Journal of Power and Energy Engineering, 2015, 3, 85-91
Published Online April 2015 in SciRes. http://www.scirp.org/journal/jpee
http://dx.doi.org/10.4236/jpee.2015.34013
How to cite this paper: Wang, Y.L., Pan, Z.J., Hao, H.T. and Zhou, Z.Q. (2015) Study on Multi-Objective Effect Evaluation
System of Smart Grid Construction. Journal of Power and Energy Engineering, 3, 85-91.
http://dx.doi.org/10.4236/jpee.2015.34013
Study on Multi-Objective Effect Evaluation
System of Smart Grid Construction
Yanling Wang, Zhengjie Pan, Haitian Hao, Ziqing Zhou
Research Institute of Electric Power Market, North China Electric Power University, Beijing, China
Email: wangyanling@ncepu.edu.cn, panzhengjie1992@163.com, haohaitian@sina.com,
zhouziqing92@163.com
Received January 2015
Abstract
This paper builds multi-objective effect evaluation indicator system of smart grid construction
from five connotations including strong and reliable, clean and green, friendly and interactive,
transparent and open, economical and effective, which is embodied in the power generation, tran-
smission, transformation, distribution, consumption, dispatching and information communication
platform of smart grid. Taking the construction of smart grid in a certain area of China as an ex-
ample, this paper uses analytic hierarchy process (AHP) to make an empirical analysis on it, and
makes a comprehensive and objective evaluation on its construction effect.
Keywords
Smart Grid, Multi-Objective Effect, Evaluation Indicator System, AHP
1. Introduction
In order to tackle climate change and ensure energy security, countries around the world are increasing emphasis
on the development of clean energy and the improvement of energy efficiency at present. As the basis and pre-
mise for achieving low-carbon electricity, smart grid technology has developed rapidly in many countries in re-
cent years, and effectively promotes the grid smart [1] [2].
Some countries have put forward appropriate evaluation system of smart grid based on their basic national
conditions and development stage of power industry, in order to cooperate with the construction of strong smart
grid and reflect its technical characteristics and functional properties comprehensively.
The foreign typical evaluation systems of smart grid mainly contain the smart grid maturity model proposed
by IBM [3], the framework system of smart grid assessment drafted by DOE [4], the smart grid construction
evaluation indicator of EPRI [5], the smart grid profit evaluation system of EU [6] and so on. It should be noted
that the evaluation system of US pays more attention to the safety and reliability of power system because of its
obsolete facilities and the hidden dangers against security and stability; the evaluation system of Europe focuses
on development and utilization of new energy and low carbon due to the shortage of fossil energy and large spe-
cific gravity of new energy generation.
Along with the deepening of smart grid construction in China, domestic scholars are researching and explor-
ing smart grid evaluation hotly, mainly including the establishment of evaluation indicator system, research for
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evaluation model and method [7] [8], etc.
Combined with the target and development direction of smart grid in China, this paper has built multi-objec-
tive effect evaluation indicator system of smart grid construction from five connotations including “strong and
reliable”, “clean and green”, “friendly and interactive”, “transparent and open”, “economical and effective” [9],
which can make a comprehensive and objective evaluation on the effect of smart grid construction.
2. Multi -objective Effect Evaluation Indicator System of Smart Grid Construction
2.1. Construction Principle of the Indicator System
Currently, the World Bank and the national government departments commonly adopt the SMART criterion to
select indicators, and the 5 letters of SMART represent specific, measurable, attainable, relevant and trackable.
The advantage of this criterion is having a relatively clear standard, which makes evaluation easy.
Considering the characteristics and connotations of smart grid, according to SMART criteria, this paper has
proposed the principle of establishing indicator system. 1) Comprehensiveness. Indicators should reflect the ac-
tion of each construction link as much as possible. 2) Independence. Various indicators in the same level should
have clear connotation, mutual independence and cannot overlap each other. 3) Typicality. Indicators should
make key points of construction stand out and grasp the main aspect of problem. 4) Measurability. Evaluation
indicators of each construction action should have the appropriate standards and use the same standard as uni-
fied evaluation dimension.
2.2. Five Connotations of Smart Grid
The State Grid Corporation has proposed the development train of thought about unified strong smart grid with
Chinese characteristics, which is “one goal, two main lines, three stages, four systems, five connotations, six
links”. The five connotations are:
1) Strong and reliable, which mean strong grid structure, strong power transmission capacity, safe and reliable
power supply ability.
2) Clean and green, which mean promoting development and utilization of renewable energy, reducing energy
consumption and pollutant emission, and improving the proportion of clean energy in final energy consumption.
3) Friendly and interactive, which mean flexible adjustment of power grid operation mode, easy for various
types of power and users accessing or exiting the grid, promoting the generation companies and users to actively
participate in grid operation regulation.
4) Transparent and open, which mean the transparent and shared information of power grid, power sources
and users, and open grid without discrimination.
5) Economical and effective, which mean improving the operation and transportation efficiency of power grid,
reducing operating costs, promoting the efficient utilization of energy resources and electric power assets.
According to these five connotations above, the effect evaluation indicator system of smart grid construction
extracts effect indicators from each construction link of smart grid, which can embody the smart grid characte-
ristics scientifically and comprehensivel y.
2.3. Multi-Objective Effect Evaluation Indicator System
The smart grid has five connotations including “strong and reliable”, “clean and green”, “friendly and interac-
tive”, “transparent and open”, “economical and effective”, which are embodied in the power generation, trans-
mission, transformation, distribution, consumption, dispatching and information communication platform of
smart grid. Build multi-objective effect evaluation indicator system of smart grid construction based on these
connotations, as shown in Table 1.
3. Effect Evaluation Model Based on AHP
3.1. Determine the Weight of Indicators by AHP
The multi-objective effect evaluation indicator system of smart grid construction has obvious hierarchical struc-
ture, as shown in Figure 1. Because there are more species and quantity of indicator, and the indicator system is
large, it is suitable to use AHP to solve the problem of reasonable weight of indicator and then evaluate the
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Table 1. Multi-objective effect evaluation indicator system.
Primary Indicator
Second-level Indicator Third-level Indicator Fourth-level Indicator
1
x
Strong and
reliable
11
x
Transmission reliability
1
11
x
System recovery performance
2
11
x
Transformer forced outage rate
3
11
x
Transformer availability coefficient
4
11
x
Overhead lines forced outage rate
5
11
x
Overhead lines availability coefficient
6
11
x
Breaker forced outage rate
7
11
x
Breaker availability coefficient
8
11
x
The N-1 pass rate of 220 kV and above grid
12
x
Power supply reliability
1
12
x
Power supply reliability rate
11
12
x
Reliability rate in city
12
12
x
Reliability rate in countryside
2
12
x
Comprehensive voltage pass rate
21
12
x
Pass rate in city
22
12
x
Pass rate in countryside
3
12
x
Frequency pass rate
13
x
Information security
1
13
x
The level of safe operation of information and
communication systems
2
13
x
The number of information events
2
x
Clean and
green
21
x
Capacity for environmental
conservation of generation
1
21
x
The proportion of clean energy supply
2
21
x
The proportion of distributed power supply
3
21
x
Growth rate of coal-electricity efficiency
22
x
Capacity for
environmen
-tal conservation
of transmission and
distribution network
1
22
x
Capability to reducing power loss
2
22
x
Completion rate of saving electricity
23
x
Capacity for environmental
conservation of consumption
1
23
x
Substitution proportion of electric energy
3
x
Friendly and
interactive
31
x
Compatibility degree for
power source
1
31
x
Growth rate of new energy proportion
32
x
Operational flexibility for
grid
1
32
x
Processing speed of the accident
2
32
x
Reduction rate of network congestion
33
x
User engagement
1
33
x
Interactive services index of smart consumption
2
33
x
The proportion of electric power customer
3
33
x
Demand-side management level
4
x
Transparent
and open
41
x
Information openness of
market
1
41
x
Completion rate of information disclosure
2
41
x
Promptness rate of information disclosure
3
41
x
Diversity of information channels
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Conti n ue d
42
x
Open grid without
discrimination
1
42
x
Growth rate of trade electricity for generation
right
2
42
x
Growth rate
electricity for large consumers
3
42
x
Growth rate of inter-provincial electricity trade
volume
5
x
Economical
and effective
51
x
Operation efficiency of
power grid
1
51
x
Generation efficiency of renewable energy
2
51
x
Operating efficiency of distribution automation
3
51
x
Operating efficiency of Information
commun ication
52
x
Utilization efficiency of
power grid
1
52
x
Capacity utilization of 220kV and above lines
11
52
x
Conventional power lines
capacity utilization
12
52
x
New energy lines capacity
utilization
13
52
x
Load feeders capacity utilization
14
52
x
Main network frame and contact
lines capacity utilization
2
52
x
Capacity utilization of 220kV and above
tran sformer
21
52
x
Main transformer capacity
utilization
3
52
x
Capacity utilization of 110kV and below lines
31
52
x
Municipal power supply lines
capacity utilization
32
52
x
County power supply lines
capacity utilization
4
52
x
Capacity utilization of 110kV and below
tran sformer
41
52
x
Municipal main transformer
capacity utilization
42
52
x
County main
transformer capacity
utilization
construction effect of smart grid. Specific steps are as follows:
1) Build the hierarchic analysis structure. The Figure 1 just shows typical AHP model structure.
2) Construct the judgment matrix. The judgment matrix compares the relative importance degree of evalua-
tion indicators at the same level which are associated with the indicator in upper level.
3) Order the single hierarchical. Calculate relative importance of a factor in one hierarchy to a factor in the
upper hierarchy, which is called single hierarchical ordering. It can come down to calculating the largest eigen-
values and eigenvectors of the judgment matrix.
4) Test the consistency of judgment matrix. The indicator weight assignment is successful if the result of sin-
gle hierarchical ordering has an ideal consistency; otherwise, the values of element in judgment matrix need to
be adjusted.
3.2. Classify the Indicator Evaluation Grade
Set four evaluation grades for effect indicators, give each grade the corresponding score interval, and then we
can classify the effect level of smart grid construction, as shown in Table 2.
3.3. Calculate the Evaluation Result
Calculate each indicator score by using weighted means method, the evaluation results of five primary indicators
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Figure 1. Hierarchical chart of multi-objective effect evaluation system.
Table 2. Evaluation grade and score interval of effect.
No. Indicator Evaluation Grade Score Interval
A Unqualified 0 - 59
B Qualified 60 - 69
C Good 70 - 84
D Excellent 85 - 100
in multi-objective effect evaluation indicator system can be obtained according to the score interval and evalua-
tion grade in Table 2, as shown in Table 3.
Finally, we can judge the overall level of smart grid construction effect by using the weighted means method
to obtain total score according to the scores of five primary indicators.
4. Example Analysis
Use the method in this paper to evaluate construction effect of smart grid in one region.
4.1. Determine the Indicator Weight and Score
Determine the indicator weight by using AHP, and let experts give the corresponding scores on the basis of ac-
tual data of smart grid. The indicator weight and score are as shown in Figure 2.
4.2. Calculate the Evaluation Result
Use weighted means method to calculate scores of the five primary indicators including “strong and reliable”,
“clean and green”, “friendly and interactive”, “transparent and open”, “economical and effective”, and finally
obtain the total score of effect. Then judge the grade of construction effect according to Table 2, as shown in
Table 4.
Finally, we can judge the overall level of smart grid construction effect by using the weighted means method
to obtain total score according to the scores of five primary indicators.
We can see from Table 4 that the overall effect of the smart grid construction shows a good level. “Strong
and reliable” and “friendly and interactive” are excellent, while “clean and green”, “transparent and open” and
“economical and effective” are good. Weak part of smart grid construction in one region can be found out
through in-depth analysis of basic indicators. For example, the quality of power supply in rural areas is relatively
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Table 3. Evaluation result of smart grid construction effect example.
Indicator Score Evaluation Grade
Strong and reliable 90 Excellent
Clean and green 84 Good
Friendly and interactive 92 Excellent
Transparent and open 81 Good
Economical and effective 72 Good
Table 4. Evaluation result of smart grid construction effect.
Indicator Score Evaluation Grade
Strong and reliable 94.02 Excellent
Clean and green 82.14 Good
Friendly and interactive
87.17
Excellent
Transparent and open 81.43 Good
Economical and effective 71.05 Good
Total effect 83.16 Good
Figure 2. Indicator weight and score. Note: “x, Digital 1/Digital 2” represent “indicator, weight/value”.
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poor, distributed power develops slowly, the level of environmental protection on power demand side is low,
various electricity trades increase slow, utilization efficiency of grid a little low, etc. Therefore, appropriate
measures should be taken to continuously strengthen and improve the construction work of smart grid, such as
reinforcing the construction and renovation of rural power grid, rational development of distributed power, ac-
tively promoting the strategy of electric energy substitution, further improving the trading rules and trading sys-
tem functions of power market, further optimizing the grid structure.
5. Conclusions
This paper constructs multi-objective effect evaluation indicator system around five connotations including
strong and reliable, clean and green, friendly and interactive, transparent and open, economical and effective;
and builds the evaluation model based on AHP. Through the evaluation and analysis of smart grid construction
in one region of China, it is found that “clean and green”, “transparent and open” and “economical and effective”
get low scores. There is a need to improve the construction work of smart grid for its weak part, thereby guaran-
teeing the scientifically and orderly development of the construction work.
The case in this paper shows that the evaluation system can objectively evaluate the construction effect of
smart grid in the round, quickly and accurately identify the deficiencies in smart grid construction, so that it can
help to grasp the development direction of smart grid construction and provide reference for the planning and
construction of smart grid.
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