AI 中文总结
该研究提出结合人工智能与模型预测控制的燃料混合算法，通过神经网络计算甲烷值确定混合比限值，经仿真测试可降低燃气电厂运营成本与火炬排放量。
AI 中文摘要
本文介绍一种基于人工智能与模型预测控制的燃料混合算法。利用物理定律和现场测量值对燃气发电厂进行建模，采用神经网络计算燃料的甲烷值并确定燃料混合比限值，确保甲烷值处于发动机制造商规定的范围内。模型预测控制器调整最终混合比，以满足安全要求并最小化运营成本。该算法在不同场景的仿真中进行测试，结果显示运营成本和火炬排放量均有所降低。
英文摘要
This paper describes a fuel blending algorithm based on artificial intelligence and model predictive control. A gas-fired power plant was modeled using physical laws and on-site measurements. A neural network is used to calculate the methane number of the fuel and determine the fuel blending ratio limits so that the methane number is within the limits specified by the engine manufacturer. A model predictive controller adjusts the final blending ratio to meet safety requirements and minimize operating costs. The algorithm was tested in simulations with different scenarios and a reduction in both the operating costs and amount of flaring was observed.
Comments6 pages, 10 figures
Journal ref2023 46th MIPRO ICT and Electronics Convention (MIPRO), 2023, pp. 994-999
DOI：10.23919/MIPRO57284.2023.10159741
