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 evaluation of composite system reliability is extremely complex as it is necessary to include detailed modeling of both generation and transmission facilities and their auxiliary elements. The most significant quantitative indices in composite power system adequacy evaluation are those which relate to load curtailment. Many utilities have difficulty in interpreting the expected load curtailment indices as the existing models are based on adequacy analysis and in many cases do not consider realistic operating conditions in the system under study. This thesis presents a security based approach which alleviates this difficulty and provides the ability to evaluate the well-being of customer load points and the overall composite generation and transmission power system. Acceptable deterministic criteria are included in the probabilistic evaluation of the composite system reliability indices to monitor load point well-being. The degree of load point well-being is quantified in terms of the healthy and marginal state indices in addition to the traditional risk indices. The individual well-being indices of the different system load points are aggregated to produce system indices. This thesis presents new models and techniques to quantify the well-being of composite generation and, direct and alternating current transmission systems. Security constraints are basically the operating limits which must be satisfied for normal system operation. These constraints depend mainly on the purpose behind the study. The constraints which govern the practical operation of a power system are divided, in this thesis, into three sets namely, steady-state, voltage stability and transient stability constraints. The inclusion of an appropriate transient stability constraint will lead to a more accurate appraisal of the overall power system well-being. This thesis illustrates the utilization of a bisection method in the analytical evaluation of the critical clearing time which forms the basis of most existing stability assessments. The effect of employing high-speed-simultaneous or adaptive reclosing schemes is presented in this thesis. An effective and fast technique to incorporate voltage stability considerations in composite generation and transmission system reliability evaluation is also presented. The proposed technique can be easily incorporated in an existing composite power system reliability program using voltage stability constraints that are constructed for individual load points based on a relatively simple risk index. It is believed that the concepts, procedures and indices presented in this thesis will provide useful tools for power system designers, planners and operators and assist them to perform composite system well-being analysis in addition to traditional risk assessment.

Renewable energy policies, such as the Renewable Portfolio Standard, arising from increasing environmental concerns have set very ambitious targets for wind power penetration in electric power systems throughout the world. In many cases, the geographical locations with good wind resources are not close to the main load centers. It becomes extremely important to assess adequate transmission facility to deliver wind power to the power grid. <p>Wind is a highly variable energy source, and therefore, transmission system planning for wind delivery is very different from conventional transmission planning. Most electric power utilities use a deterministic n-1 criterion in transmission system planning. Deterministic methods cannot recognize the random nature of wind variation that dictates the power generated from wind power sources. This thesis presents probabilistic method to evaluate the contribution of a wind power delivery system to the overall system reliability. The effects of site-specific wind regime, system load, transmission line unavailability, and redundancy on system reliability were studied using a basic system model. The developed method responds to the various system parameters and is capable of assessing the actual system risks. <p>Modern power system aims to provide reliable as well as cost effective power supply to its consumers. Reliability benefits, environmental benefits and operating cost savings from wind power integration should be compared with the associated investment costs in order to determine optimum transmission facility for wind power delivery. This thesis presents the reliability/cost techniques for determining appropriate transmission line capacity to connect a wind farm to a power grid. The effect of transmission system cost, line length, wind regime, wind penetration and customer interruption cost on the optimum transmission line sizing were studied using a basic system model. The methodology and results presented in this thesis should be useful in transmission system planning for delivering wind power to a power system.

Renewal process has been often employed as a mathematical model of the failure and repair cycle of components in power system reliability assessment. This implies that after repair, the component is assumed to be restored to be in as good as new condition in terms of reliability perspective. However, some of the components may enter an aging stage as the system grows older. This thesis describes how aging characteristics of a system may impact the calculation of commonly used quantitative reliability indices such as Loss of Load Expectation (LOLE), Loss of Load Duration (LOLD), and Expected Energy Not Supplied (EENS). To build the history of working and failure states of a system, Stochastic Point Process modeling based on Sequential Monte Carlo simulation is introduced. Power Law Process is modeled as the failure rate function of aging components. Power system reliability analysis can be made at the generation capacity level where transmission constraints may be included. The simulation technique is applied to the Single Area IEEE Reliability Test System (RTS) and the results are evaluated and compared. The results show that reliability indices become increased as the age of the system grows.

Circuit breakers are used in a power system to break or make current flow through power system apparatus. Reliable operation of circuit breakers is very important to the well-being of the power system. Historically this is achieved by regular inspection and maintenance of the circuit breakers. An automated online circuit breaker monitoring system is proposed to monitor condition, operation and status of high and medium voltage circuit breakers. By tracking equipment condition, this system could be used to perform maintenance only when it is needed. This could decrease overall maintenance cost and increase equipment reliability. Using high accurate time synchronization, this system should enable development of system-wide applications that utilize the data recorded by the system. This makes possible tracking sequence of events and making conclusions about their effect on-line. This solution also enables reliable topology analysis, which can be used to improve power flow analysis, state estimation and alarm processing.

Power system operation requires accurate monitoring of electrical quantities and a reliable database of the power system. As the power system operation becomes more competitive, the secure operation becomes highly important and the role of state estimation becomes more critical. Recently, due to the development of new technology in high power electronics, new control and monitoring devices are becoming more popular in power systems. It is therefore necessary to investigate their models and integrate them into the existing state estimation applications. This dissertation is dedicated to exploiting the newly appeared controlling and monitoring devices, such as Flexible AC Transmission System (FACTS) devices and (Phasor Measurement Units) PMUs, and developing new algorithms to include them into power system analysis applications. Another goal is to develop a 3D visualization tool to help power system operators gain an in-depth image of the system operation state and to identify limit violations in a quick and intuitive manner. An algorithm of state estimation of a power system with embedded FACTS devices is developed first. This estimator can be used to estimate the system state quantities and Unified Power Flow Controller (UPFC) controller parameters. Furthermore, it can also to be used to determine the required controller setting to maintain a desired power flow through a given line. In the second part of this dissertation, two methods to determine the optimal locations of PMUs are derived. One is numerical and the other one is topological. The numerical method is more effective when there are very few existing measurements while the topology-based method is more applicable for a system, which has lots of measurements forming several observable islands. To guard against unexpected failures of PMUs, the numerical method is extended to account for single PMU loss. In the last part of this dissertation, a 3D graphic user interface for power system analysis is developed. It supports two basic application functions, power flow analysis and state estimation. Different visualization techniques are used to represent different kinds of system information.

This objective of thesis is to derive the adaptive load shedding by artificial neural network (ANN) so that the amount of load shedding can be minimized. An actual industrial customer and Taipower system are selected for computer simulation to fit the ANN model. The mathematical models of generation, exciters, governors and loads are used in the simulator program. The back propagation neural method is considered for the neural network training of load shedding.To create the training data set for ANN models, the transient stability analysis is performed to fit the load shedding under different operation and fault condition. The back propagation method and L-M learning process are then used to fit the minimum load shedding without causing system stability problem. To verify the effectiveness of the proposed methodology for adaptive load shedding, three fault contingencies for both the industrial cogeneration system and Taipower system have been simulated. By compare to the conventional load shedding, it is found that the amount of load shedding can be minimized and adjusted according to the real time operation conditions of power systems.

The electric power systems in U.S. Navy ships supply energy to sophisticated systems for weapons, communications, navigation and operation. The reliability and survivability of the Shipboard Power System (SPS) are critical to the mission of a surface combatant ship, especially under battle conditions. In the event of battle, various weapons might attack a ship. When a weapon hits the ship it can cause severe damage to the electrical system on the ship. This damage can lead to de-energization of critical loads on a ship that can eventually decrease a ship’s ability to survive the attack. It is very important, therefore, to maintain availability of energy to the connected loads that keep the power systems operational. Technology exists that enables the detection of an incoming weapon and prediction of the geographic area where the incoming weapon will hit the ship. This information can then be used to take reconfiguration actions before the actual hit so that the actual damage caused by the weapon hit is reduced. The Power System Automation Lab (PSAL) has proposed a unique concept called "Predictive Reconfiguration" which refers to performing reconfiguration of a ship’s power system before a weapon hit to reduce the potential damage to the electrical system caused by the impending weapon hit. The concept also includes reconfiguring the electrical system to restore power to as much of the healthy system as possible after the weapon hit. This dissertation presents a new methodology for Predictive Reconfiguration of a Shipboard Power System (SPS). This probabilistic approach includes a method to assess the damage that will be caused by a weapon hit. This method calculates the expected probability of damage for each electrical component on the ship. Also a heuristic method is included, which uses the expected probability of damage to determine reconfiguration steps to reconfigure the ship’s electrical network to reduce the damage caused by a weapon hit. This dissertation also presents a modified approach for performing a reconfiguration for restoration after the weapon hits the system. In this modified approach, an expert system based restoration method restores power to loads de-energized due to the weapon hit. These de-energized loads are restored in a priority order. The methods were implemented using multi-agent technology. A test SPS model based on the electrical layout of a non-nuclear surface combatant ship was presented. Complex scenarios representing electrical casualties caused due to a weapon hit, on the test SPS model, were presented. The results of the Predictive Reconfiguration methodology for complex scenarios were presented to illustrate the effectiveness of the developed methodology.

This dissertation has focused on automated power system fault analysis. New contributions to fault section estimation, protection system performance evaluation and power system/protection system interactive simulation have been achieved. Intelligent techniques including expert systems, fuzzy logic and Petri-nets, as well as data from remote terminal units (RTUs) of supervisory control and data acquisition (SCADA) systems, and digital protective relays have been explored and utilized to fufill the objectives. The task of fault section estimation is difficult when multiple faults, failures of protection devices, and false data are involved. A Fuzzy Reasoning Petri-nets approach has been proposed to tackle the complexities. In this approach, the fuzzy reasoning starting from protection system status data and ending with estimation of faulted power system section is formulated by Petri-nets. The reasoning process is implemented by matrix operations. Data from RTUs of SCADA systems and digital protective relays are used as inputs. Experiential tests have shown that the proposed approach is able to perform accurate fault section estimation under complex scenarios. The evaluation of protection system performance involves issues of data acquisition, prediction of expected operations, identification of unexpected operations and diagnosis of the reasons for unexpected operations. An automated protection system performance evaluation application has been developed to accomplish all the tasks. The application automatically retrieves relay files, processes relay file data, and performs rule-based analysis. Forward chaining reasoning is used for prediction of expected protection operation while backward chaining reasoning is used for diagnosis of unexpected protection operations. Lab tests have shown that the developed application has successfully performed relay performance analysis. The challenge of power system/protection system interactive simulation lies in modeling of sophisticated protection systems and interfacing the protection system model and power system network model seamlessly. An approach which utilizes the "compiled foreign model" mechanism of ATP MODELS language is proposed to model multifunctional digital protective relays in C++ language and seamlessly interface them to the power system network model. The developed simulation environment has been successfully used for the studies of fault section estimation and protection system performance evaluation.

Circuit breakers are used in a power system to break or make current flow through power system apparatus. Reliable operation of circuit breakers is very important to the well-being of the power system. Historically this is achieved by regular inspection and maintenance of the circuit breakers. An automated online circuit breaker monitoring system is proposed to monitor condition, operation and status of high and medium voltage circuit breakers. By tracking equipment condition, this system could be used to perform maintenance only when it is needed. This could decrease overall maintenance cost and increase equipment reliability. Using high accurate time synchronization, this system should enable development of system-wide applications that utilize the data recorded by the system. This makes possible tracking sequence of events and making conclusions about their effect on-line. This solution also enables reliable topology analysis, which can be used to improve power flow analysis, state estimation and alarm processing.