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Optimal Time-of-use Pricing for Renewable Energy-powered Microgrids: A Multi-agent Evolutionary Game Theory-based Approach

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 162-174页

作者： Yu Zeng Yinliang Xu xinwei shen Hongbin Sun Tsinghua-Berkeley shenzhen Institute.Tsinghua shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Department of Electrical Engineering Tsinghua UniversityBeijing 100084China

While price schedules can help improve the economic efficiency of renewable energy-powered microgrids,timeof-use(TOU)pricing has been identified as an effective way for microgrid development,which is presently limited by its high *** this study,we propose an evolutionary game theoretic model to explore optimal TOU pricing for development of renewable energy-powered microgrids by applying a multi-agent system,that comprises a government agent,local utility company agent,and different types of consumer *** the proposed model,we design objective functions for the company and the consumers and obtain a Nash equilibrium using backward *** pricing strategies,namely,the TOU seasonal pricing and TOU monthly pricing,are evaluated and compared with traditional fixed *** numerical results demonstrate that TOU schedules have significant potential for development of renewable energy-powered microgrids and are recommended for an electric company to replace traditional fixed ***,TOU monthly pricing is more suitable than TOU seasonal pricing for microgrid development.

关键词： Game theory microgrid multi-agent system renewable energy time-of-use pricing

Joint Planning of Active Distribution Network and EV Charging Stations Considering Vehicle-to-Grid Functionality and Reactive Power Support

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CSEE Journal of Power and Energy Systems 2024年第5期10卷 2100-2113页

作者： Yongheng Wang xinwei shen Yan Xu Institute for Tsinghua shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore

This paper proposes a collaborative planning model for active distribution network(ADN)and electric vehicle(EV)charging stations that fully considers vehicle-to-grid(V2G)function and reactive power support of EVs in different *** paper employs a sequential decomposition method based on physical characteristics of the problem,breaking down the holistic problem into two sub-problems for *** I optimizes the charging and discharging behavior of autopilot electric vehicles(AEVs)using a mixed-integer linear programming(MILP)*** II uses a mixed-integer secondorder cone programming(MISOCP)model to plan ADN and retrofit or construct V2G charging stations(V2GCS),as well as multiple distributed generation resources(DGRs).The paper also analyzes the impact of bi-directional active-reactive power interaction of V2GCS on ADN *** presented model is tested in the 47-node ADN in Longgang District,shenzhen,China,and the IEEE 33-node ADN,demonstrating that decomposition can significantly improve the speed of solving large-scale problems while maintaining accuracy with low AEV penetration.

关键词： Active distribution network large-scale problem reactive power support sequential decomposition V2G charging station

Combined Electric and Heat System Testbeds for Power Flow Analysis and Economic Dispatch

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CSEE Journal of Power and Energy Systems 2021年第1期7卷 34-44页

作者： Xin Qin xinwei shen Ye Guo Zhaoguang Pan Qinglai Guo Hongbin Sun the Tsinghua-Berkeley shen zhen Institute Tsinghua UniversityShenzhen 518055China the department of electric engineering Tsinghua UniversityBeijing 100084China

In combined electric and heat systems,selecting a suitable testbed for power flow analysis or economic dispatch is not easy:a large number of existing testbeds are not opensource,while others are difficult to be reused by other researchers due to the particularity of system scale,topology,and *** this paper,we present three open-source testbeds with different scales based on practical combined electric and heat *** satisfy researchers"specific demands on the system topology and data,we also discuss how to modify testbeds based on existing topologies and *** can use the testbeds presented in this paper to test their innovative methods for power flow analysis and economic dispatch,and can also design their own testbeds based on the methodology in this paper,using published topologies and data.

关键词： Combined heat and power system economic dispatch power flow testbed

Very Short-term Spatial and Temporal Wind Power Forecasting: A Deep Learning Approach

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CSEE Journal of Power and Energy Systems 2020年第2期6卷 434-443页

作者： Tianyu Hu Wenchuan Wu Qinglai Guo Hongbin Sun Libao Shi xinwei shen Tsinghua-Berkeley shenzhen Institute(TBSI) Shenzhen 518055China TBSI Shenzhen 518055China Department of Electrical Engineering State Key Laboratory of Power SystemsTsinghua UniversityBeijing 100084China Graduate School at shenzhen Tsinghua UniversityShenzhen 518055China

In power systems that experience high penetration of wind power generation,very short-term wind power forecast is an important prerequisite for look-ahead power *** univariate wind power forecasting methods at presentonly utilize individual wind farm historical ***,studies have shown that forecasting accuracy canbe improved by exploring both spatial and temporal correlations among adjacent wind *** research on spatial-temporal wind power forecasting is based on relatively shallow time series models that,to date,have demonstrated unsatisfactory *** this paper,a convolution operation is used to capture the spatial and temporal correlations among multiple wind farms.A novel convolution-based spatial-temporal wind power predictor(CSTWPP)is *** to CSTWPP’s high nonlinearity and deep architecture,wind power variation features and regularities included in the historical data can be more effectively ***,the online training of CSTWPP enables incremental learning,which makes CSTWPP non-stationary and in conformity with real *** processing units(GPU)is used to speed up the training process,validating the developed CSTWPP for real-time *** studies on 28 adjacent wind farms are conducted to show that the proposed model can achieve superior performance on 5-30 minutes ahead wind power forecasts.

关键词： Convolution neural network deep learning incremental learning short-term wind power forecast spatialtemporal correlation

Application of Modified Progressive Hedging for Stochastic Unit Commitment in Electricity-Gas Coupled Systems

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CSEE Journal of Power and Energy Systems 2021年第4期7卷 840-849页

作者： Haizhou Liu xinwei shen Qinglai Guo Hongbin Sun Mohammad Shahidehpour Wenzhi Zhao Xinyi Zhao Tsinghua-Berkeley shenzhen Institute Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Electrical and Computer Engineering Department Illinois Institute of Technology60616ChicagoILUnited States

The increasing number of gas-fired units has significantly intensified the coupling between electric and gas power ***,nonlinearity and nonconvexity in gas flow equations,together with renewable-induced stochasticity,resulted in a computationally expensive model for unit commitment in electricity-gas coupled integrated energy systems(IES).To accelerate stochastic day-ahead scheduling,we applied and modified Progressive Hedging(PH),a heuristic approach that can be computed in parallel to yield scenario-independent unit *** early termination and enumeration techniques,the modified PH algorithm saves considerable com,putational time for certain generation cost settings or when the scale of the IES is ***,an adapted second-order cone relaxation(SOCR)is utilized to tackle the nonconvex gas flow *** studies were performed on the IEEE *** system/Belgium 20-node gas system and the IEEE 118-bus system/Belgium 20-node gas *** computational efficiency when employing PH is 188 times that of commercial software,and the algorithm even outperforms Benders *** the same time,the gap between the PH algorithm and the benchmark is less than 0.01% in both IES systems,which proves that the solutions produced by PH reach acceptable optimality in this stochastic UC problem.

关键词： Electricity-gas coupled system integrated energy system modified Progressive Hedging second-order cone relaxation unit commitment

Comprehensive power-supply planning for active distribution system considering cooling,heating and power load balance

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Journal of Modern Power Systems and Clean Energy 2015年第4期3卷 485-493页

作者： xinwei shen Yingduo HAN Shouzhen ZHU Jinghong ZHENG Qingsheng LI Jing NONG State Key Lab of Control and Simulation of Power Systems and Generation Equipments Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Grid Planning&Research Center Guizhou Power Grid CooporationCSGGuiyang 550002China

An active distribution system power-supply planning model considering cooling,heating and power load balance is proposed in this paper.A regional energy service company is assumed to be in charge of the investment and operation for the system in the *** expansion of substations,building up distributed combined cooling,heating and power(CCHP),gas heating boiler(GHB)and air conditioner(AC)are included as investment planning *** terms of operation,the load scenarios are divided into heating,cooling and transition ***,the extreme load scene is included to assure the power supply reliability of the *** results demonstrate the effectiveness of the proposed model and illustrate the economic benefits of applying distributed CCHP in regional power supply on investment and operation.

关键词： Active distribution system Combined cooling heating and power(CCHP) Power-supply planning Load balance

Energy Internet:Redefinition and categories

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Energy Internet 2024年第1期1卷 3-8页

作者： Hongbin Sun Qinglai Guo xinwei shen Yixun Xue Mohammad Shahidehpour Nikos Hatziargyriou Department of Electrical Engineering Tsinghua UniversityBeijingChina College of Electrical and Power Engineering and Key Laboratory of Cleaner Intelligent Control on Coal&Electricity Ministry of EducationTaiyuan University of TechnologyTaiyuanChina shenzhen International Graduate School Tsinghua UniversityShenzhenChina Department of Electrical and Computer Engineering Illinois Institute of TechnologyChicagoIllinoisUSA National Technical University of Athens AthensGreece

The concept of‘Energy Internet’(EI)has been widely accepted by both academic and industry experts after more than a decade of *** it was proposed,EI has been discussed and applied to many technical works in power and energy *** specific definitions were proposed for EI by those who have applied it to respective fields of engineering,but a comprehensive and widely accepted definition of EI is still being *** this paper,we propose the redefinition of EI,based on a comprehensive literature review,some latest trends and driving forces in the global energy industry,as well as its development in the past *** addition,we summarise the EI framework and features for future applications,where EI is categorised by its scale into local‐and wide‐area applications to manifest its effectiveness in power and energy.

关键词： categories Energy Internet redefinition

基于混合整数规划的配电网检修多目标优化决策及其灵敏度分析

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电网技术 2024年第11期48卷 4680-4689,I0065页

作者：夏添沈欣炜尚宇炜清华大学深圳国际研究生院广东省深圳市518055 中国电力科学研究院有限公司北京市海淀区100192

合理的检修计划编排可以提升配网经济性和可靠性,配电网数字化提供的准确故障率信息有助于检修决策。该文针对配网馈线长周期检修计划编排问题,把故障风险分为3类,并采取对应运维动作,构建了多目标混合整数线性模型,实现了配网精益化的... 详细信息

合理的检修计划编排可以提升配网经济性和可靠性,配电网数字化提供的准确故障率信息有助于检修决策。该文针对配网馈线长周期检修计划编排问题,把故障风险分为3类,并采取对应运维动作,构建了多目标混合整数线性模型,实现了配网精益化的检修编排,优化求解后的运维成本和可靠性指标均有提升。基于所提模型,改变故障率曲线参数验证模型对信息准确性的灵敏度。结果表明,故障率偏差影响运维决策,进而导致配网各项指标变化最高可达30%。为保证配电系统的可靠性和经济性,应快速推进配网数字化建设,及时更新故障率数据,并重点关注对系统可靠性影响更大的故障类型。

关键词：配电网检修决策优化配网数字化故障率可靠性

考虑储热装置的风电-热电机组联合优化运行策略

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电力自动化设备 2017年第6期37卷 139-145页

作者：于婧孙宏斌沈欣炜清华-伯克利深圳学院广东深圳518000 清华大学电机系电力系统及发电设备控制和仿真国家重点实验室北京100084

基于日前供热负荷预测和风电出力预测,考虑储热装置运行机理,研究风电场与热电机组联合运行的优化方法。将含储热装置的热电厂和风电场组成一个发电利益集合体,在满足地区供热负荷和提升风电消纳的同时,通过调节热电机组和储热装置的出... 详细信息

基于日前供热负荷预测和风电出力预测,考虑储热装置运行机理,研究风电场与热电机组联合运行的优化方法。将含储热装置的热电厂和风电场组成一个发电利益集合体,在满足地区供热负荷和提升风电消纳的同时,通过调节热电机组和储热装置的出力最大化发电利益集合体的收益。考虑热电机组的热-电耦合特性和储热装置的运行约束,建立了日前调度模型并进行求解。在此基础上,考虑风电出力的随机性,建立了相应的随机优化模型。算例分析表明,考虑储热的风电-热电机组联合优化所获得的收益高于风电场和热电机组单独运行获得的总收益,并且可在现行"以热定电"运行机制下提高风电的消纳能力。同时采用随机优化模型能有效降低系统联合出力的不确定性,可较好地解决风功率预测中的不确定性问题。

关键词：风电热电联产储热系统随机优化不确定性