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Risk-Based Approaches to Transmission Expansion Planning
Abstract
The best course of action to increase the transmission capacity of a network is decided by implementing either an investor-planner process or a planner-investor process. In these processes, transmission planners must evaluate, in an uncertain environment, the operational and/or economic merit of transmission capacity proposals to select the most favorable proposal for electric power consumers. Criteria for selection are embodied in the objective function of stochastic optimization models that are formulated to compare the proposals' merit. The objective function value is a random variable represented by a probability distribution, and the expected value of the distribution is, in general, the criterion of preference for the selection. This dissertation investigates new criteria for solving the proposal selection problem. Two new procedures are developed, each procedure uses its own criterion and is general in a sense that any optimization model and any relevant uncertain parameters can be accommodated for the selection. The procedures implement simulation techniques to estimate the distribution of the objective function value associated with proposals, and value-at-risk and mean-and-variance value of the objective function value are the criteria for proposal selection. The procedures estimate the distribution with a given user's specified level of confidence that is representative of the criteria value used for the selection. To test the procedures, this dissertation presents two optimization models that include relevant uncertain parameters. Numerical examples are used to demonstrate the implementation of the proposed procedures and to contrast their selection with the selection obtained by implementing expected value-based approaches.
Subject Area
Electrical engineering|Energy
Recommended Citation
Cervantes, Jairo, "Risk-Based Approaches to Transmission Expansion Planning" (2019). ETD collection for University of Nebraska-Lincoln. AAI13860274.
https://digitalcommons.unl.edu/dissertations/AAI13860274