ENERGY SCHEDULING STRATEGY OF NEAR SPACE SOLAR POWERED VEHILCLE

Li Xinfang; Zeng Guohong; Chen Tianmu

doi:10.19912/j.0254-0096.tynxb.2021-1032

PDF(1863 KB)

Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (2) : 288-297. DOI: 10.19912/j.0254-0096.tynxb.2021-1032

ENERGY SCHEDULING STRATEGY OF NEAR SPACE SOLAR POWERED VEHILCLE

Li Xinfang, Zeng Guohong, Chen Tianmu

Author information +

History +

Abstract

Considering the problem that the capacity of the energy system cannot be fully utilized due to the uneven solar radiation on the surface of solar cells and the uncertainty of the load caused by the solar UAV near space, this paper proposes a real-time energy optimization scheduling strategy, which aims to minimize the difference in the battery power of each optical storage module at the end of the 24-hour period and maximize the storaged energy by the time of sun set. By constructing the scheduling model and energy forward correction strategy, the goal of fully utilizing the installed power generation and energy storage equipment capacity is achieved. Using Python software to do simulation, the rationality and feasibility of proposed model and scheduling strategy is verified.

Key words

near space / UAV / energy system / photovoltaic cell / energy storage unit / scheduling algorithm / capacity utilization

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Li Xinfang, Zeng Guohong, Chen Tianmu. ENERGY SCHEDULING STRATEGY OF NEAR SPACE SOLAR POWERED VEHILCLE[J]. Acta Energiae Solaris Sinica. 2023, 44(2): 288-297 https://doi.org/10.19912/j.0254-0096.tynxb.2021-1032

References

[1] 张健, 王江三, 耿延升, 等. 高空长航时太阳能无人机的技术挑战[J]. 航空科学技术, 2020, 31(4): 14-20.
ZHANG J, WANG J S, GENG Y S, et al.Technology challenges for high altitude long endurance solar powered UAV[J]. Aeronautical science & technology, 2020, 31(4): 14-20.
[2] 马东立, 张良, 杨穆清, 等. 超长航时太阳能无人机关键技术综述[J]. 航空学报, 2020, 41(3): 34-63.
MA D L, ZHANG L, YANG M Q, et al.Review of key technologies of ultra-endurance solar powered unmanned aerial vehicle[J]. Acta aeronautica et astronautica sinica,2020, 41(3): 34-63.
[3] 朱立宏, 孙国瑞, 呼文韬, 等. 太阳能无人机能源系统的关键技术与发展趋势[J]. 航空学报, 2020, 41(3): 85-96.
ZHU L H, SUN G R, HU W T, et al.Key technology and development trend of energy system in solar powered unmanned aerial vehicles[J]. Acta aeronautica et astronautica sinica, 2020, 41(3): 85-96.
[4] 刘邦银, 梁超辉, 段善旭. 直流模块式建筑集成光伏系统的拓扑研究[J]. 中国电机工程学报, 2008, 28(20): 99-104.
LIU B Y, LIANG C H, DUAN S X.Research on topology of DC-module-based building integrated photovoltaic system[J]. Proceedings of the CSEE, 2008, 28(20): 99-104.
[5] SCLOCCHI M.分布式MPPT提高太阳能光伏系统的效率[J]. 集成电路应用, 2009(12): 40-41.
SCLOCCHI M.Distributed MPPT improves the efficiency of solar photovoltaic systems[J]. Application of IC, 2009(12): 40-41.
[6] 曾国宏, 郭亚男, 吴学智, 等. 基于光储模块的发电系统及其控制策略研究[J]. 电力电子技术, 2019, 53(6): 72-75, 103.
ZENG G H, GUO Y N, WU X Z, et al.A photovoltaic generating system based on photovoltaic-storage modules and the study of control strategy[J]. Power electronics, 2019, 53(6): 72-75, 103.
[7] 曾国宏, 潘一飞, 吴学智. 新型分布式光伏-储能系统设计及控制策略的研究[J]. 电源学报, 2020, 18(4): 144-150.
ZENG G H, PAN Y F, WU X Z.Research on design and control strategy for novel distributed PV-battery system[J]. Journal of power supply, 2020, 18(4): 144-150.
[8] 彭春华, 余愿, 孙惠娟. 基于源网荷协同优化的配电网光储联合系统规划[J]. 电网技术, 2019, 43(11): 3944-3951.
PENG C H, YU Y, SUN H J.Planning of combined PV-ESS system for distribution network based on source-network-load collaborative optimization[J]. Power system technology, 2019, 43(11): 3944-3951.
[9] 林舜江, 杨智斌, 卢苑, 等. 含光伏的天然气冷热电联供园区微网能量优化调度[J]. 华南理工大学学报(自然科学版), 2019, 47(3): 9-19.
LIN S J, YANG Z B, LU Y, et al.Optimal energy scheduling of photovoltaic natural gas, cooling, heating and power co-supply parkmicro-network[J]. Journal of South China University of Technology (natural science edition), 2019, 47(3): 9-19.
[10] 高昇宇, 柳志航, 卫志农, 等. 城市智能光储充电塔自适应鲁棒日前优化调度[J]. 电力系统自动化, 2019, 43(20): 39-48.
GAO S Y, LIU Z H, WEI Z N, et al.Adaptive robust day-ahead optimal dispatch for urban smart photovoltaic storage and charging tower[J]. Automation of electric power systems, 2019, 43(20): 39-48.
[11] 肖浩, 裴玮, 孔力. 基于模型预测控制的微电网多时间尺度协调优化调度[J]. 电力系统自动化, 2016, 40(18): 7-14, 55.
XIAO H, PEI W, KONG L.AC and DC fault ride-through technology for wind power integration via VSC-HVDC overhead lines[J]. Automation of electric power systems, 2016, 40(18): 7-14, 55.
[12] 冯智慧, 吕林, 许立雄. 基于能量枢纽的沼-风-光全可再生能源系统日前-实时两阶段优化调度模型[J]. 电网技术, 2019, 43(9): 3101-3109.
FENG Z H, LYU L, XU L X.Two-stage optimal dispatch model of day-ahead and real-time forbiogas-wind-solar fully renewable energy system based on energy hub[J]. Power system technology, 2019, 43(9): 3101-3109.
[13] 陈中, 陈妍希, 车松阳. 新能源汽车一体充能站框架及能量优化调度方法[J]. 电力系统自动化, 2019, 43(24): 41-49.
CHEN Z, CHEN Y X, CHE S Y.Framework of integrated charging station for renewable energy vehicle and energy optimal dispatching method[J]. Automation of electric power systems, 2019, 43(24): 41-49.
[14] 王恭, 张栋, 李相俊, 等. 考虑弃光的光储联合电站输出功率控制策略[J]. 太阳能学报, 2019, 40(3): 817-824.
WANG G, ZHANG D, LI X J, et al.Control strategy of phontovoltaic-energy storage power generation system considering phontovoltaic power curtailment[J]. Acta energiae solaris sinica, 2019, 40(3): 817-824.
[15] 路欣怡, 刘念, 陈征, 等. 电动汽车光伏充电站的多目标优化调度方法[J]. 电工技术学报, 2014, 29(8): 46-56.
LU X Y, LIV N, CHEN Z, et al.Multi-objective optimal scheduling for PV-assisted charging station of electric vehicle[J]. Transactions of China Electroltechnical Society, 2014, 29(8): 46-56.
[16] 杜进桥, 田杰, 秦毅, 等. 基于多目标优化的含电动汽车充换储一体化设施的微电网能量管理及协调控制策略研究[J]. 机电信息, 2020(14): 4-6.
DU J Q, TIAN J, QIN Y, et al.Research on energy management and coordinated control strategy of microgrid including electric vehicle charging, swap and storage integrated facilities based on multi-objective optimization[J]. Mechanical and electrical information, 2020(14): 4-6.
[17] 李睿雪, 胡泽春. 电动公交车光储充电站日运行随机优化策略[J]. 电网技术, 2017, 41(12): 3772-3780.
LI R X, HU Z C.Stochastic optimization strategy for daily operation of electric bus charging station with PV and energy storage[J]. Power system technology, 2017, 41(12): 3772-3780.
[18] 李雪, 张琳玮, 姜涛, 等. 基于拉格朗日乘子的电力系统安全域边界通用搜索方法[J]. 中国电机工程学报, 2021, 41(15): 5139-5153.
LI X, ZHANG L W, JIANG T, et al.General algorithm for exploring security region boundary in power systems using Lagrange multiplier[J]. Proceedings of the CSEE, 2021, 41(15): 5139-5153.
[19] 王宏伦, 黄宇. 太阳能无人机能量生产估计模型及应用[J]. 战术导弹技术, 2017(1): 9-16, 33.
WANG H L, HUANG Y.An integrated energy model of solar-powered unmanned aerial vehicles for predicting collected solar energy and application[J]. Tactical missile technology, 2017(1): 9-16, 33.