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Modelling in Hydro-Thermal Optimization

  • A. Schadler
  • E. Steinbauer
Conference paper

Abstract

The energy requirements of STEWEAG — the power and energy supply utility of the Austrian province of Styria — are met by water power, thermal power stations and by contracted power supply from the national utility (VG). The power system consists of thermal power stations with and without fuel contracts; combined heat and power stations, run-of-river plants, series of run-of-river-plants and water power stations with storage (year, week or day). The peak power demand is estimated and has to be contracted in advance. If it is exceeded, a rather expensive penalty must be paid. The contracted energy must be paid according to a strict tariff taking into account a rather high fixed premium related to power. Hence STEWEAG has been interested in the optimization of its energy resources and in determining optimal schedules and contracts. In a first approach which was oriented towards a horizon of a year, methods of calculus of variations have been used thereby accepting far reaching simplifications. Recently emphasis was put on daily, weekly optimization as well as on annual optimization for operations planning. For this purpose a software package based on mixed-integer programming and suitable hardware was used. Starting from an annual optimal schedule the weekly commitment schedule is optimized based on time steps of 2 to 4 hours. The main goal of the weekly optimization is to deal with the influence of the water reservoirs during the weekends and with the start-up and shut-down decisions. Embedded in the weekly optimization the daily optimization is calculated based on 48 time steps. The model expressed in tableau size is approximately 7000 rows by 10 000 columns for the week and 4000 rows by 5000 columns for the day. Details on modeling approaches, computational experiences and considerations on the economic gains will be given.

Keywords

Thermal Power Station Power Change Thermal Plant Hydro Power Plant National Utility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • A. Schadler
    • 1
  • E. Steinbauer
    • 1
  1. 1.STEWEAGGrazAustria

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