Transmission cost allocation using cooperative game theory: a comparative study

In this paper is presented a Game Theory based methodology to allocate transmission costs, considering cooperation and competition between producers. As original contribution, it finds the degree of participation on the additional costs according to the demand behavior. A comparative study was carried out between the obtained results using Nucleolus balance and Shapley Value, with other techniques such as Averages Allocation method and the Generalized Generation Distribution Factors method (GGDF). As example, a six nodes network was used for the simulations. The results demonstrate the ability to find adequate solutions on open access environment to the networks.

Dgenco market balancing - cost repartition under light regulation markets

In this paper we present a new methodology, based in game theory, to obtain the market balancing between Distribution Generation Companies (DGENCO), in liberalized electricity markets. The new contribution of this methodology is the verification of the participation rate of each agent based in Nucléolo Balancing and in Shapley Value. To validate the results we use the Zaragoza Distribution Network with 42 Bus and 5 DGENCO.

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.

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.

Intelligent multi-player smart grid management considering distributed energy resources and demand response

The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.

Energy resources management for more sustainable distribution systems: an intelligent approach

Energy Resources Management can play a very relevant role in future power systems in SmartGrid context, with high penetration of distributed generation and storage systems. This paper deals with the importance of resources management in incident situation. The system to consider a high penetration of distributed generation, demand response, storage units and network reconfiguration. A case study evidences the advantages of using a flexible SCADA to control the energy resources in incident situation.

Emergency energy resource management in SmartGrids

Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

Dual source/dual energy-renal applications

Development of Dual Source Computed Tomography (Definition, Siemens Medical Solutions, Erlanger, Germany) allowed advances in temporal resolution, with the addition of a second X-ray source and an array of detectors to the TCM 64 slices. The ability to run exams on Dual Energy, allows greater differentiation of tissues, showing differences between closer attenuation coefficients. In terms of renal applications, the distinction of kidney stones and masses become one of the main advantages of the use of dual-energy technology. This article pretends to demonstrate operating principles of this equipment, as its main renal applications.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Modelação e simulação de sistemas fotovoltaicos

Os sistemas fotovoltaicos produzem energia eléctrica limpa, e inesgotável na nossa escala temporal. A Agência Internacional de Energia encara a tecnologia fotovoltaica como uma das mais promissoras, esperando nas suas previsões mais optimistas, que em 2050 possa representar 20% da produção eléctrica mundial, o equivalente a 18000 TWh. No entanto, e apesar do desenvolvimento notável nas últimas décadas, a principal condicionante a uma maior proliferação destes sistemas é o ainda elevado custo, aliado ao seu fraco desempenho global. Apesar do custo e ineficiência dos módulos fotovoltaicos ter vindo a diminuir, o rendimento dos sistemas contínua dependente de factores externos sujeitos a grande variabilidade, como a temperatura e a irradiância, e às limitações tecnológicas e falta de sinergia dos seus equipamentos constituintes. Neste sentido procurou-se como objectivo na elaboração desta dissertação, avaliar o potencial de optimização dos sistemas fotovoltaicos recorrendo a técnicas de modelação e simulação. Para o efeito, em primeiro lugar foram identificados os principais factores que condicionam o desempenho destes sistemas. Em segundo lugar, e como caso prático de estudo, procedeu-se à modelação de algumas configurações de sistemas fotovoltaicos, e respectivos componentes em ambiente MatlabTM/SimulinkTM. Em seguida procedeu-se à análise das principais vantagens e desvantagens da utilização de diversas ferramentas de modelação na optimização destes sistemas, assim como da incorporação de técnicas de inteligência artificial para responder aos novos desafios que esta tecnologia enfrentará no futuro. Através deste estudo, conclui-se que a modelação é não só um instrumento útil para a optimização dos actuais sistemas PV, como será, certamente uma ferramenta imprescindível para responder aos desafios das novas aplicações desta tecnologia. Neste último ponto as técnicas de modelação com recurso a inteligência artificial (IA) terão seguramente um papel preponderante. O caso prático de modelação realizado permitiu concluir que esta é igualmente uma ferramenta útil no apoio ao ensino e investigação. Contudo, convém não esquecer que um modelo é apenas uma aproximação à realidade, devendo recorrer-se sempre ao sentido crítico na interpretação dos seus resultados.

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.

Avaliação da rentabilidade económica dos sistemas de microgeração fotovoltaica em Portugal (1990-2010)

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica - ramo de Energia

Cost of schizophrenia: direct costs and use of resources in the State of São Paulo

OBJECTIVE: To estimate the direct costs of schizophrenia for the public sector. METHODS: A study was carried out in the state of São Paulo, Brazil, during 1998. Data from the medical literature and governmental research bodies were gathered for estimating the total number of schizophrenia patients covered by the Brazilian Unified Health System. A decision tree was built based on an estimated distribution of patients under different types of psychiatric care. Medical charts from public hospitals and outpatient services were used to estimate the resources used over a one-year period. Direct costs were calculated by attributing monetary values for each resource used. RESULTS: Of all patients, 81.5% were covered by the public sector and distributed as follows: 6.0% in psychiatric hospital admissions, 23.0% in outpatient care, and 71.0% without regular treatment. The total direct cost of schizophrenia was US$191,781,327 (2.2% of the total health care expenditure in the state). Of this total, 11.0% was spent on outpatient care and 79.2% went for inpatient care. CONCLUSIONS: Most schizophrenia patients in the state of São Paulo receive no regular treatment. The study findings point out to the importance of investing in research aimed at improving the resource allocation for the treatment of mental disorders in Brazil.

Controlo estratégico dos custos das atividades e recursos da Direção Comercial da Eletricidade dos Açores, S.A.

Dissertação de Mestrado, Ciências Económicas e Empresariais, 16 de Janeiro 2014, Universidade dos Açores.