CN114897265A - Multi-factor-considered energy storage location and volume optimization method, system, terminal and medium - Google Patents

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

Optimization method, system, terminal and medium of energy storage site selection and capacity considering multiple factors

technical field

The invention relates to the technical field of electric power systems, and more particularly, to an optimization method, system, terminal and medium for energy storage location selection and capacity determination considering multiple factors.

Background technique

With the vigorous development of new energy at home and abroad, the random uncertainty of the output of new energy has brought a serious impact on the safe and stable operation of the power system. Correspondence, power imbalance and other problems, followed by the difficulty of predicting new energy output caused by the random uncertainty of new energy output, low precision, low predictable resolution and other problems, and finally, in order to promote the consumption of new energy is significantly reduced. The output planning of traditional thermal power units has led to a significant reduction in the stable power supply resources of the system, resulting in problems such as power cuts, power shortages, and difficulty in power consumption.

The existing energy storage planning mainly starts from the perspective of the power system, and seldom considers the needs of regional economic development; while the energy storage planning technology developed from the perspective of the government focuses on the cost of land use, local economic development, industrial chain construction, and comprehensive demonstration applications. factors, lack of analysis of the power system. However, in the planning and layout of energy storage, it is not only necessary to consider the improvement and support of the power system, but also to consider the power consumption support of energy storage for local residents, industrial and commercial users, and to ensure the maximum social benefits of users' power reliability.

Therefore, how to research and design an optimization method, system, terminal and medium for energy storage location and capacity that can overcome the above defects is an urgent problem that we need to solve at present.

SUMMARY OF THE INVENTION

In order to solve the deficiencies in the prior art, the purpose of the present invention is to provide an optimization method, system, terminal and medium for energy storage site selection and capacity determination that consider multiple factors, and consider both regional economic development and power system peak shaving and valley filling improvement. Factors, not only have the effect of improving and supporting the power system, but also consider the power support of energy storage to local residents, industrial and commercial users, and take into account the priorities of different planners, which is conducive to the implementation and implementation of planning schemes and ensures users’ power consumption. Reliability and social benefits are maximized.

The above-mentioned technical purpose of the present invention is achieved through the following technical solutions:

In the first aspect, an optimization method for energy storage site selection and capacity determination considering multiple factors is provided, including the following steps:

According to the annual maximum load and rated capacity of the power system, the load rate of each node of the power system is obtained, and the influence of the load rate of each node of the power system on the security of power supply in the power supply area is analyzed to obtain the risk electricity;

According to the economic output value data of each region, the output value corresponding to the risk electricity is analyzed to obtain the risk output value;

The risk output value and the total energy storage configuration of each region are input into the pre-built energy storage location and capacity model for optimization analysis, and the energy storage power and energy storage capacity of each node of the power system are obtained.

Further, the process of obtaining the risk output value is as follows:

Determine the kWh output value of the area where the overloaded substation is located according to the economic output value data;

The risk output value of the corresponding overloaded substation is determined by the product of the risk quantity and the kWh output value.

Further, the kWh output value is the ratio of the economic output value data to the electricity consumption of the whole society in the corresponding area.

Further, the risk power is the power supply power corresponding to the nodes in each region exceeding the safe load rate.

Further, the safe load rate is determined according to the product of the percentage of the rated capacity of each substation and the configuration coefficient of the corresponding substation.

Further, the calculation formula of the energy storage power is specifically:

表示变电站j优化分析后应配置的储能功率；f_j表示变电站j的风险产值；f_i表示变电站i的风险产值；N表示变电站数量；P₀表示各区域内储能允许配置的总功率。in,

represents the energy storage power that should be configured after the optimization analysis of substation j; _{f j} represents the risk output value of substation j; f _i represents the risk output value of substation i; N represents the number of substations;

Further, the calculation formula of the energy storage capacity is specifically:

表示变电站j优化分析后应配置的储能容量；t₀表示配置的储能所允许的最大充电时间；

表示变电站j优化分析后应配置的储能功率；E_es,j,T表示变电站j第T天的储能容量需求，max(E_es,j,T)表示变电站j在全年中储能容量需求的最大值。in,

Represents the energy storage capacity that should be configured after the optimization analysis of substation j; t ₀ represents the maximum charging time allowed by the configured energy storage;

Represents the energy storage power that should be configured after the optimization analysis of substation j; E _es,j,T represents the energy storage capacity demand of substation j on the T day, and max(E _es,j,T ) represents the energy storage capacity of substation j in the whole year maximum demand.

In the second aspect, it provides an energy storage site selection and capacity optimization system that considers multiple factors, including:

The power analysis module is used to obtain the load rate of each node of the power system according to the annual maximum load and rated capacity of the power system, and analyze the influence of the load rate of each node of the power system on the security of power supply in the power supply area to obtain the risk power;

The output value analysis module is used to analyze the output value corresponding to the risk electricity according to the economic output value data of each region, and obtain the risk output value;

The fixed capacity analysis module is used to input the risk output value and the total energy storage configuration of each region into the pre-built energy storage location and fixed capacity model for optimization analysis, and obtain the energy storage power and energy storage capacity of each node of the power system.

In a third aspect, a computer terminal is provided, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, when the processor executes the program, any one of the first aspect can be implemented. The optimization method of energy storage site selection and capacity considering multiple factors mentioned above.

In a fourth aspect, there is provided a computer-readable medium on which a computer program is stored, the computer program being executed by a processor to implement the multi-factor energy storage location selection as described in any one of the first aspect capacity optimization method.

Compared with the prior art, the present invention has the following beneficial effects:

1. The multi-factor energy storage site selection and capacity-determining optimization method proposed by the present invention also takes into account two factors: regional economic development and the improvement of peak shaving and valley filling of the power system, which not only improves and supports the power system, but also makes overall planning Considering the power support of energy storage for local residents, industrial and commercial users, and taking into account the priorities of different planners, it is conducive to the implementation and implementation of the planning scheme, ensuring the reliability of power consumption of users and maximizing social benefits;

2. The present invention determines the safe load rate according to the product of the percentage of the rated capacity of each substation and the configuration coefficient of the corresponding substation, and considers the layout of the substation in the entire power system, making the determination of the risk power more accurate and reliable.

Description of drawings

The accompanying drawings described herein are used to provide further understanding of the embodiments of the present invention, and constitute a part of the present application, and do not constitute limitations to the embodiments of the present invention. In the attached image:

Fig. 1 is the flow chart in the embodiment of the present invention;

Fig. 2 is the flow chart in the embodiment of the present invention;

FIG. 3 is a system block diagram in an embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and the accompanying drawings. as a limitation of the present invention.

Embodiment 1: The optimization method for energy storage location selection and capacity determination considering multiple factors, as shown in Figure 1, includes the following steps:

Step 1: Obtain the load rate of each node of the power system according to the annual maximum load and rated capacity of the power system, and analyze the influence of the load rate of each node of the power system on the security of power supply in the power supply area to obtain the risk electricity;

Step 2, analyze the output value corresponding to the risk electricity according to the economic output value data of each region, and obtain the risk output value;

Step 3: Input the risk output value and the total energy storage configuration of each region into the pre-built energy storage location and capacity model for optimization analysis, and obtain the energy storage power and energy storage capacity of each node of the power system.

The specific process of obtaining the risk output value is as follows: determine the kWh output value of the area where the overloaded substation is located according to the economic output value data; determine the risk output value of the corresponding overload substation by the product of the risk electricity and the kWh output value.

Specifically, the calculation formula of risk output value is:

f _i =C _GDP,u E _risk,i

Among them, f _i represents the risk output value of substation i; C _GDP,u represents the kWh output value of the area u where the overloaded substation i is located; E _risk,i represents the risky electricity of the substation i; M _u represents the economic output value data of the area u, for example Gross GDP; E _u represents the electricity consumption of the whole society in region u.

As shown in Figure 2, in order to alleviate the high load rate of overloaded substations in each area, take each substation in each area as the object, select a certain percentage of the rated capacity of each substation as the safe operation threshold, for example, 80% of the rated capacity as the substation Safe operation threshold, then the safe operation threshold of a substation with a rated capacity of 100MW is 80MW. Select a substation whose maximum load rate exceeds the safe operation threshold for energy storage capacity configuration. If the maximum load rate of node 3 exceeds 80%, then it is necessary to install energy storage to reduce this. Part of the risk power, the risk power is the power supply corresponding to the nodes in each region exceeding the safe load rate.

In this embodiment, the calculation formula of energy storage power is specifically:

表示变电站j优化分析后应配置的储能功率；f_j表示变电站j的风险产值；N表示变电站数量；P₀表示各区域内储能允许配置的总功率。in,

represents the energy storage power that should be configured after the optimization analysis of substation j; f _j represents the risk output value of substation j; N represents the number of substations; P ₀ represents the total power allowed to configure energy storage in each area.

In addition, the calculation formula of energy storage capacity is as follows:

表示变电站j优化分析后应配置的储能容量；t₀表示配置的储能所允许的最大充电时间；E_es,j,T表示变电站j第T天的储能容量需求，max(E_es,j,T)表示变电站j在全年中储能容量需求的最大值。in,

Represents the energy storage capacity that should be configured after the optimization analysis of substation j; t ₀ represents the maximum charging time allowed by the configured energy storage; E _{es, j, T} represents the energy storage capacity demand of substation j on the T day, max(E _{es, j,T} ) represents the maximum energy storage capacity demand of substation j in the whole year.

In addition, the energy storage power and energy storage capacity must meet the following conditions:

Among them, P _es,i,T represents the energy storage power demand of substation i on the T day; S _i represents the rated capacity of substation i; ρ _i,t represents the real-time acquisition load rate of substation i at time t; ρ ₀ represents the The safe load rate is determined according to the product of the percentage of the rated capacity of each substation and the configuration coefficient of the corresponding substation, which is set to 85% in this embodiment; E _es,i,T represents the energy storage capacity demand of the substation i on the T day ; Δt is the sampling interval, which can be set to 5 minutes in this embodiment; K is the total sampling time.

Embodiment 2: An energy storage location and capacity optimization system considering multiple factors, the system is used to implement the energy storage location and capacity optimization method described in Embodiment 1, as shown in Figure 3, including a power analysis module, output value Analysis module and constant volume analysis module.

The power analysis module is used to obtain the load rate of each node of the power system according to the annual maximum load and rated capacity of the power system, and analyze the influence of the load rate of each node of the power system on the security of power supply in the power supply area to obtain the risk power;

The output value analysis module is used to analyze the output value corresponding to the risk electricity according to the economic output value data of each region, and obtain the risk output value;

The fixed capacity analysis module is used to input the risk output value and the total energy storage configuration of each region into the pre-built energy storage location and fixed capacity model for optimization analysis, and obtain the energy storage power and energy storage capacity of each node of the power system.

Working principle: The present invention takes into account both the regional economic development and the improvement of the peak and valley filling of the power system, which not only improves and supports the power system, but also considers the power support of the energy storage for local residents, industrial and commercial users. Taking into account the priorities of different planners, it is conducive to the implementation and execution of the planning scheme, ensuring the reliability of users' electricity consumption and maximizing social benefits; in addition, the present invention is determined according to the product of the percentage of the rated capacity of each substation and the configuration coefficient of the corresponding substation The safe load rate takes into account the layout of the substation in the entire power system, which makes the determination of the risk power more accurate and reliable.

As will be appreciated by those skilled in the art, the embodiments of the present application may be provided as a method, a system, or a 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, etc.) 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 present application. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

The above specific embodiments further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Within the spirit and principle of the present invention, any modifications, equivalent replacements, improvements, etc. made should be included within the protection 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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