INVESTIGATION OF THERMOSTAT-SET CONTROL AS A NEW DIRECT LOAD CONTROL METHOD

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1 INVESTIGATION OF THERMOSTAT-SET CONTROL AS A NEW DIRECT LOAD CONTROL METHOD Canbolat Uçak canbolat@elk.itu.edu.tr Gökçe Dokuyucu gokce776@uperonline.com Department of Electrical Engineering Electrical & Electronic Faculty Itanbul Technical Univerity Malak, Itanbul, Turkey Abtract The goal of Direct Load Control i to reduce daily peak demand and to maximie the utility profit with leat reduction of dicomfort caued to conumer erved. In thi paper, a new Direct Load Control method called Thermotat-et control i preented. Thermotat-Set Control method i baed on the direct acce to the thermotat of conumer' load from the ditribution management center or dipatch center. Controlled conumer load i uually a heater or an air conditioner. Thi new control method i imulated by uing a phyically baed load model, which account the behaviour of the thermotatically controlled load in the ditribution ytem. Thermotat-Set Control method i compared to Load Cycling Control method and concluion are preented. Keyword: Demand-Side Management, Direct Load Control, Load Modelling, Load Cycling Control method, Thermotat-Set Control method. I. INTRODUCTION Demand-Side Management could be defined a planning and implementation of the utility activitie, which are deigned to influence cutomer ue of electricity, in way that will produce deired change in the magnitude and hape of utility load. Change of load hape may be needed to meet peak demand or to repond flexibly to the price change in the deregulated power market without contructing new power plant. Load Control i an application of Demand-Side Management. Load Control ha different apect uch a reducing peak demand, maximiing utility profit and minimiing dicomfort caued to cutomer. Load control program are being developed to help utilitie ue their generation facilitie more efficiently. Thee ytem will hift load to off-peak time or actually reduce the amount of electric energy required. Load control can be claified into two group; indirect load control and Direct Load Control (DLC). Indirect load control i applied upon a contract between the cutomer and the electric utility company; which offer cutomer different time-of-day tariff for the ue of electricity. Many work have been done in the literature dealing with the demand ide management [1-6]. There are two different group of individual load in ditribution ytem; thermotatically controlled and manually controlled load. Thermotatically controlled load are witched to on tate or to off tate depending on the et value and dead band of their thermotat. Manually controlled load are witched on and off by occupant of the houe in undetermined fahion. The lifetyle of the occupant of the houe ha a ignificant influence on the contribution of thee load to the total load of the houe. In DLC, thermotatically controlled load are preferred becaue thee load could be interrupted for a hort duration without leading to a ignificant decreae in the comfort level of cutomer. There are many tudie on modelling thee type of load [7-12]. The concept of load model i important becaue it enable to etimate the poible effect before control i applied on a real ytem. Therefore, the load model hould be expected to reliably reflect the dynamic of the device. Load model can be categoried into two group; tatitically baed and phyically baed load model. Load model baed on tatitical analyi of hitorical data may not reflect the effect of load control application. But, phyically baed load model may reveal the effect of load control action in a ditribution ytem. Another feature of phyically baed load model i that, the effect of model parameter on the aggregated load could alo be analyed eaily. In thi paper, a new DLC method called Thermotat-Set Control (TSC) method i preented. Firt, the firt-order time-varying differential equation model i adapted. Then, the firt-order time-varying load model i converted to a dicrete time model and imulated by uing Monte

2 Carlo method developed with C programming language [13]. Alo, Load Cycling Control (LCC) method i imulated and compared to TSC method. The reult of the tudy are ummaried in the concluion part of the paper. II. DYNAMIC OF AN AIR CONDITIONER The load model preented by Ihara and Schweppe [12], a a firt order hybrid differential equation, i given in Equation 1 below. d ( t) 1 = [ ( t) a + w( t) g ] (1) dt τ Here, the parameter are a follow; (t) ( ο C) i the inide temperature of the houe, a ( ο C) i the ambient temperature, g ( ο C) i the temperature gain of air conditioner, and τ (hr) i the time contant of the houe. The variable i a binary variable denoting the tate of the air conditioner. When the air conditioner i off it value i zero and when it i on it value i one. The tate of an air conditioner change when the temperature of the houe reache the thermotat upper or lower limit, given by + / 2 and / 2, repectively. When the inide temperature of the houe reache the upper limit, air conditioner tate change from zero to one, and when the lower limit i reached, the tate change from one to zero. Figure 1 how the tate of thermotat and the houe temperature a a function of time when the ambient temperature i contant. III. STOCHASTIC DIFFERENCE EQUATION MODEL There are many different load model that can be ued to account for the behaviour of thermotatically controlled load tarting from a very imple firt order differential equation model to much more complex higher order model, tatitical aggregated load model, or tochatic difference equation model. Stochatic difference equation model i derived from the firt order hybrid differential equation given by Equation 1. The ignificant difference of tochatic difference equation model from the other type of load model i that it i uitable for the computer analyi. Thu, in Monte Carlo imulation houe are modelled with tochatic difference equation hown in Equation 2 and Equation 3, below. Equation 3 model the thermotat tate change when the temperature of the houe reache the upper and lower limit of the dead band. The aumption i that the thermotat alway witche exactly at ampling intant. Time, t, i made dicrete by h /τ uing a ampling period h with the notation a = e and b = 1 a a in reference [11], the difference equation for air conditioner load will be [( n + 1) h] = a ( + b[ c( w( ] V ( (2) a g + 0, if ( < / 2 w[ ( n + 1) h] = 1, if ( > + (3) / 2 w( Otherwie In Equation 2, V( i a Gauian white noie dicrete time proce with zero mean. DLC action can be incorporated to Equation 2 and Equation 3. For LCC control action, the term c (, which i a binary variable, can be ued to imulate the control action end from the ditribution management center or dipatch center. Alo TSC action can be imulated by changing the thermotat et value in Equation 3. IV. LOAD CYCLING CONTROL AND THERMOSTAT-SET CONTROL METHODS Figure 1. The tate of thermotat and houe temperature a a function of time during teady tate ([14], page 15). In Figure 1, a three dimenional picture of an air conditioner dynamic i hown for teady tate. The hyterei loop of thermotat tate can be een when it i looked to the figure from the time axi direction and the change of temperature of the houe can be een when it i looked from the direction of w (t) axi. LCC method i a commonly ued method to reduce daily peak demand. The cycling i accomplihed by the ignal ent from the control center to the group of thermotatically controlled load. The principle of LCC method i firt grouping the device and then witching one group of device to off tate for certain duration. All group are witched off in different time interval. For example, if four group are exit, each group will be witched off for 15 minute, that i, the period of cycling i one hour o that each group will be off 15 minute and will be left alone for 45 minute to continue it natural cycle. In the following 15 minute, the next group will be witched off and thi cycle will continue until to the end time of control period. Figure 2 how the LCC Method

3 applied to one thermotatically controlled device. When the device i forced to witch off then there will be a payback duration to recover the interrupted energy a hown in Figure 2. One of the ucceful tudie on application of DLC in ditribution ytem had been done by South California Edion Company [1]. In thi tudy, controlling 100,000 air conditioner from the center, by offering 50%, 67%, and 100% control alternative to the cutomer had reduced the peak in the ytem. The conumer air conditioner were interrupted in-group at different time. ON OFF ON OFF Signal ent to increae the Temperature Set value by Load Cycling Control Period Payback Figure 2. Principle of LCC method. + Hyterei loop hift (t) Figure 3. Principle of TSC method. Termotat-Set Control method introduced in thi paper i alo a DLC method. The principle of the method hide behind the adjutment of the temperature et value of the thermotat of the controlled device. To achieve thi, it i aumed that the thermotat et value of thermotatically controlled device can be adjuted from control center. The adjutment of the temperature et value i ent a a ignal from the electric utility, to all of the controlled air conditioner, that i, the device allow their et value to be changed from a remote center. Figure 3 how the principle of TSC method. In Figure 3, a ignal from the ditribution center i ent to the air conditioner to increae it temperature et value by. The new temperature et value will be equal to + and hyterei loop will hift to the left a hown in Figure 3. Thi will reult with the reduction of conumed power of air conditioner. In t t Reduction in Conumed Power thi tudy, air conditioner, which are thermotatically controlled load, have been choen a the controlled load in a ditribution region. Control ignal ent from the center to increae the temperature et value of air conditioner will reduce the aggregated load in the ytem. Objective of TSC method i to achieve a ignificant reduction in daily peak load while minimiing the decreaed comfort level of cutomer caued by the control action. Comfort level of cutomer i important in today' utilitie becaue of the competition introduced a a reult of deregulation. The competition among the electricity upplier and provider are tough, therefore the electric utilitie now pay more attention to their cutomer need. V. MONTE CARLO SIMULATION Temperature hitogram and graph of total power change had been analyed uing Matlab and it had been oberved that the temperature-et control method i effective in reducing peak power a well a maintaining the comfort level of cutomer [13]. But, thee reult can not be accepted for getting a tatitical concluion about thi method ince the imulation are made for only forty houe. Therefore, there had been a need for a larger ytem to be tudied. Thu, Monte Carlo imulation had been tudied for 10,000 houe. Monte Carlo imulation had been done uing C programming language. 10,000 houe had been imulated with thi program. Each houe i modelled with tochatic difference equation a given in Equation 2 and Equation 3. LCC and TSC method had been imulated for the parameter given in Table 1. In Table 1, the mean and the variance of the parameter are hown. The mean and the variance are ued in a gau random generator to generate parameter value, pecific for each houe to account for the diverity of the ytem. That i, 10,000 houe will have different value for their parameter. Table 1. Parameter of tochatic difference equation for 10,000 houe. Parameter µ σ V 0 ο C / min ο C ο C 6.00 g 2 ο C 0.3 τ 120 min 20 LCC method, which the application to a true ytem exit in ome utilitie, and new TSC method are compared in Figure 4. Both LCC method and TSC method are applied between the time 11:00 and 23:00. In

4 Figure 4, the normalied load change without any control action i hown a NoC to have a a reference for the controlled cae. In LCC method, 10,000 houe are divided to four group of each having 2500 houe. Each group are controlled for 15 minute in conecutive time egment and releaed for 45 minute to continue to their natural cycle. The normalied load change for the control action i hown in Figure 4 a CycC. With thi LCC method the peak load ha been reduced by 15% approximately. There i load deep at the beginning and payback at the end of entire control period. But, thee load tranient are not very ignificant and epecially they do not exceed the peak load during the control period. Normalized Load TSC-2 NoC TSC-4 CycC Hour Figure 4. Normalied load change when LCC and TSC method are applied. TSC method i imulated for two different thermotat-et value. The firt one i when the thermotat-et value of the houe are increaed by 2 o C. The reulting load change i hown in Figure 4 a TSC-2. With 2 o C control, approximately 5% load reduction i achieved. The econd imulation for TSC method i done with 4 o C increae in thermotat-et value of the houe. In thi cae, the normalied load change i decreaed around 5% more during the entire control period a hown in Figure 4 with legend TSC-4. The LCC method (hown a CycC) and TSC method (hown a TSC-4) give approximately the ame peak value in the control period conidered. Epecially, the normalied load change between the time 14:00 and 16:00 i comparable for both of the control action. In TSC method, the load deep at the beginning and the payback at the end of the control action are more than thoe of the LCC cae. When the control i applied, the aggregated load approximately become zero and when the control i finihed, the payback magnitude reache the maximum value of 1. The reaon for that i becaue the thermotat-et value of whole air conditioner increaed by 4 o C and thi caued the houe temperature value to be le than the upper limit of the dead band in the beginning of the control duration. Thu, air conditioner tate for the mot of the houe became zero. Alo, imilar concluion can be drawn for the payback magnitude. Grouping the air conditioner a it i done in LCC method can reduce thee unwanted high magnitude. In thi paper, cutomer comfort level i conidered, therefore method which deal with the reduction of magnitude are not tudied. Application of load control to the cutomer will affect their houe temperature. In the air conditioner cae, it will increae the average temperature inide the houe. Thu, the comfort level of the cutomer will be reduced accordingly. For 10,000 houe, it will be intereting to ee the ditribution of the houe temperature when the control method are applied. Thi will give an indication of how much the temperature ditribution ha hifted and changed when the control i applied. Cauing too much increae in the houe temperature reult with many unatified cutomer and it could danger the load management program. The ditribution of houe temperature of the 10,000 houe i hown in Figure 5 for uncontrolled (NoC), LCC (CycC), and TSC cae. The ditribution of houe temperature hown in Figure 5 can be cloely repreented with Gamma ditribution. The ditribution of TSC of 4 o C i imilar to that of the uncontrolled cae with approximately 4 o C hift to the left. The ditribution of temperature in LCC method i wider and it ha more houe with higher temperature over 26 o C when it i compared to the TSC-4. The number of houe with lower temperature i alo higher in LCC method compared to that of TSC cae. The ucce of load management program i more affected by the higher temperature region becaue cutomer with higher temperature will complain more and may give up to participate in load management program. Thu, utilitie hould be careful on deciding what type of control action mut be performed to keep cutomer atified. Number of Houe NoC TSC-4 CycC Temperature (Degree Celciu) Figure 5. Temperature ditribution of 10,000 houe at 4 pm when LCC and TSC method are applied. Both TSC and LCC method reduce the peak load when control i applied. The magnitude of load reduction depend on both to the ytem parameter and to the control trategie applied. In LCC method, the number of houe with higher temperature may be larger than TSC

5 method. Therefore, it may caue more cutomer related problem to the utilitie. A utility hould carefully examine the option for DLC to reduce the number of unatified cutomer a an outcome of the load management program. Application of TSC action may reult over-reduction of the load in the beginning and high payback at the end of the control duration a it i mentioned before. Two olution to thi problem may be ued. Firt olution may be the application of TSC in a whole day that prevent the payback that lead to a evere peak a tated above. But thi i not a uitable olution becaue the cutomer would be facing higher temperature a a reult of the load control application even at the night time. Although load control i not needed at night time of a day, a the temperature i not a high a the daytime, control would lower the comfort level of cutomer. The other olution may be grouping of the houe. Grouping would lower the number of interrupted houe in certain interval of time and thi will reult with the maller over-reduction and payback. VI. CONCLUSION It i oberved that new Thermotat-Set Control method i effective in reducing peak power in noticeable rate. The tudy pointed out that TSC application can be better than the LCC cae in higher temperature range. In other word, the number of houe with higher temperature i le than that of LCC. Thi i an important reult becaue the ucce of DLC depend on the number of atified cutomer. Load management procedure mut reduce the number of unatified cutomer to be able to ue the peak load reduction method. Cutomer can tolerate the increae in lower temperature region, thi may not caue an uncomfortable ituation, wherea the increae of temperature in higher temperature region may become intolerable for cutomer and they may reject the DLC to their appliance. Thu, the paper conclude that TSC method reduce (compared to LCC method) the number of houe at higher temperature region when the DLC action i applied to the cutomer. The work i continuing to incorporate TSC and LCC. A better control trategy i earched both to reduce the load deep and payback magnitude and to minimie the comfort level reduction caued to the cutomer. Acknowledgment: Thi tudy i ponored by the Graduate Thei Support Program of Intitute of Science and Technology, Itanbul Technical Univerity. REFERENCES: [1] Strickler, G.F. and Noell, S.K., Reidential air conditioner cycling: a cae tudy, IEEE Tranaction on Power Sytem, Vol.3, No.1, pp , February [2] Orphelin, M. and Adnot, J., Improvement of method for recontruction water heating aggregated load curve and evaluating Demand-Side control benefit, IEEE Tranaction on Power Sytem, Vol.14, No.4, pp , November [3] Wei, D.C. and Chen, N., Air-conditioner Direct Load Control by multi-pa dynamic programming, IEEE Tranaction on Power Sytem, Vol.10, No.1, pp , February [4] Nordell, D.E., Principle for effective load management, IEEE Tranaction on Power Apparatu and Sytem, Vol.PAS-104, No.6, pp , June [5] Jorge, H., at. al., A multiple objective deciion upport model for the election of remote load control trategie, IEEE Tranaction on Power Sytem, Vol.15, No.2, pp , May [6] Gome, A., at. al., Simulation-baed aement of electric load management program, International Journal of Energy Reearch, No.23, pp , [7] Mortenen, R.E. and Haggerty, K.P., Dynamic of heating and cooling load: Model, imulation, and actual utility data, IEEE Tranaction on Power Sytem, Vol.5, pp , February [8] Laurent, J.C. and Malhame, R.P., A phyicallybaed computer model of aggregate electric water heating load, IEEE Tranaction on Power Sytem, Vol.9, pp , Augut [9] Chong, C.Y. and Deb, A.S., Statitical ynthei of power ytem functional load model, in Proc. IEEE Conf. Deciion Control, pp , Fort Lauderdale, Fla., 1979, eion WP-4. [10] Chong, C.Y. and Malhami, R.P., Statitical ynthei of phyically baed load model with application to cold load pickup, IEEE Tranaction on Power Apparatu and Sytem, Vol. PAS-103, pp , July [11] Mortenen, R.E. and Haggerty, K.P., A tochatic computer model for heating and cooling load, IEEE Tranaction on Power Sytem, Vol.3, pp , Augut [12] Ihara, S. and Schweppe, F.C., Phyically baed modelling of cold load pickup, IEEE Tranaction of Power Apparatu and Sytem, Vol.PAS-100, pp , September [13] Dokuyucu, G., Invetigation of Thermotat-Set Control a a new Direct Load Control method, Mater Thei, Intitute of Science and Technology, Itanbul Technical Univerity, June [14] Uçak, C., Retoration of ditribution ytem following extended outage, Ph.D. Thei, Kana State Univerity, Manhattan, 1994.