Interdependent social-technical modeling for the transformation of the multi-level energy system

整个项目包含三个子项目，它们相辅相成，处理多层次能源系统改造的不同维度。目标是设计一个联合的跨学科模型。首字母缩略词多层次包括技术设备，电网水平，天然气和供热系统的互连以及地方，区域和超区域区域的社会活动，包括各种短期和长期决策。这包括个人和机构，如生产消费者、公司，甚至政治决策。该项目的联合方法在多主体框架内对复杂社会技术系统的不同层次上的各种实体进行建模。在这方面，将对技术和社会模块内部和之间的动态相互依赖和非线性相互作用进行建模和分析。因此，得出能源系统向可再生能源系统转型的情景和发展路径及其优化结论是可行的。作为整个项目的一部分，以下研究问题是该子项目的核心：—如何减少大量设备和参与者的复杂性，以模拟能源系统的超区域发展？-如何在一个模拟框架中包含各种时间框架，从小时发电计划到网络负载，直到多年决策？-如何在整个系统的时间框架和层次上对代理的优化策略进行建模？-控制系统输入和系统解决方案的稳健性的结果是什么？-激励措施对个体实体长期投资光伏、储能、电站等的决策有何影响？-如何在整体建模框架中实施政治决策，例如eeg补贴、区域化、电站罚款等？

The overall project contains three subprojects, which are supplementary to each other and deal with different dimensions of the transformation of the multi-level energy system. The target is to design a joint interdisciplinary model. The acronym multi-level comprises of technical devices, grid levels, interconnections to gas and heat systems as well as social activities in local, regional and supra-regional areas including various short- and longterm decisions. This contains individual persons and institutions like prosumers, companies and even political decisions.The joint approach of the project models the various entities on the different levels of the complex social-technical system within a multi-agent framework. In this respect the dynamic interdependencies and non-linear interactions within and between the technical and social modules will be modeled and analyzed. As a consequence it will be feasible to draw conclusions about scenarios and development paths and its optimization for the transformation of the energy system towards a system based on renewable energies. The following research questions are the core of this subproject as part of the overall project:- How can the complexity of very large numbers of devices and actors be reduced to model a supra-regional development of the energy system?- How can various time frames, from hourly generation schedules, to network loading until multi-year decisions, be included within one simulation framework?- How can optimization strategies of agents be modeled throughout time-frames and levels of the system?- What is the consequence of controlling inputs to the system and for the robustness of the system solution?- What is the impact of incentives on decisions of individual entities regarding long-term investments into PV, storages, power plants, etc.?- How can political decisions be implemented in the overall modeling framework, e.g. EEG-subsidies, regionalization, power station penalty payment, etc.?