Three-Phase Photovoltaic Grid-Connected Inverter using dSPACE DS1104 Platform

Z A Ghani, M A Hannan, A Mohamed and Subiyanto Dept. of Electrical, Electronic & Systems Engineering

Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia E-mail: zamree64@eng.ukm.my; hannan@eng.ukm.my; azah@eng.ukm.my; biyantote_unnes@yahoo.com

Abstract- This paper presents a simulation modeling for the hardware development of photovoltaic three-phase voltage source inverter utilizing dSPACE DS1104 controller platform. The controller links the MATLAB/Simulink simulated model to the inverter prototype for operation in real-time. It generates a sinusoidal pulse-width modulation (SPWM) signals for switching devices (IGBTs) with the accomplishment of fuzzy logic controller and Park transformation. Consequently, the inverter provides power not only to the local loads but also feeds the available excess power to the grid. The current and voltage control strategies which are implemented by using the fuzzy logic controller regulate the 50 Hz sinusoidal ac output current and voltage for both modes of operations namely isolated and grid-connected mode. The simulation was carried out with the PV generator simulator to facilitate the real PV power transfer to the local loads and grid. With the excellent results of 2.48% in the total harmonic distortion (THD) of output voltage, suggests that the proposed control system exhibits a good performance, thus can be translated into a prototype by utilizing the dSPACE platform. The simulation results waveforms such as ac output voltages, current and system power flow are presented to validate the efficacy of the control system.

INTRODUCTION

A photovoltaic (PV) energy is becoming one of the important renewable energy sources. In order to transport this kind of energy to the electric utility, an interface such as inverter is necessary. Inverter efficiency is not up to the mark due to its self-consumption losses [1]. Moreover the impact of unbalanced load on inverter output voltage [2], nonlinearity, and low efficiency of the PV devices [3][4], electromagnetic interference, harmonics level [5][6][7], capability to operate with high speed and frequency for generating pulse-width modulation (PWM ) signals [8] respectively, are the crucial issues for inverters and its controllers. Thus, for regulated inverter output voltage and current, an efficient and enhanced inverter controller is necessary to improve the inverter performance in PV or renewable energy applications.

Globally, researches in the development of inverter control algorithm are still going on to advocate the applications of renewable energy. Various types of controller and processor are being adopted for design, analysis and implementation of PWM controlled inverters. Among them are analogue circuit controllers, microcomputers, digital circuit controllers, field programmable gate arrays (FPGAs) and digital signal processors (DSP) [9][10][11][12].

According to Messenger and Ventre, the opportunities are still exist for the design engineers to improve the inverter controller, since inverter failure remains one of the primary causes for photovoltaic (PV) system failure [13]. For this reason, the enhanced inverter controllers are necessary for improving the inverter performance in PV or renewable energy applications.

Selvaraj and Rahim [11] and Saad and Rahim [12] have developed DSP TMS320F2812 and FPGA based PV inverters, employing the proportional-integral (PI) controller and PWM control algorithm, respectively. However, it requires users to develop a quite lengthy software programming or codes for the control algorithm. This might be a hassle and time consuming task, especially for those who have little experience and background dealing with the software programming. Besides, a simulation model has to be developed prior to the hardware realization as well. A different approach to this development process is by integrating the dSPACE DS1104 [14] DSP real-time data acquisition control platform into the system which enables users to employ the MATLAB/Simulink linking tools available features for the control algorithm development and simulation and hardware implementation as well. The dSPACE DS1104 control platform simplifies the control algorithm programming task by means of its library blocksets. Moreover, the data and codes of the successfully simulated model can be linked and loaded directly to the controller for real time hardware operation.

Salam et al. [15] have implemented the dSPACE DS1104 controller board in the design of high frequency link inverter. Another different way to control and regulate the ac output current and voltage is by implementing the fuzzy logic controller (FLC). Hannan et al. [16] and Ghani [17] employed the dSPACE DS1104 controller in a PV standalone prototype inverter development. Another application of the dSPACE DS1104 platform is in the grid-connected inverter. By using the graphical object-oriented package, a dSPACE system has enables the development of user-friendly inverter control panels for on line monitoring and supervision [18]. A dSPACE system is quite popular in controlling platform and is widely used in automation systems and car manufacturing industries [19]. Controlling power converters such as an inverter is one of the alternatives of the dSPACE system application.

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In this paper, the control system and the modeling for the inverter hardware are developed which are then simulated in MATLAB/Simulink. The main element of the inverter output parameters controlling is the switching signals generation, e.g. sinusoidal pulse-width modulation (SPWM) that responsible for the output voltage and current control regulation scheme. The control system architecture employs the fuzzy logic controller (FLC) which shows better performance in reducing overshoot parameter in the performance of the inverter compared to PI controller. A detail explanation of the control strategy of for the inverter has been discussed. FLC has the advantage of controlling a nonlinear system such as the PV inverter system and there is no special design procedure involved in fuzzy control such as root-locus design, frequency response design, pole placement design, or stability margins, because the rules are often nonlinear [20].

SIMULATION MODEL

In order to validate the effectiveness of the proposed inverter control system, a simulation was conducted in the MATLAB/Simulink with SimPowerSystem blockset. It was simulated for a period of 0.16 seconds with a sampling period of 5 µs. The detail inverter system simulation model is shown in Fig. 1.

Fig.1. Inverter system simulation model

In this simulation, the PV simulator has the capacity of 5.8kW. To simplify the analysis, the simulation is executed at a fixed irradiation of 1000 watt/m2 and at a temperature of 25º Celsius so that the PV simulator output power is at a constant peak. With the built in dc-dc boost converter and the maximum power point tracking (MPPT) feature to extract as much power as possible from the PV, the PV simulator is able to generate the output voltage of 700Vdc as required by the inverter input. To visualize the control system function, this simulation was done with the following resistive load profile which consists of: (i) 100% load – full-load scenario (5.8kW), a balance

between generation and absorption. (ii) 50% load – under-load scenario (3.0kW), the

generation is higher than absorption.

(iii) 150% load – overload scenario (8.8kW), the generation is less than absorption.

(iv) Grid voltage and frequency disturbance – over and under disturbances

By applying different loads, the dynamic of the system power balance (generation and absorption) and the power flow can be observed whether the inverter dispatches excess power to the grid or drawn power from the grid.

The main objective of the control system is to regulate a nearly sinusoidal inverter output current and inject it to the utility at unity power factor with an acceptable level of total harmonic distortion (THD). According to the standard code, IEEE Std. 929-2000 [21], the THD level must be below 5% for connecting to the utility grid. The system is also managed to protect the system under disturbances such as changes occur in the grid/utility voltage parameters such as frequency and voltage level managing.

INVERTER CONTROL STRATEGY

The configuration of the PV grid-connected inverter control system is illustrated in Fig. 2. It consists of a PV simulator with a MPPT feature, an inverter that is connected to the load and grid, and the control system. The connection to the grid is made possible by a three-phase controllable breaker or switch.

Fig.2. Block diagram of the grid-connected inverter system configuration.

The control system manages the data acquisition of the

relevant variable system parameters and signals such as voltages, currents and control signals in order to maintain the system operation and stabilize the output voltage. Fig. 3 shows the block diagram structure for the control system components. The system reads the grid voltage and frequency (50 Hz) for the grid synchronization which is accomplished by the phase lock loop (PLL) function block. The PLL gives outputs in terms of sinωt and cosωt which are used as the reference frequency in the calculation of the abc/dq transformation of the inverter current in the current control loop.

By using the Park’s transformation method, the sampled signals of the inverter current are transformed from a three axes abc frame into a dq reference frame system. The dq currents are compared with the reference current which is

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generated from the voltage control loop so as to generate the error signals which are fed to the fuzzy logic controller for the output current regulation.

Fig. 3: Grid-connected inverter control strategy

In the voltage control loop, the dc input voltage, Vdc is regulated by the fuzzy logic controller which generates the current reference, Idref to be tracked on by the controller in the previous current control loop. The output signals from the current control loop are fed to the conversion and PWM generator block which uses a triangular wave of 15 kHz for generating the switching signals for the IGBTs.

By utilizing the ‘Real-Time Workshop’ (RTW) feature available in MATLAB/Simulink environment, the inverter control system algorithm is converted to the C-codes and simultaneously linked to the real inverter hardware. This is one of the advantages of the dSPACE DS1104 which makes it suitable for research and development purposes. In order to link the algorithm to the real inverter hardware, the dSPACE input-output (I/O) library blocks are added to the MATLAB/Simulink inverter model. They are analog-to-digital converter (ADC) units, DS1104ADC, bit input-output (I/O) unit, DS1104BIT_OUT, and 3-phase PWM generation unit, DS1104SL_DSP_PWM3. With the aid of the dSPACE graphical user interface (GUI) software, ControlDesk, the control and monitoring of the real-time hardware parameters is made possible.

RESULT AND DISCUSSION

Fig. 4 and Fig. 5 show the snapshots of the three-phase output voltage and current waveforms of the inverter in per unit (p.u) format respectively.

Fig. 4. Inverter output voltage waveform, vabc

Fig. 5 Inverter output current waveform, iabc

From Fig. 4, the 50 Hz sinusoidal waveforms, va (blue), vb (red) and vc (green) have peak voltages of 1.0 p.u which is equivalent to phase voltage of 240Vrms or line voltage of 415Vrms. As can be seen, they are displaced by 120º of each other. Initially, it started in standalone mode as a voltage controlled inverter, and then connected to grid at t = 0.03 second with current controlled strategy. It is shown by the small ripples in the current waveforms after 0.03 second as shown in Fig. 5.

The total harmonic distortion (THD) for the phase voltage waveform is 2.48% as shown in Fig. 6, which is below 5% of IEEE standard.

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Fig. 6. THD and harmonics spectrum of inverter output waveform, va

The system power flow is shown in Fig. 7. For the period of t = 0 second to t = 0.03 second, since the PV power generation is equal to the load demand and the system is in a standalone mode, there is no power drawn from or dispatched to the grid.

From the figure, it can be seen that the load drawn additional 3kW required power from the grid for the period between t = 0.05 second and t = 0.1 second. It is shown by the amount of -3kW section on the grid contribution profile (in purple) in the figure. This is a condition of 150% load condition where the PV power generation is 5.8kW (in blue) but the load demand (in red) is 8.8kW which is higher than the generation. Hence, the additional required power is drawn from the grid.

Another scenario can be seen from the figure is between the period of t = 0.1 second to 0.16 second, where the load (in red) is 3kW and the PV generation is 5.8kW (in blue). There is an excess power of 2.8kW generated by the PV and it is dispatched to the grid. This is shown in the grid contribution curve (in purple).

Fig.7. Power flow, Pload, PPV and Pgrid showing power drain from grid and

dispatch to the grid

CONCLUSION

The simulation modeling and control system algorithm for the hardware development of photovoltaic three-phase voltage source inverter has been presented. It has been verified with the simulation results in MATLAB/Simulink for the inverter output voltage stabilization and system power flow with different load profiles, which suggested the effectiveness of the inverter control strategy. These results serve as a justification for the inverter prototype development.

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International Journal of Photoenergy, vol. 2010, doi:10.1155/2010/457562, pp 1-10, 2010.

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