ABSTRACTThe hydrogen industry is of great significance for global energy system transition and decarbonization; thus, the holistic planning of hydrogen infrastructure from a supply chain level is necessary. To this end, first, the framework and methods in the hydrogen infrastructure deployment research were investigated systematically. Second, a hydrogen supply chain design (HSCD) model and a hydrogen refueling station location (HRSL) model were constructed. In view of the limitations of the two models, this paper reformulated the HRSL model through alternating the objective function and constraint, then proposed an integrated planning model using the ‐constraint method, which relaxed the assumption condition and expanded the decision‐making boundary of the original model, realizing the reasonable equilibrium of multiple segments. Finally, a case study was conducted using the Yangtze River Delta region as an example, and the main findings were as follows: (1) To meet the hydrogen demand of 25494t/d, the Yangtze River Delta region needs to build 94 coal gasification hydrogen plants, storage facilities with capacity of 12747t, transmission modes with capacity of 2333t/d, and 150 hydrogen refueling stations. (2) Railways have more advantages in large capacity and long‐distance hydrogen transmission. (3) Road segments with higher traffic flow often have a higher capture proportion. (4) The investment cost accounts for the majority of hydrogen production plant construction, which is 43.80%.

新型电力系统是构建新型能源体系和实现"双碳"目标的基础支撑,电力市场、碳市场、绿证市场协同运行是实现新型电力系统市场化运行的必然路径.为此,提出了电-碳-绿证市场协同运行的区块链关键技术体系.首先,提炼了电-碳-绿证市场协同运行的体系架构,从产品、主体、政策 3 个角度分析了市场间的协同运作情况.其次,构建了基于区块链技术的市场运行体系:建立了一个统一的积分认证机制来衔接电-碳-绿证市场之间的交易标的物;结合区块链技术的智能合约确保交易的透明和可靠性;将共识机制结合积分认证应用于协同市场,确保参与方之间的一致性以及协同性;通过跟踪电力的来源去向,构建了电-碳-绿证溯源模型来确保电力数据的准确性.最后,提出建设电-碳-绿证体系建议,聚焦于政策、技术、试点三方面为新型电力系统市场化运行提供辅助决策.

以宏观系统角度研究能源大数据生态系统发展的影响因素,分析能源大数据生态系统的内涵和架构,建立了能源大数据生态系统演化发展的系统动力学模型,并运用Vensim软件进行模拟仿真验证了模型的有效性,分析了影响能源大数据生态系统演化发展的关键因素.研究结果表明,影响能源大数据生态系统发展的最关键因素为消费趋势影响因子,其次为技术研发投入因子和技术升级需求,最后为财政投入因子、环境影响因子和法律法规政策投入因子.

随着全球能源危机不断加剧,可再生能源在电力系统中的占比不断增加.需求侧响应可以通过引入柔性可控负荷来增强新型电力系统的调节能力.基于此,研究了需求侧响应中的柔性温控负荷控制问题,基于多智能体一致性算法提出了柔性温控负荷分布式分层控制策略.该策略在上层优化层考虑温控负荷聚合商的最优功率分配,在下层协调层考虑温控负荷的分布式协调机制.面向用户用电行为的不确定性问题,从理论上证明了上层分布式优化算法和下层协调控制算法的收敛性,并在MATLAB环境中进行了数值仿真实验,以验证所提策略的有效性.相较于传统集中式控制方法,所提出的分布式分层控制策略有利于减轻响应事件中管理单元的通信负担并保护电力用户隐私.

政产学研协同创新发展模式可推动中国综合能源系统相关技术发展.为研究政产学研模式在综合能源关键技术研发及应用中的效果,构建了由政府、综合能源相关企业和学研机构三方组成的演化博弈模型,对三方构成的系统进行了演化稳定分析,并运用系统动力学模型分析了各主体初始参与意愿、违约惩罚系数以及政府补贴等因素变化对系统演化结果的影响.研究结果表明:初始参与意愿、违约惩罚系数等都将影响综合能源相关企业和学研机构的策略选择结果,且政府补贴能对综合能源相关综合能源相关企业和学研机构的合作策略选择有促进效用.此外,相较于固定违约金机制,设置与各主体初始意愿相关联的动态违约金机制能促进综合能源行业综合能源产学研形成稳定的合作关系.

研究了虚拟电厂运营风险综合评价体系,为虚拟电厂建设运营提供支撑与指导.首先以运行风险、经济风险、安全风险和管理风险为一级指标构建了虚拟电厂风险综合评价指标库,为虚拟电厂安全可靠运行评价提供了支撑.其次提出了虚拟电厂风险综合评价模型,选用有序加权平均(ordered weighted average,OWA)—改进的层次分析法(analytic hierarchy process,AHP)对指标进行赋权,进而通过基于贝叶斯反馈修正的云模型评价方法得出各级指标的评价分数,用以评价虚拟电厂的风险程度,为虚拟电厂运行改进与优化提供判断依据.最后选取某虚拟电厂进行算例分析验证了所提基于贝叶斯改进云模型的虚拟电厂风险评价指标体系的有效性及优越性.

为保障可再生能源可持续发展,我国先后推行了绿色证书(以下简称绿证)和可再生能源配额制(Renewable Portfolio Standard,RPS)机制.为明确相应政策组合对责任主体交易行为的影响效用,首先,分析了"绿证交易+配额制考核"下电力市场与绿证市场耦合机理;其次,基于反身性视角构建了消费侧责任主体参与电力市场与绿证市场交易的序贯优化模型;最后,通过算例模拟了责任主体在考核期内的交易决策过程.算例结果表明,在RPS下,相较固定价格模式,绿证的市场化交易可在不显著增加责任主体成本的前提下有效提升可再生能源电力消纳量和绿证市场交易额.另外,RPS权重和近期利益偏好对责任主体的月度和年度交易策略制定有明显影响,但并不总为正相关,需要进一步考虑可再生能源不确定性及不同电力商品价差等因素的影响.

The configuration of energy storage with reasonable capacity in the photovoltaic microgrid is a powerful way to promote the local consumption of distributed photovoltaic and improve the efficiency of photovoltaic system. DSM can effectively reduce grid investment and become an important regulation means for efficient operation of power system. The main innovation of this research is to consider the utilization of demand side resources in microgrid planning, which is rarely deployed in previous studies. Firstly, the models of renewable energy output characteristics and energy storage SOC characteristics are established, and the demand response mechanism is analysed; Secondly, taking the minimization of the comprehensive cost of the system as the objective function and the energy balance, equipment characteristics as constraints, a collaborative planning model of PV-Battery storage system for microgrid considering demand response is constructed. Finally, the rationality and effectiveness of the proposed optimization model are verified by the actual data of a microgrid in Fuzhou.

In order to cope with the objective contradiction of the worsening environmental problems and the rigid demand for energy due to the rapid economic development, it is of great significance to explore the technology and management mode of microgrid which is self-used and locally consumed with renewable energy. In this study, on the basis of clarifying the construction goal of microgrid, the energy management system of microgrid is designed, the control mode consistent with the characteristics of renewable energy is selected, the business scope of microgrid is expanded according to the interactive needs of different users, and the intelligent interactive operation of microgrid is realized, which can make better use of renewable energy to meet the rising demand for energy while protecting the environment.

提出一种计及碳排放约束及源荷不确定性的电力系统双层协调优化配置模型.该模型上层以系统规划成本最小化为优化目标,对各类电源机组及储能设备配置容量进行优化.下层运行优化模型以系统碳排放量最小化为优化目标,采用模糊随机机会约束法对源、荷双侧不确定性因素进行处理,优化电源、储能、需求侧资源的出力.结果表明,综合考虑源荷储灵活性资源的电力系统协调规划可有效降低系统碳排放量,可兼顾电力系统规划的经济性与环保性.

建设源荷协调、灵活互动的综合能源系统是构建新型电力系统的有效路径.在综合能源系统下,通过价格、补贴等激励手段合理调节用户侧需求响应机制可以促进综合能源系统的经济高效运行.为制定合理的需求响应激励机制,首先充分考虑源侧可再生能源出力和负荷侧多类能源需求的不确定性,提出随机场景生成策略;然后提出计及用户需求响应的综合能源系统博弈优化框架,分别以园区综合能源系统运营商和综合能源用户效益最大化为目标,建立双主体博弈优化调度模型,并提出快速高效的求解算法;最后,基于某实际园区综合能源系统开展多场景算例仿真分析,制定合理有效的需求响应价格激励方案.调度结果表明,所提出方案可以有效提升综合能源系统运行商和用户的效益.

构建面向智能园区的多能源微网是实现不同类型物理能源系统耦合,提高可再生能源终端能源消费占比的重要途经.通过制定恰当的多能源微网规划,对于保证多能源微网项目投资收益以及推动多能源微网有序发展具有重要意义.鉴于此,该文以园区级多能源微网为研究对象,在利用隐马尔可夫构建典型场景集以压缩系统历史数据的基础上,构建多能源微网配置多目标优化模型架构,并利用某园区实际负荷数据和分布情况,对比分析不同情景下2种不同配置方案的结果和优劣势,定量阐述了多能源微网在降低系统排放强度和系统投资成本方面的优势.

With the development of the Energy Internet and the Internet of Things, diversified social production activities are making the interactions between energy, business, and information flow among physical, social, and information systems increasingly complex. As the carrier of information and the hub between physical and social systems, the effective management of energy big data has attracted the attention of scholars. This work indicates that China's energy companies have carried out a series of activities that are centered on energy big data collection, as well as development and exchange, and that the energy big data ecosystem has begun to take shape. However, the research on and the application of energy big data are mainly limited to micro-level fields, and the development of energy big data in China remains disordered because the corresponding macro-level instructive governance frameworks are lacking. In this work, to facilitate the sustainable development of the energy big data ecosystem and to solve existing problems, such as the difficult-to-determine governance boundaries and the difficult-to-coordinate interests, and to analyze the structure and mechanism of the energy big data ecosystem, data curation is introduced into energy big data governance, and a paradigm is constructed for sustainable energy big data curation that encompasses its full life cycle, including the planning, integration, application, and maintenance stages. Key paradigmatic issues are analyzed in-depth, including data rights, fusion, security, and transactions.

需求响应在协助维持电力系统稳定性、提高可再生能源消纳能力、降低电力系统峰谷差、延缓电网建设投资等方面发挥重要的作用,基于实时电价的实时需求响应更是把需求响应从实时性、最优性上推到了一个新的高度.从分析准实时电价存在问题出发,提出了实时电价的基本特征,从而提出一种新的需求响应形式:实时需求响应.具体算法上,以单设备潜力聚合法负荷调节能力模型为基础,建立完整的实时需求响应数学模型,明确其求解和效益评估过程,通过用例分析,不仅验证了实时需求响应模型的有效性,还验证了该模型适合实时电价的实时快速计算.

In order to meet the challenge of global low-carbon development, the concept of integrated energy system (IES) has been proposed and demonstrated, and its low-carbon operation mode is the research hotspot at present. In this paper, a multi-objective optimal scheduling model considering the participation of park-level IES (PIES) in the carbon market is proposed, which takes into account the multiple uncertainties on the renewable energy and load. Firstly, for the PIES operator (PIESO) participate in the carbon market, this paper introduces the ladder type carbon trading mechanism. Then, for the uncertainties of the renewable energy and load, this paper carries out uncertainty modeling from the perspective of PIESO risk aversion and risk preference based on IGDT method. Finally, a multi-objective optimal scheduling model including economic and environmental objective is established. The actual PIES is selected for case study, and the results show that the operating profit of PIESO under the risk aversion strategy decreases by 5.91%, the operating profit of PIESO under the risk seeking strategy increases by 6.12%. Aiming at the impact of ladder-type carbon trading on system operation profits and carbon emissions, three scenarios were set, including whether to introduce a ladder-type carbon trading mechanism, changes in the initial price and the tradable carbon emission ratio. The results show that compared with the traditional carbon trading mechanism, the introduction of the ladder-type carbon trading mechanism reduces carbon emissions by 2.73%, and the setting of reasonable ladder-type carbon trading price and tradable carbon emission ratio can significantly reduce the carbon emissions, improve operating profit of PIES.

随着能源革命不断推进,综合能源服务应运而生.如何把握市场规律,识别关键竞争者,采取正确的发展策略成为电网企业在转型综合能源服务商进程中亟须解决的关键问题.本文以电网企业作为研究对象,选取发电企业为博弈对象,通过建立基于演化视角的竞合博弈模型,得出电网企业与发电企业的稳定演化策略为(合作,合作)和(竞争,竞争),且合作效益增益、合作收益、合作成本以及违约金数额与双方选择合作策略的概率成正比,因终止合作关系而产生的时间及相关费用与双方选择竞争策略的概率成反比.并通过仿真分析验证模型及策略选择的正确性.最后,从综合能源服务的合作模式选取、交流平台搭建、技术创新保护制度建立等方面提出电网企业参与综合能源市场发展的相关建议.

在"2030碳达峰、2060碳中和"双碳目标的政策背景下,社会进一步推动可再生能源电力消纳责任权重的实行.作为可以有效支撑清洁低碳能源体系的区域综合系统,需要在考虑可再生能源电力消纳责任权重情况下保证系统经济低碳运行.结合绿色证书交易机制,提出了一种计及可再生能源电力消纳责任权重的区域综合能源系统运行优化模型.以系统总收益最大化为目标,综合考虑可再生能源消纳责任权重、绿色证书交易、碳排放等因素,构建了包含电、热、冷负荷的区域综合能源系统运行优化模型.通过设置不同场景进行算例分析,结果表明考虑了可再生能源电力消纳责任权重和绿证交易的区域综合能源系统优化模型可有效提高系统总收益且兼顾了环境效益,为系统的经济低碳运行提供了有效借鉴.

需求响应作为电力系统的重要调节手段,可显著提升系统灵活性和经济性.利用价格弹性构建了包含价格与激励措施的需求响应模型,并在此基础上考虑需求响应的不确定性,以综合能源系统经济性和环保性为优化目标,构建了综合能源系统多目标优化调度模型.利用E约束法将多目标优化模型转化为单目标优化模型,得到Pareto最优解集,运用模糊决策法从中选取最优方案.基于实际案例进行测算,结果表明价格型与激励型需求响应手段的结合能够实现削峰填谷,有效降低系统的运行成本和碳排放量.

Multi-energy load forecast is different from traditional electric energy load forecast to a certain extent, and it can not be regarded as a simple independent forecast of electricity, heat and gas loads. On the basis of fully considering the multi-energy coupling characteristics of the three loads at different user sides due to different process requirements, this paper proposes a weighted average combined forecasting to obtain the three loads per unit land of the city. Then, based on the development maturity of urban land, the load forecast value is revised to obtain the improved forecast value of electricity, heat and gas load in X city in the next five years.

随着电力市场和碳市场的发展,将需求响应和碳交易机制引入综合能源系统运行调度中,有助于引导用户和系统运营商优化用电和调度计划.通过分时电价和需求响应激励补贴等综合型激励措施引导用户参与需求响应,并基于IGDT(information gap decision theory)理论构建了考虑阶梯式碳交易机制以及需求响应的综合能源系统双层随机优化调度模型,并通过KKT条件和大M法将双层模型转化为单层模型进行求解.结果表明,引入需求响应和阶梯式碳交易机制之后能够实现综合能源系统的低碳环保运行.