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Generalized optimization in the British Columbia hydroelectric system

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Title: Generalized optimization in the British Columbia hydroelectric system
Author: Fane, Lindsay Alison
Degree: Master of Applied Science - MASc
Program: Civil Engineering
Copyright Date: 2003
Issue Date: 2009-10-21
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]
Abstract: The purpose of this thesis is to provide a decision analysis tool for BC Hydro medium-term planning engineers to enable them to derive optimal generation schedules to assess the feasibility, advantages and disadvantages of operational alternatives. The development of a six-component system facilitates the analysis of BC Hydro operations. A graphical user interface, preprocessor and spreadsheet were designed to collect and manipulate the raw model data, which is copied with communication protocols from a client workstation to a dedicated server for the Generalized Optimization Model. AMPL and CPLEX are the programming language and off-the-shelf solver that find the optimization problem solution, whose results are copied to the client workstation to be displayed in results software. The first stage of the Generalized Optimization Model is operational and producing feasible results for different scenarios on BC Hydro's Columbia River generating system. Stakeholders determined five suitable alternatives for minimum Revelstoke plant discharge. Each of these studies was completed with different historical plant inflows to simulate the uncertainty of the forecasted inflow. The results showed that the value of BC Hydro resources would decrease if the minimum discharge limit were increased. They also showed that the operation of other BC Hydro plants on the Columbia River and Peace River would change to meet the new minimum flow. The model has demonstrated that the operating flexibility is key to the value of BC Hydro resources; the less constraints on the system, the more operational choices, thus creating more value for stored water. Future development of the Generalized Optimization Model will combine short and long-term studies within the same model. This requires using multiple input data sets to represent the corresponding planning horizons. It will also provide solutions to meet the reliability and capacity requirements of BC Hydro and to sustain the value of the present and future resources for its customers. Modifications will have to be carefully planned to ensure the model's integrity. BC Hydro's residential, commercial and industrial customers will benefit from the results of all of the phases of the Generalized Optimization Model.
Affiliation: Applied Science, Faculty of
URI: http://hdl.handle.net/2429/14123
Scholarly Level: Graduate

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