Decentralized Optimal Control With Application In Power System

An output-feedback decentralized optimal controller is proposed for power systems with renewable energy penetration. Renewable energy source is modeled similar to the classical generator model and is equipped with the unified power flow controller (UPFC). The transient performance of power system is considered and stability of the dynamical states are investigated. An offline decentralized optimal controller is designed that utilizes only the local states. The network comprises conventional synchronous generators as well as renewable sources with inverter equipped with UPFC. Subsequently, the optimal decentralized controller is compared to the initial stabilizing controller used to obtain the optimal controller. An online decentralized optimal controller is designed for discrete-time system. Two neuro networks are utilized to estimate value function and optimal control strategy. Furthermore, a novel observer-based decentralized optimal controller is developed on small scale discrete-time power system. The system is trained followed by least square rules and successive approximation. Simulation results on IEEE 14-, 30-, and 118-bus power system benchmarks shows satisfactory performance of the online decentralized controller. And also, simulation results demonstrate great performance of the observer and the optimal controller compare to the centralized optimal controller

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

Voltage Stability Assessment and Enhancement in Power Systems

Voltage stability is a long standing issue in power systems and also is critical in the power system. This thesis aims to address the voltage stability problems. When wind generators reach maximum reactive power output, the bus voltage will operate near its steady-state stability limit. In order to avoid voltage instability, a dynamic L-index minimization approach is proposed by incorporating both wind generators and other reactive power resources. It then verifies the proposed voltage stability enhancement method using real data from load and wind generation in the IEEE 14 bus system. Additionally, power system is not necessary to always operate at the most voltage stable point as it requires high control efforts. Thus, we propose a novel L-index sensitivity based control algorithm using full Phasor measurement unit measurements for voltage stability enhancement. The proposed method uses both outputs of wind generators and additional reactive power compensators as control variables. The L-index sensitivity with respect to control variables is introduced. Based on these sensitivities, the control algorithm can minimise all the control efforts, while satisfying the predetermined L-index value. Additionally, a subsection control scheme is applied where both normal condition and weak condition are taken into account. It consists of the proposed L-index sensitivities based control algorithm and an overall L-index minimisation method. Threshold selection for the subsection control scheme is discussed and extreme learning machine is introduced for status fast classification to choose the method which has less power cost on the transmission line. Due to the high cost of PMUs, a voltage stability assessment method using partial Phasor measurement unit (PMU) measurements is proposed. Firstly, a new optimisation formulation is proposed that minimizes the number of PMUs considering the most sensitive buses. Then, extreme learning machine (ELM) is used for fast voltage estimation. In this way, the voltages at buses without PMUs can be rapidly obtained based on the PMUs measurements. Finally, voltage stability can be assessed by using L-index

Optimal energy management and control of microgrids in modern electrical power systems

Microgrids (MGs) are becoming more popular in modern electric power systems owing to their reliability, efficiency, and simplicity. The proportional-integral (PI) based droop control mechanism has been widely used in the MG control domain as the setpoint generator for the primary controller which has several drawbacks. In order to mitigate these issues, and to enhance the transient and steady-state operations in islanded MGs, advanced control and intelligent optimization methodologies are presented in this dissertation. First, to improve the existing PI-based droop relationship in DCMGs, a multi-objective optimization (MOO) based optimal droop coefficient computation method is proposed. Considering the system voltage regulation, system total loss minimization, and enhanced current sharing among the distributed generators (DGs), the Pareto optimal front is obtained using the Elitist non dominated sorting genetic algorithm (NSGA II). Then, a fuzzy membership function approach is introduced to extract the best compromise solution from the Pareto optimal front. The drawbacks of PI-based droop control cannot be entirely mitigated by tuning the droop gains. Hence, a droop free, approximate optimal feedback control strategy is proposed to optimally control DGs in islanded DCMGs. Further, to gain the fully optimal behavior, and to mitigate constant power load (CPL) instabilities, a decentralized optimal feedback control strategy is also introduced for the active loads (ALs) in the MG. In both algorithms, the approximate dynamic programming (ADP) method is employed to solve the constrained input infinite horizon optimal control problem by successive approximation of the value function via a linear in the parameter (LIP) neural network (NN). The NN weights are updated online by a concurrent reinforcement learning (RL) based tuning algorithm, and the convergence of the unknown weights to a neighborhood of the optimal weights is guaranteed without the persistence of excitation (PE). Finally, a local optimal control strategy is presented to path optimization of islanded ACMGs to enhance the transient operations while mitigating the voltage and frequency deviations caused by the traditional droop control. Optimal state and control transient trajectories in the d-q reference frame are obtained by Pontryagin's minimum principle which drives each DG from a given initial condition to their steady-state manifold. Both simulation and experimental results are presented to validate the concepts

Utilizing Converter-Interfaced Sources for Frequency Control with Guaranteed Performance in Power Systems

To integrate renewable energy, converter-interfaced sources (CISs) keep penetrating into power systems and degrade the grid frequency response. Control synthesis towards guaranteed performance is a challenging task. Meanwhile, the potentials of highly controllable converters are far from fully developed. With properly designed controllers the CISs can not only eliminate the negative impacts on the grid, but also provide performance guarantees.First, the wind turbine generator (WTG) is chosen to represent the CISs. An augmented system frequency response (ASFR) model is derived, including the system frequency response model and a reduced-order model of the WTG representing the supportive active power due to the supplementary inputs.Second, the framework for safety verification is introduced. A new concept, region of safety (ROS), is proposed, and the safe switching principle is provided. Two different approaches are proposed to estimate the largest ROS, which can be solved using the sum of squares programming.Third, the critical switching instants for adequate frequency response are obtained through the study of the ASFR model. A safe switching window is discovered, and a safe speed recovery strategy is proposed to ensure the safety of the second frequency dip due to the WTG speed recovery.Fourth, an adaptive safety supervisory control (SSC) is proposed with a two-loop configuration, where the supervisor is scheduled with respect to the varying renewable penetration level. For small-scale system, a decentralized fashion of the SSC is proposed under rational approximations and verified on the IEEE 39-bus system.Fifth, a two-level control diagram is proposed so that the frequency of a microgrid satisfies the temporal logic specifications (TLSs). The controller is configured into a scheduling level and a triggering level. The satisfaction of TLSs will be guaranteed by the scheduling level, and triggering level will determine the activation instant.Finally, a novel model reference control based synthetic inertia emulation strategy is proposed. This novel control strategy ensures precise emulated inertia by the WTGs as opposed to the trial and error procedure of conventional methods. Safety bounds can be easily derived based on the reference model under the worst-case scenario

Modellierung und verteilte Regelung dezentraler Energieerzeuger: ein MIMO-Ansatz

The ongoing increase of inverter-interfaced distributed energy generation based on renewable energy sources is notably changing the structure of modern power systems. Particularly in low-voltage grids, the large-scale implementation of droop-controlled distributed generation gives rise to stability issues, given the dynamic response of the power inverters and the complex coupling that arises from the inductive and resistive behavior of the power lines. This work focuses on the analysis of the small-signal stability of a low-voltage grid with distributed generation and on the design of a proper control law that assures stability independently from the chosen power droops. After a detailed introduction on the fundamentals of the operation of a low-voltage grid with distributed generation, appropriate models are introduced for the power inverters and the grid to which they are connected, followed by a discussion on their dynamics and the limits to which these models are subject. The implementation of a so-called improved droop controller on a single inverter is proposed and studied in depth, which modifies the dynamics with which a power inverter operates. The damping and stabilizing capabilities of the improved droop controller are studied at full length with the help of graphical control tools such as root-locus, Bode, and Nyquist diagrams. From this analysis, three systematical design methods are derived, which allow for the tuning of the improved droop controller in a way that enough damping can be guaranteed. Subsequently, the analysis is extended to a grid with several inverters. Although the tuning of a group of inverters is traditionally done disregarding their coupling, this work considers a low voltage grid as a whole, explicitly contemplating the interaction between power inverters. Accordingly, two methods to tune the improved droop controller for a given group of inverters are derived. Finally, a reduced-order model of the grid is derived, which captures the most significant aspects of the dynamic behavior of a low-voltage grid with distributed generation. Laboratory small-scale experiments are included to show the performance and the limits of the proposed approach.Die Struktur moderner Energiesysteme hat sich durch das laufende Wachstum der umrichterbasierten dezentralen Energieerzeugung auf Basis erneuerbarer Energiequellen enorm geändert. Besonders in Niederspannungsnetzen führt der großflächige Einsatz von verteilten Erzeugungsanlagen führt zu Stabilitätsproblemen, denn die Dynamik der Wechselrichter und die durch das ohmsche und induktive Verhalten der Stromleitungen komplexe Verkopplung können zu ungedämpften Schwingungen führen. Diese Arbeit setzt den Schwerpunkt auf die Analyse der Kleinsignalstabilität eines Niederspannungsnetzes mit dezentraler Erzeugung und auf die Auslegung eines geeigneten Regelgesetzes, das Stabilität gewährleisten kann. Nach einer detaillierten Einführung in die Arbeitsweise eines Niederspannungsnetzes mit dezentraler Erzeugung werden geeignete Umrichter- und Netzmodelle eingeführt. Darauf folgt eine Diskussion des dynamischen Verhaltens dieser Modelle und deren Grenzen. Als Regler wird ein so genannter improved-droop Regler vorgeschlagen, der als PDT-Regler auf die Wirkleistungsstatikkennlinie des Umrichters wirkt. Das Dämpfungs- und Stabilisierungsvermögen des PDT-Reglers werden in vollem Umfang mit Hilfe von Wurzelortskurven, Bode- und Nyquist-Diagramme untersucht. Aus dieser Analyse werden drei Design-Methoden abgeleitet, die die systematische Auslegung des Reglers ermöglichen. Anschließend wird die Analyse auf ein Niederspannungsnetz mit mehreren dezentralen Umrichtern erweitert. Im Gegensatz zur traditionellen entkoppelten Reglerauslegung mehrerer Umrichter wird in dieser Arbeit deren Kopplung explizit betrachtet. Zwei solcher Verfahren zur Auslegung der PDT-Regler jeder Umrichter werden entsprechend entworfen. Schließlich wird ein Modell reduzierter Ordnung hergeleitet, das die wesentlichen Aspekte des dynamischen Verhaltens eines Niederspannungsnetzes mit dezentraler Erzeugung nachbildet. Die Leistungsfähigkeit und die Grenzen der vorgeschlagenen Ansätze werden mittels Laborversuchen demonstriert

Distributed multi-phase distribution power flow: modeling, solution algorithm, and simulation results

With the increasing presence of distributed intelligence throughout power distribution systems, the possibilities for distributed control and operation schemes are becoming progressively more attractive and feasible. Distributed operations will require tools to properly assess and predict the present and future status of the system in order to make proper control decisions. Multi-phase distribution power flow is a basic tool which calculates the operating state of the distribution system and is used to support all other applications. Therefore, this thesis will present a new method for calculating distribution power flow using physically remote distributed processors.The proposed power flow requires the distribution system to be partitioned with each partition distributed to a remote processor. Each processor then only requires detailed information about the portion of the network it will represent. Distributed analysis component models for multi-phase distribution systems have been developed to model the remaining network not explicitly retained in each partition. These models are embedded in a new distributed algorithm for multi-phase distribution power flow. Properties of the converged solution of this algorithm have been investigated and will be reported. A distributed processor test bed was designed to emulate the distribution of intelligent devices throughout power distribution networks and simulations were conducted to asses the proposed algorithm. Results have shown the proposed method will converge to the same solution as that of an un-partitioned traditional power flow validating the accuracy of the proposed models and algorithm.M.S., Electrical Engineering -- Drexel University, 200

Microgrids

Microgrids are a growing segment of the energy industry, representing a paradigm shift from centralized structures toward more localized, autonomous, dynamic, and bi-directional energy networks, especially in cities and communities. The ability to isolate from the larger grid makes microgrids resilient, while their capability of forming scalable energy clusters permits the delivery of services that make the grid more sustainable and competitive. Through an optimal design and management process, microgrids could also provide efficient, low-cost, clean energy and help to improve the operation and stability of regional energy systems. This book covers these promising and dynamic areas of research and development and gathers contributions on different aspects of microgrids in an aim to impart higher degrees of sustainability and resilience to energy systems