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Zhaoyang Qu,Jiajun Song,Yuqing Liu,Hongbo Lv,Kewei Hu,Jian Sun,Miao Li,Wei Liu,Mingshi Cui,Wanxin Wang 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.6
The problem of load fuctuation in the distribution network and increasing power grid cost input caused by the unpredictable behavior of electric vehicle (EV) users in response to electricity price is investigated in this paper. An optimization model method for the charging and discharging price of electric vehicles is proposed, considering the vehicle owner response and power grid cost. The rule of EV user travel is frst analyzed, and the travel and battery state constraints are defned. Under the constraints of user charging and discharging behavior and battery characteristics, a user transfer rate and unit energy cost function is designed to construct a multi-objective model of charging and discharging price that minimizes electricity expenditure and avoids an increase in power grid investment. Finally, an improved multi-target fsh swarm algorithm is presented to solve the model optimization problem. The example analysis shows that the proposed method can reduce the peak-valley load diference of the system and cost input of the power grid, as well as provide users with regulation ability to access the power grid at diferent time periods
Zhaoyang Qu,Wanxin Wang,Nan Qu,Yuqing Liu,Hongbo Lv,Kewei Hu,Jianyou Yu,Manyang Gao,Jiajun Song 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.4
In order to improve the accuracy of forecasts of the electricity sales of power sales companies, a depth forecast model of electricity sales based on the characteristics of the power market is proposed. First, based on survival analysis, the calculation method of the user churn rate in the electricity market is given, and the number of users at a certain moment in the future is predicted. Then, users’ electricity consumption that calculated by the deep belief network and the predicted quantity of users are combined to design a forecast model of electricity sales. Finally, the model is solved utilizing the weighting algorithm of adaptive inertia. The analysis of the example shows that the proposed method achieves a signifi cant improvement in the accuracy of power sales forecasting.
Zhaoyang Qu,Wanxin Wang,Nan Qu,Yuqing Liu,Hongbo Lv,Kewei Hu,Jianyou Yu,Manyang Gao,Jiajun Song 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.6
Due to unfortunate mistake the grant numbers have been omitted in the acknowledgments section: This work is supported by the National Natural Science Foundation of China (No. 51437003), Jilin Province Science and Technology Development Plan Project of China (20160623004TC, 20180201092GX), Jilin Science and Technology Innovation Development Plan Project of China (201830817).