Intelligent optimization of a PV/T–ORC coupled microgrid: towards reliable, high tenacity and cost-efficient energy systems

Abstract

Microgrid systems integrating heterogeneous energy flows face underexplored challenges in real-time electro-thermal synergy under intermittent renewable input—a gap this study addresses via a dynamically coupled multi-domain optimization framework. To bridge the theoretical gap in coordinated energy dispatch across thermal-electric domains, this paper formulates a DBO-based hybrid microgrid model where the optimizer’s phase-based behavioral logic is intrinsically coupled with dynamic thermodynamic constraints. First, the PV/T system leverages its combined heat and power capabilities to meet thermal loads. Then, thermoelectric conversion is realized by integrating an ORC with an air-source heat pump, while energy storage systems—batteries and thermal tanks—recover and utilize waste heat, ensuring electro-thermal balance. The framework internalizes dual-objective trade-offs—economic and reliability—within a multi-domain equilibrium model, enabling emergent decision behavior through thermodynamic-aware swarm evolution. The DBO algorithm, inspired by the rolling behavior of dung beetles and equipped with dynamic boundary adjustments, optimizes system capacity and operational strategies with objectives of reducing grid dependence and enhancing economic efficiency. The results show that the proposed microgrid framework achieves a total cost reduction of 7.01% and a grid dependence of 38.7% through DBO optimization. Empirical simulations on an industrial microgrid reveal emergent electro-thermal coordination behaviors and validate the generalizability of the model across high-dimensional operational states. This study demonstrates a new theoretical paradigm for intelligent optimization in complex energy-coupled microgrid systems, it provides an important reference for the future microgrid in the coordinated energy supply of electricity and heat.