Education, Science, Technology, Innovation and Life
Open Access
Sign In

Research on Short-Term Load Forecasting of Micro-Grid Based on PSO-SVM Model

Download as PDF

DOI: 10.23977/jeis.2020.51004 | Downloads: 9 | Views: 840


Shaomin Zhang 1, Xuebao Li 1, Baoyi Wang 1


1 Department of Control and Computer, North China Electric Power University, HuaDian Road, BaoDing, China

Corresponding Author

Shaomin Zhang


Due to the uncertainty and volatility of micro-grid load, conventional load forecasting methods cannot be directly used in micro-grid load forecasting. Therefore a hybrid load forecasting model of micro-grid based on particle swarm optimization (PSO) and Support Vector Machine (SVM) is proposed in this paper. Particle swarm optimization (PSO) was used to optimize the model parameters of SVM regression, and the optimized SVM prediction model was obtained. Through the comparative analysis of the experiment, it is concluded that the hybrid prediction model of PSO-SVM is more accurate for the load prediction of micro grid, which can provide a decision basis for the safe and economic dispatch of micro grid and play a positive role in the stable operation of micro grid power system.


Micro-grid, Support Vector Machine, Short-term Load Forecasting


Shaomin Zhang, Xuebao Li, Baoyi Wang. Research on Short-Term Load Forecasting of Micro-Grid Based on PSO-SVM Model. Journal of Electronics and Information Science (2020) 5: 17-22. DOI:


[1]Tai Xue, sun Hongbin, Guo Qinglai. Power trading and congestion management based on blockchain in energy Internet [J]. Grid technology, 2016, 40 (12): 3630-3638
[2]Su Xiaolin, Liu Xiaojie, Yan Xiaoxia, Wang Muqing, Han Xuenan. Short-term load prediction of active distribution network based on demand response [J]. Power system automation,2018,42(10):60-66+134.
[3]Mahmood Hosseini Imani,M. Jabbari Ghadi,Sahand Ghavidel,Li Li. Demand Response Modeling in Micro-grid Operation: a Review and Application for Incentive-Based and Time-Based Programs[J]. Renewable and Sustainable Energy Reviews,2018,94.486-499.
[4]Pouria Sheikhahmadi, Ramyar Mafakheri ,Salah Bahramara.Risk-Based Two-Stage Stochastic Optimization Problem of Micro-Grid Operation with Renewables and Incentive-Based Demand Response Programs. Energies 2018, 11,1-17.
[5]Luan Kaining, Bao min, Yi Yongxian, Zhao Shuangshuang. Research on short-term prediction technology of large user load based on power consumption pattern number [J]. Power engineering technology,2018,37(03):33-37.
[6]Tang Qingfeng, Liu nian, Zhang Jianhua, Yu Zhuangzhuang, Zhang Qingxin, Lei Jinyong. A short-term load forecasting method based on EMD-KELM-EKF and parameter optimization for user-side micro-grid[J]. Power grid technology, 2014, 38(10):2691 -2699.
[7]Qian zhi. Short-term load prediction of power grid based on improved SVR [J]. China electric power, 2016, 49(08): 54-58.
[8]Lin shunfu, Hao chao, Tang Xiaodong, Li Dongdong, Fu yang. Research on short-term load prediction method of building based on data mining [J]. Power system protection and control,2016,44(07):83-89.
[9]Yu Xinyan, Shen Yanxia, Chen Jie. A Multi-Objective Prediction Method for Short-Term Micro-grid Load Considering Interval Probability, 2017(04): 165-171.
[10]Xu Jianjun, Zhang Yanfu. Load prediction method of micro grid based on improved support vector machine and its simulation analysis [J]. Automation technology and application,2017,36(03):64-66+74.

Downloads: 918
Visits: 86875

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.