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.

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

VPP´s multi-level negotiation in smart grids and competitive electricity markets

The increase of distributed generation (DG) has brought about new challenges in electrical networks electricity markets and in DG units operation and management. Several approaches are being developed to manage the emerging potential of DG, such as Virtual Power Players (VPPs), which aggregate DG plants; and Smart Grids, an approach that views generation and associated loads as a subsystem. This paper presents a multi-level negotiation mechanism for Smart Grids optimal operation and negotiation in the electricity markets, considering the advantages of VPPs’ management. The proposed methodology is implemented and tested in MASCEM – a multiagent electricity market simulator, developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations.

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.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Lesões Músculo-Esqueléticas Ligadas ao Trabalho (LMELT) nos operários das fábricas de queijo da Ilha de São Jorge

O presente artigo tem por objectivo conhecer a existência de LMELT (Lesões Músculo-Esqueléticas Ligadas ao Trabalho), através da avaliação de sintomas, movimentos e posições auto-referidos pelos operários das Fábricas de Queijo da Ilha de São Jorge, através da aplicação de dois Questionários. A amostra foi constituída por 61 operários das três Fábricas. Através dos resultados obtidos pode-se afirmar que estes operários apresentam LMELT, manifestando-se por dores nas diferentes zonas corporais, devido a realização de tarefas repetidas, levantamento e transporte de cargas, a temperaturas extremas e ainda pelo facto dos locais de trabalho não estarem adaptados ergonomicamente.

Exposure to larva migrans syndromes in squares and public parks of cities in Chile

Between November 2001 and December 2002, 600 dog fecal samples were collected in main squares and public parks of 13 cities in Chile, from the extreme north to the extreme south of the country. The samples were processed in the laboratory by centrifugal sedimentation and the Harada-Mori methods. T. canis eggs were found in 12 cities. Detection rates ranged from 1.9 to 12.5% with an average of 5.2%. Seven percent of the samples had eggs and 9.5% had rhabditoid and/or filariform larvae of Ancylostomatidae. Strongyloides stercoralis were not found. Squares and public parks in Chile pose a potential risk of exposure to visceral, ocular, and/or cutaneous larva migrans syndromes.

The role of demand response in future power systems

Power systems are planed and operated according to the optimization of the available resources. Traditionally these tasks were mostly undertaken in a centralized way which is no longer adequate in a competitive environment. Demand response can play a very relevant role in this context but adequate tools to negotiate this kind of resources are required. This paper presents an approach to deal with these issues, by using a multi-agent simulator able to model demand side players and simulate their strategic behavior. The paper includes an illustrative case study that considers an incident situation. The distribution company is able to reduce load curtailment due to load flexibility contracts previously established with demand side players.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

Ancillary service market simulation

Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.

Demsi - a demand response simulator in the context of intensive use of distributed generation

Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.

Certificação de um troço de via alvo de ataque mecânico pesado

Qualidade é a palavra de ordem pelo qual se regem todos os processos e intervenções da REFER (Rede Ferroviária Nacional). Com a evolução de requisitos exigidos pelo transporte em caminho de ferro, há que procurar sempre as últimas inovações, para que a circulação se faça sempre com maior segurança e comodidade, dando aos utilizadores deste tipo transporte uma qualidade extrema. Nos últimos anos esses requisitos tornaram-se cada vez mais exigentes, pois as condições de circulação aumentam tais como a prática de maiores velocidades, tonelagem e frequência das composições, o que leva a um maior rigor nos processos construtivos e conservativos das vias. A REFER, depois de grandes investimentos em novas infraestruturas ferroviárias, detém agora um decisivo e importante papel na resolução das problemáticas que emergem, apostando sempre em tecnologia de ponta para que possa desenvolver um trabalho de conservação que satisfaça todas as necessidades exigidas. Este trabalho desenvolver-se-á nesta ótica de conservação e manutenção, acompanhando todo um processo específico de ataque mecânico pesado, até à sua certificação. A análise dos vários processos caracterizará a exigência referida na manutenção, principalmente da via moderna, onde a fasquia de requisitos é mais elevada.

Articulação do tratamento das águas lixiviantes de infraestruturas de resíduos com ETAR urbanas: caso de estudo

A deposição de resíduos sólidos urbanos (RSU) em aterros sanitários (AS) tem uma dimensão que necessita de uma atenção especial por parte da sociedade. Deste acto podem resultar situações gravosas para o meio ambiente se não forem tomadas as medidas correctas. Um dos pontos que necessita de uma particular atenção é o tratamento das águas lixiviantes dos aterros sanitários, uma vez que estas apresentam geralmente cargas altamente poluentes. O presente trabalho apresenta a estrutura de um aterro sanitário, definindo os seus princípios de funcionamento, bem como as principais características a ter em consideração para a sua concepção e construção. É ainda abordada a composição dos resíduos sólidos produzidos em Portugal de acordo com (1) e as características quantitativas e qualitativas do lixiviado produzido por um AS. São apresentados os sistemas tratamento convencionais, biológicos e físico-químicos, mais utilizados em Portugal para o tratamento de águas lixiviantes, relacionando as problemáticas e as limitações associadas a cada um deles. É ainda apresentado o tratamento combinado de águas lixiviantes com águas residuais e a recirculação de lixiviado no sistema de tratamento, assim como algumas das vantagens associadas a estas práticas. Tendo por base, uma situação real, avalia-se um caso de estudo, que visa a avaliação do funcionamento da estação de pré-tratamento das águas lixiviantes produzidas no aterro sanitário do ecoparque de Palmela, tendo em consideração o facto de este tratamento ser realizado em combinação com o tratamento de águas residuais urbanas. A avaliação do funcionamento da estação de pré-tratamento de águas lixiviantes (EPTAL) é realizada de acordo com os dados fornecidos nos relatórios elaborados pela empresa LUSÁGUA, que apresentam os valores das cargas poluentes medidos à entrada e saída da EPTAL, verificando com estes dados se os valores limite de emissão medidos à saída da EPTAL são respeitados. São ainda propostas algumas alterações baseadas em pareceres técnicos que acompanham os relatórios elaborados pela LUSÁGUA e um estudo elaborada pela ECOserviços em Fevereiro de 2010 onde se obtêm eficiências de etapas de tratamentos com base em testes laboratoriais e testes realizados na própria EPTAL.