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Participatory engagement of stakeholders with energy models

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Participatory engagement of stakeholders with energy models:
developing feasible energy concepts for small municipalities

Published in: Environment
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Participatory engagement of stakeholders with energy models

  1. 1. Participatory engagement of stakeholders with energy models: developing feasible energy concepts for small municipalities Prof. Russell McKenna Energy System Analysis Group Systems Analysis Division McKenna, R., Bertsch, V., Mainzer, K., Fichtner, W. (2018):  Combining local preferences with multi‐criteria decision analysis  and linear optimisation to develop feasible energy concepts in  small communities, European Journal of Operational Research,  Volume 268, Issue 3, https://doi.org/10.1016/j.ejor.2018.01.036
  2. 2. Feasible energy concept development in Ebhausen, Baden-Württemberg (~5000 pop.)  Iterative process of interaction with stakeholders required
  3. 3. Geodata: OpenStreetMap, Satellite images: Bing Maps more details in: [Mainzer 2016] Cost-potential methods: rooftop PV • Data gathering – Building footprints – Satellite images • Determination of roof orientations through line detection algorithms • Detection of roof structures like chimneys, roof windows, etc. • Algorithm iterates stepwise over usable areas, places as many modules as possible • Existing modules detection using neural networks • simulation of irradiation, energy yield & costs calculation Outlook: Improve existing plant recognition accuracy Improve the 3D geometry detection with remote sensing methods Mainzer PhD 2018
  4. 4. A transferable model for developing municipal energy concepts: RE3ASON* *Renewable Energies and Energy Efficiency Analysis and System OptimizatioN  Input data based largely on open sources and model therefore highly transferable
  5. 5. Energy concept development in Ebhausen, Baden-Württemberg: CO2 Emissions
  6. 6. Problem structuring: construction of an attribute tree Cost min CO2 min autonomy CO2 min @110% costs autonomy @110% costs CO2 min @120% costs autonomy @120% costs Total expenses CO2 emissions Community energy imports (autonomy) Primary energy imports Overall goal
  7. 7. MCDA: weight elicitation • The SWING weighting method was used for eliciting the weights within the workshop • Linear value functions assumed • Controversial discussion concerning the relative importance of the four criteria • Highest uncertainty concerning the weight of ‚autonomy‘ • Calculation of intervals including the three sets of weights Criterion Weight Interval Costs 0.40-0.60 CO2 0.15-0.30 Autonomy 0.10-0.35 Primary 0.00-0.05
  8. 8. Ranking of the considered alternatives for the assumed deterministic weights Cost min CO2 min auto- nomy CO2 min @110 % costs auton omy @110 % costs CO2 min @120 % costs auton omy @120 % costs Results of 1000 randomly sampled weights (within the weight intervals): alternatives with highest scores - “CO2 min”: 23% - “CO2 min @110% costs”: 30% - “CO2 min @120% costs”: 11% - “autonomy @120% costs”: 36% 0.506       0.620        0.431 0.637 0.622 0.634          0.634
  9. 9. 3. Energy concept development in Ebhausen, Baden-Württemberg: 8 Alternatives McKenna et al. 2018a Moderate compromise in costs yield substantial benefits in terms of CO2 emissions and autonomy
  10. 10. Total expenses Env. Sustainability Community energy imports (autonomy) Primary energy imports Overall goal Outlook: sustainability assessment Santoyo-Castelazo & Azapagic 2014
  11. 11. Backup 23 October 2018Russell McKenna11

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