Computation-power Coupled Modeling for IDCs and Collaborative Optimization in ADNs

TL;DR

This paper presents a coupled modeling and optimization approach for geographically distributed Internet Data Centers (IDCs) and active distribution networks (ADNs), leveraging workload flexibility to optimize power flow and reduce costs.

Contribution

It introduces a novel computation-power coupling model and an iterative solution algorithm for collaborative optimization of IDCs and ADNs, incorporating a Nash bargaining approach for multi-objective coordination.

Findings

Effective workload scheduling improves power flow management.

The proposed algorithm converges efficiently in test cases.

Model enhances energy efficiency and cost savings in distribution systems.

Abstract

The batch and online workload of Internet data centers (IDCs) offer temporal and spatial scheduling flexibility. Given that power generation costs vary over time and location, harnessing the flexibility of IDCs' energy consumption through workload regulation can optimize the power flow within the system. This paper focuses on multi-geographically distributed IDCs managed by an Internet service company (ISC), which are aggregated as a controllable load. The load flexibility resulting from spatial load regulation of online workload is taken into account. A two-step workload scheduling mechanism is adopted, and a computation-power coupling model of ISC is established to facilitate collaborative optimization in active distribution networks (ADNs). To address the model-solving problem based on the assumption of scheduling homogeneity, a model reconstruction method is proposed. An efficient iterative algorithm is designed to solve the reconstructed model. Furthermore, the Nash bargaining solution is employed to coordinate the different optimization objectives of ISC and power system operators, thereby avoiding subjective arbitrariness. Experimental cases based on a 33-node distribution system are designed to verify the effectiveness of the model and algorithm in optimizing ISC's energy consumption and power flow within the system.