An Advanced LMI-Based-LQR Design for Load Frequency Control of an Autonomous Hybrid Generation System

Part 13: Energy GenerationInternational audienceThis paper proposes a load frequency control scheme for an autonomous hybrid generation system consisting of wind turbine generator (WTG), diesel engine generator (DEG), fuel cell (FC), aquaelectrolyzer (AE) and battery energy storage system (BESS). In wind power generation systems, operating conditions are changing continually due to wind speed and load changes, having an effect on system frequency. Therefore, a robust controller is required for load frequency control. The control scheme is based on Linear Matrix Inequality (LMI)-Linear Quadratic Regulator (LQR). The control optimization problem is obtained in terms of a system of LMI constraints and matrix equations that are simultaneously solved. The proposed load frequency control scheme with the advanced LMI-based-LQR (ALQR) design is applied for the autonomous hybrid generation system. The effectiveness and robustness of the proposed controller is demonstrated for different load and wind power perturbations. The results suggest superior performance of the proposed ALQR controller against an optimal output state feedback controller. The integrated control could be realized though the web by applying Internet of Things technologies within the future smart grid

Distributed LQR Design for a Class of Large-Scale Multi-Area Power Systems

Load frequency control (LFC) is one of the most challenging problems in multi-area power systems. In this paper, we consider power system formed of distinct control areas with identical dynamics which are interconnected via weak tie-lines. We then formulate a disturbance rejection problem of power-load step variations for the interconnected network system. We follow a top-down method to approximate a centralized linear quadratic regulator (LQR) optimal controller by a distributed scheme. Overall network stability is guaranteed via a stability test applied to a convex combination of Hurwitz matrices, the validity of which leads to stable network operation for a class of network topologies. The efficiency of the proposed distributed load frequency controller is illustrated via simulation studies involving a six-area power system and three interconnection schemes. In the study, apart from the nominal parameters, significant parametric variations have been considered in each area. The obtained results suggest that the proposed approach can be extended to the non-identical case

Advances in Control of Power Electronic Converters

This book proposes a list of contributions in the field of control of power electronics converters for different topologies: DC-DC, DC-AC and AC-DC. It particularly focuses on the use of different advanced control techniques with the aim of improving the performances, flexibility and efficiency in the context of several operation conditions. Sliding mode control, fuzzy logic based control, dead time compensation and optimal linear control are among the techniques developed in the special issue. Simulation and experimental results are provided by the authors to validate the proposed control strategies

Enhacement of microgrid technologies using various algorithms

The electric power systems around the globe are gradually shifting from conventional fossil fuel-based generating units to green renewable energy sources. The motivation behind this change is the environmental and economic concerns. Furthermore, the existing power systems are being overloaded day by day due to the continuously increasing population, which consequently led to the overloading of transformers, transmission, and distribution lines. Despite the overwhelming advantages of renewable energy sources, there are few major issues associated with them. For example, the injection and detachment of DGs into the current power system causes disparity among produced power along with connected load, thus distracting system’s equilibrium and causes unwanted voltage and frequency oscillations and overshoots. These oscillations and overshoots may cause the failure of connected equipment or power system if not properly controlled. The investigation as such challenges to improve the frequency and voltage, the islanded’s power regulation and connected MG under source and load changes, which contain classic and artificial intelligence techniques. Moreover, these techniques are used also for economic analysis. To evaluate the exhibitions of microgrid (MG) operations and sizing economic analysis acts as a significant tool. Optimization method is obligatory for sizing and operating an MG as reasonably as feasible. Diverse optimization advances remain pertained to microgrid to get optimal power flow and management

Optimal Control Design for Multiterminal HVDC

This thesis proposes an optimal-control based design for distributed frequency control in multi-terminal high voltage direct current (MTDC) systems. The current power grid has become overstressed by rapid growth in the demand for electric power and penetration of renewable energy. To address these challenges, MTDC technology has been developed, which has the potential to increase the flexibility and reliability of power transmission in the grid. Several control strategies have been proposed to regulate the MTDC system and its interaction with connected AC systems. However, all the existing control strategies are based on proportional and integral (PI) control with predetermined controller structures. The objective of the thesis is to first determine if existing control structures are optimal, and if improved controller structures can be developed.The thesis proposes a general framework to determine the optimal structure for the control system in MTDC transmission through optimal feedback control. The proposed method is validated and demonstrated using an example of frequency control in a MTDC system connecting five AC areas

A Systematic Survey of Control Techniques and Applications: From Autonomous Vehicles to Connected and Automated Vehicles

Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger comfort, transportation efficiency, and energy saving. This survey attempts to provide a comprehensive and thorough overview of the current state of vehicle control technology, focusing on the evolution from vehicle state estimation and trajectory tracking control in AVs at the microscopic level to collaborative control in CAVs at the macroscopic level. First, this review starts with vehicle key state estimation, specifically vehicle sideslip angle, which is the most pivotal state for vehicle trajectory control, to discuss representative approaches. Then, we present symbolic vehicle trajectory tracking control approaches for AVs. On top of that, we further review the collaborative control frameworks for CAVs and corresponding applications. Finally, this survey concludes with a discussion of future research directions and the challenges. This survey aims to provide a contextualized and in-depth look at state of the art in vehicle control for AVs and CAVs, identifying critical areas of focus and pointing out the potential areas for further exploration

Advances and Trends in Mathematical Modelling, Control and Identification of Vibrating Systems

This book introduces novel results on mathematical modelling, parameter identification, and automatic control for a wide range of applications of mechanical, electric, and mechatronic systems, where undesirable oscillations or vibrations are manifested. The six chapters of the book written by experts from international scientific community cover a wide range of interesting research topics related to: algebraic identification of rotordynamic parameters in rotor-bearing system using finite element models; model predictive control for active automotive suspension systems by means of hydraulic actuators; model-free data-driven-based control for a Voltage Source Converter-based Static Synchronous Compensator to improve the dynamic power grid performance under transient scenarios; an exact elasto-dynamics theory for bending vibrations for a class of flexible structures; motion profile tracking control and vibrating disturbance suppression for quadrotor aerial vehicles using artificial neural networks and particle swarm optimization; and multiple adaptive controllers based on B-Spline artificial neural networks for regulation and attenuation of low frequency oscillations for large-scale power systems. The book is addressed for both academic and industrial researchers and practitioners, as well as for postgraduate and undergraduate engineering students and other experts in a wide variety of disciplines seeking to know more about the advances and trends in mathematical modelling, control and identification of engineering systems in which undesirable oscillations or vibrations could be presented during their operation

Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency