Automatic Electricity Markets Data Extraction for Realistic Multi-agent Simulations

Electricity markets worldwide suffered profound transformations. The privatization of previously nationally owned systems; the deregulation of privately owned systems that were regulated; and the strong interconnection of national systems, are some examples of such transformations [1, 2]. In general, competitive environments, as is the case of electricity markets, require good decision-support tools to assist players in their decisions. Relevant research is being undertaken in this field, namely concerning player modeling and simulation, strategic bidding and decision-support.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

Programas de self-management em pacientes com DPOC: uma revisão sistemática

Introdução: Programas de self-management têm como objectivo habilitar os pacientes com estratégias necessárias para levar a cabo procedimentos específicos para a patologia. A última revisão sistemática sobre selfmanagament em DPOC foi realizada em 2007, concluindo-se que ainda não era possível fornecer dados claros e suficientes acerca de recomendações sobre a estrutura e conteúdo de programas de self-managament na DPOC. A presente revisão tem o intuito de complementar a análise da revisão anterior, numa tentativa de inferir a influência do ensino do self-management na DPOC. Objectivos: verificar a influência dos programas de self-management na DPOC, em diversos indicadores relacionados com o estado de saúde do paciente e na sua utilização dos serviços de saúde. Estratégia de busca: pesquisa efectuada nas bases de dados PubMed e Cochrane Collaboration (01/01/2007 – 31/08/2010). Palavras-chave: selfmanagement education, self-management program, COPD e pulmonary rehabilitation. Critérios de Selecção: estudos randomizados sobre programas de selfmanagement na DPOC. Extracção e Análise dos Dados: 2 investigadores realizaram, independentemente, a avaliação e extracção de dados de cada artigo. Resultados: foram considerados 4 estudos randomizados em selfmanagement na DPOC nos quais se verificaram benefícios destes programas em diversas variáveis: qualidade de vida a curto e médio prazo, utilização dos diferentes recursos de saúde, adesões a medicação de rotina, controle das exacerbações e diminuição da sintomatologia. Parece não ocorrer alteração na função pulmonar e no uso de medicação de emergência, sendo inconclusivo o seu efeito na capacidade de realização de exercício. Conclusões: programas de self-management aparentam ter impacto positivo na qualidade de vida, recurso a serviços de saúde, adesão à medicação, planos de acção e níveis de conhecimento da DPOC. Discrepâncias nos critérios de selecção das amostras utilizadas, períodos de seguimento desiguais, consistência das variáveis mensuradas, condicionam a informação disponibilizada sobre este assunto.

A eficácia e segurança da fisioterapia respiratória no tratamento da bronquiolite aguda em crianças até 2 anos de idade: revisão sistemática

Contexto: a bronquiolite aguda é a principal patologia a afectar a criança nos primeiros 2 anos de vida, a fisioterapia respiratória é uma intervenção terapêutica utilizada com a intenção de melhorar o curso desta doença mantendo-se a incerteza sobre a sua eficácia. Objectivo: determinar a eficácia e segurança da fisioterapia respiratória em crianças com menos de 2 anos com bronquiolite aguda. Fontes de Informação: Medline (1966 a Agosto 2010), EMBASE(1990 a Agosto 2010), Pedro e Lilacs (1982 a Agosto 2010). Outra fonte de informação incluiu a bibliografia dos estudos obtidos. Selecção de estudos: estudos experimentais comparando a fisioterapia respiratória com cuidados habituais, em crianças com menos de 2 anos e bronquiolite aguda, em ventilação espontânea, em qualquer contexto. Estudos pré-experimentais ou observacionais com os mesmos participantes e intervenções foram admitidos complementarmente aos experimentais. Extracção de dados e análise: um investigador extraiu os dados dos artigos obtidos e avaliou o risco de viés. A eficácia e segurança da fisioterapia respiratória foram determinadas pelos seguintes outcomes: duração do internamento hospitalar ou do evento, variação de scores de severidade clínica, saturação periférica e suplementação de oxigénio, recidivas, recurso a antibióticos e efeitos deletérios ou deterioração clínica reportada. Síntese de dados: 6 estudos experimentais foram admitidos. As suas amostras provinham de criança internadas em hospital. As técnicas de fisioterapia respiratória foram comparadas com cuidados habituais. Nenhum estudo evidenciou melhoria dos outcomes de interesse na comparação entre grupos, excepto avaliações de curta duração da saturação periférica de oxigénio e scores de severidade clínica. 1 estudo reportou uma percentagem significativamente maior no grupo submetido a fisioterapia respiratória de crianças que vomitaram, tiveram uma desestabilização respiratória transitória, e na percepção de stress da criança pelos cuidadores. São relatadas ainda fracturas costais a causa de fisioterapia respiratória. Limitações: o risco de viés era alto em 2 estudos, baixo num estudo e indeterminado nos restantes. Conclusões: aparentemente a fisioterapia respiratória não é eficaz e pode produzir efeitos deletérios importantes, mas a evidência é pobre, carecendo de novos estudos.

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

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.

Multi-criteria short-term maintenance outage scheduling in smart distribution systems

Effective legislation and standards for the coordination procedures between consumers, producers and the system operator supports the advances in the technologies that lead to smart distribution systems. In short-term (ST) maintenance scheduling procedure, the energy producers in a distribution system access to the long-term (LT) outage plan that is released by the distribution system operator (DSO). The impact of this additional information on the decision-making procedure of producers in ST maintenance scheduling is studied in this paper. The final ST maintenance plan requires the approval of the DSO that has the responsibility to secure the network reliability and quality, and other players have to follow the finalized schedule. Maintenance scheduling in the producers’ layer and the coordination procedure between them and the DSO is modelled in this paper. The proposed method is applied to a 33-bus distribution system.

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.

Adaptive tool for automatic data collection of real electricity markets

The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.

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.

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.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

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.

Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems

Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .