Worst Case Scenario for Large Distribution Networks ... - IEEE Xplore

Worst Case Scenario for Large Distribution Networks with Distributed Generation M. A. Mahmud, Student Member, IEEE, M. J. Hossain, and H. R. Pota

Abstract—Integration of distributed generation (DG) in distribution network has significant effects on voltage profile for both customers and distribution network service providers (DNSPs). This impact may manifest itself positively or negatively, depending on variation of the voltage and the amount of DG that can be connected to the distribution networks. This paper presents a way to estimate the voltage variation and the amount of the DG that can be accommodated into the distribution networks. To do this, a voltage rise formula is used with some approximation and the validation of this formula is checked by comparing with the existing power systems simulation software. Using the voltage variation formula, the worst case scenario of the distribution network with DG is used to estimate the amount of voltage variation and maximum permissible DG.

I. I NTRODUCTION The electric power system is traditionally designed to transport large amount of power from generation units through transmission and distribution networks, finally to the electric energy consumers. The life style of a nation is measured by electricity consumptions. If a nation consumes more electricity, the nation is more developed. Due to this development, there is an increased demand in electricity. The increased demand for electricity has outstripped that for other forms of energy. Renewable energy which comes from natural resources such as sunlight, wind, rain, tides, and geothermal heat, is the best choice as alternative source of energy. The interconnection of these renewable energy sources and other forms of small generation such as combined heat and power (CHP) units, fuel cells, etc., into the distribution network is known as distributed generation. The present status of distributed generation is still at an early stage of development due to the several regulatory, economic, and technical barriers to the integration of DG in electric power systems [1]. However, there is an ongoing international effort on investigating the necessary arrangements such as an effective market mechanism, and technical and regulatory guidance to provide a sufficient ground for promoting a greater uptake of distributed generation investment [2], [3], [4]. Penetration of DG into distribution network is entering an emerging era of rapid expansion and commercialization. Traditionally, the distribution networks are passive networks where the flow of both real and reactive power is always from the higher to lower voltage levels. However, with significant penetration of distributed generation, the power flows may M. A. Mahmud, M. J. Hossain and H. R. Pota are with the School of Engineering and Information Technology (SEIT), The University of New South Wales at Australian Defence Force Academy (UNSW@ADFA), Canberra, ACT 2600, Australia. E-mail: [email protected] and (m.hossain and h.pota)@adfa.edu.au.

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become reversed since the distribution network is no longer a passive circuit supplying loads but an active system with power flows and voltages determined by the generation as well as load. Hence, there are dramatic changes in the nature of distribution networks with distributed generation. There have been a number of studies [5], [6], [7], [8], [9], [10] for DG planning models which consider the various technical requirements such as thermal ratings of the equipments, voltage rise, systems fault levels, line drop compensation, reverse power flow capability of the tap-changers, power losses, power quality (such as flicker, harmonics), protection, etc. Integration of distributed generation in distribution systems is susceptible to voltage rise. Moreover, the impact of losing a single or a few distributed generation following a remote fault may not be a significant issue, but the connection or disconnection of a large distributed generation unit may become problematic which may lead to sudden appearance of hidden loads and affect the voltage profile of low voltage distribution network. To overcome these problems, the distribution network capacity for distributed generation by using optimal power flow with voltage step constraints is determined in [11]. The concepts of voltage steps and voltage rise are related to each other but they are different which is also described in [11]. The voltage rise issues due to the distributed generation is discussed nicely by giving some theoretical background in [10]. But the detailed analysis of voltage rise effects is not discussed in [10]. Also there is no indication in [10], about how much DG can be connected to the distribution networks. A multi-period AC optimal power flow (OPF)-based technique is proposed in [12], for evaluating the maximum capacity of new variable distributed generation which be connected to a distribution network when active network management (ANM) control strategies are in place. In [12], the physical limitations of the networks are considered. But there is no clear indication about the relationship between voltage variation and the amount of DG that can penetrate into the distribution network. So far in the literature [112], there is no clarification on the worst case scenario of the network. But the concept of worst case scenario is essential to demonstrate the relationship between voltage rise and DG connected to the distribution network as well as to ensure that distribution network and customer will not be affected adversely. The aim of this paper is to estimate the voltage variation and the amount of DG that can be integrated within a distribution network. The formulation and validation of voltage variation formula for small as well as large distribution systems is also shown in this paper. Based on this formula, the worst case scenario of the distribution network is considered and through

Fig. 1.

Conventional Two-bus Distribution System

the illustration of worst case scenario, this paper presents the estimation of voltage variation and the maximum capacity of DG that can penetrate into the existing distribution networks. The rest of the paper is organized as follows. The voltage variation in conventional distribution systems is presented in Section II. Section III presents the generalized voltage variation formula for distribution network with DG. Some case studies are shown in Section IV, to validate the voltage rise formula. The consideration of worst case scenario for distribution networks with DG and the estimation of voltage variations and distributed generation capacity is shown in Section V. Finally, the paper is concluded by brief remarks in Section VI. II. VOLTAGE VARIATION IN C ONVENTIONAL D ISTRIBUTION N ETWORK Most of the distribution networks are modeled as passive networks with radial configuration and as mentioned in the literature, the flow of power both real (P ) and reactive (Q), is always from the higher to lower voltage levels. Since the reactance to resistance ratio ( X R ), for transmission network is ≥ 10 and that of for distribution network is ≤ 0.5, therefore the value of resistances in the distribution networks are high. These high resistances lead to the voltage drop along the line from the primary substation to the point of connection of the customer. The amount of voltage drop can be calculated from the analysis of two-bus distribution system as shown in Fig. 1. In Fig. 1, DS and OLT C stand for the distribution systems and on-load tap-changer respectively, V S is the sending end voltage, VR is the receiving end voltage, P and Q are the real and reactive power flowing through the distribution network to the customer, i.e., these are supplied from distribution substation (DS), and P L and QL are the real and reactive power of the load. The voltage at the sending end can be written as  + jX) VS = VR + I(R  is the current flowing through the distribution where I = |I|  VS , and VR represent the corresponding phasor network and I, quantities. The power supplying from the distribution system can be written as P + jQ = VS I∗ Therefore, the current flowing through the line can be written as P − jQ I = VS

Fig. 2.

Conventional n-bus Large Distribution System

 the sending end voltage can be By using the value of I, expressed as P − jQ VS = VR + (R + jX) VS RP + XQ XP − RQ = VR + +j  VS VS Therefore, the voltage drop between the sending end and recieving end can be written as RP + XQ XP − RQ +j ΔV = VS − VR =  VS VS Since the angle between the sending end voltage and the receiving end voltage is very small, the voltage drop is approximately equal to the real part of the drop [13] and if the sending end bus is considered as reference bus, the angle of this voltage is 0, i.e., VS = |VS | = VS . Therefore, the above equation can be approximated as RP + XQ ΔV ≈ (1) VS If the sending end voltage of the system as shown in Fig. 1 is considered as the base voltage, then V S can be assumed as unity. Therefore, equation (1) can be written as follows: ΔV ≈ RP + XQ

(2)

The amount of voltage variation in a large distribution network as shown Fig. 2 can be determined by using the same formula as shown by equation (1). In Fig. 2, an n-bus system is considered. The voltage drop between i th and j th bus can be written as Rij Pij + Xij Qij ΔVij ≈ (3) Vi where, ΔVij is the variation of voltage between i th and j th bus, Rij is the resistance between i th and j th bus, Xij is the reactance between i th and j th bus, Vi is the voltage at ith bus, and Pij and Qij are the active and reactive power flowing from ith to j th bus. The voltage level at each connection point of the load is very important for the quality of the supply. Since there are no internationally agreed rules that define the allowed steadystate voltage range, the maximum permitted voltage variation on each bus-bar is defined by some technical regulations or specific contracts. The variation of voltage on a small as well as large conventional distribution network using our proposed formula is compared next with the existing software simulation results in the following sections through some case studies.

Fig. 3.

Two-bus Distribution System with DG

III. VOLTAGE VARIATION IN D ISTRIBUTION N ETWORK WITH DG When generators are connected to the distribution system, the power flow and the voltage profiles are affected as well as the system is no longer passive but active. In order to export power, a generator is likely to operate at a higher voltage as compared to the other nodes where it is supplying power. This can be explained by using equation (2). In this case, the receiving end voltage (V R ) will be VR ≈ VS + RP + XQ

(4)

as the direction of the power flow is reversed. Thus, the voltage at the point of connection of the generator will rise above the sending end voltage which can be clarified through Fig. 3. In Fig. 3, a distributed generator (DG) is connected where the voltage (VGEN ) is assumed to be 11 kV, P G and QG are the generated active and reactive power, respectively, by the DG, PL and QL are the active and reactive power of the load respectively and Q C is reactive power of the shunt compensator. This DG with load and compensator is connected to the distribution system (DS) via overhead distribution line with impedance R + jX and through OLTC. The voltage rise along the distribution network as shown in Fig. 3 can be written as follows: ΔV = VGEN − VS ≈

RP + XQ VGEN

(5)

where, P = (PG − PL ), Q = (±QC − QL ± QG ). If VGEN is expressed in terms of per unit, then equation (4) can be written as ΔV = VGEN −VS ≈ R(PG −PL )+X(±QC −QL ±QG ) (6) The generators always export active power(+P G) and may export or import reactive power(±Q G), whereas the load consumes both active (−P L ) and reactive (−Q L ) power and the compensators may export or absorb only reactive power (±QC ). Recently, small synchronous generators through combined heat power (CHP) generation scheme, small wind turbine, and photovoltaic (PV) are widely used as distributed generators. In CHP generation scheme, the synchronous generator exports real power even when the electrical load of the systems falls below the output of the generator but it may absorb or export reactive power depending on the setting of the excitation system of the generator. The wind turbine also exports real power but it absorbs reactive power as its induction generator requires a source of reactive power to operate. The photovoltaic (PV) systems are used to export

Fig. 4.

n-bus Large Distribution System with Distributed Generation

real power at a set power factor but may introduce harmonic currents. Therefore, the power flows through the circuits may be in either direction depending on the relative magnitudes of the real and reactive network loads compared to the generator outputs and any losses in the network. There is some fluctuation in power output of distributed generators based on primary sources such as wind generators, photovoltaics, and certain CHP units. These variations in the power generation cause voltage variation in the voltage supplied to the customers. The variation of wind speed and the tower shadow of the fixed speed wind turbines produce power pulsations. Moving clouds cause the power generation of photovoltaic systems to fluctuate. The operation of CHP mostly depends on the customers’ heat demand. The variations in the customers’ heat demand from time to time lead the variation in the power generation of CHP units. The voltage variation in the large distribution networks with distributed generation can be analyzed in a similar way to that of conventional distribution networks as mentioned in the previous section. If we integrate distributed generation at j th bus of the conventional distribution network as shown in Fig. 2, the system will be converted like Fig. 4. The voltage variation ΔV ji at the DG connection point, i.e., at the j th bus of a radial distribution feeder can be written as ΔVji ≈

Rij (PGj − PLj ) + Xij (±QGj − QLj ) Vj

(7)

where, PGj is the active power supplied by DG, Q Gj is the reactive power supplied or absorbed by DG depending on the nature of DG as discussed before, P Lj and QLj are the active and reactive power of the load connected to the j th bus of the distribution system respectively. If we connect a shunt compensator at point of DG connection with reactive power QCj , the equation (7) can be written as ΔVji ≈

Rij (PGj − PLj ) + Xij (±QGj ± QCj − QLj ) (8) Vj

The variation of voltages in the small as well as large distribution network can be determined by using the formulae (4)-(8). The voltage variation on small and large distribution network with and without distributed generation is discussed in the following section through some case studies.

Fig. 5. Voltage variation in a conventional two-bus distribution system (The solid line represents the results obtained from PSAT, the dotted line that of from the derived formula and the two bold solid lines indicate the allowable range of voltage variation)

Fig. 6. Voltage variation in a two-bus distribution system with 200 kW of DG (The solid line represents the results obtained from PSAT, the dotted line that of from the derived formula and the two bold solid lines indicate the allowable range of voltage variation)

IV. C ASE S TUDY: VALIDATION OF VOLTAGE VARIATION F ORMULA DNSPs should maintain the voltage variation in the distribution network within the permissible limits fixed by national and international standards, to guarantee a reliable and economic service to the customers. In most cases, the allowable voltage variation along the distribution network is ±6%, but it may vary depending on the regulations of each country. In this paper, to clearly demonstrate the effect of integration of DG into distribution network, we have considered that the voltages are allowed to vary by ±6% of the nominal voltage. In this section, the validation of voltage variation formula obtained in the previous section is checked by comparing with existing simulation softwares. The difference between voltage variation in a distribution network with and without distributed generation will be more clear through the following case studies: Case 1: Validation on a conventional two-bus distribution network A conventional two bus distribution network is shown in Fig. 1. In this figure, if we consider that 11 kV, 1 MW, power is supplied to the from the distribution system, i.e., from bus 1 through the distribution line with length 1.64 km and impedance, 2.7995 + j1.48855 Ω to bus 2. The voltage variation between bus 1 and bus 2 by using equation (1) and simulation software power system analysis toolbox (PSAT) is shown in Fig. 5. From Fig. 5, it is seen that the voltage variation in a conventional two-bus distribution network is within the permissible limits of ±6%. From this figure, it is also seen that the amount of voltage variation obtained by using equation (1) and that of obtained from PSAT are nearly same. Case 2: Validation on two-bus distribution network with DG If we connect a 200 kW of distributed generator at bus 2 as shown in Fig. 3, the voltage variation between bus 1 and

Fig. 7. Voltage variation in a two-bus distribution system with 400 kW of DG (The solid line represents the results obtained from PSAT, the dotted line that of from the derived formula and the two bold solid lines indicate the allowable range of voltage variation)

bus 2 can be shown as Fig. 6. From Fig. 6, it seen that the voltage variation obtained from PSAT and by using equation (6) are very close to each other. The integration of 200 kW distributed generators does not cause too much voltage variation within the distribution network as still it is within the permissible range. But if we connect 400 kW of distributed generators at bus 2, the voltage variation can be shown as Fig. 7 From Fig. 7, it is seen that the results in both cases are close to each other but the variation of voltage is outside the permissible limits. This is due to the integration of larger amount of distributed generation. The more the penetration level of distribution generation, the more the voltage variation within the distribution network. Case 3: Validation on large distribution network-IEEE 34 Node Test Feeder

Fig. 8.

IEEE 34 Node Test Feeder [14]

Fig. 9. Voltage variation in IEEE 34 Node Test Distribution System (The solid line represents the results obtained from PSSE, the dotted line that of from the derived formula and the two bold solid lines indicate the allowable range of voltage variation)

To validate the voltage variation formula for large distribution system represented by equation (3), we have considered here IEEE 34 node test feeder [14] which is shown in Fig. 8. The details about the feeder data as shown in Fig. 8 can be found in [14]. The voltage variation in this test system is shown in Fig. 9. From Fig. 9, it is seen that the results obtained by using equation (3) and simulation software PSSE are nearly equal. In Fig. 9, there is some voltage variation outside the permissible range. Case 4: Validation on large distribution network with DGIEEE 34 Node Test Feeder with DG

Fig. 10. Voltage variation in IEEE 34 Node Test Distribution System with 25% Penetration of DG at Node 834 (The solid line represents the results obtained from PSSE, the dotted line that of from the derived formula and the two bold solid lines indicate the allowable range of voltage variation)

Now if we integrate about 450 kW of distribute generators, i.e., if the penetration level is about 25% at node 834, the voltage profile of the system will change. The change in voltage profile with 25% penetration of DG is shown in Fig. 10 From Fig. 10, it is clear that there are voltage rises in some portion of feeder but now all the variation are within the allowable ranges of ±6%. In this figure, the results obtained from PSSE and by using equation (8) are close to each other. Now if the penetration level is about 50%, the voltage variation within the feeder will be different from Fig. 10. In this condition, the voltage variation is shown in Fig. 11. Though the results shown in Fig. 11 are nearly same for the approximate formula and exact solution. But there are voltage rises in some nodes of the feeder which are outside the range

voltage at the primary DES voltage level of the receiving end • size of the conductors as well the distance from primary DES • load demand on the system • other generation on the system When a generator is to be connected to the distribution system, the DNSP should consider the worst case operating scenarios to easily demonstrate the relationship between voltage rise and the DG connected to the DES and also they should ensure that their network and customer will not be adversely affected. Generally, these worst case scenarios are: • minimum load maximum generation • maximum load minimum generation • maximum load maximum generation The amount of voltage rise on a distribution system can easily be described through worst case scenario. This can be done by using the simple algebraic equation (6). If we consider the worst case scenario as minimum load and maximum generation, then we can write: • •

Fig. 11. Voltage variation in IEEE 34 Node Test Distribution System with 50% Penetration of DG at Node 834 (The solid line represents the results obtained from PSSE, the dotted line that of from the derived formula and the two bold solid lines indicate the allowable range of voltage variation)

PL = 0, of maximum allowable limits. This is due to the same reason as mentioned in Case 2. From the case studies, described in Case 1, Case 2, Case 3, and Case 4, it is seen that the voltage variation formulas derived in Section III are valid for small as well as large distribution network with or without DG and it can be concluded that there is no serious voltage variation problem on conventional distribution network and distribution network with small amount of DG. But voltage variation is a serious problem when large amount of DG is connected to the distribution network as the voltage variation exceeds the limits of allowable range. This voltage variation may reduce the lifetime of the appliances connected to the distribution network, or sometimes may damage the appliances. Therefore, it is essential to properly estimate the amount of DG and voltage variation. The estimation of DG capacity and voltage variation using worst case scenario are described in the following section. V. E STIMATION OF VOLTAGE VARIATION AND D ISTRIBUTED G ENERATION C APACITY USING WORST CASE SCENARIO

The distributed generators are connected to the distribution system due to the technological innovations and change in economic and regulatory environment as well as to meet the increased load demand. From equation (6), we can write, VGEN − VS + RPL − X(±QC − QL ± QG ) (9) R For large distribution network, the above equation can be written as Vj − Vi + Rij PLj − Xij (±QCj − QLj ± QGj ) PGj ≈ Rij From equation (9), it is clear that the level of generation that can be connected to the distribution system depends on the following factors: PG ≈

QL = 0,

and

PG = PGmax

Again, if we assume that the system is operating at unity power factor, then ±Q G and ±QC will be zero. In this condition equation (6) can be written as: ΔVworst = VGEN max − VS ≈ RPGmax

(10)

For large system, the worst case voltage variation is ΔVworstji = Vjmax − Vi ≈ Rij PGjmax From equation (10), it is clear that the voltage rise depends on the resistance of the distribution line and the power supplied by the distributed generator. If the resistance of the distribution line is constant, then we can write ΔVworst ∝ PGmax

(11)

and that of for large system is ΔVworstji ∝ PGjmax Therefore, the voltage variation in distribution network with distributed generation is directly proportional to the amount the active power supplied by the distributed generators. There is a linear relationship between the voltage rise and the amount of active power supplied by distributed generators. Therefore, the voltage rise is more onerous when there there is no demand on the system, as all the generation is exported back to the primary distribution system. The voltage rise in the distribution system also limits how much distributed generation can be connected. This can be shown by the simple algebraic equation (10). From equation (6), we can write VGEN max − VS (12) R The capacity of the generator that can be accommodated in the existing system is clearly limited by the maximum voltage PGmax ≈

at the distributed generator connected busbar which can be written as VGEN max − VS (13) PGmax ≤ R The same thing will be happened for large distribution network and it can be written as PGjmax ≤

[14] “IEEE 34 node test feeder,” IEEE PES Distribution System Analysis Subcommittee, Available Online: http://www.ewh.ieee.org/soc/pes/dsacom/testfeeders/index.html.

Vjmax − Vi Rij

Therefore, from the worst case scenario it is seen that the resistance of the line as well as the voltage rise along the system is critical for the amount of generation that can be connected. VI. C ONCLUSION The voltage variation in a small as well as large distribution network distribution network is estimated through a simple formula. The simple formula derived in this paper can be used in practice. The validation of voltage variation formula is checked through some case studies on the existing two-bus distribution system and IEEE 34 node test feeder. Finally, the worst case scenario of the distribution network is considered to estimate the amount of voltage variation and the maximum capacity of DG that can be connected to the network without affecting the customers adversely. Future works will deal with the dynamic analysis of this distribution system with different types of distributed energy resources such as CHP, wind generators, PV etc. R EFERENCES [1] B. Alderfer, M. Eldridge, and T. Starrs, “Making connection: Case studies of interconnection barriers and their impact on distributed power projects,” National Renewable Energy Laboratory, 2000. [2] H. L. Willis and W. G. Scott, Distributed Power Generation: Planning and Evaluation. New York: Marcel Dekker, 2000. [3] G. Welch, “Distributed generation planning,” In Proc. of IEEE Summer Meeting, 2000. [4] A. J. Wright and J. R. Formby, “Overcoming barriers to scheduling embedded generation to support distribution networks,” EA TechnologyDepartment of Trade and Industry, 2000. [5] P. Chiradeja and R. Ramakumar, “An approach to quantify the technical benefits of distributed generation,” IEEE Trans. on Energy Conversion, vol. 19, no. 4, pp. 764–773, 2004. [6] L. F. Ochoa, A. Padilha-Feltrin, and G. P. Harrison, “Evaluating distributed generation impacts with a multiobjective index,” IEEE Trans. on Power Delivery, vol. 21, no. 3, pp. 1452–1458, 2006. [7] L. F. Ochoa, “Time-series based maximization of distributed wind power generation integration,” IEEE Trans. on Energy Conversion, vol. 23, no. 3, pp. 968–974, 2008. [8] C. Wang and M. H. Nehrir, “Analytical approaches for optimal placement of distributed generation sources in power systems,” IEEE Trans. on Power Systems, vol. 19, no. 4, pp. 2068–2076, 2004. [9] N. Acharya, P. Mahat, and N. Mithulananthan, “An analytical approach for DG allocation in primary distribution network,” Int. J. Elect. Power and Energy Syst., vol. 28, no. 10, pp. 669–678, 2006. [10] C. L. Masters, “Voltage rise: the big issue when connecting embedded generation to long 11 kV overhead lines,” IET Power Engineering Journal, vol. 16, no. 2, pp. 5–12, 2002. [11] C. J. Dent, L. F. Ochoa, and G. P. Harrison, “Network distribution capacity analysis using OPF with voltage step constraints,” IEEE Trans. on Power Systems, vol. 25, no. 1, pp. 296–304, 2010. [12] L. F. Ochoa, C. J. Dent, and G. P. Harrison, “Distribution network capacity assessment: Variable DG and active networks,” IEEE Trans. on Power Systems, vol. 25, no. 1, pp. 87–95, 2010. [13] W. H. Kersting, Distribution System Modeling and Analysis. London: CRC Press, Second Edition, 2007.

M. A. Mahmud was born in Rajshahi, Bangladesh in 1987. He has received the B.Sc. in Electrical and Electronic Engineering with honours from Rajshahi University of Engineering and Technology (RUET), Bangladesh, in 2008. He is currently a PhD candidate at the University of New South Wales, Australian Defence Force Academy. His research interests are dynamic stability power systems, solar integration and stabilization, voltage stability, distributed generation, nonlinear control, electrical machine, and HVDC transmission system.

M. J. Hossain was born in Rajshahi, Bangladesh, on October 30, 1976. He received the B.Sc. and M.Sc. Eng. degrees from Rajshahi University of Engineering and Technology (RUET), Bangladesh, in 2001 and 2005, respectively, all in electrical and electronic engineering. He has finished his Ph.D. degree from the University of New South Wales, Australian Defence Force Academy in 2010. Currently, he is working as a research publication fellowship in the same university. His research interests are power systems, wind generator integration and stabilization, voltage stability, micro grids, robust control, electrical machine, FACTS devices, and energy storage systems.

H. R. Pota received the B.E. degree from SVRCET, Surat, India, in 1979, the M.E. degree from the IISc, Bangalore, India, in 1981, and the Ph.D. degree from the University of Newcastle, NSW, Australia, in 1985, all in electrical engineering. He is currently an Associate Professor at the University of New South Wales, Australian Defence Force Academy, Canberra, Australia. He has held visiting appointments at the University of Delaware; Iowa State University; Kansas State University; Old Dominion University; the University of California, San Diego; and the Centre for AI and Robotics, Bangalore. He has a continuing interest in the area of power system dynamics and control, flexible structures, and UAVs.