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学者姓名：江岳文
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Abstract ：
Due to the large number and strong randomness of EVs (electric vehicles), their participation in the peak adjustment demand response of the grid through V2G aggregators is highly uncertain, which not only affects the operation quality of the grid, but also cannot guarantee the economic benefits of aggregators and users. Therefore, an effective response mechanism is urgently needed to guide EV to reasonably participate in the grid service. In consideration of the profitability requirements and development prospects for V2G aggregation businesses, we propose a multi-temporal optimization scheduling strategy that takes into account the reliability of EV peak demand response.Firstly, the day-ahead pre-scheduling of EV demand response is carried out with the goal of optimal integrity-capacity comprehensive index of EV cluster. Secondly, in order to cope with the adverse impact of intra-day EV default uncertainty on peak demand response, the V2G aggregator uses the intra-day default emergency mechanism to conduct emergency response invitation for the whole range of EVs, and then optimizes EV scheduling with the dynamic evaluation model with the optimal response reliability index. Then, the benefits related to peak regulation demand response are evaluated by V2G aggregators and on EVs sides, including the demand response benefits and default costs of the power grid and aggregators, as well as aggregators and EVs. In addition, the surplus of the default capital pool of V2G aggregators is issued to EV with good credit in the form of credit incentives to encourage EV to keep its promise. Finally, a simulation example is used to verify that the proposed optimal scheduling strategy for peak demand response can effectively improve the reliability of EV cluster response and increase the effectiveness of economic benefits for EV and V2G aggregators. © 2025 Science Press. All rights reserved.
Keyword ：
Risk assessment Risk assessment Vehicle-to-grid Vehicle-to-grid
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| GB/T 7714 | Huang, Zhenyao , Cheng, Nuo , Jiang, Yuewen . Multi-time-scale Scheduling Strategy of V2G Aggregators Considering EV Peak Regulating Demand Response Reliability [J]. | High Voltage Engineering , 2025 , 51 (1) : 401-411 . |
| MLA | Huang, Zhenyao 等. "Multi-time-scale Scheduling Strategy of V2G Aggregators Considering EV Peak Regulating Demand Response Reliability" . | High Voltage Engineering 51 . 1 (2025) : 401-411 . |
| APA | Huang, Zhenyao , Cheng, Nuo , Jiang, Yuewen . Multi-time-scale Scheduling Strategy of V2G Aggregators Considering EV Peak Regulating Demand Response Reliability . | High Voltage Engineering , 2025 , 51 (1) , 401-411 . |
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An operating model for nuclear-hydrogen integration (NHI) is developed based on an in-depth analysis of the future trajectories of the electricity and hydrogen markets. A planning model is proposed to determine the optimal capacity allocation ratio between nuclear power and hydrogen storage systems, while also optimizing the on-grid output of NHI within a reasonable range of system load factors. The results indicate that the optimal capacity ratio of nuclear power to electrolyzers and fuel cells is approximately 1: 0.41: 0.36. Flexibility analysis shows that NHI adjusts output from 51.3 % to 128 % of the rated power for nuclear power, enabling it to adapt effectively to load variations. Economically, NHI achieves a total revenue of 18.37 billion CNY, which is approximately 56.0 % lower than that of nuclear-pumped storage integration (NPSI). These findings suggest in regions with favorable geographical conditions for constructing pumped storage power plants, NPSI may represent a more economically viable operating strategy.
Keyword ：
Business model Business model Comprehensive utilization of nuclear energy Comprehensive utilization of nuclear energy Electricity-hydrogen coupling Electricity-hydrogen coupling Hydrogen storage capacity planning Hydrogen storage capacity planning Nuclear-hydrogen integration Nuclear-hydrogen integration
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| GB/T 7714 | Jiang, Yuewen , Ou, Shanshan . Hydrogen storage capacity planning of nuclear-hydrogen integration under coupling of electricity and hydrogen [J]. | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY , 2025 , 126 : 238-250 . |
| MLA | Jiang, Yuewen 等. "Hydrogen storage capacity planning of nuclear-hydrogen integration under coupling of electricity and hydrogen" . | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 126 (2025) : 238-250 . |
| APA | Jiang, Yuewen , Ou, Shanshan . Hydrogen storage capacity planning of nuclear-hydrogen integration under coupling of electricity and hydrogen . | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY , 2025 , 126 , 238-250 . |
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由于电动汽车(electric vehicle,EV)存在数量多、随机性强等特点,其通过车网互动(vehicle-to-grid,V2G)聚合商参与电网调峰需求响应具有很强的不确定性,不仅影响电网运行质量,而且无法保证聚合商与用户的经济效益,因此亟需有效的响应机制引导EV合理参与电网服务.针对该问题,计及EV与V2G聚合商的盈利需求与发展前景,提出考虑EV调峰需求响应可靠性的V2G聚合商多时间尺度优化调度策略.首先,以EV集群诚信-容量综合指标最优对EV进行日前的需求响应预调度.其次,为应对EV日内违约不确定性,V2G聚合商采用日内违约应急机制对全域内EV进行应急邀约,以响应综合指标最优的动态评估模型对EV进行优化调度.接着,V2G聚合商和EV进行调峰需求响应的相关效益评估,包括电网与聚合商及聚合商与EV间的需求响应收益与违约成本,并对信用度好的EV进行诚信奖励,以激励EV守约.最后,通过算例仿真验证了所提调峰需求响应优化调度策略可有效提高EV集群响应的可靠性,增加EV和V2G聚合商的经济收益.
Keyword ：
V2G聚合商 V2G聚合商 响应可靠执行概率 响应可靠执行概率 电动汽车 电动汽车 调峰需求响应 调峰需求响应 违约不确定性 违约不确定性 违约应急机制 违约应急机制
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| GB/T 7714 | 黄珍瑶 , 程诺 , 江岳文 . 考虑EV调峰需求响应可靠性的V2G聚合商多时间尺度调度策略 [J]. | 高电压技术 , 2025 , 51 (1) : 401-411 . |
| MLA | 黄珍瑶 等. "考虑EV调峰需求响应可靠性的V2G聚合商多时间尺度调度策略" . | 高电压技术 51 . 1 (2025) : 401-411 . |
| APA | 黄珍瑶 , 程诺 , 江岳文 . 考虑EV调峰需求响应可靠性的V2G聚合商多时间尺度调度策略 . | 高电压技术 , 2025 , 51 (1) , 401-411 . |
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为了解决传统无功优化模型所得最优决策难以适应实际调度中风电功率超短期预测偏差引起的电压越限问题,提出一种考虑海上风电超短期预测偏差的无功调整降损策略.为了评估有功出力预测偏差下有电压越限风险的节点和电压波动范围,基于高斯混合模型和线性化潮流方程获取电压偏差概率密度函数.基于此,结合有功出力预测偏差对电压的影响机理,建立基于某一风险节点规模影响因子下风险节点最大电压偏差缩减相应风电机组无功优化范围的无功调整降损优化模型,提高无功调整降损策略的安全经济性.以某一实际91节点海上风电场为算例进行仿真分析,验证所提方法能够最大限度地避免高额的电压越限惩罚费用,同时获得较高的无功调整降损收益.
Keyword ：
无功优化 无功优化 有功降损 有功降损 海上风电 海上风电 电压偏差 电压偏差 超短期预测偏差 超短期预测偏差
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| GB/T 7714 | 郑弘奇 , 江岳文 , 邹舒瑾 et al. 考虑抑制海上风电超短期预测偏差引发电压越限的无功调整降损优化决策 [J]. | 电力自动化设备 , 2025 , 45 (5) : 84-92,109 . |
| MLA | 郑弘奇 et al. "考虑抑制海上风电超短期预测偏差引发电压越限的无功调整降损优化决策" . | 电力自动化设备 45 . 5 (2025) : 84-92,109 . |
| APA | 郑弘奇 , 江岳文 , 邹舒瑾 , 李哲 . 考虑抑制海上风电超短期预测偏差引发电压越限的无功调整降损优化决策 . | 电力自动化设备 , 2025 , 45 (5) , 84-92,109 . |
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In order to solve the problem that the optimal decision obtained by the traditional reactive power optimization model is difficult to adapt to the voltage over-limit caused by the ultra-short-term forecast deviation of wind power in the actual scheduling, a reactive power adjustment strategy for loss reduction considering the ultra-short-term forecast deviation of offshore wind power is proposed. The probability density function of voltage deviation is obtained based on Gaussian mixture model and linearized power flow equa-tion in order to evaluate the nodes with the risk of voltage over-limit and the voltage fluctuation ränge under the forecast deviation of active power Output. Based on this, combined with the influence mechanism of the forecast deviation of active power Output on voltage, an optimization model of reactive power adjustment for loss reduction is established to reduce the reactive power optimization ränge of the corresponding wind turbines based on the maximum voltage deviation of the risk node under the influence factor of a certain risk node, so as to improve the safety and economy of the reactive power adjustment strategy for loss reduction. A real 91-bus offshore wind farm is taken as a Simulation example to verify that the proposed method can avoid high voltage over-limit penalty costs to the maximum extent, and obtain high loss reduction benefits by reactive power adjustment. © 2025 Electric Power Automation Equipment Press. All rights reserved.
Keyword ：
Gaussian distribution Gaussian distribution
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| GB/T 7714 | Zheng, Hongqi , Jiang, Yuewen , Zou, Shujin et al. Optimization decision of reactive power adjustment for loss reduction considering suppression of voltage over-limit caused by ultra-short-term forecast deviation of offshore wind power [J]. | Electric Power Automation Equipment , 2025 , 45 (5) : 84-92 and 109 . |
| MLA | Zheng, Hongqi et al. "Optimization decision of reactive power adjustment for loss reduction considering suppression of voltage over-limit caused by ultra-short-term forecast deviation of offshore wind power" . | Electric Power Automation Equipment 45 . 5 (2025) : 84-92 and 109 . |
| APA | Zheng, Hongqi , Jiang, Yuewen , Zou, Shujin , Li, Zhe . Optimization decision of reactive power adjustment for loss reduction considering suppression of voltage over-limit caused by ultra-short-term forecast deviation of offshore wind power . | Electric Power Automation Equipment , 2025 , 45 (5) , 84-92 and 109 . |
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In order to adapt the network structure of a distribution network to the access of new energy technologies such as distributed generation (DG), energy storage and DC loads, a new network planning method for AC/DC hybrid distribution networks is proposed. The method considered all possibilities of the AC/DC configuration to improve the economic benefits of the network construction, and constructed a linearized single-layer network planning model to improve the global optimization capability in view of the difficulty of obtaining global optimal solutions for the network planning model. Firstly, considering that AC/DC types of buses and the connection states between buses determine the investment cost of converters and lines, which determines the economic benefits of distribution network planning, a binary bus type matrix is used to represent AC/DC types of buses, a binary network association matrix is developed to represent the connection states between buses, and binary line type variables are adopoted to represent line type selection to construct network structure decision variables, achieving a description of the overall network structure. Secondly, with an objective of converter installation cost, line construction cost and system operation and maintenance cost, a single-layer network planning model is established considering elaborated and practical constraints, such as the number of node-connected lines, line selection constraint, power flow, voltage source converter (VSC) reactive power compensation capacity, system safety operation, energy storage operation, network connectivity and so on. In this proposed model, the AC and DC current models is unified by introducing branch type variables, thus linking the planning layer and operation layer, so that network planning variables and operation optimization variables consisting of power purchased from the distribution network to the grid, DG output, energy storage charging and discharging power and VSC power were optimized simultaneously to enhance the possibility of obtaining a global optimal solution. Finally, to achieve better sulution, power flow equations and line transmission capacity constraints are linearized by a series of linearization methods, such that the mixed integer nonlinear programming (MINLP) problem was transformed into a mixed integer linear programming (MILP) problem, and the GUROBI solver is invoked in Matlab to solve it. The validity of the planning method was verified in a 13-node distribution system. The simulation results show that: (1) The AC/DC hybrid distribution network planning scheme can save 5.05% of the total investment and operation cost compared with the pure AC distribution network planning, and the network structure of the planned AC/DC hybrid distribution network also has greater network supply capacity, which illustrates that the AC/DC hybrid distribution network is more advantageous in the case of mixed AC/DC sources and loads. (2) The proposed planning method saves 13.54% of the total investment and operation cost and 91.32% of the computation time compared with the traditional bi-layer planning model solved by genetic algorithm, which indicates that the single-layer network planning method has prominent global optimization performance and faster computational efficiency. (3) As the method does not require relaxation of constraints, compared to second-order cone planning techniques, there are no limitations in terms of grid topology, etc, and it is suitable for the planning of both radial and meshed distribution networks. © 2024 China Machine Press. All rights reserved.
Keyword ：
Costs Costs Electric load flow Electric load flow Electric power distribution Electric power distribution Electric power transmission Electric power transmission Electric power transmission networks Electric power transmission networks Energy storage Energy storage Global optimization Global optimization Integer programming Integer programming Investments Investments Linearization Linearization MATLAB MATLAB Network layers Network layers Nonlinear equations Nonlinear equations Optimal systems Optimal systems Reactive power Reactive power
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| GB/T 7714 | Jiang, Yuewen , Luo, Zeyu , Cheng, Nuo . Network Planning of AC/DC Hybrid Distribution System Based on Linearization Method [J]. | Transactions of China Electrotechnical Society , 2024 , 39 (5) : 1404-1418 . |
| MLA | Jiang, Yuewen et al. "Network Planning of AC/DC Hybrid Distribution System Based on Linearization Method" . | Transactions of China Electrotechnical Society 39 . 5 (2024) : 1404-1418 . |
| APA | Jiang, Yuewen , Luo, Zeyu , Cheng, Nuo . Network Planning of AC/DC Hybrid Distribution System Based on Linearization Method . | Transactions of China Electrotechnical Society , 2024 , 39 (5) , 1404-1418 . |
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To effectively address the issues of low utilization and challenging cost recovery in distributed energy storage, it is crucial to study trading mechanisms tailored to distributed energy storage. The business model of the sharing economy applied to the energy storage field has potential, and many existing methods have implemented diverse energy sharing transactions using blockchain technology. However, these studies have not adequately considered the convenience of energy storage operations. To tackle this problem, this paper views energy storage as a physical device and designs a more user-friendly coupled charging and discharging sharing mechanism. This approach reduces transaction risks while enhancing the control rights of energy storage participants. First, a business model for energy storage sharing was explored, and a sharing mechanism that separates ownership and usage rights was studied. The trading process, application scenarios, pricing mechanisms, credit management, settlement mechanisms, and rolling trading models supported by blockchain technology were investigated. An optimization model for energy storage sharing that couples charging and discharging rights was established. Then, a decentralized and privacy-focused blockchain platform was built. Smart contracts were used to facilitate the transfer of energy usage rights and control of charging and discharging. This platform ensures the sustainability of energy storage systems while highlighting their role as leaseable physical assets. By simulating scenarios where distributed energy sources and electricity consumers participate in energy storage sharing for deviation handling, we assess the feasibility of the energy storage sharing market. From the perspective of energy storage, profitability depends on initial investment and maintenance costs, as well as equipment parameters. Under current cost levels, energy storage systems with power-to-capacity ratios exceeding 1/4 can profit in this market. From the perspective of energy storage participants, if market prices for distributed electricity transactions are higher than 0.74 ¥/(kW∙h), and the price difference between peak and off-peak electricity sales is greater than 0.4 ¥/(kW∙h), market participants can gain 2.4% to 14.3% more profit through energy storage sharing than through grid backup mode. Conversely, when market prices are lower and price differences are smaller, participants may earn 0.71% to 10.69% less through energy storage sharing. Thus, under specific market conditions, distributed energy storage sharing can create mutually beneficial transactions. Additionally, blockchain technology supports an automated end-to-end trading process, including transaction submission, matching, energy usage rights transfer, on-chain data storage, and real-time settlement. The following conclusions can be drawn from the simulation analysis: (1) The profitability of energy storage participation in the sharing market is subject to the constraints of initial construction, operational costs, and the parameters of energy storage devices. Technological improvements, coupled with cost reductions, are expected to promote the development of the energy storage sharing market. (2)Market conditions characterized by significant fluctuations in grid electricity prices and high levels of trading prices for distributed electricity are more likely to attract market participants to engage in energy storage sharing transactions. (3)Blockchain technology ensures transparency and traceability in energy storage sharing transactions while enhancing the trust of energy storage sharing participants in the platform. This provides robust technical support for the further implementation and promotion of distributed energy storage sharing transactions. © 2024 China Machine Press. All rights reserved.
Keyword ：
Blockchain Blockchain Commerce Commerce Costs Costs Investments Investments Profitability Profitability
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| GB/T 7714 | Jiang, Yuewen , Lin, Peiling , Huang, Chongyang . Blockchain-Based Distributed Energy Storage Charge-Discharge Rights Coupled with Shared Transactions [J]. | Transactions of China Electrotechnical Society , 2024 , 39 (23) : 7512-7527 . |
| MLA | Jiang, Yuewen et al. "Blockchain-Based Distributed Energy Storage Charge-Discharge Rights Coupled with Shared Transactions" . | Transactions of China Electrotechnical Society 39 . 23 (2024) : 7512-7527 . |
| APA | Jiang, Yuewen , Lin, Peiling , Huang, Chongyang . Blockchain-Based Distributed Energy Storage Charge-Discharge Rights Coupled with Shared Transactions . | Transactions of China Electrotechnical Society , 2024 , 39 (23) , 7512-7527 . |
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With the goal of 'carbon peaking and carbon neutrality', the process of carbon reduction in the power industry has been accelerated. The carbon emissions trading, the green certificate trading and the excessive renewable electricity consumption trading have become important market instruments to reduce carbon emissions and promote the development of new power systems. First of all, based on the bilateral centralized bidding, this paper establishes a power energy market trading mechanism considering the coupling of the carbon-green certificate–renewable electricity consumption market with the participation of thermal power, wind power, photovoltaic enterprises and power users. Secondly, a hierarchical iterative interactive transaction optimization model is constructed by taking into account the optimal goals of the market members' benefits and the social welfare of the electricity markets. Finally, the alternating direction multiplier method is used for iterative solution and the impact of the carbon quota benchmark, the green certificate ratio and the renewable electricity consumption trading prices on the electricity market clearing results and the proceeds from generators and users’ costs are analyzed on the IEEE-30 node system. The results show that the power energy market trading mechanism considering the coupling of carbon-green certificate–renewable electricity consumption market is able to significantly reduce the carbon emissions of the thermal power companies compared with the single energy market trading mechanisms. Meanwhile, the mechanism can improve the wind power and photovoltaic enterprises to win the power bids, incentivize users to track the new energy output of the system and mitigate systematic wind and light abandonment. © 2024 Power System Technology Press. All rights reserved.
Keyword ：
Carbon Carbon Costs Costs Electric industry Electric industry Electric power utilization Electric power utilization Iterative methods Iterative methods Power markets Power markets Wind power Wind power
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| GB/T 7714 | Chen, Wei , Jiang, Yuewen . Interactive Optimization of Day-ahead Market Trading Considering Coupling of Carbon-green Certificate-renewable Electricity Consumption Market [J]. | Power System Technology , 2024 , 48 (5) : 1967-1979 . |
| MLA | Chen, Wei et al. "Interactive Optimization of Day-ahead Market Trading Considering Coupling of Carbon-green Certificate-renewable Electricity Consumption Market" . | Power System Technology 48 . 5 (2024) : 1967-1979 . |
| APA | Chen, Wei , Jiang, Yuewen . Interactive Optimization of Day-ahead Market Trading Considering Coupling of Carbon-green Certificate-renewable Electricity Consumption Market . | Power System Technology , 2024 , 48 (5) , 1967-1979 . |
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为了达到海上风电输电工程降损的目的,该文首先详细推导海上风电输电工程海缆传输效率函数,分析海缆传输效率影响因素和有载变压器分接头挡位优化降损原理,建立海缆输电工程日损耗优化模型;其次,考虑降损优化中风电场出力及并网点电压的波动,鉴于随机变量时间序列自相关性分析,提出一种基于预测数据驱动的高维凸包不确定集合建模方法,获得极限场景,降低决策保守性的同时提升计算效率;然后,采用 Q 学习算法进行训练,并结合多智能体系统优化方法求解优化模型,分接头挡位优化和调整时刻优化交替进行,智能体在动作策略与风电场运行状态的交互中不断学习,形成海上风电场日最佳分接头挡位及分接头挡位最佳调整时刻策略.最后,通过对某一海上风电场 220 kV交流海缆输电工程的仿真分析,验证所提模型的合理性以及方法的有效性.
Keyword ：
不确定性 不确定性 多智能体Q学习算法 多智能体Q学习算法 有功降损 有功降损 有载变压器挡位优化 有载变压器挡位优化 海上风电输电工程 海上风电输电工程
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| GB/T 7714 | 郑弘奇 , 江岳文 , 戴锦山 . 不确定环境下基于多智能体Q学习的海上风电输电工程电压调整降损优化 [J]. | 中国电机工程学报 , 2024 , 44 (20) : 7995-8008,中插7 . |
| MLA | 郑弘奇 et al. "不确定环境下基于多智能体Q学习的海上风电输电工程电压调整降损优化" . | 中国电机工程学报 44 . 20 (2024) : 7995-8008,中插7 . |
| APA | 郑弘奇 , 江岳文 , 戴锦山 . 不确定环境下基于多智能体Q学习的海上风电输电工程电压调整降损优化 . | 中国电机工程学报 , 2024 , 44 (20) , 7995-8008,中插7 . |
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在绿色经济和新能源快速发展的背景下,可再生能源供电得到了迅速发展.为应对分布式能源波动性大、抗干扰能力较弱的问题,探索以可再生能源供电为主的独立供电微网群运行策略具有重要意义.根据微电网的规划建设及相应控制模式,提出了微电网独立运行与互联运行的策略.为了减少微电网独立运行中的弃风、弃光现象,提高其经济效益,以最小化微电网独立运行成本和最大化微电网互联运行社会效益为目标,建立了涵盖微电网内部调度与微电网间调度的双层优化模型.采用交替方向乘子法(alternating direction multiplier,ADM)进行迭代求解,以获得兼顾各个微网络体及其群体整体运营效益的可再生能源输出功率、储能输出功率以及购售电策略.最后,通过对14节点独立供电微网群进行仿真分析,验证了所提模型的合理性及方法的有效性.
Keyword ：
互联运行 互联运行 交替乘子法(ADM) 交替乘子法(ADM) 分布式能源 分布式能源 双层优化模型 双层优化模型 微网群 微网群
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| GB/T 7714 | 郑弘奇 , 张芳颖 , 林佩伶 et al. 含多个投资主体的独立供电微网群运行策略 [J]. | 分布式能源 , 2024 , 9 (5) : 41-49 . |
| MLA | 郑弘奇 et al. "含多个投资主体的独立供电微网群运行策略" . | 分布式能源 9 . 5 (2024) : 41-49 . |
| APA | 郑弘奇 , 张芳颖 , 林佩伶 , 江岳文 . 含多个投资主体的独立供电微网群运行策略 . | 分布式能源 , 2024 , 9 (5) , 41-49 . |
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