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arXiv 2024年

作者： Limeng, Wang Shuo, Wang Na, Wang Yuze, Ma Yang, Li Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Ministry of Education Jilin132012 China

In order to improve energy utilization and reduce carbon emissions, this paper presents a comprehensive energy system economic operation strategy of Incineration power plant power-to-gas (P2G) with waste heat recovery. First, consider the coordinated operation of Incineration power plant - P2G, introduce the refined power-to-gas two-stage operation process, add Hydrogen fuel cells on the basis of traditional power-to-gas to reduce the energy ladder loss, and recycle the Methanation reaction heat;Secondly, in order to improve the energy utilization efficiency of Incineration, it is considered to install a waste heat recovery device containing a water source heat pump to recover the waste heat of flue gas and consume some electric energy, sourced from wind power, and add a CO2 separation device to combine the recovered CO2 with P2G to synthesize CH4 to achieve carbon recycling. Finally, within the framework of a tiered carbon trading mechanism an IES optimization model for electricity-heat with the goal of minimizing the system operating cost is constructed, and the GUROBI modeling optimization engine is used to solve this model. The results verify the effectiveness of the model. © 2024, CC BY-NC-ND.

关键词： Waste heat

Dual Nwp Wind Speed Correction Based on Trend Fusion and Fluctuation Clustering and its Application in Short-Term Wind power Prediction

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SSRN 2024年

作者： Yang, Mao Che, Runqi Yu, Xinnan Su, Xin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

Accurate wind power prediction (WPP) can effectively ensure the safe and stable operation of power system. At present, the main input of short-term power prediction based on data-driven model is numerical weather prediction (NWP), and its prediction accuracy leads to the failure to effectively improve the accuracy of short-term power prediction. To solve this problem, this paper proposes a dual NWP wind speed (WS) correction method based on trend fusion and fluctuation clustering. First, the WS trend is used to construct a new input feature. Secondly, the error is decomposed by Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and the trend and fluctuation components are defined by Pearson coefficient. The trend curve features in the short 24h period were extracted from two dimensions of time and value, and the trend and fluctuation curve databases under different scenarios were formed by K-Medoids clustering. Finally, the trend component is modified by the Attention-GRU model, and the corresponding trend component is searched and matched from the database to correct the fluctuation component. The NWP WS is modified by the superposition of the two components and the short-term WPP is made. And the prediction accuracy was improved by 10% and 13.1% respectively。 © 2024, The Authors. All rights reserved.

关键词： Wind speed

Dual Nwp Wind Speed Correction Based on Trend Fusion and Fluctuation Clustering and its Application in Short-Term Wind power Prediction

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SSRN 2024年

关键词： Wind speed

Coordinated control Strategy for Improving Frequency Stability of Lcc-Hvdc Sending-End system with Large-Scale Wind power

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SSRN 2024年

作者： Jiang, Shouqi Du, Yanli Li, Guoqing Xin, Yechun Wang, Lixin Wang, Weiru The Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China

To improve the frequency stability of the LCC-HVDC sending-end system with high penetration of wind power the system and achieve optimal utilization of frequency regulation resources, a cooperative control strategy involving wind power and LCC-HVDC in frequency regulation is proposed. Firstly, under a variety of scenarios, the power support requirements of LCC-HVDC sending-end system are analyzed according to the power regulation margin of various frequency regulation resources and the disturbance power, and a multi-time scale frequency regulation control strategy for DFIG based wind farms is proposed, which combines the advantages of variable speed control and variable pitch angel control. And a cooperative control strategy of DFIG and LCC-HVDC considering the frequency regulation deadband is proposed. Then, based on the maximum power regulation margin of synchronous generators and wind farms, the key control parameters of relative control links are designed to enable them autonomously adjust the active power according to various scenarios to involve in inertia response and primary frequency regulation task. Finally, the effectiveness of the control strategy is verified by the simulation model of LCC-HVDC sending-end system with large-scale wind power, which significantly improves frequency stability. © 2024, The Authors. All rights reserved.

关键词： Frequency stability

Techno-Economic of Electric-Hydrogen-Ammonia Coupling in Mul-Ti-Scenario:Analysis of Seven Major Regions in China

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SSRN 2024年

作者： Kong, Lingguo Jia, Zhonghua Shi, Zhenyu Liu, Chuang Cai, Guowei Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

This paper evaluates the techno-economic aspects of electric-hydrogen-ammonia coupling systems across China's seven major regions, aiming to provide strategic guidance for energy transition and carbon neutrality. The operation of each plant was simulated with 1-hour wind power data from each region, and a specific control strategy was introduced to control the energy flow, taking into account all the costs of the system, with the objective of minimizing the levelized cost of ammonia (LCOA), to analyze the economics and equipment configuration of wind-powered hydrogen synthesis ammonia plants in each region. It finds that the Northwest and Southwest regions, owing to their abundant wind resources and lower costs, are more suitable for establishing such facilities. The levelized prices of ammonia in these areas can reach RMB 6,844 per ton and RMB 6,663 per ton, respectively, indicating the potential for development of these plants. In contrast, the high costs of wind and grid electricity, along with fewer wind utilization hours in the South China region, lead to a levelized ammonia cost of RMB 11,215 per ton, suggesting the unsuitability of this region for developing the system. The results underscore the importance of selecting appropriate new energy technology pathways based on geographical and economic conditions, critical for optimizing the energy structure and achieving carbon neutrality goals. © 2024, The Authors. All rights reserved.

关键词： Ammonia

Optimization Method of Shared energy Storage Configuration on Source-Grid-Load Side of power system

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Optimization Method of Shared Energy Storage Configuration o...

2023 International Conference on power system technology, powerCon 2023

作者： Li, Cuiping Liu, Yang Zhang, Tianxun Zhao, Zhiqiang Liu, Haojun Zhu, Xingxu Li, Zhi An, Chenyu Li, Junhui Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin132012 China Beijing Technology and Business University Beijing China State Grid Hami Power Supply Company Xinjiang Uygur Autonomous Region Hami Hami839000 China

ISBN: (纸本)9798350300222

With the rise of the application of sharing economy in various fields of power system, As a typical application of shared economy in the field of energy storage, the optimal allocation of shared energy storage on the source-network-load side has been a great topic. The problem dealt with in this paper is the configuration result of the source-grid-load energy storage system under the same control strategy. This paper designs an optimization method for the source-network-load side configuration of generalized shared energy storage in regional power grid: Firstly, according to the extensional usage scenario and demand of energy storage, the alternative set of shared energy storage configuration is constructed. Secondly, based on the profit model of shared energy storage, a power system source-network-load optimization scheduling strategy is proposed. Finally, a numerical example is carried out to prove the feasibility and efficacy of the suggested method. © 2023 IEEE.

关键词： Profitability

Extraction and application of intrinsic predictable component in day-ahead power prediction for wind farm cluster

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energy 2025年 328卷

作者： Yang, Mao Jiang, Renxian Yu, Xinnan Wang, Bo Su, Xin Ma, Chenglian The 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 Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing100912 China

With the continuous updating and iteration of artificial intelligence algorithms, prediction models emerge one after another, but the research and utilization of the predictability of wind power is still less. Therefore, this paper proposed a day-ahead power prediction method for Wind Farm Cluster (WFC) based on intrinsic predictable component extraction. Firstly, based on the difference of power distribution between wind farm and WFC, a method of Wind power Curve (WPC) modeling for WFC is proposed, which provides the basis for establishing the Final Set of Wind power Curve (FSWPC). Secondly, the Intrinsic Predictable Component (IPC) of wind power is extracted based on the FSWPC, and the Interference Component (IC) of wind power is separated to eliminate the influence of IC on IPC in the process of prediction. Thirdly, the historical similarity matching method with large threshold is used to predict the IC to make up for the numerical deficiency of the IPC. Finally, the proposed method was applied to a WFC in China to verify its effectiveness. Compared with the traditional prediction strategy, the NRMSE, NMAE and MAPE are reduced by 1.59 %, 1.15 % and 6.42 %, respectively. © 2025 Elsevier Ltd

关键词： Iterative methods

Fault Diagnosis Method for DC Distribution Networks Based on Semitensor Product Bayesian Networks

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Fault Diagnosis Method for DC Distribution Networks Based on...

International Youth Scientific and Technical Conference on Relay Protection and Automation (RPA)

作者： He Wang Shiqiang Li Huanan Yu Jing Bian Bo Wei Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China

As distributed generators and new loads spread, grid operations have grown more complex, transitioning from AC to hybrid AC/DC and pure DC distribution grids [1] .

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Fault Location Method for Dc Distribution Network Based on Compressed Sensing Group Sparse Representation

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SSRN 2024年

作者： Wang, He Liu, Yiqi Li, Shiqiang Yu, Huanan Bian, Jing Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Ministry of Education Jilin Province Jilin132012 China

The common faults in a direct current (DC) distribution network consist of pole-to-pole faults and pole-to-ground faults. Under conditions of sparse configuration of measurement devices, existing fault location methods are unable to simultaneously locate pole-to-ground faults and pole-to-pole faults, and issues such as indistinct fault characteristics under the influence of transition resistance and noise are encountered. In response to these challenges, a fault location method for DC distribution networks is proposed based on compressed sensing group sparse representation. Firstly, the pole-to-mode transformation is utilized to convert the positive and negative pole electrical quantities of the DC distribution network into zero-mode and one-mode electrical quantities. Equivalent circuits for pole-to-ground faults and pole-to-pole faults are established separately, enhancing the fault characteristics corresponding to the two different short circuit faults. Secondly, the obtained impedance matrices for zero-mode and one-mode are constructed into a group sparse dictionary. By utilizing compressed sensing group sparse representation, the sparse current vector of high-frequency mode quantities is obtained, enabling the correct identification of fault types and accurate location of fault sections. Finally, a simulation model of the DC distribution network is built on the PSCAD platform to validate the effectiveness of the proposed fault location method. © 2024, The Authors. All rights reserved.

关键词： Electric power distribution

Emergency Direct Current power Support for High-Percentage renewable energy systems Based on Deep Reinforcement Learning

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SSRN 2024年

作者： Sun, Zhenglong Zhuang, Junzhi Chao, Pan Chao, Jiang Cai, Guowei The Department of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

As a low-cost emergency frequency control method, emergency direct current power support (EPS) is crucial for frequency stabilization of alternating current (AC)–direct current (DC) hybrid systems. In the context of highly integrated renewable energy sources, the uncertainty of AC-DC hybrid systems increases and the inertia decreases during the transition process, and the existing EPS methods face prominent adaptation and mismatch problems in meeting the frequency restoration requirements. To fill this gap, this study proposes a deep reinforcement learning (DRL)-based EPS frequency control method. The EPS decision is transformed into a Markov decision process (MDP) and solved using the proximal policy optimization (PPO) algorithm. This paper designs a DRL reward function for EPS while taking into account the EPS line overload and phase change failure problems. In order to solve the contradiction between limited observation and global safety, this paper designs a data characterization method based on mechanism fusion. Meanwhile, this paper develops an open-source power system simulation platform with DRL control function by using Python and the power system simulation software DIgSILENT/powerFactory to realize the EPS frequency stabilization decision based on DRL control. Through a case study of the IEEE 39-bus system and a real power system in Northwest China, it is verified that the proposed DRL-based EPS agent is able to quickly, accurately, and securely restore the frequency and reduce the frequency oscillations while considering the security constraints. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning