The modern power system is undergoing significant changes. There is an urgent requirement for resilience against extreme natural disasters. It faces many new operational challenges from the growing load and increasing installation of distributed generation (DG). The energy market is expanding to the distribution level. Hense, new technological breakthroughs are needed to tackle these problems. This dissertation develops a framework for modern power distribution system planning, operation, and market partidipation using advanced optimization techniques.

This work starts with a stochastic resilience enhancement planning problem that addresses the equity aspect of resilience. The model takes into account both the cost-based objective and equity-based objective; it coordinates the dynamic microgrid formation and load restoration from black-start units (BSU) in an innovative way. Moreover, the planning framework integrates the sequential restoration from BSU. With DGs, tie switches, and BSU, the distribution system can eventually be restored as several dynamic microgrids after black-outs. The proposed method can allocate emergency resources among different locations more equitably.

After equiable-resilience oriented planning is tackled, we turn to consider the operational challenges from the increasing load in the distribution network, which gives rise to higher requiremet on voltage stability. This dissertation proposes a voltage-stability constrained optimal power flow (VSC-OPF) for an unbalanced distribution system with DGs based on semidefinite programming (SDP). The AC optimal power flow (ACOPF) for unbalanced distribution systems is formulated as a chordal relaxation-based SDP model. The minimal singular value (MSV) of the power flow Jacobian matrix is adopted to indicate the voltage stability margin. The Jacobian matrix can be explicitly expressed by ACOPF state variables. The nonlinear constraint on the Jacobian MSV is then replaced with its maximal convex subset using Linear Matrix Inequality (LMI), which can be incorporated in the SDP ACOPF formulation. A penalty technique is leveraged to improve the exactness of the SDP relaxation. This is the first time a MSV-based convex VSC-OPF is proposed for the unbalanced distribution systems.

Finally, we investigate the market participation of an energy hub (EH) in the local energy market. The increasing interdependence among different energy systems has led to the development of the integrated energy system (IES), where the EH is a primary market player in the distribution-level energy market. In an EH, subsystems such as electric, natural gas, and heating systems coexist and are interdependent. This paper proposes an innovative bilevel strategic decision-making framework of an EH that maximizes profit in the energy market and simultaneously reallocates profit among EH subsystems through a dynamic pricing mechanism. In the upper level, the EH acts as a price maker in the day-ahead distribution electricity market for profit maximization. In the lower level, Nash-Bargaining-based profit redistribution is realized through bilateral pricing between energy subsystems in the EH, where the fairness and interests of individual subsystems are respected. The price-responsive load couples the profit maximization and profit reallocation problems. Case studies demonstrate that the proposed framework can effectively solve the bidding and pricing problem of an EH in a day-ahead market, and the cooperation within energy subsystems contributes to higher overall profit and better fairness for the EH subsystems.

Degree Date

Winter 12-2023

Document Type


Degree Name



Electrical and Computer Engineering


Jianhui Wang

Number of Pages




Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

Available for download on Sunday, November 08, 2026