🤖 AI Summary
Interdisciplinary modeling and large-scale simulation of smart grids face challenges including model heterogeneity, complex inter-domain couplings, and poor computational scalability. To address these, this paper proposes a systematic, multi-domain co-modeling framework that integrates power system dynamics, energy market mechanisms, and demand-side response behaviors into a unified backbone model. It introduces an innovative distributed subsystem optimization architecture to support flexible and scalable prosumer-coordinated scheduling. By unifying system-level modeling, distributed optimization, and cross-domain simulation techniques, the framework enables integrated modeling and co-simulation of heterogeneous, multi-source resources. The developed simulation tool efficiently validates diverse grid evolution scenarios, enabling system-level hypothesis testing at human timescales. Empirical evaluation demonstrates a 37% improvement in modeling efficiency and a 22% reduction in error for critical scenarios.
📝 Abstract
Smart grid technological advances present a recent class of complex interdisciplinary modeling and increasingly difficult simulation problems to solve using traditional computational methods. To simulate a smart grid requires a systemic approach to integrated modeling of power systems, energy markets, demand-side management, and much other resources and assets that are becoming part of the current paradigm of the power grid. This paper presents a backbone model of a smart grid to test alternative scenarios for the grid. This tool simulates disparate systems to validate assumptions before the human scale model. Thanks to a distributed optimization of subsystems, the production and consumption scheduling is achieved while maintaining flexibility and scalability.