pwc-archive/papers-with-abstracts huggingface dataset:
Distributed Energy Trading Management for Renewable Prosumers with HVAC and Energy Storage
Authors: Qing Yang, Hao Wang
Date: 2021-05-01 00:00:00
Tasks: Distributed Optimization, energy management, energy trading, Management

Heating, ventilating, and air-conditioning (HVAC) systems consume a large amount of energy in residential houses and buildings. Effective energy management of HVAC is a cost-effective way to improve energy efficiency and reduce the energy cost of residential users. This work develops a novel distributed method for the residential transactive energy system that enables multiple users to interactively optimize their energy management of HVAC systems and behind-the-meter batteries. Specifically, this method effectively reduces the cost of smart homes by employing energy trading among users to leverage their power usage flexibility without compromising the users' privacy. To achieve this goal, we design a distributed optimization algorithm based on the alternating direction method of multipliers (ADMM) to automatically operate the HVAC system and batteries, which minimizes the energy costs of users. Specifically, we decouple the optimization problem into a primal subproblem and a dual subproblem. The primal subproblem is solved by the users, and the dual subproblem is solved by the grid operator. Unlike the existing centralized method, our approach only uses the users' private information locally for solving the primal subproblem hence preserves the users' privacy. Using real-world data, we validate our proposed algorithm through extensive simulations in Matlab. The results demonstrate that our method effectively incentivizes the energy trading among the users to reduce users' peak load and reduce the overall energy cost of the system by 23% on average.
Detection and Inference of Randomness-based Behavior for Resilient Multi-vehicle Coordinated Operations
Authors: Paul J Bonczek, Nicola Bezzo
Date: 2021-04-30 00:00:00

A resilient multi-vehicle system cooperatively performs tasks by exchanging information, detecting, and removing cyber attacks that have the intent of hijacking or diminishing performance of the entire system. In this paper, we propose a framework to: i) detect and isolate misbehaving vehicles in the network, and ii) securely encrypt information among the network to alert and attract nearby vehicles toward points of interest in the environment without explicitly broadcasting safety-critical information. To accomplish these goals, we leverage a decentralized virtual spring-damper mesh physics model for formation control on each vehicle. To discover inconsistent behavior of any vehicle in the network, we consider an approach that monitors for changes in sign behavior of an inter-vehicle residual that does not match with an expectation. Similarly, to disguise important information and trigger vehicles to switch to different behaviors, we leverage side-channel information on the state of the vehicles and characterize a hidden spring-damper signature model detectable by neighbor vehicles. Our framework is demonstrated in simulation and experiments on formations of unmanned ground vehicles (UGVs) in the presence of malicious man-in-the-middle communication attacks.
Detection of Hidden Attacks on Cyber-Physical Systems from Serial Magnitude and Sign Randomness Inconsistencies
Authors: Paul J Bonczek, Nicola Bezzo
Date: 2021-04-30 00:00:00
Tasks: Fault Detection

Stealthy false data injection attacks on cyber-physical systems (CPSs) introduce erroneous measurement information to on-board sensors with the purpose to degrade system performance. An intelligent attacker is able to leverage knowledge of the system model and noise characteristics to alter sensor measurements while remaining undetected. To achieve this objective, the stealthy attack sequence is designed such that the detector performs similarly in the attacked and attack-free cases. Consequently, an attacker that wants to remain hidden will leave behind traces of inconsistent behavior, contradicting the system model. To deal with this problem, we propose a runtime monitor to find these inconsistencies in sensor measurements by monitoring for serial inconsistencies of the detection test measure. Specifically, we employ the chi-square fault detection procedure to monitor the magnitude and signed sequence of its chi-square test measure. We validate our approach with simulations on an unmanned ground vehicle (UGV) under stealthy attacks and compare the detection performance with various state-of-the-art anomaly detectors.
Impact on power system transient stability of AC-line-emulation controllers of VSC-HVDC links
Authors: Javier Renedo, Lukas Sigrist, Luis Rouco, Aurelio Garcia-Cerrada
Date: 2021-04-30 00:00:00

High voltage direct current links based on voltage source converters (VSC-HVDC) embedded in alternating current (AC) systems are receiving a great deal of attention recently because they can contribute positively to the flexibilisation of modern power systems. Among several possibilities, AC-line-emulation control has been highlighted as an simple-but-useful alternative for these type of systems. With this strategy, the power flow through the link is controlled proportionally to the angle difference between its two AC terminals and this provides self-adaptation of the power flow in case of contingencies in the parallel AC lines, naturally. Although this controller is mainly concerned with steady state, it can also have an impact on the dynamic behaviour of the system, which has not been sufficiently analysed. Along this line, this paper analyses the impact of AC-line-emulation controllers of VSC-HVDC on power system transient stability. Nonlinear time-domain simulations were carried out by using PSS/E on a small test system with an embedded point-to-point VSC-HVDC link. The critical clearing time (CCT) of a test fault has been used to assess transient-stability margins of the whole system. The paper provides recommendations for the design of AC-line-emulation controllers in order to ensure that transient stability is not jeopardised.
Envisioning security control in renewable dominated power systems through stochastic multi-period AC security constrained optimal power flow
Authors: Mohammad Iman Alizadeh, Muhammad Usman, Florin Capitanescu
Date: 2021-04-30 00:00:00
Tasks: Management

The accelerated penetration rate of renewable energy sources (RES) brings environmental benefits at the expense of increasing operation cost and undermining the satisfaction of the N-1 security criterion. To address the latter issue, this paper envisions N-1 security control in RES dominated power systems through stochastic multi-period AC security constrained optimal power flow (SCOPF). The paper extends the state-of-the-art, i.e. deterministic and single time period AC SCOPF, to capture two new dimensions, RES stochasticity and multiple time periods, as well as emerging sources of flexibility such as flexible loads (FL) and energy storage systems (ESS). Accordingly, the paper proposes and solves for the first time a new problem formulation in the form of stochastic multi-period AC SCOPF (S-MP-SCOPF). The S-MP-SCOPF is formulated as a non-linear programming (NLP) problem. It computes optimal setpoints of flexibility resources and other conventional control means for congestion management and voltage control in day-ahead operation. Another salient feature of this paper is the comprehensive and accurate modelling, using: AC power flow model for both pre-contingency and post-contingency states, inter-temporal constraints for resources such as FL and ESS in a 24-hours time horizon and RES uncertainties. The importance and performances of the proposed model through a direct approach, pushing the problem size up to the solver limit, are illustrated on two test systems of 5 nodes and 60 nodes, respectively, while future work will develop a tractable algorithm.
Privacy-Preserving Co-synthesis Against Sensor-Actuator Eavesdropping Intruder
Authors: Ruochen Tai, Liyong Lin, Yuting Zhu, Rong Su
Date: 2021-04-30 00:00:00
Tasks: Privacy Preserving

In this work, we investigate the problem of privacy-preserving supervisory control against an external passive intruder via co-synthesis of dynamic mask, edit function, and supervisor for opacity enforcement and requirement satisfaction. We attempt to achieve the following goals: 1) the system secret cannot be inferred by the intruder, i.e., opacity of secrets against the intruder, and the existence of the dynamic mask and the edit function should not be discovered by the intruder, i.e., covertness of dynamic mask and edit function against the intruder; 2) the closed-loop system behaviors should satisfy some safety and nonblockingness requirement. We assume the intruder can eavesdrop both the sensing information generated by the sensors and the control commands issued to the actuators, and we refer to such an intruder as a sensor-actuator eavesdropping intruder. Our approach is to model the co-synthesis problem as a distributed supervisor synthesis problem in the Ramadge-Wonham supervisory control framework, and we propose an incremental synthesis heuristic to incrementally synthesize a dynamic mask, an edit function, and a supervisor, which consists of three steps: 1) we first synthesize an ensemble ME of dynamic mask and edit function to ensure the opacity and the covertness against a sensor eavesdropping but command non-eavesdropping intruder, and marker-reachability; 2) we then decompose ME into a dynamic mask and an edit function by using a constraint-based approach, with the help of a Boolean satisfiability (SAT) solver; 3) finally, we synthesize a supervisor such that opacity and covertness can be ensured against the sensor-actuator eavesdropping intruder, and at the same time safety and nonblockingness requirement can be ensured. The effectiveness of our approach is illustrated on an example about the enforcement of location privacy for an autonomous vehicle.
On the Undesired Equilibria Induced by Control Barrier Function Based Quadratic Programs
Authors: Xiao Tan, Dimos V. Dimarogonas
Date: 2021-04-30 00:00:00

In this paper, we analyze the system behavior for general nonlinear control-affine systems when a control barrier function-induced quadratic program-based controller is employed for feedback. In particular, we characterize the existence and locations of possible equilibrium points of the closed-loop system and also provide analytical results on how design parameters affect them. Based on this analysis, a simple modification on the existing quadratic program-based controller is provided, which, without any assumptions other than those taken in the original program, inherits the safety set forward invariance property, and further guarantees the complete elimination of undesired equilibrium points in the interior of the safety set as well as one type of boundary equilibrium points, and local asymptotic stability of the origin. Numerical examples are given alongside the theoretical discussions.
A Thermodynamic based and Data Driven Hybrid Network for Gas Turbine Modeling
Authors: Likun Ren
Date: 2021-04-30 00:00:00

The on-wing engine performance is difficult to track for thermodynamic models because of its inaccurate component maps, and also difficult for data driven methods for their over-fitting to measurement errors. So, we propose a thermodynamic based and data driven hybrid network for gas turbine modeling. Different from thermodynamic models, our network reconstructs the component characteristics in a data-driven way to take component degeneration and individual difference into consideration. Moreover, different from data driven methods, in the training phase, physical based equations and the analytical mathematical description are used to ensure that the optimization converges to the gas turbine's dynamics. A huge number of relaxed quasi steady state flight data to 26970 is used to train and test our hybrid network. The result shows that the accuracy of our hybrid network can reach about 7% measured by max T6 relative error, 5% better than map fitting based thermodynamic model and 8% better than pure data driven method with similar model volume.
A Compact Model for SiC Power MOSFETs for Large Current and High Voltage Operation
Authors: Cristino Salcines, Sourabh Khandelwal, Ingmar Kallfass
Date: 2021-04-30 00:00:00

This work presents a physics based compact model for SiC power MOSFETs that accurately describes the I-V characteristics up to large voltages and currents. Charge-based formulations accounting for the different physics of SiC power MOSFETs are presented. The formulations account for the effect of the large SiC/SiO2 interface traps density characteristic of SiC MOSFETs and its dependence with temperature. The modeling of interface charge density is found to be necessary to describe the electrostatics of SiC power MOSFETs when operating at simultaneous high current and high voltage regions. The proposed compact model accurately fits the measurement data extracted of a 160 milli ohms, 1200V SiC power MOSFET in the complete IV plane from drain-voltage $V_d$ = 5mV up to 800 V and current ranges from few mA to 30 A.
A Novel Real-Time Energy Management Strategy for Grid-Supporting Microgrid: Enabling Flexible Trading Power
Authors: Cunzhi Zhao, Xingpeng Li
Date: 2021-04-29 00:00:00
Tasks: energy management, Management

In recent years, there has been significant growth of distributed energy resources (DERs) penetration in the power grid. The stochastic and intermittent features of variable DERs such as roof top photovoltaic (PV) bring substantial uncertainties to the grid on the consumer end and weaken the grid reliability. In addition, the fact that numerous DERs are widespread in the grid makes it hard to monitor and manage DERs. To address this challenge, this paper proposes a novel real-time grid-supporting energy management (GSEM) strategy for grid-supporting microgrid (MG). This strategy can not only properly manage DERs in a MG but also enable DERs to provide grid services, which enables a MG to be grid-supporting via flexible trading power. The proposed GSEM strategy is based on a 2-step optimization which includes a routine economic dispatch (ED) step and an acceptable trading power range determination step. Numerical simulations demonstrate the performance of the proposed GSEM strategy which enables the grid operator to have a dispatch choice of trading power with MG and enhance the reliability and resilience of the main grid.
Intelligent Decision Method for Main Control Parameters of Tunnel Boring Machine based on Multi-Objective Optimization of Excavation Efficiency and Cost
Authors: Bin Liu, Yaxu Wang, Guangzu Zhao, Bin Yang, Ruirui Wang, Dexiang Huang, Bin Xiang
Date: 2021-04-29 00:00:00

Timely and reasonable matching of the control parameters and geological conditions of the rock mass in tunnel excavation is crucial for hard rock tunnel boring machines (TBMs). Therefore, this paper proposes an intelligent decision method for the main control parameters of the TBM based on the multi-objective optimization of excavation efficiency and cost. The main objectives of this method are to obtain the most important parameters of the rock mass and machine, determine the optimization objective, and establish the objective function. In this study, muck information was included as an important parameter in the traditional rock mass and machine parameter database. The rock-machine interaction model was established through an improved neural network algorithm. Using 250 sets of data collected in the field, the validity of the rock-machine interaction relationship model was verified. Then, taking the cost as the optimization objective, the cost calculation model related to tunneling and the cutter was obtained. Subsequently, combined with rock-machine interaction model, the objective function of control parameter optimization based on cost was established. Finally, a tunneling test was carried out at the engineering site, and the main TBM control parameters (thrust and torque) after the optimization decision were used to excavate the test section. Compared with the values in the section where the TBM operators relied on experience, the average penetration rate of the TBM increased by 11.10%, and the average cutter life increased by 15.62%. The results indicate that this method can play an effective role in TBM tunneling in the test section.
Comparing Power Processing System Approaches in Second-Use Battery Energy Buffering for Electric Vehicle Charging
Authors: Xiaofan Cui, Alireza Ramyar, Jason Siegel, Peyman Mohtat, Anna Stefanopoulou, Al-Thaddeus Avestruz
Date: 2021-04-29 00:00:00

The heterogeneity in pack voltages and capacity of aged packs limits the performance and economic viability of second-use battery energy storage systems (2-BESS) due to issues of reliability and available energy. Overcoming these limitations could enable extended use of batteries and improve the environmental impacts of electric vehicles by reducing the number of batteries produced. This paper compares Lite-Sparse Hierarchical Partial Power Processing (LS-HiPPP), a new method for power processing in 2-BESS, to conventional power processing architectures using a stochastic EV charging plaza model. This method for performance evaluation allows a fair comparison among power processing architectures for 2-BESS. Results show that LS-HiPPP increases the battery energy utilization to 94% as compared to 78% for conventional partial power processing (C-PPP) and 23% for full power processing. These results were obtained with 25% heterogeneity in individual battery capacities and 20% power processing within the 2-BESS. Derating and captured value are two derived performance metrics for comparing LS-HiPPP and C-PPP in this work. The derating for LS-HiPPP is 84.3% in comparison to 63.1% for C-PPP. The captured value for LS-HiPPP is 79.8% versus 51% for C-PPP.
AI-assisted super-resolution cosmological simulations II: Halo substructures, velocities and higher order statistics
Authors: Yueying Ni, Yin Li, Patrick Lachance, Rupert A. C. Croft, Tiziana Di Matteo, Simeon Bird, Yu Feng
Date: 2021-05-03 00:00:00
Tasks: Super-Resolution

In this work, we expand and test the capabilities of our recently developed super-resolution (SR) model to generate high-resolution (HR) realizations of the full phase-space matter distribution, including both displacement and velocity, from computationally cheap low-resolution (LR) cosmological N-body simulations. The SR model enhances the simulation resolution by generating 512 times more tracer particles, extending into the deeply non-linear regime where complex structure formation processes take place. We validate the SR model by deploying the model in 10 test simulations of box size 100 Mpc/h, and examine the matter power spectra, bispectra and 2D power spectra in redshift space. We find the generated SR field matches the true HR result at percent level down to scales of k ~ 10 h/Mpc. We also identify and inspect dark matter halos and their substructures. Our SR model generate visually authentic small-scale structures, that cannot be resolved by the LR input, and are in good statistical agreement with the real HR results. The SR model performs satisfactorily on the halo occupation distribution, halo correlations in both real and redshift space, and the pairwise velocity distribution, matching the HR results with comparable scatter, thus demonstrating its potential in making mock halo catalogs. The SR technique can be a powerful and promising tool for modelling small-scale galaxy formation physics in large cosmological volumes.
Optogenetic control of intracellular flows and cell migration: a comprehensive mathematical analysis with a minimal active gel model
Authors: Oliver M. Drozdowski, Falko Ziebert, Ulrich S. Schwarz
Date: 2021-04-29 00:00:00

The actin cytoskeleton of cells is in continuous motion due to both polymerization of new filaments and their contraction by myosin II molecular motors. Through adhesion to the substrate, such intracellular flow can be converted into cell migration. Recently, optogenetics has emerged as a new powerful experimental method to control both actin polymerization and myosin II contraction. While optogenetic control of polymerization can initiate cell migration by generating protrusion, it is less clear if and how optogenetic control of contraction can also affect cell migration. Here we analyze the latter situation using a minimal variant of active gel theory into which we include optogenetic activation as a spatiotemporally constrained perturbation. The model can describe the symmetrical flow of the actomyosin system observed in optogenetic experiments, but not the long-lasting polarization required for cell migration. Motile solutions become possible if cytoskeletal polymerization is included through the boundary conditions. Optogenetic activation of contraction can then initiate locomotion in a symmetrically spreading cell and strengthen motility in an asymmetrically polymerizing one. If designed appropriately, it can also arrest motility even for protrusive boundaries.
A transport approach to relate asymmetric protein segregation and population growth
Authors: Jiseon Min, Ariel Amir
Date: 2020-12-24 00:00:00

Many unicellular organisms allocate their key proteins asymmetrically between the mother and daughter cells, especially in a stressed environment. A recent theoretical model is able to predict when the asymmetry in segregation of key proteins enhances the population fitness, extrapolating the solution at two limits where the segregation is perfectly asymmetric (asymmetry $a$ = 1) and when the asymmetry is small ($0 \leq a \ll 1$). We generalize the model by introducing stochasticity and use a transport equation to obtain a self-consistent equation for the population growth rate and the distribution of the amount of key proteins. We provide two ways of solving the self-consistent equation: numerically by updating the solution for the self-consistent equation iteratively and analytically by expanding moments of the distribution. With these more powerful tools, we can extend the previous model by Lin et al. to include stochasticity to the segregation asymmetry. We show the stochastic model is equivalent to the deterministic one with a modified effective asymmetry parameter ($a_{\rm eff}$). We discuss the biological implication of our models and compare with other theoretical models.
Quasiperiodic functions theory and the superlattice potentials for a two-dimensional electron gas
Authors: Andrei Ya. Maltsev
Date: 2003-02-02 00:00:00

We consider Novikov problem of the classification of level curves of quasiperiodic functions on the plane and its connection with the conductivity of two-dimensional electron gas in the presence of both orthogonal magnetic field and the superlattice potentials of special type. We show that the modulation techniques used in the recent papers on the 2D heterostructures permit to obtain general quasiperiodic potentials for 2D electron gas and consider the asymptotic limit of conductivity when $\tau \rightarrow \infty$. Using the theory of quasiperiodic functions we introduce here the topological characteristics of such potentials observable in the conductivity. The corresponding characteristics are the direct analog of the "topological numbers" introduced previously in the conductivity of normal metals.