RESTLESS / ESTIMO:

Energy Space Time progress

 

Ed Sharp :

ed.sharp@ucl.ac.uk | www.esenergyvis.wordpress.com | @steadier_eddy

Overview

  • Working towards the completion of the Energy Space Time Integrated Model Optimiser (ESTIMO)
  • The model has an overall aim to optimise transmission and storage for a high renewable future for Europe
  • Transmission will be adaptable, but is initially going to be simplified, then complexity added if computationally viable
  • Storage will be contained within nodes, nodes will increase in number as development continues
  • The model structure includes pre-simulation of renewable generation capacity factors (see next slides)
  • Renewable generation scenario modelling
  • Demand simulation and scenario modelling
  • Integration of simulated timeseries (by country) into an optimisation module including feedback to relevant simulation timeseries (e.g. hydro)
  • Simulation modules are very nearly complete - work has begun on scenarios and integration
  • PV output simulated using top of atmosphere and ground level irradiance and ground temperature data and a physical model - adapted from Stefan's method
  • All hours from 1980 simulated for entire grid - Non tracking panels 1 MW per grid centroid assumed.
  • Aggregated to country by assuming either geographically distributed or population weighted capacity currently testing method.  can be aggregated using any desired geography.
  • Output = long time series of capacity factors for all global countries - easy to use in scenarios.  Renewables ninja provide European timeseries (only 10 years)

Module - Global PV simulation

Simulated monthly mean global capacity factors using 1980 meteorology

  • Estimating the accuracy of PV simulations is difficult as there aren't great data on capacities
  • CapFacs can be compared to renewables ninja, but they use different assumptions on capacity.  Covariance should match very well due to the temporal profile of solar radiation.

Module - Global PV simulation, evaluating simualation

  • An adapted version of Staffells method
  • All European wind farms, derived from windpower.net db (which we bought), simulated at specific location
    • bilinear interpolation to point, scipy.optimise extrapolation to height of turbine
    • Site specific curves used where available, also derived from wind power.net
    • Evaluation of wind speed with met mast data show correlation coefficients between 0.82 and 0.9, figure below
    • There is geographical variation in accuracy as the second plot shows

Module: European Wind simulation

Comparison of mast wind speed and interpolated extrapolated MERRA data

Some sites are not quite as accurate

Module: European Wind simulation, evaluating simulation

Site specific simulation accuracy can be good if the right capacity is allocated (wndpower.net capacities don't always match bm units),

Where there is geographical diversity and large capacity simulations match history well, elsewhere it is more difficult

Germany

Finland

Population weighted temperature

Module : Electricity demand

  • hourly modelling of energy service demands
  • some engineering approach, some top-down
  • compromise between accuracy and speed due to model scale (EU)
  • current output: Electricity (specific and total), Heat (Space and other), battery electric vehicles

Modules: Scenario modelling

  • Currently developing in notebooks - gui to be defined, intention to run on laptops.
  • Renewables scenarios use annual national capacities as inputs
  • These are added smoothly over the course of a year
  • In the case of wind all installed capacity is used first, then that under construction, approved, planned.  
    • ​countries with little or no capacity also have some generic locations available to improve geographical smoothing of timeseries
    • Onshore and offshore timeseries are seperately modelled
    • ​​This is made possible by charcaterisation of each farm by windpower.net
  • Solar are modelled as a single country capacity
  • Other renewables to be defined.....
  • Demand??

Modules: Integration and Optimisation

  • Mark has developed algorithms
  • Yet to be integrated into scenarios and simulation framework

Future work  and collaboration

  • Climate change adaptations
  • Optimisation method, python packages etc
  • Comparison of outputs under the same scenarios
    • Publish results
  • Your experience of using TIAM outputs, an obligation of ours under the RESTLESS project
  • Model inputs from HighRES to a European system?
    • Publish results
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