Synergetic optimal scheduling of grid-connected household photovoltaic system considering demand response for loads

被引：0

作者：

Ai Y. ^{[1
]}

Ding J. ^{[1
]}

Liu Q. ^{[1
]}

Han C. ^{[1
]}

Jing Y. ^{[2
]}

Li S. ^{[3
]}

机构：

[1] College of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo

[2] State Grid Mingguang Power Supply Company, Mingguang

[3] Zhejiang Zhengtai Electric Appliance Co., Ltd., Yueqing

来源：

Ding, Jianying (2765243436@qq.com) | 1600年 / Science Press卷 / 42期

关键词：

Demand response; Optimal scheduling model; Particle swarm optimization(PSO); Photovoltaic system; Uncertainty;

D O I：

10.19912/j.0254-0096.tynxb.2019-0943

中图分类号：

学科分类号：

摘要：

To solve the economic dispatching problem of household photovoltaic(PV) system caused by not fully utilizing the demand response of loads, a synergetic economic dispatching strategy that takes into account the demand response of load is proposed, which achieves the synergetic scheduling of source and load. Firstly, the demand response model of the load is established to handle the household load. Secondly, considering the uncertainty of PV output, the optimal scheduling model of grid-connected household PV system is constructed, which takes into account the user's power sold income, power purchased cost, government subsidy, operation and maintenance cost and the construction cost of PV system. Then, this model is solved by using dynamic grid-connected transmission power as optimization variable, combining with Latin hypercube sampling and scene reduction (LHSSR), improved particle swarm optimization algorithm. Finally, the simulation results show the correctness of the proposed model and method. © 2021, Solar Energy Periodical Office Co., Ltd. All right reserved.

引用

页码：104 / 114

页数：10

共 18 条

[1] KOH L H, WANG P, CHOO F H, Et al., Operational adequacy studies of a PV-based and energy storage stand-alone microgrid, IEEE transactions on power systems, 30, 2, pp. 892-900, (2015)
[2] WEN Z K, QIU G Y., Economic and environmental analysis of household photovoltaic system: taking 5 kW photovoltaic system in Jiangxi province as an example, Acta scientiarum naturalium universitatis pekinensis, 54, 2, pp. 443-450, (2018)
[3] DIPESH L, VICTOR S, YATEENDRA M, Et al., Smoothing control strategy of wind and photovoltaic output power fluctuation by considering the state of health of battery energy storage system, IET renewable power generation, 13, 4, pp. 578-586, (2019)
[4] HAN X D, WANG H H, LI J F., Design of small distributed photovoltaic generation system, Electric power construction, 35, 1, pp. 104-108, (2014)
[5] MA L, ZHANG S R., Optimal operation scheduling of family grid-connected photovoltaic systems under time-of-use and ladder tariffs, Power system technology, 40, 3, pp. 819-825, (2016)
[6] CHEN Q Y., Research on economic operation optimization in micro-grid based on improved PSO algorithm, (2015)
[7] JIN S J., Research on design and optimal scheduling algorithm of home energy management system based on distributed generation and energy storage, (2017)
[8] HUANG Z R., Design and implementation of home energy management system based on real-time electricity price, (2017)
[9] YU G Q, LI L D, YUAN Y F., A hybrid particle swarm optimization algorithm with adaptive inertia weight, Journal of Harbin University of Science and Technology, 21, 3, pp. 49-53, (2016)
[10] GONZALEZ O, REYES M, NIEN J, Et al., Choosing a starting configuration for particle swarm optimization, IEEE International Joint Conference on Neural Networks, (2004)

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