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Date of Award


Document Type

Campus Access Master's Thesis

Degree Name

Master of Science in Electrical Engineering (MS)

Administrative Home Department

Department of Electrical and Computer Engineering

Advisor 1

Sumit Paudyal

Committee Member 1

Daniel R. Fuhrmann

Committee Member 2

Mads R. Almassalkhi


This work proposes a Mixed Integer Second Order Cone Programming (MISOCP) model for Distribution Optimal Power Flow (DOPF) by incorporating conic model of voltage control through a Load Tap Changer (LTC) as discrete control. A novel algorithm, Sequential Bound Tightening Algorithm (SBTA), is also developed to solve the proposed model. The algorithm improves accuracy and the formulation along with the algorithm permits computational tractability on practical-sized systems. The proposed model and the algorithm are tested and benchmarked against the results from a standard Mixed Integer Nonlinear Programming (MINLP) model. The results show that the model is sufficiently accurate and scales well on larger systems.

Additionally, a Mixed Integer Conic Reformulation of the UC problem is also proposed whose computational efficiency is further enhanced by incorporating convex hull of difficult inter-temporal constraints. The results show that the proposed model outperforms MINLP by a large factor and it even outperforms commonly used MILP model on larger systems.