CN114897265A - Multi-factor-considered energy storage location and volume optimization method, system, terminal and medium - Google Patents
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Abstract
The invention discloses a multi-factor considered energy storage site selection constant volume optimization method, a system, a terminal and a medium, which relate to the technical field of power systems, and the technical scheme key points are as follows: obtaining the load rate of each node of the power system according to the maximum load and rated capacity of annual operation in the power system, and analyzing the influence of the load rate of each node of the power system on the power supply guarantee of a power supply area to obtain the risk electric quantity; analyzing an output value corresponding to the risk electric quantity according to economic output value data of each region to obtain a risk output value; and inputting the risk output value and the total energy storage configuration amount of each region into a pre-constructed energy storage location constant volume model for optimization analysis to obtain the energy storage power and the energy storage capacity of each node of the power system. The invention simultaneously considers two factors of regional economic development and peak clipping and valley filling improvement of the power system, not only improves and supports the power system, but also comprehensively considers the electricity utilization support of energy storage to local residents and industrial and commercial users.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a method, a system, a terminal and a medium for optimizing energy storage, site selection and volume fixing considering multiple factors.
Background
With the rapid development of new energy at home and abroad, the random uncertainty of new energy output brings serious influence to the safe and stable operation of an electric power system, the main influence comprises the problems of non-correspondence between peak and valley time of new energy output and peak and valley time of a power utilization side, unbalanced power and the like, the problems of difficult prediction, low precision, low predictable resolution and the like of new energy output caused by the random uncertainty of new energy output are solved, and finally, the output planning of the traditional thermal power generating unit is remarkably reduced in order to promote the consumption of new energy, so that the stable power supply resources of the system are remarkably reduced, and the problems of power limitation, power shortage, power utilization difficulty and the like are caused.
The existing energy storage planning is mainly from the perspective of an electric power system, and the regional economic development requirement is rarely considered; the energy storage planning technology developed from the government view mainly considers factors such as land cost, local economic development, industrial chain construction and comprehensive demonstration application, and the like, and is lack of analysis on the power system. However, in the planning layout of the energy storage, not only the improvement and the support of the power system need to be considered, but also the support of the energy storage on the electricity utilization of local residents and industrial and commercial users needs to be considered comprehensively, so that the reliability of the electricity utilization of the users is guaranteed, and the social benefit is maximized.
Therefore, how to research and design an energy storage site selection constant volume optimization method, system, terminal and medium which can overcome the defects is a problem which is urgently needed to be solved at present.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide an energy storage site selection constant volume optimization method, system, terminal and medium considering multiple factors, and simultaneously considers two factors of regional economic development and power system peak clipping and valley filling improvement, thereby not only improving and supporting the power system, but also comprehensively considering the power utilization support of energy storage to local residents and industrial and commercial users, giving consideration to the side points of different planning parties, facilitating the landing and execution of a planning scheme, and ensuring the power utilization reliability of users and the maximization of social benefits.
The technical purpose of the invention is realized by the following technical scheme:
in a first aspect, a method for optimizing the location and volume of stored energy in consideration of multiple factors is provided, which comprises the following steps:
obtaining the load rate of each node of the power system according to the maximum load and rated capacity of annual operation in the power system, and analyzing the influence of the load rate of each node of the power system on the power supply guarantee of a power supply area to obtain the risk electric quantity;
analyzing an output value corresponding to the risk electric quantity according to economic output value data of each region to obtain a risk output value;
and inputting the risk output value and the total energy storage configuration amount of each region into a pre-constructed energy storage location constant volume model for optimization analysis to obtain the energy storage power and the energy storage capacity of each node of the power system.
Further, the process of obtaining the risk value specifically comprises:
determining the kilowatt-hour power generation value of the area where the overload transformer substation is located according to the economic power generation value data;
and determining the risk output value of the corresponding overload substation according to the product of the risk electric quantity and the kilowatt-hour power output value.
Further, the kilowatt-hour power generation value is the ratio of the economic power generation value data to the power consumption of the whole society in the corresponding area.
Further, the risk electric quantity is the power supply electric quantity corresponding to the exceeding safety load rate of each region node.
Further, the safety load rate is determined according to the product of the percentage of rated capacity of each substation and the configuration coefficient of the corresponding substation.
Further, the calculation formula of the energy storage power is specifically as follows:
wherein,
representing the energy storage power which should be configured after the optimized analysis of the transformer substation j; f. of j Representing a risk value of substation j; f. of i Representing a risk value of substation i; n represents the number of substations; p 0 Indicating the total power of the energy storage allowable configuration in each region.
Further, the calculation formula of the energy storage capacity is specifically as follows:
wherein,
representing the energy storage capacity which should be configured after the optimized analysis of the transformer substation j; t is t 0 Representing a maximum charge time allowed by the configured stored energy;
representing the energy storage power which should be configured after the optimized analysis of the transformer substation j; e es,j,T Represents the energy storage capacity requirement, max (E), of substation j on day T es,j,T ) Representing the maximum energy storage capacity demand of substation j throughout the year.
In a second aspect, a system for energy storage localization and sizing optimization considering multiple factors is provided, which includes:
the electric quantity analysis module is used for obtaining the load rate of each node of the power system according to the maximum load and rated capacity of annual operation in the power system, analyzing the influence of the load rate of each node of the power system on the power supply guarantee of a power supply area and obtaining the risk electric quantity;
the output value analysis module is used for analyzing the output value corresponding to the risk electric quantity according to the economic output value data of each region to obtain a risk output value;
and the constant volume analysis module is used for inputting the risk output value and the total energy storage configuration amount of each region into a pre-constructed energy storage site selection constant volume model for optimization analysis to obtain the energy storage power and the energy storage capacity of each node of the power system.
In a third aspect, a computer terminal is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the method for optimizing an energy storage site location capacity considering multiple factors according to any one of the first aspect is implemented.
In a fourth aspect, a computer-readable medium is provided, on which a computer program is stored, the computer program being executed by a processor to implement the method for optimizing an energy storage siting volume considering multiple factors according to any one of the first aspect.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the energy storage site selection constant volume optimization method considering the multiple factors, two factors of regional economic development and power system peak clipping and valley filling improvement are considered at the same time, the effect of improving and supporting a power system is achieved, the power utilization support of energy storage to local residents and industrial and commercial users can be considered comprehensively, the side points of different planning parties are considered, the landing and the execution of a planning scheme are facilitated, and the power utilization reliability and the social benefit maximization of the users are guaranteed;
2. according to the method, the safe load rate is determined according to the product of the percentage of the rated capacity of each transformer substation and the configuration coefficient of the corresponding transformer substation, and the arrangement condition of the transformer substation in the whole power system is considered, so that the determination of the risk electric quantity is more accurate and reliable.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart in an embodiment of the invention;
FIG. 2 is a flow chart in an embodiment of the invention;
fig. 3 is a block diagram of a system in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example 1: the method for optimizing the energy storage site selection capacity by considering the multiple factors, as shown in fig. 1, comprises the following steps:
the method comprises the steps that firstly, the load rate of each node of the power system is obtained according to the maximum load and rated capacity of annual operation in the power system, the influence of the load rate of each node of the power system on the power supply guarantee of a power supply area is analyzed, and the risk electric quantity is obtained;
analyzing an output value corresponding to the risk electric quantity according to economic output value data of each region to obtain a risk output value;
and thirdly, inputting the risk output value and the total energy storage configuration amount of each region into a pre-constructed energy storage location constant volume model for optimization analysis to obtain the energy storage power and the energy storage capacity of each node of the power system.
The process for obtaining the risk output value specifically comprises the following steps: determining the kilowatt-hour power generation value of the area where the overload transformer substation is located according to the economic power generation value data; and determining the risk output value of the corresponding overload substation according to the product of the risk electric quantity and the kilowatt-hour power output value.
Specifically, the calculation formula of the risk yield value is as follows:
f i ＝C GDP,u E risk,i
wherein f is i Representing a risk value of substation i; c GDP,u Representing the kilowatt-hour power generation value of the area u where the overload substation i is located; e risk,i Representing the risk electric quantity of the transformer substation i; m u Economic production value data representing region u, such as the total value of GDP; e u Indicating the total social power usage for area u.
As shown in fig. 2, in order to alleviate the situation of high load rate of an overloaded substation in each area, each substation in each area is taken as an object, a certain percentage of the rated capacity of each substation is selected as a safe operation threshold, for example, 80% of the rated capacity is taken as a safe operation threshold of the substation, then the safe operation threshold of the substation with the rated capacity of 100MW is 80MW, the substation with the maximum load rate exceeding the safe operation threshold is selected to perform energy storage capacity configuration, the maximum load rate of the node 3 exceeds 80%, then energy storage needs to be installed to reduce the risk electric quantity, and the risk electric quantity is the power supply electric quantity corresponding to the node exceeding the safe load rate in each area.
In this embodiment, the calculation formula of the energy storage power is specifically as follows:
wherein,
representing the energy storage power which should be configured after the optimized analysis of the transformer substation j; f. of j Representing a risk value of substation j; n represents the number of substations; p 0 Indicating the total power of the energy storage allowable configuration in each region.
In addition, the calculation formula of the energy storage capacity is specifically as follows:
wherein,
representing the energy storage capacity which should be configured after the optimized analysis of the transformer substation j; t is t 0 Representing a maximum charge time allowed by the configured stored energy; e es,j,T Represents the energy storage capacity requirement, max (E), of substation j on day T es,j,T ) Representing the maximum energy storage capacity requirement for substation j throughout the year.
In addition, the energy storage power and the energy storage capacity need to satisfy the following conditions:
wherein, P es,i,T Representing the energy storage power demand of the transformer substation i on the Tth day; s i Representing the rated capacity of substation i; rho i,t Representing the real-time collection load rate of the transformer substation i at the time t; rho 0 Representing the safe load rate of the transformer substation, and determining the safe load rate according to the product of the percentage of the rated capacity of each transformer substation and the configuration coefficient of the corresponding transformer substation, wherein the safe load rate is set to be 85% in the embodiment; e es,i,T Representing the energy storage capacity requirement of the transformer substation i on the Tth day; Δ t is the sampling interval, which in this embodiment may be set to 5 minutes; and K is the total sampling time.
Example 2: an energy storage localization and volume optimization system considering multiple factors is used for implementing the energy storage localization and volume optimization method described in embodiment 1, and includes an electric quantity analysis module, an output value analysis module and a volume analysis module, as shown in fig. 3.
The electric quantity analysis module is used for obtaining the load rate of each node of the power system according to the maximum load and rated capacity of annual operation in the power system, analyzing the influence of the load rate of each node of the power system on the power supply guarantee of a power supply area and obtaining the risk electric quantity;
the output value analysis module is used for analyzing the output value corresponding to the risk electric quantity according to the economic output value data of each region to obtain a risk output value;
and the constant volume analysis module is used for inputting the risk output value and the total energy storage configuration amount of each region into a pre-constructed energy storage site selection constant volume model for optimization analysis to obtain the energy storage power and the energy storage capacity of each node of the power system.
The working principle is as follows: the method simultaneously considers two factors of regional economic development and peak clipping and valley filling improvement of the power system, not only improves and supports the power system, but also can comprehensively consider the power utilization support of energy storage to local residents and industrial and commercial users, gives consideration to the side points of different planners, is favorable for landing and executing a planning scheme, and ensures the power utilization reliability of the users and the maximization of social benefits; in addition, the safe load rate is determined according to the product of the percentage of the rated capacity of each transformer substation and the configuration coefficient of the corresponding transformer substation, and the arrangement condition of the transformer substation in the whole power system is considered, so that the determination of the risk electric quantity is more accurate and reliable.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, it should be understood that the above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. The energy storage site selection constant volume optimization method considering the multiple factors is characterized by comprising the following steps of:
obtaining the load rate of each node of the power system according to the maximum load and rated capacity of annual operation in the power system, and analyzing the influence of the load rate of each node of the power system on the power supply guarantee of a power supply area to obtain the risk electric quantity;
analyzing an output value corresponding to the risk electric quantity according to economic output value data of each region to obtain a risk output value;
and inputting the risk output value and the total energy storage configuration amount of each region into a pre-constructed energy storage location constant volume model for optimization analysis to obtain the energy storage power and the energy storage capacity of each node of the power system.
2. The method for energy storage site selection and volume optimization considering multiple factors according to claim 1, wherein the risk output value is obtained by the following specific steps:
determining the kilowatt-hour power generation value of the area where the overload transformer substation is located according to the economic power generation value data;
and determining the risk output value of the corresponding overload substation according to the product of the risk electric quantity and the kilowatt-hour power output value.
3. The method for optimizing energy storage, site selection, volume determination and the like by considering multiple factors according to claim 2, wherein the kilowatt-hour power generation value is a ratio of economic power generation value data to the power consumption of the whole society in the corresponding area.
4. The method for optimizing the location and the volume of the energy storage system based on the multi-factor consideration of claim 1, wherein the risk electric quantity is a power supply electric quantity corresponding to the exceeding of the safe load rate of each regional node.
5. The method of claim 1, wherein the safe load rate is determined by a product of a percentage of rated capacity of each substation and a configuration coefficient of the corresponding substation.
6. The method for optimizing the location and volume of the energy storage system based on the multi-factor consideration of claim 1, wherein the calculation formula of the energy storage power is as follows:
wherein,
representing the energy storage power which should be configured after the optimized analysis of the transformer substation j; f. of j Representing a risk value of substation j; f. of i Representing a risk value of substation i; n represents the number of substations; p 0 Indicating the total power of the energy storage allowable configuration in each region.
7. The method for optimizing the location and volume of the energy storage system based on the multi-factor consideration of claim 1, wherein the formula for calculating the energy storage capacity is as follows:
wherein,
representing the energy storage capacity which should be configured after the optimized analysis of the transformer substation j; t is t 0 Representing a maximum charge time allowed by the configured stored energy;
representing the energy storage power which should be configured after the optimized analysis of the transformer substation j; e es,j,T Represents the energy storage capacity requirement, max (E), of substation j on day T es,j,T ) Representing the maximum energy storage capacity demand of substation j throughout the year.
8. The energy storage locating and sizing optimization system considering the multiple factors is characterized by comprising the following components:
the electric quantity analysis module is used for obtaining the load rate of each node of the power system according to the maximum load and rated capacity of annual operation in the power system, analyzing the influence of the load rate of each node of the power system on the power supply guarantee of a power supply area and obtaining the risk electric quantity;
the output value analysis module is used for analyzing the output value corresponding to the risk electric quantity according to the economic output value data of each region to obtain a risk output value;
and the constant volume analysis module is used for inputting the risk output value and the total energy storage configuration amount of each region into a pre-constructed energy storage site selection constant volume model for optimization analysis to obtain the energy storage power and the energy storage capacity of each node of the power system.
9. A computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method of multi-factor considered energy storage siting volume optimization as claimed in any one of claims 1 to 7 when executing the program.
10. A computer-readable medium, on which a computer program is stored, the computer program being executable by a processor to implement the method of multi-factor considered energy storage siting volume optimization according to any of claims 1 to 7.
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