Evaluating the Long-term Impact of a Continuously Increasing Harmonic Load Demand on Feeder Level Voltage Distortion

Transcription

1 Evaluating the Long-term Impact of a Continuously Increasing Harmonic Load Demand on Feeder Level Voltage Distortion Kerry D. McBee Member, IEEE Colorado School of Mines 1500 Illinois Street Denver, CO power.engineer@ymail.com Marcelo G. Simões Member, IEEE Colorado School of Mines 1500 Illinois Street Golden, CO 80401, USA mgodoysimoes@gmail.com Abstract The increasing implementation of nonlinear devices in residential homes may have a significant impact on feeder level harmonic distortion. Because most utilities do not monitor feeder level harmonics, the existing levels of harmonic distortion are unknown, which hinders a utility s ability to forecast future feeder level harmonic distortion. Within this paper the authors analyze the long-term feeder level distortion possibilities based on a large number of residential customers producing harmonic currents near and above the IEEE 519 harmonic current threshold limits. Field experiments were performed to determine the relationship between the harmonic current produced by a single residential customer and the corresponding customer harmonic impedance. Utilizing the IEEE 13 Node Test Feeder and the developed harmonic impedance function, the authors utilized the current injection method with residential customers represented by a Norton equivalent circuit to evaluate the aggregate effects of customers with high harmonic load demand. Also included is an analysis of the effects that the increased harmonic demand will have on harmonic resonance points on the feeder. Index Terms-- Current Injection, Harmonics, IEEE 519, Harmonic Resonance, THD I. INTRODUCTION The increased implementation of nonlinear devices within residential households has led some electric utility companies to become more concerned about the resulting harmonic distortion that is induced onto the distribution system. From a distribution planning perspective the question becomes how will the increased use of these nonlinear devices affect future distribution operation and designs, which have historically ignored the effects of harmonics. In the last 20 years nonlinear devices such adjustable speed driven air conditioning units, fluorescent tube lighting, pc s and laptops have become more prominent in the residential household. With an expectation of higher penetrations of electric vehicle chargers and renewable energy devices on the distribution system, the utility engineer must forecast how these new nonlinear devices will add to the existing harmonic distortion. For the last 30 years researchers have investigated the increased use of nonlinear devices on the distribution system. Most of the research has focused on the implementation of a specific type of nonlinear device. The impact of adjustable speed driven air conditioning units was studied in [1]. The authors of [2] - [5] analyzed the effects of residential PV installations. The harmonic impact of compact fluorescent lighting was analyzed in [6] [10]. Because of the expectation that electric vehicle purchase will increase, the authors of [11]-[13] evaluated the impact of a high penetration of electric vehicle chargers on feeder level harmonic distortion. Although some of these papers incorporate a limited amount of other nonlinear devices within their models, the authors mainly address the harmonic distortion as a result of the subject matter of the paper and not the aggregate sum of all devices with increased penetration levels. These research endeavors mostly focused on the harmonic impact of specific devices based on a given penetration level. Little concern was given to how the harmonic distortion will increase yearly, which is the concern of utility planning engineers. One exception is the work performed by the authors in [14], who attempted to predict the yearly rate of harmonic distortion increase by forecasting the increased usage of nonlinear devices by type. The disadvantage to this approach is that it relies upon knowing specifics of customers load types and how they change over time, which is typically inaccessible to utility companies on a regular basis. For distribution planning purposes, utility engineers rely upon indicators, usually in the form of load demand, to signify when design standards require revision or system infrastructure requires upgrades. With so many harmonic producing customers, the question that many utilities must answer is Will the harmonic distortion produced by the aggregate sum of all customers result in operational or system deficiencies that should be considered when planning future system upgrades, including capacitor bank and harmonic filter installation? This paper describes the research performed by the authors to evaluate the long-term effect of a continuingly increasing harmonic demand. As with most forecasting

2 techniques, the authors evaluated the harmonic distortion on 134 feeders to understand the existing conditions of a typical system. The second part of the evaluation consists of applying the current injection method to an expanded version of the IEEE 13 Node Test Feeder to evaluate how voltage distortion will be affected by increased nonlinear device usage. The amount of current injected into the system was varied between 3% and 30% of the residential peak demand. Residential customers with linear and nonlinear loads were represented by a Norton equivalent circuit, which required the authors to determine the relationship between the current injected into a distribution system by a single customer and the harmonic impedance of that customer. Field measurements were acquired from residential customers located throughout Denver, Colorado to determine the harmonic impedance and current injected relationship. II. EXISTING LEVELS OF DISTORTION Many utilities believe that customer current limitations set forth by IEEE 519 will prevent any adverse harmonic distortion effects at the system level. Within IEEE 519 are current harmonic limits for customers and voltage harmonic limits for utility companies [15]. The thought behind the standard is that customers are responsible for the amount of harmonic current demanded, while the utility company is responsible for the resulting voltage harmonic distortion. Unfortunately the document was developed in 1992 when most of the harmonic current sources were located at industrial and commercial facilities. Because of the push for energy efficiency appliances and lighting, today many residential homes could be considered small harmonic sources, suggesting that the limitations set forth in IEEE 519 may be too stringent for the utility company and too relaxed for customers. Since the implementation of power electronics 25 years ago, harmonic current distortion has only resulted in isolated voltage distortion problems, which where typically traced back to large industrial customer. With so few problems associated with harmonic distortion, utilities have essentially ignored monitoring customer and feeder level harmonics. This lack of historical and active data prevents utility planning engineers from accurately predicting the long-term effects even if they so desired. Typical forecasting approaches, whether for long-term or short-term planning, utilize historical data and regression curve fitting to predict demand growth [16]. The accepted growth pattern for demand takes the shape of the typical S-Shape curve, which is illustrated in figure 1. Without information regarding historical harmonic load demand, it s nearly impossible to apply any existing forecasting techniques to the future feeder level harmonic distortion. Fig. 1. Typical load growth S-Curve The authors surveyed seven utility distribution companies in regards to their increased number of harmonic related issues and the implementation of proactive monitoring programs. The results indicated that only 2 of the utilities were implementing a proactive program and none of them had seen an increase in harmonic related problems. One of the utility companies performed a detailed feeder level voltage total harmonic distortion (THDv) study. Utilizing Outram Ranger 7000 power quality recorders, the THDv was measured for a week on 134 different 13.2kV feeders. The measurements were required over a two year period in an urban environment. The penetration of EVs and PVs on the monitored circuits was less than 1% of the total customers. Fig. 2. Histogram illustrating the voltage THD of kV feeders. The monitoring revealed that the average THDv was 4.73%, which is just below the 5% voltage limit set forth by IEEE 519 for utility voltage distortion. Although the monitoring revealed that some feeders possessed voltage distortion above the IEEE 519 thresholds, the distribution company did not experience any adverse effects or record any complaints related to harmonic distortion on any of the monitored feeders. Figure 2 illustrates a histogram of the THDv monitoring results. The results of the monitoring study suggests that even today many distribution feeders may have voltage

3 distortion levels that exceed IEEE 519 even if customers or utilities are not witnessing the destructive impact of harmonics. Although harmonics can disrupt electronic control equipment that rely upon sinusoidal waveforms, the largest impact of harmonics on power delivery devices consists of long-term effects [17]-[19]. Harmonics increase the heat generated by electrical devices. The increased thermal environment essentially degrades equipment insulation properties and can significantly reduce the life of equipment depending upon the magnitude of the distortion. However most utility equipment is manufactured to operate for 20, 30, and possible 40 years [20]; therefore noticing a reduced life between 0 40% may be impossible. With levels of harmonic distortion increasing on the distribution system, the questions that utility engineers must answer are: How will existing harmonic distortion levels be affected by the increased use of nonlinear devices? If customers produce harmonic currents below IEEE 519 limitations will the resulting feeder level voltage distortion exceed IEEE 519 limitations? Does increased nonlinear device implementation affect existing harmonic resonance points? Where does the existing level of harmonic distortion level fall on the typical load growth S- Curve? Will there be a saturation point for harmonic distortion as with the typical load growth S-Curve? III. AGGREGATE HARMONIC LOAD EFFECTS A. Development of Analysis Model The traditional current injection method was utilized to evaluate the effects of increasing customer harmonic demand. Residential customers are modeled by their Norton equivalent circuit as described in [21] - [24]. For large scale distribution analysis regarding harmonics, current injection method has proven to be an accepted technique [25]. The current injection is based on upon (1). Historically nonlinear devices have been modeled as current sources. However, research has proven that some nonlinear devices that utilize diode bridge rectifiers with capacitive filter outputs can have characteristics that resemble harmonic voltage sources instead. [26][27]. Because a utility company is concerned about the voltage at the PCC, other linear devices that are connected to the voltage source acting nonlinear device must be included in the home representation. These linear devices along with the resistance of conductors are seen as impedances from the point of view of the utility. Residential conductors sized 10awg 18awg possess resistance between 0.1 and 0.6 Ohms for distances of 100ft, which is an average distance for residential wiring [28]. These impedances when combined with the nonlinear devices that have voltage source characteristics can be represented by a Thevenin or Norton equivalent circuit, which is utilized in this analysis. The authors do agree that for analyses that evaluate the effects that a voltage source acting device has on other household appliances, the Norton equivalent circuit cannot be utilized if the nonlinear device acts like a pure voltage source [27]. The main focus of the analysis performed in this paper is the bus voltage as a function of a fixed harmonic current magnitude, which is the attribute that IEEE 519 limits for customers. For example, if all residential customers demand 5 th harmonic current in access of the 15% allowed by IEEE 519, will the resulting PCC voltages exceed the voltage thresholds set forth by IEEE 519? 1 [ I ] [ Y ][ V ] Sh = (1) Where: I Sh Norton Current source at frequency h Y h System admittance matrix at frequency h V nh Voltage node n at frequency h h The model utilized by the authors was developed from the IEEE 13 Node Test Feeder [29]. The test system was expanded to include lateral conductors, 50 kva transformers, secondary conductors, and individual residential customers. Figure 3 illustrates the general expansion of the 13 Node Test Feeder. The load delivered through each lateral, which are connected to one of the 13 test nodes, was set equal to the amount of kva specified by [29]. This demand information was utilized to determine the number of homes and transformers per lateral. Each home was rated at 5kVA, while the lateral conductors were sized in accordance to the current demanded by the aggregate sum of the homes it serves. With the transformers being rated at 50kVA, the maximum number of homes per transformer was 10. All secondary conductors were comprised of 350 kcmil 600V triplex cable. Conductor sizes for lateral conductors are listed in Table II. The laterals were designed in radial pattern as illustrated in figure 4. Combining all of the transformers, residential customers, and primary busses, the final model consisted of a Y matrix with 298 buses. With the system impedances determined, the authors were left with modeling the individual homes. nh

4 Fig. 3. IEEE 13 Node Test Feeder with load expansions. TABLE II Load Information for Test System 634 Load A 160kW, 110kVAr Load Amps 80 amps Lateral Size #4 Cable Rating 120 amps Transformers 3 Homes Load B 170kW, 80kVAr Load Amps 78 amps Lateral Size #4 Cable Rating 120 amps Transformers 3 Homes Load C 385kW, 220kVAr Load Amps 184 amps Lateral Size.1/0 Cable Rating 275 amps Transformers 8 Homes Load D 460kW, 360kVAr Load Amps 242 amps Lateral Size 1/0 Cable Rating 275 amps Transformers 10 Homes 95 Fig. 4. Representation of lateral connected IEEE 13 Node Test Feeder. The authors utilized the Norton equivalent circuit model as described in [21] - [24], which consists of a current source in parallel with an impedance as illustrated in figure 5. Although the current can be adjusted to inject any amount of current back into the distribution system, an impedance that represents the typical residential customer impedance is unknown. Since the harmonic current (I dh ) demanded by customers is a representation of the type and number of devices drawing power, it can be inferred that customer harmonic impedance varies with I dh. Therefore utilizing an assumed fixed value that is unrelated to I dh would lead to inaccurate analysis results. To determine the relationship between residential customer harmonic impedance and the amount of harmonic current demanded by the customer, the authors monitored 25 residential homes located in an urban area. Harmonic impedance of a load is determined by measuring harmonic current and voltage at the frequency of concern while varying the system impedance. The voltage and current from the two operating conditions are utilized in (2) to calculate the harmonic impedance. For the analysis, current and voltage were monitored on the customer side of the revenue meter, which is considered the PCC. Once again Outram PM7000 power quality recorders were utilized to acquire the field readings. While the recorders were set, capacitor banks rated between 900kVAr and 1500kVAr were operated so as to satisfy the required system impedance fluctuation as described in [21]. Z V h h = (2) I h Where: Z h Harmonic impedance of current source ΔV h Change in harmonic voltage at frequency h ΔI h Change in harmonic current at frequency h The results of the harmonic impedance analysis revealed a nonlinear relationship between the harmonic impedance and the amount of harmonic current demanded

5 by the customer. The nonlinear relationship for the 3 rd, 5 th, and 7 th harmonic frequencies is illustrated in (3). Attributes for other frequencies were too diminished to rely upon the outcome. These results match the measured harmonic current and voltage magnitudes acquired in the city networks monitoring study performed in [30], which identified the 3 rd, 5 th, and 7 th harmonics as the most dominant in urban areas. Figures 6-8 illustrate the results for the three different frequencies. Evident in the results is the high harmonic impedance associated with little harmonic current demand. Although further research is required in this area, the authors believe that this occurrence may reflect a low number of connected appliances within the home. As more devices are energized within the home, which are connected in parallel to other devices, the home impedance as seen from the utility decreases. Fig. 5. Diagram of residential home model. (B) I dh A I dh 16 amps (3) Where: A Constant between 10.2 and 11.2 B Constant between 1.5 and 1.7 I dh Harmonic current demanded by customer at frequency h The observed phase angle of the harmonic impedance varied between 68 and -53. To implement these angle fluctuations into the analysis, harmonic impedance angles of 45, 0, and -45 were evaluated. The final component of the model was determining how to adjust the current source so that the desired amount of current was injected into the Y matrix. To actually solve for the proper amount of current with every residential home connected would require solving a system of nonlinear equations, each representing all 298 buses of the system. To simplify the approach, the authors determined the equivalent impedance of the distribution system as seen from each home assuming that none of the other homes were connected. This approach assumes that the majority of the impedance seen from each home is driven mostly by transformer impedance and conductor/cable impedance. Utilizing current division and (3), the magnitude of the current source (I S) can be determined with (4). Results of the analysis revealed that this approach was accurate within % for adjusting I S for a specific I dh. Diversity between residential customers was accounted for by varying the phase angle of I S in accordance with [31]. The authors utilized the number of residential homes on each lateral to determine how to apply diversity calculation from [31]. Fig. 6. Graph illustrating 3 rd harmonic impedance as a function of current injected. Fig. 7. Graph illustrating 5 th harmonic impedance as a function of current injected. Fig. 8. Graph illustrating 7 th harmonic impedance as a function of current injected. I S dh th ( 1+ B) dh = I + Z AI (4)

6 B. Aggregate effects on harmonic voltage Harmonic current was equally injected into the Y- matrix to calculate the resulting voltage harmonic distortion. The amount current injected represented the average customer harmonic current demanded. The results revealed that the IEEE 519 voltage threshold limit for individual harmonic voltages, which is 3%, are exceeded for some instances when the average customer injected current is greater than 3%. Figures 9-14 illustrate the resulting harmonic voltage at the customers PCC on laterals A, B, C, and D as a function of injected harmonic current. The results indicate that the peak voltage is followed by a saturation zone. The harmonic peak occurs at the point where the customer harmonic impedance is equivalent to the distribution system impedance as seen from the customer, which can be describe by the maximum power transfer theorem. These results suggest that the impedance of the system as seen from the customer s PCC and the harmonic impedance of said customer dictate the occurrence of peak voltage values. For the IEEE 13 Node Test feeder, these matching impedances occur between 3% and 15% injected current. For a distribution system that has a higher impedance, the peak voltage will occur at lower levels of injected current. Conversely, having low system impedance will shift the peak to the right. These results should not be surprising considering that harmonic devices are modeled as voltage and current sources. The maximum power delivered to any network by a source is dependant upon the impedance of the network and the source. The only difference in this case is that there are hundreds of sources and the harmonic impedance of the homes fluctuates. The PCC experiences harmonic saturation after the occurrence of the harmonic peak. The magnitude of the harmonic saturation can be as low as a 30% of the peak harmonic value. The characteristics of the saturation follow the characteristics of the nonlinearly declining Z h. The results also indicate that voltage harmonic distortion increases with harmonic frequency, which is evident when comparing analysis results for the 3 rd and 5 th harmonic frequencies. This occurrence reflects the frequency dependant nature of inductive and capacitive impedance. Although the individual harmonic voltages at high current injection levels are less than the individual harmonic voltage thresholds set by IEEE 519, the resulting THDv can be significantly higher than the 5%. Because THD is the normalized aggregate of each individual harmonic voltage, having a number of frequencies with voltages near the IEEE 519 individual harmonic threshold can result in high voltage distortion. Fig. 9. Illustration of the 3 rd harmonic voltage as function average harmonic injected by customers. Residential harmonic impedance is purely resistive. Each lateral is represented by A, B, C, and D. Fig. 10. Illustration of the 3 rd harmonic voltage as function average harmonic injected by customers. Residential harmonic impedance is inductive. Each lateral is represented by A, B, C, and D. Fig. 11. Illustration of the 3 rd harmonic voltage as function average harmonic injected by customers. Residential harmonic impedance is capacitive. Each lateral is represented by A, B, C, and D. Fig. 12. Illustration of the 5 th harmonic voltage as function average harmonic injected by customers. Residential harmonic impedance is purely resistive. Each lateral is represented by A, B, C, and D.

7 indicates that harmonic filters, which are designed to eliminate harmonics at a given frequency, may require retuning as the amount of current injection changes over time. Other devices that may be affected are capacitor banks, which may have been installed at locations to prevent harmonic resonance. Tables 3 and 4 list the changing Z D for several mainline buses along with the impedance of the capacitor bank. Fig. 13. Illustration of the 3 rd harmonic voltage as function average harmonic injected by customers. Residential harmonic impedance is inductive. Each lateral is represented by A, B, C, and D. Harmonic Impedance (Ohms) TABLE III Z D and Capacitor Impedance at the 5 th Harmonic Cap Z TABLE IV Z D and Capacitor Impedance at the 7 th Harmonic Fig. 14. Illustration of the 5 th harmonic voltage as function average harmonic injected by customers. Residential harmonic impedance is capacitive. Each lateral is represented by A, B, C, and D. C. Impact on Harmonic Resonance Since customer harmonic impedances vary depending upon the amount of current injected into the system, it is perceivable to believe that existing harmonic resonance points on the distribution system will fluctuate as more nonlinear devices are utilized. To examine this occurrence, the authors calculated the driving reactance (Z D) as seen from each bus located on the backbone of the test feeder. Utilizing the approach defined in [11], the authors calculated Z D at different system buses for average customer impedances ranging between Ohms, which represent harmonic current injections of amp (.2pu 1.5pu). To evaluate the occurrence of resonance, Z D is compared to the impedance of a 1200kVAr capacitor bank, which is 10.7 Ohms at the 5 th harmonic and 7.6 Ohms at the 7 th harmonic. Harmonic resonance will occur when Z D is equal to the impedance of the capacitor bank. The results indicated that Z D fluctuates by several ohms when transitioning between low current injection and high current injection. For 611 at the 5 th harmonic frequency, Z D is equivalent to the capacitor bank impedance at low injection levels but transitions out of this harmonic resonance zone as harmonic current increases. For es 633, 634, 611, and 675 the increase of current injection moves the resonance point from the 5 th harmonic frequency to the 7 th harmonic frequency. This IV. CONCLUSION The results of the analysis revealed that utility companies should be concerned with the amount of harmonic distortion that is produced by the increased implementation of nonlinear devices. The preliminary analysis revealed that even at today s low levels of nonlinear device penetration that voltage distortion can exceed levels set by IEEE 519. The amount of voltage distortion is dependant upon the system impedance as viewed from the residential customer. These results suggest that a utility may be able to predict the maximum levels of voltage distortion based on its system infrastructure. Through field measurements the authors were able to determine harmonic impedances associated with residential customers will decrease the more nonlinear devices are implemented, which also suggests that existing harmonic resonance points on the system may change. V. REFERENCES [1] R. S. Thallam, W. M. Grady, M. J. Samotyj, Estimating future harmonic distortion levels in distribution system due to single-phase adjustable-speed-drive air conditioners: a case study, International Conference on Harmonics in Power Systems, pgs , 1992.

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McBee (BS 99-MS 00) is pursuing his Ph.D. degree in the Department of Engineering at Colorado School of Mines, Golden, Colorado, which is where he received his B.Sc. degree in He received his M.Sc. degree in Electric Power Engineering at Rensselaer Polytechnic Institute, Troy, New York, in During his career he has focused on power quality, reliability, forensic engineering, and distribution design for companies such as NEI Power Engineers, Peak Power Engineering, Knott Laboratory, and Xcel Energy. His field of interest is Smart Grid implementation affects upon distribution engineering and utility operations. Marcelo G. Simões (IEEE S 89 M 95 SM 98) received his Ph.D. from the University of Tennessee, Knoxville, in He is with Colorado School of Mines, Department of Electrical Engineering and Computer Science, where he is the director of the Center for Advanced Control of Energy and Power Systems (ACEPS). He has been conducting research and education activities in the development of intelligent control for high-power-electronics applications in renewable- and distributed energy systems and smart-grid technology. He is currently Past-Chair for the IEEE IAS IACC and Co-Chair for the IEEE IES Smart Grid Committee. He has been involved in activities related to the control and management of smartgrid applications since 2002 with his NSF CAREER award Intelligent Based Performance Enhancement Control of Micropower Energy Systems.