A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

Energy Resource Management under the Influence of the Weekend Transition Considering an Intensive use of Electric Vehicles

Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.

Contextual and Environmental Awareness Laboratory for Energy Consumption Management

The recent changes on power systems paradigm requires the active participation of small and medium players in energy management. With an electricity price fluctuation these players must manage the consumption. Lowering costs and ensuring adequate user comfort levels. Demand response can improve the power system management and bring benefits for the small and medium players. The work presented in this paper, which is developed aiming the smart grid context, can also be used in the current power system paradigm. The proposed system is the combination of several fields of research, namely multi-agent systems and artificial neural networks. This system is physically implemented in our laboratories and it is used daily by researchers. The physical implementation gives the system an improvement in the proof of concept, distancing itself from the conventional systems. This paper presents a case study illustrating the simulation of real-time pricing in a laboratory.

Resource Scheduling in Residential Microgrids Considering Energy Selling to External Players

The operation of distribution networks has been facing changes with the implementation of smart grids and microgrids, and the increasing use of distributed generation. The specific case of distribution networks that accommodate residential buildings, small commerce, and distributed generation as the case of storage and PV generation lead to the concept of microgrids, in the cases that the network is able to operate in islanding mode. The microgrid operator in this context is able to manage the consumption and generation resources, also including demand response programs, obtaining profits from selling electricity to the main network. The present paper proposes a methodology for the energy resource scheduling considering power flow issues and the energy buying and selling from/to the main network in each bus of the microgrid. The case study uses a real distribution network with 25 bus, residential and commercial consumers, PV generation, and storage.

Industry level foresight: designing foresight methods for Lithuanian energy sector

Enterprise and Work Innovation Studies,6,IET, pp.9-51

Projecto de um circuito conversor DC-DC para aplicações de “energy harvest”

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Development of new methodologies in sample treatment for proteomics workflow based on enzymatic probe sonication technology and mass spectrometry

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia, for the degree of Doctor of Philosophy in Biochemistry

Impacto das opções de conceção em edifícios zero energy o caso dos grandes edifícios de serviços

Atualmente, o parque edificado é responsável pelo consumo de 40% da energia total consumida em toda a União Europeia. As previsões apontam para o crescimento do sector da construção civil, nomeadamente a construção de edifícios, o que permite perspetivar um aumento do consumo de energia nesta área. Medidas importantes, como o lançamento da Diretiva 2010/31/EU do Parlamento Europeu e do Conselho de 19 de Maio de 2010 relativa ao desempenho energético dos edifícios, abrem caminho para a diminuição das necessidades energéticas e emissões de gases de efeito de estufa. Nela são apontados objetivos para aumentar a eficiência energética do parque edificado, tendo como objetivo que a partir de 2020 todos os novos edifícios sejam energeticamente eficientes e de balanço energético quase zero, com principal destaque para a compensação usando produção energética própria proveniente de fontes renováveis. Este novo requisito, denominado nearly zero energy building, apresenta-se como um novo incentivo no caminho para a sustentabilidade energética. As técnicas e tecnologias usadas na conceção dos edifícios terão um impacto positivo na análise de ciclo de vida, nomeadamente na minimização do impacto ambiental e na racionalização do consumo energético. Desta forma, pretendeu-se analisar a aplicabilidade do conceito nearly zero energy building a um grande edifício de serviços e o seu impacto em termos de ciclo de vida a 50 anos. Partindo da análise de alguns estudos sobre o consumo energético e sobre edifícios de balanço energético quase nulo já construídos em Portugal, desenvolveu-se uma análise de ciclo de vida para o caso de um edifício de serviços, da qual resultou um conjunto de propostas de otimização da sua eficiência energética e de captação de energias renováveis. As medidas apresentadas foram avaliadas com o auxílio de diferentes aplicações como DIALux, IES VE e o PVsyst, com o objetivo de verificar o seu impacto através da comparação com estado inicial de consumo energético do edifício. Nas condições iniciais, o resultado da análise de ciclo de vida do edifício a 50 anos no que respeita ao consumo energético e respetivas emissões de CO2 na fase de operação foi de 6 MWh/m2 e 1,62 t/m2, respetivamente. Com aplicação de medidas propostas de otimização, o consumo e as respetivas emissões de CO2 foram reduzidas para 5,2 MWh/m2 e 1,37 t/m2 respetivamente. Embora se tenha conseguido reduzir ao consumo com as medidas propostas de otimização de energia, chegou-se à conclusão que o sistema fotovoltaico dimensionado para fornecer energia ao edifício não consegue satisfazer as necessidades energéticas do edifício no final dos 50 anos.

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

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.

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