CN111080133A - Photovoltaic power station financing risk assessment method, system, equipment and storage medium - Google Patents
Photovoltaic power station financing risk assessment method, system, equipment and storage medium Download PDFInfo
- Publication number
- CN111080133A CN111080133A CN201911309874.4A CN201911309874A CN111080133A CN 111080133 A CN111080133 A CN 111080133A CN 201911309874 A CN201911309874 A CN 201911309874A CN 111080133 A CN111080133 A CN 111080133A
- Authority
- CN
- China
- Prior art keywords
- financing
- information
- power station
- determining
- photovoltaic power
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 58
- 238000012502 risk assessment Methods 0.000 title claims description 27
- 238000010276 construction Methods 0.000 claims abstract description 55
- 238000011156 evaluation Methods 0.000 claims description 31
- 238000012797 qualification Methods 0.000 claims description 8
- 238000004590 computer program Methods 0.000 claims description 7
- 238000012423 maintenance Methods 0.000 claims description 5
- 230000005611 electricity Effects 0.000 claims description 3
- 230000001960 triggered effect Effects 0.000 claims description 2
- 230000008569 process Effects 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 6
- 230000009471 action Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 230000007423 decrease Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000010248 power generation Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 238000011069 regeneration method Methods 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/90—Financial instruments for climate change mitigation, e.g. environmental taxes, subsidies or financing
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The embodiment of the invention discloses a method, a system, equipment and a storage medium for evaluating financing risk of a photovoltaic power station. The method comprises the following steps: acquiring income information, construction information, controller information and subsidy information of the photovoltaic power station, and determining a power station stability coefficient, a debt repayment stability coefficient, a subsidy stability coefficient and a discount value; determining a first financing upper limit according to the correlation coefficient and the discount value; determining the total amount of the project of the power station and the total amount of the value of the leased goods according to the construction information; determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit; and acquiring the rent starting amount of the photovoltaic power station, and judging whether the financing risk is controllable according to the final financing upper limit and the rent starting amount. The method has the advantages that the used related parameters are richer and have strong correlation with the photovoltaic power station, the estimated first financing upper limit is more accurate and has decision reference value, each complex influence factor is quantized, the use is convenient, and the universality is strong.
Description
Technical Field
The invention belongs to the technical field of power station asset value evaluation, and particularly relates to a method, a system, equipment and a storage medium for evaluating financing risk of a photovoltaic power station.
Background
Under the strong support of national policies, the photovoltaic power station industry in China has been obviously scaled in recent years. And the '531 photovoltaic new administration' in 2018 further standardizes the industry development, reduces the dependence of the industry on financial subsidies, and pushes related enterprises to the way of self-regeneration and self-innovation.
Under the influence of the policies, the asset trading market of the photovoltaic power station needs a more accurate asset evaluation method, the existing asset value evaluation of the photovoltaic power station mainly focuses on the value evaluation of the photovoltaic power station for equity trading, and the existing asset value evaluation of the operated photovoltaic power station mainly uses a profit method based on future cash flow for evaluating the value due to the stable future cash flow.
The existing asset value evaluation method is only suitable for the condition of asset value evaluation of equity trading, is not suitable for creditor trading, and does not completely consider the special policy characteristics of the photovoltaic power station, so that the judgment is not accurate enough when risk evaluation is carried out on the basis of the asset value in the financing trading of the photovoltaic power station.
Disclosure of Invention
The invention aims to provide a method, a system, equipment and a storage medium for evaluating financing risk of a photovoltaic power station, so as to solve the problem that the evaluation of the value of the power station is inaccurate, which causes the inaccurate evaluation of the financing risk in the prior art.
In order to solve the above problem, in a first aspect, an embodiment of the present invention provides a method for evaluating a risk of financing of a photovoltaic power station, including:
acquiring income information, construction information, control person information and subsidy information of the photovoltaic power station;
determining a stability coefficient of the power station according to the construction information, determining a repayment stability coefficient according to the controller information, determining a subsidy stability coefficient according to the subsidy information, and determining a discount value according to the income information and the controller information;
determining a first financing upper limit according to the power station stability coefficient, the debt paying stability coefficient, the subsidy stability coefficient and the discount value;
determining the total amount of the project of the power station and the total amount of the price of the leasehold according to the construction information;
determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit;
and acquiring the rent starting amount of the photovoltaic power station, and judging whether the financing risk is controllable or not according to the final upper financing limit and the rent starting amount.
On the other hand, the embodiment of the invention provides a photovoltaic power station financing risk assessment system, which comprises:
the information acquisition module is used for acquiring income information, construction information, control person information and subsidy information of the photovoltaic power station;
the coefficient determining module is used for determining a stability coefficient of the power station according to the construction information, determining a repayment stability coefficient according to the controller information, determining a subsidy stability coefficient according to the subsidy information, and determining a discount value according to the income information and the controller information;
the first financing upper limit determining module is used for determining a first financing upper limit according to the power station stability coefficient, the debt paying stability coefficient, the subsidy stability coefficient and the discount value;
the first determining module is used for determining the total amount of project of the power station and the total amount of value of the leasehold according to the construction information;
the final financing upper limit determining module is used for determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit;
and the risk evaluation module is used for acquiring the rent starting amount of the photovoltaic power station and judging whether the financing risk is controllable or not according to the final upper financing limit and the rent starting amount.
In still another aspect, an embodiment of the present invention provides a photovoltaic power plant financing risk assessment device, which includes a memory and a processor, where the memory stores a computer program executable by the processor, and the processor executes the computer program to implement the photovoltaic power plant financing risk assessment method according to the first aspect.
In yet another aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program, the computer program comprising program instructions, which when executed, implement the method for assessing financing risk of a photovoltaic power plant according to the first aspect.
The photovoltaic power station financing risk assessment method provided by the embodiment of the invention has the advantages that the used related parameters are richer, the relevance with the photovoltaic power station is strong, the first financing upper limit assessed by the method is more accurate, the method has a decision reference value, each complex influence factor is quantized, the use is convenient, and the universality is strong.
Drawings
Fig. 1 is a flowchart of a method for assessing financing risk of a photovoltaic power station according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for assessing financing risk of a photovoltaic power plant according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a system for evaluating financing risk of a photovoltaic power station according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a photovoltaic power station financing risk assessment device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It is to be further noted that, for the convenience of description, only a part of the structure relating to the present invention is shown in the drawings, not the whole structure.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Furthermore, the terms "first," "second," and the like may be used herein to describe various orientations, actions, steps, elements, or the like, but these orientations, actions, steps, or elements are not limited by these terms. These terms are only used to distinguish one direction, action, step or element from another direction, action, step or element. For example, a first model may be referred to as a second model, and similarly, a second model may be referred to as a first model, without departing from the scope of the present invention. The first model and the second model are both models, but they are not the same model. The terms "first", "second", etc. are not to be construed as indicating or implying any relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise. It should be noted that when one portion is referred to as being "secured to" another portion, it may be directly on the other portion or there may be an intervening portion. When a portion is said to be "connected" to another portion, it may be directly connected to the other portion or intervening portions may be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not denote a single embodiment.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. A process may be terminated when its operations are completed, but may have additional steps not included in the figure. Processing may correspond to methods, functions, procedures, subroutines, and the like.
Example one
Fig. 1 is a flowchart of a method for evaluating financing risk of a photovoltaic power station according to an embodiment of the present invention, where the method provided by the embodiment is applicable to value evaluation of a photovoltaic power station for creditor trading in an asset trading market, and the specific flow is as follows:
and S110, acquiring income information, construction information, control person information and subsidy information of the photovoltaic power station.
In the embodiment, the assessment of the financing risk of the photovoltaic power station is based on the asset value of the photovoltaic power station, and regarding the asset value, the asset value assessment based on a future cash flow income method is used in the prior art.
Step S120, determining a stability coefficient of the power station according to the construction information, determining a repayment stability coefficient according to the controller information, determining a subsidy stability coefficient according to the subsidy information, and determining a discount value according to the income information and the controller information.
More specifically, the income information comprises installed capacity, available hours per year, decline rate, post price, land rent per year, operation and maintenance per year and other expenses of the photovoltaic power station; the construction information comprises necessary files, equipment manufacturers and construction enterprises; the controller information comprises controller qualification and controller credit; the subsidy information comprises a compensation type and a compensation force. The income information is used for calculating the net cash flow of the photovoltaic power station, namely, the income information is used for calculating the future cash flow of the photovoltaic power station, the larger the net cash flow is, the higher the value of the photovoltaic power station is, the construction information is used for evaluating the quality of the photovoltaic power station, the main evaluation equipment quality and the construction facility quality are, the better the quality is, the more stable the power generation performance of the photovoltaic power station is, the lower the possibility that the photovoltaic power station has faults and other problems is, the higher the value evaluation of the photovoltaic power station is, the higher the credit rating of a controller is, the higher the value evaluation of the photovoltaic power station is, the subsidy information is the subsidy of the state or government to the electricity price of renewable energy sources, and the larger and more stable the subsidy is, the.
For example, in some embodiments, different evaluation criteria may be set to obtain the corresponding coefficients: regarding the stability coefficient of the power station, the grading relation among the necessary files, the equipment manufacturers and the construction enterprises can be adjusted according to different specific conditions, the files are graded according to the missing degree of the necessary files to obtain the grading of the files, the equipment grading is graded according to the industry ranking or the product quality ranking of the equipment manufacturers (the equipment grading can be obtained by grading the manufacturers of various adopted equipment respectively and then integrating the grading of the equipment), the construction grading is obtained according to the industry ranking and the construction quality grading of the construction enterprises, the three grading can be combined in various operation modes, for example, the sum of the equipment grading and the construction grading is taken according to a certain proportion, the sum of the equipment grading and the construction grading is multiplied by the file grading to serve as the stability coefficient of the power station, for example, A ═ a1*(k1a2+k2a3) Wherein A is the stability factor of the power station, a1Is a text ofPiece score, a2Score the device, a3To build a score, k1、k2Is a proportionality coefficient; regarding the repayment stability coefficient, the qualification of the controller can be independent and joint, whether an external enterprise exists or not, and the like, the credit of the controller can be based on whether the past credit record of the controller has default or not and the default times, the specific scoring standard is not limited, the repayment stability coefficient is obtained according to the information, the qualification scoring can be obtained according to the qualification of the controller, the credit scoring is obtained according to the past credit record of the controller, and the sum of the two is taken as the repayment stability coefficient in a certain proportion, for example, if B is j, j1b1+j2b2Where B is the repayment stability factor, B1Scoring for qualification, b2Scoring the credit, j1、j2Is a proportionality coefficient; the subsidy stability coefficient can be divided into local subsidies and national subsidies according to the subsidy types, different subsidy strengths are different, and the subsidy income evaluation can be calculated by integrating the subsidy policy to obtain the subsidy stability coefficient according to the customized subsidy income grading standard; regarding the discount value, the discount value can be obtained by adopting a simple fixed discount rate method, namely, the discount value is calculated according to the future cash flow and the discount rate of the photovoltaic power station, the future cash flow of the photovoltaic power station is calculated based on the factors such as the installed capacity, the annual available hours, the decay rate, the benchmarking electricity price, the land rent, the rentable age limit and the operation and maintenance fee, other factors except the rentable age limit can be counted to obtain a stable parameter, the rentable age limit mainly depends on the comprehensive evaluation of a power station controller within the design working age limit of the photovoltaic power station, and exemplarily, a credit grading standard (different credit grading intervals correspond to different rentable age limits) can be customized, and the corresponding rentable age limit is obtained according to the credit grading standard of the controller. Therefore, in this embodiment, the rentable period is determined based on the information of the controller, and the determination process of the discount value is as follows: determining rentable years of the photovoltaic power station according to the controller information, and determining discount values according to the rentable years of the photovoltaic power station and the income information.
It should be noted that the above-mentioned power station stability coefficient, the repayment stability coefficient, and the subsidy stability coefficient are obtained by quantitatively evaluating the relevant information, and the specific evaluation criteria thereof are not fixed, and may be different for different photovoltaic power stations, and the purpose thereof is to obtain a reasonable upper limit of financing, so that the corresponding parameter value in the evaluation criteria needs to correspond to the calculation formula of the upper limit of financing, and the evaluation example provided in this embodiment is not a limitation on the corresponding criteria or rules.
And step S130, determining a first financing upper limit according to the power station stability coefficient, the repayment stability coefficient, the subsidy stability coefficient and the discount value.
After the stability coefficient, the repayment stability coefficient, the subsidy stability coefficient and the discount value of the power station are determined, the asset value of the photovoltaic power station can be determined, a suggested first financing upper limit is obtained according to the asset value, and specifically, the determination process of the first financing upper limit meets the following formula:
wherein, Y1The first upper limit of financing is X, the discount value is X, A is the stability coefficient of the power station, B is the repayment stability coefficient, C is the subsidy stability coefficient, 120% is the coverage rate standard of the discount value to the financing amount in the lease period, and X (0.3A +0.4B +0.3C) can be regarded as the asset value of the photovoltaic power station.
And step S140, determining the total amount of the project of the power station and the total amount of the value of the leasehold according to the construction information.
The total amount of the power station project and the total amount of the rental value are two general standards for evaluating the financing risk, the two parameters can be obtained according to related project information, namely construction information, when the photovoltaic power station invests in construction, and the upper limit of financing of the photovoltaic power station cannot exceed eighty percent of the total amount of the power station project and cannot exceed the total amount of the rental value under normal conditions.
And S150, determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit.
After three values for evaluating the financing risk, namely the first financing upper limit, the total amount of the power station project and the total amount of the rental value, are obtained, the final financing upper limit needs to be comprehensively considered for financing risk evaluation, and in the embodiment, the final financing upper limit needs to satisfy the following formula:
Y＝min(Y1,0.8Y2,Y3)
wherein Y is the final financing upper limit, Y1Is the first financing upper limit, Y2For the total of the power station project, Y3Is a rental price total.
And S160, acquiring the rent starting amount of the photovoltaic power station, and judging whether the financing risk is controllable according to the final upper financing limit and the rent starting amount.
Based on the final financing upper limit obtained in step S150, the initial rent amount of the photovoltaic power station for lease needs to be further obtained to evaluate the financing risk, in this embodiment, when the initial rent amount is greater than or equal to the final financing upper limit, it may be determined that the financing risk is uncontrollable, that is, the risk is high, and when the initial rent amount is less than the final financing upper limit, it may be determined that the financing risk is controllable, that is, the risk is low.
More specifically, a certain actual 20MW photovoltaic power station is taken as an example evaluation object. The power station is connected to the grid in 2015 at full capacity of 12-month-31-day, the price of the standard pole is 1.0 yuan/kwh, and the total amount of the power station project is 1.5 million yuan. In 2016, 6 months, the photovoltaic power station financing risk assessment method provided by the embodiment is adopted to assess the power station due to business needs: the first-year available hours of the power station are 1060 hours/year, the power generation attenuation rate is 2% in 1 st year, the second year is 1.2%, the subsequent years are 0.8%, local subsidies are 0.2 yuan/kwh, the subsidy period is 20 years, 25-year land rent is paid for 638.48 yuan in one time, the annual operation and maintenance cost is 100 yuan/year, the relevant essential files of the projects approved by relevant organizations such as county-level development committee, national soil resource bureau, government, power grid company and the like are all obtained, the evaluation of the files is 1, the main equipment manufacturer of the power station is the leading manufacturer of the domestic industry, the evaluation of the major equipment manufacturer of the power station is 1 (the evaluation of the manufacturers of various equipment is 1), the qualification of the underwriting enterprises is good, the establishment period is long, and the over-bidding operation is carried outHas a quality good hypothesis score of 0.95 at k1、k2The stability coefficient of the power station is 0.975 under the condition of 0.5; the actual controller is a civil enterprise, and the credit record is good and the assumed score is 0.9, and the actual controller is assumed that the credit record is good and the assumed score is 71.25 and the assumed score is 1.0, and j is assumed1、j2The stability coefficient of the repayment of 0.5 is B which is 0.95, the power station has a national subsidy and enters a catalogue, the stability coefficient of the repayment is C which is 0.95 according to a self-defined standard, the credit rating of a main body of an actual project controller is 71.25, and the rentable age obtained according to the corresponding relation of the credit rating and the rentable age is 9.75 years; the reduction rate of the internal guide of the company is 7.24 percent, the reduction value X obtained by the net cash flow of the power station is 15,332 ten thousand yuan, and the upper limit of the financing amount is recommended by the project
The total investment of the project is 15,000 ten thousand yuan, the value of leased objects (equipment and part of project money) is 12,936 ten thousand yuan, the final financing upper limit of the project is Y min (12,234,0.8 × 15,000,12,936) 12,000 ten thousand yuan, and the financing risk of the photovoltaic power station is controllable on the assumption that the planned lease amount of the photovoltaic power station is 11,000 ten thousand yuan.
The method for evaluating the financing risk of the photovoltaic power station, provided by the embodiment, can determine a stability coefficient, a liability stability coefficient, a subsidy stability coefficient and a discount value of the power station by integrating the dimensions of the revenue information, the construction information, the controller information and the subsidy information of the photovoltaic power station, further determine a first financing upper limit based on the asset value of the photovoltaic power station, determine a final financing upper limit as a financing risk evaluation standard by combining the total amount of the project of the power station and the total amount of the value of the leases, compare the lease-starting amount of the photovoltaic power station with the final financing upper limit to judge whether the financing risk is controllable, comprehensively analyze the combination of the stability coefficient, the liability stability coefficient and the subsidy stability coefficient on the basis of the discount value to obtain the first financing upper limit, have richer used related parameters and strong correlation with the photovoltaic power station, and have more accurate decision reference value for the first financing upper limit evaluated, each complex influence factor is quantized, and the method is convenient to use and high in universality.
Example two
The present embodiment is implemented on the basis of the first embodiment, and is different from the first embodiment in that the method for evaluating a financing risk of a photovoltaic power plant provided by the present embodiment further includes a risk monitoring process for continuously evaluating a risk condition of a project during a lease period of the photovoltaic power plant, and a specific flow is as shown in fig. 2:
and S210, acquiring income information, construction information, control person information and subsidy information of the photovoltaic power station.
Step S220, determining a power station stability coefficient according to the construction information, determining a debt paying stability coefficient according to the controller information, determining a subsidy stability coefficient according to the subsidy information, and determining a discount value according to the income information and the controller information.
And step S230, determining a first financing upper limit according to the power station stability coefficient, the repayment stability coefficient, the subsidy stability coefficient and the discount value.
And step S240, determining the total amount of the project of the power station and the total amount of the value of the leasehold according to the construction information.
And S250, determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit.
And S260, acquiring the rent starting amount of the photovoltaic power station, and judging whether the financing risk is controllable according to the final financing upper limit and the rent starting amount.
Step S270, obtaining the residual risk exposure and the residual lease time of the photovoltaic power station, obtaining the updated income information, construction information, control person information and subsidy information of the photovoltaic power station, determining a second financing upper limit according to the residual lease time and the updated income information, construction information, control person information and subsidy information of the photovoltaic power station, and evaluating whether to trigger risk pre-warning according to the second financing upper limit and the residual risk exposure.
In step S220, the calculation of the cash flow in the acquisition of the first financing upper limit is based on the rentable time of the photovoltaic power station, risk early warning may be required for a stock project in practice, at this time, rentable time does not need to be calculated again but remaining rentable time needs to be acquired, the risk of financing of the photovoltaic power station is continuously early warned when the project is performed, a remaining evaluation value in a renting period, that is, a second financing upper limit, may be obtained according to the remaining rentable time of the photovoltaic power station and an updated value of the photovoltaic power station (updated revenue information, construction information, controller information, and subsidy information of the photovoltaic power station), the remaining risk of the photovoltaic power station is acquired again, and when the remaining financing upper limit is less than the remaining risk, it is stated that the financing risk is uncontrollable, and otherwise, it is controllable. It should be noted that the specific calculation process of the second financing upper limit is actually consistent with the calculation process of the first financing upper limit, and the difference is that, except for the difference between the income information, the construction information, the controller information and the subsidy information of the photovoltaic power station, the rentable years are used in the calculation of the first financing upper limit, and the remaining rentable years are used in the calculation of the second financing upper limit.
Taking the actual photovoltaic power plant provided in the first embodiment as an example, the project was rented at the end of 2016 at 6 months, and the residual risk exposure of the project at the end of 2019 at 6 months was 9,104 ten thousand yuan. And (4) performing risk assessment by project time point data at the end of 6 months in 2019, wherein the upper limit of the surplus financing corresponding to the residual lease age is 9,497 ten thousand yuan which is more than 9,104 ten thousand yuan of project residual risk opening, so that the project condition is good, the risk is controllable, and the risk early warning is not triggered.
The method further supplements the financing risk assessment process during the photovoltaic power station lease on the basis of the first embodiment, and realizes immediate risk assessment to avoid the situation that the risk is uncontrollable and cannot be discovered in time along with the progress of the project.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a photovoltaic power station financing risk assessment system 300 according to a third embodiment of the present invention, where the system is capable of executing a photovoltaic power station financing risk assessment method according to any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method, and the method provided by this embodiment may be applied to photovoltaic power station financing risk assessment meeting the requirements of economic indicators of investment subjects, and specifically includes:
the information acquisition module 310 is configured to acquire revenue information, construction information, control person information, and subsidy information of the photovoltaic power station.
More specifically, the income information comprises installed capacity, available hours per year, decline rate, post price, land rent per year, operation and maintenance per year and other expenses of the photovoltaic power station; the construction information comprises necessary files, equipment manufacturers and construction enterprises; the controller information comprises controller qualification and controller credit; the subsidy information comprises a compensation type and a compensation force.
The coefficient determining module 320 is configured to determine a power station stability coefficient according to the construction information, determine a repayment stability coefficient according to the controller information, determine a subsidy stability coefficient according to the subsidy information, and determine a discount value according to the income information and the controller information.
The determining of the discount value needs to be based on the rentable age, which is affected by credit of the controller in this embodiment, that is, the determining of the discount value according to the income information and the controller information includes: determining the rentable years of the photovoltaic power station according to the information of the control persons; and determining a discount value according to the rentable age of the photovoltaic power station and the income information.
Specifically, according to the rentable age of the photovoltaic power station and the income information, determining that the discount value meets the following formula:
wherein X is the cash value, n is the rentable year, t represents the rentable year, XtThe net cash flow in the t year of lease is calculated from the profit information, and r is the discount rate.
And the first financing upper limit determining module 330 is configured to determine a first financing upper limit according to the power station stability coefficient, the debt paying stability coefficient, the subsidy stability coefficient, and the discount value.
Specifically, the first upper financing limit is determined according to the power station stability coefficient, the repayment stability coefficient, the subsidy stability coefficient and the discount value to satisfy the following formula:
wherein, Y1Is the first financing upper limit, X is the discount value, A is the plant stability coefficient, B is the repayment stability coefficient, and C is the subsidy stability coefficient.
And the first determining module 340 is used for determining the total amount of the power station project and the total amount of the rental value according to the construction information.
And a final financing upper limit determining module 350, configured to determine a final financing upper limit according to the total amount of the power station project, the total amount of the rental goods value, and the first financing upper limit.
And the risk evaluation module 360 is used for acquiring the rent starting amount of the photovoltaic power station and judging whether the financing risk is controllable according to the final financing upper limit and the rent starting amount.
Optionally, in some embodiments, the system for assessing financing risk of a photovoltaic power plant further includes:
and the risk early warning module is used for acquiring the residual risk exposure and the residual lease time of the photovoltaic power station, acquiring the updated income information, construction information, control person information and subsidy information of the photovoltaic power station, determining a second financing upper limit according to the residual lease time and the updated income information, construction information, control person information and subsidy information of the photovoltaic power station, and evaluating whether to trigger risk early warning according to the second financing upper limit and the residual risk exposure.
The embodiment provides a photovoltaic power station financing risk assessment system, which can determine a power station stability coefficient, a debt stability coefficient, a subsidy stability coefficient and a discount value by integrating several dimensions of revenue information, construction information, controller information and subsidy information of a photovoltaic power station, further determine a first financing upper limit based on the asset value of the photovoltaic power station, determine a final financing upper limit as a financing risk assessment standard by combining a total amount of power station projects and a total amount of leasehold values, compare the lease-starting amount of the photovoltaic power station with the final financing upper limit to judge whether the financing risk is controllable, comprehensively analyze the power station stability coefficient, the debt stability coefficient and the subsidy stability coefficient on the basis of the discount value to obtain the first financing upper limit, have richer used related parameters and strong correlation with the photovoltaic power station, and have more accurate decision reference value for the first financing upper limit assessed, each complex influence factor is quantized, and the method is convenient to use and high in universality.
Example four
Fig. 4 is a schematic structural diagram of a photovoltaic power plant financing risk assessment apparatus according to a fourth embodiment of the present invention, where the apparatus includes a memory 410 and a processor 420, the number of the processors 420 in the apparatus may be one or more, and fig. 4 takes one processor 420 as an example; the memory 410 and the processor 420 in the device may be connected by a bus or other means, and fig. 4 illustrates the connection by a bus as an example.
The memory 410 is used as a computer-readable storage medium and can be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the method for evaluating the financing risk of a photovoltaic power plant in the embodiment of the present invention (for example, the information acquisition module 310, the coefficient determination module 320, the first financing upper limit determination module 330, the first determination module 340, the first determination module 350, and the risk evaluation module 360 in the system for evaluating the financing risk of a photovoltaic power plant). The processor 420 executes various functional applications and data processing of the photovoltaic power station financing risk assessment device by running the software programs, instructions and modules stored in the memory 410, that is, the above-mentioned photovoltaic power station financing risk assessment method is realized.
Wherein the processor 420 is configured to run the computer executable program stored in the memory 410 to implement the following steps: step S110, obtaining income information, construction information, control person information and subsidy information of the photovoltaic power station; step S120, determining a stability coefficient of the power station according to the construction information, determining a repayment stability coefficient according to the controller information, determining a subsidy stability coefficient according to the subsidy information, and determining a discount value according to the income information and the controller information; step S130, determining a first financing upper limit according to the power station stability coefficient, the repayment stability coefficient, the subsidy stability coefficient and the discount value; step S140, determining the total amount of the project of the power station and the total amount of the price of the rental goods according to the construction information; s150, determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit; and S160, acquiring the rent starting amount of the photovoltaic power station, and judging whether the financing risk is controllable according to the final upper financing limit and the rent starting amount.
Of course, the equipment for evaluating the financing risk of the photovoltaic power station provided by the embodiment of the present invention is not limited to the above method operations, and may also perform the relevant operations in the method for evaluating the financing risk of the photovoltaic power station provided by any embodiment of the present invention.
The memory 410 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 410 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 410 may further include memory remotely located from the processor 620, which may be connected to the photovoltaic power plant financing risk assessment device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The embodiment provides a photovoltaic power station financing risk assessment device, a first financing upper limit is obtained by comprehensively analyzing a power station stability coefficient, a repayment stability coefficient and a subsidy stability coefficient on the basis of a discount value, used related parameters are richer and have strong relevance with a photovoltaic power station, the first financing upper limit assessed by the photovoltaic power station financing risk assessment device has more accurate decision reference values, each complex influence factor is quantized, the photovoltaic power station financing risk assessment device is convenient to use and strong in universality.
EXAMPLE five
An embodiment of the present invention further provides a storage medium containing computer executable instructions, where the computer executable instructions are executed by a computer processor to perform a method for assessing financing risk of a photovoltaic power station, where the method for assessing financing risk of a photovoltaic power station includes:
acquiring income information, construction information, control person information and subsidy information of the photovoltaic power station;
determining a stability coefficient of the power station according to the construction information, determining a repayment stability coefficient according to the controller information, determining a subsidy stability coefficient according to the subsidy information, and determining a discount value according to the income information and the controller information;
determining a first financing upper limit according to the power station stability coefficient, the debt paying stability coefficient, the subsidy stability coefficient and the discount value;
determining the total amount of the project of the power station and the total amount of the price of the leasehold according to the construction information;
determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit;
and acquiring the rent starting amount of the photovoltaic power station, and judging whether the financing risk is controllable or not according to the final upper financing limit and the rent starting amount.
Of course, the storage medium provided by the embodiment of the present invention contains computer-executable instructions, and the computer-executable instructions are not limited to the above method operations, and may also perform related operations in the method for assessing financing risk of a photovoltaic power plant provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for a person skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a device, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the above-mentioned equipment for assessing financing risk of a photovoltaic power plant, each unit and each module included in the equipment are only divided according to functional logic, but are not limited to the above-mentioned division as long as the corresponding function can be realized; in addition, the specific names of the functional units are only for convenience of distinguishing from each other and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. Those skilled in the art will appreciate that the present invention is not limited to the particular embodiments disclosed, but is capable of numerous rearrangements, modifications, and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in more detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (9)
1. A photovoltaic power station financing risk assessment method is characterized by comprising the following steps:
acquiring income information, construction information, control person information and subsidy information of the photovoltaic power station;
determining a stability coefficient of the power station according to the construction information, determining a repayment stability coefficient according to the controller information, determining a subsidy stability coefficient according to the subsidy information, and determining a discount value according to the income information and the controller information;
determining a first financing upper limit according to the power station stability coefficient, the debt paying stability coefficient, the subsidy stability coefficient and the discount value;
determining the total amount of the project of the power station and the total amount of the price of the leasehold according to the construction information;
determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit;
and acquiring the rent starting amount of the photovoltaic power station, and judging whether the financing risk is controllable or not according to the final upper financing limit and the rent starting amount.
2. The method of claim 1, wherein:
the income information comprises installed capacity, available annual hours, attenuation rate, post electricity price, annual land rent, annual operation and maintenance cost and other expenses of the photovoltaic power station;
the construction information comprises necessary files, equipment manufacturers and construction enterprises;
the controller information comprises controller qualification and controller credit;
the subsidy information comprises a compensation type and a compensation force.
3. The method of claim 1, wherein determining a discount value based on the benefit information and the controller information comprises:
determining the rentable years of the photovoltaic power station according to the information of the control persons;
and determining a discount value according to the rentable age of the photovoltaic power station and the income information.
4. The method of claim 3, wherein the determining a discount value from the rentable age of the photovoltaic power plant and the revenue information satisfies the following equation:
5. The method of claim 1, wherein determining a first financing cap based on the plant stability factor, the repayment stability factor, the subsidy stability factor, and the discount value satisfies the following equation:
wherein, Y1Is the first financing upper limit, X is the discount value, A is the plant stability coefficient, B is the repayment stability coefficient, and C is the subsidy stability coefficient.
6. The method of claim 1, wherein after determining the final upper financing limit based on the total amount of the power project, the total amount of the rental value, and the first upper financing limit, further comprising:
the method comprises the steps of obtaining the residual risk exposure and the residual lease time of the photovoltaic power station, obtaining updated income information, construction information, control person information and subsidy information of the photovoltaic power station, determining a second financing upper limit according to the residual lease time and the updated income information, construction information, control person information and subsidy information of the photovoltaic power station, and evaluating whether risk early warning is triggered according to the second financing upper limit and the residual risk exposure.
7. A photovoltaic power plant financing risk assessment system, comprising:
the information acquisition module is used for acquiring income information, construction information, control person information and subsidy information of the photovoltaic power station;
the coefficient determining module is used for determining a stability coefficient of the power station according to the construction information, determining a repayment stability coefficient according to the controller information, determining a subsidy stability coefficient according to the subsidy information, and determining a discount value according to the income information and the controller information;
the first financing upper limit determining module is used for determining a first financing upper limit according to the power station stability coefficient, the debt paying stability coefficient, the subsidy stability coefficient and the discount value;
the first determining module is used for determining the total amount of the project of the power station and the total amount of the value of the leasehold according to the construction information;
the final financing upper limit determining module is used for determining a final financing upper limit according to the total amount of the power station project, the total amount of the rental value and the first financing upper limit;
and the risk evaluation module is used for acquiring the rent starting amount of the photovoltaic power station and judging whether the financing risk is controllable or not according to the final upper financing limit and the rent starting amount.
8. A photovoltaic power plant financing risk assessment device comprising a memory and a processor, the memory having stored thereon a computer program operable on the processor, when executing the computer program, implementing the photovoltaic power plant financing risk assessment method according to any one of claims 1-6.
9. A computer-readable storage medium, characterized in that the storage medium stores a computer program comprising program instructions which, when executed, implement the method of assessing financing risk of a photovoltaic power plant according to any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911309874.4A CN111080133A (en) | 2019-12-18 | 2019-12-18 | Photovoltaic power station financing risk assessment method, system, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911309874.4A CN111080133A (en) | 2019-12-18 | 2019-12-18 | Photovoltaic power station financing risk assessment method, system, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111080133A true CN111080133A (en) | 2020-04-28 |
Family
ID=70315480
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911309874.4A Pending CN111080133A (en) | 2019-12-18 | 2019-12-18 | Photovoltaic power station financing risk assessment method, system, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111080133A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111754264A (en) * | 2020-06-24 | 2020-10-09 | 国家电网有限公司大数据中心 | Data analysis method based on clean energy subsidy data |
| CN115205695A (en) * | 2022-04-06 | 2022-10-18 | 布瑞克(苏州)农业互联网股份有限公司 | Method and system for determining planting strategy according to planting data |
| CN116151670A (en) * | 2023-02-01 | 2023-05-23 | 北京共识数信科技有限公司 | Intelligent evaluation method, system and medium for marketing project quality of marketing business |
-
2019
- 2019-12-18 CN CN201911309874.4A patent/CN111080133A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111754264A (en) * | 2020-06-24 | 2020-10-09 | 国家电网有限公司大数据中心 | Data analysis method based on clean energy subsidy data |
| CN111754264B (en) * | 2020-06-24 | 2024-04-16 | 国家电网有限公司大数据中心 | Data analysis method based on clean energy subsidy data |
| CN115205695A (en) * | 2022-04-06 | 2022-10-18 | 布瑞克(苏州)农业互联网股份有限公司 | Method and system for determining planting strategy according to planting data |
| CN115205695B (en) * | 2022-04-06 | 2024-03-15 | 布瑞克(苏州)农业互联网股份有限公司 | Method and system for determining planting strategy according to planting data |
| CN116151670A (en) * | 2023-02-01 | 2023-05-23 | 北京共识数信科技有限公司 | Intelligent evaluation method, system and medium for marketing project quality of marketing business |
| CN116151670B (en) * | 2023-02-01 | 2023-11-24 | 北京共识数信科技有限公司 | Intelligent evaluation method, system and medium for marketing project quality of marketing business |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111080133A (en) | Photovoltaic power station financing risk assessment method, system, equipment and storage medium | |
| Amidu et al. | The Effects of Financial Reporting Standards on Tax Avoidance and Earnings Quality: A Case of an Emerging Economy. | |
| McAleer et al. | Has the Basel Accord improved risk management during the global financial crisis? | |
| Gatti et al. | Measuring value‐at‐risk in project finance transactions | |
| Casarin et al. | Risk management of risk under the Basel Accord: A Bayesian approach to forecasting Value-at-Risk of VIX futures | |
| Adewuyi et al. | Electricity outages and firm performance across the six geo-political zones in Nigeria: The role of corruption | |
| CN113095931A (en) | Post-loan risk monitoring method and device and computer equipment | |
| CN116777652A (en) | Risk evaluation model-based financial analysis method | |
| CN116384680A (en) | Visual monitoring method, device and equipment for research and development quality and readable storage medium | |
| CN115600972A (en) | Method, device, equipment and storage medium for verifying and selling of bad assets | |
| An et al. | Impact of transition risks of climate change on Chinese financial market stability | |
| CN110837980A (en) | Enterprise credit rating method, device, equipment and storage medium | |
| Gulati | Relationship between price and open interest in Indian futures market: An empirical study | |
| Dănilă | Credit risk assessment under Basel accords | |
| Pinder | Decision analysis using multinomial logit models: Mortgage portfolio valuation | |
| PARK | A Study on the predictors for O&M cost estimation of K-water's overseas hydropower projects (focused on the E&M equipment) | |
| CN117689482A (en) | Financial evaluation method, system, medium and terminal for power grid asset acquisition project | |
| CN117474640B (en) | Deposit-free leasing device and method | |
| Lisi et al. | Evaluation of Cost-at-Risk related to the procurement of resources in the ancillary services market. The case of the Italian electricity market | |
| Gurenko et al. | Insurance risk transfer and categorization of reinsurance contracts | |
| Gleißner | Risk Management–The Basics | |
| Li et al. | Research on supply chain financing risk assessment of China's commercial banks | |
| US20140330751A1 (en) | Method and system to capture credit risks in a portfolio context | |
| Kutasi | Risks of Commercial Real Estate Financing Based on the Experiences of Supervisory Reviews | |
| Su | Risk Management Research on BOT Project Financing: Based on the Perspective of Commercial Banks |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200428 |