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在构建绿氢市场、全国碳排放权交易市场以及电力市场的耦合模型之前,需要厘清每个市场的运行机制,以及多个市场的链接点。随着技术的进步,我国的可再生能源发电成本越来越具有竞争力。这将为发展绿氢提供了一定的有利条件。2020年中国氢气产量大约为3.34亿t,其中灰氢占比67%,而绿氢占比仅3%。2021年,我国氢能产能提高至4亿t。中国氢能联盟发布的《中国氢能源及燃料电池产业白皮书2020》显示,在碳排放约束下,2020-2030年间绿氢比例将从3%上升至15%[28]。由此可见,我国为实现脱碳远景将大规模部署绿氢。与欧洲和美国的碳排放交易系统相比,我国的碳市场尚处于初期运行阶段,碳价水平较低。但是,碳定价机制正在逐步被社会广泛接受,碳交易的产品种类也将不断丰富。碳交易给碳排放一个明确的价格信号,通过价格传导机制,传导至企业的生产成本当中。目前,绿氢的成本远远高于其他工艺,在没有碳定价的情况下,传统化石能源制氢所产生的负外部性无法被内部化,绿氢的正外部性也无法得到有效的补偿。因此,建设碳交易中心氢能产业板块交易机制具有必要性。图1为基于绿氢市场、全国碳交易市场和电力市场运行体系而设计的多市场耦合机制。
图 1 “绿氢市场-全国碳交易市场-电力市场”耦合机制
Figure 1. Coupling mechanism of "green hydrogen market - national carbon trading market - electricity market"
从图中可以发现:(1)与灰氢相比较,绿氢更加清洁。弃风弃光等可再生能源通过电解产生绿氢并进行储存,在需要的时候绿氢转化为电能。相比于火力发电,绿氢减少碳排放。利用基准线法计算绿氢发电相比于火力发电所降低的减排量,并将减排量通过国家核证体系申请CCER,从而将绿氢的环境价值转化成CCER,并通过抵消机制参与碳市场交易。绿氢获取CCER并通过参与碳市场交易既缓解绿氢的制氢成本,也丰富了碳交易市场的产品交易品种。由此,通过CCER可以将绿氢市场与碳交易市场进行连接;(2)目前,全国碳交易市场只覆盖了部分火力发电行业。利用历史排放法,政府确定火电行业控排企业的初始碳配额。高耗能机组对碳配额的需求量较大,而低耗能机组对碳配额的需求量较小,对于碳配额的不足与剩余将在碳交易市场上开展交易。由此电力市场与碳交易市场进行了耦合;(3)对于低耗能的火力发电商也可以通过在碳交易市场上购买CCER进行碳抵消。由此,火力发电市场与绿氢市场进行了耦合。综上,绿氢市场、碳交易市场和电力市场产生耦合。
我国CCER项目由于供大于求、项目交易量小、项目不够规范等问题在实施的过程中暂停,但是随着全国碳市场的启动,CCER存量的降低和碳交易的扩容,CCER市场重启成为必然趋势。CCER除具有减排作用,还可以适当降低企业的履约成本,助推碳配额价格发现,促进可再生能源的发展。绿氢具有天然的减排优势,也具备开发CCER的条件。通过全国碳市场为绿氢提供额外的市场化收益,有助于改变其收益结构,支持绿氢的投资。另外,电力市场也通过参与碳交易市场,既可以消纳CCER,也可以参与碳配额的交易。通过碳定价机制对电源结构进行优化。
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基于2.1部分构建的多市场耦合机制,本部分将研究实现多个市场协同发展的路径。可见,上述问题是一个多变量、高阶次、非线性的动态反馈复杂系统问题。而系统动力学是一门研究信息反馈系统的学科。它根据系统内部组成要素互为因果反馈特点,从系统的微观结构角度分析各决策之间的因果关系和反馈机制。从而预测模拟系统未来的动态行为,适合分析复杂系统随时间的变化趋势[29-30]。因此,本部分采用系统动力学模型研究氢能市场、碳交易市场和电力市场协同发展问题。
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本研究所构建的模型划分为3个模块,主要研究绿氢市场子系统、电力市场子系统和碳市场子系统相互作用的机理。其中,辅助服务市场作为电力市场的一个子市场,与能量市场在调频和备用服务方面有耦合关系,二者共同构成电力市场。而文章研究的电力市场,重点放在能量市场。因此辅助服务市场并不在文章的研究范围内。所构建的系统动力学模型在特定的环境下运行,因此需要满足一定的假设条件。文章主要作出如下假设:
1)风、光、水等可再生能源通过制氢、用氢的过程,将能量进行存储、转换,使能量对用户的供应过程变得更加便捷灵活。绿氢生产所使用的可再生能源发电量是采用的弃电。
2)碳交易市场中需求方为高耗能火力发电商,供给方为低耗能火力发电商。碳配额不足的主体既可以通过购买碳配额满足自身的碳排放,也可以通过CCER进行抵消。从全国碳市场运行以来的履约情况看,市场交易量与控排企业的配额需求较为接近,因此,将碳配额买方和碳配额卖方装机容量设置成整个火电市场的一半。
3)由于碳交易市场只覆盖了部分控排企业,因此对电力市场文章只考虑了火力发电商,不考虑可再生能源发电商。假设火电机组的建设周期为12个月,电力需求按照一定的比率增长。
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本部分构建了一个包括绿氢市场、电力市场和碳交易市场反馈结构,如图2所示。其中,绿色线条连接了绿氢市场变量间的因果关系,橘色线条连接了碳市场系统变量间的因果关系,蓝色线条连接了电力市场变量间的因果关系。对图2分析可以发现:3个市场耦合的因果关系图包括1个正反馈和5个负反馈。
图 2 “绿氢市场-全国碳交易市场-电力市场”因果关系
Figure 2. Causality of "green hydrogen market - national carbon trading market - electricity market"
1)绿氢市场的正反馈:绿氢生产量增加使得绿氢出售量增加,绿氢生产商获得更多的环境收益,绿氢生产商的利润空间增加。在利益的驱动下,绿氢生产厂商将生产更多的绿氢。
2)电力市场供需负反馈:电力价格的上升使得电力需求降低,导致供给大于需求,在此情况下电力价格下降使得电力需求增加,电力市场的供需达到稳态。
3)电力市场碳排放权买方火电生产:利润驱动下碳排放权买方增加火电的生产,电力供给增加导致电价下降;当电价下降时,发电商利润降低,碳排放权买方减少火力生产,电力供给减少,电价得到回升。
4)电力市场碳排放权卖方火电生产:电价上升使得碳排放权卖方利润增加,碳排放权卖方电力生产量增加,电力供需增加;在市场调节作用下,电力供给增加使得电价下降,在利润驱动下碳排放权卖方减少电力生产。
5)碳市场碳排放权买方购买碳配额过程:碳价上升使得碳排放权买方的成本上升,利润降低,碳排放权买方电力生产量降低,对碳配额的需求降低;通过碳市场的调节,碳配额需求减少,碳价下降,碳排放买方利润空间增加,火力发电量增加。
6)碳市场碳排放权卖方出售碳配额过程:碳价上升使得碳排放权卖方利润增多,碳排放权卖方的建设、装机和生产增加,从而导致自身配额需求量增加,用于出售配额减少,碳配额超额需求减少;在碳市场供大于求的情况下,碳价下降,碳排放权卖方减少电力生产,配额的供给又增加。
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基于上述因果分析进一步构建绿氢市场、碳交易市场和电力市场的存量流量图,如图3所示。绿色框内部分为绿氢市场与碳市场耦合部分,橘色框内部分为电力市场与碳市场耦合部分,黑色箭头表示流量,云朵形状表示流量的源和漏。模型采用DYNAMO语言。基于变量间的关系,在Vensim PLE软件中设定了变量间函数关系,包括积分函数(INTEG)、延迟函数(DELAY1)和平滑函数(SMOOTH)。
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模型中火电生产、碳交易和绿氢生产过程中所需数据主要来源于国家统计局、上海环境能源数据交易所、中电联官网和中国氢能联盟。对于模型中CCER初始价格设定为40元/t,碳排放权的初始价格设定为50元/t,参数来自文献[31-32]。
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为了检验模型仿真模拟结果的有效性,文章选取了两个变量进行误差检验,分别是碳排放权价格和火力发电量总供给。对两个变量在2021年7月-2021年9月模拟值和真实值进行对比,考察其误差率,所得结果如表1所示。从表中可以发现,碳排放权价格模拟的误差率均值为−1.92%,而火力发电量总供给模拟的误差率均值为−5.06%,处于可接受范围,文章构建模型的拟合度较好。
表 1 模型有效性检验
Table 1. Model effectiveness test
时间 碳排放权价格 火力发电量总供给 模拟值/
(元·t−1)真实值/
(元·t−1)误差/
%模拟值/
TWh真实值/
TWh误差/
%2021.7 50.00 50.33 0.66 4808.89 4813.20 −0.09 2021.8 49.89 49.76 −0.26 4809.68 5239.70 −8.21 2021.9 48.32 45.35 −6.15 4810.47 5166.90 −6.89 均值 - - −1.92 - - −5.06 -
表2是文章设定的多种情景,主要从未来绿氢市场、电力市场和碳市场的改革方向上进行情景的设定。在绿氢市场中,根据2021年绿氢的年生产量将绿氢认证比例设定为2.5%。随着绿氢储能技术的成熟以及可再生能源发电比例的增加,绿氢的生产量将增加,进而认证比例也将增加。在碳市场中,CCER抵消机制将重启,为鼓励节能减排项目发展,CCER抵消比例将增加。初始碳配额分配为免费分配的方式,随着碳约束的增强,碳市场中将引入有偿拍卖机制。在电力市场中,政府为促进煤炭清洁利用效率,落后煤电机组将逐步被淘汰,这一改革措施产生的作用在多情景仿真模拟中进行分析。
表 2 情景参数设定
Table 2. Scenario parameter setting
影响因素 情景 参数设定 CCER抵消比例/% 绿氢认证比例/% 落后机组淘汰率/% 碳配额拍卖比例/% 基础情景 BAU 5 2.5 0 0 CCER抵消比例 A1 7 2.5 0 0 A2 10 2.5 0 0 绿氢认证比例 B1 5 3 0 0 B2 5 4 0 0 落后机组淘汰率 C1 5 2.5 5 0 C2 5 2.5 20 0 配额拍卖比例 D1 5 2.5 0 10 D2 5 2.5 0 20 综合情景 E1 7 3 5 10 E2 10 4 20 20
Analysis of Coupling Effect Between Green Hydrogen Trading Market and Electricity Market Under Carbon Trading Policy
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摘要:
目的 实现“双碳”目标需要充分挖掘企业节能减排的路径和发挥绿色低碳政策工具的作用。绿氢作为清洁能源以其全链路零碳排放的优势成为社会低碳转型的关键,而碳排放权交易市场是利用市场化机制控制和减少碳排放的重要政策工具。建设碳交易中心氢能产业板块交易机制,实现碳交易与氢能的耦合对落实“双碳”目标具有极大的推动作用。 方法 基于此,文章将构建“绿氢市场-全国碳交易市场-电力市场”耦合机制。进一步利用系统动力学方法对“绿氢市场-全国碳交易市场-电力市场”进行建模仿真,研究多个市场的交互关系。 结果 研究发现:首先,绿氢市场、碳交易市场与电力市场之间可以通过绿氢认证和碳配额交易实现3个市场的耦合,通过模拟仿真发现耦合模型具有可行性。其次,通过基础情景模拟仿真发现多重市场耦合可以促进刺激碳价的升高,且可以控制火力发电量和绿氢生产量的上升。最后,提升绿氢认证比例、落后机组淘汰机制和碳配额拍卖机制有助于碳定价机制的形成,促进绿氢项目规模的扩大和控制火力发电量。 结论 本研究既丰富绿氢交易模型,促进绿氢通过参与碳交易获取部分收益,减缓氢能成本压力,又通过多市场联动,发挥碳价的倒逼作用,促进传统化石制氢和火力发电比例的降低。 -
关键词:
- 市场耦合协同 /
- 绿氢 /
- 全国碳排放权交易政策 /
- 电力市场 /
- 能源结构调整
Abstract:Introduction To achieve the "carbon peak and neutrality" goals, the ways for enterprise energy conservation and emission reduction need to fully explored, and the green and low-carbon policy tools should be fully exploited. Green hydrogen, as a clean energy, has become the key to social low-carbon transition thanks to its full link zero carbon emission. Carbon emission rights trading market is a key policy tool to control and reduce carbon emissions by making use of the market-oriented mechanism. Building a carbon trading center hydrogen energy industry trading mechanism to achieve the coupling of carbon trading and hydrogen energy will greatly promote the achieving of the "carbon peak and neutrality" goals. Method Based on this, a coupling mechanism of "green hydrogen market - national carbon trading market - electricity market" was built in this paper. The "green hydrogen market - national carbon trading market - electricity market" was modeled and simulated by further utilizing the system dynamics method, and the interaction of multiple markets was studied. Result The results show that: Firstly, the coupling among the green hydrogen market, carbon trading market and electricity market can be realized through green hydrogen certification and carbon quota trading, and it is found that the coupling model is feasible through simulation. Secondly, it is found through the simulation of the basic scenario that the coupling of multiple markets can stimulate the increase of carbon price and control the increase of thermal power generation and green hydrogen production. Finally, increasing the proportion of green hydrogen certification and improving the obsolete unit elimination mechanism and carbon quota auction mechanism will help form a carbon pricing mechanism. Conclusion On the one hand, this study diversifies the green hydrogen trading models, promotes the participation of green hydrogen in carbon trading to obtain certain benefits, and reduces the hydrogen energy cost. On the other hand, it makes use of the multi-market linkage mechanism to bring into play the forced effect of carbon price and promote the reduction of the proportion of traditional fossil hydrogen production and thermal power generation. -
表 1 模型有效性检验
Tab. 1. Model effectiveness test
时间 碳排放权价格 火力发电量总供给 模拟值/
(元·t−1)真实值/
(元·t−1)误差/
%模拟值/
TWh真实值/
TWh误差/
%2021.7 50.00 50.33 0.66 4808.89 4813.20 −0.09 2021.8 49.89 49.76 −0.26 4809.68 5239.70 −8.21 2021.9 48.32 45.35 −6.15 4810.47 5166.90 −6.89 均值 - - −1.92 - - −5.06 表 2 情景参数设定
Tab. 2. Scenario parameter setting
影响因素 情景 参数设定 CCER抵消比例/% 绿氢认证比例/% 落后机组淘汰率/% 碳配额拍卖比例/% 基础情景 BAU 5 2.5 0 0 CCER抵消比例 A1 7 2.5 0 0 A2 10 2.5 0 0 绿氢认证比例 B1 5 3 0 0 B2 5 4 0 0 落后机组淘汰率 C1 5 2.5 5 0 C2 5 2.5 20 0 配额拍卖比例 D1 5 2.5 0 10 D2 5 2.5 0 20 综合情景 E1 7 3 5 10 E2 10 4 20 20 -
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