B. Anand

Artificial Intelligence in Performance Analysis of Load Frequency Control in Thermal-Wind-Hydro Power Systems

In this article, Load Frequency Control (LFC) of three area unequal interconnected thermal, wind and Hydro power generating units has been developed with Proportional-Integral (PI) controller under MATLAB/SIMULINK environment. Further, the PI controller gains values that optimized using trial and error method with two different objective functions, namely the Integral Time Square Error (ITSE) and the Integral Time Absolute Error (ITAE). The performance of ITAE objective function based PI controller is compared with the ITSE objective function optimized PI controller. Analysis reveals that the ITSE optimized controller gives more superior performance than ITAE based controller during one percent Step Load Perturbation (1% SLP) in area 1 (thermal area). In addition, Proportional–Integral –Derivative (PID) controller is employed to improve the same power system performance. The controller gain values are optimized using Artificial Intelligence technique based Ant Colony Optimization (ACO) algorithm. The simulation performance compares the ACO-PID controller to the conventional PI. The results proved that the proposed optimization technique based the ACO-PID controller provides a superior control performance compared to the PI controller. As the system using the ACO-PID controller yield minimum overshoot, undershoot and settling time compared to the conventional PI controlled equipped system performance.

Design of a proportional-integral-derivative controller for an automatic generation control of multi-area power thermal systems using firefly algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control, automatic generation control ( AGC ) plays a crucial role. In this paper, multi-area ( Five areas: area 1, area 2, area 3, area 4 and area 5 ) reheat thermal power systems are considered with proportional-integral-derivative ( PID ) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm ( FFA ). The experimental results demonstrated the comparison of the proposed system performance ( FFA-PID ) with optimized PID controller based genetic algorithm ( GA-PID ) and particle swarm optimization ( PSO ) technique ( PSO-PID ) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error ( ITAE ) cost function with one percent step load perturbation ( 1 % SLP ) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot / undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

Design of Proportional-Integral-Derivative Controller Using Stochastic Particle Swarm Optimization Technique for Single-Area AGC Including SMES and RFB Units

In this work, electromechanical oscillations in single-area power systems can be effectively reduced by the influence of energy storage unit, and it helps in the load leveling process and performance improvement of the system. This proposed paper describes the application of super magnetic energy storage (SMES) unit and redox flow battery (RFB) in single-area non-reheat, single, and double reheat thermal power system. The commonly used industrial PID controller act as a control strategy and the optimal gain values are obtained using three different cost functions with stochastic particle swarm optimization technique (SPSO). The dynamic performance of the investigated power system is obtained and examined with one percent step load perturbation.

Load Frequency Control of Hydro-Hydro System with Fuzzy Logic Controller Considering Non-linearity

The current work handles Automatic Generation Control (AGC) of an interconnected two area hydro-hydro system. The proposed system is integrated with conventional Proportional Integral (PI) as well as Fuzzy Logic Controller (FLC). Since, the conventional PI controller does not offer sufficient control performance. Thus, non-linearities such as the Generation Rate Constraint (GRC) and Governor Dead Band (GDB) are included in the system in order to overcome this drawback with employing Fuzzy Logic Controller (FLC) in the system. The results reported the time domain simulation that used to study the performance, when 1% step load disturbance is given in either area of the system. Furthermore, the conventional PI controller simulation results are compared to fuzzy logic controller. The simulation results depicted that the FLC achieved superior control performance.

Dynamic performance analysis of AGC of multi-area power system considering Proportional-Integral-Derivative controller with different cost functions

This work presents Automatic Generation Control (AGC) of multi-area reheat thermal power system with Proportional-Integral-Derivative (PID) controller. The investigated power system comprises of four equal reheat thermal power system and all four areas are interconnected through tie-line. The gain values of PID controller parameters are tuned by using proposed Artificial Intelligence (AI) based optimization technique with different objective functions. Performance of proposed algorithm is tested with objective functions by considering one percent Step Load Perturbation (1% SLP) in area 1 and compared. Time domain specification analysis is considered to evaluate the performance of objective functions.

A Design of PI Controller using Stochastic Particle Swarm Optimization in Load Frequency Control of Thermal Power Systems

In this work Proportional-Integral (PI) controller was designed and proposed for Load Frequency Control (LFC) of a single area reheat thermal power system. The controller parameters, Proportional (Kp), Integral gain (Ki) values, were optimized and properly tuned using the Stochastic Particle Swarm Optimization (SPSO) technique. Investigate power system comprises suitable governor, reheater and generator units. Three different objective functions are considered for investigation, Integral Absolute Error (IAE), Integral Square Error (ISE) and Integral Time Absolute Error (ITAE) with one percent Step Load (1% SLP). Finally, simulation results show that IAE based PI controller response settled quickly with minimum over and undershoot compared to other objective function based controller performance.

Ant Colony Optimization Based Load Frequency Control of Multi-area Interconnected Thermal Power System with Governor Dead-Band Nonlinearity

The interconnected thermal power system consists of several areas. Various parameters should be provided to reach power systems’ firm operation. The current work proposed an optimization algorithm, namely Ant colony optimization (ACO) to optimize the Proportional-Integral-Derivative (PID) controller for the load frequency control of two-area interconnected non-reheat thermal power system with Governor dead band nonlinearity. The ACO in used to determine optimal controller’s parameters, where an objective function, namely Integral Time Absolute Error is conducted. A comparative study for the ACO performance to the Craziness based Particle swarm optimization (CPSO) is studied to examine the proposed approach performance in the interconnecting thermal power system. The result established the ACO optimized PID controller response superiority of the compared to the CPSO optimized controller.

Conventional controller based AGC of multi-area hydro-thermal power systems

The present study proposed the Automatic Generation Control (AGC) of multi-area hydrothermal interconnected power system with conventional controller. Multi-area power system consists of four power generating units (Two Hydro and two thermal). The thermal power generating is equipped with appropriate single stage reheater unit and the hydro power generating unit is equipped with a suitable mechanical governor. All four areas are interconnected through tie-line. The conventional integral controller is employed into power system to improve the dynamic performance. The gain value of the integral controller is tuned using trial and error method with three different objective functions (Integral Time Square Error (ITSE), Integral Time Absolute Error (ITAE)) and one percent Step Load Perturbation (1%SLP) in area 1. It is observed from the response that the ITAE objective function tuned integral controller provided better result compared to ISE tuned controller. The time domain specification for the simulation is utilized to study the performance of the system with different objective functions and conventional controller.

Evolutionary Algorithm Based LFC of Single Area Thermal Power System with Different Steam Configurations and Non-linearity

Load Frequency Control (LFC) of single area thermal power system is presented in this work. Commonly used industrial Proportional-Integral-Derivative (PID) controller is considered as a supplementary controller and parameters are optimized by using evolutionary algorithm (Ant Colony Optimization (ACO)). Three cost functions are considered to optimize controller gain values. Such as, Integral Absolute Error (IAE), Integral Time Absolute Error (ITAE) and Integral Square Error (ISE) and also three different stem configurations (Non Reheat turbine, Single Stage Reheat turbine and Double stage reheat turbine) are considered in this work. Further the performance of proposed algorithm is proved by adding non-linearity (Generation Rate Constrain, Governor Dead Band and Boiler Dynamics) into the same power system and value of Step Load Perturbation (SLP) in all three steam configurations. Time domain analysis is used to study the performance of power system with different scenarios.

Evolutionary Computational Technique in Automatic Generation Control of Multi-area Power Systems with Nonlinearity and Energy Storage Unit

In this study, a new meta-heuristic based evolutionary computational technique is reported for solving Automatic Generation Control (AGC) or Load Frequency Control (LFC) issue in multi-area power system with nonlinearity and an energy storage unit. Multi-area power system consists of two area equal reheat thermal power systems with Governor Dead Band (GDB) and Generation Rate Constraint (GRC) nonlinearity and boiler dynamics and energy storage element. During normal operating conditions, there no change in system parameters (Frequency and tie-line power flow) and stability. When sudden load demand occurs in any one of interconnected power, it affects system parameters and stability and system yield damping oscillation in their response with steady state error and settling time. In order to mitigate this biggest pose the proper selection of the controller is a major issue. In power system Automatic Voltage Regulator (AVR) loop is a primary control loop and in addition Proportional-Integral-Derivative (PID) controller is proposed as a secondary controller in AGC. The better performance of power system depends on proper selection of controller gain and also depends on the selected objective function for optimization of controller gain values. A new meta-heuristic based Ant Colony Optimization (ACO) evolutionary computational technique is used for tuning of PID controller with different operating conditions. Three different objective functions Integral Square Error (ISE), Integral Time Absolute Error (ITAE) and Integral Absolute Error (IAE) are used in ACO for tuning of controller gain. An electromechanical oscillation of power system is effectively damp out by introducing an energy storage unit in two area interconnected power system because of their inherent energy storage capacity with kinetic energy of the rotor. In this study Hydrogen generative Aqua Electroliser (HAE) with a fuel cell is incorporated into the investigated power system. The response of the proposed approach with different cost functions are obtained and compared with and without considering the effect of energy storage unit in LFC problem.