Load Frequency Control Of Power System Research Articles

Load Frequency Control of Interconnected Hydro-Thermal System with Conventional Controllers and Expert Controllers

Load-frequency control (LFC) is a part of the Automatic Generation Control (AGC) in power systems, the aim of which is to maintain the system frequency and tie line flow at their scheduled values during normal period in an interconnected system. This research paper is devoted to explore the interconnection of the load frequency control of hydro power system and the thermal system. The thermal system is comprised with governor dead band, generation rate constraint and boiler dynamics where as the hydro system is comprised with generation rate constraint. The conventional PID controller does not have adequate control performance with the consideration of nonlinearities and boiler dynamics. To overcome this drawback, Genetic Algorithm helps in solving optimization problems by exploitation of random search. The aim of the proposed expert controller is to restore the frequency to its nominal value in the smallest possible time whenever there is any change in the load demand etc.

A robust PID controller based on imperialist competitive algorithm for load-frequency control of power systems

A new PID controller for resistant differential control against load disturbance is introduced that can be used for load frequency control (LFC) application. Parameters of the controller have been specified by using imperialist competitive algorithm (ICA). Load disturbance, which is due to continuous and rapid changes of small loads, is always a problem for load frequency control of power systems. This paper introduces a new method to overcome this problem that is based on filtering technique which eliminates the effect of this kind of disturbance. The object is frequency regulation in each area of the power system and decreasing of power transfer between control areas, so the parameters of the proposed controller have been specified in a wide range of load changes by means of ICA to achieve the best dynamic response of frequency. To evaluate the effectiveness of the proposed controller, a three-area power system is simulated in MATLAB/SIMULINK. Each area has different generation units, so utilizes controllers with different parameters. Finally a comparison between the proposed controller and two other prevalent PI controllers, optimized by GA and Neural Networks, has been done which represents advantages of this controller over others.

H∞ load frequency control of interconnected power systems with communication delays

This paper considers the problem of power system load frequency control design incorporating the effect of using open communication network instead of a dedicated one for the area control error signals. To have this, we appropriately consider time-delays in the ACE signals. A delay-dependent two-term H∞ controller design has then been proposed using linear matrix inequalities. Comparison of effectiveness of the proposed two-term controller with that of existing one-term and two-term controller designs establishes the superiority as well as applicability of the present design for the LFC problem.

Hierarchical optimal robust load-frequency control for power systems

In this study, a hierarchical optimal robust controller is presented for the power system load-frequency control problem. In this approach, the multi-area power system is first decomposed into several sub-systems (areas). Then by using a two-level control strategy, the overall optimal solution is obtained. At the first level, the optimal control of each area is obtained with respect to local information and also considering interactions coming from other areas. At the second level, by using a coordination strategy, the local controllers will converge to global solution and optimal robust controller is achieved. This approach is applicable to both single-area and multi-area interconnected power systems. Simulation results show the effectiveness and optimality of the proposed robust controller in power systems.

A functional model predictive control approach for power system load frequency control considering generation rate constraint

In this paper, a wide area measurement, centralized, load frequency control using model predictive control (MPC) is presented for multi-area power systems. A multivariable constrained MPC was used to calculate optimal control actions including generation rate constraints. To alleviate computational effort and to reduce numerical problems, particularly in large prediction horizon, an exponentially weighted functional MPC was employed. Time-based simulation studies were performed on a three-area power system, and the results were then compared with decentralized MPC and classical PI controller. The results show that the proposed MPC scheme offers significantly better performance against load disturbance. Copyright © 2013 John Wiley & Sons, Ltd.

Decentralized robust load-frequency control of power system based on quantitative feedback theory

This paper aims at investigating the problem of Load Frequency Control (LFC) in interconnected power systems in order to obtain robustness against uncertainties. A design method for a robust controller, based on Quantitative Feedback Theory (QFT), has been presented in this paper. For a two-area power system, the simulation results show that the system response with the proposed QFT controller exhibits transient response beyond PI controllers. It is also shown that the transient response of the tie line power can also be improved.

Robust decentralized load frequency control in multi- area electric power system using quantitative feedback theory

The load frequency control (LFC) problem has been one of the major subjects in electric power system design and operation. LFC is becoming much more significant today in accordance with increasing size, changing structure and complexity in interconnected power systems. Practice LFC systems use simple proportional-integral (PI) controllers, but parameters of PI controllers are usually tuned based on the trial-and-error approaches and they are incapable to obtain good dynamic performance under a wide range of operating conditions. For this problem, in this paper quantitative feedback theory (QFT) method is used for LFC problem. A multi-area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of proposed method, a classical PI type controller optimized by genetic algorithms (GA) is designed to compare with QFT controller. The simulation results visibly show the validity of QFT method in comparison with traditional method. Key words: Multi-area electric power system, electric power system load frequency control, robust control, quantitative feedback theory method.

Applying Optimal Sliding Mode Based Load-Frequency Control in Power Systems with Controllable Hydro Power Plants

In this paper an optimal load-frequency controller for a nonlinear power system is proposed. The mathematical model of the power system consists of one area with several power plants, a few concentrated loads and a transmission network, along with simplified models of the neighbouring areas. Firstly, a substitute linear model is derived, with its parameters being identified from the responses of the nonlinear model. That model is used for load-frequency control (LFC) algorithm synthesis, which is based on discrete-time sliding mode control. Due to a non-minimum phase behaviour of hydro power plants, full-state feedback sliding mode controller must be used. Therefore, an estimation method based on fast output sampling is proposed for estimating the unmeasured system states and disturbances. Finally, the controller parameters are optimized using a genetic algorithm. Simulation results show that the proposed control algorithm with the proposed estimation technique can be used for LFC in a nonlinear power system.

Sliding mode based load-frequency control in power systems

The paper presents a new discrete-time sliding mode controller for load-frequency control (LFC) in control areas (CAs) of a power system. As it uses full-state feedback it can be applied for LFC not only in CAs with thermal power plants but also in CAs with hydro power plants, in spite of their non-minimum phase behaviors. To enable full-state feedback we have proposed a state estimation method based on fast sampling of measured output variables, which are frequency, active power flow interchange and generated power from power plants engaged in LFC in the CA. The same estimation method is also used for the estimation of external disturbances in the CA, what additionally improves the overall system behavior. Design of the discrete-time sliding mode controller for LFC with desired behavior is accomplished by using a genetic algorithm. To the best of our knowledge, proposed controller outperforms any of the existing controllers in fulfilling the requirements of LFC. It was thoroughly compared to the commonly used PI controller by extensive simulation experiments on a power system with four interconnected CAs. These experiments show that the proposed controller ensures better disturbance rejection, maintains required control quality in the wider operating range, shortens the frequency’s transient response avoiding the overshoot and is more robust to uncertainties in the system.

On feasibility of regional frequency-based emergency control plans

Decentralized and regional load-frequency control of power systems operating in normal and near-normal conditions has been well studied; and several analysis/synthesis approaches have been developed during the last few decades. However in contingency and off-normal conditions, the existing emergency control plans, such as under-frequency load shedding, are usually applied in a centralized structure using a different analysis model. This paper discusses the feasibility of using frequency-based emergency control schemes based on tie-line measurements and local information available within a control area. The conventional load-frequency control model is generalized by considering the dynamics of emergency control/protection schemes and an analytic approach to analyze the regional frequency response under normal and emergency conditions is presented.

On Embedded Energy Storage for High Penetration of Wind Power

It is recognised that to enable high penetration of wind power it is essential for modern wind farms to meet some technical requirements. These requirements are specified, or planned to be included, in grid codes by some utilities around the world. In this paper it is shown that having an Embedded Energy Storage (EES) unit, a battery bank, in a wind turbine can help to meet these requirements and to reduce the overall wind farm development and system integration costs. After a review of wind power integration and power system load frequency control, two cases are presented. These are based on (a) the statistics of the wind speeds measured at Dunstaffnage, Scotland, (b) the manufacturers' data for two turbine generators, and (c) some mild assumptions used for the calculations. In the first case, for the same amount of wind energy annual output and a specified frequency control requirement: the delta production constraint, a wind farm of 50 wind turbines can be replaced by 10 wind turbines with an EES in each of them plus 33 ordinary wind turbines. In the second case, again for the same amount of wind energy annual output, wind turbines with EESs can meet the absolute power constraint and at the same time the ratings of transformers, transmission lines and other equipments associated with a wind farm development can be reduced, leading to a significant reduction in costs. Wind farms with such wind turbines can also provide some vital support in an emergency, for example, the event in Denmark on the 8th January 2005, when the total wind power output dropped suddenly from the scheduled 1843MW to 126MW, due to the shut down of most wind turbines under strong winds.

Design of Variable Structure Controller Using Fuzzy PI Type Sliding Surface: An Application to Load-Frequency Control Problem

In this paper, a proportional plus integral (PI) type sliding surface has been proposed for designing a fuzzy variable structure controller to solve load-frequency control problem in presence of load disturbances. It is shown that the proposed controller is effective and robust enough when the system suffers from mismatched condition but the model uncertainty and disturbance are assumed to be bounded. Furthermore, the proposed control strategy drives the states to the sliding surface and also maintains the sliding motion. To illustrate the approach presented has been tested on load-frequency control of power systems and the analytical claims have been justified under the uncertainty involved in the load demand of inter-connected power systems.

Load-frequency control by hybrid evolutionary fuzzy PI controller

Power-system load-frequency control by fuzzy-PI (FPI) controller is proposed. During control, a fuzzy system is used to decide adaptively the proper proportional and integral gains of a PI controller according the area-control error and its change. To ease the design effort and improve the performance of the controller, design of the FPI controller by hybridising a genetic algorithm and particle-swarm optimisation, called FPI–HGAPSO, is proposed. FPI–HGAPSO is based on the hybrid of the genetic algorithm and particle-swarm optimisation. In FPI–HGAPSO, elites in the population of GAs are enhanced by particle-swarm optimisation and these enhanced elites are selected as parents for crossover and mutation operations. Simulations of the proposed evolutionary FPI-control approach on a multiarea interconnected power system with different kinds of perturbations are performed. The performance of the proposed approach is verified from simulations and comparisons.

Power system load frequency control by genetic fuzzy gain scheduling controller

A Genetic Algorithm (GA) based fuzzy gain scheduling approach for load frequency control is proposed in this paper. In this approach, a fuzzy system is used to adaptively decide the integral or PI controller gain according to the area control errors (ACE) and their changes. To reduce both the fuzzy system design effort and the number of fuzzy rules, the fuzzy system is designed automatically by genetic algorithms. To improve the design performance, a new genetic algorithm using elitist strategy combined with similarity measure on relatives between individuals is proposed. Based on similarity measure, mutated reproduction is adopted to increase the chance for reaching better solutions and to avoid premature phenomena. Simulations on a two‐area interconnected power system with different kinds of perturbation are performed. The superiority of the proposed method over existing ones is verified from simulations and comparisons.

Power System Stabilizer Design based on Structured Singular Values

Decentralized control and robustness are two important issues in power system operation and planning. A recent study shows that, for power system load frequency control, a design method based on the structured singular values can be applied to address these two issues effectively. This article shows that, for another power system engineering problem, power system stabilizer (PSS) design, the structured singular values can also be applied to develop a decentralized multimachine PSS design method. A simulation study and frequency-response analysis on a model of a practical 10-machine power system have demonstrated that the system with decentralized PSSs designed in this article has good robustness in stability.

Decentralized robust adaptive-output feedback controller for power system load frequency control

In this paper, a new model reference-decentralized robust adaptive-output feedback controller is proposed for the load frequency control (LFC) of large-scale power systems with unknown parameters. This control strategy requires only local input–output data and can follow random changes in the operating conditions. The controller is designed such that the trajectory errors and the control gains of each area remain uniformly bounded. In the proposed method, firstly an adaptive observer is designed to estimate the state variables and system parameters using local data only. Then a locally linear combination of the estimated states and the model reference states are used to design a robust adaptive-output feedback controller for each area. Simulation results for a three-area power system show that the proposed controller achieves good performance even in the presence of plant parameter changes and system non-linearities.

Load frequency control for power system with reheat steam turbine and governor deadband non‐linearity by using neural network controller

AbstractIn this paper, a neural network (NN) controller is presented for load‐frequency control of power system. The NN controller uses back propagation‐through‐time algorithm. In the power system, the reheat effect of the steam turbine and the effect of governor deadband non‐linearity are considered by describing function approach in the state space model. By comparing the results of simulations, the performance of the NN controller is better than conventional controller. NN controller gives a shorter settling time and eliminates the necessity of parameter estimation time required in conventional adaptive control techniques.

Decentralised power system load frequency control beyond the limit of diagonal dominance

The design of decentralised robust load frequency control for interconnected multi-area power systems is studied in this paper. It is shown that although the design can be naturally formulated as a large-scale system decentralised control problem, it can be translated into an equivalent problem of decentralised controller design for a multi-input multi-output (MIMO) control system. It is known that simple controllers can be designed to achieve satisfactory performances if diagonal dominance can be achieved in a multivariable system. This is further extended in this paper. Using the design method proposed in this paper, even when the diagonal dominance cannot be achieved, subject to a condition based on the structured singular values (SSVs), each local area load-frequency controller can be designed independently. The robust stability condition for the overall system can be easily stated as to achieve a sufficient interaction margin, and a sufficient gain and phase margin during each independent design.

Application of neural networks to load-frequency control in power systems

This paper describes an application of layered neural networks to nonlinear power systems control. A single generator unit feeds a power line to various users whose power demand can vary over time. As a consequence of load variations, the frequency of the generator changes over time. A feedforward neural network is trained to control the steam admission valve of the turbine that drives the generator, thereby restoring the frequency to its nominal value. Frequency transients are minimized and zero steady-state error is obtained. The same technique is then applied to control a system composed of two single units tied together through a power line. Electric load variations can happen independently in both units. Both neural controllers are trained with the back propagation-through-time algorithm. Use of a neural network to model the dynamic system is avoided by introducing the Jacobian matrices of the system in the back propagation chain used in controller training.

New robust adaptive load-frequency control with system parametric uncertainties

In the paper, based on a combination of the robust control approach and an adaptive control technique, a design procedure of a new robust adaptive controller is proposed for power system load-frequency control with system parametric uncertainties. The system parametric uncertainties are obtained by changing parameters by 30% to 50% simultaneously from their typical values. In the design of the proposed controller, only the bounds of system parameters are required. The motivation of combining the robust control with an adaptive control is to use the robust control approach to deal with the small parametric uncertainties and to use the adaptive control for large parametric uncertainties so that stability of the overall system and good performance can both be achieved for all admissible uncertainties. The simulation results demonstrate that for the example system the proposed load-frequency controller can achieve good performance even in the presence of the generation rate constraint (GRC).