Methods For High Resistivity Measurements Related To Spacecraft Charging

A key parameter in modeling differential spacecraft charging is the resistivity of insulating materials. This parameter determines how charge will accumulate and redistribute across the spacecraft, as well as the time scale for charge transport and dissipation. ASTM constant voltage methods are shown to provide inaccurate resistivity measurements for materials with resistivities greater than ~1017 Ω-cm or with long polarization decay times such as are found in many polymers. These data have been shown to often be inappropriate for spacecraft charging applications, and have been found to underestimate charging effects by one to four orders of magnitude for many materials. The charge storage decay method is shown to be the preferred method to determine the resistivities of such highly insulating materials. A review is presented of methods to measure the resistivity of highly insulating materials—including the electrometer-resistance method, the electrometer-constant voltage method, and the charge storage method. The different methods are found to be appropriate for different resistivity ranges and for different charging circumstances. A simple, macroscopic, physics-based model of these methods allows separation of the polarization current and dark current components from long duration measurements of resistivity over day- to month-long time scales. Model parameters are directly related to the magnitude of charge transfer and storage and the rate of charge transport. The model largely explains the observed differences in resistivity found using the different methods and provides a framework for recommendations for the appropriate test method for spacecraft materials with different resistivities and applications

Proposed Modifications to Engineering Design Guidelines Related to Resistivity Measurements and Spacecraft Charging

A key parameter in modeling differential spacecraft charging is the resistivity of insulating materials. This determines how charge will accumulate and redistribute across the spacecraft, as well as the time scale for charge transport and dissipation. Existing spacecraft charging guidelines recommend use of tests and imported resistivity data from handbooks that are based principally upon ASTM methods that are more applicable to classical ground conditions and designed for problems associated with power loss through the dielectric, than for how long charge can be stored on an insulator. These data have been found to underestimate charging effects by one to four orders of magnitude for spacecraft charging applications. A review is presented of methods to measure the resistive of highly insulating materials, including the electrometer-resistance method, the electrometer-constant voltage method, the voltage rate-of-change method and the charge storage method. This is based on joint experimental studies conducted at NASA Jet Propulsion Laboratory and Utah State University to investigate the charge storage method and its relation to spacecraft charging. The different methods are found to be appropriate for different resistivity ranges and for different charging circumstances. A simple physics-based model of these methods allows separation of the polarization current and dark current components from long duration measurements of resistivity over day- to month-long time scales. Model parameters are directly related to the magnitude of charge transfer and storage and the rate of charge transport. The model largely explains the observed differences in resistivity found using the different methods and provides a framework for recommendations for the appropriate test method for spacecraft materials with different resistivities and applications. The proposed changes to the existing engineering guidelines are intended to provide design engineers more appropriate methods for consideration and measurements of resistivity for many typical spacecraft charging scenarios

Tele-Neurorehabilitation During the COVID-19 Pandemic: Implications for Practice in Low- and Middle-Income Countries

The importance of neurorehabilitation services for people with disabilities is getting well-recognized in low- and middle-income countries (LMICs) recently. However, accessibility to the same has remained the most significant challenge, in these contexts. This is especially because of the non-availability of trained specialists and the availability of neurorehabilitation centers only in urban cities owned predominantly by private healthcare organizations. In the current COVID-19 pandemic, the members of the Task Force for research at the Indian Federation of Neurorehabilitation (IFNR) reviewed the context for tele-neurorehabilitation (TNR) and have provided the contemporary implications for practicing TNR during COVID-19 for people with neurological disabilities (PWNDs) in LMICs. Neurorehabilitation is a science that is driven by rigorous research-based evidence. The current pandemic implies the need for systematically developed TNR interventions that is evaluated for its feasibility and acceptability and that is informed by available evidence from LMICs. Given the lack of organized systems in place for the provision of neurorehabilitation services in general, there needs to be sufficient budgetary allocations and a sector-wide approach to developing policies and systems for the provision of TNR services for PWNDs. The pandemic situation provides an opportunity to optimize the technological innovations in health and scale up these innovations to meet the growing burden of neurological disability in LMICs. Thus, this immense opportunity must be tapped to build capacity for safe and effective TNR services provision for PWNDs in these settings

Measurement of Charge Storage Decay Time and Resistivity of Spacecraft Insulators

Insulators used in the construction of spacecraft are irradiated with high-energy electrons in the space environment and this sometimes causes the insulators to charge to very high voltages. Such charged insulators can generate spontaneous electric partial-discharge pulses of the order of mA to tens of A. These pulses sometimes last enough time to destroy the expensive micro-circuitry present in the spacecraft. In evaluating the threat to the spacecraft due to these discharges, calculation of the resistivity becomes a critical parameter since it determines how accumulated charge will distribute across the spacecraft and how rapidly charge imbalance will dissipate. So far, resistivity values for the insulators for spacecraft applications have been simply imported from tabulated results measured using standard American Society for Testing and Materials (ASTM) and International Electro-technical Commission (IEC) methods. This thesis work provides the details of the charge storage method which has been found to be more appropriate in calculating the resistivity of spacecraft insulators by emulating the space environment better. This method is based on the concept that the resistivity is better measured as the decay of the charge deposited on the surface of an insulator, rather than by the flow of current across two electrodes around the sample which is the case with the classical method of measurements. From the results obtained from the charge storage method, it has been found that the ASTM resistivity values for thin film insulating spacecraft materials have been found to under-predict charge transport values applicable to many spacecraft charging problems, by 10 to 104 times. The charge storage method has only one side of the insulator in vacuum exposed to charged particles, light and plasma, with a metal electrode attached to the other side of the insulator. The chamber for measuring the charge storage decay has been designed with the capability to measure 32 samples simultaneously. The details of the apparatus, instrumentation, test methods, data acquisition methods, and data analysis for measuring resistivity of the spacecraft insulators are given here. Details about the vacuum environment, sample mounting, isolation of the samples, charging of the samples, measurement of the surface charge, rotary motion of the sample carousel, etc., are also given. The report also includes differences between the classical methods and the charge storage method both in terms instrumentation and methodology. The results obtained from both methods are tabulated showing the superiority of the charge storage method. Recommendations for future work are also included

Gestion prévisionnelle des réseaux actifs de distribution - relaxation convexe sous incertitude

Power systems are faced by the rising shares of distributed renewable energy sources (DRES) and the deregulation of the electricity system. Distribution networks and their operators (DSO) are particularly at the front-line. The passive operational practives of many DSOs today have to evolve to overcome these challenges. Active Distribution Networks (ADN), and Active Network Management (ANM) have been touted as a potential solution. In this context, DSOs will streamline investment and operational decisions, creating a cost-effective framework of operations. They will evolve and take up new roles and optimally use flexibility to perform, for example, short-term op- erational planning of their networks. However, the development of such methods poses particular challenges. They are related to the presence of discrete elements (OLTCs and reconfiguration), the use of exogenous (external) flexibilities in these networks, the non-linear nature of optimal power flow (OPF) calculations, and uncertainties present in forecasts. The work leading to this thesis deals with and overcomes these challenges. First, a short-term economic analysis is done to ascertain the utilisation costs of flexibilities. This provides a common reference for different flexibilities. Then, exact linear flexibility models are developed using mathematical reformulation techniques. The OPF equations in operational planning are then convexified using reformulation techniques as well. The mixed-integer convex optimisation model thus developed, called the novel OP formulation, is exact and can guarantee globally optimal solutions. Simulations on two test networks allow us to evaluate the performance of this formulation. The uncertainty in DRES forecasts is then handled via three different formulations developed in this thesis. The best performing formulations under uncertainty are determined via comparison framework developed to test their performance.Les réseaux électriques subissent deux changements majeurs : le taux croissant de générateurs d’énergie distribuée (GED) intermittents et la dérégulation du système électrique. Les réseaux de distribution et leurs gestionnaires (GRD) sont plus particulièrement touchés. La planification, construction et exploitation des réseaux de la plupart des GRD doivent évoluer face à ces change- ments. Les réseaux actifs de distribution et la gestion intelligente de associée est une solution potentielle. Les GRD pourront ainsi adopter de nouveaux rôles, interagir avec de nouveaux acteurs et proposer de nouveaux services. Ils pourront aussi utiliser la flexibilité de manière optimale au travers, entre autres, d’outils intelligents pour la gestion prévisionnelle de leurs réseaux de moyenne tension (HTA). Développer ces outils est un défi, car les réseaux de distribution ont des spécificités techniques. Ces spécificités sont la présence d’éléments discrets comme les régleurs en charge et la reconfiguration, les flexibilités exogènes, la non-linéarité des calculs de répartition de charge, et l’incertitude liée aux prévisions des GED intermittents. Dans cette thèse, une analyse économique des flexibilités permet d’établir une référence commune pour une utilisation rentable et sans biais dans la gestion prévisionnelle. Des modèles linéaires des flexibilités sont développés en utilisant des reformulations mathématiques exactes. Le calcul de répartition de charge est “convexifié” à travers des reformulations. L’optimalité globale des solutions obtenues, avec ce modèle d’optimisation exact et convexe de gestion prévisionnelle, sont ainsi garanties. Les tests sur deux réseaux permettent d’en valider la performance. L’incertitude des prévisions de GED peut pourtant remettre en cause les solutions obtenues. Afin de résoudre ce problème, trois formulations différentes pour traiter cette incertitude sont développées. Leurs performances sont testées et comparées à travers des simulations. Une analyse permet d’identifier les formulations les plus adaptées pour la gestion prévisionnelle sous incertitude

Gestion prévisionnelle des réseaux actifs de distribution - relaxation convexe sous incertitude

Power systems are faced by the rising shares of distributed renewable energy sources (DRES) and the deregulation of the electricity system. Distribution networks and their operators (DSO) are particularly at the front-line. The passive operational practives of many DSOs today have to evolve to overcome these challenges. Active Distribution Networks (ADN), and Active Network Management (ANM) have been touted as a potential solution. In this context, DSOs will streamline investment and operational decisions, creating a cost-effective framework of operations. They will evolve and take up new roles and optimally use flexibility to perform, for example, short-term op- erational planning of their networks. However, the development of such methods poses particular challenges. They are related to the presence of discrete elements (OLTCs and reconfiguration), the use of exogenous (external) flexibilities in these networks, the non-linear nature of optimal power flow (OPF) calculations, and uncertainties present in forecasts. The work leading to this thesis deals with and overcomes these challenges. First, a short-term economic analysis is done to ascertain the utilisation costs of flexibilities. This provides a common reference for different flexibilities. Then, exact linear flexibility models are developed using mathematical reformulation techniques. The OPF equations in operational planning are then convexified using reformulation techniques as well. The mixed-integer convex optimisation model thus developed, called the novel OP formulation, is exact and can guarantee globally optimal solutions. Simulations on two test networks allow us to evaluate the performance of this formulation. The uncertainty in DRES forecasts is then handled via three different formulations developed in this thesis. The best performing formulations under uncertainty are determined via comparison framework developed to test their performance.Les réseaux électriques subissent deux changements majeurs : le taux croissant de générateurs d’énergie distribuée (GED) intermittents et la dérégulation du système électrique. Les réseaux de distribution et leurs gestionnaires (GRD) sont plus particulièrement touchés. La planification, construction et exploitation des réseaux de la plupart des GRD doivent évoluer face à ces change- ments. Les réseaux actifs de distribution et la gestion intelligente de associée est une solution potentielle. Les GRD pourront ainsi adopter de nouveaux rôles, interagir avec de nouveaux acteurs et proposer de nouveaux services. Ils pourront aussi utiliser la flexibilité de manière optimale au travers, entre autres, d’outils intelligents pour la gestion prévisionnelle de leurs réseaux de moyenne tension (HTA). Développer ces outils est un défi, car les réseaux de distribution ont des spécificités techniques. Ces spécificités sont la présence d’éléments discrets comme les régleurs en charge et la reconfiguration, les flexibilités exogènes, la non-linéarité des calculs de répartition de charge, et l’incertitude liée aux prévisions des GED intermittents. Dans cette thèse, une analyse économique des flexibilités permet d’établir une référence commune pour une utilisation rentable et sans biais dans la gestion prévisionnelle. Des modèles linéaires des flexibilités sont développés en utilisant des reformulations mathématiques exactes. Le calcul de répartition de charge est “convexifié” à travers des reformulations. L’optimalité globale des solutions obtenues, avec ce modèle d’optimisation exact et convexe de gestion prévisionnelle, sont ainsi garanties. Les tests sur deux réseaux permettent d’en valider la performance. L’incertitude des prévisions de GED peut pourtant remettre en cause les solutions obtenues. Afin de résoudre ce problème, trois formulations différentes pour traiter cette incertitude sont développées. Leurs performances sont testées et comparées à travers des simulations. Une analyse permet d’identifier les formulations les plus adaptées pour la gestion prévisionnelle sous incertitude

Operational Planning of Active Distribution Networks - Convex Relaxation under Uncertainty

Les réseaux électriques subissent deux changements majeurs : le taux croissant de générateurs d’énergie distribuée (GED) intermittents et la dérégulation du système électrique. Les réseaux de distribution et leurs gestionnaires (GRD) sont plus particulièrement touchés. La planification, construction et exploitation des réseaux de la plupart des GRD doivent évoluer face à ces change- ments. Les réseaux actifs de distribution et la gestion intelligente de associée est une solution potentielle. Les GRD pourront ainsi adopter de nouveaux rôles, interagir avec de nouveaux acteurs et proposer de nouveaux services. Ils pourront aussi utiliser la flexibilité de manière optimale au travers, entre autres, d’outils intelligents pour la gestion prévisionnelle de leurs réseaux de moyenne tension (HTA). Développer ces outils est un défi, car les réseaux de distribution ont des spécificités techniques. Ces spécificités sont la présence d’éléments discrets comme les régleurs en charge et la reconfiguration, les flexibilités exogènes, la non-linéarité des calculs de répartition de charge, et l’incertitude liée aux prévisions des GED intermittents. Dans cette thèse, une analyse économique des flexibilités permet d’établir une référence commune pour une utilisation rentable et sans biais dans la gestion prévisionnelle. Des modèles linéaires des flexibilités sont développés en utilisant des reformulations mathématiques exactes. Le calcul de répartition de charge est “convexifié” à travers des reformulations. L’optimalité globale des solutions obtenues, avec ce modèle d’optimisation exact et convexe de gestion prévisionnelle, sont ainsi garanties. Les tests sur deux réseaux permettent d’en valider la performance. L’incertitude des prévisions de GED peut pourtant remettre en cause les solutions obtenues. Afin de résoudre ce problème, trois formulations différentes pour traiter cette incertitude sont développées. Leurs performances sont testées et comparées à travers des simulations. Une analyse permet d’identifier les formulations les plus adaptées pour la gestion prévisionnelle sous incertitude.Power systems are faced by the rising shares of distributed renewable energy sources (DRES) and the deregulation of the electricity system. Distribution networks and their operators (DSO) are particularly at the front-line. The passive operational practives of many DSOs today have to evolve to overcome these challenges. Active Distribution Networks (ADN), and Active Network Management (ANM) have been touted as a potential solution. In this context, DSOs will streamline investment and operational decisions, creating a cost-effective framework of operations. They will evolve and take up new roles and optimally use flexibility to perform, for example, short-term op- erational planning of their networks. However, the development of such methods poses particular challenges. They are related to the presence of discrete elements (OLTCs and reconfiguration), the use of exogenous (external) flexibilities in these networks, the non-linear nature of optimal power flow (OPF) calculations, and uncertainties present in forecasts. The work leading to this thesis deals with and overcomes these challenges. First, a short-term economic analysis is done to ascertain the utilisation costs of flexibilities. This provides a common reference for different flexibilities. Then, exact linear flexibility models are developed using mathematical reformulation techniques. The OPF equations in operational planning are then convexified using reformulation techniques as well. The mixed-integer convex optimisation model thus developed, called the novel OP formulation, is exact and can guarantee globally optimal solutions. Simulations on two test networks allow us to evaluate the performance of this formulation. The uncertainty in DRES forecasts is then handled via three different formulations developed in this thesis. The best performing formulations under uncertainty are determined via comparison framework developed to test their performance