Evaluation and Ranking of Electrical Transmission Reinforcement Options Using Machine Learning Techniques

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An electrical power grid comprises of three basic elements: power generating stations, load centres, andtransmission lines. A transmission line connects a generating station with a load centre, and the topology of apower grid evolves over time. Drawing a new transmission line from a generating station to a load centre is acomplex decision process involving: (D1) satisfaction of feasibility constraints, policies, and environmentalconstraints, among others; (D2) cost-benefit analysis; and (D3) optimization of power flow. Before carrying outsteps D2 and D3, a grid operator may want to evaluate and rank all possible instances of a new transmissionline by considering D1. In this project, we will develop a framework to evaluate and rank the instances of anew transmission line in a given power grid. The inputs to the framework will be: (i) the topology of the powergrid; (ii) a GPS (Global Positioning System) annotated geographic map of the physical space covered by thegrid; (iii) important features of the geographic space, namely, cities, water bodies, mountains, and off-limitareas; and (iv) regulatory and environmental constraints. The output from the framework will be a ranked listof potential routes for a new transmission line. Each instance of a new transmission line will be described bymeans of a tuple: