Yes / In this paper, a stochastic method for active distribution networks planning within a distribution market environment considering multi-configuration of wind turbines is proposed. Multi-configuration multi-scenario market-based optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand and different operational status of wind turbines (multiple-wind turbine configurations). Scenario-based approach is used to model the abovementioned uncertainties. The method evaluates the impact of multiple-wind turbine configurations and active network management schemes on the amount of wind power that can be injected into the grid, the distribution locational marginal prices throughout the network and on the social welfare. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system. It was shown that multi-wind turbine configurations under active network management schemes, including coordinated voltage control and adaptive power factor control, can increase the amount of wind power that can be injected into the grid; therefore, the distribution locational marginal prices reduce throughout the network significantly.

No / This chapter proposes a novel method for the operation of active distribution networks within a distribution market environment taking into account multi-configuration of wind turbines. Multi-configuration multi-scenario market-based optimal power flow is used to maximise the social welfare considering uncertainties related to wind speed and load demand. Scenario based approach is used to model the uncertainties. The method assesses the impact of multiple-wind turbine configurations on the amount of wind power that can be injected into the grid and the distribution locational marginal prices throughout the network. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system.

Yes / In this paper, a novel deterministic approach for the planning of active distribution networks within a distribution market environment considering multi-configuration of wind turbines (WTs) and photovoltaic (PV) cells is proposed. Multi-configuration multi-period market-based optimal power flow is utilized for maximizing social welfare taking into account uncertainties associated with wind speed, solar irradiance and load demand as well as different operational status of WTs and PVs. Multi-period scenarios method is exploited to model the aforementioned uncertainties. The proposed approach assesses the effect of multiple-configuration of PVs and WTs on the amount of wind and solar power that can be produced, the distribution locational marginal prices all over the network and on the social welfare. The application of the proposed approach is examined on a 30-bus radial distribution network. / This work was supported in part by the Royal Academy of Engineering Distinguished Visiting Fellowship Grant DVF1617/6/45 and by the University of Bradford, UK under the CCIP grant 66052/000000.

Submitted by DARWIN ALEXIS QUIJANO RODEZNO (alexisqr@yahoo.es) on 2018-05-08T15:12:06Z No. of bitstreams: 1 TeseDarwinQuijano.pdf: 3515679 bytes, checksum: f52d72089eda5a3bb15b367d3afbf33a (MD5) / Approved for entry into archive by Cristina Alexandra de Godoy null (cristina@adm.feis.unesp.br) on 2018-05-08T17:48:35Z (GMT) No. of bitstreams: 1 quijanorodezno_da_dr_ilha.pdf: 3515679 bytes, checksum: f52d72089eda5a3bb15b367d3afbf33a (MD5) / Made available in DSpace on 2018-05-08T17:48:35Z (GMT). No. of bitstreams: 1 quijanorodezno_da_dr_ilha.pdf: 3515679 bytes, checksum: f52d72089eda5a3bb15b367d3afbf33a (MD5) Previous issue date: 2018-04-19 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Atualmente, existe uma tendência para aumentar a participação da Geração Distribuída (GD) baseada em Fontes de Energia Renováveis (FER) no suprimento do consumo global de energia elétrica. Esta tendência está sendo impulsionada principalmente por iniciativas governamentais destinadas a aumentar a eficiência energética, aumentar o uso da energia proveniente das FER e reduzir as emissões de gases de efeito estufa. No entanto, à medida que seu nível de penetração aumenta, a GD pode dar origem a um sistema incapaz de fornecer energia de forma confiável e de acordo com os padrões de qualidade. Nesse cenário, a Gestão de Redes Ativas (GRA) surge como uma alternativa para a integração de grandes montantes de GD. A GRA promove a disponibilização de instrumentos comerciais e regulatórios, e o fornecimento das redes de distribuição com tecnologias de automação para procurar serviços ancilares e flexibilidade a partir da GD. A GRA requer o desenvolvimento de ferramentas computacionais para coordenar a implementação de esquemas de controle inteligentes, chamados de esquemas de GRA, a fim de otimizar a utilização e operação das redes. Neste trabalho, são propostos modelos de otimização e técnicas de solução para a GRA considerando a integração de GD solar fotovoltaica e eólica e a eficiência energética. O primeiro modelo é desenvolvido para determinar a capacidade máxima de GD que pode ser alocada em uma rede de distribuição quando se considera o efeito da tensão na eficiência das cargas. No segundo modelo, o procedimento de controlar os níveis de tensão para reduzir a demanda das cargas é implementado para economia de energia e para o balanço de geração e demanda, através de uma estratégia projetada para o planejamento da operação de redes de distribuição ativas. Em ambos os modelos as incertezas são consideradas através de formulações de programação estocásticas de dois estágios. Os esquemas de GRA considerados são o controle coordenado da tensão através de reguladores de tensão e transformadores com comutador de tap sob carga, suporte de potência reativa através da GD, e corte de geração. A técnica de solução envolve a discretização das funções de densidade de probabilidade que definem os parâmetros incertos através de um processo de geração e redução de cenários. Depois, o método de decomposição de Benders é aplicado para reduzir o esforço computacional necessário para resolver os problemas formulados. Os algoritmos desenvolvidos foram testados em dois sistemas teste IEEE e os resultados mostraram benefícios importantes para a integração de GD e a eficiência energética. / Nowadays, there is a trend to increase the participation of distributed generation (DG) based on renewable energy sources in supplying the global electricity consumption. This trend is being driven mainly by government initiatives to increase energy efficiency, convert the energy use to renewable sources and reduce greenhouse gas emissions. However, as its penetration level increases, the DG can give rise to a system unable to deliver energy reliably and according to quality standards. In this scenario, active network management (ANM) emerges as an alternative for the integration of large amounts of DG. ANM promotes the availability of commercial and regulatory instruments and the provision of distribution networks with automation technologies for procuring ancillary services and flexibility from the DG. ANM requires the development of computational tools to coordinate the implementation of intelligent control schemes, called ANM schemes, in order to optimize the utilization and operation of distribution networks. In this work, optimization models and solution techniques are proposed for ANM considering the integration of solar and wind-based DG and energy efficiency. The first model is developed to determine the maximum capacity of DG that can be allocated in a distribution network when considering the effect of voltage on load efficiency. In the second model, the procedure of controlling the voltage levels to reduce the load demand is implemented for energy saving and for balancing the demand and generation, in a strategy designed for the operation planning of active distribution networks. In both models the uncertainties are considered through two-stage stochastic programming formulations. The ANM schemes considered are the coordinated voltage control through voltage regulators and transformers with on-load tap changer, reactive power support from the DG, and DG generation curtailment. The solution technique involves the discretization of the probability density functions that define the uncertain parameters through a scenario generation and reduction process. Then, the Benders decomposition method is applied in order to reduce the computational effort required to solve the formulated problems. The developed algorithms were tested in two IEEE test systems and the results showed important benefits for the integration of DG and energy efficiency. / 2014/14201-0 e 2015/12911-3

Orientador: Antonio Padilha Feltrin / Resumo: Atualmente, existe uma tendência para aumentar a participação da Geração Distribuída (GD) baseada em Fontes de Energia Renováveis (FER) no suprimento do consumo global de energia elétrica. Esta tendência está sendo impulsionada principalmente por iniciativas governamentais destinadas a aumentar a eficiência energética, aumentar o uso da energia proveniente das FER e reduzir as emissões de gases de efeito estufa. No entanto, à medida que seu nível de penetração aumenta, a GD pode dar origem a um sistema incapaz de fornecer energia de forma confiável e de acordo com os padrões de qualidade. Nesse cenário, a Gestão de Redes Ativas (GRA) surge como uma alternativa para a integração de grandes montantes de GD. A GRA promove a disponibilização de instrumentos comerciais e regulatórios, e o fornecimento das redes de distribuição com tecnologias de automação para procurar serviços ancilares e flexibilidade a partir da GD. A GRA requer o desenvolvimento de ferramentas computacionais para coordenar a implementação de esquemas de controle inteligentes, chamados de esquemas de GRA, a fim de otimizar a utilização e operação das redes. Neste trabalho, são propostos modelos de otimização e técnicas de solução para a GRA considerando a integração de GD solar fotovoltaica e eólica e a eficiência energética. O primeiro modelo é desenvolvido para determinar a capacidade máxima de GD que pode ser alocada em uma rede de distribuição quando se considera o efeito da tensão na eficiência das cargas.... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Nowadays, there is a trend to increase the participation of distributed generation (DG) based on renewable energy sources in supplying the global electricity consumption. This trend is being driven mainly by government initiatives to increase energy efficiency, convert the energy use to renewable sources and reduce greenhouse gas emissions. However, as its penetration level increases, the DG can give rise to a system unable to deliver energy reliably and according to quality standards. In this scenario, active network management (ANM) emerges as an alternative for the integration of large amounts of DG. ANM promotes the availability of commercial and regulatory instruments and the provision of distribution networks with automation technologies for procuring ancillary services and flexibility from the DG. ANM requires the development of computational tools to coordinate the implementation of intelligent control schemes, called ANM schemes, in order to optimize the utilization and operation of distribution networks. In this work, optimization models and solution techniques are proposed for ANM considering the integration of solar and wind-based DG and energy efficiency. The first model is developed to determine the maximum capacity of DG that can be allocated in a distribution network when considering the effect of voltage on load efficiency. In the second model, the procedure of controlling the voltage levels to reduce the load demand is implemented for energy saving and for b... (Complete abstract click electronic access below) / Doutor

Yes / This article proposes a novel technique for operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment. The objective of the proposed model is to maximize social welfare using market-based joint active and reactive optimal power flow. First, the intermittent behavior of renewable sources (solar irradiance, wind speed) and load demands is modeled through scenario-tree technique. Then, a network frame is recast using mixed-integer linear programming, which is solvable using efficient off-the-shelf branch-and cut solvers. Additionaly, this article explores the impact of wind and solar power penetration on the active and reactive distribution locational prices within the distribution market environment with integration of ANM schemes and DR. A realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. / This work was supported in part by the Ministry of Higher Education Scientific Research in Iraq and in part by British Academy under Grant GCRFNGR3\1541.

Distributed generators (DGs) are proposed as a possible solution to supply economic and reliable electricity to customers. It is adapted to overcome the challenges that are characterized by centralized generation such as transmission and distribution losses, high cost of fossil fuels and environmental damage. This work presents the basic principles of integrating renewable DGs in low voltage distribution networks and particularly focuses on the operation of DG installations and their impacts on active and reactive power. In this thesis, a novel technique that applies the stochastic approach for the operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment is proposed. The projected model is maximized based on social welfare (SW) using market-based joint active and reactive optimal power flow (OPF). The intermittent behaviour of renewable sources (such as solar irradiance and wind speed) and the load demands are modelled through Scenario-Tree technique. The distributed network frame is recast using mixed-integer linear programming (MILP) that is solved by using the GAMS software and then the obtained results are being analysed and discussed. In addition, the impact of wind and solar power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment is explored in terms of the maximization of SW considering the uncertainty related to solar irradiance, wind speed and load demands. Finally, a realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. Results show that ANM schemes and DR integration lead to an increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs. / Ministry of Higher Education and Scientific Research - Iraq / The selected author's publications, the published versions of which were attached at the end of the thesis, have been removed due to copyright.

No description available.

This masters thesis describes simulation of network using Network Simulator. Model of network and description of simulation is extracted from the analysis of configuration files of active network devices, and translated by a parser. Concept and implementation of the parser is described here. Because IPv4 addressing is not supported in Network Simulator, it was added as a new module. The Network Simulator is also extended by filtering properties of packets using access control lists. Practical usage of the implemented modules is demonstrated on a simulation of real network.

The thesis deals with the use of neuronal networks for the control of telecommunication network elements. The aim of the thesis is to create a simulation model of network element with switching array with memory, in which the optimization kontrol switching array is solved by means of the neural network. All source code is created in integrated environment MATLAB. To training are used feed-forward backpropagation network. Miss achieve satisfactory result mistakes. Work apposite decision procedure given to problem and it is possible on ni tie up in an effort to find optimum solving.