Systemic approach for modeling a generic smart grid

TL;DR

The work addresses the need for a systemic, scalable approach to modeling smart grids by proposing a discrete-time backbone that partitions the system into a T&D network, microgrid, and local layer, coordinated through sequences and feedback. The approach combines knapsack-based local demand selection, game-theoretic microgrid interactions, and Busacker–Gowen min-cost routing within a pret topology-based network construction, validated via a GAMA-based multi-agent framework. Key contributions include a modular separation of concerns, reusable optimization modules, and a demonstrated workflow for testing alternative scenarios prior to human-scale deployment. The framework offers a flexible platform for exploring demand response, energy routing, and market interactions, with potential extensions to incorporate more complex patterns and learning-based strategies.

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.

Figures (12)

• Figure 1: Sequential Scheme.
• Figure 2: Family of topologic spaces.
• Figure 3: Network according to topologic spaces.
• Figure 4: Forecast for microgrid's consumption and plants' production.
• Figure 5: Simulation of a microgrid.