考虑碳自然循环的离网型风/光-火联合供能系统容量优化配置

冉亮; 费斯奇; 袁铁江; 吕清泉; 李国锋

doi:10.19912/j.0254-0096.tynxb.2021-0958

PDF(1757 KB)

太阳能学报 ›› 2023, Vol. 44 ›› Issue (1) : 509-515. DOI: 10.19912/j.0254-0096.tynxb.2021-0958

考虑碳自然循环的离网型风/光-火联合供能系统容量优化配置

冉亮^1,2, 费斯奇², 袁铁江², 吕清泉¹, 李国锋²

作者信息 +

OPTIMAL CAPACITY ALLOCATION OF OFF-GRID WIND/PV-THERMAL ENERGY SUPPLY SYSTEM CONSIDERING THE CARBON CYCLE

Ran Liang^1,2, Fei Siqi², Yuan Tiejiang², Lyu Qingquan¹, Li Guofeng²

Author information +

文章历史 +

摘要

针对合理规划离网型风/光-火联合供能系统使其达到碳中和要求的问题,首先考虑风光出力不确定性对新能源为主的离网型供能系统可靠性的影响,提出离网型风/光-火联合供能系统的基本结构;其次,基于自然界可消纳CO₂上限与世界能源需求总量之间的关系,建立供能系统的碳自然循环模型;以系统年总费用值最小为目标,建立供能系统容量优化配置数学模型,并采用粒子群算法求解。基于某实际离网型联合供能系统算例分析表明：所述容量优化配置方法在以较低成本保证供能可靠性的同时,可实现离网型风/光-火联合供能系统CO₂的“净零排放”。

Abstract

This paper developed an optimal configuration method for an off-grid combined wind/PV-thermal energy supply system considering the natural carbon cycle. Firstly, we analyzed the influence of the uncertainty of wind and PV energy output on the reliability of the functional system and proposed the basic structure of the off-grid wind/PV-thermal combined energy supply system. Secondly, a natural carbon cycle model of functional systems is established based on the relationship between the maximum CO₂ absorbed by nature and the total energy demand of the world. Finally, we established a mathematical model for capacity optimal allocation of the power supply system, aiming at minimizing the total annual cost of the system, and solved it using a particle swarm optimization algorithm. The results of numerical experiments show that the proposed method achieves “net zero emission” of CO₂ in an off-grid wind/PV-thermal combined power supply system while ensuring the reliability of the power supply at a lower cost.

导出引用

冉亮, 费斯奇, 袁铁江, 吕清泉, 李国锋. 考虑碳自然循环的离网型风/光-火联合供能系统容量优化配置[J]. 太阳能学报. 2023, 44(1): 509-515 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0958

Ran Liang, Fei Siqi, Yuan Tiejiang, Lyu Qingquan, Li Guofeng. OPTIMAL CAPACITY ALLOCATION OF OFF-GRID WIND/PV-THERMAL ENERGY SUPPLY SYSTEM CONSIDERING THE CARBON CYCLE[J]. Acta Energiae Solaris Sinica. 2023, 44(1): 509-515 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0958

中图分类号： TM73

参考文献

[1] KRARTI M, ALDUBYAN M.Role of energy efficiency and distributed renewable energy in designing carbon neutral residential buildings and communities: case study of Saudi Arabia[J]. Energy & buildings, 2021, 250: 111309.
[2] 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 optimization of day-ahead dispatching of wind power- photovoltaic-hydropower-thermal power-pumped storage combined power generation system[J]. Acta energiae solaris sinica, 2020, 41(8): 79-85.
[3] 高荣刚, 杨洋, 袁铁江, 等. 面向储能容量配置数据驱动的负荷分区[J]. 热力发电, 2020, 49(8): 97-103.
GAO R G, YANG Y, YUAN T J, et al.Data driven load partition for energy storage capacity configuration[J]. Thermal power generation, 2020, 49(8): 97-103.
[4] 孙珂, 赵鹏飞, 韩晓男, 等. 考虑高比例可再生能源出力不确定性的电力流规划方法[J]. 电网技术, 2020, 44(1): 79-85.
SUN K, ZHAO P F, HAN X N, et al.Electricity flow planning method for high penetration of renewable energy[J]. Power system technology, 2020, 44(1): 79-85.
[5] CHANG J F, QUN Y.Evolution model of power failure considering new energy uncertainty[J]. IOP conference series: earth and environmental science, 2019, 237(6): 62042-62042.
[6] 丁明, 林玉娟. 考虑风光荷不确定性的随机生产模拟[J]. 太阳能学报, 2018, 39(10): 2937-2944.
DING M, LIN Y J.Probabilistic production simulation considering randomness of renewable wind power, photovoltaic and load[J]. Acta energies solaris sinica, 2018, 39(10): 2937-2944.
[7] 高春辉, 肖冰, 尹宏学, 等. 新能源背景下储能参与火电调峰及配置方式综述[J]. 热力发电, 2019, 48(10): 38-43.
GAO C H, XIAO B, YIN H X, et al.Energy storage participating in thermal power peaking and configuration in background of new energy: a review[J]. Thermal power generation, 2019, 48(10): 38-43.
[8] 孙玉树, 唐西胜, 孙晓哲, 等. 基于MPC-HHT的多类型储能协调控制策略研究[J]. 中国电机工程学报, 2018, 38(9): 2580-2588, 2826.
SUN Y S, TANG X S, SUN X Z, et al.Research on multi-type energy storage coordination control strategy based on MPC-HHT[J]. Proceedings of the CSEE, 2018, 38(9): 2580-2588, 2826.
[9] 刘辉, 葛俊, 巩宇, 等. 风电场参与电网一次调频最优方案选择与风储协调控制策略研究[J]. 全球能源互联网, 2019, 2(1): 44-52.
LIU H, GE J, GONG Y, et al.Optimization scheme selection of wind farm participation in grid primary frequency modulation and study of wind-storage coordination control strategy[J]. Journal of global energy interconnection, 2019, 2(1): 44-52.
[10] NASSAR R, MASTROGIACOMO J, BASTEMAN- HEMPHILL W, et al.Advances in quantifying power plant CO₂ emissions with OCO-2[J]. Remote sensing of environment, 2021, 264:112579.
[11] 蔡国伟, 西禹霏, 杨德友, 等. 基于风-氢的气电热联合系统模型的经济性能分析[J]. 太阳能学报, 2019, 40(5): 1465-1471.
CAI G W, XI Y F, YANG D Y, et al.Economic performance analysis of model of combined gas-heat-power system based on wind-hydrogen[J]. Acta energiae solaris sinica, 2019, 40(5): 1465-1471.
[12] 李彦哲, 郭小嘉, 董海鹰, 等. 风/光/储微电网混合储能系统容量优化配置[J]. 电力系统及其自动化学报, 2020, 32(6): 123-128.
LI Y Z, GUO X J, DONG H Y, et al.Optimal capacity configuration of wind/PV/storage hybrid energy storage system in microgrid[J]. Proceedings of the CSU-EPSA, 2020, 32(6): 123-128.
[13] 戴璐平, 陈佩莉, 钱毅慧. 冷热电微电网分布式电源的区间优化模型[J]. 电测与仪表, 2018, 55(22): 59-66.
DAI L P, CHEN P L, QIAN Y H.Internal optimal model for distributed generators in a multi-energy micro-grid[J]. Electrical measurement & instrumentation, 2018, 55(22): 59-66.
[14] 梁阳豆, 宁阳天, 杨有慧, 等. 区域电网调峰调频电源需求与容量配置分析[J]. 电力设备管理, 2019(5): 22-23, 47.
LIANG Y D, NING Y T, YANG Y H, et al.Analysis on demand and capacity configuration of peak modulation and FM power supply in regional power grid[J]. Electric power equipment management, 2019(5): 22-23, 47.
[15] 祁超. 生物质和太阳能互补的分布式供能系统研究[D]. 北京: 华北电力大学, 2018: 5-6.
QI C.Research on distributed energy supply system with complementary biomass and solar energy[D]. Beijing: North China Electric Power University, 2018: 5-6.
[16] 陈曦, 曹杰, 盛勇, 等. 基于布谷鸟搜索算法的天然气储气库综合能源系统容量优化配置研究[J]. 重庆理工大学学报(自然科学版), 2021, 35(6): 209-219.
CHEN X, CAO J, SHENG Y, et al.Research on optimal allocation of comprehensive energy system capacity of natural gas storage based on cuckoo algorithm[J]. Journal of Chongqing University of Technology (natural science edition), 2021, 35(6): 209-219.
[17] 周欣欣, 刘魁星, 刘书贤. 应用于分布式能源系统的设备选择和容量配置模型[J]. 热能动力工程, 2019, 34(7): 24-29.
ZHOU X X, LIU K X, LIU S X.Equipment selection and capacity allocation model for distributed energy systems[J]. Journal of engineering for thermal energy and power, 2019, 34(7): 24-29.
[18] 王雁凌, 李蓓, 崔航. 天然气分布式能源站综合价值分析[J]. 电力系统自动化, 2016, 40(1): 136-142.
WANG Y L, LI P, CUI H.Comprehensive value analysis for gas distributed energy station[J]. Automation of electric power systems, 2016, 40(1): 136-142.
[19] 王宗礼, 李明, 陈建, 等. 基于改进蚁群算法的分布式电源容量优化配置[J]. 中国电力, 2016, 49(9): 51-55.
WANG Z L, LI M, CHEN J, et al.Optimal allocation of distributed power supply capacity based on improved ant colony algorithm[J]. Electric power, 2016, 49(9): 51-55.
[20] 丁胜, 周博滔, 胡宝华. 基于NSGA-Ⅱ算法的小型分布式能源系统设计优化[J]. 太阳能学报, 2021, 42(1): 438-445.
DING S, ZHOU B T, HU B H.Design optimization of small distributed energy system based on NSGA-Ⅱ algorithm[J]. Acta energiae solaris sinica, 2021, 42(1): 438-445.
[21] 丁明, 王波, 赵波,等. 独立风光柴储微网系统容量优化配置[J]. 电网技术, 2013, 37(3): 575-581.
DING M, WANG B, ZHAO B, et al.Configuration optimization of capacity of standalone PV-wind-diesel-battery hybrid microgrid[J]. Power system technology, 2013, 37(3): 575-581.
[22] 赵晶晶, 徐传琳, 吕雪, 等. 微电网一次调频备用容量与储能优化配置方法[J]. 中国电机工程学报, 2017, 37(15): 4324-4332, 4572.
ZHAO J J, XU C L, LYU X, et al.Optimization of micro-grid primary frequency regulation reserve capacity and energy storage system[J]. Proceedings of the CSEE, 2017, 37(15): 4324-4332, 4572.