Abstract

Abstract. Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies conceptually and practically integrate urban spatial and energy planning approaches. The combined modelling approach that will be developed based on the described sectorial models holds the potential to represent hybrid energy systems coupling distributed generation of electricity with thermal conversion systems.

Highlights

  • Today’s needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns corresponding to their specific context. Heppenstall, Crooks et al (2012) argue that there is an inherent need to develop robust research approaches to address societal grand challenges such as energy depletion and use as well as climate change

  • The heat energy demand of all 17 000 residential buildings was calculated along a year

  • The global average in the scenario A (279 kWh/m2a) is higher than in the scenario B (86 kWh/m2a). It shows that the refurbishment clearly causes a reduction of 70% of the total heat energy demand of the residential building stock

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Summary

Introduction

Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments require a spatial representation in order to reflect the local context and the boundary conditions. Simulation through an Agent-Based Modelling (ABM) approach allows for representing the dynamic behaviour of the system over time, in which the different entities of the system (called agents) are represented autonomously and interact with a common environment. This approach can be used to reflect operational strategies as well as decentralised decision making in distributed energy systems by representing the communication between the agents

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