Thesis (M.S.)--University of Missouri--Rolla, 2007. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed April 17, 2007) Includes bibliographical references (p. 88-91).

The United State’s renewable portfolio standards call for a large increase of renewable energy and improved conservation efforts over today’s current system. Wind will play a ma jor role in meeting the renewable portfolio standards. As a result, the amount of wind capacity and generation has been growing exponentially over the past 10 to 15 years. The proposed unit commitment method integrates wind energy into a scheduable resource while keeping the formulation simple using mixed integer programming. A reserve constraint is developed and added to unit commitment giving the forecasted wind energy an effective cost. The reserve constraint can be scaled based on the needs of the system: cost, reliability, or the penetration of wind energy. The results show that approximately 24% of the load can be met in the given test system, while keeping a constant reliability before and after wind is introduced. This amount of wind will alone meet many of the renewable portfolio standards in the United States.

The U.S. Navy has developed in their ships, and is continually improving, electric propulsion, ship service power, and electric loads. The latest topology under design is the integrated power system (IPS). The IPS entails the all electric ship concept with electric propulsion, direct current (DC) distribution, and modular technology. In the all electric ship concept, ship propulsion and ship service loads are powered by alternating current (AC) generation. For the IPS, power electronics conversion is to be utilized to convert alternating current (AC) generation to direct current (DC) distribution. As state-of-the-art power electronics, the Navy plans to use power electronic building blocks (PEBB) technology in its IPS. A U.S. naval shipboard power system is required to be a highly reconfigurable system to enhance its survivability and reliability. Reconfiguration is a change in the shipboard power system state for various reasons such as new topology, changing missions and emergencies. It was decided to study the behavior of a PEBB-based integrated shipboard power system during reconfiguration. Since no real time operation data was available, the problem was studied through the simulation of reconfiguration scenarios on a scaled-down computer model of an IPS in MATLAB. Reconfiguration scenarios were determined and staged, and an AC/DC power system stability assessment methodology was applied by decoupling the IPS test system around an intrazonal bus. The coupled system of the test IPS, consisted of two dynamic 4160 VAC generators, two rectifiers, two DC-DC converters between the rectifiers' output looped bus and the downstream intrazonal 775V busses, inverters, buck converters, AC loads and DC loads. There was modeling of excitation perturbations which introduced errors in the assessment of the stability requiring an approximation analysis. The study found that the DC bus of interest was stable for all nine reconfiguration scenarios staged, but it found that other busses were not stable for two of the scenarios. The study further found that lower stability margins occurred at lower frequencies of about 1Hz for stable scenarios. It concluded that there were tangible benefits to advancing the shipboard power system architecture to the IPS topology because of the good stability results.

Future development of electric power systems must pursue anumber of different goals. The power system should beeconomically efficient, it should provide reliable energysupply and should not damage the environment. At the same time,operation and development of the system is influenced by avariety of uncertain and random factors. The planner attemptsto find the best strategy from a large number of possiblealternatives. Thus, the complexity of the problems related topower systems planning is mainly caused by presence of multipleobjectives, uncertain information and large number ofvariables. This dissertation is devoted to consideration of themethods for development planning of a certain subsystem, i.e.the distribution network. The dissertation first tries to formulate the networkplanning problem in general form in terms of Bayesian DecisionTheory. However, the difficulties associated with formulationof the utility functions make it almost impossible to apply theBayesian approach directly. Moreover, when approaching theproblem applying different methods it is important to considerthe concave character of the utility function. Thisconsideration directly leads to the multi-criteria formulationof the problem, since the decision is motivated not only by theexpected value of revenues (or losses), but also by theassociated risks. The conclusion is made that the difficultiescaused by the tremendous complexity of the problem can beovercome either by introducing a number of simplifications,leading to the considerable loss in precision or applyingmethods based on modifications of Monte-Carlo or fuzzyarithmetic and Genetic Algorithms (GA), or Dynamic Programming(DP). In presence of uncertainty the planner aims at findingrobust and flexible plans to reducethe risk of considerablelosses. Several measures of risk are discussed. It is shownthat measuring risk by regret may lead to risky solutions,therefore an alternative measure - Expected Maximum Value - issuggested. The general future model, called fuzzy-probabilistictree of futures, integrates all classes of uncertain parameters(probabilistic, fuzzy and truly uncertain). The suggested network planning software incorporates threeefficient applications of GA. The first algorithm searchessimultaneously for the whole set of Pareto optimal solutions.The hybrid GA/DP approach benefits from the global optimizationproperties of GA and local search by DP resulting in originalalgorithm with improved convergence properties. Finally, theStochastic GA can cope with noisy objective functions. Finally, two real distribution network planning projectsdealing with primary distribution network in the large city andsecondary network in the rural area are studied.

Renewable energy applications in electric power systems have undergone rapid development and increased use due to global environmental concerns associated with conventional energy sources. Photovoltaics and wind energy sources are considered to be very promising alternatives for power generation because of their tremendous environmental, social and economic benefits, together with public support. </p> <p>Electrical power generation from wind and solar energy behaves quite differently from that of conventional sources. The fundamentally different operating characteristics of these facilities therefore affect power system reliability in a different manner than those of conventional systems. The research work presented in this thesis is focused on the development of appropriate models and techniques for wind energy conversion and photovoltaic conversion systems to assess the adequacy of composite power systems containing wind or solar energy.</p> <p>This research shows that a five-state wind energy conversion system or photovoltaic conversion system model can be used to provide a reasonable assessment in practical power system adequacy studies using an analytical method or a state sampling simulation approach. The reliability benefits of adding single or multiple wind/solar sites in a composite generation and transmission system are examined in this research. The models, methodologies, results and discussion presented in this thesis provide valuable information for system planners assessing the adequacy of composite electric power systems incorporating wind or solar energy conversion systems.

The research conducted in this thesis provides a robust implementation of a preconditioned iterative linear solver on programmable graphic processing units (GPUs). Solving a large, sparse linear system is the most computationally demanding part of many widely used power system analysis. This thesis presents a detailed study of iterative linear solvers with a focus on Krylov-based methods. Since the ill-conditioned nature of power system matrices typically requires substantial preconditioning to ensure robustness of Krylov-based methods, a polynomial preconditioning technique is also studied in this thesis. Implementation of the Chebyshev polynomial preconditioner and biconjugate gradient solver on a programmable GPU are presented and discussed in detail. Evaluation of the performance of the GPU-based preconditioner and linear solver on a variety of sparse matrices shows significant computational savings relative to a CPU-based implementation of the same preconditioner and commonly used direct methods.

Wind power is being added to the supply mix of numerous jurisdictions, and an increasing level of uncertainties will be the new reality for many system operators. Accurately estimating these uncertainties and properly analyzing their effects will be very important to the reliable operation of the grid. A method is proposed to use historical wind speed, power, and forecast data to estimate the potential future forecast errors. The method uses the weather conditions and ramp events to improve the accuracy of the estimation. A bilevel programming technique is proposed to quantify the effects of the estimated uncertainties. It improves upon existing methods by modeling the transmission network and the re-dispatch of the generators by operators. The technique is tested with multiple systems to illustrate the feasibility of using this technique to alert system operators to potential problems during operation.

The research conducted in this thesis provides a robust implementation of a preconditioned iterative linear solver on programmable graphic processing units (GPUs). Solving a large, sparse linear system is the most computationally demanding part of many widely used power system analysis. This thesis presents a detailed study of iterative linear solvers with a focus on Krylov-based methods. Since the ill-conditioned nature of power system matrices typically requires substantial preconditioning to ensure robustness of Krylov-based methods, a polynomial preconditioning technique is also studied in this thesis. Implementation of the Chebyshev polynomial preconditioner and biconjugate gradient solver on a programmable GPU are presented and discussed in detail. Evaluation of the performance of the GPU-based preconditioner and linear solver on a variety of sparse matrices shows significant computational savings relative to a CPU-based implementation of the same preconditioner and commonly used direct methods.

Wind power is being added to the supply mix of numerous jurisdictions, and an increasing level of uncertainties will be the new reality for many system operators. Accurately estimating these uncertainties and properly analyzing their effects will be very important to the reliable operation of the grid. A method is proposed to use historical wind speed, power, and forecast data to estimate the potential future forecast errors. The method uses the weather conditions and ramp events to improve the accuracy of the estimation. A bilevel programming technique is proposed to quantify the effects of the estimated uncertainties. It improves upon existing methods by modeling the transmission network and the re-dispatch of the generators by operators. The technique is tested with multiple systems to illustrate the feasibility of using this technique to alert system operators to potential problems during operation.

This thesis presents a method of detecting electrical islands in low voltage distributed generator networks by measuring negative sequence impedance differences between islanded and utility connections. Extensive testing was conducted on a commercial building and 25 kV distributed generator fed network by measuring naturally occurring and artificially injected negative sequence components. Similarly, this technique was tested using the IEEE 399-1990 bus test case using the EMTP software. The practical measurements have been matched to simulations where further system performance characteristics of detecting power system islands has been successfully demonstrated. Measured results indicate that unbalanced load conditions are naturally occurring and readily measurable while deliberately unbalanced loads can increase the accuracy of negative sequence impedance islanding detection. The typically low negative sequence impedance of induction motors was found to have only a small effect in low voltage busses, though large machines can effect the threshold settings. Careful placement of the island detector is required in these situations. The negative sequence impedance measurement method is an improvement on previous impedance measurement techniques for islanding detection due to its accuracy, and distinctly large threshold window which have challenged previous impedance based islanding detection techniques.