Power system stability enhancement via coordinated design of a PSS and an SVC-based controller

Power system stability enhancement via robust coordinated design of a power system stabilizer (PSS) and a static VAR compensator (SVC)-based stabilizer is thoroughly investigated in this paper. The coordinated design problem of robust excitation and SVC-based controllers over a wide range of loading conditions and system configurations is formulated as an optimization problem with an eigenvalue-based objective function. The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. This study also presents a singular value decomposition (SVD) based approach to assess and measure the controllability of the poorly damped electromechanical modes by different control inputs. The damping characteristics of the proposed schemes are also evaluated in terms of the damping torque coefficient over a wide range of loading conditions. The proposed stabilizers are tested on a weakly-connected power system. The nonlinear simulation results and eigenvalue analysis show the effectiveness and robustness of the proposed approach

Power system stability enhancement via coordinated design of a PSS and an SVC-based controller

Power system stability enhancement via robust coordinated design of a power system stabilizer (PSS) and a static VAR compensator (SVC)-based stabilizer is thoroughly investigated in this paper. The coordinated design problem of robust excitation and SVC-based controllers over a wide range of loading conditions and system configurations is formulated as an optimization problem with an eigenvalue-based objective function. The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. This study also presents a singular value decomposition (SVD) based approach to assess and measure the controllability of the poorly damped electromechanical modes by different control inputs. The damping characteristics of the proposed schemes are also evaluated in terms of the damping torque coefficient over a wide range of loading conditions. The proposed stabilizers are tested on a weakly-connected power system. The nonlinear simulation results and eigenvalue analysis show the effectiveness and robustness of the proposed approach

Power system damping controllers design using a backstepping control technique

The objective of this dissertation is to design and coordinate controllers that will enhance transient stability of power systems subject to large disturbances. Two specific classes of controllers have been investigated, the first one is a type of supplementary signals added to the excitation systems of the generating units, and the second is a type of damping signal added to a device called a Static Var Compensator that can be placed at any node in the system. To address a wide range of operating conditions, a nonlinear control design technique, called backstepping control, is used. While these two types of controllers improve the dynamic performance significantly, a coordination of these controllers is even more promising. Control coordination is presented in two parts. First part concerns simultaneous optimization of selected control gains of exciter and SVC in coping with the complex nature of power systems. Second part proposes a combination of reinforcement learning and a backstepping control technique for excitation control system. The reinforcement learning progressively learns and adapts the backstepping control gains to handle a wide range of operating conditions. Results show that the proposed control technique provides better damping than conventional power system stabilizers and backstepping fixed gain controllers

Adaptive Rat Swarm Optimization for Optimum Tuning of SVC and PSS in a Power System

This paper presents a new approach for the coordinated design of a power system stabilizer- (PSS-) and static VAR compensator- (SVC-) based stabilizer. For this purpose, the design problem is considered as an optimization problem, while the decision variables are the controllers' parameters. This paper proposes an effective optimization algorithm based on a rat swarm optimizer, namely, adaptive rat swarm optimization (ARSO), for solving complex optimization problems as well as coordinated design of controllers. In the proposed ARSO, instead of a random initial population, the algorithm starts the search process with fitter solutions using the concept of the opposite number. In addition, in each iteration of the optimization, the new algorithm replaces the worst solution with its opposite or a random part of the best solution to avoid getting trapped in local optima and increase the global search ability of the algorithm. The performance of the new ARSO is investigated using a set of benchmark test functions, and the results are compared with those of the standard RSO and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed ARSO for coordinated design of controllers in a power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. The numerical investigations show that the new approach may provide better optimal damping and outperform previous methods

Study and Analysis of Power System Stability Based on FACT Controller System

Energy framework soundness is identified with standards rotational movement and the swing condition administering electromechanical unique conduct. In the exceptional instance of two limited machines, the basis of equivalent territory security can be utilized to ascertain the basic clearing point in the force framework, It is important to look after synchronization, in any case the degree of administration for customers won't be accomplished. This term steadiness signifies "looking after synchronization." This paper is an audit of three kinds of consistent state. The main sort of adjustment, consistent state steadiness clarifies the most extreme consistent state quality and force point chart. The transient solidness clarifies the wavering condition and the idleness steady while dynamic soundness manages the transient security time frame. There are a few different ways to improve framework soundness a portion of the techniques are clarified. Versatile AC Transmission Frameworks (FACTS) Flexible AC Transmission System (FACTS) regulators have been utilized frequently to comprehend the different issues of a non-variable force structure. Versatile AC Transmission Frames or FACTS are devices that permit versatile and dynamic control of intensity outlines. Improving casing respectability has been explored with FACTS regulators. This examination focuses to the upsides of utilizing FACTS apparatuses with the explanation behind improving electric force tire activity. There has been discussion of an execution check for different FACTS regulators

Robust Design of FACTS Wide-Area Damping Controller Considering Signal Delay for Stability Enhancement of Power System

制度:新 ; 報告番号:甲3426号 ; 学位の種類:博士(工学) ; 授与年月日:2011/9/15 ; 早大学位記番号:新575

Decentralized Synergetic Control of Power Systems

The objective of this dissertation is to design decentralized controllers to enhance the transient stability of power systems. Due to the nonlinearities and complexities of the system, nonlinear control design techniques are required to improve its dynamic performance. In this dissertation a synergetic control technique is being proposed to design supplementary controller that is added to the exciter of the generation unit of the system. Although this method has been previously applied to a Single Infinite Machine Bus (SMIB) system with high degree of success, it has not been employed to systems with multi machine. Also, the method has good robust characteristic like that of the popular Sliding Mode Control (SMC) technique. But the latter technique introduces steady state chattering effect which can cause wear and tear in actuating system. This gives the proposed technique a major advantage over the SMC. In this work, the method is employed for systems with multi machine. Each of the machines is considered to be a subsystem and decentralized controller is designed for each subsystem. The interconnection term of each subsystem with the rest of the system is estimated by a polynomial function of the active power generated by the subsystem. Particle Swarm Optimization (PSO) technique is employed for optimum tuning of the controller\u27s parameters. To further enhance the performance of the system by widening its range of operation, Reinforcement Learning (RL) technique is used to vary the gains of the decentralized synergetic supplementary controller in real time. The approach is illustrated with several case studies including a SMIB system with or without a Static Var Compensator (SVC), a Two Area System (TAS) with or without an SVC, a three --machines-nine-bus system and a fifty machine system. Results show that the proposed control technique provides better damping than the conventional power system stabilizers and synergetic controllers with fixed gains