pwc-archive/papers-with-abstracts huggingface dataset:
CHoKI-based MPC for blood glucose regulation in Artificial Pancreas
Authors: Beatrice Sonzogni, José María Manzano, Marco Polver, Fabio Previdi, Antonio Ferramosca
Date: 2024-01-30 00:00:00
Tasks: Model Predictive Control

This work presents a Model Predictive Control (MPC) for the artificial pancreas, which is able to autonomously manage basal insulin injections in type 1 diabetic patients. Specifically, the MPC goal is to maintain the patients' blood glucose level inside the safe range of 70-180 mg/dL, acting on the insulin amount and respecting all the imposed constraints, taking into consideration also the Insulin On Board (IOB), to avoid excess of insulin infusion. MPC uses a model to make predictions of the system behaviour. In this work, due to the complexity of the diabetes disease that complicates the identification of a general physiological model, a data-driven learning method is employed instead. The Componentwise H\"{o}lder Kinky Inference (CHoKI) method is adopted, to have a customized controller for each patient. For the data collection phase and also to test the proposed controller, the virtual patients of the FDA-accepted UVA/Padova simulator are exploited. The proposed MPC is also tested on a modified version of the simulator, that takes into consideration also the variability of the insulin sensitivity. The final results are satisfying since the proposed controller reduces the time in hypoglycemia (which is more dangerous) if compared to the outcome obtained with the standard constant basal insulin therapy provided by the simulator, satisfying also the time in range requirements and avoiding long-term hyperglycemia events.
Study of Applicability of Simple Closed Loop Input Impedance Model for Grid-Tie Inverters
Authors: Daniel Santamargarita, Francisco Huerta, Marina Sanz, Antonio Lazaro, Salvatore DArco, Santiago Sanchez, Elisabetta Tedeschi, Javier Roldan
Date: 2024-01-30 00:00:00

In recent years the need for DC distribution buses has increased considerably. As it can be noticed in the transport for example the distribution systems of the more electric aircrafts, ships, or electric cars. Given the complexities of the systems presented above, the need to use more and more switched power converters has arisen. The main problem of the connection of multiple controlled switched converters acting as source and load is the degradation of stability that occurs on the DC distribution bus due to the converter interactions. To study the stability in the distribution bus there are some wellestablished criteria. These criteria require knowledge of the input impedance of the converters that act as load and the output impedance of the equipment that acts as source. In order to reduce the complexity of obtaining the input impedance a model based on a controlled converter acting as a constant power load (CPL) is commonly used. This article studies the accuracy of this model for a commonly used topology in distribution systems nowadays, Two Level Voltage Source Converter (2L-VSC), studying different scenarios that make the model become inaccurate.
Platoon Fundamental Diagram estimation can be Markovian: evidence from human- and self-driven vehicle trajectories
Authors: Michail A. Makridis, Anastasios Kouvelas, Jorge A. Laval
Date: 2024-01-30 00:00:00

We propose a simple and effective method to derive the Fundamental Diagram (FD) from platoon vehicle trajectories. Average traffic state variables are computed using Edie's generalized definitions within time-dependent trapezoidal space-time areas. To obtain a clear FD, we employ a bivariate data aggregation technique to eliminate scatter. Our findings are as follows: (i) The proposed method demonstrates a remarkably consistent relation between the traffic variables and a clear triangular shape for autonomously-driven vehicles. (ii) The FDs are invariant to several factors of heterogeneity such as the platoon length, vehicle characteristics, road particularities, and data acquisition accuracy. (iii) ACC-driven vehicle platoons with minimum headway setting achieve much higher capacity, roughly 90\% than those with a large headway setting. (iv) Connectivity might increase capacity. (v) Human drivers have a wider near-capacity operation area, showing different behaviors at high speeds than low ones, and (vi) Safety concerns might arise due to high values of backward wave speed for ACC-driven vehicles. Comparative analysis with the state-of-the-art confirms the validity of our approach. The proposed method stands out due to its simplicity and accuracy, which paves the way for practical applications in real-time traffic flow monitoring and control within modern intelligent transportation systems.
Node Flux-Linkage Synchronizing Control of Power Systems with 100% Wind Power Generation Based on Capacitor Voltage Balancing Scheme
Authors: Yang Liu, Yanshan Chen, Yuexi Yang, Xiangyu Pei, Feng Ji
Date: 2024-01-30 00:00:00

This paper proposes a node flux-linkage synchronizing control method (NFSCM) for power systems with 100% wind power generation based on a capacitor voltage balancing scheme (CVBS). Different from the conventional grid-forming controllers, NFSCM is designed to regulate inverters as virtual flux-linkage sources. Auto-synchronization of flux-linkage vectors is achieved through the CVBS-based NFSCM. The mismatch among the angular frequencies of flux-linkage vectors is eliminated by regulating the tracking errors of DC-link voltages, which establishes a negative feedback between the output frequency and active power of the inverter. NFSCM is adaptive to weak and strong grids. It avoids the excitation inrush currents in the step-up transformer of wind power generators. It also eliminates the DC components of the three-phase currents, and avoids low-frequency oscillations in active power. In order to limit the short-circuit current of inverters, a logic-based bang-bang funnel control (LBFC) is designed to control the switches of inverter bridges when over-current is detected. LBFC is able to restrict various fault currents within an acceptable range within the shortest time. LBFC and NFSCM are designed to operate in a switched manner according to a state-dependent switching strategy. Time-domain simulations were conducted on a 100% wind power generation test system, and the performance of NFSCM and LBFC were investigated.
Application of Methods of Artificial Intelligence in Systems for Continuous Automatic Monitoring of Dust Concentration and Deposits in Mine Atmosphere
Authors: Daria Trubicina, Kirill Varnavskiy, Alexander Ermakov, Fedor Nepsha, Roman Kozlov, Naser Golsanami, Sergey Zhironkin
Date: 2024-01-30 00:00:00

With the growth of coal production, the load on the production capacity of coal enterprises also increases, which leads to a concomitant increase in dust formation in both opencast and underground methods of mining coal deposits. Dust, generated during drilling, blasting operations, excavation, loading, crushing and transportation of mined rock is one of the factors that has a negative impact on the health of mining workers and on the level of environmental pollution with solid particles. Thus, increasing the efficiency of controlling the concentration of solid particles in the mine atmosphere and dust deposits is an urgent scientific and technical task. In doing so, the use of modern digital technologies within the framework of the industry 4.0 concept makes it possible to develop approaches that can significantly improve the quality of monitoring the state of the mine atmosphere at coal mining enterprises. This article provides a theoretical basis and test results for a system for continuous automatic monitoring of dust concentration in a mine atmosphere as the component of the multifunctional coal mine safety system. It is shown that monitoring the state of mine workings aerological safety can be carried out in real time through the system of the new generation using artificial intelligence. The ability of the proposed system to measure basic physical parameters affecting dust deposition (disperse composition, air humidity, dust concentration and air flow velocity) is noted.
On the Stability of Datatic Control Systems
Authors: Yujie Yang, Zhilong Zheng, Shengbo Eben Li
Date: 2024-01-30 00:00:00

The development of feedback controllers is undergoing a paradigm shift from $\textit{modelic}$ (model-driven) control to $\textit{datatic}$ (data-driven) control. Stability, as a fundamental property in control, is less well studied in datatic control paradigm. The difficulty is that traditional stability criteria rely on explicit system models, which are not available in those systems with datatic description. Some pioneering works explore stability criteria for datatic systems with special forms such as linear systems, homogeneous systems, and polynomial systems. However, these systems imply too strong assumptions on the inherent connection among data points, which do not hold in general nonlinear systems. This paper proposes a stability verification algorithm for general datatic control systems called $\eta$-testing. Our stability criterion only relies on a weak assumption of Lipschitz continuity so as to extend information from known data points to unmeasured regions. This information restricts the time derivative of any unknown state to the intersection of a set of closed balls. Inside the intersection, the worst-case time derivative of Lyapunov function is estimated by solving a quadratically constrained linear program (QCLP). By comparing the optimal values of QCLPs to zero in the whole state space, a sufficient condition of system stability can be checked. We test our algorithm on three datatic control systems, including both linear and nonlinear ones. Results show that our algorithm successfully verifies the stability, instability, and critical stability of tested systems.
Exploiting Equivariance in the Design of Tracking Controllers for Euler-Poincare Systems on Matrix Lie Groups
Authors: Matthew Hampsey, Pieter van Goor, Ravi Banavar, Robert Mahony
Date: 2024-01-30 00:00:00

The trajectory tracking problem is a fundamental control task in the study of mechanical systems. A key construction in tracking control is the error or difference between an actual and desired trajectory. This construction also lies at the heart of observer design and recent advances in the study of equivariant systems have provided a template for global error construction that exploits the symmetry structure of a group action if such a structure exists. Hamiltonian systems are posed on the cotangent bundle of configuration space of a mechanical system and symmetries for the full cotangent bundle are not commonly used in geometric control theory. In this paper, we propose a group structure on the cotangent bundle of a Lie group and leverage this to define momentum and configuration errors for trajectory tracking drawing on recent work on equivariant observer design. We show that this error definition leads to error dynamics that are themselves ``Euler-Poincare like'' and use these to derive simple, almost global trajectory tracking control for fully-actuated Euler-Poincare systems on a Lie group state space.
Plane Wave Dynamic Model of Electric Power Networks with High Shares of Inverter-Based Resources
Authors: Amirhossein Sajadi, Bri-Mathias Hodge
Date: 2024-01-30 00:00:00

Contemporary theories and models for electric power system stability are predicated on a widely held assumption that the mechanical inertia of the rotating mass of synchronous generators provides the sole contribution to stable and synchronized operation of this class of complex networks on subsecond timescales. Here we formulate the electromagnetic momentum of the field around the transmission lines that transports energy and present evidence from a real-world bulk power network that demonstrates its physical significance. We show the classical stability model for power networks that overlooks this property, known as the "swing equation", may become inadequate to analyze systems with high shares of inverter-based resources, commonly known as "low-inertia power systems". Subsequently, we introduce a plane wave dynamic model, consistent with the structural properties of emerging power systems with up to 100% inverter-based resources, which identifies the concept of inertia in power grids as a time-varying component. We leverage our theory to discuss a number of open questions in the electric power industry. Most notably, we postulate that the changing nature of power networks with a preponderance of variable renewable energy power plants could strengthen power network stability in the future; a vision which is irreconcilable with the conventional theories.
Recent Advances in Model-Based Fault Diagnosis for Lithium-Ion Batteries: A Comprehensive Review
Authors: Yiming Xu, Xiaohua Ge, Ruohan Guo, Weixiang Shen
Date: 2024-01-30 00:00:00
Tasks: Fault Diagnosis

Lithium-ion batteries (LIBs) have found wide applications in a variety of fields such as electrified transportation, stationary storage and portable electronics devices. A battery management system (BMS) is critical to ensure the reliability, efficiency and longevity of LIBs. Recent research has witnessed the emergence of model-based fault diagnosis methods in advanced BMSs. This paper provides a comprehensive review on the model-based fault diagnosis methods for LIBs. First, the widely explored battery models in the existing literature are classified into physics-based electrochemical models and electrical equivalent circuit models. Second, a general state-space representation that describes electrical dynamics of a faulty battery is presented. The formulation of the state vectors and the identification of the parameter matrices are then elaborated. Third, the fault mechanisms of both battery faults (incl. overcharege/overdischarge faults, connection faults, short circuit faults) and sensor faults (incl. voltage sensor faults and current sensor faults) are discussed. Furthermore, different types of modeling uncertainties, such as modeling errors and measurement noises, aging effects, measurement outliers, are elaborated. An emphasis is then placed on the observer design (incl. online state observers and offline state observers). The algorithm implementation of typical state observers for battery fault diagnosis is also put forward. Finally, discussion and outlook are offered to envision some possible future research directions.
Implications of Zoning Ordinances for Rural Utility-Scale Solar Deployment and Power System Decarbonization in the Great Lakes Region
Authors: Papa Yaw Owusu-Obeng, Sarah Banas Mills, Michael T. Craig
Date: 2024-01-29 00:00:00

Local zoning ordinances across the United States have the impact of restricting development of energy infrastructure, including utility-scale solar photovoltaics. While these ordinances may be developed for legitimate purposes to protect public health and safety, they could impede or increase costs of power sector decarbonization. We quantify the role of utility-scale solar zoning ordinances on power sector decarbonization across the Great Lakes region (Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin) by integrating 6,300 rural community zoning ordinances into a power system planning model. Relative to no ordinances, solar zoning ordinances reduce total potential deployment of solar PV by 52% (or 1.6 TW) across our region. Currently, however, the biggest zoning barrier to deployment is zoning ordinances which are silent on utility-scale solar. Deployment restrictions translate to up to 4 GW greater investment needs and 5.6% greater PV investment costs to achieve a 10% PV generation target. Starker shifts occur at the state level, e.g. Wisconsin sees a 40% reduction in PV investments due to zoning restrictions. Our results underscore the need for planning that aligns local zoning laws with state and regional goals.
Towards Robust and Scalable Dispatch Modeling of Long-Duration Energy Storage
Authors: Omar J. Guerra, Sourabh Dalvi, Amogh A. Thatte, Brady Cowiestoll, Jennie Jorgenson, Bri-Mathias Hodge
Date: 2024-01-29 00:00:00
Tasks: Scheduling

Existing modeling approaches for long-duration energy storage (LDES) are often based either on an oversimplified representation of power system operations or limited representation of storage technologies, e.g., evaluation of only a single application. This manuscript presents an overview of the challenges of modeling LDES technologies, as well as a discussion regarding the capabilities and limitations of existing approaches. We used two test power systems with high shares of both solar photovoltaics- and wind (70% - 90% annual variable renewable energy shares) to assess LDES dispatch approaches. Our results estimate that better dispatch modeling of LDES could increase the associated operational value by 4% - 14% and increase the standard capacity credit by 14% - 34%. Thus, a better LDES dispatch could represent significant cost saving opportunities for electric utilities and system operators. In addition, existing LDES dispatch modeling approaches were tested in terms of both improved system value (e.g., based on production cost and standard capacity credit) and scalability (e.g., based on central processing unit time and peak memory usage). Both copper plate and nodal representations of the power system were considered. Although the end volume target dispatch approach, i.e., based on mid-term scheduling, showed promising performance in terms of both improved system value and scalability, there is a need for robust and scalable dispatch approaches for LDES in transmission-constrained electric grids. Moreover, more research is required to better understand the optimal operation of LDES considering extreme climate/weather events, reliability applications, and power system operational uncertainties.
Stochastic Hybrid System Modeling and State Estimation of Modern Power Systems under Contingency
Authors: Shuo Yuan, Le Yi Wang, George Yin, Masoud H. Nazari
Date: 2024-01-29 00:00:00
Tasks: State Estimation

This paper introduces a stochastic hybrid system (SHS) framework in state space model to capture sensor, communication, and system contingencies in modern power systems (MPS). Within this new framework, the paper concentrates on the development of state estimation methods and algorithms to provide reliable state estimation under randomly intermittent and noisy sensor data. MPSs employ diversified measurement devices for monitoring system operations that are subject to random measurement errors and rely on communication networks to transmit data whose channels encounter random packet loss and interruptions. The contingency and noise form two distinct and interacting stochastic processes that have a significant impact on state estimation accuracy and reliability. This paper formulates stochastic hybrid system models for MPSs, introduces coordinated observer design algorithms for state estimation, and establishes their convergence and reliability properties. A further study reveals a fundamental design tradeoff between convergence rates and steady-state error variances. Simulation studies on the IEEE 5-bus system and IEEE 33-bus system are used to illustrate the modeling methods, observer design algorithms, convergence properties, performance evaluations, and impact sensor system selections.
Discontinuous PWM Strategy with Frequency Modulation for Vibration Reduction in Asynchronous Machines
Authors: A Ruiz-Gonzalez, JR Heredia-Larrubia, FM Perez-Hidalgo, M Meco-Gutierrez
Date: 2024-01-29 00:00:00

The objective of this research is to mitigate vibrations in induction motors. To achieve this goal, a discontinuous pulse width modulation (PWM) control strategy based on carrier wave modulation is proposed for multilevel inverters. This study provides justification for the reduction of machine vibrations compared to existing control techniques documented in the technical literature. Additionally, the proposed technique offers the advantage of attenuating the Total Harmonic Distortion of the multilevel inverter's output voltage while simultaneously achieving a higher RMS value for the same DC level. By modifying a parameter of the carrier wave, the control strategy allows for variations in the electrical spectrum while avoiding natural mechanical resonance frequencies, thereby reducing motor vibrations. Laboratory results demonstrating the application of different modulation strategies in a multilevel inverter for an induction motor and a comparison with the presented strategy are provided
Practical Framework for Problem-Based Learning in an Introductory Circuit Analysis Course
Authors: Sebastian Martin, Salvador Pineda, Juan Perez-Ruiz, Natalia Alguacil, Antonio Ruiz-Gonzalez
Date: 2024-01-29 00:00:00
Tasks: Scheduling

Introductory courses on electric circuits at undergraduate level are usually presented in quite abstract terms, with questions and problems quite far from practical problems. This causes the students have difficulties to apply that theory to solve practical technical problems. On the other hand, electric circuits are everywhere in our lives, so we have plenty of real practical problems. Here we compile a selection of practical contexts suited for implementing Problem Based Learning approach in an introductory course on circuit analysis. And some examples describing the gamification process that uses these problems to build single-player role-playing games that fulfil the course contents and scheduling. The key point of the assessment and how it is related to the progress in the game is also described.
Digital requirements engineering with an INCOSE-derived SysML meta-model
Authors: James S. Wheaton, Daniel R. Herber
Date: 2024-01-29 00:00:00
Tasks: Attribute

Traditional requirements engineering tools do not readily access the SysML-defined system architecture model, often resulting in ad-hoc duplication of model elements that lacks the connectivity and expressive detail possible in a SysML-defined model. Without that model connectivity, requirement quality can suffer due to imprecision and inconsistent terminology, frustrating communication during system development. Further integration of requirements engineering activities with MBSE contributes to the Authoritative Source of Truth while facilitating deep access to system architecture model elements for V&V activities. The Model-Based Structured Requirement SysML Profile was extended to comply with the INCOSE Guide to Writing Requirements updated in 2023 while conforming to the ISO/IEC/IEEE 29148 standard requirement statement templates. Rules, Characteristics, and Attributes were defined in SysML according to the Guide to facilitate requirements definition and requirements V&V. The resulting SysML Profile was applied in two system architecture models at NASA Jet Propulsion Laboratory, allowing us to explore its applicability and value in real-world project environments. Initial results indicate that INCOSE-derived Model-Based Structured Requirements may rapidly improve requirement expression quality while complementing the NASA Systems Engineering Handbook checklist and guidance, but typical requirement management activities still have challenges related to automation and support with the system architecture modeling software.