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Optimal multi-time scale coordination method for electricity-heating integrated energy system scheduling

IOP Conference Series: Earth and Environmental Science 2021年第1期645卷

作者： Zhuoran Lin Shouxiang Wang Shaomin Wang Aoyang Han Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin 300072 China Tianjin Key Laboratory of Power System Simulation and Control Tianjin University Tianjin 300072 China State Grid Qingdao Electric Supply Company Qingdao Shandong 266000 China

Considering that different energy subsystems have different control characteristics in equipment operations, an optimal multi-time scale coordination method for electricity-heating integrated system scheduling is proposed. It merges three optimal scheduling models based on three-time scales of day-ahead, rolling, and real-time. The coordinated optimization of electricity and heating energies with the same dispatch instruction is fulfilled in day-ahead scheduling. And all feasible scheduling instruction cycles are traversed in the rolling stage to improve the stability of system economic operation. The calculation examples show that the proposed overall strategy for multi-time scale scheduling can achieve multi-energy complementarity, and the optimization results have less deviation from the actual load.

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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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A novel frequency regulation control strategy based on the external characteristics of PV generation

A novel frequency regulation control strategy based on the e...

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8th Renewable power Generation Conference (RPG 2019)

作者： Gangui Yan Dan Wang Qi Jia Wenbo Hu 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-connected PV generation results in the power system facing with the problem of reduced inertia and inadequate frequency regulation capability, which is urgent for PV generation to take participate in frequency regulation. In this paper, the research object is the double-stage PV generation, a novel frequency regulation control strategy based on the external characteristics of PV generation is proposed. f-U PV compensation is introduced into DC low-voltage control loop, which makes the DC low-voltage vary with the grid frequency, thus controlling the output power of PV generation. The influence mechanism of the control strategy on the frequency dynamic process of power system is also analysed based on the frequency response model (SFR). The results show that: the larger the ΔU PV generated by the f-U PV compensation unit, the more power of PV generation can be generated; the control strategy essentially affects the damping coefficient of the system, which not only affects the transient process of the system frequency, but also the steady-state frequency deviation.

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A Review on Virtual power Plants Interactive Resource Characteristics and Scheduling Optimization 3

A Review on Virtual Power Plants Interactive Resource Charac...

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3rd IEEE Conference on Energy Internet and Energy system Integration, EI2 2019

作者： Cheng, Lin Zhou, Xuyan Yun, Qiuchen Tian, Liting Wang, Xuanyuan Liu, Zhen Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Beijing China Beijing Jiaotong University Center of Electrical Laboratories and National Teching Center of Electrotechnics and Electronics Beijing China State Grid Jibei Electric Power Company Jibei Electric Power Company Power Exchange Center Beijing China State Grid Jibei Electric Power Company North China Electric Power Research Institute Beijing China

ISBN: (纸本)9781728131375

With a high penetration of distributed energy resources (DER) connected to the power grid, the reliability and safety of the power grid compromised by the uncertainty of energy output. Many utilities adopted strategies to abandon excessive wind and solar energy generation to ensure reliable operations of the power grid. The virtual power plant (VPP) is a way of aggregating various types of energy resources and optimizing resources utilization. It participates in the electricity market and improves the utilization of energy resources within the VPP. VPP provides services such as peak shaving, frequency regulation, and emergency power support for the power grid. It intends to prevent the negative impact caused by the uncertainty of power generation of the distributed energy resources. In this paper, three kinds of typical VPP interactive resource are introduced, which differ in characteristics, control modes, and output characteristics. In addition, the VPP achieves improved energy efficiency through rational optimized resource allocation and optimized scheduling, including internal and external scheduling optimization. © 2019 IEEE.

关键词： Virtual power Plants

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A Statistical Upscaling Approach of Region Wind power Forecasting Based on Combination Model

A Statistical Upscaling Approach of Region Wind Power Foreca...

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IEEE Student Conference on Electric Machines and systems

作者： Tingting Ding Peng Li Guilin Huang Yixiao Yu Zhiyuan Si Fangqing Yan Xiaoyi Liu Menglin Li Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan China Electrical and Electronic Engineering Imperial College London London England Laiwu Electric Power Supply Company of State Grid Shandong Electric Power Company Laiwu China State Grid of China Technology College Jinan China

ISBN: (数字)9781728156224

ISBN: (纸本)9781728156231

Regional wind power forecasting is of great significance to ensure the wind power absorption and power grid safety economy. This paper proposes a regional wind power statistical upscaling forecasting method based on the combination model to improve the forecasting accuracy of the region wind power. The K-means clustering algorithm is used to divide the region, the forecasting accuracy of the wind farms, and the correlation coefficient between wind farms and sub-regions are used to select the reference wind farms in each sub-region. The BP neural network quantile regression model is used to forecast the wind power of the reference wind farm. Based on the prediction results of reference wind farms, the combined model formed by the beta distribution estimation, kernel density estimation, and sparse Bayesian learning is used to forecast the wind power of the sub-region. The region power forecasting results can be obtained by adding the forecasting results of the sub-regions. Case studies verify the effectiveness of the method proposed in this paper.

关键词： Estimation Wind power generation Wind farms Predictive models Data models Forecasting Wind forecasting

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A Nonnegativity-Constraint Sparse Stacked Denoising Autoencoder for Anomaly Detection in Electric power Communication Network

A Nonnegativity-Constraint Sparse Stacked Denoising Autoenco...

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IEEE International Symposium on Broadband Multimedia systems and Broadcasting (BMSB)

作者： Zhuo Tao Yong Yan Yang Yang Yuanyuan Wang Jiang Luo State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China State Grid Zhejiang Electric Power Company LTD Zhejiang China Science and Technology on Information System Engineering Laboratory Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (数字)9781728157849

ISBN: (纸本)9781728157856

As the scale of the electric power communication network is getting larger and larger, network security issues are becoming more and more complex. as an effective protection method, network traffic anomaly detection can provide important technical support for network situation awareness. In some cases, plenty of labeled data are unavailable, which may lead to low detection accuracy. To deal with this problem, a nonnegativity-constraint sparse stacked denoising autoencoder(NSSDAE) is proposed. Meanwhile, we propose a method called dynamic parameter freezing(DPF) for parameter transfer, which allows to find the best performance that may exist between the freezing and fine-tuning within a layer by adjusting the variable alpha. And discriminative joint probability maximum mean discrepancy is introduced for distribution adaptation. The results for NSL-KDD show that the proposed NSSDAE-TL algorithm is effective.

关键词： Noise reduction Telecommunication traffic power systems Communication networks Security Multimedia communication Anomaly detection

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Nonlinearity Characteristic of High Impedance Fault at Resonant Distribution Networks: Theoretical Basis to Identify the Faulty Feeder

arXiv

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arXiv 2020年

作者： Wei, Mingjie Zhang, Hengxu Shi, Fang Chen, Weijiang Terzija, Vladmir Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan250061 China State Grid Corporation of China China School of Electrical and Electronic Engineering University of Manchester United Kingdom

Feeder identification is indispensable for distribution networks to locate faults at a specific feeder, especially when measuring devices are insufficient to locate faults more precisely. For the high impedance fault (HIF), the feeder identification is much more challengeable and related approaches are still in the early stage. This paper thoroughly reveals the nonlinearity characteristics of different feeders when a HIF happens at a three-wire system that is with the resonant grounded neutral (RGN). Firstly, the diversity of nonlinearity existing in HIFs is explained from the perspective of energy. Then, the nonlinearity of zero-sequence current that differs between healthy and faulty feeders are deduced theoretically. Effects of the detuning index of Petersen coil, the damping ratio of system, and the length of feeder are all considered. Afterward, these theoretical conclusions are verified by the HIF cases experimented in a real 10kV system. Finally, after indicating the problems of a classic phase-relationship-based algorithm, we suggest an improved method based on the phase differences between the harmonic currents of different feeders. The effectiveness of the method has been verified. © 2020, CC BY.

关键词： Feeding

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Early Warning Method for power Station Auxiliary Failure Considering Large-Scale Operating Conditions 2

Early Warning Method for Power Station Auxiliary Failure Con...

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2nd IEEE International Conference on power and Energy Applications, ICPEA 2019

作者： Tingting, Yang Yang, Bai Weichun, Ge Huanhuan, Luo Guiping, Zhou You, Lv Beijing Key Laboratory of New Technology and System on Measuring and Control for Industrial Process North China Electric Power University Beijing102206 China State Grid Liaoning Electric Power Supply CO. LTD Shenyang Liaoning Province110004 China

ISBN: (纸本)9781728115962

Large-scale deep variable load of thermal power units will increase the hidden trouble of auxiliary equipment failure. Timely detection of minor faults and early warning are conducive to the safe operation of units. With the large-scale deep variable load of units, the operating conditions of auxiliary equipment also change in a large range, and the operating parameters fluctuate in a large range, which directly affects the accuracy of fault early warning algorithm based on operation data. In order to solve this problem, this paper uses a multivariate state estimation technique (MSET) algorithm for fault early warning. Firstly, the cluster method is used to divide the operating conditions of units, and process memory matrix is constructed under different operating conditions for modeling and calculation. The simulation results show that compared with the traditional method using one process memory matrix this method significantly improves the accuracy of fault early warning. © 2019 IEEE.

关键词： state estimation

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A Semi-smooth Projected Levenberg-Marquardt power Flow Method to Cope with the Constraints Exchange Issue 3

A Semi-smooth Projected Levenberg-Marquardt Power Flow Metho...

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3rd IEEE Conference on Energy Internet and Energy system Integration, EI2 2019

作者： Ju, Yuntao Wang, Jiankai Zhang, Zifeng Chen, Jianhua Dong, Mingyu Li, Dezhi Shi, Kun Zhang, Haibo China Agricultural University College of Information and Electrical Engineering Beijing China State Grid Jibei Electric Power Company Power Control Center Beijing China Carriers Optimization and Interaction Technique Beijing Key Laboratory of Demand Side Multi-Energy Beijing China China Electric Power Research Institute Beijing China North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China

ISBN: (纸本)9781728131375

In the conventional power flow (PF) calculation, when using the PV-PQ bus switching to deal with the problem of the generator buses reactive power limits violation for power systems, this method may cause the power flow calculation to fail. If using the Fischer-Burmeister (FB) function to handle constraint exchange issues, then using the Newton-Raphson (NR) method to solve PF, this operation will lead to a slow convergence. In this paper, a semi-smooth projected Levenberg-Marquardt (PLM) power flow method based on the FB function to deal with the constraints exchange issues is proposed. This method can change the search direction when the constraint exchange positions are at sharp corners, and adjust the size of the trust region to prevent the power flow from divergence due to excessive step size in the iterative process, thus improving convergence and reliability. Furthermore, the traditional power flow calculation method is sensitive to the initial value, which may cause the PF divergence, however the method of PLM proposed in this paper is globally convergent, which is not sensitive to the initial value. Numerical tests implemented on a small 3-bus network and a modified IEEE 118-bus system show that the proposed method is more efficient and robust than existing methods. © 2019 IEEE.

关键词： Newton-Raphson method

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