Intelligent Frequency Control in an AC Microgrid: Online PSO-Based Fuzzy Tuning Approach (original) (raw)
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An on-line PSO-based fuzzy logic tuning approach: Microgrid frequency control case study
2014
In recent years, with significant growth in electrical energy consumption, conventional generating units in power systems are faced with a variety of problems, such as global warming, energy crisis, deficiency of fossil fuels and high cost of building new power plants and so on. Hence, environmental concerns, reducing dependency on fossil fuels, improvements of new energy technologies and also enhancing the reliability of power systems, are the factors that have been affected on the entrance of Distributed Generation Resources (DGRs).
Fuzzy-PI-based supervisory frequency control design in a stand-alone AC microgrid
2014
Frequency stability in microgrids under islanded operation mode is one of the most important control problems in new power system design. Due to increasing number of microgrids (MGs) in power systems, and variable inherent of renewable energy sources, this issue gets more attention recently. In industrial environments, PI controllers due to low-cost, reliability and simplicity in design are more popular; but in new power systems these controllers may not provide desirable performance. For sake of this challenge, in this paper after a brief review on the frequency control in MGs, a new intelligent secondary control method using a supervisory fuzzy logic controller is proposed with two main goals: holding of structure simplicity that is desirable in industrial environment and implementable capability without opening the existing conventional PI control loops. In this method which is applied on an AC MG, if system dynamics change, the PI controller parameters do not need to be retuning, and the supervisory fuzzy logic controller minimizes the MG frequency deviation.
International Journal of Electrical and Computer Engineering (IJECE), 2021
In this study, a control strategy based on the self-tuning method and synchronous reference frame (SRF) with PI regulator is proposed to achieve optimum quality of power in an autonomous microgrid (MG). The MGS is based on multiple distributed generation (DG) connected with 120 kV power grid. The proposed system is first simulated with fixed gain values for PI controller which are not optimal for sudden changes in the system i.e. transition of MG to islanding mode, load variations. So, the particle swarm optimization (PSO) has been utilized for tuning of PI controller parameters which ensure flexible performance and superior quality of power. The principal parameters considered in this study are, regulation of voltage and frequency, steady-state and dynamic response and harmonic distortion, mainly when microgrid is islanded. The performance of PI and PI-PSO is compared in this study by simulating AC microgrid in the MATLAB/Simulink environment. Summarized results of the system are provided to authenticate viability of proposed arrangement. The proposed controller performs intelligently while regulating voltage and frequency of the MGS and utility system. Keywords: Autonomous microgrid Current controller Islanding mode PSO This is an open access article under the CC BY-SA license.
Fuzzy Based Intelligent Frequency Control Strategy in Standalone Hybrid AC MicroGrid
Due to environmental concerns, there is lot of emphasis on the use of renewable energy sources as distribution generation sources for electric power generation. These distributed sources have resulted in the concept of AC/DC micro-grids. But the intermittent nature of these sources cause many control problems and thereby affect the quality of the power within a micro-grid operating in a standalone or grid connected mode. In this paper an AC micro-grid operating in standalone mode and consisting of wind turbine generators (WTGs), solar photovoltaic (PV), diesel engine generators (DEGs), fuel cells (FCs) and battery energy storage system (BESS) has been considered for simulation studies. An intelligent control technique based on fuzzy gain scheduling of the conventional proportional-integral-derivative (PID) controller is proposed for frequency regulation for sudden changes in load or generation power or both. The performance of the fuzzy gain scheduled PID (FGSPID) controller is compared with that of the conventional PID controller for comparative analysis. The simulation results demonstrate the effectiveness of the FGSPID controller in terms of less oscillations and reduced settling time and overshoot.
Journal of Automation and Control Engineering
In recent years worldwide, there is considerable focus on the growth of renewable energy sources (RESs) and distributed generation system (DGs) leading to the concept of microgrid (MG), which is becoming increasingly very popular. The RESs, constituting a MG, by nature have intermittent power output. Therefore, due to unpredictable uncertainties in power output of these systems it becomes very difficult for the conventional controllers to give satisfactory performance over a wide range and under different operating conditions. This paper addresses the problem of frequency regulation in an AC microgrid under variable wind speed and multiple random load disturbances and proposes a fuzzy gain scheduled proportional-integralderivative (FGSPID) controller to withstand these uncertainties and disturbances and provide an improved performance. For comparative analysis, the conventional PID controller is also implemented on the same microgrid system. Simulation results clearly indicate significant improvement in the frequency regulation of the microgrid system with FGSPID controller as compared to conventional PID controller. Index Terms-frequency regulation, AC-microgrid, renewable energy sources, intelligent control
IEEE Access, 2020
The increasing penetration of Microgrids (MGs) into existing power systems and ''plug and play'' capability of Distributed Generators (DGs) causes large overshoots and settling times along with various power quality issues such as voltage and frequency flickers, current harmonics and short current transients. In this context, over the past few years, considerable research has been undertaken to investigate and address the mentioned issues using different control schemes in conjunction with soft computational techniques. The recent trends and advancements in the field of Artificial Intelligence (AI) have led the development of Swarm Intelligence (SI) based optimized controllers for smooth Renewable Energy Sources (RES) penetration and optimal voltage, frequency, and power-sharing regulation. Moreover, the recent studies have proved that the SI-based controllers provide enhanced dynamic response, optimized power quality and improved the dynamic stability of the MG systems as compared to the conventional control methods. Their importance in modern AC MG architectures can be judged from the growing number of publications in the recent past. However, literature, pertaining to SI applications to AC MG, is scattered with no comprehensive review on this significant development. As such, this study provides an overview of 15 different SI optimization techniques as applied to AC MG controls from 43 research publications including a detailed review of one of the elementary and most widely used SI based metaheuristic optimization algorithms called Particle Swarm Optimization (PSO) algorithm. This comprehensive review provides a valuable one-stop source of knowledge for the researchers and experts working on SI controller's applications for AC MG dynamic response and power quality improvements.
MVO-PS Optimized Hybrid FOFPID Controller for Load Frequency Control of an AC Micro-Grid System
International Journal of Recent Technology and Engineering (IJRTE), 2019
This paper proposes a new approach for load frequency control in a multi micro grid system by using hybrid multi verse with pattern search (hMVO-PS) algorithm based Fractional Order Fuzzy PID controller. A multi micro grid system may be molded by some of the renewable resources (RESs) like photovoltaic (PVs), wind (WTGs), energy storage system (ESSs) and loads. The fractional order fuzzy PID (FOFPID) controller parameters are optimized by novel hybrid Multi verse with pattern search (hMVO-PS) technique. The flexibility and robustness of proposed FOFPID controller is inspected under different disturbance like stochastic variations. The superiority of FOFPID structure over conventional Fuzzy PID/PID and hMVO-PS technique over multi verse optimization (MVO), particle swarm optimization (PSO) and genetic algorithm (GA) has been manifested.
International Journal of Electrical Power & Energy Systems, 2013
This paper presents an optimal power control strategy, for an inverter based Distributed Generation (DG) unit, in an autonomous microgrid operation based on real-time self-tuning method. This research seeks to improve the quality of power supplied by DG units connected to the grid. Voltage and frequency regulation, dynamic response, steady-state response, and harmonic distortion are the main performance parameters considered, particularly when the microgrid is islanded or under the load change condition. The controller scheme comprises an inner current control loop and an outer power control loop based on a synchronous reference frame and conventional PI regulators. The power controller is designed for voltage-frequency (Vf) power control mode. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the power control parameters. In this paper, the proposed strategy is that when the microgrid is islanded or under load change condition, the DG unit adopts the Vf control mode in order to regulate the system voltage and frequency. The simulation results show that the proposed controller provided an excellent response to satisfy the power quality requirements and proved the validity of the proposed strategy.
DEVELOPMENT OF A LOAD FREQUENCY CONTROL SCHEME FOR AN AUTONOMOUS HYBRID MICROGRID
Zaria Journal of Electrical Engineering Technology, Department of Electrical Engineering, Ahmadu Bello University, Zaria – Nigeria., 2022
The research is aimed at developing a proportional-integral-derivative (PID) based load frequency control scheme for an autonomous hybrid microgrid using a Moth-Flame Optimization Algorithm (MFOA). This scheme is developed to ensure steady frequency at nominal value by maintaining continuous balance between the power generation and demand. The microgrid system considered in this work comprises of renewable and nonrenewable energy-based Power Generating Units and Energy storage units (PGU) and Battery Energy Storage System (BESS). These PGU and ESU are selected and combined into different microgrid architecture to actualize different scenarios for the purpose of this study. For each scenario, MFOA optimized Proportional-Integral-Derivative (PID) controllers were utilized to coordinate the microgrid operations by balancing the power generation-load demand profiles (minimizing fluctuations from the output power of the non-dispatchable sources and from sudden load change). The performance of the developed scheme was evaluated with the previous scheme based on Quasi-Oppositional Harmony Search Algorithm by comparing the responses in terms of settling time, overshoot and undershoot of the frequency deviation. From the simulations, the superiority of the developed MFOA optimized control scheme was evident with clear average percentage improvement of 38.92% on overshoot, 57.93% on undershoot and a faster settling time improvement of 33.17% for the step input scenarios when compared to the QOHSA optimized frequency controller using the same test scenario 1 parameters for the step input system perturbations. All modelling analysis was carried out in MATLAB R2019a modelling environment.
Recently, microgrid has become popular in the electric power industry and the important performance parameters considered, particularly when it is operating in islanded mode or under the load change condition, are voltage-frequency regulation, dynamic and steady-state response. In this paper, an intelligent optimal power control strategy, based on fuzzy gain scheduling of the conventional proportional-integral controller, is proposed for voltage-frequency control in an inverter based distributed generation unit. Simulations results, of the proposed control strategy, are compared against that of the conventional PI controller under islanded mode and under load change condition. It is evident that the proposed control strategy provides improved response.