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Ijetae Ncmira 0113 01

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    International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459 (Online), An ISO 9001:2008 Certified Journal, Volume 3, Special Issue 2, January 2013) National conference on Machine Intelligence Research and Advancement (NCMIRA, 12), INDIA.    Shri Mata Vaishno Devi University (SMVDU), Kakryal, Katra, INDIA.  Page 1 A Novel Hysteresis Technique for Improvement of Power System Dynamic Stability by Using Battery Energy Storage System (BESS) With Fuzzy Logic Controller Arshad. Mohammed 1 , Upender Reddy 2 , J. Jawaharlal 3 , G.Trinath 4   1 Sr.Assistant Professor, 2 Sr.Assistant Professor, 3  Associate Professor, 4  B-Tech Student,    Aurora Technological and Research  Institute, Uppal, Hyderabad  Abstract A novel Hysteresis Technique in Fuzzy Logic Controller (FLC) is designed for a Battery Energy Storage System (BESS) to improve the stability of an interconnected multi-machine Power system. The studied system consists of two generating areas interconnected by a long transmission line. Detailed model of BESS is developed for accurate dynamic assessment. The model takes into account the switching actions of the converter as well as the battery characteristics. And also describes the use of hysteresis technique to control directly the BESS output current. This reduces the complexity of the control system while at the same time provides a tight control of the BESS output. Test results under a variety of disturbances show the proposed BESS is effective in damping out power system oscillations. Index Terms  —   Battery Energy Storage System (BESS), Power System Stability, Fuzzy Logic controller. I.   I  NTRODUCTION  When power system disturbances occur, synchronous generators are not always able to respond rapidly enough to keep the system stable. If high-speed real or reactive power control is available, load shedding or generator dropping may be avoided during the disturbance. High speed reactive power control is possible through the use of flexible ac transmission systems (FACTS) devices. In a few cases, these devices are also able to provide some measure of high speed real power control through power circulation within the converter, with the real power coming from the same line or in some cases from adjacent lines leaving the same substation. However, a better solution would be to have the ability to rapidly vary real power without impacting the system through power circulation. This is where energy storage technology can play a very important role in maintaining system reliability and  power quality. The ideal solution is to have means to rapidly damp oscillations, respond to sudden changes in load, supply load during transmission or distribution interruptions, correct load voltage  profiles with rapid reactive power control, and still allow the generators to  balance with the system load at their normal speed. Custom power devices use power converters to  perform either current interruption or voltage regulation functions for  power distribution systems. Recent developments and advances in energy storage and power electronics technologies are making the application of energy storage technologies a viable solution for modern power applications. Viable storage technologies include batteries, flywheels, ultra capacitors, and superconducting energy storage systems. Although several of these technologies were initially envisioned for Large -scale load-leveling applications, Battery energy storage is now seen more as a tool to enhance system stability, aid power transfer, and improve power quality in  power systems. Some model-based approaches have  been proposed for energy storage to enhance power system damping. The results showed that such model- based control strategies are very effective in solving a well-defined system Nevertheless, today ‟ s modem interconnected power system is highly complex and non-linear in nature making it very difficult to accurately model the power system without sacrificing considerable amount of computation time. Recently, artificial intelligence techniques have been reported in the literature that apparently can deal with non- linear and complex systems by introducing fuzziness in the analysis.    International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459 (Online), An ISO 9001:2008 Certified Journal, Volume 3, Special Issue 2, January 2013) National conference on Machine Intelligence Research and Advancement (NCMIRA, 12), INDIA.    Shri Mata Vaishno Devi University (SMVDU), Kakryal, Katra, INDIA.  Page 2 Several applications of the fuzzy logic control (FLC) in  power system stabilizers have been reported and shown to be effective through simulation and experimental verifications. In this paper, an effective and easy-to-understand Fuzzy Logic based algorithm is employed to control the BESS to improve power system stability. With the proposed FLC control scheme, the active and reactive power outputs of the BESS can be rapidly controlled. FLC is model-free in nature, requires less development time and can handle highly complicated and non-linear systems, etc. With these virtues and assets, FLC has been regarded as one of the most suitable substitution for the conventional control techniques. This paper also reports on the use of a new control strategy based on hysteresis technique to control the AC/DC converter of the BESS. This has the advantage of reducing the complexity of the converter control. The detailed BESS model and its controller proposed in this  paper are suitable not only for dynamic but also transient study of the performance of the BESS. II.   B ATTERY E  NERGY S TORAGE S YSTEM (BESS) The schematic diagram of the BESS is shown in Fig. 1.   Fig. 1 Schematic Diagram of BESS Plant The main components of BESS are Battery bank, Power. Switching module associated with AC/DC converter Control system, Transformer & AC supply. The  battery bank consists of a set of battery cells connected in  parallel and series. The batteries of the BESS is rated at 10 MW, 40 MWh. Ultra capacitors (0.5F) are placed in  parallel with the battery bank to stabilize the terminal voltage. To reflect the charging and discharging characteristics of the battery cells, a comprehensive non-linear model has been used Due to the non-linear nature of the internal resistance of the battery cells, different curves are used for charging and discharging depending on the state of charge. The equivalent circuit of a battery cell is shown in Fig 2. Fig. 2 Battery equivalent circuit The AC/DC converter, rated at 20 MVA, such that the BESS can provide up to 10 MW, 17.3 MVAr, is used to interface between the AC power system and DC  battery.The schematic diagram of the converter is shown in Fig. 3 . Fig. 3 Schematic diagram of AC/DC converter  In the control circuit, the angular speed of the generator and the BESS ac terminal voltages are omega and Vabc_2 respectively. Omega* represent the angular speed after the measurement devices. Omega* is then compared with angular speed reference, to obtain the angular speed deviation. Based on this deviation, the controllers determine the needs to be supplied by the BESS.    International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459 (Online), An ISO 9001:2008 Certified Journal, Volume 3, Special Issue 2, January 2013) National conference on Machine Intelligence Research and Advancement (NCMIRA, 12), INDIA.    Shri Mata Vaishno Devi University (SMVDU), Kakryal, Katra, INDIA.  Page 3 With reference to Pbes, Qbes and Vt* the thetaref,  phase angle, and Ipeak_ref, peak value, of BESS phase current target can be determined. At the same time, freq, the frequency of the BESS terminal voltage, is also acquired from the system. Based on, Ipeakref and freq, the reference phase currents of the BESS can be generated as follows for use in the hysteresis control. The embedded MATLAB function allows to you add matlab functions to simulink models for development of embedded processors. This capability is useful for coding algorithms. The phase locked loop system can be used to synchronize on variable frequency sinusoidal signal. The saturation block imposes upper and lower bounds on a signal. When input signal is within a range specified by lower limit and upper limit parameter, the input signal  passes through unchanged. When input signal is outside of these bounds, the signal is clipped to upper or lower bound. Fig. 4 Control circuit    International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459 (Online), An ISO 9001:2008 Certified Journal, Volume 3, Special Issue 2, January 2013) National conference on Machine Intelligence Research and Advancement (NCMIRA, 12), INDIA.    Shri Mata Vaishno Devi University (SMVDU), Kakryal, Katra, INDIA.  Page 4 Fig.4.1 Control Circuit Block Diagram   In hysteresis control, the controlled variable, as shown in Fig. 5 is only allowed to oscillate within a defined upper and lower hysteresis band limits around the reference waveform. The switching function is generated from the intersection of the triangular wave with the hysteresis band limits. The conduction of a switch is transferred from one to the other in a phase, when the triangular wave meets the hysteresis limits so as to control the actual current not to go  beyond the hysteresis band. Similar switching actions occur in the other two phases. In such a control scheme, the switching frequency is not fixed and depends on how fast the current changes from the upper limit to the lower limit and vice versa. It depends on the phase inductance, the voltage difference between the step down bus voltage and battery bank terminal voltage, the system frequency and the width of the hysteresis band. Fig 5: Hysteresis Control The block diagram of the hysteresis control loop is shown in Fig. 6 the relay block allows its output to switch  between two specified values. When the relay is on, it remains on until the input drops below the value of switch off point parameter. When the relay is off, it remains off until the input exceed the value of switch on point  parameter. Fig. 6 Hysteresis Control Loop III.   F UZZY L OGIC C ONTROLLER   In this study, the generator speed deviation, ∆ẃ , and the acceleration deviation, ∆ w, are chosen as the FLC inputs. Each input and output fuzzy variables of FLC is mapped into seven linguistic fuzzy sets varying from Negative Big (NB) to Positive Big (PB).
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