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).

Reactive power management strategies in future smart grids

The reactive power management in distribution network with large penetration of distributed energy resources is an important task in future power systems. The control of reactive power allows the inclusion of more distributed recourses and a more efficient operation of distributed network. Currently, the reactive power is only controlled in large power plants and in high and very high voltage substations. In this paper, several reactive power control strategies considering a smart grids paradigm are proposed. In this context, the management of distributed energy resources and of the distribution network by an aggregator, namely Virtual Power Player (VPP), is proposed and implemented in a MAS simulation tool. The proposed methods have been computationally implemented and tested using a 32-bus distribution network with intensive use of distributed resources, mainly the distributed generation based on renewable resources. Results concerning the evaluation of the reactive power management algorithms are also presented and compared.

Reactive power compensation by EPSO technique

This paper presents a methodology to address reactive power compensation using Evolutionary Particle Swarm Optimization (EPSO) technique programmed in the MATLAB environment. The main objective is to find the best operation point minimizing power losses with reactive power compensation, subjected to all operational constraints, namely full AC power flow equations, active and reactive power generation constraints. The methodology has been tested with the IEEE 14 bus test system demonstrating the ability and effectiveness of the proposed approach to handle the reactive power compensation problem.

Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

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.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

Bancada didáctica para simulação de uma Unidade de Microgeração

Neste trabalho é desenvolvida uma bancada didáctica que permite simular o funcionamento de um sistema de microgeração. A bancada inclui uma máquina síncrona responsável pela geração de energia eléctrica acoplada a uma máquina de indução que simula a máquina primária. A máquina de indução é controlada por um sistema electrónico de controlo de potência (variador de velocidade) que permite manter constante a velocidade de rotação e consequentemente a frequência da tensão gerada pela máquina síncrona. Por sua vez, a excitação da máquina síncrona é controla por uma fonte de tensão externa. A parametrização e controlo do variador de velocidade, assim como o controlo da fonte de tensão externa, são feitos a partir dum software que corre num PC, que também monitoriza a tensão gerada pela máquina síncrona. Este software é ainda responsável pela interface com o utilizador. O software desenvolvido permite manter as características da tensão gerada pela máquina síncrona independentemente da carga imposta.

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Dimensionamento do Sistema Híbrido para Alimentação de Energia Elétrica da Escola Rural de Nangade (Cabo Delgado)

Os combustíveis fósseis, como o carvão, o petróleo e o gás, constituem fontes de energia que em breve se esgotarão e que são demasiado caras para serem desperdiçadas pelas centrais elétricas na produção de electricidade. Para além desse facto, existem outros argumentos (sobretudo económicos) que inviabilizam a utilização destas fontes de energia em algumas regiões, abrindo caminho a fontes de energia alternativas (e.g. solar, eólica, biomassa, mini-hídricas, geotérmicas, etc) e preferencialmente com contornos locais. No caso particular de Moçambique, tem-se verificado um interesse crescente por parte do governo e de várias ONGs na promoção do uso de energias alternativas para as zonas onde a energia convencional não chega e não chegará, devido aos custos muito elevados que esse processo acarretaria. Esta dissertação apresenta um estudo aprofundado do dimensionamento dum sistema híbrido de geração de energia elétrica envolvendo gerador FV e grupo eletrogéneo de emergência para a Escola Rural da Nangade, situada no Distrito de Nangade, na Província do Cabo Delgado. São também descritos os diversos componentes e as tecnologias associadas a um sistema deste género, com a inclusão de sistemas inteligentes de controlo de energia com a utilização de inversores bidireccionais (inversores de bateria e carregadores) para sistemas isolados. Os resultados são apresentados de forma a facilitar a aplicação e montagem deste tipo de sistemas in loco. Espera-se que esta dissertação possa servir de base no futuro próximo, para a implementação deste tipo de sistemas para permitir a melhoria da qualidade de ensino através de melhores infraestruturas, democratizando desta forma o acesso à educação para as crianças das zonas rurais das várias províncias de Moçambique. Como as energias renováveis são parte integrante do Sistema Elétrico Nacional, apresenta-se resumidamente, no anexo 17, o “Plano de Desenvolvimento na Área de Energia de Moçambique”.

Using an ambient intelligent architecture for developing an intelligent tutoring system for training operators of power system control centres

This paper describes an architecture conceived to integrate Power Sys-tems tools in a Power System Control Centre, based on an Ambient Intelligent (AmI) paradigm. This architecture is an instantiation of the generic architecture proposed in [1] for developing systems that interact with AmI environments. This architecture has been proposed as a consequence of a methodology for the inclu-sion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Sys-tems Research for Ambient Intelligence). The architecture presented in the paper will be able to integrate two applications in the control room of a power system transmission network. The first is SPARSE expert system, used to get diagnosis of incidents and to support power restoration. The second application is an Intelligent Tutoring System (ITS) incorporating two training tools. The first tutoring tool is used to train operators to get the diagnosis of incidents. The second one is another tutoring tool used to train operators to perform restoration procedures.

Training control centers' operators in incident diagnosis and power restoration using intelligent tutoring systems

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

Cyber-ambient intelligent training of operators in power systems control centres

Cyber-Physical Systems and Ambient Intelligence are two of the most important and emerging paradigms of our days. The introduction of renewable sources gave origin to a completely different dimension of the distribution generation problem. On the other hand, Electricity Markets introduced a different dimension in the complexity, the economic dimension. Our goal is to study how to proceed with the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

An intelligent tutoring system for operators’ training in power system control centres

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, taking into account context awareness and the unobtrusive integration in the working environment.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

Control and comparison of the antioxidant capacity of beers

The purpose of the present work is to determine the antioxidant capacity (AC) of 27 commercial beers. The AC indicates the degree of protection of a certain organism against oxidative damage provoked by reactive oxygen and nitrogen species. Assays were carried out by the following methods: (i) total radical trapping antioxidant parameter (TRAP); (ii) trolox equivalent antioxidant capacity (TEAC); (iii) trolox equivalent antioxidant capacity (DPPH); (iv) ferric-ion reducing antioxidant parameter (FRAP); (v) cupric reducing antioxidant capacity (CUPRAC); (vi) oxygen radical absorbance capacity (ORAC). Ascorbic acid (AA), gallic acid (GA) and trolox (TR) were used as standards. All beers showed antioxidant power, but a wide range of ACs was observed. The effect of several factors upon these differences was studied. Statistical differences were found between ACs of beers of different colours. ORAC method provided always higher experimental ACs, of significant statistical differences to other assays.