考虑分时电价下基于改进蛇算法的混合能源微电网群低碳经济优化调度研究

李宏玉; 续海宝; 张浪; 周刚

doi:10.19912/j.0254-0096.tynxb.2023-1790

PDF(2117 KB)

太阳能学报 ›› 2025, Vol. 46 ›› Issue (3) : 132-140. DOI: 10.19912/j.0254-0096.tynxb.2023-1790

考虑分时电价下基于改进蛇算法的混合能源微电网群低碳经济优化调度研究

李宏玉¹, 续海宝¹, 张浪¹, 周刚²

作者信息 +

RESEARCH ON LOW CARBON ECONOMIC OPTIMAL DISPATCH OF HYBRID ENERGY MICROGRID GROUP BASED ON IMPROVED SNAKE ALGORITHM UNDER TIME-OF-USE ELECTRICITY PRICE

Li Hongyu¹, Xu Haibao¹, Zhang Lang¹, Zhou Gang²

Author information +

文章历史 +

摘要

在考虑风光不确定性条件下建立一个低碳背景下含电转气的多微网架构分层管理的能量调度模型。上层构建一个混合能源运营商模型,利用改进的蛇算法寻求运营商与微电网群的最优内部电价,在进行功率交换和主网应用分时电价条件下,实现电氢互转,分别协调与主网和微网群调度;下层利用求解器构建微网群间实现相互协作调度模型,将梯度碳交易机制引入各微电网调度阶段。通过仿真验证,该模型最终通过分时电价以及运营商储能储氢实现对主网削峰填谷的作用,同时在阶梯式碳交易模式下,降低碳排,考虑到环境成本,实现微网群与协同运营商的合作联盟。

Abstract

In this paper, an energy dispatching model for hierarchical management of multi-microgrid architecture with electricity-to-gas in low-carbon background is established under the condition of considering the uncertainty of wind and solar. In the upper layer, a hybrid energy operator model is constructed, and the improved snake algorithm is used to seek the optimal internal electricity price between the operator and the microgrid group, and the power and hydrogen transfer is realized under the condition of power exchange and time-of-use electricity price applied to the main network, and the dispatch of the main network and the microgrid group is coordinated respectively. The lower layer uses the solver to construct a mutual cooperative scheduling model between microgrid groups, and introduces the gradient carbon trading mechanism into the dispatching stage of each microgrid. Through simulation verification, the model finally realizes the role of peak shaving and valley filling of the main grid through time-of-use electricity price and energy storage and hydrogen storage by operators, and at the same time, reduces carbon emissions in the stepped carbon trading mode, considers the environmental cost, and realizes the cooperation alliance between the microgrid group and the cooperative operator.

导出引用

李宏玉, 续海宝, 张浪, 周刚. 考虑分时电价下基于改进蛇算法的混合能源微电网群低碳经济优化调度研究[J]. 太阳能学报. 2025, 46(3): 132-140 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1790

Li Hongyu, Xu Haibao, Zhang Lang, Zhou Gang. RESEARCH ON LOW CARBON ECONOMIC OPTIMAL DISPATCH OF HYBRID ENERGY MICROGRID GROUP BASED ON IMPROVED SNAKE ALGORITHM UNDER TIME-OF-USE ELECTRICITY PRICE[J]. Acta Energiae Solaris Sinica. 2025, 46(3): 132-140 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1790

中图分类号： TM734

参考文献

[1] 陈冠益, 夏晒歌, 李婉晴, 等. 面向碳中和的生物柴油制备及应用研究进展[J]. 太阳能学报, 2022, 43(9): 343-353.
CHEN G Y, XIA S G, LI W Q, et al.Research progress in preparation and application of biodiesel for carbon neutralty[J]. Acta energiae solaris sinica, 2022, 43(9): 343-353.
[2] 谭九鼎, 李帅兵, 李明澈, 等. 计及不确定性的分布式微网参与电网优化调度方法综述[J]. 综合智慧能源, 2024, 46(1): 38-48.
TAN J D, LI S B, LI M C, et al.Optimized scheduling of the power grid with participation of distributed microgrids considering their uncertainties[J]. Integrated intelligent energy, 2024, 46(1): 38-48.
[3] 南斌, 董树锋, 唐坤杰, 等. 考虑需求响应和源荷不确定性的光储微电网储能优化配置[J]. 电网技术, 2023, 47(4): 1340-1352.
NAN B, DONG S F, TANG K J, et al.Optimal configuration of energy storage in PV-storage microgrid considering demand response and uncertainties in source and load[J]. Power system technology, 2023, 47(4): 1340-1352.
[4] 米阳, 李战强, 吴彦伟, 等. 基于两级需求响应的并网微电网双层优化调度[J]. 电网技术, 2018, 42(6): 1899-1906.
MI Y, LI Z Q, WU Y W, et al.Bi-layer optimal dispatch of grid-connected microgrid based on two-stage demand response[J]. Power system technology, 2018, 42(6): 1899-1906.
[5] 刘林鹏, 朱建全, 陈嘉俊, 等. 基于柔性策略-评价网络的微电网源储协同优化调度策略[J]. 电力自动化设备, 2022, 42(1): 79-85.
LIU L P, ZHU J Q, CHEN J J, et al.Cooperative optimal scheduling strategy of source and storage in microgrid based on soft actor-critic[J]. Electric power automation equipment, 2022, 42(1): 79-85.
[6] 桑博, 张涛, 刘亚杰, 等. 多微电网能量管理系统研究综述[J]. 中国电机工程学报, 2020, 40(10): 3077-3093.
SANG B, ZHANG T, LIU Y J, et al.Energy management system research of multi-microgrid: a review[J]. Proceedings of the CSEE, 2020, 40(10): 3077-3093.
[7] 芮涛, 李国丽, 胡存刚, 等. 考虑电价机制的微电网群主从博弈优化方法[J]. 中国电机工程学报, 2020, 40(8): 2535-2546.
RUI T, LI G L, HU C G, et al.Stackelberg game optimization method for microgrid cluster considering electricity price mechanism[J]. Proceedings of the CSEE, 2020, 40(8): 2535-2546.
[8] 焦建芳, 王安杰, 王光, 等. 考虑储能寿命和通信故障的微电网群优化调度[J]. 系统仿真学报, 2024, 36(2): 352-362.
JIAO J F, WANG A J, WANG G, et al.Optimal dispatch of microgrid clusters considering energy storage life and communication failures[J]. Journal of system simulation, 2024, 36(2): 352-362.
[9] 毛亚哲, 何柏娜, 王德顺, 等. 基于改进深度强化学习的智能微电网群控制优化方法[J]. 智慧电力, 2021, 49(3): 19-25, 58.
MAO Y Z, HE B N, WANG D S, et al.Optimization method for smart multi-microgrid control based on improved deep reinforcement learning[J]. Smart power, 2021, 49(3): 19-25, 58.
[10] 阚圣钧, 魏少雄, 赵继钢, 等. 考虑分时电价的微电网储能容量优化配置[J]. 分布式能源, 2022, 7(2): 44-49.
KAN S J, WEI S X, ZHAO J G, et al.Optimal allocation of micro-grid energy storage capacity considering time-of-use electricity price[J]. Distributed energy, 2022, 7(2): 44-49.
[11] 董海, 曹晓兰. 基于策略驱动的混合能源微电网动态调度[J]. 太阳能学报, 2023, 44(7): 22-29.
DONG H, CAO X L.Dynamic dispatching of hybrid energy microgrids based on strategy-driven[J]. Acta energiae solaris sinica, 2023, 44(7): 22-29.
[12] 赵峰, 罗鑫, 高锋阳. 考虑网内实时电价的微电网经济优化运行研究[J]. 太阳能学报, 2020, 41(9): 53-60.
ZHAO F, LUO X, GAO F Y.Research on optimal operation for micro-grid considering real-time price[J]. Acta energiae solaris sinica, 2020, 41(9): 53-60.
[13] 程杉, 陈梓铭, 王瑞, 等. 基于混合博弈的多微电网双层协调优化调度[J]. 电力自动化设备, 2021, 41(8): 41-46.
CHENG S, CHEN Z M, WANG R, et al.Double-layer coordinated optimal dispatching of multi-microgrid based on mixed game[J]. Electric power automation equipment, 2021, 41(8): 41-46.
[14] 余娟, 时权妍, 杨知方, 等. 考虑电解水与甲烷化运行特性的电转气系统日前调度方法[J]. 电力系统自动化, 2019, 43(18): 18-25.
YU J, SHI Q Y, YANG Z F, et al.Day-ahead scheduling method of power-to-gas system considering operation characteristics of water electrolysis and methanation[J]. Automation of electric power systems, 2019, 43(18): 18-25.
[15] 蔡钦钦, 肖宇, 朱永强. 计及电转氢和燃料电池的电热微网日前经济协调调度模型[J]. 电力自动化设备, 2021, 41(10): 107-112, 161.
CAI Q Q, XIAO Y, ZHU Y Q.Day-ahead economic coordination dispatch model of electricity-heat microgrid considering P2H and fuel cells[J]. Electric power automation equipment, 2021, 41(10): 107-112, 161.
[16] 吴盛军, 李群, 刘建坤, 等. 基于储能电站服务的冷热电多微网系统双层优化配置[J]. 电网技术, 2021, 45(10): 3822-3832.
WU S J, LI Q, LIU J K, et al.Bi-level optimal configuration for combined cooling heating and power multi-microgrids based on energy storage station service[J]. Power system technology, 2021, 45(10): 3822-3832.
[17] 卫志农, 张思德, 孙国强, 等. 计及电转气的电-气互联综合能源系统削峰填谷研究[J]. 中国电机工程学报, 2017, 37(16): 4601-4609, 4885.
WEI Z N, ZHANG S D, SUN G Q, et al.Power-to-gas considered peak load shifting research for integrated electricity and natural-gas energy systems[J]. Proceedings of the CSEE, 2017, 37(16): 4601-4609, 4885.
[18] 秦婷, 刘怀东, 王锦桥, 等. 基于碳交易的电-热-气综合能源系统低碳经济调度[J]. 电力系统自动化, 2018, 42(14): 8-13, 22.
QIN T, LIU H D, WANG J Q, et al.Carbon trading based low-carbon economic dispatch for integrated electricity-heat-gas energy system[J]. Automation of electric power systems, 2018, 42(14): 8-13, 22.
[19] 韩莹, 于三川, 李荦一, 等. 计及阶梯式碳交易的风光氢储微电网低碳经济配置方法[J]. 高电压技术, 2022, 48(7): 2523-2533.
HAN Y, YU S C, LI L Y, et al.Low-carbon and economic configuration method for solar hydrogen storage microgrid including stepped carbon trading[J]. High voltage engineering, 2022, 48(7): 2523-2533.
[20] HASHIM F A, HUSSIEN A G.Snake Optimizer: a novel meta-heuristic optimization algorithm[J]. Knowledge-based systems, 2022, 242: 108320.
[21] 欧阳婷, 蔡晔, 王炜宇, 等. 计及风电、光伏预测不确定性的抽水蓄能日前全调度优化[J]. 综合智慧能源, 2022, 44(11): 20-27.
OUYANG T, CAI Y, WANG W Y, et al.Overall day-ahead scheduling optimization for pumped-storage power stations considering the uncertainty of wind and photovoltaic power prediction[J]. Integrated intelligent energy, 2022, 44(11): 20-27.