Network-Constrained Energy Trading for Integrated Energy Microgrid Clusters with Data Centers

As prosumers, data centers can achieve multi-energy coupling through the scheduling of computational tasks. Establishing a rational framework for energy and information trading in integrated energy systems that include data centers is crucial for enhancing renewable energy utilization and reducing energy costs. This paper proposes an energy trading model for integrated energy microgrids (IEMs) with data centers, considering both information flow and energy flow within multienergy networks. First, an IEM operation model is developed, consisting of a data center, photovoltaic generation system, small diesel generator, heat pump, and energy storage. The model also includes an electric-thermal network that connects the IEMs at various nodes. Compared to previous IEM cluster models, this model improves energy coupling through waste heat recovery from the data center and enhances the flexibility of energy transmission by establishing connections between IEMs and the network. Additionally, a mechanism is adopted that enables simultaneous peer-to-peer energy trading between IEMs and energy transactions between IEMs and the multi-energy networks. Finally, alternating direction method of multipliers algorithm is employed to optimize the dispatch strategies for each time period. Case studies demonstrate that the proposed method effectively reduces energy costs and increases the consumption of renewable energy.