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Description
In the deregulated power system, locational marginal prices are used in transmission engineering predominantly as near real-time pricing signals. This work extends this concept to distribution engineering so that a distribution class locational marginal price might be used for real-time pricing and control of advanced control systems in distribution circuits.

In the deregulated power system, locational marginal prices are used in transmission engineering predominantly as near real-time pricing signals. This work extends this concept to distribution engineering so that a distribution class locational marginal price might be used for real-time pricing and control of advanced control systems in distribution circuits. A formulation for the distribution locational marginal price signal is presented that is based on power flow sensitivities in a distribution system. A Jacobian-based sensitivity analysis has been developed for application in the distribution pricing method. Increasing deployment of distributed energy sources is being seen at the distribution level and this trend is expected to continue. To facilitate an optimal use of the distributed infrastructure, the control of the energy demand on a feeder node in the distribution system has been formulated as a multiobjective optimization problem and a solution algorithm has been developed. In multiobjective problems the Pareto optimality criterion is generally applied, and commonly used solution algorithms are decision-based and heuristic. In contrast, a mathematically-robust technique called normal boundary intersection has been modeled for use in this work, and the control variable is solved via separable programming. The Roy Billinton Test System (RBTS) has predominantly been used to demonstrate the application of the formulation in distribution system control. A parallel processing environment has been used to replicate the distributed nature of controls at many points in the distribution system. Interactions between the real-time prices in a distribution feeder and the nodal prices at the aggregated load bus have been investigated. The application of the formulations in an islanded operating condition has also been demonstrated. The DLMP formulation has been validated using the test bed systems and a practical framework for its application in distribution engineering has been presented. The multiobjective optimization yields excellent results and is found to be robust for finer time resolutions. The work shown in this report is applicable to, and has been researched under the aegis of the Future Renewable Electric Energy Delivery and Management (FREEDM) center, which is a generation III National Science Foundation engineering research center headquartered at North Carolina State University.
ContributorsRanganathan Sathyanarayana, Bharadwaj (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2012
Description
Power flow calculation plays a significant role in power system studies and operation. To ensure the reliable prediction of system states during planning studies and in the operating environment, a reliable power flow algorithm is desired. However, the traditional power flow methods (such as the Gauss Seidel method and the

Power flow calculation plays a significant role in power system studies and operation. To ensure the reliable prediction of system states during planning studies and in the operating environment, a reliable power flow algorithm is desired. However, the traditional power flow methods (such as the Gauss Seidel method and the Newton-Raphson method) are not guaranteed to obtain a converged solution when the system is heavily loaded.

This thesis describes a novel non-iterative holomorphic embedding (HE) method to solve the power flow problem that eliminates the convergence issues and the uncertainty of the existence of the solution. It is guaranteed to find a converged solution if the solution exists, and will signal by an oscillation of the result if there is no solution exists. Furthermore, it does not require a guess of the initial voltage solution.

By embedding the complex-valued parameter α into the voltage function, the power balance equations become holomorphic functions. Then the embedded voltage functions are expanded as a Maclaurin power series, V(α). The diagonal Padé approximant calculated from V(α) gives the maximal analytic continuation of V(α), and produces a reliable solution of voltages. The connection between mathematical theory and its application to power flow calculation is described in detail.

With the existing bus-type-switching routine, the models of phase shifters and three-winding transformers are proposed to enable the HE algorithm to solve practical large-scale systems. Additionally, sparsity techniques are used to store the sparse bus admittance matrix. The modified HE algorithm is programmed in MATLAB. A study parameter β is introduced in the embedding formula βα + (1- β)α^2. By varying the value of β, numerical tests of different embedding formulae are conducted on the three-bus, IEEE 14-bus, 118-bus, 300-bus, and the ERCOT systems, and the numerical performance as a function of β is analyzed to determine the “best” embedding formula. The obtained power-flow solutions are validated using MATPOWER.
ContributorsLi, Yuting (Author) / Tylavsky, Daniel J (Thesis advisor) / Undrill, John (Committee member) / Vittal, Vijay (Committee member) / Arizona State University (Publisher)
Created2015