Date of Award
Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering
Jun Zhang, Ph.D.
Smart grid, Distribution level, Real-rime nodal pricing
During the development of smart grid at distribution level, the realization of real-time nodal pricing is one of the key challenges. This thesis proposes a novel methodology of locational marginal pricing at power distribution level. The nodal pricing mechanism is implemented utilizing both Direct Current Optimal Power Flow and Alternate Current Optimal Power Flow. The University of Denver campus power grid is used to develop the simulation test bed of the distribution level power system. In order to realize our approach, the first step is to extract the network topology from the DU campus grid utility map. The network topology is used to represent the power buses and connections. The extracted network topology is used to develop a Matlab Simulink based simulation test bed for study the proposed nodal pricing mechanism. The proposed nodal pricing mechanism utilizes optimal power flow to calculate the corresponding distributional nodal prices. The two different DLMP approaches have the same objective function, and different constraints are added in the formulation of the two models, according to the different characteristics of AC transmission system and DC transmission system. Both of the two models utilize the major principles of Locational Marginal Pricing to calculate the nodal pricing, which means the DLMP take considerations on marginal energy cost, marginal congestion cost and marginal loss cost. The detailed descriptions of the approaches and evaluation results are documented in this thesis. The experimental results using DU campus power grid verify the feasibility and effectiveness of the proposed approaches for the DLMP mechanism.
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Received from ProQuest
Hao, Jun, "Locational Marginal Pricing at the Power Distribution Level" (2015). Electronic Theses and Dissertations. 1070.
Electrical Engineering, Engineering