imostocky / hydrooperationsim

MATLAB/Simulink model of hydro-power plant, optimization of maintenance planning

Hydroelectric power plant in Imatrankoski

(Source: https://www.energiauutiset.fi/tuotanto/lisarahoitusta-oulujoelle.html)

This project is part of Model and system dynamics course at LUT univeristy in Finland

Case & Task description

Your task is to optimize yearly maintenance schedule of two hydroelectric power plants located subsequently in a same river. The overall objective is to maximize yearly revenue. Model (built in Matlab 2017b)

• Run InitializeModel.m, which will create you 1000 random realizations of variables The maintenance schedule by default is planned as follows:

• Plant 1: two weeks in the summer; can be started anywhere between Mar-Jun = day numbers 60x152 (block: "maint1")
• Plant 2: two weeks in the fall; can be started anywhere between Aug-Nov = day numbers 213x305 ("maint2")
• In both cases, the two week stoppage can be divided into two one week stoppages (if needed)

Function block diagram of the model "HydroPowerSheet.slx".

A function block diagram of the case is illustrated in Figure 2:

• Plant 1 and 2 have distinct catchment areas for daily rainfall
• The output water of Plant 1 is fed to the storage pond of Plant 2
• The conversion of water output to MWh is more efficient in Plant 1 (efficiency ratio = 0.1) compared to Plant 2 (eff = 0.075)

Key uncertainties:

• Amount of daily rainfall (drawn from a generalized Pareto distribution, "rain")
• Price of electricity (geometric Brownian Motion, "price") Default plan The simulated cash flow outcome with default maintenance plan.

Mean
(50%) = 17.33
10% = 14.96
90% = 19.91

Tips & Tricks

• To speed up random simulation in Matlab, close the Simulink-window (function block diagram). For some reason this increases the speed of simulation by tens of percent in any model.

Meanwhile learn about

• Building System Dynamic models
• Running Monte Carlo simulations
• Implementing flexibilities (this lecture & assignment 4)
• Data analysis and visualization
• State-of-the-Art in economic modeling with System Dynamics

Results

Focus of this project was simulink model and analysis of its behaviour.

For test simulation runs adjust "rounds" variable in InitializeModel.m to lower values. 10

For simulation output, main.m runs sensitivity analysis on mean increase of price and volatillity of price parameters.

Report on results of this optimization and description of employed techniques can be found in "project_report.pdf"