Toward Intelligent Energy Governance in Solar-Powered Data Centers: A Hybrid Study of Models, Strategies, and Future Architectures

Data centers are among the largest consumers of electricity in the digital era, with power demands growing due to increased computational workloads and the adoption of AI-driven services. Integrating renewable energy sources, particularly solar power, offers a promising path toward sustainability, but also introduces variability and complexity in energy availability. This paper presents a hybrid academic contribution that combines a literature survey, conceptual modeling, pilot experimental simulation, and a forward-looking systems design. We introduce an adaptive energy governance framework for solar-powered data centers that utilizes Dynamic Voltage and Frequency Scaling (DVFS), server consolidation, and Quality of Service (QoS) degradation to manage energy consumption under fluctuating solar input. A mathematical model is developed to evaluate energy flows across IT equipment and cooling systems. Simulation results show that intelligent energy governance can reduce power usage by up to 40% with minimal service degradation. In addition, the paper proposes an AI/ML-enhanced Software-Defined Networking (SDN) architecture for predictive power control and workload orchestration. This integrated approach supports a vision of future-ready, intelligent, and sustainable data center operations.