Dimensionamento de Sistemas de Compensação do Fator de Potência com Filtragem Passiva de Harmónicos

A eficiência energética tem um papel de importância crescente devido a questões ambientais e ao aumento dos custos energéticos. Recentemente foram tomadas medidas para regular o consumo e o fornecimento de energia reativa em Portugal, que tornaram mais rigorosas as condições de faturação. O custo crescente da energia e a implementação das smart grids apontam para um futuro de maior rigor sobre a utilização da energia reativa. Não será de estranhar que as regras de faturação sejam mais severas daqui a uns anos. O desenvolvimento tecnológico nas áreas da análise da energia e nas formas de controlo da compensação de energia reativa permitem resultados muito mais eficazes que aqueles apresentados pelos vulgares sistemas a contactores que constituem a maioria dos cenários. Apesar de terem um custo inicial superior, os sistemas de compensação do fator de potência com filtragem passiva de harmónicos, desde que projetados corretamente, trazem vantagens evidentes na sua exploração a longo prazo. Com este trabalho pretende-se promover a sensibilização para o uso de sistemas mais eficientes na compensação de energia reativa e para que estes sejam projetados mais à medida das necessidades de cada local. Também se demonstra a extrema importância da adequação destes sistemas à qualidade de energia do local, principalmente em termos de conteúdo harmónico. Desta forma, os sistemas serão mais flexíveis em termos de utilização e possibilitam a sua adaptação às necessidades mesmo que as regras de faturação de energia reativa se tornem mais rigorosas.

Produção Sustentável em BT- Análise de Características de Contadores Inteligentes

A crescente necessidade de reduzir a dependência energética e a emissão de gases de efeito de estufa levou à adoção de uma série de políticas a nível europeu com vista a aumentar a eficiência energética e nível de controlo de equipamentos, reduzir o consumo e aumentar a percentagem de energia produzida a partir de fontes renováveis. Estas medidas levaram ao desenvolvimento de duas situações críticas para o setor elétrico: a substituição das cargas lineares tradicionais, pouco eficientes, por cargas não-lineares mais eficientes e o aparecimento da produção distribuída de energia a partir de fontes renováveis. Embora apresentem vantagens bem documentadas, ambas as situações podem afetar negativamente a qualidade de energia elétrica na rede de distribuição, principalmente na rede de baixa tensão onde é feita a ligação com a maior parte dos clientes e onde se encontram as cargas não-lineares e a ligação às fontes de energia descentralizadas. Isto significa que a monitorização da qualidade de energia tem, atualmente, uma importância acrescida devido aos custos relacionados com perdas inerentes à falta de qualidade de energia elétrica na rede e à necessidade de verificar que determinados parâmetros relacionados com a qualidade de energia elétrica se encontram dentro dos limites previstos nas normas e nos contratos com clientes de forma a evitar disputas ou reclamações. Neste sentido, a rede de distribuição tem vindo a sofrer alterações a nível das subestações e dos postos de transformação que visam aumentar a visibilidade da qualidade de energia na rede em tempo real. No entanto, estas medidas só permitem monitorizar a qualidade de energia até aos postos de transformação de média para baixa tensão, não revelando o estado real da qualidade de energia nos pontos de entrega ao cliente. A monitorização nestes pontos é feita periodicamente e não em tempo real, ficando aquém do necessário para assegurar a deteção correta de problemas de qualidade de energia no lado do consumidor. De facto, a metodologia de monitorização utilizada atualmente envolve o envio de técnicos ao local onde surgiu uma reclamação ou a um ponto de medição previsto para instalar um analisador de energia que permanece na instalação durante um determinado período de tempo. Este tipo de monitorização à posteriori impossibilita desde logo a deteção do problema de qualidade de energia que levou à reclamação, caso não se trate de um problema contínuo. Na melhor situação, o aparelho poderá detetar uma réplica do evento, mas a larga percentagem anomalias ficam fora deste processo por serem extemporâneas. De facto, para detetar o evento que deu origem ao problema é necessário monitorizar permanentemente a qualidade de energia. No entanto este método de monitorização implica a instalação permanente de equipamentos e não é viável do ponto de vista das empresas de distribuição de energia já que os equipamentos têm custos demasiado elevados e implicam a necessidade de espaços maiores nos pontos de entrega para conter os equipamentos e o contador elétrico. Uma alternativa possível que pode tornar viável a monitorização permanente da qualidade de energia consiste na introdução de uma funcionalidade de monitorização nos contadores de energia de determinados pontos da rede de distribuição. Os contadores são obrigatórios em todas as instalações ligadas à rede, para efeitos de faturação. Tradicionalmente estes contadores são eletromecânicos e recentemente começaram a ser substituídos por contadores inteligentes (smart meters), de natureza eletrónica, que para além de fazer a contagem de energia permitem a recolha de informação sobre outros parâmetros e aplicação de uma serie de funcionalidades pelo operador de rede de distribuição devido às suas capacidades de comunicação. A reutilização deste equipamento com finalidade de analisar a qualidade da energia junto dos pontos de entrega surge assim como uma forma privilegiada dado que se trata essencialmente de explorar algumas das suas características adicionais. Este trabalho tem como objetivo analisar a possibilidade descrita de monitorizar a qualidade de energia elétrica de forma permanente no ponto de entrega ao cliente através da utilização do contador elétrico do mesmo e elaborar um conjunto de requisitos para o contador tendo em conta a normalização aplicável, as características dos equipamentos utilizados atualmente pelo operador de rede e as necessidades do sistema elétrico relativamente à monitorização de qualidade de energia.

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.

Multi-agent simulation of continental, regional, and micro electricity markets

Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.

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.

Combined heat and power and consumption optimization in a SCADA-based system

The operation of power systems in a Smart Grid (SG) context brings new opportunities to consumers as active players, in order to fully reach the SG advantages. In this context, concepts as smart homes or smart buildings are promising approaches to perform the optimization of the consumption, while reducing the electricity costs. This paper proposes an intelligent methodology to support the consumption optimization of an industrial consumer, which has a Combined Heat and Power (CHP) facility. A SCADA (Supervisory Control and Data Acquisition) system developed by the authors is used to support the implementation of the proposed methodology. An optimization algorithm implemented in the system in order to perform the determination of the optimal consumption and CHP levels in each instant, according to the Demand Response (DR) opportunities. The paper includes a case study with several scenarios of consumption and heat demand in the context of a DR event which specifies a maximum demand level for the consumer.

Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

Maximum penetration of microgeneration photovoltaic panels in distribution network

In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.

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.

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.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Reliable and Fast Hand-Offs in Low-Power Wireless Networks

Hand-off (or hand-over), the process where mobile nodes select the best access point available to transfer data, has been well studied in wireless networks. The performance of a hand-off process depends on the specific characteristics of the wireless links. In the case of low-power wireless networks, hand-off decisions must be carefully taken by considering the unique properties of inexpensive low-power radios. This paper addresses the design, implementation and evaluation of smart-HOP, a hand-off mechanism tailored for low-power wireless networks. This work has three main contributions. First, it formulates the hard hand-off process for low-power networks (such as typical wireless sensor networks - WSNs) with a probabilistic model, to investigate the impact of the most relevant channel parameters through an analytical approach. Second, it confirms the probabilistic model through simulation and further elaborates on the impact of several hand-off parameters. Third, it fine-tunes the most relevant hand-off parameters via an extended set of experiments, in a realistic experimental scenario. The evaluation shows that smart-HOP performs well in the transitional region while achieving more than 98 percent relative delivery ratio and hand-off delays in the order of a few tens of a milliseconds.

SCADA House Intelligent Management for Energy Efficiency Analysis in Domestic Consumers

The implementation of smart homes allows the domestic consumer to be an active player in the context of the Smart Grid (SG). This paper presents an intelligent house management system that is being developed by the authors to manage, in real time, the power consumption, the micro generation system, the charge and discharge of the electric or plug-in hybrid vehicles, and the participation in Demand Response (DR) programs. The paper proposes a method for the energy efficiency analysis of a domestic consumer using the SCADA House Intelligent Management (SHIM) system. The main goal of the present paper is to demonstrate the economic benefits of the implemented method. The case study considers the consumption data of some real cases of Portuguese house consumption over 30 days of June of 2012, the Portuguese real energy price, the implementation of the power limits at different times of the day and the economic benefits analysis.