Representações dos técnicos de intervenção precoce sobre as famílias e práticas de IP em contexto rural e urbano

O presente estudo visou caraterizar as representações que técnicos de intervenção precoce têm sobre famílias que vivem em meio rural e em meio urbano que recebem apoio das equipas. Foram realizadas entrevistas semi-diretivas, os participantes e entrevistados foram dez docentes com intervenção educativa nas equipas, cinco em apoio direto a famílias de meio rural e cinco a realizar intervenções com famílias de meio urbano. Deste estudo resultaram vários dados qualitativos que depois de analisados e discutidos, levaram a diversas conclusões que vem dar respostas às questões e problemática iniciais. As famílias inseridas nestes contextos têm características que as diferenciam; habilitações, recursos, necessidades e comportamentos em comunidade. Tem aspetos culturais que influenciam as suas atitudes, participação e autonomia e são ou não decisivas no desenvolvimento da criança. Em contexto rural as famílias apresentam um maior número de necessidades comparativamente às famílias de meio urbano. As maiores necessidades das famílias em contexto rural situam-se nas questões financeiras, de formação e apoio técnico e especializado. As maiores necessidades das famílias de contexto urbano situam-se ao nível do fraco apoio familiar e das redes sociais. As necessidades comuns situam-se nas necessidades de informação e promoção da autonomia e competências parentais. As visitas e intervenções domiciliares podem permitir melhorar a identificação das necessidades e recursos das famílias e compreender melhor os critérios de referência de algumas crianças. As oportunidades de aprendizagem são maiores nestes encontros em domicílio, estão presentes em muitos casos, elementos da família alargada, que muitas vezes tem um papel fundamental na educação e estimulação destas crianças. Os docentes de IP em intervenção em contexto urbano, comparativamente com os docentes inseridos em contexto rural, apoiam famílias que na generalidade abrangem áreas profissionais mais vantajosas financeiramente. Estas famílias terão á partida melhores condições para aceder a mais recursos e apoios. Nos dois contextos existe uma necessidade comum, falta de informação e alguma autonomia e competências parentais em relação ao crescimento das crianças. A realização de iii encontros de pais ou criação de grupos de pais que tenham por base a partilha de experiencias e informação, estão planeadas mas não são uma realidade nestas equipas. Nas práticas de qualidade, o profissional deve atuar nos contextos naturais como, a família, ou a comunidade, mas pode incluir também rotinas, brincadeiras, festas etc. cenários que facilitem o dia-a-dia. As famílias têm contextos e rotinas próprias que os profissionais devem identificar, os dados que recolhemos indicam essa necessidade de proceder a avaliação mais atenta das necessidades das famílias. As práticas recomendadas e o enquadramento legislativo são tidos em conta pelos docentes e profissionais das equipas, os recursos documentais são na sua maioria comuns, a todas as equipas participantes, seguindo as orientações e documentos/minutas facultadas pela comissão coordenadora do SNIPI (Sistema Nacional de Intervenção Precoce na Infância) Apesar das recomendações teóricas para práticas de qualidade centradas na família, verificamos que estas fazem parte das preocupações destes docentes, mas nem sempre são implementadas. A problemática da criança parece ser ainda o ponto mais importante dos programas e planos de intervenção e mesmo o critério decisivo para delinear a duração e frequência das intervenções, seja em contexto urbano ou rural. - ABSTRACT This study aimed to characterize the families of rural and urban areas that receive support from Early Intervention Teams. It has been proposed yet whether professionals IP suit their practices to the characteristics of these families and communities integrated in different cultural contexts. Interviews were conducted semidirective, participants were ten respondents and teachers with educational intervention teams, five in direct support to families in rural areas and five interventions with families in urban areas. This study resulted in a number of qualitative data that then analyzed and discussed, led to several conclusions that comes to answer the questions and problems early. The families included in these contexts have characteristics that differentiate them; qualifications, resources, needs and behaviors in the community. Has cultural aspects that influence their attitudes, participation and autonomy and are not decisive in the development of the child. In the rural households have a greater number of needs compared to urban families. The greatest needs of families in rural settings are located in financial matters, training and technical support and expertise. The greatest needs of the urban households are located at the level of weak family support and social networks. Common needs lie in information needs and promoting autonomy and parenting skills. The home visits and interventions may allow improved identification of needs and resources of families and understand the benchmarks of some children. Learning opportunities are greater in these meetings at home, are present in many cases, elements of the extended family, which often plays a key role in education and stimulation of these children. Teachers IP intervention in the urban compared with rural teachers placed in context, support families in general include professional areas more financially advantageous. These families will have better starting conditions for access to more resources and support. In both contexts there is a common need, lack of information and some autonomy and parenting skills in relation to the growth of children. The meetings of parents or creating parent groups that are based on the sharing of information and experiences are planned but are not a reality in these teams. In quality practices, the professional must act in natural contexts like the family or the community, but may also include routines, jokes, and parties’ etc. scenarios that v facilitate the day-to-day. Families have their own contexts and routines that professionals should identify, collect the data indicate that the need for more careful assessment of the needs of families. Best practices and legislative environment are taken into account by teachers and professional teams, the documentary resources are mostly common to all participating teams, following the guidelines and documents / drafts provided by the coordinating committee SNIPI (National Intervention Early Childhood) Despite the theoretical recommendations for quality practices family-centered, we see that these are part of the concerns of teachers, but are not always implemented. The issue of child seems to be still the most important programs and plans and even the decisive criterion for delineating the duration and frequency of interventions whether in urban or rural.

Multi-criteria short-term maintenance outage scheduling in smart distribution systems

Effective legislation and standards for the coordination procedures between consumers, producers and the system operator supports the advances in the technologies that lead to smart distribution systems. In short-term (ST) maintenance scheduling procedure, the energy producers in a distribution system access to the long-term (LT) outage plan that is released by the distribution system operator (DSO). The impact of this additional information on the decision-making procedure of producers in ST maintenance scheduling is studied in this paper. The final ST maintenance plan requires the approval of the DSO that has the responsibility to secure the network reliability and quality, and other players have to follow the finalized schedule. Maintenance scheduling in the producers’ layer and the coordination procedure between them and the DSO is modelled in this paper. The proposed method is applied to a 33-bus distribution system.

MASGriP – a Multi-Agent Smart Grid Simulation Platform

The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Electric vehicles in urban areas: test cases using a scenario simulator

Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

A regulatory framework for short-term stochastic maintenance outage scheduling in smart grids

The current regulatory framework for maintenance outage scheduling in distribution systems needs revision to face the challenges of future smart grids. In the smart grid context, generation units and the system operator perform new roles with different objectives, and an efficient coordination between them becomes necessary. In this paper, the distribution system operator (DSO) of a microgrid receives the proposals for shortterm (ST) planned outages from the generation and transmission side, and has to decide the final outage plans, which is mandatory for the members to follow. The framework is based on a coordination procedure between the DSO and other market players. This paper undertakes the challenge of optimization problem in a smart grid where the operator faces with uncertainty. The results show the effectiveness and applicability of the proposed regulatory framework in the modified IEEE 34- bus test system.

Advances in smart grids - benefits on sharing background experiences from Portugal, Central Europe and Brazil

This paper presents ELECON - Electricity Consumption Analysis to Promote Energy Efficiency Considering Demand Response and Non-technical Losses, an international research project that involves European and Brazilian partners. ELECON focuses on energy efficiency increasing through consumer´s active participation which is a key area for Europe and Brazil cooperation. The project aims at significantly contributing towards the successful implementation of smart grids, focussing on the use of new methods that allow the efficient use of distributed energy resources, namely distributed generation, storage and demand response. ELECON puts together researchers from seven European and Brazilian partners, with consolidated research background and evidencing complementary competences. ELECON involves institutions of 3 European countries (Portugal, Germany, and France) and 4 Brazilian institutions. The complementary background and experience of the European and Brazilian partners is of main relevance to ensure the capacities required to achieve the proposed goals. In fact, the European Union (EU) and Brazil have very different resources and approaches in what concerns this area. Having huge hydro and fossil resources, Brazil has not been putting emphasis on distributed renewable based electricity generation. On the contrary, EU has been doing huge investments in this area, taking into account environmental concerns and also the economic EU external dependence dictated by huge requirements of energy related products imports. Sharing these different backgrounds allows the project team to propose new methodologies able to efficiently address the new challenges of smart grids.

Smart Electric Vehicle Charging System

In this work is proposed the design of a system to create and handle Electric Vehicles (EV) charging procedures, based on intelligent process. Due to the electrical power distribution network limitation and absence of smart meter devices, Electric Vehicles charging should be performed in a balanced way, taking into account past experience, weather information based on data mining, and simulation approaches. In order to allow information exchange and to help user mobility, it was also created a mobile application to assist the EV driver on these processes. This proposed Smart ElectricVehicle Charging System uses Vehicle-to-Grid (V2G) technology, in order to connect Electric Vehicles and also renewable energy sources to Smart Grids (SG). This system also explores the new paradigm of Electrical Markets (EM), with deregulation of electricity production and use, in order to obtain the best conditions for commercializing electrical energy.

A study on dynamic state information (DSI) around users for safe urban life

To select each node by devices and by contexts in urban computing, users have to put their plan information and their requests into a computing environment (ex. PDA, Smart Devices, Laptops, etc.) in advance and they will try to keep the optimized states between users and the computing environment. However, because of bad contexts, users may get the wrong decision, so, one of the users’ demands may be requesting the good server which has higher security. To take this issue, we define the structure of Dynamic State Information (DSI) which takes a process about security including the relevant factors in sending/receiving contexts, which select the best during user movement with server quality and security states from DSI. Finally, whenever some information changes, users and devices get the notices including security factors, then an automatic reaction can be possible; therefore all users can safely use all devices in urban computing.

Electric vehicle scenario simulator tool for smart grid operators

This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operator´s planning and operations but can be used by other entities for related studies. The paper describes the parameters supported by the current version of the Electric Vehicle Scenario Simulator (EVeSSi) tool and its current algorithm. EVeSSi enables the definition of electric vehicles scenarios on distribution networks using a built-in movement engine. The scenarios created with EVeSSi can be used by external tools (e.g., power flow) for specific analysis, for instance grid impacts. Two scenarios are briefly presented for illustration of the simulator capabilities.

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.

Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems

Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.

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 .

Particle swarm optimization applied to integrated demand response resources scheduling

The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.