Nos dias atuais, há muitos casos em que sistemas de potência estão operando perto dos seus limites de estabilidade devido a restrições econômicas e leis ambientais. A estabilidade de tensão é uma matéria de muita pesquisa e interesse devido a que é considerado como uma das maiores ameaças na segurança dos sistemas. Uma prevenção exitosa de colapso do sistema baseia-se na precisão do método, a simplicidade dos índices, e muito baixo tempo de computação. Este trabalho apresenta uma rede Perceptron Multicamada (PMC) como proposta para monitoramento em tempo real da estabilidade de tensão de sistemas de potência usando como principais dados de entrada medidas obtidas do sistema SCADA. Os dados de treinamento são obtidos com cálculos de fluxo de potência continuado. A rede Perceptron Multicamadas é apresentada como um aproximador universal de funções, que diminui o tempo computacional dos métodos convencionais como o fluxo de potência continuado. Por fim, a topologia da rede PMC proposta é avaliada com o sistema de 30 barras do IEEE, e os resultados em relação ao tempo de computação e precisão são comparados com o método de fluxo de potência continuado. / Nowadays, many power systems are operating near their limits of stability due to economic restrictions and environmental laws. Voltage stability is a subject of great interest because it is considered one of the greatest threats for power systems security. The keys to preventing blackouts are the accuracy of the method, speed indication, and low computation time. This work presents a Multi-layer Perceptron (PMC) network as a proposal for real-time monitoring of voltage stability in power systems using input data obtained from the SCADA system. The training data are obtained by running Continuation Power Flow (CPF) routine. The multi-layer Perceptron network is presented as a universal approximator, reducing the computation time of conventional methods such as the Finally, the proposed PMC network is evaluated in the IEEE 30-bus system. Computation time and accuracy are compared with the continuation power flow method.

Neste trabalho, as restrições de estabilidade transitória são incorporadas ao problema de Fluxo de Potência Ótimo (FPO) por meio da aproximação de equações diferenciais do problema de estabilidade por um conjunto de equações algébricas provenientes de procedimentos de integração numérica. Uma contribuição original desta dissertação é a proposição de um procedimento de otimização multi-passos que minimiza problemas de convergência e acelera o processo computacional. O procedimento de otimização proposto foi testado com sucesso num sistema pequeno de 3 geradores, tendo as potências geradas como variáveis de controle. / In this work, transient stability constraints are incorporated into the Optimal Power Flow (OPF) problem by approximating differential equations constraints by a set of equivalent algebraic equations originated from numerical integration procedures. A contribution of this dissertation is the proposal of a multi-step optimization procedure, which minimizes convergence problems and speeds up computation. The proposed optimization procedure was successfully tested on a small 3-machine power system, having the generated powers as control variables.

Recent years have seen a growing tendency that a large number of generators are connected to the electricity distribution networks, including renewables such as solar photovoltaics, wind turbines and biomass-fired power plants. Meanwhile, on the demand side, there are also some new types of electric loads being connected at increasing rates, with the most important of them being the electric vehicles (EVs). Uncertainties both from generation and consumption of electricity mentioned above are thereby being introduced, making the management of the system more challenging. With the proportion of electric vehicle ownership rapidly increasing, uncontrolled charging of large populations may bring about power system issues such as increased peak demand and voltage variations, while at the same time the cost of electricity generation, as well as the resulting Greenhouse Gases (GHG) emissions, will also rise. The work reported in this PhD Thesis aims to provide solutions to the three significant challenges related to EV integration, namely voltage regulation, generation cost minimisation and GHG emissions reduction. A novel, high-resolution, bottom-up probabilistic EV charging demand model was developed, that uses data from the UK Time Use Survey and the National Travel Survey to synthesise realistic EV charging time series based on user activity patterns. Coupled with manufacturers' data for representative EV models, the developed probabilistic model converts single user activity profiles into electrical demand, which can then be aggregated to simulate larger numbers at a neighbourhood, city or regional level. The EV charging demand model has been integrated into a domestic electrical demand model previously developed by researchers in our group at the University of Edinburgh. The integrated model is used to show how demand management can be used to assist voltage regulation in the distribution system. The node voltage sensitivity method is used to optimise the planning of EV charging based on the influence that every EV charger has on the network depending on their point of connection. The model and the charging strategy were tested on a realistic "highly urban" low voltage network and the results obtained show that voltage fluctuation due to the high percentage of EV ownership (and charging) can be significantly and maintained within the statutory range during a full 24-hour cycle of operation. The developed model is also used to assess the generation cost as well as the environmental impact, in terms of GHG emissions, as a result of EV charging, and an optimisation algorithm has been developed that in combination with domestic demand management, minimises the incurred costs and GHG emissions. The obtained results indicate that although the increased population of EVs in distribution networks will stress the system and have adverse economic and environmental effects, these may be minimised with careful off-line planning.

In recent years, power systems are facing with various challenges arising from the increased share of renewable energy systems. Among all sections of power systems, distribution grids are affected the most since the majority of renewable energy sources are connected to distribution grids. As the penetration of Variable Energy Sources increases in electric grids, energy storage systems have become more influential. In this context, this thesis presents a new algorithm for the optimal operation of Battery Energy Storage Systems in distribution grids. The proposed algorithm aims to define the optimal operation of Battery Energy Storage Systems considering the network topology, the output power of Variable Energy Sources and the electricity prices from the one-day ahead electric market as well as real time control of the batteries through smart appliances. In order to do this, firstly a comprehensive study on the existing Optimal Power Flow methods is carried out. Then, AR-OPF which is a novel Optimal Power Flow method for radial distribution systems is presented and the required mathematical constraints, equations and parameters of Battery Energy Storage Systems for modelling in distribution systems are described. Then, the problem formulation and the proposed algorithm are discussed in detail. Further to energy storage as the main function of Battery Energy Storage Systems, the impact of the proposed method on other functions of Battery Energy Storage Systems such as voltage control, grid support and loss reduction will be investigated. In order to do so, the proposed algorithm is applied to the IEEE 34 node test system as a case study. This will be carried out through defining several different scenarios. Finally, a sensitivity analysis is performed on the size of the existing batteries and the electricity price. The thesis will be concluded by the findings and possible future works.

<p>The purpose of this thesis was to investigate the possibility of power flow control, on a section of a railway grid fed by rotary converters, using an extra feeding line. Two possible solutions for the power flow control were examined. The first using a series reactance in connection to each converter station and the second by changing the tap changer level of the transformer between the converter station and the feeding line.</p><p>In the two models a distance, comparable to the distance between Boden and Häggvik, in Stockholm, was used. The simulations were performed using the software SIMPOW.</p><p>The results from the performed simulations show that series reactances, under the stated conditions, can essentially improve the power flow. To implement this air coils with inductances in the approximate size of 10 to 45 mH could be used. Further, the tap changer levels of the transformer may be used, for individual converter stations, as a way to control the reactive power flow.</p>

Large interruptions of power supply in the transmission system have considerable impact on modern society. The goal for the transmission system operator (TSO) is to prevent and mitigate such events with optimal decisions in design, planning, operation and maintenance. Identifying critical power components for system reliability provides one important input to this decision-making. This thesis develops quantitative component reliability importance indices applicable for identifying critical components in real transmission systems. Probabilistic models with component failure statistics are combined with detailed power system models evaluated with the AC power flow technique. In the presented method each system component is assigned three importance indices based on outage events expected probability and consequence to (i) reduced system security margin, (ii) interrupted load supply and (iii) disconnected generation units. By ranking components by each of the three interests, a more complete view of the risks to system reliability can be assessed than if, as traditionally, only (ii) is modelled. The impact on security margin is studied in well established critical transfer sections (CTS) supervised by the TSO. TSOs set the CTSs limits [MW] based on deterministic security criteria, with regard to thermal, voltage level, and system stability limits, and the CTSs' condition at post-contingency state is in the method used as an indicator of the system security margin. The methodology is extended with three indices modified to quantify the component importance for common-cause events initiated by acts of sabotage. The developed methods are applied on a significant part of the Great Britain transmission system, modelling 7000 components and 107 substation layouts. The study includes several load demand scenarios, 200 million initiating outage events and non-functioning protection equipment. The resulting component ranking provides an important input to the TSO's decision-making, and could be implemented as a complement to the existing deterministic N-1 criterion. With the methods applied a TSO can perform further and more detailed assessments on a few critical components in order to enhance system reliability for equipment failures and strengthen the system vulnerability against sabotage. / QC 20110920

Optimal transmission switching (OTS) enables us to remove selected transmission lines from service as a cost reduction method. A mixed integer programming (MIP) model has been proposed to solve the OTS problem based on the direct current optimal power flow (DCOPF) approximation. Previous studies indicated computational issues regarding the OTS problem and the need for a more accurate model. In order to resolve computational issues, especially in large real systems, the MIP model has been followed by some heuristics to find good, near optimal, solutions in a reasonable time. The line removal recommendations based on DCOPF approximations may result in poor choices to remove from service. We assess the quality of line removal recommendations that rely on DCOPF-based heuristics, by estimating actual cost reduction with the exact alternating current optimal power flow (ACOPF) model, using the IEEE 118-bus test system. We also define an ACOPF-based line-ranking procedure and compare the quality of its recommendations to those of a previously published DCOPF-based procedure. For the 118-bus system, the DCOPF-based line ranking produces poor quality results, especially when demand and congestion are very high, while the ACOPF-based heuristic produces very good quality recommendations for line removals, at the expense of much longer computation times. There is a need for approximations to the ACOPF that are accurate enough to produce good results for OTS heuristics, but fast enough for practical use for OTS decisions.

The purpose of this thesis was to investigate the possibility of power flow control, on a section of a railway grid fed by rotary converters, using an extra feeding line. Two possible solutions for the power flow control were examined. The first using a series reactance in connection to each converter station and the second by changing the tap changer level of the transformer between the converter station and the feeding line. In the two models a distance, comparable to the distance between Boden and Häggvik, in Stockholm, was used. The simulations were performed using the software SIMPOW. The results from the performed simulations show that series reactances, under the stated conditions, can essentially improve the power flow. To implement this air coils with inductances in the approximate size of 10 to 45 mH could be used. Further, the tap changer levels of the transformer may be used, for individual converter stations, as a way to control the reactive power flow.

In recent year, the awareness of environmental protection has made the power dispatch problem not necessarily economy-oriented. This thesis proposed the application of Particle Swarm Optimization (PSO) algorithm to solve the Unit Commitment (UC) problem for 24 hours with maximum profit in the power and carbon market. Optimal Power Flow (OPF) is used to solve the UC problem for the interconnected power network that is comprised of three independent areas to optimize the dispatching strategy. The UC problem must satisfy the constraints of the load demand, generating limits, minimum up/down time, ramp rate limits, and also the limits of power flow, buses voltage and transmission line capacity. The other objective of this thesis is to employ the Static Synchronous Series Compensator (SSSC) to integrate with OPF based on Equivalent Current Injection (ECI) power flow model, and install it at interconnected lines between each independent area controlling the power flow to reduce emission. In order to avoid the local optimality problem, this thesis proposed the utilization of the Multiple Particle Swarm Optimization (MPSO), which can quickly reach the optimal solution with a better performance and accuracy. The Independent Power Producer (IPP) can get the maximum profit with installed SSSC from the power and carbon trading with the calculation of power wheeling expense and carbon forecasting data. Furthermore, it can also assess the need of participating in the trading market or not.

In recent years, with the energy shortage, the use of renewable energy is inevitable. With CO2 the most important greenhouse gas causing global warming as well as the increase of population, renewable energy is one way to save energy and reduce carbon emissions. The traditional capacity investment for serving the load in distribution systems usually considered the addition of new substations or expansion of the existing substation and associated new feeder requirement. Nowadays, there are a lots of distributed generations (DG¡¦s) to be chosen. Factors of the choice taken into account will include lower pollution, higher efficiency, higher return rate for construction of distributed power generation systems. This thesis assumes that the distributed generation can be invested for long-term power plant planning. The planning of DG would be investigated from the perspectives of the independent investors. The modified Particle Swarm Optimization is proposed to determine the optimal sizing and sit of DG¡¦s addition in distribution systems with the constrains of CO2 limitation and addition of distributed generation to maximize profits. This thesis deals with discrete programming problem of optimal power flow, which includes continuous and discrete types of variables. The continuous variables are the generating unit real power output and the bus voltage magnitudes, the discrete variables are the shunt capacitor banks and sit problems. The Miaoli-Houlong system of Taiwan power will be used in this thesis for the verification of the feasibility of the proposed method.