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Smart grid architecture model for control, optimization and data analytics of future power networks with more renewable energy

机译:具有更可再生能源的未来电网控制,优化和数据分析的智能电网架构模型

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This paper describes a generic methodology to develop mathematical and computational models of different components of the smart grid architecture model (SGAM). The SGAM inspired integrated mathematical modelling will help develop interoperable complex system simulations for integrating different smart grid components, associated communication models for data exchange and software modules, control, estimation, and data analytics functionalities with the business perspectives. This paper is based on the existing component models inspired by SGAM, which provides a holistic view for integrating the models under operational and security constraints. Achievable results and open research problems for the SGAM mapping have also been discussed in these models supporting the interoperability challenges. The models described in this paper can serve as a guideline to design efficient and robust control strategies for smart grids against uncertain loading, generation, and communication constraints, thus optimizing and improving the whole system & rsquo;s performance. Mathematical and computational models of cyber-physical systems have also been discussed along with their potential challenges. Based on the above concepts, unsolved and open challenges in the smart grid control, optimization and data analytics are highlighted.(c) 2021 Elsevier Ltd. All rights reserved.
机译:本文介绍了一种通用方法,用于开发智能电网架构模型(SGAM)的不同组件的数学和计算模型。 SGAM启发的集成数学建模将有助于开发可互操作的复杂系统模拟,用于集成不同的智能电网组件,相关通信模型的数据交换和软件模块,控制,估计和数据分析功能与业务观点。本文基于由SGAM启发的现有组件模型,它提供了集成在操作和安全约束下的模型的整体视图。在支持互操作性挑战的这些模型中也讨论了SGAM映射的可实现结果和开放研究问题。本文描述的模型可以作为设计智能电网的有效和稳健控制策略的指导,防止不确定的装载,发电和通信约束,从而优化和改善整个系统和rsquo; S的性能。还讨论了网络 - 物理系统的数学和计算模型以及它们的潜在挑战。基于上述概念,智能电网控制中的未解决和开放挑战,突出显示优化和数据分析。(c)2021 Elsevier Ltd.保留所有权利。

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