Quantitative Stability Conditions for Grid-Forming Converters With Complex Droop Control

In this paper, we study analytically the transient stability of grid-connected distributed generation systems with grid-forming (GFM) complex droop control, also known as dispatchable virtual oscillator control (dVOC). We prove theoretically that complex droop control, as a state-of-the-art GFM control, always possesses steady-state equilibria whereas classical droop control does not. We provide quantitative conditions for complex droop control maintaining transient stability (global asymptotic stability) under grid disturbances, which is beyond the well-established local (non-global) stability for classical droop control. For the transient instability of complex droop control, we reveal that the unstable trajectories are bounded, manifesting as limit cycle oscillations. Moreover, we extend our stability results from second-order GFM control dynamics to full-order system dynamics that additionally encompass both circuit electromagnetic transients and inner-loop dynamics. Our theoretical results contribute an insightful understanding of the transient stability and instability of complex droop control and offer practical guidelines for parameter tuning and stability guarantees

Microgrids/Nanogrids Implementation, Planning, and Operation

Today’s power system is facing the challenges of increasing global demand for electricity, high-reliability requirements, the need for clean energy and environmental protection, and planning restrictions. To move towards a green and smart electric power system, centralized generation facilities are being transformed into smaller and more distributed ones. As a result, the microgrid concept is emerging, where a microgrid can operate as a single controllable system and can be viewed as a group of distributed energy loads and resources, which can include many renewable energy sources and energy storage systems. The energy management of a large number of distributed energy resources is required for the reliable operation of the microgrid. Microgrids and nanogrids can allow for better integration of distributed energy storage capacity and renewable energy sources into the power grid, therefore increasing its efficiency and resilience to natural and technical disruptive events. Microgrid networking with optimal energy management will lead to a sort of smart grid with numerous benefits such as reduced cost and enhanced reliability and resiliency. They include small-scale renewable energy harvesters and fixed energy storage units typically installed in commercial and residential buildings. In this challenging context, the objective of this book is to address and disseminate state-of-the-art research and development results on the implementation, planning, and operation of microgrids/nanogrids, where energy management is one of the core issues

Optimal parameters of inverter-based microgrid to improve transient response

The inertia issues in a microgrid can be improved by modifying the inverter control strategies to represent a virtual inertia simulation. This method employs the droop control strategy commonly used to share the power of a load among different power sources in the microgrid. This paper utilizes a modified droop control that represents this virtual inertia and applies an optimization algorithm to determine the optimal parameters and improve transient response. The results show better control when different variations are presented in the loads, leading the microgrid to have a better control of the operation. The optimization method applied in this research allows improvement to the transient response, thus avoiding unnecessary blackouts in the microgrid

Overview of Technical Challenges, Available Technologies and Ongoing Developments of AC/DC Microgrids

Gradual depletion of fossil fuel resources, poor energy efficiency of conventional power plants, and environmental pollution have led to a new grid architecture known as smart microgrid. The smart microgrid concept provides a promising solution that enables high penetration of distributed generation from renewable energy sources without requiring to redesign the distribution system, which results in stable operation during faults and disturbances. However, distributed generators/loads and interaction between all nodes within a microgrid will substantially increase the complexity of the power system operation, control, and communications. Many innovative techniques and technologies have been proposed to address the complexity and challenges of microgrids including power quality, power flow balancing, real‐time power management, voltage and frequency control, load sharing during islanding, protection, stability, reliability, efficiency, and economical operation. All key issues of the microgrids, different solutions, and available methods and technologies to address such issues are reviewed in this chapter. Pros and cons of each method are discussed. Furthermore, an extensive comprehensive review for researchers and scholars working on microgrid applications is provided in this chapter to help them identify the areas that need improvements and innovative solutions for increasing the efficiency of modern power distribution grid

Network Synchronization and Control Based on Inverse Optimality : A Study of Inverter-Based Power Generation

This thesis dwells upon the synthesis of system-theoretical tools to understand and control the behavior of nonlinear networked systems. This work is at the crossroads of three topics: synchronization in coupled high-order oscillators, inverse optimal control and the application of inverter-based power systems. The control and stability of power systems leverages the theoretical results obtained for synchronization in coupled high-order oscillators and inverse optimal control.First, we study the dynamics of coupled high-order nonlinear oscillators. These are characterized by their rotational invariance, meaning that their dynamics remain unchanged following a static shift of their angles. We provide sufficient conditions for local frequency synchronization based on both direct, indirect Lyapunov methods and center manifold theory. Second, we study inverse optimal control problems, embedded in networked settings. In this framework, we depart from a given stabilizing control law, with an associated control Lyapunov function and reverse engineer the cost functional to guarantee the optimality of the controller. In this way, inverse optimal control generates a whole family of optimal controllers corresponding to different cost functions. This provides analytically explicit and numerically feasible solutions in closed-form. This approach circumvents the complexity of solving partial differential equations descending from dynamic programming and Bellman's principle of optimality. We show this to be the case also in the presence of disturbances in the dynamics and the cost. In networks, the controller obtained from inverse optimal control has a topological structure (e.g., it is distributed) and thus feasible for implementation. The tuning is analogous to that of linear quadratic regulators.Third, motivated by the pressing changes witnessed by the electrical grid toward renewable energy generation, we consider power system stability and control as the main application of this thesis. In particular, we apply our theoretical findings to study a network of power electronic inverters. We first propose a controller we term the matching controller, a control strategy that, based on DC voltage measurements, endows the inverters with an oscillatory behavior at a common desired frequency. In closed-loop with the matching control, inverters can be considered as nonlinear oscillators. Our study of the dynamics of nonlinear oscillator network provides feasible physical conditions that ask for damping on DC- and AC-side of each converter, that are sufficient for system-wide frequency synchronization.Furthermore, we showcase the usefulness of inverse optimal control for inverter-based generation at two different settings to synthesize robust angle controllers with respect to common disturbances in the grid and provable stability guarantees. All the controllers proposed in this thesis, provide the electrical grid with important services, namely power support whenever needed, as well as power sharing among all inverters

Robust adaptive nonlinear control of microgrid frequency and voltage in the presence of renewable energy sources

Global warming of the planet and air pollution have prompted an increased use of renewable energy sources for power generation. These new sources of clean energy are now very much in demand for setting up microgrids that provide energy independence to communities far from major urban centers. These microgrids should be able to operate either in isolated mode or to be connected to the main power grid. These requirements pose significant challenges. Indeed, in isolated mode, small and medium power grids are very sensitive to fluctuations in consumer power use as well as changes in the power produced by generators. In gridconnected mode, renewable energy sources do not contribute to the grid's stability and robustness as well as conventional generators do. Photovoltaic power plants pose some challenges when integrated with the power grid. The PV plants always focus on extracting the maximum power from the arrays. This makes the PV system unavailable for helping in regulating the grid frequency as compared to conventional generators. One of the main objectives of this research is to develop a robust adaptive nonlinear control technique which provides frequency regulation functionality to PV systems as well as voltage regulation. A small-scale power microgrid incorporating photovoltaic generators, synchronous generator and load is considered in our study. Dynamic models of the proposed microgrid were determined. The final model highlights the interactions between the sources of renewable energy and the rest of the network. A new robust adaptive nonlinear (exact input-output feedback linearization) control strategy was developed in order to meet the requirement of frequency regulation as well as voltage regulation. The new control strategy allows the PV system to have a similar response to changes in microgrid frequency as that of a conventional generator. The controller is also self-adjusting (adaptive) as well as robust in order to compensate the perturbation due to the changes in users’ power consumption, or any defects in the MG electrical network. The performance of the proposed solutions was evaluated in simulation using the Matlab/Simulink. For further verification, a small-scale laboratory experimental prototype of proposed microgrid was developed in laboratory to implement the proposed technique. This research may be regarded as an important basis for the development of microgrid power station for remote communities isolated from the main power system or large-scale power network with higher penetration of renewable energy sources

Overview of AC microgrid controls with inverter-interfaced generations

Distributed generation (DG) is one of the key components of the emerging microgrid concept that enables renewable energy integration in a distribution network. In DG unit operation, inverters play a vital role in interfacing energy sources with the grid utility. An effective interfacing can successfully be accomplished by operating inverters with effective control techniques. This paper reviews and categorises different control methods (voltage and primary) for improving microgrid power quality, stability and power sharing approaches. In addition, the specific characteristics of microgrids are summarised to distinguish from distribution network control. Moreover, various control approaches including inner-loop controls and primary controls are compared according to their relative advantages and disadvantages. Finally, future research trends for microgrid control are discussed pointing out the research opportunities. This review paper will be a good basis for researchers working in microgrids and for industry to implement the ongoing research improvement in real systems