上海交通大学学报, 2024, 58(5): 647-658 doi: 10.16183/j.cnki.jsjtu.2022.350

新型电力系统与综合能源

考虑广义储能和LCA碳排放的综合能源系统低碳优化运行策略

孙毅,1, 谷家训1, 郑顺林1, 李熊2, 陆春光2, 刘炜2

1.华北电力大学 电气与电子工程学院,北京 102206

2.国网浙江省电力有限公司营销服务中心,杭州 311121

Low-Carbon Optimal Operation Strategy of Integrated Energy System Considering Generalized Energy Storage and LCA Carbon Emission

SUN Yi,1, GU Jiaxun1, ZHENG Shunlin1, LI Xiong2, LU Chunguang2, LIU Wei2

1. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China

2. Marketing Service Center, State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 311121, China

责任编辑: 王历历

收稿日期: 2022-09-8   修回日期: 2022-12-15   接受日期: 2022-12-30  

基金资助: 国家电网公司总部科技项目“电力系统碳核查计量支撑基础网络构建与关键技术研究”(5400-202255274A-2-0-XG)

Received: 2022-09-8   Revised: 2022-12-15   Accepted: 2022-12-30  

作者简介 About authors

孙毅(1972-),教授,博士生导师,从事能源互联网及其信息通信技术、物联网及现代传感技术等方面的研究.E-mail:sy@ncepu.edu.cn.

摘要

综合能源系统(IES)是当前能源转型低碳发展背景下实现“双碳”目标的关键,为了提高IES碳减排能力,需要充分利用需求侧负荷资源和传统储能设备等广义储能资源参与IES优化.首先,建立一种综合考虑可再生能源、能源转换设备、广义储能设备、能源市场交易的IES优化运行模型.然后,使用生命周期评估法(LCA)对IES中能源循环、设备循环的全过程进行碳排放量计算,并将碳排放成本纳入系统总成本.最后,利用仿真实验验证所提模型不仅有利于降低IES总调度成本,还能降低系统的碳排放量,有效促进IES的低碳发展.

关键词: 广义储能; 碳排放; 综合能源系统; 优化运行; 生命周期评估法

Abstract

Integrated energy system (IES) is the key to achieve the “dual carbon goals” in face of the current energy industry transformation and low-carbon development. In order to improve the carbon emission reduction capacity of the IES, it is necessary to make full use of the load resources on the demand side and the generalized energy storage resources such as traditional energy storage equipment to participate in the optimization of the IES. First, an IES optimization operation model considering renewable energy, energy conversion equipment, generalized energy storage equipment, and energy market transaction is established. Then, the life cycle assessment (LCA) method is used to calculate the carbon emission of the whole process of energy cycle and equipment cycle in the IES, and the carbon emission cost is included in the total cost of the system. The results of simulation experiments show that the proposed model is not only conducive to reducing the total scheduling cost of the IES, but also able to reduce the carbon emissions of the system and effectively promote the low-carbon development of the IES.

Keywords: generalized energy storage; carbon emissions; integrated energy system (IES); optimized operation; life cycle assessment (LCA)

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本文引用格式

孙毅, 谷家训, 郑顺林, 李熊, 陆春光, 刘炜. 考虑广义储能和LCA碳排放的综合能源系统低碳优化运行策略[J]. 上海交通大学学报, 2024, 58(5): 647-658 doi:10.16183/j.cnki.jsjtu.2022.350

SUN Yi, GU Jiaxun, ZHENG Shunlin, LI Xiong, LU Chunguang, LIU Wei. Low-Carbon Optimal Operation Strategy of Integrated Energy System Considering Generalized Energy Storage and LCA Carbon Emission[J]. Journal of Shanghai Jiaotong University, 2024, 58(5): 647-658 doi:10.16183/j.cnki.jsjtu.2022.350

在当前世界化石燃料枯竭和环境污染加剧的背景下,我国正着力推进实现“双碳”目标,严格实施能源“双控”制度.作为《巴黎协定》的积极践行者,中国向全世界承诺:到2030年,中国单位国内生产总值CO2排放将比2005年下降65%以上[1].为进一步贯彻落实国家能源安全新战略,大力发展使用清洁和可持续能源的综合能源系统(Integrated Energy System, IES)已成为全方位支撑“双碳”目标落地的重要手段,也是实现能源转型和能源结构调整的重要举措.

作为新一代高效、低碳的能源供应系统[2-4],IES能满足需求侧对电力、供热、供冷和燃气等多种形式能源的综合需求[5-7].在IES中,储能装置(Energy Storage, ES)凭借对能量强大的时段转移能力而成为IES的重要组成部分.文献[8]中使用储能系统和需求响应提高了风力发电商在短期电力市场中的利润;文献[9]中研究了储能系统对提高IES灵活性的影响.除了传统储能设备,空调[10]、电动汽车[11]等具备一定储能特性的可控负荷也可以通过某些措施来改变能量时空分布,转化为一类成本较低,调控特性较好的广义储能[12].在IES中,考虑广义储能设备不仅可以节约建设常规储能设备所需的高额成本[13-14],还可以减少传统储能设备在生产、运行和退役等环节产生的碳排放.文献[15]中利用广义储能,充分发挥电-热-气资源的灵活耦合与多能互补特性,提高了系统的经济性与灵活性.文献[16]中针对灾时容灾阶段提出可改善电网弹性的广义储能调度方法,该方法能改善电网灾后性能并提高其运行弹性的有效性.

随着“双碳”背景下IES优化调度相关研究的深入[17-20],对IES进行碳排放定量计算是实现IES低碳运行的先决条件[21-22].文献[23]中针对现有电力系统碳排放流理论存在的若干问题提出一种碳排放量计算的改进方法.文献[24]中将碳排放流理论和需求响应引入IES优化调度,有效提高能源利用率,降低系统的碳排放和运行成本.以上研究基于碳排放流理论分析IES运营中各负荷的碳排放量,但没有考虑系统设备的多样性和环境因素的复杂性.为了分析从能源生产源头到退役设备处理全过程的碳排放,全生命周期评估法(Life Cycle Assessment, LCA)成为精确分析系统碳排放的有效手段[25].文献[26]中对3种大规模储能应用系统进行全生命周期分析,得出它们的度电成本.文献[27]中利用LCA计算和研究了海、陆风电系统的碳排情况,结果表明海上风电系统经济效益更高,对环境更友好.以上研究为使用LCA分析IES的碳排放提供了探索性的成果,但所评估的对象均局限于某一具体设备或能源,未能综合考虑IES中所有的设备循环与能源循环.

综合上述分析,为实现IES的低碳优化运行,本文将多能源储能设备和需求侧灵活性负荷视为广义储能资源,节约建设成本及碳排放成本,同时使用LCA计算全设备和多能源的碳排放量,全方位、多角度地对IES进行碳排放评估,将碳排放成本和系统运行成本纳入IES经济性决策指标,建立一种考虑广义储能和LCA碳排放的IES优化运行模型.该模型不仅可以降低IES的总运行成本,还能降低系统的碳排放量,为IES的低碳发展提供参考.

1 IES的结构和广义储能设备模型

1.1 考虑广义储能的IES结构

建立的IES包括电能、气能和热能,系统结构如图1所示.IES内的能源供应不仅包括外部电网、气网和热网的供能,还包括来自风力发电和光伏发电等可再生能源的供能.能源聚合商间还有一些能源转换设备,主要包括燃煤热电联产机组(Combined Heat and Power, CHP)、燃气轮机(Gas Turbines, GT)、电转气(Power to Gas, P2G)、电锅炉(Electric Boilers, EB),能源转换设备可以实现不同能源间的协调利用和灵活转化.需求侧的能源用户在能源聚合商处进行能源消费,主要包含电能、气能和热能.广义储能设备包括实际储能和虚拟储能,储能设备可以在时间尺度上进行能源的互补利用.

图1

图1   考虑广义储能的IES结构

Fig.1   Structure of IES considering generalized energy storage


1.2 广义储能设备模型

考虑的广义储能设备主要由实际储能设备和虚拟储能设备构成,其中实际储能设备包括储电、储气和储热设备,虚拟储能设备包括参与激励型需求响应的可转移负荷和可削减负荷.

1.2.1 实际储能模型

储电设备包括锂离子电池储能电站及压缩空气储能电站等,它们在可再生能源出力高峰和用电谷段时储电,在可再生能源出力不足和用电峰段时放电.储热设备包括水储热站和熔融盐(固体)储热站等,它们可以储存热量,在IES需要时释放热量.同理,储气设备包括储气罐等,它们可以储存天然气,在IES需要时供给天然气.据此,基于文献[28-29],实际储能的一般模型可归纳为

SES,tEN=(1-ηES)SES,t-1EN+ηESENPES,t-1ENΔTSESEN,max0SES,tENSESEN,maxPESEN,minPES,tENPESEN,maxEN{e,h,g}

式中:EN为能源,e、h、g分别为电、热、气3类能源;SES,tENt时段实际储能设备的储能量;ηES为实际储能设备的自放能率;ηESEN为实际储能设备的运行效率,当实际储能设备充能时为充能效率,放能时为放能效率;PES,tEN为t时段实际储能设备的运行功率,充能时其值为正,反之则为负;ΔT为单个时段的时长;SESEN,max为实际储能设备的储能容量;PESEN,maxPESEN,min分别为实际储能设备运行功率的上下限,上限表示最大充能功率,下限表示最大放能功率.

1.2.2 可转移负荷模型

可转移负荷在一个调度周期内总用电量一定,但可以在一定时间范围内“转移”其耗能时间,实现能量的时移.增加或减少的用电量可视为虚拟储能的充、放电量,其模型如下:

0PTL,t,ioutxTL,t,iout(PTL,t-1,iout,max-PTL,t-1,iout)0PTL,t,iinxTL,t,iin(PTL,t-1,iin,max-PTL,t-1,iin)xTL,t.iinxTL,t.iout=0tTi(xTL,t,iout+xTL,t,iin)=0Ti=ti,startTL,ti,endTLi=1It=1T(xTL,t,iinPTL,t,iin-xTL,t,ioutPTL,t,iout)=0

式中:PTL,t,ioutPTL,t,iin分别为t时段第i种可转移负荷的等效放、充能功率;PTL,t-1,iout,maxPTL,t-1,iin,max分别为t-1时段第i种可转移负荷最大充放能功率;xTL,t,iinxTL,t,iout分别为等效充、放能状态变量,充能状态为1,反之为0;Ti为第i种可转移负荷的调度周期;ti,startTLti,endTL分别为调度周期的开始与结束时间.

1.2.3 可削减负荷模型

可削减负荷(Reducible Load, RL)通过在一定范围内削减功率来等效虚拟储能的放能过程,其模型如下:

0Pt,jRLyt,jRLPt,jRL,maxt=1T(yt,jRL-yt-1,jRL)yt,jRL=nt,jRLtTjyt,jRL=0Tj=tj,startRL,tj,endRL0nt,jRLnt,jRL,maxzjRL,minzjRLzjRL,max

式中:Pt,jRLt时段第j种可削减负荷功率;Pt,jRL,maxt时段第j种可削减负荷的削减上限;yt,jRLt时段第j种可削减负荷状态变量,1为调度,0为不调度;nt,jRLt时段第j种可削减负荷的调度次数;Tj为第j种可削减负荷的调度周期;tj,startRLtj,endRL分别为第j种可削减负荷调度周期的开始与结束时间;nt,jRL,maxt时段第j种可削减负荷的调度次数上限;zjRL为第j种可削减负荷的单次调度时长;zjRL,maxzjRL,min分别为调度时长上下限.

2 面向IES碳排放的生命周期评估

2.1 基于生命周期评估的碳排放分析方法

为了实现IES的科学低碳运行,需要在目标函数中引入使用LCA的碳排放因子.LCA可以更精确地分析IES全生命周期能流过程中的碳排放.综合考虑能源循环和电厂运行周期过程中的碳排放,对IES进行生命周期评估,过程如图2所示.

图2

图2   IES的LCA过程

Fig.2   LCA process of IES


LCA方法可以全面跟踪IES各个环节的碳排放轨迹,有利于更好地进行低碳减排优化,有效降低碳排放.为了全面分析IES中各种设备的碳排放,使用基于文献[30-31]的能源、设备循环LCA碳排放分析法,即对各类能源循环的碳排放进行全面的分析,考虑不同发电设备的运行参数和各环节的能量损失,对不同发电设备的温室气体排放进行定量计算,再标准化为CO2排放量.然后将能源循环分为开采、运输、使用和处理4个环节,设备循环分为设备生产、运输建设、运行和退役4个环节.

2.2 IES的碳排放生命周期评估

2.2.1 设备循环

为了全面分析IES中各种设备在系统运行过程中的温室气体排放,参考文献[32]中提出的基于LCA设备链的碳排放分析方法.设备循环的LCA温室气体排放主要来自设备生产、运输建设、发电运行和退役处理.考虑的IES设备包括燃气轮机、CHP、风电、光伏、电锅炉、P2G和储能设备.将4个环节的碳排放量相加,得到总碳排放量,再除以总发电量,可得单位发电量的碳排放系数.过程如下:

δEQ=nIEN,nQEQφloadSpgLEQ{PV,WT,CHP,GT,P2G,EB,ES}

式中:EQ为设备,PV、WT、CHP、GT、P2G、EB、ES分别为光伏、风力机、热电联产机组、燃气轮机、电转气设备、电锅炉、储能设备;δEQ为EQ的单位电量碳排放系数;IEN,n为设备循环中环节n所用能量EN的能耗;QEQ为EQ的碳排放强度;φload为负荷系数;Spg为发电规模;L为设备运行寿命.经计算可得到IES中各类设备的度电碳排放系数.

上述设备中,P2G设备的碳原料来源为设备中的碳捕获装置,该装置可以分离和捕获IES排放气体中的CO2,送入P2G设备中进行处理,将其转化为天然气后重新输送到系统内气网.虽然包含碳捕获装置的P2G设备与IES中其他设备相比运行成本较高,但环境效益提高,系统碳排放量降低,尤其是与储气装置的配合可以进一步降低额外增加的系统运行成本[6,18,32].

2.2.2 能源循环

为了全面分析IES中各类能源在系统运行过程中的温室气体排放,参考文献[32]中提出的基于LCA能源链的碳排放分析方法.能源循环的LCA温室气体排放主要来自能源开采、能源运输、发电运行和废气处理.考虑的能源包括IES从外部购买的煤炭和从能源市场购买的电能、热能和气能.

煤炭在LCA能源循环中的温室气体排放主要来自煤炭开采和洗选、加工和运输以及燃烧发电,表达式如下:

δpm=IcpηcpQcm(1+α+β)δtm=a=1Aab=1BbIa,bQa,b,cka,bMaDaδum=IumQum,c
δm=δpm+δtm+δum+δcm

式中:δpm为能源循环中煤炭生产环节的度电碳排放系数;Icp为煤炭的单位损失;ηcp为煤炭的转换效率;Qcm为煤炭生产的碳排放强度;α为原煤自燃引起的单位功率损失率;β为原煤洗选引起的单位功率损耗率;δtm为能源循环中煤炭运输环节的度电碳排放系数;Aa为煤炭运输方式,主要包括铁路、公路和水路;Bb为燃料类型,主要包括汽油、柴油和电力;Ia,b为第a种运输模式下第b种燃料的单位损失;Qa,b,c为使用第b种燃料的第a种运输方式产生的第c种温室气体的碳排放强度;ka,b为使用第b种燃料的第a种运输方式的运输距离与能量循环中总距离的比率;Ma为使用第a种运输方法运输的煤炭总量;Da为使用第a种运输方法运输的煤炭的平均距离;δum为燃煤发电环节产生的度电碳排放系数;Ium为发电环节的单位煤耗;Qum,c为能源循环中燃煤发电机组每单位标准煤当量的第c种温室气体碳排放强度;δm为燃煤发电的碳排放系数;δcm为废气处理环节产生的度电碳排放系数.同理可得IES中天然气能源的碳排放系数δg.

根据IES中各设备产电、热的比例及对应的碳排放系数可得IES中电能和热能的碳排放系数 δeδh.

2.2.3 考虑设备循环和能源循环的LCA碳排放

IES的碳排放生命周期评估包括电厂循环和能源循环,具体包括其中的生产环节、运输环节和使用环节,并考虑每个环节中相应设备单元的碳排放.IES中的实际碳排放源包括可再生能源发电设备、能源转换设备和储能设备.其中可再生能源发电设备的碳排放LCA计算如下:

EWT=δWTt=1TPWT,tEPV=δPVt=1TPPV,t

式中:EWTEPV分别为风电机组和光伏机组的实际碳排放量;δWTδPV分别为风电机组和光伏机组的实际度电碳排放系数;PWT,tPPV,t分别为风电机组和光伏机组在时段t内的实际出力.

能源转换设备的碳排放LCA计算如下:

ECHP=(δCHP+δm)t=1TPCHP,tEGT=(δGT+δg)t=1TPGT,tEEB=(δEB+δe)t=1TPEB,tEP2G=(δP2G+δe)t=1TPP2G,t

式中:ECHPEGTEEBEP2G分别为燃煤CHP机组、燃气轮机机组、电锅炉机组和P2G机组的实际碳排放量,由于其中P2G机组可以在运行过程中吸收部分CO2,减少IES的实际碳排放量,所以EP2G<0;δCHPδGTδEB分别为燃煤CHP机组、燃气轮机机组、电锅炉机组的实际度电碳排放系数;δP2G为P2G机组的实际度电碳排放系数,一般为负;PCHP,tPGT,tPEB,tPP2G,t分别是燃煤CHP机组、燃气轮机机组、电锅炉机组和P2G机组在时段t内的实际出力.

储能设备的碳排放LCA计算如下:

EESEN=δESENt=1TPES,tENEN{e, h, g}

式中:EESEN为储能设备的实际碳排放量;δESEN为储能设备实际度电碳排放系数.

IES市场购能的碳排放LCA计算如下:

EMar= t=1TePMar,thHMar,tgGMar,t)

式中:EMar为市场购能的实际碳排放量;PMar,tHMar,tGMar,t分别为t时段的市场购电、热、气功率.

综上,IES的碳排放LCA计算如下:

Eall=EWT+EPV+ECHP+EGT+EEB+EP2G+ EESEN+EMar

式中:Eall为IES的碳排放量.

3 考虑广义储能和LCA碳排放的IES优化运行模型

3.1 目标函数

IES在考虑能源供给、能源储存和LCA碳排放的前提下,以运行成本CIES最小为目标,建立IES优化运行模型:

min CIES= t=1T(CDEV,t+CMAR,t+CCAR,t)

式中:CDEV,tt时段IES内设备运行成本,具体包括可再生能源、能源转换设备和储能设备的运行成本;CMAR,tt时段IES从外部能源网络购能的成本;CCAR,tt时段IES的碳排放成本.

3.1.1 设备运行成本

计算如下:

CDEV,t=CRE,t+CCV,t+CES,t

式中:CRE,tt时段可再生能源设备运行成本;CCV,tt时段能源转换设备运行成本;CES,tt时段储能设备运行成本.各变量的表达式为

CRE,t=kWTPWT,t+kPVPPV,t+ kWTp(PWT,tfor-PWT,t)+ kPVp(PPV,tfor-PPV,t)
CCV,t=kCHPPCHP,t+kGTPGT,t+kEBPEB,t+kP2GPP2G,t
CES,t= kESePES,te+ kEShPES,th+ kESgPES,tg+kTL(PTL,tin+ PTL,tout)+kRLPtRL

式(14~16)中:kWTkPV分别为风机和光伏的单位运行成本;kWTpkPVp为单位弃风/光惩罚系数;PWT,tforPPV,tfor分别为风机和光伏在t时段的预测出力;kCHPkGTkEBkP2G分别为CHP机组、燃气轮机、电锅炉和P2G的单位运行成本;kESekEShkESg分别为电储能、热储能、气储能设备的单位运行成本;PES,tePES,thPES,tg分别为电储能、热储能、气储能设备在t时段的运行功率;kTLkRL分别为可转移负荷和可削减负荷的单位补偿成本;PTL,tinPTL,tout分别为t时段等效充、放能功率.

3.1.2 市场购能成本

计算如下:

CMAR,t=(kMar,tePMar,t+ kMar,thHMar,t+ kMar,tgGMar,t)ΔT

式中:kMar,tekMar,thkMar,tg分别为t时段的市场购电、热、气价格.

3.1.3 系统碳排放成本

IES的碳排放成本与其碳排放量成正比.前文中已经详细阐述如何基于LCA方法计算IES的碳排放量,因此IES的碳排放成本可表示为

CCAR,t=τtaxEall

式中:τtax为碳排放税.

3.2 约束条件

3.2.1 设备运行约束

可再生能源设备运行约束为

0PWT,tPWT,tfor0PPV,tPPV,tfor

燃煤热电联产机组的运行约束为

PCHP,t=ηe,CHPICHP,tHCHP,t=ηh,CHPICHP,tPCHPminPCHP,tPCHPmax

式中:HCHP,t为CHP在t时段的热出力;ηe,CHPηh,CHP分别为CHP的电出力、热出力效率;ICHP,t为CHP在t时段的燃煤消耗量;PCHPmaxPCHPmin分别为CHP的出力上下限.考虑的CHP为定热电比运行模式.

燃气轮机设备的运行约束为

PGT,t=ηe,GTGGT,tHGT,t=ηh,GTGGT,tPGTminPGT,tPGTmax

式中:HGT,t为燃气轮机在t时段的热出力;ηe,GTηh,GT分别为燃气轮机的电出力、热出力效率;GGT,t为燃气轮机在t时段的燃气消耗量;PGTmaxPGTmin分别为燃气轮机的出力上下限.

电锅炉设备的运行约束为

HEB,t=ηEBPEB,tHEBminHEB,tHEBmax

式中:HEB,t为电锅炉在t时段的产热功率;ηEB为电锅炉的产热效率;HEBmaxHEBmin分别为电锅炉的产热量上下限.

电转气设备的运行约束为

GP2G,t=ηP2GPP2G,tGP2GminGP2G,tGP2Gmax

式中:GP2G,t为P2G在t时段的产气量;ηP2G为P2G的制气效率;GP2GmaxGP2Gmin分别为P2G的产气量上下限.

3.2.2 市场购能约束

表示为

PMarminPMar,tPMarmaxHMarminHMar,tHMarmaxGMarminGMar,tGMarmax

式中:PMarminPMarmax分别为市场购电功率的上下限;HMarminHMarmax分别为市场购热功率的上下限;GMarminGMarmax分别为市场购气功率的上下限.

3.2.3 功率平衡约束

表示为

PMar,t+PWT,t+PPV,t+PCHP,t+ PGT,t-PP2G,t-PEB,t-PES,t= P0,t+(PTL,tin-PTL,tout)+PRL,tHMar,t+HCHP,t+HGT,t+ HEB,t-HES,t=H0,tGMar,t+GP2G,t-GGT,t-GES,t=G0,t

式中:P0,tH0,tG0,t分别为t时段需求侧的电、热、气基线负荷;HEB,tGES,t 分别为t时段实际储热、储气设备运行功率.

3.3 模型求解分析

由式(12)~(18)可知,所设置的考虑广义储能和LCA碳排放的IES优化运行模型的目标函数为一个线性函数,同时由式(19)~(25)可知,其约束条件均为线性约束.由此可知,此优化模型为一个典型的线性规划模型,可基于梯度的方法进行求解.

4 算例分析

为验证上述算法的有效性,在不考虑广义储能或考虑碳排放的情况下对比所提算法的仿真结果.IES内用户的基线负荷和风电、光伏的预测出力情况参考文献[33],IES日前购能如图3所示,市场购能价格如图4所示.

图3

图3   IES日前购能

Fig.3   Day-ahead energy purchase of IES


图4

图4   能源市场中的能源交易价格

Fig.4   Energy transaction price in energy market


4.1 基础运行仿真结果分析

根据前文所述IES的LCA碳排放分析方法,计算碳排放系数,其计算过程的数据来源如表1所示.

表1   碳排放计量参数来源

Tab.1  Measuring parameters of carbon emission sources

能源循环环节参考文献
风电设备循环生产[35-36]
风电设备循环运输建设[35]
风电设备循环退役[35,37]
光伏设备循环生产[35,37]
光伏设备循环运输建设[35]
光伏设备循环退役[35,38]
煤电设备循环全过程[39]
煤电能源循环生产[40-41]
煤电能源循环运输[40-41]
煤电能源循环运行[40-42]
气电设备循环全过程[39]
气电能源循环生产、运输[43-44]
气电能源循环运行[43]
气电能源循环处理[43]
储能设备循环全过程[45]

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系统其余运行参数设置参考文献[34],基准碳价设置为50元/t.模型使用基于MATLAB的IPOPT工具箱进行求解.

图5为IES在考虑和不考虑碳排放两种情况下电能的出力情况.由图可见,两种情况对风电及光伏的出力影响不大,这是因为对弃风或弃光现象的惩罚会使得IES尽可能选择消纳可再生能源出力;由于P2G设备中的碳捕获装置可以吸附废气中的CO2,所以在考虑碳排放的场景下,系统会尽量增加P2G设备出力以减少碳排放量;在电价上涨同时又是用电高峰的时段(7:00—23:00),电锅炉会停止工作以减少系统用电量;由于煤炭燃料的低成本等因素,CHP设备在不考虑碳排放时会增加出力来增加系统发电量,但在考虑碳排放时会减少出力来减少系统碳排;在考虑碳排放的情况下,广义储能也在用能谷期储能,在用能峰期放能,发挥削峰填谷、平抑波动的作用.

图5

图5   各时段IES中各设备的电能出力

Fig.5   Electric output of each equipment in the IES in each period


图6为IES在考虑和不考虑碳排放两种情况下热能的出力情况.由图可见,由于CHP设备运行的碳排高而市场购能和燃气轮机设备运行的碳排低,所以在考虑碳排放的情况下,CHP设备会减少出力,转而增加燃气轮机出力和市场购能;同时在用电高峰期,考虑碳排放的系统发电量会下降,此时电锅炉设备会停止出力.

图6

图6   各时段IES中各设备的热能出力

Fig.6   Thermal output of each equipment in the IES in each period


图7为IES在考虑和不考虑碳排放两种情况下气能的出力情况.由图可见,在考虑碳排放的情况下,由于燃气轮机设备运行的碳排低,系统会倾向于增加燃气轮机设备的出力进行替代,同时增加P2G设备的出力以减少系统碳排.

图7

图7   各时段IES中各设备的气能出力

Fig.7   Gas output of each equipment in the IES in each period


综上所述,考虑广义储能和LCA碳排放的IES低碳优化调度策略可以有效调度IES内设备,尽可能地消纳可再生能源出力,减少高碳排设备出力,增加低碳排设备出力,在用电谷期调度广义储能设备充能,在用电峰期放能,达到节能减排削峰填谷的目的.

4.2 引入广义储能/LCA碳排放的有效性分析

为验证引入广义储能和LCA碳排放参与IES运行的有效性,在前述基础场景上,设置对比场景:场景A,考虑碳排放同时考虑广义储能;场景B,不考虑碳排放但考虑广义储能;场景C,考虑碳排放但不考虑广义储能;场景D,不考虑碳排放也不考虑广义储能.基于上述场景重新对模型进行求解,结果如图89表2所示.

图8

图8   不同场景下IES的分时段碳排放量

Fig.8   Carbon emissions of IES by time period in different scenarios


图9

图9   不同场景下IES的分时段成本

Fig.9   Cost of IES by time period in different scenarios


表2   不同场景下IES的运行成本、碳排放成本和总成本

Tab.2  Operation cost, carbon emission cost, and total cost of integrated energy system in different scenarios 元

场景CDEVCCARCIES
A16394.335610.8122005.14
B15971.536458.7122430.24
C16303.065813.3822116.44
D15955.876557.0322512.90

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图8中可以看到,场景A、C的分时段碳排放量在大部分时段都小于场景B、D的分时段碳排放量,这是因为在优化目标函数中考虑碳排放成本会使系统减少如CHP等碳排放量大的设备出力,转而增加P2G等可以减少碳排放量的设备出力,导致系统的碳排放量减少.在6:00前,电价较低,IES会调度广义储能设备进行充能,故此时场景A的碳排放量会略高于场景C;12:00—22:00,负荷侧需求增加,场景A中的广义储能设备放能,但场景C中的IES只能通过增加产能设备的出力来满足负荷需求,故此时场景A的碳排放量小于场景C.

图9中可以看到,场景A、C的分时段成本在大部分时段都小于场景B、D的分时段成本,说明在优化函数中考虑系统碳排放成本不仅可以减少系统的碳排放量,还可以降低系统的运行成本.广义储能设备虽然可以减少系统的碳排放量,但调度广义储能设备的成本较高,故在用电谷期,广义储能设备充能,场景A的成本高于场景C;在用电峰期,广义储能设备放能,场景A的成本低于场景C.

表2中可以看到,场景B、D由于不考虑碳排放,其运行成本,包括设备成本和市场购能成本略低于场景A、C,但其碳排放成本高于场景A、C,最终总成本也高于场景A、C.由于实际储能具有低运行成本、高碳排放,虚拟储能具有高运行成本、低碳排放的性质,不考虑广义储能的场景C的运行成本略低于场景A,但其碳排放成本高于场景A,最终总成本高于场景A.综合上述分析,同时考虑广义储能和LCA碳排放会使IES的总成本最低,碳排放成本也最低,可以使系统碳减排16.86%,同时使总成本减少2.31%.

综上可知,所提考虑广义储能和LCA碳排放的IES低碳优化调度策略可以有效降低系统的碳排放量与总运行成本.

5 结语

为解决IES运行中的碳计量和碳减排问题,提出一种考虑广义储能和LCA碳排放的IES低碳优化运行策略.首先,针对减碳问题,在IES中考虑可以减少传统储能设备在生产、退役处理等环节的碳排放的广义储能设备;其次,针对碳计量问题,使用可以精确计算IES的总碳排放量的LCA方法.最后,基于LCA碳排放建立了一种综合考虑可再生能源设备、能源转换设备、广义储能设备及能源市场交易的IES低碳优化运行模型.算例结果表明,所提优化模型可以使系统碳减排16.86%,同时也使总成本减少2.31%.所提计及广义储能和LCA碳排放的IES低碳优化运行策略能充分发挥各类能源形式之间的互补优势和协同效益,科学精准地减少系统的碳排放量,并有效促进IES的低碳发展.

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With the development of the electricity market and carbon market,the introduction of demand response and carbon trading mechanisms into the operation and dispatch of integrated energy systems will help guide users and system operators to optimize electricity consumption and dispatch plans.The comprehensive incentive measures such as time-of-use electricity prices and demand response incentive subsidies are used to guide users to participate in demand response.A two-layer stochastic optimal scheduling model for a comprehensive energy system considering the ladder-type carbon trading mechanism and demand response is constructed based on IGDT (information gap decision theory) theory.The two-layer model is converted into a single-layer model by KKT condition and big M method for solving.The results show that the introduction of the demand response and carbon trading mechanisms can achieve low-carbon and environmentally friendly operation of the integrated energy system.

JAMALI A, AGHAEI J, ESMAILI M, et al.

Self-scheduling approach to coordinating wind power producers with energy storage and demand response

[J]. IEEE Transactions on Sustainable Energy, 2020, 11(3): 1210-1219.

[本文引用: 1]

NIKOOBAKHT A, AGHAEI J, SHAFIE-KHAH M, et al.

Assessing increased flexibility of energy storage and demand response to accommodate a high penetration of renewable energy sources

[J]. IEEE Transactions on Sustainable Energy, 2018, 10(2): 659-669.

[本文引用: 1]

王瑞东, 吴杰康, 蔡志宏, .

含广义储能虚拟电厂电-气-热三阶段协同优化调度

[J]. 电网技术, 2022, 46(5): 1857-1866.

[本文引用: 1]

WANG Ruidong, WU Jiekang, CAI Zhihong, et al.

Three-stage collaborative optimal scheduling of electricity, gas and heat in virtual power plant with generalized energy storage

[J]. Power System Technology, 2022, 46(5): 1857-1866.

[本文引用: 1]

代琼丹, 杨莉, 林振智, .

考虑功能区差异性和虚拟储能的综合能源系统多元储能规划

[J]. 电力自动化设备, 2021, 41(9): 182-190.

[本文引用: 1]

DAI Qiongdan, YANG Li, LIN Zhenzhi, et al.

Multi-storage planning of integrated energy system considering functional area difference and virtual storage

[J]. Electric Power Automation Equipment, 2021, 41(9): 182-190.

[本文引用: 1]

WANG D X, MENG K, GAO X D, et al.

Coordinated dispatch of virtual energy storage systems in LV grids for voltage regulation

[J]. IEEE Transactions on Industrial Informatics, 2018, 14(6): 2452-2462.

[本文引用: 1]

朱旭, 杨军, 李高俊杰, .

计及虚拟储能系统的区域综合能源系统优化调度策略

[J]. 电力建设, 2020, 41(8): 99-110.

DOI:10.12204/j.issn.1000-7229.2020.08.012      [本文引用: 1]

储能设备可以实现负荷的跨时段平移,在综合能源系统的经济稳定运行中能够起到重要作用。但当下储能投建费用较高,难以大规模应用。而通过优化用户侧可控负荷,可达到类似储能设备平移负荷的效果。从电能、热能2个角度出发,提出了利用用户侧虚拟储能的区域综合能源系统(regional integrated energy system,RIES)优化调度策略。首先基于电动汽车充电管理方法和楼宇蓄热特性,对电、热虚拟储能(virtual energy storage,VES)系统进行建模;进而将虚拟储能系统集成到考虑天气不确定性的区域综合能源系统调度模型中,该模型以降低能源系统日运行费用为优化目标,合理安排电动汽车充电并在温度舒适度范围内对建筑物室温进行调节,实现虚拟储能系统的充放能管理;最后以夏季系统用能场景为例,对优化模型进行仿真实证。仿真结果表明,虚拟储能设备可以起到负荷平移效果,削减储能配置容量。应用虚拟储能系统的区域综合能源系统优化调度模型可以在满足能源需求和温度舒适度的前提下降低系统日运行成本,提升系统运行稳定性。

ZHU Xu, YANG Jun, LI Gaojunjie, et al.

Optimal dispatching strategy of regional integrated energy system considering virtual energy storage system

[J]. Electric Power Construction, 2020, 41(8): 99-110.

DOI:10.12204/j.issn.1000-7229.2020.08.012      [本文引用: 1]

Transferring loads across time periods, energy storage device plays an important role in the economic and stable operation of multi-energy system. But construction cost of energy storage device is high, which makes it difficult to apply energy storage device on a large scale. From the perspective of electric energy and heat energy, this paper proposes an optimal scheduling strategy for regional integrated energy system (RIES) considering virtual energy storage (VES) system, which can also transfer energy loads across time periods. According to the electric vehicle charging management method and building heat storage characteristics, virtual electric energy and thermal energy storage model is developed. The virtual energy storage system is integrated into the RIES optimal dispatching model. By arranging the charging of electric vehicles and adjusting indoor temperature within the temperature comfort range rationally, charging/discharging power management of virtual energy storage system can be realized. Finally, different energy supply modes under the summer refrigeration scenario are simulated to demonstrate the effectiveness of the proposed optimal dispatching method. Simulation results show that the proposed strategy can improve the economy and stability of the multi-energy system while guarantee the customer temperature comfort and meet regional energy demands.

刘洋, 李立生, 刘志伟, .

考虑广义储能集群参与的配电网协同控制策略

[J]. 电力建设, 2021, 42(8): 89-98.

DOI:10.12204/j.issn.1000-7229.2021.08.011      [本文引用: 1]

随着需求响应技术的发展,温控负荷、电动汽车等具有灵活调控特性的需求侧资源可作为广义储能参与孤岛配电网的功率波动平抑控制。文章面向空调与电动汽车两类典型的广义储能,提出一种考虑广义储能集群参与的配电网协同控制策略。首先,以负荷聚合商作为控制中心,构建了多元广义储能集群控制架构;其次,分别建立了空调集群与电动汽车集群的广义储能控制模型,在空调群内,计及各空调受控次数的差异,提出改进温度优先序列控制策略,在电动汽车群内,提出了基于荷电状态的功率分配策略;随后,根据空调集群与电动汽车集群的功率响应特性,提出了一种基于低通滤波的多元广义储能协同控制策略;最后,基于Matlab/Simulink的仿真结果验证了所提控制策略的有效性。

LIU Yang, LI Lisheng, LIU Zhiwei, et al.

Cooperative control strategy of distribution network considering generalized energy storage cluster participation

[J]. Electric Power Construction, 2021, 42(8): 89-98.

DOI:10.12204/j.issn.1000-7229.2021.08.011      [本文引用: 1]

With the development of demand response technology, demand-side resources with flexible regulation characteristics such as temperature-controlled loads and electric vehicles can be used as generalized energy storage to participate in the control of power fluctuations in island distribution networks. This paper is oriented to two types of generalized energy storage, air conditioners and electric vehicles, and proposes a collaborative control strategy for distribution network that considers the participation of generalized energy storage clusters. Firstly, the load aggregator is used as the control center to build a multi-dimensional generalized energy storage cluster control architecture. Secondly, the generalized energy storage control model for the air-conditioning cluster and the electric vehicle cluster is established separately, and the number of controlled times of each air-conditioning is considered in the air-conditioning group. In the electric vehicle group, a power distribution strategy based on the state of charge is proposed. Then, according to the power response characteristics of the air-conditioning cluster and the electric vehicle cluster, a low-pass filtering-based multiple generalized energy storage coordinated control strategy is given. Finally, the simulation results based on Matlab/Simulink verify the effectiveness of this control strategy.

张大海, 贠韫韵, 王小君, .

考虑广义储能及光热电站的电热气互联综合能源系统经济调度

[J]. 电力系统自动化, 2021, 45(19): 33-42.

[本文引用: 1]

ZHANG Dahai, YUN Yunyun, WANG Xiaojun, et al.

Economic dispatch of integrated electricity-heat-gas energy system considering generalized energy storage and concentrating solar power plant

[J]. Automation of Electric Power Systems, 2021, 45(19): 33-42.

[本文引用: 1]

孙伟卿, 张婕, 叶磊, .

考虑广义储能的电力系统运行弹性优化

[J]. 系统仿真学报, 2021, 33(4): 962-972.

DOI:10.16182/j.issn1004731x.joss.19-0632      [本文引用: 1]

基于电力系统弹性定义及原理,将传统电储能设备与需求响应相结合,提出一种考虑广义储能的电网运行弹性优化方法。根据4种指标来综合评价5种基于拓扑的攻击方案,选取对系统性能最不利的攻击策略以模拟对电力系统的破坏。以系统运行成本最小为目标进行含风力电站、储能机组组合调度。针对灾时容灾阶段提出可改善运行期电网弹性的广义储能调度方法,并建立以系统弹性最大为目标的灾后恢复优化模型,通过遗传算法计算最优恢复策略。以IEEE-30节点系统为算例验证了广义储能改善系统灾后性能并提高电网运行弹性的有效性。

SUN Weiqing, ZHANG Jie, YE Lei, et al.

Operation resilience optimization of power system considering generalized energy storage

[J]. Journal of System Simulation, 2021, 33(4): 962-972.

DOI:10.16182/j.issn1004731x.joss.19-0632      [本文引用: 1]

Based on the definition and principle of power system resilience, combining the traditional energy storage equipment with the demand response, <em>an optimization method of power system operation resilience considering generalized energy storage is proposed</em>. Five attack schemes based on topology are evaluated according to four indexes, and the most disadvantageous attack strategy is selected to simulate the damage of power system. Taking the minimum operating cost of the system as the objective, a combined scheduling model involving wind power station and energy storage unit is carried out. A<em> generalized energy storage scheduling method</em> is proposed to improve the resilience of power grid in operation period in recovery stage, and an optimal model of disaster recovery is established to maximize the system resilience. The optimal recovery strategy is calculated by genetic algorithm. The IEEE 30-bus system is taken as an example to verify the effectiveness of the generalized energy storage in improving the system performance and the resilience of power grid operation.

吕祥梅, 刘天琪, 刘绚, .

考虑高比例新能源消纳的多能源园区日前低碳经济调度

[J]. 上海交通大学学报, 2021, 55(12): 1586-1597.

DOI:10.16183/j.cnki.jsjtu.2021.339      [本文引用: 1]

为提高清洁能源利用率和降低碳排放,缓解全球能源危机和温室效应,提出一种考虑高比例新能源消纳的多能源园区日前低碳经济调度模型.首先,向园区引入储气设备和储热设备后,进一步挖掘能源耦合设备的潜力,探究电动汽车充电方式的影响;其次,基于阶梯型价格曲线建立了价格型联合热电需求响应模型;然后,考虑综合能源系统低碳运行,构建了碳捕集和储碳设备模型;最后,提出多能源园区日前低碳经济调度混合整数线性规划模型.算例分析表明,所提模型能提高能源利用率和园区调度灵活性,有效降低园区碳排放量,增加园区收益,促进高比例新能源的消纳.

Xiangmei, LIU Tianqi, LIU Xuan, et al.

Low-carbon economic dispatch of multi-energy park considering high proportion of renewable energy

[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1586-1597.

[本文引用: 1]

祝荣, 任永峰, 孟庆天, .

基于合作博弈的综合能源系统电-热-气协同优化运行策略

[J]. 太阳能学报, 2022, 43(4): 20-29.

DOI:10.19912/j.0254-0096.tynxb.2022-0112      [本文引用: 2]

在&#x0201c;双碳&#x0201d;背景下,为有效提高综合能源系统(IES)的能源利用率,减少碳排放量,同时提升系统运行的灵活性,提出一种基于合作博弈的IES优化运行模型。首先构建IES框架,针对电转气(P2G)、碳捕集、燃气轮机、热储能等设备进行建模;其次考虑系统内各主体之间存在协同合作的可能,将系统内各运营主体分为三方构建合作联盟,阐述能源互补提高整体收益的原理;最后建立基于合作博弈的IES协同优化调度模型,利用Shapley值法对合作剩余按贡献进行分配。该文通过内蒙古地区某综合能源系统实例仿真分析,验证了所提出的策略能有效减少各合作主体的运行成本及合作联盟的运行总成本,促进联盟内多主体开展合作,同时有效提升系统内风电消纳能力,减少系统碳排放量,可为电力系统低碳经济调度提供理论参考。

ZHU Rong, REN Yongfeng, MENG Qingtian, et al.

Electricity-heat-gas cooperative optimal operation strategy of integrated energy system based on cooperative game

[J]. Acta Energiae Solaris Sinica, 2022, 43(4): 20-29.

DOI:10.19912/j.0254-0096.tynxb.2022-0112      [本文引用: 2]

Under the background of " peak carbon dioxide emissions" and " carbon neutrality ", in order to effectively improve the energy efficiency of integrated energy system(IES), reduce carbon emissions and improve the flexibility of system operation, an optimal operation model of IES based on cooperative game is proposed. The first step is to build an IES framework and a model for the devices of P2G, carbon capture, gas turbine and thermal energy storage. Then, divide the operation subjects in the system into three parts and construct a cooperative alliance within them considering the possibility of their coordination, and illustrate how to increase the overall interests through energy complementarity. Finally, set up an IES cooperative optimal operation model, and use Shapley value to distribute the cooperative surplus according to their contributions. By the simulation analysis of an IES in Inner Mongolia region, this paper verified that the proposed strategy can evidently reduce the operating cost of the cooperative subjects and the overall cost of the cooperative alliance. It prompts the cooperation within the subjects in the alliance, improves the wind power accommodation capacity of the system, and reduces the carbon emission, prorides theoretical support for the operation of the low-carbon economy of the power systems.

江婷, 邓晖, 陆承宇, .

电能量和旋转备用市场下电-热综合能源系统低碳优化运行

[J]. 上海交通大学学报, 2021, 55(12): 1650-1662.

DOI:10.16183/j.cnki.jsjtu.2021.297      [本文引用: 1]

建立电-热综合能源系统,同时参与电能量市场和旋转备用市场的日前优化决策模型,并将阶梯式碳交易引入该模型中.模型采用条件风险价值方法对新能源和电负荷不确定性风险进行管理,以电-热综合能源系统运营方案成本和碳排放成本最低为目标函数,制定运行计划和安排备用资源.算例分析表明,该模型通过发挥综合能源系统多能互补优势和合理安排备用资源应对不确定性因素引发的风险,提高了能源供应的可靠性、经济性和低碳性.

JIANG Ting, DENG Hui, LU Chengyu, et al.

Low-carbon optimal operation of an integrated electricity-heat energy system in electric energy and spinning reserve market

[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1650-1662.

[本文引用: 1]

赵海彭, 苗世洪, 李超, .

考虑冷热电需求耦合响应特性的园区综合能源系统优化运行策略研究

[J]. 中国电机工程学报, 2022, 42(2): 573-588.

[本文引用: 1]

ZHAO Haipeng, MIAO Shihong, LI Chao, et al.

Study on optimal operation strategy of comprehensive energy system in park considering coupling response characteristics of cooling, heating and power demand

[J]. Proceedings of the CSEE, 2022, 42(2): 573-588.

[本文引用: 1]

黄景光, 熊华健, 李振兴, .

基于生命周期法和碳权交易的综合能源系统低碳经济调度

[J]. 电测与仪表, 2022, 59(3): 82-91.

[本文引用: 1]

HUANG Jingguang, XIONG Huajian, LI Zhenxing, et al.

Low-carbon economic dispatch of integrated energy system based on life cycle method and carbon trading

[J]. Electrical Measurement & Instrumentation, 2022, 59(3): 82-91.

[本文引用: 1]

尹硕, 郭兴五, 燕景, .

考虑高渗透率和碳排放约束的园区综合能源系统优化运行研究

[J]. 华电技术, 2021, 43(4): 1-7.

[本文引用: 1]

YIN Shuo, GUO Xingwu, YAN Jing, et al.

Study on optimized operation on integrated energy system in parks with high permeability and carbon emission constraints

[J]. Huadian Technology, 2021, 43(4): 1-7.

[本文引用: 1]

汪超群, 陈懿, 文福拴, .

电力系统碳排放流理论改进与完善

[J]. 电网技术, 2022, 46(5): 1683-1693.

[本文引用: 1]

WANG Chaoqun, CHEN Yi, WEN Fushuan, et al.

Improvement and perfection of carbon emission flow theory in power systems

[J]. Power System Technology, 2022, 46(5): 1683-1693.

[本文引用: 1]

刘哲远, 邢海军, 程浩忠, .

考虑碳排放流及需求响应的综合能源系统双层优化调度

[J]. 高电压技术, 2023, 49(1): 169-178.

[本文引用: 1]

LIU Zheyuan, XING Haijun, CHENG Haozhong, et al.

Bi-Level optimal scheduling of integrated energy system considering carbon emission flow and demand response

[J]. High Voltage Engineering, 2023, 49(1): 169-178.

[本文引用: 1]

耿晓倩, 徐玉杰, 黄景坚, .

先进压缩空气储能系统全生命周期能耗及二氧化碳排放

[J]. 储能科学与技术, 2022, 11(9): 2971-2979.

DOI:10.19799/j.cnki.2095-4239.2022.0129      [本文引用: 1]

先进压缩空气储能系统是一种具有广泛应用前景的储能技术,对其展开全生命周期能耗及二氧化碳排放研究,对促进储能技术发展和政策制定有指导意义。本工作以10 MW先进压缩空气储能系统为研究对象,建立了压缩空气储能系统的全生命周期模型,基于实际机组、国家标准及相关文献等对生命周期各阶段进行清单分析,获得了压缩空气储能系统的全生命周期能耗、能效及二氧化碳排放,并进行了敏感性分析。研究结果表明,系统全生命周期度电能耗和度电二氧化碳排放量分别为5.653 MJ和36.73 g,净能量效率为63.68%;运行阶段的能耗和二氧化碳排放占比最大,分别为99.16%和90.49%;系统运行效率、系统寿命及发电时间都是全生命周期二氧化碳排放的重要影响因素,而全生命周期能耗对系统运行效率的敏感性较大。

GENG Xiaoqian, XU Yujie, HUANG Jingjian, et al.

Life cycle energy consumption and carbon emissions of advanced adiabatic compressed air energy storage

[J]. Energy Storage Science & Technology, 2022, 11(9): 2971-2979.

[本文引用: 1]

文军, 刘楠, 裴杰, .

储能技术全生命周期度电成本分析

[J]. 热力发电, 2021, 50(8): 24-29.

[本文引用: 1]

WEN Jun, LIU Nan, PEI Jie, et al.

Life cycle cost analysis for energy storage technology

[J]. Thermal Power Generation, 2021, 50(8): 24-29.

[本文引用: 1]

向宁, 王礼茂, 屈秋实, .

基于生命周期评估的海、陆风电系统排放对比

[J]. 资源科学, 2021, 43(4): 745-755.

DOI:10.18402/resci.2021.04.09      [本文引用: 1]

为了应对气候变化、资源短缺与环境污染问题,各国都在积极开发清洁能源,风能作为可再生的清洁能源,得到了世界各国的高度重视。在实现2030年碳排放达峰的目标约束下,近年来,中国风电规模也处于快速增长的阶段。风力发电过程虽然不会排放温室气体和污染物,但从产业的生命周期角度分析,在设备制造、运输、安装、运行、废弃等环节也会带来一定量的温室气体和污染物的排放,因此风力发电并不是零排放的能源。本文利用全生命周期评价方法对比研究了100 MW海上和陆上风电系统的全生命周期的排放情况,重点分析了不同功率风机的风电场的全生命周期温室气体排放情况,并分析了一般污染物对于环境的影响。研究结果表明:①海上风电场全生命周期温室气体排放量平均为1.49 g CO<sub>2</sub>/kWh,陆上风电场平均排放量3.62 g CO<sub>2</sub>/kWh,均远远小于传统火力发电,比较而言,在减少温室气体排放方面,海上风电系统更具优势;②在全生命周期污染物排放方面,海上风电场全生命周期污染物的排放量要小于陆上风电场,且具有更短的能源回报时间,经济效益更高,对环境更友好;③在全生命周期中,风机的生产过程所产生的温室气体排放占到总温室气体排放的40%以上,同时风机生产所排放的污染物对于环境的负面影响最大,约占整个生命周期影响的50%以上;④配备更大功率的风机将有助于减少温室气体和污染物的排放。研究结果可为减少环境污染、实现碳排放达峰目标提供参考依据。

XIANG Ning, WANG Limao, QU Qiushi, et al.

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DOI:10.18402/resci.2021.04.09      [本文引用: 1]

In order to cope with climate change, resource shortage, and environmental pollution, all countries are actively developing clean energy. Wind energy is one of the renewable clean energy sources, which has been vigorously developed by many countries in the world. In recent years, in order to meet the requirement of carbon emission peak in 2030, wind power in China is also rapidly developing. Although the process of wind power generation will not emit greenhouse gases and pollutants, from the perspective of the life cycle of the industry, it still produces a certain amount of greenhouse gases and pollutants in equipment manufacturing, transportation, installation, operation, waste disposal, and other links, so wind power is not zero emission energy. In this study, the life cycle assessment method was used to compare the life cycle emissions of 100 MW offshore and onshore wind power systems. The key point is to analyze the greenhouse gas emissions of wind farms equipped with different power wind turbines in the whole life cycle and the impact of emissions on the environment. The results show that: the average life cycle carbon emission of offshore wind farms is 1.49 g CO2/kWh, and that of onshore wind farms is 3.62 g CO2/kWh. The average life cycle carbon emission of both wind farms are far less than that of traditional thermal power generation. In terms of reducing greenhouse gas emissions, the offshore wind power system has more advantages; The emission of offshore wind farms in the whole life cycle is less than that of onshore wind farms, and the offshore system has shorter energy return time and is more environmentally friendly; In the whole life cycle, the greenhouse gas emissions produced by the production of wind turbines account for more than 40% of the total greenhouse gases emissions. At the same time, the pollutants from the production of wind turbines have the greatest negative impact on the environment, accounting for more than 50% of the entire life cycle impact; By comparing the life cycle emissions of offshore and onshore wind power systems with different power wind turbines, more powerful wind turbines will help reduce greenhouse gas and pollutant emissions. This study compares the life cycle emissions of offshore and onshore wind farm construction, and provides a reference for China to reduce environmental pollution and achieve the goal of carbon emissions to peak.

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