Controlo da velocidade e posição de um tapete rolante

A utilização eficiente da energia é essencial para a competitividade económica de um país. Sendo a intensidade energética de Portugal elevada, onde a utilização de motores elétricos, absorve cerca de metade da energia elétrica consumida na indústria, a utilização de conversores eletrónicos de potência permite obter economias de energia. Nesta tese pretende-se controlar a velocidade e o posicionamento de um tapete rolante através da utilização de um conversor eletrónico de potência. Na fundamentação teórica são referidos os conceitos de variação da tensão e frequência, controle escalar e vetorial, modelação por largura de pulso (PWM) assim como a retificação e ondulação da tensão de um variador de velocidades. Na parte prática será utilizado um servo motor, controlado por um variador eletrónico de velocidades, para efetuar o referido projeto. É ainda objeto desta tese o estudo dos parâmetros fundamentais assim como a pesquisa dos parâmetros a utilizar para o desempenho pretendido.

Contributo da manutenção técnica de edifícios para a sustentabilidade

A manutenção, durante vários anos, traduziu-se num conceito paliativo de instalações e equipamentos, o que se veio a revelar como uma atitude negligente perante o Homem e o Ambiente. As preocupações ambientais estão na ordem do dia e têm sido muitas as vozes que se têm levantado para que o consumo de energia seja mais equilibrado e para que as emissões de CO2 diminuam de forma a preservar o Planeta. De acordo com a resolução do Conselho Europeu, em 2007 (1), foi apresentado um pacote de propostas que visam a sustentabilidade e estimulam a Eficiência Energética (EE), com o objectivo de reduzir os consumos energéticos dos edifícios, quer estes sejam novos ou reabilitados. Segundo a Direcção Geral de Energia e Geologia os edifícios são responsáveis por 60% dos consumos de energia eléctrica, consumo esse que pode ser reduzido em mais de 50%, através de medidas de EE, traduzindo-se numa redução de 400 milhões de toneladas de CO2 por ano. (2) Para além de medidas de EE, também as práticas de manutenção preventiva podem contribuir para a diminuição dos consumos energéticos e de emissões de CO2. Segundo o Institute for Building Efficiency práticas de manutenção preventiva em equipamentos de Aquecimento Ventilação e Ar Condicionado (AVAC) reduzem os consumos energéticos de 10 a 20% e, em contrapartida, a negligência na execução da manutenção pode aumentar os consumos energéticos de 30 a 60%. (3) Uma outra análise de valores a ter em conta, é a Intensidade Energética (IE). Leia-se IE como sendo o valor global da energia consumida num país a dividir pelo seu produto interno bruto. A contribuição do sector dos serviços para a IE nacional era de 17% no ano de 2005. (4) Se a estes dados acrescentarmos que 70% dessa energia é consumida por equipamentos AVAC (5) e que práticas de manutenção reduzem esses valores entre 10 a 20%, pode concluir-se que a redução de custos energéticos associada à manutenção preventiva é efectiva e significativa. Apresentando um cenário ideal e hipotético, se ao contributo do sector dos serviços, para a IE nacional, se isolar o valor referente a equipamentos de AVAC, obtem-se uma IE de aproximadamente 12%. Se adicionalmente se considerar uma taxa de redução, relativa à execução da manutenção, entre 10 e 20%, Portugal obteria uma IE, relativamente aos consumos energéticos em edificios de serviços, não de 17% mas sim entre 14,6% e 15,8%. Neste trabalho pretende-se comprovar que um plano de actividades de manutenção equilibrado, monitorizado, e gerido de forma eficaz e funcional, é uma ferramenta fundamental no cumprimento de objectivos e metas europeias traçadas, que se reúnem num objectivo comum de preservação do planeta. A adopção deste tipo de medidas contribuirá para a racionalização dos consumos energéticos e para o aumento da vida útil dos equipamentos, bem como para a melhoria do desempenho económico e financeiro das organizações, tal como se poderá ler mais à frente neste trabalho. Será também analisado um caso prático, verificando a eficácia das medidas tomadas durante as intervenções preventivas de manutenção, sendo que para isso será estudado o comportamento de um equipamento, antes e após a realização de tarefas de manutenção preventiva. Tentar-se-á, junto de gestores de edifícios, recolher a opinião que têm sobre a importância da manutenção. Ao longo de toda a pesquisa foi possível consolidar a hipótese formulada inicialmente no que concerne ao contributo da manutenção para a sustentabilidade, quer através da revisão da literatura, quer nos testes efectuados a equipamentos. Foi possível confirmar que um plano de manutenção ajustado, monitorizado e cumprido é uma ferramenta na diminuição dos consumos energéticos, aumento da vida útil de equipamentos e por sua vez na diminuição de emissões de CO2. Verificou-se também que o controlo de poluentes e ventilação adequada dos edifícios são uma ferramenta essencial para a qualidade do ar interior, parâmetros facilmente controlados nas actividades de manutenção. O contributo das opiniões recolhidas entre os gestores de edifícios, para este estudo, foi também bastante importante, uma vez que todos eles reconhecem o papel importante da manutenção, mas nem todos estão sensibilizados para o seu papel na sustentabilidade do planeta. Nesta dissertação é deixado um alerta: o crescimento da população mundial e a consequente utilização de recursos naturais que são finitos, não sendo controlado de uma forma sustentada, pode resultar na destruição de um planeta único. O papel negativo do Homem nas alterações climáticas é inequívoco e é necessário melhorar a sua relação com o Ambiente. Cada ser humano está inserido na sua comunidade e dentro dela tem a sua função, cabe a cada um exercer esta responsabilidade nas suas actividades do dia-a-dia.

Short-term wind forecasting for energy resources scheduling

This paper proposes a wind power forecasting methodology based on two methods: direct wind power forecasting and wind speed forecasting in the first phase followed by wind power forecasting using turbines characteristics and the aforementioned wind speed forecast. The proposed forecasting methodology aims to support the operation in the scope of the intraday resources scheduling model, namely with a time horizon of 5 minutes. This intraday model supports distribution network operators in the short-term scheduling problem, in the smart grid context. A case study using a real database of 12 months recorded from a Portuguese wind power farm was used. The results show that the straightforward methodology can be applied in the intraday model with high wind speed and wind power accuracy. The wind power forecast direct method shows better performance than wind power forecast using turbine characteristics and wind speed forecast obtained in first phase.

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is 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 mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a 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.

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.

Residential energy resources management by a SCADA system in case of excess wind generation

The end consumers in a smart grid context are seen as active players. The distributed generation resources applied in smart home system as a micro and small-scale systems can be wind generation, photovoltaic and combine heat and power facility. The paper addresses the management of domestic consumer resources, i.e. wind generation, solar photovoltaic, combined heat and power, electric vehicle with gridable capability and loads, in a SCADA system with intelligent methodology to support the user decision in real time. The main goal is to obtain the better management of excess wind generation that may arise in consumer’s distributed generation resources. The optimization methodology is performed in a SCADA House Intelligent Management context and the results are analyzed to validate the SCADA system.

Energy efficiency analysis considering the use of an intelligent systems management in a smart home

In this abstract is presented an energy management system included in a SCADA system existent in a intelligent home. The system control the home energy resources according to the players definitions (electricity consumption and comfort levels), the electricity prices variation in real time mode and the DR events proposed by the aggregators.

Energy and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

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.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

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.