实现2020年15%非化石能源目标路径研究

大力发展非化石能源是保障我国能源供应安全、应对气候变化、调整能源结构的重要举措。我国提出2020年非化石能源占一次能源消费比重达到15%左右的发展目标。研究基于电力系统整体优化规划模型,通过系统化定量研究测算,构建了完整的清洁能源与电力协调发展情景,分析了实现15%非化石能源目标的关键问题,提出了可行的发展路径和政策建议。     

电力部门要承担起发展清洁能源的重任

我国"十二五"期间要实现能源结构调整和电力发展方式的转变,大力发展清洁能源。应当说,新能源、可再生能源、非化石能源和新兴能源都是清洁能源,它包括洁净煤、天然气(含煤层气、页岩气、致密砂岩气等)、核电、水电、风能、太阳能、生物质能等。由于清洁能源大部分需要通过电力来实现,所以在清洁能源发展中电力部门必然是主力军。电力部门一是要研究开发清洁能源新技术,把清洁能源转变成安全、稳定、经济的电力;二是要使清洁能源生产出来的电力能为广大用户所接受。只有达到这两个条件,由清洁能源转变而来的电力才能提高其在电力总供应量中的比重。在IEA和BP的世界一次能源统计中,中国"非化石能源+天然气"的比重都非常低,均不到20%。统计数据反映出的中国能源结构的突出问题是煤炭比例太高,石油、天然气、核电比例太低。因此,与发达国家不同,中国改善能源结构、发展清洁能源的重点应该是主攻洁净煤技术(包括CCS),同时加快发展天然气、核能和水电。     

2010～2020年我国能源和电力发展前景分析

本文对我国2015及2020年能源、电力消费以及碳排放强度进行高中低三种情景分析。结果表明,中方案和低方案能够实现到2020年非化石能源消费占一次能源消费比重达到15%的目标,而高方案要实现该目标,必须将人均能源消费弹性系数降至0.6左右;2020年,低碳能源发电量比例有望提高至29%～43%,核电装机比例能达到5%左右;在2010～2015年期间,清洁能源发电装机增量将首次超过煤电装机增量。     

我国防止雾霾污染的对策与建议

一般认为煤炭和石油对雾霾的贡献最大,尤其是燃煤电厂,因为煤炭占我国能源消费量的90％,燃煤电厂约占煤炭消费量的50％.我国防止雾霾污染的对策应基于:解决气候变化与环境保护问题,要靠发展非化石能源毕其功于一役是难以办到的,我们应像发达国家那样,先解决好化石能源利用中的环境问题,然后再解决化石能源利用中的气候变化问题.电力是最能清洁利用煤炭的部门,我国燃煤电厂的烟尘和二氧化硫控制已达到世界先进水平,已不是形成雾霾的主要原因.短期内应对雾霾气候的措施为:下决心解决好大气、水、土壤污染;控制大气污染要把控制PM2.5放在重要位置;天然气要优先用于替代分散的燃煤部门,并把替代下来的煤炭交给煤电厂应用;如果我国煤炭消费量中的80％～90％的煤炭供燃煤电厂用,就可控制燃煤污染.燃煤电厂对降低燃煤污染物排放负有重要责任.     

燃煤发电机组灵活性改造的研究进展综述

  目的  “碳达峰、碳中和”战略目标的提出增加了对新能源电力并网的需求,因此有必要提高燃煤发电机组的灵活性运行能力。  方法  文章详细介绍了现有燃煤机组灵活改造技术及常见的评价指标。灵活性改造主要包括:凝结水节流技术、燃煤机组耦合生物质混烧改造技术、燃煤机组制粉系统灵活性技术等;燃煤发电机组灵活性常用评价指标包括:发电机组厂用电率、锅炉热效率、机组发电标准煤耗率等。在此基础上,对灵活性改造技术以及评价指标进行总结和分析。  结果  文章提出了燃煤发电机组灵活性技术改造的7个发展方向及相关建议。  结论  原有机组的结构改进、新能源多形式的嵌入以及多储能协同提高燃煤机组灵活性是后续发展的主要方向,为后续燃煤发电机组适应“双碳”能源规划提供参考。     

破立并举、稳扎稳打有序推进非化石能源替代

积极发展非化石能源,有序推进非化石能源替代,是我国实现碳达峰、碳中和目标的关键途径.2021年,全国非化石能源装机突破10亿千瓦,清洁电力产能进一步提升,非化石能源重点建设项目取得良好开端,电力市场建设稳步推进.本文梳理了 2021年涉及非化石能源的主要政策,总结了2021年非化石能源发展取得的主要成就,并分析我国非化...     

中国中长期碳减排战略目标初探(Ⅰ)——中国分阶段温室气体减排目标的提出及其依据

减少温室气体排放已刻不容缓,一系列研究显示,温升2℃是人类生活不受气候变化干扰的上限,大致550μL/L二氧化碳当量的温室气体浓度或约450～500μL/L的二氧化碳浓度对应2℃的温升。达到稳定浓度时的2005年以后的累积排放量和2005年的排碳数据一起才可以计算出最终的减排量化指标,而拐点年代和逐年排放量是可调控的动态指标。核实本世纪上半叶的累积排放量,并将排放额度分解到各个国家和地区是一项十分艰巨且很迫切的任务。我国的碳减排可分为2005～2020年的前期、2021～2035年的中期和2036～2050年的后期。权威部门曾推算了一系列数据,但与当前掌握的实际数据对比,对2010年的碳排放预测数据均偏低。有学者提出我国2005～2050年间的排碳额度为370Gt,约为全世界的28%,比例基本合理。如果2050年二氧化碳排放总量确定为140×108t,则中国为40×108t,人均2.6t,形势非常严峻。把我国2020年二氧化碳排放量控制在100×108t以内十分必要;我国碳减排中期处于拐点过渡期,我国的拐点将直接影响世界的拐点,应争取拐点出现在2025年,过渡期为2020～2030年;我国2050年与2035年的二氧化碳排放量差值应为45×108t,只要依靠非化石能源替代化石能源、采用CCS技术、最大限度地采用零碳排放甚至负碳排放的替代燃料就能得到控制,但仍然存在许多不确定因素,有待深入研究。     

我国应适当提高煤电的比重

我国2005年电源投资3228亿元,其中火电投资2270.6亿元,占70.3％;非化石电源投资957.4亿元,占29.7％.2010年我国电源投资3641亿元,其中火电投资1311亿元,占36％;非化石电源投资2330亿元,占64％.“十一五”期间,我国火电新增装机容量锐减,非化石电源新增装机容量剧增,而每年新增发电量则逐年减少.我国2006年火电新增装机容量9287×104kW,到2010年新增火电装机容量降为5872×104kW;我国2006年非化石电源新增装机容量1216×104kW,到2010年非化石电源新增装机容量上升到3256×104kW.每年新增装机容量可增加的年发量,2006年估计为5400×108kW·h,到2010年已降为4000×108kW·h左右.2010年我国电源投资中仅占36％的火电,却提供了64％的新增装机容量,而占64％的非化石电源只提供了约36％的新增装机容量,如果按新增发电量计,则火电机组提供的发电量比例更高.按中国电力企业联合会的规则,“十二五”期间我国非化石电源比例进一步增加,火电增幅继续下降.按火电机组等效容量计,2010～2015年年均增长率仅为8％,低于同期国内年均用电量增长率8.5％.鉴于我国的资源禀赋条件和“十一五”、“十二五“电源构成的变化趋势及其后果,建议我国应适应增加煤电的比重.     

中国新能源发展研究

分析了中国新能源发展现状（水电装机跃居世界前列。核电从无到有、快速发展,风电开发方兴为艾,烟煤电站清洁化水平提高）及面临的问题（燃煤火电绿色发展任务艰巨．水电发展举步维艰,新能源发展任重道远,核电安全有序发展需要引起高度重视）,并给出了相应的应对措施（统筹做好相关规划,大力发展可再生电力,有序开展核电建设．积极推进水电开发,提高火电清洁化水平）。     

Renewable power for China: Past,present, and future

This paper briefly examines the history, status, policy situation, development issues, and prospects for key renewable power technologies in China. The country has become a global leader in wind turbine and solar photovoltaic (PV) production, and leads the world in total power capacity from renewable energy. Policy frameworks have matured and evolved since the landmark 2005 Renewable Energy Law, updated in 2009. China’s 2020 renewable energy target is similar to that of the EU. However, China continues to face many challenges in technology development, grid-integration, and policy frameworks. These include training, research and development, wind turbine operating experience and performance, transmission constraints, grid interconnection time lags, resource assessments, power grid integration on large scales, and continued policy development and adjustment. Wind and solar PV targets for 2020 will likely be satisfied early, although domestic demand for solar PV remains weak and the pathways toward incorporating distributed and building-integrated solar PV are uncertain. Prospects for biomass power are limited by resource constraints. Other technologies such as concentrating solar thermal power, ocean energy, and electricity storage require greater attention.     

Renewable power for China: Past, present, and future

This paper briefly examines the history, status, policy situation, development issues, and prospects for key renewable power technologies in China. The country has become a global leader in wind turbine and solar photovoltaic (PV) production, and leads the world in total power capacity from renewable energy. Policy frameworks have matured and evolved since the landmark 2005 Renewable Energy Law, updated in 2009. China’s 2020 renewable energy target is similar to that of the EU. However, China continues to face many challenges in technology development, grid-integration, and policy frameworks. These include training, research and development, wind turbine operating experience and performance, transmission constraints, grid interconnection time lags, resource assessments, power grid integration on large scales, and continued policy development and adjustment. Wind and solar PV targets for 2020 will likely be satisfied early, although domestic demand for solar PV remains weak and the pathways toward incorporating distributed and building-integrated solar PV are uncertain. Prospects for biomass power are limited by resource constraints. Other technologies such as concentrating solar thermal power, ocean energy, and electricity storage require greater attention.     

低碳发展时代的世界与中国能源格局

哥本哈根会议认定了"2℃"和"在2050年前全球排放量减到1990年的一半",到2050年,碳减排要求世界人均能耗不高于2.5t标煤/a。能源碳强度ω是一个反映碳排放与能源结构关系的新指标,利用它与一次能源消费中生成并排放二氧化碳的各种形式能源所占比率γ的关联式ω=2.4γ进行推算:按照450情景方案,二氧化碳排放峰值307×108t出现在2020年,而能耗峰值在2030年左右;按照丹麦方案,二氧化碳排放峰值320×108t出现在2025年,能耗峰值也大约在2030年,将达到273×108t标煤/a,人均3.3t标煤/a。碳排放峰值年越推迟,达到2050年远期目标的难度越大。按照丹麦方案,2030~2050年的20年间,需平均每年减排10×108t二氧化碳,同时与450情景方案相比,大气中二氧化碳总量将增加400×108t以上。根据中国政府宣布的2010~2020年的减排目标推算,2020年能耗为41×108t标煤,二氧化碳排放约74×108t,中国只要能做到能耗强度每5年降低20%,就能够实现此目标。中国应在2020年之前快速发展非化石能源、加速产业转型、大力发展天然气、大幅提高能效,这样就完全能够与世界减排同行。     

Hydrogen energy deployment in decarbonizing transportation sector using multi-supply-demand integrated scenario analysis with nonlinear programming — A Shanxi case study

Peaking CO₂ emissions and reaching carbon neutrality create a major role for hydrogen in the transportation field where decarbonization is difficult. Shanxi, as a microcosm of China in the systematic transformation of energy end-use consumption, is selected to investigate the hydrogen energy development forecast for decarbonization in the transportation sector. Multi-supply-demand integrated scenario analysis with nonlinear programming (NLP) model is established to analyze hydrogen energy deployment in varied periods and regions under minimum environmental, energy and economic objectives, to obtain CO₂ emission reduction potential. Results reveal that green hydrogen contributes most to low-carbon hydrogen development strategies. In high-hydrogen demand scenarios, carbon emission reduction potential is significantly higher under environmental objectives, estimated at 297.68 × 10⁴–848.12 × 10⁴ tons (2025–2035). The work provides a strategy to forecast hydrogen energy deployment for transportation decarbonization, being of vital significant guide for planning of hydrogen energy transportation in other regions.     

中国中长期碳减排战略目标初探(Ⅱ)——中国煤炭消费过程的碳排放及减排措施

中国能源领域排放的二氧化碳主要来自煤炭,因此煤炭消费过程中的碳减排措施尤为重要。煤炭的主要用户是发电部门,基于应对气候变化的需要,煤电行业的低碳途径不得不考虑采用CCS技术。不论是新建燃煤电厂,还是今后在传统电厂改建过程中增设CCS设施已是大势所趋,预计多数仍将采用MEA法脱除烟气中二氧化碳这一成熟技术。由于MEA法技术经济指标不够先进,估计10~20年内必将出现更先进的脱二氧化碳工艺技术。传统的燃煤锅炉增加CCS的经济效益已经逊于IGCC-CCS,预计2020年后IGCC电厂将成为新建煤电厂的首选方案。20年后采用临氢气化炉与燃料电池FC发电相结合、把高温的热能和甲烷的化学能直接转化为电力的IGFC高效燃煤电厂或将成功应用,IGFC综合能量转化效率比IGCC相对高出1/2~3/4,发展前景不可低估。钢铁、水泥和化工等高耗煤工业部门可通过节能和采用CCS技术降低碳排放,其余用煤的工业部门和分散用户则应考虑节能或用天然气等低碳燃料替代,间接起到减排效果。预计2050年燃煤发电和高耗煤工业总计将排放二氧化碳4.6Gt,如果二氧化碳捕集量是2.9Gt,则净排放量为1.7Gt。加上其他难以捕集二氧化碳的工业、部门及民用煤排放二氧化碳1.0Gt,合计二氧化碳净排放量为2.7Gt(情景A)。如果采用更先进的技术和严格的节能减排措施,可减少煤炭消耗0.31Gt标煤,减少二氧化碳排放0.5Gt,使煤源二氧化碳净排放量减少到2.2Gt(情景B)。无论哪种情景,实施CCS的任务都十分艰巨。     

我国天然气发电现状及前景分析

天然气发电在优化我国能源结构、天然气利用结构、电源结构,节能环保和应对气候变化等诸多方面具有独特的优势,根据主要省市"十二五"发展规划判断,2015年我国天然气发电装机容量有望超过6000万kW。本文详细分析了燃气发电面临的主要问题、影响我国未来气电发展的有利因素和不利因素,建议更加重视燃气发电的战略地位,加强上下游产业链统筹规划,因地制宜、循序渐进;在风电等间歇性能源丰富而调峰资源贫乏的地区,可建设"风气互补"的清洁能源基地,减少弃风量;进一步完善气电价格及服务补偿机制,加强多方互利合作。     

我国可再生能源发展对策

可再生能源的开发利用是应对气候变化和满足能源需求持续增长的最现实的举措。2009年我国风电和太阳能光伏发电保持了快速发展势头,其中风电装机容量估计达到约2200×104kW,但非化石能源消费量在能源消费总量中所占的比重仍然很低。2009年,我国能源消费总量约为31×108t标煤,其中水电、核电、风电等商品化非化石能源消费量约为2.3×108t标煤,约占能源消费总量的7.4%。要完成到2020年我国非化石能源在能源消费总量中所占比例达到15%的目标,任务非常艰巨。加快开发利用可再生能源是能源发展的重要任务之一,到2020年,可再生能源开发利用总量将在2008年的基础上增加2倍以上。我国目前和今后10多年时间内,可再生能源发展的重点是水电、风电、太阳能和生物质能。加快发展我国可再生能源的举措有:①继续做好水电建设工作,促进水电持续健康发展;②有序推进风电的规模化发展,显著提高风电在电力结构中的比重;③加快推广太阳能利用技术,扩大太阳能开发利用规模;④因地制宜开发利用生物质能,提高生物质能利用的现代技术水平。     

Identification of optimal strategies for sustainable energy management in Taiwan

In this study, an optimization model was developed for identifying optimal strategies in adjusting the existing fossil fuel‐based energy structure in Taiwan. In this model, minimization of the total system cost was adopted as the objective function, which was subject to a series of constraints related to energy demand, greenhouse gas (GHG) emission restriction, and energy balance. Feasibility of several potential energy structures was also evaluated through tradeoff analysis between energy system costs and GHG emission targets. Three scenarios were established under several GHG emission restriction targets and potential nuclear power expansion options. Under the three scenarios, optimal energy allocation patterns were generated. In terms of the total energy system cost, the scenario that restricted GHG emissions and nuclear power growth would result in the highest one, with an average annual increase of 4.2% over the planning horizon. Also, the results indicated that the energy supply structure would be directly influenced by energy cost and GHG emission reduction targets. Scenario 2 would lead to the greatest dependence on clean energy, which would take up 41.8% in 2025. In comparison, with no restriction on nuclear energy, it would replace several energy sources and contribute to 34.0% of the total energy consumption. Significant reduction in GHG emission could be identified under scenario 2 due to the replacement of conventional fossil fuels with clean energies. Under scenario 3, GHG emission would be significantly reduced due to the adoption of nuclear power. After 2015, energy structure in Taiwan would be slightly adjusted due to synthetic impacts of energy demand growth and GHG emission restriction. The results also indicated that further studies would be necessarily needed for evaluating impacts and feasibilities of clean energy and nuclear power utilization in Taiwan. Copyright © 2011 John Wiley & Sons, Ltd.     

并网风光互补资源评价与系统容量优化配置

为降低风电并网后冲击电网,充分利用风能和太阳能等清洁能源,以并网风光互补发电系统年内出力最平稳为前提,对风光互补资源评价和容量优化配置方法进行了研究。基于平均距平百分率和变异系数等指标,提出了衡量年内发电量波动性的方法,以发电量年内波动性最小作为求解条件,建立了风光互补系统最优装机容量比例计算方法,并确定了进行风光互补性资源禀赋定量评价的指标。以湖北省内石首市桃花山和阳新县富池风光资源状况为计算实例,验证了该方法的正确性。     

Assessment of China's climate commitment and non-fossil energy plan towards 2020 using hybrid AIM/CGE model

China made a commitment in Copenhagen to reduce its carbon dioxide emissions per unit of GDP from 40% to 45% compared with the 2005 level by 2020, and is determined to vigorously develop non-fossil fuels. This study analyzes the effects and impacts of policies that could help to achieve China's Copenhagen commitments with a hybrid static CGE model in which the electricity sector is disaggregated into 12 generation technologies. Four scenarios are developed, including the reference scenario A, the reference scenario B and two carbon constraint scenarios. The results show that carbon intensity in terms of GDP will fall by 30.97% between 2005 and 2020 in the reference scenario A, and will be reduced further by 7.97% if China's targeted non-fossil energy development plans can be achieved in the reference scenario B. However, the rest of the 40–45% target must be realized by other measures such as carbon constraint. It is also observed that due to carbon intensity constraints, GDP loss would be from 0.032% to 0.24% compared to the reference scenario B, and CO₂ emission reductions are due mainly to decreases in coal consumption in the electricity sector and manufacturing sector.     

A dynamic risk aversion model for virtual energy plant considering uncertainties and demand response

To full use clean energy to meet load demand of electrical and thermal, the paper proposed a novel concept of virtual energy plant (VEP) including wind power plant (WPP), photovoltaic power generation (PV), combined heat and power generation (CHP), solar collectors (SC), electric boiler (EB), heat storage tank (HSK), and incentive‐based demand response (IBDR). Firstly, the basic structure of VEP is designed, including three subsystems, namely, electricity, heating, and energy storage. Then, a basic scheduling model is constructed under the objective of maximizing operating revenue without considering uncertainty. Thirdly, the conditional value at risk (CVaR) method and the robust optimization theory are used to handle the uncertainty factors in objective functions and condition constraints, and the risk aversion scheduling model is proposed. Finally, industrial park group in northern China are chosen, for example, analysis results show (1) VEP could convert the abandoned clean energy, use HSK to store heating energy during the valley load period, and supply heating energy in the peak period to obtain the excess economic benefits. (2) Lower‐prediction accuracy will amplify the uncertainty risk, when the robust β∈[0.8,0.825]&(0.925,1], the increase of confidence level β will lead to larger increase in CVaR. Especially when β∈(0.925,1), decision makers are extremely disgusted with the risks brought by the uncertainty factors, and correspondingly, the output of clean energy becomes minimum. (3) When the capacity ratio of HSK, EB and the electricity price of peak, valley are lower than 3, the values of revenue, VaR and CVaR change faster, but the ratios are larger than 3, the values change slower, which indicates that the scale of HSK capacity needs to be properly controlled to optimize the use of clean energy, and price‐based demand response could improve the operation profit while controlling risk properly. In general, the proposed scheduling model can maximize the use of clean energy to obtain economic benefits while rationally controlling risks.