11 resultados para Guanling Formation
em Instituto Politécnico do Porto, Portugal
Resumo:
All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. To get negotiation power and advantages of scale economy, distributed producers can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multitechnology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the development of a multi-agent market simulator – MASCEM – able to study alternative coalitions of distributed producers in order to identify promising Virtual Power Producers in an electricity market.
Resumo:
Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.
Resumo:
This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.
Resumo:
Negotiation is a fundamental tool for reaching understandings that allow each involved party to gain an advantage for themselves by the end of the process. In recent years, with the increasing of compe-titiveness in most sectors, negotiation procedures become present in practically all of them. One particular environment in which the competitiveness has been increasing exponentially is the electricity markets sector. This work is directed to the study of electricity markets’ partici-pating entities interaction, namely in what concerns the formation, management and operation of aggregating entities – Virtual Power Players (VPPs). VPPs are responsible for managing coalitions of market players with small market negotiating influence, which take strategic advantage in entering such aggregations, to increase their negotiating power. This chapter presents a negotiation methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using MASCEM, taking advantage of its ability to provide the means to model and simulate VPPs. VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself.
Resumo:
Group decision making plays an important role in today’s organisations. The impact of decision making is so high and complex, that rarely the decision making process is made just by one individual. The simulation of group decision making through a Multi-Agent System is a very interesting research topic. The purpose of this paper it to specify the actors involved in the simulation of a group decision, to present a model to the process of group formation and to describe the approach made to implement that model. In the group formation model it is considered the existence of incomplete and negative information, which was identified as crucial to make the simulation closer to the reality.
Resumo:
In this work, tin selenide thin films (SnSex) were grown on soda lime glass substrates by selenization of dc magnetron sputtered Sn metallic precursors. Selenization was performed at maximum temperatures in the range 300 °C to 570 °C. The thickness and the composition of the films were analysed using step profilometry and energy dispersive spectroscopy, respectively. The films were structurally and optically investigated by X-ray diffraction, Raman spectroscopy and optical transmittance and reflectance measurements. X-Ray diffraction patterns suggest that for temperatures between 300 °C and 470 °C, the films are composed of the hexagonal-SnSe2 phase. By increasing the temperature, the films selenized at maximum temperatures of 530 °C and 570 °C show orthorhombic-SnSe as the dominant phase with a preferential crystal orientation along the (400) crystallographic plane. Raman scattering analysis allowed the assignment of peaks at 119 cm−1 and 185 cm−1 to the hexagonal-SnSe2 phase and those at 108 cm−1, 130 cm−1 and 150 cm−1 to the orthorhombic-SnSe phase. All samples presented traces of condensed amorphous Se with a characteristic Raman peak located at 255 cm−1. From optical measurements, the estimated band gap energies for hexagonal-SnSe2 were close to 0.9 eV and 1.7 eV for indirect forbidden and direct transitions, respectively. The samples with the dominant orthorhombic-SnSe phase presented estimated band gap energies of 0.95 eV and 1.15 eV for indirect allowed and direct allowed transitions, respectively.
Resumo:
Users of wireless devices increasingly demand access to multimedia content with speci c quality of service requirements. Users might tolerate di erent levels of service, or could be satis ed with di erent quality combinations choices. However, multimedia processing introduces heavy resource requirements on the client side. Our work tries to address the growing demand on resources and performance requirements, by allowing wireless nodes to cooperate with each other to meet resource allocation requests and handle stringent constraints, opportunistically taking advantage of the local ad-hoc network that is created spontaneously, as nodes move in range of each other, forming a temporary coalition for service execution. Coalition formation is necessary when a single node cannot execute a speci c service, but it may also be bene cial when groups perform more e ciently when compared to a single s node performance.
Resumo:
Hexagonal wireless sensor network refers to a network topology where a subset of nodes have six peer neighbors. These nodes form a backbone for multi-hop communications. In a previous work, we proposed the use of hexagonal topology in wireless sensor networks and discussed its properties in relation to real-time (bounded latency) multi-hop communications in large-scale deployments. In that work, we did not consider the problem of hexagonal topology formation in practice - which is the subject of this research. In this paper, we present a decentralized algorithm that forms the hexagonal topology backbone in an arbitrary but sufficiently dense network deployment. We implemented a prototype of our algorithm in NesC for TinyOS based platforms. We present data from field tests of our implementation, collected using a deployment of fifty wireless sensor nodes.
Resumo:
S100A6 is a small EF-hand calcium- and zinc-binding protein involved in the regulation of cell proliferation and cytoskeletal dynamics. It is overexpressed in neurodegenerative disorders and a proposed marker for Amyotrophic Lateral Sclerosis (ALS). Following recent reports of amyloid formation by S100 proteins, we investigated the aggregation properties of S100A6. Computational analysis using aggregation predictors Waltz and Zyggregator revealed increased propensity within S100A6 helices HI and HIV. Subsequent analysis of Thioflavin-T binding kinetics under acidic conditions elicited a very fast process with no lag phase and extensive formation of aggregates and stacked fibrils as observed by electron microscopy. Ca2+ exerted an inhibitory effect on the aggregation kinetics, which could be reverted upon chelation. An FT-IR investigation of the early conformational changes occurring under these conditions showed that Ca2+ promotes anti-parallel β-sheet conformations that repress fibrillation. At pH 7, Ca2+ rendered the fibril formation kinetics slower: time-resolved imaging showed that fibril formation is highly suppressed, with aggregates forming instead. In the absence of metals an extensive network of fibrils is formed. S100A6 oligomers, but not fibrils, were found to be cytotoxic, decreasing cell viability by up to 40%. This effect was not observed when the aggregates were formed in the presence of Ca2+. Interestingly, native S1006 seeds SOD1 aggregation, shortening its nucleation process. This suggests a cross-talk between these two proteins involved in ALS. Overall, these results put forward novel roles for S100 proteins, whose metal-modulated aggregation propensity may be a key aspect in their physiology and function.
Resumo:
Advanced glycation end-products are Maillard reaction products that are found in thermal processed food. This compounds are often referred as unhealthy for human diet, namely because of their capacity to form amino-acid dimers. There is a broad range of answers to get about how these products are formed, how they interact with the organism and how these reactions can be inhibited to prevent the referred effects. Some compounds from garlic are thought to be able to inhibit these reactions. This study using spectrophotometric, High Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) and Fourier transformed infrared spectroscopy (FTIR) analysis, helps to understand better not only not only the effect of some compounds obtained from garlic, diallyl sulfide (DAS), diallyl disulfide (DADS) and diallyl trisulfide (DATS), on these AGEs production reaction, but also helped to understand better the reaction itself.
Resumo:
In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.