Modeling of Consumption and Generation Dynamics in socio-technical Energy Systems

该项目是三个独立项目的一部分，这些项目无缝地合作，以研究建模和优化多层社会技术能源系统及其转换过程的不同方面。术语“多层系统”反映了相互关联的技术和社会系统的各个方面。该技术系统跨越多个配电和输电层，连接不同规模和容量的发电和消费单元。社会系统包括个人、公司甚至政治的短期和长期规划和决策过程。该研究项目的总体方法是使用多智能体系统对多个复杂的相互依赖关系进行建模，以分析此类社会技术系统中的相互作用。根据模块化方法，将确定以可再生能源为基础的高效和可持续能源系统方向的稳健转型和优化步骤。基于申请人的相关前期工作，他们一直在研究技术和社会领域的多代理系统，将开发和探索整体跨学科模型。主要的新奇是再现和分析社会技术现象和相互依存关系。手头的项目定义和具体化的代理为基础的模型，再现个人用户的决策时，操作灵活的设备在需求侧管理/需求响应的情况下。在这里，向个人提供（货币）激励以改变占空比或打开/关闭消费设备。对这些激励措施的反应很难预测，因为它在很大程度上取决于社会的各个方面。因此，这些方案的成功取决于对社会技术系统中复杂相互作用的正确理解。

This project is part of a packet of three individual projects working seamlessly together to investigate different aspects of modelling and optimizing the multi-layer socio-technical energy system as well as its transformation processes.The term "multi-layer system" reflects the various dimensions of the interconnected technical as well as social systems. The technical system spans multiple distribution and transmission levels with connected generation and consumption units of different sizes and capacities. It also spans various energy sectors, e.g. power, gas and heat.The social system encompasses short- as well as long-term planning and decision processes by individuals, companies and even politics.The overarching approach of this research project is to model the multiple and complex interdependencies using multi-agent systems in order to analyse the interactions in such socio-technical systems. Following a modular approach, robust transformation as well as optimization steps in the direction of an efficient and sustainable energy system - based on renewable energies - are to be identified.Based on relevant preliminary work by the applicants, who have been researching multi-agent systems in the technical as well as social domain, a holistic interdisciplinary model shall be developed and explored. The major novelty is to reproduce and analyse socio-technical phenomena and interdependencies. The project at hand defines and concretises the agent-based model for reproducing individual user decisions when operating flexible devices in the context of demand side management/demand response scenarios. Here, individuals are presented with (monetary) incentives to shift duty cycles or switch on/off consumption devices. The reaction to these incentives is hard to predict since it significantly depends on various social aspects. Thus the success of these scenarios depends on a proper understanding of the complex interactions in socio-technical systems.