Proposed Load Frequency Control Research Articles

Optimal Tuning of PID Controllers for LFC in Renewable Energy Source Integrated Power Systems Using an Improved PSO

The constant rise in energy demand and concerns about climate change have led to increased penetration of renewable energy sources (RES). Maintaining active power balance between generation and demand in power systems with significant penetration of these highly variable and intermittent renewable sources requires an efficient load frequency control (LFC) strategy. One such strategy that has gained the attention of researchers is optimal tuning of PID controllers of LFC using metaheuristic method. This paper presents a PSO variant for optimal tuning of PID controllers for load frequency control of power system integrated with renewable energy resources. The proposed PID tuning technique is tested on a two-area power system commonly used in the literature. Seven scenarios have been used to validate the effectiveness of the proposed Load Frequency Control. For more realistic evaluation, governor dead band and communication time delays have been incorporated in the test system in one of the scenarios. Simulation results obtained when compared with those of three well-known PID-tuning metaheuristic algorithms produced shorter settling time and smaller frequency and tie line power deviations.

A quantum particle swarm optimization-based optimal LQR-PID controller for load frequency control of an isolated power system

One of the characteristics of a robust power grid is minimal variations in its frequency to load change or loss in generating unit(s). From the perspective of optimal control theory, the issue of load frequency control in the context of the interconnected functioning of power systems is investigated in this work, and a novel load frequency controller is proposed for a single area isolated power network. This novelty incorporates all the primary characteristics of the solutions that are based on a mixture of optimal controller designs by establishing a linear quadratic regulator optimized with quantum particle swarm optimization to design a proportional integral derivative (PID) controller unlike the conventional PID controller designs that are based on a combined Ziegler-Nichols and root locus (ZN-RL) method and manual tuning. The simulation results of the proposed controller using MATLAB show its efficacy in not only ensuring that there is no steady-state error in terms of the system frequency with load changes but also in achieving smoother transients. Following these landmark achievements, a transfer function model of the resulting power grid is constructed. The outcome of the model reveals that the system transients have been improved while keeping the intended steady-state characteristics. Furthermore, it is observed that the proposed load frequency controller has the best performance when compared with the combined ZN-RL method and the manual PID designs. This, therefore, demonstrates the superiority of the proposed design for load frequency control in power systems.

Virtual synchronous generator based superconducting magnetic energy storage unit for load frequency control of micro-grid using African vulture optimization algorithm

An isolated microgrid has significant frequency stability issues due to the erratic nature of renewable energy sources, stochastic load behaviour, and low system inertia. Consequently, this paper presents a Virtual Synchronous Generator (VSG) based Superconducting Magnetic Energy Storage (SMES) unit for frequency stability enhancement of microgrid. A newly developed metaheuristic algorithm named African Vulture Optimization Algorithm (AVOA) is used to optimize the proportional-integral controller parameters with the help of the Integral Time Absolute Error criterion. The proposed Load Frequency Control (LFC) model of an isolated microgrid is evaluated against numerous scenarios and well-known algorithms like Genetic Algorithm, Particle Swarm Optimization, Grey Wolf Optimization, and Harris Hawks Optimization. The MATLAB simulation results of the proposed system demonstrate a significant improvement in the dynamic response pertaining to maximum overshoot, settling duration, and frequency oscillations when contrasted to the other algorithms. Also, observed that the LFC system with VSG-based SMES unit improves the frequency response of 77.37 % and 86.56 % in peak overshoot and settling time respectively as compared to the system without energy storage units. Finally, real-time simulations are carried out in OPAL-RT (OP-4500) to validate the proposed system.

Modified manta ray foraging optimization algorithm based improved load frequency controller for interconnected microgrids

The recent environmental crisis and global warming have compelled an energy transition, particularly in the power generation and transportation sectors. Increased energy competence and production will necessitate enormous efforts. Admittedly, power system inertia metrics have revealed reduced inertia attributes, which could lead to a catastrophic shutdown and security issues in future electrical power systems. The design of the load frequency controller is essential for improving frequency regulation and power system stability. Nonetheless, more research is needed into control development and design approaches that take into account renewable energy characteristics, complexities, connected electric vehicles (EVs), and uncertainties. Metaheuristic-based design methods and fractional order control have recently demonstrated an improved response when compared to classical design methods and integer-order controllers. This work presents an improved fractional order hybrid control system based on two modified versions of the Manta Ray Foraging Optimization (MRFO) Algorithm. The exploration and exploitation stages of the modified MRFO are enhanced by utilizing a chaotic map and a weighting factor. The transients and steady-state performance of the studied two-areas interconnected microgrids have been significantly improved by incorporating the advantages of both the suggested fractional order-based control approach and the proposed modified MRFO algorithms. While assessing the feasibility of the developed controller and modified optimizers, uncertainty, renewable energy fluctuations, load transients, and electric vehicle attributes are all properly considered. The modified MRFO's performances are evaluated using 23 benchmark functions, and the results are compared to the original MRFO and recent well-known optimization algorithms. Both statistical analysis and time-domain results demonstrate the superiority of the proposed modified optimizers and the proposed load frequency controller.

Sine cosine adopted Harris' hawks optimization for function optimization and power system frequency controller design

A considerable number of intermittent renewable resources like photovoltaic generation and wind energy when integrated into the conventional grid technology causes serious issues in the power systems like frequency instability. So an intelligent controller is desired for steady and reliable operation of the electric grid. This paper deals with the frequency control of hybrid power system (HPS) employing a sine cosine adopted Harris' hawks optimization (SCaHHO) technique. The proposed technique aims at improving the performance of the original Harris' hawks optimization (HHO) algorithm by incorporating a sine and cosine function in the calculation of escaping energy and chances of escaping of prey respectively to emphasize the exploitation process of hawks. The effectiveness of the SCaHHO technique is validated with the novel HHO technique as well as moth flame optimization, sine cosine algorithm, grey wolf optimization, salp swarm algorithm and gravitational search algorithm using 23 standard test functions. A non-parametric statistical investigation is also carried out to verify the effectiveness of the suggested technique. Later the SCaHHO technique is utilized to tune a newly proposed adaptive fuzzy proportional integral derivative controller (AFPID) for frequency control of HPS. The suggested SCaHHO-tuned AFPID controller achieves an improved control action by moderating the frequency fluctuations as compared to the PID controller. Hardware-in-loop validation of the proposed load frequency control scheme is also carried out using OPAL-RT to measure its fidelity with the numerical simulation results.

Load Frequency Control for Power System using Generalized Extended State Observer

This study investigates load frequency control based generalized extended state observer (GESO) for interconnected power systems subject to multi-kind of the power plant. First, the mathematical model of the interconnected power system is proposed based on the dynamic model of thermal power plant with reheat turbine and hydropower plant. Second, the GESO is designed to estimate the system states and disturbances. In addition, the problem of unmeasurable system states in the interconnected power network due to lack of sensor has been solved by using the proposed load frequency control based GESO. The numerical experiments are carried out by using MATLAB/ SIMULINK simulation. The simulation results point out that the proposed control approach has the capacity to handle the uncertainties and disturbances in the interconnected power system with better transient performances in comparison with the existing control approach. The relevant dynamic models have already been used for the simulation of the physical constraints of the governor dead band (GDB) and generation rate constraint (GRC) effect in the power plants. It is evident that the robustness of the suggested controller in terms of stability and effectiveness of the system. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

Modelling issues and aggressive robust load frequency control of interconnected electric power systems

This article is concerned with modelling, controllability analysis and the design of aggressive robust controllers for interconnected electric power systems. The proposed Load Frequency Control (LFC), relying on methodologies enhanced with integral action and pole clustering, can provide frequency regulation and fast transient response despite the presence of unknown disturbance load application. The inherent saturation constraints are handled by the combination of a controller gain minimisation framework and an anti-windup enhanced controller design which provides stability guarantees, while avoiding frequency and tie-line power oscillations. For this scheme, particular attention should be paid on the modelling and controllability aspects of the power system, where it is shown that due to the singularity of the Laplacian matrix of the network's graph, a reduction of the state vector is necessary. Simulation studies are offered to illustrate the effectiveness of the suggested scheme.

Real-time adjustment of load frequency control based on controllable energy of electric vehicles

The time-varying characteristics of electric vehicle (EV) controllable energy and the rationality of frequency regulation (FR) demand power allocation have significant influences on participating in system FR. Combined with the state transition characteristics of EVs, the calculation models of real-time controllable quantities and real-time controllable energy of EVs are established. Then, considering the dynamic changes of EVs’ controllable energy, the system FR strategy with real-time adjusting scheme of FR coefficients is put forward. Finally, based on the unit participation time contribution, the selecting strategy for individual EVs to participate in FR is proposed. The simulation results show that based on the calculation of EVs’ real-time controllable energy, the proposed load frequency control model with real-time allocation of FR demand power suppresses the frequency deviation effectively, and the private electric car is found to have the most potential for the FR system.

Automatic generation control of a multi-area power system with renewable energy source under deregulated environment: adaptive fuzzy logic-based differential evolution (DE) algorithm

In this paper, an adaptive fuzzy logic-based differential evolution (DE) algorithm is proposed to optimize the gain of proportional–integral–derivative (PID) controllers. Using the proposed controller, the speed regulation parameters are tuned. Here, fuzzy logic is used to generate the controlled range of population set to DE algorithm. So that most favourable offspring population is created and the drawback of conventional DE algorithm is reduced. Using the proposed controller, the approximation errors and the external disturbance effects are minimized. The proposed method is implemented in MATLAB/Simulink working platform and the effectiveness is verified by multi-source two-area power generation system with renewable energy source. Three test cases are used to evaluate the simulation behaviour of proposed method. Simulation results of the tested power systems prove the effectiveness of the proposed load frequency control and proved its superiority over traditional PID controller, DE-tuned PID controller and fuzzy logic—DE algorithm-based PID controller. Comparison results show that proposed method has less overshoot, undershoot and fast settling time.

Differential Evolution Algorithm Optimized Dual Mode Load Frequency Controller for Isolated Wind-Diesel Power System with SMES & Fuel Cell

Background: This paper presents dynamic performance analysis of isolated wind-diesel power system. A dual mode controller is proposed for pitch control of wind turbine generator. Methods: The parameters of the controller are optimized by Differential Evolution (DE) algorithm. The hybrid model was simulated with the proposed load frequency controller (LFC) by considering step load perturbation. The minimization of time multiplied integral of absolute error is considered as the objective function. The performance of the proposed controller is compared with the published result of the optimal controller. Further, the performance of the system is investigated by incorporating Super Conducting Magnetic Energy Storage (SMES) and Fuel Cell (FC). Also, the dynamic performance is investigated for changing step load perturbations. Furthermore, the response of the system is analyzed towards random loading. Results: Finally, sensitivity analysis is done by varying the system parameters and operating conditions from their nominal values. Conclusion: The simulation results show that the proposed dual mode DE optimized controller gives better transient and steady state response.

Load frequency control for mini-hydropower system: A new approach based on self-tuning fuzzy proportional-derivative scheme

This paper presents a new method for load frequency control (LFC) based on self-tuning fuzzy Proportional-Derivative method. Under dynamic frequency variations, the proportional-derivative (PD) gains will automatically tuned by the fuzzy rules in order to maintain frequency at nominal value. In this paper, the proposed controller was used to controls the frequency of a high-penetration mini-hydropower system. In the microgrid, both diesel generator and mini-hydropower system were designed to meet the demand at low stream flow. However, the diesel generator will be shut down if hydropower generation surpasses the consumer demand. The frequency was controlled by absorbing excess generation from hydropower system through secondary load bank. The system performance with the new control scheme was assessed by simulation under dynamic frequency variations. The simulation result shows the employment of the proposed load frequency controller demonstrates robust and high-performance frequency control compared to conventional fixed-gain PD controller.

Load frequency control in multiple microgrids based on model predictive control with communication delay

The time delay caused by the communication network will influence the load frequency control (LFC) of the power system including multiple microgrids. A multi-area power system consisting of multiple standard microgrids connected with tie lines is built in this study. Then the LFC equivalent model is constructed based on the proposed system considering the time delay. After that, a coordinated controller based on the model predictive algorithm is designed to deal with the load disturbances and the fluctuation of the wind power with communication delays in the LFC model. Case studies based on a multiple delays LFC system demonstrate the effectiveness of the proposed load frequency controller comparing with the conventional proportional integral load frequency controller.

Robust Load Frequency Control with Dynamic Demand Response for Deregulated Power Systems Considering Communication Delays

Communication networks are used in load frequency control (LFC) for transmitting remote measurements and control commands, and in demand side response (DSR) for aggregating small-scale controllable loads. This paper investigates modeling and controller design for LFC together DSR in a deregulated environment, considering multiple time delays introduced by the usage of communication channels. Time delay model of the deregulated multi-area LFC with dynamic demand control (DDC) is obtained at first, in which a typical thermostatically controlled appliance, air conditioner, is used for DDC. A robust proportional integral derivative (PID) load frequency controller is designed, through the H∞ performance analysis and the particle swarm optimization (PSO) searching algorithm, to deal with the load disturbances and multiple delays in the LFC loop and the DDC loop. Case studies based on a three-area deregulated LFC system demonstrate the effectiveness of the proposed load frequency controller and the performance improvement from the DDC. Simulation results show that the DDC can increase the delay margin of the LFC scheme. Moreover, several delay stable regions are revealed via simulation method.