Optimal Workload Allocation for Distributed Edge Clouds with Renewable Energy and Battery Storage

This paper studies an optimal workload allocation problem for a network of renewable energy-powered edge clouds serving users across various geographical areas. Each edge cloud has on-site renewable energy generating units and a battery storage unit. Due to the discrepancy in electricity pricing and the diverse temporal-spatial characteristics of renewable energy generation, how to optimally allocate workload to different edge clouds to minimize the total operating cost while maximizing renewable energy utilization is a crucial and challenging problem. To this end, we introduce an optimization framework designed for Edge Service Providers (ESPs), aiming to reduce energy costs and environmental impacts, while ensuring essential quality-of-service standards. Numerical results demonstrate the effectiveness of the proposed model and solution in maintaining service quality as well as reducing operational costs and emissions. Furthermore, the impacts of renewable energy generation and battery storage on optimal system operations are rigorously analyzed.