Judicious Power System Planning ensures the adequacy of infrastructure to support continuous reliability and economy of power system operations. Planning processes have a long and rather successful history in the United States, but the recent infl‚ux of unpredictable, nondispatchable generation such as Wind Energy Conversion Systems (WECS) necessitates the re-evaluation of the merit of planning methodologies in the changing power system context. Traditionally, planning has followed a logical progression through generation, transmission, reactive power, and finally auxiliary system planning using expertise and ranking schemes. However, it is challenging to incorporate all of the inherent dependencies between expansion candidates' system impacts using these schemes. Simulation based optimization provides a systematic way to explore acceptable expansion plans and choose one or several "best" plans while considering those complex dependencies. Using optimization to solve the minimum-cost, reliability-constrained Generation and Transmission Expansion Problem (GTEP) is not a new concept, but the technology is not mature. This work inspects: load uncertainty modeling; sequential (GEP then TEP) versus unified (GTEP) models; and analyzes the impact on the methodologies achieved near-optimal plan. A sensitivity simulation on the original system and final, upgraded system is performed. / Master of Science

Two of the most significant challenges facing the world in the 21st century are improving energy security and mitigating the effects of climate change. To counter these challenges, renewable energy sources, such as wind, are considered a possible solution and have gained importance worldwide. With many jurisdictions setting high wind-energy targets for the coming decades, risks have grown as the demand for new wind turbines has outstripped the growth of its suppliers. Integrating significant amounts of wind-electricity into existing networks raises reliability concerns due to variable nature of wind. A method for estimating the reliability of wind-energy systems is presented which is a combination of a forecasting method (probabilistic approach) and RL (Resistance-Load) technique (risk-based approach), demonstrated through a case study, and verified using real-time wind farm data.

abstract: Contemporary methods for dynamic security assessment (DSA) mainly re-ly on time domain simulations to explore the influence of large disturbances in a power system. These methods are computationally intensive especially when the system operating point changes continually. The trajectory sensitivity method, when implemented and utilized as a complement to the existing DSA time domain simulation routine, can provide valuable insights into the system variation in re-sponse to system parameter changes. The implementation of the trajectory sensitivity analysis is based on an open source power system analysis toolbox called PSAT. Eight categories of sen-sitivity elements have been implemented and tested. The accuracy assessment of the implementation demonstrates the validity of both the theory and the imple-mentation. The computational burden introduced by the additional sensitivity equa-tions is relieved by two innovative methods: one is by employing a cluster to per-form the sensitivity calculations in parallel; the other one is by developing a mod-ified very dishonest Newton method in conjunction with the latest sparse matrix processing technology. The relation between the linear approximation accuracy and the perturba-tion size is also studied numerically. It is found that there is a fixed connection between the linear approximation accuracy and the perturbation size. Therefore this finding can serve as a general application guide to evaluate the accuracy of the linear approximation. The applicability of the trajectory sensitivity approach to a large realistic network has been demonstrated in detail. This research work applies the trajectory sensitivity analysis method to the Western Electricity Coordinating Council (WECC) system. Several typical power system dynamic security problems, in-cluding the transient angle stability problem, the voltage stability problem consid-ering load modeling uncertainty and the transient stability constrained interface real power flow limit calculation, have been addressed. Besides, a method based on the trajectory sensitivity approach and the model predictive control has been developed for determination of under frequency load shedding strategy for real time stability assessment. These applications have shown the great efficacy and accuracy of the trajectory sensitivity method in handling these traditional power system stability problems. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

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The objectives of this study are (1) to develop an accurate and efficient fatigue analysis procedure that can be used in reliability analysis and reliability-based design optimization (RBDO) of composite wind turbine blades; (2) to develop a wind load uncertainty model that provides realistic uncertain wind load for the reliability analysis and the RBDO process; and (3) to obtain an optimal composite wind turbine blade that satisfies target reliability for durability under the uncertain wind load. The current research effort involves: (1) developing an aerodynamic analysis method that can effectively calculate detailed wind pressure on the blade surface for stress analysis; (2) developing a fatigue failure criterion that can cope with non-proportional multi-axial stress states in composite wind turbine blades; (3) developing a wind load uncertainty model that represents realistic uncertain wind load for fatigue reliability of wind turbine systems; (4) applying the wind load uncertainty model into a composite wind turbine blade and obtaining an RBDO optimum design that satisfies a target probability of failure for a lifespan of 20 years under wind load uncertainty. In blade fatigue analysis, resultant aerodynamic forces are usually applied at the aerodynamic centers of the airfoils of a blade to calculate stress/strain. However, in reality the wind pressures are applied on the blade surface. A wind turbine blade is often treated as a typical beam-like structure for which fatigue life calculations are limited in the edge-wise and/or flap-wise direction(s). Using the beam-like structure, existing fatigue analysis methods for composite wind turbine blades cannot cope with the non-proportional multi-axial stress states that are endured by wind turbine blades during operation. Therefore, it is desirable to develop a fatigue analysis procedure that utilizes detailed wind pressures as wind loads and considers non-proportional multi-axial stress states in fatigue damage calculation. In this study, a 10-minute wind field realization, determined by a 10-minute mean wind speed V10 and a 10-minute turbulence intensity I10, is first simulated using Veers’ method. The simulated wind field is used for aerodynamic analysis. An aerodynamic analysis method, which could efficiently generate detailed quasi-physical blade surface pressures, has been developed. The generated pressures are then applied on a high-fidelity 3-D finite element blade model for stress and fatigue analysis. The fatigue damage calculation considers the non-proportional multi-axial complex stress states. A detailed fatigue damage contour, which indicates the fatigue failure locally, can be obtained using the developed fatigue analysis procedure. As the 10-minute fatigue analysis procedure is deterministic in this study, the calculated 10-minute fatigue damage is determined by V10 and I10. It is necessary to clarify that the rotational speed of the wind turbine blade is assumed to be constant (12.1 rpm) and the pitch angle is fixed to be 0 degree for different wind conditions, since the rotational speed control and pitch angle control have not been considered in this study. For predicting the fatigue life of a wind turbine, a fixed Weibull distribution is widely used to determine the percentage of time the wind turbine experiences different mean wind speeds during its life-cycle. Meanwhile, fixed turbulence intensities are often used based on the designed wind turbine types. These simplifications, i.e., fixed Weibull distribution and fixed turbulence intensities, ignore the realistic uncertain wind load when designing a reliable wind turbine system. In the real world, both the mean wind speed and turbulence intensity vary constantly over one year, and their annual distributions are different at different locations and in different years. Thus, it is necessary to develop a wind load uncertainty model that can provide a realistic uncertain wind load for designing reliable wind turbine systems. In this study, 249 groups of measured wind data, collected at different locations and in different years, are used to develop a dynamic wind load uncertainty model. The dynamic wind load uncertainty model consists of annual wind load variation and wind load variation in a large spatiotemporal range, i.e., at different locations and in different years. The annual wind load variation is represented by the joint probability density function of V10 and I10. The wind load variation in a large spatiotemporal range is represented by the probability density functions of five parameters, C, k, a, b, and τ, which determine the joint probability density function of V10 and I10. In order to obtain the RBDO optimum design efficiently, a deterministic design optimization (DDO) procedure of a composite wind turbine blade has been first carried out using averaged percentage of time (probability) for each wind condition. A wind condition is specified by two terms: 10-minute mean wind speed and 10-minute turbulence intensity. In this research, a probability table, which consists of averaged probabilities corresponding to different wind conditions, is referred as a mean wind load. The mean wind load is generated using the dynamic wind load uncertainty model. During the DDO process, the laminate thickness design variables are tailored to minimize the total cost of composite materials while satisfying the target fatigue lifespan of 20 years. It is found that, under the mean wind load condition, the fatigue life of the initial design is only 0.0004 year. After the DDO process, even though the cost at the DDO optimum design is increased by 31.5% compared to that at the initial design, the predicted fatigue life at the DDO optimum design is significantly increased to 19.9995 years. Reliability analyses of the initial design and the DDO optimum design have been carried out using the wind load uncertainty model and Monte Carlo simulation. The reliability analysis results show that the DDO procedure reduces the probability of failure from 100% at the initial design to 49.9% at the DDO optimum design considering only wind load uncertainty. In order to satisfy the target 2.275% probability of failure, it is necessary to further improve the fatigue reliability of the composite wind turbine blade by RBDO. Reliability-based design optimization of the composite wind turbine blade has been carried out starting at the DDO optimum design. Fatigue hotspots for RBDO are identified among the laminate section points, which are selected from the DDO optimum design. Local surrogate models for 10-minute fatigue damage have been created at the selected hotspots. Using the local surrogate models, both the wind load uncertainty and manufacturing variability has been included in the RBDO process. It is found that the probability of failure is 50.06% at the RBDO initial design (DDO optimum design) considering both wind load uncertainty and manufacturing variability. During the RBDO process, the normalized laminate thickness design variables are tailored to minimize the total cost of composite materials while satisfying the target 2.275% probability of failure. The obtained RBDO optimum design reduces the probability of failure from 50.06% at the DDO optimum design to 2.28%, while increasing the cost by 3.01%.

The basic objective in bulk electrical system planning is to determine the necessary generating facilities required to ensure an adequate and economic supply of electrical energy and the development of an adequate transmission network to transport the generated energy to the customers. Quantitative adequacy assessment is a basic task in achieving this objective. An important requirement in this task is the ability to forecast the system load requirements at specific times in the future. These forecasts must also recognize the inherent uncertainty in predicting the future load demands.<p> The primary focus of the research described in this thesis is to examine the effects and implications of load forecast uncertainty on the load point and system adequacy indices of a composite generation and transmission system. This thesis considers two techniques to incorporate the inherent uncertainty associated with future load forecasts in the adequacy assessment of bulk electrical systems. Base case and factor analyses are performed on a number of power system configurations to identify and address the relative contributions to the load point and system indices due to load forecast uncertainty. A transmission reinforcement option and a number of generation system expansion options are presented to examine the system reliability response due to load forecast uncertainty.<p> The actual magnitudes of the changes due to load forecast uncertainty in the load bus and system risk indices and in the percentage change values are different for each generation expansion scenario. The topology and parameters of the system are different in each of the studied power system configurations. The effect of load forecast uncertainty on the system and load point adequacy can be quantified and utilized in the decision-making process associated with system generation and transmission planning. Load forecast uncertainty has important impacts on the system and load point indices that can only be appreciated by conducting comprehensive bulk system adequacy assessment. The actual effects are a complicated function of the system topology and parameters, and the system load curtailment philosophy.

The basic objective in bulk electrical system planning is to determine the necessary generating facilities required to ensure an adequate and economic supply of electrical energy and the development of an adequate transmission network to transport the generated energy to the customers. Quantitative adequacy assessment is a basic task in achieving this objective. An important requirement in this task is the ability to forecast the system load requirements at specific times in the future. These forecasts must also recognize the inherent uncertainty in predicting the future load demands.<p> The primary focus of the research described in this thesis is to examine the effects and implications of load forecast uncertainty on the load point and system adequacy indices of a composite generation and transmission system. This thesis considers two techniques to incorporate the inherent uncertainty associated with future load forecasts in the adequacy assessment of bulk electrical systems. Base case and factor analyses are performed on a number of power system configurations to identify and address the relative contributions to the load point and system indices due to load forecast uncertainty. A transmission reinforcement option and a number of generation system expansion options are presented to examine the system reliability response due to load forecast uncertainty.<p> The actual magnitudes of the changes due to load forecast uncertainty in the load bus and system risk indices and in the percentage change values are different for each generation expansion scenario. The topology and parameters of the system are different in each of the studied power system configurations. The effect of load forecast uncertainty on the system and load point adequacy can be quantified and utilized in the decision-making process associated with system generation and transmission planning. Load forecast uncertainty has important impacts on the system and load point indices that can only be appreciated by conducting comprehensive bulk system adequacy assessment. The actual effects are a complicated function of the system topology and parameters, and the system load curtailment philosophy.