In recent decades, there has been a dramatic increase in utilizing renewable energy resources by many power utilities around the world. The tendency toward using renewable energy resources is mainly due to the environmental concerns and fuel cost escalation associated with conventional fossil generation. Among renewable resources, wind energy is a proven source for power generation that positively contributes to global, social, and economic environments. Nowadays, wind energy is a mature, abundant, and emission-free power generation technology, and a significant percentage of electrical power demand is supplied by wind. However, the intermittent nature of wind generation introduces various challenges for both the operation and planning of power systems. One of the problems of increasing the use of wind generation can be seen from the reliability assessment point of view. Indeed, there is a recognized need to study the contribution of wind generation to overall system reliability and to ensure the adequacy of generation capacity. Wind power generation is different than conventional generation (i.e., fossil-based) in that wind power is variable and non-controllable, which can affect power system reliability. Therefore, modeling wind generation in a reliability assessment calls for reliable stochastic simulation techniques that can properly handle the uncertainty and precisely reflect the variable characteristics of the wind at a particular site. The research presented in this thesis focuses on developing a reliable and appropriate model for the reliability assessment of power system generation, including wind energy sources. This thesis uses the Monte Carlo Markov Chain (MCMC) technique due to its ability to produce synthetic wind power time series data that sufficiently consider the randomness of the wind along with keeping the statistical and temporal characteristics of the measured data. Thereafter, the synthetic wind power time series based on MCMC is coupled with a probabilistic sequential methodology for conventional generation in order to assess the overall adequacy of generating systems. The study presented in this thesis is applied to two test systems, designated the Roy Billinton Test System (RBTS) and the IEEE Reliability Test System (IEEE-RTS). A wide range of reliability indices are then calculated, including loss of load expectation (LOLE), loss of energy expectation (LOEE), loss of load frequency (LOLF), energy not supplied per interruption (ENSPI), demand not supplied per interruption (DNSPI), and expected duration per interruption (EDPI). To show the effectiveness of the proposed methodology, a further study is conducted to compare the obtained reliability indices using the MCMC model and the ARMA model, which is often used in reliability studies. The methodologies and the results illustrated in this thesis aim to provide useful information to planners or developers who endeavor to assess the reliability of power generation systems that contain wind generation.

Approaching problems with global warming due to the use of fossil fuels, means that new system solutions have to be investigated. This report investigates the possibility to expand an existing photovoltaic system with a wind turbine generator to simplify the expansion of renewable energy sources. Through an extensive literature study and simulation in SIMULINK the result has been developed and tested. It shows that it is possible to connect a wind turbine generator to the same inverter as the PV-modules if no MPPT algorithm for the PV-modules is integrated. To protect the inverter a dump load has to be connected. Because of the complexity a DC-coupled system brings, AC-coupling is advised when expanding PV-modules with a WTG. The optimal wind turbine is considered to be a permanent magnet synchronous generator connected to the AC-bus through a full-effect inverter. The turbine should be chosen according to the intended location based on wind conditions and desired energy production.

ABSTRACT Voltage instability has become a major concern in power systems. Many blackouts have been reported where the main cause is voltage instability. This thesis deals with two specific areas of voltage stability in on-line power system security assessments: small-disturbance (long-term) and large-disturbance (short-term) voltage stability assessment. For each category of voltage stability, both voltage stability analysis and controls are studied. The overall objective is to use the learning capabilities of computational intelligence technology to build up the comprehensive on-line power system security assessment and control strategy as well as to enhance the speed and efficiency of the process with minimal human intervention. The voltage stability problems are quantified by voltage stability indices which measure the system for the closeness of current operating point to voltage instability. The indices are different for small-disturbance and large-disturbance voltage stability assessment. Conventional approaches, such as continuation power flow or time-domain simulation, can be used to obtain voltage stability indices. However, these conventional approaches are limited by computation time that is significant for on-line computation. The Artificial Neural Network (ANN) approach is proposed to compute voltage stability indices as an alternative to the conventional approaches. The proposed ANN algorithm is used to estimate voltage stability indices under both normal and contingency operating conditions. The input variables of ANN are obtained in real-time by an on-line measurement system, i.e. Phasor Measurement Units (PMU). This thesis will propose a suboptimal approach for seeking the best locations for PMUs from a voltage stability viewpoint. The ANN-based method is not limited to compute voltage stability indices but can also be extended to determine suitable control actions. Load shedding is one of the most effective approaches against short-term voltage instability under large disturbances. The basic requirement of load shedding for recovering voltage stability is to seek an optimal solution for when, where, and how much load should be shed. Two simulation based approaches, particle swarm optimization (PSO) algorithm and sensitivity based algorithm, are proposed for load shedding to prevent voltage instability or collapse. Both approaches are based on time-domain simulation.

Widespread access to renewable electricity is seen as a viable method to mitigate carbon emissions, although problematic are the issues associated with the integration of the generation systems within current power system configurations. Wind power plants are the primary large-scale renewable generation technology applied globally, but display considerable short-term supply variability that is difficult to predict. Power systems are currently not designed to operate under these conditions, and results in the need to increase operating reserve in order to guarantee stability. Often, operating conventional generation as reserve is both technically and economically inefficient, which can overshadow positive benefits associated with renewable energy exploitation. The purpose of this thesis is to introduce and assess an alternative method of enhancing power system operations through the control of electric loads. In particular, this thesis focuses on managing highly-distributed sustainable demand-side infrastructure, in the form of heat pumps, electric vehicles, and electrolyzers, as dispatchable short-term energy balancing resources. The main contribution of the thesis is an optimal control strategy capable of simultaneously balancing grid- and demand-side objectives. The viability of the load control strategy is assessed through model-based simulations that explicitly track end-use functionality of responsive devices within a power systems analysis typically implemented to observe the effects of integrated wind energy systems. Results indicate that there is great potential for the proposed method to displace the need for increased reserve capacity in systems considering a high penetration of wind energy, thereby allowing conventional generation to operate more efficiently and avoid the need for possible capacity expansions. / Graduate

The system frequency of a synchronous power system varies with the imbalance of energy supplied and the electrical energy consumed. When large generating blocks are lost, the system undergoes a frequency swing relative to the size of the loss. Limits imposed on the magnitude of frequency deviation† prevent system collapse. Operation of frequency responsive plant to control frequency, results in lower machine efficiencies. Changes to the generation mix on the British transmission system have occurred in the past ten years, when the response requirement was last reviewed. Future increased levels of wind turbines‡ will alter the operational characteristics of the system and warrant investigation. A process to optimise the response requirements while maintaining statutory limits on frequency deviation has been identified. The method requires suitable load and generator models to replicate transmission system performance. A value to substitute for current load sensitivity to frequency has been presented from empirical studies. Traditional coal fired generator models have been improved with additional functions to provide a comparable response with existing units. A novel combined cycle gas turbine model using fundamental equations and control blocks has also been developed. A doubly fed induction generator model, based on existing literature, has been introduced for representing wind turbine behaviour in system response studies. Validation of individual models and the complete system against historic loss events has established confidence in the method. A review of the current system with the dynamic model showed that current primary response requirements are inadequate. The secondary response requirements generally show a slight reduction in the holding levels. Simulations including extra wind generation have shown that there is potential to reduce the primary response requirement in the future. The secondary response requirements are maintained with added wind farms.

Ontario, as the rest of the world, is moving towards a clean energy sector and green economy and to this effect, the Government of Ontario has set a goal of phasing out all coal-fired generation by the end of the year 2014. Wind energy is one of the most mature renewable energy technologies; it is clean and abundant. With Canada’s wind profile and wind energy potential, Ontario has focused on increasing the wind generation penetration in its electrical grid to compensate for the phasing out of coal-fired generation. In this thesis, long-term statistical trend analysis of wind generation patterns in Ontario is carried out, using wind generation data sets of Ontario wind farms during 2007 – 2010, on hourly, monthly, seasonal, and yearly time-scales. The analysis carried out, includes, long-term total wind generation capacity factor (CF) trends on yearly, seasonal, and monthly scales. To arrive at a better understanding of the wind generation intermittency and variability in Ontario, long term wind generation variability trends are presented. The correlation between the CFs of Ontario’s wind farms is determined using the Pearson Product- Moment Correlation Coefficient and examined against their distances from one another to understand the effect of geographic diversity for wind farms on total wind generation. The electricity system demand for on- and off-peak periods is analyzed to examine the contribution of wind generation during these periods. These analyses provide critical inputs and guidelines to planners and policy makers on the role that wind can play in the supply mix of Ontario when coal-fired generating units are replaced with wind generation. Expansion of wind generation capacity requires a closer examination of the location and quality of wind resources and a detailed understanding of its operational impacts on the transmission grid. A transmission network model is further developed in the thesis, for Ontario, based on the 500 kV and 230 kV transmission corridors with their planned enhancements for the three specific years under study- 2010, 2015 and 2025. The zonal supply mix of generation resources included are, nuclear, wind, hydro, gas-fired and coal-fired generation. An optimal power flow model is developed considering the future years’ demand and generation scenarios, and used in a deterministic case study. Subsequently, Monte Carlo simulations are carried out considering the variability and uncertainty of wind generation. Both case studies examine the effect of different wind generation penetration levels on the Ontario electrical grid and analyze long-term wind generation impacts. Wind generation is characterized by its variability and uncertainty. Hence, wind penetration in the electricity grid presents major challenges to power system operators. Some of these challenges are tackled by this thesis, such as the operating reserves required for different levels of wind penetration to maintain the system’s adequacy, the operating costs as a result of wind generation’s intermittent nature, and the impact on power losses as a result of wind generation’s dependability on its location. Moreover, the associated Green-House-Gas emissions with different penetration level are determined. The results quantify the impact of the different wind generation penetration levels on the Ontario’s power system.

The analysis and characterization of the steady-state security of a bulk-power electric system is investigated in a region-wise or set-theoretic framework. The study is divided into three parts: a detailed examination of the theoretical aspects of general security regions; a formulation and analysis of the problem of characterizing a set of secure operating points by a simple, explicit function; and an investigation into the secure loadability of a power system. Based on the results of the theoretical study, general approximate relations expressing dependent load flow variables in terms of the nodal injections are derived. Their degree of accuracy and extent of validity are investigated through analytical and simulation-based analyses. The general problem of characterizing subsets of a security region by simple, explicit functions is formulated as an optimization problem. For the case where the subsets are expressed by ellipsoids, two algorithms are developed and tested. The problem is then extended to include embedding the largest ellipsoid of a £ixed orientation inside a security region. The application of explicit security sets to the problem of predictive security assessment is studied in detail. A number of explicit security subsets overlapping along the predicted daily trajectory is used to define a "security corridor". This predicted corridor has the property that as long as the actual trajectory stays within it, very little computation is needed to assess the system security. The secure loadability of a power system is first studied in the demand space by considering the orthogonal projection of security sets into that space. It is then studied in the voltage space in the context of existence of a secure load flow solution to a given loading condition. Properties of the set of secure voltage solutions are explored by enclosing it with a linear set. Furthermore, it is shown that, under favorable conditions, one can easily characterize a subset of the set / L'analyse et la caracterisation de la securite en regime permanent pour un reseau et transmission ont ete etudiees dans le contexte de la theorie des ensembles. L'etude est divisee en trois parties: un examen detaille: des aspects theoriques des regions de securite generale; la formulation et l'analyse de probleme de la caracterisation d'un ensemble de points de fonctionnement par une fonction simple, sous forme explicite, et l'etude de la capacite de charge d'un reseau. Une analyse theorique a permis de deriver des relations approximative generales, exprimant les variables dependantes de l'ecoulement de puissance en terme des injections de noeud. Le degre de precision de ces approximations ainsi que leurs limites d'application sont determinees a l'aide de simulations et d'analyses theoriques. Le probleme general de la caracterisation des sous-ensembles d'une region de securite par des fonctions simples et sous forme explicite est formule comme probleme d'optimisation. Dans le cas ou les sous-ensembles sont exprimes par des ellipsoides, deux algorithmes sont developpes et verifies. Le probleme est alors elargi de facon a inclure le plus grand ellipsoide d'orientation fixe a l'interieur d'une region de securite. L'application d'ensembles de securite au prob1eme de l'evaluation preventive est etudiee en detail. On utilise un certain nombre d'ensembles de securite se recoupant long de la trajectoire journaliere prevue de facon a definir un corridor de securite. Ce corridor prevu possede la propriete qu'aussi longtemps que la trajectoire y est confinee, un minimum de calculs est requis pour evaluer la securite du systeme. Le chargement securitaire d'un reseau est en premier lieu etudie en considerant la projection orthogonale des ensembles de securite sur cet espace. Il est ensuite etudie dans l'espace des tensions, dans le contexte de l'existence d'une solution pour une charge donnee. Les proprietes de l'ensemble des solutions securitaires sont explorees en l'enchas

For reliable service, a power system must remain stable and capable of withstanding a wide range of disturbances especially for the large interconnected systems. In the last decade and a half and in particular after the famous blackout in N.Y. U.S.A. 1965, considerable research effort has gone in to the stability investigation of power systems. To deal with the requirements of real power systems, various stabilizing control techniques were being developed over the last decade. Conventional control engineering approaches are unable to effectively deal with system complexity, nonlinearities, parameters variations and uncertainties. This dissertation presents a non-linear control technique which relies on prediction of the large power system behaviour. One example of a large modern power system formed by interconnecting the power systems of various states is the South-Eastern Australian power network made up of the power systems of Queensland, New South Wales, Victoria and South Australia. The Model Predictive Control (MPC) for the total power system has been shown to be successful in addressing many large scale nonlinear control problems. However, for application to the high order problems of power systems and given the fast control response required, total MPC is still expensive and is structured for centralized control. This thesis develops a MPC algorithm to control the field currents of generators incorporating them in a decentralized overall control scheme. MPC decisions are based on optimizing the control action in accordance with the predictions of an identified power system model so that the desired response is obtained. Energy Function based design provides good control for direct influence items such as SVC (Static Var Compensators), FACTS (Flexible AC Transmission System) or series compensators and can be used to define the desired flux for generator. The approach in this thesis is to use the design flux for best system control as a reference for MPC. Given even a simple model of the relation between input control signal and the resulting machine flux, the MPC can be used to find the control sequence which will start the correct tracking. The continual recalculation of short time optimal control and then using only the initial control value provides a form of feedback control for the system in the desired tracking task but in a manner which retains the nonlinearity of the model.

Thesis (Ph. D.)--University of Wyoming, 2005. / Title from PDF title page (viewed on Oct. 16, 2007). Includes bibliographical references (p. 117-120).

Thesis (Ph. D.)--University of Adelaide, 1992. / Includes bibliographical references (leaves 329-349).