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2023 IEEE Sustainable power and Energy Conference, iSPEC 2023

作者： Li, Zhendong Yan, Jiongcheng Liu, Yutian Li, Li Qu, Hanbing The Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Jinan Power Supply Company Jinan China

ISBN: (纸本)9798350322699

The widespread integration of renewable generation and the changes in load structure bring significant challenges to the transient voltage stability of large-scale power systems. In order to achieve fast decision of preventive control for improving transient voltage stability, this paper proposes a preventive control method based on the attention of Convolutional Neural Network (CNN). An optimization decision model is established, which not only considers multiple traditional constraints but also introduces the model attention indicator based on Gradient-weighted Class Activation Mapping (Grad-CAM), enabling a more targeted improvement of transient voltage stability. The proposed indicator is capable of extracting the knowledge learned by CNN-based transient voltage assessment model, and utilizing it to guide the optimization decision-making of preventive control. Simulation results of provincial grid of eastern China demonstrate that the optimized control scheme can effectively enhance the transient voltage stability of power systems. © 2023 IEEE.

关键词： model attention indicator power system preventive control transient voltage stability

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Adaptive Inertial control for Wind Turbine Generators in Fast Frequency Response Based on the power Reduction Period Assessment

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2025年第1期16卷 377-391页

作者： Heidari, Mahdi Ding, Lei Kheshti, Mostafa Zhao, Xiaowei Terzija, Vladimir Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Univ Warwick Sch Engn Intelligent Control & Smart Energy ICSE Grp Coventry CV4 7AL England Newcastle Univ Sch Engn Newcastle Upon Tyne NE1 7RU England

Fast frequency response of wind turbine generators (WTGs) is achieved by injecting incremental power to the grid followed by power reductions to avoid over-deceleration and ensure secure rotor speed recovery. Second frequency deeps (SFDs) are the results of such power reductions that are challenging during abrupt frequency transients that may lead to under-frequency load shedding, or cascading events leading to blackouts. To address this issue, this paper presents an adaptive inertial control (AIC) scheme for WTGs designed to maximize the improvement in frequency nadir without causing SFD. The proposed method is developed through an assessment of power reduction period of WTGs during fast frequency response. This analysis investigates the impacts on the system frequency of a) injecting different shares of disturbance size (SoDSs) by WTGs and b) latency/delay in power injection. Derived from this analysis, the AIC is proposed to inject the maximum possible SoDS during the over-production period and successfully stabilize and recover the rotor speed during the assigned optimal power reduction period with SFDs disabled. This is achieved by adaptively adjusting the AIC in the reduction period based on the SoDS injected by WTGs during the over-production stage. Also, the AIC is modified to adapt against wind speed deviations. To evaluate the performance of the AIC, a comprehensive verification is carried out by comparing AIC with thirteen existing inertial control schemes and maximum power point tracking control in various cases using wind-integrated IEEE 39-bus system in Digsilent powerFactory and real-time experimental tests. The results confirm the effectiveness of AIC in terms of achieving maximum improvement in frequency nadir without generating SFD.

关键词： Frequency control Rotors power system dynamics Frequency response power system stability Generators Wind speed Disturbance frequency nadir frequency stability inertial control wind turbine generator

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Search direction optimization of power flow analysis based on physics-informed deep learning

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2025年 167卷

作者： Li, Baoliang Wu, Qiuwei Cao, Yongji Li, Changgang Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Shandong Univ Acad Intelligent Innovat Jinan 250101 Peoples R China

power flow analysis is crucial for obtaining power system operation states and optimizing control measures. The increasing integration of renewable energy sources has resulted in a more complex power system, posing challenges to the computational efficiency and convergence of conventional power analysis methods. Based on the physics-informed deep learning, this paper proposes an optimization scheme for the search direction to improve the performance of power flow analysis. The higher-order information originating from the Taylor series expansion of the power flow equation is utilized to optimize the search direction. The deep belief network is used to establish a nonlinear mapping between the power flow equations and the optimized search direction. Additionally, the physical information of the power system is encoded into the deep learning model to meet the real physical constraints. Case study results show that the proposed scheme contributes to improve the computational efficiency and convergence in power analysis, and is feasible for the scenarios of ill-conditioned power flow.

关键词： Physics-informed deep learning Deep belief network Physical constraints power flow analysis Search direction

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Closed-Loop Synthetic Inertia control for Wind Turbine Generators in Association With Slightly Over-Speeded Deloading Operation

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IEEE TRANSACTIONS ON power systemS 2023年第6期38卷 5022-5032页

作者： Bao, Weiyu Ding, Lei Kang, Yong Cheol Sun, Long Shandong Univ Sch Elect Engn Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Yonsei Univ Sch Elect & Elect Engn Seoul 03722 South Korea

Following a frequency event in a power system, synthetic inertia control (SIC) of a wind turbine generator (WTG) can improve the frequency nadir by instantly releasing the stored kinetic energy in the rotating masses. However, SIC might lower the settling frequency below the maximum steady-state frequency deviation, thereby disabling automatic generation control (AGC). This delays frequency recovery to the nominal value. This paper proposes a closed-loop SIC scheme for a WTG in association with slightly over-speeded deloading operation (SODO) that can improve both the frequency nadir and settling frequency. To achieve this, prior to an event, the proposed SIC scheme performs SODO, which can store more releasable energy into the rotating masses of a WTG while minimizing the energy loss. The proposed scheme can improve the frequency nadir by releasing more energy, improve the settling frequency, which enables AGC, and avoid over-deceleration of the rotor speed of a WTG in the low wind speed region. Simulation results clearly demonstrate that the proposed SIC scheme can improve both the frequency nadir and settling frequency under various wind conditions, event sizes, and penetration levels, thereby supporting the frequency stability in a power system that has a high penetration of wind power.

关键词： Frequency control Doubly fed induction generators power system stability Automatic generation control Wind speed power system reliability Frequency nadir primary frequency control settling frequency slightly over-speeded operation synthetic inertia control

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Reference Phasor-Based Data Self-Synchronization Scheme for Line Current Differential Protection in Active Distribution Networks

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IEEE TRANSACTIONS ON SMART GRID 2024年第2期15卷 1466-1480页

作者： Zhou, Chenghan Zou, Guibin Zheng, Maoran Tian, Junyang Li, Haiyong Du, Tao Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China China Southern Power Grid Dispatching Control Ctr Guangzhou 510623 Peoples R China Guangxi Power Grid Co Ltd Dispatching Control Ctr Nanning 530023 Peoples R China Shandong Shanda Elect Power Technol Co Ltd Ctr Res & Dev Jinan 250101 Peoples R China

Line current differential protection (CDP) is very suitable for active distribution networks (ADNs) with complex fault characteristics in principle, but its high cost limits its application. The data self-synchronization (DSS) methods do not require investing in additional synchronization equipment and provide a low-cost solution for line CDP in ADNs. However, the existing DSS methods based on time-domain features still have some shortcomings, such as they cannot be applied to lines with T-connected branches and are vulnerable to noise. In this paper, the existing DSS methods are first reviewed. On this basis, an improved DSS scheme based on reference phasor is proposed. This scheme calculates reference phasors based on the full-cycle data in a specific period before the fault and corrects the CDP criterion according to reference phasors. The proposed scheme includes three correction methods designed for lines without T-connected branches, lines with measurable T-connected branches and lines with unmeasurable T-connected branches, respectively. Finally, the performance of the proposed scheme is verified by an ADN simulation model based on PSCAD/EMTDC. Simulation results show that compared with existing DSS methods, the proposed scheme has the advantages unaffected by fault inception angles, better anti-noise ability, lower sampling frequency requirements, and wider application scenarios.

关键词： Circuit faults Synchronization Relays Fault detection Fault currents Current measurement Costs Active distribution network current differential protection data self-synchronization reference phasor T-connected branch

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Carbon Cost Pass-through Analysis Considering Renewable Energy Consumption 4

Carbon Cost Pass-through Analysis Considering Renewable Ener...

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4th International Conference on Smart power and Internet Energy systems (SPIES)

作者： Su, Xinyan Zhang, Li Wang, Hao Wang, Yuxi Song, Shihang Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

ISBN: (纸本)9781665489577

The establishment of carbon allowances and carbon market has changed the competitiveness of thermal-generating units in the energy market and produced carbon cost passing through to electricity prices. With the increase in the proportion of renewable energy connected to the grid, thermal units have a strong performance in the ancillary service market due to their good regulation characteristics. For this situation, this paper establishes the carbon cost pass-through rate calculation model based on simulating energy market transactions which used the energy-reserve joint optimization model to consider the participation of thermal units in the energy market and reserve market under the condition of a high proportion of renewable energy connected to the grid. A 10-unit system is taken as an example to verify the effectiveness of the improved carbon cost pass-through analysis, and analyze the impact of changes in wind power integration on carbon cost pass-through.

关键词： carbon cost pass-through renewable energy energy-reserve joint optimization Least Squares regression

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A Practical Reference Network Planning Model Based on Load Moment and Acceptable Range 2

A Practical Reference Network Planning Model Based on Load M...

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IEEE 2nd International Conference on power Science and Technology (ICPST)

作者： Li, Jianjie Zhong, Wentao Mu, Mingliang Wang, Jialiang Binzhou Power Supply Co State Grid Shandong Prov Power Co Binzhou Peoples R China Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

ISBN: (纸本)9798350349047;9798350349030

There is a big gap between theoretical research and practical application of reference network planning. Most of the existing planning models in academic research take cost as the objective function. Although various advanced models and methods are proposed based on this, they are rarely applied in actual power companies. In this paper, a new reference network planning model is proposed according to the actual demand. According to the field investigation, "power supply to the nearest load" is taken as the goal, and the load moment is expressed analytically. In order to meet the increasing demand of renewable energy integrating into the power grid, the concept of acceptable disturbance range is added to the model constraint to improve the system's absorption capacity of renewable energy. Finally, the N-1 security constraint is considered to improve the reliability of the model. The model is transformed into a mixed integer linear programming (MILP)problem by priority objective programming method and can be solved with mature commercial solvers. The validity of the model is verified by IEEE-RTS24 node system. When N-1 safety constraints are taken into account, the advantages of the proposed model become apparent, with a total cost reduction of about 2.5%.

关键词： reference network planning load moment acceptable disturbance range N-1 security constraint mixed integer linear programming priority objective programming

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A Wind Speed Correction Method Based on Modified Hidden Markov Model for Enhancing Wind power Forecast

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2022年第1期58卷 656-666页

作者： Li, Menglin Yang, Ming Yu, Yixiao Lee, Wei-Jen Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Univ Texas Arlington Arlington TX 76019 USA

Short-term wind power forecast (WPF) depends highly on the wind speed forecast (WSF), which is the prime contributor to the forecasting error. To achieve more accurate WPF results, this article proposes a wind speed correction method to improve the WSF result obtained by using the weather research and forecasting (WRF) model. First, the WRF model is constructed to forecast the wind speed, and its performance is analyzed. Second, a novel hidden Markov model (HMM) is developed to explore both the temporal autocorrelation of WSF error and the nonlinear correlation between the WSF result and the error. In the model, the fuzzy C-means cluster is introduced to properly divide the hidden state space of HMM and the emission probability of HMM is improved as continuous by the kernel density estimation (KDE) to make full use of the observation information. The proposed HMM model is better at wind speed correction through modification. Third, the HMM is solved by the Viterbi algorithm and the minimum mean-square error regulation to correct the predicted wind speed. Finally, the deterministic and probabilistic WPF results are obtained by using another KDE model, the proposed method is demonstrated to be superior to the benchmarks in case studies.

关键词： Hidden Markov models Wind forecasting Forecasting Predictive models Wind speed Mathematical models Wind power generation Hidden markov model (HMM) kernel density estimation (KDE) weather research and forecasting (WRF) model wind power forecast (WPF) wind speed correction

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Multi-level Voltage Coordination Optimization Strategy of Distribution Network Considering Multiple Devices 6

Multi-level Voltage Coordination Optimization Strategy of Di...

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6th Asia Energy and Electrical Engineering Symposium (AEEES)

作者： Liang, Caishuai Wang, Mingqiang Sun, Fengbin Zhang, Xia Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan Peoples R China Luyuan Elect Grp Co LTD Jinan Peoples R China

ISBN: (纸本)9798350373486;9798350373479

The presence of wind power, photovoltaic, and other distributed energy sources within the distribution network. The power quality of the distribution network degrades as the proportion of distributed energy increases. To address the uncertainty introduced by the integration of distributed energy, it is essential to coordinate and optimize the multi-voltage levels within the distribution network. Currently, most studies focus on achieving voltage control in the distribution network by minimizing either network loss or voltage fluctuation, often limiting consideration to a single voltage stage. Minimizing network loss can enhance the overall operational cost efficiency of the distribution network, but it has a limited impact on suppressing voltage fluctuation. Hence, this paper initially establishes a two-layer voltage control model for the distribution network through priority target programming. The first layer employs the minimum voltage deviation as the objective function to meet the 10-0.38 kV voltage control requirements. The second layer minimizes the total operational cost of the distribution network, incorporating network loss costs as the objective function to meet economic operational requirements. The programming is subsequently implemented in GAMS. Lastly, the effectiveness of the proposed model is validated using the IEEE-33 node system.

关键词： multistage voltage distribution network power quality distributed energy priority goal programming

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Source-Load-Storage Coordinated Optimal Scheduling Model Considering Admissible Region of Net Load 6

Source-Load-Storage Coordinated Optimal Scheduling Model Con...

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6th Asia Energy and Electrical Engineering Symposium (AEEES)

作者： Sun, Fengbin Wang, Mingqiang Liang, Caishuai Zhang, Xia Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China Luyuan Elect Grp Co Ltd Jinan Peoples R China

ISBN: (纸本)9798350373486;9798350373479

With the increasing penetration of renewable energy, the urgent issue of maximizing the integration of renewable energy while meeting economy security and reliability requirements needs to be addressed. Based on the theory of admissible region, integrating models of renewable energy, energy storage systems, and demand response, this paper proposes a source-load-storage coordinated optimal scheduling model considering admissible region of net load. The model uses the generation-load transfer factors based on decoupled linearized power flow to construct power flow constraints, enabling coordinated optimization of active power, reactive power, and voltage in the power system. Uncertainty constraints in the model are transformed into deterministic constraints based on affine strategy, and the entire model is transformed into a bilinear programming model using duality theory and power circle linearization, facilitating solution using mature commercial solvers. Finally, the effectiveness and superiority of the model are verified on the IEEE-RTS system.

关键词： admissible region of net load affine strategy optimal scheduling model source-load-storage

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