Research on power data element pricing mechanism optimization in the context of digitalization

doi:10.3969/j.issn.2097-0706.2022.07.010

Abstract

Abstract:

To achieve dual carbon target,power industry applies big data and other technologies in industry digitalization to realize quality and efficiency improvement, energy conservation and emission reduction. However, most of current researches on power data asset pricing mechanism have not taken risk factors into consideration. And power data factor pricing mechanism and its optimization have drawn great academic attention. Firstly, the cost method,data value realization risk and power data factor pricing optimization model are summarized theoretically. Then, the power data factor pricing optimization model is constructed with two risk factors, data value realization risk and supply-demand risk, taken into account. Finally, taking an energy efficiency monitoring product of an enterprises as an example, the effectiveness of the power data factor pricing optimization model is verified.

Key words: dual carbon target, digital asset, power data factor pricing mechanism, data value realization risk, supply-demand risk, price optimization model

CLC Number:

TK01：F426

YU Xiaobao, ZHANG Tianhao, DENG Siwei. Research on power data element pricing mechanism optimization in the context of digitalization[J]. Integrated Intelligent Energy, 2022, 44(7): 81-89.

Figures/Tables 13

Fig.1

Fig.2

Table 1

Table 2

Judgement matrix

评价指标	$B 1$ （易获得性）	$B 2$ （一致性）	$…$	$B n$ （完整性）
$B 1$ （易获得性）	$b 11$	$b 12$	$…$	$b 1 n$
$B 2$ （一致性）	$b 21$	$b 22$	$…$	$b 2 n$
︙	︙	︙	︙	︙
$B n$ （完整性）	$b n 1$	$b n 2$	$…$	$b n n$

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Table 8

Fig.3

Table 9

Fig.4

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一级指标	二级指标	三级指标
数据价值实现风险	数据管理风险	设备故障
	数据管理风险	数据描述不当
	数据开发风险	系统不兼容
		政策影响
		应用需求
	数据流通风险	数据开发水平
	数据流通风险	数据泄露
	数据安全风险	数据损坏

指标项	强	较强	一般	较弱	弱
易获得性	0.32	0.42	0.13	0.10	0.03
一致性	0.53	0.36	0.10	0.01	0
可理解性	0.78	0.19	0.03	0	0
完整性	0.24	0.53	0.12	0.09	0.02
准确性	0.41	0.43	0.10	0.06	0
正确性	0.26	0.43	0.21	0.08	0.02
客观性	0.37	0.31	0.26	0.06	0
有效性	0.43	0.54	0.21	0.10	0
可靠性	0.34	0.52	0.13	0.01	0
相关性	0.43	0.42	0.15	0	0
稀缺性	0.32	0.47	0.11	0.10	0
使用场景	0.25	0.46	0.29	0	0
适用情形	0.14	0.53	0.33	0	0
时效性	0.38	0.45	0.15	0.02	0

一级指标	权重	二级指标	基本权重	组合权重
数据形式	0.547	易获得性	0.576	0.315
		一致性	0.253	0.138
		可理解性	0.128	0.070
		完整性	0.044	0.024
数据内容	0.345	准确性	0.379	0.131
		正确性	0.324	0.112
		客观性	0.180	0.062
		有效性	0.064	0.022
		可靠性	0.053	0.018
数据绩效	0.109	相关性	0.455	0.049
		稀缺性	0.319	0.035
		使用场景	0.125	0.014
		适用情形	0.053	0.006
		时效性	0.048	0.005

一级指标	二级指标	三级指标	专家评分	权重
数据价值实现风险	数据管理风险	设备故障	77	0.253
	数据管理风险	数据描述不当	65	0.105
	数据开发风险	系统不兼容	73	0.167
		政策影响	37	0.080
		应用需求	39	0.195
	数据流通风险	数据开发水平	57	0.070
	数据流通风险	数据泄露	38	0.121
	数据安全风险	数据损坏	79	0.009