GSJ: Volume 5, Issue 5, May 2017 163
MODELING OF MICROGRID SYSTEM COMPONENTS USING MATLABSIMULINK
M.A. Fouad, M.A. Badr, M.M. Ibrahim
Mechanical Power Engineering Dept, Faculty of Engineering, Cairo University Mechanical Engineering Dept, Nationa l Research Centre, Cairo
ABSTRACT
Microgrid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. Renewable power sources such as wind, solar and hydro offer high potential of benign power for future microgrid systems. MicroGrid MG is basically a low voltage LV or medium voltage MV distribution network which consists of a number of called distributed generators DGs; microsources such as photovoltaic array, fuel cell, wind turbine etc. energy storage systems and loads; operating as a single controllable system, that could be operated in both gridconnected and islanded mode. The capacity of the DGs is sufficient to support all; or most, of the load connected to the microgrid. This paper presents a microgrid system based on wind and solar power sources and addresses issues related to operation, control, and stability of the system. Using MatlabSimulink, the system is modeled and simulated to identify the relevant technical issues involved in the operation of a microgrid system based on renewable power generation units.
Keywords Microgrid system, photovoltaic, wind turbine, energy storage, distributed generation, GSJ
1. INTRODUCTION
Modeling and Simulation.
The increasing need for energy generated with clean technologies has driven researchers to develop distributed power generation systems using renewable energy sources 1, 2. On the other hand, the integration of a large number of distributed generations into distribution networks is restricted due to the limitation of the networks capacity and unidirectional power flow behavior 3,4. Such barriers have motivated the search for to an alternative conceptual solution to enhance the distributed generation integration into the distribution networks.
Microgrid approach was proposed as a means of integrating more distributed generations into the distribution networks 5. Distributed Generation DG in microgrid operation provides multi benefits to the utility operators, DG owners and consumers in terms of reliable power supply, reduction in transmission system expansion and enhancement of renewable power penetration.
R. H. Lasseter proposed the first microgrid architecture that was called Clean Energy Resources Teams CERTS 5, 6. CERTS microgrid generally assumes converterinterfaced distributed generation units based on both renewable and nonrenewable power sources. A microgrid system was also proposed by Barnes et al 7 under the umbrella of Microgrids European project .
Future power network is expected to a focus on a microgrid system based on renewable power generation units. The characteristics of a microgrid system depend on the type and size of the micro generation units, as well as the site, and the availability of the primary energy resources on the site, especially renewable power sources.
1
GSJ: Volume 5, Issue 5, May 2017 164
Advancement in Distributed Generations DGs and microgrids is accompanied by the development of various essential power conditioning interfaces and their associated control to connect multiple micro sources to the microgrid, and tie the microgrids to the traditional network 8. Microgrid operation becomes highly flexible, with such interconnection and can be operated freely in the grid connected or islanded mode of operation. The islanded mode of operation with more balancing requirements of supplydemand may be started when the main grid disconnected due to any fault.
All the above mentioned literature presented single renewable source microgrids. The current work presents the simulation of a micro grid model that includes two renewable energy sources; Photovoltaic PV and a wind turbine WT in addition two operational modes of operation island and Grid connected are investigated.
This paper is organized as follows: Section 2; describes the modeling of Photovoltaic PV and Wind Turbine WT systems, energy storage, backup Diesel Generator along with their power electronic interfacing circuits in MatlabSimulink. Verifying the characteristics, of the developed models, the generated voltage is synchronized to form a Microgrid which is capable of operating grid connected as well as in islanded mode. Section 3 shows results of simulation components. Section 4 exhibits control switch of microgrid model. Section 5 illustrates overall microgrid model using MatlabSimulink package. Section 6 presents simulation results showing results of synchronous voltage and power generated. Finally, Section 7 presents conclusion.
2. Modeling MG Components
2.1 PV Module
GSJ
As me nt io ned abo ve t he co mpo ne nt s o f t he ide nt if ied s ys te m are mode led us ing MATLABSIMULINK software tool.
A generalized PV model is built using MatlabSimulink to illustrate and verify the nonlinear IV and PV output characteristics of PV module.
The behavior of photovoltaic PV cells can be modeled with an equivalent circuit that includes a photocurrent source, a single diode junction and a series resistance and a shunt resistance, 9. The Simulink model of PV module is shown in the Fig.1.
100W each cell
Fig.1: MatlabSimulink model of the PV array
2
GSJ: Volume 5, Issue 5, May 2017 165
2.2 WT Module
Wind turbine is composed of a rotor, a generator, threeblades, and a drive train. In case of high wind speed, the generator output power is controlled by adjusting the pitch angle. Power is transmitted to the grid through power electronic interface, the. A wind turbine extracts kinetic energy from the wind blowing through the blades. The power developed by a wind turbine is given by 10. The Simulink model of a wind turbine equation is shown in figure 2.
GSJ
Fig.2: MatlabSimulink model of the wind turbine block
2.3 Energy Storage Modules
The electricity demand fluctuates depending on the time of the day and the time of a year. Since the traditional power grid is not able to store up electricity, the mismatch between supply and demand is more likely observed. As the concept of Microgrid is becoming more pervasive, a mixed power system makes the best use of the different types of local generation. Some forms of generations have large response time and others have little flexibility in operation. In addition, some forms of generations can start up very quickly to provide more or less energy depending on the realtime load demand pattern. Provided these reasons clearly, the energy storage is beneficial in managing such a system. A desired form of energy storage is expected to provide the required power into the power system and store up sufficient energy at low electricity consumption. Two types of shortterm storage are studied and modeled: Storage batteries, and Supercapacitor.
2.3.1 Battery Bank
There are several approaches to model a battery. A commonly used battery model is the Thevenin equivalent circuit, 11. In this case Simulink implements set of predetermined charge behavior for four types of battery: LeadAcid, LithiumIon, NickelCadmium and NickelMetal Hydride. Figure 3 illustrates a detailed modeling of chargedischarge battery in MatlabSimulink.
3
GSJ: Volume 5, Issue 5, May 2017 166
Charge Model Discharge Model Fig. 3: ChargeDischarge battery modeling in MatlabSimulink
2.3.2 Supercapacitor
The Supercapacitor, also known as ultracapacitor, is the electrochemical capacitor that has higher energy density than common capacitors on the order of thousands of times. The equivalent circuit used for conventional capacitors can also be applied to supercapacitors, 12.
GSJ
If the simulation time is much larger than the selfdischarge time, the equivalent parallel
resistance might be neglected as well. The actual capacity C varies with quantities as current,
voltage and temperature. Equations of RLRC circuits are shown in 12. Figure 4 illustrates
modeling of supercapacitor block.
Fig.4: Supercapacitor block Model in MatlabSimulink
2.4 DieselGeneratorModel
Diesel Engines; both spark ignition, SI and compression ignition CI, were first among distribution generator technologies. The Diesel Engine model gives a description of the fuel consumption rate as a function of speed and mechanical power at the output of the engine, and is usually modeled by a simple first order model relating the fuel consumption to the engine
4
GSJ: Volume 5, Issue 5, May 2017 167
mechanical power. The power output of the engine and the generator varies according to load in order to meet the demand.
The governor can be defined as a mechanical or electromechanical device for automatically controlling the speed of an engine by relating the intake of the fuel, 13. The task of the governor is to adjust the fuel flow and then regulate the input of the engine and generator, hence provides the required power to meet the change in the load. Several types of governors exist such as mechanical, electronic, microprocessor based and others. Figure 5 illustrates the diesel engine model in Mat lab S imulink .
15 kW
GSJ
Square Wave
Modified Square Wave Modified Sine WavePure Sine Wave True Sine Wave
The three different wave signals represent three different qualities of power output. Square wave inverters result in uneven power delivery that is not efficient for running most devices. Modified square wave modified sine wave inverters deliver power that is consistent and efficient enough to run most devices fine while sensitive equipment requires a sine wave, 14. Figure 6 shows Model of Inverter block Matlab Simulink.
2.6 Load and Utility Grid Models
The utility grid is modeled as a three phases ideal voltage source with infinite power rate. This simplified model is only used for analyzing the dynamic behaviorof the proposed systems. A Utility grid model is shown in figure 7 while figure 8 describes three phase load model. The models of three dynamic load and three phase fixed load with constant impedances are available in the standard SimPower Systems library. The active power and reactive power can be controlled via the external control signals. It is especially useful when the demand response or demand side management is taken into account.
2.5 Inverter Controller Model
Fig. 5: Model of Diesel Generator in Matlab Simulink
Inverter or power inverter is a device that converts the DC sources to AC sources. Power inverters produce one of three different types of wave output:
5
GSJ: Volume 5, Issue 5, May 2017
168
Fig.6: Inverter block model in MatlabSimulink
3. RESULTS OF COMPONENTS SIMULATION
Figure 9a represents the IV PV characteristics obtained from the PV array, while figure 9b illustrates power curve from WT. Charge output curves from battery bank are presented in figure 9 c while figure 9 d shows output curve in discharge battery. Output curves from diesel generator are described in figure 9 e while figure 9 f presents inverter output curves.
Fig.7: Utility grid model in MatlabSimulink
GSJ
Fig.8: Three phase load model in MatlabSimulink
6
GSJ: Volume 5, Issue 5, May 2017
169
Current I
Power P
GSJ
Power P
Voltage V
IV curve
Fig.9a: Simulation results of IVPV curves of PV Array output
Voltage V
PVcurve
SOC
Time T
Fig.9b: Simulation results of WT Power Curve
Voltage V
Time T
Time T
Fig.9c: Simulation results of SOCV Curves in Charge Battery
7
GSJ: Volume 5, Issue 5, May 2017
170
SOC
Voltage V
Time Fig.9d: Simulation results of SOCV Curves in Discharge Battery
Time
GSJ
Time
Fig.9f Simulation results of IV Curves from Inverter Output
4. MICROGRID CONTROL SWITCH UNIT
In order to operate the MicroGrid in gridconnected mode or offgrid mode, a simple control logic circuit is designed in MatlabSimulink in figure 10. In the ongrid system, when Power output from renewable greater than load power, excess power exported to grid sell block and when renewable output less than load power, grid purchase block used. In the offgrid system, when Power output from renewable greater than load power, batteries operate and excess energy stored in its and when renewable output less than load power, diesel generator used to cover this shortage.
Fig.9e: Simulation results of I V Curves from Diesel Generator
8
GSJ: Volume 5, Issue 5, May 2017 171
Fig.10: MicroGrid Control Model in MatlabSimulink OnOffgrid mode
5. COMPLETE SIMULINK MODEL OF A MICROGRID SYSTEM
GSJ
After implementing all these models in MatlabSimulink, the models are combined together to form a MicroGrid system offon grid as shown in figure 11 a, b.
Fig.11 a: Complete MatlabSimulink Model of a MicroGrid system off grid
9
GSJ: Volume 5, Issue 5, May 2017 172
The below illustrated Microgrid is small scale which is divided into three important parts: Renewable Energy Sources, Load and Grid. Two renewable energy sources are included; PV array and a simplified model of a wind turbine. The load is the energy required for two small industries: Fodder production and Hydrogel. Simulating the system using Simulink tool, the following power measurements are observed on display as explained in the following section.
20 kW
GSJ
30 kW
Max:50kW
Fig.11 b: Complete MatlabSimulink Model of a MicroGrid system on grid
10
GSJ: Volume 5, Issue 5, May 2017 173
6. SIMULATION RESULTS
The results of simulation of the performance of the above modeled microgrid are shown in figure 12. The figure is divided into ten illustrations that represent different outputs. The first six figures show a, b, c, d, ef PV and WT characteristicpower curves. The rest four parts of figure 12 exhibit the power flow from renewable to either grid, or load.
GSJ
Time Time
Fig.12c: Simulation results of PV Power Curve Fig.12d: Simulation results of WT Power Curve
Fig.12a: Simulation results of IVPV curves of PV Array output
Fig.12b: Simulation results WT characteristics
kW
11
GSJ: Volume 5, Issue 5, May 2017
174
Time
Fig.12e: Simulation results of PV Array Voltage
Time
Fig.12f: Simulation results of WT CurrentVoltage
SJ
G
PRL PRL
Fig.12g: Renewable ToGrid Curve Fig.12h: GridToLoad Curve
12
GSJ: Volume 5, Issue 5, May 2017 175
Fig.12i: Ruler Viewer 0PRl5104 Fig.12k: Ruler Viewer 0PRl5104Note: PRl is the difference power between renewable sources and the load
GSJ
Figure 12gh demonstrates the energy flow from RES to the grid and from grid to load, respectively. The vertical axis represents the fuzzy membership function 15 as shown in figure 12l, while the horizontal axis represents the difference between the generated RE and the load REL, at any time
In figure 12i the three columns that represent; from left to right, the difference REL output, power flow
from Grid to load and the power from renewable to Grid. In case that the difference is positive, so the
energy flows directly to the grid while negative value means that the power is flowing from grid to load. At
the top left it could be seen that the power is about 40 kW. As for figure 12k, it could be seen that the difference is less than zero, hence the load is supplied from the grid. The red vertical line represents the fuzzy logic control position.
Fig.12l: System Fuzzy Membership Function
13
GSJ: Volume 5, Issue 5, May 2017 176
7. CONCLUSION
A MicroGrid MG system that is based on renewable power generation units is presented in this paper. The proposed system has been designed to operate in two operational modes; islandedgrid connected. The system performance is investigated using a simulation based on MatlabSimulink software package. A control coordinator and monitoring system is also included to monitor micro grid system state and decide the necessary control action for an operational mode. The system design took into consideration cost reduction through using a single 3phase inverter instead of three onephase inverters. Moreover, transformer has been eliminated to supply power to its local loads. It is intended that this work will be the base for the developing more sophisticated Micro Grid designes.
REFERENCES:
GSJ
9. W.D.Soto, Improvement and Validation of a Model for Photovoltaic Array Performance, M.Sc. Thesis, Solar Energy Laboratory, University of Wisconsin Madison, 2012.
10. J.G.Slootweg, S.W.De Haan, H.Polinder and W.L.Kling, Modeling wind turbines in power system dynamics simulations, Power Engineering Society Summer Meeting, Conference Proceedings, pp. 222, 2015.
11. O.Tremblay, L.A.Dessaint and A.I.Dekkiche, A generic battery model for the dynamic simulation of Hybrid Electric Vehicles, IEEE Vehicle Power and Propulsion Conference, Vol.1, pp.284289, 2007.
12. Electric doublelayer capacitor Wikipedia, Cited on Oct 12, 2009 Online Available: ht tp :e n. w ik iped ia.o r g w ik iS upe rcapac itor.
1 T.Ackermann and V.Knyazkin, Interaction between distributed generation and the distribution
network: Operation aspects, Second Int. Symp. Distributed Generations: Power System Market
Aspects, Stockholm, Sweden, 2013.
2 C. Abbey, F.Katiraei, C.Brothers, Integration of distributed generation and wind energy in
Canada, Invited paper IEEE Power Engineering Society General Meeting and Conference,
Montreal, Canada, June 1822, 2015.
3 Frede Blaabjerg, Remus Teodorescu, Marco Liserre, Adrian V.Timbus, Overview of control and
gridsynchronizationfordistributedpowergenerationsystems,IEEETransactionsonIndus trial
Electronics, Vol. 53, No. 5,October 2012.
4 F.Katiraei, C.Abbey, Richard Bahry, Analysis of voltage regulation problem for 25kV
distribution network with distributed generation, IEEE Power Engineering Society General
Meeting, Montreal, 2013
5 R.H.Lasseter, Microgrids distributed power generation, IEEE Power Engineering Society Winter Meeting, Vol.01, pp.146149, Columbus, Ohio, Feb 2014.
6 R.H.Lasseter, Microgrids, IEEE Power Engineering Society Winter Meeting, Vol.01, pp. 305
308, New York, NY, 2015.
7 M.Barnes, A. Dimeas, A. Engler, C. Fitzer, N. Hatziargyriou, C. Jones, S. Papathanassiou, M.
Vandenbergh, Microgrid laboratory facilities, International Conference on Future Power
System,November 2015.
8. M.Barnes, J.Kondoh, H.Asano, and J.Oyarzabal, RealWorld MicroGrids an Overview, in IEEE Int. Conf. Systems of Systems Engineering, pp.18, 2014.
14
GSJ: Volume 5, Issue 5, May 2017 177
13. G.S.Stavrakakis and G.N.Kariniotakis, A General Simulation Algorithm for the Accurate Assessment of Isolated DieselWind Turbines Systems Interaction.1. A General Multi Machine PowerSystem Model, IEEE Transactions on Energy Conversion, Vol.10, pp.577583, Sep 1995.
14. Neng Cao, Yajun Cao and Jiaoyu Liu, Modeling and Analysis of GridConnected Inverter for PV Generation, Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering ICCSEE 2013.
15. Pedrycz and Witold, Fuzzy control and fuzzy systems, Research Studies Press Ltd, 2013.
GSJ
15
Reviews
There are no reviews yet.