油田联合站多能互补系统构建及其节能降碳分析

Research of multi-energy complementary systems for oilfield joint stations: construction and energy-saving and carbon-reduction analysis

  • 摘要:
    目的 “双碳”背景下,节能降碳已成为保障国家能源安全与实现绿色转型的关键。油田联合站作为油气集输与处理的能耗“大户”,传统的“电网+燃气锅炉”供能模式成本高、排放大、韧性差等矛盾突出,亟需构建适应高比例可再生能源、季节调控能力强大的多能互补系统。
    方法 针对油田联合站高耗能、高排放、高韧性风险的“三高”问题,提出了“风光-氢-储-荷”多能系统协同架构:以风光发电替代网购电,以电解制氢-储氢-燃料电池形成电-氢-电闭环,以热电联产机组、热泵、储热多源供热;创新性地将阶梯碳交易与价格/激励双重需求响应纳入统一优化模型,从经济、低碳、韧性多重目标对所建系统进行评价分析。
    结果 基于混合整数线性规划(Mixed-integer Linear Programming, MILP)问题,设置了4种场景,以大庆油田某联合站为例分析表明:①与传统供能模式相比,含氢循环的多能互补系统能源利用效率提高了30%以上,年运行成本降低41.2%,碳排放强度下降为2.1 kg/(kW·h);②阶梯碳交易通过递增碳价杠杆,使系统总成本降低16.05%、碳排放下降6.74%,且可再生能源消纳率提升至90%以上;③叠加需求响应后,可削减峰值负荷5.8%,进一步降低碳排放1.3%、碳交易成本下降12.7%,实现减排与降本“双赢”;④氢能子系统作为跨时空调节器,在风光发电时段存储富余绿电,在负荷高峰或极端天气下反向供电、供热,全年弃风弃光率控制在1%以内,显著增强供能韧性。经济性测算显示,在现行碳价与电解槽投资水平下,新建系统增量投资回收期为5~8年,若碳价低于80 元/t、电解槽成本下降至2 500 元/kW以内,回收期可缩短至4 年。
    结论 研究成果已形成可复制的油田联合站供能低碳改造技术路线,有助于伴生气资源丰富、电热负荷稳定的老联合站提质增效,也可为高比例可再生能源新区块微网规划提供“电-热-氢”协同范式。

     

    Abstract:
    Objective In the context of the “dual carbon” goals, energy conservation and carbon reduction are essential for national energy security and green transformation. As major energy consumers in oil and gas gathering, transportation, and processing, oilfield joint stations using the traditional “power grid + gas-fired boiler” supply model face significant challenges, including high costs, large emissions, and limited resilience. Therefore, it is urgent to develop a multi-energy complementary system capable of integrating a high share of renewables and providing robust seasonal regulation.
    Methods To address the issues of high energy consumption, emission, and resilience risks in oilfield joint stations, a collaborative “wind-solar-hydrogen-storage-load” multi-energy system architecture was proposed. Wind and solar generation replaced purchased electricity, while an “electricity-hydrogen-electricity” closed loop was established through electrolytic hydrogen production, hydrogen storage, and fuel cells. Multi-source heat supply was achieved via combined heat and power units, heat pumps, and heat storage. The system innovatively incorporated stepped carbon trading and dual demand response (price/incentive) into a unified optimization model, which was evaluated across economic, low-carbon, and resilience objectives.
    Results Based on mixed-integer linear programming (MILP), four scenarios were analyzed using a joint station in Daqing Oilfield as a case study. The findings were as follows: (1) Compared to the traditional supply mode, the multi-energy complementary system with hydrogen cycling increased energy utilization efficiency by over 30%, reduced annual operating costs by 41.2%, and lowered carbon emission intensity to 2.1 kg/(kW·h). (2) Leveraging stepped carbon trading, total system costs decreased by 16.05%, carbon emissions dropped by 6.74%, and renewable energy consumption exceeded 90%. (3) With superimposed demand response, peak load was reduced by 5.8%, carbon emissions decreased by an additional 1.3%, and carbon trading costs fell by 12.7%, achieving both emission and cost reductions. (4) The hydrogen subsystem acted as a spatio-temporal regulator, storing surplus green electricity during wind and solar generation and supplying power and heat during peak loads or extreme weather. The annual wind and solar curtailment rate was kept below 1%, significantly improving energy supply resilience. Economic analysis indicated that, at current carbon prices and electrolyzer investment levels, the payback period for incremental investment was 5–8 years; if the carbon price dropped below RMB 80/t and electrolyzer costs fell below RMB 2 500/kW, the payback period could be shortened to 4 years.
    Conclusion The research establishes a replicable low-carbon transformation pathway for energy supply in oilfield joint stations, supporting quality and efficiency improvements in existing stations with abundant associated gas and stable electric and thermal loads. It also provides an “electricity-heat-hydrogen” collaborative model for microgrid planning in new blocks with high renewable energy penetration.

     

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