New Control Algorithms for the Robust Operation and Stabilization of Active Distribution Networks

The integration of renewable distributed generation units (DGs) alters distribution systems so that rather than having passive structures, with unidirectional power flow, they become active distribution networks (ADNs), with multi-directional power flow. While numerous technical, economic, and environmental benefits are associated with the shift toward ADNs, this transition also represents important control challenges from the perspective of both the supervisory and primary control of DGs. Voltage regulation is considered one of the main operational control challenges that accompany a high penetration of renewable DGs. The intermittent nature of renewable energy sources, such as wind and solar energy, can significantly change the voltage profile of the system and can interact negatively with conventional schemes for controlling on-load tap changers (OLTCs). Another factor is the growing penetration of plug-in electric vehicles (PEVs), which creates additional stress on voltage control devices due to their stochastic and concentrated power profiles. These combined generation and load power profiles can lead to overvoltages, undervoltages, increases in system losses, excessive tap operation, infeasible solutions (hunting) with respect to OLTCs, and/or limits on the penetration of either PEVs or DGs. With regard to the dynamic control level, DG interfaces are typically applied using power electronic converters, which lack physical inertia and are thus sensitive to variations and uncertainties in the system parameters. Grid impedance (or admittance), which has a substantial effect on the performance and stability of primary DG controllers, is nonlinear, time-varying, and not passive in nature. In addition, constant-power loads (CPLs), such as those interfaced through power electronic converters, are also characterized by inherited negative impedance that results in destabilizing effects, creating instability and damping issues. Motivated by these challenges, the research presented in this thesis was conducted with the primary goal of proposing new control algorithms for both the supervisory and primary control of DGs, and ultimately of developing robust and stable ADNs. Achieve this objective entailed the completion of four studies: Study#1: Development of a coordinated fuzzy-based voltage regulation scheme with reduced communication requirements Study#2: Integration of PEVs into the voltage regulation scheme through the implementation of a vehicle-to-grid reactive power (V2GQ) support strategy Study#3: Creation of an estimation tool for multivariable grid admittance that can be used to develop adaptive controllers for DGs Study#4: Development of self-tuning primary DG controllers based on the estimated grid admittance so that stable performance is guaranteed under time-varying DG operating points (dispatched by the schemes developed in Study#1 and Study#2) and under changing grid impedance (created by network reconfiguration and load variations). As the first research component, a coordinated fuzzy-based voltage regulation scheme for OLTCs and DGs has been proposed. The primary reason for applying fuzzy logic is that it provides the ability to address the challenges associated with imperfect information environments, and can thus reduce communication requirements. The proposed regulation scheme consists of three fuzzy-based control algorithms. The first control algorithm was designed to enable the OLTC to mitigate the effects of DGs on the voltage profile. The second algorithm was created to provide reactive power sharing among DGs, which will relax OLTC tap operation. The third algorithm is aimed at partially curtailing active power levels in DGs so as to restore a feasible solution that will satisfy OLTC requirements. The proposed fuzzy algorithms offer the advantage of effective voltage regulation with relaxed tap operation and with utilization of only the estimated minimum and maximum system voltages. Because no optimization algorithm is required, it also avoids the numerical instability and convergence problems associated with centralized approaches. OPAL real-time simulators (RTS) were employed to run test simulations in order to demonstrate the success of the proposed fuzzy algorithms in a typical distribution network. The second element, a V2GQ strategy, has been developed as a means of offering optimal coordinated voltage regulation in distribution networks with high DG and PEV penetration. The proposed algorithm employs PEVs, DGs, and OLTCs in order to satisfy the PEV charging demand and grid voltage requirements while maintaining relaxed tap operation and minimum curtailment of DG active power. The voltage regulation problem is formulated as nonlinear programming and consists of three consecutive stages, with each successive stage applying the output from the preceding stage as constraints. The task of the first stage is to maximize the energy delivered to PEVs in order to ensure PEV owner satisfaction. The second stage maximizes the active power extracted from the DGs, and the third stage minimizes any deviation of the voltage from its nominal value through the use of available PEV and DG reactive power. The primary implicit objective of the third stage problem is the relaxation of OLTC tap operation. This objective is addressed by replacing conventional OLTC control with a proposed centralized controller that utilizes the output of the third stage to set its tap position. The effectiveness of the proposed algorithm in a typical distribution network has been validated in real time using an OPAL RTS in a hardware-in-the loop (HiL) application. The third part of the research has resulted in the proposal of a new multivariable grid admittance identification algorithm with adaptive model order selection as an ancillary function to be applied in inverter-based DG controllers. Cross-coupling between the and grid admittance necessitates multivariable estimation. To ensure persistence of excitation (PE) for the grid admittance, sensitivity analysis is first employed as a means of determining the injection of controlled voltage pulses by the DG. Grid admittance is then estimated based on the processing of the extracted grid dynamics by the refined instrumental variable for continuous-time identification (RIVC) algorithm. Unlike nonparametric identification algorithms, the proposed RIVC algorithm provides a parametric multivariable model of grid admittance, which is essential for designing adaptive controllers for DGs. HiL applications using OPAL RTS have been utilized for validating the proposed algorithm for both grid-connected and isolated ADNs. The final section of the research is a proposed adaptive control algorithm for optimally reshaping DG output impedance so that system damping and bandwidth are maximized. Such adaptation is essential for managing variations in grid impedance and changes in DG operating conditions. The proposed algorithm is generic so that it can be applied for both grid-connected and islanded DGs. It involves three design stages. First, the multivariable DG output impedance is derived mathematically and verified using a frequency sweep identification method. The grid impedance is also estimated so that the impedance stability criteria can be formulated. In the second stage, multi-objective programming is formulated using the -constraint method in order to maximize system damping and bandwidth. As a final stage, the solutions provided by the optimization stage are employed for training an adaptation scheme based on a neural network (NN) that tunes the DG control parameters online. The proposed algorithm has been validated in both grid-connected and isolated distribution networks, with the use of OPAL RTS and HiL applications.1 yea

Nonlinear Modeling of Power Electronics-based Power Systems for Control Design and Harmonic Studies

The massive integration of power electronics devices in the modern electric grid marked a turning point in the concept of stability, power quality and control in power systems. The evolution of the grid toward a converter-dominated network motivates a deep renovation of the classical power system theory developed for machine-dominated networks. The high degree of controllability of power electronics converters, furthermore, paves the way to the investigation of advanced control strategies to enhance the grid stability, resiliency and sustainability. This doctoral dissertation explores four cardinal topics in the field of power electronics-based power systems: dynamic modeling, stability analysis, converters control, and power quality with particular focus on harmonic distortion. In all four research areas, a particular attention is given to the implications of the nonlinearity of the converter models on the power system

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

Universal Grid-forming Method for Future Power Systems

Power system inertia typically refers to the energy stored in large rotating synchronous generators. Dynamics and stability of the traditional power system is closely linked to the natural inertia of these synchronous generators. In recent years, increasing amount of synchronous generators have been replaced by high amount of different type of inverter-based generating units connected at different voltage levels of the power system. Therefore, the dynamics and stability of future low-inertia power systems will be increasingly dominated by the control and synchronization of these inverter-based resources. One essential issue is that the typical grid-following control with phase-locked-loop (PLL) -based synchronization of inverter-based generation is not enough to guarantee frequency stability in future low-inertia power systems. Therefore, different grid-forming inverter control and synchronization methods have been proposed and developed. Currently there does not exist any universal grid-forming control and synchronization method. Therefore, this paper tries to propose a new universal frequency-locked-loop (U-FLL) -based synchronization method which is grid-forming for inverter-based generating units and grid-supporting for inverter-based loads. Advantageous operation of the new U-FLL synchronization and control strategy is confirmed by multiple simulations with different shares of inverter-based resources and synchronous generators in MV and HV hybrid power systems as well as with 100 % inverter-based LV, MV and HV networks.©2022 the Author. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed

The Role of Inverter-based Generation in Future Energy Systems: An Oriented Decentralized Strategy for Reactive Power Sharing in Islanded AC Microgrids and a Techno-Economic Approach to Inertia Requirements Assessment of the Italian Transmission Network

One of the most impacting changes in the electricity energy scenario of the latest decades is the extensive increase of Distributed Energy Resources (DER) including Electrical Storage Systems (EES), fuel cells and Renewable Energy Sources (RES), such as Photovoltaic (PV) and Wind Turbines (WT). The integration of a rapidly increasing share of inverter-based generation poses relevant challenges in terms of frequency and voltage control both in Islanded Microgrids (MG) and traditional transmission networks. For the sake of complementarity, the thesis focuses on reactive power and voltage regulation in MG and frequency instability problems in a future Italian transmission network. In MG with converter-based energy production, one of the main problems is the proper reactive power sharing among DER and related voltage regulation. In this concern the most used approach is based on the conventional droop control; however, it presents some relevant drawbacks. In SECTION A an Advanced Droop Control strategy (ADC) and an Advanced Boost Control strategy (ABC) are proposed, to approach primary voltage control and reactive power sharing among Grid-Supporting inverters in islanded MG. The strategies are presented defining their control laws and the control schemes together with the relevant stability analysis. Then, an analytical procedure is developed for each control methods to set proper control parameters. Next, a comparison between the new strategies and droop conventional control is performed with simulations on a common benchmark MG, in order to show that new strategies, according to their specific control logics, are able to guarantee improved performance in terms of the combined regulation of voltage and reactive power. Considering the traditional electric system, one of the main consequences of the increasing penetration of RES is, besides of the decrease of the system short-circuit power, the reduction of the electric system inertia: this could lead to frequency instability problems in case of severe perturbations, especially for what concerns the Rate of Change of Frequency (RoCoF)and the frequency nadir. In SECTION B, the thesis provides a technical-economic methodology for the estimation of the amount of additional inertia that will be needed in the Italian Transmission Network in a prospective 2030 scenario, in order to limit the RoCoF within sustainable values. Moreover, the algorithm optimally commits synthetic inertia contribution from RES and Battery Energy Storage Systems (BESS) and installation of Synchronous Compensators (SC) among the Italian market areas. The method is designed to be sufficiently simple to process a relevant number of working scenarios in order to exploit the relevant quantity of information owned by the TSO. Results have shown to be highly accurate as outline by comparison with detailed time domain simulations

Optimal H2 control design of active front-end integrating grid model identification

Small-signal stability and dynamic performance are of great concern for AC power grids with high penetration of power converters. The interactions between these converters may lead to performance degradation or even system instability and failure at certain conditions. To deal with such problems, global modelling and integrated control are proposed. However, because of the highly integration of power grids in commercial industry environment, the lack of information about parameters and methods of the embedded converters, impedes the development of global models for system analysis and control design. To fill the gap, this research investigated the utility of system identification techniques to estimate a state space model of the unknown power grid, and proposed an approach to incorporate it into the design of local converters. Hence interactions between the grid and the to be designed converters could be taken into account and issues mitigated. Specifically in this research, the proposed method is applied to the control design of a grid-connected active front end (AFE). In a notional system, a voltage source inverter (VSI) is included to emulate the unknown grid and supplies power to an AFE feeding a constant power load (CPL). Firstly, a state space model of the grid is identified through perturbation and response test at the point of common coupling (PCC) in a specially designed experiment. It is then combined with the open loop model of the AFE to build a global model of the grid-AFE system. The plant for the control design will then be not only represented by the AFE's dynamics, but will also include that of the identified grid at the PCC. Implementation of the identification experiment involved and mathematical manipulations used to merge the two subsystem models are presented in detail. The global model is utilized to synthesize a state feedback controller, denoted as `optimal $H_2$ controller' in this thesis for the AFE by the use of a structured $H_2$ algorithm, which optimizes the dynamic performance of AFE while intrinsically ensuring stability of the grid-AFE system. Effectiveness and advantages of the proposed control design method is validated by simulations and experiments. The grid-AFE system performance when the AFE adopts the optimal $H_2$ controller or best-tuned proportional-integral (PI) controllers is compared. The use of optimal $H_2$ controller outperforms with faster dynamic response and greater stability margin the PI based solution. Scalability of the proposed method in more complex power grids and its robustness against system parameters drifting are also discussed