Power Flow Control of Power Systems Using UPFC Based on Adaptive Neuro Fuzzy

Optimization of system capacity electric power transmission systems requires a reliable power flow controller. The power flow controllers must be able to control the level of electrical voltage and active and reactive power flow without reducing the level of stability and security of the transmission system. Latest technology in the control of power flow is a Unified Power Flow Controller (UPFC). The entire transmission line parameters are impedance, voltage, and phase angle can be controlled simultaneously by the UPFC. The method used in the conventional algorithms based UPFC is still firmly with logic. These algorithms have difficulties to electric power transmission systems multimachine very dynamic, i.e. systems that are experiencing rapid changes in the electrical load from time to time. Therefore, in this study was developed based on neuro-fuzzy method is applied to the adaptive UPFC for adaptively controlling the power flow in electric power transmission systems multimachine very dynamic. In this study, three phase fault is applied to the multimachine system. The results are taken to be consideration of PI and neuro-fuzzy controllers. The PI and neuro-fuzzy controllers show nearly same results but there is a low overshoot occurred during the fault in the neuro-fuzzy controllers results. According to results that UPFC improves the system performance under the transient and the normal conditions. However, it can control the power flow in the transmission line, effectively

Fuzzy System Identification Based Upon a Novel Approach to Nonlinear Optimization

Fuzzy systems are often used to model the behavior of nonlinear dynamical systems in process control industries because the model is linguistic in nature, uses a natural-language rule set, and because they can be included in control laws that meet the design goals. However, because the rigorous study of fuzzy logic is relatively recent, there is a shortage of well-defined and understood mechanisms for the design of a fuzzy system. One of the greatest challenges in fuzzy modeling is to determine a suitable structure, parameters, and rules that minimize an appropriately chosen error between the fuzzy system, a mathematical model, and the target system. Numerous methods for establishing a suitable fuzzy system have been proposed, however, none are able to demonstrate the existence of a structure, parameters, or rule base that will minimize the error between the fuzzy and the target system. The piecewise linear approximator (PLA) is a mathematical construct that can be used to approximate an input-output data set with a series of connected line segments. The number of segments in the PLA is generally selected by the designer to meet a given error criteria. Increasing the number of segments will generally improve the approximation. If the location of the breakpoints between segments is known, it is a straightforward process to select the PLA parameters to minimize the error. However, if the location of the breakpoints is not known, a mechanism is required to determine their locations. While algorithms exist that will determine the location of the breakpoints, they do not minimize the error between data and the model. This work will develop theory that shows that an optimal solution to this nonlinear optimization problem exists and demonstrates how it can be applied to fuzzy modeling. This work also demonstrates that a fuzzy system restricted to a particular class of input membership functions, output membership functions, conjunction operator, and defuzzification technique is equivalent to a piecewise linear approximator (PLA). Furthermore, this work develops a new nonlinear optimization technique that minimizes the error between a PLA and an arbitrary one-dimensional set of input-output data and solves the optimal breakpoint problem. This nonlinear optimization technique minimizes the approximation error of several classes of nonlinear functions leading up to the generalized PLA. While direct application of this technique is computationally intensive, several paths are available for investigation that may ease this limitation. An algorithm is developed based on this optimization theory that is significantly more computationally tractable. Several potential applications of this work are discussed including the ability to model the nonlinear portions of Hammerstein and Wiener systems

Dynamic Stability Studies Of Generators In Power System Using Fuzzy Logic Controller Based Power System Stabilizer

Excitation systems are affected by low frequency oscillation (LFO)when they are subjected to small perturbations.Damping during the LFOis enhanced via the addition of power system stabilizer (PSS) to the excitation system.This research entails a study on fuzzy logic controller power system stabilizer (FLCPSS) for the purpose of enhancing the stability of a single machine power system.In order to accomplish the stability enhancement,two approaches were used to design fuzzy logic controller (FLC).The first approach includes the use ofgenetic algorithm (GA) to design the PSS.The second approach entails the use of particle swarm optimization (PSO) to design the PSS.The performance of these two approaches is compared with the systemand without PSS.The stabilizing signals were computed using the fuzzy membership functions depending on these variables.The simulations were tested under different operating conditions and also tested with different membership functions.The simulation is implemented using Matlab /Simulink and the results have been found to be quite good and satisfactory.Electro-mechanical oscillations were created in the event of trouble or when there was high power transfer through weak tie-line in the machines of an interrelated power network.This research presents an analysis on the change of speed (Δω), change of angle position (Δδ) and tie-line power flow (Δp).FLC which includes two areas of symmetrical systems are connected via tie-line to identify the performance of the controllers.Simulation results of the fuzzy logic based controller indicate dual inputs of rotor speed deviation and generator’s accelerating power.Two generators have been used to control the arrangement in the tie-line system.The single fuzzy logic controller (S-FLC) has been used as a primary controller and the double fuzzy logic controller(D-FLC) has been used as a secondary controller.Additionally,the system shows a comparison between the two controllers,namely the S-FLC and D-FLC which have been used to achieve the best results.Notably, the double fuzzy controller has been found to have a greater effect on the multi-machine system and it is smoother than the single fuzzy controller as it increased the damping of the speed Δω and rotorangle (degree) Δδ. Its simplicity has made it to be a good controller.In conclusion,much better response can be attained from the S-FLC) if there is careful timing of the scaling factors

A binary particle swarm optimization approach for power system security enhancement

Improvement of power system security manages the errand of making healing move against conceivable system overloads in the framework following the events of contingencies. Generation re-dispatching is answer for the evacuation of line overloads. The issue is the minimization of different goals viz. minimization of fuel cost, minimization of line loadings and minimization of overall severity index. Binary particle swarm optimization (BPSO) method was utilized to take care of optimal power flow issue with different targets under system contingencies. The inspiration to introduce BPSO gets from the way that, in rivalry with other meta-heuristics, BPSO has demonstrated to be a champ by and large, putting a technique as a genuine alternative when one needs to take care of a complex optimization problem. The positioning is assessed utilizing fuzzy logic. Simulation Results on IEEE-14 and IEEE-30 bus systems are presented with different objectives

Nonlinear modelling and optimal control via Takagi-Sugeno fuzzy techniques: A quadrotor stabilization

Using the principles of Takagi-Sugeno fuzzy modelling allows the integration of flexible fuzzy approaches and rigorous mathematical tools of linear system theory into one common framework. The rule-based T-S fuzzy model splits a nonlinear system into several linear subsystems. Parallel Distributed Compensation (PDC) controller synthesis uses these T-S fuzzy model rules. The resulting fuzzy controller is nonlinear, based on fuzzy aggregation of state controllers of individual linear subsystems. The system is optimized by the linear quadratic control (LQC) method, its stability is analysed using the Lyapunov method. Stability conditions are guaranteed by a system of linear matrix inequalities (LMIs) formulated and solved for the closed loop system with the proposed PDC controller. The additional GA optimization procedure is introduced, and a new type of its fitness function is proposed to improve the closed-loop system performance.Web of Science71110

A fuzzy approach to building thermal systems optimization.

Optimization of building thermal systems is treated in the paper in the framework of fuzzy mathematical programming. This new approach allows to formulate more precisely the problem which compromises energy saving and thermal comfort satisfaction under given constraints. Fuzzy optimization problem is solved analytically under some assumptions. An example illustrates the viability of the approach proposed. A solution which significantly (with 38%) improves comfort is found which is more energetically expensive with only 0.6%. (c) IFS

Penguasaan kemahiran generik di kalangan graduan hospitaliti di politeknik : satu kajian berkenaan keperluan industri perhotelan, persepsi pensyarah dan pelajar

Kajian yang dijalankan ini bertujuan untuk mengenal pasti kepentingan kemahiran generik mengikut keperluan industri perhotelan di Malaysia dengan persepsi pensyarah dan persepsi pelajar Jabatan Hospitaliti. Oleh kerana matlamat kurikulum pendidikan kini adalah untuk melahirkan graduan yang dapat memenuhi keperluan pihak industri, maka kajian ini dijalankan untuk menilai hubungan di antara keperluan industri perhotelan di Malaysia dengan persepsi pensyarah dan pelajar Jabatan Hospitaliti di Politeknik. Terdapat 13 kemahiran generik yang diperolehi daripada Kementerian Pelajaran dan Latihan Ontario (1997) dijadikan sebagai skop kepada instrumen kajian. Responden kajian terdiri daripada tiga pihak utama iaitu industri perhotelan di Malaysia yang melibatkan 40 buah hotel yang diwakili oleh MAH Chapter dan jawatankuasa dalam Malaysian Associated of Hotel (MAH), pensyarah Unit Hotel dan Katering dan pelajar semester akhir Diploma Hotel dan Katering di Politeknik Johor Bahru, Johor dan Politeknik Merlimau, Melaka. Kajian rintis yang dijalankan menunjukkan nilai Alpha Cronbach pada 0.8781. Data yang diperolehi dianalisis secara deskriptif dan inferensi dengan menggunakan perisian Statistical Package for Social Science (SPSS) versi 11.5. Melalui dapatan kajian, satu senarai berkenaan kemahiran generik yang diperlukan oleh industri perhotelan telah dapat dihasilkan. Selain itu, senarai kemahiran generik menurut persepsi pensyarah dan juga persepsi pelajar turut dihasilkan. Hasil statistik dan graf garis yang diperolehi menunjukkan terdapat perbezaan di antara kemahiran generik yang diperlukan oleh industri perhotelan di Malaysia dengan kemahiran generik menurut persepsi pensyarah dan persepsi pelajar Politeknik. Dapatan analisis menggunakan korelasi Pearson mendapati bahawa tidak terdapat perhubungan yang signifikan di antara kemahiran generik yang diperlukan oleh industri perhotelan dengan persepsi pensyarah dan persepsi pelajar. Namun begitu, terdapat hubungan yang signifikan di antara persepsi pensyarah dengan persepsi pelajar berkenaan dengan amalan kemahiran generik di Politeknik