This dissertation is a systematic study of artificial neural networks (ANN) applications in power system restoration (PSR). PSR is based on available generation and load to be restored analysis. A literature review showed that the conventional PSR methods, i.e. the pre-established guidelines, the expert systems method, the mathematical programming method and the petri-net method have limitations such as the necessary time to obtain the PSR plan. ANN may help to solve this problem presenting a reliable PSR plan in a smaller time. Based on actual and past experiences, a PSR engine based on ANN was proposed and developed. Data from the Iowa 162 bus power system was used in the implementation of the technique. Reactive and real power balance, fault location, phase angles across breakers and intentional islanding were taken into account in the implementation of the technique. Constraints in PSR as thermal limits of transmission lines (TL), stability issues, number of TL used in the restoration plan and lockout breakers were used to create feasible PSR plans. To compare the time necessary to achieve the PSR plan with another technique a PSR method based on a breadth-search algorithm was implemented. This algorithm was also used to create training and validation patterns for the ANN used in the scheme. An algorithm to determine the switching sequence of the breakers was also implemented. In order to determine the switching sequence of the breakers the algorithm takes into account the most priority loads and the final system configuration generated by the ANN. The PSR technique implemented is composed by several pairs of ANN, each one assigned to an individual island of the system. The restoration of the system is done in parallel in each island. After each island is restored the tie lines are closed. The results encountered shows that ANN based schemes can be used in PSR helping the operators restore the system under the stressful conditions following a blackout. / Ph. D.

This thesis proposes an algorithm and develops a program for fault detection and system restoration in medium voltage distribution systems. In Turkey, TUBITAK-UZAY developed distribution automation system including fault detection and service restoration functions for Bogazici Electricity Distribution Company. By the time, expanding of distribution system with nonstandardized infrastructure (for example more than one circuit breaker in the feeder, mesh and closed loop feeder structure), developed automation system have not properly worked under these unplanned situations. Taking into consideration of previously utilized TUBITAK Distribution Automation System (TUDOSIS), fault isolation algorithm is improved to cope with practical problems as non-standardized infrastructure and selectivity issue in protection system, and the proposed isolation algorithm is simulated. Further system restoration solution for mesh distribution systems is analyzed for distribution system in Turkey and expert system based algorithm is proposed.

The interdependencies that exist within and between infrastructures can cause unexpected system properties to emerge when their components fail due to large disruptions. As witnessed following emergencies such as Hurricane Katrina, the complexities of these interdependencies make it very difficult to effectively recover infrastructure because of the challenges they create in prioritizing the most critical components for repair. The Joint Infrastructure Interdependencies Research Program was initiated by Public Safety Canada (PSC) and the Natural Sciences and Engineering Research Council of Canada (NSERC) in 2005 to research methods for remedying this problem. As a part of this research, the University of British Columbia (UBC) is developing an infrastructure interdependency simulator, named I2Sim, to simulate disasters and develop strategies for dealing with emergencies. Part of this development is to construct a model of the UBC electrical distribution system and interface it with I2Sim. In this research, a general methodology for such a model is presented, which employs an off-the-shelf powerflow modeling tool. In addition, a model of the UBC information technology infrastructure is developed to provide a second infrastructure model to demonstrate the electrical model's usefulness in multi-infrastructure disaster recovery simulations. Simulations with these models have shown that the recovery of this two-infrastructure system can be carried out more effectively following an earthquake if both infrastructures are considered together in the repair approach, rather than individually. This difference was on the order of thirty percent. To extend this research from electrical distribution systems to electrical bulk systems, an interdependency model of the British Columbia Transmission Corporation bulk power network and its communications system was also developed, along with a post-blackout restoration procedure. Using these, simulations of a post-blackout recovery were carried out to study the level of risk that communications outages may pose to the electrical network's recovery. These simulations revealed a correlation between restoration time and the number of communication points lost. This research also demonstrates there is value in combining the results of such simulations with risk evaluation tools. Together these results provided a clearer indication of where vulnerabilities exist.

The interdependencies that exist within and between infrastructures can cause unexpected system properties to emerge when their components fail due to large disruptions. As witnessed following emergencies such as Hurricane Katrina, the complexities of these interdependencies make it very difficult to effectively recover infrastructure because of the challenges they create in prioritizing the most critical components for repair. The Joint Infrastructure Interdependencies Research Program was initiated by Public Safety Canada (PSC) and the Natural Sciences and Engineering Research Council of Canada (NSERC) in 2005 to research methods for remedying this problem. As a part of this research, the University of British Columbia (UBC) is developing an infrastructure interdependency simulator, named I2Sim, to simulate disasters and develop strategies for dealing with emergencies. Part of this development is to construct a model of the UBC electrical distribution system and interface it with I2Sim. In this research, a general methodology for such a model is presented, which employs an off-the-shelf powerflow modeling tool. In addition, a model of the UBC information technology infrastructure is developed to provide a second infrastructure model to demonstrate the electrical model's usefulness in multi-infrastructure disaster recovery simulations. Simulations with these models have shown that the recovery of this two-infrastructure system can be carried out more effectively following an earthquake if both infrastructures are considered together in the repair approach, rather than individually. This difference was on the order of thirty percent. To extend this research from electrical distribution systems to electrical bulk systems, an interdependency model of the British Columbia Transmission Corporation bulk power network and its communications system was also developed, along with a post-blackout restoration procedure. Using these, simulations of a post-blackout recovery were carried out to study the level of risk that communications outages may pose to the electrical network's recovery. These simulations revealed a correlation between restoration time and the number of communication points lost. This research also demonstrates there is value in combining the results of such simulations with risk evaluation tools. Together these results provided a clearer indication of where vulnerabilities exist.

The interdependencies that exist within and between infrastructures can cause unexpected system properties to emerge when their components fail due to large disruptions. As witnessed following emergencies such as Hurricane Katrina, the complexities of these interdependencies make it very difficult to effectively recover infrastructure because of the challenges they create in prioritizing the most critical components for repair. The Joint Infrastructure Interdependencies Research Program was initiated by Public Safety Canada (PSC) and the Natural Sciences and Engineering Research Council of Canada (NSERC) in 2005 to research methods for remedying this problem. As a part of this research, the University of British Columbia (UBC) is developing an infrastructure interdependency simulator, named I2Sim, to simulate disasters and develop strategies for dealing with emergencies. Part of this development is to construct a model of the UBC electrical distribution system and interface it with I2Sim. In this research, a general methodology for such a model is presented, which employs an off-the-shelf powerflow modeling tool. In addition, a model of the UBC information technology infrastructure is developed to provide a second infrastructure model to demonstrate the electrical model's usefulness in multi-infrastructure disaster recovery simulations. Simulations with these models have shown that the recovery of this two-infrastructure system can be carried out more effectively following an earthquake if both infrastructures are considered together in the repair approach, rather than individually. This difference was on the order of thirty percent. To extend this research from electrical distribution systems to electrical bulk systems, an interdependency model of the British Columbia Transmission Corporation bulk power network and its communications system was also developed, along with a post-blackout restoration procedure. Using these, simulations of a post-blackout recovery were carried out to study the level of risk that communications outages may pose to the electrical network's recovery. These simulations revealed a correlation between restoration time and the number of communication points lost. This research also demonstrates there is value in combining the results of such simulations with risk evaluation tools. Together these results provided a clearer indication of where vulnerabilities exist. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Under the envisioned smart city paradigm, there is an increasing demand for the coordinated operation of our infrastructure networks. In this context, this thesis puts forth a comprehensive toolbox for the optimization of electric power and water distribution networks. On the analytical front, the toolbox consists of novel mixed-integer (non)-linear program (MINLP) formulations; convex relaxations with optimality guarantees; and the powerful technique of McCormick linearization. On the application side, the developed tools support the operation of each of the infrastructure networks independently, but also towards their joint operation. Starting with water distribution networks, the main difficulty in solving any (optimal-) water flow problem stems from a piecewise quadratic pressure drop law. To efficiently handle these constraints, we have first formulated a novel MINLP, and then proposed a relaxation of the pressure drop constraints to yield a mixed-integer second-order cone program. Further, a novel penalty term is appended to the cost that guarantees optimality and exactness under pre-defined network conditions. This contribution can be used to solve the WF problem; the OWF task of minimizing the pumping cost satisfying operational constraints; and the task of scheduling the operation of tanks to maximize the water service time in an area experiencing electric power outage. Regarding electric power systems, a novel MILP formulation for distribution restoration using binary indicator vectors on graph properties alongside exact McCormick linearization is proposed. This can be used to minimize the restoration time of an electric system under critical operational constraints, and to enable a coordinated response with the water utilities during outages. / Master of Science / The advent of smart cities has promoted research towards interdependent operation of utilities such as water and power systems. While power system analysis is significantly developed due to decades of focused research, water networks have been relying on relatively less sophisticated tools. In this context, this thesis develops Advanced efficient computational tools for the analysis and optimization for water distribution networks. Given the consumer demands, an optimal water flow (OWF) problem for minimizing the pump operation cost is formulated. Developing a rigorous analytical framework, the proposed formulation provides significant computational improvements without compromising on the accuracy. Explicit network conditions are provided that guarantee the optimality and feasibility of the obtained OWF solution. The developed formulation is next used to solve two practical problems: the water flow problem, that solves the complex physical equations yielding nodal pressures and pipeline flows given the demands/injections; and an OWF problem that finds the best operational strategy for water utilities during power outages. The latter helps the water utility to maximize their service time during power outages, and helps power utilities better plan their restoration strategy. While the increased instrumentation and automation has enabled power utilities to better manage restoration during outages, finding an optimal strategy remains a difficult problem. The operational and coordination requirements for the upcoming distributed resources and microgrids further complicate the problem. This thesis develops a computationally fast and reasonably accurate power distribution restoration scheme enabling optimal coordination of different generators with optimal islanding. Numerical tests are conducted on benchmark water and power networks to corroborate the claims of the developed formulations.

abstract: After a power system blackout, system restoration is the most important task for the operators. Most power systems rely on an off&ndashline; restoration plan and the experience of operators to select scenarios for the black start path. Using an off&ndashline; designed restoration plan based on past experience may not be the most reliable approach under changing network configurations and loading levels. Hence, an objective restoration path selection procedure, including the option to check constraints, may be more responsive in providing directed guidance to the operators to identify the optimal transmission path to deliver power to other power plants or to pick up load as needed. After the system is subjected to a blackout, parallel restoration is an efficient way to speed up the restoration process. For a large scale power system, this system sectionalizing problem is quite complicated when considering black&ndashstart; constraints, generation/load balance constraints and voltage constraints. This dissertation presents an ordered binary decision diagram (OBDD) &ndashbased; system sectionalizing method, by which the splitting points can be quickly found. The simulation results on the IEEE 39 and 118&ndashbus; system show that the method can successfully split the system into subsystems satisfying black&ndashstart; constraints, generation/load balance constraints and voltage constraints. A power transfer distribution factor (PTDF)&ndashbased; approach will be described in this dissertation to check constraints while restoring the system. Two types of restoration performance indices are utilized considering all possible restoration paths, which are then ranked according to their expected performance characteristics as reflected by the restoration performance index. PTDFs and weighting factors are used to determine the ordered list of restoration paths, which can enable the load to be picked up by lightly loaded lines or relieve stress on heavily loaded lines. A transmission path agent can then be formulated by performing the automatic path selection under different system operating conditions. The proposed restoration strategy is tested on the IEEE&ndash39; bus system and on the Western region of the Entergy system. The testing results reveal that the proposed strategy can be used in real time. / Dissertation/Thesis / Ph.D. Electrical Engineering 2010

Orientador: Andre Luiz Morelato França / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T08:14:44Z (GMT). No. of bitstreams: 1 Mota_LiaToledoMoreira_D.pdf: 2050832 bytes, checksum: 67d474d280eaf6b619b3f766e55b9010 (MD5) Previous issue date: 2005 / Resumo: Neste trabalho, foram desenvolvidos dois métodos para prever o comportamento da carga durante a reenergização de redes elétricas pós-blecaute total ou parcial e instantes posteriores. O primeiro consiste em um Método Heurístico Top-Down, baseado em regras extraídas da experiência de especialistas e eventos anteriores, caracterizado por uma capacidade de representação aproximada do comportamento da carga e por um baixo esforço computacional requerido em sua utilização. Nessa metodologia, as incertezas associadas às variáveis e regras são modeladas usando-se lógica fuzzy. O segundo método consiste em um Método Caixa-Branca Bottom-Up que permite a representação do comportamento da carga agregada de forma mais precisa, partindo-se da modelagem individual dos vários tipos de equipamentos e dos principais fenômenos físicos envolvidos na reenergização dos mesmos. Nessa metodologia, os modelos implementados levam em conta as parcelas de consumo residencial, comercial e industrial, bem como a classificação dos equipamentos quanto a seu tipo de controle (controlados termostaticamente, fixos e controlados manualmente). Testes e simulações foram realizados, visando a verificação da adequação dos métodos desenvolvidos, bem como uma análise comparativa entre eles, destacando vantagens e desvantagens da aplicação de cada um / Abstract: This work is focused on developing methods to forecast the load behavior during power systems restoration. Two methodologies were implemented. The first one is the Top-Down Heuristic Method, based on rules extracted from expert experiences and also on past events, that yields an approximate representation of the load behavior at a low computational effort. In this method, the uncertainties associated to the variables and rules are modeled using fuzzy logic. The second method is the Bottom-Up White-Box Method that alows a more adequate representation of the load behavior, by modelling both the functioning of individual equipments and the physical phenomena involved with the reenergization process. In this methodology, the implemented models take into account the residential, the commercial and the industrial consume parcels and the control type of each equipment (thermostatically controlled, fixed and manually controlled). Tests and simulations were carried out in order to verify the adequacy of the proposed methodologies and to compare the advantages and disadvantages of each one / Doutorado / Energia Eletrica / Doutor em Engenharia Elétrica

The work presented in this thesis was concerned with the implementation of a damage control method for U.S. Navy shipboard power systems (SPS). In recent years, the Navy has been seeking an automated damage control and power system management approach for future reconfigurable shipboard power systems. The methodology should be capable of representing the dynamic performance (differential algebraic description), the steady state performance (algebraic description), and the system reconfiguration routines (discrete events) in one comprehensive tool. The damage control approach should also be able to improve survivability, reliability, and security, as well as reduce manning through the automation of the reconfiguration of the SPS network. To this end, this work implemented a damage control method for a notional Next Generation Integrated Power System. This thesis presents a static implementation of a dynamic formulation of a new damage control method at the DC zonal Integrated Flight Through Power system level. The proposed method used a constrained binary genetic algorithm to find an optimal network configuration. An optimal network configuration is a configuration which restores all of the de-energized loads that are possible to be restored based on the priority of the load without violating the system operating constraints. System operating limits act as constraints in the static damage control implementation. Off-line studies were conducted using an example power system modeled in PSCAD, an electromagnetic time domain transient simulation environment and study tool, to evaluate the effectiveness of the damage control method in restoring the power system. The simulation results for case studies showed that, in approximately 93% of the cases, the proposed damage algorithm was able to find the optimal network configuration that restores the power system network without violating the power system operating constraints.

Orientador: Andre Luiz Morelato França / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T08:13:24Z (GMT). No. of bitstreams: 1 Mota_AlexandredeAssis_D.pdf: 2550000 bytes, checksum: d1b87870a85e6720b234c4e11cce99a8 (MD5) Previous issue date: 2005 / Resumo: O sucesso da recomposição de sistemas interligados está diretamente associado à qualidade dos planos de recomposição. Esses planos descrevem as seqüências de ações de controle que devem ser tomadas para energizar as diferentes áreas geoelétricas do sistema após a ocorrência de blecautes totais ou parciais. Nesse contexto, o objetivo deste trabalho é propor uma metodologia para avaliação da qualidade de planos de recomposição, que permita o uso de ferramentas computacionais para avaliar a qualidade de forma automática e sob alguns critérios como (a) grau de flexibilidade quanto a imprevistos durante a execução, (b) índices de qualidade globais determinados a partir da representação do plano de recomposição através de grafos conexos e (c) facilidade de acesso, visualização, atualização e treinamento. Diferentes técnicas e métodos foram empregados para atingir esse objetivo (busca de caminho mínimo, utilização de índices nebulosos, métodos de caminho crítico - CPM/PERT), visando a determinação dos índices numéricos relacionados à qualidade do plano, tais como: duração total prevista para a recomposição, eficiência da fase fluente, evolução da carga interrompida e custos estimados para a interrupção / Abstract: A successful restoration depends on the quality of the restoration plans, that describe the sequence of control actions that must be executed to reenergize different areas (of the power system) just after total or partial blackouts. This work proposes a methodology to automatically evalute the quality of power system restoration plans, related to (a) the flexibility of the plan, (b) numerical quality indexes, extracted using a graph representation for the plan and (c) the easiness of use, visualization, training and access to restoration instructions. Different techniques and methods were used to achieve this goal (minimum path search, adoption of fuzzy indexes, critical path methods), focusing on the determination of numerical indexes that express the quality of the plan, such as total restoration duration, fluent phase efficiency, interrupted load evolution and estimated interruption costs / Doutorado / Energia Eletrica / Doutor em Engenharia Elétrica