A Comparative Analysis of Resource Aggregation and Low-Carbon Dispatch Paradigms for Carbon-Aware Power Systems

Driven by the dual-carbon strategic mandates, the transition of power dispatch paradigms—from traditional economic-centric balance to carbon-power synergistic optimization—has become a pivotal research frontier. This paper provides a comprehensive taxonomy of the current state-of-the-art in distributed energy resource (DER) aggregation and low-carbon dispatch within the context of deep electricity-carbon coupling. We categorize the theoretical landscape into three pillars: high-fidelity carbon flow tracing, carbon-feature-aware aggregation, and resilient low-carbon dispatch strategies. Key technological breakthroughs, including distributionally robust optimization (DRO) and multi-agent reinforcement learning (MARL), are critically analyzed regarding their efficacy in addressing DER stochasticity and carbon-flow non-linearity. Finally, we delineate future trajectories, such as physics-informed edge intelligence and blockchain-facilitated carbon certification, providing a visionary roadmap for constructing next-generation carbon-aware power systems.