A sensitivity study of the WRF model in wind simulation for an area of high wind energy

The performance of the Weather Research and Forecast (WRF) model in wind simulation was evaluated under different numerical and physical options for an area of Portugal, located in complex terrain and characterized by its significant wind energy resource. The grid nudging and integration time of the simulations were the tested numerical options. Since the goal is to simulate the near-surface wind, the physical parameterization schemes regarding the boundary layer were the ones under evaluation. Also, the influences of the local terrain complexity and simulation domain resolution on the model results were also studied. Data from three wind measuring stations located within the chosen area were compared with the model results, in terms of Root Mean Square Error, Standard Deviation Error and Bias. Wind speed histograms, occurrences and energy wind roses were also used for model evaluation. Globally, the model accurately reproduced the local wind regime, despite a significant underestimation of the wind speed. The wind direction is reasonably simulated by the model especially in wind regimes where there is a clear dominant sector, but in the presence of low wind speeds the characterization of the wind direction (observed and simulated) is very subjective and led to higher deviations between simulations and observations. Within the tested options, results show that the use of grid nudging in simulations that should not exceed an integration time of 2 days is the best numerical configuration, and the parameterization set composed by the physical schemes MM5–Yonsei University–Noah are the most suitable for this site. Results were poorer in sites with higher terrain complexity, mainly due to limitations of the terrain data supplied to the model. The increase of the simulation domain resolution alone is not enough to significantly improve the model performance. Results suggest that error minimization in the wind simulation can be achieved by testing and choosing a suitable numerical and physical configuration for the region of interest together with the use of high resolution terrain data, if available.

Wear resistance of TiAlSiN thin coatings

In the last decades TiAlN coatings deposited by PVD techniques have been extensively investigated but, nowadays, their potential development for tribological applications is relatively low. However, new coatings are emerging based on them, trying to improve wear behavior. TiAlSiN thin coatings are now investigated, analyzing if Si introduction increases the wear resistance of PVD films. Attending to the application, several wear test configurations has been recently used by some researchers. In this work, TiAlSiN thin coatings were produced by PVD Unbalanced Magnetron Sputtering technique and they were conveniently characterized using Scanning Electron Microscopy (SEM) provided with Energy Dispersive Spectroscopy (EDS), Atomic Force Microscopy (AFM), Electron Probe Micro-Analyzer (EPMA), Micro Hardness (MH) and Scratch Test Analysis. Properties as morphology, thickness, roughness, chemical composition and structure, hardness and film adhesion to the substrate were investigated. Concerning to wear characterization, two very different ways were chosen: micro-abrasion with ball-on-flat configuration and industrial non-standardized tests based on samples inserted in a feed channel of a selected plastic injection mould working with 30% (wt.) glass fiber reinforced polypropylene. TiAlSiN coatings with a small amount of about 5% (wt.) Si showed a similar wear behavior when compared with TiAlN reported performances, denoting that Si addition does not improve the wear performance of the TiAlN coatings in these wear test conditions.

Mechanical and tribological characterization of TiB2 thin films

Titanium Diboride (TiB2) presents high mechanical and physical properties. Some wear studies were also carried out in order to evaluate its tribological properties. One of the most popular wear tests for thin films is the ball-cratering configuration. This work was focused on the study of the tribological properties of TiB2 thin films using micro-abrasion tests and following the BS EN 1071-6: 2007 standard. Due to high hardness usually patented by these films, diamond was selected as abrasive on micro-abrasion tests. Micro-abrasion wear tests were performed under five different durations, using the same normal load, speed rotation and ball. Films were deposited by unbalanced magnetron sputtering Physical Vapour Deposition (PVD) technique using TiB2 targets. TiB2 films were characterized using different methods as Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), Atomic Force Microscopy (AFM), X-ray Diffraction (XRD), Electron Probe Micro-Analyser (EPMA), Ultra Micro Hardness and Scratch-test Analysis, allowing to confirm that TiB2 presents adequate mechanical and physical properties. Ratio between hardness (coating and abrasive particles), wear resistance and wear coefficient were studied, showing that TiB2 films shows excellent properties for tribological applications.

Increasing the wear resistance of molds for injection of glass fiber reinforced plastics

Abrasion by glass fibers during injection molding of fiber reinforced plastics raises new challenges to the wear performance of the molds. In the last few decades, a large number of PVD and CVD coatings have been developed with the aim of minimizing abrasion problems. In this work, two different coatings were tested in order to increase the wear resistance of the surface of a mold used for glass fiber reinforced plastics: TiAlSiN and CrN/CrCN/DLC. TiAlSiN was deposited as a graded monolayer coating while CrN/CrCN/DLC was a nanostructured coating consisting of three distinct layers. Both coatings were produced by PVD unbalanced magnetron sputtering and were characterized using scanning electron microscopy (SEM) provided with energy dispersive spectroscopy (EDS), atomic force microscopy (AFM), micro hardness (MH) and scratch test analysis. Coating morphology, thickness, roughness, chemical composition and structure, hardness and adhesion to the substrate were investigated. Wear resistance was characterized through industrial tests with coated samples and an uncoated reference sample inserted in a feed channel of a plastic injection mold working with 30 wt.% glass fiber reinforced polypropylene. Results after 45,000 injection cycles indicate that the wear resistance of the mold was increased by a factor of 25 and 58, by the TiAlSiN and CrN/CrCN/DLC coatings, respectively, over the uncoated mold steel.

Credit risk measures: a case of renewable energy companies

The Basel III will have a significant impact on the European banking sector. In September 2010, supervisors of various countries adopted the new rules proposed by the prudential Committee on Banking Supervision to be applied to the business of credit institutions (hereinafter called ICs) in a phased manner from 2013, assuming to its full implementation by 2019. The purpose of this new regulation is to limit the excessive risk that these institutions took on the period preceding the global financial crisis of 2008. This new regulation is known in slang by Basel III. Depending on the requirement of Basel II for banks and their supervisors to assess the soundness and adequacy of internal risk measurement and credit management systems, the development of methodologies for the validation of internal and external evaluation systems is clearly an important issue . More specifically, there is a need to develop tools to validate the systems used to generate the parameters (such as PD, LGD, EAD and ratings of perceived risk) that serve as starting points for the IRB approach for credit risk. In this context, the work is composed of a number of approaches and tools used to evaluate the robustness of these elements IRB systems.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Energy efficiency of quadruped gaits

This paper studies periodic gaits of quadruped locomotion systems. The purpose is to determine the best set of gait and locomotion variables during walking, for different robot velocities, based on two formulated performance measures. A set of experiments reveals the influence of the gait and locomotion variables upon the proposed indices, namely that the gait and the locomotion parameters should be adapted to the robot forward velocity.

Optimising the energy consumption on pultrusion process

This study is based on a previous experimental work in which embedded cylindrical heaters were applied to a pultrusion machine die, and resultant energetic performance compared with that achieved with the former heating system based on planar resistances. The previous work allowed to conclude that the use of embedded resistances enhances significantly the energetic performance of pultrusion process, leading to 57% decrease of energy consumption. However, the aforementioned study was developed with basis on an existing pultrusion die, which only allowed a single relative position for the heaters. In the present work, new relative positions for the heaters were investigated in order to optimise heat distribution process and energy consumption. Finite Elements Analysis was applied as an efficient tool to identify the best relative position of the heaters into the die, taking into account the usual parameters involved in the process and the control system already tested in the previous study. The analysis was firstly developed based on eight cylindrical heaters located in four different location plans. In a second phase, in order to refine the results, a new approach was adopted using sixteen heaters with the same total power. Final results allow to conclude that the correct positioning of the heaters can contribute to about 10% of energy consumption reduction, decreasing the production costs and leading to a better eco-efficiency of pultrusion process.

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%.

Towards high-available and energy-efficient virtual computing environments in the cloud

Empowered by virtualisation technology, cloud infrastructures enable the construction of flexi- ble and elastic computing environments, providing an opportunity for energy and resource cost optimisation while enhancing system availability and achieving high performance. A crucial re- quirement for effective consolidation is the ability to efficiently utilise system resources for high- availability computing and energy-efficiency optimisation to reduce operational costs and carbon footprints in the environment. Additionally, failures in highly networked computing systems can negatively impact system performance substantially, prohibiting the system from achieving its initial objectives. In this paper, we propose algorithms to dynamically construct and readjust vir- tual clusters to enable the execution of users’ jobs. Allied with an energy optimising mechanism to detect and mitigate energy inefficiencies, our decision-making algorithms leverage virtuali- sation tools to provide proactive fault-tolerance and energy-efficiency to virtual clusters. We conducted simulations by injecting random synthetic jobs and jobs using the latest version of the Google cloud tracelogs. The results indicate that our strategy improves the work per Joule ratio by approximately 12.9% and the working efficiency by almost 15.9% compared with other state-of-the-art algorithms.

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.

How to reduce energy consumption on pultrusion

The global warming due to high CO2 emission in the last years has made energy saving a global problem nowadays. However, manufacturing processes such as pultrusion necessarily needs heat for curing the resin. Then, the only option available is to apply all efforts to make the process even more efficient. Different heating systems have been used on pultrusion, however, the most widely used are the planar resistances. The main objective of this study is to develop another heating system and compares it with the former one. Thermography was used in spite of define the temperature profile along the die. FEA (finite element analysis) allows to understand how many energy is spend with the initial heating system. After this first approach, changes were done on the die in order to test the new heating system and to check possible quality problems on the product. Thus, this work allows to conclude that with the new heating system a significant reduction in the setup time is now possible and an energy reduction of about 57% was achieved.

Support System for Rational Use of Electric Energy

This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform - the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.

A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.

Distributed Generation and Demand Response Dispatch for a Virtual Power Player Energy and Reserve Provision

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.