New Analysis Framework for Transient Stability Evaluation of DC Microgrids

Because of the low inertia of dc microgrids, system state variables are easily changed acutely after being disturbed. Hence, dc microgrids meet the serious transient stability issues especially for some stressed states. But the transient stability analysis is a very challenging problem since the dc microgrid system is high-order and nonlinear. To offer a new and more effective analysis framework, this paper proposes a nonlinear decoupling method to evaluate the transient stability of dc microgrids. The proposed nonlinear decoupling method takes full consideration of the nonlinearity of the dc microgrid system and approximately transforms the original nonlinear system into a series of decoupled first-order quadratic or second-order quadratic systems. For these decoupled low-order quadratic systems, their dynamics and stability can be analyzed easily, then the transient stability of the original system can be reflected indirectly. Also, the nonlinear decoupling based analysis framework can be extended to other power electronics dominated power systems to evaluate their transient stability. The accuracy of the proposed analysis method has been validated through related case studies

Destabilizing attack and robust defense for inverter-based microgrids by adversarial deep reinforcement learning

The droop controllers of inverter-based resources (IBRs) can be adjustable by grid operators to facilitate regulation services. Considering the increasing integration of IBRs at power distribution level systems like microgrids, cyber security is becoming a major concern. This paper investigates the data-driven destabilizing attack and robust defense strategy based on adversarial deep reinforcement learning for inverter-based microgrids. Firstly, the full-order high-fidelity model and reduced-order small-signal model of typical inverter-based microgrids are recapitulated. Then the destabilizing attack on the droop control gains is analyzed, which reveals its impact on system small-signal stability. Finally, the attack and defense problems are formulated as Markov decision process (MDP) and adversarial MDP (AMDP). The problems are solved by twin delayed deep deterministic policy gradient (TD3) algorithm to find the least effort attack path of the system and obtain the corresponding robust defense strategy. The simulation studies are conducted in an inverter-based microgrid system with 4 IBRs and IEEE 123-bus system with 10 IBRs to evaluate the proposed method

The Modeling and Advanced Controller Design of Wind, PV and Battery Inverters

Renewable energies such as wind power and solar energy have become alternatives to fossil energy due to the improved energy security and sustainability. This trend leads to the rapid growth of wind and Photovoltaic (PV) farm installations worldwide. Power electronic equipments are commonly employed to interface the renewable energy generation with the grid. The intermittent nature of renewable and the large scale utilization of power electronic devices bring forth numerous challenges to system operation and design. Methods for studying and improving the operation of the interconnection of renewable energy such as wind and PV are proposed in this Ph.D. dissertation.;A multi-objective controller including is proposed for PV inverter to perform voltage flicker suppression, harmonic reduction and unbalance compensation. A novel supervisory control scheme is designed to coordinate PV and battery inverters to provide high quality power to the grid. This proposed control scheme provides a comprehensive solution to both active and reactive power issues caused by the intermittency of PV energy. A novel real-time experimental method for connecting physical PV panel and battery storage is proposed, and the proposed coordinated controller is tested in a Hardware in the Loop (HIL) experimental platform based on Real Time Digital Simulator (RTDS).;This work also explores the operation and controller design of a microgrid consisting of a direct drive wind generator and a battery storage system. A Model Predictive Control (MPC) strategy for the AC-DC-AC converter of wind system is derived and implemented to capture the maximum wind energy as well as provide desired reactive power. The MPC increases the accuracy of maximum wind energy capture as well as minimizes the power oscillations caused by varying wind speed. An advanced supervisory controller is presented and employed to ensure the power balance while regulating the PCC bus voltage within acceptable range in both grid-connected and islanded operation.;The high variability and uncertainty of renewable energies introduces unexpected fast power variation and hence the operation conditions continuously change in distribution networks. A three-layers advanced optimization and intelligent control algorithm for a microgrid with multiple renewable resources is proposed. A Dual Heuristic Programming (DHP) based system control layer is used to ensure the dynamic reliability and voltage stability of the entire microgrid as the system operation condition changes. A local layer maximizes the capability of the Photovoltaic (PV), wind power generators and battery systems, and a Model Predictive Control (MPC) based device layer increases the tracking accuracy of the converter control. The detail design of the proposed SWAPSC scheme are presented and tested on an IEEE 13 node feeder with a PV farm, a wind farm and two battery-based energy storage systems

Technical solutions for low-voltage microgrid concept

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Modeling and stability analysis of an island microgrid

This master thesis is intended to help the CITCEA-UPC research group on the execution of its FlexRed European project solution by covering two chapters. On one hand, a methodology of modeling islanded microgrids is built in order to perform a posterior analysis of their stability. To obtain the model, the inverters working both as Grid-Following and Grid-Forming need to be modeled first. This study takes more interest every day as synchronous generators, which provide inertia to the grid, are being replaced by inverters which have a much faster response but least resilience in front of sudden power changes. On the other hand, a laboratory microgrid is sized according to regulations and some project?s requirements, to be later implemented

DC & Hybrid Micro-Grids

This book is a printed version of the papers published in the Special Issue “DC & Hybrid Microgrids” of Applied Sciences. This Special Issue, co-organized by the University of Pisa, Italy and Østfold University College in Norway, has collected nine papers and the editorial, from 28 submitted, with authors from Asia, North America and Europe. The published articles provide an overview of the most recent research advances in direct current (DC) and hybrid microgrids, exploiting the opportunities offered by the use of renewable energy sources, battery energy storage systems, power converters, innovative control and energy management strategies

EcoBlock: Grid Impacts, Scaling, and Resilience

Widespread deployment of EcoBlocks has the potential to transform today's electricity system into one that is more resilient, flexible, efficient and sustainable. In this vision, the system will consist of self- su cient, renewable-powered, block-scale entities that can deliberately adjust their net power exchange and can optimize performance, maintain stability, support each other, or disconnect entirely from the grid as needed. This report is intended as an independent analysis of the potential relationships, both constructive and adverse, between EcoBlocks and the grid