基于改进鲸鱼优化算法的共享储能优化配置研究

doi:10.3969/j.issn.2097-0706.2023.09.009

摘要/Abstract

摘要：

针对新能源消纳场景中储能资源闲置和商业模式缺乏的现象，在保证储能功率容量和消纳目标相匹配的基础上，提出了一种基于改进鲸鱼优化算法（WOA）的共享储能优化配置方法。该方法基于发电侧共享储能运行模式，考虑储能电站运行状态、并网功率需求约束下储能在新能源消纳场景的投资运维成本和效益。建立以共享储能系统收益最大为目标的优化配置模型，结合新能源出力及并网功率需求，使用改进WOA对模型进行求解。通过算例对比分析表明：配置共享储能后提升了新能源消纳率，提高了共享储能的投资回报率，与独立储能相比较，储能利用率、消纳调节能力和经济性都得到了大幅提高，能有效弥补因新能源出力不足导致的并网功率缺额，有利于共享储能大规模投资建设。

关键词: 新能源消纳, 共享储能, 优化配置, 发电侧, 改进鲸鱼优化算法, 功率缺额

Abstract:

Since energy storage resources always be left unused and lack proper business modes in the renewable energy consumption，an optimal allocation method of shared energy storage based on improved whale optimization algorithm（WOA） is proposed to match the power capacity of energy storage systems to new energy consumption target. Taking sharing mode for energy storage on power generation side，this method considers the investment， operation and maintenance costs and benefits of the energy storage system assisting renewable energy consumption，under the constraints of its operation and grid-connected power. Combined the renewable energy output with grid-connected power，an optimal configuration model aiming at maximizing the revenue of the shared energy storage system is established，and solved by improved WOA. The contrastive analysis on examples shows that energy storage sharing can improve the consumption rate of new energy and the return on investment of energy storage systems. Compared with independent energy storage， energy storage sharing mode improves the utilization rate and economy of energy storage devices，and adjustment ability on new energy consumption，which can effectively make up for the grid-connected power shortage caused by new energy generation. Large-scale investment in shared energy storage systems is promising.

Key words: renewable energy consumption, energy storage sharing, optimal configuration, power generation side, improved whale optimization algorithm, power shortage

中图分类号:

TK01

栗庆根, 孙娜, 董海鹰. 基于改进鲸鱼优化算法的共享储能优化配置研究[J]. 综合智慧能源, 2023, 45(9): 65-76.

LI Qinggen, SUN Na, DONG Haiying. Optimal configuration for shared energy storage based on improved whale optimization algorithm[J]. Integrated Intelligent Energy, 2023, 45(9): 65-76.

图/表 15

图1

图2

表1

集中式共享储能系统参数

参数	值
单位功率投资成本 $c P$ /(万元·MW^-1)	40
单位容量投资成本 $c E$ /[万元·(MW·h)^-1]	70
基准折现率 $r$ /%	0.5
共享储能电站运行寿命 $n$ /a	10
共享储能电站运行维护系数 $ζ$ /%	6
充放电效率 $η E S S, c$ ， $η E S S, d$	0.95,0.95

表1

图3

图4

图5

图6

表2

图7

图8

表3

图9

图10

图11

图12

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类型	功率/MW	容量/（MW·h）	配置成本/(万元·a^-1)
光伏电站1	15	90	631.79
光伏电站2	15	90	631.79
风电场	27	162	1 137.22
总计	57	342	2 400.80

序号	功率/MW	容量/(MW·h)	储能配比/%	消纳率/%	配置成本/(万元·a^-1)
1	56.37	302.54	14.83	95.52	2 180.35
2	56.37	324.64	14.83	96.00	2 300.44
3	56.37	370.85	14.83	97.00	2 551.59
4	56.37	417.06	14.83	98.00	2 802.73
5	60.94	462.70	16.04	99.00	3 094.20
6	80.59	508.91	21.21	100.00	3 532.30