As the first industry to participate in the national carbon market,thermal power companies need to fulfill their compliance obligations according to market rules.The power supply carbon emission intensity and power supply of these companies jointly influence their compliance requirements in the carbon market.With the development of the new type power systems,coal-fired units will take on more system regulation responsibilities,and their power supply carbon emission intensity will be increasingly affected by their operational conditions.In light of the current situation of thermal power companies,this paper proposes a low carbon economic operation assessment and decision making for coal-fired units based on measured-data-driven causal inference method.By depicting the causal graph among variables using prior knowledge,a generalized propensity score matching model is constructed to assess the impact functions of power supply on carbon emission intensity and coal consumption of power supply.This assists in decision making for low carbon operation of coal-fired units.The case study results verify the feasibility and effectiveness of the proposed method,providing an efficient and convenient approach for the assessment and decision making of low carbon economic operation of coal-fired units.

The national carbon market is one of the core policy tools to achieve the carbon peaking and carbon neutrality goals. In 2021, the first performance period of the power generation industry in the national carbon market was officially launched, and the thermal power industry is the only emission control industry in the national carbon market. Under the background of the current dual carbon revolution, emission control requirements are gradually increased, and the impact on the economic efficiency of thermal power plants is further amplified by whether low-carbon operation can be realized. However, due to the impact of technology and other objective factors, the carbon emission intensity of thermal power units is affected by the unit characteristics, fuel, load rate and other factors, and there are many factors affecting the carbon emission level of thermal power plants. Therefore, how to achieve reasonable control of thermal power plant carbon emissions under given conditions becomes an important factor affecting the economics of thermal power plants. Since various operational control quantities of thermal power plants, such as power supply and heat supply, are closely related to carbon emissions, it is effective to construct a cause-effect diagram to fit the relationship between operational control quantities and carbon emissions based on data-driven cause-effect inference, and to perform sensitivity analysis on carbon emission levels to achieve reasonable control of carbon emissions for low-carbon operation of thermal power plants. In this paper, we present a data-driven causal inference method for low-carbon operation of thermal power plants. The causal diagram is constructed through a priori knowledge, and the relationship equation between the intervening variables and the outcome variables is fitted based on the matching model, and the sensitivity analysis of the unit carbon emissions is carried out to realize the auxiliary decision-making for low-carbon operation of thermal power plants.

随着《碳排放权交易管理办法》的正式实施,加速了碳排放权交易的进度,在此背景下考虑区域综合能源系统(re-gional integrated energy system,RIES)接入配网后需求响应、可再生资源消纳和碳排放交易成本的影响,提出一种新的配电网规划方法.首先,对区域综合能源系统结构进行概述,介绍典型区域综合能源系统的构成及特点;其次,将碳交易成本、弃风弃光成本和需求响应引入配电网扩展模型当中,综合考虑系统的碳排放、弃风弃光和需求侧响应对区域综合能源系统的影响,促进系统整体的优化运行.在上述基础上构建考虑区域综合能源系统优化的配网扩展优化双层模型,采用改进粒子群算法(improved particle swarm optimization,IPSO)和预测校正内点法(prediction correction interior point method,PCIP)求解规划层和运行层模型.最后,运用算例系统对构建的模型和方法进行验证.结果表明:配电网扩展规划时,充分考虑区域综合能源系统优化,能够提升可再生能源的消纳,降低整体的扩展规划成本.

针对储能光热电站运行特性建立了基于利润最大化的机组启停优化模型.该模型考虑了吸热系统和发电岛3种开机模式和一个停机模式的能量需求,通过优化启停时间,吸热系统、储能系统和发电岛之间的热能交换以及发电和储热水平来最大化机组运行利润.与传统模型相比,本模型考虑了启停过程中的启停能量和热功率约束、太阳能辐射资源以及储能套利机会.给出了一个算例模拟了电站以15 min为调度区间的168 h启停和运行,模型提供的启停和运行决策与资源可用性和电价模式高度吻合,能较好地为机组运行提供决策参考.

In 2018, Qinghai Province was approved to build the National Clean Energy Demonstration Province and proposed the "Qinghai Province National Clean Energy Demonstration Province Work Plan (2018-2020)" in the same year. The work plan takes the greennesss, high efficiency and safety as the overall goal, and promotes the revolution in energy production and consumption, so as to make a contribution to the clean transition of China’s energy and the construction of a modern energy system. Under this background, a study is made on the Qinghai energy demand forecasting and clean development strategy under the background of clean energy demonstration province construction. Firstly, the paper analyzes the current status and challenges of clean energy development in Qinghai Province. Then, a DMDE-BPNN hybrid prediction model is established by optimizing the BP neural network prediction model with the double mutation differential evolution algorithm. By taking Qinghai Province as an example, the annual energy demand in typical years is forecasted, and some measures are proposed for the development of clean energy in Qinghai Province.

为应对中国严峻的弃风问题,讨论风电参与电采暖的运行优化策略,以协调满足电负荷和热负荷.首先,将风电场、蓄热式电锅炉和燃气轮机整合为电热互联系统,并考虑激励型需求响应和价格型需求响应对系统运行的优化效应.然后,选择最大化运行收益和和最小化运行风险作为目标函数,考虑风险不确定性的影响,构造电热互联系统(Electro-thermal interconnect system,EST)最优电热耦合调度模型;最后,通过对所提模型进行算例分析,结果表明:1)若决策者能够适当承受一定风险,利用风电满足终端用于热负荷,会极大提升风电并网空间,带来显著的增量经济效益;2)价格型需求响应能够平缓电热负荷需求曲线,促进风电并网的同时降低系统运行风险;3)激励型需求响应能为风电提供更多的备用服务,实现集中式和分散式协同互补供暖,取得最佳的系统运行结果.因此,所提电热互联系统调度运行模型有利于促进风电发电并网,能够为电热互联系统的最优运行提供决策支撑.

大规模新能源的并网,导致电力系统的波动性增加,产生较为严重的调峰和爬坡问题。为了研究面向灵活资源的配置如何在超短期优化调度中进行灵活资源的使用以满足系统调峰、爬坡的要求,首先提出超短期时段内的灵活资源运行模型和电力系统优化调度模型;其次,为考虑电力系统灵活性不足时需增加灵活资源的数量,提出灵活资源配置模型,并给出面向灵活资源配置的超短期优化调度流程;最后通过某省实际算例,对灵活资源两种情形的超短期优化调度进行仿真分析,证明了所提方法的有效性。

随着青海新能源装机规模的增大,黄河上游水电日内运行方式较常态运行发生了变化.文章选取黄河上游青海境内已建大型水电站为例,根据水电实际运行资料对系统有无新能源情况下水电日内运行方式进行了对比分析,研究了配合新能源运行后对水电站日调节库容需求的变化.研究成果可为高比例新能源并网情况下水电调度运行提供参考,同时也为承担水风光互补运行任务的水电站设计提供一定的指导.

青海省太阳能资源丰富,按全国风能资源分区划分标准属于Ⅳ类资源区.近年来,青海省光伏、风电发展迅速.截至2016年年底,青海光伏并网发电装机容量为6814MW,占全网电源总装机容量的29.7％.已开发的光伏装机规模中,94％分布在海西州和海南州;风电装机容量为685MW,其中,海西州已建成并网风电项目666.5MW,占全省风电总装机容量的97％.根据青海省"十三五"能源发展规划,至2020年年底,青海光伏装机容量将达到24000MW,风电装机容量将达到7110MW.风电、光伏发电出力存在间歇性、波动性和随机性等特点,随着青海省风电、光伏并网规模的增大,其给电力系统电网建设、电源结构配置和运行调度模式等带来新的挑战,应对风、光互补特性进行研究,以使青海电网更好地消纳新能源以及电力系统可调节电源更好地配合风、光稳定运行.

随着电网规模的不断增大,短路电流超标已成为电力系统安全运行所面临的重大问题.文中提出了一种限制电网短路电流的综合等效灵敏度法,将限制短路电流问题分为限制短路电流和电气安全校核2个子问题.在限制短路电流子问题中,统一了线路开断、发电机停运、线路出串、线路装设串联阻抗、更换高阻抗变压器、母线分裂等限流措施的模拟,进而利用支路阻抗追加法计算上述措施实施后的节点阻抗参数和元件开断的短路电流综合等效灵敏度.在电气安全校核子问题中,对电网进行潮流和稳定校核,实现短路电流限制.青海电网的实际算例验证了文中方法的有效性,研究成果可为青海电网限制短路电流提供借鉴.

青海省新能源发展迅速,配套纯可再生能源的特高压直流外送通道建成后,青海电网将发展成为含超高比例可再生能源的特高压交直流送端系统,本项目针对该系统可能出现的电网调峰、高比例电力电子化器件带来的电力系统安全稳定问题等开展研究分析,并提出解决方案,保障了青海纯可再生能源特高压直流平稳外送.

串补装置首次应用于750 kV电压等级,为准确了解影响串补平台电场分布的关键因数,基于沙洲-鱼卡、柴达木-海西-日月山750 kV串补装置的初步设计图纸,建立了单相串补的模型,借助有限元计算工具,研究了影响离地面1.5m处电场强度的主要因素:地面围栏高度、管型母线高度.结果表明:地面围栏越高,电场强度的15 kV/m场强的边界范围越小;管型母线越高,电场强度的15 kV/m场强的边界范围越小.

介绍了高负荷密度工业园区电网的特征及其短路电流超标这一突出问题,以青海省西宁甘河工业园区供电电网为例,分析了目前控制短路电流的各种措施对于此类电网的适应性,得出了以优化电网结构(采取高低压电磁解环)为主,调整电网设备(主变加装中型点小电抗)为辅的解决策略,为今后同类型园区电网规划提供指导.

串补装置首次应用于750 kV电压等级,其设备庞大,结构复杂,对电站内电磁环境影响较大.为了使750 kV串补工程的电磁环境满足标准要求,研究基于沙洲—鱼卡、柴达木—海西—日月山750 kV串补装置的初步设计图纸,建立了单相串补、三相串补和2套串补的模型,结合西北二通道串补工程可能的环境条件,分别对海拔3000m和3500m下的模型进行详细的有限元计算,计算结果表明,初步设计下串补装置的电场强度满足标准要求.

光伏、水电出力都与天气条件有关,水电能够快速调节并具有可储能的库容,可以与光伏互补运行,弥补光伏的间歇性,目前研究2种电源在不同时间维度上的互补特性的论文较少.该文提出了水电与光伏的互补特性分析方法,建立了基于弃光率以及火电机组负荷率的水光互补评价指标,采用光伏时序出力模拟以及包含水电的电力系统运行模拟实现对水光互补评价指标的计算.以青海省2020年电力系统规划数据为例,研究了青海省2020年水光互补的特性,根据计算结果对青海省未来水光互补运行提出了建议.