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The solution of generation scheduling (GS) problems involves the determination of the unit commitment (UC) and economic dispatch (ED) for each generator in a power system at each time interval in the scheduling period. The solution procedure requires the simultaneous consideration of these two decisions. In recent years researchers have focused much attention on new solution techniques to GS. This paper proposes the application of a variety of genetic algorithm (GA) based approaches and investigates how these techniques may be improved in order to more quickly obtain the optimum or near optimum solution for the GS problem. The results obtained show that the GA-based hybrid approach offers an effective alternative for solving realistic GS problems within a realistic timeframe.

<p dir="ltr">There are 150 fatal occupational injuries on average per year due to exposure to electricity in the United States (U.S.) [1]. Power utility workers are exposed to electrical hazards when restoring power service to utility customers, who experience an average of 2 hours of power outages per year in the U.S. [2]. Utility companies struggle to keep qualified workers from quitting during the highest ever-recorded voluntary turnover in the U.S. with 55 million people quitting their jobs in 2022, raising the risk of safety incidents [3].</p><p dir="ltr">This research studies the department responsible for the operations in the power distribution system, Distribution Dispatch Center (DDC), based on a case study of a power company called Ohm-Sweet-Ohm (OSO) Inc. This thesis proposes a 12-step methodology and approach to assess the efficiency of OSO DDC by using a variation of the Collective System Design methodology for the design of enterprises [4].</p><p dir="ltr">The methodology consists of developing a system design decomposition that defines the functions and improvements to existing solutions of OSO DDC. The decomposition addresses the inconsistencies of the functions identified without a solution in the current state of OSO DDC.</p><p dir="ltr">The proposed methodology's impact is safety improvements in power distribution operations and the potential cost benefit for OSO Inc. of almost four million dollars a year. The measurements to evaluate the success of the proposed solutions are the number of safety incidents per year, the time taken to restore utility customers after power outages, and the voluntary turnover rate in the OSO DDC.</p>

An electric power system consists of several generating stations which cater to the load demands of various regions. The prime function of any generating utility is to optimally schedule the real power output of its generating units to meet any specified real power demand subject to various constraints on the operation of the units and the system. The optimal scheduling of individual generators at the least possible cost is referred to as the economic dispatch or economic load dispatch (ELD) problem. The ELD studies play a vital role in the day­to­day operation of the power system and in formulating economic operating strategies, besides ensuring the stability and security of the system. This thesis work makes an effort to probe deeper into some aspects of the economic load dispatch problem and the underlying mathematical formulations and attempts to come up with generalized algorithms that can effectively handle different types of systems under different operating conditions and, to a certain extent, to try and resolve some aspects hitherto unresolved. The primary focus is on developing efficient computational techniques to solve some Specific types of ELD problems in a simple and systematic manner. In the course of this investigation, we highlight some imperfect assumptions involved in the solutions proposed for the ELD problems for systems with complicated constraints like prohibited operating zones (POZ). We also set forth new concepts and strategies and develop new techniques in this investigation to help resolve some of these incorrect propositions and ambiguities. The first chapter introduces the ELD problem in general and proceeds to discuss the effects of the transmission losses and the presence of POZs on both the scheduling of the generators and the complexity of the ELD analysis. It also provides a brief review of some relevant aspects of the state-of-the-art solution techniques and clearly spells out the motivation for the present work. The second chapter presents a generalized algorithm for solving the ELD problem efficiently. The algorithm is effectively applicable to any system comprising power generating units with any type of well-defined, smooth and monotonic cost functions, besides quadratic cost functions usually considered in conventional algorithms. The proposed method first identifies the units that are forced to operate at their generating limits for any given value of the system demand. Subsequently, it limits the ELD problem to calculating The system's incremental cost of received power and the power output of only those units operating within their normal feasible range. The specific improvement introduced here is the development of an efficient computational scheme for calculating the value of the system incremental cost accurately. In addition to quadratic and higher order polynomial cost functions, the proposed algorithm can easily be generalized to include units with smooth, monotonic, non­ polynomial cost functions. The major advantages of the proposed ELD scheme are its inherent simplicity, scalability, rapid convergence and high computational efficiency. These characteristics are particularly important for real-time online implementation. The results obtained for test cases from the literature and some new ones as well are presented to illustrate the effectiveness of the proposed scheme. The third chapter proposes an algorithm for solving the ELD problem considering power losses in the transmission network. The losses are computed using the transmission loss­ formula A coefficients method suggested by Nanda and Bijwe as an alternative to the conventional B­loss coefficients approach popularized by Kirchmayer. The proposed ELD­with­ Losses scheme builds upon the ELD scheme developed in the second chapter for the lossless case. The specific contribution of the third chapter is the computational approximation suggested for the iterative procedure involving The Newton­Raphson (NR) method with the losses considered, while still retaining the elegant solution scheme developed in the earlier chapter. The results obtained using test cases from the literature are presented to demonstrate the precision and effectiveness of the proposed technique. The fourth chapter presents a novel algorithm for efficiently solving the ELD problem for systems having generators with prohibited operating zones. The proposed ELD­ POZ scheme partitions the no convex solution space into simpler convex intervals in which the ELD scheme developed in the second chapter can be applied directly. The improvisation lies in the optimal ordering­cum­sorting strategy adopted to systematically determine the output levels of the units constrained by POZs and to adjust the output power of the remaining units appropriately. The proposed scheme also recognizes and exactly computes the multiple, equivalent optimal solutions wherever applicable–– another significant contribution of this thesis work. It also seeks to clarify and set right some unintentionally imperfect propositions and assumptions currently prevalent in the literature regarding the formulation and analysis of the ELD problem considering POZs. The results generated for a number of systems using test cases from the literature along with some new ones are presented to clearly illustrate the validity as well as the Simplicity and superiority of the proposed scheme for different types of systems. The final chapter briefly recounts the work done in this thesis work. It also presents a summary of the significant results obtained using the schemes proposed in the earlier chapters, along with the conclusions drawn in support of the validity and superiority of the proposed algorithms. More areas for further investigation and some possible avenues for future applications of the proposed techniques are also indicated.

Adaptive software becomes more and more important as computing is increasingly context-dependent. Runtime adaptability can be achieved by dynamically selecting and applying context-specific code. Role-oriented programming has been proposed as a paradigm to enable runtime adaptive software by design. Roles change the objects’ behavior at runtime and thus allow adapting the software to a given context. However, this increased variability and expressiveness has a direct impact on performance and memory consumption. We found a high overhead in the steady-state performance of executing compositions of adaptations. This paper presents a new approach to use run-time information to construct a dispatch plan that can be executed efficiently by the JVM. The concept of late binding is extended to dynamic function compositions. We evaluated the implementation with a benchmark for role-oriented programming languages leveraging context-dependent role semantics achieving a mean speedup of 2.79× over the regular implementation.

Emerging integration of renewable energy has prompted a wide range of research on the use of energy storage to compensate for the added uncertainty that accompanies these resources. In the Electric Reliability Council of Texas (ERCOT), compressed air energy storage (CAES) has drawn particular attention because Texas has suitable geology and also lacks appropriate resources and locations for pumped hydroelectric storage (PHS). While there have been studies on incorporation of renewable energy, utilization of energy storage, and dispatch optimization, this is the first body of work to integrate all these subjects along with the proven ability to recreate historical dispatch and price conditions. To quantify the operational behavior, economic feasibility, and environmental impacts of CAES, this work utilized sophisticated unit commitment and dispatch (UC&D) models that determine the least-cost dispatch for meeting a set of grid and generator constraints. This work first addressed the ability of these models to recreate historical dispatch and price conditions through a calibration analysis that incorporated major model improvements such as capacity availability and sophisticated treatment of combined heat and power (CHP) plants. These additions appreciably improved the consistency of the model results when compared to historical ERCOT conditions. An initial UC&D model was used to investigate the impacts on the dispatch of a future high wind generation scenario with the potential to utilize numerous CAES facilities. For all future natural gas prices considered, the addition of CAES led to reduced use of high marginal cost generator types, increased use of base-load generator types, and average reductions in the total operating costs of 3.7 million dollars per week. Additional analyses demonstrated the importance of allowing CAES to participate in all available energy and ancillary services (AS) markets and that a reduction in future thermal capacity would increase the use of CAES. A second UC&D model, which incorporated advanced features like variable marginal heat rates, was used to analyze the influence of future wind generation variability on the dispatch and resulting environmental impacts. This analysis revealed that higher amounts of wind variability led to an increase in the daily net load ramping requirements which resulted in less use of coal and nuclear generators in favor of faster ramping units along with reductions in emissions and water use. The changes to the net load also resulted in increased volatility of the energy and AS prices between daily minimum and maximum levels. These impacts were also found to increase with compounding intensity as higher levels of wind variability were reached. Lastly, the advanced UC&D model was also used to evaluate the operational behavior and potential economic feasibility of a first entrant conventional or adiabatic CAES system. Both storage systems were found to operate in a single mode that enabled very high utilization of their capacity indicating both systems have highly desirable characteristics. The results suggest that there is a positive case for the investment in a first entrant CAES facility in the ERCOT market. / text

Orientador: Antonio Roberto Balbo / Banca: Márcia Marcondes Altimari Samed / Banca: Edmea Cassia Baptista / Resumo: 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 / Abstract: 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 / Mestre

Submitted by Fernando Souza (fernandoafsou@gmail.com) on 2017-08-16T11:08:57Z No. of bitstreams: 1 arquivototal.pdf: 14592184 bytes, checksum: e1af48f8997b6af87f0fc91dd6d4a697 (MD5) / Made available in DSpace on 2017-08-16T11:08:57Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 14592184 bytes, checksum: e1af48f8997b6af87f0fc91dd6d4a697 (MD5) Previous issue date: 2016-08-31 / One of the most important aspects concerning the implementation of a Wireless Local Area Network (WLAN) is that in an area covered by several Access Points (APs), there must exist mechanisms to keep the user connected at any time, regardless of his/her physical location in the network and, primarily, ensure that the applications do not suffer from loss of connectivity. In this context, handoff performance, which consists of changing the AP as the station moves within the same area, is a preponderant factor when it comes to applications that are delay-sensitive. The process is usually started by the stations that once disconnected from an AP, start scanning the existing channels searching for other available APs in a smooth fashion, but in the order of seconds, which makes it difficult to use real-time applications. The challenge is to create a more efficient mechanism to manage this process, providing the required Quality of Service (QoS) for the applications. This work presents the use of mechanisms to improve the performance of the handoff process by employing an approach based on the a Software DefinedWireless Network (SDWN), which was implemented to validate the proposal. The tests performed showed a decrease in the time spent in the handoff, contributing to guarantee the QoS of the applications. / Um dos aspectos mais importantes na implantação de uma rede local sem fio Wireless Local Area Network (WLAN) é que em uma área coberta por vários Access Points (APs), devem existir mecanismos que sejam suficientes para que o usuário possa se manter conectado a qualquer hora independentemente de sua localização física dentro da rede e, principalmente, garantir que as aplicações não sofram com falhas ou perdas de conexão. Neste contexto, o desempenho do handoff, que consiste na troca de AP à medida que uma estação se move dentro de uma mesma área, é fator determinante para o uso de aplicações sensíveis ao atraso. Normalmente o processo é iniciado pelas estações, que ao se desconectarem de um AP iniciam uma varredura nos canais existentes buscando outros APs disponíveis de forma suave, porém na ordem de segundos, o que dificulta o uso de aplicações em tempo real. O desafio é criar um mecanismo mais eficiente para gerenciar este processo provendo a Qualidade de Serviço (QoS) necessária para as aplicações. Este trabalho apresenta uma solução denominada Detection and dIScovery Control in Handoff (DISpatCH) que utiliza mecanismos para melhorar o desempenho do processo de handoff utilizando uma abordagem baseada na arquitetura Software Defined Wireless Network (SDWN) os quais foram implementados para validar a proposta. Testes realizados demonstraram uma diminuição no tempo gasto no handoff contribuindo para garantir o QoS das aplicações.

It is expected that the grid of the future differs from the current system by the increased integration of distributed generation, distributed storage, demand response, power electronics, and communications and sensing technologies. The consequence is that the physical structure of the system becomes significantly more distributed. The existing centralized control structure is not suitable any more to operate such a highly distributed system. This thesis is dedicated to providing a promising solution to a class of energy management problems in power systems with a high penetration of distributed resources. This class includes optimal dispatch problems such as optimal power flow, security constrained optimal dispatch, optimal power flow control and coordinated plug-in electric vehicles charging. Our fully distributed algorithm not only handles the computational complexity of the problem, but also provides a more practical solution for these problems in the emerging smart grid environment. This distributed framework is based on iteratively solving in a distributed fashion the first order optimality conditions associated with the optimization formulations. A multi-agent viewpoint of the power system is adopted, in which at each iteration, every network agent updates a few local variables through simple computations, and exchanges information with neighboring agents. Our proposed distributed solution is based on the consensus+innovations framework, in which the consensus term enforces agreement among agents while the innovations updates ensure that local constraints are satisfied.

Autonomous electric vehicles are set to replace most conventional vehicles in the near future. Extensive research is being done to improve efficiency at the individual and fleet level. There is much potential benefit in optimizing the deployment and rebalancing of Autonomous Electric Taxi Fleets (AETF) in cities with dynamic demand and limited charging infrastructure. We propose a Fleet Management System with an Online Optimization Model to assign idle taxis to either a region or a charging station considering the current demand and charging station availability. Our system uses real-time information such as demand in regions, taxi locations and state of charge (SoC), and charging station availability to make optimal decisions in satisfying the dynamic demand considering the range-based constraints of electric taxis. We integrate our Fleet Management System with MATSim, an agent-based transport simulator, to simulate taxis serving real on-demand requests extracted from the San Francisco taxi mobility dataset. We found our system to be effective in rebalancing and ensuring efficient taxi operation by assigning them to charging stations when depleted. We evaluate this system using different performance metrics such as passenger waiting time, fleet efficiency (taxi empty driving time) and charging station utilization by varying initial SoC of taxis, frequency of optimization and charging station capacity and power.