Energy Management for Renewable-Colocated Artificial Intelligence Data Centers
We develop an energy management system (EMS) for artificial intelligence (AI) data centers with colocated renewable generation. Under a cost-minimizing framework, the EMS of renewable-colocated data center (RCDC) co-optimizes AI workload scheduling, on-site renewable utilization, and electricity market participation. Within both wholesale and retail market participation models, the economic benefit of the RCDC operation is maximized. Empirical evaluations using real-world traces of electricity prices, data center power consumption, and renewable generation demonstrate significant electricity cost reduction from renewable and AI data center colocations.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Renewable-Colocated Green Hydrogen Production: Optimal Scheduling and Profitability
We study the optimal green hydrogen production and energy market participation of a renewable-colocated hydrogen producer (RCHP) that utilizes onsite renewable generation for both hydrogen production and grid services. U…
SchedulingAn Overview of the Prospects and Challenges of Using Artificial Intelligence for Energy Management Systems in Microgrids
Microgrids have emerged as a pivotal solution in the quest for a sustainable and energy-efficient future. While microgrids offer numerous advantages, they are also prone to issues related to reliably forecasting renewabl…
energy managementManagementA Federated learning model for Electric Energy management using Blockchain Technology
Energy shortfall and electricity load shedding are the main problems for developing countries. The main causes are lack of management in the energy sector and the use of non-renewable energy sources. The improved energy …
energy managementFederated LearningManagementReinforcement Learning for Battery Management in Dairy Farming
Dairy farming is a particularly energy-intensive part of the agriculture sector. Effective battery management is essential for renewable integration within the agriculture sector. However, controlling battery charging/di…
ManagementQ-Learningreinforcement-learningReinforcement LearningA Reinforcement Learning Approach to Dairy Farm Battery Management using Q Learning
Dairy farming consumes a significant amount of energy, making it an energy-intensive sector within agriculture. Integrating renewable energy generation into dairy farming could help address this challenge. Effective batt…
ManagementQ-LearningScheduling