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Ultra-Short-Term Wind power Interval Prediction Based on Fluctuating Process Partitioning and Quantile Regression Forest

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FRONTIERS IN energy RESEARCH 2022年 10卷

作者： Sun, Yong Huang, Yutong Yang, Mao Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Grid Jilin Electric Power Company Ltd. Changchun China

As errors in point forecasts of wind power are unavoidable, interval forecasts can adequately describe the uncertainty in wind power and thus provide further guidance to dispatchers in their decision making. Current interval prediction methods are still incomplete in terms of tapping into the physical variability of wind power, especially for the specific time scale of the ultra-short term. This paper therefore proposes a new framework for interval forecasting of ultra-short-term wind power that incorporates the power fluctuation process. Firstly, a fluctuating process of wind power series is defined and a Kalman-SOM method for clustering the fluctuating processes of wind power is constructed. Secondly, a quantile regression forest interval prediction model is constructed for multiple fluctuation processes for ultra-short-term time scales. Finally, the effectiveness of the overall framework is validated at a wind farm in Jilin Province, China. Compared with the traditional interval prediction method. The interval bandwidth is reduced by 0.86% on average, and the interval coverage is increased by 1.4% on average. The results demonstrate the effectiveness and feasibility of the method in this paper.

关键词： wind power ultra-short-term prediction self-organizing map fluctuation quantile regression forest

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Pre-configuration Method and Scheduling Strategy of Distribution Network Mobile energy Storage Vehicle Considering Intermittent Load of Rural Network

Pre-configuration Method and Scheduling Strategy of Distribu...

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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Lu, Xiaoming Yao, Yiwen Xin, Yechen Wang, Dingheng Wang, Xinhong Xu, Xin Li, Hao State Grid Jilin Electric Power Co. Ltd Economic and Technological Research Institute Changchun China Ministry of Education Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin China State Grid Jilin Electric Power Co. Ltd Changchun China

ISBN: (纸本)9798331527624

Aiming at the problem of heavy overload in the distribution station area during the peak period of energy consumption caused by intermittent loads such as agricultural motor wells, the mobile energy storage technology is considered to meet the agricultural power demand, and a two-stage mobile energy storage vehicle pre configuration and dynamic adjustment strategy of "Rural busy power energization"and "rural idle distributed energy storage"is proposed, taking into account the guarantee of load power demand and the efficiency and economy of energy storage. Firstly, the mathematical model of agricultural motor well load considering the time shift characteristics and the mobile energy storage vehicle model considering the power supply time constraint are established;Secondly, a multi-stage mobile energy storage configuration and scheduling strategy is established. In the Rural busy power generation stage, the mobile energy storage vehicle capacity is configured with the minimum daily power supply cost as the goal, and the power supply path is optimized with the highest charge state consistency at the completion of power supply as the goal;At the stage of distributed energy storage in rural slack, the collaborative optimization of mobile energy storage vehicles participating in multi scenario power services is carried out with the goal of maximizing the annual net income. Finally, the proposed two-stage strategy has certain economic benefits under the premise of meeting the power demand of the load, which is verified by combining the power consumption data of wells in Jilin Province and IEEE 33 bus system simulation. © 2024 IEEE.

关键词： Charge storage

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Optimization control Strategy of Pumped Storage power Station Considering Cost Allocation

Optimization Control Strategy of Pumped Storage Power Statio...

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2023 International Conference on power system technology, powerCon 2023

作者： Yan, Jun Song, Qinglong Guo, Qi Xin, Lijian Meng, Fancheng Yu, Shuo Zhou, Jiaxu Li, Cuiping Li, Junhui Co. Ltd. Hohhot China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin China Co. Ltd. Power Dispatching and Control Branch Hohhot China Co. Ltd. Inner Mongolia Electric Power Research Institute Branch Hohhot China

ISBN: (纸本)9798350300222

Against the backdrop of the increasing proportion of new energy generation, pumped storage, as the main energy storage method, face problems of low utilization and poor economic benefits. To improve the enthusiasm and overall efficiency of pumped storage power stations, this article proposes an optimized control strategy for pumped storage power stations that takes into account cost sharing. This strategy combines the PSS allocation system operation rules and control strategies to improve the utilization of PSS capacity by expanding its application scenario range, and to increase its enthusiasm for extraction by increasing rental income;This article takes a regional power grid in northwest China as an example for analysis, and the results show that the proposed strategy can effectively improve the utilization level and economic benefits of PSS. © 2023 IEEE.

关键词： Cost effectiveness

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Multi-Timescale Risk Scheduling for Transmission and Distribution Networks for Highly Proportional Distributed energy Access

SSRN

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SSRN 2023年

作者： Wang, He Liu, Ziyue Bian, Jing Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

With the incorporation of more renewable energy sources, distribution networks are shifting from passive to active. The enhanced coupling of transmission and distribution networks is enhanced and bidirectional tides affect the reliable and secure operation of such networks. This paper proposes a multi-timescale risk dispatch study for transmission and distribution networks that have a high proportion of distributed energy access to meet the rising demand for coupling between the two types of networks. First, a day-ahead scheduling model that takes into account various operational risks is developed with the goal of minimizing total operating costs, and it optimizes the source network load and storage of multiple adjustable resources of the transmission network and distribution network jointly under the risk limit constraint. Second, an intraday scheduling model is built with the goal of minimizing the overall risk value of the transmission network and distribution network, and the day-ahead scheduling plan is modified to realize this, considering the magnitude of different operational risk values of the transmission network and distribution network. Finally, the effectiveness of the proposed multi-time-scale risk dispatch model is verified through the analysis of arithmetic cases, and it is proved that the model can enable the interaction and coordination between transmission and distribution networks as well as the synergistic optimization of operating costs and operating risks. © 2023, The Authors. All rights reserved.

关键词： Electric power transmission networks

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Multi-objective Optimal Allocation Strategy for Distributed energy Storage in Distribution Networks Adapted to High Penetration Distributed Photovoltaics 9

Multi-objective Optimal Allocation Strategy for Distributed ...

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9th Asia Conference on power and Electrical Engineering, ACPEE 2024

作者： Li, Cuiping Wang, Yanli Chen, Yiming Qi, Xuesong Liu, Yunjing Fang, Qian Cui, Shengyuan Wang, Yuming Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin China State Grid Shanghai South Power Supply Company Science and Technology Section Shanghai China Jilin Power Supply Company Power Dispatching and Control Center Jilin China Jilin Power Supply Company Science and Technology Section Jilin China Jilin Power Supply Company Ministry of Science and Technology Jilin China

ISBN: (纸本)9798350309638

High percentage of photovoltaic gain connect to the wire line, so that the electricity grid from power distribution of the receiving end of the network into a set of production, storage, distribution of multi-source complex new network, the distribution network security operation and new energy consumption pressure increases. In response to the above, this paper puts forward the distributed ES multi-objective optimization configuration strategy of distribution network adapted to the high penetration rate distributed PV. And through a county power grid practical example to certify that the ES configuration approach proposed can effectively mitigate the impact of a high proportion of PV accessed, and it can reduce the abandonment of light. © 2024 IEEE.

关键词： Electric power distribution

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Coordination of Electricity and Heat Dispatch Strategy Combining Carbon Trading and Peak Shaving Compensation Mechanism

Coordination of Electricity and Heat Dispatch Strategy Combi...

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2020 International Conference on Electronic, Electrical and Computer Applications, ICEECA 2020

作者： Ge, Weichun Li, Zhao Zhao, Dong Li, Zhenyu Ye, Qing Fu, Yu Yu, Na State Grid Liaoning Province Electric Power Company Limited Shenyang110006 China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Fuxin Power Supply Company of Liaoning Electric Power Co. Ltd Liaoning Fuxin123000 China

Integrated power generation group's participation in the carbon trading market and peaking auxiliary service market is one of the effective ways to promote low carbon power development and wind power consumption. Aiming at the serious problem of wind abandonment during the low temperature period of winter heating period in Northeast China, a multi-market mechanism is proposed. The carbon trading is analysed. Firstly, and the regional peak demand optimization model based on multi-scenario stochastic programming and the maximum wind power acceptance power calculation model of regional power grid is constructed to calculate the peak shaving demand and existing peak shaving in each period of the regional power grid. Maximum wind power acceptance under resources;Based on the coordination of carbon quotas among power generation groups and the subsection compensation mechanism of compensated peak shaving costs, and aiming at the minimum sum of total coal consumption costs, wind abandonment penalties and compensation costs, integrated dispatching model considering carbon trading and peak shaving compensation is established. Finally, an example is given to verify the rationality and effectiveness of the proposed strategy. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Wind power

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Strategic Optimization and Demand Response for Thermal Load Management in Multi-Regional Integrated energy systems: A Stackelberg Game Approach

arXiv

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arXiv 2024年

作者： Yang, Ranran Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Ministry of Education Jilin132012 China

In the context of high fossil fuel consumption and inefficiency within China's energy systems, effective demand-side management is essential. This study examines the thermal characteristics of various building types across different functional areas, utilizing the concept of body coefficient to integrate their unique structural and energy use traits into a demand response framework supported by real-time pricing. We developed a Stackelberg game-based bi-level optimization model that captures the dynamic interplay of costs and benefits between integrated energy providers and users. This model is formulated into a Mixed Integer Linear Programming (MILP) problem using Karush-Kuhn-Tucker (KKT) conditions and linearized with the Big M method, subsequently solved using MATLAB and CPLEX. This approach enables distinctive management of heating loads in public and residential areas, optimizing energy efficiency while balancing the interests of both providers and users. Furthermore, the study explores how the proportion of different area types affects the potential for reducing heat loads, providing insights into the scalability and effectiveness of demand response strategies in integrated energy systems. This analysis not only highlights the economic benefits of such strategies but also their potential in reducing dependency on traditional energy sources, thus contributing to more sustainable energy system practices. © 2024, CC BY-NC-ND.

关键词： Demand response

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Fault Location Method of Dc Distribution Network Based on Multivariate Information Fusion

SSRN

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SSRN 2023年

作者： Wang, He Zhang, Zekun Yu, Huanan Li, Shiqiang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

The accuracy of Direct Current (DC) distribution network fault location for a single electrical or switching quantity fault information is difficult to meet the requirements. This paper proposes a fault location method of DC distribution network based on multivariate information fusion. Firstly, the compressed sensing algorithm is used to reconstruct the fault transient electrical data to obtain the sparse characteristics of the high-frequency fault current. Secondly, the Bayesian network is established to obtain the fault probability of the faulty component based on the protection action inf0ormation generated by the faulty component, and then the sparse fault characteristics and fault probability of the fault current are normalized to obtain the fault degree of the electrical quantity and switching quantity. Finally, the traditional Dempster Shafer (DS) evidence theory fusion algorithm is improved to solve the problem of conflict of uncertain subsets by weight allocation method, and then the fault degree of electrical quantity and switching quantity is fused by combining Bayesian estimation method and weighting method, so as to achieve accurate fault location. simulation experiments conducted using MATLAB software demonstrate that the proposed method can effectively reduce the evidence conflict at the fault point, and the fault location accuracy is improved by 2% to 4% compared with the traditional DS evidence theory, which has a good engineering application prospect for the fault location of DC distribution network. © 2023, The Authors. All rights reserved.

关键词： Bayesian networks

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Ultra-Short-Term Prediction of Wind power Based on Chaos Theory and ABC Optimized RBF Neural Network

Ultra-Short-Term Prediction of Wind Power Based on Chaos The...

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China International Electrical and energy Conference (CIEEC)

作者： Yang Cui Shi Yan Huiquan Zhang Siyu Huang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Ji Lin China

ISBN: (数字)9781728116754

ISBN: (纸本)9781728116761

Wind energy has strong randomness and volatility, which makes the prediction accuracy of wind power low. In an attempt to improve the accuracy and robustness of ultra-short term prediction of wind power, a wind power prediction method in ultra-short term combining chaos theory and artificial bee colony(ABC) algorithm to optimize RBF neural network is studied in this paper. Firstly, based on chaos theory, the historical wind power data with the highest correlation is found, which is used for RBF neural network training after phase space reconstruction. Then, the artificial bee colony algorithm is used to solve the optimal RBF neural network parameters through multiple iterations to construct the optimized neural network model. Finally, considering the uncertainty of the prediction model and data noise, the prediction results are interval, and the robustness of the prediction results is evaluated by calculating the confidence of the corresponding interval. The results of the example show that the method proposed in this paper has good accuracy and robustness.

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power grid frequency regulation participated by photovoltaic generation to adapt to different control modes of grid-side AGC

Power grid frequency regulation participated by photovoltaic...

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8th renewable power Generation Conference (RPG 2019)

作者： Gangui Yan Wenbo Hu Qi Jia Dan Wang Guoqing Zhou Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

Large-scale grid-connection of photovoltaic (PV) generation causes the power system to face the problem of insufficient inertia and insufficient frequency modulation capability. One of the important means to solve this problem is to take part in grid frequency regulation actively. On the basis of spare certain active power, this paper puts forward the active power-frequency droop control strategy. By modifying the original control structure of the inverter, PV generation actively takes part in the grid frequency primary regulation. In order to achieve non-error adjustment of frequency, this paper further proposes a secondary frequency regulation control strategy that adapts to different grid-side AGC control modes (constant frequency control mode, constant tie line power control mode and tie line power frequency deviation control mode). The effectiveness and feasibility of the control strategies are verified based on the PSCAD/EMTDC simulation platform.

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