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.

Dynamic programming for a Markov-switching jump–diffusion

We consider an optimal control problem with a deterministic finite horizon and state variable dynamics given by a Markov-switching jump–diffusion stochastic differential equation. Our main results extend the dynamic programming technique to this larger family of stochastic optimal control problems. More specifically, we provide a detailed proof of Bellman’s optimality principle (or dynamic programming principle) and obtain the corresponding Hamilton–Jacobi–Belman equation, which turns out to be a partial integro-differential equation due to the extra terms arising from the Lévy process and the Markov process. As an application of our results, we study a finite horizon consumption– investment problem for a jump–diffusion financial market consisting of one risk-free asset and one risky asset whose coefficients are assumed to depend on the state of a continuous time finite state Markov process. We provide a detailed study of the optimal strategies for this problem, for the economically relevant families of power utilities and logarithmic utilities.

Dynamic cluster scheduling for cluster-tree WSNs

While Cluster-Tree network topologies look promising for WSN applications with timeliness and energy-efficiency requirements, we are yet to witness its adoption in commercial and academic solutions. One of the arguments that hinder the use of these topologies concerns the lack of flexibility in adapting to changes in the network, such as in traffic flows. This paper presents a solution to enable these networks with the ability to self-adapt their clusters’ duty-cycle and scheduling, to provide increased quality of service to multiple traffic flows. Importantly, our approach enables a network to change its cluster scheduling without requiring long inaccessibility times or the re-association of the nodes. We show how to apply our methodology to the case of IEEE 802.15.4/ZigBee cluster-tree WSNs without significant changes to the protocol. Finally, we analyze and demonstrate the validity of our methodology through a comprehensive simulation and experimental validation using commercially available technology on a Structural Health Monitoring application scenario.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Fractional order modelling of dynamic backlash

This paper studies the dynamical properties of systems with backlash and impact phenomena. This type of non-linearity can be tackled in the perspective of the fractional calculus theory. Fractional and integer order models are compared and their influence upon the emerging dynamics is analysed. It is demonstrated that fractional models can memorize dynamical effects due to multiple micro-collisions.

Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

Impact of compliance with different guidelines on physical activity during pregnancy and perceived barriers to leisure physical activity

The aims of the this prospective study were to analyze physical activity (PA) engagement during the first and second trimesters, considering the different guidelines published on PA, to document the individual characteristics associated with the accomplishment of these guidelines and to examine pregnant women’s perceived barriers to leisure PA, using a socioecological framework. A sample of 133 pregnant women in two stages – at 10–12 weeks’ gestation (T1) and 20– 22 weeks’ gestation (T2) – were evaluated. PA was assessed by accelerometry during the T1 and T2 evaluation stages. Socio-demographic characteristics, lifestyle factors and barriers to leisure PA were assessed via questionnaire. A large proportion of women (ranging from 32% to 96%) did not reach the levels of PA recommended by the guidelines. There were no significant differences between T1 and T2 with regard to compliance with PA recommendations. A decrease in PA levels from T1 to T2 was noted for all recommendations. No associations were found between participants’ characteristics and adherence to the recommendations in T1 and T2. No significant differences were found in barriers to leisure PA between T1 and T2. The most commonly reported barriers to leisure PA were intrapersonal, not health related. Our results indicate that there were no differences between trimesters regarding compliance of PA recommendations, and perceived barriers were similar in both trimesters.

Selection Constructive based Hyper-heuristic for Dynamic Scheduling

A função de escalonamento desempenha um papel importante nos sistemas de produção. Os sistemas de escalonamento têm como objetivo gerar um plano de escalonamento que permite gerir de uma forma eficiente um conjunto de tarefas que necessitam de ser executadas no mesmo período de tempo pelos mesmos recursos. Contudo, adaptação dinâmica e otimização é uma necessidade crítica em sistemas de escalonamento, uma vez que as organizações de produção têm uma natureza dinâmica. Nestas organizações ocorrem distúrbios nas condições requisitos de trabalho regularmente e de forma inesperada. Alguns exemplos destes distúrbios são: surgimento de uma nova tarefa, cancelamento de uma tarefa, alteração na data de entrega, entre outros. Estes eventos dinâmicos devem ser tidos em conta, uma vez que podem influenciar o plano criado, tornando-o ineficiente. Portanto, ambientes de produção necessitam de resposta imediata para estes eventos, usando um método de reescalonamento em tempo real, para minimizar o efeito destes eventos dinâmicos no sistema de produção. Deste modo, os sistemas de escalonamento devem de uma forma automática e inteligente, ser capazes de adaptar o plano de escalonamento que a organização está a seguir aos eventos inesperados em tempo real. Esta dissertação aborda o problema de incorporar novas tarefas num plano de escalonamento já existente. Deste modo, é proposta uma abordagem de otimização – Hiper-heurística baseada em Seleção Construtiva para Escalonamento Dinâmico- para lidar com eventos dinâmicos que podem ocorrer num ambiente de produção, a fim de manter o plano de escalonamento, o mais robusto possível. Esta abordagem é inspirada em computação evolutiva e hiper-heurísticas. Do estudo computacional realizado foi possível concluir que o uso da hiper-heurística de seleção construtiva pode ser vantajoso na resolução de problemas de otimização de adaptação dinâmica.

Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid Network

IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Impacto das medidas de conservação de energia em projeto na redução da intensidade de utilização de matérias-primas na construção de um edifício

O presente trabalho pretende mostrar que a aplicação de medidas de conservação de energia (MCE) pode representar uma redução da intensidade de utilização de matérias-primas na construção de um edifício. Mais concretamente, pode representar uma redução da utilização de materiais e equipamentos, e como consequência, uma redução no esforço económico ao primeiro investimento. Podendo posteriormente representar uma redução na utilização de energia durante o período de funcionamento do edifício. A aplicação de MCE no sector da construção tem vindo a ser uma prática corrente nos novos edifícios e edifícios sujeitos a grandes intervenções de reabilitação. Esta prática deve-se à obrigatoriedade de cumprimento de requisitos regulamentares aplicados à otimização do desempenho energético dos edifícios e dos seus sistemas técnicos, nomeadamente, o RCCTE e o RSECE, entretanto revogados pelo REH e pelo RECS, respetivamente. A implementação de MCE apresenta, na maioria dos casos, benefícios económicos para o promotor do edifício, uma vez que se traduz muitas vezes, na otimização do dimensionamento dos sistemas de Aquecimento, Ventilação e Ar Condicionado (AVAC). Esta otimização permite reduzir os custos associados ao primeiro investimento, bem como na utilização de energia por parte do utilizador, logo na redução dos custos de exploração. No entanto, a falta de quantificação dos impactos do dimensionamento dos sistemas AVAC, da redução de utilização de energia e da análise do custo-benefício da sua aplicação pode condicionar o interesse na sua implementação. Neste contexto, surge a presente dissertação, por iniciativa do Instituto Soldadura e Qualidade (ISQ), aplicado a um caso prático de um edifício já construído e propriedade daquela empresa. Com este trabalho pretende-se avaliar o contributo efetivo das MCE implementadas na fase de projeto e na fase de construção, quer na otimização da dimensão de sistemas e equipamentos AVAC, por via da redução das necessidades energéticas, quer na redução de utilização de energia, permitindo, de seguida, uma avaliação custo-benefício.Na base do caso de estudo está o ECOTERMOLAB, o edifício acima referido, adquirido pelo ISQ para instalação de um laboratório de formação, investigação e desenvolvimento na área da energia. Após aquisição pelo ISQ, o edifício sofreu várias alterações/beneficiações, entre as quais a implementação de MCE, tais como, a aplicação de isolamento térmico na envolvente opaca (paredes, pavimentos e coberturas), duplicação dos vãos envidraçados simples, conferindo-lhes melhores caraterísticas térmicas, e pela aplicação de proteções solar. Foram ainda adotadas MCE aos sistemas AVAC, designadamente, pela adoção de recuperadores de calor nas Unidades de Tratamento de Ar Novo (UTAN’s) e de variadores de velocidade nas bombas de circulação de água e nos ventiladores de ar das UTAN’s. Pretendia o ISQ concluir se a aplicação de todas as MCE contribuiu de forma efetiva para o dimensionamento de sistemas e equipamentos AVAC de menor capacidade e, consequentemente, numa redução de utilização de energia. Em sequência, pretendia avaliar a viabilidade económica da aplicação de todas as MCE, estimando o sobrecusto inicial e o tempo necessário para o retorno financeiro daquele investimento. Para alcançar os objetivos propostos, procedeu-se à simulação energética dinâmica do ECOTERMOLAB, utilizando o programa EnergyPlus. Primeiro foi simulada uma situação base do edifício, sem quaisquer MCE. Posteriormente foi caraterizada cada uma das situações de aplicação das MCE, com o objetivo de avaliar o respetivo impacto individual na utilização de energia pelos sistemas AVAC. Por último foram assumidas todas as soluções em conjunto para avaliar o impacto final de todas as MCE na utilização de energia dos sistemas AVAC, bem como no seu dimensionamento. Das simulações dinâmicas foram obtidos os valores das necessidades de aquecimento e arrefecimento, de energia utilizada pelos sistemas AVAC e de caudais de água aquecida e arrefecida circulada. Com estes valores foi feita uma estimativa de dimensionamento dos equipamentos e componentes AVAC para as situações da aplicação de todas as MCE no ECOTERMOLAB e a sua ausência. A partir da diferença dos custos de aquisição dos respetivos equipamentos e dos valores de poupança em energia foi realizado o estudo da viabilidade económica da implementação das MCE neste edifício. Este estudo permitiu concluir que a aplicação das MCE no ECOTERMOLAB levou à redução da dimensão na generalidade dos equipamentos e componentes AVAC. Permitiu, ainda, concluir que houve uma diminuição de utilização de energia por parte destes sistemas e equipamentos para o aquecimento e arrefecimento. Conclui-se ainda que o período de retorno (Payback) do sobrecusto inicial, estimado em 37.822€ é de, aproximadamente, onze anos e meio, para um valor atual líquido (VAL) de 8.061€ e à taxa interna de rentabilidade (TIR) de 7,03%.

Embedded Multi-Core systems for Mixed Criticality applications in dynamic and changeable real-time environments

EMC2 finds solutions for dynamic adaptability in open systems. It provides handling of mixed criticality multicore applications in r eal-time conditions, withscalability and utmost flexibility, full-scale deployment and management of integrated tool chains, through the entire lifecycle.

Asymmetric dynamic price competition with uncertainty

We consider a dynamic setting-price duopoly model in which a dominant (leader) firm moves first and a subordinate (follower) firm moves second. We suppose that each firm has two different technologies, and uses one of them according to a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We analyse the effect of the production costs uncertainty on the profits of the firms, for different values of the intercept demand parameters.

Dynamic stability metrics for the container loading problem

The Container Loading Problem (CLP) literature has traditionally evaluated the dynamic stability of cargo by applying two metrics to box arrangements: the mean number of boxes supporting the items excluding those placed directly on the floor (M1) and the percentage of boxes with insufficient lateral support (M2). However, these metrics, that aim to be proxies for cargo stability during transportation, fail to translate real-world cargo conditions of dynamic stability. In this paper two new performance indicators are proposed to evaluate the dynamic stability of cargo arrangements: the number of fallen boxes (NFB) and the number of boxes within the Damage Boundary Curve fragility test (NB_DBC). Using 1500 solutions for well-known problem instances found in the literature, these new performance indicators are evaluated using a physics simulation tool (StableCargo), replacing the real-world transportation by a truck with a simulation of the dynamic behaviour of container loading arrangements. Two new dynamic stability metrics that can be integrated within any container loading algorithm are also proposed. The metrics are analytical models of the proposed stability performance indicators, computed by multiple linear regression. Pearson’s r correlation coefficient was used as an evaluation parameter for the performance of the models. The extensive computational results show that the proposed metrics are better proxies for dynamic stability in the CLP than the previous widely used metrics.