Dynamic analysis of renewable energy systems and their impact on smart grid

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1 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, Dynamic analysis of renewable energy systems and their impact on smart grid Suhas Shirbavikar S. shok M. M Babu Narayanan bstract This paper presents the modeling and performance analysis of integrated renewable system connected with the smart power distribution grid. The renewable energy sources considered in the analysis are wind and biomass generation. The smart grid has been simulated using PSCD/EMTDC software considering various dynamic conditions of renewable energy sources. Results show that when Renewable energy sources are connected to the Distribution system, the power flow gets altered and this would necessitate a change in the protection system settings. lso, sudden connection or disconnection of renewable energy sources due to faults etc. may result in unacceptable transients in voltages in the distribution system which needs to be mitigated. The study reported here makes an important contribution to the concept of smart grid in Indian power distribution system. Keywords: Electromagnetic transients, Wind, Biomass, Smart grid I. Introduction Distributed power generation system is emerging as a complementary infrastructure to the traditional central power plants. This infrastructure is constructed on the basis of decentralized generation of electricity close to consumption sites using Distributed Generation (DG) sources [1].The increase in DG penetration and the presence of multiple DG units in electrical proximity to one another have brought about the concept of the Smart grid. smart grid is a digital upgrade of power system that is capable of assessing its health in real-time, predicting its behavior, adaptation to new environment, handling distributed resources, stochastic demand and optimal response to the smart appliances. smart grid also includes diverse and distributed energy sources like wind, biomass, solar P etc; to improve overall system reliability and availability for the benefit of customers and the environment. Integration of two or more DGs improves reliability of smart grid but poses a variety of issues like dynamic response and advanced protection to take into account the bi directional flow of power.[1] Transients during start-up might affect the operation of these plants and other dispersed generation sources connected at the distribution level. In case of distributed generation which comprises a significant part of the generation system, their sudden disconnection might lead to a large unbalance of power and in worst cases to system collapse. This becomes more pronounced in cases where the renewable energy sources are connected to weak C systems. The study reported in this paper addresses some of the above issues and attempts at parametric analysis. Besides, the study is also aimed at investigating the optimal location and sizing of renewable energy sources in the context of typical distribution system in India. ccurate model of biomass-wind generation suitable for electromagnetic transient simulation has been developed and the results are presented in this paper. s an introduction, the paper also gives a status of various renewable energy sources in India. II. Biomass energy in India Biomass is a primary source of energy. Biomass is very versatile in terms of variety of forms and number of options available for its utilization. Biomass is a renewable energy source derived from various humane and natural waste products [2]. Biomass is considered as renewable source of energy because the organic matter is generated every day. Present contribution of biomass energy is between 4% and 18% of total primary energy consumption of various developed and developing countries respectively. By 2015.D. the situation is likely to change with increase in the biomass energy consumption to 25%-40% [2].The estimated potential of Biomass based renewable energy options in India are as follows: Biomass energy - 16,000 MW Biogas Co-generation - 3,500 MW Total - 19,500 MW Electrical energy can be obtained from biomass using one of several processes such as direct combustion, gasification, pyrolysis, anaerobic digestion etc. One of the popular methods is direct combustion. In this method biomass is used to heat up water and generate steam and the steam is used to rotate a turbine that is connected to a synchronous generator. Electricity from biomass reduces our dependence on fossil fuels. Being renewable source of energy there is no threat of running out of resources. Electricity produced by biomass reduces the threat of global climate change. Clearing biomass from forest areas Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

2 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, help to prevent forest fires. Biomass by-product methane gas eliminates odor and reduces air pollution[2]. Use of biomass waste for electricity generation eliminates the need to place it in landfills. Biomass based power generation has been considered to be an important component of the Distributed generation being planned in India during the coming decade. Besides, increased penetration of renewable energy sources would go a long way in reducing carbon emission from the conventional coal based thermal power generating stations in India. III. Wind energy conversion system The wind-turbine based DG unit is one of the fastest growing sources of power generation in the world mainly due to (i) strong worldwide available wind resources, (ii) environment friendly power generation source especially suitable for remote areas, and (iii) rapid technological development [4]. The continuous trend of increase in the rate of DG connection and penetration depth of wind-turbine based DG units can provoke several technical concerns and adverse impact on the operation of distribution systems [4]. Control and protection, stability issues and power quality of the supply are the main concerns. However, the presence of an electronically-interfaced DG unit in a Smart grid environment an ensure stability of the grid and maintain power quality of the system. I. Renewable integration in smart grid Smart Grid technology is recognized as a key component of the solution to challenges such as increasing electric demand, an ageing utility infrastructure and workforce, and the environmental impact of greenhouse gases produced during electric power generation. Integrated Smart Grid solutions combine advanced sensing technology, two-way highspeed communications using the utilities assets, 24/7 monitoring and enterprise analysis software and related services to provide location-specific, real-time actionable data as well as home energy management solutions to provide enhanced services for the endusers. s a result, these solutions increase the efficiency and reliability of the electric grid while reducing the environmental impact of electric usage benefiting utilities, their customers, and the environment [6]. Renewable energy sources such as wind or solar are variable and thus the operating schedules of such plants are largely dictated by the changing fuel supply. This is especially pertinent in the case of wind, photovoltaic solar and run-of-the-river hydro, none of which have inherent storage in their power plant design. These systems cannot be controlled in the same manner as a conventional generation facility. With low levels of wind or solar energy penetration the overall effect on grid operations is limited, yet as the penetration levels increase so too do the effects. It has been recognized that as the penetration levels increase, more advanced control of the power system will be required to maintain system reliability [6]. These controls include more efficient use of transmission, use of demand response and intelligent energy storage, all of which can be enabled through the application of a smart grid. In fact, the ability to better integrate renewable energy is one of the driving factors in some smart grid installations.. Study system KIDB industrial feeder The problems associated with integration of renewable energy sources in a smart grid have been studied by considering an actual 11 k power distribution feeder in Karnataka. The KIDB Industrial Feeder (ppendix1) in Tumkur District of BESCOM is fed from ntharasanahalli 220/66/11k Substation. This is an industrial feeder which contains most of the HT consumers. The radial network consists of 8km length of 11 k feeder. lthough there are more than 19 nos. of Distribution Transformer Centres (DTC) of various ratings, transformers of lower ratings have been lumped with their equivalent ratings being considered for the study without changing the characteristics of the loads. Ratings of transformers are 250k, 500k and 1000 k respectively. The utility substation is represented as a 11k source with its equivalent power frequency short circuit capacity of 750 M. The 11 k feeder includes two DG units. DG1 is a M conventional Biomass synchronous generator equipped with excitation and governor control systems. DG2 represents a fixed-speed induction generator type wind-turbine set with rated capacity of 1.25-M. I. System model The well known PSCD/EMTDC software package is used for the simulation of the Smart-grid Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

3 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, system of Fig. 6. The component models used for the simulation are as follows: The main grid is represented by an equivalent model of an 11-k three-phase voltage source with the shortcircuit capacity of 750 M and appropriate X/R ratio. The loads are modelled as constant impedances. DG1 is modelled as a single-mass synchronous machine. The machine electrical system is represented in the d-q-0 frame with one rotor winding on each axis. The excitation and governor systems of the machine are also included in the model. During start-up procedure, the synchronous generator is treated as a source where the rotor speed is constant. fter 0.3 s the machine model is activated and at 0.4 s the rotor speed is released to be adjusted by the governor. The synchronous machine parameters are given in table given below. DG2 is modelled as a squirrel cage induction generator with a wind source, turbine and a governor.. Optimum location of REs In the first study we will find the optimal locations of both the renewable. The objective function is to achieve minimum total losses in the network. There is a constraint for the optimal location. (i) oltage should be within permissible limits (10.5 k to 11.5 k). nnual energy loss calculation is given in table 1. TBLE 1 NNUL ENERGY LOSS CLCULTION. Biomass generator model The electrical part of DG1 is represented by a synchronous generator connected to the utility grid. The biomass system consists of synchronous generator, exciter, steam turbine and governor. The rated power is M, rated voltage 11 k (L-L rms) and generated power is 1.5 MW. B. Wind generator Model The electrical part of DG2 is represented by a squirrel cage induction generator connected to the utility grid. The mechanical systems of the DG2 are also modelled. The variable nature of the wind speed and its reflection on the input mechanical torque of the induction generator are also modelled by a wind-speed control panel. The rated power is 1.25 M, rated voltage is 11 k and generated power is 1.4 MW. II. Study cases Table 1 show that when we integrate renewable energy sources into the system, the losses reduces the losses in the system and the optimum location of biomass generator is Bus 5 and wind generator is Bus 8. B. Steady state analysis Base case consists of 11 k radial distribution network without the integration of any renewable energy sources. Power flow study was conducted. The PSCD/EMTDC representation of the 11 k study system of fig 1 is shown in fig 4.The bus 5 and bus 8 voltages, active and reactive powers are given in table 2. Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

4 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, TBLE 2 COMPRISON OF OLTGE, POWER ND RECTIE POWER IN RENEWBLE INTEGRTION Table 2 shows that when we integrate renewable into the system, the voltage profile on remote buses will improve. Simultaneously reliability of the system increased. Comparison graphs of voltages, active powers and reactive powers during integration of renewables are shown {fig 1(a), 1(b) and 1(c)} below. Fig 1(b) ctive powers at all buses Fig 1(a) oltages at all buses Fig 1(c) Reactive powers at all buses Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

5 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, C. Dynamic nalysis In this case, power flow studies were initially carried out by including the two renewable energy sources. Subsequently, the impact of disconnection of renewable sources is simulated by disconnecting each of the two sources, one at a time and observing the change in the load flow as also the voltage profile of the buses to which these sources are originally connected in the distribution system. t t=1 sec, wind system is disconnected and remains in the same condition. Dynamic analysis of renewable integration with the smart grid is studied. Comparison graphs of voltages, active powers and reactive powers during integration of renewables are shown in Table 3 and same is represented as fig. 2(a)(b) and(c) in graphical representation. TBLE 3 COMPRISON OF OLTGE, POWER ND RECTIE POWER IN RENEWBLE DISCONNECTION Fig 2(a) oltages at all buses Fig 2(b) ctive power at all buses Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

6 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, Case 2: In this case a 3phase symmetrical fault is applied on the bus 5. The fault occurs at t= 1 sec and remains for 5 cycles in the system. The bus voltage and fault current with biomass renewable integration are shown in fig below:- Fig 2(c) Reactive power at all buses We observe that when renewable are disconnected from the network, voltage profile of all buses reduces and reliability of the system weakens. Simultaneously load on the grid increases in view of disconnected renewable. Fig 3(c) Fault oltage at Bus 5 with biomass integration D. Fault analysis Case 1: In this case a 3phase symmetrical fault is applied on the bus 5. The fault occurs at t= 1 sec and remains for 5 cycles in the system. The bus voltage and fault current without renewable are shown in fig below:- Fig 3(d) Fault current at Bus 5 with biomass integration Case 3: In this case a 3phase symmetrical fault is applied on the bus 5. The fault occurs at t= 1 sec and remains for 5 cycles in the system. The bus voltage and fault current with wind renewable are shown in fig below:- Fig 3(a) Fault oltage at Bus 5 without REs Fig 3(e) Fault oltage at Bus 5 with wind integration Fig 3(b) Fault current at Bus 5 without REs Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

7 oltage(k) oltage(k) 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, Es Time in sec Fig 3(f) Fault current at Bus 5 with wind integration We observe from all the above mentioned 3 cases that when fault is cleared at t=1 sec, in that case time of recovery voltage with biomass renewable integration is very less but with wind integration time of recovery voltage is very high. Table 4 shows the comparison of TRs with biomass and wind integration. Faulted bus number TBLE 4 COMPRISON OF TIME OF RECOERY OLTGES Without REs integration (TR) in sec With only biomass integration(tr) in sec With only wind(tr) in sec Bus sec sec 2.5 sec It is seen from table 4 that time of recovery voltage is more in case of wind induction generator. E.Unbalance voltage In this case voltage unbalance occurs in the system and Fig 4.1(a) shows the unbalance in voltage without renewable integration and fig 4.1(b) shows the unbalance with integration of renewables Time Fig 4.1(a) oltage unbalances at bus 1 without REs Es Time in sec Fig 4.1(b) oltage unbalances at bus 1with REs It is observed that at t= 1sec, renewables are integrated into the system and percentage unbalance reduced significantly. Table 5 shows the comparison of percentage unbalance without renewable and with renewables. TBLE 5 COMPRISON OF PERCENTGE UNBLNCE WITH ND WITHOUT RENEWBLES Bus No oltage unbalance without REs(in %) oltage unbalance with REs (in %) Near feeder t biomass bus t wind bus Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

8 y y 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, F. Islanding phenomenon Frequency Main : Graphs n island is That part of a power system consisting of one or more power sources and load that is, for some period of time, separated from the rest of the system. n effect of large power unbalance in a newly formed island can be serious; such an island may not survive very long. On the other hand an island with perfect production balance can very well survive for a long time, even if there are no voltage or frequency controllers. Islanding condition occurs when breaker is intentionally opened to create an island. controller has been designed in order to shed the loads to bring the frequency at steady state condition i.e.50 Hz. priority index for shedding of loads has been shown in table Fig 5.1(a) Frequency before controller operation Fig 5.1 (a) shows the condition when grid is disconnected and renewables are not sufficient to supply the entire load of the network. TBLE 6 PRIORITY INDEX FOR LOD SHEDDING Frequency Main : Graphs Fig 5.1(b) Frequency after controller operation Fig 5.1 (b) shows the condition with controller operation and shedding of the load as per priority index(table 6) in order to bring the frequency back to 50 Hz. II Results & Discussion Fig 5 shows the algorithm for load shedding. This paper investigates dynamics of a 11-k multiple DG smart-grid system and performance of the adopted power management strategies in two analysis,(a) steady state analysis,(b) dynamic analysis. In steady state analysis when we connect renewable energy sources at bus 5 and bus 8.In dynamic analysis the radial network consists of biomass and wind generators. During disconnection of renewable voltage profile is reduced. When 3phase symmetrical fault is applied on bus 5, it is observed that time of recovery voltage is very high in case of wind integration. During unbalance percentage unbalance reduced with renewable integration. In Islanding phenomenon algorithm is developed for load shedding of non-sensitive loads. Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

9 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, Fig 5 lgorithm for load shedding Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

10 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, sudden fluctuation in power and voltage is observed which may cause severe disturbance in the systems, which needs to be mitigated. The future work is to mitigate these transients with different techniques. III. Conclusion The smart grid has been simulated using PSCD/EMTDC software considering various dynamic conditions of renewable energy sources. Results show that when Renewable energy sources are connected to the Distribution system, the voltage profile gets improved and this improves reliability of the system. lso, sudden connection or disconnection of renewable energy sources due to faults etc. may result in unacceptable transients in voltages in the distribution system which needs to be mitigated. IX. cknowledgement This work is carried out at Central Power Research Institute, Bangalore. The authors wish to thank CPRI and NITC for permitting to publish this work. The assistance rendered by Ms. Reshma, Project Engineer in simulation is gratefully acknowledged. XII. References [1] Robert H. Lasseter, Microgrids and Distributed Generation Transaction on journal of Energy Engineering, merican Society of Civil Engineers, Sept [2] Dr. Mrinalini Das,Nripen Das, Biomass : sustainable source of energy IEEE-transaction,olume 1,issue 3,pp ,2009. [3] mit Kumar Jindal, niruddha M. Gole and Dharshana Muthumuni, Modeling and performance analysis of an integrated wind/diesel power system for off-grid Locations Fifteenth National Power Systems Conference (NPSC) Transaction pp , December,2008. [4]Badrul Chowdhury,Srinivas Chellapilla Double-fed induction generator control for variable speed wind power generation Science@Direct on Electric Power Research,ol.76,PP ,2006. [5] F. Mei, B. C. Pal: Modeling and small-signal analysis of a grid connected doublyfed induction generator, presented at Proceeding of IEEE PES General Meeting 2005, San Francisco, US, [6] X. P. Zhang, Framework for Operation and Control of Smart Grids with Distributed Generation,IEEE transaction ol 29,issue 2,pp 1-5,2008. uthors information 1 Suhas shirbavikar, department of Electrical Engg., NIT Calicut (suhas_shir@yahoo.co.in) 2 S.shok, department of Electrical Engg. NIT Calicut 3 M. M Babu Narayanan, central power research institute, Bangalore. Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

11 IF 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, P = BUS 1 Q = = [mh] 0.2[ohm] BUS [ohm] P = Q = = [mh] BUS [ohm] BUS 4 P = P = Q = Q = = [mh] = [mh] 0.27[ohm] BUS 5 RLC P = Q = 1.79 = P = Q = = [mH] 0.26[ohm] P = Q = = P = Q = = P = Q = = 0.41 P = Q = = ref0 Ef0 Ef S / H in hold out S2M ref Exciter_(C1) T IT 3 If P = Q = = Es Main : Controls 1.16[ohm] GR P = Q = P = Q = = BUS 6 = BUS [mh] 2.35[mH] 1.008[ohm] 1.12[ohm] P = Q = = P = Q = = P = Q = = I M wind gen W S T P = Q = = [mH] * -1 P = Q = = TIME BUS M 1.5 MW 6.3k 0.1 k 1.0 w Cv Steam Gov 2 Iv Wref Ef0 Te Tm EF w Cv Ef If S w Tm Tm1 Steam_Tur_2 Iv Wref Tm2 3 Tm0 P = Q = = Tmstdy POUT Ef QOUT ES ES Wind Source Mean w w w W Wind Turbine MOD 5 Type Tm P W 1.0 Ctrl = 1 B Ctrl CNT * N 3.0 Pole pairs N/D D W Beta GR 2 Pi * 50.0 BET Beta Pwind * Ctrl = 1 B Ctrl Pg Wind Turbine Governor MOD 2 Type TIME CNT Fig 6.PSCD/EMTDC model of biomass and wind integrated system Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.

12 16th NTIONL POWER SYSTEMS CONFERENCE, 15th-17th DECEMBER, ppendix Study system is taken as KIDB feeder in Tumkur district in Karnataka. Rabbit conductor is used for transmission line.the total length of distribution network is 8 kms.17 distribution transformers are taken into consideration for the study. Ratings of transformers are 250k, 500k and 1000 k respectively. Loading on the transformer is 90% as per the survey conducted. The utility substation is represented as a 11k source with its equivalent power frequency short circuit capacity of 750 M. Study system Department of Electrical Engineering, Univ. College of Engg., Osmania University, Hyderabad,.P, INDI.