Modeling intelligent energy systems: Co-Simulation platform for validating flexible-demand EV charging management
Modeling intelligent energy systems: Co-Simulation platform for validating flexible-demand EV charging management
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DOI：
10.1109/pesgm.2014.6939434
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发表时间：
2014-07
期刊：
影响因子：
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通讯作者：
Peter Palensky;E. Widl;M. Stifter;Atiyah Elsheikh
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文献类型：
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作者：
Peter Palensky;E. Widl;M. Stifter;Atiyah Elsheikh
仅提供摘要形式。能源系统的复杂性有所增加：新技术、拓扑结构和组件、与市场等其他系统的联系更加紧密以及信息技术的使用增加。这导致了一些具有挑战性的问题，这些问题无法通过传统方法来回答。然而，将可再生能源和清洁技术纳入电网的目标需要解决由此产生的复杂问题。本文研究了智能电动汽车充电的动态需求响应，作为详细的混合动力模型的用例，不能单独使用传统工具进行适当处理。通用建模语言和特定领域的专用建模解决方案通过标准化的协同仿真接口结合在一起，以实现最大的灵活性和最小的实施工作。这种以前数值上不兼容的建模范式的组合，使详细的混合组件模型的动态，同时保持舒适性和建立的工具的力量。基于Modelica的物理仿真引擎，商业电力系统仿真工具和基于代理的离散事件模拟器的能源电网的耦合结果在一个新的协同仿真平台。这一富有远见的概念提供了分析和优化未来能源系统所需的模拟的高水平细节，范围，灵活性，可扩展性和准确性。
Summary form only given. Energy systems experience a rise in complexity: new technologies, topologies and components, tighter links to other systems like markets and the increased usage of information technology. This leads to challenging questions that can not be answered via traditional methods. The goal of including renewable energy and clean technologies in the grid, however, requires solutions for the resulting complex problems. This paper investigates dynamic demand response for intelligent electric vehicle charging as a use-case for detailed hybrid models that cannot be properly handled by traditional tools alone. Universal modeling languages and specialized domain-specific modeling solutions are brought together via standardized cosimulation interfaces to achieve maximal flexibility and minimal implementation efforts. This combination of previously numerically incompatible modeling paradigms enables a detailed look into the dynamics of hybrid component models while keeping the comfort and the strength of established tools. This coupling of a Modelica-based physical simulation engine, a commercial power system simulation tool and an agent-based discrete event simulator for energy grids results in a novel co-simulation platform. This visionary concept provides the high level of detail, scope, flexibility, scalability and accuracy in simulations needed to analyze and optimize energy systems of the future.