CN117744972A

CN117744972A - Energy storage planning method and device for power system, computer equipment and storage medium

Info

Publication number: CN117744972A
Application number: CN202311627986.0A
Authority: CN
Inventors: 孙庆超; 谢莹华; 李植鹏; 王若愚; 李婧; 李嘉靓; 江万里; 王智贤
Original assignee: Shenzhen Power Supply Co ltd
Current assignee: Shenzhen Power Supply Co ltd
Priority date: 2023-11-30
Filing date: 2023-11-30
Publication date: 2024-03-22

Abstract

The application relates to an energy storage planning method, an energy storage planning device, computer equipment and a storage medium of a power system. The method comprises the following steps: acquiring an energy storage planning type; under the condition that the energy storage planning type is energy storage capacity planning, determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation power sequence and a first demand power sequence of the regional power grid; under the condition that the energy storage planning type is energy storage position planning, distributing the second target energy storage capacity according to the first capacity distribution granularity, and obtaining first target distribution capacity corresponding to each key node in the regional power grid; and under the condition that the energy storage planning type is the energy storage comprehensive planning, acquiring a third target energy storage capacity of the regional power grid and a second target allocation capacity corresponding to each key node in the regional power grid according to a second generation power sequence and a second demand power sequence of the regional power grid and a second capacity allocation granularity. By adopting the method, the energy storage planning efficiency can be improved.

Description

Energy storage planning method and device for power system, computer equipment and storage medium

Technical Field

The present disclosure relates to the field of power system planning technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for energy storage planning of a power system.

Background

With the great development of renewable energy sources, the permeability of renewable energy sources such as wind energy, solar energy and the like is continuously improved. Although the use of renewable energy sources can reduce carbon emission, the renewable energy sources have the characteristics of poor controllability, high instability and the like, and are easy to cause unbalance of supply and demand of an electric power system. On a multiple time scale, the unbalance of supply and demand of the power system can have adverse effects on peak shaving, climbing and frequency modulation of the system. Under the condition, the energy storage participates in frequency modulation, and the energy storage has the advantages of small volume, wide distribution, short response time, bidirectional regulation capability and the like, and has good development prospect in the aspect of participating in the frequency modulation of a power system.

In the related art, an energy storage planning scheme is usually calculated manually according to historical data of a power system, and the energy storage planning efficiency is low due to the fact that the calculation process is complex, the manual processing speed is low, and errors are prone to occurring.

Disclosure of Invention

In view of the foregoing, it is desirable to provide an energy storage planning method, apparatus, computer device, computer readable storage medium and computer program product for an electric power system capable of improving energy storage planning efficiency.

In a first aspect, the present application provides a method for energy storage planning of an electric power system, including:

acquiring an energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan the energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning is to perform double planning on energy storage capacity and energy storage distribution of key nodes;

under the condition that the energy storage planning type is energy storage capacity planning, determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation power sequence and a first demand power sequence of the regional power grid;

under the condition that the energy storage planning type is energy storage position planning, distributing the second target energy storage capacity according to the first capacity distribution granularity, and obtaining first target distribution capacity corresponding to each key node in the regional power grid;

under the condition that the energy storage planning type is energy storage comprehensive planning, determining a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second generated power sequence and a second required power sequence of the regional power grid; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacity corresponding to each key node in the regional power grid.

In one embodiment, determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation sequence and a first demand power sequence of the regional power grid comprises:

acquiring a plurality of capacity test values in a first energy storage capacity interval according to the capacity step value;

acquiring a frequency deviation sequence corresponding to each capacity test value according to the first power generation sequence and the first power demand sequence;

obtaining the root mean square of the frequency deviation corresponding to each frequency deviation sequence;

and determining a first target energy storage capacity from the capacity test values according to the capacity test values and the root mean square of the frequency deviation corresponding to the capacity test values.

In one embodiment, according to the first power generation sequence and the first power demand sequence, obtaining a frequency deviation sequence corresponding to each capacity test value includes:

acquiring an overall power sequence corresponding to each capacity test value according to the first power generation sequence and the first required power sequence;

and respectively inputting the whole power sequences corresponding to the capacity test values into a preset first-order inertia link to obtain frequency deviation sequences corresponding to the capacity test values.

In one embodiment, determining the first target energy storage capacity from the plurality of capacity test values according to each capacity test value and a root mean square of the frequency deviation corresponding to each capacity test value includes:

Obtaining a target weighting coefficient;

according to the target weighting coefficient, weighting and summing each capacity test value and the frequency deviation root mean square corresponding to each capacity test value to obtain a comprehensive index value corresponding to each capacity test value;

and taking the capacity test value corresponding to the minimum comprehensive index value as a first target energy storage capacity.

In one embodiment, the allocating the second target energy storage capacity according to the first capacity allocation granularity, to obtain the first target allocation capacity corresponding to each key node in the regional power grid, includes:

acquiring a plurality of capacity allocation test groups according to the first capacity allocation granularity, the second target energy storage capacity and the number of key nodes of the regional power grid;

respectively carrying out load flow calculation on the regional power grid according to different capacity allocation test groups to obtain test voltage sets corresponding to the capacity allocation test groups; the test voltage set comprises the voltage per unit value of each key node in the regional power grid;

determining a target capacity allocation group from a plurality of capacity allocation test groups according to the test voltage sets corresponding to the capacity test groups;

and determining a first target allocation capacity corresponding to each key node in the regional power grid according to the target capacity allocation group.

In one embodiment, determining a target capacity allocation group from a plurality of capacity allocation test groups according to the test voltage set corresponding to each capacity test group includes:

acquiring a target voltage set from a plurality of test voltage sets according to the voltage deviation threshold;

under the condition that a plurality of target voltage sets are provided, obtaining a voltage deviation root mean square corresponding to each target voltage set;

and taking the capacity allocation test group corresponding to the minimum voltage deviation root mean square as a target capacity allocation group.

In a second aspect, the present application further provides an energy storage planning device of an electric power system, including:

the acquisition module is used for acquiring the energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan the energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning is to perform double planning on energy storage capacity and energy storage distribution of key nodes;

the first planning module is used for determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation power sequence and a first demand power sequence of the regional power grid under the condition that the energy storage planning type is energy storage capacity planning;

The second planning module is used for distributing the second target energy storage capacity according to the first capacity distribution granularity under the condition that the energy storage planning type is energy storage position planning, and obtaining first target distribution capacity corresponding to each key node in the regional power grid;

the third planning module is used for determining a third target energy storage capacity of the regional power grid in the second energy storage capacity interval according to a second generated power sequence and a second required power sequence of the regional power grid under the condition that the energy storage planning type is energy storage comprehensive planning; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacity corresponding to each key node in the regional power grid.

In a third aspect, the present application also provides 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:

In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

In a fifth aspect, the present application also provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of:

According to the energy storage planning method, the device, the computer equipment, the storage medium and the computer program product of the power system, the first target energy storage capacity of the regional power grid is determined according to the first power generation sequence and the first demand power sequence of the regional power grid in the first energy storage capacity interval under the condition that the energy storage planning type is the energy storage capacity planning, or the second target energy storage capacity is allocated according to the first capacity allocation granularity under the condition that the energy storage planning type is the energy storage position planning, the first target allocation capacity corresponding to each key node in the regional power grid is obtained, or the third target energy storage capacity of the regional power grid is determined according to the second power generation sequence and the second demand power sequence of the regional power grid in the second energy storage capacity interval under the condition that the energy storage planning type is the energy storage comprehensive planning, the second target allocation capacity corresponding to each key node in the regional power grid is obtained, and the operation data of the regional power grid can be automatically obtained according to the energy storage planning requirement of a target user, and the energy storage planning efficiency can be improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person having ordinary skill in the art.

FIG. 1 is an application environment diagram of a method for energy storage planning of an electrical power system in one embodiment;

FIG. 2 is a flow chart of a method for energy storage planning of an electrical power system according to one embodiment;

FIG. 3 is a flow chart illustrating a method of energy storage planning for an electrical power system according to another embodiment;

FIG. 4 is a block diagram of an energy storage planning device of an electrical power system in one embodiment;

fig. 5 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The energy storage planning method of the power system provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network, and the server 104 communicates with the regional power dispatching center 106 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The server 104 may receive the energy storage planning type uploaded by the terminal 102, obtain the operation data of the regional power grid from the regional power dispatching center 106 according to the energy storage planning type, and then automatically perform energy storage planning according to the operation data of the regional power grid. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, which may be smart watches, smart bracelets, headsets, etc. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.

In an exemplary embodiment, as shown in fig. 2, there is provided a method for energy storage planning of an electric power system, which is illustrated by using the method applied to the server 104 in fig. 1 as an example, and includes the following steps:

S202: acquiring an energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan the energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning refers to double planning of energy storage capacity and energy storage distribution of key nodes.

The energy storage capacity of the regional power grid refers to total energy storage assembly power of the regional power grid, the key nodes refer to nodes capable of being assembled with energy storage in the regional power grid, the energy storage distribution of the key nodes refers to the distribution of the energy storage capacity of the regional power grid to different key nodes, and the sum of the energy storage capacities distributed by the key nodes is equal to the energy storage capacity of the regional power grid.

Optionally, considering different energy storage planning requirements, the server firstly acquires an energy storage planning type selected by a target user from the terminal, so as to acquire corresponding power grid operation data from the regional power dispatching center according to the energy storage planning type to perform energy storage calculation.

S204: and determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to the first power generation power sequence and the first demand power sequence of the regional power grid under the condition that the energy storage planning type is the energy storage capacity planning.

The first power generation power sequence refers to a total power generation power sequence of the regional power grid in a target time period, and the first power demand sequence refers to a total power utilization power sequence of the regional power grid in the target time period. The target time period may be determined according to a starting time point of the energy storage plan and a preset time length. The first energy storage capacity interval may be preset or may be input by a target user.

Optionally, the target user may choose to plan the energy storage capacity without knowing how much energy storage capacity the regional power grid needs to be configured. Under the condition that the energy storage planning type is energy storage capacity planning, the server firstly acquires a first power generation sequence and a first demand power sequence of the regional power grid in a target time period from the regional power dispatching center, and then, based on the frequency deviation requirement of the regional power grid, the first target energy storage capacity of the regional power grid is determined in a first energy storage capacity interval according to the first power generation sequence and the first demand power sequence.

S206: and under the condition that the energy storage planning type is energy storage position planning, distributing the second target energy storage capacity according to the first capacity distribution granularity, and obtaining the first target distribution capacity corresponding to each key node in the regional power grid.

The first capacity classification granularity refers to the minimum value of the energy storage capacity allocated in a single way, and can be preconfigured or input by a target user. The second target energy storage capacity is input by a target user.

Optionally, the target user may choose to plan the energy storage location in the case of a clear regional power grid configuration of energy storage capacity and key nodes that need to distribute energy storage. And under the condition that the energy storage planning type is energy storage position planning, the server can sequentially allocate the second target energy storage capacity to key nodes which enable the voltage deviation to be minimum in the regional power grid according to the first capacity allocation granularity until the second target energy storage capacity is completely allocated, so as to obtain the first target allocation capacity corresponding to each key node in the regional power grid.

S208: under the condition that the energy storage planning type is energy storage comprehensive planning, determining a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second generated power sequence and a second required power sequence of the regional power grid; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacity corresponding to each key node in the regional power grid.

Optionally, the target user may choose to perform comprehensive planning of energy storage under the condition that neither the energy storage capacity required by the regional power grid nor the key nodes to which energy storage needs to be allocated are clear. Under the condition that the energy storage planning type is energy storage comprehensive planning, the server firstly determines a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second power generation power sequence and a second demand power sequence of the regional power grid, and then allocates the third target energy storage capacity according to a second capacity allocation granularity to acquire a second target allocation capacity corresponding to each key node in the regional power grid.

It should be noted that, the process of obtaining the third target energy storage capacity of the regional power grid may refer to the process of obtaining the first target energy storage capacity when the energy storage planning type is energy storage capacity planning, the process of obtaining the second target allocation capacity corresponding to each key node in the regional power grid, and the process of obtaining the first target allocation capacity corresponding to each key node in the regional power grid when the energy storage planning type is energy storage position planning, which are not described herein.

In the energy storage planning method of the electric power system, the first target energy storage capacity of the regional power grid is determined according to the first power generation sequence and the first demand power sequence of the regional power grid under the condition that the energy storage planning type is the energy storage capacity planning, or the second target energy storage capacity is distributed according to the first capacity distribution granularity under the condition that the energy storage planning type is the energy storage position planning, the first target distribution capacity corresponding to each key node in the regional power grid is obtained, or the third target energy storage capacity of the regional power grid is determined according to the second power generation sequence and the second demand power sequence of the regional power grid under the condition that the energy storage planning type is the energy storage comprehensive planning, the second target distribution capacity corresponding to each key node in the regional power grid is obtained in the second energy storage capacity section, the distribution capacity of the third target energy storage capacity is distributed according to the second capacity distribution granularity, the operation data of the regional power grid can be automatically obtained according to the energy storage planning requirement of target users, and the energy storage planning calculation is completed, and therefore the energy storage efficiency can be improved.

In one embodiment, determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval from a first power generation sequence and a first demand power sequence of the regional power grid comprises: acquiring a plurality of capacity test values in a first energy storage capacity interval according to the capacity step value; acquiring a frequency deviation sequence corresponding to each capacity test value according to the first power generation sequence and the first power demand sequence; obtaining the root mean square of the frequency deviation corresponding to each frequency deviation sequence; and determining a first target energy storage capacity from the capacity test values according to the capacity test values and the root mean square of the frequency deviation corresponding to the capacity test values.

The capacity step value may be preset or input by the target user.

Optionally, in the case that the energy storage planning type is an energy storage capacity planning, the server first obtains a plurality of capacity test values from the first energy storage capacity interval according to the capacity step value. For example, the first energy storage capacity test interval is [ ECS _min ，ECS _max ]In the case of a capacity step value ΔESC, a capacity test value ECS can be obtained _min 、ECS _min +ΔESC、ECS _min +2ΔESC, etc., and so on.

Then, the server calculates a frequency deviation sequence corresponding to each capacity test value according to each capacity test value, the first power generation sequence and the first required power sequence in sequence. The frequency deviation sequence comprises frequency deviation values corresponding to different time points of the regional power grid in the target time period, wherein the frequency deviation values refer to the difference value between the frequency per unit value and 1.

Further, the server calculates a root mean square of the frequency deviation corresponding to each frequency deviation sequence. For example, the frequency deviation sequence is [ ΔF ₁ ，ΔF ₂ ，...，ΔF _M ]The calculation mode of the frequency deviation root mean square corresponding to the frequency deviation sequence is specifically as follows:

wherein DeltaF _i Representing the ith frequency deviation value, Δf, in the sequence of frequency deviations _RMS The root mean square of the frequency deviation is indicated.

After obtaining the root mean square of the frequency deviation corresponding to each capacity test value, the server determines a first target energy storage capacity from the plurality of capacity test values according to each capacity test value and the root mean square of the frequency deviation corresponding to each capacity test value.

In this embodiment, the energy storage planning efficiency can be improved by automatically measuring and calculating different capacity test values and selecting an optimal capacity test value from a plurality of capacity test values as the first target energy storage capacity.

In one embodiment, obtaining a frequency deviation sequence corresponding to each capacity test value according to the first power generation sequence and the first power demand sequence includes: acquiring an overall power sequence corresponding to each capacity test value according to the first power generation sequence and the first required power sequence; and respectively inputting the whole power sequences corresponding to the capacity test values into a preset first-order inertia link to obtain frequency deviation sequences corresponding to the capacity test values.

Optionally, in the process of obtaining the frequency deviation sequence corresponding to each capacity test value, the server firstly obtains the integral power sequence corresponding to each capacity test value according to the first power generation sequence and the first required power sequence. For example, the first power sequence is [ P ] ₁₁ ，P ₁₂ ，...，P _1N ]The first power demand sequence is [ P ] ₂₁ ，P ₂₂ ，...，P _2N ]Capacity test value P _test In the case of (2), the capacity test value P _test The corresponding overall power sequence is [ P ] ₁₁ -P ₂₁ +P _test ，P ₁₂ -P ₂₂ +P _test ，......，P _1N -P _2N +P _test ]。

And the server inputs the whole power sequence corresponding to each capacity test value into a preset first-order inertia link respectively to obtain a frequency deviation sequence corresponding to each capacity test value. The first-order inertia link is specifically as follows:

M＝2H

wherein Δf(s) represents a frequency domain sequence corresponding to the frequency deviation sequence, Δp(s) represents a frequency domain sequence corresponding to the overall power sequence, H represents an inertia constant of the regional power grid, and D represents a load-damping constant.

In one embodiment, determining a first target energy storage capacity from a plurality of capacity test values based on each capacity test value and a root mean square of frequency deviations corresponding to each capacity test value comprises: obtaining a target weighting coefficient; according to the target weighting coefficient, weighting and summing each capacity test value and the frequency deviation root mean square corresponding to each capacity test value to obtain a comprehensive index value corresponding to each capacity test value; and taking the capacity test value corresponding to the minimum comprehensive index value as a first target energy storage capacity.

The target weighting coefficient may be preset or input by a target user.

Optionally, after obtaining the root mean square of the frequency deviation corresponding to each capacity test value, the server performs weighted summation on each capacity test value and the root mean square of the frequency deviation corresponding to each capacity test value according to the target weighting coefficient, obtains the comprehensive index value corresponding to each capacity test value, and uses the capacity test value corresponding to the minimum comprehensive index value as the first target energy storage capacity. The calculation mode of the comprehensive index value is specifically as follows:

M＝k ₁ ΔF _RMS +k ₂ P _test

wherein M represents a comprehensive index value, k ₁ Represents a first weighting coefficient, deltaF _RMS Representing the root mean square, k of the frequency deviation ₂ Representing the second weighting coefficient, P _test Representing the capacity test value.

And then, the server sorts the comprehensive index values corresponding to the capacity test values, and takes the capacity test value corresponding to the minimum comprehensive index value as a first target energy storage capacity.

In this embodiment, the integrated index value corresponding to each capacity test value is obtained by performing weighted summation on each capacity test value and the frequency deviation root mean square corresponding to each capacity test value, and then the capacity test value corresponding to the minimum integrated index value is used as the first target energy storage capacity, so that the economy of the energy storage capacity and the frequency deviation requirement of the regional power grid can be comprehensively considered, and the determined first target energy storage capacity is more in accordance with the actual requirement.

In one embodiment, the allocating the second target energy storage capacity according to the first capacity allocation granularity, to obtain a first target allocation capacity corresponding to each key node in the regional power grid, includes: acquiring a plurality of capacity allocation test groups according to the first capacity allocation granularity, the second target energy storage capacity and the number of key nodes of the regional power grid; respectively carrying out load flow calculation on the regional power grid according to different capacity allocation test groups to obtain test voltage sets corresponding to the capacity allocation test groups; the test voltage set comprises the voltage per unit value of each key node in the regional power grid; determining a target capacity allocation group from a plurality of capacity allocation test groups according to the test voltage sets corresponding to the capacity test groups; and determining a first target allocation capacity corresponding to each key node in the regional power grid according to the target capacity allocation group.

The tide calculation method can be, but is not limited to, gaussian-Saidel iteration method, P-Q decomposition method and Newton-Laporton method.

Optionally, when obtaining the first target allocation capacity corresponding to each key node in the regional power grid, the server may first obtain a plurality of capacity allocation test groups according to the first capacity allocation granularity, the second target energy storage capacity, and the number of key nodes of the regional power grid. For example, when the first capacity allocation granularity is 10MW, the second target energy storage capacity is 30MW, and the number of key nodes of the regional power grid is 2, there are 4 corresponding capacity allocation test groups (30 MW,0 MW), (20 MW,10 MW), (10 MW,20 MW), (0 MW,30 MW), respectively.

And then, the server respectively performs load flow calculation on the regional power grid according to the different capacity allocation test groups to obtain test voltage sets corresponding to the capacity allocation test groups, wherein the test voltage sets comprise the voltage per unit value of each key node in the regional power grid.

Further, the server determines a target capacity allocation group from the plurality of capacity allocation test groups according to the test voltage sets corresponding to the capacity test groups, and determines a first target allocation capacity corresponding to each key node in the regional power grid according to the target capacity allocation group.

In this embodiment, the energy storage planning efficiency can be improved by automatically measuring and calculating different capacity allocation test groups, selecting an optimal capacity allocation test group from the capacity allocation test groups, and performing energy storage capacity allocation on each key node in the regional power grid.

In one embodiment, determining a target capacity allocation group from a plurality of capacity allocation test groups according to a set of test voltages corresponding to each capacity test group includes: acquiring a target voltage set from a plurality of test voltage sets according to the voltage deviation threshold; under the condition that a plurality of target voltage sets are provided, obtaining a voltage deviation root mean square corresponding to each target voltage set; and taking the capacity allocation test group corresponding to the minimum voltage deviation root mean square as a target capacity allocation group.

Optionally, after obtaining the test voltage sets corresponding to each capacity allocation test group, in order to avoid that the voltage of the key node does not meet the voltage deviation requirement of the regional power grid, the server further filters the test voltage sets with the voltage deviation value greater than the voltage deviation threshold according to the voltage deviation threshold to obtain the target voltage set. For example, in the case where the test voltage set {0.9962, 0.9815, 0.9703, 0.9687, 0.9411} has a voltage deviation threshold of 0.04, the voltage deviation values of the test voltage set are 0.0038, 0.0185, 0.0297, 0.0313, and 0.0589, respectively, and one of the test voltage sets has a voltage deviation value 0.0589 greater than the voltage deviation threshold of 0.04, the test voltage set needs to be discarded.

Under the condition that the target voltage set is single, the server directly takes the capacity allocation test group corresponding to the target voltage set as a target capacity allocation group; when the target voltage sets are plural, the server acquires the voltage deviation root mean square corresponding to each target voltage set, and sets the capacity allocation test set corresponding to the minimum voltage deviation root mean square as the target capacity allocation set. The specific calculation mode of the voltage deviation root mean square is as follows:

Wherein DeltaV _RMS Representing the voltage deviation root mean square, V _i Representing the per-unit value of the ith voltage in the test voltage set, and N represents the number of elements in the test voltage set.

In this embodiment, the target voltage sets are screened from the test voltage sets according to the voltage deviation threshold, and then, under the condition that the target voltage sets are multiple, the voltage deviation root mean square corresponding to each target voltage set is obtained, and the capacity allocation test set corresponding to the minimum voltage deviation root mean square is used as the target capacity allocation set, so that the voltage deviation requirement of the regional power grid can be better met.

In one embodiment, as shown in fig. 3, there is provided a method for energy storage planning of an electric power system, the method comprising the steps of:

acquiring an energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan the energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning refers to double planning of energy storage capacity and energy storage distribution of key nodes.

Under the condition that the energy storage planning type is energy storage capacity planning, acquiring a plurality of capacity test values in a first energy storage capacity interval according to the capacity stepping value; acquiring an overall power sequence corresponding to each capacity test value according to the first power generation sequence and the first required power sequence; respectively inputting the whole power sequences corresponding to the capacity test values into a preset first-order inertia link to obtain frequency deviation sequences corresponding to the capacity test values; obtaining the root mean square of the frequency deviation corresponding to each frequency deviation sequence; obtaining a target weighting coefficient; according to the target weighting coefficient, weighting and summing each capacity test value and the frequency deviation root mean square corresponding to each capacity test value to obtain a comprehensive index value corresponding to each capacity test value; and taking the capacity test value corresponding to the minimum comprehensive index value as a first target energy storage capacity.

Under the condition that the energy storage planning type is energy storage position planning, acquiring a plurality of capacity allocation test groups according to the first capacity allocation granularity, the second target energy storage capacity and the number of key nodes of the regional power grid; respectively carrying out load flow calculation on the regional power grid according to different capacity allocation test groups to obtain test voltage sets corresponding to the capacity allocation test groups; the test voltage set comprises the voltage per unit value of each key node in the regional power grid; acquiring a target voltage set from a plurality of test voltage sets according to the voltage deviation threshold; under the condition that a plurality of target voltage sets are provided, obtaining a voltage deviation root mean square corresponding to each target voltage set; taking a capacity allocation test group corresponding to the minimum voltage deviation root mean square as a target capacity allocation group; and determining a first target allocation capacity corresponding to each key node in the regional power grid according to the target capacity allocation group.

Under the condition that the energy storage planning type is energy storage comprehensive planning, determining a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second generated power sequence and a second required power sequence of the regional power grid; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacity corresponding to each key node in the regional power grid. It should be noted that, the process of obtaining the third target energy storage capacity of the regional power grid may refer to the process of obtaining the first target energy storage capacity when the energy storage planning type is energy storage capacity planning, the process of obtaining the second target allocation capacity corresponding to each key node in the regional power grid, and the process of obtaining the first target allocation capacity corresponding to each key node in the regional power grid when the energy storage planning type is energy storage position planning, which are not described herein.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides an energy storage planning device of the electric power system for realizing the energy storage planning method of the electric power system. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the energy storage planning device for one or more power systems provided below may refer to the limitation of the energy storage planning method for the power system hereinabove, and will not be repeated herein.

In one exemplary embodiment, as shown in fig. 4, there is provided an energy storage planning apparatus of an electric power system, including: an acquisition module 410, a first planning module 420, a second planning module 430, and a third planning module 440, wherein:

an acquisition module 410, configured to acquire an energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan the energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning is to perform double planning on energy storage capacity and energy storage distribution of key nodes;

the first planning module 420 is configured to determine, in a first energy storage capacity interval, a first target energy storage capacity of the regional power grid according to a first power generation sequence and a first demand power sequence of the regional power grid when the energy storage planning type is an energy storage capacity plan;

the second planning module 430 is configured to allocate a second target energy storage capacity according to a first capacity allocation granularity when the energy storage planning type is energy storage position planning, and obtain a first target allocation capacity corresponding to each key node in the regional power grid;

The third planning module 440 is configured to determine a third target energy storage capacity of the regional power grid according to the second generated power sequence and the second required power sequence of the regional power grid in the second energy storage capacity interval when the energy storage planning type is an energy storage comprehensive planning; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacity corresponding to each key node in the regional power grid.

In one embodiment, the first planning module 420 is further configured to obtain a plurality of capacity test values in the first energy storage capacity interval according to the capacity step value; acquiring a frequency deviation sequence corresponding to each capacity test value according to the first power generation sequence and the first power demand sequence; obtaining the root mean square of the frequency deviation corresponding to each frequency deviation sequence; and determining a first target energy storage capacity from the capacity test values according to the capacity test values and the root mean square of the frequency deviation corresponding to the capacity test values.

In one embodiment, the first planning module 420 is further configured to obtain an overall power sequence corresponding to each capacity test value according to the first power generation sequence and the first power demand sequence; and respectively inputting the whole power sequences corresponding to the capacity test values into a preset first-order inertia link to obtain frequency deviation sequences corresponding to the capacity test values.

In one embodiment, the first planning module 420 is further configured to obtain a target weighting coefficient; according to the target weighting coefficient, weighting and summing each capacity test value and the frequency deviation root mean square corresponding to each capacity test value to obtain a comprehensive index value corresponding to each capacity test value; and taking the capacity test value corresponding to the minimum comprehensive index value as a first target energy storage capacity.

In one embodiment, the second planning module 430 is further configured to obtain a plurality of capacity allocation test groups according to the first capacity allocation granularity, the second target energy storage capacity, and the number of key nodes of the regional power grid; respectively carrying out load flow calculation on the regional power grid according to different capacity allocation test groups to obtain test voltage sets corresponding to the capacity allocation test groups; the test voltage set comprises the voltage per unit value of each key node in the regional power grid; determining a target capacity allocation group from a plurality of capacity allocation test groups according to the test voltage sets corresponding to the capacity test groups; and determining a first target allocation capacity corresponding to each key node in the regional power grid according to the target capacity allocation group.

In one embodiment, the second planning module 430 is further configured to obtain a target voltage set from the plurality of test voltage sets according to the voltage deviation threshold; under the condition that a plurality of target voltage sets are provided, obtaining a voltage deviation root mean square corresponding to each target voltage set; and taking the capacity allocation test group corresponding to the minimum voltage deviation root mean square as a target capacity allocation group.

The modules in the energy storage planning device of the power system can be realized in whole or in part by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one exemplary embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing business data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of energy storage planning for an electrical power system.

It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In one exemplary embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of: acquiring an energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan the energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning is to perform double planning on energy storage capacity and energy storage distribution of key nodes; under the condition that the energy storage planning type is energy storage capacity planning, determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation power sequence and a first demand power sequence of the regional power grid; under the condition that the energy storage planning type is energy storage position planning, distributing the second target energy storage capacity according to the first capacity distribution granularity, and obtaining first target distribution capacity corresponding to each key node in the regional power grid; under the condition that the energy storage planning type is energy storage comprehensive planning, determining a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second generated power sequence and a second required power sequence of the regional power grid; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacity corresponding to each key node in the regional power grid.

In one embodiment, the processor when executing the computer program further performs the steps of: acquiring a plurality of capacity test values in a first energy storage capacity interval according to the capacity step value; acquiring a frequency deviation sequence corresponding to each capacity test value according to the first power generation sequence and the first power demand sequence; obtaining the root mean square of the frequency deviation corresponding to each frequency deviation sequence; and determining a first target energy storage capacity from the capacity test values according to the capacity test values and the root mean square of the frequency deviation corresponding to the capacity test values.

In one embodiment, the processor when executing the computer program further performs the steps of: acquiring an overall power sequence corresponding to each capacity test value according to the first power generation sequence and the first required power sequence; and respectively inputting the whole power sequences corresponding to the capacity test values into a preset first-order inertia link to obtain frequency deviation sequences corresponding to the capacity test values.

In one embodiment, the processor when executing the computer program further performs the steps of: obtaining a target weighting coefficient; according to the target weighting coefficient, weighting and summing each capacity test value and the frequency deviation root mean square corresponding to each capacity test value to obtain a comprehensive index value corresponding to each capacity test value; and taking the capacity test value corresponding to the minimum comprehensive index value as a first target energy storage capacity.

In one embodiment, the processor when executing the computer program further performs the steps of: acquiring a plurality of capacity allocation test groups according to the first capacity allocation granularity, the second target energy storage capacity and the number of key nodes of the regional power grid; respectively carrying out load flow calculation on the regional power grid according to different capacity allocation test groups to obtain test voltage sets corresponding to the capacity allocation test groups; the test voltage set comprises the voltage per unit value of each key node in the regional power grid; determining a target capacity allocation group from a plurality of capacity allocation test groups according to the test voltage sets corresponding to the capacity test groups; and determining a first target allocation capacity corresponding to each key node in the regional power grid according to the target capacity allocation group.

In one embodiment, the processor when executing the computer program further performs the steps of: acquiring a target voltage set from a plurality of test voltage sets according to the voltage deviation threshold; under the condition that a plurality of target voltage sets are provided, obtaining a voltage deviation root mean square corresponding to each target voltage set; and taking the capacity allocation test group corresponding to the minimum voltage deviation root mean square as a target capacity allocation group.

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 an energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan the energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning is to perform double planning on energy storage capacity and energy storage distribution of key nodes; under the condition that the energy storage planning type is energy storage capacity planning, determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation power sequence and a first demand power sequence of the regional power grid; under the condition that the energy storage planning type is energy storage position planning, distributing the second target energy storage capacity according to the first capacity distribution granularity, and obtaining first target distribution capacity corresponding to each key node in the regional power grid; under the condition that the energy storage planning type is energy storage comprehensive planning, determining a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second generated power sequence and a second required power sequence of the regional power grid; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacity corresponding to each key node in the regional power grid.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a plurality of capacity test values in a first energy storage capacity interval according to the capacity step value; acquiring a frequency deviation sequence corresponding to each capacity test value according to the first power generation sequence and the first power demand sequence; obtaining the root mean square of the frequency deviation corresponding to each frequency deviation sequence; and determining a first target energy storage capacity from the capacity test values according to the capacity test values and the root mean square of the frequency deviation corresponding to the capacity test values.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring an overall power sequence corresponding to each capacity test value according to the first power generation sequence and the first required power sequence; and respectively inputting the whole power sequences corresponding to the capacity test values into a preset first-order inertia link to obtain frequency deviation sequences corresponding to the capacity test values.

In one embodiment, the computer program when executed by the processor further performs the steps of: obtaining a target weighting coefficient; according to the target weighting coefficient, weighting and summing each capacity test value and the frequency deviation root mean square corresponding to each capacity test value to obtain a comprehensive index value corresponding to each capacity test value; and taking the capacity test value corresponding to the minimum comprehensive index value as a first target energy storage capacity.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a plurality of capacity allocation test groups according to the first capacity allocation granularity, the second target energy storage capacity and the number of key nodes of the regional power grid; respectively carrying out load flow calculation on the regional power grid according to different capacity allocation test groups to obtain test voltage sets corresponding to the capacity allocation test groups; the test voltage set comprises the voltage per unit value of each key node in the regional power grid; determining a target capacity allocation group from a plurality of capacity allocation test groups according to the test voltage sets corresponding to the capacity test groups; and determining a first target allocation capacity corresponding to each key node in the regional power grid according to the target capacity allocation group.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a target voltage set from a plurality of test voltage sets according to the voltage deviation threshold; under the condition that a plurality of target voltage sets are provided, obtaining a voltage deviation root mean square corresponding to each target voltage set; and taking the capacity allocation test group corresponding to the minimum voltage deviation root mean square as a target capacity allocation group.

In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of: acquiring an energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan the energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning is to perform double planning on energy storage capacity and energy storage distribution of key nodes; under the condition that the energy storage planning type is energy storage capacity planning, determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation power sequence and a first demand power sequence of the regional power grid; under the condition that the energy storage planning type is energy storage position planning, distributing the second target energy storage capacity according to the first capacity distribution granularity, and obtaining first target distribution capacity corresponding to each key node in the regional power grid; under the condition that the energy storage planning type is energy storage comprehensive planning, determining a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second generated power sequence and a second required power sequence of the regional power grid; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacity corresponding to each key node in the regional power grid.

It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use, and processing of the related data are required to meet the related regulations.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims

1. A method of energy storage planning for an electrical power system, the method comprising:

acquiring an energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning refers to double planning of the energy storage capacity and the energy storage distribution of the key nodes;

Determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation power sequence and a first demand power sequence of the regional power grid under the condition that the energy storage planning type is the energy storage capacity planning;

under the condition that the energy storage planning type is the energy storage position planning, distributing a second target energy storage capacity according to a first capacity distribution granularity to obtain a first target distribution capacity corresponding to each key node in the regional power grid;

determining a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second generated power sequence and a second required power sequence of the regional power grid under the condition that the energy storage planning type is the energy storage comprehensive planning; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacities corresponding to all key nodes in the regional power grid.

2. The method of claim 1, wherein determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval from the first power generation sequence and the first demand power sequence of the regional power grid comprises:

Acquiring a plurality of capacity test values in the first energy storage capacity interval according to the capacity step value;

and determining the first target energy storage capacity from the capacity test values according to the capacity test values and the root mean square of the frequency deviation corresponding to the capacity test values.

3. The method according to claim 2, wherein the obtaining a frequency deviation sequence corresponding to each capacity test value according to the first power generation sequence and the first power demand sequence includes:

4. The method of claim 2, wherein determining the first target energy storage capacity from the plurality of capacity test values based on the capacity test values and the root mean square of the frequency deviation corresponding to the capacity test values comprises:

Obtaining a target weighting coefficient;

according to the target weighting coefficient, weighting and summing each capacity test value and the root mean square of the frequency deviation corresponding to each capacity test value to obtain a comprehensive index value corresponding to each capacity test value;

and taking the capacity test value corresponding to the minimum comprehensive index value as the first target energy storage capacity.

5. The method of claim 1, wherein the allocating the second target energy storage capacity according to the first capacity allocation granularity to obtain the first target allocation capacity corresponding to each key node in the regional power grid includes:

respectively carrying out load flow calculation on the regional power grid according to different capacity allocation test groups to obtain test voltage sets corresponding to the capacity allocation test groups; the test voltage set comprises voltage per unit values of all key nodes in the regional power grid;

6. The method of claim 5, wherein determining a target capacity allocation group from the plurality of capacity allocation test groups based on the set of test voltages corresponding to each capacity test group comprises:

and taking the capacity allocation test group corresponding to the minimum voltage deviation root mean square as the target capacity allocation group.

7. An energy storage planning device for an electrical power system, the device comprising:

the acquisition module is used for acquiring the energy storage planning type; the energy storage planning type comprises energy storage capacity planning, energy storage position planning and energy storage comprehensive planning; the energy storage capacity planning is to plan the energy storage capacity of the regional power grid only; the energy storage position planning is to plan energy storage distribution of key nodes in the regional power grid only; the energy storage comprehensive planning refers to double planning of the energy storage capacity and the energy storage distribution of the key nodes;

The first planning module is used for determining a first target energy storage capacity of the regional power grid in a first energy storage capacity interval according to a first power generation sequence and a first demand power sequence of the regional power grid under the condition that the energy storage planning type is the energy storage capacity planning;

the second planning module is used for distributing second target energy storage capacity according to the first capacity distribution granularity under the condition that the energy storage planning type is the energy storage position planning, and obtaining first target distribution capacity corresponding to each key node in the regional power grid;

the third planning module is used for determining a third target energy storage capacity of the regional power grid in a second energy storage capacity interval according to a second power generation power sequence and a second demand power sequence of the regional power grid under the condition that the energy storage planning type is the energy storage comprehensive planning; and distributing the third target energy storage capacity according to the second capacity distribution granularity to obtain second target distribution capacities corresponding to all key nodes in the regional power grid.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.