Optimization For The Design Of Load Frequency Control

It is observed that the power factor is maintained closer to unity when the input voltage is reduced from 230V to 110Vrms. Figure 11 (a) and (b) shows the power factor correction of controller for various load condition such as 20% (60W) and 75% (230W). The power factor for the system is found to be 0.84 for light load condition and 0.99 for full load condition. The THD of input current at full load with predominant third and fifth harmonic components are shown in Figure 12(a) and (b).Third harmonics is found to be 4.8% and fifth harmonic component is 4.9% which are well within IEC 61000-3-2 standard during wide range of load variations. The variation in power factor with load is shown graphically in Figure 13(a). It can be inferred from the graph that improved resettable control operates at high power factor for all load condition whereas the conventional PI control has poor power factor under light load conditions. Figure 13(b) shows the comparison between the efficiency of the converter for varying load conditions with the conventional control method and the resettable integrator control. The converter’s efficiency is maintained at 92% for light load conditions and 96% for fully loaded condition with integrator control technique. Thus the improved resettable integrator controller provides a very simple and reliable solution for power factor correction and

The parameters of this controller (PI- 1) can be decreased during the voltage sag in order to improve the performance of the proposed method.

Traditionally conventional aircraft uses the secondary power system of electric, pneumatic, hydraulic and mechanical power transfer system. Increasing demand of more advance electrical system in aircraft industries has refined the electronic power, fault-control actuator systems into a new level. To reinforce the technological progress of an aircraft electrical system, the concept of More Electric Aircraft (MEA) has been introduced in the electrical system of the aircraft by “replacing non electrical power in the aircraft with electricity.” (Corcau. J.I., Dinca. L., 2012)

To halt the drop in frequency, it is necessary to intentionally, and automatically disconnect a portion of the load equal to or greater than the generation deficiency in order to achieve balanced power economics while maintaining system stability. Automated load shedding systems are necessary for industrial power systems since sudden disturbances can plunge a system into a hazardous state much faster than an operator can react. These automated schemes must be designed and implemented to possess in-depth knowledge of system operating parameters and must rely on time sensitive

Through the implementation of peak load leveling utilities can offer better stability regulation services for voltage and frequency, and sudden demands for power can also be met much easier. Via a simple frequency measurement, dynamic load leveling can be provided and determine local demand. This would result in less natural gas or coal-fired power plants being required to meet peak demand or as a back up to protect against unexpected blackouts.

Abstract— This paper presents an efficient and reliable evolutionary based approach to solve the optimal power flow(OPF) problem. The proposed approach employs differential evolution algorithm for optimal settings of control variables. The proposed approach is examined and tested on the standard IEEE 30-bus test system with fuel cost minimization as objective. The proposed approach results are compared with the results reported in the literature. The results show the effectiveness and robustness of the proposed approach.

Along with the system design, detailed numerical models (e.g. control models, mathematical models, data constraints) can be added into the analytical framework to decrease the uncertainty of simulation results. In this process, the qualitative models should be validated to ensure consistency with numerical models. During this process, the expressions of propositional logics and linear temporal logics are replaced by High Order Logics. An example of numerical model implementation is demonstrated in Fig 5; after specifying plant power, a form of proportional-integral-derivative (PID) control can be implemented and assigned to the software “Control Routine”. Note that the meaning and actual values of each parameter are gathered from the

The above method suggests optimal combination of construction method with the large fuzzy composite utility by the means of “particle swarm optimization” (PSO) technique will be searched out. The fuzzy multiple attribute required function governed by constrained fuzzy operations will be added with the PSO method.

In this paper, islanded microgrid system is considered in order to supply the continuous power with the optimum cost for the office buildings which is situated in Hlaing Tharyar Township, Yangon division of Myanmar. According to the collected data, the load demand of the proposed area is approximately about 150 kW and the load demand varies throughout the day. After that, the stand-alone microgrid system is designed regarding to the levelized cost of energy. The simulation, sensitivity analysis and optimization of microgrid system have been performed by using HOMER software and Particle Swarm Optimization (PSO) and the two simulation results are compared to achieve the optimum cost of the proposed system.

This is to certify that the work embodied in this Literature Review Report entitled” Maximum demand control with microcontroller” was carried out by Tailor Chitrang Manojkumar (110373109014), Nayak Karan Iiashbhai (100370109091), Bhingaradiya Darshan Rameshbhai (120370109038), Radadiya Darshan Rameshbhai (120370109040) at Electrical Engineering Department of Parul Institute of Engineering & Technology, Limda in Partial Fulfillment of the Requirements for the Degree of B.E. to be awarded by Gujarat Technological University. This work has been carried out under my supervision and is to my satisfaction.

Table.4 shows step response parameters of the closed loop system with GA-PID controller using IAE based fitness function. From the results of Table.4, the value at the maximum overshoots is quite small, nearly zero percent and the values of the settling times, the rise time, and the integral of the absolute error obtained by multiobjective genetic optimization were much less than those values by the other methods. From the results, the proposed algorithm produces better responses than that obtained using the conventional method. So, we can say that the MPPT based multiobjective genetic algorithm well improves the performance of the PID controllers. As shown in results of Table.5, the value of the maximum overshoot is quite small, nearly zero percent and the values at the settling times, the rise time, and the integral of the absolute error obtained by particle swarm optimization were much less than those values by the other methods. From the results, the proposed algorithm produces better responses than that obtained using the GA method. So, we can say that the MPPT based PSO algorithm well improves the performance of the PID controllers.

In 2017, S. Kayalvizhi et. al. [49] presented a paper “Frequency Control of Micro Grid with Wind Perturbations using Levy Walks with Spider Monkey Optimization Algorithm.” In this paper, a new eagle strategy, which is a combination of levy flights and SMO, is utilized in the optimization of the gains of PI controllers which helps in regulating the frequency of the micro grid. A typical micro grid test system and a real time micro grid setup at British Columbia are the two case studies considered, in which the frequency control is implemented. The implementation is done in two-step search process; in the first place, levy flights do the random search and after that SMO does a thorough local search. Results demonstrate that the proposed method outperforms the results of other well-known algorithms and is

Neha Kundariya, Jyoti Ohri in their research paper titled ‘Design of Intelligent PID Controller using Particle Swarm Optimization with different Performance Indices’ proposed a PSO based PID controller for controlling of DC shunt motor using different performance indices like Integral of Time multiplied by Absolute Error (ITAE), Integral of Absolute magnitude of Error (IAE) and Integral of Square of Error (ISE). From the results obtained, it was found that integral time of absolute error(IAE) gives better results in time domain compared to other performance indices PID control

In this chapter we focus on describe the most controller type of controllers that are particularly appropriate for control engineering applications, Which is a PID Controller, We applying this controller to control the speed of BLDC motor, in which its parameters are tuned by many methods such as Ziegler-Nichols method and optimization techniques which include genetic algorithm (GA) and artificial bee colony algorithm (ABC). The chapter is organized as follows. In Section 3.1 a conventional PID controller is introduced. Section 3.2 illustrate Ziegler and Nichols Tuning method which tune parameters of the PID controller, Section 3.3 is a Genetic algorithm based PID controller, Section 3.4 gives Artificial bee colony (ABC) algorithm.

Abstract— In this paper, determination of optimal parameters of a PID controller in an Automatic Voltage Regulation (AVR) system by the approach of Particle Swarm Optimization (PSO) and Differential Evolution (DE) Techniques is presented. This paper demonstrated in detail how to employ the PSO and DE methods to search efficiently the optimal PID controller parameters of an AVR system. A MATLAB simulation has been performed. The proposed approach had superior features, including easy implementation, stable convergence characteristic, and good computational efficiency. In order to assist estimating the performance of the PID controller using PSO and DE, Minimum Error Integral (MEI) criterion Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE) and Integral Time Square Error (ITSE) are used.