In dieser Arbeit wird die Konzeption und Umsetzung einer digitalen Echtzeit-Lagedarstellung für Mittel der nichtpolizeilichen Gefahrenabwehr im Umfeld der Integrierten Regionalleitstelle Leipzig beschrieben. Das Ziel besteht darin, eine automatische, selbstfüllende Lösung zur Datenintegration und -darstellung zu konzipieren, die eine umfassende und bedarfsgerechte Informationsversorgung ohne direkte Zuarbeiten des Leitstellenpersonals ermöglicht. Die in der Leitstelle vorhandenen Daten sollen genutzt werden, um unter anderem die Auslastung und Verfügbarkeit von Ressourcen sowie Einsatzschwerpunkte zu visualisieren und diese Informationen den Nutzergruppen bedarfsgerecht zur Verfügung zu stellen, um basierend darauf taktische Entscheidungen treffen zu können. Um den Bedarf und die Anforderungen zu ermitteln, wurde eine qualitative und quantitative Umfrage durchgeführt. Die Ergebnisse haben den grundlegenden Bedarf mit verschiedenen Bedürfnissen und Prioritäten der unterschiedlichen Nutzergruppen bestätigt. In dieser Arbeit wurden verschiedene Lösungsansätze verglichen und die Entwicklung eines Prototypen für eine Echtzeit-Lagedarstellung vorgestellt. Die Anwendbarkeit und Grenzen des entwickelten Prototypen wurden durch praktische Untersuchungen mit direktem Feedback und einer Überprüfung der Korrektheit der Daten bewertet. Die Evaluation ergab, dass der Prototyp bereits in seiner derzeitigen Form ein sehr genaues Lagebild liefert und die Erwartungen der Nutzer erfüllt.:Inhaltsverzeichnis Abkürzungsverzeichnis 1 Übersicht 1.1 Zielstellung 1.2 Methodisches Vorgehen 2 Betrachtung der Ausgangssituation 2.1 Die Integrierte Regionalleitstelle Leipzig 2.2 Technischer Aufbau der IRLS 2.3 Lagedarstellung 2.3.1 Lagedarstellung im Kontext der nichtpolizeilichen Gefahrenabwehr 2.3.2 Lagedarstellung im Kontext der Leitstelle 2.3.3 Einordnung der Lagedarstellung in einen allgemeinen Kontext 3 Anforderungen 3.1 Ermittlung des optimalen Informationsbedarfs 3.2 Durchführung einer Umfrage 3.2.1 Im Bereich Feuerwehr 3.2.2 Im Bereich Rettungsdienst 3.2.3 Im Bereich Katastrophenschutz 3.2.4 Zusammenfassung der Ergebnisse 3.3 Vergleich von Lösungsansätzen 3.3.1 Anruf in der Leitstelle 3.3.2 Bereitstellung des Einsatzleitsystems für Anwender 3.3.3 Gang in die Leitstelle 3.3.4 LvS Display 3.3.5 MobiKat 4 Entwicklung eines Prototypen zur Echtzeit-Lagedarstellung 4.1 Lösungsansatz 4.2 Implementierung 4.2.1 Werkzeuge 4.2.2 Daten und Datenquellen 4.2.3 Herangehensweise 4.3 Datenschutzkriterien 4.4 Plausibilität 5 Untersuchung des Prototypen im Leitstellenumfeld und der Gefahrenabwehr 5.1 Im Einsatzfeld der Stabsarbeit 5.2 Ressourcenbetrachtung 5.2.1 HLF 5.2.2 RTW 5.3 Schlussfolgerung 5.4 Grenzfälle 5.5 Kritik des Modells 6 Fazit und Ausblick Abbildungsverzeichnis Tabellenverzeichnis Quellcodeverzeichnis Literaturverzeichnis Anhang / This paper describes the design and implementation of a digital real-time management display for resources of emergency services in the vicinity of the Leipzig Regional Dispatch Center. The objective is to create an automated and self-populating system for data integration and display, facilitating the extensive and tailored supply of information without the need for direct human involvement within the control center. The data available in the control center provides visualization of resource utilization and availability, operational priorities, and other key information that can be made available to user groups on demand for tactical decision making. A qualitative and quantitative survey was conducted to identify needs and requirements. The results confirmed the demand with different demands and priorities of the various user groups. The paper compares different approaches and presents the development of a prototype for a real-time management display. Practical tests with direct feedback and a verification of accuracy were used to evaluate the capabilities and limitations of the developed prototype. The evaluation demonstrated that the prototype currently offers a fairly accurate picture of the situation and meets the expectations of the users.:Inhaltsverzeichnis Abkürzungsverzeichnis 1 Übersicht 1.1 Zielstellung 1.2 Methodisches Vorgehen 2 Betrachtung der Ausgangssituation 2.1 Die Integrierte Regionalleitstelle Leipzig 2.2 Technischer Aufbau der IRLS 2.3 Lagedarstellung 2.3.1 Lagedarstellung im Kontext der nichtpolizeilichen Gefahrenabwehr 2.3.2 Lagedarstellung im Kontext der Leitstelle 2.3.3 Einordnung der Lagedarstellung in einen allgemeinen Kontext 3 Anforderungen 3.1 Ermittlung des optimalen Informationsbedarfs 3.2 Durchführung einer Umfrage 3.2.1 Im Bereich Feuerwehr 3.2.2 Im Bereich Rettungsdienst 3.2.3 Im Bereich Katastrophenschutz 3.2.4 Zusammenfassung der Ergebnisse 3.3 Vergleich von Lösungsansätzen 3.3.1 Anruf in der Leitstelle 3.3.2 Bereitstellung des Einsatzleitsystems für Anwender 3.3.3 Gang in die Leitstelle 3.3.4 LvS Display 3.3.5 MobiKat 4 Entwicklung eines Prototypen zur Echtzeit-Lagedarstellung 4.1 Lösungsansatz 4.2 Implementierung 4.2.1 Werkzeuge 4.2.2 Daten und Datenquellen 4.2.3 Herangehensweise 4.3 Datenschutzkriterien 4.4 Plausibilität 5 Untersuchung des Prototypen im Leitstellenumfeld und der Gefahrenabwehr 5.1 Im Einsatzfeld der Stabsarbeit 5.2 Ressourcenbetrachtung 5.2.1 HLF 5.2.2 RTW 5.3 Schlussfolgerung 5.4 Grenzfälle 5.5 Kritik des Modells 6 Fazit und Ausblick Abbildungsverzeichnis Tabellenverzeichnis Quellcodeverzeichnis Literaturverzeichnis Anhang

<p>Smart and connected technology solutions have emerged as a promising way to enhance EMS services, particularly in areas where access to professional services is limited. However, a significant challenge for improving their implementation is determining which technologies to use and how they will change current logistic operations to enhance service efficiencies and expand access to care. In this context, this thesis explores opportunities for the smart and connected technology solutions.</p> <p>The first study explores the use of medically trained volunteers in the community, known as Citizen Responders (CRs). These individuals can be quickly notified of an EMS request upon its arrival via a mobile alert receiver, which allows them to provide timely and potentially life-saving assistance before an ambulance arrives. However, traditional EMS logistic decision platforms are not equipped to effectively leverage the sharing of the real-time CR information enabled by connected technologies, such as their location and availability. To improve coordination between CRs and ambulances, this study proposes two decision tools that incorporate real-time CR information: one for redeploying ambulances after they complete service and another for dispatching ambulances in response to calls. The redeployment procedure uses mixed-integer linear programming (MILP) to maximize patient survival, while the dispatch procedure enhances a locally optimal dispatch procedure by integrating real-time CR information for priority-differentiated emergencies.</p> <p>In the second study, a third decision tool was developed to take advantage of the increasing availability of feature information provided by connected technologies: an AI-enabled dispatch rule recommendation model that is more usable for dispatchers than black-box decision models. This is a model based on supervised learning that outputs a “promising” metric-based dispatch rule for the human decision-maker. The model maintains the usability of rules while enhancing the system’s performance and alleviating the cognitive burden of dispatchers. A set of experiments were performed on a self-developed simulator to assess the performance of all the decision tools. The findings suggest they have the potential to significantly enhance the EMS system performance. </p>

No / A genetic algorithm (GA) augmented with knowledge-based methods has been developed for solving the unit commitment economic dispatch problem. The GA evolves a population of binary strings which represent commitment schedules. The initial population of schedules is chosen using a method based on elicited scheduling knowledge. A fast rule-based dispatch method is then used to evaluate candidate solutions. The knowledge-based genetic algorithm is applied to a test system of ten thermal units over 24-hour time intervals, including minimum on/off times and ramp rates, and achieves lower cost solutions than Lagrangian relaxation in comparable computational time.

Electric grids across the world are experiencing an ever increasing number of extreme events ranging from extreme weather events to cyberattacks. Such extreme events have the potential to cause widespread power outages and even a blackout. A vast majority of power outages impacting the U.S. electric grid impact the distribution system. There are an estimated five million miles of distribution lines in the US electric grid. A majority of these lines are low-clearance overhead lines making them even more susceptible to damage during extreme events. However, this vital component of the U.S. electric grid remained neglected until recently. In recent decades, the integration of distributed energy resources (DERs) such as solar photovoltaic systems and battery energy storage systems at the grid edge have provided a major opportunity for enhancing the resilience of distribution systems. These DERs can be used to restore power supply when the bulk grid becomes unavailable. However, managing the interactions among different types of DERs has been challenging. Low inertia and significant differences in time constants of operation between conventional generation and inverter based resources (IBRs) are some of these challenges. Widespread deployment of microgrid controller capabilities can be a promising solution to manage these interactions. However, due to interoperability and integration challenges of optimization and dynamics control systems, power conversion systems and communication systems, the adoption of microgrids especially in underserved communities has been slow. The research presented in this dissertation is a significant step forward in this direction by proposing an approach which integrates optimal dispatch, sequential microgrid restoration and control algorithms. Potential cyberattack paths are identified by creating a detailed cyber-physical system model for microgrids. A two-tiered intrusion detection system is developed to detect and mitigate cyberattacks within the cyber layer itself. The developed sequential microgrid restoration algorithm coordinates optimal DER dispatch with the operation of legacy devices with no remote control or communication capabilities and net-metered loads with limited communications. By better utilizing the control capabilities of IBRs, reliance on low-latency centralized control algorithms has also been reduced. The developed approach systematically ensures adequate availability of control during dispatch and restoration to maintain microgrid stability. This research can thus pave the way for faster and more cost-effective deployment of microgrids. / Doctor of Philosophy / A U.S. National Academy of Engineering report has described the power grid as the greatest engineering achievement of the 20th century. The power grid is a complex interconnected system consisting of the power transmission system and the distribution system. The power transmission system consists of the power lines seen while driving on the freeways and the large power generating stations consisting of renewable, coal or nuclear power plants. Ensuring the reliable operation of the transmission system has always been a priority. The distribution system on the other hand consists of pole top transformers seen closer to homes which reduce the voltage to levels safe for electrical appliances. It also consists of the millions of miles of low-clearance overhead distribution lines deployed across the U.S. that provide electricity to every household. This critical part of U.S. electricity infrastructure had remained neglected which is the reason why 90% of power outages impact the distribution system. In recent decades, the integration of renewable energy sources like solar systems and battery storage systems has created an unprecedented opportunity for increasing the resilience of distribution systems against extreme events. These energy sources can provide power supply when the transmission system becomes unavailable. However, ensuring safe and reliable integrated operation of these sources with conventional diesel generators especially while isolated from the transmission system is challenging. This is where microgrids, which are self-sufficient miniature power grids, can help. Microgrids provide required control, communication and cybersecurity features necessary for reliable integrated operation of renewable and conventional energy sources. However, the challenges involved with interoperability of these systems has slowed down the deployment of microgrids especially in underserved communities. This is the research gap addressed in this dissertation. This research provides an approach for integrating the optimization, control, power electronics and cybersecurity systems. Reliance on expensive low-latency communication systems is reduced by utilizing the emerging capabilities of power electronics devices used for integrating the renewable energy sources with the electric power grid. Voltage control devices already deployed in the distribution systems which do not have remote control or communication capabilities have also been coordinated with energy sources. The research presented in this dissertation is a significant step forward for increasing access to power supply during outages and for reducing the time and cost of deployment of microgrids.

Made available in DSpace on 2014-06-11T19:22:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-08-23Bitstream added on 2014-06-13T20:48:01Z : No. of bitstreams: 1 souza_mas_me_bauru.pdf: 1718716 bytes, checksum: 06558a2073d16192fb7eaf1e9f95ca28 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este trabalho visa a investigação e implementação de métodos Primal - Dual Previsor-Corretor de Pontos Interiores com a estratégia de busca unidimensional, e a aplicação destes em problemas de Despacho Econômico e Ambiental. Objetiva-se utilizar estes métodos para determinar soluções aproximadas e consistentes dos problemas causados citados, que forneçam a solução de minimização dos custos dos combustíveis empregados na geração termoelétrica de energia, otimizando um processo de alocação da demanda de energia elétrica entre as unidades geradoras disponíveis, de tal forma que as restrições operacionais sejam atendidas e que o custo de geração é minimizado. Pretende-se também, analisar o problema de Despacho Ambiental com um objetivo único quando se acopla a este o Problema de Despacho Econômico e busca-se, simultaneamente, a minimização dos custos de geração e a redução da emissão de poluentes na natureza. Os métodos foram implementados, testados em Problemas de Despacho Econômico e Ambiental, e o seu desempenho foi comparado com outros métodos já utilizados, cujos resultados são encontrados na literatura / This work aims the investigation and implementation of Primal-Dual Predictor-Corrector interior points methods, with the strategy of one-dimensional search, and its application in Economic and Environmental Dispatch Problems. It pretends to use these methods to determine approximate and consistent solutions of the mentioned problems, that provide the solution to minimize the fuel costs used in thermoelectric power generation, optimizing an allocations process of eletric power demand among available generation units, such that the operational constraints are attended and that generation cost is minimized. It too pretends to analyze the Environmental Dispatch Problem with the one objective when it is joined with the Dispatch Problems and it searchs, simultaneously, the minimization of the generation costs and the reduction of emission of the polluants in the nature. The methods were implemented, tested on the Economic and Environemental Dispatch Problems and its performance was compared with others method currently used, whose results are found in the literature

Monomorphization and dynamic dispatch are two common techniques for implementing polymorphism in statically typed programming languages. Function templates in C++ use the former technique to enable algorithms written as generic functions to be efficiently reused with multiple different data types by producing a separate function instantiation for each invocation that uses a unique permutation of argument types. This avoids the overhead of indirection associated with dynamic dispatch and allows the generated code of each instantiation to be optimized by the compiler for its specific concrete types, which typically yields great improvements in runtime performance over any dynamic approach. The disadvantage of this implementation, compared to the type-erased generics found in many other programming languages, is that careless over-use of templates with many different argument types can lead to an excessive amount of redundant code being generated for the same function. This increase in code size may increase the binary size of the final program and reduce the amount of useful code that can fit into the processor's instruction cache during execution, reducing code locality and thereby potentially reducing performance. Monomorphization can also increase compilation time due to the increase in generated code that needs to be compiled and optimized. This thesis presents a heuristic-based approach to generic programming that allows function templates to be automatically converted to use dynamic dispatch in scenarios where the resulting negative impact on runtime performance is predicted to be low. The thesis project includes the development of a proof of concept plugin for the Clang compiler frontend that can be used to compile existing C++ projects with the conversions applied. The design of a heuristic function for determining whether a given function template should use monomorphization or dynamic dispatch based on statically known metrics is proposed based on the results of an experiment. This heuristic is shown to achieve a small general improvement in program size across a set of open-source C++ projects when they are compiled using the plugin. The key findings from the experiment and from the development of the plugin are summarized with a general strategy for how the approach can be integrated into the design of future programming languages to promote more extensive use of generic programming in performance-sensitive code while avoiding regressions in program size and compilation time.

Master of Science / Department of Electrical and Computer Engineering / Anil Pahwa / A time may soon come where prices of electricity vary by time of day or season. Time of Day (TOD) pricing is considered by many to be a key part of creating a more energy-efficient and renewable-energy friendly grid. TOD pricing is also an integral part of Smart Grid and is already available to some customers. With TOD pricing becoming a reality, intelligent dispatching systems that utilize Energy Storage Devices (ESDs) to maximize the use of renewable resources, such as energy produced by small, customer owned wind generators and roof-top solar generators, and grid energy while determining the most economical dispatch schedule could play an important role for both the customer and the utility. This purpose of this work is to create an algorithm upon which these dispatching systems can be based. The details of one proposed algorithm are presented. The full development of the algorithm from its most simplistic form into a much more complex system that takes into account all of the major nonidealities of a real system is given. Additionally, several case studies are presented to show the effectiveness of the algorithm from both a technical standpoint and an economic standpoint. The case studies simulated both wind and solar powered devices using data taken in the state of Kansas, but case studies to emulate electric rates and renewable resources in other areas of the country are presented as well. For each of these case studies, 20 year net present value calculations are presented to determine the economic viability of both the renewable energy production and the dispatching systems.

Introduktion: Dagens sjukvård består av olika vårdkedjor där larmcentralen och ambulanssjukvården utgör den första länken för många patienter. Larmcentralen ansvarar för att ta emot, hantera och prioritera nödsamtal som sedan dirigeras ut till ambulansverksamheten. God interprofessionell kommunikation är en förutsättning för att länken ska vara intakt och därmed främja en patientsäker vård. Den forskningsbrist som råder i området motiverar studiens genomförande.   Syfte: Att beskriva förutsättningar för kommunikation mellan ambulansdirigenter och ambulanspersonal utifrån ambulansdirigenters och ambulanssjuksköterskors erfarenheter.   Metod: Studien är en kvalitativ intervjustudie med induktiv ansats. Ett bekvämlighetsurval tillämpades och tolv semistrukturerade intervjuer genomfördes. Analysen utgick ifrån en latent innehållsanalys i enlighet med Lundman och Hällgren Graneheim (2012).   Resultat: Ett tema formades ur den latenta analysen, vilket benämns Mot samma mål trots olika förutsättningar. Resultatet redovisas utifrån två huvudkategorier; teknikens förtjänster och begränsningar samt personliga förmågor. Dessa bygger på sex underkategorier som beskriver informanternas erfarenheter gällande kommunikationen dem emellan. Underkategorierna benämns vara beroende av kommunikationsteknik, behov av samtal, bemötande, hantera stress, ifrågasättande och bristande tillit samt förståelse för varandras uppdrag. Det framkom att fungerande teknik och korrekt hantering av den är centralt för kommunikationen. Oavsett vad rutiner säger så finns det i vissa situationer ett behov av muntlig kommunikation. De personliga egenskaperna påverkar hur kommunikationen fortlöper.   Slutsats: Tekniken måste fungera och personalen måste vara välutbildade inom det tekniska handhavandet. Möjligheten till hospitering inom de båda verksamheterna anses vara av stor vikt för att bidra till en ökad förståelse, vilket på sikt kan förbättra den interprofessionella kommunikationen mellan dem. / Introduction: Today's health care consists of different care chains where SOS Alarm and the ambulance service constitute the first link for many patients. SOS Alarm is responsible for receiving, manage and prioritize emergency calls which are then routed out to the ambulance. Good interprofessional communication is a prerequisite for the link to be intact and thereby achieve a safe care for the patient. The lack of research in the area justifies the implementation of this study.   Aim: To describe the conditions for communication between ambulance conductors and ambulance staff based on the experiences of ambulance conductors and ambulance nurses.   Method: The study is a qualitative interview study with an inductive approach. A convenience sample was applied and twelve semi-structured interviews were conducted. The analysis was based on a latent content analysis in accordance with Lundman and Hällgren Graneheim (2012).   Result: A theme was formed from the latent analysis, which is called Towards the same goals despite different conditions. The result is reported on two main categories: The benefits and limitations of the technology as well as personal abilities. These are based on six subcategories which describes the informants' experiences regarding communication between them. The subcategories are called dependency on communication technology, need for conversation, attitude, dealing with stress, questioning and lack of confidence, and understanding of each other's assignments. It emerged that working technology and proper handling of it are central to communication. Regardless of what routines say, there is a need for oral communication in certain situations. Personal qualities affect how communication progresses.   Conclusion: Is that the technology must be working and the staff must be well-trained in the technical handling. The possibility of visits in each other’s organizations are considered to be of great importance to contribute to a greater understanding, which ultimately can improve communication between them.

Variable generator output levels from renewable energies is an important technical obstacle to the transition from fossil fuels to renewable resources. Super grids and smart grids are among the most effective solutions to mitigate generation variability. In a super grid, electric utilities within an interconnected system can share generation and reserve units so that they can produce electricity at a lower overall cost. Smart grids, in particular demand response programs, enable flexible loads such as plug-in electric vehicles and HVAC systems to consume electricity preferntially in a grid-friendly way that assists the grid operator to maintain the power balance. These solutions, in conjunction with energy storage systems, can facilitate renewable integration. This study aims to provide an understanding of the achievable benefits from integrating demand response into wholesale and retail electricity markets, in particular in the presence of significant amounts of variable generation. Among the options for control methods for demand response, market-based approaches provide a relatively efficient use of load flexibility, without restricting consumers' autonomy or invading their privacy. In this regard, a model of demand response integration into bulk electric grids is presented to study the interaction between variable renewables and demand response in the double auction environment, on an hourly basis. The cost benefit analysis shows that there exists an upper limit of renewable integration, and that additional solutions such as super grids and/or energy storage systems are required to go beyond this threshold. The idea of operating an interconnection in an unified (centralized) manner is also explored. The traditional approach to the unit commitment problem is to determine the dispatch schedule of generation units to minimize the operation cost. However, in the presence of price-sensitive loads (market-based demand response), the maximization of economic surplus is a preferred objective to the minimization of cost. Accordingly, a surplus-maximizing hour-ahead scheduling problem is formulated, and is then tested on a system that represents a 20-area reduced model of the North America Western Interconnection for the planning year 2024. The simulation results show that the proposed scheduling method reduces the total operational costs substantially, taking advantage of renewable generation diversity. The value of demand response is more pronounced when ancillary services (e.g. real-time power balancing and voltage/frequency regulation) are also included along with basic temporal load shifting. Relating to this, a smart charging strategy for plug-in electric vehicles is developed that enables them to participate in a 5-minute retail electricity market. The cost reduction associated with implementation of this charging strategy is compared to uncontrolled charging. In addition, an optimal operation method for thermostatically controlled loads is developed that reduces energy costs and prevents grid congestion, while maintaining the room temperature in the comfort range set by the consumer. The proposed model also includes loads in the energy imbalance market. The simulation results show that market-based demand response can contribute to a significant cost saving at the sub-hourly level (e.g. HVAC optimal operation), but not at the super-hourly level. Therefore, we conclude that demand response programs and super grids are complementary approaches to overcoming renewable generation variation across a range of temporal and spatial scales. / Graduate / 0791 / sahandbehboodi@gmail.com

In this thesis, we propose novel optimization and spatial queueing models that expand the currently existing methods by allowing multiple servers to be located at the same station and multiple servers to be dispatched to a single call. In particular, a mixed integer linear programming (MILP) model is introduced that determines how to locate and dispatch ambulances such that the coverage level is maximized. The model allows multiple servers to be located at the same station and balances the workload among them while maintaining contiguous first priority response districts. We also propose an extension to the approximate Hypercube queueing model by allowing multi-server dispatches. Computational results suggest that both models are effective in optimizing and analyzing the emergency systems. We also introduce the M[G]/M/s/s queueing model as an extension to the M/M/s/s model which allows for multiple servers to be assigned to a single customer.