Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

Assessment and control of nanoparticles exposure in welding operations by use of a control banding tool

This paper describes the use of a Control Banding Tool to assess and further control of exposure of nanoparticles emitted during welding operations. The tool was applied to Metal Active Gas (MAG) arc welding of mild and stainless steel, providing semi-quantitative data on the process, so that protection measures could be derived, e.g. exhaust gas ventilation by hoods, local ventilation devices and containment measures. This tool is quite useful to compare and evaluate the characteristics of arc welding procedures so that more eco-friendly processes could be preferred over the more potentially noxious ones.

The discovery of three lost ‘Salting’ carpets: science as a tool for revealing their history

Thesis presented at the Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, to obtain a Master degree in Conservation and Restoration,Specialization in Textiles

ISO 14001:2015: An Improved Tool for Sustainability

ISO 14001 is an International Standard of worldwide acceptance based on the concept that better environmental performance can be achieved when environmental aspects are systematically identified and managed giving a major contribution to Sustainability, through pollution prevention, improved environmental performance and complying with applicable laws. This paper aims to discuss the Sustainability approach through the use of Environmental Management Standards (EMS), the results achieved by organizations that implement and certify those EMS and a special focus on the current process of ISO 14001:2015 revision and the logic behind it.

Microencapsulation technology: a powerful tool for human embryonic stem cells expansion and cryopreservation

Dissertation presented to obtain a Master degree in Biotechnology at the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

China's space program : a new tool for PRC "soft power" in international relations?

When China launched an anti-satellite (ASAT) weapon in January 2007 to destroy one of its inactive weather satellites, most reactions from academics and U.S. space experts focused on a potential military “space race” between the United States and China. Overlooked, however, is China’s growing role as global competitor on the non-military side of space. China’s space program goes far beyond military counterspace applications and manifests manned space aspirations, including lunar exploration. Its pursuit of both commercial and scientific international space ventures constitutes a small, yet growing, percentage of the global space launch and related satellite service industry. It also highlights China’s willingness to cooperate with nations far away from Asia for political and strategic purposes. These partnerships may constitute a challenge to the United States and enhance China’s “soft power” among key American allies and even in some regions traditionally dominated by U.S. influence (e.g., Latin America and Africa). Thus, an appropriate U.S. response may not lie in a “hard power” counterspace effort but instead in a revival of U.S. space outreach of the past, as well as implementation of more business-friendly export control policies.

Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets

The study of electricity markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring process produced. Currently, lots of information concerning electricity markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge to define realistic scenarios, which are essential for understanding and forecast electricity markets behavior. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of electricity markets and of the behaviour of the involved entities. In this paper an adaptable tool capable of downloading, parsing and storing data from market operators’ websites is presented, assuring constant updating and reliability of the stored data.

An automatic tool to Extract, Transform and Load data from real electricity markets

The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

Smart meters as a tool for energy efficiency

Gradually smart grids and smart meters are closer to the home consumers. Several countries has developed studies focused in the impacts arising from the introduction of these technologies and one of the main advantages are related to energy efficiency, observed through the awareness of the population on behalf of a more efficient consumption. These benefits are felt directly by consumers through the savings on electricity bills and also by the concessionaires through the minimization of losses in transmission and distribution, system stability, smaller loading during peak hours, among others. In this article two projects that demonstrate the potential energy savings through smart meters and smart grids are presented. The first performed in Korea, focusing on the installation of smart meters and the impact of use of user interfaces. The second performed in Portugal, focusing on the control of loads in a residence with distributed generation.

Terminology as a sensemaking social tool

Since the middle of the first decade of this century, several authors have announced the dawn of a new Age, following the Information/ Knowledge Age (1970-2005?). We are certainly living in a Shift Age (Houle, 2007), but no standard designation has been broadly adopted so far, and others, such as Conceptual Age (Pink, 2005) or Social Age (Azua, 2009), are only some of the proposals to name current times. Due to the amount of information available nowadays, meaning making and understanding seem to be common features of this new age of change; change related to (i) how individuals and organizations engage with each other, to (ii) the way we deal with technology, to (iii) how we engage and communicate within communities to create meaning, i.e., also social networking-driven changes. The Web 2.0 and the social networks have strongly altered the way we learn, live, work and, of course, communicate. Within all the possible dimensions we could address this change, we chose to focus on language – a taken-for-granted communication tool, used, translated and recreated in personal and geographical variants, by the many users and authors of the social networks and other online communities and platforms. In this paper, we discuss how the Web 2.0, and specifically social networks, have contributed to changes in the communication process and, in bi- or multilingual environments, to the evolution and freeware use of the so called “international language”: English. Next, we discuss some of the impacts and challenges of this language diversity in international communication in the shift age of understanding and social networking, focusing on specialized networks. Then we point out some skills and strategies to avoid babelization and to build meaningful and effective content in mono or multilingual networks, through the use of common and shared concepts and designations in social network environments. For this purpose, we propose a social and collaborative approach to terminology management, as a shared, strategic and sense making tool for specialized communication in Web 2.0 environments.

Self-assessment of writing skills: a reliable and valid tool in an efl classroom

Trabalho de projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ensino da Língua Inglesa

Analysis of Synaptic Proteins in the Cerebrospinal Fluid as a New Tool in the Study of Inborn Errors of Neurotransmission

Abstract In a few rare diseases, specialised studies in cerebrospinal fluid (CSF) are required to identify the underlying metabolic disorder. We aimed to explore the possibility of detecting key synaptic proteins in the CSF, in particular dopaminergic and gabaergic, as new procedures that could be useful for both pathophysiological and diagnostic purposes in investigation of inherited disorders of neurotransmission. Dopamine receptor type 2 (D2R), dopamine transporter (DAT) and vesicular monoamine transporter type 2 (VMAT2) were analysed in CSF samplesfrom 30 healthy controls (11 days to 17 years) by western blot analysis. Because VMAT2 was the only protein with intracellular localisation, and in order to compare results, GABA vesicular transporter, which is another intracellular protein, was also studied. Spearman’s correlation and Student’s t tests were applied to compare optical density signals between different proteins. All these synaptic proteins could be easily detected and quantified in the CSF. DAT, D2R and GABA VT expression decrease with age, particularly in the first months of life, reflecting the expected intense synaptic activity and neuronal circuitry formation. A statistically significant relationship was found between D2R and DAT expression, reinforcing the previous evidence of DAT regulation by D2R. To our knowledge, there are no previous studies on human CSF reporting a reliable analysis of these proteins. These kinds of studies could help elucidate new causes of disturbed dopaminergic and gabaergic transmission as well as understanding different responses to L-dopa in inherited disorders affecting dopamine metabolism. Moreover, this approach to synaptic activity in vivo can be extended to different groups of proteins and diseases.