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T. Trötscher, M. Korpås SINTEF Energy Research AS

Optimal design of a subsea power grid in the North Sea. T. Trötscher, M. Korpås SINTEF Energy Research AS. General problem description. ~. ~. ~. ?. How to connect nodes with transmission lines to achieve optimal social benefit?. 2. Input data assumptions.

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T. Trötscher, M. Korpås SINTEF Energy Research AS

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  1. Optimal design of a subsea power grid in the North Sea T. Trötscher, M. Korpås SINTEF Energy Research AS

  2. General problem description ~ ~ ~ ? • How to connect nodes with transmission lines to achieve optimal social benefit? 2

  3. Input data assumptions • Land connection nodes in relevant countries as latitude-longitude pairs • Selected relevant connection points from the TradeWind project • Marginal cost of generation, generation capacities and time series of load. • Official ENTSO-E scenarios, same as in TradeWind • Capacity and location of offshore wind power clusters • Selected a few large clusters as identified in the TradeWind project • Existing exchange capacity between nodes • Used the net transfer capacities as published by ENTSO-E • Cost scenarios for cables, converter stations, switchgear, and offshore platforms • Adapted from the EU-IEE project WindSpeed. Work in progress. • Wind data • Interpolated reanalysis data with added variations • Sources • TradeWind http://www.trade-wind.eu/ • WindSpeed http://www.windspeed.eu/

  4. Reanalysis wind velocity is used as basis • Adjustment factors as described in the TradeWind project are applied to better represent onshore and offshore wind conditions • A sample is drawn using empirical latin hypercube sampling • Correlation in velocity is captured • The sample size can be kept relatively small • Wind velocity is converted to power generation by applying a power curve • Power curves are made to represent large clusters • Individual power curves are used for onshore and offshore wind turbines

  5. All considered interconnectors 1000MW 8800MW • 33 considered projects • Leads to 1e25 possible configurations • Impossible to enumerate • Onshore wind, TradeWind ”2030 medium wind” scenario • Norway: 4980MW • Denmark: 7291MW • Germany: 45444MW • Netherlands: 3050MW • Belgium: 1183MW • UK: 10136MW 8000MW 4000MW 3800MW

  6. An example of an optimized grid...

  7. Locked to radial connections only... • Investement in grid infrastructure 6.5 – 13.5 billion. € • Depending on cost scenario • Savings by allowing a meshed grid: ~2 billion € • Better reliability for wind farms with a meshed grid • Meshed grid is more complex to operate • Uncertain costs of t-offs/circuit breakers

  8. ~ ~ ~ ~ Conclusions • Meshed grids give better economic benefit for the EU as a whole than do radial connections • Steps should be taken to reduce regulatory barriers • Potential of savings of around 25% of investment cost • Meshed grid have a higher utilization rate than do radial wind farm connections (~70% vs ~45%) • Cost of VSC HVDC T-offs/circuit breakers as opposed to distance to shore will influence optimal grid structure • Higher costs short distance  radial + bilateral interconnectors • Lower costs long distance  meshed grid • Meshed grids also... • ... Improves reliability of grid connection for wind farms • ... Makes it viable to connect wind farms further offshore

  9. Challenges A grid solution that is cost effective for the society must be attractive for the developers! • Sharing of costs and benefits between TSOs • Construction costs, losses, congestion rent, operation costs • Support for wind power is different around the North Sea • Different legalisation for • Permissions, system operation, grid codes, system operation • Market integration and balancing of wind power Joint ”North Sea TSO” Harmonized support schemes for wind power • Sources: • An analysis of Offshore Grid connection at Kriegers Flak in the Baltic Sea By Energinet.dk Svenska Kraftnät Vattenfall Europe Transmission • Pentalateral Energy Forum : Working plan proposal on offshore electricity infrastructure

  10. Further work • Stepwise building • Current model optimizes the grid all at once • Better assumption: The grid is built in steps to accomodate more wind power. Costs fall. • Can be achieved with dynamic programming • Generator marginal costs from TradeWind don’t give rise to price variations as experienced in the market • Result: value of grid is underestimated • Use actual prices with a sesitivity to power infeed or... • Construct better/more realistic MC curves

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