CN110766482A - Deep peak regulation compensation cost allocation method and device considering power supply peak regulation quality - Google Patents
Deep peak regulation compensation cost allocation method and device considering power supply peak regulation quality Download PDFInfo
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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Abstract
The application relates to a method and a device for allocating deep peak shaving compensation cost considering power supply peak shaving quality. The method comprises the following steps: acquiring basic data; calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data; establishing and solving a deep peak regulation compensation cost allocation model to obtain deep peak regulation auxiliary service market allocation cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient. By adopting the method, the compensation can be carried out according to the peak regulation effect of each market main body, so that the peak regulation effect and the income degree of each market main body can be simultaneously reflected, the accuracy of the deep peak regulation compensation cost required by each market main body can be improved, and the resource allocation is maximized.
Description
Technical Field
The present application relates to the field of power market technologies, and in particular, to a method and an apparatus for allocating deep peak shaving compensation costs considering peak shaving quality of a power supply, a computer device, and a storage medium.
Background
With the gradual decline trend of the utilization hours of the coal-electric set, the problems of contradiction between wind abandonment, light abandonment, water abandonment, nuclear limitation, system peak regulation, electric heating in the heating season and the like in local areas are gradually highlighted, and the insufficient valley peak regulation capability becomes a main factor for restricting wind power consumption in China. In order to solve the above-mentioned outstanding problems and implement various measures for power system innovation, further improvement and deepening of power auxiliary service compensation (market) mechanism are urgently needed.
However, in the deep peak shaving compensation cost apportionment method for perfecting the power auxiliary service compensation mechanism in the prior art, the apportionment is performed according to the proportion of the internet power of each market subject in the deep peak shaving auxiliary service transaction period based on the principle of who benefits and who undertakes, and the contribution degree (the unit output curve is relative to the system load shape) of each market subject to the system operation cannot be reflected, so that the compensation effect is poor.
Therefore, the method for allocating the deep peak-shaving compensation cost in the prior art has the problem of low allocation accuracy.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a computer device, and a storage medium for allocating the deep peak shaving compensation cost considering the power supply peak shaving quality, which can reasonably solve the above technical problem.
A deep peak regulation compensation cost allocation method considering power supply peak regulation quality comprises the following steps:
acquiring basic data;
calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
establishing and solving a deep peak regulation compensation cost allocation model to obtain deep peak regulation auxiliary service market allocation cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
A depth peaking compensation cost apportionment apparatus considering power supply peaking quality, the apparatus comprising:
the data acquisition module is used for acquiring basic data;
the data calculation module is used for calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
the model solving module is used for establishing and solving a deep peak regulation compensation cost apportionment model to obtain deep peak regulation auxiliary service market apportionment cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring basic data;
calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
establishing and solving a deep peak regulation compensation cost allocation model to obtain deep peak regulation auxiliary service market allocation cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring basic data;
calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
establishing and solving a deep peak regulation compensation cost allocation model to obtain deep peak regulation auxiliary service market allocation cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
According to the method, the device, the computer equipment and the storage medium for allocating the deep peak shaving compensation cost considering the power supply peak shaving quality, the basic data are obtained, the full-network deep peak shaving compensation cost and the unit peak shaving quality coefficient are calculated according to the basic data, and then a deep peak shaving compensation cost allocation model is established and solved by utilizing the full-network deep peak shaving compensation cost and the unit peak shaving quality coefficient, so that the allocating cost of a deep peak shaving auxiliary service market is obtained. By adopting the method, the compensation can be carried out according to the peak regulation effect of each market main body, so that the peak regulation effect and the income degree of each market main body can be simultaneously reflected, the accuracy of the deep peak regulation compensation cost required by each market main body can be improved, and the resource allocation is maximized.
Drawings
FIG. 1 is a diagram of an embodiment of an application environment of a deep peaking compensation cost apportionment method considering power peaking quality;
FIG. 2 is a schematic flow chart illustrating a method for deep peak shaving compensation cost sharing in consideration of peak shaving quality of a power supply according to an embodiment;
FIG. 3 is a block diagram of an embodiment of a deep peaking compensation cost apportionment apparatus that takes into account the peaking quality of the power supply;
FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
First, it should be noted that the power peak shaving auxiliary service provided by the present application refers to a marketable peak shaving service provided by a grid-connected power plant or an electrical energy storage facility, and mainly includes a basic peak shaving service and a compensated peak shaving service, where the basic peak shaving service belongs to a basic obligation borne by a unit, and is called by a power dispatching center irregularly according to the system operation need, and the compensated peak shaving service includes a deep peak shaving transaction, an emergency start-stop peak shaving transaction, and an electrical energy storage peak shaving transaction.
Specifically, the deep peak shaving transaction refers to the auxiliary service transaction provided when the output of the grid-connected unit is reduced according to the operation requirement of a power grid to enable the output of the unit to be smaller than the compensated peak shaving reference, in the initial stage of a market, a deep peak shaving transaction seller is a coal-fired thermal power unit, a buyer is a thermal power plant, a hydropower station, a wind power plant, a photovoltaic power station and a trans-provincial area tie line, and other market main bodies are gradually increased along with the maturity of the market, so that different peak shaving effects are actually achieved for different market main bodies, compensation sharing cost of each market main body is calculated based on the peak shaving effects, and the sharing accuracy of the power system on the deep peak shaving compensation cost can be greatly improved.
The deep peak regulation compensation cost allocation method considering the peak regulation quality of the power supply can be applied to the application environment shown in fig. 1. In an electric power system, a terminal 102 and a server 104 are included, a communication connection is established between the terminal 102 and the server 104 through a network, and the server 104 can obtain basic data sent by the terminal 102, and further perform modeling solution by using the basic data to obtain the deep peak shaving auxiliary service market share cost which needs to be paid by each market main body and has higher accuracy. Meanwhile, the terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, a method for allocating deep peak shaving compensation cost considering power supply peak shaving quality is provided, which is illustrated by applying the method to the server 104 in fig. 1, and includes the following steps:
step S210, basic data is acquired.
In a specific implementation, the basic data includes at least one of power system operation data, unit actual power generation data, and deep peak shaving market trading data.
For example, the system load curve, the unit output curve, the unit network power, the unit deep peak-shaving output price, the unit deep peak-shaving power, and the like.
And step S220, calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data.
In a specific implementation, before the server 104 calculates the full-network deep peak shaving compensation cost according to the basic data, it first needs to calculate the unit deep peak shaving compensation cost in a unit statistical period, and then calculates the fleet deep peak shaving compensation cost in which multiple units participate in deep peak shaving, i.e., the enterprise deep peak shaving compensation cost, and finally calculates the full-network deep peak shaving compensation cost in which multiple enterprises participate in deep peak shaving.
Further, a peak shaving quality coefficient of the unit in a unit statistical period is calculated according to basic data, a virtual synthetic curve is compared with a system load curve, wherein the virtual synthetic curve can be a (N-1) virtual synthetic curve, specifically, an electric power curve formed by subtracting a certain unit output curve from the system load curve is eliminated, different (N-1) virtual synthetic curves are obtained by eliminating the influence of different unit outputs, the difference between each virtual synthetic curve and the system load curve is evaluated, so that the evaluation index of the contribution degree of the different unit outputs to the system operation is obtained, and a basic index is constructed for establishing a deep peak shaving compensation cost allocation model.
Step S230, establishing and solving a deep peak regulation compensation cost allocation model to obtain deep peak regulation auxiliary service market allocation cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
In the concrete implementation, after the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient are obtained through calculation, a depth peak regulation compensation cost allocation model can be established, and the depth peak regulation compensation cost allocation model is used for calculating the allocation cost of the depth peak regulation auxiliary service market with stronger pertinence and higher allocation accuracy under the condition that the market main body is increased or reduced subsequently.
More specifically, when the deep peak shaving compensation cost allocation model is established, the on-line electricity quantity of each market subject can be corrected according to the peak shaving quality coefficient of the unit, and the corrected on-line electricity quantity is obtained and used for establishing the deep peak shaving compensation cost allocation model. The full-network deep peak shaving compensation cost related in the application needs to be shared by all market main bodies (machine sets) according to the ratio of the on-line electricity quantity corrected in the deep peak shaving trading period.
According to the method for allocating the deep peak shaving compensation cost considering the peak shaving quality of the power supply, the basic data are obtained, the full-network deep peak shaving compensation cost and the unit peak shaving quality coefficient are calculated according to the basic data, and a deep peak shaving compensation cost allocation model is established and solved by utilizing the full-network deep peak shaving compensation cost and the unit peak shaving quality coefficient, so that the deep peak shaving auxiliary service market allocation cost is obtained. By adopting the method, the compensation can be carried out according to the peak regulation effect of each market main body, so that the peak regulation effect and the income degree of each market main body can be simultaneously reflected, the accuracy of the deep peak regulation compensation cost required by each market main body can be improved, and the resource allocation is maximized.
In one embodiment, the base data includes power system operating data, unit actual power generation data, and deep peak shaver market trading data; wherein the power system operating data comprises a system load curve; the actual generating data of the unit comprises a unit output curve and unit online electric quantity; the deep peak shaving market transaction data comprise a unit deep peak shaving clear price and a unit deep peak shaving electric quantity.
The unit deep peak regulation electric quantity is the non-generated electric quantity formed when the regulation output of the coal-fired thermal power generating unit is below a compensated peak regulation reference value.
And the unit deep peak shaving clear price is quoted in the deep peak shaving grading interval where the unit is located.
In one embodiment, the basic data comprises unit deep peak shaving electric quantity and unit deep peak shaving clear price; the step of calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data comprises the following steps:
calculating the product of the unit deep peak shaving electric quantity and the unit deep peak shaving output price to obtain the unit deep peak shaving compensation cost; determining the number of preset depth peak shaving units, and performing multi-term summation on the depth peak shaving compensation cost of the units according to the number of the depth peak shaving units to obtain the depth peak shaving compensation cost of an enterprise; and determining the number of preset deep peak shaving enterprises, and performing multi-term summation on the deep peak shaving compensation cost of the enterprises according to the number of the deep peak shaving enterprises to obtain the full-network deep peak shaving compensation cost.
In a specific sight, the unit can be a coal-fired thermal power unit, the deep peak regulation compensation cost of the unit can be the deep peak regulation compensation cost of the coal-fired thermal power unit, the deep peak regulation compensation cost of an enterprise can be the deep peak regulation compensation cost of a coal-fired thermal power enterprise, and the deep peak regulation compensation cost of the coal-fired thermal power unit can be the product of the deep peak regulation electric quantity of the coal-fired power unit and the deep peak regulation clearing price of the coal-fired power unit; the deep peak regulation compensation cost of the coal-fired thermal power enterprises can be a plurality of sum values of the deep peak regulation compensation cost of the coal-fired thermal power units under the total number of the deep peak regulation units; the total network deep peak shaving compensation cost can be a plurality of items of sum values of the deep peak shaving compensation cost of the coal-fired thermal power enterprises under the total number of the deep peak shaving enterprises.
For example, the deep peak shaving compensation cost of the coal-fired thermal power generating unit can be calculated by the following formula:
Fi＝Qi·Pi
wherein, FiRepresenting the deep peak regulation compensation cost of the coal-fired generator set i in a unit statistical period; qiIndicating the deep peak regulation electric quantity of the coal-fired generator set i in a unit statistical period; piAnd expressing the deep peak regulation clearing price of the coal-fired generator set i in a unit statistical period.
For another example, the deep peak shaving compensation cost of the coal-fired thermal power enterprise can be calculated by the following formula:
wherein, FjRepresenting the j deep peak regulation compensation cost of the coal-fired power generation enterprise in a unit statistical period; fiUnit of expressionIn a statistical period, the deep peak regulation compensation cost of the coal-fired generator set i is calculated; and n represents the number of the units participating in deep peak shaving in the coal-fired thermal power enterprise j.
As another example, the full-network depth peak shaving compensation cost may be calculated by the following formula:
wherein, FWhole netRepresenting the full-network depth peak regulation compensation cost in a unit statistical period; fjRepresenting the j deep peak regulation compensation cost of the coal-fired power generation enterprise in a unit statistical period; and m represents the number of enterprises participating in deep peak shaving in the whole network.
In one embodiment, the base data includes a system load curve and a unit output curve; the step of calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data comprises the following steps:
acquiring a virtual synthetic curve according to the system load curve and the unit output curve; calculating a peak-to-valley ratio of the virtual synthetic curve according to the virtual synthetic curve and the system load curve; the peak-to-valley ratio of the virtual synthetic curve is the ratio of the average values of the power of the virtual synthetic curve in the peak time period and the valley time period of the system load curve respectively; calculating the ratio of the peak-to-valley ratio of the system load curve to the peak-to-valley ratio of the virtual synthetic curve to obtain the peak-to-valley ratio quality coefficient of the unit; the peak-to-valley ratio of the system load curve is the ratio of the load average values of the system load curve in the peak time period and the valley time period respectively.
In the specific implementation, the virtual synthetic curve may be an (N-1) virtual synthetic curve, that is, power curves with the number of (N-1) formed by subtracting a certain unit output curve from a system load curve including N unit output curves, different (N-1) virtual synthetic curves are obtained by eliminating the output influence of different units, and the difference between each virtual synthetic curve and the system load curve is evaluated to obtain evaluation indexes of the contribution degree of the output of different units to the system operation.
More specifically, the virtual composite curve peak-to-valley ratio is the ratio of the average power of the composite curve during the peak time period (N-1) of the system load curve to the average power of the composite curve during the valley time period (N-1) of the system load curve; the peak-valley ratio of the system load curve is the ratio of the average load value at the peak time period and the average load value at the valley time period of the system load curve; and calculating the ratio of the peak-to-valley ratio of the system load curve to the peak-to-valley ratio of the virtual synthetic curve to obtain the peak-to-valley ratio of the unit.
For example, the peak shaving quality factor of the unit can be calculated by the following formula:
in one embodiment, the step of establishing and solving a depth peak shaving compensation cost allocation model to obtain a depth peak shaving auxiliary service market allocation cost includes:
acquiring the unit internet surfing electric quantity in the basic data; acquiring unit online correction electric quantity according to the unit online electric quantity and the unit peak regulation quality coefficient; calculating the ratio of the unit internet surfing correction electric quantity to the cluster internet surfing correction electric quantity; the machine group online correction electric quantity is the number N items and the value of the machine group online correction electric quantity; establishing a depth peak regulation compensation cost allocation model by calculating the product of the ratio and the depth peak regulation compensation cost of the whole network; and solving the deep peak shaving compensation cost apportionment model to obtain the deep peak shaving auxiliary service market apportionment cost.
In the specific implementation, the depth peak regulation compensation cost allocation model can be represented by a formula for calculating the allocation cost of the depth peak regulation auxiliary service market as follows:
wherein R isjIndicating the cost of the deep peak regulation auxiliary service market of the market main body j in a unit statistical period; wjIndicating the corrected on-line electricity quantity of the market main body j (unit) in the unit statistical period, namely the unit on-line correctionAn amount; the machine group online correction electric quantity is represented as n items of sum of the machine group online correction electric quantity under the total number j of the market main body; fWhole netRepresenting the full-network depth peak regulation compensation cost in a unit statistical period; n represents the total number of market entities j participating in the deep peak shaver.
In an embodiment, the step of obtaining the unit on-line correction electric quantity according to the unit on-line electric quantity and the unit peak shaving quality coefficient includes:
acquiring an online electricity quantity correction coefficient corresponding to the peak shaving quality coefficient of the unit according to a preset coefficient mapping table; and calculating the product of the online electric quantity correction coefficient and the unit online electric quantity to obtain the unit online correction electric quantity.
Wherein, the preset coefficient mapping table can be the peak shaving quality coefficient K of the unitjAnd the correction coefficient P of the network electricity quantityjThe mapping table between, expressed as follows:
| peak shaving quality coefficient K of machine setj | Correction coefficient P of network electricity quantityj |
| Less than 0.5 | 1.5 |
| [0.5，1) | 1.2 |
| 1 | 1 |
| (1，1.5] | 0.8 |
| Greater than 1.5 | 0.5 |
In the specific implementation, the unit internet-surfing correction electric quantity can be calculated by the following formula:
Wj＝Wi×Pj
wherein, WjExpressing the corrected internet surfing electric quantity of the market main body j (unit) in a unit statistical period, namely the corrected internet surfing electric quantity of the unit; wiRepresenting the unit online electric quantity in a unit statistical period; pjAnd expressing the correction coefficient of the internet surfing electric quantity.
It should be noted that, if the real-time power generation information collection of the market main body is incomplete, the output is calculated according to the online electric quantity of the unit at a load rate of 85%.
In one embodiment, the full-network depth peak-shaving compensation cost is the full-network depth peak-shaving compensation cost within a preset unit statistic period; the unit peak regulation quality coefficient is a unit peak regulation quality coefficient in a preset unit statistical period; the allocation cost of the deep peak shaving auxiliary service market is the allocation cost of the deep peak shaving auxiliary service market in a preset unit statistic period.
In the embodiment, compensation can be performed according to the peak regulation effect of each market main body, so that the peak regulation effect and the income degree of each market main body can be simultaneously reflected, the accuracy of the deep peak regulation compensation cost required by each market main body can be improved, and the resource allocation is maximized.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in a strict order unless explicitly stated herein, and may be performed in other, sequential orders. Moreover, at least a portion of the steps in fig. 2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 3, there is provided a depth peaking compensation cost apportionment apparatus 300 considering power supply peaking quality, comprising a data acquisition module 310, a data calculation module 320 and a model solving module 330, wherein:
a data obtaining module 310, configured to obtain basic data;
the data calculation module 320 is used for calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
the model solving module 330 is configured to establish and solve a deep peak shaving compensation cost apportionment model to obtain deep peak shaving auxiliary service market apportionment cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
According to the scheme provided by the embodiment of the invention, the compensation can be carried out according to the peak regulation effect of each market main body, so that the peak regulation effect and the income degree of each market main body can be simultaneously reflected, the accuracy of the depth peak regulation compensation cost required by each market main body can be improved, and the resource allocation is maximized.
In one embodiment, the data obtaining module 310 is further configured to obtain power system operation data, unit actual power generation data, and deep peak shaving market trading data; wherein the power system operation data comprises a system load curve; the actual power generation data of the unit comprises a unit output curve and unit online electric quantity; the deep peak regulation market transaction data comprises a unit deep peak regulation clearing price and a unit deep peak regulation electric quantity.
In one embodiment, the basic data comprises unit deep peak shaving electric quantity and unit deep peak shaving clear price; the data calculation module 320 is further configured to calculate a product between the unit deep peak shaving electric quantity and the unit deep peak shaving clearing price, so as to obtain a unit deep peak shaving compensation cost; determining the number of preset depth peak shaving units, and performing multi-term summation on the depth peak shaving compensation cost of the units according to the number of the depth peak shaving units to obtain the depth peak shaving compensation cost of an enterprise; and determining the number of preset deep peak shaving enterprises, and performing multi-term summation on the deep peak shaving compensation cost of the enterprises according to the number of the deep peak shaving enterprises to obtain the full-network deep peak shaving compensation cost.
In one embodiment, the base data includes a system load curve and a unit output curve; the data calculation module 320 is further configured to obtain a virtual synthetic curve according to the system load curve and the unit output curve; calculating a peak-to-valley ratio of the virtual synthetic curve according to the virtual synthetic curve and the system load curve; the peak-to-valley ratio of the virtual synthetic curve is the ratio of the average values of the power of the virtual synthetic curve in the peak time period and the valley time period of the system load curve respectively; calculating the ratio of the peak-to-valley ratio of the system load curve to the peak-to-valley ratio of the virtual synthetic curve to obtain the peak-to-valley ratio quality coefficient of the unit; the peak-to-valley ratio of the system load curve is the ratio of the load average values of the system load curve in the peak time period and the valley time period respectively.
In one embodiment, the model solving module 330 is further configured to obtain the on-line power of the unit from the basic data; acquiring unit online correction electric quantity according to the unit online electric quantity and the unit peak regulation quality coefficient; calculating the ratio of the unit internet surfing correction electric quantity to the cluster internet surfing correction electric quantity; the machine group online correction electric quantity is the number N items and the value of the machine group online correction electric quantity; establishing a depth peak regulation compensation cost allocation model by calculating the product of the ratio and the depth peak regulation compensation cost of the whole network; and solving the deep peak shaving compensation cost apportionment model to obtain the deep peak shaving auxiliary service market apportionment cost.
In an embodiment, the model solving module 330 is further configured to obtain an internet power correction coefficient corresponding to the peak shaving quality coefficient of the unit according to a preset coefficient mapping table; and calculating the product of the online electric quantity correction coefficient and the unit online electric quantity to obtain the unit online correction electric quantity.
In one embodiment, the full-network depth peak-shaving compensation cost is the full-network depth peak-shaving compensation cost within a preset unit statistic period; the unit peak regulation quality coefficient is a unit peak regulation quality coefficient in a preset unit statistical period; the allocation cost of the deep peak shaving auxiliary service market is the allocation cost of the deep peak shaving auxiliary service market in a preset unit statistic period.
According to the scheme provided by the embodiment of the invention, the compensation can be carried out according to the peak regulation effect of each market main body, so that the peak regulation effect and the income degree of each market main body can be simultaneously reflected, the accuracy of the depth peak regulation compensation cost required by each market main body can be improved, and the resource allocation is maximized.
For specific limitations of the depth peak-shaving compensation cost apportionment device considering the power peak-shaving quality, reference may be made to the above limitations of the depth peak-shaving compensation cost apportionment method considering the power peak-shaving quality, and details thereof are not repeated herein. The above-mentioned modules in the deep peak shaving compensation expense allocation device considering the peak shaving quality of the power supply can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing identification information and device information. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method for deep peaking compensation cost amortization that takes into account power supply peaking quality.
Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring basic data;
calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
establishing and solving a deep peak regulation compensation cost allocation model to obtain deep peak regulation auxiliary service market allocation cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating the product of the unit deep peak shaving electric quantity and the unit deep peak shaving output price to obtain the unit deep peak shaving compensation cost; determining the number of preset depth peak shaving units, and performing multi-term summation on the depth peak shaving compensation cost of the units according to the number of the depth peak shaving units to obtain the depth peak shaving compensation cost of an enterprise; and determining the number of preset deep peak shaving enterprises, and performing multi-term summation on the deep peak shaving compensation cost of the enterprises according to the number of the deep peak shaving enterprises to obtain the full-network deep peak shaving compensation cost.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring a virtual synthetic curve according to the system load curve and the unit output curve; calculating a peak-to-valley ratio of the virtual synthetic curve according to the virtual synthetic curve and the system load curve; the peak-to-valley ratio of the virtual synthetic curve is the ratio of the average values of the power of the virtual synthetic curve in the peak time period and the valley time period of the system load curve respectively; calculating the ratio of the peak-to-valley ratio of the system load curve to the peak-to-valley ratio of the virtual synthetic curve to obtain the peak-to-valley ratio quality coefficient of the unit; the peak-to-valley ratio of the system load curve is the ratio of the load average values of the system load curve in the peak time period and the valley time period respectively.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring the unit internet surfing electric quantity in the basic data; acquiring unit online correction electric quantity according to the unit online electric quantity and the unit peak regulation quality coefficient; calculating the ratio of the unit internet surfing correction electric quantity to the cluster internet surfing correction electric quantity; the machine group online correction electric quantity is the number N items and the value of the machine group online correction electric quantity; establishing a depth peak regulation compensation cost allocation model by calculating the product of the ratio and the depth peak regulation compensation cost of the whole network; and solving the deep peak shaving compensation cost apportionment model to obtain the deep peak shaving auxiliary service market apportionment cost.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring an online electricity quantity correction coefficient corresponding to the peak shaving quality coefficient of the unit according to a preset coefficient mapping table; and calculating the product of the online electric quantity correction coefficient and the unit online electric quantity to obtain the unit online correction electric quantity.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring basic data;
calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
establishing and solving a deep peak regulation compensation cost allocation model to obtain deep peak regulation auxiliary service market allocation cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating the product of the unit deep peak shaving electric quantity and the unit deep peak shaving output price to obtain the unit deep peak shaving compensation cost; determining the number of preset depth peak shaving units, and performing multi-term summation on the depth peak shaving compensation cost of the units according to the number of the depth peak shaving units to obtain the depth peak shaving compensation cost of an enterprise; and determining the number of preset deep peak shaving enterprises, and performing multi-term summation on the deep peak shaving compensation cost of the enterprises according to the number of the deep peak shaving enterprises to obtain the full-network deep peak shaving compensation cost.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a virtual synthetic curve according to the system load curve and the unit output curve; calculating a peak-to-valley ratio of the virtual synthetic curve according to the virtual synthetic curve and the system load curve; the peak-to-valley ratio of the virtual synthetic curve is the ratio of the average values of the power of the virtual synthetic curve in the peak time period and the valley time period of the system load curve respectively; calculating the ratio of the peak-to-valley ratio of the system load curve to the peak-to-valley ratio of the virtual synthetic curve to obtain the peak-to-valley ratio quality coefficient of the unit; the peak-to-valley ratio of the system load curve is the ratio of the load average values of the system load curve in the peak time period and the valley time period respectively.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring the unit internet surfing electric quantity in the basic data; acquiring unit online correction electric quantity according to the unit online electric quantity and the unit peak regulation quality coefficient; calculating the ratio of the unit internet surfing correction electric quantity to the cluster internet surfing correction electric quantity; the machine group online correction electric quantity is the number N items and the value of the machine group online correction electric quantity; establishing a depth peak regulation compensation cost allocation model by calculating the product of the ratio and the depth peak regulation compensation cost of the whole network; and solving the deep peak shaving compensation cost apportionment model to obtain the deep peak shaving auxiliary service market apportionment cost.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring an online electricity quantity correction coefficient corresponding to the peak shaving quality coefficient of the unit according to a preset coefficient mapping table; and calculating the product of the online electric quantity correction coefficient and the unit online electric quantity to obtain the unit online correction electric quantity.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A deep peak regulation compensation cost allocation method considering the peak regulation quality of a power supply is characterized by comprising the following steps:
acquiring basic data;
calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
establishing and solving a deep peak regulation compensation cost allocation model to obtain deep peak regulation auxiliary service market allocation cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
2. The method of claim 1, wherein the base data includes power system operating data, unit actual power generation data, and deep peaking market trading data; wherein the content of the first and second substances,
the power system operating data comprises a system load curve;
the actual generating data of the unit comprises a unit output curve and unit online electric quantity;
the deep peak shaving market transaction data comprise a unit deep peak shaving clear price and a unit deep peak shaving electric quantity.
3. The method of claim 1, wherein the base data includes a unit deep peak shaver power and a unit deep peak shaver clearing price; the step of calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data comprises the following steps:
calculating the product of the unit deep peak shaving electric quantity and the unit deep peak shaving output price to obtain the unit deep peak shaving compensation cost;
determining the number of preset depth peak shaving units, and performing multi-term summation on the depth peak shaving compensation cost of the units according to the number of the depth peak shaving units to obtain the depth peak shaving compensation cost of an enterprise;
and determining the number of preset deep peak shaving enterprises, and performing multi-term summation on the deep peak shaving compensation cost of the enterprises according to the number of the deep peak shaving enterprises to obtain the full-network deep peak shaving compensation cost.
4. The method of claim 1, wherein the base data includes a system load curve and a unit output curve; the step of calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data comprises the following steps:
acquiring a virtual synthetic curve according to the system load curve and the unit output curve;
calculating a peak-to-valley ratio of the virtual synthetic curve according to the virtual synthetic curve and the system load curve; the peak-to-valley ratio of the virtual synthetic curve is the ratio of the average values of the power of the virtual synthetic curve in the peak time period and the valley time period of the system load curve respectively;
calculating the ratio of the peak-to-valley ratio of the system load curve to the peak-to-valley ratio of the virtual synthetic curve to obtain the peak-to-valley ratio quality coefficient of the unit; the peak-to-valley ratio of the system load curve is the ratio of the load average values of the system load curve in the peak time period and the valley time period respectively.
5. The method of claim 1, wherein the step of establishing and solving a depth peaking compensation cost share model to obtain a depth peaking assisted service market share cost comprises:
acquiring the unit internet surfing electric quantity in the basic data;
acquiring unit online correction electric quantity according to the unit online electric quantity and the unit peak regulation quality coefficient;
calculating the ratio of the unit internet surfing correction electric quantity to the cluster internet surfing correction electric quantity; the machine group online correction electric quantity is the number N items and the value of the machine group online correction electric quantity;
establishing a depth peak regulation compensation cost allocation model by calculating the product of the ratio and the depth peak regulation compensation cost of the whole network;
and solving the deep peak shaving compensation cost apportionment model to obtain the deep peak shaving auxiliary service market apportionment cost.
6. The method according to claim 5, wherein the step of obtaining the unit on-line correction power according to the unit on-line power and the unit peak shaving quality coefficient comprises:
acquiring an online electricity quantity correction coefficient corresponding to the peak shaving quality coefficient of the unit according to a preset coefficient mapping table;
and calculating the product of the online electric quantity correction coefficient and the unit online electric quantity to obtain the unit online correction electric quantity.
7. The method according to claim 1, wherein the full-network depth peak-shaving compensation cost is a full-network depth peak-shaving compensation cost within a preset unit statistical period; the unit peak regulation quality coefficient is a unit peak regulation quality coefficient in a preset unit statistical period; the allocation cost of the deep peak shaving auxiliary service market is the allocation cost of the deep peak shaving auxiliary service market in a preset unit statistic period.
8. A depth peaking compensation cost apportionment apparatus considering power supply peaking quality, the apparatus comprising:
the data acquisition module is used for acquiring basic data;
the data calculation module is used for calculating the full-network depth peak regulation compensation cost and the unit peak regulation quality coefficient according to the basic data;
the model solving module is used for establishing and solving a deep peak regulation compensation cost apportionment model to obtain deep peak regulation auxiliary service market apportionment cost; and the deep peak regulation compensation cost allocation model is determined according to the basic data, the whole network deep peak regulation compensation cost and the unit peak regulation quality coefficient.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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