Optimization of the electricity consumption strategy for agricultural irrigation districts with distributed photovoltaic and energy storage systems

doi:10.19799/j.cnki.2095-4239.2025.0388

Abstract

Abstract:

Irrigation is crucial for agricultural production. Traditional irrigation systems are commonly limited by high energy consumption and low efficiency. To address this challenge, this study introduces a distributed photovoltaic-storage (PV-storage) system as a clean energy solution for agricultural irrigation by focusing on exploring electricity consumption optimization strategies. An electricity consumption model was constructed by analyzing the seasonal characteristics of agricultural irrigation load in Heilongjiang region. This model encompasses multiple types of electrical equipment and intermittent load characteristics. A load transfer and interruption operation model was established by combining the intermittency and adjustable characteristics of the load during the irrigation cycle. Then, a system output model was built based on the power generation characteristics of the PV-storage system. Furthermore, for minimizing electricity costs within the park, an electricity consumption optimization model under time-of-use pricing was constructed. Simulation of summer irrigation scenarios validated the proposed strategy, showing that it reduced electricity costs by 41.2% compared to traditional methods. Thus, the economic benefits of PV-storage systems in the field of agricultural irrigation were demonstrated.

Key words: agricultural irrigation park, intermittent load, light-storage system, electricity optimization, load shifting

CLC Number:

TM 732

Kun ZHUANG, Pengcheng FAN, Chenyu JIANG, Wenqian YIN, Jilei YE, He WANG, Chunlei WANG. Optimization of the electricity consumption strategy for agricultural irrigation districts with distributed photovoltaic and energy storage systems[J]. Energy Storage Science and Technology, 2025, 14(7): 2782-2790.

Figures/Tables 12

Table 1

Table 2

Parameter settings"

项目	变量符号	设置参数
储能自放电率	$μ l o s s$	0.99
储能充/放电效率	$ρ i b a t, c h a r / ρ i b a t, d i s$	0.95/0.95
储能充/放电功率上限/kW	$P i c h a r, m a x / P i d i s, m a x$	150/150
储能容量上/下限/kW	$S i b a t, m a x / S i b a t, m i n$	50/200
储能单位运维成本	$c d i s, b a t / c c h a r, b a t$	0.05万元/kWh
光伏单位运维成本	$C p v$	0.21万元/kW
机井水泵提水效率	$η p u m p$	0.812
机井电机工作效率	$η m a c h i n e$	0.91

Table 2

Fig. 1

Table 3

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Table 4

References 18

[1]	汤俊超, 吴宜文, 张姚, 等. 浅谈"光伏+农业" 产业的发展模式[J]. 中国农学通报, 2022, 38(11): 144-152.
	TANG J C, WU Y W, ZHANG Y, et al. A brief introduction on the industrial development mode of photovoltaic agriculture[J]. Chinese Agricultural Science Bulletin, 2022, 38(11): 144-152.
[2]	江亿, 胡姗. 屋顶光伏为基础的农村新型能源系统战略研究[J]. 气候变化研究进展, 2022, 18(3): 272-282.
	JIANG Y, HU S. Research on the development strategy of production and consumption integrated roof-top PV system in rural China[J]. Climate Change Research, 2022, 18(3): 272-282.
[3]	吕双辉, 蔡声霞, 王守相. 分布式光伏-储能系统的经济性评估及发展建议[J]. 中国电力, 2015, 48(2): 139-144.
	LYU S H, CAI S X, WANG S X. Economy evaluation and development suggestions for distributed PV-energy storage system in China[J]. Electric Power, 2015, 48(2): 139-144.
[4]	董强, 徐君, 方东平, 等. 基于光伏出力特性的分布式光储系统优化调度策略[J]. 综合智慧能源, 2024, 46(4): 17-23.
	DONG Q, XU J, FANG D P, et al. Optimal scheduling strategy of distributed PV-energy storage systems based on PV output characteristics[J]. Integrated Intelligent Energy, 2024, 46(4): 17-23.
[5]	MOUSAVI N, KOTHAPALLI G, HABIBI D, et al. A novel photovoltaic-pumped hydro storage microgrid applicable to rural areas[J]. Applied Energy, 2020, 262: 114284. DOI: 10.1016/j.apenergy.2019.114284.
[6]	赵小磊, 姚良忠, 刘运鑫, 等. 面向储能多应用价值协同的风光储系统日前优化调度方法[J]. 高电压技术, 2024, 50(6): 2511-2522. DOI: 10.13336/j.1003-6520.hve.20231392.
	ZHAO X L, YAO L Z, LIU Y X, et al. Day-ahead optimal dispatch for wind-photovoltaic-storage system considering synergistic multi-application value of energy storage[J]. High Voltage Engineering, 2024, 50(6): 2511-2522. DOI: 10.13336/j.1003-6520.hve.20231392.
[7]	杨森, 郭宁, 张寿明. 不确定性条件下农业微电网与灌溉系统相结合的鲁棒优化调度[J]. 上海交通大学学报, 2024, 58(9): 1432-1442. DOI: 10.16183/j.cnki.jsjtu.2023.035.
	YANG S, GUO N, ZHANG S M. Robust optimal scheduling of agricultural microgrid combined with irrigation system under uncertainty conditions[J]. Journal of Shanghai Jiao Tong University, 2024, 58(9): 1432-1442. DOI: 10.16183/j.cnki.jsjtu. 2023.035.
[8]	AMMAR M, SHARAF A M. Optimized use of PV distributed generation in voltage regulation: A probabilistic formulation[J]. IEEE Transactions on Industrial Informatics, 2019, 15(1): 247-256. DOI: 10.1109/TII.2018.2829188.
[9]	PRINSLOO G, DOBSON R, MAMMOLI A. Synthesis of an intelligent rural village microgrid control strategy based on smartgrid multi-agent modelling and transactive energy management principles[J]. Energy, 2018, 147: 263-278. DOI: 10.1016/j.energy.2018.01.056.
[10]	于港旭, 李中伟, 金显吉, 等. 基于光伏和蓄电池的智能小区能量调度优化策略研究[J]. 自动化仪表, 2022, 43(7): 21-27. DOI: 10.16086/j.cnki.issn1000-0380.2021050007.
	YU G X, LI Z W, JIN X J, et al. Study on optimization strategy of energy dispatching in intelligent community based on photovoltaic and battery[J]. Process Automation Instrumentation, 2022, 43(7): 21-27. DOI: 10.16086/j.cnki.issn1000-0380. 2021050007.
[11]	徐玉韬, 刘千杰, 谈竹奎, 等. 分布式风储系统与配电网间的协同运行控制研究[J]. 可再生能源, 2018, 36(11): 1645-1650. DOI: 10.13941/j.cnki.21-1469/tk.2018.11.011.
	XU Y T, LIU Q J, TAN Z K, et al. Research on cooperative operation control between windess distributed system and distribution network[J]. Renewable Energy Resources, 2018, 36(11): 1645-1650. DOI: 10.13941/j.cnki.21-1469/tk.2018.11.011.
[12]	徐慧慧, 陈兆雁, 田云飞, 等. 甘肃农业排灌负荷新能源供电[J]. 农村电气化, 2020(1): 34-37. DOI: 10.13882/j.cnki.ncdqh.2020.01.008.
	XU H H, CHEN Z Y, TIAN Y F, et al. Research on new energy power supply of agricultural irrigation load in Gansu[J]. Rural Electrification, 2020(1): 34-37. DOI: 10.13882/j.cnki.ncdqh. 2020.01.008.
[13]	赵彦琳, 张宇峰, 张敬博. 基于物联网技术的农业智能灌溉系统探究[J]. 现代农村科技, 2024(12): 73-74.
[14]	魏光明, 邱东, 慕俊强, 等. 分布式电源接入对配电网网络损耗的影响研究[J]. 石河子科技, 2024(1): 34-35.
	WEI G M, QIU D, MU J Q, et al. Research on the influence of distributed power supply access on network loss of distribution network[J]. Shihezi Science and Technology, 2024(1): 34-35.
[15]	樊红梅, 刘晓民, 王文娟, 等. 基于多种方法的"以电折水" 系数研究[J]. 灌溉排水学报, 2021, 40(11): 98-105. DOI: 10.13522/j.cnki.ggps.2021202.
	FAN H M, LIU X M, WANG W J, et al. Estimating water consumption from electricity consumption: How to calculate the conversion coefficient[J]. Journal of Irrigation and Drainage, 2021, 40(11): 98-105. DOI: 10.13522/j.cnki.ggps.2021202.
[16]	纪历, 杨晓伟, 陈振宇, 等. 考虑农业电排灌负荷的配电网运行优化策略研究[J]. 电力需求侧管理, 2020, 22(4): 66-70, 76. DOI: 10.3969/j.issn.1009-1831.2020.04.014.
	JI L, YANG X W, CHEN Z Y, et al. Research on power distribution network operation optimization strategy considering agricultural electric drainage and irrigation load[J]. Power Demand Side Management, 2020, 22(4): 66-70, 76. DOI: 10.3969/j.issn.1009-1831.2020.04.014.
[17]	王雯沁, 高红均, 徐琳, 等. 基于主从博弈的配电网-农灌园区互动协调优化方法[J]. 电网技术, 2023, 47(11): 4698-4711. DOI: 10.13335/j.1000-3673.pst.2022.1819.
	WANG W Q, GAO H J, XU L, et al. Interactive coordination optimization of electrical distribution network and agricultural irrigation park based on master-slave game[J]. Power System Technology, 2023, 47(11): 4698-4711. DOI: 10.13335/j.1000-3673.pst.2022.1819.
[18]	冯晓莉, 仇宝云. 考虑河道输水损失的大型泵站系统运行优化[J]. 农业工程学报, 2015, 31(17): 35-41. DOI: 10.11975/j.issn.1002-6819.2015.17.005.
	FENG X L, QIU B Y. Optimal operation for large pumping station system based on water transferring losses of river[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(17): 35-41. DOI: 10.11975/j.issn.1002-6819.2015.17.005.

用电设备	运行时间/h	功率/kW	数量
水泵机井设备	6~10、10~14、14~16、16~18	7.5	10/15/20
照明设备	18~24	0.04	10
传感设备	0~24	0.004	250

场景	考虑负荷转移	考虑光储出力
初始	×	×
1	√	×
2	×	√
3	√	√

场景	初始场景	场景1	场景2	场景3
用电成本/CNY	1280.03	1167	852.3	752
相比初始场景成本减少幅度/%	0	8.8	33.4	41.2