Explain the structural model based on risk factors for Analysis of Power Investment

[Abstract] This paper gives a qualitative point of view the impact of power sector Investment risk factors, and how the various risk factors have an impact on Investment in the power industry, as well as the influence of the size of the issues specific analysis, Investment risks for power generation industry factors, the establishment of a structural model to explain (ISM), the use of this model for power sector Investment risk level classification to identify the various risk factors for primary and secondary relations and internal relations, the main risk for investors to seize control, through specific case analysis of the scientific method and feasibility.

[Keywords] Power Investment; risk assessment, structural model to explain

1 Power Investment risk factors explain the structural model analysis

1.1 ISM Introduction
ISM is the United States, Professor J. Felt China in 1973 as the analysis of complex issues related to socio-economic system and the development of its features is to first decompose complex system into several subsystems (elements), and then analyze a complex system composed of a large number of elements binary relation between, and ultimately construct the system into a multi-level hierarchical structure model.

1.2 to determine the power Investment project faces the risk factors set
Through data analysis and risk management of existing experience and technical personnel at different levels of research and understanding of the needs, this article from the perspective of the general risk management, Investment risk in power generation industry, for example, summed up the implementation process of the main risk factors: price risk, construction cost risk, financing risk and exchange rate risk, the risk of cost of power generation, power industry restructuring, the state's tax, energy, environmental policy; sewage charges, the price of clean alternative energy; the country's GDP growth; coal price risk, market supply and demand, electricity market structure reform, development and Application of new energy sources. So, get power industry Investment risk elements of the system set S = {S1, S2, S3, ..., S13}. pay attention here listed in the feature set and its relationship, but the results of a typical analysis conditions in the specific Application, the specific circumstances of visual project increase or decrease in the risk factor or factors affect the relationship be adjusted.

1.3 to establish the relationship between the risk of adjacent structure and reachability matrix
Here began the gradual ISM model the structural relationship between the risk analysis.

Impact of power generation industry Investment risks set of n elements constitute the set S = {Si ︱ i = 1 ~ n}. Corresponds to the above, n = 13. From Table 1 can create a collection of elements of the adjacency matrix A = (aij) m × n A different risk factors that direct structural relationship between which, when a relationship exists between the two risk factors, the matrix corresponding position value is set to 1, otherwise set to 0, namely:
aij = [JB ({] 1, i ≠ j and Si, Sj has a direct relationship
0, i ≠ j and Si, Sj is no direct relationship or i = j [JB)]
1.4 pairs divided up between the matrix class
The so-called inter-stage division, is to be divided into different levels of different risk, so risk managers when making risk management, so that there is a mind in advance our priorities, varies inside the framework to first understand a few concepts. Up sets: the first Si matrix line up all the elements of a column corresponding to the elements of the set up is defined as the set of elements of Si, with R (Si) said. antecedent sets: Si will be up to the first column of the matrix all the elements of a row corresponding to the elements of a collection of elements of Si is defined as the antecedent set, and T (Si) said.'s most advanced feature set: if R (Si) ∩ T (Si) = R (Si), then definition of R (Si) is the most advanced feature set. From this definition, when R (Si) is the most advanced feature sets, Si impact factor (up to constitute the set of S) is completely contained in the impact factor of Si (Si composition of the antecedent set), which shows, R (Si) in the elements can in the T (Si) found in Si antecedent.

Below the first defined above, from (1) results to find the most advanced elements.

By M known: R (Si) = {S1, S4, S8, S10, S11, S13}, T (S1) = {S1, S2, S3, ..., S13}. Because R (S1) ∩ T (S1) = {S1, S4, S8, S10, S11, S13} = R (S1), so R (S1) is the most advanced feature set. Similarly, R (S2) = {S1, S4, S8, S10, S11, S13}, T (S2) = {(S2)}. because R (S2) ∩ T (S2) ≠ R (S2), so R (S2) is not the most advanced set of features.

Similarly, to determine R (S1), R (S4), R (S8), R (S10) and R (S13) for the most advanced feature set. By the most advanced set of features corresponding to the elements of Level 1 L1 = {S1, S4, S8, S10, S11, S13}. In the reachability matrix, the program corresponding to the L1 element rows and columns, get up to level 2 matrix in Table 1.

In the first two up on the basis of the matrix, according to the definition of the most advanced feature set, determine R (S2), R (S3), R (S7) and R (S12) is the most advanced feature set. Obtained by the time the most advanced set of features corresponding to the elements of level 2 L2 = {S2, S3, S7, S12}. L2 level from the first draw up the matrix elements corresponding to the L2 line and get the first three columns reachability matrix.

1.5 N and the establishment of the skeleton structure of the matrix model of ISM
Will be a completely connected elements of a strong association known as the elements of the so-called fully connected, mutually between these elements is the antecedent, the consequences of each relationship, according to this definition, can determine the L1 ~ L5, only S1 and L1 elements in the S4, S8, S10, S11, S13 is a strong correlation factor can be the S4, S8, S10, S11, S13 to lose, just select the elements of S1, represented by the establishment of the skeleton matrix skeleton is actually a matrix species of reduced reachability matrix, Table 2.


2 thermal power project investment risk structure analysis of the case

2.1 Case conditions
M along the southeast coast in 2009, the city plans to invest 300 × 2MW its suburbs coal-fired units to meet the needs of the future social and economic development. M is not near the city can develop hydropower resources, the state has no urban development in the new energy plan However, there is the city near the coal companies, so its thermal power is the best option, however, the project faced coal prices continued to rise, electricity market reform was accelerated, the state has promulgated a series of high-cost use of energy policy and environmental constraints protection measures and other uncertainties that would bring about investment risk. how to avoid investment risks, become more competitive electric power investment projects need to focus on risk management to consider and solve problems. Links to free download http://www . hi138.com 2.2 Structural analysis of risk
The following section explains the use of structural model analysis on the results of the urban thermal power project investment risk analysis of the major explanatory factors. The first six elements of a general sense there is a strong association, but from the city's thermal power project investment the overall situation, some elements of its share is still in early stages of development or small scale, it is difficult in the risk of the total investment on the threat, for example, because it is not near the city's water resources can be developed, but not in the city state development of new energy plan, the alternative energy and new energy in M ​​city thermal power project investment in the impact can be basically negligible, so in this thermal power project investment risk factors for explanatory analysis omitted element S8 and S13. In addition , considering that the city is tourist city, heavy industry in its share of the total is not high, there is low probability of power shortages, so the elements of S11 can be omitted. In addition, consider the first two elements of the first one factors affect the relationship, given M and the city is a tourist city environmental quality are higher, so important to consider sewage charges, electricity market reform on the electricity price impact, as above, ignoring the S11, so you can remove the first three (S9), and that the level 4 (S5) the direct impact of electricity market reform, while the first five (S6) into environmental policy, energy policy and tax policy, three sub-elements so that Table 1 can be turned into tables 2 shows the level 4 (S5) the direct impact of electricity market reform, while the first five (S9) into environmental policy, energy policy and tax policy, three sub-elements so that Table 1 can be turned into Table 2 show form.

Table 2 combined with the characteristics of the city can clearly see: the environment, energy, tax policy is affecting the thermal power investment project risk root causes, and the city is a tourist city features make the environment even more severe problem. In addition, electricity coal prices, the cost of electricity and fuel, electricity price risk management need to focus on the elements, control them, project risk management is half the battle now, the price of coal-fired power plants in electricity costs in about 60% , and how to use the city near the coal companies an advantage in Chang Wangfen away, bidding in electricity market environment to improve their competitiveness is particularly important. Similarly, how to control the thermal power enterprises operating costs of the tariff reduction also has very important significance.

In summary, the project pay attention to controlling the risk factors of the first one, we must increase the emphasis on sewage charges, which is the city's tourist city by the characteristics of the decision, although this does not fall within a factor, but the urban thermal power investment projects, as important as the first one of its elements.

2.3 The proposed measures to avoid risks
For the electricity price risk, power generation companies in order to obtain stable and relatively cheap supply of coal, must try to reduce intermediate links, M city just near the coal mining enterprises with long-term cooperation, or to be regarded as a wise buy for lower fuel outside the operating costs, by strengthening the internal cost management in all aspects of cost reduction and tapping the potential synergies. As for the issue of sewage charges, and now the main means or through technological innovation to reduce exhaust emissions of waste water, such as incinerators for desulphurization can reduce sulfur dioxide emissions, although the transformation will increase the risk of construction costs, but in the long run is more good than harm.


3 Conclusion

Affect the power generation industry investment risk factors, this method of analysis with the systems Engineering of power generation industry, the impact of investment risk factors and establish a model to explain the structure can be positive for investors to play the following role: to help investors sort out the various risk the intrinsic link between the factors. generating investment risk is a mutual influence of the whole, can not be separated when making risk management inherent relationship between them. the use of ISM modeling approach can be a clear hierarchy, a clear risk of system architecture context, for investors to conduct a comprehensive risk management provides a complete framework for providing a quantitative model based on risk. for investors to sort out the relationship between primary and secondary risk factors for risk managers when making risk management, so that there is a prior heart our priorities, varies inside the frame.


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