基于源荷不确定性的油田综合能源系统优化调度方法

An optimal scheduling method for oilfield integrated energy system considering source-load uncertainty

摘要

为促进＂双碳＂目标下油田区域低碳转型，考虑热电联产（CHP）、碳捕集与封存（CCS）和光电储加热炉 （PTSF），提出机组协同运行的油田综合能源系统优化调度方法。优化源侧运行架构，利用 CCS 和 PTSF 耦合单元，建立双重解耦的油田综合能源系统（OIES）低碳经济调度模型；利用信息间隙决策理论（IGDT），量化分析可再生能源的不确定性和油田电热负荷用能的随机性，建立风险规避型 OIES 模型；通过算例仿真分析，验证 OIES 鲁棒调度模型的有效性。结果表明：应用基于源荷不确定性的油田综合能源系统优化调度方法，系统碳排放量可有效降低 75.11% ，实现系统内部碳循环；风、光利用率分别提升至 96.20% 和 95.78% ，有效提高新能源上网空间和消纳率。该优化调度方法可为油田综合能源系统低碳运行提供参考。

Abstract

To promote the low-carbon transformation of oilfield areas under the "dual carbon" goal, a comprehensive energy system optimization and scheduling method for oil fields is proposed, which considers combined heat and power (CHP), carbon capture and storage(CCS), and photovoltaic storage and heating furnaces(PTSF) for coordinated operation of units. Optimizing the source side operation architecture, utilizing CCS and PTSF as coupling units, a dual decoupling low-carbon economic dispatch model for the oilfield integrated energy system (OIES) is established. Using information gap decision theory(IGDT) to quantitatively analyze the uncertainty of renewable energy and the randomness of energy consumption for oilfield electric and thermal loads, and a risk averse OIES model is established. Verify the effectiveness of the OIES robust scheduling model considering IGDT through numerical simulation analysis. The results show that the low-carbon economic dispatch model using CHP-PTSF-CCS joint operation can effectively reduce system carbon emissions by 75.11% and achieve internal carbon cycling. The utilization rates of wind and solar energy have been increased to 96.20% and 95.78% respectively, effectively improving the space for new energy to be connected to the grid and the consumption rate. This optimization scheduling method can provide reference for the low-carbon operation of integrated energy systems in oil fields.

关键词

油田综合能源系统 / 热电联产 / 碳捕集与封存 / 光电储加热炉 / 源荷不确定性 / 信息间隙决策理论

Key words

oilfield integrated energy system / combined heat and power / carbon capture and storage / photovoltaic thermal storage furnace / source and load uncertainty / information gap decision theory

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基金资助

黑龙江省自然科学基金项目(LH2019E016)

黑龙江省省属本科高校基本科研业务费项目(15071202301)