Ultimate boundedness of droop controlled Microgrids with secondary loops

In this paper we study theoretical properties of inverter-based microgrids controlled via primary and secondary loops. Stability of these microgrids has been the subject of a number of recent studies. Conventional approaches based on standard hierarchical control rely on time-scale separation between primary and secondary control loops to show local stability of equilibria. In this paper we show that (i) frequency regulation can be ensured without assuming time-scale separation and, (ii) ultimate boundedness of the trajectories starting inside a region of the state space can be guaranteed under a condition on the inverters power injection errors. The trajectory ultimate bound can be computed by simple iterations of a nonlinear mapping and provides a certificate of the overall performance of the controlled microgrid.Comment: 8 pages, 1 figur

Robust Decentralized Secondary Frequency Control in Power Systems: Merits and Trade-Offs

Frequency restoration in power systems is conventionally performed by broadcasting a centralized signal to local controllers. As a result of the energy transition, technological advances, and the scientific interest in distributed control and optimization methods, a plethora of distributed frequency control strategies have been proposed recently that rely on communication amongst local controllers. In this paper we propose a fully decentralized leaky integral controller for frequency restoration that is derived from a classic lag element. We study steady-state, asymptotic optimality, nominal stability, input-to-state stability, noise rejection, transient performance, and robustness properties of this controller in closed loop with a nonlinear and multivariable power system model. We demonstrate that the leaky integral controller can strike an acceptable trade-off between performance and robustness as well as between asymptotic disturbance rejection and transient convergence rate by tuning its DC gain and time constant. We compare our findings to conventional decentralized integral control and distributed-averaging-based integral control in theory and simulations

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

Modélisation et contrôle de systèmes électriques de puissance avec propriétés de stabilité

To deal with nonlinear, large scale, multidomain, systems, as power systems are, we have witnessed in the last few years an increasing interest in energy–based modeling, analysis and controller design techniques. Energy is one of the fundamental concepts in science and engineering practice, where it is common to view dynamical systems as energy-transformation devices. This perspective is particularly useful in studying complex nonlinear systems by decomposing them into simpler subsystems which, upon interconnection, add up their energies to determine the full systems behavior. This is obviously the most natural and intuitive language to represent power systems. In particular, the use of port–Hamiltonian (pH) systems has been already proven highly successful in many applications, namely for mechanical, electrical and electromechanical systems. The port-Hamiltonian systems paradigm theremore provides a solid foundation, which suggests new ways to look at power systems analysis and control problems.Based on this framework, this thesis is structured in three main steps.1 - Modelling of a generalized class of electric power systems, based on graph theory and port-Hamiltonian representation of the individual components.2 - Modelling, analysis and control of multiterminal hvdc transmission systems. With the intention to bridge the gap between theory and applications, one of the main concerns is to establish connections between existing engineering solutions, usually derived via ad hoc considerations, and the solutions stemming from theoretical analysis.3 - Additional contributions of the author in other fields of electric power systems, including traditional ac power systems an microgrids.Pour traiter les systèmes non linéaires, à grande échelle, multi-domaine tels que les systèmes électriques de puissance, nous avons remarqué dans les dernières années un intérêt croissant pour les techniques de modélisation, analyse et contrôle basées sur la notion d'énergie. L'énergie est en fait un concept fondamental en science et en ingénierie, où typiquement les systèmes dynamiques sont regardés comme des dispositifs de transformation d'énergie. Cette perspective est particulièrement utile pour étudier des systèmes non linéaires assez complexes, qui peuvent être décomposés en sous-systèmes plus simples, caractérisés au niveau énergétique, et qui, à travers leurs interconnexions, déterminent le comportement global du système tout entier. Il représente bien évidemment le langage le plus naturel et intuitif pour représenter les systèmes électriques de puissance. En particulier, l'utilisation de systèmes Hamiltoniens à Ports a eu un impact très fort dans différentes applications, plus précisément dans le cas de systèmes mécaniques, électriques et électromécaniques. Dans ce contexte alors, l'approche Hamiltonien à Ports représentent sans doute une base solide qui montre une nouvelle fac{c}on d'aborder les problèmes d'analyse et contrôle de systèmes électriques de puissance. Basée sur cette approche, la thèse est structurée en trois étapes fondamentales:1 - Modélisation d'une classe très générale de systèmes électriques de puissance, basée sur la théorie des graphes et la formulation en Systèmes Hamiltoniens à Ports des composantes.2 - Modélisation, analyse et commande de systèmes de transmission de courant continu haute tension. Avec l'intention de construire un pont entre la théorie et les éventuelles applications, un des objectifs fondamentaux consiste à établir des relations évidentes entre les solutions adoptées dans la pratique et les solutions obtenues à travers une analyse mathématique précise.3 - Travaux apparentés de l'auteur, dans différents domaines des systèmes électriques de puissance: systèmes ac conventionnels et micro réseaux

Distributed Control and State Estimation of DC Microgrids Based on Constrained Communication Networks.

PhD ThesesThe intermittent nature of renewable energy sources (RES) such as wind turbines and photovoltaic panels, requires advanced control systems to provide the balance between energy supply and demand in any power system. For better management of power quality and security issues, energy storage systems (ESSs) are deployed to compensate for the temporary mismatch of supply and demand. Furthermore, in rural areas with no connection to the main grid, ESSs such as batteries are deployed in large quantities as a solution for temporary power stabilization during RES unavailability. However, the control complexity of the power system increases as more ESSs are getting installed due to the need for coordination of the power transfer among them. This thesis undertakes a thorough analysis of distributed control and state estimation designs for direct current (DC) microgrids with ESSs based on constrained communication networks. The developed distributed control and estimation strategies are designed for operation over constrained communication networks. They don't require a central coordinator for synchronization of the control tasks between the ESSs. This forms a multi-agent environment where the controllers cooperatively achieve the DC microgrid objectives, i.e. voltage stabilization, proportional power-sharing, and balancing of ESSs' energy level. To overcome the communication network constraints, event-based controllers and estimators are designed, which e ectively reduce the network tra c and as a result, provide higher throughput with reduced delays for the real-time control loops of the DC microgrids. The controllers are designed to be distributed, leading to use cases such as autonomous islanded microgrids, smart villages, and plug-and-play mobile microgrids. The feasibility and performance of the proposed control and estimation strategies are con rmed in several experimental test benches by showing the higher reliability and robustness in the delivered power quality. The results have shown considerable reduction in the network tra c, meanwhile the control system provided high performance in terms of stability, robustness, power quality and endurabilit

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

Emerging Technologies for the Energy Systems of the Future

Energy systems are transiting from conventional energy systems to modernized and smart energy systems. This Special Issue covers new advances in the emerging technologies for modern energy systems from both technical and management perspectives. In modern energy systems, an integrated and systematic view of different energy systems, from local energy systems and islands to national and multi-national energy hubs, is important. From the customer perspective, a modern energy system is required to have more intelligent appliances and smart customer services. In addition, customers require the provision of more useful information and control options. Another challenge for the energy systems of the future is the increased penetration of renewable energy sources. Hence, new operation and planning tools are required for hosting renewable energy sources as much as possible