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• New algorithm particle swarm optimization with oscillatory inertia factor with exponential decay. • Simultaneous adjustment of the AVR and PSS parameters through the PSO-OED optimization technique. • Better adjustment of the AVR and PSS providing a better dynamic performance and transient system response. • New objective function capable of analyzing the performance of several generators simultaneously. This paper presents a new algorithm for simultaneous tuning of the optimal parameters of Automatic Voltage Regulator (AVR) and the Power System Stabilizer (PSS) using a new technique of Particle Swarm Optimization with Oscillating Exponential Decay (PSO-OED). The proposed algorithm was applied both the Single-Machine Infinite-Bus (SMIB) Power System and the 9-Bus Multi-Machine Power System. The results of the simulation show that the proposed method is efficient and guarantees an improvement in the dynamic stability and convergence rate of the simulations. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a Biogeography Based Optimization (BBO) technique is introduced to solve multi-constrained optimal reactive power flow (ORPF) problem in power system. ORPF is a multi-objective nonlinear optimization problem that minimizes the bus voltage deviation and real power loss. The feasibility of the proposed algorithm is demonstrated for IEEE 30-bus system and IEEE 118-bus system. A comparison of simulation results reveals optimization efficacy of the proposed scheme over other well established population based optimization techniques like conventional particle swarm optimization (PSO), general passive congregation PSO (GPAC), local passive congregation PSO (LPAC), coordinated aggregation (CA) and interior point based OPF (IP-OPF). [Copyright &y& Elsevier]

Abstract: This paper develops a novel algorithm for simultaneous coordinated designing of power system stabilizers (PSSs) and thyristor controlled series capacitor (TCSC) in a multimachine power system. The coordinated design problem of PSS and TCSC over a wide range of loading conditions is formulated as an optimization problem. The bacterial swarm optimization (BSO) algorithm is employed to search for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is improved. To compare the capability of PSS and TCSC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the bacterial swarm based coordinated controllers gives robust damping performance over wide range of operating conditions, and different disturbances in compare to optimized PSS controller based on BSO (BSOPSS) and optimized TCSC controller based on BSO (BSOTCSC). Moreover, the results are compared to the results obtained using the bacteria foraging (BF) and particle swarm optimization (PSO) to show the effectiveness of using BSO to attain a global optimal solution of the proposed coordinated design problem. [Copyright &y& Elsevier]

Abstract: In this paper, chaotic ant swarm optimization (CASO) is utilized to tune the parameters of both single-input and dual-input power system stabilizers (PSSs). This algorithm explores the chaotic and self-organization behavior of ants in the foraging process. A novel concept, like craziness, is introduced in the CASO to achieve improved performance of the algorithm. While comparing CASO with either particle swarm optimization or genetic algorithm, it is revealed that CASO is more effective than the others in finding the optimal transient performance of a PSS and automatic voltage regulator equipped single-machine-infinite-bus system. Conventional PSS (CPSS) and the three dual-input IEEE PSSs (PSS2B, PSS3B, and PSS4B) are optimally tuned to obtain the optimal transient performances. It is revealed that the transient performance of dual-input PSS is better than single-input PSS. It is, further, explored that among dual-input PSSs, PSS3B offers superior transient performance. Takagi Sugeno fuzzy logic (SFL) based approach is adopted for on-line, off-nominal operating conditions. On real time measurements of system operating conditions, SFL adaptively and very fast yields on-line, off-nominal optimal stabilizer variables. [Copyright &y& Elsevier]

Abstract: This paper presents a harmony search algorithm for optimal reactive power dispatch (ORPD) problem. Optimal reactive power dispatch is a mixed integer, nonlinear optimization problem which includes both continuous and discrete control variables. The proposed algorithm is used to find the settings of control variables such as generator voltages, tap positions of tap changing transformers and the amount of reactive compensation devices to optimize a certain object. The objects are power transmission loss, voltage stability and voltage profile which are optimized separately. In the presented method, the inequality constraints are handled by penalty coefficients. The study is implemented on IEEE 30 and 57-bus systems and the results are compared with other evolutionary programs such as simple genetic algorithm (SGA) and particle swarm optimization (PSO) which have been used in the last decade and also other algorithms that have been developed in the recent years. [Copyright &y& Elsevier]

Abstract: This paper describes an algorithm for rescheduling reactive power control variables so as to have an adequate loadability margin for current operating point. Co-ordinated aggregation based PSO (CAPSO) has been used as optimization technique. Two objective functions have been selected for load margin enhancement. One is minimization of total reactive power loss and other considers minimization of incremental reactive power loss. The developed algorithm has been implemented on 14-bus and 57-bus standard test systems. Results obtained have been compared with those obtained using Davidon–Fletcher–Powell’s (DFP) optimization technique. CAPSO performance is better over DFP method. It has been observed that incremental loss minimization formulation does not require additional voltage stability related constraints hence computational time required is less as compared to reactive power loss minimization. Reactive power loss minimization formulation is of significance when limited reactive power source is available. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a new formulation of multi-objective reactive power and voltage control for power system. The objectives are active power loss, voltage deviation and the voltage stability index of the system. The load constrains and operational constrains are also taken into consideration. The multi-objective formulation of the problem requires a global performance index of the problem. A pseudogoal function derived on the basis of the fuzzy sets theory gives a unique expression for the global objective function, eliminating the use of weighing coefficients or penalty terms. Both objective functions and constraints are evaluated by membership functions. The inequality constrains are embedded into the fitness function by pseudogoal function which guarantees that the searched optimal solution is feasible. Moreover, a new type of evolutionary algorithm, particle swarm optimization (PSO), has been adopted and improved for this problem. To improve the performance of PSO, a fuzzy adaptive PSO (FAPSO) is proposed. A fuzzy system is employed to adaptively adjust the parameters of PSO, such as the inertia weight and learning factors, during the evolutionary process. The proposed approach has been examined and tested with promising numerical results of the IEEE 30-bus and IEEE 118-bus power systems. [Copyright &y& Elsevier]