Emission-Aware Stochastic Resource Planning Scheme for Data Center Microgrid Considering Batch Workload Scheduling and Risk Management
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Abstract
Internet data centers are booming in the last few years, leading to gigantic amount of energy consumption and greenhouse gas emission. In this paper, a data center microgrid including conventional units, energy storage, and renewable generation is modeled to optimize its electricity bill and carbon footprint. Considering the randomness of electricity price, renewable output and workload distribution, the volatility risk is incorporated to measure the associated operation risk. Then, a day-ahead emission-aware stochastic resource planning scheme is formulated to decide the strategy on power procurement, energy storage operation, batch workload allocation, and unit commitment of conventional units. Simulation results show the effectiveness of the proposed approach.
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