Energy and Power Engineering, 2013, 5, 884-888
doi:10.4236/epe.2013.54B170 Published Online July 2013 (http://www.scirp.org/journal/epe)
Extension Study on Electricity Market of Power Plant
Investment Environment
Yuting Wang1, Kezhen Liu1, Chenkai Mo2
1Faculty of Power Engineering, Kunming University of Science and Technology, Kunming, Yunnan Province, China
2Jiaxin Power Plant, Jiaxin, Zhejiang Province, China
Received February, 2013
ABSTRACT
When the global electricity indu stry has reorganized th e structure and introduced co mpetitive market mechanism world
widely, China is no exception. Since 2002, “Electricity System Reform Program” was enacted. The mode of the State
Power Corporation was divided. It means China's electricity market steps into the mode of Wholesale Competition. The
meaning of the evaluation of power plant investment decision is to provide references for the market members when
they made the decisions throug h the comprehensive evaluation of inter nal performance of Power Plant and th e external
investment environment, therefore further optimizing the allocation of funds, avoiding the risks, pursuing maximize of
the profits.
Keywords: Power Plant Investment Environment; Evaluation Index System; Extension Evaluation
1. Introduction
Since China’s first construction of power lines in 1882,
China has gradually become one of the largest power
systems in the world [1]. Closely related to the develop-
ment of China's electric power industry and the reform of
the electricity system, the government’s over interference
in enterprises and highly unified planning economic sys-
tem from the beginning of the liberation to reform and
open up the separation of government administration
from enterprise management and self-exploration of the
market-oriented operating system and then gradually try
to plant network separate competitive bidding market.
China’s electric power system reform has gone through a
tortuous and long road. From the separation of plant and
grid, power plant investment project always has been the
focus of the electric power investment research because
as its large investment and long construction cycle since
2002. Therefore, investment environment evaluation can
make investment decision more scientific, standardized
and programming before the power project investment,
thus reducing the maximum degree of the risk from the
policy [2,3].
2. China’s Power Market Characteristics
Analysis
Since the enactment of promulgated The Power System
Reform Plan from 2002, our country’s electric power
market gradually began to change to Wholesale Compe-
tition mode [4-7]. In this mode, all power generation
companies and transmission network is no longer a ver-
tically integrated operation monopoly power company
must be in the vertical split its affiliated power genera-
tion companies to pull away from the grid in removing
all independent into a self-financing independent power
producers. At the same time, establish a relatively sound
basis the separation of plant and grid the electricity mar-
ket, power generation companies in this electricity mar-
ket bidding. Wholesale competition model is shown in
Figure 1.
At present, China’s power market is moving towards
Independent
pow er producersIndependent pow er producersIndependent pow er producersIndependent pow er producers
D is trib utio n
companies Distribution companies
L arge u sersLarge users
Small end-userSma ll end-user
Tra n smiss io n Netwo rk
The Wholesale Market
Figure 1. Wholesale competition model.

Y. T. WANG ET AL. 885
wholesale competition mode, only the power suppliers to
participate in the competition in which the identity of th e
third party. However, in order to achieve the maximiza-
tion of profits within the electricity market, improve
production efficiency, perfect competition is necessary.
So before plant construction, power plant investment
environment evaluation help power plant to save their
own competitive torrents gains.
3. Constructing an Extension Evaluation
Model
Extension assessment method [8-10] is the extension
theory applied to evalua tion of things, establishing multi-
indicators evaluation model parameters, and quantifying
the quality of the evaluation results. It can reflect the
actual features to be evaluated the comprehensive fea-
tures of things level integrally. In this paper, the exten-
sion assessment model is defined as follows:
Let M represent matter-element E for the space of the
basic power plant investment evaluation factors, C is a
set of evaluation factors, n is the num-
ber of evaluation factors. Will be invested in accordance
with the characteristics of the power plant investment
evaluation factors affect the number of levels of the fac-
tors are divided into several different levels, the estab-
lishment of a power plant investment evaluation level
domain , m is an investment evalua-
tion.
12
{,,, }
n
Ccc c
}
m
u
12
{, ,,Uuu
3.1. Determine the Classical Domain and Section
Domain
The Power plant investment evaluation of classical do-
main and joint domain respectively are 0
j
M
and u
M
.
101
202
00 0
0
(,,)
jj
j
jjoj kj
nj
ucV
cV
MNCV cV
cV













k
n










10101
20202
00
00
,
,
,
,
jj
jj
kjkjk
njnjn
uc ab
cab
cab
cab













j




(1)
The above formula, 0
j
N represents the j investment
grade, 1, 2,,
j
m

; said the evaluation factors in the
level of investment level, is on
the magnitude of the evaluation factors range, each
power plant investment grades taken on its multi corre-
sponding characteristic d ata range
k
c
1, 2,,,kk
;
c
n
oj
V
k
j
u
0
,
jk
11
22
nn
0jk
ab .
3.2. Determine the Power Plant to be Evaluated
Model
Evaluation of Power plant investments E the results of
the actual data obtained or calculated using physical
element M is expressed as follows:
(,,)
E
cV
cV
cV
MECV














k
c
(2)
The above equation, E is the power plant investment
performance to be evaluated; the magnitude of the
corresponding k power plant is to be evaluated invest-
ment performance E.
V
Due to investment performance evaluation of seated
structural upper factors is composed of a number of low-
er factors. The single factor at the low level may be
composed by the lower layer of the multi-factor. If you
want to evaluate the performance of a power plant in-
vestment, so the impact on the basis of the power plant
performance factors stratified, low-level factors and
comprehensive, the last factor of the high-level synthesis,
and then was the investment performance of the plant
level. Therefore, according to the characteristics of mat-
ter-element divergence, matter-element M can be ex-
panded to :

 

11
| ,,2 , ,2 , ,(,,),
M
ECVE CVECV

 

,,
kk
ECV, ,n E
kn
,,
n
CV (3)
constraint condition: 12
E
EE E E
, ,

,
k
In the above formula: 12
{, ,}
n
E
EEE is invest-
ment evaluation factors subset for E, n is investment
evaluation s ub divide d set n u mber.
For kkk
(,,)
M
ECV

can be further expanded according
to the actual situation, based on the contents of the pre-
vious modeling, the model only needs to expand to two
layers .The bottom evaluation factors is: kp
E
kp
nk
Ec
11
22
,)
kp
kp
kp
p
V
CV









(,
kpkp
ME
n
cV
cV
 (4)
3.3. Determine the Evaluation Level Associated
Let 0
x
be an arbitrary point on the real axis (,)

,
0,
X
ab


for any real number field interval, 0)(,
x
X

to point 0
x
to the interval distance, so:

Y. T. WANG ET AL.
886
00 1
(, )()
22
ab
x
Xx b 

a
(5)
Away from the basis to establish the correlation func-
tion, the elementary correlatio n function can be expressed
as:
0
0
(, )
() (, )(,)
xX
kx
x
XxX


 (6)
To be evaluated investment performance factors kp
E
about levels associated can be expressed as:
0
0
(, )
() (,)(, )
kpi ji
jkpi
kpi Uikpiji
vV
kv vV vV


 (7)
Let a be evaluated factors weight coefficient of
and is to be rated investment performance
k
c
i
a1
n
i
i
a

factors kp
E
association level j:
() (
n)
j
kpii kpi
i
kE akv (8)
3.4. Grading to be Evaluated Investment
Performance Ekp
If
0
0{1,2, , }
max ()
jj
jm
kk



kp
E
(9)
then assess the performance of investment factors
belongs to level . kp
E
0
j
3.5. The Results of Evaluation of the Determined
Transformation matrices by evaluating a performance
investment subset i
E
extension comprehensive evalua-
tion m odel, the com preh ensi v e eval uati on of the resul ts of
the evaluation factors set i
E
.
i
E
Evaluation transform matrix obtained by the step (3 )
as:
11 211
122222
12 2
() ()()
()()() ()
() ()()
ii mi
ii i
ipj nm
in inin
kEkEk E
kEkEkE
Kk
kE kEkE

















(10)
Assumptions subset of, the weight of each fac-
tor is i
E
(
ii
12 1, 2i in
,,,
iii
EE En,..., )
A
aa a
meet the , then the power plant investment per-
formance evaluation model can create:
respectively, to
1
i
i
a

n
1, 2
(,..., )
iii iiin
B
AK aaa
11 211
12 2222
122
() ()()
() ()()
() ()()
ii m
ii
in inin
kEkEk E
kE kEkE
kEkEkE










3.6. Investment Grading
If
0
0{1,2,, }
max{ }
j
j
j
m
b

B

(12), and assesses the performance of E is
J level.
Repeat steps (3.1)-(3.6), you can come to the level of
the final power plant investment environment E belongs.
4. Determined the Weights Based on AHP
Analytical Hierarchy Process is a combination of a quan-
titative and qualitative analysis of decision-making me-
thod. This method was applied to the power plant in-
vestment decisions evaluation of them. First, the invest-
ment decision-making to the complex issues broken
down into a variety of factors, these factors attribute
grouping has a different level, the same level factors as
criteria, the next level of factors play a dominant role, at
the same time by the previous constraints on the level
factors. Topmost only one factor, namely the evaluation
objectives, the middle level is a factor layer and the sub-
factors layer (index layer), the bottom of each factor is to
be the evaluation the area object[11]. Hierarchical rela-
tionship of each factor is shown in Figure 2.
In judgment matrix is constructed based on the calcu-
lation of the relative weights of the factors under single
criteria. Finally, the calculated weight value for consis-
tency checking, when 0.10
CI
CR RI  , indicating that the
matrix having the consistency of the judgment can be
accepted; or should re-adjust the judgment matrix until
the consistency can be accepted.
5. Example Analysis
According to the exposition of the previous sections, the
use of extension model is based on the actual investment
of the power plant model structures [12].
The establishment of the evaluation factors 1234
{,, , }Ccccc

,
which represent the possibility of capital appreciation,
capital investment risks, the possibility of transfer of
capital and power plant enterprises the ability to take
risks in four areas.
i
i

(11)
Target layer
Criterion 1C riterion 2…… Criterion n
M easures
layer 1 Measures layer 2…… Measu res laye r n
Figure 2. Hierarchy relationship of each factor.

Y. T. WANG ET AL. 887
Assumed analysis, inspection this to establish the ac-
curacy of the model selected Yunnan territory of a power
plant operational data. Assuming a hydropow er station in
Yunnan province, the surrounding is rich in water re-
sources. The main stream of water resources is in the
Lancang river, Jinsha river the theoretical potential of 13
730 MW, development and utilizatio n of 8 450 MW. The
other tributary hydropower resources theory bears 2 806
MW, development and utilization of 200 MW, been de-
veloped use 157.644 MW, there is considerable potential
to be developed. Power station is 23 km away from the
load area, and 700 km away from Kunming. Hydropower
needs reservoir support the reservoir without inundated
farming woodland, only submerged about 6 acres of dry
land, 29.56 acres of shrub land (apart from a small
amount of broad-leaved forest, are the bushes), and little
damage to the surrounding environment. Power plant
investment decisions evaluation and Extension levels are
shown in Figure 3.
Evaluation
index
system of
power
plant
investment
decisions
Econom ic factors(E1)
0.324
Investment level of econom ic developm ent
an d its ma tu rity (E 11) 0 .0 8
Industry level tax policy(E12) 0.0 8
Pow er generation cost of doing
business(E13) 0.1 8
Inte rn al R a te o f R e turn(E14) 0.2 5
Investment le ading role in the local
economy(E15) 0 .1 5
Equipment utilization(E11) 0 .0 8
P o litic a l fa cto r s( E 2)
0.220
Pow er plant investm ent in governm ent
support(E21) 0 .5
Th e adm inistrative efficiency of the local
government officials from corruption(E22) 0.25
A ttitude of the local government and the public
to foreign funds(E23) 0 .2 5
Electricity m arket
factors(E3)
0.189
Local m arket size and opportunity(E31)
0.22
Future dem and for capacity forecast(E32)
0.22
Th e imp act of cyclical fluctuations in
demand(E33) 0.2 2
Inte raction between the m ulti-power
plant(E34) 0 .1 1
Investment density(E35) 0 .1 1
Forward pricing(E36) 0 .1 1
Infra stru ctu re fa cto rs (E 4)
0.134
Traffic conditions(E41) 0 .2
E n erg y av aila b ility(E 42) 0 .6
L ife s erv ice fac ilities(E 43) 0 .2
Social and cultural
factors(E5)
0.055
The supply of labor and w age
levels(E51) 0 .3 3
The quality of the population and
people's living habits(E52) 0 .1 7
Th e level of research support(E53) 0.33
D ifferences in the degree of religious
culture (values)(E54) 0.1 7
N a tu ral en v iro nmen tal
factors(E6)
0.134
The im pact of power plants on the
local natural environment(E61) 0 .5
C lim ate im p act(E62) 0.5
Figure 3. The identification of diagram about evaluation of
power plant investment deci sion-making.
According to the initial power planning of Yunnan
Electric Power Industry “11th Five-Year” Development
Plan and the 2020 Vision of the Preliminary Studies,
completed and put into operation in the year 2010, the
surrounding four cascade hydropower stations installed
capacity of up to 188 MW four steps were: A power
plant 15 MW, B power station expansion 48 MW, C
power station 25 MW and D power plant 100 MW. The
maximum power load in 2010 will reach 102,000 kW in
this state, existing power installed capacity of 92,000 kW
only. Visibly the end load market demand is great and
the surround ing power plant does no t constitute competi-
tion. The units can achiev e higher utilization hours.
According to the characteristics of the investment en-
vironment, investment environment is divided into five
levels: A (8 to 10), A-(6 to 8), B (4 to 6), C (2 to 4), and
C-(0 to 2). Value for the amount of matter-element, be-
fore Delphi method, confirmation of three experts in the
different working environment, is shown in the following
Table 1.
Table 1. The evaluation summary of the final decision pow-
er plant investment.
Evaluation of projectsMatter Element
for money Deviation value Rank
Decision Overall rating —————— -0.014 A-
E1 overall evaluation —————— -0.0054 A-
 E11 3.5，4，6，6 -0.041 B
 E12 6，4，5，5 0.125 B
 E13 5，6，6，5 0.125 B
 E14 7，4，5，5 0.0417 B
 E15 8，7，7，6 0.25 A-
 E16 8.5，7，6，8.5 0.097 A
E2 overall evaluation —————— 0.033 A-
 E21 8.5，4，5，6 -0.097 A
 E22 8，4，7，3 0.027 A-
 E23 7，4，5，6 0.194 A-
E3 overall evaluation —————— -0.076 B
 E31 8，3，6，4 -0.139 A-
 E32 6，4，4，5 0.041 B
 E33 5，6，4，7 0.042 B
 E34 8，4，6，7 0.027 A-
 E35 8.5，4，5，4 -0.124 B
 E36 3.5，7，4，3.5 -0.104 B
E4 overall evaluation —————— -0.224 B
 E41 4，7，3，6 -0.083 B
 E42 8.5，3，4，8 -0.104 A
 E43 3.5，5，4，7 -0.041 B
E5 overall evaluation —————— -0.208 B
 E51 8，4,6,8 -0.055 A-
 E52 3，7，4，6 -0.083 C
 E53 8，3，6，7 0 A-
 E54 3，7，4，6 -0.083 C-
E6 overall evaluation —————— -0.0625 B
 E61 4，6，4，6 0 B
 E62 7，3，5，8 0.027 A-

Y. T. WANG ET AL.
888
6. Conclusions
This example assumes that the new hydropower station
in Yunnan and the overall results of th e evaluation as A-.
As can be seen from the results of the analysis of the
above table, planning the construction of the hydropower
station is located in the more remote areas, so the infra-
structure layer score is not too high. As far away from
the political and commercial center of Yunnan, so the
layer evaluation in the social and cultural factors is not
too high. But the load point surrounding the power sta-
tion construction behind, the entire electricity market is
not in a state of competition, there will be no access to
electricity system, but due to the limited level of social
development, the end of the load demand in the next pe-
riod of time will not significantly improve. From a mar-
ket point of view, the construction of the power station's
decision-making does no t seem to .
The purpose of building one of the power station is
able to play a part in driven investment of the construc-
tion of the power station in local economic development,
which makes the construction of the plant has adequate
social significance, so the relative evaluation results the
results of the evaluation of the political and economic
layer is relatively high. Promote local economic devel-
opment at the same time, the income of the power station
will promote but in the short term it can not be brought
huge benefit for investors, but when the surrounding
economic has sufficient development, the power plant
gains will also have some imp roved. Although it may not
be reflected in initial construction and operation stage,
but after the loan repayment period power plant will
gradually reflect its strong economic benefits.
Rich in water resources is another advantage of the
power station construction in the building location. High
water season accounted for most of the year. Also be-
cause the innate advantage, resulting save a lot of fuel
cost. But operation of the power station need the support
of the reservoir, power station at a disadvantage not only
in construction investment and the construction period,
but also to some extent in the construction of the reser-
voir damage to the surrounding environment, which is
the reason of a low overall evaluation of the natural en-
vironment.
REFERENCES
[1] J. P. Liu. “China Power Industrial Policy and Industry
Development,” Beijing: China Electric Power Press,
2006.
[2] J. F. Shen, “China Power Industry Market Structure
Analysis,” Modern Power, Vol. 21, No. 2, 2004, pp.
95-100.
[3] G. W. Han, J. J. Zheng and J. C. Lu, “Power Sustainable
Development System Evaluation,” Power Technology
Economy, Vol. 3, 2002, pp. 11-13.
[4] DOE, “American Clean Energy and Security act
(ACES),”[EB-OL][2009-06], Available at:http://www.op
engress.org/bill/111-h2454/show.
[5] FERC, “The Technical Conference of Integrating Re-
newable Resources into the Wholesale Electric Grid,”
[EB-OL][2009-04]，Available at : http://www.ferc.gov.
[6] The UK, “Low Carbon Transition Plan,” The Department
of Energy and Climate Change,UK, 2009.
[7] K. F. Zhou, D. X. Qin, S. M. Jiang. W. Wu and X. K.
Yang, “Evaluation of the Mining Investment Environ-
ment about Four Neighboring Countries by Using Exten-
sion Method,” China Mining Magazine, 2010. 9.
[8] C. Y. Yang and W. Cai, “Extension Engineering Set,”
Beijing: Science Press, 2007.
[9] C. Y. Yang and Y. J. Zhang, “Extension Planning,” Bei-
jing: Science Press, 2002.
[10] G. N. Liu, X. Q. Chen, G. Y. He and S. X. Zhou. “The
Principle of the Evaluation Index System of Electricity
Market and Build,” Automation of Electric Power Sys-
tems Press, Vol. 29, No. 23, 2005, pp. 2-9.
[11] G. N. Liu, R. Q. Li, X. Q. Chen, G. Y. He and S. X. Zhou,
“Electricity Market Regulatory Indicators and Market
Rating System,” Automation of Electric Power Systems
Press, Vol. 28, No. 9, 2004, pp. 16-22.
[12] J. S. Liu and M. Sun, “Power Generation Enterprise Core
Competitiveness Evaluation System,” North China Elec-
tric Power University (Social Sciences), Vol. 1, 2006, pp.
54-58.