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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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Coordinated Flexibility Provision Strategy for Multi-Area Interconnected IEHS

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2025年第1期61卷 1675-1682页

作者： Jiao, Min Li, Peng Yang, Ming Wang, Qiushi Han, Longxiao Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China

To enhance the flexibility support and uncertainty mitigation capability of power system, a novel coordination framework is developed to efficiently manage the operational flexibility in a multi-area interconnected energy system that is integrated the electricity system and heating system. This presented approach introduces the term "credible flexibility capacity" to characterize the available flexibility shared to other systems, which considers the transmission time delays, heat losses of district heating system (DHS), and uncertainty from renewable energy generation. Meanwhile, to improve renewable energy accommodation benefit, the operational risk resulting from wind power uncertainty is also identified to make a tradeoff between the operational costs and wind power accommodation risk in interconnected systems. And a decentralized coordinated robust dispatch model is then established based on the alternating direction multiplier method to coordinate operational flexibility capacity among multi-area interconnected energy systems, which significantly improve the flexibility capacity utilization efficiency and effectively enhance the uncertainty mitigation capability. Finally, case studies are carried out to verify the validity of the proposed coordinated dispatch strategy.

关键词： Heating systems Wind power generation Pipelines Delay effects Costs Wind farms Uncertainty Coordinated dispatch credible flexibility capacity dynamic characteristics flexibility sharing multi-area interconnected energy system

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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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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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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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Adaptive Quasi-power Differential Protection Scheme for Active Distribution Networks

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IEEE TRANSACTIONS ON SMART GRID 2024年第1期15卷 324-339页

作者： Yuan, Tong Gao, Houlei Peng, Fang Li, Lin Zhang, Yunchi Zhao, Qian Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China

With the massive integration of distributed generations (DGs), distribution networks gradually become more active and flexible. Conventional overcurrent protection is difficult to adapt to such active distribution networks (ADNs). Current differential protection (CDP) is a good choice for solving this issue, but the multi-branch structure of ADNs especially the unmeasured T-connected load branch affects the protection's sensitivity. Therefore, the paper proposes a quasi-power differential protection (QDP) scheme based on Tellegen's theorem. First, the feasibility of applying Tellegen's theorem to ADNs was analyzed. On this basis, reasonable protection criteria were designed for different scenarios of ADNs. Then, an adaptive protection scheme was established, which can automatically adjust the criteria depending on the presence of T-connected branches within the protected section. Finally, extensive simulations were carried out in an ADN model using PSCAD/EMTDC software. The simulation results demonstrate that the proposed protection scheme has excellent adaptability to network topologies, fault types, fault resistances, and network structures of ADNs.

关键词： Circuit faults Distribution networks Voltage power transmission lines Sensitivity Manganese Equivalent circuits Active distribution network Tellegen's theorem unmeasured T-connected load branch differential protection

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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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Improved AAVM and Small-Signal Model of Hybrid MMC Considering Dynamic Differences Between Full-Bridge and Half-Bridge Submodules

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IEEE TRANSACTIONS ON power ELECTRONICS 2024年第7期39卷 8215-8228页

作者： Guo, Meng Hao, Quanrui Ding, Lei Shandong Univ Sch Elect Engn Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China

The hybrid modular multilevel converter (MMC), which consists of half-bridge submodules ( HBSMs ) and full-bridge submodules (FBSMs), is the general form of MMC. The conventional arm average value model (AAVM) of hybrid MMC assumes that the dynamics of HBSMs and FBSMs are identical and does not consider capacitor voltage differences between FBSM and HBSM, so it cannot describe the dynamics of hybrid MMC accurately. This article proposes an improved AAVM of a hybrid MMC, which includes an equivalent circuit and an arm modulation signal allocation algorithm: first, considering the dynamic difference between HBSM and FBSM, the equivalent circuit of improved AAVM was derived;second, an allocation algorithm that describes the nonlinear distribution of arm modulation signal between HBSM and FBSM was proposed. Considering the influence of high-order harmonics, the differential equation of the electrical part of hybrid MMC in the d-q frame was derived. Based on the nonlinear allocation algorithm of reference voltage and the piecewise solution method, the expressions of HBSM and FBSM equivalent reference voltages in the d-q frame were derived. A modular small-signal model of a hybrid MMC in the d-q frame was established. The correctness and accuracy of the proposed models are verified by simulation and experimental results.

关键词： Arm average value model (AAVM) equivalent circuit modular multilevel converter (MMC) small-signal model

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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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