SearcharxivSearch

arXiv subjects

Juan Ospina

Publications and source records attributed to Juan Ospina.

At least 19 recordsLinked to original sources

Technical Report on Resilient and Secure Large-Scale Energy Internet Systems

This IEEE PES Task Force report examines the security and resilience of large-scale Energy Internet (EI) systems, in which electricity, information, and market layers are tightly coupled through pervasive digitalization. The report characterizes the EI cyber-physical threat landscape and surveys detection, assurance, and mitigation techniques, presents modeling, control, and decision-making frameworks that capture cyber-physical interdependencies, including storage integration, multi-dimensional resilience, and electricity price forecasting, examines adversarial risks and trustworthy deployment of artificial intelligence, and introduces graph-based, attack-resilient information routing. The report closes with recommendations for research, standardization, and regulatory efforts needed to realize a resilient and secure large-scale EI.

eess.SY

Smoothed Two-Stage Decomposition Algorithm for Solving Large-Scale Transmission and Distribution AC-OPF Problems

The integration of distributed energy resources (DERs) into the power grid has introduced new challenges to AC optimal power flow (AC-OPF) problems. Traditional OPF optimize consider transmission systems, treating distribution networks as static loads. However, the growing presence of DERs makes accurate distribution system modeling crucial for grid operations. Consequently, efficiently solving the resultant large-scale, nonconvex transmission and distribution (T&D) AC-OPF problem remains a significant challenge. This paper proposes a Smoothed Two-Stage Decomposition Optimizer (StsDOpt) to address these complexities by decomposing the T&D AC-OPF problem into a master-subproblem(s) structure, enabling parallel solving. Unlike traditional methods, StsDOpt does not rely on approximations or relaxations. It uses a smoothing technique to render the subproblems responses differentiable with respect to the master problem, leveraging the barrier problem properties inherent in primal-dual interior point methods. This approach is crucial for accurately modeling and solving distribution systems, which are multiphase, unbalanced, and nonlinear, distinguishing StsDOpt apart from other methods. Integrated into the PowerModelsITD framework, StsDOpt has been validated through numerical experiments, demonstrating reduced wall-clock solve time and increased scalability. Results highlight its efficacy as a robust, scalable solution for large-scale T&D AC-OPF problems, facilitating the reliable integration of DERs into complex T&D systems.

math.OC

Modeling and Rapid Prototyping of Integrated Transmission-Distribution OPF Formulations with PowerModelsITD.jl

Conventional electric power systems are composed of different unidirectional power flow stages of generation, transmission, and distribution, managed independently by transmission system and distribution system operators. However, as distribution systems increase in complexity due to the integration of distributed energy resources, coordination between transmission and distribution networks will be imperative for the optimal operation of the power grid. However, coupling models and formulations between transmission and distribution is non-trivial, in particular due to the common practice of modeling transmission systems as single-phase, and distribution systems as multi-conductor phase-unbalanced. To enable the rapid prototyping of power flow formulations, in particular in the modeling of the boundary conditions between these two seemingly incompatible data models, we introduce PowerModelsITD.jl, a free, open-source toolkit written in Julia for integrated transmission-distribution (ITD) optimization that leverages mature optimization libraries from the InfrastructureModels.jl-ecosystem. The primary objective of the proposed framework is to provide baseline implementations of steady-state ITD optimization problems, while providing a common platform for the evaluation of emerging formulations and optimization problems. In this work, we introduce the nonlinear formulations currently supported in PowerModelsITD.jl, which include AC-polar, AC-rectangular, current-voltage, and a linear network transportation model. Results are validated using combinations of IEEE transmission and distribution networks.

eess.SY

CPES-QSM: A Quantitative Method Towards the Secure Operation of Cyber-Physical Energy Systems

Power systems are evolving into cyber-physical energy systems (CPES) due to the integration of modern communication and Internet-of-Things (IoT) devices. CPES security evaluation is challenging since the physical and cyber layers are often not considered holistically. Existing literature focuses on only optimizing the operation of either the physical or cyber layer while ignoring the interactions between them. This paper proposes a metric, the Cyber-Physical Energy System Quantitative Security Metric (CPES-QSM), that quantifies the interaction between the cyber and physical layers across three domains: electrical, cyber-risk, and network topology. A method for incorporating the proposed cyber-metric into operational decisions is also proposed by formulating a cyber-constrained AC optimal power flow (C-ACOPF) that considers the status of all the CPES layers. The cyber-constrained ACOPF considers the vulnerabilities of physical and cyber networks by incorporating factors such as voltage stability, contingencies, graph-theory, and IoT cyber risks, while using a multi-criteria decision-making technique. Simulation studies are conducted using standard IEEE test systems to evaluate the effectiveness of the proposed metric and the C-ACOPF formulation.

eess.SY

Load-Altering Attacks Against Power Grids under COVID-19 Low-Inertia Conditions

The COVID-19 pandemic has impacted our society by forcing shutdowns and shifting the way people interacted worldwide. In relation to the impacts on the electric grid, it created a significant decrease in energy demands across the globe. Recent studies have shown that the low demand conditions caused by COVID-19 lockdowns combined with large renewable generation have resulted in extremely low-inertia grid conditions. In this work, we examine how an attacker could exploit these {scenarios} to cause unsafe grid operating conditions by executing load-altering attacks (LAAs) targeted at compromising hundreds of thousands of IoT-connected high-wattage loads in low-inertia power systems. Our study focuses on analyzing the impact of the COVID-19 mitigation measures on U.S. regional transmission operators (RTOs), formulating a plausible and realistic least-effort LAA targeted at transmission systems with low-inertia conditions, and evaluating the probability of these large-scale LAAs. Theoretical and simulation results are presented based on the WSCC 9-bus {and IEEE 118-bus} test systems. Results demonstrate how adversaries could provoke major frequency disturbances by targeting vulnerable load buses in low-inertia systems and offer insights into how the temporal fluctuations of renewable energy sources, considering generation scheduling, impact the grid's vulnerability to LAAs.

cs.CR

Faster than Real-Time Simulation: Methods, Tools, and Applications

Real-time simulation enables the understanding of system operating conditions by evaluating simulation models of physical components running synchronized at the real-time wall clock. Leveraging the real-time measurements of comprehensive system models, faster than real-time (FTRT) simulation allows the evaluation of system architectures at speeds faster than real-time. FTRT simulation can assist in predicting the system's behavior efficiently, thus assisting the operation of system processes. Namely, the provided acceleration can be used for improving system scheduling, assessing system vulnerabilities, and predicting system disruptions in real-time systems. The acceleration of simulation times can be achieved by utilizing digital real-time simulators (RTS) and high-performance computing (HPC) architectures. FTRT simulation has been widely used, among others, for the operation, design, and investigation of power system events, building emergency management plans, wildfire prediction, etc. In this paper, we review the existing literature on FTRT simulation and its applications in different disciplines, with a particular focus on power systems. We present existing system modeling approaches, simulation tools and computing frameworks, and stress the importance of FTRT accuracy.

eess.SY

Cyber-Physical Energy Systems Security: Threat Modeling, Risk Assessment, Resources, Metrics, and Case Studies

Cyber-physical systems (CPS) are interconnected architectures that employ analog, digital, and communication resources for their interaction with the physical environment. CPS are the backbone of enterprise, industrial, and critical infrastructure. Thus, their vital importance makes them prominent targets for malicious attacks aiming to disrupt their operations. Attacks targeting cyber-physical energy systems (CPES), given their mission-critical nature, can have disastrous consequences. The security of CPES can be enhanced leveraging testbed capabilities to replicate power system operations, discover vulnerabilities, develop security countermeasures, and evaluate grid operation under fault-induced or maliciously constructed scenarios. In this paper, we provide a comprehensive overview of the CPS security landscape with emphasis on CPES. Specifically, we demonstrate a threat modeling methodology to accurately represent the CPS elements, their interdependencies, as well as the possible attack entry points and system vulnerabilities. Leveraging the threat model formulation, we present a CPS framework designed to delineate the hardware, software, and modeling resources required to simulate the CPS and construct high-fidelity models which can be used to evaluate the system's performance under adverse scenarios. The system performance is assessed using scenario-specific metrics, while risk assessment enables system vulnerability prioritization factoring the impact on the system operation. The overarching framework for modeling, simulating, assessing, and mitigating attacks in a CPS is illustrated using four representative attack scenarios targeting CPES. The key objective of this paper is to demonstrate a step-by-step process that can be used to enact in-depth cybersecurity analyses, thus leading to more resilient and secure CPS.

cs.CR

On the Feasibility of Load-Changing Attacks in Power Systems during the COVID-19 Pandemic

The electric power grid is a complex cyberphysical energy system (CPES) in which information and communication technologies (ICT) are integrated into the operations and services of the power grid infrastructure. The growing number of Internet-of-things (IoT) high-wattage appliances, such as air conditioners and electric vehicles, being connected to the power grid, together with the high dependence of ICT and control interfaces, make CPES vulnerable to high-impact, low-probability load-changing cyberattacks. Moreover, the side-effects of the COVID-19 pandemic demonstrate a modification of electricity consumption patterns with utilities experiencing significant net-load and peak reductions. These unusual sustained low load demand conditions could be leveraged by adversaries to cause frequency instabilities in CPES by compromising hundreds of thousands of IoT-connected high-wattage loads. This paper presents a feasibility study of the impacts of load-changing attacks on CPES during the low loading conditions caused by the lockdown measures implemented during the COVID-19 pandemic. The load demand reductions caused by the lockdown measures are analyzed using dynamic mode decomposition (DMD), focusing on the March-to-July 2020 period and the New York region as the most impacted time period and location in terms of load reduction due to the lockdowns being in full execution. Our feasibility study evaluates load-changing attack scenarios using real load consumption data from the New York Independent System Operator (NYISO) and shows that an attacker with sufficient knowledge and resources could be capable of producing frequency stability problems, with frequency excursions going up to 60.5 Hz and 63.4 Hz, when no mitigation measures are taken.

eess.SY

Deep Reinforcement Learning for Cybersecurity Assessment of Wind Integrated Power Systems

The integration of renewable energy sources (RES) is rapidly increasing in electric power systems (EPS). While the inclusion of intermittent RES coupled with the wide-scale deployment of communication and sensing devices is important towards a fully smart grid, it has also expanded the cyber-threat landscape, effectively making power systems vulnerable to cyberattacks. This paper proposes a cybersecurity assessment approach designed to assess the cyberphysical security of EPS. The work takes into consideration the intermittent generation of RES, vulnerabilities introduced by microprocessor-based electronic information and operational technology (IT/OT) devices, and contingency analysis results. The proposed approach utilizes deep reinforcement learning (DRL) and an adapted Common Vulnerability Scoring System (CVSS) score tailored to assess vulnerabilities in EPS in order to identify the optimal attack transition policy based on N-2 contingency results, i.e., the simultaneous failure of two system elements. The effectiveness of the work is validated via numerical and real-time simulation experiments performed on literature-based power grid test cases. The results demonstrate how the proposed method based on deep Q-network (DQN) performs closely to a graph-search approach in terms of the number of transitions needed to find the optimal attack policy, without the need for full observation of the system. In addition, the experiments present the method's scalability by showcasing the number of transitions needed to find the optimal attack transition policy in a large system such as the Polish 2383 bus test system. The results exhibit how the proposed approach requires one order of magnitude fewer transitions when compared to a random transition policy.

eess.SY

Harness the Power of DERs for Secure Communications in Electric Energy Systems

Electric energy systems are undergoing significant changes to improve system reliability and accommodate increasing power demands. The penetration of distributed energy resources (DERs) including roof-top solar panels, energy storage, electric vehicles, etc., enables the on-site generation of economically dispatchable power curtailing operational costs. The effective control of DERs requires communication between utilities and DER system operators. The communication protocols employed for DER management and control lack sophisticated cybersecurity features and can compromise power systems secure operation if malicious control commands are issued to DERs. To overcome authentication-related protocol issues, we present a bolt-on security extension that can be implemented on Distributed Network Protocol v3 (DNP3). We port an authentication framework, DERauth, into DNP3, and utilize real-time measurements from a simulated DER battery energy storage system to enhance communication security. We evaluate our framework in a testbed setup using DNP3 master and outstation devices performing secure authentication by leveraging the entropy of DERs.

cs.CR

Modeling Communication Networks in a Real-Time Simulation Environment for Evaluating Controls of Shipboard Power Systems

Interest by the U.S. Navy in the development and deployment of advanced controls in future shipboard platforms has motivated the development of the Controls Evaluation Framework (CEF) for use in investigating dynamics present in complex automated systems. This paper reports on the implementation and investigation of a communication network component within the CEF. This implementation is designed to augment the CEF's available feature set, permitting the exploration of various communication conditions on advanced control performance. Results obtained from controller hardware-in-the-loop testing are presented and analyzed to demonstrate performance characteristics pertaining to the implemented module.

eess.SP

Topological Quantum Computation from the 3-dimensional Bordism 2-Category

A great part of the mathematical foundations of topological quantum computation is given by the theory of modular categories which provides a description of the topological phases of matter such as anyon systems. In the near future the anyonic engineering will provide the anyonic devices from which the topological quantum computers will be constructed. From other side the string anyons are interesting topological phases of matter which can be described using mathematical constructions such as Frobenius algebras and open-closed string topological quantum field theories which are based on cobordism categories. Recently was proposed that is possible to obtain representations of cobordism categories using modular categories. In the present work, the modular categories resulting as representations of the 3 dimensional bordism 2 category are used with the aim to construct a new model of topological quantum computation. Such new model is named Sanyon Topological Quantum Computation and it is is theoretically performed by evolving non abelian string anyons (sanyons) using the Loop Braid Group and the open closed cobordism category. The output of the computation uniquely depends on how the sanyons have been braided by the Loop Braid Group and operated by the generators of the cobordism category. Small disturbances do not unravel the loop braids and the cobordisms, making the computation resistant to errors and decoherence.

math.GM

Pricing the Aunt Michaela Option with a Modified Black-Scholes Equation with a Maturity Condition of Gamma Type

Using Maple, we compute a new exact series solution of a modified Black-Scholes equation, recently proposed, for the case of the Aunt Michaela option with a maturity condition of gamma type. We show that the modified Black-Scholes equation with the Aunt Michaela option is exactly solvable in terms of associated Laguerre polynomials or equivalently, in terms of Whittaker M functions. Finally, we make some numerical experiments with the analytical solutions

q-fin.MF

The reproductive number of Zika in municipalities of Antioquia, Colombia: stratifying the potential transmission of an ongoing epidemic

Introduction: Zika epidemic in America was declared a public health emergency of international concern after the rapid spread in the region. Stratification of the potential transmission of the disease is needed to address the efforts surveillance and disease control. The goal of this research is to compare the basic reproductive number of Zika in different municipalities, from an SIR model with implicit vector dynamics, based on the daily case reporting data of Antioquia, Colombia, the second most affected country after Brazil. Methods: An simple SIR model with implicit vector dynamics was derived and used. The approximate solution of the model in terms of individuals recovered in each time unit, allowed to obtain estimate of the model parameters including the basic reproduction number (Ro) and its 95% confidence intervals. These parameters were estimated via fitting the solution of the model to the daily reported cumulative cases data from the regional surveillance system. Results: Ro was estimated for 20 municipalities, all located at less than 2200 meters above sea level. From January to April 2016, between 17 and 347 cases were reported from these municipalities. Of these, 15 municipalities had a high potential for transmission (Ro>1) and 5 had less potential (Ro<1), although in 3 of these, transmission was later possible because its upper confidence interval of Ro was greater than one. Conclusion: Surveillance and control of Zika should be directed primarily to municipalities with Ro>1. Furthermore, strategies that will strengthen the detection and management of cases in the remaining municipalities should be beneficial to the whole Antioquia region.

q-bio.PE

Approximated Analytical Solution to an Ebola Optimal Control Problem

An analytical expression for the optimal control of an Ebola problem is obtained. The analytical solution is found as a first-order approximation to the Pontryagin Maximum Principle via the Euler-Lagrange equation. An implementation of the method is given using the computer algebra system Maple. Our analytical solutions confirm the results recently reported in the literature using numerical methods.

math.OC

New Analytical Solutions of a Modified Black-Scholes Equation with the European Put Option

Using Maple, we compute some analytical solutions of a modified Black-Scholes equation, recently proposed, in the case of the European put option. We show that the modified Black-Scholes equation with the European put option is exactly solvable in terms of associated Laguerre polynomials. We make some numerical experiments with the analytical solutions and we compare our results with the results derived from numerical experiments using the standard Black-Scholes equation.

q-fin.CP

Quantum hypercomputation based on the dynamical algebra su(1,1)

An adaptation of Kieu's hypercomputational quantum algorithm (KHQA) is presented. The method that was used was to replace the Weyl-Heisenberg algebra by other dynamical algebra of low dimension that admits infinite-dimensional irreducible representations with naturally defined generalized coherent states. We have selected the Lie algebra $\mathfrak{su}(1,1)$, due to that this algebra posses the necessary characteristics for to realize the hypercomputation and also due to that such algebra has been identified as the dynamical algebra associated to many relatively simple quantum systems. In addition to an algebraic adaptation of KHQA over the algebra $\mathfrak{su}(1,1)$, we presented an adaptations of KHQA over some concrete physical referents: the infinite square well, the infinite cylindrical well, the perturbed infinite cylindrical well, the P{ö}sch-Teller potentials, the Holstein-Primakoff system, and the Laguerre oscillator. We conclude that it is possible to have many physical systems within condensed matter and quantum optics on which it is possible to consider an implementation of KHQA.

quant-ph

A possible hypercomputational quantum algorithm

The term `hypermachine' denotes any data processing device (theoretical or that can be implemented) capable of carrying out tasks that cannot be performed by a Turing machine. We present a possible quantum algorithm for a classically non-computable decision problem, Hilbert's tenth problem; more specifically, we present a possible hypercomputation model based on quantum computation. Our algorithm is inspired by the one proposed by Tien D. Kieu, but we have selected the infinite square well instead of the (one-dimensional) simple harmonic oscillator as the underlying physical system. Our model exploits the quantum adiabatic process and the characteristics of the representation of the dynamical Lie algebra su(1,1) associated to the infinite square well.

quant-ph