Semester

Fall

Date of Graduation

2010

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Industrial and Managements Systems Engineering

Committee Chair

Wafik Iskander

Abstract

Electric Power Distribution Expansion Planning (PDEP) is concerned with finding the best topology of the power distribution grid and component sizing such that power demand at each load bus is satisfied and some objectives are optimized. In this research, a new integrated time-phased problem is considered, where demand changes through the planning horizon and distributed generation sources and energy storages are integrated into the planning process. The growth of power demand in consecutive periods may require an upgrade of existing or construction of new substations and/or feeders during the planning time-span. An alternative solution to meet the growing demand and to defer (or avoid) the transmission and distribution upgrades may be the addition of energy storage and/or generation sources into the grid. The objective of the problem is to minimize the present worth of installation, upgrade, operation and maintenance, customer interruption, and fuel costs throughout the planning horizon while satisfying a set of given criteria. Thermal capacities of feeders, node voltage constraints, reliability and security issues, renewable portfolio obligations, as well as restrictions on the available capital for investments are considered in the research.;Due to the many one-time decisions (construct or not, upgrade or retain) and the non-linear nature of power flows, the problem has a combinatorial structure and a mixed integer non-linear formulation could be developed. Hence, only small size problems can be solved in a reasonable time using exact optimization techniques. To mitigate the computational burden, and to speed up the solution procedure for real size networks, a two-phase heuristic algorithm is developed. The algorithm employs a piecewise linearization procedure to convert the non-linear terms into linear. The resulting mixed integer linear programming problem is then solved using intelligent search techniques. The heuristic algorithm provides a set of good expansion alternatives that gives the decision maker flexibility in choosing the final expansion plan.

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