Development and evaluation of a multi-objective optimization model for multi-reservoir systems

by Daniel Archila

Institution: University of British Columbia
Department: Civil Engineering
Degree: Master of Applied Science - MASc
Year: 2015
Record ID: 2057932
Full text PDF: http://hdl.handle.net/2429/51894


The BC Hydro and Power Authority is the largest electric utility in the province of British Columbia, Canada. With a generating capacity of more than 12,000 MW, it serves almost 2 million customers in the province. It operates 31 hydroelectric facilities, most of them located in multi-reservoir systems. In order to facilitate the operation of these reservoirs, BC Hydro developed an in-house application called the Operations Planning Tool (OPT), a deterministic Linear Programming (LP) model that provides the optimal operation of the multi-reservoir systems considering multiple purposes. The objective of this research was to investigate, develop, incorporate and test additional modeling features that would expand the current capabilities of the OPT. This included developing a formulation for the analysis of units’ maintenance outages and changing the optimization model to consider inflow uncertainty and avoid the use of weight coefficients and penalty functions. The formulation developed for the analysis of units’ maintenance outages is based on a two-stage algorithm. In the first stage, a pre-processor defines all the possible outage solutions given some initial configurations. In the second stage, a modified OPT model is run to find an outage solution that optimizes the objectives using a Mixed-Integer Linear Programming (MILP) algorithm. The formulation was tested using the Bridge River system in British Columbia, Canada. An alternative OPT model was also developed to consider the uncertainty in the reservoir’s inflow and modify the formulation of the objective function. It was desired to avoid the use of weight coefficients and penalty functions due to the limitations that they present. The proposed alternative was based on the development of a linear decision rule and the use of chance constraints. The linear decision rule is an operating rule that defines the spillway releases and forebay elevation as a linear function of the inflow, the turbine releases and a deterministic decision variable. The chance constraints were used to consider the probability of the spillway releases and forebay elevation not being within a preferred range of values established by the user. The developed formulation was tested using the Stave Falls system.