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Global Energy Interconnection 2024年第4期7卷 415-428页

作者： Kecun Li Zhenyu Huang youbo liu Yaser Qudaih Junyong liu College of Electrical Engineering Sichuan UniversityChengdu 610065P.R.China Department of Electrical engineering Higher Colleges of TechnologyAbu DhabiUAE

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV ***,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully *** study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the ***,SD and SMC models were set ***,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was ***,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS ***,negative electricity prices were considered during clearing *** simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

关键词： Optimal allocation Profitability analysis Photovoltaic Energy storage system Dual timescale dynamics model Spot market clearing

A Special Issue:“Energy Transition Technology for Emission Peak and Carbon Neutrality”for Global Energy Interconnection

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Global Energy Interconnection 2024年第4期7卷 I0002-I0003页

作者： Junyong liu youbo liu Sichuan University Chengdu

In 2020,China made a solemn commitment to the world:striving to achieve carbon peak before 2030 and carbon neutrality before *** energy industry is the main source of carbon emissions and the key path to achieving the“dual carbon”*** revolution in energy production and consumption has already sparked a ***,the energy transition still faces challenges such as a high proportion of fossil fuel usage,multiple constraints on clean energy supply,urgent request to improve the carrying capacity and flexible regulation capability of the power system,and rising energy costs for the entire *** cope with these difficulties and challenges,it is necessary to balance safety and stability,economic efficiency,and clean and low-carbon development three aspects;strengthen energy technology innovation;and deepen institutional and market reform and ***,the editorial department of Global Energy Interconnection has planned the special issue of“Energy Transition Technology for Emission Peak and Carbon Neutrality”.

关键词： Transition challenges urgent

GRU-integrated constrained soft actor-critic learning enabled fully distributed scheduling strategy for residential virtual power plant

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Global Energy Interconnection 2024年第2期7卷 117-129页

作者： Xiaoyun Deng Yongdong Chen Dongchuan Fan youbo liu Chao Ma College of Electrical Engineering Sichuan UniversityChengdu 610065P.R.China State Grid Sichuan Comprehensive Energy Service Co.Ltd. Chengdu 610072P.R.China

In this study,a novel residential virtual power plant(RVPP)scheduling method that leverages a gate recurrent unit(GRU)-integrated deep reinforcement learning(DRL)algorithm is *** the proposed scheme,the GRU-integrated DRL algorithm guides the RVPP to participate effectively in both the day-ahead and real-time markets,lowering the electricity purchase costs and consumption risks for *** Lagrangian relaxation technique is introduced to transform the constrained Markov decision process(CMDP)into an unconstrained optimization problem,which guarantees that the constraints are strictly satisfied without determining the penalty ***,to enhance the scalability of the constrained soft actor-critic(CSAC)-based RVPP scheduling approach,a fully distributed scheduling architecture was designed to enable plug-and-play in the residential distributed energy resources(RDER).Case studies performed on the constructed RVPP scenario validated the performance of the proposed methodology in enhancing the responsiveness of the RDER to power tariffs,balancing the supply and demand of the power grid,and ensuring customer comfort.

关键词： Residential virtual power plant Residential distributed energy resource Constrained soft actor-critic Fully distributed scheduling strategy

基于校准窗口集成与耦合市场特征的可解释双层日前电价预测

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中国电机工程学报 2024年第4期44卷 1272-1285,I0003页

作者：刘慧鑫沈晓东魏泽涛刘友波刘俊勇白元宝四川大学电气工程学院四川省成都市610065 四川能投综合能源公司四川省成都市611130

随着电力市场之间耦合程度不断加深,只局限于单个市场内部的传统特征集不足以支撑高精度预测的需求。而且模型预测性能对校准窗口的选择敏感,而传统电价预测仅使用一个固定时间长度的数据集,同时预测模型的“黑盒”结构导致预测结果在... 详细信息

随着电力市场之间耦合程度不断加深,只局限于单个市场内部的传统特征集不足以支撑高精度预测的需求。而且模型预测性能对校准窗口的选择敏感,而传统电价预测仅使用一个固定时间长度的数据集,同时预测模型的“黑盒”结构导致预测结果在工程应用中可信度偏低。针对上述问题,该文提出一种考虑校准窗口集成与耦合市场特征的可解释双层日前电价预测框架。内层框架为基于改进自适应噪声完备集合经验模态分解(improved complete ensemble empirical mode decomposition,ICEEMDAN)的择优预测,首先分解原始电价序列,然后应用Lasso估计回归(lassoestimated autoregressive,LEAR)、长期和短期时间序列网络(long-term and short-term time-series networks,LSTNet)、卷积神经网络-长短记忆神经网络(convolutionalneuralnetworks-longshort termmemory,CNN-LSTM)、移动平均(autoregressive integrated moving average,ARIMA)和核极限学习机(kernel extreme learning machines,KELM)模型预测子序列并选择最优预测算法。外层框架为基于贝叶斯模型平均(bayes modelaveraging,BMA)的校准窗口集成预测,针对每个不同校准窗口长度数据集下的预测分配权重并集成得到预测电价。最后,通过可解释方法沙普利加性解释模型(shapley additiveexplanations,SHAP)分析耦合市场特征如何影响预测电价。该文通过北欧电力市场数据集的算例分析证明了所提算法的优越性和校准窗口集成方案的有效性。

关键词：校准窗口集成耦合市场特征双层预测框架改进自适应噪声完备集合经验模态分解(ICEEMDAN) 贝叶斯模型平均(BMA) 沙普利加性解释模型(SHAP)

计及参与成本贡献的用户侧云储能服务及其纳什议价模型

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电力自动化设备 2024年第2期44卷 9-17页

作者：谢涵铮刘友波马超殷科向月荆渝唐早刘俊勇四川大学电气工程学院四川成都610065 国网四川综合能源服务有限公司四川成都610031 杭州电子科技大学自动化学院浙江杭州310038

为了解决以共享经济概念为基础的云储能服务中用户与运营商之间的成本贡献及收益分配问题,提出了计及参与成本贡献的用户侧云储能服务及其纳什议价模型,对运营商独立投资的集中式云储能服务进行定价。在所述服务框架中,运营商优先对充... 详细信息

为了解决以共享经济概念为基础的云储能服务中用户与运营商之间的成本贡献及收益分配问题,提出了计及参与成本贡献的用户侧云储能服务及其纳什议价模型,对运营商独立投资的集中式云储能服务进行定价。在所述服务框架中,运营商优先对充放电需求互补的用户交换电能,再通过充放电或购售电来满足总体的净充放电需求;然后,采用Shapley值法为用户分配储能损耗贡献度,并综合考虑用户的新能源余量能量互济率及虚拟储能利用率,对分配结果改进,以进一步刻画用户服务费的差异性;最后,求解计及用户成本贡献的纳什议价模型,计算各用户的服务费。算例结果表明:所提方法减小了储能充放电损耗及总体用能成本,并提升了新能源消纳率;且改进Shapley值法的分配结果促进了用户将新能源余量上网及按需租赁虚拟储能。同时,纳什议价模型在保证用户服务费差异合理的前提下,兼顾了用户群体和运营商之间的利益诉求,促进了双方合作。

关键词：云储能成本贡献收益分配纳什议价改进Shapley值法

基于双向循环插补网络的分布式光伏集群时序数据耦合增强方法

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电网技术 2024年第7期48卷 2784-2794,I0042-I0048页

作者：廖若愚刘友波沈晓东高红均唐冬来刘俊勇四川大学电气工程学院四川省成都市610065 四川中电启明星信息技术有限公司四川省成都市610067

分布式光伏点多面广、局部渗透率高、安装环境复杂多变,真实可靠的量测数据是其性能分析、出力预测、运维调控的基础。然而,传感器故障和通信堵塞等因素会造成量测值缺失,恶化原始数据质量,进而影响配电网运行决策的准确性。传统数据修... 详细信息

分布式光伏点多面广、局部渗透率高、安装环境复杂多变,真实可靠的量测数据是其性能分析、出力预测、运维调控的基础。然而,传感器故障和通信堵塞等因素会造成量测值缺失,恶化原始数据质量,进而影响配电网运行决策的准确性。传统数据修复方法只考虑单一量测值的分布特征,忽略了多维时序数据的潜在耦合关系,修复精度有限。为此,该文提出一种基于双向多阶段循环插补网络和Seq2SeqAttention的时序数据耦合增强方法,改进了循环插补网络的结构,并引入衰减机制,能利用少量未缺失数据,潜在地挖掘原始数据的整体分布规律,一次性对多个光伏场站完成高质量数据修复。实验结果表明,所提方法在高比例缺失情况下仍有良好的修复性能,可明显增强分布式光伏集群的基础数据质量,提升电网运营商对光伏集群的细粒度感知能力。

关键词：缺失数据修复双向循环插补网络耦合时序数据分布式光伏集群

A Hybrid Agent-based Model Predictive Control Scheme for Smart Community Energy System with Uncertain DGs and Loads

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Journal of Modern Power Systems and Clean Energy 2021年第3期9卷 573-584页

作者： Xiaodi Wang youbo liu Junbo Zhao Junyong liu the College of Electrical Engineering Sichuan UniversityChengdu 610065China the Department of Electrical and Computer Engineering Mississippi State UniversityStarkville 39762USA

A multi-agent consensus-based market scheme is proposed for the cooperation of community and multiple microgrids(MGs)in a distributed,economic and hierarchal *** proposed community-based market framework with frequency regulation(FR)market is formulated as a two-level scheduling problem:the global decision-making process of community agent(CA)to participate in the FR market and the interaction and control process of local MGs to achieve collaboration in response to the global target with efficient pricing ***,the model predictive control(MPC)is integrated with the consensus-based theory to allow MG to obtain an economic and reliable dispatch in the presence of uncertainties of distributed generators and *** to the distributed nature of the proposed scheme,its robustness to communication issues has been strengthened and a win-win situation for all energy stakeholders can be *** robustness of the proposed scheme is investigated in various conditions,including different implementation strategies,communication topologies,and the level of uncertainties.

关键词： Community market model predictive control(MPC) energy management consensus-based market scheme

A Data-driven Distributionally Robust Operational Model for Urban Integrated Energy Systems

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CSEE Journal of Power and Energy Systems 2022年第3期8卷 789-800页

作者： Hongjun Gao Zhenyu liu youbo liu Lingfeng Wang Junyong liu College of Electrical Engineering Sichuan UniversityChengdu 610065China Department of Electrical Engineering and Computer Science University of Wisconsin-MilwaukeeMilwaukeeWI 53211USA

A multi-energy conversion can effectively increase the utilization of renewable energy in the urban integrated energy system(UIES).Meanwhile,the uncertainties of renewable energy resources(e.g.,wind energy)also bring increased challenges to the operation of *** this study,a typical two-stage datadriven distributionally robust operation(DDRO)model based on finite scenarios is proposed for UIES including power,gas and heat networks to obtain a salient strategy from both an economic and robustness *** the first stage,the forecasted information for wind power is especially included to improve the economic aspect of robust *** worst probability distribution for the selected known real-time wind power scenarios can be identified in the second stage where the power differences caused by the real-time uncertainties of wind power can be mitigated by flexible regulation of energy purchasing and coupling units(such as gas turbine,power to gas equipment,electric boiler and gas boiler).Moreover,norm-1 and norm-inf co-constraints are utilized to construct a confidence set for the probability distributions of uncertain wind *** whole two-stage model is solved by the column-and-constraint generation(CCG)***,case studies are conducted to show the performance of the proposed model and various *** Terms-Data-driven methods,distributionally robust optimization,urban integrated energy system,wind power.

关键词： Data-driven methods distributionally robust optimization urban integrated energy system wind power

基于数据驱动预测控制的有源配电网电压控制策略

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电力系统自动化 2024年第20期48卷 100-108页

作者：祝泳琪刘友波唐志远许梓荣高红均刘俊勇四川大学电气工程学院四川省成都市610065

高比例分布式光伏接入配电网使得系统的不确定性更加严峻,而配电网的网络拓扑与线路参数等数据很难准确获取,使得基于精确物理建模的传统配电网控制方法难以发挥作用。随着配电网量测装置的普及应用,配电网运行数据的获取愈发容易。文... 详细信息

高比例分布式光伏接入配电网使得系统的不确定性更加严峻,而配电网的网络拓扑与线路参数等数据很难准确获取,使得基于精确物理建模的传统配电网控制方法难以发挥作用。随着配电网量测装置的普及应用,配电网运行数据的获取愈发容易。文中提出一种基于配电网量测数据的有源配电网无模型电压控制方法。首先,基于配电网历史数据构建Hankel矩阵,建立网络节点电压与储能输出功率的关系;其次,利用局部量测数据,在考虑不确定干扰因素以及储能寿命衰减模型的同时,构建数据驱动预测控制下的配电网电压优化框架,实现控制周期内配电网电压的滚动优化;最后,通过IEEE 34节点标准算例与改进的IEEE 123节点算例仿真验证了所提方法的有效性和优越性。

关键词：有源配电网电压控制数据驱动预测控制衰减模型储能

Integrated traffic-power simulation framework for electric vehicle charging stations based on cellular automaton

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Journal of Modern Power Systems and Clean Energy 2018年第4期6卷 816-820页

作者： Yue XIANG Zipeng liu Jichun liu youbo liu Chenghong GU College of Electrical Engineering and Information Technology Sichuan University State Key Laboratory of Electrical Insulation and Power Equipment School of Electrical Engineering Xi'an Jiaotong University Department of Electronic and Electrical Engineering University of Bath

This paper presents a novel integrated framework for simulating the charging load of an electric vehicle charging station. The framework is built based on the cellular automaton model, including five modules: vehicle generation, charging station, lane change, speed update and boundary clear. The proposed framework can effectively stimulate the system dynamics of the traffic system and charging power process in a charging station. Case studies have verified its feasibility and effectiveness.

关键词： Charging station Charging load Traffic flow Simulation Cellular automaton