Grid-Connected PV Array with Supercapacitor Energy Storage System for Fault Ride Through

ABSTRACT:

A fault ride through, power management and control strategy for grid integrated photovoltaic (PV) system with supercapacitor energy storage system (SCESS) is presented in this paper. During normal operation the SCESS will be used to minimize the short term fluctuation as it has high power density and during fault at the grid side it will be used to store the generated power from the PV array for later use and for fault ride through. To capture the maximum available solar power, Incremental Conductance (IC) method is used for maximum power point tracking (MPPT). An independent P-Q control is implemented to transfer the generated power to the grid using a Voltage source inverter (VSI). The SCESS is connected to the system using a bi-directional buck boost converter. The system model has been developed that consists of PV module, buck converter for MPPT, buck-boost converter to connect the SCESS to the DC link. Three independent controllers are implemented for each power electronics block. The effectiveness of the proposed controller is examined on Real Time Digital Simulator (RTDS) and the results verify the superiority of the proposed approach.

KEYWORDS:

1.      Active and reactive power control

2.      Fault ride through

3.      MPPT

4.      Photovoltaic system

5.      RTDS Supercapacitor

6.      Energy storage

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1. Grid connected PV system with energy storage

 EXPECTED SIMULATION RESULTS:

Fig.2. Grid voltage after three phase fault is applied

Fig.3. PV array power P_PV with SCESS and with no energy storage

Fig.4. Grid active power P_g for a three phase fault with and without energy storage

Fig.5.SCESS power P_SC for the applied fault on the grid side

Fig.6. Grid reactive power Q_g during three phase fault

Fig.7. DC link voltage for the applied fault

Fig.8. PV array voltage V_PV during three phase fault

Fig.9. MPPT output voltage V_ref for the applied fault

CONCLUSION:

This paper presents grid connected PV system with supercapacitor energy storage system (SCESS) for fault ride through and to minimize the power fluctuation. Incremental conductance based MPPT is implemented to track the maximum power from the PV array. The generated DC power is connected to the grid using a buck converter, VSI, buck-boost converter with SCESS. The SCESS which is connected to the DC link controls the DC link voltage by charging and discharging process. A P-Q controller is implemented to transfer the DC link power to the grid. During normal operation the SCESS minimizes the fluctuation caused by change in irradiation and temperature. During a grid fault the power generated from the PV array will be stored in the SCESS. The SCESS supplies both active and reactive power to ride through the fault. RTDS based results have shown the validity of the proposed controller.

REFERENCES:

[1] T. Esram, P.L. Chapman, “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques,” IEEE Transaction on Energy Conversion, vol.22, no.2, pp.439-449, June 2007

[2] J. M. Enrique, E. Durán, M. Sidrach-de-Cardona, and J. M. Andújar,“Theoretical assessment of the maximum power point tracking efficiency of photovoltaic facilities with different converter topologies,” Sol. Energy, vol. 81, no. 1, pp. 31–38, Jan. 2007.

[3] W. Xiao, N. Ozog, and W. G. Dunford, “Topology study of photovoltaic interface for maximum power point tracking,” IEEE Trans. Ind. Electron., vol. 54, no. 3, pp. 1696–1704, Jun. 2007.

[4] J. L. Agorreta, L. Reinaldos, R. González, M. Borrega, J. Balda, and L. Marroyo, “Fuzzy switching technique applied to PWM boost converter operating in mixed conduction mode for PV systems,” IEEE Trans. Ind. Electron., vol. 56, no. 11, pp. 4363– 4373, Nov. 2009.

[5] A.Schneuwly, “Charge ahead [ultracapacitor technology and applications]”, IET Power Engineering Journal, vol.19, 34-37, 2005.

Novel Development of A Fuzzy Control Scheme with UPFC’s For Damping of Oscillations in Multi-Machine Power Systems

ABSTRACT:

This paper presents a novel development of a fuzzy logic controlled power system using UPFCs to damp the oscillations in a FACTS based integrated multi-machine power system consisting of 3 generators, 3 transformers, 9 buses, 4 loads & 2 UPFCs. Oscillations in power systems have to be taken a serious note of when the fault takes place in any part of the system, else this might lead to the instability mode & shutting down of the power system. UPFC based POD controllers can be used to suppress the oscillations upon the occurrence of a fault at the generator side or near the bus side. In order to improve the dynamic performance of the multi-machine power system, the behavior of the UPFC based POD controller should be coordinated, otherwise the power system performance might be deteriorated. In order to keep the advantages of the existing POD controller and to improve the UPFC-POD performance, a hybrid fuzzy coordination based controller can be used ahead of a UPFC based POD controller to increase the system dynamical performance & to coordinate the UPFC-POD combination. This paper depicts about this hybrid combination of a fuzzy with a UPFC & POD control strategy to damp the electro-mechanical oscillations. The amplification part of the conventional controller is modified by the fuzzy coordination controller. Simulink models are developed with & without the hybrid controller. The 3 phase to ground symmetrical fault is made to occur near the first generator for 200 ms. Simulations are performed with & without the controller. The digital simulation results show the effectiveness of the method presented in this paper.

KEYWORDS:

1.      UPFC

2.      POD

3.      Fuzzy logic

4.      Coordination

5.      Controller

6.      Oscillations

7.      Damping

8.      Stability

9.      SIMULINK

10.  State space model

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1 : A 3-machine, 9-bus interconnected power system model with 4-loads without the controllers

Fig. 2: A 3-machine, 9-bus interconnected power system model with 4-loads & 2 POD-UPFC & the fuzzy controller

EXPECTED SIMULATION RESULTS:

 Fig. 3 : Simulation result of power angle v/s time (without Fuzzy-POD-UPFC)

 Fig. 4 : Simulation result of power angle v/s time (with UPFC & fuzzy control)

Fig. 5 : Comparison of the simulation results of power angle v/s time (without UPFC & with UPFC & fuzzy control)

 CONCLUSION:

AFACTS based multi-machine power system comprising of 3 generators, 9 buses, 3 loads with and without the 2 Fuzzy-POD-UPFC controllers was considered in this paper. SIMULINK models were developed in MATLAB 7 with & without the Fuzzy- POD-UPFC controllers for the considered multi machine model in order to damp out the oscillations. The control strategy was also developed by writing a set of fuzzy rules. The fuzzy control strategy was designed based on the conventional POD-UPFC controller & put before the POD-UPFC in the modeling.

            The main advantage of putting the fuzzy coordination controller before the POD-UPFC in modeling is the amplification part of the conventional controller being modified by the fuzzy coordination unit, thus increasing the power system stability. Simulations were run in Matlab 7 & the results were observed on the scope. Graphs of power angle vs. time were observed with and without the controller. From the simulation results, it was observed that without the Fuzzy-POD-UPFC controller, the nine bus system will be having more disturbances, while we check the power angle on the first generator.

            There are lot of ringing oscillations (overshoots / undershoots) & the output takes a lot of time to stabilize, which can be observed from the simulation results. But, from the incorporation of the Fuzzy- POD-UPFC coordination system in loop with the plant gave better results there by reducing the disturbances in the power angle and also the post fault settling time also got reduced a lot. The system stabilizes quickly, thus damping the local mode oscillations and reducing the settling time immediately after the occurrence of the fault.

            The developed control strategy is not only simple, reliable, and may be easy to implement in real time applications. The performance of the developed method in this paper thus demonstrates the damping of the power system oscillations using the effectiveness of Fuzzy-POD-UPFC coordination concepts over the damping of power system oscillations without the Fuzzy-POD-UPFC coordination scheme.

REFERENCES:

[1]. L. Gyugi, “Unified Power flow concept for flexible AC transmission systems”, IEE Proc., Vol. 139, No. 4, pp. 323–332, 1992.

[2]. M. Noroozian, L. Angquist, M. Ghandari, and G. Anderson, “Use of UPFC for optimal power flow control”, IEEE Trans. on Power Systems, Vol. 12, No. 4, pp. 1629–1634, 1997.

[3]. Nabavi-Niaki and M.R. Iravani, “Steady-state and dynamic models of unified power flow controller (UPFC) for power system studies”, IEEE’96 Winter Meeting, Paper 96, 1996.

[4]. C.D. Schauder, D.M. Hamai, and A. Edris. “Operation of the Unified Power Flow Controller (UPFC) under Practical constraints”, IEEE Trans. On Power Delivery, Vol. 13, No. 2. pp. 630~639, Apr. 1998.

[5]. Gyugyi, L., “Unified power flow controller concept for flexible AC transmission systems”, IEE Proc. Gener. Transm. Distrib., No.139, pp. 323-331, 1992

A Control Technique for Integration of DG Units to the Electrical Networks

ABSTRACT:

This paper deals with a multi objective control technique for integration of distributed generation (DG) resources to the electrical power network. The proposed strategy provides compensation for active, reactive, and harmonic load current components during connection of DG link to the grid. The dynamic model of the proposed system is first elaborated in the stationary reference frame and then transformed into the synchronous orthogonal reference frame. The transformed variables are used in control of the voltage source converter as the heart of the interfacing system between DG resources and utility grid. By setting an appropriate compensation current references from the sensed load currents in control circuit loop of DG, the active, reactive, and harmonic load current components will be compensated with fast dynamic response, thereby achieving sinusoidal grid currents in phase with load voltages, while required power of the load is more than the maximum injected power of the DG to the grid. In addition, the proposed control method of this paper does not need a phase-locked loop in control circuit and has fast dynamic response in providing active and reactive power components of the grid-connected loads. The effectiveness of the proposed control technique in DG application is demonstrated with injection of maximum available power from the DG to the grid, increased power factor of the utility grid, and reduced total harmonic distortion of grid current through simulation and experimental results under steady-state and dynamic operating conditions.

KEYWORDS:

1.      Digital signal processor

2.      Distributed generation (DG)

3.      Renewable energy sources

4.      Total harmonic distortion (THD)

5.      voltage source converter (VSC)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. General schematic diagram of the proposed control strategy for DG system.

EXPECTED SIMULATION RESULTS:

Fig. 2. Load voltage, load, grid, and DG currents before and after connection

of DG and before and after connection and disconnection of additional load into

the grid.

Fig. 3. Grid, load, DG currents, and load voltage (a) before and after connection

of additional load and (b) before and after disconnection of additional

load.

Fig. 4. Phase-to-neutral voltage and grid current for phase (a).

Fig. 5. Reference currents track the load current (a) after interconnection of

DG resources and (b) after additional load increment.

Fig. 6. Load voltage, load, grid, and DG currents during connection of DG

link to the unbalanced grid voltage.

CONCLUSION:

A multi objective control algorithm for the grid-connected converter-based DG interface has been proposed and presented in this paper. Flexibility of the proposed DG in both steady-state and transient operations has been verified through simulation and experimental results.

Due to sensitivity of phase-locked loop to noises and distortion, its elimination can bring benefits for robust control against distortions in DG applications. Also, the problems due to synchronization between DG and grid do not exist, and DG link can be connected to the power grid without any current overshoot. One other advantage of proposed control method is its fast dynamic response in tracking reactive power variations; the control loops of active and reactive power are considered independent. By the use of the proposed control method, DG system is introduced as a new alternative for distributed static compensator in distribution network. The results illustrate that, in all conditions, the load voltage and source current are in phase and so, by improvement of power factor at PCC, DG systems can act as power factor corrector devices. The results indicate that proposed DG system can provide required harmonic load currents in all situations. Thus, by reducing THD of source current, it can act as an active filter. The proposed control technique can be used for different types of DG resources as power quality improvement devices in a customer power distribution network.

REFERENCES:

[1] T. Zhou and B. François, “Energy management and power control of a hybrid active wind generator for distributed power generation and grid integration,” IEEE Trans. Ind. Electron., vol. 58, no. 1, pp. 95–104, Jan. 2011.

[2] M. Singh, V. Khadkikar, A. Chandra, and R. K. Varma, “Grid interconnection of renewable energy sources at the distribution level with power quality improvement features,” IEEE Trans. Power Del., vol. 26, no. 1, pp. 307–315, Jan. 2011.

[3] M. F. Akorede, H. Hizam, and E. Pouresmaeil, “Distributed energy resources and benefits to the environment,” Renewable Sustainable Energy Rev., vol. 14, no. 2, pp. 724–734, Feb. 2010.

[4] C. Mozina, “Impact of green power distributed generation,” IEEE Ind. Appl. Mag., vol. 16, no. 4, pp. 55–62, Jun. 2010.

[5] B. Ramachandran, S. K. Srivastava, C. S. Edrington, and D. A. Cartes, “An intelligent auction scheme for smart grid market using a hybrid immune algorithm,” IEEE Trans. Ind. Electron., vol. 58, no. 10, pp. 4603–4611, Oct. 2011.

Fuzzy Controller for Three Phases Induction Motor Drives

ABSTRACT:

Because of the low maintenance and robustness induction motors have many applications in the industries. Most of these applications need fast and smart speed control system. This paper introduces a smart speed control system for induction motor using fuzzy logic controller. Induction motor is modeled in synchronous reference frame in terms of dq form. The speed control of induction motor is the main issue achieves maximum torque and efficiency. Two speed control techniques, Scalar Control and Indirect Field Oriented Control are used to compare the performance of the control system with fuzzy logic controller. Indirect field oriented control technique with fuzzy logic controller provides better speed control of induction motor especially with high dynamic disturbances. The model is carried out using Matlab/Simulink computer package. The simulation results show the superiority of the fuzzy logic controller in controlling three-phase induction motor with indirect field oriented control technique.

KEYWORDS:

1.      Vector control

2.      Fuzzy logic

3.      Induction motor drive

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. Block diagram of scalar controller for IM.

Fig. 2. Indirect Field Oriented Control of IM.

EXPECTED SIMULATION RESULTS:

Fig. 3. Speed response of scalar and vector control

Fig 4. Torque response of scalar and vector control.

 Fig. 5. Flux response of scalar control.

Fig. 6. Flux response of vector control.

CONCLUSION:

Fuzzy logic controller shows fast control response with three-phase induction motor. Two different control techniques are used with Fuzzy logic controllers which are scalar and field oriented control techniques. Fuzzy logic controller system shows better response with these two techniques. Meanwhile, the scalar controller has a sluggish response than FOC because of the inherent coupling effect in field and torque components. However, the developed fuzzy logic control with FOC shows fast response, smooth performance, and high dynamic response with speed changing and transient conditions.

REFERENCES:

[1] A. Mechernene, M. Zerikat and M. Hachblef, “Fuzzy speed regulation for induction motor associated with field-oriented control”, IJ-STA, volume 2, pp. 804-817, 2008.

[2] Leonhard, W.,” Controlled AC drives, a successful transfer from ideas to industrial practice”, CETTI, pp: 1-12, 1995.

[3] M. Tacao, “Commandes numérique de machines asynchrones par lagique floue”, thése de PHD, Université de Lava- faculté des science et de génie Québec, 1997.

[4] Fitzgerald, A.E. et al., Electric Machinery, 5th Edn, McGraw-Hill, 1990.

[5] Marino, R., S. Peresada and P. Valigi, “Adaptive input-output linearizing control of induction motors”, IEEE Trans. Autom. Cont., 1993.