Enhancement of microgrid operation by considering the cascaded impact of communication delay on system stability and power management

Power management, system stability and communication structure are three key aspects of microgrids (MGs) that have been explored in many research studies. However, the cascaded effect of communication structure on system stability followed by the impact of stability on the power management has not been fully explored in the literature yet and needs more attention. This paper not only explores this cascaded impact, but also provides a comprehensive platform to optimally consider three layers of MG design and operation from this perspective. For generation cost minimization and stability assessment, the proposed platform uses an adaptive particle swarm optimization (PSO) while a new class of data exchange scheme based on IEC 61850 protocol is proposed to reduce the communication time delays among the inverters of distributed generations and the MG control center. This paper also considers the system stability using small-signal model of a MG in a real-time manner as an embedded function in the PSO. In this context investigations have been conducted by modeling an isolated MG with solar farm, fuel cell generator and micro-turbine in MATLAB Simulink. Detailed simulation results indicate the proposed power and stability management method effectively reduces the MG generation cost through maximizing the utilization of the available renewable generations while considering system stability. © 2020 Elsevier Lt

Wide Area Oscillation Damping using Utility-Scale PV Power Plants Capabilities

With increasing implementation of Wide Area Measurement Systems (WAMS) in power grids, application of wide area damping controllers (WADCs) to damp power system oscillations is of interest. On the other hand it is well known that rapidly increasing integration of renewable energy sources into the grid can dangerously reduce the inertia of the system and degrade the stability of power systems. This paper aimed to design a novel WADC for a utility-scale PV solar farm to damp out inter area oscillations while the main focus of the work is to eliminate the impact of communication delays of wide-area signals from the WAMS. Moreover the PV farm impact on inter area oscillation mitigation is investigated in various case studies, namely, with WADC on the active power control loop and with WADC on the reactive power control loop. The Quantum Particle Swarm Optimization (QPSO) technique is applied to normalize and optimize the parameters of WADC for inter-area oscillations damping and continuous compensation of time-varying latencies. The proposed method is prosperously applied in a 16-bus six-machine test system and various case studies are conducted to demonstrate the potential of the proposed structure

Analysis And Mitigation Of The Impacts Of Delays In Control Of Power Systems With Renewable Energy Sources

ABSTRACT Analysis and Mitigation of the Impacts of Delays in Control of Power Systems with Renewable Energy Sources by Chang Fu Apr. 2019 Advisor : Dr. Caisheng Wang Major : Electrical and Computer Engineering Degree : Doctor of Philosophy With the integration of renewable resources, electric vehicles and other uncertain resources into power grid, varieties of control topology and algorithms have been proposed to increase the stability and reliability of the operation system. Load modeling is an critical part in such analysis since it significantly impacts the accuracy of the simulation in power system, as well as stability and reliability analysis. Traditional power system composite load model parameter identification problems can be essentially ascribed to optimization problems, and the identied parameters are point estimations subject to dierent constraints. These conventional point estimation based composite load modeling approaches suer from disturbances and noises and provide limited information of the system dynamics. In this thesis, a statistic (Bayesian Estimation) based distribution estimation approach is proposed for composite load models, including static (ZIP) and dynamic (Induction Motor) parts, by implementing Gibbs sampling. The proposed method provides a distribution estimation of coecients for load models and is robust to measurement errors. The overvoltage issue is another urgent issues need to be addressed, especially in a high PV penetration level system. Various approaches including the real power control through photovoltaic (PV) inverters have been proposed to mitigate such impact, however, most of the existing methods did not include communication delays in the control loop. Communication delays, short or long, are inevitable in the PV voltage regulation loop and can not only deteriorate the system performance with undesired voltage quality but also cause system instability. In this thesis, a method is presented to convert the overvoltage control problem via PV inverters for multiple PVs into a problem of single-input-single-output (SISO) systems. The method can handle multiple PVs and dierent communication delays. The impact of communication delays is also systematically analyzed and the maximum tolerable delay is rigorously obtained. Dierent from linear matrix inequality (LMI) techniques that have been extensively studied in handling systems with communication delays, the proposed method gives the necessary and sucient condition for obtaining a controller and the design procedure is explicitly and constructively given in the paper. The effectiveness of the proposed method is veried by simulation studies on a distribution feeder and the widely-used 33-bus distribution test system. The similar design strategy can be utilized to mitigate delay impacts in Load frequency control (LFC) as well. LFC has been considered as one of the most important frequency regulation mechanisms in modern power system. One of the inevitable problems involved in LFC over a wide area is communication delay. In this thesis, an alternative design method is proposed to devise delay compensators for LFC in one or multiple control areas. For one-area LFC, a sucient and necessary condition is given for designing a delay compensator. For multiarea LFC with area control errors (ACEs), it is demonstrated that each control area can have its delay controller designed as that in a one-area system if the index of coupling among the areas is below the threshold value determined by the small gain theorem. Effectiveness of the proposed method is veried by simulation studies on LFCs with communication delays in one and multiple interconnected areas with and without time-varying delays, respectively

Analysis And Mitigation Of The Impacts Of Delays In Control Of Power Systems With Renewable Energy Sources

ABSTRACT Analysis and Mitigation of the Impacts of Delays in Control of Power Systems with Renewable Energy Sources by Chang Fu Apr. 2019 Advisor : Dr. Caisheng Wang Major : Electrical and Computer Engineering Degree : Doctor of Philosophy With the integration of renewable resources, electric vehicles and other uncertain resources into power grid, varieties of control topology and algorithms have been proposed to increase the stability and reliability of the operation system. Load modeling is an critical part in such analysis since it significantly impacts the accuracy of the simulation in power system, as well as stability and reliability analysis. Traditional power system composite load model parameter identification problems can be essentially ascribed to optimization problems, and the identied parameters are point estimations subject to dierent constraints. These conventional point estimation based composite load modeling approaches suer from disturbances and noises and provide limited information of the system dynamics. In this thesis, a statistic (Bayesian Estimation) based distribution estimation approach is proposed for composite load models, including static (ZIP) and dynamic (Induction Motor) parts, by implementing Gibbs sampling. The proposed method provides a distribution estimation of coecients for load models and is robust to measurement errors. The overvoltage issue is another urgent issues need to be addressed, especially in a high PV penetration level system. Various approaches including the real power control through photovoltaic (PV) inverters have been proposed to mitigate such impact, however, most of the existing methods did not include communication delays in the control loop. Communication delays, short or long, are inevitable in the PV voltage regulation loop and can not only deteriorate the system performance with undesired voltage quality but also cause system instability. In this thesis, a method is presented to convert the overvoltage control problem via PV inverters for multiple PVs into a problem of single-input-single-output (SISO) systems. The method can handle multiple PVs and dierent communication delays. The impact of communication delays is also systematically analyzed and the maximum tolerable delay is rigorously obtained. Dierent from linear matrix inequality (LMI) techniques that have been extensively studied in handling systems with communication delays, the proposed method gives the necessary and sucient condition for obtaining a controller and the design procedure is explicitly and constructively given in the paper. The effectiveness of the proposed method is veried by simulation studies on a distribution feeder and the widely-used 33-bus distribution test system. The similar design strategy can be utilized to mitigate delay impacts in Load frequency control (LFC) as well. LFC has been considered as one of the most important frequency regulation mechanisms in modern power system. One of the inevitable problems involved in LFC over a wide area is communication delay. In this thesis, an alternative design method is proposed to devise delay compensators for LFC in one or multiple control areas. For one-area LFC, a sucient and necessary condition is given for designing a delay compensator. For multiarea LFC with area control errors (ACEs), it is demonstrated that each control area can have its delay controller designed as that in a one-area system if the index of coupling among the areas is below the threshold value determined by the small gain theorem. Effectiveness of the proposed method is veried by simulation studies on LFCs with communication delays in one and multiple interconnected areas with and without time-varying delays, respectively

Oscillation Analysis and its Mitigation Using Inverter-Based Resources in Large-Scale Power Grids

In today\u27s interconnected power grids, forced oscillations and poorly damped low-frequency oscillations are major concerns that can damage equipment, limit power transfer capability, and deteriorate power system stability. The first part of the dissertation focuses on the impact of a wide-area power oscillation damping (POD) controller via voltage source converter-based high voltage direct current (VSC-HVDC) in enhancing the power system stability and improving the damping of low-frequency oscillation. The POD controller\u27s performance was investigated under a three-phase temporary line fault. The Great Britain (G.B.) power grid model validated the POD controller performance via active power modulation of VSC-HVDC through TSAT-RTDS hybrid simulation. The developed POD controller is also implemented on a general-purpose hardware platform CompactRIO and tested on a hardware-in-the-loop (HIL) test setup with actual PMU devices and a communication network impairment simulator. A variety of real-world operating conditions is considered in the HIL tests, including measurement error/noise, occasional/consecutive data package losses, constant/random time delays, and multiple backups PMUs. The second part of the dissertation proposes a two‐dimensional scanning forced oscillation grid vulnerability analysis method to identify areas/zones and oscillation frequency in the system critical to forced oscillation. These critical areas/zones can be considered effective actuator locations to deploy forced oscillation damping controllers. Additionally, a POD controller through inverter-based resources (IBRs) is proposed to reduce the forced oscillation impact on the entire grid. The proposed method is tested when the external perturbation is active power and compared with the reactive power perturbation result. The proposed method is validated through a case study on the 2000-bus synthetic Texas power system model. The simulation results demonstrate that the critical areas/zones of forced oscillation are related to the areas that highly participate in the natural oscillation. Furthermore, forced oscillation through active power disturbance can have a more severe impact than reactive power disturbance, especially at resonance. The proposed forced oscillation controller can mitigate the impact of the forced oscillation on the entire system when the actuator is close to the forced oscillation source. In addition, active power modulation of IBR can provide better damping performance than reactive power modulation

Impact evaluation of cyber-physical uncertainty on power systems

This thesis evaluates the impact on power system performance of uncertainty arising from physical and cyber components of power systems. If the impact of the uncertainty arising from emerging technologies is not fully understood, it will likely lead to the deployment of unreliable and unsafe systems, which could have catastrophic consequences. In this thesis, we first identify sources of uncertainty, and their impact on both system dynamic security and relia- bility. Then, we recognize the gaps that have not been studied in the existing related work, and develop models and methods to fill the gaps. We mainly focus on the evaluation of uncertainty impact in two applica- tions: (i) the impact of measurement uncertainty on power system dynamic performance (at the transmission level), and (ii) the impact of uncertain phenomena on power systems coordinating demand response resources (at distribution level). With respect to the first application, we focus on the impact of both measurement errors and delays on the dynamic performance of power systems with automatic generation control (AGC). A framework to model the deterministic and random measurement errors, and measure- ment delays, as well as the corresponding analysis methods, are developed. Along the process, the different time scales of the system dynamics, as well as the discrete nature of the sampling process in AGC, should be considered. Eventually, with the developed framework, we can determine system stability under various measurement uncertainty scenarios. In the second application, we have developed a stochastic hybrid system (SHS) model that can capture both continuous dynamics and discrete events that arise from random fail- ures and repairs. A reliability measure is also proposed and evaluated. In order to illustrate and validate the proposed evaluation methods proposed in this thesis, the results of all proposed analytical methods addressing the random factors are compared with those obtained by Monte Carlo methods via examples and case studies

Self-Organized Dynamics of Power Grids: Smart Grids, Fluctuations and Cascades

Climate change is one of the most pressing issues of our time and mitigating it requires a reduction of CO2 emissions. A big step towards achieving this goal is increasing the share of renewable energy sources, as the energy sector currently contributes 35% to all greenhouse gas emissions. However, integrating these renewable energy sources challenges the current power system in two major ways. Firstly, renewable generation consists of more spatially distributed and smaller power plants than conventional generation by nuclear or coal plants, questioning the established hierarchical structures and demanding a new grid design. Restructuring becomes necessary because wind and solar plants have to be placed at favorable sites, e.g., close to coasts in the case of wind. Secondly, renewables do not provide a deterministic and controllable power output but introduce power fluctuations that have to be controlled adequately. Many solutions to these challenges are build on the concept of smart grids, which require an extensive information technology (IT) infrastructure communicating between consumers and generators to coordinate efficient actions. However, an intertwined power and IT system raises great privacy and security concerns. Is it possible to forgo a large IT infrastructure in future power grids and instead operate them purely based on local information? How would such a decentrally organized system work? What is the impact of fluctuation on short time scales on the dynamical stability? Which grid topologies are robust against random failures or targeted attacks? This thesis aims to establish a framework of such a self-organized dynamics of a power grid, analyzing its benefits and limitations with respect to fluctuations and discrete events. Instead of a centrally monitored and controlled smart grid, we propose the concept of Decentral Smart Grid Control, translating local power grid frequency information into actions to stabilize the grid. This is not limited to power generators but applies equally to consumers, naturally introducing a demand response. We analyze the dynamical stability properties of this framework using linear stability methods as well as applying numerical simulations to determine the size of the basin of attraction. To do so, we investigate general stability effects and sample network motifs to find that this self-organized grid dynamics is stable for large parameter regimes. However, when the actors of the power grid react to a frequency signal, this reaction has to be sufficiently fast since reaction delays are shown to destabilize the grid. We derive expressions for a maximum delay, which always desynchronizes the system based on a rebound effect, and for destabilizing delays based on resonance effects. These resonance instabilities are cured when the frequency signal is averaged over a few seconds (low-pass filter). Overall, we propose an alternative smart grid model without any IT infrastructure and analyze its stable operating space. Furthermore, we analyze the impact of fluctuations on the power grid. First, we determine the escape time of the grid, i.e., the time until the grid desynchronizes when subject to stochastic perturbations. We simulate these events and derive an analytical expression using Kramer's method, obtaining the scaling of the escape time as a function of the grid inertia, transmitted power, damping etc. Thereby, we identify weak links in networks, which have to be enhanced to guarantee a stable operation. Second, we collect power grid frequency measurements from different regions across the world and evaluate their statistical properties. Distributions are found to be heavy-tailed so that large disturbances are more common than predicted by Gaussian statistics. We model the grid dynamics using a stochastic differential equation to derive the scaling of the fluctuations based on power grid parameters, identifying effective damping as essential in reducing fluctuation risks. This damping may be provided by increased demand control as proposed by Decentral Smart Grid Control. Finally, we investigate discrete events, in particular the failure of a single transmission line, as a complementary form of disturbances. An initial failure of a transmission line leads to additional load on other lines, potentially overloading them and thereby causing secondary outages. Hence, a cascade of failures is induced that propagated through the network, resulting in a large-scale blackout. We investigate these cascades in a combined dynamical and event-driven framework, which includes transient dynamics, in contrast to the often used steady state analysis that only solves static flows in the grid while neglecting any dynamics. Concluding, we identify critical lines, prone to cause cascades when failing, and observe a nearly constant speed of the propagation of the cascade in an appropriate metric. Overall, we investigate the self-organized dynamics of power grids, demonstrating its benefits and limitations. We provide tools to improve current grid operation and outline a smart grid solution that is not reliant on IT. Thereby, we support establishing a 100% renewable energy system

Taming Instabilities in Power Grid Networks by Decentralized Control

Renewables will soon dominate energy production in our electric power system. And yet, how to integrate renewable energy into the grid and the market is still a subject of major debate. Decentral Smart Grid Control (DSGC) was recently proposed as a robust and decentralized approach to balance supply and demand and to guarantee a grid operation that is both economically and dynamically feasible. Here, we analyze the impact of network topology by assessing the stability of essential network motifs using both linear stability analysis and basin volume for delay systems. Our results indicate that if frequency measurements are averaged over sufficiently large time intervals, DSGC enhances the stability of extended power grid systems. We further investigate whether DSGC supports centralized and/or decentralized power production and find it to be applicable to both. However, our results on cycle-like systems suggest that DSGC favors systems with decentralized production. Here, lower line capacities and lower averaging times are required compared to those with centralized production.Comment: 21 pages, 6 figures This is a pre-print of a manuscript submitted to The European Physical Journal. The final publication is available at Springer via http://dx.doi.org/10.1140/epjst/e2015-50136-