Real-Time Tariffs for Electric Vehicles in Wind Power based Power Systems

The use of Electric Vehicles (EVs) will change significantly the planning and management of power systems in a near future. This paper proposes a real-time tariff strategy for the charge process of the EVs. The main objective is to evaluate the influence of real-time tariffs in the EVs owners’ behaviour and also the impact in load diagram. The paper proposes the energy price variation according to the relation between wind generation and power consumption. The proposed strategy was tested in two different days in the Danish power system. January 31st and August 13th 2013 were selected because of the high quantities of wind generation. The main goal is to evaluate the changes in the EVs charging diagram with the energy price preventing wind curtailment.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.

Impacto da influência do ar novo na climatização de edifícios

Este trabalho surgiu do âmbito da Tese de Dissertação do Mestrado em Energias Sustentáveis do Instituto Superior de Engenharia do Porto, tendo o acompanhamento dos orientadores da empresa Laboratório Ecotermolab do Instituto de Soldadura e Qualidade e do Instituto Superior de Engenharia do Porto, de forma a garantir a linha traçada indo de acordo aos objectivos propostos. A presente tese abordou o estudo do impacto da influência do ar novo na climatização de edifícios, tendo como base de apoio à análise a simulação dinâmica do edifício em condições reais num programa adequado, acreditado pela norma ASHRAE 140-2004. Este trabalho pretendeu evidenciar qual o impacto da influência do ar novo na climatização de um edifício com a conjugação de vários factores, tais como, ocupação, actividades e padrões de utilização (horários), iluminação e equipamentos, estudando ainda a possibilidade do sistema funcionar em regime de “Free-Cooling”. O princípio partiu fundamentalmente por determinar até que ponto se pode climatizar recorrendo único e exclusivamente à introdução de ar novo em regime de “Free-Cooling”, através de um sistema tudo-ar de Volume de Ar Variável - VAV, sem o apoio de qualquer outro sistema de climatização auxiliar localizado no espaço, respeitando os caudais mínimos impostos pelo RSECE (Decreto-Lei 79/2006). Numa primeira fase foram identificados todos os dados relativos à determinação das cargas térmicas do edifício, tendo em conta todos os factores e contributos alusivos ao valor da carga térmica, tais como a transmissão de calor e seus constituintes, a iluminação, a ventilação, o uso de equipamentos e os níveis de ocupação. Consequentemente foram elaboradas diversas simulações dinâmicas com o recurso ao programa EnergyPlus integrado no DesignBuilder, conjugando variáveis desde as envolventes à própria arquitectura, perfis de utilização ocupacional, equipamentos e taxas de renovação de ar nos diferentes espaços do edifício em estudo. Obtiveram-se vários modelos de forma a promover um estudo comparativo e aprofundado que permitisse determinar o impacto do ar novo na climatização do edifício, perspectivando a capacidade funcional do sistema funcionar em regime de “Free-Cooling”. Deste modo, a análise e comparação dos dados obtidos permitiram chegar às seguintes conclusões: Tendo em consideração que para necessidades de arrefecimento bastante elevadas, o “Free-Cooling” diurno revelou-se pouco eficaz ou quase nulo, para o tipo de clima verificado em Portugal, pois o diferencial de temperatura existente entre o exterior e o interior não é suficiente de modo a tornar possível a remoção das cargas de forma a baixar a temperatura interior para o intervalo de conforto. Em relação ao “Free-Cooling” em horário nocturno ou pós-laboral, este revelou-se bem mais eficiente. Obtiveram-se prestações muito interessantes sobretudo durante as estações de aquecimento e meia-estação, tendo em consideração o facto de existir necessidades de arrefecimento mesmo durante a estação de aquecimento. Referente à ventilação nocturna, isto é, em períodos de madrugada e fecho do edifício, concluiu-se que tal contribui para um abaixamento do calor acumulado durante o dia nos materiais construtivos do edifício e que é libertado ou restituído posteriormente para os espaços em períodos mais tardios. De entre as seguintes variáveis, aumento de caudal de ar novo insuflado e o diferencial de temperatura existente entre o ar exterior e interior, ficou demonstrado que este último teria maior peso contributivo na remoção do calor. Por fim, é ponto assente que de um modo geral, um sistema de climatização será sempre indispensável devido a cargas internas elevadas, requisitos interiores de temperatura e humidade, sendo no entanto aconselhado o “Free- Cooling” como um opção viável a incorporar na solução de climatização, de forma a promover o arrefecimento natural, a redução do consumo energético e a introdução activa de ar novo.

A parallel programming model for ada

Over the last three decades, computer architects have been able to achieve an increase in performance for single processors by, e.g., increasing clock speed, introducing cache memories and using instruction level parallelism. However, because of power consumption and heat dissipation constraints, this trend is going to cease. In recent times, hardware engineers have instead moved to new chip architectures with multiple processor cores on a single chip. With multi-core processors, applications can complete more total work than with one core alone. To take advantage of multi-core processors, parallel programming models are proposed as promising solutions for more effectively using multi-core processors. This paper discusses some of the existent models and frameworks for parallel programming, leading to outline a draft parallel programming model for Ada.

A framework for programming sensor networks with scheduling and resource-sharing optimizations

Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

Energy and delay trade-off of the GTS allocation mechanism in IEEE 802.15.4 for wireless sensor networks

The IEEE 802.15.4 protocol proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks (LR-WPAN) including wireless sensor networks (WSNs). It presents the advantage to fit different requirements of potential applications by adequately setting its parameters. When in beaconenabled mode, the protocol can provide timeliness guarantees by using its Guaranteed Time Slot (GTS) mechanism. However, power-efficiency and timeliness guarantees are often two antagonistic requirements in wireless sensor networks. The purpose of this paper is to analyze and propose a methodology for setting the relevant parameters of IEEE 802.15.4-compliant WSNs that takes into account a proper trade-off between power-efficiency and delay bound guarantees. First, we propose two accurate models of service curves for a GTS allocation as a function of the IEEE 802.15.4 parameters, using Network Calculus formalism. We then evaluate the delay bound guaranteed by a GTS allocation and express it as a function of the duty cycle. Based on the relation between the delay requirement and the duty cycle, we propose a power-efficient superframe selection method that simultaneously reduces power consumption and enables meeting the delay requirements of real-time flows allocating GTSs. The results of this work may pave the way for a powerefficient management of the GTS mechanism in an IEEE 802.15.4 cluster.

On-line self-healing of circuits implemented on reconfigurable FPGAs

To boost logic density and reduce per unit power consumption SRAM-based FPGAs manufacturers adopted nanometric technologies. However, this technology is highly vulnerable to radiation-induced faults, which affect values stored in memory cells, and to manufacturing imperfections. Fault tolerant implementations, based on Triple Modular Redundancy (TMR) infrastructures, help to keep the correct operation of the circuit. However, TMR is not sufficient to guarantee the safe operation of a circuit. Other issues like module placement, the effects of multi- bit upsets (MBU) or fault accumulation, have also to be addressed. In case of a fault occurrence the correct operation of the affected module must be restored and/or the current state of the circuit coherently re-established. A solution that enables the autonomous restoration of the functional definition of the affected module, avoiding fault accumulation, re-establishing the correct circuit state in real-time, while keeping the normal operation of the circuit, is presented in this paper.

Estimating Effective Slowdown of Tasks in Energy-Aware Clouds

Consolidation consists in scheduling multiple virtual machines onto fewer servers in order to improve resource utilization and to reduce operational costs due to power consumption. However, virtualization technologies do not offer performance isolation, causing applications’ slowdown. In this work, we propose a performance enforcing mechanism, composed of a slowdown estimator, and a interference- and power-aware scheduling algorithm. The slowdown estimator determines, based on noisy slowdown data samples obtained from state-of-the-art slowdown meters, if tasks will complete within their deadlines, invoking the scheduling algorithm if needed. When invoked, the scheduling algorithm builds performance and power aware virtual clusters to successfully execute the tasks. We conduct simulations injecting synthetic jobs which characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our strategy can be efficiently integrated with state-of-the-art slowdown meters to fulfil contracted SLAs in real-world environments, while reducing operational costs in about 12%.

Saving energy in the GFRP pultrusion process

This study addresses to the optimization of pultrusion manufacturing process from the energy-consumption point of view. The die heating system of external platen heaters commonly used in the pultrusion machines is one of the components that contribute the most to the high consumption of energy of pultrusion process. Hence, instead of the conventional multi-planar heaters, a new internal die heating system that leads to minor heat losses is proposed. The effect of the number and relative position of the embedded heaters along the die is also analysed towards the setting up of the optimum arrangement that minimizes both the energy rate and consumption. Simulation and optimization processes were greatly supported by Finite Element Analysis (FEA) and calibrated with basis on the temperature profile computed through thermography imaging techniques. The main outputs of this study allow to conclude that the use of embedded cylindrical resistances instead of external planar heaters leads to drastic reductions of both the power consumption and the warm-up periods of the die heating system. For the analysed die tool and process, savings on energy consumption up to 60% and warm-up period stages less than an half hour were attained with the new internal heating system. The improvements achieved allow reducing the power requirements on pultrusion process, and thus minimize industrial costs and contribute to a more sustainable pultrusion manufacturing industry.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Estudo comparativo entre o sistema convencional de arrefecimento e o arrefecedor evaporativo para os edifícios industriais portugueses

Em Portugal existem muitos espaços comerciais e industriais em que as necessidades térmicas de arrefecimento são muito superiores às necessidades de aquecimento devido aos ganhos internos que advêm da existência de equipamentos e da iluminação dos edifícios, assim como, da presença das pessoas. A instalação de sistemas convencionais de ar condicionado para espaços comerciais e industriais de grande dimensão está geralmente associada ao transporte de grandes caudais de ar, e consequentemente, a elevados consumos de energia primária, e também, elevados custos de investimento, de manutenção e de operação. O arrefecedor evaporativo é uma solução de climatização com elevada eficiência energética, cujo princípio de funcionamento promove a redução do consumo de energia primária nos edifícios. A metodologia utilizada baseou-se na criação de uma ferramenta informática de simulação do funcionamento de um protótipo de um arrefecedor evaporativo. Foi efetuada a modelação matemática das variáveis dinâmicas envolvidas, dos processos de transferência de calor e de massa, assim como dos balanços de energia que ocorrem no arrefecedor evaporativo. A ferramenta informática desenvolvida permite o dimensionamento do protótipo do arrefecedor evaporativo, sendo determinadas as caraterísticas técnicas (potência térmica, caudal, eficiência energética, consumo energético e consumo e água) de acordo com o tipo de edifício e com as condições climatéricas do ar exterior. Foram selecionados três dimensionamentos de arrefecedores evaporativos, representativos de condições reais de uma gama baixa, média e elevada de caudais de ar. Os resultados obtidos nas simulações mostram que a potência de arrefecimento (5,6 kW, 16,0 kW e 32,8 kW) e o consumo de água (8 l/h, 23,9 l/h e 48,96 l/h) aumentam com o caudal de ar do arrefecedor, 5.000 m3/h, 15.000 m3/h e 30.000 m3/h, respetivamente. A eficácia de permuta destes arrefecedores evaporativos, foi de 69%, 66% e 67%, respetivamente. Verificou-se que a alteração de zona climática de V1 para V2 implicou um aumento de 39% na potência de arrefecimento e de 20% no consumo de água, e que, a alteração de zona climática de V2 para V3 implicou um aumento de 39% na potência de arrefecimento e de 39% no consumo de água. O arrefecedor evaporativo apresenta valores de consumo de energia elétrica entre 40% a 80% inferiores aos dos sistemas de arrefecimento convencionais, sendo este efeito mais intenso quando a zona climática de verão se torna mais severa.

SCADA House Intelligent Management for Energy Efficiency Analysis in Domestic Consumers

The implementation of smart homes allows the domestic consumer to be an active player in the context of the Smart Grid (SG). This paper presents an intelligent house management system that is being developed by the authors to manage, in real time, the power consumption, the micro generation system, the charge and discharge of the electric or plug-in hybrid vehicles, and the participation in Demand Response (DR) programs. The paper proposes a method for the energy efficiency analysis of a domestic consumer using the SCADA House Intelligent Management (SHIM) system. The main goal of the present paper is to demonstrate the economic benefits of the implemented method. The case study considers the consumption data of some real cases of Portuguese house consumption over 30 days of June of 2012, the Portuguese real energy price, the implementation of the power limits at different times of the day and the economic benefits analysis.

A Data Mining Framework for Electric Load Profiling

This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.