Area Automatic Generation Control Research Articles

Emergency fault affected wide-area automatic generation control via large-scale deep reinforcement learning

When a complex large power system is in an emergency, the conventional discrete emergency control strategy implemented will cause excess load or derivative accidents like line power overload, thereby raising the operation risk. To overcome the problems of excessive/insufficient regulation and subsequent accidents in the above context, this paper proposes a wide area automatic generation control (WA-AGC) framework, which integrates the emergency control strategy and a performance-based frequency regulation market mechanism. According to the frequency status of the power system, WA-AGC divides the AGC into four intervals, emergency AGC (EAGC), conventional AGC (CAGC), AGC transition and optimal power flow (OPF). These four together realize a comprehensive optimization of frequency and system stability as well as economy Based on the above framework, a swarm agent exploration distributed multiple delayed deep policy gradient algorithm (SAE-MD3) is developed, which uses multiple explorers with different exploration strategies for distributed optimization. In addition, several technologies are introduced to prevent Q value overestimation and generate a more robust optimal AGC strategy. Afterward, the effectiveness and feasibility of WA-AGC are verified through the simulations of an IEEE-9 two-area system and an IEEE-118 two-area system. Compared to conventional AGC strategies, the WA-AGC algorithm reduces the constraint violation time of the power line by 92.06% and the power generation cost by 0.27% as well as improves the CPS1 index by 0.04%.

Estimation of Regulation Reserve Requirement Based on Control Performance Standard

This paper proposes a method to estimate the real-time regulation reserve requirement based on the NERC Control Performance Standard (CPS). This method is constructed via three steps: first, a Multiple Linear Regression (MLR) model is applied to abstract the relationship between CPS and regulation reserve and other system conditions using training observations generated from a load frequency control model; second, a stepwise method with cross validation is used to select the most relevant features of MLR; and third, the regulation reserve requirement is computed by the MLR model as a function of the predicted system conditions and target CPS score. The recursive least square (RLS) method is used to update the model parameters in an online environment. Testing on a single area automatic generation control model with load and wind data from CAISO 33% Renewable Portfolio Standard scenario indicates the method outperforms methods used in the industry today.

Robustness and Stability analysis of Renewable Energy Based Two Area Automatic Generation Control

Principally, it is important to provide the customer with reliable and adequate power. As, power quality is measured by the stability in frequency and power exchange among control areas. Accordingly, automatic generation control (AGC) plays a vital role in power system operation and control. In this article, a renewable energy source (RES) such as wind turbine system (WTS) is added into the thermal unit in each area. The inclusion of wind turbine system has better frequency and power line exchange profile as demonstrated in the result analysis. An attempt is made to apply the successful evolutionary optimization technique named as firefly algorithm for multi objective, such as controller gains, set point weights etc. The firefly algorithm reduces the required control effort for achieving the dynamic response of system like settling time, overshoot and integral square error. Furthermore the stability aspects of the system are taken care of by applying different criteria and analysis. The execution of firefly algorithm PID enhances the system performance in contrast with PID, and DE-PID controller with respect to stability, overshoot and damping.

Multi Area AGC Problem of T.G.U Solved Through GA (Using Tuning of PID) Controller

Major issue of modern power system having complex power structure, it is necessary for Thermal Generating Unit (TGU) to continuous supplying an electric power with the increasing demand. Owing to this Automatic Generation Control (AGC) play a key role for maintaining the frequency oscillation and tie-line power due to unpredictable load changes. This paper help to solve the settling time issue of load frequency and tie-line power for multi area (Five area) AGC interconnected TGU Reheat and Non-Reheat system using different controllers like GA (Using Tuning of PID) controller, Fuzzy controller and PID controller. For better results the combined response of frequency and tieline deviation has been obtained separately for multi areas reheat and non-reheat T.G.U system and the comparative Tables of the entire controller’s response is taking place separately. The results obtain from the combined response and comparative table, shows that GA controller gives the better dynamic performance due to settle down frequency and tie-line power deviation in less time and satisfy the automatic generation control requirements.

Design of Proportional - Integral - Derivative controller using Ant Colony Optimization technique in multi - area Automatic Generation Control

Design of Proportional - Integral - Derivative controller using Ant Colony Optimization technique in multi - area Automatic Generation Control

Application of modular multilevel converter for AGC in an interconnected power system

Abstract This article demonstrates the maiden application of a new Modular Multi level Converter based Series Compensation (MMCS) technique for multi area Automatic Generation Control (AGC) interconnected system. Primarily MMCS has been modeled in state space form and proposes an appropriate location in AGC to obtain the better dynamic responses in frequency, tie-line power and individual generating power; further to quench the oscillation for sudden changes in load. The system has been studied the operation of MMCS and investigated with Generation Rate Constraints (GRC) of reheat turbines used in system. Further, selection of suitable integral and proportional–integral controller gain has been investigated with Integral Square Error (ISE) technique and Particle Swarm Optimization (PSO) technique for step load perturbation (SLP) in area-1 with performance index as its objective function by making control parameters as variables. System with MMCS is compared with out MMCS and observed performance has been increased and results are explored.

Design of GA Tuned Two-degree Freedom of PID Controller for an Interconnected Three Area Automatic Generation Control System

In this paper an innovative controller named parallel two-degree freedom of PID controller has deliberated and employed in an interconnected three area reheat thermal power system. The optimal controller gains obtained by using Genetic algorithm and the Integral Time Squared Error (ITSE) employed as an objective function. To realize the system practically, physical constraints like generator rate constraints and governor dead band nonlinearities have considered. To compensate the loss of kinetic energy during sudden load increase Superconducting Magnetic Energy Storage used in each area. The results gained by using GA tuned parallel two-degree freedom PID controller has compared with the conventional Ziegler’s Nichols tuned PID controller and genetically tuned PID controller. The GA tuned parallel two-degree freedom of PID controller produces better transient response characteristics for frequency and tie line power deviations under step load perturbations. The system simulation have realized by means of MATLAB/SIMULINK software.

Impact of wind power on control performance standards

As the penetration of wind power continuously increases, the impacts of wind power on frequency control have become of great concern. Frequency control requires real time balance between system generation and load, with system frequency deviation maintained within a certain range. Control Performance Standards (CPS) are indices for evaluating a balancing area’s frequency control performance in an interconnected system. They are important for quantifying the frequency control performance of the interconnected system and the relative distribution of frequency control responsibility among areas. Without mitigating action, the increasing wind power may inhibit a balancing area’s ability to comply with CPS due to variability in power output from wind plants and reduced system frequency response. This paper assesses the impacts of wind power on a balancing area’s frequency control characteristics and studies the wind power impacts on CPS. A two area Automatic Generation Control (AGC) model is used to verify these impacts. AGC changes the valve reference positions of units and restores system frequency to nominal values. Both theoretical study and simulation results show that CPS indices deteriorate as wind power penetration increases. Measures to improve CPS are provided.

Advanced Automatic Generation Control with Automatic Compensation of Tie-Line Losses

This article proposes the improvement of present-day common automatic generation control schemes by the simple addition of area tie-line loss compensation to the standard conventional control algorithm. Conventional automatic generation control regulators of interconnected power systems are developed, assuming the same tie-line power flows on both tie-line terminals. This assumption has the systematic (steady-state) output errors on controlled variables: the system frequency (and indirectly on the synchronous time) and areas tie-line exchanges. To eliminate large deviations of these variables outside of prescribed limits, their periodical corrections are necessary. This is achieved by simple modification of classical automatic generation control regulators, with the addition of corresponding tie-line losses to the area control error signal on standard automatic generation control regulator inputs. With such a modification, area automatic generation control regulators would attain better control performance, with less frequent operation switching from normal to the corrective mode. In addition, they become able to share tie-line power losses to interested parties by a simple adjustment of agreed participation coefficients set on corresponding automatic generation control regulators. The benefits obtained by such modified automatic generation control are paid by one additionally needed remote measurement per tie-line from their terminals in neighboring areas, while all other elements of existing automatic generation control schemes remain unchanged.

Performance evaluation of evolutionary designed conventional AGC controllers for interconnected electric power system studies in a deregulated market environment

Electric power industry is currently in transition from vertically integrated utilities to an industry that will incorporate competitive companies. This increases the complexity of the load frequency issue and calls for more insight and research. In this context, the tuning of a multi-area automatic generation control (AGC) system after deregulation and furthermore, the effect of reheat turbines dynamics in the power system performance, are not yet discussed in depth and are studied in this work. The effect of bilateral contracts on the dynamics of the system is taken into account and the concept of DISCO participation matrix for these bilateral contracts is simulated. Genetic algorithms are adopted in order to obtain the optimal parameters of the load-frequency controllers as well as of the frequency biases of thermal systems with reheat turbines. Also, since the optimum parameter values of the classical AGC have been obtained in the literature by minimizing the popular integral of the squared errors criterion (ISE) only, an effort is made in this study to show that this criterion does not give always the best system performance especially in a deregulated environment. In this work, we investigate the optimum adjustment of the load frequency controllers using a set of performance indices which are various functions of error and time. In this way, someone can observe the various performances that such a kind of power system might have when a different performance index is used. It should be noted that to the extent of the authors' knowledge, this kind of optimization has not been done yet in the literature. The performances of the tuned two–area AGC system are obtained using appropriate Matlab/Simulink models. Finally, it is envisaged that the synthesis procedure highlighted in this paper could be of practical significance for tuning conventional AGC controllers for an interconnected thermal-electric power system in a deregulated environment. Keywords: AGC, load frequency control, power systems, deregulation, bilateral contracts, genetic algorithms

Optimized multi area AGC simulation in restructured power systems

In this paper, the traditional automatic generation control loop with modifications is incorporated for simulating automatic generation control (AGC) in restructured power system. Federal energy regulatory commission (FERC) encourages an open market system for price based operation. FERC has issued a notice for proposed rulemaking of various ancillary services. One of these ancillary services is load following with frequency control which comes broadly under Automatic Generation Control in deregulated regime. The concept of DISCO participation matrix is used to simulate the bilateral contracts in the three areas and four area diagrams. Hybrid particle swarm optimization is used to obtain optimal gain parameters for optimal transient performance.

A reinforcement learning approach to automatic generation control

This paper formulates the automatic generation control (AGC) problem as a stochastic multistage decision problem. A strategy for solving this new AGC problem formulation is presented by using a reinforcement learning (RL) approach. This method of obtaining an AGC controller does not depend on any knowledge of the system model and more importantly it admits considerable flexibility in defining the control objective. Two specific RL based AGC algorithms are presented. The first algorithm uses the traditional control objective of limiting area control error (ACE) excursions, where as, in the second algorithm, the controller can restore the load-generation balance by only monitoring deviation in tie line flows and system frequency and it does not need to know or estimate the composite ACE signal as is done by all current approaches. The effectiveness and versatility of the approaches has been demonstrated using a two area AGC model.

Short term hydrothermal coordination using multi-pass dynamic programming

A technique that combines multipass dynamic programming (MPDP) technique with successive approximations to solve the daily hydrothermal coordination problem is presented. The long computation time and the large storage memory requirement are reduced. Due to the characteristics of hydrothermal coordination, the resulting load-following capability is much better than that achieved by applying MPDP to area automatic generation control. The generation can follow any shape load curve instead of only constant loads and ramps as in previous applications. >

Area automatic generation control by multi-pass dynamic programming

Current research in Automatic Generation Control emphasizes coordination of the regulation and the economic dispatch functions into a single systems problem. A dynamic optimal control problem formulation has previously been suggested. In this paper optimal trajectories are found for up to five maneuverable generators, using a new multi-pass dynamic programming method to make such solutions feasible. Dynamic valve point loading and singular solutions are considered. Computer studies have applied the method to several examples, including sudden changes in area load, and supplying the morning rise in area load.