Multiscenario energy storage selection method based on AHP and TOPSIS-fuzzy comprehensive evaluation

doi:10.19799/j.cnki.2095-4239.2023.0624

Abstract

Abstract:

The energy storage technology roadmap is diverse, and different types of energy storage have their application prospects. The selection of energy storage is a key issue in engineering applications. However, the selection of energy storage requires comprehensive consideration of factors such as economics and safety, making it a complex multi-objective decision-making problem. A hybrid energy storage selection evaluation system is proposed that combines the analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) with a fuzzy comprehensive analysis method. First, the judgment matrix of the evaluation system is established, and then the indicator weights undergo diagonalization and multiplication with the standardized matrix to yield the weighted judgment matrix to obtain the proximity vector. The membership assessment results of energy storage types are obtained by multiplying the weighted judgment matrix with the correlation matrix of the fuzzy comprehensive analysis method. Data in grade I indicates the energy storage system is at its optimum level, grade II follows as the next tier, and so forth in descending order. Thus, by employing TOPSIS, a more objective weight vector can be obtained, mitigating the subjectivity inherent in the AHP method. Taking seven types of energy storage, such as lithium-ion batteries, sodium-sulfur batteries, and lead-acid batteries, applied to peak load shaving, grid supply, and voltage quality improvement scenarios as examples, a comparative analysis is conducted with existing energy storage selection methodologies, highlighting the innovative nature of this evaluation framework. The effectiveness of the proposed evaluation system and selection method is verified.

Key words: energy storage system, analytic hierarchy process(AHP), technique for order preference by similarity to ideal solution(TOPSIS), fuzzy comprehensive evaluation method

CLC Number:

TK 02

Yangkai LIU, Weiqing SUN, Wei LIU. Multiscenario energy storage selection method based on AHP and TOPSIS-fuzzy comprehensive evaluation[J]. Energy Storage Science and Technology, 2024, 13(2): 691-701.

Figures/Tables 14

Table 1

Fig. 1

Fig. 2

Table 2

Meaning of the nine-level scale"

标度	含义(对应两指标之间)
1	两指标同样重要
3	指标 $i$ 比指标 $j$ 稍微重要
5	指标 $i$ 比指标 $j$ 明显重要
7	指标 $i$ 比指标 $j$ 强烈重要
9	指标 $i$ 比指标 $j$ 极端重要
2、4、6、8	对应两指标的中间值
对应倒数	指标 $i$ 比指标 $j$ 重要性相反

Table 2

Table 3

Average random consistency metric"

$n$	$R I$	$n$	$R I$
1	0	6	1.26
2	0	7	1.36
3	0.52	8	1.41
4	0.89	9	1.46
5	1.12	10	1.49

Table 3

Table 4

Scoring criteria"

评价等级	等级制	评分准则	评分标准
很好	Ⅰ	$X i > x i 1$	$> s 1$
良好	Ⅱ	$x i 2 < X i ≤ x i 1$	$s 2 ∼ s 1$
一般	Ⅲ	$x i 3 < X i ≤ x i 2$	$s 3 ∼ s 2$
较差	Ⅳ	$x i 4 < X i ≤ x i 3$	$s 4 ∼ s 3$
很差	Ⅴ	$X i ≤ x i 4$	$< s 4$

Table 4

Fig. 3

Fig. 4

Table 5

Fig. 5

Fig. 6

Table 6

Fig. 7

Table 7

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储能类型	技术成熟度	优势	不足	响应时间	适用场景
抽水蓄能^[8]	商用	机组容量大、不受季节径流影响，具有出色的调峰、调频、调相、应急储备等功能	响应慢，选址受地理条件限制	分钟级	调峰、调压、调频
锂离子电池^[9]	商用-示范	高比能、长寿命、环保、配置灵活	高堆积密度和相对紧凑的工作环境会导致过热	秒级	调峰、调压、调频
全钒液流电池^[10]	示范	设计灵活、循环寿命长、深度放电容量大	能量转换效率低	秒级	调峰、调压、调频
先进绝热压缩空气储能^[11]	示范	为系统提供调峰、备用、无功调节等多种辅助服务，还具有冷热电联产的显著优势	响应慢	分钟级	调峰、调压、调频，促进新能源消纳
地下压缩空气储能^[12]	示范	利用地下洞穴等空间增加储能容量，且对环境影响较小	响应慢，且受环境因素限制，若开采人工硐室增加成本	分钟级	调峰、调压、调频，促进新能源消纳
飞轮储能^[13]	商用	效率高、体积小、寿命长、瞬时功率大、响应速度快等	受限于材料、技术和生产成本限制，单个飞轮的容量很难提高；功率密度低，多个飞轮组合需要合理的协调控制	毫秒级	调频，新能源电站
超级电容器储能^[14]	示范	维护要求低、充电速度快、循环寿命长、功率密度高、效率高、环保	成本高	毫秒级	调频，新能源消纳

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