Power System Control Research Articles

Similarity matching method of power distribution system operating data based on neural information retrieval

Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy. Therefore, improvement of the ability of data-driven operation management, intelligent analysis, and mining is urgently required. To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation, maintenance experience, and knowledge by rule and line, a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology. Based on the processing flow of the operating data of the power distribution system, a technical framework of neural information retrieval is established. Combined with the natural graph characteristics of the power distribution system, a unified graph data structure and a data fusion method of data access, data complement, and multi-source data are constructed. Further, a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed. The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set. The model is verified on the operating section of the power distribution system of a provincial grid area. The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.

Fault Analysis of a Small PV/Wind Farm Hybrid System Connected to the Grid

The dynamic modeling, control, and simulation of renewable energy sources connected to the electrical grid are investigated in this study. Photovoltaic (PV) systems and wind systems connected to the power grid via the point of common connection (PCC) were the only two systems included in our study. Simulation and control methodologies are provided. For both PV arrays, the method of extracting maximum power point tracking (MPPT) is utilized to obtain the highest power under standard test conditions (STC: 1000 W/m2, 25 °C). A power electronics converter that can transform DC voltage into three-phase AC voltage is required to connect a PV system to the grid. Insulated gate bipolar transistors (IGBTs) are utilized in a three-level voltage source converter (VSC). The distribution network is connected to this three-phase VSC by way of a step-up transformer and filter. During synchronous rotation in the d−q reference frame, the suggested control for the three-level solar power system that is connected to the grid is constructed. To obtain a power factor as near to one as possible, the phase-locked loop (PLL) is employed to align the angle of the power grid voltage with the angle of the current coming from the inverter. Squirrel-cage induction generators (SCIGs), which are utilized as fixed speed generators and are linked directly to the power network, are the foundation of the wind system. Additionally, a pitch angle control approach is suggested to keep the wind turbine’s rotor speed stable. MATLAB/Simulink software is utilized to model and simulate the suggested hybrid system. Under fault scenarios such as the line to line to line to ground fault (LLLG fault), the suggested hybrid system’s dynamic performance is examined. The simulation results prove the ability to manage the small hybrid system that combines solar and wind power, as well as its dynamic performance.

CPSOGSA Optimization Algorithm Driven Cascaded 3DOF-FOPID-FOPI Controller for Load Frequency Control of DFIG-Containing Interconnected Power System

This paper proposes a new cascaded fractional-order controller (CC-FOC) to solve the load frequency control (LFC) problem of an interconnected power system. The CC-FOC consists of a three-degree-of-freedom fractional-order proportional-integral-differential (3DOF-FOPID) controller and a fractional-order proportional-integral (FOPI) controller. Each area of the two-area interconnected power system in this study consists of a thermal unit, a hydro unit, a diesel unit, and a doubly-fed induction generator (DFIG). The enhanced particle swarm optimization (PSO) and gravitational search algorithm (GSA) under the chaotic map optimization (CPSOGSA) technique are used to optimize the controller gains and parameters to enhance the load frequency control performance of the cascade controller. Moreover, simulation experiments are conducted for the interconnected power system under load perturbation and random wind speed fluctuations. The simulation results demonstrate that the proposed cascaded fractional-order controller outperforms the traditional proportional-integral-differential (PID) controller and three other fractional-order controllers in terms of LFC performance. The suggested cascade controller displays strong dynamic control performance and the resilience of the cascade fractional-order controller by adjusting the load disturbance and analyzing the system characteristics.

Design and Implementation of Real-time Fault Location Experimental System for Teaching and Training University Students

The fault location problem is one of the most important issues in power system operation and control. To obtain an experimental system for teaching and training electrical engineering students, this paper performed a study to design and implement a real-time fault location laboratory-scale model from practical hardware components. The impedance-based fault location method is embedded in the system to determine the distance to fault in the transmission line. Furthermore, the monitoring and controlling program is designed by the Matlab App Designer – A new professional app to create the graphical user interface and use the integrated editor quickly. Several fault types including three-phase fault, phase-to-phase fault, phase-to-ground fault are created to evaluate the performance of the fault location experimental system. The real-time measurement results which are acquired and observed on the user guide interface of the program confirm the effectiveness of the experimental system; therefore, the system can be considered a powerful tool for electrical engineering students.

Hybrid kernel search and particle swarm optimization with Cauchy perturbation for economic emission load dispatch with valve point effect

Due to growing concerns over environmental protection, economic and environmentally responsible power dispatching has become a hot topic in the field of power system control. Multi-objective optimization minimizes fuel costs and pollution emissions without violating operational constraints. To solve this problem, the MOP is decomposed into individual objects via the weighted sum method, and Newton’s method is used to tackle equality constraints iteratively. To this end, a hybrid algorithm (HKSOPSO-CP) based on kernel search optimization (KSO) and particle swarm optimization (PSO) with Cauchy perturbation is proposed in this paper. An experiment with 23 CEC benchmark functions shows that HKSOPSO-CP offers better performance compared with various popular algorithms proposed in recent years. When employed to solve the IEEE standard economic emission dispatch (EED) problems with 6, 10, 40, and 110 units, the proposed HKSOPSO-CP algorithm produces results indicating a better trade-off between the objectives relating to fuel costs and emissions compared to other algorithms that have recently been reported on in the literature.

Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology

This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. Thus, the adaptability of the dynamic stability assessment is achieved. The selected research topic relates to the issue of changing the structure and parameters of modern power systems. The key features of modern power systems include the following: decreased total inertia caused by integration of renewable sources energy, stricter requirements for emergency control accuracy, highly digitized operation and control of power systems, and high volumes of data that describe power system operation. Arranging emergency control in these new conditions is one of the prominent problems in modern power systems. In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. Transient stability of a power system was analyzed as the base function. Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. In the case of the test sample, accuracy of instability classification for XGBoost was 91.5%, while that for Random Forest was 81.6%. The accuracy of algorithms increased by 10.9% and 1.5%, respectively, when the topology of the power system was taken into account.

Special issue on “Optimal design and operation of energy systems”

Special issue on “Optimal design and operation of energy systems”

Proportional-Integral-Derivative Controller Based-Artificial Rabbits Algorithm for Load Frequency Control in Multi-Area Power Systems

A major problem in power systems is achieving a match between the load demand and generation demand, where security, dependability, and quality are critical factors that need to be provided to power producers. This paper proposes a proportional–integral–derivative (PID) controller that is optimally designed using a novel artificial rabbits algorithm (ARA) for load frequency control (LFC) in multi-area power systems (MAPSs) of two-area non-reheat thermal systems. The PID controller incorporates a filter with such a derivative coefficient to reduce the effects of the accompanied noise. In this regard, single objective function is assessed based on time-domain simulation to minimize the integral time-multiplied absolute error (ITAE). The proposed ARA adjusts the PID settings to their best potential considering three dissimilar test cases with different sets of disturbances, and the results from the designed PID controller based on the ARA are compared with various published techniques, including particle swarm optimization (PSO), differential evolution (DE), JAYA optimizer, and self-adaptive multi-population elitist (SAMPE) JAYA. The comparisons show that the PID controller’s design, which is based on the ARA, handles the load frequency regulation in MAPSs for the ITAE minimizations with significant effectiveness and success where the statistical analysis confirms its superiority. Considering the load change in area 1, the proposed ARA can acquire significant percentage improvements in the ITAE values of 1.949%, 3.455%, 2.077% and 1.949%, respectively, with regard to PSO, DE, JAYA and SAMPE-JAYA. Considering the load change in area 2, the proposed ARA can acquire significant percentage improvements in the ITAE values of 7.587%, 8.038%, 3.322% and 2.066%, respectively, with regard to PSO, DE, JAYA and SAMPE-JAYA. Considering simultaneous load changes in areas 1 and 2, the proposed ARA can acquire significant improvements in the ITAE values of 60.89%, 38.13%, 55.29% and 17.97%, respectively, with regard to PSO, DE, JAYA and SAMPE-JAYA.

Innovative Higher Education Approaches for Power System Courses

Higher education plays a crucial role in modern society and in emerging energy systems, due to the rising complexity of the phenomena and the interplay among various layers (physical, cyber, social and economic). To cope with this context, universities need to develop new visions and tools for education and training. Real-time simulation (RTS) is emerging as a novel and effective approach to analyzing power system aspects, and this characteristic can be effectively used in power system courses. Hence, after the presentation of the basics about the RTS, the paper will show the advantages of employing RTS for teaching activities. Finally, two examples of didactic activities involving RTS at Politecnico di Torino will be presented. In fact, RTS is part of both multi-disciplinary projects (where students with different backgrounds can face the issues affecting the protection and control of power systems) and the course “Electrical systems and safety”, where RTS is used to study the behavior of voltage transformers in saturation.

Participation of Renewable Energy Sources in the Frequency Regulation Issues of a Five-Area Hybrid Power System Utilizing a Sine Cosine-Adopted African Vulture Optimization Algorithm

In this article, a novel methodology is proposed by utilizing a technique which, in light of the change in the African vulture optimization known as Sine Cosine, adopted an African vulture optimization algorithm (SCaAVOA)-based tilt integral derivative (TID) regulator for the load frequency control (LFC) of a five-area power system with multi-type generations. At first, the execution of the Sine Cosine-adopted calculation is tried by contrasting it with the standard AVOA calculation while considering different standard benchmark functions. To demonstrate the superiority of the proposed SCaAVOA algorithm, the results are contrasted using different standard approaches. In the next stage, the proposed method is used in a five-area thermal power system and is likewise applied to a five-area, ten-unit system comprising different conventional sources as well as some renewable energy sources. The performance analysis of the planned regulator is completed for various system boundaries and loading conditions. It is seen that the said regulator is more viable in comparison to the other standard controllers.

A Robust Controller Design based on Kharitonov’s Theorem for Frequency Control in an Interconnected Power System

The load frequency control of power systems is often carried out using methods that are dependent on the system load and parameters. Therefore, the controller design is not robust in unforeseen cases such an attack on the power system, variations in system parameters, or changes in load. In such methods, there is a need for an attack detection tool, and moreover, the controller parameters need to be adjusted as the load and power system parameters change. In this paper, Kharitonov's theorem was applied to design a robust decentralized load frequency control for a two-area power system in the presence of electric vehicle fleets as a power source that were targeted by a cyberattack. Furthermore, the robustness of the system against system nonlinearities was demonstrated by testing the efficacy of the controller on both linear and nonlinear systems. The controller design was robust such that there was no need to change the gains of the controller even during an attack. This was compared with the performance of controllers designed using GWO algorithm and fuzzy logic that needed retuning for different case studies with different variations in system parameters, load, or inclusion of a cyberattack to the electric vehicle fleets.

Effective Load Frequency Control of Power System with Two-Degree Freedom Tilt-Integral-Derivative Based on Whale Optimization Algorithm

Nowadays, the operation and control of power systems are a big challenge. An essential part of the power system (PS) control is load frequency control (LFC). Different secondary controllers are implemented for the frequency control problem. Hence, cascaded two-degree freedom and a tilt-integral-derivative controller having a filter (2DOFTIDF) are intended in this paper and implemented for load frequency control. In order to determine the efficiency of the 2DOFTIDF controller, a well-known non-reheat thermal system with/without a governor dead band is considered. A new whale optimization algorithm (WOA) is used to enhance the suggested controller parameters. The predominance of the presented method is exhibited by comparing the consequences with different heuristic techniques tuned to controllers published recently. Further, the simulation results for two test cases indicate that system enactments are enhanced by introducing the suggested controller and are also best suited in the presence of system nonlinearity. Finally, random load fluctuation along with noise and changing the system parameters are also used to determine the reliability of the suggested controller. Compared to the WOA-tuned TIDF controller, the settling time of ΔF1, ΔF2, and ΔPTie is improved by 45.45%, 56.77%, and 20.26%, respectively, with the WOA-tuned 2DOFTIDF controller and by 40%, 48.27%, and 20%, respectively, with the DE-tuned TIDF controller. Experimental validation using the hardware-in-the-loop real-time simulation based on OPAL-RT has been carried out to confirm the viability of the proposed approach.

Load Frequency Control of Single-Area Power System with PI–PD Controller Design for Performance Improvement

Load Frequency Control of Single-Area Power System with PI–PD Controller Design for Performance Improvement

The observability and controllability metrics of power system oscillations and the applications

Power system oscillation has caused many serious accidents in renewable energy grid connection system. The concept of observability and controllability in control theory has been widely applied to power system oscillation study. In this paper, observability metric (OM) and controllability metric (CM) are defined from the perspective of oscillation modes, acting as a novel quantification method to quantify the observability and controllability of power system with distinct or repeated eigenvalues. Furthermore, in order to compare the reflection degree and control effect of signals in different oscillation modes, the mode comprehensive observability metric (MCOM) and comprehensive controllability metric (MCCM) are proposed. The proposed method shows clearer relationship between controllability/observability and oscillation modes by combining the information of conjugate eigenvalues together. The advantages of metrics are illustrated by comparing with theoretical derivations and calculation results of three traditional methods: participation factor, residue method and geometric measures. Finally, the metrics are applied to a subsynchronous damping controller (SSDC) design for better performance in oscillation monitoring and suppression. With the small-signal model and corresponding time-domain simulation, the effectiveness of the proposed method is verified.

Contribution of the thermal inertia of trains to the primary frequency control of electric power systems

There is a wide consensus about substituting fossil fuel-based electric generation with renewable resource-based one. However, the displacement of conventional power plants with power electronics-interfaced plants implies several technical issues that must be addressed. Among these needs, providing ancillary services to electric power systems is fundamental to maintain power quality and system reliability. There is a considerable amount of literature about providing ancillary services from renewable power plants and an increasingly important effort to complement these services with loads. However, the contribution of railway systems to these services has been less explored. Considering the world-wide expansion of railway systems, it is appropriate to consider them as relevant contributors to ancillary services. The present work presents a novel approach to assess the possibilities of contribution of railways to grid primary frequency control based on the thermal inertia of trains. This approach aims at determining how railways can support frequency control tasks without affecting the circulation time of trains and thermal comfort of passengers. This paper proposes to act on the power consumption of the air conditioning system of trains as the way of making the train whole consumption responsive to frequency deviations. In addition, the paper proposes a methodology for analyzing the effectivity of the approach. It defines the extent of the modeling detail of railway and electric power system, and the coupling between them. To validate the feasibility, its application is illustrated with a case study. The results show that frequency deviations can be reduced without affecting passengers’ thermal comfort.

Distributed resilient multi-event cooperative triggered mechanism based discrete sliding-mode control for wind-integrated power systems under denial of service attacks

In wind-integrated power systems (WIPSs), denial of service (DoS) attacks bring about time delays and packages dropout in system data transmission, it may even deteriorate system performance. In order to maintain the reliability and safety of WIPSs, under the dynamical event triggered framework, a novel distributed resilient multi-event cooperative triggered scheme is derived to decrease the occupation of network channel. Furthermore, considering the random load disturbance of WIPSs and wind speed fluctuation, the resilient triggered scheme based H∞ load frequency sliding-mode control strategy is proposed. Based on Lyapunov stability theory, the controller is obtained by solving linear matrix inequality. Compared with the traditional event triggered mechanism, the proposed distributed resilient multi-event cooperative triggered mechanism based sliding-mode controller provides stronger robustness, higher wind energy capture efficiency for WIPSs under DoS attacks. Meanwhile, the resilient triggered scheme improves the utilization efficiency of network resources. A four-area WIPSs is investigated and the numerical analysis shows the proposed strategy is feasibility and effectiveness.

Stability analysis of load frequency control for power systems with interval time-varying delays

This study investigates the stability problem of load frequency control (LFC) for power systems with interval time-varying delays. The two categories of time delays, the lower bound being zero and non-zero, are considered. The systems can be described as time delay systems of load disturbances. First, an augmented Lyapunov–Krasovskii functional (LKF) is constructed. Some delay-dependent nonintegral terms and single integral terms are additionally introduced to make full use of the information on the system state variables and the time-varying delays. Second, to overcome the problem of nonlinear inequalities caused by the augmented LKF, the nonlinear inequalities are converted into linear matrix inequalities (LMIs) by applying the new negative definite inequality equivalence transformation lemma, which can be solved easily by the MATLAB LMI toolbox. A new stability criterion is presented by applying the Lyapunov stability theory. The stability criterion is less conservative than some existing literature studies, which further improves the stability margin for the power systems based on LFC. Finally, some numerical examples are given to show the effectiveness of the proposed method and the superiority of the results.

Indirect adaptive fuzzy finite time synergetic control for power systems

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults. Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems. Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.

Design of a 2DOF-PID Control Scheme for Frequency/Power Regulation in a Two-Area Power System Using Dragonfly Algorithm with Integral-Based Weighted Goal Objective

The increase in power demand, nonlinearity, complexity, varying structure, and other important causes has necessitated the implementation of artificial intelligent control methodologies for safe and acceptable operation of the electric power systems. Therefore, in this article, an improved two-degrees-of-freedom (2DOF-PID) control scheme is proposed for power/frequency control of a two-area interconnected electric power system. The parameters of the 2-DOF-PID control scheme are optimized using the Dragonfly Algorithm (DA) via a new integral-based weighted goal fitness function (IB-WGFF) (i.e., DF-2DOF-PID-IB-WGFF). The superiority of the suggested scheme is proved by comparing the results obtained using the proposed IB-WGFF with those obtained using the conventional controllers, and the 2DOF-PID controllers optimized using the DA and Genetic Algorithm (GA) via the frequently published performance criterion. To verify the stability, efficacy, and robustness of the proposed control scheme, a load disturbances and parameters perturbations with various percentages are implemented in the controlled system under the same controllers. Finally, verification results proved that the proposed 2DOF-PID optimized using DA via the IB-WGFF is more stable, efficient, and robust than the other controllers recently used in the literature.

Linear Quadratic Differential Games based MIMO-PID design for Load Frequency Control of a 2-area interconnected power system: An Iterative LMI approach

In this paper a Multi-input-Multi-output (MIMO)-Proportional-Integral-Derivative (PID) control design method via sub-optimal solution of Linear Quadratic Differential Games (LQDG) for Load frequency Control (LFC) of a 2-area interconnected power system is proposed. The main motivation behind the proposed centralised LFC design scheme is to solve multi-objective optimization problem that can accomplish improvement in transient response & disturbance rejection simultaneously. The proposed iterative optimization algorithm in Linear matrix Inequality (LMI) framework yields appropriate sub-optimal PID gains. A 2-area LFC problem is solved using the proposed design and comparative results suggests that the proposed design can significantly attenuate the load disturbances as well as provide improved transient response specifications.