This work proposes a multi-agent system aimed at increasing the computing sustainability of high-performance computing data centers that are distributed among several wind farms. The novel approach of wind turbines housing high-performance computing data centers seeks to maximize renewable energy usage by supplying the data centers with otherwise curtailed wind energy, thus increasing wind farm efficiency as well. To optimize data center operation in this unique environment, job execution should be prioritized during periods of high availability of renewable energy. When wind power generation is low, resource utilization should be continuously adjusted to minimize gray electricity consumption with high carbon intensity or high grid consumption costs. Furthermore, green service-level agreements are introduced allowing for more flexibility in terms of deadline compliance, thereby fostering energy-aware data center operation. The proposed multi-agent system realizes a moving-horizon, multi-objective optimization problem to find the best operational strategy, taking into account both sustainability and performance concerns, and is compared against a selection of baseline job scheduling strategies. • Historic Data-Driven Data Center Placement Strategy. • Scalable Multi-Agent System for Energy-Optimized Data Center Operation. • Two-step Moving-Horizon (Multi-Objective) Optimization Approach for Scheduling. • Implementation of Green Service-Level Agreements. • Thorough Evaluation of the Optimization Approach.
Kilian et al. (Thu,) studied this question.