pwc-archive/papers-with-abstracts huggingface dataset:
Synthesis of Event-triggered Controllers for SIRS Epidemic Models
Authors: Lichen Ding, Kazumune Hashimoto, Shigemasa Takai
Date: 2023-10-14 00:00:00

In this paper, we investigate the problem of mitigating epidemics by applying an event-triggered control strategy. We consider a susceptible-infected-removed-susceptible (SIRS) model, which builds upon the foundational SIR model by accounting for reinfection cases. The event-triggered control strategy is formulated based on the condition in which the control input (e.g., the level of public measures) is updated only when the fraction of the infected subjects changes over a designed threshold. To synthesize the event-triggered controller, we leverage the notion of a symbolic model, which represents an abstracted expression of the transition system associated with the SIRS model under the event-triggered control strategy. %The symbolic model is constructed based on an approximate alternating simulation relation. Then, by employing safety and reachability games, two event-triggered controllers are synthesized to ensure a desired specification, which is more sophisticated than the one given in previous works. The effectiveness of the proposed approach is illustrated through numerical simulations.
Extremum seeking in the presence of large delays via time-delay approach to averaging
Authors: Xuefei Yang, Emilia Fridman
Date: 2023-10-14 00:00:00

In this paper, we study gradient-based classical extremum seeking (ES) for uncertain n-dimensional (nD) static quadratic maps in the presence of known large constant distinct input delays and large output constant delay with a small time-varying uncertainty. This uncertainty may appear due to network-based measurements. We present a quantitative analysis via a time-delay approach to averaging. We assume that the Hessian has a nominal known part and norm-bounded uncertainty, the extremum point belongs to a known box, whereas the extremum value to a known interval. By using the orthogonal transformation, we first transform the original static quadratic map into a new one with the Hessian containing a nominal diagonal part. We apply further a time-delay transformation to the resulting ES system and arrive at a time-delay system, which is a perturbation of a linear time-delay system with constant coefficients. Given large delays, we choose appropriate gains to guarantee stability of this linear system. To find a lower bound on the dither frequency for practical stability, we employ variation of constants formula and exploit the delay-dependent positivity of the fundamental solutions of the linear system with their tight exponential bounds. Sampled-data ES in the presence of large distinct input delays is also presented. Explicit conditions in terms of simple scalar inequalities depending on tuning parameters and delay bounds are established to guarantee the practical stability of the ES control systems. We show that given any large delays and initial box, by choosing appropriate gains we can achieve practical stability for fast enough dithers and small enough uncertainties.
Non-intrusive Enforcement of Decentralized Stability Protocol for IBRs in AC Microgrids
Authors: Tong Huang
Date: 2023-10-13 00:00:00

This paper presents decentralized, passivity-based stability protocol for inverter-based resources (IBRs) in AC microgrids and a non-intrusive approach that enforces the protocol. By "non-intrusive" we mean that the approach does not require reprogramming IBRs' controllers to enforce the stability protocol. Implementing the approach only requires very minimal information of IBR dynamics, and sharing such information with the non-IBR-manufacturer parties does not cause any concerns on intellectual property privacy. Enforcing the protocol allows for plug-and-play operation of IBRs, while maintaining microgrid stability. The proposed method is tested by simulating two networked microgrids with tie lines and two IBRs modeled in the electromagnetic transient (EMT) time scale. Simulations show that oscillations with increasing amplitudes can occur, when two stable AC microgrids are networked. Simulations also suggest that the proposed approach can mitigate such a system-level symptom by changing less than 2 percent of energy produced by IBRs.
An integrated and flexible ultrasonic device for the continuous bladder volume monitoring
Authors: Alp Timucin Toymus, Umut Can Yener, Emine Bardakci, Ozgur Deniz Temel, Ersin Koseoglu, Dincay Akcoren, Burak Eminoglu, Mohsin Ali, Tufan Tarcan, Levent Beker
Date: 2023-10-13 00:00:00
Tasks: Management

Bladder volume measurement is critical for early detection and management of lower urinary tract dysfunctions. The current gold standard is invasive, and alternative technologies either require trained personnel or do not offer medical grade information. Here, we report an integrated wearable ultrasonic bladder volume monitoring (UBVM) device for accurate and autonomous continuous monitoring of the bladder volume. The device incorporates flexible and air-backed ultrasonic transducers and miniaturized control electronics with wireless data transmission capability. We demonstrated the real-life application of the device on healthy volunteers with various bladder shapes and sizes with high accuracy. Apart from the lower urinary tract dysfunctions, the proposed technology could also be adapted for various wearable ultrasonic applications.
Control of Vehicle Platoons with Collision Avoidance Using Noncooperative Differential Games
Authors: Hossein B. Jond
Date: 2023-10-13 00:00:00
Tasks: Collision Avoidance

This paper considers a differential game approach to the predecessor-following vehicle platoon control problem without and with collision avoidance. In this approach, each vehicle tries to minimize the performance index (PI) of its control objective, which is reaching consensual velocity with the predecessor vehicle while maintaining a small inter-vehicle distance from it. Two differential games were formulated. The differential game problem for platoon control without collision avoidance is solved for the open-loop Nash equilibrium and its associated state trajectories. The second differential game problem for platoon control with collision avoidance has a non-quadratic PI, which poses a greater challenge to obtaining its open-loop Nash equilibrium. Since the exact solution is unavailable, we propose an estimated Nash strategy approach that is greatly simplified for implementation. An illustrative example of a vehicle platoon control problem was solved under both the without and with collision avoidance scenarios. The results showed the effectiveness of the models and their solutions for both scenarios.
Effects of Distributed Generation on the Bidirectional Operation of Cascaded Step Voltage Regulators: Case Study of a Real 34.5 kV Distribution Feeder
Authors: Hugo Rodrigues de Brito, Valéria Monteiro de Souza, João Paulo Abreu Vieira, Maria Emília de Lima Tostes, Ubiratan Holanda Bezerra, Vanderson Carvalho de Souza, Daniel da Conceição Pinheiro, Heitor Alves Barata, Hugo Nazareno de Souza Cardoso, Marcelo Sousa Costa
Date: 2023-10-13 00:00:00

This work investigates the impact of feeder bidirectional active power flow on the operation of two cascaded step voltage regulators (SVRs) located at a 34.5 kV rural distribution feeder. It shows that, when active power flow reversal is possible both by network reconfiguration and by high penetration levels of distributed generation (DG), typical SVR control mode settings are unable to prevent the occurrence of runaway condition, a phenomenon characterized by loss of SVR voltage control capabilities. Such developments are the basis for a DG pre-dispatch control strategy that aims to avoid the adverse effects of the described power flow reversal scenarios, as well as to ensure reliable operation of the utility distribution network.
Comparison between Conventional Load Flow, QSTS Simulation, and Dynamic Simulation to Assess the Operation of Step Voltage Regulators in Active Distribution Networks
Authors: V. M. Souza, H. R. Brito, J. P. A. Vieira, M. E. L. Tostes, U. H. Bezerra, H. N. S. Cardoso, M. S. Costa
Date: 2023-10-13 00:00:00
Tasks: Time Series

The assessment of step voltage regulator (SVR) operation in active distribution networks requires computational analysis tools capable of tackling the emerging technical challenges. Conventional load flow (CLF), quasi-static time series (QSTS) and dynamic simulations are typically employed to investigate high-penetration distributed generation (DG) interconnection impacts. Regarding the SVR runaway condition phenomenon, however, a consensus has yet to be reached on the most cost-effective simulation technique for capturing and reproducing the correct sequence of events. This work presents a comparative study of the CLF, QSTS and dynamic simulation techniques through modelling and analysis of two SVR-controlled test-feeders, in order to evaluate each approach performance in addressing scenarios of DG-caused reverse active power flow. Detailed descriptions of feeder voltage profile and SVR tap operations are provided to facilitate understanding of the mechanisms that characterize SVR runaway condition, as well as the advantages and drawbacks of each of the studied simulation techniques.
Transmission Expansion Planning for Renewable-energy-dominated Power Grids Considering Climate Impact
Authors: Jin Lu, Xingpeng Li
Date: 2023-10-13 00:00:00

As renewable energy is becoming the major resource in future grids, the weather and climate can have a higher impact on grid reliability. Transmission expansion planning (TEP) has the potential to reinforce a transmission network that is suitable for climate-impacted grids. In this paper, we propose a systematic TEP procedure for climate-impacted renewable energy-enriched grids. Particularly, this work developed an improved model for TEP considering climate impact (TEP-CI) and evaluated the system reliability with the obtained transmission investment plan. Firstly, we created climate-impacted spatio-temporal future grid data to facilitate the TEP-CI study, which includes the future climate-dependent renewable production as well as the dynamic rating profiles of the Texas 123-bus backbone transmission system (TX-123BT). Secondly, we proposed the TEP-CI which considers the variation in renewable production and dynamic line rating, and obtained the investment plan for future TX-123BT. Thirdly, we presented a customized security-constrained unit commitment (SCUC) specifically for climate-impacted grids. The future grid reliability under various investment scenarios is analyzed based on the daily operation conditions from SCUC simulations. The whole procedure presented in this paper enables numerical studies on grid planning considering climate impacts. It can also serve as a benchmark for other TEP-CI research and performance evaluation.
Nash Equilibrium of Joint Day-ahead Electricity Markets and Forward Contracts in Congested Power Systems
Authors: Mohsen Banaei, Majid Oloomi Buygi, Hani Raouf-Sheybani, Razgar Ebrahimy, Henrik Madsen
Date: 2023-10-12 00:00:00

Uncertainty in the output power of large-scale wind power plants (WPPs) can face the electricity market players with undesirable profit variations. Market players can hedge themselves against these risks by participating in forward contracts markets alongside the day-ahead markets. The participation of market players in these two markets affects their profits and also the prices and power quantities of each market. Moreover, limitations in the transmission grid can affect the optimal behavior of market players. In this paper, a Cournot Nash equilibrium model is proposed to study the behavior of market players in the forward contract market and the day-ahead electricity market in a congested power system with large-scale integration of WPPs. The proposed method is applied to a test system, and the results are discussed.
Flexible Transmission: A Comprehensive Review of Concepts, Technologies, and Market
Authors: Omid Mirzapour, Xinyang Rui, Brittany Pruneau, Mostafa Sahraei-Ardakani
Date: 2023-10-12 00:00:00

As global concerns regarding climate change are increasing worldwide, the transition towards clean energy sources has accelerated. Accounting for a large share of energy consumption, the electricity sector is experiencing a significant shift towards renewable energy sources. To accommodate this rapid shift, the transmission system requires major upgrades. Although enhancing grid capacity through transmission system expansion is always a solution, this solution is very costly and requires a protracted permitting process. The concept of flexible transmission encompasses a broad range of technologies and market tools that enable effective reconfiguration and manipulation of the power grid for leveraged dispatch of renewable energy resources. The proliferation of such technologies allows for enhanced transfer capability over the current transmission network, thus reducing the need for grid expansion projects. This paper comprehensively reviews flexible transmission technologies and their role in achieving a net-zero carbon emission grid vision. Flexible transmission definitions from different viewpoints are discussed, and mathematical measures to quantify grid flexibility are reviewed. An extensive range of technologies enhancing flexibility across the grid is introduced and explored in detail. The environmental impacts of flexible transmission, including renewable energy utilization and carbon emission reduction, are presented. Finally, market models required for creating proper incentives for the deployment of flexible transmission and regulatory barriers and challenges are discussed.
An Efficient Resilient MPC Scheme via Constraint Tightening against Cyberattacks: Application to Vehicle Cruise Control
Authors: Milad Farsi, Shuhao Bian, Nasser L. Azad, Xiaobing Shi, Andrew Walenstein
Date: 2023-10-12 00:00:00
Tasks: Model Predictive Control

We propose a novel framework for designing a resilient Model Predictive Control (MPC) targeting uncertain linear systems under cyber attack. Assuming a periodic attack scenario, we model the system under Denial of Service (DoS) attack, also with measurement noise, as an uncertain linear system with parametric and additive uncertainty. To detect anomalies, we employ a Kalman filter-based approach. Then, through our observations of the intensity of the launched attack, we determine a range of possible values for the system matrices, as well as establish bounds of the additive uncertainty for the equivalent uncertain system. Leveraging a recent constraint tightening robust MPC method, we present an optimization-based resilient algorithm. Accordingly, we compute the uncertainty bounds and corresponding constraints offline for various attack magnitudes. Then, this data can be used efficiently in the MPC computations online. We demonstrate the effectiveness of the developed framework on the Adaptive Cruise Control (ACC) problem.
Data-driven Invariance for Reference Governors
Authors: Ali Kashani, Claus Danielson
Date: 2023-10-12 00:00:00
Tasks: Autonomous Driving, Unity

This paper presents a novel approach to synthesizing positive invariant sets for unmodeled nonlinear systems using direct data-driven techniques. The data-driven invariant sets are used to design a data-driven reference governor that selects a reference for the closed-loop system to enforce constraints. Using kernel-basis functions, we solve a semi-definite program to learn a sum-of-squares Lyapunov-like function whose unity level-set is a constraint admissible positive invariant set, which determines the constraint admissible states as well as reference inputs. Leveraging Lipschitz properties of the system, we prove that tightening the model-based design ensures robustness of the data-driven invariant set to the inherent plant uncertainty in a data-driven framework. To mitigate the curse-of-dimensionality, we repose the semi-definite program into a linear program. We validate our approach through two examples: First, we present an illustrative example where we can analytically compute the maximum positive invariant set and compare with the presented data-driven invariant set. Second, we present a practical autonomous driving scenario to demonstrate the utility of the presented method for nonlinear systems.
Asymptotic Stability of Active Disturbance Rejection Control for Linear SISO Plants with Low Observer Gains
Authors: James Berneburg, Daigo Shishika, Cameron Nowzari
Date: 2023-10-12 00:00:00

This paper theoretically investigates the closed-loop performance of active disturbance rejection control (ADRC) on a third-order linear plant with relative degree 3, subject to a class of exogenous disturbances. While PID control cannot be guaranteed to be capable of stabilizing such plants, ADRC offers a model-free alternative. However, many existing works on ADRC consider the observer gains to be taken arbitrarily large, in order to guarantee desired performance, such as works which consider parameterizing ADRC by bandwidth. This work finds that, for constant exogenous disturbances, arbitrary eigenvalue assignment is possible for the closed-loop system under linear ADRC, thus guaranteeing the existence of an ADRC controller for desired performance without taking any gains arbitrarily large. We also find that stabilization is possible when the exogenous disturbance is stable, and show how ADRC can recover the performance of model-based observers. We demonstrate aspects of the resulting closed-loop systems under ADRC in simulations.
Transmission line dynamics on inverter-dominated grids: analysis and simulations
Authors: Gabriel E. Colon-Reyes, Ruth Kravis, Sunash Sharma, Duncan Callaway
Date: 2023-10-12 00:00:00

In this work, we study fast time scale dynamic interactions between inverters, synchronous machines, and transmission lines. The overlapping time scales between inverter controls and electromagnetic phenomena idfentified in recent years has necessitated a re-evaluation of assumptions made in power system dynamics studies. We utilize an open-source modeling platform to perform both small signal stability and dynamic time domain studies of networks containing inverters, machines, and loads. We use transmission line models of varying fidelity, including models with multiple segments and frequency dependence. Our results indicate that, for the cases we study, line dynamics are not important for characterizing small signal stability. However, while in many cases the high fidelity line models are unnecessary for dynamic simulations, there are some cases in which simpler models omit dynamics that could be important to the operation of inner inverter control loops.
Risk-informed Resilience Planning of Transmission Systems Against Ice Storms
Authors: Chenxi Hu, Yujia Li, Yunhe Hou
Date: 2023-10-12 00:00:00
Tasks: Decision Making

Ice storms, known for their severity and predictability, necessitate proactive resilience enhancement in power systems. Traditional approaches often overlook the endogenous uncertainties inherent in human decisions and underutilize predictive information like forecast accuracy and preparation time. To bridge these gaps, we proposed a two-stage risk-informed decision-dependent resilience planning (RIDDRP) for transmission systems against ice storms. The model leverages predictive information to optimize resource allocation, considering decision-dependent line failure uncertainties introduced by planning decisions and exogenous ice storm-related uncertainties. We adopt a dual-objective approach to balance economic efficiency and system resilience across both normal and emergent conditions. The first stage of the RDDIP model makes line hardening decisions, as well as the optimal sitting and sizing of energy storage. The second stage evaluates the risk-informed operation costs, considering both pre-event preparation and emergency operations. Case studies demonstrate the model's ability to leverage predictive information, leading to more judicious investment decisions and optimized utilization of dispatchable resources. We also quantified the impact of different properties of predictive information on resilience enhancement. The RIDDRP model provides grid operators and planners valuable insights for making risk-informed infrastructure investments and operational strategy decisions, thereby improving preparedness and response to future extreme weather events.
Privacy-Preserved Aggregate Thermal Dynamic Model of Buildings
Authors: Zeyin Hou, Shuai Lu, Yijun Xu, Haifeng Qiu, Wei Gu, ZhaoYang Dong, Shixing Ding
Date: 2023-10-12 00:00:00
Tasks: model, parameter estimation

The thermal inertia of buildings brings considerable flexibility to the heating and cooling load, which is known to be a promising demand response resource. The aggregate model that can describe the thermal dynamics of the building cluster is an important interference for energy systems to exploit its intrinsic thermal inertia. However, the private information of users, such as the indoor temperature and heating/cooling power, needs to be collected in the parameter estimation procedure to obtain the aggregate model, causing severe privacy concerns. In light of this, we propose a novel privacy-preserved parameter estimation approach to infer the aggregate model for the thermal dynamics of the building cluster for the first time. Using it, the parameters of the aggregate thermal dynamic model (ATDM) can be obtained by the load aggregator without accessing the individual's privacy information. More specifically, this method not only exploits the block coordinate descent (BCD) method to resolve its non-convexity in the estimation but investigates the transformation-based encryption (TE) associated with its secure aggregation protocol (SAP) techniques to realize privacy-preserved computation. Its capability of preserving privacy is also theoretically proven. Finally, simulation results using real-world data demonstrate the accuracy and privacy-preserved performance of our proposed method.
Control-Based Planning over Probability Mass Function Measurements via Robust Linear Programming
Authors: Mehdi Kermanshah, Calin Belta, Roberto Tron
Date: 2023-10-12 00:00:00

We propose an approach to synthesize linear feedback controllers for linear systems in polygonal environments. Our method focuses on designing a robust controller that can account for uncertainty in measurements. Its inputs are provided by a perception module that generates probability mass functions (PMFs) for predefined landmarks in the environment, such as distinguishable geometric features. We formulate an optimization problem with Control Lyapunov Function (CLF) and Control Barrier Function (CBF) constraints to derive a stable and safe controller. Using the strong duality of linear programs (LPs) and robust optimization, we convert the optimization problem to a linear program that can be efficiently solved offline. At a high level, our approach partially combines perception, planning, and real-time control into a single design problem. An additional advantage of our method is the ability to produce controllers capable of exhibiting nonlinear behavior while relying solely on an offline LP for control synthesis.