Optimização da gestão de energia e da segurança de um edifício baseada num sistema técnico centralizado

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica Perfil Energia, Refrigeração e Climatização

Credit risk measures: a case of renewable energy companies

The Basel III will have a significant impact on the European banking sector. In September 2010, supervisors of various countries adopted the new rules proposed by the prudential Committee on Banking Supervision to be applied to the business of credit institutions (hereinafter called ICs) in a phased manner from 2013, assuming to its full implementation by 2019. The purpose of this new regulation is to limit the excessive risk that these institutions took on the period preceding the global financial crisis of 2008. This new regulation is known in slang by Basel III. Depending on the requirement of Basel II for banks and their supervisors to assess the soundness and adequacy of internal risk measurement and credit management systems, the development of methodologies for the validation of internal and external evaluation systems is clearly an important issue . More specifically, there is a need to develop tools to validate the systems used to generate the parameters (such as PD, LGD, EAD and ratings of perceived risk) that serve as starting points for the IRB approach for credit risk. In this context, the work is composed of a number of approaches and tools used to evaluate the robustness of these elements IRB systems.

Race-to-halt energy saving strategies

Energy consumption is one of the major issues for modern embedded systems. Early, power saving approaches mainly focused on dynamic power dissipation, while neglecting the static (leakage) energy consumption. However, technology improvements resulted in a case where static power dissipation increasingly dominates. Addressing this issue, hardware vendors have equipped modern processors with several sleep states. We propose a set of leakage-aware energy management approaches that reduce the energy consumption of embedded real-time systems while respecting the real-time constraints. Our algorithms are based on the race-to-halt strategy that tends to run the system at top speed with an aim to create long idle intervals, which are used to deploy a sleep state. The effectiveness of our algorithms is illustrated with an extensive set of simulations that show an improvement of up to 8% reduction in energy consumption over existing work at high utilization. The complexity of our algorithms is smaller when compared to state-of-the-art algorithms. We also eliminate assumptions made in the related work that restrict the practical application of the respective algorithms. Moreover, a novel study about the relation between the use of sleep intervals and the number of pre-emptions is also presented utilizing a large set of simulation results, where our algorithms reduce the experienced number of pre-emptions in all cases. Our results show that sleep states in general can save up to 30% of the overall number of pre-emptions when compared to the sleep-agnostic earliest-deadline-first algorithm.

Multi-agent management system for electric vehicle charging

This paper proposes an implementation, based on a multi-agent system, of a management system for automated negotiation of electricity allocation for charging electric vehicles (EVs) and simulates its performance. The widespread existence of charging infrastructures capable of autonomous operation is recognised as a major driver towards the mass adoption of EVs by mobility consumers. Eventually, conflicting requirements from both power grid and EV owners require automated middleman aggregator agents to intermediate all operations, for example, bidding and negotiation, between these parts. Multi-agent systems are designed to provide distributed, modular, coordinated and collaborative management systems; therefore, they seem suitable to address the management of such complex charging infrastructures. Our solution consists in the implementation of virtual agents to be integrated into the management software of a charging infrastructure. We start by modelling the multi-agent architecture using a federated, hierarchical layers setup and as well as the agents' behaviours and interactions. Each of these layers comprises several components, for example, data bases, decision-making and auction mechanisms. The implementation of multi-agent platform and auctions rules, and of models for battery dynamics, is also addressed. Four scenarios were predefined to assess the management system performance under real usage conditions, considering different types of profiles for EVs owners', different infrastructure configurations and usage and different loads on the utility grid (where real data from the concession holder of the Portuguese electricity transmission grid is used). Simulations carried with the four scenarios validate the performance of the modelled system while complying with all the requirements. Although all of these have been performed for one charging station alone, a multi-agent design may in the future be used for the higher level problem of distributing energy among charging stations. Copyright (c) 2014 John Wiley & Sons, Ltd.

Gestão Inteligente de uma Habitação considerando o Controlo de Cargas, de Microgeração e Veículos Elétricos em Função do seu Perfil de Utilização

Os consumidores finais são vistos, no novo paradigma da operação das redes elétricas, como intervenientes ativos com capacidade para gerir os seus recursos energéticos, nomeadamente as cargas, as unidades de produção, os veículos elétricos e a participação em eventos de Demand Response. Tem sido evidente um aumento do consumo de energia, sendo que o setor residencial representa uma importante parte do consumo global dos países desenvolvidos. Para que a participação ativa dos consumidores seja possível, várias abordagens têm vindo a ser propostas, com ênfase nas Smart Grids e nas Microgrids. Diversos sistemas têm sido propostos e desenvolvidos com o intuito de tornar a operação dos sistemas elétricos mais flexível. Neste contexto, os sistemas de gestão de instalações domésticas apresentam-se como um elemento fulcral para a participação ativa dos consumidores na gestão energética, permitindo aos operadores de sistema coordenarem a produção mas também a procura. No entanto, é importante identificar as vantagens da implementação e uso de sistemas de gestão de energia elétrica para os consumidores finais. Nesta dissertação são propostas metodologias de apoio ao consumidor doméstico na gestão dos recursos energéticos existentes e a implementação das mesmas na plataforma de simulação de um sistema de gestão de energia desenvolvido para consumidores domésticos, o SCADA House Intelligent Management (SHIM). Para tal, foi desenvolvida uma interface que permite a simulação em laboratório do sistema de gestão desenvolvido. Adicionalmente, o SHIM foi incluído no simulador Multi-Agent Smart Grid Simulation Plataform (MASGriP) permitindo a simulação de cenários considerando diferentes agentes. Ao nível das metodologias desenvolvidas são propostos diferentes algoritmos de gestão dos recursos energéticos existentes numa habitação, considerando utilizadores com diferentes tipos de recursos (cargas; cargas e veículos elétricos; cargas, veículos elétricos e microgeração). Adicionalmente é proposto um método de gestão dinâmica das cargas para eventos de Demand Response de longa duração, considerando as características técnicas dos equipamentos. Nesta dissertação são apresentados cinco casos de estudos em que cada um deles tem diferentes cenários de simulação. Estes casos de estudos são importantes para verificar a viabilidade da implementação das metodologias propostas para o SHIM. Adicionalmente são apresentados na dissertação perfis reais dos vários recursos energéticos e de consumidores domésticos que são, posteriormente, utilizados para o desenvolvimento dos casos de estudo e aplicação das metodologias.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.

Intra-Task Device Scheduling for Real-Time Embedded Systems

An ever increasing need for extra functionality in a single embedded system demands for extra Input/Output (I/O) devices, which are usually connected externally and are expensive in terms of energy consumption. To reduce their energy consumption, these devices are equipped with power saving mechanisms. While I/O device scheduling for real-time (RT) systems with such power saving features has been studied in the past, the use of energy resources by these scheduling algorithms may be improved. Technology enhancements in the semiconductor industry have allowed the hardware vendors to reduce the device transition and energy overheads. The decrease in overhead of sleep transitions has opened new opportunities to further reduce the device energy consumption. In this research effort, we propose an intra-task device scheduling algorithm for real-time systems that wakes up a device on demand and reduces its active time while ensuring system schedulability. This intra-task device scheduling algorithm is extended for devices with multiple sleep states to further minimise the overall device energy consumption of the system. The proposed algorithms have less complexity when compared to the conservative inter-task device scheduling algorithms. The system model used relaxes some of the assumptions commonly made in the state-of-the-art that restrict their practical relevance. Apart from the aforementioned advantages, the proposed algorithms are shown to demonstrate the substantial energy savings.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Review of the Nursing Home Subvention Scheme

Review of the Nursing Home Subvention Scheme The government decided in 1997 to approve proposals from the Minister for Finance for a process of expenditure reviews as a key part of the financial management systems that are central to the Strategic Management Initiative and are intended to ensure greater predictability in resource planning. The aims of the expenditure review process are as follows: Click here to download PDF 873kb

Management information systems: The balanced scorecard in Spanish public universities

Organisations are becoming increasingly aware of the need for management information systems, due largely to the changing environment and a continuous process of globalisation. All of this means that managers need to adapt the structures of their organisations to the changes and, therefore, to plan, control and manage better. The Spanish public university cannot avoid this changing (demographic, economic and social changes) and globalising (among them the convergence of European qualifications) environment, to which we must add the complex organisation structure, characterised by a high dispersion of authority for decision making in different collegiate and unipersonal organs. It seems obvious that these changes must have repercussions on the direction, organisation and management structures of those public higher education institutions, and it seems natural that, given this environment, the universities must adapt their present management systems to the demand by society for the quality and suitability of the services they provide.

Optimal management of microgrids

Desenvolupament dels models matemàtics necessaris per a controlar de forma òptima la microxarxa existent als laboratoris del Institut de Recerca en Energia de Catalunya. Els algoritmes s'implementaran per tal de simular el comportament i posteriorment es programaran directament sobre els elements de la microxarxa per verificar el seu correcte funcionament.. Desenvolupament dels models matemàtics necessaris per a controlar de forma òptima la microxarxa existent als laboratoris del Institut de Recerca en Energia de Catalunya. Els algoritmes s'implementaran per tal de simular el comportament i posteriorment es programaran directament sobre els elements de la microxarxa per verificar el seu correcte funcionament.

Soil microbial biomass under different management and tillage systems of permanent intercropped cover species in an orange orchard

To mitigate soil erosion and enhance soil fertility in orange plantations, the permanent protection of the inter-rows by cover species has been suggested. The objective of this study was to evaluate alterations in the microbial biomass, due to different soil tillage systems and intercropped cover species between rows of orange trees. The soil of the experimental area previously used as pasture (Brachiaria humidicola) was an Ultisol (Typic Paleudult) originating from Caiuá sandstone in the northwestern part of the State of Paraná, Brazil. Two soil tillage systems were evaluated: conventional tillage (CT) in the entire area and strip tillage (ST) (strip width 2 m), in combination with different ground cover management systems. The citrus cultivar 'Pera' orange (Citrus sinensis) grafted onto 'Rangpur' lime rootstock was used. Soil samples were collected after five years of treatment from a depth of 0-15 cm, under the tree canopy and in the inter-row, in the following treatments: (1) CT and an annual cover crop with the leguminous species Calopogonium mucunoides; (2) CT and a perennial cover crop with the leguminous peanut Arachis pintoi; (3) CT and an evergreen cover crop with Bahiagrass Paspalum notatum; (4) CT and a cover crop with spontaneous Brachiaria humidicola grass vegetation; and (5) ST and maintenance of the remaining grass (pasture) of Brachiaria humidicola. Soil tillage and the different cover species influenced the microbial biomass, both under the tree canopy and in the inter-row. The cultivation of brachiaria increased C and N in the microbial biomass, while bahiagrass increased P in the microbial biomass. The soil microbial biomass was enriched in N and P by the presence of ground cover species and according to the soil P content. The grass species increased C, N and P in the soil microbial biomass from the inter-row more than leguminous species.

Home Heating and Cooling, 2011

Every year, a typical family in the United States spends around half of its home energy budget on heating and cooling. In Iowa, that percentage can be higher, due to temperature extremes reached during the winter and summer months. Unfortunately, many of those dollars often are wasted, because conditioned air escapes through leaky ceilings, walls and foundations—or flows through inadequately insulated attics, exterior walls and basements. In addition, many heating systems and air conditioners aren’t properly maintained or are more than 10 years old and very inefficient, compared to models being sold today. As a result, it makes sense to analyze your home as a collection of systems that must work together in order to achieve peak energy savings. For example, you won’t get anywhere near the savings you’re expecting from a new furnace if your airhandling ducts are uninsulated and leak at every joint. The most energy-efficient central air-conditioning setup won’t perform to your expectations if your attic insulation is inadequate and can’t reduce solar heat gain to help keep your home cool. And planting the wrong types of trees or shrubs close to your home adversely can affect potential energy savings all year long.

Interoperability of learning objects copyright in the LUISA semantic learning management system

Semantic Web technology is able to provide the required computational semantics for interoperability of learning resources across different Learning Management Systems (LMS) and Learning Object Repositories (LOR). The EU research project LUISA (Learning Content Management System Using Innovative Semantic Web Services Architecture) addresses the development of a reference semantic architecture for the major challenges in the search, interchange and delivery of learning objects in a service-oriented context. One of the key issues, highlighted in this paper, is Digital Rights Management (DRM) interoperability. A Semantic Web approach to copyright management has been followed, which places a Copyright Ontology as the key component for interoperability among existing DRM systems and other licensing schemes like Creative Commons. Moreover, Semantic Web tools like reasoners, rule engines and semantic queries facilitate the implementation of an interoperable copyright management component in the LUISA architecture.