Decreasing costs of renewable energy resources and net-zero emission energy production policy, set by U.S. government, are two preeminent factors that motivate power utilities to deploy more system- or consumer-centric distributed energy resources (DERs) to decarbonize electricity production. Since, deep energy decarbonization cannot be achieved without high penetration of renewable energy sources, utilities should develop and invest in new business models for power system operation and planning during the energy transition. Considering the pathways to deeply decarbonize power systems, first, this dissertation proposes a novel hierarchical peer-to-peer (P2P) energy market design in active distribution networks. The framework integrates the distributional locational marginal price to a multi-round double auction with average price mechanism to integrate the network usage charges into the bills of customers. Second, this dissertation investigates the role of grid-integrated hydrogen (H2) systems for improved utility operations and to supply fuel to transportation sector. Power quality concerns as well as risk of uncertain parameters are considered using conditional value at risk based epsilon constraint method. Third, this dissertation proposes a bi-level proactive rolling-horizon based scheduling of H2 systems in integrated distribution and transmission networks considering the flexibility of these assets as controllable load or generation, in addressing the utility operators' normal and emergency operation signals. Fourth, a detailed model is developed for grid-integrated Electrolyzer considering polarization curve and non-linear conversion efficiency of these assets in the P2P enabled distribution network. This framework shows that reasonable penetration of P2P energy exchanges can significantly lower the H2 production cost. Finally, this dissertation proposes a cyber-physical vulnerability assessment of P2P energy exchanges in an unbalanced active distribution networks. Simulation results of this dissertation show the effectiveness of the proposed frameworks.


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Graduation Date





Sun, Wei


Doctor of Philosophy (Ph.D.)


College of Engineering and Computer Science


Electrical and Computer Engineering

Degree Program

Electrical Engineering


CFE0009182; DP0026778





Release Date

August 2022

Length of Campus-only Access


Access Status

Doctoral Dissertation (Open Access)