Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

Efficient Legendre spectral tau algorithm for solving two-sided space-time Caputo fractional advection-dispersion equation

In this paper we present the operational matrices of the left Caputo fractional derivative, right Caputo fractional derivative and Riemann–Liouville fractional integral for shifted Legendre polynomials. We develop an accurate numerical algorithm to solve the two-sided space–time fractional advection–dispersion equation (FADE) based on a spectral shifted Legendre tau (SLT) method in combination with the derived shifted Legendre operational matrices. The fractional derivatives are described in the Caputo sense. We propose a spectral SLT method, both in temporal and spatial discretizations for the two-sided space–time FADE. This technique reduces the two-sided space–time FADE to a system of algebraic equations that simplifies the problem. Numerical results carried out to confirm the spectral accuracy and efficiency of the proposed algorithm. By selecting relatively few Legendre polynomial degrees, we are able to get very accurate approximations, demonstrating the utility of the new approach over other numerical methods.

Lanczos algorithm on the grassmann manifold

5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 8th. World Congress on Computational Mechanics (WCCM8)

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.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

A study on the encryption algorithm for RFID tag (SEED : 8 Rounds × 64 bits block)

Although it is always weak between RFID Tag and Terminal in focus of the security, there are no security skills in RFID Tag. Recently there are a lot of studying in order to protect it, but because it has some physical limitation of RFID, that is it should be low electric power and high speed, it is impossible to protect with the skills. At present, the methods of RFID security are using a security server, a security policy and security. One of them the most famous skill is the security module, then they has an authentication skill and an encryption skill. In this paper, we designed and implemented after modification original SEED into 8 Round and 64 bits for Tag.

Optimização dos parâmetros de um robô hexápode através de algoritmos genéticos

Mestrado em Engenharia Electrotécnica e de Computadores

Sequential application of soil vapor extraction and bioremediation processes for the remediation of ethylbenzene-contaminated soils

Soil vapor extraction (SVE) is an efficient, well-known and widely applied soil remediation technology. However, under certain conditions it cannot achieve the defined cleanup goals, requiring further treatment, for example, through bioremediation (BR). The sequential application of these technologies is presented as a valid option but is not yet entirely studied. This work presents the study of the remediation of ethylbenzene (EB)-contaminated soils, with different soil water and natural organic matter (NOMC) contents, using sequential SVE and BR. The obtained results allow the conclusion that: (1) SVE was sufficient to reach the cleanup goals in 63% of the experiments (all the soils with NOMC below 4%), (2) higher NOMCs led to longer SVE remediation times, (3) BR showed to be a possible and cost-effective option when EB concentrations were lower than 335 mg kgsoil −1, and (4) concentrations of EB above 438 mg kgsoil −1 showed to be inhibitory for microbial activity.

Inperlys – independente personal location system

O desenvolvimento de sistemas de localização pedestre com recurso a técnicas de dead reckoning tem mostrado ser uma área em expansão no mundo académico e não só. Existem algumas soluções criadas, no entanto, nem todas as soluções serão facilmente implementadas no mercado, quer seja pelo hardware caro, ou pelo sistema em si, que é desenvolvido tendo em conta um cenário em particular. INPERLYS é um sistema que visa apresentar uma solução de localização pedestre, independentemente do cenário, utilizando recursos que poderão ser facilmente usados. Trata-se de um sistema que utiliza uma técnica de dead reckonig para dar a localização do utilizador. Em cenários outdoor, um receptor GPS fornece a posição do utilizador, fornecendo uma posição absoluta ao sistema. Quando não é possível utilizar o GPS, recorre-se a um sensor MEMS e a uma bússola para se obter posições relativas à última posição válida do GPS. Para interligar todos os sensores foi utilizado o protocolo de comunicações sem fios ZigBee™. A escolha recaiu neste protocolo devido a factores como os seus baixos consumos e o seu baixo custo. Assim o sistema torna-se de uso fácil e confortável para o utilizador, ao contrário de sistemas similares desenvolvidos, que utilizam cabos para interligarem os diferentes componentes do sistema. O sensor MEMS do tipo acelerómetro tem a função de ler a aceleração horizontal, ao nível do pé. Esta aceleração será usada por um algoritmo de reconhecimento do padrão das acelerações para se detectar os passos dados. Após a detecção do passo, a aceleração máxima registada nesse passo é fornecida ao coordenador, para se obter o deslocamento efectuado. Foram efectuados alguns testes para se perceber a eficiência do INPERLYS. Os testes decorreram num percurso plano, efectuados a uma velocidade normal e com passadas normais. Verificou-se que, neste momento, o desempenho do sistema poderá ser melhorado, quer seja a nível de gestão das comunicações, quer a nível do reconhecimento do padrão da aceleração horizontal, essencial para se detectar os passos. No entanto o sistema é capaz de fornecer a posição através do GPS, quando é possível a sua utilização, e é capaz de fornecer a orientação do movimento.

Validation of a single-extraction procedure for sequential analysis of vitamin E, cholesterol, fatty acids, and total fat in seafood

Food lipid major components are usually analyzed by individual methodologies using diverse extractive procedures for each class. A simple and fast extractive procedure was devised for the sequential analysis of vitamin E, cholesterol, fatty acids, and total fat estimation in seafood, reducing analyses time and organic solvent consumption. Several liquid/liquid-based extractive methodologies using chlorinated and non-chlorinated organic solvents were tested. The extract obtained is used for vitamin E quantification (normal-phase HPLC with fluorescence detection), total cholesterol (normal-phase HPLC with UV detection), fatty acid profile, and total fat estimation (GC-FID), all accomplished in <40 min. The final methodology presents an adequate linearity range and sensitivity for tocopherol and cholesterol, with intra- and inter-day precisions (RSD) from 3 to 11 % for all the components. The developed methodology was applied to diverse seafood samples with positive outcomes, making it a very attractive technique for routine analyses in standard equipped laboratories in the food quality control field.

Assigning real-time tasks on heterogeneous multiprocessors with two unrelated types of processors

A preliminary version of this paper appeared in Proceedings of the 31st IEEE Real-Time Systems Symposium, 2010, pp. 239–248.

Laxity dynamics and LLF schedulability analysis on multiprocessor platforms

LLF (Least Laxity First) scheduling, which assigns a higher priority to a task with a smaller laxity, has been known as an optimal preemptive scheduling algorithm on a single processor platform. However, little work has been made to illuminate its characteristics upon multiprocessor platforms. In this paper, we identify the dynamics of laxity from the system’s viewpoint and translate the dynamics into LLF multiprocessor schedulability analysis. More specifically, we first characterize laxity properties under LLF scheduling, focusing on laxity dynamics associated with a deadline miss. These laxity dynamics describe a lower bound, which leads to the deadline miss, on the number of tasks of certain laxity values at certain time instants. This lower bound is significant because it represents invariants for highly dynamic system parameters (laxity values). Since the laxity of a task is dependent of the amount of interference of higher-priority tasks, we can then derive a set of conditions to check whether a given task system can go into the laxity dynamics towards a deadline miss. This way, to the author’s best knowledge, we propose the first LLF multiprocessor schedulability test based on its own laxity properties. We also develop an improved schedulability test that exploits slack values. We mathematically prove that the proposed LLF tests dominate the state-of-the-art EDZL tests. We also present simulation results to evaluate schedulability performance of both the original and improved LLF tests in a quantitative manner.

Device power management for real-time embedded systems

A large part of power dissipation in a system is generated by I/O devices. Increasingly these devices provide power saving mechanisms to inter alia enhance battery life. While I/O device scheduling has been studied in the past for realtime systems, the use of energy resources by these scheduling algorithms may be improved. These approaches are crafted considering a huge overhead of device transition. The technology enhancement has allowed the hardware vendors to reduce the device transition overhead and energy consumption. We propose an intra-task device scheduling algorithm for real time systems that allows to shut-down devices while ensuring the system schedulability. Our results show an energy gain of up to 90% in the best case when compared to the state-of-the-art.