Abstract: The optimal control of distributed energy systems relies on information exchange among nodes. However, in practical industrial networks, limited communication bandwidth and high-frequency data exchange can easily cause network congestion. To address this issue, we propose a prescribed-time distributed cooperative optimization method based on dynamic event-triggered quantized communication. First, a dynamic encoding-decoding quantized communication scheme is introduced. By transmitting state differences and constructing auxiliary equations, this scheme dynamically eliminates quantization errors and effectively compresses the number of transmitted data bits. Second, an event-triggered mechanism with a dynamic threshold is designed to transform periodic communication into on-demand triggering. This reduces communication frequency and theoretically excludes Zeno behavior. Finally, by combining time-varying gains and state decomposition, a prescribed-time convergent distributed optimization algorithm is designed. The convergence time of this algorithm is pre-definable and independent of the initial states. Moreover, a smooth penalty function is used to effectively handle the local capacity constraints of the units. Simulation results of the energy system show that the algorithm can accurately converge to the optimal total cost within the prescribed time. Compared with centralized optimization results, the error is less than 0.05%. Regarding communication overhead, the quantization mechanism controls the transmitted variables within an integer range of ±2, avoiding quantization saturation. Compared with continuous communication, the dynamic event-triggered mechanism significantly reduces the cumulative number of communications and suppresses the transmission of redundant information. In addition, when the system scale expands from 10 to 80 nodes, the computation time increases by only 0.19s. The proposed optimization method achieves efficient cooperative optimization of the energy system with extremely low communication overhead.