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Network modelling and power flow simulations Lessons learned. Konrad Purchala Tractebel Engineering. EWEC conference - TradeWind 18.3.2009, Marseille. Grid modeling. Objectives of the TradeWind study Investigate power flows across Europe Effect of moving weather conditions
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Network modelling and power flow simulations Lessons learned Konrad Purchala Tractebel Engineering EWEC conference - TradeWind 18.3.2009, Marseille
Grid modeling Objectives of the TradeWind study • Investigate power flows across Europe • Effect of moving weather conditions • Identify main bottlenecks Context • Europe is zonal markets • National networks developed to be cooper plates • Main structural bottlenecks at national frontiers Note: issue of network data availability
UCTE grid – the modeling challenge 4000+ nodes 6000+ lines
Grid modeling Dilemmas • Can we get the detailed model from the TSOs? • Robustness of the model? • solving 8760 hourly snapshots, data processing • Location of generation, wind farms, demand? • Temporal variations of the demand? • Budget? The chosen approach • Public grid model • Only cross-border constraints • DC power flow • At the end of the project, grid model available from the TSOs
DC power flow or PTDF-solution Grid modeling (example of UCTE) Grid representation UCTE
Modeling issues Transmission bottlenecks • Anticipated main bottlenecks • Detailed task in the project • Cross-country analyses • All relevant bottlenecks should be included • Surely cross-border • For some countries also internal lines • Future network reinforcements • Modeling of wind farms • Correlation with the wind speed data • Grid connection? • Treatment of hydro power • Water reservoir levels
Main lessons learned • TradeWind changed the scene for integration studies • Breakthrough on data availability • UCTE research model now available • Fruitful collaboration with the TSOs • Methodology and data for future integration studies • Hour-by-hour investigations covering multiple years • Huge database of wind speeds, conversion curves, wind capacity expansion scenarios, etc • Large scale market simulations with grid constraints • Allowing for more realistic results