Avaliação da comunicação da sustentabilidade de energy utilities e análise dos principais rankings de sustentabilidade

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente Perfil de Gestão e Sistemas Ambientais

Electricity markets modeling considering complex contracts and aggregators

All over the world, the liberalization of electricity markets, which follows different paradigms, has created new challenges for those involved in this sector. In order to respond to these challenges, electric power systems suffered a significant restructuring in its mode of operation and planning. This restructuring resulted in a considerable increase of the electric sector competitiveness. Particularly, the Ancillary Services (AS) market has been target of constant renovations in its operation mode as it is a targeted market for the trading of services, which have as main objective to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. In this way, with the increasing penetration of distributed energy resources including distributed generation, demand response, storage units and electric vehicles, it is essential to develop new smarter and hierarchical methods of operation of electric power systems. As these resources are mostly connected to the distribution network, it is important to consider the introduction of this kind of resources in AS delivery in order to achieve greater reliability and cost efficiency of electrical power systems operation. The main contribution of this work is the design and development of mechanisms and methodologies of AS market and for energy and AS joint market, considering different management entities of transmission and distribution networks. Several models developed in this work consider the most common AS in the liberalized market environment: Regulation Down; Regulation Up; Spinning Reserve and Non-Spinning Reserve. The presented models consider different rules and ways of operation, such as the division of market by network areas, which allows the congestion management of interconnections between areas; or the ancillary service cascading process, which allows the replacement of AS of superior quality by lower quality of AS, ensuring a better economic performance of the market. A major contribution of this work is the development an innovative methodology of market clearing process to be used in the energy and AS joint market, able to ensure viable and feasible solutions in markets, where there are technical constraints in the transmission network involving its division into areas or regions. The proposed method is based on the determination of Bialek topological factors and considers the contribution of the dispatch for all services of increase of generation (energy, Regulation Up, Spinning and Non-Spinning reserves) in network congestion. The use of Bialek factors in each iteration of the proposed methodology allows limiting the bids in the market while ensuring that the solution is feasible in any context of system operation. Another important contribution of this work is the model of the contribution of distributed energy resources in the ancillary services. In this way, a Virtual Power Player (VPP) is considered in order to aggregate, manage and interact with distributed energy resources. The VPP manages all the agents aggregated, being able to supply AS to the system operator, with the main purpose of participation in electricity market. In order to ensure their participation in the AS, the VPP should have a set of contracts with the agents that include a set of diversified and adapted rules to each kind of distributed resource. All methodologies developed and implemented in this work have been integrated into the MASCEM simulator, which is a simulator based on a multi-agent system that allows to study complex operation of electricity markets. In this way, the developed methodologies allow the simulator to cover more operation contexts of the present and future of the electricity market. In this way, this dissertation offers a huge contribution to the AS market simulation, based on models and mechanisms currently used in several real markets, as well as the introduction of innovative methodologies of market clearing process on the energy and AS joint market. This dissertation presents five case studies; each one consists of multiple scenarios. The first case study illustrates the application of AS market simulation considering several bids of market players. The energy and ancillary services joint market simulation is exposed in the second case study. In the third case study it is developed a comparison between the simulation of the joint market methodology, in which the player bids to the ancillary services is considered by network areas and a reference methodology. The fourth case study presents the simulation of joint market methodology based on Bialek topological distribution factors applied to transmission network with 7 buses managed by a TSO. The last case study presents a joint market model simulation which considers the aggregation of small players to a VPP, as well as complex contracts related to these entities. The case study comprises a distribution network with 33 buses managed by VPP, which comprises several kinds of distributed resources, such as photovoltaic, CHP, fuel cells, wind turbines, biomass, small hydro, municipal solid waste, demand response, and storage units.

TEA: Timing and Energy Aware compression architecture for Efficient Configuration in CGRAs

Coarse Grained Reconfigurable Architectures (CGRAs) are emerging as enabling platforms to meet the high performance demanded by modern applications (e.g. 4G, CDMA, etc.). Recently proposed CGRAs offer time-multiplexing and dynamic applications parallelism to enhance device utilization and reduce energy consumption at the cost of additional memory (up to 50% area of the overall platform). To reduce the memory overheads, novel CGRAs employ either statistical compression, intermediate compact representation, or multicasting. Each compaction technique has different properties (i.e. compression ratio, decompression time and decompression energy) and is best suited for a particular class of applications. However, existing research only deals with these methods separately. Moreover, they only analyze the compaction ratio and do not evaluate the associated energy overheads. To tackle these issues, we propose a polymorphic compression architecture that interleaves these techniques in a unique platform. The proposed architecture allows each application to take advantage of a separate compression/decompression hierarchy (consisting of various types and implementations of hardware/software decoders) tailored to its needs. Simulation results, using different applications (FFT, Matrix multiplication, and WLAN), reveal that the choice of compression hierarchy has a significant impact on compression ratio (up to 52%), decompression energy (up to 4 orders of magnitude), and configuration time (from 33 n to 1.5 s) for the tested applications. Synthesis results reveal that introducing adaptivity incurs negligible additional overheads (1%) compared to the overall platform area.

Desempenho energético de edifícios residenciais no contexto da regulamentação térmica com recurso ao Energy Plus e TRNSYS

Dissertação para obtenção do Grau de Mestre em Engenharia Civil

Energy analysis of Multi-legged Locomotion Systems

4th International Conference on Climbing and Walking Robots - From Biology to Industrial Applications

Co-Authorship of scientists in the energy field: an exploratory study of the ETDE World Energy Database (ETDEWEB) using Social Network Analysis

Paper presented at the 5th European Conference Economics and Management of Energy in Industry, Vilamoura, Algarve. Apr. 14-17, 2009, 11p. URL: http:// www.cenertec.pt/ecemei/

Energy Harvesting for Autonomous Underwater Vehicles

In this study, energy production for autonomous underwater vehicles is investigated. This project is part of a bigger project called TURTLE. The autonomous vehicles perform oceanic researches at seabed for which they are intended to be kept operational underwater for several months. In order to ful l a long-term underwater condition, powerful batteries are combined with \micro- scale" energy production on the spot. This work tends to develop a system that generates power up to a maximum of 30 W. Latter energy harvesting structure consists basically of a turbine combined with a generator and low-power electronics to adjust the achieved voltage to a required battery charger voltage. Every component is examined separately hence an optimum can be de ned for all, and subsequently also an overall optimum. Di erent design parameters as e.g. number of blades, solidity ratio and cross-section area are compared for di erent turbines, in order to see what is the most feasible type. Further, a generator is chosen by studying how ux distributions might be adjusted to low velocities, and how cogging torque can be excluded by adapted designs. Low-power electronics are con gured in order to convert and stabilize heavily varying three-phase voltages to a constant, recti ed voltage which is usable for battery storage. Clearly, di erent component parameters as maximum power and torque are matched here to increase the overall power generation. Furthermore an overall maximum power is set up for achieving a maximum power ow at load side. Due to among others typical low velocities of about 0.1 to 0.5 m/s, and constructing limits of the prototype, the vast range of components is restricted to only a few that could be used. Hence, a helical turbine is combined in a direct drive mode to a coreless-stator axial- ux permanent-magnet generator, from which the output voltage is adjusted subsequently by a recti er, impedance matching unit, upconverter circuit and an overall control unit to regulate di erent component parameters. All these electronics are combined in a closed-loop design to involve positive feedback signals. Furthermore a theoretical con guration for the TURTLE vehicle is described in this work and a solution is proposed that might be implemented, for which several design tests are performable in a future study.

Energy-aware Task Allocation onto Unrelated Heterogeneous Multicore Platform for Mixed Criticality Systems

Presented at Work in Progress Session, IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

Environmental impact assessment of energy crops cultivation in the Mediterranean Europe

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa Para a obtenção do Grau de Mestre em Energia e Bioenergia

Co-Authorship of scientists in the energy field: a study of the ETDE World Energy Database (ETDEWEB) using social network analysis

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Gestão de Informação

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

A aplicação de redes neuronais na deteção da influência do High Frequency Trading na negociação de ações (caso português)

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão da Informação

Energy-efficient MAC protocols for WBANs: Opportunities and challenges

Wireless body area networks (WBANs) are expected to play a significant role in smart healthcare systems. One of the most important attributes of WBANs is to increase network lifetime by introducing novel and low-power techniques on the energy-constrained sensor nodes. Medium access control (MAC) protocols play a significant role in determining the energy consumption in WBANs. Existing MAC protocols are unable to accommodate communication requirements in WBANs. There is a need to develop novel, scalable and reliable MAC protocols that must be able to address all these requirements in a reliable manner. In this special issue, we attracted high quality research and review papers on the recent advances in MAC protocols for WBANs.