Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Intelligent training in control centres based on an ambient intelligence paradigm

This article describes a new approach in 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.

Demsi - a demand response simulator in the context of intensive use of distributed generation

Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.

Dispachability improvement of wind generation by the virtual power producers

Nowadays, there is a growing environmental concern about were the energy that we use comes from, bringing the att ention on renewable energies. However, the use and trade of renewable e nergies in the market seem to be complicated because of the lack of guara ntees of generation, mainly in the wind farms. The lack of guarantees is usually addressed by using a reserve generation. The aggregation of DG p lants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of wind generation technologies, making them valuable in electricity markets. This paper presents some resul ts obtained with a simulation tool (ViProd) developed to support VPPs in the analysis of their operation and management methods and of their strat egies effects.

Comparison between deterministic and meta-heuristic methods applied to ancillary services dispatch

This paper proposes two meta-heuristics (Genetic Algorithm and Evolutionary Particle Swarm Optimization) for solving a 15 bid-based case of Ancillary Services Dispatch in an Electricity Market. A Linear Programming approach is also included for comparison purposes. A test case based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is used to demonstrate that the use of meta-heuristics is suitable for solving this kind of optimization problem. Faster execution times and lower computational resources requirements are the most relevant advantages of the used meta-heuristics when compared with the Linear Programming approach.

Ancillary services market clearing simulation: a comparison between deterministic and heuristic methods

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

AI in power systems and energy markets

In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.

Estratégias de oferta em leilões simétricos no âmbito dos mercados liberalizados de electricidade

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Demand response in future power systems management – a conceptual framework and simulation tool

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Avaliação energética de uma escola

Mestrado em Engenharia Química

Estudo da eficiência de sistemas fotovoltaicos

Mestrado em Engenharia Química. Ramo optimização energética na indústria química

Gestão do risco em mercados de energia eléctrica recorrendo ao VaR por simulação de Monte Carlo

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia.

Análise e optimização dos consumos de utilidades (vapor e energia eléctrica) na Petibol – Embalagens de Plásticos, S.A.

Mestrado em Engenharia Química. Ramo optimização energética na indústria química.

Emissões de carbono: caracterização do perfil de emissões de gases de efeito de estufa associadas à Monteiro, Ribas - Embalagens Flexíveis, S.A.

A presente dissertação tem como principal objectivo estimar as emissões de carbono resultantes das actividades da Monteiro, Ribas- Embalagens Flexíveis, S.A. A realização do inventário de gases de efeito estufa permite que a Monteiro, Ribas- Embalagens Flexíveis, S.A, identifique quais as suas fontes emissoras e quantifique as emissões de gases de efeito estufa, permitindo criar estratégias de redução das mesmas. A elaboração do inventário foi fundamentada nas directrizes do Greenhouse Gas Protocol, obedecendo aos princípios de relevância, integrabilidade, consistência, transparência e exactidão. A metodologia adoptada utiliza factores de emissão documentados para efectuar o cálculo das emissões de gases de efeito de estufa (GEE). Estes factores são rácios que relacionam as emissões de GEE com dados de actividade específicos para cada fonte de emissão. Como emissões directas (âmbito 1), foram quantificadas as emissões provenientes do uso de gás natural nas caldeiras, consumo de vapor e de água quente, e as emissões do veículo comercial da empresa. Como emissões indirectas de âmbito 2, incluem-se as resultantes da electricidade consumida. As emissões indirectas estimadas de âmbito 3 referem-se, no caso em estudo, ao transporte de resíduos, ao deslocamento de funcionários para a empresa e às viagens de negócio. Face ao tipo de emissões identificadas, criou-se uma ferramenta de cálculo que contém todos os valores de factores de emissão que podem ser utilizados em função das características específicas dos dados de actividade relativos às várias fontes emissoras da Empresa. Esta ferramenta permitirá, no futuro, aperfeiçoar o cálculo das emissões, a partir de uma melhor sistematização da informação disponível. Com este trabalho também foi possível identificar a necessidade de recolher e organizar alguma informação complementar à já existente. O ano base considerado foi 2011. Os resultados obtidos mostram que, neste ano, as actividades da Monteiro, Ribas- Embalagens Flexíveis, S.A serão responsáveis pela emissão de 2968,6 toneladas de CO2e (dióxido de carbono equivalente). De acordo com a Decisão 2007/589/CE da Comissão de 18 de Julho de 2007 conclui-se que a Monteiro, Ribas Embalagens e Flexíveis S.A. se enquadra na categoria de instalações com baixo níveis de emissões pois as suas emissões médias anuais são inferiores a 25000 toneladas de CO2e. Conclui-se que a percentagem maior das emissões estimadas (50,7 %) é proveniente do consumo de electricidade (emissões indirectas, âmbito 2), seguida pelo consumo de gás natural (emissões directas) que representa 39,4% das emissões. Relacionando os resultados obtidos com a produção total da Monteiro, Ribas- Embalagens Flexíveis, S.A, em 2011, obtém-se o valor de 0,65 kg de CO2e por cada quilograma de produto final. Algumas das fontes emissoras identificadas não foram incorporadas no inventário da empresa, nomeadamente o transporte das matérias-primas e dos produtos. Isto deve-se ao facto de não ter sido possível compilar a informação necessária, em tempo útil. Apesar de se tratar de emissões indirectas de âmbito 3, consideradas opcionais, recomenda-se que num próximo trabalho deste tipo, essas emissões possam vir a ser quantificadas. As principais incertezas associadas às estimativas de emissão dizem respeito aos dados de actividade uma vez que foi a primeira vez que a empresa realizou um inventário de gases de efeito de estufa. Há informações mais específicas sobre os dados de actividade que a empresa dispõe e que poderá, de futuro, sistematizar de uma forma mais adequada para a sua utilização com este fim.