Control of Multiple Energy Sources’ converters Connected to a DC Micro-Grid

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International Journal of Recent Advances in Engineering & Technology (IJRAET)

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Control of Multiple Energy Sources’ converters Connected to a DC Micro-Grid

1AswathySKumar, ²A:V ijayakumari, ³S:RMohanrajan

1,2,3Amrita School of Engineering Coimbatore

Email: ¹aswathyskumar9@gmail:com, ²71viji@gmail:com, ³srmohanrajan@gmail:com

Abstract—DC microgrids are gaining popularity due to high efficiency, high reliability, and easy interconnection of renewable sources as compared to the ac system. This paper describes a control scheme for a DC micro-grid system having distributed generators. It consists of multiple solar energy sources. The control scheme is developed to extract maximum power from the sources with reduced circulating current. To evaluate the performance, MATLAB/SIMULINK model is developed and dynamic variations in the system have been verified.

The dynamic variations in the system input is reflected within 0.1s transient time.

Index Terms—Circulating current, Current control, DC microgrid, MPPT .

I. INTRODUCTION

The increasing energy demand and global warming resulted in the use of renewable energy sources like solar and wind, for generating power. These generated power is always given at the distribution level since the generated power is not large enough to be transmitted for longer distances; hence these sources named as distributed generations(DGs). The concept of micro-grid has been evolved for smooth integration and control of DGs with the utility grid.A micro grid comprises of low voltage distributed systems with distributed generations, storage devices, loads and interconnecting switches. A microgrid can be operated in islanded mode, grid connected mode and a transition between these two. By making use of existing grid technologies and protection standards; AC micro-grids have been suggested. But the power generated by these DGs are DC and the increased use of DC loads like Uninterrupted Power Supplies(UPS) flourescent lights, LEDs, variable motor drives etc. results in multiple conversion stages which results in heavy losses . Hence DC micro-grids can be considered which reduces conversion losses.

Different control issues and comparative studies of DC microgrid have been reported in the literature. In [1] a comparison between AC and DC distribution networks for low and medium voltages have been considered. The major drawback is that due to high semiconductor losses DC distribution network is less efficient. This becomes a serious concern while designing a DC micro-grid.

Another DC micro-grid for super high quality

distribution with control of distributed generations and energy storage devices is proposed in [2].A tolerance level has been set for DC micro-grid voltage, however the instantaneous voltage difference at the converter output stages have not been accounted. Another micro- grid architecture is proposed in [3] which considered the maximum utilization of distributed generations and smooth transition between different operating modes.

The control scheme was based on Proportional-Integral controller; hence tuning of PI controller is required, which is not mentioned. Different types of micro-grid architectures and their control schemes have been discussed in [4], [5], [6] and [7] but none of them mentioned about the circulating current issue due to parallel connection of converters. A control strategy for improving the stability of the system by considering rectifier and feeder parameters using active damping has been introduced in [4]; however the complexity of the system makes it less reliable. In order to improve reliability and for secure power supply a new method is proposed in [5], and for improving load sharing among DGs a control scheme based on primary secondary and tertiary controllers have been considered in [8], but both failed to mention about circulating current which occurs due to the difference in instantaneous voltages at converter output; where as in [9] the problem due to circulating current is solved but the use of generation limiters affects the maximum power extracting from the sources.In [7], another micro-grid architecture based on multiple modes control has been discussed, but proper load sharing was not obtained since transmission line impedances were not taken into account. Droop controlled DC micro-grid has been discussed in [10]

which has the inherent defects of droop control, voltage regulation and power sharing was not accurate. The dynamic behaviour of power electronics interfaces also affects micro-grid operation which has been discussed in [11] but failed to consider the difference in instantaneous voltages at converter outputs and tuning of PI controller used in the control scheme.

The following are the issues addressed by several authors[1]- [11]

 Voltage regulation of DC bus.

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 Circulating current due to difference in instantaneous values of voltages.

 Load sharing among sources.

 Power balance between source and load.

 Maximum power extraction from the DGs.

In this paper, a DC micro-grid with multiple energy sources is considered which addresses maximum power extraction from the sources with reduced circulating current. System configuration and different operating modes are discussed in the following sections. The effectiveness of the proposed

Fig. 1: System block diagram

Fig. 2: Single diode equivalent circuit of a PV cell system is validated by SIMULINK/MATLAB simulations and results are shown in Section III .

II. SYSTEM DESCRIPTION

The system described in this paper consists of multiple energy sources feeding a DC grid. The DC grid supplies power to the loads connected on it. Energy sources are connected to the grid through power electronic interfaces. The basic system structure is shown in Fig.1.

The control issues addressed in this paper are;

 maximum power extraction from the sources and

 circulating current.

– when multiple energy sources are connected in

parallel, the difference in instantaneous values of voltages results in large amount of current among the sources.

A control scheme is required to meet both the issues simultaneously.

A. Energy Sources

Distributed generations typically use renewable energy sources, including solar power wind power, small hydro, biomass, biogas and geothermal power. In this paper solar energy systems are considered as the DGs.

Different models of solar panel have already been developed by many of the authors([16], [17], [18], [19], [20]). Most commonly used one is the single diode equivalent circuit[20], which is shown in Fig.2. The circuit consists of a current source, a diode in

Fig. 3: I-V characteristics of a typical Solar Cell

Fig. 4: Control block diagram

parallel with the current source, and series resistance.

The current(I)-voltage(V) characteristics of a typical solar cell is shown in Fig.3. This equivalent circuit is considered in this paper for simulation studies.

B. Proposed Control Scheme

The control scheme is developed to maximize the power extracted from the sources and to reduce the circulating current. The control block diagram is shown in Fig.4.

For maximum power extraction from the sources different types of maximum power point tracking(MPPT) controllers have already been

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developed. In conventional MPPT controllers, the load voltage is allowed to vary in order to extract maximum power under varying atmospheric conditions. So, conventional method cannot be applied for the system shown in Fig.1 since the energy sources are connected to a DC grid. As the voltage of the grid is constant, voltage control method cannot be used and in order pump varying power to the grid , the only parameter which can be used is current. Hence a current control scheme is also required along with the MPPT controller to supply variable power by injecting different values of current.

Tolerance band current control method is used; where a reference current is compared with the measured current which decides the duty ratio of the converter. This method is described in Fig.5.

For MPPT, incremental conductance method [21] is used. The

Fig. 5: Tolerance band control

Fig. 6: Simulation Block Diagram

conventional algorithm is modified in such a way that when maximum power is reached, the power value and voltage corresponding to the maximum power will be stored in the memory and used to generate the reference current. This reference current will be given to the tolerance band control which compares with the measured current and generate the switching pulses for

the converter; assuming efficiency is 100%.

III. SIMULATION RESULTS

For simulation studies two solar energy sources of different ratings are considered. First source consists of four solar panels connected in series and second source consists of eight solar panels, in which four are connected in series and four are connected in parallel.

Specifications for a single panel UL1703 TABLE I: Test specifications

under Standard Test Conditions(STC) and Nominal Operating Cell Temperature(NOCT) given in Table.I.

The simulation model is shown in Fig.6. From Table.I;

Maximum power generated by a single panel under STC is 68W. So the power output from the first source(P(c1))is 272W and the power output from the second source(P(c2)) is 544W under STC.

The total power becomes 816W Under NOCT a single panel can generate maximum power of 53W [Table I], that means P(c1) becomes 212W and P(c2) becomes 424W, so the total power is 636W.

The DC bus voltage is fixed to be 120V. The output of a single PV panel under open circuit condition is found to be 23.1V[22], which is the maximum voltage that can be obtained from a single panel. In both sources only four panels are connected in series and the maximum output voltage will be 92.4W; hence a boost converter is required to raise the voltage to 120V. For a boost converter;

V_o = V_in=(1 - D) (1)

where V_o is the converter output voltage, V_in is the input voltage and D is the duty ratio.

To validate the proposed control method for integration of multiple energy sources in a DC micro-grid, simulation studeis have been carried out for the system shown in Fig.6 using SIMULINK/MATLAB. Based on operating conditions different cases are considered to verify the control scheme.

Each case is simulated for 5s and variations are applied when time is 2.5s.

A. Case-1

Solar energy sources have been operated under STC. A load of 500W is connected to the grid. From Fig.7i it is clear that the total output power of the two converters(Pc) is maximum and Fig.7iii shows that load power(PL) remains constant. Since the supplied power is greater than the load power grid is absorbing extra

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power(Pg) which is shown in Fig.7ii. The time taken by the system to generate maximum power is less than 0.1s.

B. Case-2

Variation in irradiance and temperature have been applied to the first energy source; where the operating conditions are varied from NOCT to STC at 2.5s. So, the power output of the first converter is increased from 212W to 272W at 2.5s and the second source has been operated under STC ; so the output

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Fig. 7: (i)Power from converter, (ii) Grid Power, (iii) Load Power

power of second source is 544W. Total power supplied by the converter (Pc) to the grid is greater than the load power(PL) which is shown in Fig.8i. Since the supplied power is increased at 2.5s, the extra power absorbed by the grid is also increased which is shown in Fig.8ii. The transient time taken by the system to vary from one operating condition to the other is lees than 0.1s.

C. Case-3

In this case change in irradiance and temperature from NOCT to STC has been given to the second source at 2.5s and first source has been operated under STC.

Output power of the first converter is 272W and output power of the second converter is increased from 424W to 544W at 2.5s. So, the total power(Pc) supplied to the grid is increased which is clear from the Fig.9i. The load power(PL) remains constant[Fig.9iii] and the extra power absorbed by the grid is also increased which is shown in 9ii.The change in operating condition is

reflected in the power generation within a transient time of 0.1s.

D. Case-4

Both the energy sources have been operated under NOCT as well as STC. The change in operating conditions have been given at 2.5s. The total power supplied by the converter also increased from 636W to 816W at 2.5s. In both conditions the supplied power is greater than the load power. So the amount

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of power absorbed by the grid is also increased which is clear from the Fig.10ii. Change in operating condition has been given to both sources and system reached its maximum point condition within 0.1s.

E. Case-5

In all the other cases only a constant load was connected to the grid. Here the load power is increased from 500W to 1200W at 2.5s and both the sources have been operated under STC. From Fig.11iii, it is clear that the load power is increased at 2.5s and the supplied power is lesser than the load power at 2.5; the required power has been supplied by the grid which is shown in Fig.11ii.

The sudden variation in load took a transient time less than 0.1s.

Using all the graphs shown here, it is clear that the proposed control scheme for a DC micro-grid with multiple energy sources is working properly. The addressed issues have been solved; i.e, maximum power

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has been generated by the energy sources with reduced circulating current.

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IV. CONCLUSION

This paper presented a DC micro-grid based power generation system with multiple energy sources. A new control method is proposed to extract maximum power from the sources and to suppress the circulating current simultaneously. The simulated results have been verified. Different cases considered in this paper have proven that the system performance is fast and accurate.

The transient time for the system when a sudden variation has been applied is less than 0.1s.The results clarified that each source worked according to the control, and maximum power has been extracted from the sources with reduced circulating current.

REFRENCES

[1] D. Nilsson and A. Sannino, “Efficiency analysis of low-and medium-voltage dc distribution systems,” in Power Engineering Society General Meeting, 2004. IEEE. IEEE, 2004, pp. 2315–

2321.

[2] H. Kakigano, Y. Miura, T. Ise, and R. Uchida,

“Dc micro-grid for super high quality distributionsystem configuration and control of distributed generations and energy storage devices,” in Power Electronics Specialists Conference, 2006. PESC’06. 37th IEEE. IEEE, 2006, pp. 1–7.

[3] X. She, S. Lukic, and A. Q. Huang, “Dc zonal microgrid architecture and control,” in IECON

(6)

2010-36th Annual Conference on IEEE Industrial Electronics Society. IEEE, 2010, pp. 2988–2993.

[4] J. Lago and M. L. Heldwein, “Operation and controloriented modeling of a power converter for current balancing and stability improvement of dc active distribution networks,” Power Electronics, IEEE Transactions on, vol. 26, no. 3, pp. 877–885, 2011.

[5] L. Xu and D. Chen, “Control and operation of a dc microgrid with variable generation and energy storage,” Power Delivery, IEEE Transactions on, vol. 26, no. 4, pp. 2513–2522, 2011.

[6] S. Anand, B. G. Fernandes, and M. Guerrero,

“Distributed control to ensure proportional load sharing and improve voltage regulation in low- voltage dc microgrids,” Power Electronics, IEEE Transactions on, vol. 28, no. 4, pp. 1900–1913, 2013.

[7] X. Jianfang and W. Peng, “Multiple modes control of household dc microgrid with integration of various renewable energy sources,”

in Industrial Electronics Society, IECON 2013- 39th Annual Conference of the IEEE. IEEE, 2013, pp. 1773–1778.

[8] S. Anand and B. Fernandes, “Steady state performance analysis for load sharing in dc distributed generation system,” in Environment and Electrical Engineering (EEEIC), 2011 10th International Conference on. IEEE, 2011, pp.1–4.

[9] Y. Ito, Y. Zhongqing, and H. Akagi, “Dc microgrid based distribution power generation system,” in Power Electronics and Motion Control Conference, 2004. IPEMC 2004. The 4th International, vol. 3. IEEE, 2004, pp. 1740–1745.

[10] C. Li, S. K. Chaudhary, T. Dragicevic, J. C.

Vasquez, and J. M. Guerrero, “Power flow analysis for dc voltage droop controlled dc microgrids,” in Multi-Conference on Systems, Signals & Devices (SSD), 2014 11th International. IEEE, 2014, pp. 1–5.

[11] M. Martino, Y. F. Qui˜nones, P. Raboni, and Z.

Chen, “Intelligent control for a dc micro-grid system,” in Universities Power Engineering Conference (UPEC), 2012 47th International.

IEEE, 2012, pp. 1–5.

[12] N. Eghtedarpour and E. Farjah, “Control strategy for distributed integration of photovoltaic and

energy storage systems in dc micro-grids,”

Renewable energy, vol. 45, pp. 96–110, 2012.

[13] Mummadi, Veerachary, and B. S. Singamaneni,

“Stability analysis of cascaded dc–dc power electronic system,” IEEJ Transactions on Electrical and Electronic Engineering, vol. 4, no.

6, pp. 763–770, 2009.

[14] R. W. Erickson and D. Maksimovic, Fundamentals of power electronics. Springer Science & Business Media, 2001.

[15] N. Mohan and T. M. Undeland, Power electronics: converters, applications, and design.

John Wiley & Sons, 2007.

[16] H. Nagayoshi, S. Orio, Y. Kono, and H.

Nakajima, “Novel pv array/module iv curve simulator circuit,” in Photovoltaic Specialists Conference, 2002. Conference Record of the Twenty-Ninth IEEE. IEEE, 2002, pp. 1535–

1538.

[17] J. Ollila, “A medium power pv-array simulator with a robust control strategy,” in Control Applications, 1995., Proceedings of the 4th IEEE Conference on. IEEE, 1995, pp. 40–45.

[18] E. Koutroulis, K. Kalaitzakis, and V. Tzitzilonis,

“Development of an fpga-based system for real- time simulation of photovoltaic modules,”

Microelectronics journal, vol. 40, no. 7, pp.

1094–1102, 2009.

[19] Y. Li, T. Lee, F. Z. Peng, and D. Liu, “A hybrid control strategy for photovoltaic simulator,” in Applied Power Electronics Conference and Exposition, 2009. APEC 2009. Twenty-Fourth Annual IEEE. IEEE, 2009, pp. 899–903.

[20] A. Vijayakumari, A. T. Devarajan, and N.

Devarajan, “Design and development of a model- based hardware simulator for photovoltaic array,”

Electrical Power and Energy Systems, vol. 43, pp. 40–46, April 2012.

[21] Z. Xuesong, S. Daichun, M. Youjie, and C.

Deshu, “The simulation and design for mppt of pv system based on incremental conductance method,” in information engineering (ICIE), 2010 WASE international conference on, vol. 2.

IEEE, 2010, pp. 314–317.

[22] UNI-SOLAR Power Bond Technical Data Sheet.

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