Advanced Controls Of Cyber Physical Energy Systems

Cyber system is a fairly important component of the energy systems. The network imperfections can significantly reduce the control performance if not be properly treated together with the physical system during the control designs. In the proposed research, the advanced controls of cyber-physical energy systems are explored in depth. The focus of our research is on two typical energy systems including the large-scale smart grid (e.g. wide-area power system) and the smart microgrid (e.g. shipboard power system and inverter-interfaced AC/DC microgrid). In order to proactively reduce the computation and communication burden of the wide-area power systems (WAPSs), an event/self-triggered control method is developed. Besides, a reinforcement learning method is designed to counteract the unavoidable network imperfections of WAPSs such as communication delay and packet dropout with unknown system dynamics. For smart microgrids, various advanced control techniques, e.g., output constrained control, consensus-based control, neuro network and game theory etc., have been successfully applied to improve their physical performance. The proposed control algorithms have been tested through extensive simulations including the real-time simulation, the power-hardware-in-the-loop simulation and on the hardware testbed. Based on the existing work, further research of microgrids will be conducted to develop the improved control algorithms with cyber uncertainties

Stability Analysis Using Fractional-Order PI Controller in a Time-Delayed Single-Area Load Frequency Control System with Demand Response

The current study investigates the stability analysis based on gain and phase margin (GPM) using fractional-order proportional-integral (FOPI) controller in a time-delayed single-area load frequency control (LFC) system with demand response (DR). The DR control loop is introduced into the classical LFC system to improve the frequency deviation. Although the DR enhances the system’s reliability, the excessive use of open communication networks in the control of the LFC results in time delays that make the system unstable. A frequency-domain approach is proposed to compute the time delay that destabilizes the system using GPM values and different parameter values of the FOPI controller. This method converts the equation into an ordinary polynomial with no exponential terms by eliminating the exponential terms from the system’s characteristic equation. The maximum timedelay values at which the system is marginally stable are calculated analytically using the new polynomial. Finally, the verification of the time delays calculated is demonstrated by simulation studies in the Matlab/Simulink environment and the root finder (quasi-polynomial mapping-based root finder, QPmR) algorithm to define the roots of polynomials with exponential terms providing information about their locations

Advanced Modeling, Design, and Control of ac-dc Microgrids

An interconnected dc grid that comprises resistive and constant-power loads (CPLs) that is fed by Photovoltaic (PV) units is studied first. All the sources and CPLs are connected to the grid via dc-dc buck converters. Nonlinear behavior of PV units in addition to the effect of the negative-resistance CPLs can destabilize the dc grid. A decentralized nonlinear model and control are proposed where an adaptive output-feedback controller is employed to stabilize the dc grid with assured stability through Lyapunov stability method while each converter employs only local measurements. Adaptive Neural Networks (NNs) are utilized to overcome the unknown dynamics of the dc-dc converters at Distributed Energy Resources (DERs) and CPLs and those of the interconnected network imposed on the converters. Additionally, the use of the output feedback control makes possible the utilization of other measured signals, in case of loss of main signal, at the converter location and creates measurement redundancy that improves reliability of the dc network. The switching between measurement signals of different types are performed through using the NNs without the need to further tuning. Then, in a small-scale ac grid, PV-based Distributed Generation (DG) units, including dc/dc converters and inverters, are controlled such that mimic a synchronous generator behavior. While other control schemes such as Synchronverters are used to control the inverter frequency and power at a fixed dc link voltage, the proposed approach considers both the dc-link voltage and the inverter ac voltage and frequency regulation. The dc-link capacitor stores kinetic energy similar to the rotor of a synchronous generator, providing inertia and contributes to the system stability. Additionally, a reduced Unified Power Flow Controller (UPFC) structure is proposed to enhance transient stability of small-scale micro grids. The reduced UPFC model exploits dc link of the DG unit to generate appropriate series voltage and inject it to the power line to enhance transient stability. It employs optimal control to ensure that the stability of the system is realized through minimum cost for the system. A neural network is used to approximate the cost function based on the weighted residual method

Delay-robust distributed secondary frequency control for next-generation power systems: Stability analysis and controller synthesis

Power systems worldwide are undergoing major transformation to enable a low-carbon future. These developments require new procedures for advanced control to ensure a stable and efficient system operation. Consensus-based distributed secondary frequency control schemes have the potential to ensure real-time frequency restoration and economic dispatch simultaneously in future power systems with significant contribution of renewable energy sources. However, owing to their distributed nature, these control schemes critically depend on communication between different controlled units. Thus, robustness against communication uncertainty is crucial for their reliable operation. In this work, control design and stability analysis of delay-robust secondary frequency control in next-generation power systems are studied. The main contributions of the present thesis can be summarised as follows: (i) A design procedure for a consensus-based secondary frequency controller in microgrids is proposed that ensures robustness with respect to heterogeneous fast-varying communication delays and simultaneously provides the option to trade off the L2-gain performance against the number of required communication links; (ii) The conditions for robust stability of a consensus-based frequency control scheme applied to a power system model with second-order turbine-governor dynamics in the presence of heterogeneous time-varying communication delays and dynamic communication topology are derived; (iii) The performance of the proposed consensus-based secondary frequency controller is analysed in a detailed model capturing the dynamic behaviour of a real system. The results provide insights to the robustness of the closed-loop system with respect to unmodelled (voltage and higher-order generator) dynamics as well as communication delays

Broadband Methods in Dynamic Analysis and Control of Battery Energy Storage Systems

Battery energy storage systems have become essential in the operation of many modern power-distribution systems, such as dc microgrids, electric ships, and electric aircraft. Energy storage systems often rely on the operation of bidirectional converters to control the power flow. In modern power systems, these bidirectional converters are typically a part of an extensive converter system, a multi-converter system that consists of several electrical converter-based sources and loads. Even though each converter in a multi-converter system is standalone stable, adverse interactions between the interconnected converters can present issues to the system’s performance and stability. Assessing the stability of multi-converter systems is usually challenging, given that the systems are complex, and the dynamics are affected by various operating modes and points. Recent studies have presented methods for assessing the stability of interconnected converters through impedance-based stability criterion. Impedance-based analysis is particularly advantageous for complex multi-converter systems as this method does not require the knowledge of intricate details of the system’s parameters. The method can also facilitate adaptive stabilizing control schemes using reliable and fast identification implementations. However, impedance identification of multi-converter systems is typically challenging due to the coupled nature of the interconnected converters and potential non-linear behavior. Moreover, the bidirectional power flow of battery energy storage systems further complicates the stability assessment. This thesis presents small-signal modeling methods, online stability assessment methods, and adaptive stabilizing control strategies for multi-converter systems that have bidirectional converters. The accuracy of traditional, small-signal-model-based converter control design is enhanced with a procedure that extends a converter’s small-signal model with given load and source dynamics. In addition, frequency response identification methods are used to assess the system stability under varying operating conditions. The presented identification methods offer reliable and quick impedance measurements and stability assessment among several converters. The design aims to minimize the interference on the system, which allows the identification during the system’s regular operation. The stability assessment provides a platform for adaptive stabilizing control methods, and two such techniques are implemented on a bidirectional converter. Several experimental results confirm the effectiveness of the proposed methods

DC Networks on the Distribution Level – New Trend or Vision?

"DC networks on Distribution Level – are they a new trend or a Vision?" That is the question that has focused the efforts of the Working Group the last two years, and whose consideration is summarized in this report. This report represents the first phase evaluation of this topic and is focused primarily on medium (MVDC) and low voltage (LVDC) level applications

Power quality improvement utilizing photovoltaic generation connected to a weak grid

Microgrid research and development in the past decades have been one of the most popular topics. Similarly, the photovoltaic generation has been surging among renewable generation in the past few years, thanks to the availability, affordability, technology maturity of the PV panels and the PV inverter in the general market. Unfortunately, quite often, the PV installations are connected to weak grids and may have been considered as the culprit of poor power quality affecting other loads in particular sensitive loads connected to the same point of common coupling (PCC). This paper is intended to demystify the renewable generation, and turns the negative perception into positive revelation of the superiority of PV generation to the power quality improvement in a microgrid system. The main objective of this work is to develop a control method for the PV inverter so that the power quality at the PCC will be improved under various disturbances. The method is to control the reactive current based on utilizing the grid current to counteract the negative impact of the disturbances. The proposed control method is verified in PSIM platform. Promising results have been obtaine