[1] H. Shayeghi, A. Safari, and H. A. Shayanfar, "PSS and TCSC damping controller coordinated design using PSO in multi-machine power system," Energy Conversion and Management, vol. 51, no. 12, pp. 2930-2937, Dec.2010.
Abstract: The paper develops a new design procedure for simultaneous coordinated designing of the thyristor controlled series capacitor (TCSC) damping controller and power system stabilizer (PSS) in multi-machine power system. The coordinated design problem of PSS and TCSC damping controllers over a wide range of loading conditions is converted to an optimization problem with the time domain-based objective function that is solved by a particle swarm optimization (PSO) technique which has a strong ability to find the most optimistic results. By minimizing the proposed fitness function in which oscillatory characteristics between areas are included and thus the interactions among the TCSC controller and PSS under transient conditions in the multi-machine power system are improved. To ensure the robustness of the proposed stabilizers, the design process takes a wide range of operating conditions into account. The effectiveness of the proposed controller is demonstrated through the nonlinear time-domain simulation and some performance indices studies. The results of these studies show that the proposed coordinated controllers have an excellent capability in damping power system inter-area oscillations and enhance greatly the dynamic stability of the power system. Moreover, it is superior to both the uncoordinated designed stabilizers of the PSS and the TCSC damping controller.
Abstract: The paper develops a new design procedure for simultaneous coordinated designing of the thyristor controlled series capacitor (TCSC) damping controller and power system stabilizer (PSS) in multi-machine power system. The coordinated design problem of PSS and TCSC damping controllers over a wide range of loading conditions is converted to an optimization problem with the time domain-based objective function that is solved by a particle swarm optimization (PSO) technique which has a strong ability to find the most optimistic results. By minimizing the proposed fitness function in which oscillatory characteristics between areas are included and thus the interactions among the TCSC controller and PSS under transient conditions in the multi-machine power system are improved. To ensure the robustness of the proposed stabilizers, the design process takes a wide range of operating conditions into account. The effectiveness of the proposed controller is demonstrated through the nonlinear time-domain simulation and some performance indices studies. The results of these studies show that the proposed coordinated controllers have an excellent capability in damping power system inter-area oscillations and enhance greatly the dynamic stability of the power system. Moreover, it is superior to both the uncoordinated designed stabilizers of the PSS and the TCSC damping controller.
[2] T. T. Ma, "Design of Fuzzy Based UPFC Damping Controllers Using Particle Swarm Optimization Algorithm," International Review of Electrical Engineering-Iree, vol. 5, no. 3, pp. 1087-1094, May2010.
Abstract: This paper describes the design of a Takagi-Sugeno type fuzzy controller for the unified power flow controller (UPFC) to enhance the dynamic stability of power systems. The proposed fuzzy controller uses a regular rule base structure and the Takagi-Sugeno type defuzzification algorithm which offers the possibility of optimally designing either linear or nonlinear control gains over a wide operating range. This type of fuzzy controllers is expected to be robust and effective in complex control applications, e.g. damping electromechanical oscillations of multi-machine power systems. To achieve the best control results, a direct search optimization technique, particle swarm optimization (PSO) algorithm is used to find the best parameters for the designed UPFC damping controllers. Nonlinear time domain simulations on a two-area, multi-machine power system embedded with a UPFC are carried out. Typical simulation results including the comparison with the conventional PI type regulators used for the same UPFC control objectives are presented to validate the superior performance of the proposed control scheme.
[3] T. K. Das, G. K. Venayagamoorthy, and U. O. Aliyu, "Bio-inspired algorithms for the design of multiple optimal power system stabilizers: SPPSO and BFA," Ieee Transactions on Industry Applications, vol. 44, no. 5, pp. 1445-1457, Sept.2008.
Abstract: Damping intra-area and interarea oscillations are critical to optimal power flow and stability in a power system. Power system stabilizers (PSSs) are effective damping devices, as the), provide auxiliary control signals to the excitation systems of generators. The proper selection of PSS parameters to accommodate variations in the power system dynamics is important and is a challenging task particularly when several PSSs are involved. Two classical bio-inspired algorithms, which are small-population-based particle swarm optimization (SPPSO) and bacterial foraging algorithm (BFA), are presented in this paper for the simultaneous design of multiple optimal PSSs in two power systems. A classical PSO with a small population of particles is called SPPSO in this paper. The SPPSO uses the regeneration concept, introduced in this paper, to attain the same performance as a PSO algorithm with a large population. Both algorithms use time domain information to obtain the objective function for the determination of the optimal parameters of the PSSs. The effectiveness of the two algorithms is evaluated and compared for damping the system oscillations during small and large disturbances, and their robustness is illustrated using the transient energy analysis. In addition, the computational complexities of the two algorithms are also presented.
Abstract: Damping intra-area and interarea oscillations are critical to optimal power flow and stability in a power system. Power system stabilizers (PSSs) are effective damping devices, as the), provide auxiliary control signals to the excitation systems of generators. The proper selection of PSS parameters to accommodate variations in the power system dynamics is important and is a challenging task particularly when several PSSs are involved. Two classical bio-inspired algorithms, which are small-population-based particle swarm optimization (SPPSO) and bacterial foraging algorithm (BFA), are presented in this paper for the simultaneous design of multiple optimal PSSs in two power systems. A classical PSO with a small population of particles is called SPPSO in this paper. The SPPSO uses the regeneration concept, introduced in this paper, to attain the same performance as a PSO algorithm with a large population. Both algorithms use time domain information to obtain the objective function for the determination of the optimal parameters of the PSSs. The effectiveness of the two algorithms is evaluated and compared for damping the system oscillations during small and large disturbances, and their robustness is illustrated using the transient energy analysis. In addition, the computational complexities of the two algorithms are also presented.
[4] S. Panda, N. P. Padhy, and R. N. Patel, "Power-system stability improvement by PSO optimized SSSC-based damping controller," Electric Power Components and Systems, vol. 36, no. 5, pp. 468-490, May2008.
Abstract: Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated in this article. The design problem of the proposed controller is formulated as an optimization problem, and the particle swarm optimization technique is employed to search for the optimal controller parameters. By minimizing a time-domain-based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved, stability performance of the system is improved. The performance of the proposed controller is evaluated under different disturbances for both a single-machine infinite-bus power system and a multi-machine power system. Results are presented to show the effectiveness of the proposed controller. It is observed that the proposed SSSC-based controller provides efficient damping to power-system oscillations and greatly improves the system voltage profile under various severe disturbances. Furthermore, the simulation results show that in a multi-machine power system, the modal oscillations are effectively damped by the proposed SSSC controller.
Abstract: Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated in this article. The design problem of the proposed controller is formulated as an optimization problem, and the particle swarm optimization technique is employed to search for the optimal controller parameters. By minimizing a time-domain-based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved, stability performance of the system is improved. The performance of the proposed controller is evaluated under different disturbances for both a single-machine infinite-bus power system and a multi-machine power system. Results are presented to show the effectiveness of the proposed controller. It is observed that the proposed SSSC-based controller provides efficient damping to power-system oscillations and greatly improves the system voltage profile under various severe disturbances. Furthermore, the simulation results show that in a multi-machine power system, the modal oscillations are effectively damped by the proposed SSSC controller.
[5] S. Panda and N. P. Padhy, "Optimal location and controller design of STATCOM for power system stability improvement using PSO," Journal of the Franklin Institute-Engineering and Applied Mathematics, vol. 345, no. 2, pp. 166-181, Mar.2008.
Abstract: The optimal location of a static synchronous compensator (STATCOM) and its coordinated design with power system stabilizers (PSSs) for power system stability improvement are presented in this paper. First, the location of STATCOM to improve transient stability is formulated as an optimization problem and particle swarm optimization (PSO) is employed to search for its optimal location. Then, coordinated design problem of STATCOM-based controller with multiple PSS is formulated as an optimization problem and optimal controller parameters are obtained using PSO. A two-area test system is used to show the effectiveness of the proposed approach for determining the optimal location and controller parameters for power system stability improvement. The nonlinear simulation results show that optimally located STATCOM improves the transient stability and coordinated design of STATCOM-based controller and PSSs improve greatly the system damping. Finally, the coordinated design problem is extended to a four-machine two-area system and the results show that the inter-area and local modes of oscillations are well damped with the proposed PSO-optimized controllers.
Abstract: The optimal location of a static synchronous compensator (STATCOM) and its coordinated design with power system stabilizers (PSSs) for power system stability improvement are presented in this paper. First, the location of STATCOM to improve transient stability is formulated as an optimization problem and particle swarm optimization (PSO) is employed to search for its optimal location. Then, coordinated design problem of STATCOM-based controller with multiple PSS is formulated as an optimization problem and optimal controller parameters are obtained using PSO. A two-area test system is used to show the effectiveness of the proposed approach for determining the optimal location and controller parameters for power system stability improvement. The nonlinear simulation results show that optimally located STATCOM improves the transient stability and coordinated design of STATCOM-based controller and PSSs improve greatly the system damping. Finally, the coordinated design problem is extended to a four-machine two-area system and the results show that the inter-area and local modes of oscillations are well damped with the proposed PSO-optimized controllers.
[6] A. Anitha, S. Subramanian, and R. Gnanadass, "FDR PSO-based transient stability constrained optimal power flow solution for deregulated power industry," Electric Power Components and Systems, vol. 35, no. 11, pp. 1219-1232, Nov.2007.
Abstract: In this article, a novel method, called fitness distance ratio particle swarm optimization (FDR PSO) is employed to solve the optimal power flow (OPF) problem with ramp rate limits of the generators. The proposed method has been demonstrated on IEEE 30 bus test system and the results are compared with recently published works of the other optimization methods. Transient stability limit is incorporated while solving the OPF problem. Wheeling transactions are also carried out on the test system and their feasibility is checked with the transient stability limit of the generators. Contingency analysis is also carried out on the test system and the system stability is verified.
Abstract: In this article, a novel method, called fitness distance ratio particle swarm optimization (FDR PSO) is employed to solve the optimal power flow (OPF) problem with ramp rate limits of the generators. The proposed method has been demonstrated on IEEE 30 bus test system and the results are compared with recently published works of the other optimization methods. Transient stability limit is incorporated while solving the OPF problem. Wheeling transactions are also carried out on the test system and their feasibility is checked with the transient stability limit of the generators. Contingency analysis is also carried out on the test system and the system stability is verified.
[7] N. Mo, Z. Y. Zou, K. W. Chan, and T. Y. G. Pong, "Transient stability constrained optimal power flow using particle swarm optimisation," Iet Generation Transmission & Distribution, vol. 1, no. 3, pp. 476-483, May2007.
Abstract: A novel approach based on the particle swarm optimisation (PSO) technique is proposed for the transient-stability constrained optimal power flow (TSCOPF) problem. Optimal power flow (OPF) with transient-stability constraints considered is formulated as an extended OPF with additional rotor angle inequality constraints. For this nonlinear optimisation problem, the objective function is defined as minimising the total fuel cost of the system. The proposed PSO-based approach is demonstrated and compared with conventional OPF as well as a genetic algorithm based counterpart on the IEEE 30-bus system. Furthermore, the effectiveness of the PSO-based TSCOPF in handling multiple contingencies is illustrated using the New England 39-bus system. Test results show that the proposed approach is capable of obtaining higher quality solutions efficiently in the TSCOPF problem.
Abstract: A novel approach based on the particle swarm optimisation (PSO) technique is proposed for the transient-stability constrained optimal power flow (TSCOPF) problem. Optimal power flow (OPF) with transient-stability constraints considered is formulated as an extended OPF with additional rotor angle inequality constraints. For this nonlinear optimisation problem, the objective function is defined as minimising the total fuel cost of the system. The proposed PSO-based approach is demonstrated and compared with conventional OPF as well as a genetic algorithm based counterpart on the IEEE 30-bus system. Furthermore, the effectiveness of the PSO-based TSCOPF in handling multiple contingencies is illustrated using the New England 39-bus system. Test results show that the proposed approach is capable of obtaining higher quality solutions efficiently in the TSCOPF problem.
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