Optimal Bidding and Operation of a Power Plant with Solvent-BasedCarbon Capture under a CO2 Allowance Market： A Solution with aReinforcement Learning-Based Sarsa Temporal-Difference Algorithm

In this paper, a reinforcement learning （RL）-based Sarsa temporal-difference （TD） algorithm is applied tosearch for a unified bidding and operation strategy for a coal-fired power plant with monoethanolamine（MEA）-based post-combustion carbon capture under different carbon dioxide （CO2） allowance market con-ditions. The objective of the decision maker for the power plant is to maximize the discounted cumulativeprofit during the power plant lifetime. Two constraints are considered for the objective formulation. Firstly,the tradeoff between the energy-intensive carbon capture and the electricity generation should be made un-der presumed fixed fuel consumption. Secondly, the CO2 allowances purchased from the CO2 allowance mar-ket should be approximately equal to the quantity of COs emission from power generation. Three case stud-ies are demonstrated thereafter. In the first case, we show the convergence of the Sarsa TD algorithm andfind a deterministic optimal bidding and operation strategy. In the second case, compared with the inde-pendently designed operation and bidding strategies discussed in most of the relevant literature, the SarsaTD-based unified bidding and operation strategy with time-varying flexible market-oriented CO2 capturelevels is demonstrated to help the power plant decision maker gain a higher discounted cumulative profit.In the third case, a competitor operating another power plant identical to the preceding plant is consideredunder the same CO2 allowance market. The competitor also has carbon capture facilities but applies a differ-ent strategy to earn profits. The discounted cumulative profits of the two power plants are then compared,thus exhibiting the competitiveness of the power plant that is using the unified bidding and operation strat-egy explored by the Sarsa TD algorithm.

Development of Carbon Dioxide Capture Technologies in Coal-Fired Power Plants

With a particular reference to China Huaneng Group's practices in CO_2 capture, this article presents a brief ing on the current development of CO_2 capture technologies in coal-fired power plants both in China and abroad. Sooner or later, the integration of CO_2 capture and storage (CCS) facility with coal-fired power plant will be inevitably put on the agenda of developers.

Improving Prediction Accuracy of a Rate-Based Model of an MEA-BasedCarbon Capture Process for Large-Scale Commercial Deployment

Carbon capture and storage （CCS） technology will play a critical role in reducing anthropogenic carbondioxide （CO2） emission from fossil-fired power plants and other energy-intensive processes. However, theincrement of energy cost caused by equipping a carbon capture process is the main barrier to its commer-cial deployment. To reduce the capital and operating costs of carbon capture, great efforts have been madeto achieve optimal design and operation through process modeling, simulation, and optimization. Accuratemodels form an essential foundation for this purpose. This paper presents a study on developing a moreaccurate rate-based model in Aspen Plus for the monoethanolamine （MEA）-based carbon capture processby multistage model validations. The modeling framework for this process was established first. The steady-state process model was then developed and validated at three stages, which included a thermodynamicmodel, physical properties calculations, and a process model at the pilot plant scale, covering a wide rangeof pressures, temperatures, and CO2 loadings. The calculation correlations of liquid density and interfacialarea were updated by coding Fortran subroutines in Aspen Plus. The validation results show that the cor-relation combination for the thermodynamic model used in this study has higher accuracy than those ofthree other key publications and the model prediction of the process model has a good agreement with thepilot plant experimental data. A case study was carried out for carbon capture from a 250 MWe combinedcycle gas turbine （CCGT） power plant. Shorter packing height and lower specific duty were achieved usingthis accurate model.

Low-Carbon Dispatch of an Integrated Energy System Considering Confidence Intervals for Renewable Energy Generation

Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation,this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side.A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation,with the overarching goal of optimizing the system for low-carbon operation.To begin with,an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side carbon capture power plant within the context of integrated and adaptable operational paradigms.Drawing from this analysis,a model is devised to represent the adjustable resources on the charge-storage side,predicated on the principles of electro-thermal coupling within the energy system.Subsequently,the dissimilarities in the confidence intervals of renewable energy generation are considered,leading to the proposition of a flexible upper threshold for the confidence interval.Building on this,a low-carbon dispatch model is established for the integrated energy system,factoring in the margin allowed by the adjustable resources.In the final phase,a simulation is performed on a regional electric heating integrated energy system.This simulation seeks to assess the impact of source-load-storage coordination on the system’s low-carbon operation across various scenarios of reduction margin reserves.The findings underscore that the proactive scheduling model incorporating confidence interval considerations for reduction margin reserves effectively mitigates the uncertainties tied to renewable energy generation.Through harmonized orchestration of source,load,and storage elements,it expands the utilization scope for renewable energy,safeguards the economic efficiency of system operations under low-carbon emission conditions,and empirically validates the soundness and efficacy of the proposed approach.

Review on current advances,future challenges and consideration issues for post-combustion CO_2 capture using amine-based absorbents

Among the current technologies for post-combustion CO2 capture,amine-based chemical absorption appears to be the most technologically mature and commercially viable method.This review highlights the opportunities and challenges in post-combustion CO2 capture using amine-based chemical absorption technologies.In addition,this review provides current types and emerging trends for chemical solvents.The issues and performance of amine solvents are reviewed and addressed in terms of thermodynamics,kinetics,mass transfer,regeneration and solvent management.This review also looks at emerging and future trends in post-combustion CO2 capture using chemical solvents in the near to mid-term.

考虑超碳需求响应的综合能源系统低碳优化调度

西北地区新能源发展迅速,充分利用当地独有的光热资源优势,同时结合火电低碳化改造与新能源协同运行,有利于推动当地能源系统绿色低碳转型。为尽最大限度地提升系统的减碳能力,提出一种基于源荷协同降碳的超碳需求响应模型,将动态碳排放因子作为分时电价的惩罚因子,从而将源侧碳信号传递至荷侧,驱使用户侧进行低碳性状态转移。首先,在日前调度阶段,构建预调度-再调度两阶段调度运行机制,再调度根据预调度的系统状态信息进行超碳需求响应,来深度降低系统碳排量。其次,将光热电站引入综合能源系统,与风电场、碳捕集电厂协同运行,从而构建高比例新能源场景,来验证超碳需求响应在此场景下的减碳效益。最后,建立了基于超碳需求响应的预调度-再调度两阶段低碳调度模型。经算例仿真分析表明,所提源荷协同降碳的新思路能有效提高系统的减碳能力,深入挖掘系统的降碳空间,提升系统的经济效益。

考虑风电爬坡灵活调节的碳捕集电厂低碳经济调度

为实现“双碳”目标,风电等可再生能源的使用是减少碳排放的根本途径,而碳捕集电厂是降低碳排放的直接手段。但风电具有与生俱来的波动性,风电的骤升骤降会影响碳捕集电厂“电碳耦合”特性,从而对碳捕集效果带来不利影响。而储液罐通过增减自身溶液量可近似地存储释放能量,为解决上述问题提供了可能。该文首先搭建碳捕集电厂数学模型,分析储液罐通过增减溶液量带来的储放能量与碳捕集设备能耗之间的关联,研究储液罐的双向调节能力;然后,提出上爬坡碳超前补偿和下爬坡碳滞后补偿调度策略,双向调节储液罐使碳捕集电厂电碳解耦;接着,构建跟随风电爬坡进行调节的低碳经济调度模型;最后,对含碳捕集电厂、高碳电厂和风电场的电力系统进行仿真,证明所提方法的有效性。

含碳捕集电厂与氢能多元利用的综合能源系统低碳经济调度

随着中国“碳达峰·碳中和”战略的不断推进,综合能源系统的绿色低碳转型迫在眉睫。针对传统碳捕集电厂灵活性较差、风电并网难以消纳等问题,提出一种含碳捕集电厂与氢能多元利用的综合能源系统低碳经济调度模型。首先,引入储液罐对传统碳捕集电厂进行改造,提高电厂应对风电波动的运行灵活性;其次,构建含两段式电转气、氢燃料电池、储氢罐和掺氢热电联产在内的氢能多元利用结构,以充分挖掘氢能利用与碳捕集电厂的协同运行潜力。在此基础上,引入阶梯碳交易机制,建立以碳交易、碳封存、燃煤及购气成本之和最小为优化目标的低碳经济调度模型。算例结果表明,文中模型能够有效提高系统的风电消纳水平和能源利用效率,具有显著的低碳经济效益。此外,碳交易基准价格的合理设定能够引导系统提高碳捕集水平。

含整体煤气化燃料电池-碳捕集电厂的风火储系统分布鲁棒调度方法

整体煤气化燃料电池(integrated gasification fuel cell,IGFC)是与碳捕集技术高度适配的清洁、高效、稳定的绿色煤电技术,有望克服传统碳捕集技术在低浓度CO_(2)环境下产生的高成本、高能耗问题。该文构建含IGFC碳捕集电厂的风火储发电系统。研究IGFC碳捕集电厂的运行机理,对IGFC内部各环节建立数学模型,提出工况匹配时燃烧利用率和阴极空气利用率需要满足的运行条件,并针对该型碳捕集电厂的电碳特性进行分析。为计及风电出力的不确定性,构建风火储系统的两阶段分布鲁棒经济调度模型,引入k阶适应性理论,提出基于正交支撑子集策略的求解方法来获得鲁棒对等式。最后,在改进IEEE-30节点系统中进行算例分析,结果表明,该型碳捕集电厂可利用阳极碳富集的优势,实现系统低碳经济调度的目标,并验证所提优化方法能为可行解提供可解释性。

计及跨领域氢需求的电源低碳规划

大规模多领域的氢能应用会对电力负荷的规模、结构及分布等产生影响,进而对电源规划带来新的挑战。为此,文中提出一种考虑跨领域氢负荷的电源低碳规划模型。首先,计及工业、交通和供热领域的氢负荷,构建包含常规火电机组、碳捕集机组、新能源机组以及氢能系统的电-氢系统结构,并基于系统动力学理论对多领域的氢需求进行预测;其次,引入阶梯碳交易机制,在满足系统常规约束和氢能设备约束的前提下,考虑电、氢负荷需求,建立以投资、运行、碳交易以及弃电成本之和最小为优化目标的电源低碳规划模型;最后,以中国西北某地区的实际数据为例进行算例分析。结果表明,引入氢负荷和碳捕集电厂后的电源低碳规划模型能够优化电源结构、提高能源利用效率、降低系统碳排放量。

Low-carbon Operation of Combined Heat and Power Integrated Plants Based on Solar-assisted Carbon Capture

Accelerating the development of renewable energy and reducing CO_(2)emissions have become a general consensus and concerted action of all countries in the world. The electric power industry, especially thermal power industry, is the main source for fossil energy consumption and CO_(2)emissions. Since solvent-based post-combustion carbon capture technology would bring massive extra energy consumption, the application of solar-assisted carbon capture technology has attracted extensive attention. Due to the important role of coal-fired combined heat and power plants for serving residential and industrial heating districts, in this paper, the low-carbon operation benefits of combined heat and power integrated plants based on solar-assisted carbon capture(CHPIP-SACC) are fully evaluated in heat and power integrated energy system with a high proportion of wind power. Based on the selected integration scheme, a linear operation model of CHPIP-SACC is developed considering energy flow characteristics and thermal coupling interaction of its internal modules. From the perspective of system-level operation optimization, the day-ahead economic dispatch problem based on a mix-integer linear programming model is presented to evaluate the low-carbon benefits of CHPIP-SACC during annual operation simulation. The numerical simulations on a modified IEEE 39-bus system demonstrate the effectiveness of CHPIP-SACC for reducing CO_(2)emissions as well as increasing the downward flexibility. The impact of different solar field areas and unit prices of coal on the low-carbon operation benefits of CHPIP-SACC is studied in the section of sensitivity analysis.

A coal-fired power plant integrated with biomass co-firing and CO_(2) capture for zero carbon emission

A promising scheme for coal-fired power plants in which biomass co-firing and carbon dioxide capture technologies are adopted and the low-temperature waste heat from the CO_(2) capture process is recycled to heat the condensed water to achieve zero carbon emission is proposed in this paper.Based on a 660 MW supercritical coal-fired power plant,the thermal performance,emission performance,and economic performance of the proposed scheme are evaluated.In addition,a sensitivity analysis is conducted to show the effects of several key parameters on the performance of the proposed system.The results show that when the biomass mass mixing ratio is 15.40%and the CO_(2) capture rate is 90%,the CO_(2) emission of the coal-fired power plant can reach zero,indicating that the technical route proposed in this paper can indeed achieve zero carbon emission in coal-fired power plants.The net thermal efficiency decreases by 10.31%,due to the huge energy consumption of the CO_(2) capture unit.Besides,the cost of electricity(COE)and the cost of CO_(2) avoided(COA)of the proposed system are 80.37/MWhand41.63/tCO_(2),respectively.The sensitivity analysis demonstrates that with the energy consumption of the reboiler decreasing from 3.22 GJ/tCO_(2) to 2.40 GJ/tCO_(2),the efficiency penalty is reduced to 8.67%.This paper may provide reference for promoting the early realization of carbon neutrality in the power generation industry.

考虑氢能利用与碳捕集联合灵活运行的综合能源系统源荷低碳优化

为提高综合能源系统的低碳特性和新能源消纳能力,提出一种考虑氢能利用与碳捕集电厂联合灵活运行的综合能源系统源荷低碳优化调度策略。首先,引入溶液存储器和烟气旁路系统,建立碳捕集电厂综合灵活运行模型,针对氢能转换特性建立氢能利用模型,并提出碳捕集电厂-氢能利用的联合灵活运行模型;其次,构建计及价格型、激励型的综合需求响应模型;最后,以最优经济和低碳为目标,构建了综合能源系统低碳经济调度模型。仿真结果表明,考虑碳捕集电厂-氢能利用联合运行模型能有效降低系统碳排放量,实现综合能源系统经济、环保运行。

碳捕集技术应用对燃煤机组调峰能力的影响

【目的】分析碳捕集技术对燃煤电厂调峰能力的影响机制,量化碳捕集技术对燃煤电厂发电效率的影响。【方法】以国内某典型燃煤电厂为例,选取燃烧后碳捕集方案,通过ENSILON软件构建常规燃煤火电机组和碳捕集电厂的模拟模型,得出碳捕集电厂的运行区间,对比分析了碳捕集电厂与常规燃煤电厂的运行结果,对机组的调峰性能的变化展开了研究。【结果】与常规燃煤电厂相比,碳捕集电厂等效输出功率下降了1%~2%,净输出功率下降了20%~30%,全场净效率下降了8%~10%。【结论】碳捕集系统的加入会使电厂在效率降低的同时获得更大的下调峰深度和更快的调峰响应速度。

考虑灵活碳捕集电厂与抽水蓄能联合的广义经济调度策略

“双碳”背景下,灵活碳捕集电厂成为风光大规模并网后保供电和低碳化的重要过渡电源之一;然而,因其储液容量制约和风光反调峰特性造成系统在应对持续增大的负荷峰谷差时存在局限,容易造成风光流失且碳经济性不高。为此,该文引入具有双向快速功率调节能力的大容量储能-抽水蓄能,提出一种基于灵活碳捕集电厂与抽水蓄能联合的广义经济调度策略;广义经济调度综合电厂运行成本、电网净负荷经济效益、碳经济效益等多种元素。首先充分利用能耗时移特性和抽水蓄能的双倍调节能力,结合净负荷典型峰谷特征制定二者联合运行在电碳解耦下“峰互补、谷协同”机制,实现深度调峰下兼顾碳捕集和新能源消纳;进而构建电-碳市场下考虑灵活性约束等因素的广义经济成本最小为目标的调度模型,用模糊参数表征净负荷的不确定性,采用改进灰狼算法求解。仿真结果表明所提两者联合的广义经济调度策略相较于仅考虑灵活碳捕集电厂,综合成本降低25.33%,碳排放量减少18.71%,弃风弃光成本下降98.70%,验证了所提联合调度策略的优越性。

考虑绿证交易机制与碳捕集电厂深度调峰补偿的多主体联合调峰优化调度

为解决大规模风电不断并网引起的系统调峰负担增加问题,提出了一种考虑绿证交易机制与碳捕集电厂深度调峰补偿的碳-储-荷联合调峰双层优化方法。首先,分析了碳捕集电厂参与深度调峰成本损失,提出了深调服务补偿模型。其次,分析了绿证交易机制对碳-储-荷联合调峰的积极作用;上层以电价引导型需求响应、改善净负荷曲线平滑性程度最优为目标,旨在降低负荷峰谷差,提高风电消纳空间,缓解深度调峰机组压力;下层基于上层优化后的调峰容量,考虑绿证交易机制与碳捕集电厂深调补偿收益的碳-储联合深度调峰综合成本最优为目标,旨在发掘绿证交易机制与调峰辅助服务对深度调峰作用,发挥碳-储联合深度调峰的能力,优化系统经济性、风电消纳量、碳排放量。最后,在改进的IEEE 30节点系统进行仿真,结果验证了所提模型的有效性。

基于模型预测控制的源荷储低碳经济调度

为提高电力系统风电消纳的经济性以及实现低碳排放的目标,基于模型预测控制方法,构建了多时间尺度下含碳捕集电厂的源荷储低碳经济调度模型。源侧分析碳捕集电厂的运行机理及能量时移特性;荷侧根据需求响应时间尺度的差异性,调用不同响应速度的价格型、动态激励型需求响应资源分别参与日前-日内调度;储能快速调整充放电功率提高运行经济性,日前调度以运行成本和碳排放量最小为目标,通过协调调度源荷储资源优化系统各单元出力计划。日内调度在滚动优化平滑功率波动的基础上,以跟踪和修正日前调度计划为目标,实时应对风光和负荷的功率波动,通过算例验证所提方法可降低运行成本和碳排放量,实现对经济与低碳协同优化。

考虑综合需求响应及绿证-碳交易机制的能源系统低碳经济调度

“双碳”背景下,考虑电热需求响应并结合市场交易机制有助于综合能源系统低碳经济运行,由此,提出一种电热需求响应配合绿证-碳交易机制的综合能源系统模型并进行低碳经济调度。首先,通过加装储液罐的方式改造碳捕集电厂,建立以碳捕集电厂、电转气设备为主要能源耦合设备的综合能源系统数学模型;其次,为降低系统电热负荷峰谷差,进一步降低高碳排机组出力,引入电热需求响应机制;再次,建立阶梯式碳交易机制与绿证交易机制数学模型并将其引入系统低碳经济调度中;最后,以系统运行成本最小为目标函数建立低碳经济调度模型;算例表明,所提模型在系统总成本全面下降的同时实现了风电全额消纳,大幅提高了系统运行的低碳经济效益。

考虑不确定性风险的虚拟电厂优化调度模型研究

为使虚拟电厂(VPP)更好地满足我国新型电力系统的发展需要,提出了一种考虑不确定性风险的虚拟电厂优化调度模型。首先,在热电联合虚拟电厂基础上加装碳捕集和电转气设备,实现CO_(2)的循环利用,并通过储碳和储氢装置解耦碳循环和电解水过程;其次,对虚拟电厂内风光、负荷等不确定因素进行建模,基于场景分析法对日前场景进行随机优化,并利用条件风险价值理论(CVaR)衡量虚拟电厂的交易风险;最后,以虚拟电厂运行效益最大化为目标,引入阶梯型碳交易机制和需求响应,建立典型场景下虚拟电厂优化调度模型。算例分析表明,所提方法能有效降低虚拟电厂的碳排放,对VPP进行低碳经济调度具有指导意义。