Gliederung. Challenges for CHP operation in competitive markets. Christoph Weber. Competitive markets

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1 Gliederung Challenges for CHP operation in competitive markets Christoph Weber Competitive markets Starting point in most European countries: EU-directive 96/12 on liberalisation of Electricity and Gas markets Competition on the electricity wholesale market Price decrease for industrial customers and distribution companies Increased price fluctuations Since 1999: raise of gas prices following oil price increase Competitive situation of gas-fired CHP has worsened Gas-to-gas competition is slow to develop

2 70 Electricity Spot Prices Price [ /MWh] Source: Daily average prices LPX / EEX 18 Primary Energy Prices Price [ /MWh] Jan 98 Apr 98 Jul 98 Okt 98 Jan 99 Apr 99 Jul 99 Okt 99 Jan 00 Apr 00 Jul 00 Okt 00 Jan 01 Apr 01 Jul 01 Okt 01 Jan 02 Apr 02 Jul 02 Natural Gas Hard coal Source: Import energy prices BAW

3 Policy ambitions Reduce Climate Gas Emissions and meet Kyoto targets - 8 % at EU level in the period comp But how much in the power and heat generation? Introduction of emission certificate trading Increase the share of renewables Doubling by the year 2010 Which renewables? Wind and... Biomass? Which technologies? Cogeneration? Increase the share of cogeneration Directive drafted Diverse national measures implemented The challenges Increase profitability of operations Cost reductions Staff costs Maintenance costs Fuel costs Revenue increases Profit-oriented operation Flexible operation Take benefit of high prices for selling electricity Take benefit of low prices for purchasing electricity Account for operation restrictions, start-up costs and maintenance costs Manage risk Price risk Heat demand risk Outage risk Other risks: counterparty, liquidity, personnel risk etc.

4 The project Optimisation of Cogeneration Systems in a Competitive Market Environment OSCOGEN Scientific objectives of the project Development of a comprehensive optimisation tool for the operation of cogeneration plants in liberalised energy markets: Building a detailed CHP operation model which maps the technical and economic characteristics of the CHP plants and, on the other hand, with a certain degree of abstraction, so that it can be used for the construction of an optimisation model. Studying strategies for describing uncertain parameters and including them into existing stochastic models with further insights into the building of these models Solving large stochastic models by means of genetic algorithms based on the development of new genetic algorithms that are suitable for the stochastic optimisation problem faced

5 Technical objectives of the project Validation of the developed methodology on existing CHP systems connected to district heating grids Building of a user-friendly tool for the automatic generation of bid functions Insights in the economic viability of CHP investments in the liberalised energy markets. By modelling in detail the operation of the plants, information on the capital costs recovered is obtained. Workshop in co-operation with a regional energy agency in Austria in order to present the developed methodology and tool. Work packages WP0: Project Management WP1: Information collection and object definition. WP2: Development of a deterministic nonlinear model WP3: Inclusion of uncertainties and stochastic programming WP4: Development of a problem specific solver on the basis of genetic algorithms WP5: Extension of the approach for optimum electricity trading WP7: Assessment of the results and summary WP6: Case studies and Validation Phase WP8: Dissemination of results

6 Partners and Tasks Partner Main tasks Country, University of Stuttgart Co-ordination Development long term model Stochastic optimisation & Bidding tool Germany IHS, Vienna Austrian context, Stochastic analyses of spot prices Austria and heat demand IJS, Ljubljana Linear and non-linear operation optimisation model Slovenia Development short term model FE, University of Genetic algorithms Slovenia Ljubljana Electricity liberalisation in Slovenia TE-TOL, Validation short term model Slovenia Ljubljana BEWAG, Berlin Operation competitive markets Germany Validation long term model CEPE, ETH Zurich Swiss context, Spot market mechanisms Dissemination Switzerlan d Topics of the workshop Policy context and perspectives Optimisation models and methods Technology developments Modelling of uncertainties Long Term Planning Bidding Applications

Integrated Assessment Tools for Network Investments in volatile Market Environments

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