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检索条件"机构=Liaoning Key Laboratory of Regional Multi-energy System Integration and Control"

共 38 条记录，以下是1-10 订阅

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Optimal power flow calculation method for regional integrated energy system based on double-layer optimization 5

Optimal power flow calculation method for regional integrate...

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2023 5th International Conference on energy, Power and Grid, ICEPG 2023

作者： Zhang, Tianshuo Zhao, Yan Liu, Renshuo Chi, Huazhi School of Renewable Energy Shenyang Institute of Engineering Liaoning Shenyang110136 China Liaoning Key Laboratory of Regional Multi-energy System Integration and Control Liaoning Shenyang110136 China

In this paper, a two-layer optimization calculation method is proposed to improve the practical application efficiency of the integrated energy system and to improve the different problems of power flow calculation. Firstly, the power flow model is constructed and the optimization function is established based on indicators such as economy and environmental protection. The two-layer optimization method is proposed by combining the quadratic programming method and the particle swarm algorithm. Then, the obtained operating conditions of each energy equipment are used as the input of the power flow. The processing of each device and the energy flow of the power flow network are calculated and the effectiveness of the algorithm is verified by MATLAB power analysis. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： MATLAB

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Large-scale distributed photovoltaic cluster partition method based on SLM algorithm 5

Large-scale distributed photovoltaic cluster partition metho...

引用

2023 5th International Conference on energy, Power and Grid, ICEPG 2023

作者： Wang, Ziyuan Gao, Qingzhong School of Renewable Energy Shenyang Institute of Engineering Liaoning Shenyang110136 China Liaoning Key Laboratory of Regional Multi-energy System Integration and Control Liaoning Shenyang110136 China

The traditional distribution network with centralized control faces the problems of communication delay, large amount of calculation and too many control devices. This research offers a distributed power cluster division technique based on Smart Local Moving (SLM) to overcome the problem of challenging regulation of distributed power supply in modern distribution networks. First of all, on the basis of the modularity division standard, introduce the comprehensive cluster division index of intra-group reactive power and active matching degree index, so as to ensure the strength of the cluster structure on the basis of making it have a certain degree of voltage regulation capability. Secondly, the cluster division scheme of distributed power supply is formed based on SLM algorithm. Lastly, the feasibility and efficacy of the suggested method are validated using IEEE33 cluster partitioning. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Electric power distribution

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Research on short-term load forecasting based on Adam-SGD-LSTM 9

Research on short-term load forecasting based on Adam-SGD-LS...

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9th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, ISAEECE 2024

作者： Liu, Renshuo Zhao, Yan Zhang, Tianshuo Chi, Huazhi School of Renewable Energy Shenyang Institute of Engineering Liaoning Shenyang110136 China Liaoning Key Laboratory of Regional Multi-energy System Integration and Control Liaoning Shenyang110136 China

ISBN: (纸本)9781510683303

Aiming at the problem of low prediction certainty of existing load forecasting methods, this paper proposes a short-term load forecasting system that is based on the LSTM neural network. The original dataset is first processed by the median elimination method, Markov-Monte Carlo algorithm and improved hierarchical clustering algorithm. Then, the data are input into the LSTM prediction model optimized by the Adam method and SGD method for prediction. The example analysis proves that the method proposed in this paper has better prediction accuracy, which is helpful for the planning and movement of the power system. © 2024 SPIE.

关键词： Prediction models

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Photovoltaic power prediction model based on EMD-KPCA-GRU 8

Photovoltaic power prediction model based on EMD-KPCA-GRU

引用

8th International Conference on energy system, Electricity, and Power, ESEP 2023

作者： Chi, Huazhi Jiang, He Zhao, Yan School of Renewable Energy Shenyang Institute of Engineering Liaoning Shenyang110136 China Liaoning Key Laboratory of Regional Multi-energy System Integration and Control Liaoning Shenyang110136 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

With the aim of enhancing the accuracy of PV power forecasting, a PV power prediction model has been presented based on the EMD-PKCA-GRU neural network. Firstly, the sequence of four meteorological factors constraining the output power of photovoltaic power generation is decomposed using the empirical model decomposition method. The non-stationary nature of the meteorological factor sequences is reduced. Next, feature extraction is conducted from decomposed sequences using kernel principal component analysis (KPCA) methods. This eliminates the redundancy of the original sequence and reduces the dimensionality of the model input. Finally, the Gated Recurrent Unit (GRU) is established, using the GRU to predict PV power generation. The validation was conducted using the 2021 data from the Trina 1B power station in the DKASC dataset from Australia. The outcome shows that the prediction accuracy is higher than the traditional model. © 2024 SPIE.

关键词： Solar energy

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Ultra-short term wind power forecasting method based on improved VMD 2

Ultra-short term wind power forecasting method based on impr...

引用

2023 2nd International Conference on energy and Electrical Power systems, ICEEPS 2023

作者： Fu, Yunzhi Zhao, Yan Yu, Yuan School of Renewable Energy Shenyang Institute of Engineering Shenyang110136 China Liaoning Key Laboratory of Regional Multi-energy System Integration and Control Shenyang110136 China

A CNN-GRU ultra-short term wind power prediction method based on improved VMD is proposed. Firstly, in the data processing part, according to the irregularity and non-stationary peculiarities of wind power, the variational mode decomposition algorithm is adopted to decompose the original sequence of wind power to reduce the non-stationarity. At the same time, considering that the parameter setting and selection in the variational modal decomposition algorithm are of great significance to the decomposition effect, the improved whale improvement method is adopted to find the best parameters in VMD to avoid the problem of poor decomposition effect caused by artificial setting. Finally, the CNN-GRU and GRU models are simulated and compared on the Matlab platform through the field wind farm data. © Published under licence by IOP Publishing Ltd.

关键词： Variational mode decomposition

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Short-term prediction of photovoltaic power generation based on ICEEMDAN-SE-GAPSO-LSTM 2

Short-term prediction of photovoltaic power generation based...

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2023 2nd International Conference on energy and Electrical Power systems, ICEEPS 2023

作者： Wu, Shuai Jiang, He Gao, Qingzhong School of Renewable Energy Shenyang Institute of Engineering Shenyang110136 China Liaoning Key Laboratory of Regional Multi-energy System Integration and Control Shenyang110136 China

This study proposes an improved adaptive noise-complete ensemble empirical mode decomposition (ICEEMDAN), sample entropy (SE), and genetic particle swarm optimization (GAPSO) algorithm-based short-term solar power forecast model. The photovoltaic power data is first decomposed using the ICEEMDAN algorithm to produce a number of eigenmode components with various properties. The sample entropy of each component is then calculated, and the components with similar sample entropy values are combined to create new modal components. These new modal components are then input into the GAPSO-optimized LSTM model for prediction, and the prediction results of each component are summed and reconstructed to produce the final prediction. The results completely validate the efficacy and dependability of the suggested method, using the measured data from a photovoltaic power station in Xinjiang, China as an example. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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Research on building integrated energy optimization scheduling based on improved whale algorithm 9

Research on building integrated energy optimization scheduli...

引用

9th International Conference on energy Materials and Electrical Engineering, ICEMEE 2023

作者： Zhang, Tianshuo Zhao, Yan Zhang, Xinyu School of Renewable Energy Shenyang Institute of Engineering Shenyang110136 China Liaoning Key Laboratory of Regional Multi-energy System Integration and Control Shenyang110136 China

ISBN: (纸本)9781510672765

In the dual-carbon context of "peak carbon"and "carbon neutrality", the regulation of flexible resources in the electric power energy system has become an important means of reducing carbon emissions and improving energy utilization. The energy system of urban buildings contains a huge number of resources with flexible and adjustable characteristics. energy saving and emission reduction in buildings is important to achieve the goal. We take the massive heterogeneous distributed flexible loads in the energy system of urban building clusters as the research object, firstly, we introduce each component of Residential Integrated energy system (RIES), categorize the building loads according to different characteristics of electricity consumption, and model and analyze each part of the building system, the lowest operating costs as the objective function for optimization. The traditional scheduling method is difficult to meet the demand for real-time optimization of the building energy system scheduling decision-making speed, so this paper proposes an improved whale algorithm with high intelligence and fast decision-making ability to solve the model, the optimization strategy of building energy scheduling simulation and analysis, the results of the example have verified the validity of the built model. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Power grids Mathematical optimization Power consumption Solar energy system integration Photovoltaics Carbon Modeling Renewable energy systems modeling

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Optimal control method for regional integrated energy system considering optimal consumption of clean energy 9

Optimal control method for regional integrated energy system...

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9th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, ISAEECE 2024

作者： Zhang, Dong Huang, Shijie An, Yuxing School of Renewable Energy Shenyang Institute of Engineering Liaoning Shenyang110136 China Liaoning Key Laboratory of Regional Multi-energy System Integration and Control Liaoning Shenyang110136 China School of Economics Management and Law Shenyang Institute of Engineering Liaoning Shenyang110136 China

ISBN: (纸本)9781510683303

Aiming at the problems of solar curtailment and wind curtailment in the integrated energy system, an optimal control method considering the optimal consumption of clean energy is proposed. regional Integrated energy system (RIES) usually adopts multiple consumption technologies to solve problems such as curtailment of light and wind. On this basis, this paper establishes a RIES optimization model including Air Source Heat Pump (ASHP), photovoltaic units, wind turbines and energy storage systems. The source side adopts a robust optimization model including ASHP, which can not only remove the issue with wind energy output instability, but also expand grid for wind energy connection;the storage side uses the thermal energy time shifting properties of the heat storage device to establish a storage-discharge model to improve RIES. flexibility;finally, construct an optimal regulation model considering the optimal consumption of clean energy. The fake outcomes verify the potential of the suggested model. Compared with the traditional model, an optimal control model considering the optimal consumption of clean energy has more considerable renewable energy consumption capacity and economic benefits. © 2024 SPIE.

关键词： Clean energy

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Networked control Synthesis of Micro-Grid system Based on Switching Theory 42

Networked Control Synthesis of Micro-Grid System Based on Sw...

引用

42nd Chinese control Conference, CCC 2023

作者： Luo, Jinming Yao, Lei Xu, Sibo Wang, Hongtao Gao, Jing College of Automation Shenyang Institute of Engineering Key Laboratory of Regional Multi-energy System Integration and Control Shenyang110136 China

ISBN: (纸本)9789887581543

A large number of sensors and controllers in the micro-grid system transmit signals through the network, however, due to the physical limitations of the network bandwidth and service capacity, data transmission in the network will have delays, packet loss and time disorder, which will damage the performance of the system, and even lead to instability of the system. Therefore, in this paper, the switching fuzzy time-delay micro-grid system is established, and the Fuzzy controller of the micro-grid subsystem is designed according to the PDC method, and the switching law is designed, the asymptotic stability condition of the system is given by using the method of single Lyapunov function and convex combination, and the stability of the system is analyzed. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Asymptotic stability

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Fault identification method for substation power equipment based on infrared, visible light images, and YOLOv5 algorithm 3

Fault identification method for substation power equipment b...

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3rd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： Liu, Zhaoqun Zhao, Yan Wang, Donglai Graduate Faculty Shenyang Institute of Engineering Liaoning Shenyang110136 China Key Laboratory of Regional Multi-energy System Integration and Control of Liaoning Province Shenyang Institute of Engineering Liaoning Shenyang110136 China

ISBN: (纸本)9781510668522

For the issues of cable local heating, isolator ceramic disc breakage, lightning arrester and transformer local breakage among substation power equipment fault diagnosis, this study presented a YOLOv5 target detection approach based on deep convolutional neural network to identify and locate power equipment such as insulators, disconnect switch contacts, bushings, wire clips, lightning arresters and their abnormal heating areas. In the testing stage of the YOLOv5 process, the network divides the image in the database into 416∗416 pixels. By using the Yolomark tool to annotate the image, the labels are fed into the deep learning convolutional neural network together with the sample set for training, and the ultimate module is generated after several iterations. Finally, the infrared and visible spectral materials of electronic facilities gathered by the operation and monitoring units with infrared thermographers are used for effect testing. Then the fault diagnosis and grading of various power equipment in substation are carried out. The detective findings are evaluated with the quicker regional convolutional neural network algorithm, YOLOv3 algorithm and SSD algorithm for comparison. Through the experimental analysis, the average accuracy of the model is 96.7%, which can achieve the fault diagnosis target of substation power equipmentï1/4 and thus enhance the daily running, maintenance and management efficient of the power grid. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Failure analysis

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