Dissertations / Theses on the topic 'SMART objectives'

The Energy Independence and Security Act of 2007 established that the current electric grid was inadequate to serve the United States needs. Congress mandated that the U.S. transition to a more intelligent grid for the future. The Department of Energy was tasked with making this goal a reality. Six years later in 2013, only marginal progress has been made. Outside of smart meter rollouts and pilots programs funded through the American Recovery and Reinvestment Act of 2009 (ARRA), many issues still need to be addressed in order to realize the U.S. Smart Grid vision. Most of the barriers to progress are not technological; the research and business community are rising to the occasion and meeting the challenge through innovation. However, policy issues present a large barrier to overcome. With issues ranging from vague Smart Grids goals issued by the Department of Energy to a general lack of consumer knowledge about the Smart Grid. This paper seeks to identify the gaps in the current electric grid and policy schema are inadequate and suggest recommendations to encourage and expedite the growth of the U.S. Smart Grid.

Many wireless sensor network (WSN) applications depend on knowing the position of nodes within the network if they are to function efficiently. Location information is used, for example, in item tracking, routing protocols and controlling node density. Configuring each node with its position manually is cumbersome, and not feasible in networks with mobile nodes or dynamic topologies. WSNs, therefore, rely on localisation algorithms for the sensor nodes to determine their own physical location. The basis of several localisation algorithms is the theory that the higher the number of reference nodes (called “references”) used, the greater the accuracy of the estimated position. However, this approach makes computation more complex and increases the likelihood that the location estimation may be inaccurate. Such inaccuracy in estimation could be due to including data from nodes with a large measurement error, or from nodes that intentionally aim to undermine the localisation process. This approach also has limited success in networks with sparse references, or where data cannot always be collected from many references (due for example to communication obstructions or bandwidth limitations). These situations require a method for achieving reliable and accurate localisation using a limited number of references. Designing a localisation algorithm that could estimate node position with high accuracy using a low number of references is not a trivial problem. As the number of references decreases, more statistical weight is attached to each reference’s location estimate. The overall localisation accuracy therefore greatly depends on the robustness of the selection method that is used to eliminate inaccurate references. Various localisation algorithms and their performance in WSNs were studied. Information-fusion theory was also investigated and a new technique, rooted in information-fusion theory, was proposed for defining the best criteria for the selection of references. The researcher chose selection criteria to identify only those references that would increase the overall localisation accuracy. Using these criteria also minimises the number of iterations needed to refine the accuracy of the estimated position. This reduces bandwidth requirements and the time required for a position estimation after any topology change (or even after initial network deployment). The resultant algorithm achieved two main goals simultaneously: accurate location discovery and information fusion. Moreover, the algorithm fulfils several secondary design objectives: self-organising nature, simplicity, robustness, localised processing and security. The proposed method was implemented and evaluated using a commercial network simulator. This evaluation of the proposed algorithm’s performance demonstrated that it is superior to other localisation algorithms evaluated; using fewer references, the algorithm performed better in terms of accuracy, robustness, security and energy efficiency. These results confirm that the proposed selection method and associated localisation algorithm allow for reliable and accurate location information to be gathered using a minimum number of references. This decreases the computational burden of gathering and analysing location data from the high number of references previously believed to be necessary.
Thesis (PhD(Eng))--University of Pretoria, 2011.
Electrical, Electronic and Computer Engineering
unrestricted

L’autonomicité - la capacité des systèmes à se gérer eux-mêmes - est une qualité nécessaire pour parvenir à contrôler des systèmes complexes, c’est à dire des systèmes ouverts, à grande échelle, dynamiques, composés de sous-systèmes tiers hétérogènes et suivant de multiples objectifs, éventuellement en conflit. Dans cette thèse, nous cherchons à fournir des supports génériques et réutilisables pour la conception de tels systèmes autonomiques complexes. Nous proposons une formalisation des objectifs de gestion, une architecture générique pour la conception de systèmes autonomiques multi-objectifs et adaptables, et des organisations génériques pour l’intégration de tels systèmes autonomiques. Nous appliquons nôtre approche au cas d’utilisation des réseaux électriques intelligents, qui sont un parfait exemple de complexité. Nous présentons une plateforme de simulation que nous avons développée et via laquelle nous illustrons nôtre approche, au travers de plusieurs scénarios de simulation
Autonomic features, i.e. the capability of systems to manage themselves, are necessary to control complex systems, i.e. systems that are open, large scale, dynamic, comprise heterogeneous third-party sub-systems and follow multiple, sometimes conflicting objectives. In this thesis, we aim to provide generic reusable supports for designing complex autonomic systems. We propose a formalisation of management objectives, a generic architecture for designingadaptable multi-objective autonomic systems, and generic organisations integrating such autonomic systems.We apply our approach to the concrete case of smart micro-grids which is a relevant example of such complexity. We present a simulation platform we developped and illustrate our approach via several simulation scenarios

Every production unit must have a clearly determined production strategy based on the given business strategy. Today’s competitive environment is very tough and demanding and that is why each producer’s success or failure is determined by the correctly chosen productive orientation, technically advanced products and provided services, range of supply and their quality and mostly price as well. What makes firms to improve and optimize their supplies continuously is just dynamic development of the society and continuously growing consumers and users’ requirements. The keen competition on one hand makes the business more demanding, but on the other hand it brings lots of new opportunities. Looking for new ways, new procedures and management methods and especially niches in the given products and services market will bring the coveted strategy advantage. This master’s thesis deals with a change of the current production strategy in a building company, individual production aspects and improving the quality of the production process functionality itself following the objective of the firm competitiveness and business performance improvement. Within the solution I count on an ability to adapt promptly to new market requirements, I suppose that the continuing differentiation strategy will contribute to building a position of a preferential supplier of the chosen narrow market segment for large building firms in the market. Improving every production process component is the prerequisite for further development of the company.

Les Smart Grids visent à transformer le réseau électrique actuel en un réseau "plus intelligent" où la production énergétique est décentralisée et automatisée, facilitant l'intégration des sources d'énergie renouvelables. Cette évolution est rendue possible grâce à l'utilisation d'un réseau de communication pour les multiples échanges de données hétérogènes des Smart Grids. L'objectif de cette thèse est de proposer un paradigme de communication efficace en termes de qualité de service pour les Smart Grids basé sur les réseaux de capteurs.Dans un premier temps, on s’intéresse au protocole standard RPL. Nous proposons une évolution de celui-ci à travers une nouvelle fonction objectif. Celle-ci tire parti de l’hétérogénéité matérielle des nœuds et des liens pour introduire la qualité de service. Cela permet à RPL de satisfaire les multiples et différentes exigences en termes de fiabilité, de latence et de priorité dans l'acheminement des données. Nos résultats montrent que notre approche permet bien la différentiation du trafic tout en réduisant la latence du routage et en économisant l'énergie.Nous proposons également d'améliorer l'utilisation du réseau de capteurs en y introduisant l’auto-organisation et la réduction des données. Le but est alors de prédire la valeur des données mesurées plutôt que de les transmettre.Une autre approche explorée est d'agréger les différents messages transitant sur le réseau tout en considérant leurs différentes exigences de qualité de service. Ces deux approches permettent ainsi de réduire la consommation d'énergie tout en respectant les exigences des différentes applications des Smart Grids
Smart Grids aim to transform the current electric grid into a "smarter" network where energy production is decentralized and automated, which facilitates the integration of renewable energy resources. This evolution is made possible thanks to the use of a communication network for the multiple heterogeneous data exchanges of the Smart Grids. Hence, the aim of this thesis is to propose an efficient communication paradigm in terms of quality of service for Smart Grids based on wireless sensor networks.First, we study data routing in Smart Grids with the RPL standard. Nevertheless, RPL is not suitable for Smart Grid applications in terms of quality of service. Therefore, we propose an objective function for RPL that takes different features of both nodes and links into consideration. Results show that our approach improves network performance compared to existing solutions in terms of packet delivery ratio, network lifetime, latency and traffic differentiation.Then, we also propose a more efficient data collection by introducing self-organization and data reduction for these wireless sensors. The goal is to predict the value of the measured data rather than transmitting them. Another explored approach is to aggregate the different messages sent across the network while considering their different requirements in terms of quality of service.These two approaches reduce the energy consumption while respecting the requirements of the different applications of the Smart Grids

The global energy demand in residential sector is increasing steadily every year due to advancement in technologies. The present electricity grid is designed to support peak demand rather than Peak to Average (PAR) demand. Utilities are investigating the residential Demand Response (DR) to lower the (PAR) ratio and eliminate the need of building new power infrastructure. This requires Home Energy Management System (HEMS) at grid edge to manage and control the energy demand. In this thesis, we presented an MDPSO based DR enabled HEMS model for optimal allocation of energy resources in a smart dwelling. The algorithm is designed to lower peak energy demand as well as encourage the active participation of customers by offering a reward to comply with DR request. We categorized appliances as elastic non-deferrable loads and inelastic deferrable loads based on their DR potential and operating characteristics. The scheduling of elastic and inelastic class of appliances is performed separately using canonical and binary version of PSO given how we expressed out load categories. We performed use case simulation to validate the performance of MDPSO for combination of different tariffs: Time of Use (TOU), TOU and Critical peak rebate signal (CPR), TOU and upper demand limit. Simulation results show that algorithm can reduce the electricity cost in range of 28% to 7% under increasing comfort conditions in response to TOU prices and Peak demand reduction of about 24% under TOU pricing and medium comfort conditions for single household. Under CPR DR requests, with respect to TOU pricing, there is effectively no change in the peak under the minimum comfort scenario. Furthermore, algorithm is able to suppress the peak upto 25% under combination of TOU and hard constraint on maximum power withdrawn from grid with no change in the electricity cost. Scheduling of multiple houses under TOU pricing results in peak reduction of 7 % as compared to baseline state. Under combination of TOU and CPR the aggregate peak energy demand of multiple households during DR activation time intervals is reduced by 32 %. The algorithm can suppress the peak demand by 27% under TOU and hard constraint on maximum power withdrawn from grid by multiple houses.

Autonomous reconnaissance missions are called for in extreme environments, as well as in potentially hazardous (e.g., the theatre, disaster-stricken areas, etc.) or inaccessible operational areas (e.g., planetary surfaces, space). Such future missions will require increasing degrees of operational autonomy, especially when following up on transient events. Operational autonomy encompasses: (1) Automatic characterization of operational areas from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and data gathering; (3) automatic feature extraction including anomaly detection and region-of-interest identification; (4) automatic target prediction and prioritization; (5) and subsequent automatic (re-) deployment and navigation of robotic agents. This paper reports on progress towards several aspects of autonomous (CISR)-I-4 systems, including: Caltech-patented and NASA award-winning multi-tiered mission paradigm, robotic platform development (air, ground, water-based), robotic behavior motifs as the building blocks for autonomous telecommanding, and autonomous decision making based on a Caltech-patented framework comprising sensor-data-fusion (feature-vectors), anomaly detection (clustering and principal component analysis), and target prioritization (hypothetical probing).

Les systèmes de cogénération (SC) sont largement définis par la production simultanée ou coïncidente de la production combinée de chaleur et d'électricité. L’idée de la cogénération revêt une importance particulière puisqu’elle est un outil de réduction des émissions à effet de serre. Comme les systèmes électriques ont été développés selon les carburants et leur utilisation énergétique, de même, les SC ont été développés afin d'utiliser l'énergie possible du carburant pour produire de l’électricité et de la chaleur. La décentralisation de la production électrique est désormais un événement existant. La favorisation maximale de l’électricité d’origine renouvelable ou des systèmes de cogénération, a abouti à cette décentralisation formant une partie de la production électrique. Cette thèse est appliquée au cas du système électrique libanais. Elle sert à évaluer la puissance optimale de cogénération qui doit être installée par le secteur public ou le secteur privé, ainsi que la mise en évidence des impacts économiques et environnementaux dus à l’intégration des SC et des énergies renouvelables dans le réseau. Dans ce travail de thèse, nous nous sommes intéressés à l’intégration des systèmes de cogénération dans un réseau électrique. Nous avons travaillé sur deux thèmes principaux et les avons appliqués au cas du réseau électrique libanais. Le premier thème principal est l’innovation d’une stratégie de prise de décision qui sert à trouver une puissance de cogénération respectant l’économie et l’environnement. Le second thème principal est l’optimisation et le contrôle du réseau électrique en fonction des énergies renouvelables (ER) et des SC intégrés. Les deux thèmes cités sont ensuite appliqués au cas du réseau électrique libanais pour montrer les avantages de l’intégration des SC et des ER dans ce réseau
Cogeneration systems (CS) are largely defined by the simultaneous or coincident production of combined heat and power. The idea of cogeneration is of particular importance since it is a tool for reducing greenhouse gases emissions. As electrical systems have been developed according to the fuel and energy use, the CS have been developed to profit from the possible potential of the fuel energy to produce electricity and heat. Decentralization of power generation is considered an important fact. The maximum use of electricity from renewable sources or cogeneration systems, has leaded to the decentralization of power generation.This thesis is applied to the Lebanese electrical system. It is used to assess the optimum cogeneration power to be installed by the public sector or the private sector, as well as highlighting the economic and environmental impacts due to the integration of the CS and renewables into the grid. In this thesis, we focused on the integration of cogeneration systems into a grid. We worked on two major themes and have applied them to the case of the Lebanese electrical grid. The first main theme is the innovation of a new decision making strategy to find the cogeneration power respecting the economy and the environment. The second main theme is the optimization and the control of the electrical grid due to the integration of renewable energy (RE) and CS. The two themes cited are then applied to the case of the Lebanese electrical grid to show the benefits of the integration of RE and CS into this grid

yes
All successful programmes share goal-setting as a standard practice, and many write their goal statements to satisfy the S.M.A.R.T. criteria. To be SMART, objective statements should be constructed to specify four components: Outcome, Indicator, Target-level and Timeframe (O.I.T.T.). This study reviewed the goal framework of published objective statements to determine the extent to which they are SMART. The statements of 17 published examples of SMART objectives found in literature of mainly four major health organisations: CDC, WHO, NHS and Save the Children, were structurally analysed to measure the completeness of their goal framework according to the OITT components. Only four examples are outcome objectives. 13 (76%) are process or task oriented. The structure of two thirds of the statements shows the similar objective-writing templates used within CDC. All objective statements have an incomplete set of OITT components. The commonest framework has 3 components of indicator, target and timeframe (75% completeness) in 12 statements. Almost all statements specify a timeframe; three-quarter of them mention a target and three-fifth an indicator, but less than 1 in 5 state an outcome. Thus, none of the objective statement is really SMART, and goal-setters are significantly less likely to specify an outcome, than indicator, target or timeframe in their objectives. A high prevalence of non-SMART objectives with low potential for goal attainment in healthcare projects is proposed.

Yes
Introduction: Goal setting is a fundamental practice in the effective management of healthcare services worldwide. This study investigated the extent to which leprosy goal formulation in Nigeria is logical and SMART. Method: Document review of baseline problems, goal statements and goal attainments for 2016 in six leprosy projects using a customised logical framework matrix. Results: A total of 15 main problems, 6 aims, 19 objectives and 42 indicators were found. The goals were problem-based and logically linked, with a pattern of a single aim per project, multiple objectives per aim, and multiple indicators per objective. Goal statements specified only impact in 5/6 aims, and only outcome and terminal timeframe in 17/19 (89.5%) objectives. Only one objective stated all four SMART components of outcome, indicator, target and timeframe. While three (7.1%) indicators and two (10.5%) objectives were measurable, no target was attainable. Discussion: Goal-setting frameworks for leprosy projects should be problem based and logical according to best practice. That most leprosy objectives were not completely SMART is similar to the reported structure of objectives published by other health organisations globally.

No
Goal-setting is indispensable for effective healthcare management. Yet, literature evidence suggests many organisations worldwide do not know how to formulate ‘SMART’ goals. Evidence of how existing theories work in practice is scarce, and the practices in low-income countries are unknown. Therefore, this research explored how leprosy project goals were formulated to describe the theoretical practice framework of A leprosy-focused organisation in Nigeria. Using a case-study design, ten managers were interviewed individually concerning their goal-setting knowledge, experience and perspective; and documented goals of six projects were reviewed. A five-step constructionist thematic data analysis generated eleven theoretical frameworks from the concepts of the emergent core themes of ‘stakeholders’, ‘strategies’ and ‘statements.’ Further theorisation reduced them to one general framework. This revealed organisational goal-setting practice as a four-stage centre-led, top-down, beneficiary-focused and problem-based process. The stages were national preparation, baseline needs-survey, centralised goal formulation and nationalised planning. The outcome was the formulation of assigned, ‘non-SMART’ objective statements, which are then used for planning projects. Other theoretical models constructed included a Goal Effects Cycle, ‘SMARTA’ goal attributes and hierarchical criteria for differentiating goal-types. A theory developed from the goal-setting practice postulates that: ‘Assigned non-SMART goal formulation directly results from centralised goal-setting practice and is the predictor of unrealistic project planning.’ Therefore, I propose that goal statements will be ‘SMARTA’ and plans, more realistic and relevant if goal-setting is done collaboratively by all stakeholders at all stages of the process. Also, ‘Change-Beneficiary-Indicator-Target-Timeframe’ and ‘Change-Beneficiary-Location-Timeframe’ frameworks are recommended as templates for writing SMART objectives and aims respectively.

Yes
Goal-setting is fundamental to organisational management, yet not every manager knows how do it well. A narrative literature review was done to explore current knowledge of definitions and classifications of goals, and principles of goal-setting in the health sector. Online databases generated 65 relevant articles. Additional literature sources were snowballed from referenced articles, and textbooks. Most academic authors define ‘goal’ synonymously as ‘aim’ or ‘objective’, but with evidence of hermeneutical confusion in general literature. Goal classifications are diverse, differing according to their contextual, structural, functional and temporal characteristics. Many authors agree that goal-setting is problem-based, change-oriented and can effectively motivate attainment, if the goal statement is formulated with a specific and challenging or SMART framework. However, recent authors report varying defining attributes for SMART, and evidence of past studies that have empirically examined the nature and efficacy of frameworks currently used for formulating goal statements for health programmes is lacking.

In the modern generation, Electric Power has become one of the fundamental needs for humans to survive. This is due to the dependence of continuous availability of power. However, for electric power to be available to the society, it has to pass through a number of complex stages. Through each stage power quality problems are experienced on the grid. Under-voltages and over-voltages are the most common electric problems experienced on the grid, causing industries and business firms losses of Billions of dollars each year. Researchers from different regions are attracted by an idea that will overcome all the electrical issues experienced in the traditional grid using Artificial Intelligence (AI). The idea is said to provide electric power that is sustainable, economical, reliable and efficient to the society based on Evolutionary Algorithms (EAs). The idea is Smart Grid. The research focused on Power Quality Optimization in Smart Grid based on improved Differential Evolution (DE), with the objective functions to minimize voltage swells, counterbalance voltage sags and eliminate voltage surges or spikes, while maximizing the power quality. During Differential Evolution improvement research, elimination of stagnation, better and fast convergence speed were achieved based on modification of DE’s mutation schemes and parameter control selection. DE/Modi/2 and DE/Modi/3 modified mutation schemes proved to be the excellent improvement for DE algorithm by achieving excellent optimization results with regards to convergence speed and elimination of stagnation during simulations. The improved DE was used to optimize Power Quality in smart grid in combination with the reconfigured and modified Dynamic Voltage Restorer (DVR). Excellent convergence results of voltage swells and voltage sags minimization were achieved based on application of multi-objective parallel operation strategy during simulations. MATLAB was used to model the proposed solution and experimental simulations.
Electrical and Mining Engineering
M. Tech. (Electrical Engineering)

碩士
國立屏東科技大學
工業管理系所
100
This study develops a novel fuzzy multi-objective linear programming (FMOLP) model with modified S-curve membership function to solve integrated multi-component, multi-supplier, and multi-time-period production planning problems for smart-phone manufacturing with fuzzy objectives. The initial multi-objective linear programming developed in this study model attempts to simultaneously minimize total costs, total holding costs and total penalty costs in relation to manufacturer/supplier capacity and warehouse space. The proposed FMOLP model provides a systematic framework that facilitates fuzzy decision-making process, enabling the decision maker to interactively adjust the search direction during the solution procedure to obtain a decision maker’s preferred satisfactory solution. To test the models adequacy, an implementation designed as several scenarios was conducted in reality with smart-phone manufacturing production system. Analytical results presented in this study can help decision managers better understand the systematic analysis and potentials for the cost-effectiveness of production planning.

碩士
國立中興大學
資訊管理學系所
100
For energy saving, considerable progress has been achieved to improve the efficiency of home appliances. Many literatures regarding peak load reducing and load shifting from peaking to off-peaking period have been explored, and numerous actual examples have been shown. However, only a few researches regarding the electricity expenditure optimization have been proposed. This study aims at an integrated research on optimization of smart home energy saving management information system. In order to achieve this objective, a multi-objective programming (MOP) with genetic algorithm and an analytic hierarchy process (AHP) approaches are utilized. There are three objectives being considered, i.e., total electricity expenditure, total appliances shift time and total appliances shift frequency, which stands for the multi-objectives of “economy”, “convenience” and “comfort” respectively. Then, we utilized AHP to obtain the weight of each goal from 107 market-survey samples of the household sector in Taiwan, with 92 valid responses. After the weights are obtained, we employees MOP with genetic algorithm to search for the final results. This study applies relevant data from related literature and a typical real-time pricing electric rate of a USA power company to undertake the empirical analysis. The results show that this MOP with genetic algorithm enables decision maker to do better energy management on electricity expense under an acceptable level of “convenience” and “comfort”, i.e., while one saves about 9% of the total household electricity monthly bill. The research results derived from this study could reach the goal of optimal electricity bill management in the household sector without significant change of comfortable and convenient lifestyle of consumers. Therefore, it could create ”win-win-win” situation among the consumers, power company and the whole society.