TWO-STAGE OPTIMAL DISPATCHING OF WIND POWER-PHOTOVOLTAIC-THERMAL POWER-PUMPED STORAGE COMBINED SYSTEM

Luo Yuanxiang, Wang Yuhang, Liu Cheng, Fan Lidong

Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (1) : 500-508.

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (1) : 500-508. DOI: 10.19912/j.0254-0096.tynxb.2021-0945

TWO-STAGE OPTIMAL DISPATCHING OF WIND POWER-PHOTOVOLTAIC-THERMAL POWER-PUMPED STORAGE COMBINED SYSTEM

  • Luo Yuanxiang, Wang Yuhang, Liu Cheng, Fan Lidong
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Abstract

Grid-connection of wind power and photovoltaic is an effective means to reduce pollutant discharge from traditional coal-fired power plants. However, there is uncertainty in its intermittent energy output and the high-proportioned grid-connection results in challenges to the stable operation of electric power systems. In view of this, this paper utilizes the advantages of pumped storage in large capacity and fast response to establish a two-stage dynamic scheduling model of wind power, photovoltaic, thermal power and pumped storage. The long-time scale is aimed at minimizing total cost, so as to optimize controllable power output through considering the cost of system operation, emissions of SO2, NOX and PM, and punishment from wind and photovoltaic abandonment in an integrated way. With the long-time scale as the benchmark, the short-time scale is to continuously solve the output increment on the basis of the model predictive control principle and minimize the active output deviation of the pumped storage unit so as to enhance the smoothness of the scheduling. Finally, the actual data of pumped storage units in a region of northeast China and the improved IEEE-30 node system simulation are followed to verify the effectiveness of the model proposed herein, so as to bring down the pollutant-discharge level of the system and raise the capacity of the power system for consumption of wind power and photovoltaics.

Key words

model predictive control / scheduling algorithms / renewable energy resources / pumped storage power plants / environmental cost

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Luo Yuanxiang, Wang Yuhang, Liu Cheng, Fan Lidong. TWO-STAGE OPTIMAL DISPATCHING OF WIND POWER-PHOTOVOLTAIC-THERMAL POWER-PUMPED STORAGE COMBINED SYSTEM[J]. Acta Energiae Solaris Sinica. 2023, 44(1): 500-508 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0945

References

[1] 吴志力, 刘艳茹, 崔凯. “十四五” 能源转型步伐加快配电网如何高质量发展[N]. 国家电网报, 2021-03-09(008).
WU Z L, LIU Y R, CUI K. How to accelerate the high-quality development of the distribution network during the 14th Five-Year Plan of energy transformation[N]. State grid news, 2021-03-09(008).
[2] 崔杨, 周海涛, 严干贵, 等. 考虑环境成本及网络约束的风-火联合发电调度[J]. 电网技术, 2017, 41(11): 3457-3462.
CUI Y, ZHOU H T, YAN G G, et al.Wind-fire combined power generation dispatch considering environmental costs and network constraints[J]. Power system technology, 2017, 41(11): 3457-3462.
[3] 张明理, 潘霄, 侯依昕, 等. 计及风电消纳的源-荷-储环保经济型调度策略[J]. 可再生能源, 2019, 37(9): 1295-1302.
ZHANG M L, PAN X, HOU Y X, et al.Source-load-storage environmental protection economic dispatch strategy considering wind power consumption[J]. Renewable energy, 2019, 37(9): 1295-1302.
[4] 张志义, 余涛, 李昊飞, 等. 考虑大气污染物时空分布的多区域电力系统调度及其多目标分布式优化[J]. 电网技术, 2020, 44(3): 1047-1058.
ZHANG Z Y, YU T, LI H F, et al.Multi-regional power system dispatch and multi-objective distributed optimization considering the temporal and spatial distribution of air pollutants[J]. Power system technology, 2020, 44(3): 1047-1058.
[5] ZHANG X P, ZHANG Y Z.Environment-friendly and economical scheduling optimization for integrated energy system considering power-to-gas technology and carbon capture power plant[J]. Journal of cleaner production, 2020, 276(5): 30-36.
[6] 林俐, 岳晓宇, 许冰倩, 等. 计及抽水蓄能和火电深度调峰效益的抽蓄-火电联合调峰调用顺序及策略[J]. 电网技术, 2021, 45(1): 20-32.
LIN L, YUE X Y, XU B Q, et al.Pumped storage-thermal power combined peak shaving sequence and strategy taking into account the benefits of pumped storage and thermal power deep peak shaving[J]. Power system technology, 2021, 45(1): 20-32.
[7] 张国斌, 陈玥, 张佳辉, 等. 风-光-水-火-抽蓄联合发电系统日前优化调度研究[J]. 太阳能学报, 2020, 41(8): 79-85.
ZHANG G B, CHEN Y, ZHANG J H, et al.Research on day-ahead optimal dispatching of wind power, photovoltaic, hydropower, thermal power, pumped Storage combined power generation system[J]. Acta energia solaris sinica, 2020, 41(8): 79-85.
[8] 马伟, 王玮, 吴学智, 等. 光储协调互补平抑功率波动策略及经济性分析[J]. 电网技术, 2018, 42(3): 730-737.
MA W, WANG W, WU X Z, et al.Optical-storage coordinated and complementary strategies to suppress power fluctuations and economic analysis[J]. Power system technology, 2018, 42(3): 730-737.
[9] 夏鹏, 刘文颖, 张尧翔, 等. 考虑风电高阶不确定性的分布式鲁棒优化调度模型[J]. 电工技术学报, 2020, 35(1): 189-200.
XIA P, LIU W Y, ZHANG Y X, et al.Distributed robust optimal scheduling model considering the high-order uncertainty of wind power[J]. Transactions of China Electrotechnical Society, 2020, 35(1): 189-200.
[10] 金力, 房鑫炎, 蔡振华, 等. 考虑特性分布的储能电站接入的电网多时间尺度源储荷协调调度策略[J]. 电网技术, 2020, 44(10): 3641-3650.
JIN L, FANG X Y, CAI Z H, et al.Multi-time scale source storage and load coordinated dispatching strategy for power grids considering characteristic distribution of energy storage power stations[J]. Power system technology, 2020, 44(10): 3641-3650.
[11] 江千军, 王磊, 桂前进, 等. 考虑多时间尺度灵活性的含大规模风电电力系统机组组合研究[J]. 智慧电力, 2021, 49(1): 35-41, 70.
JIANG Q J, WANG L, GUI Q J, et al.Research on unit commitment of large-scale wind power system considering multi-time scale flexibility[J]. Smart electric power, 2021, 49(1): 35-41, 70.
[12] 吴岩, 王玮, 吴学智, 等. 微电网跟踪调度计划双层双时间尺度实时控制策略[J]. 电力自动化设备, 2021, 41(1): 120-134.
WU Y, WANG W, WU X Z, et al.Two-layer dual-time scale real-time control strategy for microgrid tracking and dispatching plan[J]. Electric power automation equipment, 2021, 41(1): 120-134.
[13] 刘立阳, 吴军基, 孟绍良. 基于预测控制的含风电滚动优化调度[J]. 电工技术学报, 2017, 32(17): 75-83.
LIU L Y, WU J J, MENG S L.Rolling optimal scheduling of wind power based on predictive control[J]. Transactions of China Electrotechnical Society, 2017, 32(17): 75-83.
[14] 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.Multi-time scale coordinated optimal dispatch of microgrid based on model predictive control[J]. Automation of electric power systems, 2016, 40(18): 7-14, 55.
[15] 王磊, 周建平, 朱刘柱, 等. 基于分布式模型预测控制的综合能源系统多时间尺度优化调度[J]. 电力系统自动化, 2021, 45(13): 57-65.
WANG L, ZHOU J P, ZHU L Z, et al.Multi-time scale optimal dispatch of integrated energy system based on distributed model predictive control[J]. Automation of electric power systems, 2021, 45(13): 57-65.
[16] 董雷, 陈卉, 蒲天骄, 等. 基于模型预测控制的主动配电网多时间尺度动态优化调度[J]. 中国电机工程学报, 2016, 36(17): 4609-4617.
DONG L, CHEN H, PU T J, et al.Active distribution network multi-time scale dynamic optimal scheduling based on model predictive control[J]. Proceedings of the CSEE, 2016, 36(17): 4609-4617.
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