Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

The predominance of M2-polarized macrophages in the stroma of low-hypoxic bladder tumors is associated with BCG immunotherapy failure

OBJECTIVE: Bacillus Calmette-Guérin (BCG) immunotherapy is the gold standard treatment for superficial bladder tumors with intermediate/high risk of recurrence or progression. However, approximately 30% of patients fail to respond to the treatment. Effective BCG therapy needs precise activation of the type 1 helper cells immune pathway. Tumor-associated macrophages (TAMs) often assume an immunoregulatory M2 phenotype and may directly interfere with the BCG-induced antitumor immune response. Thus, we aim to clarify the influence of TAMs, in particular of the M2 phenotype in stroma and tumor areas, in BCG treatment outcome. PATIENTS AND METHODS: The study included 99 patients with bladder cancer treated with BCG. Tumors resected before treatment were evaluated using immunohistochemistry for CD68 and CD163 antigens, which identify a lineage macrophage marker and a M2-polarized specific cell surface receptor, respectively. CD68+ and CD163+ macrophages were evaluated within the stroma and tumor areas, and high density of infiltrating cells spots were selected for counting. Hypoxia, an event known to modulate macrophage phenotype, was also assessed through hypoxia induced factor (HIF)-1α expression. RESULTS: Patients in whom BCG failed had high stroma-predominant CD163+ macrophage counts (high stroma but low tumor CD163+ macrophages counts) when compared with the ones with a successful treatment (71% vs. 47%, P = 0.017). Furthermore, patients presenting this phenotype showed decreased recurrence-free survival (log rank, P = 0.008) and a clear 2-fold increased risk of BCG treatment failure was observed in univariate analysis (hazard ratio = 2.343; 95% CI: 1.197-4.587; P = 0.013). Even when adjusted for potential confounders, such as age and therapeutic scheme, multivariate analysis revealed 2.6-fold increased risk of recurrence (hazard ratio = 2.627; 95% CI: 1.340-5.150; P = 0.005). High stroma-predominant CD163+ macrophage counts were also associated with low expression of HIF-1α in tumor areas, whereas high counts of CD163+ in the tumor presented high expression of HIF-1α in tumor nests. CONCLUSIONS: TAMs evaluation using CD163 is a good indicator of BCG treatment failure. Moreover, elevated infiltration of CD163+ macrophages, predominantly in stroma areas but not in the tumor, may be a useful indicator of BCG treatment outcome, possibly owing to its immunosuppressive phenotype.

Efficacy of low-level laser therapy on scar tissue

Background: Physiotherapy has a very important role in the maintenance of the integumentary system integrity. There is very few evidence in humans. Nevertheless, there are some studies about tissue regeneration using low-level laser therapy (LLLT). Aim: To analyze the effectiveness of LLLT on scar tissue. Methods: Seventeen volunteers were stratified by age of their scars, and then randomly assigned to an experimental group (EG) — n = 9 – and a placebo group (PG) – n = 8. Fifteen sessions were conducted to both the groups thrice a week. However, in the PG, the laser device was switched off. Scars’ thickness, length, width, macroscopic aspect, pain threshold, pain perception, and itching were measured. Results: After 5 weeks, there were no statistically significant differences in any variable between both the groups. However, analyzing independently each group, EG showed a significant improvement in macroscopic aspect (p = 0.003) using LLLT. Taking into account the scars’ age, LLLT showed a tendency to decrease older scars’ thickness in EG. Conclusion: The intervention with LLLT appears to have a positive effect on the macroscopic scars’ appearance, and on old scars’ thickness, in the studied sample. However, it cannot be said for sure that LLLT has influence on scar tissue.

Sistema pericial para suporte à decisão na alocação de recursos de emergência

O panorama atual da emergência e socorro de primeira linha em Portugal, carateriza-se por uma grande aposta ao longo dos últimos anos num incremento contínuo da qualidade e da eficiência que estes serviços prestam às populações locais. Com vista à prossecução do objetivo de melhoria contínua dos serviços, foram realizados ao longo dos últimos anos investimentos avultados ao nível dos recursos técnicos e ao nível da contratação e formação de recursos humanos altamente qualificados. Atualmente as instituições que prestam socorro e emergência de primeira linha estão bem dotadas ao nível físico e ao nível humano dos recursos necessários para fazerem face aos mais diversos tipos de ocorrências. Contudo, ao nível dos sistemas de informação de apoio à emergência e socorro de primeira linha, verifica-se uma inadequação (e por vezes inexistência) de sistemas informáticos capazes de suportar convenientemente o atual contexto de exigência e complexidade da emergência e socorro. Foi feita ao longo dos últimos anos, uma forte aposta na melhoria dos recursos físicos e dos recursos humanos encarregues da resposta àsemergência de primeira linha, mas descurou-se a área da gestão e análise da informação sobre as ocorrências, assim como, o delinear de possíveis estratégias de prevenção que uma análise sistematizada da informação sobre as ocorrências possibilita. Nas instituições de emergência e socorro de primeira linha em Portugal (bombeiros, proteção civil municipal, PSP, GNR, polícia municipal), prevalecem ainda hoje os sistemas informáticos apenas para o registo das ocorrências à posteriori e a total inexistência de sistemas de registo de informação e de apoio à decisão na alocação de recursos que operem em tempo real. A generalidade dos sistemas informáticos atualmente existentes nas instituições são unicamente de sistemas de backoffice, que não aproveitam a todas as potencialidades da informação operacional neles armazenada. Verificou-se também, que a geo-localização por via informática dos recursos físicos e de pontos de interesse relevantes em situações críticas é inexistente a este nível. Neste contexto, consideramos ser possível e importante alinhar o nível dos sistemas informáticos das instituições encarregues da emergência e socorro de primeira linha, com o nível dos recursos físicos e humanos que já dispõem atualmente. Dado que a emergência e socorro de primeira linha é um domínio claramente elegível para a aplicação de tecnologias provenientes dos domínios da inteligência artificial (nomeadamente sistemas periciais para apoio à decisão) e da geo-localização, decidimos no âmbito desta tese desenvolver um sistema informático capaz de colmatar muitas das lacunas por nós identificadas ao nível dos sistemas informáticos destas instituições. Pretendemos colocar as suas plataformas informáticas num nível similar ao dos seus recursos físicos e humanos. Assim, foram por nós identificadas duas áreas chave onde a implementação de sistemas informáticos adequados às reais necessidades das instituições podem ter um impacto muito proporcionar uma melhor gestão e otimização dos recursos físicos e humanos. As duas áreas chave por nós identificadas são o suporte à decisão na alocação dos recursos físicos e a geolocalização dos recursos físicos, das ocorrências e dos pontos de interesse. Procurando fornecer uma resposta válida e adequada a estas duas necessidades prementes, foi desenvolvido no âmbito desta tese o sistema CRITICAL DECISIONS. O sistema CRITICAL DECISIONS incorpora um conjunto de funcionalidades típicas de um sistema pericial, para o apoio na decisão de alocação de recursos físicos às ocorrências. A inferência automática dos recursos físicos, assenta num conjunto de regra de inferência armazenadas numa base de conhecimento, em constante crescimento e atualização, com base nas respostas bem sucedidas a ocorrências passadas. Para suprimir as carências aos nível da geo-localização dos recursos físicos, das ocorrências e dos pontos de interesse, o sistema CRITICAL DECISIONS incorpora também um conjunto de funcionalidades de geo-localização. Estas permitem a geo-localização de todos os recursos físicos da instituição, a geo-localização dos locais e as áreas das várias ocorrências, assim como, dos vários tipos de pontos de interesse. O sistema CRITICAL DECISIONS visa ainda suprimir um conjunto de outras carências por nós identificadas, ao nível da gestão documental (planos de emergência, plantas dos edifícios) , da comunicação, da partilha de informação entre as instituições de socorro e emergência locais, da contabilização dos tempos de serviço, entre outros. O sistema CRITICAL DECISIONS é o culminar de um esforço colaborativo e contínuo com várias instituições, responsáveis pela emergência e socorro de primeira linha a nível local. Esperamos com o sistema CRITICAL DECISIONS, dotar estas instituições de uma plataforma informática atual, inovadora, evolutiva, com baixos custos de implementação e de operação, capaz de proporcionar melhorias contínuas e significativas ao nível da qualidade da resposta às ocorrências, das capacidades de prevenção e de uma melhor otimização de todos os tipos de recursos que têm ao dispor.

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

RadiaLE: A framework for designing and assessing link quality estimators in wireless sensor networks

Stringent cost and energy constraints impose the use of low-cost and low-power radio transceivers in large-scale wireless sensor networks (WSNs). This fact, together with the harsh characteristics of the physical environment, requires a rigorous WSN design. Mechanisms for WSN deployment and topology control, MAC and routing, resource and mobility management, greatly depend on reliable link quality estimators (LQEs). This paper describes the RadiaLE framework, which enables the experimental assessment, design and optimization of LQEs. RadiaLE comprises (i) the hardware components of the WSN testbed and (ii) a software tool for setting-up and controlling the experiments, automating link measurements gathering through packets-statistics collection, and analyzing the collected data, allowing for LQEs evaluation. We also propose a methodology that allows (i) to properly set different types of links and different types of traffic, (ii) to collect rich link measurements, and (iii) to validate LQEs using a holistic and unified approach. To demonstrate the validity and usefulness of RadiaLE, we present two case studies: the characterization of low-power links and a comparison between six representative LQEs. We also extend the second study for evaluating the accuracy of the TOSSIM 2 channel model.

RiSeG: a ring based secure group communication protocol for resource-constrained wireless sensor networks

Securing group communication in wireless sensor networks has recently been extensively investigated. Many works have addressed this issue, and they have considered the grouping concept differently. In this paper, we consider a group as being a set of nodes sensing the same data type, and we alternatively propose an efficient secure group communication scheme guaranteeing secure group management and secure group key distribution. The proposed scheme (RiSeG) is based on a logical ring architecture, which permits to alleviate the group controller’s task in updating the group key. The proposed scheme also provides backward and forward secrecy, addresses the node compromise attack, and gives a solution to detect and eliminate the compromised nodes. The security analysis and performance evaluation show that the proposed scheme is secure, highly efficient, and lightweight. A comparison with the logical key hierarchy is preformed to prove the rekeying process efficiency of RiSeG. Finally, we present the implementation details of RiSeG on top of TelosB sensor nodes to demonstrate its feasibility.

The generalized multiprocessor periodic resource interface model for hierarchical multiprocessor scheduling

Composition is a practice of key importance in software engineering. When real-time applications are composed it is necessary that their timing properties (such as meeting the deadlines) are guaranteed. The composition is performed by establishing an interface between the application and the physical platform. Such an interface does typically contain information about the amount of computing capacity needed by the application. In multiprocessor platforms, the interface should also present information about the degree of parallelism. Recently there have been quite a few interface proposals. However, they are either too complex to be handled or too pessimistic.In this paper we propose the Generalized Multiprocessor Periodic Resource model (GMPR) that is strictly superior to the MPR model without requiring a too detailed description. We describe a method to generate the interface from the application specification. All these methods have been implemented in Matlab routines that are publicly available.

Real-time scheduling with resource sharing on uniform multiprocessors

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a uniform multiprocessor platform where each task may access at most one of |R| shared resources and at most once by each job of that task. The resources have to be accessed in a mutually exclusive manner. We propose an algorithm, GIS-vpr, which offers the guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that allows a task to migrate only when it accesses or releases a resource, then our algorithm also meets the deadlines with the same restriction on the task migration, if given processors 4 + 6|R| times as fast. The proposed algorithm, by design, limits the number of migrations per job to at most two. To the best of our knowledge, this is the first result for resource sharing on uniform multiprocessors with proven performance guarantee.

Provably good scheduling of sporadic tasks with resource sharing on a two-type heterogeneous multiprocessor platform

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform where a task may request at most one of |R| shared resources. There are m1 processors of type-1 and m2 processors of type-2. Tasks may migrate only when requesting or releasing resources. We present a new algorithm, FF-3C-vpr, which offers a guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that only allows tasks to migrate when requesting or releasing a resource, then FF-3Cvpr also meets deadlines if given processors 4+6*ceil(|R|/min(m1,m2)) times as fast. As far as we know, it is the first result for resource sharing on heterogeneous platforms with provable performance.

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.