- Email: [email protected]
Evaluating Power Grid Enterprise's Investment Returns
Available online at www.sciencedirect.com
Energy Procedia 5 (2011) 224–228
IACEED2010
Evaluating Power Grid Enterprise’s Investment Returns LUO Guolianga, YUAN Xiaohongb, ZHANG Xinyinga* a
North China Electric Power University, Institute of Economics and Management, Beijing 102206 b North China Electric Power University, College of Foreign Languages, Beijing 10220
Abstract Firstly, the evaluation index system of power grid enterprise’s investment returns is established under the background of electric power system reform. Secondly, the comprehensive appraisement model of power grid enterprise’s investment returns is established and the comprehensive appraisement method is formed according to the characteristics of power grid enterprise. Finally, it puts emphases on an empirical study indicating that the model is correct.
© 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of RIUDS Keywords: grid enterprise; investment benefit; evaluation; empirical study
1. Introduction After the marketization reform of e lectric power industry, the power plants and the power grids are separated and the power grid enterprises are mainly responsible for the grid ’s operation, management and construction. The existing evaluation method of power grid economy is limited to the feasibility study of a single project. The co mmonly used method is to set the internal rate of return at an appropriate level, estimate the expected price increase, and then calcu late the investment inco me accord ing to the system power capacity. But there are great differences between the actual government’s adjusted prices and the estimated ones. Therefore, there are gaps between the evaluation and the actual results; in addition, due to the lack of indicator analysis of the power grid’s actual operation, the grid’s econo mic benefits can not be fully and truly reflected. This paper has constructed evaluation models and methods of the investment returns based on the characteristics of power grid enterprises .
* Corresponding author. Tel.: +86-010-51963851 E-mail address: [email protected].
1876–6102 © 2011 Published by Elsevier Ltd. doi:10.1016/j.egypro.2011.03.040
Luo Guoliang et al. / Energy Procedia 5 (2011) 224–228
2. Design of Evaluation Index System for Power Grid Enterprise’s Investment Returns 2.1. Design of Factors To reflect the characteristics of investment returns evaluation, a number of indicator parameters which can directly reflect power grid enterprise’s investments and earnings have been selected. (1) Earn ings. Power grid enterprise’s investment returns are the electricity benefits obtained by increasing the power supply. And they are also reflected in the reduced power supply costs by optimizing the power grid’s structure and reducing the line losses. (2) Investment. Categorized by functions, the investment which includes capital investment and investment into nature can be divided into principal network construction investment, distribution network construction investment, investment in technological upgrading , maintenance investment and the non-grid project investment. (3) Assets. The indicator system should reflects incremental assets benefits besides stock assets benefits because investment returns is obtained through incremental assets and stock assets. In order to reflect the assets utilization efficiency fro m d ifferent angles, the effectiveness indicators like power transformation capacity and line length should also be established. 2.2. Index Architecture (1) Target level: The goal of Investment benefit evaluation is to get the ratio between invest ment and return, so the index of the above ratio should be established and regarded as the target index. (2) Sub-goal level: To reflect different investments ’ inco me contribution, power grid enterprise’s investment is divided into three categories: major network construction investment, distribution networks construction investment and the investment of maintenance and technological upgrading, and the corresponding investment targets are established. A set of total investment index is also established to reflect the total investment’s dominant effect. (3) Index layer: Categorized by the types of sub-goal levels, 23 ind icators are constructed to reflect the investment efficiency from different perspectives (Figure 1). 2.3. Target Indicators Investment income ratio is the target indicator in the index system. Investment income ratio = dominant income / total investment 3. Evaluati on Model of Power Grid Enterprise’s Investment Returns 3.1. Model Components The evaluation model is to integrate the evaluation data of each index as a whole into the quantitative results reflecting the investment benefits through mathemat ical methods. Evaluation model usually consists of several parts: index reduction, index data normalization, determination of index weight and comprehensive score. 3.2. The Model (1) Index reduction
225
226
Luo Guoliang et al. / Energy Procedia 5 (2011) 224–228
The method of correlation analysis is used in the index reduction. Assuming there are m evaluation indicators: S1, S2, Sm, and they are divided into k categories. The correlation coefficient absolute value of two index data can be calcu lated through the correlation matrix analysis. And the value represents the correlation level of two indices, the standard is as follows: 0.3
the total investment target
major network construction investment target
vestment target in maintenance and technological upgrading
distribution network construction investment target
rate of change of equipment defects per unit of investment
of
of
recovery ability income per unit of investment
changes in power supply reliability
trouble-free operation interval equipment availability coefficient increase equipment per unit of investment
income growth of distribution network
proportion of bottleneck line
power supply growth per unit of investment
power supply of distribution network after loss reduction
power supply per unit of line power supply growth per new unit of distribution transformer capacity
investment returns of single projects
power supply per unit of distribution transformer capacity
transformer load distribution
Increase in power supply per new line
power supply per unit of line
power supply growth per new unit of substation capacity
capacity load ratio
power supply per unit of substation capacity
Power loss reduction
new benefits per unit of fixed assets
power supply per unit of fixed assets
power supply growth per investment unit
Figure 1 Investment Evaluation Index System of Power Grid Enterprises
(3) Weighting This paper uses the weights combination method to reconcile the advantages of subjective weighting method and objective weighting method, including coefficient variation method, Delphi method and entropy method. Supposing there are m indicators, the weight w can be obtained by q methods, the combined weights are:
Tj
q
m
(1)
j 1 k 1
k 1
Tj
q
w j (k ) / ¦ w j (k ) j 1, 2,..., m;k 1, 2,..., q stands for the combined weight.
(4) The comprehensive score model Linear model is used to summarize the normalized index value, and then get the comprehensive score which makes the evaluation result more intuitive. m
y
¦w x j
j
j 1
y is the value of comprehensive score, T j is the evaluation indicator value, coefficient.
x j is the weight
227
Luo Guoliang et al. / Energy Procedia 5 (2011) 224–228
4. Empirical Study 4.1. Index Reduction The data of 15 indicators fro m 2003 to 2006 of six power grid enterprises under a provincial power company has been obtained while the other 4 indicators ’ data is not availab le for now. Here, W1, W2, W3, W4, W5, W 6 stand for the six power grid enterprises respectively. The preliminary program of the reduction indicators can be obtained, as shown in Table 1. 4.2. Data Normalization According to the available data and the premise of less data, indicators after reduction have been normalized with linear membership function and different membership functions to get the value of membership of indicators. 4.3. Weighting Multiplication synthesis has been used to get the combined weighting of these after-reduction indicators, the weights are as follows in Table 1. T able 1 the reduction indicators after correlation analysis and target weight
Number
Index name
combination weighting
Number
Index name
Combination weighting
1
power supply growth per unit of investment
0.087 8
6
power supply per unit of line 110kV
0.040 9
2
power supply per unit of fixed assets
0.080 4
7
power supply growth per unit of investment
0.037 4
0.079 1
8
power supply per unit of line(distribution network)
0.032 4
0.050 5
9
power supply after loss reduction(distribution network)
0.019 0
0.070 2
10
changes in power supply reliability
0.026 9
power supply per unit of transformer capacity 220kV
0.042 2
11
availability coefficient increase of per unit investment
0.018 0
power supply per unit of transformer capacity 110kV
0.031 8
12
trouble-free operation interval of equipment
0.033 6
3
power supply after loss reduction
capacity load ratio 220kV 4
5
6
capacity load ratio 110kV
l
it f li
0 042 0
4.4. The comprehensive score Calculated by using the normalized data obtained after reduction and the weight calculated by using various methods, we adopted the linear integrated scoring method, and obtained the following eva luation results shown in Table 2.
228
Luo Guoliang et al. / Energy Procedia 5 (2011) 224–228
T able 2 Evaluation Results area
W1
W2
W3
year
Combination weighting
2003
0.351 5
2004
0.393 5
2005
year
Combination weighting
2003
0.262 9
2004
0.299 4
0.309 8
2005
0.243 2
2006
0.390 4
2006
0.233 1
2003
0.368 0
2003
0.145 4
2004
0.452 6
2004
0.190 7
2005
0.363 0
2005
0.183 5
2006
0.326 8
2006
0.101 3
2003
0.224 3
2003
0.217 8
2004
0.313 4
2004
0.248 1
2005
0.259 1
2006
0.195 3
2005
0.176 5
2006
0.204 5
area
W4
W5
W6
5. Conclusion In the light of existing evaluation method’s shortcomings, and co mbin ing power grid enterprise’s characteristics, a more appropriate method is brought up to construct the evaluation model to evaluate power grid enterprise’s investment benefits. The method takes the cost-benefit ratio as the target, major network construction investment, distribution networks construction investment and the investment of maintenance and technological upgrading as sub-goal. And through emp irical research, the co rrectness of the model has been verified.
References [1] Hu Rongˈ Zhang Yan, Fan Chao. Research on the post -evaluation index system of distribution network planning [J].EAST CHINA ELECT RIC POWER, 2007, 35(8):70~74 (in Chinese). [2] Han Lihong. Research on the mathematic evaluation method of the investment benefit of grid enterprise [J]. JOURNAL OF HEBEI UNIVERSIT Y OF SCIENCE AND T ECHNOLOGY, 2009, 6:180~186 (in Chinese). [3] Sun Zhao-jun. Research on the evaluation method of the investment benefit [J].AUDIT ING AND FINANCE , 2005, 8: 44~46 (in Chinese). [4] Wei Gang. The contrast of the evaluation method of the investment benefit of electric investment p roject [J] .JOURNAL OF SHANGHAI UNIVERSIT Y OF ELECT RIC POWERˈ2007, 4: 23~28 (in Chinese). [5] Jin Jingyu. Fuzzy Integrated Evaluation and investment benefit appraisal [J].TECHNOECONOMICS & MANAGEMENT RESEARCH, 2000, 3:37~38 (in Chinese). [6] Li Yin-guo, Li Xin-chun. Research on Determining Avionics System's Weighting Coefficient in Integrate Evaluate Mode [J].JOURNAL OF EAST ERN LIAONING UNIVERSITYSOCIAL SCIENCES, 2007, 4: 56~62 (in Chinese). [7] Zhao Hui-ru. Research on the investment optimization of grid construction project and assistance decision support systems [J]. EAST CHINA ELECTRIC POWERˈ2007,35(6): 23~25.
Energy Procedia 5 (2011) 224–228
IACEED2010
Evaluating Power Grid Enterprise’s Investment Returns LUO Guolianga, YUAN Xiaohongb, ZHANG Xinyinga* a
North China Electric Power University, Institute of Economics and Management, Beijing 102206 b North China Electric Power University, College of Foreign Languages, Beijing 10220
Abstract Firstly, the evaluation index system of power grid enterprise’s investment returns is established under the background of electric power system reform. Secondly, the comprehensive appraisement model of power grid enterprise’s investment returns is established and the comprehensive appraisement method is formed according to the characteristics of power grid enterprise. Finally, it puts emphases on an empirical study indicating that the model is correct.
© 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of RIUDS Keywords: grid enterprise; investment benefit; evaluation; empirical study
1. Introduction After the marketization reform of e lectric power industry, the power plants and the power grids are separated and the power grid enterprises are mainly responsible for the grid ’s operation, management and construction. The existing evaluation method of power grid economy is limited to the feasibility study of a single project. The co mmonly used method is to set the internal rate of return at an appropriate level, estimate the expected price increase, and then calcu late the investment inco me accord ing to the system power capacity. But there are great differences between the actual government’s adjusted prices and the estimated ones. Therefore, there are gaps between the evaluation and the actual results; in addition, due to the lack of indicator analysis of the power grid’s actual operation, the grid’s econo mic benefits can not be fully and truly reflected. This paper has constructed evaluation models and methods of the investment returns based on the characteristics of power grid enterprises .
* Corresponding author. Tel.: +86-010-51963851 E-mail address: [email protected].
1876–6102 © 2011 Published by Elsevier Ltd. doi:10.1016/j.egypro.2011.03.040
Luo Guoliang et al. / Energy Procedia 5 (2011) 224–228
2. Design of Evaluation Index System for Power Grid Enterprise’s Investment Returns 2.1. Design of Factors To reflect the characteristics of investment returns evaluation, a number of indicator parameters which can directly reflect power grid enterprise’s investments and earnings have been selected. (1) Earn ings. Power grid enterprise’s investment returns are the electricity benefits obtained by increasing the power supply. And they are also reflected in the reduced power supply costs by optimizing the power grid’s structure and reducing the line losses. (2) Investment. Categorized by functions, the investment which includes capital investment and investment into nature can be divided into principal network construction investment, distribution network construction investment, investment in technological upgrading , maintenance investment and the non-grid project investment. (3) Assets. The indicator system should reflects incremental assets benefits besides stock assets benefits because investment returns is obtained through incremental assets and stock assets. In order to reflect the assets utilization efficiency fro m d ifferent angles, the effectiveness indicators like power transformation capacity and line length should also be established. 2.2. Index Architecture (1) Target level: The goal of Investment benefit evaluation is to get the ratio between invest ment and return, so the index of the above ratio should be established and regarded as the target index. (2) Sub-goal level: To reflect different investments ’ inco me contribution, power grid enterprise’s investment is divided into three categories: major network construction investment, distribution networks construction investment and the investment of maintenance and technological upgrading, and the corresponding investment targets are established. A set of total investment index is also established to reflect the total investment’s dominant effect. (3) Index layer: Categorized by the types of sub-goal levels, 23 ind icators are constructed to reflect the investment efficiency from different perspectives (Figure 1). 2.3. Target Indicators Investment income ratio is the target indicator in the index system. Investment income ratio = dominant income / total investment 3. Evaluati on Model of Power Grid Enterprise’s Investment Returns 3.1. Model Components The evaluation model is to integrate the evaluation data of each index as a whole into the quantitative results reflecting the investment benefits through mathemat ical methods. Evaluation model usually consists of several parts: index reduction, index data normalization, determination of index weight and comprehensive score. 3.2. The Model (1) Index reduction
225
226
Luo Guoliang et al. / Energy Procedia 5 (2011) 224–228
The method of correlation analysis is used in the index reduction. Assuming there are m evaluation indicators: S1, S2, Sm, and they are divided into k categories. The correlation coefficient absolute value of two index data can be calcu lated through the correlation matrix analysis. And the value represents the correlation level of two indices, the standard is as follows: 0.3
the total investment target
major network construction investment target
vestment target in maintenance and technological upgrading
distribution network construction investment target
rate of change of equipment defects per unit of investment
of
of
recovery ability income per unit of investment
changes in power supply reliability
trouble-free operation interval equipment availability coefficient increase equipment per unit of investment
income growth of distribution network
proportion of bottleneck line
power supply growth per unit of investment
power supply of distribution network after loss reduction
power supply per unit of line power supply growth per new unit of distribution transformer capacity
investment returns of single projects
power supply per unit of distribution transformer capacity
transformer load distribution
Increase in power supply per new line
power supply per unit of line
power supply growth per new unit of substation capacity
capacity load ratio
power supply per unit of substation capacity
Power loss reduction
new benefits per unit of fixed assets
power supply per unit of fixed assets
power supply growth per investment unit
Figure 1 Investment Evaluation Index System of Power Grid Enterprises
(3) Weighting This paper uses the weights combination method to reconcile the advantages of subjective weighting method and objective weighting method, including coefficient variation method, Delphi method and entropy method. Supposing there are m indicators, the weight w can be obtained by q methods, the combined weights are:
Tj
q
m
(1)
j 1 k 1
k 1
Tj
q
w j (k ) / ¦ w j (k ) j 1, 2,..., m;k 1, 2,..., q stands for the combined weight.
(4) The comprehensive score model Linear model is used to summarize the normalized index value, and then get the comprehensive score which makes the evaluation result more intuitive. m
y
¦w x j
j
j 1
y is the value of comprehensive score, T j is the evaluation indicator value, coefficient.
x j is the weight
227
Luo Guoliang et al. / Energy Procedia 5 (2011) 224–228
4. Empirical Study 4.1. Index Reduction The data of 15 indicators fro m 2003 to 2006 of six power grid enterprises under a provincial power company has been obtained while the other 4 indicators ’ data is not availab le for now. Here, W1, W2, W3, W4, W5, W 6 stand for the six power grid enterprises respectively. The preliminary program of the reduction indicators can be obtained, as shown in Table 1. 4.2. Data Normalization According to the available data and the premise of less data, indicators after reduction have been normalized with linear membership function and different membership functions to get the value of membership of indicators. 4.3. Weighting Multiplication synthesis has been used to get the combined weighting of these after-reduction indicators, the weights are as follows in Table 1. T able 1 the reduction indicators after correlation analysis and target weight
Number
Index name
combination weighting
Number
Index name
Combination weighting
1
power supply growth per unit of investment
0.087 8
6
power supply per unit of line 110kV
0.040 9
2
power supply per unit of fixed assets
0.080 4
7
power supply growth per unit of investment
0.037 4
0.079 1
8
power supply per unit of line(distribution network)
0.032 4
0.050 5
9
power supply after loss reduction(distribution network)
0.019 0
0.070 2
10
changes in power supply reliability
0.026 9
power supply per unit of transformer capacity 220kV
0.042 2
11
availability coefficient increase of per unit investment
0.018 0
power supply per unit of transformer capacity 110kV
0.031 8
12
trouble-free operation interval of equipment
0.033 6
3
power supply after loss reduction
capacity load ratio 220kV 4
5
6
capacity load ratio 110kV
l
it f li
0 042 0
4.4. The comprehensive score Calculated by using the normalized data obtained after reduction and the weight calculated by using various methods, we adopted the linear integrated scoring method, and obtained the following eva luation results shown in Table 2.
228
Luo Guoliang et al. / Energy Procedia 5 (2011) 224–228
T able 2 Evaluation Results area
W1
W2
W3
year
Combination weighting
2003
0.351 5
2004
0.393 5
2005
year
Combination weighting
2003
0.262 9
2004
0.299 4
0.309 8
2005
0.243 2
2006
0.390 4
2006
0.233 1
2003
0.368 0
2003
0.145 4
2004
0.452 6
2004
0.190 7
2005
0.363 0
2005
0.183 5
2006
0.326 8
2006
0.101 3
2003
0.224 3
2003
0.217 8
2004
0.313 4
2004
0.248 1
2005
0.259 1
2006
0.195 3
2005
0.176 5
2006
0.204 5
area
W4
W5
W6
5. Conclusion In the light of existing evaluation method’s shortcomings, and co mbin ing power grid enterprise’s characteristics, a more appropriate method is brought up to construct the evaluation model to evaluate power grid enterprise’s investment benefits. The method takes the cost-benefit ratio as the target, major network construction investment, distribution networks construction investment and the investment of maintenance and technological upgrading as sub-goal. And through emp irical research, the co rrectness of the model has been verified.
References [1] Hu Rongˈ Zhang Yan, Fan Chao. Research on the post -evaluation index system of distribution network planning [J].EAST CHINA ELECT RIC POWER, 2007, 35(8):70~74 (in Chinese). [2] Han Lihong. Research on the mathematic evaluation method of the investment benefit of grid enterprise [J]. JOURNAL OF HEBEI UNIVERSIT Y OF SCIENCE AND T ECHNOLOGY, 2009, 6:180~186 (in Chinese). [3] Sun Zhao-jun. Research on the evaluation method of the investment benefit [J].AUDIT ING AND FINANCE , 2005, 8: 44~46 (in Chinese). [4] Wei Gang. The contrast of the evaluation method of the investment benefit of electric investment p roject [J] .JOURNAL OF SHANGHAI UNIVERSIT Y OF ELECT RIC POWERˈ2007, 4: 23~28 (in Chinese). [5] Jin Jingyu. Fuzzy Integrated Evaluation and investment benefit appraisal [J].TECHNOECONOMICS & MANAGEMENT RESEARCH, 2000, 3:37~38 (in Chinese). [6] Li Yin-guo, Li Xin-chun. Research on Determining Avionics System's Weighting Coefficient in Integrate Evaluate Mode [J].JOURNAL OF EAST ERN LIAONING UNIVERSITYSOCIAL SCIENCES, 2007, 4: 56~62 (in Chinese). [7] Zhao Hui-ru. Research on the investment optimization of grid construction project and assistance decision support systems [J]. EAST CHINA ELECTRIC POWERˈ2007,35(6): 23~25.