Adaptive Reactive Power Control Using Static VAR Compensator (FC-TCR & TCR)


  Flexible AC transmission system (FACTS) is a technology, which is based on power electronic devices, used to enhance the existing transmission capabilities in order to make the transmission system flexible and independent operation. The FACTS technology is a promising technology to achieve complete deregulation of Power System i.e. Generation, Transmission and Distribution as complete individual units. The loading capability of transmission system can also be enhanced nearer to the thermal limits without affecting the stability.


Complete close-loop smooth control of reactive power can be achieved using shunt connected FACTS devices. Static VAR Compensator (SVC) is one of the shunt connected FACTS device, which can be utilized for the purpose of reactive power compensation.. This paper attempts to design and simulate the Fuzzy logic control of firing angle for SVC (TCR & FC-TCR) in order to achieve better, smooth and adaptive control of reactive power. The design, modeling and simulations are carried out for λ /8 Transmission line and the compensation is placed at the receiving end (load end). The results of both SVC (TCR & FC-TCR) devices


  1. Fuzzy Logic
  2. FACTS and SVC



Fig.1. Single Phase equivalent circuit and fuzzy logic control structure of SVC



Fig.2. Uncompensated voltages for R=500 Ω

Fig.3. Compensated voltages for R=500 Ω with TCR

Fig.4. Compensated voltages for R=500 Ω with FC-TCR

Fig.5. Active and Reactive powers of the Tr.line R=200 Ω after compensation with FC-TCR

Fig.6. Active and Reactive powers of the Tr.line for R=200 Ω after compensation with TCR


This paper presents an “online Fuzzy control scheme for SVC” and it can be concluded that the use of fuzzy controlled SVC (TCR & FC-TCR) compensating devices with the firing angle control is continuous, effective and it is a simplest way of controlling the reactive power of transmission line. It is observed that SVC devices were able to compensate over voltages. Compensating voltages are shown in Fig.15 and Fig.16.


The use of fuzzy logic has facilitated the closed loop control of system, by designing a set of rules, which decides the firing angle given to SVC to attain the required voltage. The active and reactive power compensation with SVC devices was shown in Fig.17 and Fig.18. With MATLAB simulations [4] [5] and actual testing it is observed that SVC (TCR & FC-TCR) provides an effective reactive power control irrespective of load variations.


 [1] Narain. G. Hingorani, “Understanding FACTS, Concepts and Technology Of flexible AC Transmission Systems”, by IEEE Press


[2] Bart Kosko, “Neural Networks and Fuzzy Systems A Dynamical Systems Approach to Machine Intelligence”, Prentice-Hall of India New Delhi, June 1994.

[3] Timothy J Ross, “Fuzzy Logic with Engineering Applications”, McGraw-Hill, Inc, New York, 1997.

[4] Laboratory Manual for Transmission line and fuzzy Trainer Kit Of Electrical Engineering Department NIT Warangal

[5] SIM Power System User Guide Version 4 MATLAB Manual Periodicals and Conference Proceedings:

A Fuzzy Logic Control Method for MPPT of PV Systems


Maximum power point trackers are so important in photovoltaic systems to increase their efficiency. Many methods have been proposed to achieve the maximum power that the PV modules are capable of producing under different weather conditions. This paper proposed an intelligent method for maximum power point tracking based on fuzzy logic controller. The system consists of a photovoltaic solar module connected to a DC-DC Buck-boost converter. The system has been experienced under disturbance in the photovoltaic temperature and irradiation level. The simulation results show that the proposed maximum power tracker could track the maximum power accurately and successfully in all condition tested. Comparison of different performance parameters such as: tracking efficiency and response time of the system shows that the proposed method gives higher efficiency and better performance than the conventional perturbation and observation method.



Fig. 1. Block diagram of the stand-alone PV system


Fig. 2: case 1: changing the solar radiation

Fig. 3: Case 1: performance of FLC method


Fig. 4: Case I: performance of P&O method

Fig, 5: Case 2: changing the solar radiation

Fig, 6: Case 2: performance of FLC method

Fig, 7: Case 2: performance of P&O method

Fig, 8: Changing the temperature

Fig, 9: Performance of FLC method

Fig, 10: Performance of P&O method


 Photovoltaic model using Matlab/STMULTNK and design of appropriate DC-DC buck-boost converter with a maximum power point tracking facility are presented in this paper. A new method for MPPT based fuzzy logic controller is presented and compared with the conventional P&O MPPT method. The models are tested under disturbance in both solar radiation and photovoltaic temperature. Simulation results show that the proposed method effectively tracks the maximum power point under different ambient conditions. The oscillation around MPP is decreased and the response is faster in compared with the conventional methods. Comparing the tracking efficiency of both methods indicates that the proposed method has a higher efficiency than the conventional P&O MPPT method.


[1] Jancarle L. Dos Santos, Fernando L. M. Antunes and Anis Chehab, “A Maximum Power Point Tracker for PV Systems Using a High Performance Boost Converter”, Solar Energy, Issue 7, Vol. 80, pp. 772- 778,2005.

[2] Ting-Chung Yu and Tang-Shiuan Chien, “Analysis and Simulation of Characteristics and Maximum Power Point Tracking for Photovoltaic Systems”, Conference,P prpo.c 1e3ed3i9n g- s1 3o4f4 ,PT aoiwpeeri, 2E0l0e9c.t ronics and Drive Systems

[3] Roberto Faranda, Sonia Leva, “Energy Comparison of MPPT techniques for PV Systems”, Wseas Transctions on Power System, Issue 6, Vol. 3, pp. 446-455, June 2008.

[4] D. P. Hohm and M. E. Ropp, “Comparative Study of Maximum Power Point Tracking Algorithms using an experimental, programmable, maximum power point tracking test bed”,P roceedings of Photovoltaic Specialists Conference ,pp. 1699 – 1702, USA,2000.

[5] Trishan Esram and Patrick 1. Chapman, “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques”, Energy ConverSion, Issue 2, Vol. 22, pp. 439 – 449, May 2007.

Design of Fuzzy Logic Based Maximum Power Point Tracking Controller for Solar Array for Cloudy Weather Conditions



This paper proposes Maximum Power Point Tracking (MPPT) of a photovoltaic system under variable temperature and solar radiation conditions using Fuzzy Logic Algorithm. The cost of electricity from the PV array is more expensive than the electricity from the other non-renewable sources. So, it is necessary to operate the PV system at maximum efficiency by tracking its maximum power point at any weather conditions 111. Boost converter increases output voltage of the solar panel and converter output voltage depends upon the duty cycle of the MOSFET present in the boost converter. The change in the duty cycle is done by Fuzzy logic controller by sensing the power output of the solar panel. The proposed controller is aimed at adjusting the duty cycle of the DC-DC converter switch to track the maximum power of a solar cell array. MATLABI Simulink is used to develop and design the PV array system equipped with the proposed MPPT controller using fuzzy logic 12][31. The results show that the proposed controller is able to track the MPP in a shorter time with less fluctuation. The complete hardware setup with fuzzy logic controller is implemented and the results are observed and compared with the system without MPPT (Fuzzy logic controller).


  1. MPPT
  2. Fuzzy Logic Control
  3. DC-DC Converter,
  4. Photo voltaic systems.



Fig. 1. Block diagram of MPPT of PV array.


 Fig. 2. Power Vs output voltage

Fig. 3. Voltage Vs Current output of solar panel

Fig. 4. Output voltage of the solar panel without MPPT.

Fig. 5. Output of the solar panel with MPPT FLC under cloudy weather conditions.

Fig. 6. PWM output when driven by FLC


This paper presents an intelligent control method of tracking maximum power and Simulation and hardware result show that proposed MPPT controller increases the efficiency of the PV array energy conversion efficiency. Results are compared with the panel without MPPT controller.


[1] Chetan Singh Solanki,” Solar Photo Voltaics “, PHI Learning pvt. Ltd ,2009.

[2] Bor-Ren Lin,”Analysis of Fuzzy Control Method Applied to DCDC Converter controf’ , IEEE Prowe .h g APK’93, pp. 22- 28,1993.

[3] Rohin M.Hillooda, Adel M.Shard,”A rule Based Fuzzy Logic controller for a PWM inverter in Photo Voltaic Energy Conversion Scheme”, IAS’SZ, PP.762-769, 1993.

[4] Pongsakor Takum, Somyot Kaitwanidvilai and Chaiyan Jettasen ; ‘Maximum POlVer Point Tracking using jilzzy logic control for photovoltaic systems.’ Proceedings Of International Multiconference of Engineers and Computer scientists ,Vol 2,March 2011.

[5] M.S.Cheik , Larbes, G.F Kebir and A ZerguelTas; ‘Maximum power point tracking using a jilzzy logic control scheme.’; ‘Departementd’Electronique’, Revue des Energies Renouvelables, VoI.lO,No 32 , September 2007, pp 387-395