditioning L_AC_7 L_AC N Load_AirConditio ni ng L_AC_14 L_AC N Load_AirConditio ni ng L_AC_9 L_AC N Load_AirConditi oning L_AC_10 L_AC N Load_AirConditioning L_AC_12 L_AC N Load_AirConditioning L_AC_13 L_AC N Load_AirConditioning L_AC_11 L_AC N Load_AirConditi oning L_AC_8 AAR AAR HTA LV2 LV11 LV14 LV5 LV4 LV3 LV6 LV7 LV12 PV13 LV10 LV9 LV8 T_Red Figure 7. Rural distribution network with air conditioners simulated with EMTP-RV 5.1 Classical temperature control For this case, the set-point temperature of each house is 20°C (±1°C) and all the air-conditioners use the classical temperature control. The permissible power is fixed to 100 kVA. This is the rated power of the HV/LV transformer. Fig. 10 shows the total power measured at the transformer. It shows that there is a 10% overload 0 2 4 6 8 10 12 14 16 18 20 22 24 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Times (H) Power load (kW, kVAR ) 744 N. M. Tri , N. H. Anh, T. Q. Tuan , H.D. Hoan , N.D.H.Phuong VCM2012 between 17 and 21H. The power of air-conditioner and the interior temperature of the house at bus 4 are presented in Figs. 11 and 12. Figure 8. Exterior temperature Figure 9. Total power obtained by solar irradiation for each house 0 2 4 6 8 10 12 14 16 18 20 22 24 0 20 40 60 80 100 120 Times (H) Total power (kW, kVAR, kVA) P Q S Smax = 100 kVA Figure 10. Total power (classical control) of the network 0 2 4 6 8 10 12 14 16 18 20 22 24 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 Times (H) Air-conditioning power (kW) Figure 11. Power of air conditioner of the house at bus 4 0 2 4 6 8 10 12 14 16 18 20 22 24 18.5 19 19.5 20 20.5 21 21.5 Times (H) Interior temperature (°C) Figure 12. Interior temperature of the house at bus 4 0 2 4 6 8 10 12 14 16 18 20 22 24 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 Times (H) Voltage (pu) Va Vb Vc Figure 13. Three phase voltage at bus 4 (with classical control) It shows that the interior temperature is maintained at 20°C (±1°C). The thermal comfort is assured for all houses. Fig. 13 shows the three phase voltage variation at bus 4. In light load (0-6H) the voltage is high, and in heavy load (10-22H) the voltage is low. The voltage is always maintained between 0.9 and 1.1 pu. 5.2 Proposed method In this case, the adaptive control is applied for all air-conditioners in this network. The set-point temperature of each house is 20°C (±1°C). 0 2 4 6 8 10 12 14 16 18 20 22 24 0 20 40 60 80 100 120 Times (H) Total power (kW, kVAR, kVA) P Q S Smax = 100 kVA Figure 14. Total power without load control of the network 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 Times (H) Exterior temperature (°C) 0 2 4 6 8 10 12 14 16 18 20 22 24 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Times (H) S olar irradiation po wer (kW ) Tuyển tập công trình Hội nghị Cơ điện tử toàn quốc lần thứ 6 745 Mã bài: 160 0 2 4 6 8 10 12 14 16 18 20 22 24 0 1 2 3 4 5 6 Times (H) Air conditioning power (kW) Figure 15. Power of air conditioner of the house at bus 4 0 2 4 6 8 10 12 14 16 18 20 22 24 18.5 19 19.5 20 20.5 21 21.5 Times (H) Interior temperature (°C ) Figure 16. Interior temperature of the house at bus 4 0 2 4 6 8 10 12 14 16 18 20 22 24 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 Times (H) Voltage (pu) Va Vb Vc Figure 17. Three phase voltage at bus 4 Fig. 14 shows the total consumption power of the network. The maximal power is always inferior to 100 kVA. With the help of the proposed method, the overload in transformer is avoided. Fig. 15 presents the operation of the air-conditioner at bus 4. The thermal comfort is maintained in this case (Fig. 16), because the maximal interior temperature is always inferior to 21°C for all houses. Fig. 17 shows the three phase voltage variation at bus 4. It shows that the voltage in heavy load is improved in comparison with the classical control case. This method can be applied to voltage control. With the help of this method, the thermal comfort is assured if the permissible power is reduced to 90 kVA (-10%) and the set-point temperature (T setpoint ) is 21°C. When the permissible power is lower than 0.9Smax (90kVA) the thermal comfort is broken. It means that with a peak load reduction to avoid congestion superior to 10%, the comfort is not maintained with T setpoint =21°C (±1°C). If the permissible power, fixed by DNO, is 0.8 Smax (80 kVA), the maximal temperature is increased to 23.5°C. This is equivalent to 20% of load shedding. 6. Conclusion The results of simulation show that the proposed method permits to reduce efficiently the peak consumption while maintaining thermal comfort. The suggested method can be applied for the various types of loads (ex: heating) and adapted to the context in the future by taking into account the economic and technical signals from manager and DNO (ex: congestion, dynamic tariff…). The obtained results show that this method can be applied to contribute to ancillary services such as voltage control in distribution networks. The proposed solution is applied to a group of loads or buildings (such as a virtual consumer) in order to reduce the peak consumption (or congestion management) in a large distribution network. In order to reduce peak consumption, this method avoids a violent load shedding. This control only modifies adaptively the set-point value of temperature for each air conditioner to obtain a desired (permissible) power, fixed by DNO. On the one hand, this method avoids a hard optimal calculation with a slow response. On the other hand, this solution avoids a load prevision that is sometimes not accurate and very complicated. References [1] D. Bargiotas and J.D. Birdwell, "Residential air conditioner dynamic model for direct load control," IEEE Trans. Power Delivery, vol. 3, no.4, pp.2119-2126, October 1988. [2] M.W. Gustafson, J. S. Baylor, and Gary Epstein, "Estimating air conditioning load control effectiveness using an engineering model," IEEE Trans. Power Systems, vol. 8, no.3, pp.972-978, August 1993. [3] D. C. Wei and N. Chen, "Air conditioner direct load control by multi-pass dynamic programming," IEEE Trans. Power Systems, vol. 10, no.1, pp.307-313, February 1995. [4] Chi-Min Chu , Tai-Lang Jong and Yue-Wei Huang, “Mitigating DLC Constraints of Air- conditioning Loads Using a group-DLC Method”, General Meeting IEEE, 2007. [5] Chi-Min Chu , Tai-Lang Jong “A novel direct Air-conditioning load control method”, IEEE Trans. on Power Systems, Vo. 23, No. 3, Aug. 2008. 746 N. M. Tri , N. H. Anh, T. Q. Tuan , H.D. Hoan , N.D.H.Phuong VCM2012 [6] D. Bargiotas and J.D. Birdwell, "Residential air conditioner dynamic model for direct load control," IEEE Trans. Power Delivery, vol. 3, no.4, pp.2119-2126, October 1988. [7] Suresh Kumar K.S. “Control Strategies for Energy Conservation in room air conditioning units – Matlab/Simulink simulation Study”, Department of Electrical Engineering, National Institute of Technology Calicut, Calicut-673601, Kerala State, India. [8] Qinhua, H., et al. "Two ANN-Based Models for a Real MVAC System", International Conference on Wireless Communications, Networking and Mobile Computing, WiCom 2007. [9] K. Le, T. Tran-Quoc, JC Sabonnadière, Ch. Kieny, N. Hadjsaid, “Peak load reduction by using heating regulators”, CIRED, Vienna, 21-24 May 2007. . temperature control for HVAC to intelligent energy management system in buildings at DaNang city Đề xuất bộ điều khiển thích nghi nhiệt độ cho thiết bị HVAC để quản lý thông minh hệ thống. để điều khiển thiết bị điều hòa không khí; cho phép giảm tiêu thụ cao điểm mà vẫn duy trì các tiện nghi về nhiệt. Điều khiển này dựa trên việc thiết lập nhiệt độ của điều hòa không khí thích. lưới phân phối có điều hòa nhiệt độ tại Đà Nẵng. Những kết quả này cho thấy rằng các giải pháp được đề xuất có thể được áp dụng quản lý hiệu quả cho một nhóm tải, các tòa nhà… để giảm công suất