A gestão do ciclo da água nos aglomerados populacionais suas limitações

Revista Lusófona de Arquitectura e Educação

A água, o saneamento básico e os residuos sólidos urbanos no desenvolvimento de São Tomé e Príncipe

RESUMO: O trabalho que se apresenta no âmbito desta dissertação, é direcionado para a problemática da Água, do Saneamento Básico e dos Resíduos Sólidos Urbanos «RSU» em São Tomé e Príncipe. Num contexto de desenvolvimento e indo ao encontro dos anseios da Organização das Nações Unidas «ONU» e da sua perspetiva de alcançar os Objetivos do Milénio nesta área tão importante. Elegeu-se como primordial objetivo, conhecer as indicações técnico políticas instituídas em São Tomé e Príncipe, para a gestão dos problemas acima enumerados. Entender esses problemas, identificar as dificuldades sentidas pelo governo e pela generalidade dos seus habitantes no acesso à água, ao saneamento básico, à recolha e tratamento de RSU. Outra vertente será direcionada para apontar caminhos nestas áreas, onde a capacidade institucional tarda em dar resposta às necessidades básicas destes setores, inviabilizando um desenvolvimento sustentado destes ramos. Esta dissertação, assenta ainda no reconhecimento e na importância estratégica em se valorizar e consolidar redes técnico-científicas no âmbito da Linha de Investigação em Estudos Africanos e Pós-Coloniais, inserida na Unidade de Estudos e Investigação em Ciência, Tecnologia e Sociedade «UEICTS» da Universidade Lusófona de Humanidades e Tecnologias «ULHT».ABSTRACT: The work presented in this dissertation, is directed to the problem of Water Sanitation and Solid Waste «RSU» in Sao Tome and Principe. In a context of development, fulfillment of the wishes of the United Nations «UN» and its prospect of achieving the Millennium Goals in this important area. The prime objective, is, to know the indications and technical policies in place in Sao Tome and Principe for the management of the problems listed above. Understanding these problems, identifying the difficulties faced by government and by most of its residents in relation, to access to water, sanitation, collection and treatment of Solid Waste. Another aspect, is directed, to point, to ways, in these subjects where institutional capacity is slow to respond to basic needs of these sectors, preventing a sustained development of these industries. This dissertation focus on the recognition and strategic importance in considering and consolidate technical and scientific networks in the line of Research in African and Lusophone, inserted at the Unit for Studies and Research in Science, Technology and Society «UEICTS» Lusophone University of Humanities and Technology «ULHT».

Learning in higher education: the ISEGI case

Comunicação apresentada na IRMA Information Resources Management Association International Conference, San Diego, CA, 15 19 May

Knowledge magement: a rewarding challenge for SME's?

Paper presented at Information Resources Management Association International Conference, in Philadelphia (PA), 18-21 May 2003

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.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

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.

An optimal scheduling problem in distribution networks considering V2G

This paper addresses the problem of energy resource scheduling. An aggregator will manage all distributed resources connected to its distribution network, including distributed generation based on renewable energy resources, demand response, storage systems, and electrical gridable vehicles. The use of gridable vehicles will have a significant impact on power systems management, especially in distribution networks. Therefore, the inclusion of vehicles in the optimal scheduling problem will be very important in future network management. The proposed particle swarm optimization approach is compared with a reference methodology based on mixed integer non-linear programming, implemented in GAMS, to evaluate the effectiveness of the proposed methodology. The paper includes a case study that consider a 32 bus distribution network with 66 distributed generators, 32 loads and 50 electric vehicles.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

LMP based bid formation for virtual power players operating in smart grids

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.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Hospital volunteers – are they satisfied?

We examine satisfaction with HRM practices, namely recruitment, training and rewarding in NPO’s and attitudes regarding the appropriateness of these practices. The participants in this study are 76 volunteers, affiliated to 4 different NPO’s, which work in hospitals and have direct contact with patients and their families. Analysing aggregate results we show that volunteers are more satisfied with training, and consider that the training strategies are very appropriate. After identifying differences between organisations we discover that in some organizations volunteers are satisfied with rewards, but in opposition they have negative attitudes regarding the appropriateness of the recognition strategies and vice-versa an opposite relation between satisfaction with reward and recognition strategies and the process of reward and recognition. We also name the more and less satisfied volunteers.

Organisational influence on volunteer satisfaction and attitudes towards HRM practices: the case of hospital volunteers

We examine volunteer satisfaction with HRM practices, namely recruitment, training and reward in NPOs and attitudes regarding the appropriateness of these practices. The participants in this study are 76 volunteers affiliated with four different NPOs, who work in hospitals and have direct contact with patients and their families. Analysing aggregate results we show that volunteers are more satisfied with training, and consider the training strategies to be very appropriate. After identifying differences between organisations we discover that in some organisations volunteers are satisfied with rewards but they have negative attitudes regarding the appropriateness of the recognition strategies. We also identify the volunteers who are the most and the least satisfied.

Práticas de Gestão de Recursos Humanos nas IPSS

As instituições particulares de solidariedade social (IPSS) são entidades constituídas por iniciativa de particulares e sem finalidade lucrativa com o propósito de dar expressão organizada ao dever moral de solidariedade e de justiça entre os indivíduos. Considerando as dificuldades económicas que Portugal atravessa estas instituições assumem um papel fundamental na sociedade de hoje, sendo o mesmo reconhecido por estado e clientes. O capital humano é o elemento central no que concerne aos ativos intangíveis e é formado pelas pessoas que integram a instituição. É essencial analisar a gestão dos recursos humanos das IPSS tendo em conta que estes, alinhados com a direção, são parte fulcral para a instituição atingir os objetivos a que se propõe. Com este estudo pretendemos analisar as práticas de gestão de recursos humanos aplicadas pelas IPSS e para o conseguir utilizamos um questionário diagnóstico, distribuído a uma amostra da população, e analisamos as práticas de uma IPSS através de um estudo de caso. O estudo mostrou que as IPSS aplicam maioritariamente a gestão administrativa de recursos humanos e que a regulamentação das instituições por parte da Segurança Social é um fator importante na tipologia de gestão aplicada. As conclusões baseiam-se na análise do estudo de caso e das respostas ao questionário, pelas IPSS da amostra, razão pela qual a generalização das conclusões deverá ser ponderada.