Real Time Pricing Approaches to Deal With Unexpected Wind Power Variations

The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs.

Analysis of Consumption Data to Detect Commercial Losses Using Performance Evaluation Methods in a Smart Grid

Electric power networks, namely distribution networks, have been suffering several changes during the last years due to changes in the power systems operation, towards the implementation of smart grids. Several approaches to the operation of the resources have been introduced, as the case of demand response, making use of the new capabilities of the smart grids. In the initial levels of the smart grids implementation reduced amounts of data are generated, namely consumption data. The methodology proposed in the present paper makes use of demand response consumers’ performance evaluation methods to determine the expected consumption for a given consumer. Then, potential commercial losses are identified using monthly historic consumption data. Real consumption data is used in the case study to demonstrate the application of the proposed method.

Real-time Energy Resource Scheduling considering a Real Portuguese Scenario

The development in power systems and the introduction of decentralized generation and Electric Vehicles (EVs), both connected to distribution networks, represents a major challenge in the planning and operation issues. This new paradigm requires a new energy resources management approach which considers not only the generation, but also the management of loads through demand response programs, energy storage units, EVs and other players in a liberalized electricity markets environment. This paper proposes a methodology to be used by Virtual Power Players (VPPs), concerning the energy resource scheduling in smart grids, considering day-ahead, hour-ahead and real-time scheduling. The case study considers a 33-bus distribution network with high penetration of distributed energy resources. The wind generation profile is based on a real Portuguese wind farm. Four scenarios are presented taking into account 0, 1, 2 and 5 periods (hours or minutes) ahead of the scheduling period in the hour-ahead and realtime scheduling.

A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

Modelação numérica de uma caldeira doméstica a pellets

A biomassa é uma das fontes de energia renovável com maior potencial em Portugal, sendo a capacidade de produção de pellets de biomassa atualmente instalada superior a 1 milhão de toneladas/ano. Contudo, a maioria desta produção destina-se à exportação ou à utilização em centrais térmicas a biomassa, cujo crescimento tem sido significativo nos últimos anos, prevendo-se que a capacidade instalada em 2020 seja de aproximadamente 250 MW. O mercado português de caldeiras a pellets é bastante diversificado. O estudo que realizamos permitiu concluir que cerca de 90% das caldeiras existentes no mercado português têm potências inferiores a 60 kW, possuindo na sua maioria grelha fixa (81%), com sistema de ignição eléctrica (92%) e alimentação superior do biocombustível sólido (94%). O objetivo do presente trabalho foi o desenvolvimento de um modelo para simulação de uma caldeira a pellets de biomassa, que para além de permitir otimizar o projeto e operação deste tipo de equipamento, permitisse avaliar as inovações tecnológicas nesta área. Para tal recorreu-se o BiomassGasificationFoam, um código recentemente publicado, e escrito para utilização com o OpenFOAM, uma ferramenta computacional de acesso livre, que permite a simulação dos processos de pirólise, gasificação e combustão de biomassa. Este código, que foi inicialmente desenvolvido para descrever o processo de gasificação na análise termogravimétrica de biomassa, foi por nós adaptado para considerar as reações de combustão em fase gasosa dos gases libertados durante a pirólise da biomassa (recorrendo para tal ao solver reactingFoam), e ter a possibilidade de realizar a ignição da biomassa, o que foi conseguido através de uma adaptação do código de ignição do XiFoam. O esquema de ignição da biomassa não se revelou adequado, pois verificou-se que a combustão parava sempre que a ignição era inativada, independentemente do tempo que ela estivesse ativa. Como alternativa, usaram-se outros dois esquemas para a combustão da biomassa: uma corrente de ar quente, e uma resistência de aquecimento. Ambos os esquemas funcionaram, mas nunca foi possível fazer com que a combustão fosse autossustentável. A análise dos resultados obtidos permitiu concluir que a extensão das reações de pirólise e de gasificação, que são ambas endotérmicas, é muito pequena, pelo que a quantidade de gases libertados é igualmente muito pequena, não sendo suficiente para libertar a energia necessária à combustão completa da biomassa de uma maneira sustentável. Para tentar ultrapassar esta dificuldade foram testadas várias alternativas, , que incluíram o uso de diferentes composições de biomassa, diferentes cinéticas, calores de reação, parâmetros de transferência de calor, velocidades do ar de alimentação, esquemas de resolução numérica do sistema de equações diferenciais, e diferentes parâmetros dos esquemas de resolução utilizados. Todas estas tentativas se revelaram infrutíferas. Este estudo permitiu concluir que o solver BiomassGasificationFoam, que foi desenvolvido para descrever o processo de gasificação de biomassa em meio inerte, e em que a biomassa é aquecida através de calor fornecido pelas paredes do reator, aparentemente não é adequado à descrição do processo de combustão da biomassa, em que a combustão deve ser autossustentável, e em que as reações de combustão em fase gasosa são importantes. Assim, é necessário um estudo mais aprofundado que permita adaptar este código à simulação do processo de combustão de sólidos porosos em leito fixo.

Auditorias energéticas em ambiente industrial

Gestão de Energia e Sustentabilidade são os pilares em que assenta esta dissertação, realizada no âmbito da Energia Elétrica em Ambiente Industrial. Neste sentido, deve entender-se “Gestão de Energia” como o planeamento de operações nas unidades de produção e de consumo. Tem como objetivos a conservação dos recursos, proteção climática e redução de custos, para que seja possível o acesso permanente à energia de que necessitamos. “Sustentabilidade”, por definição, é uma caraterística ou condição de um processo ou de um sistema que permite a sua permanência, até um determinado nível, por um determinado prazo. A Indústria Têxtil, da região do Vale do Ave, por ser extensa e muito heterogénea, quer na qualidade, quer na dimensão e nos recursos que utiliza, apresentou-se como uma oportunidade para aplicar os conhecimentos adquiridos, nas diversas disciplinas do Mestrado em Engenharia Electrotécnica - Área de Sistemas Eléctricos de Energia e como meio condutor à tentativa de optimização e racionalização do consumo de Energia Elétrica no Sector. O modelo encontrado para dar uma resposta satisfatória ao inicialmente proposto foi a Auditoria Energética. Neste sentido, foram realizadas visitas às instalações industriais, para o levantamento e recolha de informação, que posteriormente viria a ser analisada e, com base na mesma, tentou apresentar-se um conjunto de soluções que visassem a eficiência Energética do sector. Com o decorrer das visitas, surgiu a necessidade de criar um modelo, que servisse de guia da auditoria. Algo que seria um bloco de notas, mas específico, de forma a não perder a informação recolhida. Então foi desenvolvida uma aplicação para IPAD/IPHONE, o que permite também a recolha e armazenamento de fotografias, que aqui tem um papel fundamental. Salienta-se que as expectativas foram ao encontro do esperado, pois o que se encontrou foi um número significativo de empresas a precisar deste contributo. Atuando no “combate” ao consumo desnecessário e ao desperdício, é estar a contribuir ativa e positivamente, no desenvolvimento próspero da temática de Sustentabilidade Energética.

Multi-agent simulation of competitive electricity markets: Autonomous systems cooperation for European market modeling

The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.

Energia Solar Fotovoltaica como Fonte Alternativa de Produção de Energia Elétrica em Angola

Neste trabalho é efetuado o dimensionamento de sistemas fotovoltaicos para serem instalados em edificações localizadas em Angola com o objetivo de analisar a produção de energia elétrica através de sistemas fotovoltaicos. Utilizando o software PVsyst na versão 6.3.2 foram dimensionados três sistemas fotovoltaicos, dois sistemas destinados a ser instalados numa residência, um ligado à rede e o outro autónomo e por fim um sistema fotovoltaico ligado à rede para uma instalação industrial. A determinação dos custos de investimento nos três sistemas foi obtida de forma aproximada, tendo como base preços dos equipamentos no mercado Português e considerando os custos de importação de mercadorias no mercado Angolano. Para os sistemas ligados à rede é analisada a rentabilidade financeira do investimento durante o período de vida útil dos módulos fotovoltaicos considerando três cenários distintos. No primeiro cenário o valor da remuneração pela energia vendida pelo produtor é igual ao valor pago pela energia comprada. No segundo e terceiros cenário de análise económica pretende-se encontrar uma tarifa de energia que torne o investimento rentável com um período de amortização de 7 e 12 anos respetivamente.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

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.

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.

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.

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.