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Energy-based Directional Pilot Protection for Distribution Networks with IBDGs Considering Unmeasured Load Switching

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CSEE Journal of Power and Energy systems 2024年第1期10卷 139-150页

作者： Chenghan Zhou Guibin Zou Shuo Zhang Xuhui Wen Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061China

Inverter-based distributed generations(IBDGs)are the main approach to utilizing clean energy in distribution networks(DNs).Compared with synchronous source,fault response of IBDG is very *** a result,in DNs with high penetration of IBDGs,legacy protection schemes will no longer be *** this paper,an energy-based directional pilot protection scheme suitabie for DNs with IBDGs is *** scheme considers the large range of phase angle caused by IBDG integration and uses improved energy polarity criterion to determine fault *** addition,magnitude of energy is used to distinguish between faults and load switching to overcome maloperation of directional pilot protection caused by internal unmeasured load *** proposed scheme first uses local measured information to determine fault direction sign and then exchanges the direction sign with the remote *** scheme does not require high-bandwidth communication and strict data synchronization,so it can be implemented at a low ***,simulation studies verify effectiveness of the proposed scheme.

关键词： Distribution network energy polarity inverterbased distributed generation pilot protection unmeasured load

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Secondary Frequency control Considering Optimized Power Support From Virtual Power Plant Containing Aluminum Smelter Loads Through VSC-HVDC Link

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Journal of Modern Power systems and Clean Energy 2023年第1期11卷 355-367页

作者： Peng Bao Wen Zhang Yuxi Zhang Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong UniversityJinan 250061China

The growing number of renewable energy replacing conventional generators results in a loss of the reserve for frequency control in power systems,while many industrial power grids often have excess energy supply due to abundant wind and solar energy *** paper proposes a secondary frequency control(SFC)strategy that allows industrial power grids to provide emergency high-voltage direct current(HVDC)power support(EDCPS)for emergency to a system requiring power support through a voltage source converter(VSC)HVDC *** architecture including multiple model predictive control(MPC)controllers with periodic communication is designed to simultaneously obtain optimized EDCPS capacity and minimize adverse effects on the providing power support(PPS)***,a model of a virtual power plant(VPP)containing aluminum smelter loads(ASLs)and a high penetration of wind power is established for the PPS *** flexibility and controllability of the VPP are improved by the demand response of the *** uncertainty associated with wind power is considered by chance *** effectiveness of the proposed strategy is verified by simulation results using the data of an actual industrial power grid in Inner Mongolia,*** DC voltage of the VSCs and the DC in the potlines of the ASLs are also investigated in the simulation.

关键词： Secondary frequency control power support voltage source converter(VSC) high-voltage direct current(HVDC) model predictive control(MPC) virtual power plant(VPP) demand response

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system Strength Assessment Based on Multi-task Learning

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CSEE Journal of Power and Energy systems 2024年第1期10卷 41-50页

作者： Baoluo Li Shiyun Xu Huadong Sun Zonghan Li Lin Yu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250014China China Electric Power Research Institute Beijing 100192China

Increase in permeability of renewable energy sources(RESs)leads to the prominent problem of voltage stability in power system,so it is urgent to have a system strength evaluation method with both accuracy and practicability to control its access scale within a reasonable ***,a hybrid intelligence enhancement method is proposed by combining the advantages of mechanism method and data driven ***,calculation of critical short circuit ratio(CSCR)is set as the direction of intelligent enhancement by taking the multiple renewable energy station short circuit ratio as the quantitative ***,the construction process of CSCR dataset is proposed,and a batch simulation program of samples is developed accordingly,which provides a data basis for subsequent ***,a multi-task learning model based on progressive layered extraction is used to simultaneously predict CSCR of each RESs connection point,which significantly reduces evaluation error caused by weak *** performance and anti-noise performance of the proposed method are verified on the CEPRI-FS-102 bus system,which provides strong technical support for real-time monitoring of system strength.

关键词： Critical short circuit ratio hybrid intelligence enhancement multi-task learning system strength

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Multi-stage Provincial Power Expansion Planning and Multi-market Trading Equilibrium

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Journal of Modern Power systems and Clean Energy 2024年第5期12卷 1652-1665页

作者： Guangsheng Pan Zhongfan Gu Yuanyuan Sun Kaiqi Sun Wei Gu the School of Electrical Engineering Southeast UniversityNanjingChina Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education School of Electrical EngineeringShandong UniversityJinanChina

Decarbonization in the power sector is one of the critical factors in achieving carbon neutrality,and the top-level design needs to be carried out from the perspective of power planning.A multi-stage provincial power expansion planning(PPEP)model is proposed to simulate the power expansion planning at different stages of the power systems rich in renewable energy *** model covers 16 types of power supply,considering macro-policy demands and micro-operation *** stand-alone capacity aggregation model for coal-based units within the PPEP model allows for accurate construction and retirement with different stand-alone ***,the soft dynamic time warping(soft-DTW)based K-medoids technique is adopted to generate typical scenarios for balancing the model accuracy and solution ***,a multi-market trading equilibrium(MMTE)mechanism is proposed to address the differences in the levelized cost of energy between the coal-based and renewable-based units by participating in energy and ancillary service *** the coalbased units take on the task of providing ancillary services from renewable-based units in the ancillary service market,the MMTE mechanism can effectively equalize the profits of both by having renewable-based units purchase ancillary services from coal-based units and pay for them,thus improving the motivation of coal-based units.A case study in Xinjiang province,China,verifies the effectiveness of the planning results of the PPEP model and the profit equilibrium realization of the MMTE mechanism.

关键词： Power expansion planning market design ancillary service market renewable energy generation energy market

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A Wind Power Ramp Events Detection Method Based on Improved SDA and Endpoint Correction

A Wind Power Ramp Events Detection Method Based on Improved ...

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2024 IEEE IAS Industrial and Commercial Power system Asia, I and CPS Asia 2024

作者： Shan, Shuaijie Yang, Ming Tao, Lidanlan Li, Menglin Wang, Chuanqi Yu, Yixiao Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (纸本)9798350352290

To improve the wind power ramping event detection accuracy, this paper presents a method for the detection of wind power ramping events by adopting adaptive gate width parameters, trend merging and ramping event's endpoint modification. First, the unique parameter ϵ of the swinging door algorithm (SDA) is obtained by calculating the average absolute value of the difference of the initial data (AAVD), the detected SDA compression segments are screened for extreme values, and the trend segments to be measured are obtained by merging the endpoint of the compression segment with the extreme value. Second, with the bump event detection definition and trend merge rules, the set of ramping events is preliminarily determined. Finally, in accordance with the established definition of a ramp, the endpoints of each of the above sets of ramping events have been modified. The inherent defects of traditional SDA detection methods are solved, and the optimal ramping events are obtained. The results demonstrate that, in comparison to the two control detection methods, the proposed detection scheme is capable of both adaptive acquisition of the SDA's ϵ in accordance with the data characteristics and the detection of the endpoints of ramp events with high precision. © 2024 IEEE.

关键词： endpoints correction improved SDA neighbor trend segment merging ramping events detection

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Data-driven Anomaly Detection Method Based on Similarities of Multiple Wind Turbines

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Journal of Modern Power systems and Clean Energy 2024年第3期12卷 803-818页

作者： Xiangjun Zeng Ming Yang Chen Feng Mingqiang Wang Lingqin Xia the College of Electrical Engineering&New Energy China Three Gorges UniversityYichang 443002China the Key Laboratory of Power System Intelligent Dispatch and Control Shandong UniversityJinan 250061China

The operating conditions of wind turbines(WTs)in the same wind farm(WF)may share similarities due to their shared manufacturing process,control strategy,and operating ***,the similarities of WTs are seldom considered in WT anomaly detection,resulting in the disregard of useful *** paper proposes a method to improve the reliability and accuracy of WT anomaly detection using the supervisory control and data acquisition(SCADA)data of multiple WTs in the same ***,a similarity assessment method based on a comparison of different observation time series is proposed,which objectively quantifies the similarities of WT operating ***,the SCADA data of the target WT and selected WTs that are similar are used to establish several estimation models through a long short-term memory(LSTM)*** models that exhibit good estimation performance are used to construct a combined estimation model that estimates the variations in the monitored variables of the target ***,an anomaly detection method that jointly compares the effective value and information entropy of the residuals is proposed to identify *** effectiveness and accuracy of the proposed method are verified using the data of two actual WFs.

关键词： Anomaly detection information entropy long short-term memory similarity assessment wind farm wind turbines

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Power Ramp Extremes Two Stage Forecast based on Auto Encoder and Bi-LSTM

Power Ramp Extremes Two Stage Forecast based on Auto Encoder...

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2024 IEEE IAS Industrial and Commercial Power system Asia, I and CPS Asia 2024

作者： Wang, Chuanqi Yang, Ming Yu, Yixiao Li, Menglin Shan, Shuaijie Zhang, Yuanhe Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (纸本)9798350352290

Power ramp is one of the stages with the largest error of renewable energy power forecast. The deviation in the forecast of the time and values of the start-end points will lead to a significant forecast error to the whole ramp process. Therefore, accurate power ramp forecast can effectively improve the renewable energy power forecast accuracy. In this paper, SDAE is applied on encoding the meteorological features of the power ramp process. Then, the coded part is then spliced with a classifier and fine-tune, promote the output with clear category identity. Finally, the coding is fed into a bidirectional neural network to forecast the power at the start-end points. In case study, the proposed method in this paper demonstrated an improvement in the accuracy of extreme forecast of start-end points power by 4.94%in comparison to the power forecast based ramp recognition method. © 2024 IEEE.

关键词： Clean energy

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Optimizing battery deployment: Aging trajectory prediction enabling homogenous performance grouping

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Journal of Energy Chemistry 2025年第1期100卷 565-577页

作者： Shuquan Wang Feng Gao Zhan Ma Hao Tian Yusen Zhang School of Control Science and Engineering Shandong UniversityJinan 250061ShandongChina Key Lab of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061ShandongChina

As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and *** on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and *** robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.

关键词： Lithium-ion battery Battery prognostics Fusion model Convolutional neural network Transfer learning

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Integrated dispatching Model for Power system Incorporating Multiple Modules 5

Integrated Dispatching Model for Power System Incorporating ...

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5th International Conference on Advances in Electrical, Electronics and Computing Technology, EECT 2025

作者： Xu, Chang Wang, Mingqiang Wang, Zihan Zhang, Yizhe Wang, Jialiang Sun, Fengbin Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (纸本)9798331541545

The widespread integration of renewable energy presents significant challenges for power system scheduling. Traditional power system scheduling is mainly based on the concept of "coordinating on a multi-time-level and gradually refining at each level," using a sequential scheduling framework. However, with the growing integration of renewable energy, the uncertainty in power systems has significantly increased, leading to severe issues such as conflicts in the coordination between different modules. This paper first introduces the scheduling framework of the traditional sequential scheduling model. Then, addressing the problems of module coordination and insufficient flexibility, an integrated multi-time-scale scheduling model is proposed. This model combines day-ahead and intraday scheduling models, optimizing decision variables including unit start/shut states, operation points, and reserves simultaneously to maximize the collaborative potential between different scheduling modules. After linearization, the proposed model is converted into a mixed-integer linear programming (MILP) model, which can be solved directly using commercial optimization solvers. Finally, case analyses demonstrate the effectiveness and superiority of the proposed integrated model compared to the traditional sequential scheduling model. © 2025 IEEE.

关键词： Integer programming

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Enhanced Robust Scheduling Approach Considering Dynamic Flexibility Support from District Heating systems

Enhanced Robust Scheduling Approach Considering Dynamic Flex...

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2024 IEEE IAS Industrial and Commercial Power system Asia, I and CPS Asia 2024

作者： Zheng, Wenzhang Li, Peng Yang, Ming Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan250061 China

ISBN: (纸本)9798350352290

Apart from flexibility resources, e.g., thermal generators and battery energy storage system in electrical power system, dynamic heating networks and flexible heat loads in district heating systems could also provide considerable reserve capacity support for electrical power system. To accurately quantify the reserve support capacity, two operating periods of district heating systems, i.e., reserve capacity support providing period (RCPP) and reserve capacity support recovery period are designed in the paper. A novel dynamic flexibility support interaction mechanism among multiple district heating systems is then presented, and a corresponding scheduling strategy is proposed to coordinate electrical power system and district heating system (DHS), where the concept of allowable regulating capacity exchange interval is introduced to make full use of reserve capacity in DHS. And then, an enhanced robust scheduling model is developed for electrical power systems, where both of the wind power allowable region and operational costs are involved. Case studies demonstrate the proposed method effectively tackles the flexibility coordination between electrical power system and multiple district heating systems. © 2024 IEEE.

关键词： Wind power

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