Estudo da norma contabilística e de relato financeiro nº 4 – politicas contabilísticas, alterações nas estimativas contabilísticas e erros

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Auditoria Orientador: Professor Doutor José da Silva Fernandes

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Energy resource scheduling considering reactive power management

The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Emergency energy resource management in SmartGrids

Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

European information users: topics from a comparative analysis within the European Union

Purpose – The aim of this article is to present some results from research undertaken into the information behaviour of European Documentation Centre (EDC) users. It will reflect on the practices of a group of 234 users of 55 EDCs covering 21 Member States of the European Union (EU), used to access European information. Design/methodology/approach – In order to collect the data presented here, five questionnaires were sent to users in all the EDCs in Finland, Ireland, Hungary and Portugal. In the remaining EU countries, five questionnaires were sent to two EDCs chosen at random. The questionnaires were sent by post, following telephone contact with the EDC managers. Findings – Factors determining access to information on the European Union and the frequency of this access are identified. The information providers most commonly used to access European information and the information sources considered the most reliable by respondents will also be analysed. Another area of analysis concerns the factors cited by respondents as facilitating access to information on Europe or, conversely, making it more difficult to access. Parallel to this, the aspects of accessing information on EU that are valued most by users will also be assessed. Research limitations/implications – Questionnaires had to be used, as the intention was to cover a very extensive geographical area. However, in opting for closed questions, it is acknowledged that standard responses have been obtained with no scope for capturing the individual circumstances of each respondent, thus making a qualitative approach difficult. Practical implications – The results provide an overall picture of certain aspects of the information behaviour of EDC users. They may serve as a starting point for planning training sessions designed to develop the skills required to search, access, evaluate and apply European information within an academic context. From a broader perspective, they also constitute factors which the European Commission should take into consideration when formulating its information and communication policy. Originality/value – This is the first piece of academic research into the EDCs and their users, which aimed to cover all Members State of the EU.

Mental health research in Brazil: policies, infrastructure, financing and human resources

The objective of this descriptive study was to map mental health research in Brazil, providing an overview of infrastructure, financing and policies mental health research. As part of the Atlas-Research Project, a WHO initiative to map mental health research in selected low and middle-income countries, this study was carried out between 1998 and 2002. Data collection strategies included evaluation of governmental documents and sites and questionnaires sent to key professionals for providing information about the Brazilian mental health research infrastructure. In the year 2002, the total budget for Health Research was US$101 million, of which US$3.4 million (3.4) was available for Mental Health Research. The main funding sources for mental health research were found to be the São Paulo State Funding Agency (Fapesp, 53.2%) and the Ministry of Education (CAPES, 30.2%). The rate of doctors is 1.7 per 1,000 inhabitants, and the rate of psychiatrists is 2.7 per 100,000 inhabitants estimated 2000 census. In 2002, there were 53 postgraduate courses directed to mental health training in Brazil (43 in psychology, six in psychiatry, three in psychobiology and one in psychiatric nursing), with 1,775 students being trained in Brazil and 67 overseas. There were nine programs including psychiatry, neuropsychiatry, psychobiology and mental health, seven of them implemented in Southern states. During the five-year period, 186 students got a doctoral degree (37 per year) and 637 articles were published in Institute for Scientic Information (ISI)-indexed journals. The investment channeled towards postgraduate and human resource education programs, by means of grants and other forms of research support, has secured the country a modest but continuous insertion in the international knowledge production in the mental health area.

Distributed Model Predictive Control for Housing with Hourly Auction of Available Energy

This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment.

Efficient implementation of a dominance protocol for wireless medium access

Mestrado em Engenharia Electrotécnica e de Computadores

The surplus value of Azorean macroalgae as health-promoting food. Protein, fiber, carbohydrates, lipids and vitamins determination

AICMA 2012 (BIT's 1st Annual International Congress of Marine Algae), World Expo Center, Dalian, China, 20-23 de Setembro.