Evaluation method of a new power system construction based on improved LSTM neural network
Pages 1819 - 1832
Abstract
The evaluation of new power system construction is the research foundation for improving the flexible regulation ability and comprehensive operational efficiency of new power systems, and achieve the comprehensive goals of safe power supply, green consumption, and economic efficiency. However, the existing research on the evaluation index system of new power system construction can not fully reflect the main objectives of new power system construction. Therefore, this paper first develops a source-load and green-intelligence multi-level and multi-dimensional evaluation system for new power system construction from source-load side equipment, green power, reliable power supply, and intelligent power consumption. Secondly, a hybrid optimization algorithm is proposed based on fluid search algorithm (FSO) for improving the Long Short-Term Memory (LSTM) neural network parameter updating method. Then, the improved LSTM neural network is applied to the construction evaluation of the new power system. Finally, the simulation results show that the evaluation error of the new power system construction evaluation method is 0.0063, which has a high evaluation.
References
[1]
Li P, Wang JH, Xu X, Li JY, Xu XC, Xia H. Robust reactive power partitioning method for frequent power flow fluctuation in new power system. Auto Electr Power Syst. 2022; 46(11): 102-110.
[2]
Kang CQ, Du ES, Li YW, Zhang N, Chen QX, Guo HY, Wang P. Key scientific problems and research framework for carbon perspective research of new power systems. Power Syst Technol. 2022; 46(3): 821-833.
[3]
Zhang ZG, Kang CQ. Challenges and prospects for constructing the new-type power system towards a carbon neutrality future. Proc CSEE. 2022; 42(8): 2806-2818.
[4]
Kang CQ, Yao LZ. Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy. Auto Electr Power Syst. 2017; 41(9): 2-11.
[5]
Zhuo ZY, Zhang N, Xie XR, Li HZ, Kang CQ. Key technologies and developing challenges of power system with high proportion of renewable energy. Auto Electr Power Syst. 2021; 45(9): 171-191.
[6]
Ding Y, Xie K, Pang B, Li Z, Guo LB. Key issues of national unified electricity market with Chinese characteristics (1): Enlightenment, comparison and suggestions from foreign countries. Power Syst Technol. 2020; 44(7): 2401-2410.
[7]
Xia Q, Chen QX, Xie K, Pang B, Li Z, Guo HY. The key issues of the national unified electricity market with Chinese characteristics (2): The development approach, trading varieties and policy suggestions of my country’s cross-regional and cross-provincial power trading market. Power Syst Technol. 2020; 44(8): 2801-2808.
[8]
Liao QL, Xie KG, Hu B. Sequential probabilistic production simulation of power systems with wind power and energy storage. Power Syst Technol. 2017; 41(9): 2769-2776.
[9]
Yuan TJ, Gao LY, Xie YS, Zhou Z. Design and comprehensive evaluation of wind-thermal power coupling multi-energy system based on hydrogen energy. Electr Power Auto Equip. 2021; 41(10): 227-233+255.
[10]
Zhao DM, Zheng Y, Xie JL, Guo YC. Integrated assessment of power system transient frequency security based on deep residual shrinkage network. Power Syst Technol, 2022; pp. 1-13.
[11]
Zeng M, Wang YC, Yan T, Lan MX, Dong HQ, Zhang XC, Wang HL, Sun CJ. Design and model research of renewable energy policy evaluation system based on ubiquitous power IoT platform. Power Grid Technol. 2019; 43(12): 4263-4673.
[12]
Yuan YP, Wang JX, Zhang Y, Zhou L, Wang XB, Lu GQ. Panoramic operation simulation approach and estimation index system for new energy power system considering multi-period coordination. Power Syst Technol. 2020; 44(3): 799-806.
[13]
Bie ZH, Pan CQ, Chen Y, Li FR. Probabilistic risk assessment of new energy power system under energy transition. J Xi’an Jiaotong Univ. 2021; 7(55): 1-11.
[14]
Han TB, Gao ZH, Du WX, Hu SZ. Multi-dimensional evaluation method for new power system. Energy Rep. 2022; 8(Supplement 6): 618-635.
[15]
Wang YB, Wu JY, Ji JS, Li LS, Li BQ. Integrated assessment of power system transient frequency security based on deep residual shrinkage network. Power Syst Technol; 2022; pp. 1-14.
[16]
Yao WW, Li HQ, He Q, Wu X. Fuzzy synthetic evaluation method of cascading failure sequence in power grid. Proc CSU-EPSA. 2015; 27(4): 79-85.
[17]
Zhou SY, Cai GW, Yang DY, Wang LX. Ambient data-driven on-line evaluation method of power system small signal stability. Auto Electr Power Syst. 2022; 46(1): 94-100.
[18]
Li FC, Xu J, Liao SY, Sun YZ, Ke DP, Yang J, Du JM. Multi-stage power system transient stability assessment based on sample attention and hierarchical features. Proc CSEE. 2021; 41(22): 7596-7608.
[19]
Zhao K, Shi LB. Transient stability assessment of power system based on improved one-dimensional convolutional neural network. Power Syst Technol. 2021; 45(8): 2945-2957.
[20]
Zhou ZH, Bu GQ, Ma SC, Wang GZ, Shao DJ, Xu YP, Dang J. Assessment and optimization of power system transient stability based on feature-separated neural networks. Power Syst Technol. 2021; 45(9): 3658-3667.
[21]
Lin ZA, Shi YC, Chen B, Liu SY, Ge YJ, Ma J, Yang L, Lin ZZ. Early warning method for power supply service quality based on three-way decision theory and LSTM neural network. Energy Rep. 2022; 8(Supplement 5): 537-543.
[22]
Paul C, Roy PK, Mukherjee V. Chaotic whale optimization algorithm for optimal solution of combined heat and power economic dispatch problem incorporating wind. Renewable Energy Focus. 2020; 35: 56-71.
Recommendations
Voltage stability evaluation of power system with FACTS devices using fuzzy neural network
Voltage stability has been a major concern for power system utilities because of several events of voltage collapses in the recent past. With the developments of flexible ac transmission system (FACTS) devices, power system performance has improved. ...
Momentum-based wavelet and double wavelet neural networks for power system applications
In order to minimize the power loss and to control the voltage in the power systems, the proposed momentum-based wavelet neural network and proposed momentum-based double wavelet neural network are proposed in this paper. The training data are obtained ...
Efficiency Evaluation Method of Simulation System Based on BP Neural Network
ICNDC '11: Proceedings of the 2011 Second International Conference on Networking and Distributed ComputingAt the present time, it is difficult to find some good solutions to evaluate the efficiency of the simulation system yet. According to the Command & Control Simulation System(C2SS), this paper brought forward an evaluation method based on BP neural ...
Comments
Information & Contributors
Information
Published In
© 2022 – IOS Press. All rights reserved.
Publisher
IOS Press
Netherlands
Publication History
Published: 01 January 2022
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 06 Feb 2025