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Alisic, R. (2023). Defense of Cyber-Physical Systems Against Learning-based Attackers. (Doctoral dissertation). Stockholm: KTH Royal Institute of Technology
Open this publication in new window or tab >>Defense of Cyber-Physical Systems Against Learning-based Attackers
2023 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

Cyberattacks against critical infrastructures pose a serious threat to society, as they can have devastating consequences on the economy, security, or public health. These infrastructures rely on a large network of cyber components, such as sensors, controllers, computers, and communication devices, to monitor and control their physical processes. An adversary can exploit the vulnerabilities in these cyber components to gain access to the system and manipulate its behavior or functionality.

This thesis proposes methods that can be employed as a first line of defense against such attacks for Cyber-Physical Systems. In the first part of the thesis, we consider how uninformed attackers can learn to attack a Cyber-Physical System by eavesdropping through the cyber component. By learning to manipulate the plant, the attacker could figure out how to destroy the physical system before it is too late or completely take it over without raising any alarms. Stopping the attacker at the learning stage would force the attacker to act obliviously, increasing the chances of detecting them.

We analyze how homomorphic encryption, a technique that allows computation on encrypted data, hinders an attacker's learning process and reduces its capabilities to attack the system. Specifically, we show that an attacker must solve challenging lattice problems to find attacks that are difficult to detect. Additionally, we show how the detection probability is affected by the attacker's solution to the problems and what parameters of the encryption scheme can be tweaked to increase the detection probability. We also develop a novel method that enables anomaly detection over homomorphically encrypted data without revealing the actual signals to the detector, thereby discouraging attackers from launching attacks on the detector. The detection can be performed using a hypothesis test. However, special care must be taken to ensure that fresh samples are used to detect changes from nominal behavior. We also explore how the adversary can try to evade detection using the same test and how the system can be designed to make detection easier for the defender and more challenging for the attacker.

In the second part of the thesis, we study how information leakage about changes in the system depends on the system's dynamics. We use a mathematical tool called the Hammersley-Chapman-Robbins lower bound to measure how much information is leaked and how to minimize it. Specifically, we study how structured input sequences, which we call events, can be obtained through the output of a dynamical system and how this information can be hidden by adding noise or changing the inputs. The system’s speed and sensor locations affect how much information is leaked. We also consider balancing the system’s performance and privacy when using optimal control. Finally, we show how to estimate when the adversary’s knowledge of the event becomes accurate enough to launch an attack and how to change the system before that happens. These results are then used to aid the operator in detecting privacy vulnerabilities when designing a Cyber-Physical System, which increases the overall security when removed.

Abstract [sv]

Cyberattacker mot kritisk infrastruktur utgör ett allvarligt hot mot samhället, eftersom de kan få förödande konsekvenser för ekonomin, säkerheten eller folkhälsan. Dessa infrastrukturer utgörs ofta av ett stort nätverk av cyberkomponenter, såsom sensorer, styrenheter, datorer och kommunikationsenheter, för att övervaka och styra sina fysiska processer. En angripare kan utnyttja sårbarheterna i dessa cyberkomponenter för att få tillgång till systemet och därefter manipulera dess beteende eller funktionalitet.

Denna avhandling behandlar och föreslår metoder som kan användas som en första försvarslinje mot sådana attacker för cyberfysiska system. I den första delen av avhandlingen undersöker vi hur oinformerade angripare kan lära sig att attackera ett cyberfysiskt system genom att avlyssna dem via cyberkomponenten. Genom att lära sig att manipulera det fysiska systemet kan angriparen ta reda på hur man kan förstöra, eller helt ta över det cyberfysiska systemet utan att något alarm går av förrän det är försent. Genom att stoppa angriparen i inlärningsfasen tvingas angriparen att agera mer omedvetet, vilket ökar chanserna att upptäcka dem.

Vi analyserar hur homomorf kryptering, vilket är en krypteringsmetod som möjliggör beräkning med krypterad data, hindrar angriparens inlärnings-process och minskar dess förmåga att attackera systemet. Specifikt visar vi att en angripare måste lösa svåra gitterproblem för att hitta svårdetekterade cyberattacker. Dessutom visar vi hur detektionssannolikheten påverkas av hur bra angriparens lösning är och vilka parametrar i krypteringsschemat som kan justeras för att öka sannolikheten att upptäcka anfallet. Vi utvecklar också en ny metod som möjliggör anomalidetektering över homomorft krypterade data, utan att avslöja de faktiska signalerna för detektorn och därmed avskräcka angripare från att attackera detektorn. Detektionen kan utföras med hjälp av ett hypotestest. Dock måste man se till att färska prover används för att upptäcka förändringar från normalt beteende. Vi undersöker också hur angriparen kan försöka undvika detektion genom att använda samma test, och hur systemet kan utformas för att göra detektionen enklare för försvararen och svårare för angriparen.

I den andra delen av avhandlingen studerar vi hur informationsläckage om förändringar i systemet beror på dess dynamik. Vi använder ett matematiskt verktyg som kallas Hammersley-Chapman-Robbins undre gräns för att mäta hur mycket information som läcker ut och hur man minimerar den. Specifikt studerar vi hur strukturerade insignalssekvenser, som vi kallar händelser, kan uppskattas genom mätningar från ett dynamiskt system och hur denna information kan döljas genom att lägga till brus eller ändra insignalerna. Systemets hastighet och sensorplaceringar påverkar hur mycket information läcker ut. Vi behandlar också frågan om hur man balanserar systemets prestanda och integritet när vi använder optimal styrning. Slutligen visar vi hur man uppskattar när angriparens kunskap om händelsen blir tillräckligt noggrann för att starta en attack och hur man ändrar systemet innan det händer. Dessa resultat används sedan för att hjälpa operatören att upptäcka integritetsbrister vid utformningen av ett cyberfysiskt system, vilket ökar den totala säkerheten när de tas bort.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2023. p. 267
Series
TRITA-EECS-AVL ; 2023:72
Keywords
Control Theory, Security, Privacy, Machine Learning, Cyber-Physical Systems, Change Point Problems
National Category
Control Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-338318 (URN)978-91-8040-729-8 (ISBN)
Public defence
2023-11-10, Kollegiesalen, Brinellvägen 6, Stockholm, 09:00 (English)
Opponent
Supervisors
Funder
Swedish Foundation for Strategic Research, RIT17-0046
Note

QC 20231020

Available from: 2023-10-20 Created: 2023-10-20 Last updated: 2023-10-26Bibliographically approved
Alisic, R., Kim, J. & Sandberg, H. (2023). Model-Free Undetectable Attacks on Linear Systems Using LWE-Based Encryption. IEEE Control Systems Letters, 7, 1249-1254
Open this publication in new window or tab >>Model-Free Undetectable Attacks on Linear Systems Using LWE-Based Encryption
2023 (English)In: IEEE Control Systems Letters, E-ISSN 2475-1456, Vol. 7, p. 1249-1254Article in journal (Refereed) Published
Abstract [en]

We show that the homomorphic property, a desired property in encrypted control, can lead to failure in the cyber defense of a dynamical control system from undetectable attacks, even though individual signal sequences remain unknown to the attacker. We consider an encryption method based on the Learning with Errors (LWE) problem and demonstrate how model-free undetectable attacks on linear systems over integers can be computed from sampled inputs and outputs that are encrypted. Previous work has shown that computing such attacks is possible on nonencrypted systems. Applying this earlier work to our scenario, with minor modifications, typically amplifies the error in encrypted messages unless a short vector problem is solved. Given that an attacker obtains a short vector, we derive the probability that the attack is detected and show how it explicitly depends on the encryption parameters. Finally, we simulate an attack obtained by our method on an encrypted linear system over integers and conduct an analysis of the probability that the attack will be detected.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Detectors, Trajectory, Encryption, Linear systems, Dynamical systems, Control systems, Sensors, Sampled-data control, quantized systems
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-324532 (URN)10.1109/LCSYS.2023.3234004 (DOI)000917748200002 ()2-s2.0-85147205024 (Scopus ID)
Note

QC 20230307

Available from: 2023-03-07 Created: 2023-03-07 Last updated: 2023-08-25Bibliographically approved
Alisic, R., Paré, P. E. & Sandberg, H. (2022). Change time estimation uncertainty in nonlinear dynamical systems with applications to COVID-19. International Journal of Robust and Nonlinear Control
Open this publication in new window or tab >>Change time estimation uncertainty in nonlinear dynamical systems with applications to COVID-19
2022 (English)In: International Journal of Robust and Nonlinear Control, ISSN 1049-8923, E-ISSN 1099-1239Article in journal (Refereed) Published
Abstract [en]

The impact that each individual non-pharmaceutical intervention (NPI) had on the spread rate of COVID-19 is difficult to estimate, since several NPIs were implemented in rapid succession in most countries. In this article, we analyze the detectability of sudden changes in a parameter of nonlinear dynamical systems, which could be used to represent NPIs or mutations of the virus, in the presence of measurement noise. Specifically, by taking an agnostic approach, we provide necessary conditions for when the best possible unbiased estimator is able to isolate the effect of a sudden change in a model parameter, by using the Hammersley–Chapman–Robbins (HCR) lower bound. Several simplifications to the calculation of the HCR lower bound are given, which depend on the amplitude of the sudden change and the dynamics of the system. We further define the concept of the most informative sample based on the largest (Formula presented.) distance between two output trajectories, which is a good indicator of when the HCR lower bound converges. These results are thereafter used to analyze the susceptible-infected-removed model. For instance, we show that performing analysis using the number of recovered/deceased, as opposed to the cumulative number of infected, may be an inferior signal to use since sudden changes are fundamentally more difficult to estimate and seem to require more samples. Finally, these results are verified by simulations and applied to real data from the spread of COVID-19 in France.

Place, publisher, year, edition, pages
Wiley, 2022
National Category
Control Engineering Medical and Health Sciences
Identifiers
urn:nbn:se:kth:diva-319615 (URN)10.1002/rnc.5974 (DOI)000744675000001 ()2-s2.0-85123102172 (Scopus ID)
Note

QC 20221004

Available from: 2022-10-04 Created: 2022-10-04 Last updated: 2024-03-18Bibliographically approved
Alisic, R. & Sandberg, H. (2021). Data-injection Attacks Using Historical Inputs and Outputs. In: Proceedings European Control Conference, ECC 2021: . Paper presented at 2021 European Control Conference, ECC 2021, Virtual Event / Delft, The Netherlands, June 29 - July 2, 2021 (pp. 1399-1405). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Data-injection Attacks Using Historical Inputs and Outputs
2021 (English)In: Proceedings European Control Conference, ECC 2021, Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 1399-1405Conference paper, Published paper (Refereed)
Abstract [en]

Data-driven, model-free control has become popular in recent years, due to their ease of implementation and minimal information requirement about the system. In this paper, we investigate whether the same methods could be used by an adversary to synthesize undetectable data-injection attacks on cyber-physical systems using Willems' Fundamental Lemma. We show that if the adversary is able to upper bound the order of a linear, time-invariant system and read all its inputs and outputs, then the adversary will be able to generate undetectable attack signals in the form of covert attacks. Additionally, we provide conditions on the disclosed data set that enable the adversary to generate zero dynamics attacks. These conditions give operators insights into when enough information about the system has been revealed for an adversary to conduct an undetectable attack. Finally, the different attack strategies are verified through a numerical example.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2021
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-311028 (URN)10.23919/ECC54610.2021.9654938 (DOI)000768455200207 ()2-s2.0-85124897180 (Scopus ID)
Conference
2021 European Control Conference, ECC 2021, Virtual Event / Delft, The Netherlands, June 29 - July 2, 2021
Note

Part of ISBN 978-94-6384-236-5

QC 20220421

Available from: 2022-04-21 Created: 2022-04-21 Last updated: 2022-06-25Bibliographically approved
Alisic, R. & Sandberg, H. (2021). Privacy Enhancement of Structured Inputs in Cyber-Physical Systems. In: 2021 60th IEEE conference on decision and control (CDC): . Paper presented at 60th IEEE Conference on Decision and Control (CDC), DEC 13-17, 2021, ELECTR NETWORK (pp. 4888-4894). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Privacy Enhancement of Structured Inputs in Cyber-Physical Systems
2021 (English)In: 2021 60th IEEE conference on decision and control (CDC), Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 4888-4894Conference paper, Published paper (Refereed)
Abstract [en]

Privacy is often the first line of defense against cyber-physical attacks. In this paper, we derive guarantees for the privacy of structured inputs to linear time-invariant systems, where the eavesdropper either does not know the input or only knows parts of it a priori. The input is be parametrized by a mixture of discrete and continuous parameters. Privacy guarantees for these parameters are then derived using a Barankin-style bound. Given an open-loop control objective, a modification to the cost function is proposed to enhance privacy. Privacy-utility trade-off bounds are derived for these private open-loop control signals. Finally, the theoretical results are verified both using the physical Temperature Control Lab and a numerical simulation of it.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2021
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-312971 (URN)10.1109/CDC45484.2021.9683360 (DOI)000781990304049 ()2-s2.0-85125996622 (Scopus ID)
Conference
60th IEEE Conference on Decision and Control (CDC), DEC 13-17, 2021, ELECTR NETWORK
Note

QC 20220530

PArt of proceedings ISBN 978-1-6654-3659-5

Available from: 2022-05-30 Created: 2022-05-30 Last updated: 2022-06-25Bibliographically approved
Alisic, R. (2021). Privacy of Sudden Events in Cyber-Physical Systems. (Licentiate dissertation). Stockholm: KTH Royal Institute of Technology
Open this publication in new window or tab >>Privacy of Sudden Events in Cyber-Physical Systems
2021 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

Cyberattacks against critical infrastructures has been a growing problem for the past couple of years. These infrastructures are a particularly desirable target for adversaries, due to their vital importance in society. For instance, a stop in the operation of a critical infrastructure could result in a crippling effect on a nation's economy, security or public health. The reason behind this increase is that critical infrastructures have become more complex, often being integrated with a large network of various cyber components. It is through these cyber components that an adversary is able to access the system and conduct their attacks.

In this thesis, we consider methods which can be used as a first line of defence against such attacks for Cyber-Physical Systems (CPS). Specifically, we start by studying how information leaks about a system's dynamics helps an adversary to generate attacks that are difficult to detect. In many cases, such attacks can be detrimental to a CPS since they can drive the system to a breaking point without being detected by the operator that is tasked to secure the system. We show that an adversary can use small amounts of data procured from information leaks to generate these undetectable attacks. In particular, we provide the minimal amount of information that is needed in order to keep the attack hidden even if the operator tries to probe the system for attacks. 

We design defence mechanisms against such information leaks using the Hammersley-Chapman-Robbins lower bound. With it, we study how information leakage could be mitigated through corruption of the data by injection of measurement noise. Specifically, we investigate how information about structured input sequences, which we call events, can be obtained through the output of a dynamical system and how this leakage depends on the system dynamics. For example, it is shown that a system with fast dynamical modes tends to disclose more information about an event compared to a system with slower modes. However, a slower system leaks information over a longer time horizon, which means that an adversary who starts to collect information long after the event has occured might still be able to estimate it. Additionally, we show how sensor placements can affect the information leak. These results are then used to aid the operator to detect privacy vulnerabilities in the design of a CPS.

Based on the Hammersley-Chapman-Robbins lower bound, we provide additional defensive mechanisms that can be deployed by an operator online to minimize information leakage. For instance, we propose a method to modify the structured inputs in order to maximize the usage of the existing noise in the system. This mechanism allows us to explicitly deal with the privacy-utility trade-off, which is of interest when optimal control problems are considered. Finally, we show how the adversary's certainty of the event increases as a function of the number of samples they collect. For instance, we provide sufficient conditions for when their estimation variance starts to converge to its final value. This information can be used by an operator to estimate when possible attacks from an adversary could occur, and change the CPS before that, rendering the adversary's collected information useless.

Abstract [sv]

De senaste åren har cyberanfall mot kritiska infrastructurer varit ett växande problem. Dessa infrastrukturer är särskilt utsatta för cyberanfall, eftersom de uppfyller en nödvändig function för att ett samhälle ska fungera. Detta gör dem till önskvärda mål för en anfallare. Om en kritisk infrastruktur stoppas från att uppfylla sin funktion, då kan det medföra förödande konsekvenser för exempelvis en nations ekonomi, säkerhet eller folkhälsa. Anledningen till att mängden av attacker har ökat beror på att kritiska infrastrukturer har blivit alltmer komplexa eftersom de numera ingår i stora nätverk dör olika typer av cyberkomponenter ingår. Det är just genom dessa cyberkomponenter som en anfallare kan få tillgång till systemet och iscensätta cyberanfall.

I denna avhandling utvecklar vi metoder som kan användas som en första försvarslinje mot cyberanfall på cyberfysiska system (CPS). Vi med att undersöka hur informationsläckor om systemdynamiken kan hjälpa en anfallare att skapa svårupptäckta attacker. Oftast är sådana attacker förödande för CPS, eftersom en anfallare kan tvinga systemet till en bristningsgräns utan att bli upptäcka av operatör vars uppgift är att säkerställa systemets fortsatta funktion. Vi bevisar att en anfallare kan använda relativt små mängder av data för att generera dessa svårupptäckta attacker. Mer specifikt så härleder ett uttryck för den minsta mängd information som krävs för att ett anfall ska vara svårupptäckt, även för fall då en operatör tar till sig metoder för att undersöka om systemet är under attack.

I avhandlingen konstruerar vi försvarsmetoder mot informationsläcker genom Hammersley-Chapman-Robbins olikhet. Med denna olikhet kan vi studera hur informationsläckan kan dämpas genom att injicera brus i datan. Specifikt så undersöker vi hur mycket information om strukturerade insignaler, vilket vi kallar för händelser, till ett dynamiskt system som en anfallare kan extrahera utifrån dess utsignaler. Dessutom kollar vi på hur denna informationsmängd beror på systemdynamiken. Exempelvis så visar vi att ett system med snabb dynamik läcker mer information jämfört med ett långsammare system. Däremot smetas informationen ut över ett längre tidsintervall för långsammare system, vilket leder till att anfallare som börjar tjuvlyssna på ett system långt efter att händelsen har skett kan fortfarande uppskatta den. Dessutom så visar vi jur sensorplaceringen i ett CPS påverkar infromationsläckan. Dessa reultat kan användas för att bistå en operatör att analysera sekretessen i ett CPS.

Vi använder även Hammersley-Chapman-Robbins olikhet för att utveckla försvarslösningar mot informationsläckor som kan användas \textit{online}. Vi föreslår modifieringar till den strukturella insignalen så att systemets befintliga brus utnyttjas bättre för att gömma händelsen. Om operatören har andra mål den försöker uppfylla med styrningen så kan denna metod användas för att styra avvängingen mellan sekretess och operatorns andra mål. Slutligen så visar vi hur en anfallares uppskattning av händelsen förbättras som en funktion av mängden data får tag på. Operatorn kan använda informationen för att ta reda på när anfallaren kan tänka sig vara redo att anfalla systemet, och därefter ändra systemet innan detta sker, vilket gör att anfallarens information inte längre är användbar.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2021. p. 157
Keywords
Privacy, Security, Cyber-Physical Systems, Automatic Control, Estimation, Machine Learning, Change Point Detection
National Category
Control Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-299845 (URN)978-91-7873-938-7 (ISBN)
Presentation
2021-09-13, https://kth-se.zoom.us/meeting/register/u5Apde-srDsqGtLjb4Z6RvLBh8cr24Gt1g6E, U61, Brinellvägen 26, Stockholm, 16:00
Opponent
Supervisors
Funder
Swedish Foundation for Strategic Research , RIT17-0046
Note

QC 20210820

Available from: 2021-08-20 Created: 2021-08-18 Last updated: 2022-06-25Bibliographically approved
Alisic, R., Molinari, M., Pare, P. E. & Sandberg, H. (2020). Ensuring privacy of occupancy changes in smart buildings. In: CCTA 2020 - 4th IEEE Conference on Control Technology and Applications: . Paper presented at 4th IEEE Conference on Control Technology and Applications, CCTA 2020, 24 August 2020 through 26 August 2020 (pp. 871-876). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Ensuring privacy of occupancy changes in smart buildings
2020 (English)In: CCTA 2020 - 4th IEEE Conference on Control Technology and Applications, Institute of Electrical and Electronics Engineers Inc. , 2020, p. 871-876Conference paper, Published paper (Refereed)
Abstract [en]

Smart building management systems rely on sensors to optimize the operation of buildings. If an unauthorized user gains access to these sensors, a privacy leak may occur. This paper considers such a potential leak of privacy in a smart residential building, and how it may be mitigated by corrupting the measurements with additive Gaussian noise. This corruption is done in order to hide when the occupancy changes in an apartment. A lower bound on the variance of any estimator that estimates the change time is derived. The bound is then used to analyze how different model parameters affect the variance. It is shown that the signal to noise ratio and the system dynamics are the main factors that affect the bound. These results are then verified on a simulator of the KTH Live-In Lab Testbed, showing good correspondence with theoretical results.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2020
Keywords
Intelligent buildings, Signal to noise ratio, Additive Gaussian noise, Building management system, Change time, Lower bounds, Model parameters, Residential building, System Dynamics, Unauthorized users, Gaussian noise (electronic)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-290350 (URN)10.1109/CCTA41146.2020.9206317 (DOI)000668042200132 ()2-s2.0-85094102905 (Scopus ID)
Conference
4th IEEE Conference on Control Technology and Applications, CCTA 2020, 24 August 2020 through 26 August 2020
Note

QC 20230307

Available from: 2021-02-16 Created: 2021-02-16 Last updated: 2023-03-07Bibliographically approved
Alisic, R., Molinari, M., Pare, P. E. & Sandberg, H. (2020). Maximizing Privacy in MIMO Cyber-Physical Systems Using the Chapman-Robbins Bound. In: Proceedings of the IEEE Conference on Decision and Control: . Paper presented at 59th IEEE Conference on Decision and Control, CDC 2020, 14 December 2020 through 18 December 2020 (pp. 6272-6277). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Maximizing Privacy in MIMO Cyber-Physical Systems Using the Chapman-Robbins Bound
2020 (English)In: Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc. , 2020, p. 6272-6277Conference paper, Published paper (Refereed)
Abstract [en]

Privacy breaches of cyber-physical systems could expose vulnerabilities to an adversary. Here, privacy leaks of step inputs to linear time-invariant systems are mitigated through additive Gaussian noise. Fundamental lower bounds on the privacy are derived, which are based on the variance of any estimator that seeks to recreate the input. Fully private inputs are investigated and related to transmission zeros. Thereafter, a method to increase the privacy of optimal step inputs is presented and a privacy-utility trade-off bound is derived. Finally, these results are verified on data from the KTH Live-In Lab Testbed, showing good correspondence with theoretical results. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2020
Keywords
Cyber Physical System, Economic and social effects, Gaussian noise (electronic), Invariance, Linear systems, Time varying control systems, Additive Gaussian noise, Linear time invariant systems, Lower bounds, Privacy breaches, Trade off, Transmission zeros, Embedded systems
National Category
Control Engineering Telecommunications
Identifiers
urn:nbn:se:kth:diva-301201 (URN)10.1109/CDC42340.2020.9303912 (DOI)000717663405003 ()2-s2.0-85099876230 (Scopus ID)
Conference
59th IEEE Conference on Decision and Control, CDC 2020, 14 December 2020 through 18 December 2020
Funder
Swedish Foundation for Strategic Research
Note

QC 20230307

Available from: 2021-09-07 Created: 2021-09-07 Last updated: 2023-03-07Bibliographically approved
Alisic, R., Pare, P. E. & Sandberg, H. (2019). Modeling and Stability of Prosumer Heat Networks. In: IFAC PAPERSONLINE: . Paper presented at 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NECSYS), SEP 16-17, 2019, Loyola Univ, Chicago, IL (pp. 235-240). ELSEVIER, 52(20)
Open this publication in new window or tab >>Modeling and Stability of Prosumer Heat Networks
2019 (English)In: IFAC PAPERSONLINE, ELSEVIER , 2019, Vol. 52, no 20, p. 235-240Conference paper, Published paper (Refereed)
Abstract [en]

The energy sector is going through a large transformation due to public demands of renewable energy sources. However, a major issue is that these energy sources are intermittent. If designed correctly, district heating systems can naturally contain energy storing units, for example by storing heat in the isolated pipes that make up the heat grid. Additionally, this makes it easier to reuse and transport already generated heat to other users. This paper proposes a mathematical model of such a grid, where excess energy can be retracted from one user and distributed to other users using a network of heat pumps. In some cases, one can balance residual heat production with the heat consumption, temporarily eliminating the need for a centralized heating plant. Existence conditions for stable steady states of such a network with general topology are given. Finally, energy optimal stable steady states are obtained through convex optimization. 

Place, publisher, year, edition, pages
ELSEVIER, 2019
Keywords
Energy systems, Modeling, Emerging control applications
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-266499 (URN)10.1016/j.ifacol.2019.12.164 (DOI)000504302900041 ()2-s2.0-85082655508 (Scopus ID)
Conference
8th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NECSYS), SEP 16-17, 2019, Loyola Univ, Chicago, IL
Note

QC 20200406

Available from: 2020-04-06 Created: 2020-04-06 Last updated: 2022-06-26Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-6558-3807

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