Elyas Rakhshani

Multi-area load frequency control in a deregulated power system using optimal output feedback method

In this paper, the dynamical response of the load-frequency control problem in the deregulated environment is improved with a pragmatic viewpoint. In the practical environment, access to all of the state variables of system is limited and measuring all of them is also impossible. To solve this problem, in this paper the optimal output feedback method is proposed. In the output feedback method, only the measurable state variables within each control area is required to use for feedback. The optimal control law is determined by minimizing a performance index under the output feedback conditions leading to a coupled matrix equation. The proposed method is tested on a two-area power system with different contracted scenarios. The results of the proposed controller are compared with the full-state feedback method. The results are shown that when the power demands changed, the output feedback method have a good ability to tracking of contracted and/or non-contracted demands. In fact, this method provides a control system that satisfied the load frequency control requirements and with a reasonable dynamic response.

Design of the LCL+trap filter for the two-level VSC installed in a large-scale wave power plant

This paper presents a methodology for designing the link passive filter of the power converters installed in a multi-megawatt wave power plant. Such filter is based on the superposition of both LCL and trap filter configurations with the purpose of achieving enhanced grid interaction of a two-level voltage source converter. The LCL+Trap filter design is highly dependent on the electrical network characteristics; hence the distribution system of the plant is introduced in the paper to take into account its effects on the tuning parameters. The proposed LCL+trap filter topology arises as a successful alternative solution for the conventional LCL filter topology, thanks to its improved filtering capability while ensuring a reduced filter size. The validation of the proposed filter performance is evaluated in simulation by performing a comparative analysis between the LCL+trap and the LCL filters when operate in a wave farm application.

Simulation of two-area AGC system in a competitive environment using reduced-order observer method

In this paper, a reduced-order observer controller is proposed to solve the automatic generation control problem in a deregulated power system that operates under deregulation based on the bilateral policy scheme. In the practical environment (real world), access to all of the state variables of system is limited and measuring all of them is also impossible. So when we have fewer sensors available than the number of states or it may be undesirable, expensive, or impossible to directly measure all of the states, using a reduced-order observer is proposed. A proposed design, which is presented in this paper, has been developed in order to over-come this problem. The proposed strategy is tested on a two-area power system and compared with the optimal full-state feedback method by means of simulation. The results are shown that this method improved the dynamic response of system and provides a control system that satisfied the load frequency control requirements.

Intelligent Linear-Quadratic Optimal Output Feedback Regulator for a Deregulated Automatic Generation Control System

Abstract One of the main observed problems in the control of automatic generation control systems is the limitation to access and measurement of state variables in the real world. In order to solve this problem, an optimal output feedback method, the linear-quadratic regulator controller, is used. In the output feedback method, only measurable state variables within each control area are required to use for feedback. But in order to improve dynamic performance and provide a better design for this controller, the concept of an intelligent regulator is added to the linear-quadratic regulators; as a result, the particle swarm optimization based linear-quadratic output feedback regulator and the imperialist competitive algorithm based linear-quadratic output feedback are proposed to calculate the global optimal gain matrix of controller intelligently. The optimal control law of this controller must be determined by minimizing a performance index under the output feedback conditions leading to coupled matrix equations. In conventional methods, the control law is handled by pole placement, iterative, or trial-and-error methods for choosing controller gains; thus, intelligent optimization techniques are applied to solve this problem. The proposed controllers are tested on a two-area automatic generation control power system, and a complete comparison between the proposed output feedback controllers with adaptive weighted particle swarm optimization, particle swarm optimization, the imperialist competitive algorithm, and a conventional output feedback controller is presented. The results show that the proposed intelligent controller improved the dynamic response of the system faster than the conventional controller and provided a control system that satisfied the load frequency control requirements.

REDUCED-ORDER OBSERVER CONTROL FOR TWO-AREA LFC SYSTEM AFTER DEREGULATION

In this paper, a reduced-order state observer with a practical point of view for load frequency control (LFC) problem in a deregulated power system is proposed. In the practical environment, there is limited access to all state variables of system and measuring all of them is usually impossible. So when the available sensors are less than the number of states or when it may be undesirable, expensive or impossible to measure directly all of the states, a reduced-order state observer can be applied as proposed in this paper. The proposed strategy is tested on a two-area power system and compared with the optimal full-state feedback method by using computer simulation. The results show that the proposed method improves the dynamic response of system and provides a control system that satisfies the LFC requirements.

A New Combined Model for Simulation of Mutual Effects between LFC and AVR Loops

In this paper a new model is proposed to show the interaction between the LFC and the AVR loops. These coupling effects of the AVR and LFC loops are studied by extending the linearized AGC system to include the excitation system. A complete system model for low-frequency oscillation studies should be composed of mechanical and electrical loops. So one machine - infinite bus model of a power system is combined to load frequency control system. This proposed combined model is tested on one-area power system. The results are shown that by using this model more accuracy will be reachable in dynamic and steady state responses.

Effect of VSC-HVDC on load frequency control in multi-area power system

This study presents a solution for reducing the frequency oscillations in multi-area interconnected power system by means of using an VSC-HVDC interconnection transmission line. The upcoming power-electronics based HVDC transmission system offers new features that can be advantageous for improving the frequency control and thus for enhancing the stability in transmission networks. This paper is structured in two main parts; the first one is be devoted to introduce the basic elements of HVDC links and the second part will be focused on the effects of the HVDC links in the frequency control of interconnected power systems. In order to show the positive effects of HVDC links under random load disturbance, a model with parallel AC-DC interconnected power system, including a new power modulation controller of bi-directional VSC-HVDC link, is proposed and simulated. Comparisons between HVAC and HVDC transmissions are presented and its performance is evaluated using Matlab/Simulink.

Application of data mining on fault detection and prediction in Boiler of power plant using artificial neural network

This paper tries to present a new applied method on detection and prediction of faults for the boilers burner system of power plant with using data mining and artificial neural network. Boiler/Steam turbine is important equipments in the industry, especially in the electric power industry. Because of the complexity of burner management systems and particularity of its running environment, the fault rate of boilers burner system is high. So the fault prediction is a difficult problem. The proposed approach includes data mining, data preprocessing i.e. data reduction, data clustering; learning and prediction by artificial neural networks. Boiler/turbine units constitute a critical component of a co-generation system. The operative parameters in boilers burner system are measured and are characterized to obtain a set of descriptors. These sets are analyzed by data mining approach. Next, these preprocessed data are used as input data of two neural networks which detect and predict the faults in a boiler of power plant. Multiplayer back propagation neural network with four hidden layers, as one of the steps in data mining process is studied. The knowledge extracted by this data mining algorithm is an important component of an intelligent alarm system. Furthermore, using this method is more valuable for the further study.

A reduced-order estimator with prescribed degree of stability for two-area LFC system in a deregulated environment

This paper presents a reduced-order estimator by using an LQR regulator with a prescribed degree of stability for two-area load frequency control problem in a deregulated power system. In the practical power system, access to some of the state variables in LFC system is limited and measuring is also impossible. So a reduced-order estimator is proposed. But to access a good dynamic response a controller with prescribed degree of stability is combined with this estimator model. The results of the simulation are shown that with using this method, the load frequency control requirements in a practical environment are satisfied and also with so good dynamic responses, sensitivity to plant-parameter variations is reduced.

Inertia Emulation in AC/DC Interconnected Power Systems Using Derivative Technique Considering Frequency Measurement Effects

Virtual inertia is known as an inevitable part of the modern power systems with high penetration of renewable energy. Recent trend of research is oriented in different methods of emulating the inertia to increase the sustainability of the system. In the case of dynamic performance of power systems especially in Automatic Generation Control (AGC) issue, there are concerns considering the matter of virtual inertia. This paper proposes an approach for analyzing the dynamic effects of virtual inertia in two-area AC/DC interconnected AGC power systems. Derivative control technique is used for higher level control application of inertia emulation. This method of inertia emulation is developed for two-area AGC system, which is connected by parallel AC/DC transmission systems. Based on the proposed technique, the dynamic effect of inertia emulated by storage devices for frequency and active power control are evaluated. The effects of frequency measurement delay and phase-locked loop effect are also considered by introducing a second-order function. Simulations performed by MATLAB software demonstrate how virtual inertia emulation can effectively improve the performance of the power system. A detailed eigenvalue analysis is also performed to support the positive effects of the proposed method.