Project acronym CoBABATI
Project Cofactor Binding Antibodies – Basic Aspects and Therapeutic Innovations
Researcher (PI) Jordan Dimitrov
Host Institution (HI) INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE
Call Details Starting Grant (StG), LS7, ERC-2015-STG
Summary The immune repertoire of healthy individuals contains a fraction of antibodies (Abs) that are able to bind with high affinity various endogenous or exogenous low molecular weight compounds, including cofactors essential for the aerobic life, such as riboflavin, heme and ATP. Despite identification of cofactor-binding Abs as a constituent of normal immune repertoires, their fundamental characteristics and have not been systematically investigated. Thus, we do not know the origin, prevalence and physiopathological significance of cofactor-binding Abs. Moreover, the molecular mechanisms of interaction of cofactors with Abs are ill defined. Different proteins use cofactors to extend the chemistry intrinsic to the amino acid sequence of their polypeptide chain(s). Thus, one can speculate that the alliance of Abs with low molecular weight compounds results in the emergence of untypical properties of Abs and offers a strategy for designing a new generation of therapeutic Abs. Moreover, cofactor-binding Abs may be used for delivery of cytotoxic compounds to particular sites in the body, or for scavenging pro-inflammatory compounds. The principal goal of the present proposal is to gain a basic understanding on the fraction of cofactor-binding Abs in immune repertoires and to use this knowledge for the rational design of novel classes of therapeutic Abs. In this project, we will address the following questions: 1) understand the origin and prevalence of cofactor-binding Abs in immune repertoires; 2) characterize the molecular mechanisms of interaction of cofactors with Abs; 3) Understand the physiopathological roles of cofactor-binding Abs, and 4) use cofactor binding for the development of novel types of therapeutic Abs. A comprehensive understanding of various aspects of cofactor-binding Abs should lead to advances in fundamental understanding and in the development of innovative therapeutic and diagnostic tools.
Summary
The immune repertoire of healthy individuals contains a fraction of antibodies (Abs) that are able to bind with high affinity various endogenous or exogenous low molecular weight compounds, including cofactors essential for the aerobic life, such as riboflavin, heme and ATP. Despite identification of cofactor-binding Abs as a constituent of normal immune repertoires, their fundamental characteristics and have not been systematically investigated. Thus, we do not know the origin, prevalence and physiopathological significance of cofactor-binding Abs. Moreover, the molecular mechanisms of interaction of cofactors with Abs are ill defined. Different proteins use cofactors to extend the chemistry intrinsic to the amino acid sequence of their polypeptide chain(s). Thus, one can speculate that the alliance of Abs with low molecular weight compounds results in the emergence of untypical properties of Abs and offers a strategy for designing a new generation of therapeutic Abs. Moreover, cofactor-binding Abs may be used for delivery of cytotoxic compounds to particular sites in the body, or for scavenging pro-inflammatory compounds. The principal goal of the present proposal is to gain a basic understanding on the fraction of cofactor-binding Abs in immune repertoires and to use this knowledge for the rational design of novel classes of therapeutic Abs. In this project, we will address the following questions: 1) understand the origin and prevalence of cofactor-binding Abs in immune repertoires; 2) characterize the molecular mechanisms of interaction of cofactors with Abs; 3) Understand the physiopathological roles of cofactor-binding Abs, and 4) use cofactor binding for the development of novel types of therapeutic Abs. A comprehensive understanding of various aspects of cofactor-binding Abs should lead to advances in fundamental understanding and in the development of innovative therapeutic and diagnostic tools.
Max ERC Funding
1 255 000 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym COHEGRAPH
Project Electron quantum optics in Graphene
Researcher (PI) Séverin Preden Roulleau
Host Institution (HI) COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
Call Details Starting Grant (StG), PE3, ERC-2015-STG
Summary Quantum computing is based on the manipulation of quantum bits (qubits) to enhance the efficiency of information processing. In solid-state systems, two approaches have been explored:
• static qubits, coupled to quantum buses used for manipulation and information transmission,
• flying qubits which are mobile qubits propagating in quantum circuits for further manipulation.
Flying qubits research led to the recent emergence of the field of electron quantum optics, where electrons play the role of photons in quantum optic like experiments. This has recently led to the development of electronic quantum interferometry as well as single electron sources. As of yet, such experiments have only been successfully implemented in semi-conductor heterostructures cooled at extremely low temperatures. Realizing electron quantum optics experiments in graphene, an inexpensive material showing a high degree of quantum coherence even at moderately low temperatures, would be a strong evidence that quantum computing in graphene is within reach.
One of the most elementary building blocks necessary to perform electron quantum optics experiments is the electron beam splitter, which is the electronic analog of a beam splitter for light. However, the usual scheme for electron beam splitters in semi-conductor heterostructures is not available in graphene because of its gapless band structure. I propose a breakthrough in this direction where pn junction plays the role of electron beam splitter. This will lead to the following achievements considered as important steps towards quantum computing:
• electronic Mach Zehnder interferometry used to study the quantum coherence properties of graphene,
• two electrons Aharonov Bohm interferometry used to generate entangled states as an elementary quantum gate,
• the implementation of on-demand electronic sources in the GHz range for graphene flying qubits.
Summary
Quantum computing is based on the manipulation of quantum bits (qubits) to enhance the efficiency of information processing. In solid-state systems, two approaches have been explored:
• static qubits, coupled to quantum buses used for manipulation and information transmission,
• flying qubits which are mobile qubits propagating in quantum circuits for further manipulation.
Flying qubits research led to the recent emergence of the field of electron quantum optics, where electrons play the role of photons in quantum optic like experiments. This has recently led to the development of electronic quantum interferometry as well as single electron sources. As of yet, such experiments have only been successfully implemented in semi-conductor heterostructures cooled at extremely low temperatures. Realizing electron quantum optics experiments in graphene, an inexpensive material showing a high degree of quantum coherence even at moderately low temperatures, would be a strong evidence that quantum computing in graphene is within reach.
One of the most elementary building blocks necessary to perform electron quantum optics experiments is the electron beam splitter, which is the electronic analog of a beam splitter for light. However, the usual scheme for electron beam splitters in semi-conductor heterostructures is not available in graphene because of its gapless band structure. I propose a breakthrough in this direction where pn junction plays the role of electron beam splitter. This will lead to the following achievements considered as important steps towards quantum computing:
• electronic Mach Zehnder interferometry used to study the quantum coherence properties of graphene,
• two electrons Aharonov Bohm interferometry used to generate entangled states as an elementary quantum gate,
• the implementation of on-demand electronic sources in the GHz range for graphene flying qubits.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym COLORAMAP
Project Constrained Low-Rank Matrix Approximations: Theoretical and Algorithmic Developments for Practitioners
Researcher (PI) Nicolas Benoit P Gillis
Host Institution (HI) UNIVERSITE DE MONS
Call Details Starting Grant (StG), PE6, ERC-2015-STG
Summary Low-rank matrix approximation (LRA) techniques such as principal component analysis (PCA) are powerful tools for the representation and analysis of high dimensional data, and are used in a wide variety of areas such as machine learning, signal and image processing, data mining, and optimization. Without any constraints and using the least squares error, LRA can be solved via the singular value decomposition. However, in practice, this model is often not suitable mainly because (i) the data might be contaminated with outliers, missing data and non-Gaussian noise, and (ii) the low-rank factors of the decomposition might have to satisfy some specific constraints. Hence, in recent years, many variants of LRA have been introduced, using different constraints on the factors and using different objective functions to assess the quality of the approximation; e.g., sparse PCA, PCA with missing data, independent component analysis and nonnegative matrix factorization. Although these new constrained LRA models have become very popular and standard in some fields, there is still a significant gap between theory and practice. In this project, our goal is to reduce this gap by attacking the problem in an integrated way making connections between LRA variants, and by using four very different but complementary perspectives: (1) computational complexity issues, (2) provably correct algorithms, (3) heuristics for difficult instances, and (4) application-oriented aspects. This unified and multi-disciplinary approach will enable us to understand these problems better, to develop and analyze new and existing algorithms and to then use them for applications. Our ultimate goal is to provide practitioners with new tools and to allow them to decide which method to use in which situation and to know what to expect from it.
Summary
Low-rank matrix approximation (LRA) techniques such as principal component analysis (PCA) are powerful tools for the representation and analysis of high dimensional data, and are used in a wide variety of areas such as machine learning, signal and image processing, data mining, and optimization. Without any constraints and using the least squares error, LRA can be solved via the singular value decomposition. However, in practice, this model is often not suitable mainly because (i) the data might be contaminated with outliers, missing data and non-Gaussian noise, and (ii) the low-rank factors of the decomposition might have to satisfy some specific constraints. Hence, in recent years, many variants of LRA have been introduced, using different constraints on the factors and using different objective functions to assess the quality of the approximation; e.g., sparse PCA, PCA with missing data, independent component analysis and nonnegative matrix factorization. Although these new constrained LRA models have become very popular and standard in some fields, there is still a significant gap between theory and practice. In this project, our goal is to reduce this gap by attacking the problem in an integrated way making connections between LRA variants, and by using four very different but complementary perspectives: (1) computational complexity issues, (2) provably correct algorithms, (3) heuristics for difficult instances, and (4) application-oriented aspects. This unified and multi-disciplinary approach will enable us to understand these problems better, to develop and analyze new and existing algorithms and to then use them for applications. Our ultimate goal is to provide practitioners with new tools and to allow them to decide which method to use in which situation and to know what to expect from it.
Max ERC Funding
1 291 750 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym CombiCompGeom
Project Combinatorial Aspects of Computational Geometry
Researcher (PI) Natan Rubin
Host Institution (HI) BEN-GURION UNIVERSITY OF THE NEGEV
Call Details Starting Grant (StG), PE6, ERC-2015-STG
Summary The project focuses on the interface between computational and combinatorial geometry.
Geometric problems emerge in a variety of computational fields that interact with the physical world.
The performance of geometric algorithms is determined by the description complexity of their underlying combinatorial structures. Hence, most theoretical challenges faced by computational geometry are of a distinctly combinatorial nature.
In the past two decades, computational geometry has been revolutionized by the powerful combination of random sampling techniques with the abstract machinery of geometric arrangements. These insights were used, in turn, to establish state-of-the-art results in combinatorial geometry. Nevertheless, a number of fundamental problems remained open and resisted numerous attempts to solve them.
Motivated by the recent breakthrough results, in which the PI played a central role, we propose two exciting lines of study with the potential to change the landscape of this field.
The first research direction concerns the complexity of Voronoi diagrams -- arguably the most common structures in computational geometry.
The second direction concerns combinatorial and algorithmic aspects of geometric intersection structures, including some fundamental open problems in geometric transversal theory. Many of these questions are motivated by geometric variants of general covering and packing problems, and all efficient approximation schemes for them must rely on the intrinsic properties of geometric graphs and hypergraphs.
Any progress in responding to these challenges will constitute a major breakthrough in both computational and combinatorial geometry.
Summary
The project focuses on the interface between computational and combinatorial geometry.
Geometric problems emerge in a variety of computational fields that interact with the physical world.
The performance of geometric algorithms is determined by the description complexity of their underlying combinatorial structures. Hence, most theoretical challenges faced by computational geometry are of a distinctly combinatorial nature.
In the past two decades, computational geometry has been revolutionized by the powerful combination of random sampling techniques with the abstract machinery of geometric arrangements. These insights were used, in turn, to establish state-of-the-art results in combinatorial geometry. Nevertheless, a number of fundamental problems remained open and resisted numerous attempts to solve them.
Motivated by the recent breakthrough results, in which the PI played a central role, we propose two exciting lines of study with the potential to change the landscape of this field.
The first research direction concerns the complexity of Voronoi diagrams -- arguably the most common structures in computational geometry.
The second direction concerns combinatorial and algorithmic aspects of geometric intersection structures, including some fundamental open problems in geometric transversal theory. Many of these questions are motivated by geometric variants of general covering and packing problems, and all efficient approximation schemes for them must rely on the intrinsic properties of geometric graphs and hypergraphs.
Any progress in responding to these challenges will constitute a major breakthrough in both computational and combinatorial geometry.
Max ERC Funding
1 303 750 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym COMPASS
Project Control for Orbit Manoeuvring through Perturbations for Application to Space Systems
Researcher (PI) Camilla Colombo
Host Institution (HI) POLITECNICO DI MILANO
Call Details Starting Grant (StG), PE8, ERC-2015-STG
Summary Space benefits mankind through the services it provides to Earth. Future space activities progress thanks to space transfer and are safeguarded by space situation awareness. Natural orbit perturbations are responsible for the trajectory divergence from the nominal two-body problem, increasing the requirements for orbit control; whereas, in space situation awareness, they influence the orbit evolution of space debris that could cause hazard to operational spacecraft and near Earth objects that may intersect the Earth. However, this project proposes to leverage the dynamics of natural orbit perturbations to significantly reduce current extreme high mission cost and create new opportunities for space exploration and exploitation.
The COMPASS project will bridge over the disciplines of orbital dynamics, dynamical systems theory, optimisation and space mission design by developing novel techniques for orbit manoeuvring by “surfing” through orbit perturbations. The use of semi-analytical techniques and tools of dynamical systems theory will lay the foundation for a new understanding of the dynamics of orbit perturbations. We will develop an optimiser that progressively explores the phase space and, though spacecraft parameters and propulsion manoeuvres, governs the effect of perturbations to reach the desired orbit. It is the ambition of COMPASS to radically change the current space mission design philosophy: from counteracting disturbances, to exploiting natural and artificial perturbations.
COMPASS will benefit from the extensive international network of the PI, including the ESA, NASA, JAXA, CNES, and the UK space agency. Indeed, the proposed idea of optimal navigation through orbit perturbations will address various major engineering challenges in space situation awareness, for application to space debris evolution and mitigation, missions to asteroids for their detection, exploration and deflection, and in space transfers, for perturbation-enhanced trajectory design.
Summary
Space benefits mankind through the services it provides to Earth. Future space activities progress thanks to space transfer and are safeguarded by space situation awareness. Natural orbit perturbations are responsible for the trajectory divergence from the nominal two-body problem, increasing the requirements for orbit control; whereas, in space situation awareness, they influence the orbit evolution of space debris that could cause hazard to operational spacecraft and near Earth objects that may intersect the Earth. However, this project proposes to leverage the dynamics of natural orbit perturbations to significantly reduce current extreme high mission cost and create new opportunities for space exploration and exploitation.
The COMPASS project will bridge over the disciplines of orbital dynamics, dynamical systems theory, optimisation and space mission design by developing novel techniques for orbit manoeuvring by “surfing” through orbit perturbations. The use of semi-analytical techniques and tools of dynamical systems theory will lay the foundation for a new understanding of the dynamics of orbit perturbations. We will develop an optimiser that progressively explores the phase space and, though spacecraft parameters and propulsion manoeuvres, governs the effect of perturbations to reach the desired orbit. It is the ambition of COMPASS to radically change the current space mission design philosophy: from counteracting disturbances, to exploiting natural and artificial perturbations.
COMPASS will benefit from the extensive international network of the PI, including the ESA, NASA, JAXA, CNES, and the UK space agency. Indeed, the proposed idea of optimal navigation through orbit perturbations will address various major engineering challenges in space situation awareness, for application to space debris evolution and mitigation, missions to asteroids for their detection, exploration and deflection, and in space transfers, for perturbation-enhanced trajectory design.
Max ERC Funding
1 499 021 €
Duration
Start date: 2016-08-01, End date: 2021-07-31
Project acronym COMPLEXITY
Project Understanding the Complexity of Modern Financial Systems
Researcher (PI) Vikrant Vig
Host Institution (HI) LONDON BUSINESS SCHOOL
Call Details Starting Grant (StG), SH1, ERC-2015-STG
Summary The modern financial system has undergone immense transformation in recent years and is far more complex than ever before. In lockstep, financial regulation has also become more complex. This research proposal attempts to improve our understanding of potential drivers of this complexity and the implications of this change on the allocation of resources.
Taking a positive rather than a normative approach, I will analyse post-crisis changes at both the micro- and at the macro-levels to create a broader understanding of complexities in the current financial system. In order to do so, I will employ a set of advanced research designs, as well as a uniquely assembled micro-level dataset covering state and privately owned financial institutions in Asia, Africa, South America and Europe.
This project will focus on two interconnected areas of research: 1) Organisation of Credit, 2) Financial regulation in a complex environment. The aim of this project is to create a sustainable framework for the study of post-crisis financial systems, and to shape the current debate on the future of post-crisis financial structures and the development of policy in this area. Not only will this research have a considerable impact on our understanding of financial systems, it will also impact fields beyond finance, like Organisational Economics, Industrial Organisation and Development Economics.
Summary
The modern financial system has undergone immense transformation in recent years and is far more complex than ever before. In lockstep, financial regulation has also become more complex. This research proposal attempts to improve our understanding of potential drivers of this complexity and the implications of this change on the allocation of resources.
Taking a positive rather than a normative approach, I will analyse post-crisis changes at both the micro- and at the macro-levels to create a broader understanding of complexities in the current financial system. In order to do so, I will employ a set of advanced research designs, as well as a uniquely assembled micro-level dataset covering state and privately owned financial institutions in Asia, Africa, South America and Europe.
This project will focus on two interconnected areas of research: 1) Organisation of Credit, 2) Financial regulation in a complex environment. The aim of this project is to create a sustainable framework for the study of post-crisis financial systems, and to shape the current debate on the future of post-crisis financial structures and the development of policy in this area. Not only will this research have a considerable impact on our understanding of financial systems, it will also impact fields beyond finance, like Organisational Economics, Industrial Organisation and Development Economics.
Max ERC Funding
1 498 947 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym ComplexSex
Project Sex-limited experimental evolution of natural and novel sex chromosomes: the role of sex in shaping complex traits
Researcher (PI) Jessica Abbott
Host Institution (HI) LUNDS UNIVERSITET
Call Details Starting Grant (StG), LS8, ERC-2015-STG
Summary The origin and evolution of sexual reproduction and sex differences represents one of the major unsolved problems in evolutionary biology, and although much progress had been made both via theory and empirical research, recent data suggest that sex chromosome evolution may be more complex than previously thought. The concept of sexual antagonism (when there is a positive intersexual genetic correlation in trait expression but opposite fitness effects of the trait(s) in males and females) has become essential to our understanding of sex chromosome evolution. The goal of this proposal is to understand how the interacting effects of sexual antagonism, sex-linked genetic variation, and sex-specific selection shape the genetic architecture of complex traits. I will test the hypotheses that: 1) individual sexually antagonistic loci are common in the genome, both in separate-sexed species and in hermaphrodites, and drive patterns of sexual antagonism often seen on the trait level. 2) That the response to sex-specific selection in sex-linked loci is usually due to standing sexually antagonistic genetic variation. 3) That sexually antagonistic variation is primarily non-additive in nature. To accomplish this, I will use a combination of approaches, including sex-limited experimental evolution of the X chromosome and reciprocal sex chromosome introgression among distantly related populations of Drosophila, quantitative genetic analysis and experimental evolution mimicking the creation of a novel sex chromosome in the hermaphroditic flatworm Macrostomum, and analytical and simulation modeling. This project will serve to confirm or refute the assumption that trait-level sexual antagonism reflects the contributions of many individual sexually antagonistic loci, increase our understanding of the contribution of coevolution of the sex chromosomes to population divergence, and help provide us with a better general understanding of how genotype maps to phenotype.
Summary
The origin and evolution of sexual reproduction and sex differences represents one of the major unsolved problems in evolutionary biology, and although much progress had been made both via theory and empirical research, recent data suggest that sex chromosome evolution may be more complex than previously thought. The concept of sexual antagonism (when there is a positive intersexual genetic correlation in trait expression but opposite fitness effects of the trait(s) in males and females) has become essential to our understanding of sex chromosome evolution. The goal of this proposal is to understand how the interacting effects of sexual antagonism, sex-linked genetic variation, and sex-specific selection shape the genetic architecture of complex traits. I will test the hypotheses that: 1) individual sexually antagonistic loci are common in the genome, both in separate-sexed species and in hermaphrodites, and drive patterns of sexual antagonism often seen on the trait level. 2) That the response to sex-specific selection in sex-linked loci is usually due to standing sexually antagonistic genetic variation. 3) That sexually antagonistic variation is primarily non-additive in nature. To accomplish this, I will use a combination of approaches, including sex-limited experimental evolution of the X chromosome and reciprocal sex chromosome introgression among distantly related populations of Drosophila, quantitative genetic analysis and experimental evolution mimicking the creation of a novel sex chromosome in the hermaphroditic flatworm Macrostomum, and analytical and simulation modeling. This project will serve to confirm or refute the assumption that trait-level sexual antagonism reflects the contributions of many individual sexually antagonistic loci, increase our understanding of the contribution of coevolution of the sex chromosomes to population divergence, and help provide us with a better general understanding of how genotype maps to phenotype.
Max ERC Funding
1 492 011 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym ComplexSwimmers
Project Biocompatible and Interactive Artificial Micro- and Nanoswimmers and Their Applications
Researcher (PI) Giovanni Volpe
Host Institution (HI) GOETEBORGS UNIVERSITET
Call Details Starting Grant (StG), PE4, ERC-2015-STG
Summary Microswimmers, i.e., biological and artificial microscopic objects capable of self-propulsion, have been attracting a growing interest from the biological and physical communities. From the fundamental side, their study can shed light on the far-from-equilibrium physics underlying the adaptive and collective behavior of biological entities such as chemotactic bacteria and eukaryotic cells. From the more applied side, they provide tantalizing options to perform tasks not easily achievable with other available techniques, such as the targeted localization, pick-up and delivery of microscopic and nanoscopic cargoes, e.g., in drug delivery, bioremediation and chemical sensing.
However, there are still several open challenges that need to be tackled in order to achieve the full scientific and technological potential of microswimmers in real-life settings. The main challenges are: (1) to identify a biocompatible propulstion mechanism and energy supply capable of lasting for the whole particle life-cycle; (2) to understand their behavior in complex and crowded environments; (3) to learn how to engineer emergent behaviors; and (4) to scale down their dimensions towards the nanoscale.
This project aims at tackling these challenges by developing biocompatible microswimmers capable of elaborate behaviors, by engineering their performance when interacting with other particles and with a complex environment, and by developing working nanoswimmers.
To achieve these goals, we have laid out a roadmap that will lead us to push the frontiers of the current understanding of active matter both at the mesoscopic and at the nanoscopic scale, and will permit us to develop some technologically disruptive techniques, namely, targeted delivery of cargoes within complex environments, which is of interest for drug delivery and bioremediation, and efficient sorting of chiral nanoparticles, which is of interest for biomedical and pharmaceutical applications.
Summary
Microswimmers, i.e., biological and artificial microscopic objects capable of self-propulsion, have been attracting a growing interest from the biological and physical communities. From the fundamental side, their study can shed light on the far-from-equilibrium physics underlying the adaptive and collective behavior of biological entities such as chemotactic bacteria and eukaryotic cells. From the more applied side, they provide tantalizing options to perform tasks not easily achievable with other available techniques, such as the targeted localization, pick-up and delivery of microscopic and nanoscopic cargoes, e.g., in drug delivery, bioremediation and chemical sensing.
However, there are still several open challenges that need to be tackled in order to achieve the full scientific and technological potential of microswimmers in real-life settings. The main challenges are: (1) to identify a biocompatible propulstion mechanism and energy supply capable of lasting for the whole particle life-cycle; (2) to understand their behavior in complex and crowded environments; (3) to learn how to engineer emergent behaviors; and (4) to scale down their dimensions towards the nanoscale.
This project aims at tackling these challenges by developing biocompatible microswimmers capable of elaborate behaviors, by engineering their performance when interacting with other particles and with a complex environment, and by developing working nanoswimmers.
To achieve these goals, we have laid out a roadmap that will lead us to push the frontiers of the current understanding of active matter both at the mesoscopic and at the nanoscopic scale, and will permit us to develop some technologically disruptive techniques, namely, targeted delivery of cargoes within complex environments, which is of interest for drug delivery and bioremediation, and efficient sorting of chiral nanoparticles, which is of interest for biomedical and pharmaceutical applications.
Max ERC Funding
1 497 500 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym CONENE
Project Control of Large-scale Stochastic Hybrid Systems for Stability of Power Grid with Renewable Energy
Researcher (PI) Maryam Kamgarpour
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), PE7, ERC-2015-STG
Summary The increasing uptake of renewable energy sources and liberalization of electricity markets are significantly changing power system operations. To ensure stability of the grid, it is critical to develop provably safe feedback control algorithms that take into account uncertainties in the output of weather-based renewable generation and in participation of distributed producers and consumers in electricity markets. The focus of this proposal is to develop the theory and algorithms for control of large-scale stochastic hybrid systems in order to guarantee safe and efficient grid operations. Stochastic hybrid systems are a powerful modeling framework. They capture uncertainties in the output of weather-based renewable generation as well as complex hybrid state interactions arising from discrete-valued network topologies with continuous-valued voltages and frequencies. The problems of stability and efficiency of the grid in the face of its changes will be formulated as safety and optimal control problems for stochastic hybrid systems. Using recent advances in numerical optimization and statistics, provably safe and scalable numerical algorithms for control of this class of systems will be developed. These algorithms will be implemented and validated on realistic power grid simulation platforms and will take advantage of recent advances in sensing, control and communication technologies for the grid. The end outcome of the project is better quantifying and controlling effects of increased uncertainties on the stability of the grid. The societal and economic implications of this study are tied with the value and price of a secure power grid. Addressing the questions formulated in this proposal will bring the EU closer to its ambitious renewable energy goals.
Summary
The increasing uptake of renewable energy sources and liberalization of electricity markets are significantly changing power system operations. To ensure stability of the grid, it is critical to develop provably safe feedback control algorithms that take into account uncertainties in the output of weather-based renewable generation and in participation of distributed producers and consumers in electricity markets. The focus of this proposal is to develop the theory and algorithms for control of large-scale stochastic hybrid systems in order to guarantee safe and efficient grid operations. Stochastic hybrid systems are a powerful modeling framework. They capture uncertainties in the output of weather-based renewable generation as well as complex hybrid state interactions arising from discrete-valued network topologies with continuous-valued voltages and frequencies. The problems of stability and efficiency of the grid in the face of its changes will be formulated as safety and optimal control problems for stochastic hybrid systems. Using recent advances in numerical optimization and statistics, provably safe and scalable numerical algorithms for control of this class of systems will be developed. These algorithms will be implemented and validated on realistic power grid simulation platforms and will take advantage of recent advances in sensing, control and communication technologies for the grid. The end outcome of the project is better quantifying and controlling effects of increased uncertainties on the stability of the grid. The societal and economic implications of this study are tied with the value and price of a secure power grid. Addressing the questions formulated in this proposal will bring the EU closer to its ambitious renewable energy goals.
Max ERC Funding
1 346 438 €
Duration
Start date: 2016-04-01, End date: 2020-09-30
Project acronym ConFooBio
Project Resolving conflicts between food security and biodiversity conservation under uncertainty
Researcher (PI) Nils Bunnefeld
Host Institution (HI) THE UNIVERSITY OF STIRLING
Call Details Starting Grant (StG), SH3, ERC-2015-STG
Summary Resolving conflicts between food security and biodiversity conservation under uncertainty
Conflicts between food security and biodiversity conservation are increasing in scale and intensity and have been shown to be damaging for both biodiversity and human livelihoods. Uncertainty, for example from climate change, decreases food security, puts further pressure on biodiversity and exacerbates conflicts.
I propose to develop a novel model that predicts solutions to conflicts between biodiversity conservation and food security under uncertainty. ConFooBio will integrate game theory and social-ecological modelling to develop new theory to resolve conservation conflicts. ConFooBio will implement a three-tiered approach 1) characterise and analyse 7 real-world conservation conflicts impacted by uncertainty; 2) develop new game theory that explicitly incorporates uncertainty; and 3) produce and test a flexible social-ecological model, applicable to any real-world conflict where stakeholders operate under conditions of extreme uncertainty.
The project has importance for society at large because ecosystems and their services are central to human wellbeing. Managing a specific natural resource often results in conflict between those stakeholders focussing on improving food security and those focussed on biodiversity conversation. ConFooBio will illuminate resolutions to such conflicts by showing how to achieve win-win scenarios that protect biodiversity and secure livelihoods. In this project, I will develop a practical, transparent and flexible model for the sustainable future of natural resources that is also robust to uncertainty (e.g., climate change); this model will be highly relevant for environmental negotiations among stakeholders with competing objectives, e.g., the negotiations to set the United Nations Sustainable Development Goals in September 2015.
Summary
Resolving conflicts between food security and biodiversity conservation under uncertainty
Conflicts between food security and biodiversity conservation are increasing in scale and intensity and have been shown to be damaging for both biodiversity and human livelihoods. Uncertainty, for example from climate change, decreases food security, puts further pressure on biodiversity and exacerbates conflicts.
I propose to develop a novel model that predicts solutions to conflicts between biodiversity conservation and food security under uncertainty. ConFooBio will integrate game theory and social-ecological modelling to develop new theory to resolve conservation conflicts. ConFooBio will implement a three-tiered approach 1) characterise and analyse 7 real-world conservation conflicts impacted by uncertainty; 2) develop new game theory that explicitly incorporates uncertainty; and 3) produce and test a flexible social-ecological model, applicable to any real-world conflict where stakeholders operate under conditions of extreme uncertainty.
The project has importance for society at large because ecosystems and their services are central to human wellbeing. Managing a specific natural resource often results in conflict between those stakeholders focussing on improving food security and those focussed on biodiversity conversation. ConFooBio will illuminate resolutions to such conflicts by showing how to achieve win-win scenarios that protect biodiversity and secure livelihoods. In this project, I will develop a practical, transparent and flexible model for the sustainable future of natural resources that is also robust to uncertainty (e.g., climate change); this model will be highly relevant for environmental negotiations among stakeholders with competing objectives, e.g., the negotiations to set the United Nations Sustainable Development Goals in September 2015.
Max ERC Funding
1 497 151 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
