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Online Optimization to Suppress the Grid-Injected power Deviation of Wind Farms with Battery-Hydrogen Hybrid Energy Storage systems

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Energy Engineering 2025年第4期122卷 1403-1424页

作者： Min Liu Qiliang Wu Zhixin Li Bo Zhao Leiqi Zhang Junhui Li Xingxu Zhu State Grid Zhejiang Electric Power Co. Ltd.Electric Power Research InstituteHangzhou310014China Key Laboratory of Modern Power System Simulation Control and Green Power New Technology of the Ministry of Education Northeast Electric Power UniversityJilin132012China

To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is ***,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage ***,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and ***,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is *** study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable *** storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.

关键词： Battery-hydrogen hybrid energy storage systems grid-injected power deviations measurement feedback online optimization energy states

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Monthly Reduced Time-Period Scheduling of Thermal Generators and Energy Storage Considering Daily Minimum Chargeable Energy of Energy Storage

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Energy Engineering 2025年第4期122卷 1469-1489页

作者： Xingxu Zhu Shiye Wang Gangui Yan Junhui Li Hongda Dong Chenggang Li Key Laboratory of Modern Power System Simulation Control and Green Power New Technology of the Ministry of Education Northeast Electric Power UniversityJilin132012China State Grid Jilin Electric Power Co. Ltd.Electric Power Science Research InstituteJilin130021China

To address the excessive complexity of monthly scheduling and the impact of uncertain net load on the chargeable energy of storage,a reduced time-period monthly scheduling model for thermal generators and energy storage,incorporating daily minimum chargeable energy constraints,was ***,considering the variations in the frequency of unit start-ups and shutdowns under different levels of net load fluctuation,a method was proposed to reduce decision time periods for unit start-up and shut-down *** approach,based on the characteristics of net load fluctuations,minimizes the decision variables of units,thereby simplifying the monthly ***,the relationship between energy storage charging and discharging power,net load,and the total maximum/minimum output of units was *** on this,daily minimum chargeable energy constraints were established to ensure the energy storage system meets charging requirements under extreme net load ***,taking into account the operational costs of thermal generators and energy storage,load loss costs,and operational constraints,the reduced time-period monthly schedulingmodel was *** studies demonstrate that the proposedmethod effectively generates economical monthly operation plans for thermal generators and energy storage,significantly reduces model solution time,and satisfies the charging requirements of energy storage under extreme net load conditions.

关键词： Monthly scheduling thermal generators energy storage daily minimum chargeable energy decision time-period reduction unit start-up and shut-down unit commitment renewable energy

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Evaluation of Regulating Capacity of power system Nodes and Transmission Lines

Evaluation of Regulating Capacity of Power System Nodes and ...

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Smart Grid and Artificial Intelligence (SGAI), International Conference on

作者： Xiuyu Yang Zekun Fan Almasbek Shakenbek Baoyu Di Chongbi Li Yi Wang Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology of Ministry of Education Northeasst Electric Power University Jilin China State Grid Xinjiang Electric Power Co. Ltd. State Grid Xinjiang Electric Power Co. Ltd. Electric Power Research Institute Urumqi China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

The large-scale access of renewable energy to the power grid leads to a sharp increase in the demand for power system regulation capacity. In order to solve this problem, this paper explores the mechanism of supply and demand balance of power system regulation capacity, analyzes the transmission characteristics of regulation capacity, and proposes the adequacy index of node regulation capacity and the adequacy index of network transmission regulation capacity. The Garver-6 node system is used to verify the effectiveness and practicability of the proposed method. The example shows that the proposed evaluation method can accurately identify the weak links of regulation ability and clarify the causes of insufficient regulation ability.

关键词： Renewable energy sources Supply and demand power transmission lines Evaluation models Regulation Smart grids Planning Artificial intelligence Load flow Capacity planning

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Fuzzy optimal scheduling of hydrogen-integrated energy systems with uncertainties of renewable generation considering hydrogen equipment under multiple conditions

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Applied Energy 2025年 393卷

作者： Song, Jianzhao Wang, Na Zhang, Zhong Wu, Hao Ding, Yi Pan, Qingze Pan, Xingzuo Shui, Siyuan Chen, Haipeng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Department of Electrical Engineering Northeast Electric Power University Jilin132012 China Gansu Branch of Luneng New Energy Group Co. Ltd. Lanzhou730000 China Lanzhou Power Supply Company State Grid Gansu Electric Power Co. Ltd. Lanzhou730000 China TBEA Shenyang Transformer Group Co. Ltd. Shenyang110144 China Northeast Electric Power University Jilin132012 China

Developing hydrogen-integrated energy systems (HIES) represents a cutting-edge strategy for harnessing renewable energy (RE). However, the inherent unpredictability and variability of RE significantly increase the operational uncertainty of HIES, which leads to severe energy curtailment issues when HIES integrates large-scale RE, necessitating greater operational flexibility in the system. To address the challenges, this paper proposes a fuzzy optimal scheduling approach for HIES that considers the hydrogen equipment under multiple operating conditions. The analysis begins by examining the operational mechanisms of hydrogen equipment. Subsequently, a multi-conditions model is developed for electrolyzers, while a reserve model is established for hydrogen fuel cells. Furthermore, the fuzzy chance constraint (FCC) is employed to quantify the uncertainty of RE generation. An integrated demand response mechanism is implemented, incorporating human thermal comfort and building thermal inertia. Finally, a fuzzy optimization scheduling model for HIES is constructed to minimize the total operating costs. The crisp equivalent of FCC is derived to solve this model, thereby transforming the scheduling model based on fuzzy chance-constrained programming into a solvable mixed-integer programming model. The simulation results indicate that the proposed scheduling method can reduce the overall costs of the HIES by 17.98 % and increase the RE accommodation rate by 19.67 %, validating the effectiveness of the method in enhancing the operational flexibility of the HIES. In addition, this study achieves a balance between economic efficiency and reliability, offering a better economy, lower energy curtailment rates, and faster decision-making times compared to robust optimization, scenario analysis, and other common fuzzy optimization methods. © 2025

关键词： Risk perception

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Dynamic Behavior of Suspended Bubbles in Insulating Oil Correlation with Flow Field Distribution 4th

Dynamic Behavior of Suspended Bubbles in Insulating Oil Corr...

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4th International Symposium on Insulation and Discharge Computation for power Equipment, IDCOMPU 2023

作者： Zhang, Ning Hao, Jian Liu, Shili Zhang, Junyi Chen, Houhe Liao, Ruijin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400044 China

ISBN: (纸本)9789819974122

In recent years, arcing faults inside large oil-immersed power transformers have been frequent. Suspended bubbles, as the main product of high temperature, high humidity, material aging and cracking gas production inside transformers, are one of the main causes of arcing inside transformers. However, due to the complex structure of the oil channel and the large fluctuation of the internal flow field distribution, the resulting bubble morphology evolution and movement law is not clear. In this paper, the influence of the initial position of bubbles and the relative position between bubbles on the flow field distribution is fully considered, and the dynamic behavior of suspended bubbles in oil under two fluid forms of natural oil circulation and forced oil circulation is simulated and studied by combining laminar and turbulent flow models and bubble force control equations, and the correlation mechanism between suspended bubbles and flow field distribution characteristics is analyzed. The simulation results show that the flow field in the laminar state affects the bubble aggregation and trajectory, while the turbulent state affects the bubble distortion and motion time, and a reasonable model in the simulation of bubble dynamic behavior is more beneficial to improve the simulation accuracy. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Flow fields

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Analysis of the influence of wind farms in full operating conditions on the torsional vibration of the shaft system of synchronous generators

Analysis of the influence of wind farms in full operating co...

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2021 International Conference on power system technology, powerCON 2021

作者： Jia, Qi Zhai, Wenchao Zhang, Qiang Sun, Feng Shen, Mohan Research Institute State Grid Liaoning Electric Power Shenyang China Northeast Electric Power University Min. of Educ. Key Laboratory of Modern Power System Simulation Control and Green Power Technology Jilin China

ISBN: (纸本)9781665407373

The power oscillation induced by the large-scale integration of wind power into the power grid has become one of the important issues affecting the safe and stable operation of the power grid. Aiming at the dynamic interaction between wind farms and synchronous generators, based on the additional excitation signal injection method, the influence of DFIG and PMSG wind farms on the damping characteristics of each torsional vibration mode of synchronous generators under full operating conditions is analyzed. By applying an AC voltage signal at both ends of the field winding to stimulate rotational speed oscillation, observe the difference in the free response characteristics of rotational speed disturbances, identify the electromechanical coupling characteristics between the wind farm and the synchronous generator set, and reveal the influence of the wind farm type and operating conditions on the shaft system of the synchronous generator set. The mechanism of torsional vibration. Finally, the validity of the theoretical analysis is verified based on time-domain simulation. © 2021 IEEE.

关键词： Synchronous generators

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Coordinated optimal configuration scheme of wind-solar ratio and energy storage considering wind-solar complementary characteristics 6

Coordinated optimal configuration scheme of wind-solar ratio...

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6th International Conference on Energy, power and Grid, ICEPG 2024

作者： Yang, Xiuyu Li, Zhiwen Peng, Jian Miu, Gang Yuan, Shaowei Zhu, Zhengyin Northeasst Electric Power University Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology Ministry of Education Jilin China State Grid Xinjiang Power Supply Company State Grid Urumqi Power Supply Company Urumqi City China

ISBN: (纸本)9798350377798

This study proposes a collaborative optimization configuration scheme of wind-solar ratio and energy storage based on the complementary characteristics of wind and light. On the premise of maintaining the stability of the wind-solar hybrid power generation system, the optimal allocation model of wind-solar ratio and energy storage considering the complementary characteristics of wind-solar is established with the minimum total cost of planning. At the same time, three indicators of power fluctuation index, wind-solar permeability and new energy abandonment rate are proposed to evaluate the scheme. © 2024 IEEE.

关键词： Windmill

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A Bi-Level Real-Time Dispatch Strategy for Large-Scale Electric Vehicles into Smart Grid Based on an Improved Rolling Horizon Method

SSRN

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SSRN 2024年

作者： Wang, He Wang, Yao Bian, Jing Li, Guoqing Key Laboratory of Modern Power System Simulation and Control and New Green Electricity Technology Ministry of Education Northeast Electric Power University Jilin132012 China

The flexible energy storage characteristics of Electric vehicles (EVs) make them an important target for grid demand response. However, in the context of large-scale EVs into the grid, an important challenge currently is how to improve the accuracy of the V2G activity while taking into account the interests of both EVs and the grid. To address this problem, this paper proposes a bi-level real-time dispatch strategy based on an improved rolling horizon method (RHM). In the upper-level strategy, the relation between electricity price and power grid energy regulation demand is established by introducing a fixed base elasticity coefficient. An algorithm process is designed to find the relationship between the real-time price and the EVs load to be scheduled, to solve a real-time price that can maximize the income of the grid. In the lower-level strategy, the C&D schedule is developed for each EV to minimize the user cost, and the temporal scheduling constraint is ensured by grouping as well as parallel computing. simulation results show that the proposed real-time strategy effectively improves the accuracy of the V2G activity and increases profits for the grid and EVs. © 2024, The Authors. All rights reserved.

关键词： Vehicle-to-grid

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A Real-Time Charging and Discharging Scheduling Strategy for Large-Scale Electric Vehicles into Smart Grid Considering the Economic Benefits of Both Vehicle Owners and the Grid

SSRN

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SSRN 2024年

作者： Wang, He Wang, Yao Bian, Jing Li, Guoqing Key Laboratory of Modern Power System Simulation and Control and New Green Electricity Technology The Ministry of Education Northeast Electric Power University Jilin132012 China

The flexible energy storage characteristics of Electric vehicles (EVs) make them an important target for grid demand response. However, in the context of integrating large-scale EVs into the grid, a significant challenge is to improve the accuracy of the guided charging and discharging (C&D) schedule for grid energy regulation while considering the economic implications for both EV owners and the grid. To address this problem, this paper proposes a bi-level real-time dispatch strategy based on an improved rolling horizon method (RHM). In the upper-level real-time pricing optimization strategy, the relation between electricity price and power grid energy regulation demand is established by introducing a fixed base elasticity coefficient. To solve a real-time price that can maximize the income of the grid, an algorithm process is designed to find the relationship between the real-time price and the load of to-be-scheduled-EVs (TSEVs). In the lower-level EV C&D load optimization strategy, an adaptive variable horizon scale (AVHS)-RHM is proposed to enhance the correction effect of the RHM. Additionally, the temporal scheduling constraint (TSC) of real-time dispatching is ensured through grouping and parallel computing. simulation results indicate that the proposed real-time dispatch strategy, compared to the commonly used time-of-use (TOU) pricing, reduces the maximum peak-valley load differences by 17.6% and the standard deviation by 6.9%. This effectively enhances the accuracy of EVs' participation in grid energy regulation and provides a viable solution to fully utilize EVs as part of flexible resources. © 2024, The Authors. All rights reserved.

关键词： Electric vehicles

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A Hybrid Model for Building-level Day Ahead power Load Forecasting Based on Gated Recurrent Unit Networks

A Hybrid Model for Building-level Day Ahead Power Load Forec...

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2021 IEEE Sustainable power and Energy Conference, iSPEC 2021

作者： Zhang, Hualu Deng, Boya Shi, Jie Northeast Electric Power University Jilin Key Laboratory of Modern Power System Simulation Control and Green Power New Technology Ministry of Education Jilin China Nanjing Nanrui Information Communication Technology Co. Ltd. Nari Group Corporation State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9781665414395

Accurate forecasting of day-ahead electrical load is a key to optimize the operation of the integrated energy system (IES) and a fundamental function of the cyber-physical system (CPS) of IES. Due to the characteristics of different features, data collected by CPS often have different sampling frequencies, resulting in mining data trends inadequately when making a load forecast. This paper proposes an GRU-based model to combine historical data with different sampling frequencies in forecasting day-ahead building-level load. First, day-level features are clustered by K-means. Hour-levels features are then partitioned according to clustering results and inputted separately into a gated recurrent unit (GRU) based neural network to capture relationships between external features and load fluctuations. The temporal dependencies of minute-level data are captured by the GRU network directly without any external features. Finally, the least square method is used to combine forecasting results at each hour of two models. The simulation results present that the proposed model performs better than a single model when applying to real-world data. © 2021 IEEE.

关键词： Forecasting

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