CN115882478B - Energy storage capacity configuration method and system for photovoltaic-containing power distribution network - Google Patents
Energy storage capacity configuration method and system for photovoltaic-containing power distribution network Download PDFInfo
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Abstract
The application provides an energy storage capacity configuration method and system for a photovoltaic-containing power distribution network, and a photovoltaic energy storage objective function is determined; the energy storage system is connected into a power distribution system, and the charging and discharging power constraint is calculated; calculating a node sensitivity coefficient, and dividing all nodes into different blocks according to node sensitivity; superposing the energy storage energy of each time period to obtain the energy storage energy capacity of each block; constructing a confirmation relation of configuration capacity, and determining the configuration capacity of each block; and selecting the maximum allocation capacity in the block as the allocation capacity of the energy storage system.
Description
Technical Field
The application relates to the technical field of energy allocation, in particular to an energy storage capacity allocation method and system for a photovoltaic-containing power distribution network.
Background
The power distribution network is most closely related to users, and the influence on the users is the key link of the power system facing the users directly. Since the end of 90 s of the last century, our country has increased the investment in the construction of the infrastructure of the power distribution network year by year, and has been put into the construction and modification of power distribution systems beyond trillion yuan at present. However, compared with the advanced world level, the power distribution network of China still has great room for improvement in the aspects of power grid structure, information and automation level, power supply reliability, technical management and the like. Therefore, in order to increase the proportion of renewable energy power generation, ensure the power supply quality and improve the flexibility and reliability of the operation of the power distribution system, the multi-capital of the country and the society will participate in the upgrading and transformation of the power distribution system.
Energy storage technology is a technology that enables the storage of energy, converting the energy from one form to a storable form and storing it in various mediums, and then converting the stored energy back into electrical energy when needed. The energy storage may be divided into power-type energy storage and energy-type energy storage according to external characteristics of energy storage and release of the energy storage system. The power type energy storage is represented by flywheel energy storage, is suitable for being applied to the scene of compensating short-time scale power fluctuation, and has the characteristics of high charging and discharging rate, long service life and the like; the energy type energy storage is represented by pumping energy storage, is suitable for being applied to the scene of compensating the power fluctuation of a long time scale, and has the characteristics of large capacity, slow response speed compared with the power type energy storage and the like.
At present, the energy storage system has the problems of short service life and high manufacturing cost of the device, the large-scale application of the energy storage system is greatly hindered, and the configuration planning problem also becomes a research hot spot at present. The commonly used energy storage system capacity allocation and optimization methods mainly comprise a differential compensation method, a fluctuation stabilization method and an economic characteristic optimization method.
The balance compensation method is from the viewpoint of ensuring continuous power supply, and determines the configuration capacity of the energy storage by balancing the unbalance between the generating power of the generator set and the power consumption of the electric load by using the energy storage, and compensates the balance between the actual output of the wind farm or the photovoltaic power generation and a given power level (such as load, prediction or scheduling plan), but does not consider the dynamic changes of the capacity and the power in the actual running process, so the accuracy of the configuration capacity is lacking.
However, related researches are carried out on the influence of the installation position on the capacity of the energy storage system when planning the capacity of the energy storage system, and quantitative evaluation and calculation are carried out on the energy storage life while the operation of the system is considered, so that the planning result is difficult to consider the influence of the energy storage operation state on the service life, and the energy storage economy is reduced. In addition, network loss and voltage fluctuation also influence the installation node and configuration capacity of energy storage, and a plurality of distributed energy storage coordinated operations can reduce unnecessary energy storage installation capacity when guaranteeing the safe operation of distribution network. Therefore, the method for optimizing and configuring the energy storage system full life cycle cost is developed for the distribution network leading to the future distributed power supply, and has important significance.
Disclosure of Invention
In order to solve the technical problems, the application provides a method for configuring energy storage capacity of a photovoltaic-containing power distribution network, which is characterized by comprising the following steps:
s1, determining a photovoltaic energy storage objective function;
s2, connecting the energy storage system into a power distribution system, and calculating the constraint of charging and discharging power;
s3, calculating a node sensitivity coefficient, and dividing all nodes into different blocks according to node sensitivity;
s4, superposing the energy storage energy of each time period to obtain the energy storage energy capacity of each block;
s5, constructing a confirmation relation of configuration capacity, and determining the configuration capacity of each block;
s6, selecting the maximum configuration capacity in the block as the configuration capacity of the energy storage system.
Further, in step S1, the photovoltaic energy storage objective function is set as follows:
F＝min(λ 1 C 1 -λ 2 C 2 +λ 3 S) (1)；
wherein ,
in the formula ,C1 C for energy loss of energy storage system 2 For energy storage system energy income, S is energy deviation, lambda 1 、λ 2 and λ3 Respectively obtaining weight coefficients of energy loss of the energy storage system, energy storage income of the energy storage system and energy deviation; n (N) ac and Ndc The number of nodes of the alternating current subsystem and the direct current subsystem is respectively; p (P) i(t) and Qi And (t) respectively representing the active output power value and the reactive output power value of the node i at the moment t.
Further, in step S2, the output power of the energy storage system to the power grid is set to be in the positive direction, and the charging and discharging power constraints are shown in formulas (3), (4) and (5):
-P max，i ≤P i (t)≤P max，i (4)；
-Q max，i ≤Q i (t)≤Q max，i (5)；
in the formula ,Pi (t) is the active power output power value of the ith node at the moment t, and is positive when the energy storage is discharged and negative when the energy storage is charged; q (Q) i (t) is the reactive power output value of the ith node at the moment t; s is S Ei 、P max，i and Qmax，i The upper limits of the access power capacity, the active power and the reactive power of the energy storage system converter are respectively set.
Further, in step S3, a sensitivity coefficient N of any node is defined as:
in the above, alpha and beta are sensitivity systemsThe number weights satisfy α+β=1. P (P) i (delta t) is the active output power variation of the ith node in delta t time; q (Q) i (delta t) is the reactive output power variation of the ith node in delta t time; s is S i (Δt) is the energy deviation of the ith node in Δt time, S i (Δt) can be expressed as:
further, in step S4, the energy storage capacity F of each block is calculated according to formula (8);
wherein ,Ft Is the initial capacity of the stored energy, where t=1, 2, …, T.
Further, in step S5, the constraint relation of the configuration capacity is:
Min(α 1 ·S max +α 2 ·F) (9)；
wherein ,α1 、α 2 As the weight parameter, F is the energy storage capacity, S max For the maximum capacity of the stored energy power,
the application also provides an energy storage capacity configuration system containing the photovoltaic power distribution network, which is used for realizing an energy storage capacity configuration method, and comprises the following steps:
the objective function determining module is used for determining a photovoltaic energy storage objective function;
the constraint module is used for calculating the constraint of the charging and discharging power after the energy storage system is connected to the power distribution system;
the node sensitivity coefficient calculation module is used for calculating the sensitivity coefficient of each node and dividing all the nodes into different blocks according to the node sensitivity;
the energy storage energy capacity of the blocks is used for superposing the energy storage energy of each time period to obtain the energy storage energy capacity of each block;
the regional capacity configuration module is used for constructing a confirmation relation of configuration capacity and determining the configuration capacity of each block;
the energy storage system capacity allocation module is used for selecting the maximum allocation capacity in the block as the energy storage system allocation capacity.
Further, the energy storage capacity configuration system further comprises an energy storage capacity double-layer optimization system, the outer layer system is used for solving the energy storage capacity configuration method, and the inner layer system is used for solving the system operation condition under the planning of the energy storage capacity.
Compared with the prior art, the application has the following beneficial technical effects:
according to an energy storage operation strategy, energy is kept to be as close to or as kept in a node energy amplitude optimization section as possible under the condition that the energy storage system operates in an optimal operation state, a photovoltaic energy storage objective function is set, a charging and discharging process of the energy storage system operation process is divided into a plurality of sections, energy storage energy of each section is overlapped with time, and energy storage energy capacity of each section is calculated; and constructing a constraint relation of the configuration capacity, and solving the configuration capacity of each section according with a constraint formula.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a flow chart of a method of configuring energy storage capacity of a photovoltaic-containing power distribution network of the present application;
fig. 2 is a schematic structural diagram of an energy storage capacity configuration system of the photovoltaic-containing power distribution network.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the drawings of the specific embodiments of the present application, in order to better and more clearly describe the working principle of each element in the system, the connection relationship of each part in the device is represented, but only the relative positional relationship between each element is clearly distinguished, and the limitations on the signal transmission direction, connection sequence and the structure size, dimension and shape of each part in the element or structure cannot be constructed.
Energy storage technology is a technology that enables the storage of energy, converting the energy from one form to a storable form and storing it in various mediums, and then converting the stored energy back into electrical energy when needed.
The energy storage may be divided into power-type energy storage and energy-type energy storage according to external characteristics of energy storage and release of the energy storage system. The function is represented by flywheel energy storage, is suitable for being applied to the scene of compensating short-time scale power fluctuation, and has the characteristics of high charge and discharge rate, long service life and the like; the energy type energy storage is represented by pumping energy storage, is suitable for being applied to the scene of compensating the power fluctuation of a long time scale, and has the characteristics of large capacity, slow response speed compared with the power type energy storage and the like.
At present, the energy storage system has the problems of short service life and high manufacturing cost of the device, the large-scale application of the energy storage system is greatly hindered, and the configuration planning problem also becomes a research hot spot. The commonly used energy storage system capacity allocation and optimization methods mainly comprise a differential compensation method, a fluctuation stabilization method and an economic characteristic optimization method. The application provides a flow chart of an energy storage capacity configuration method of a photovoltaic-containing power distribution network, as shown in fig. 1, comprising the following steps:
s1, determining a photovoltaic energy storage objective function.
According to an operation strategy of energy storage, under the condition that the energy storage system is ensured to operate in an optimal operation state, energy is approached to or kept in a node energy amplitude optimization section as far as possible, and a photovoltaic energy storage objective function is set as follows:
F＝min(λ 1 C 1 -λ 2 C 2 +λ 3 S) (1)；
wherein ,
in the formula ,C1 C for energy loss of energy storage system 2 For energy storage system energy income, S is energy deviation, lambda 1 、λ 2 and λ3 Respectively obtaining weight coefficients of energy loss of the energy storage system, energy storage income of the energy storage system and energy deviation; na. And N dc The number of nodes of the alternating current subsystem and the direct current subsystem is respectively; p (P) i(t) and Qi And (t) respectively representing the active output power value and the reactive output power value of the node i at the moment t.
S2, the energy storage system is connected into the power distribution system, and the charging and discharging power constraint is calculated.
When the energy storage system is connected with the power distribution system, the energy storage system is connected with the power distribution system through the bidirectional ac-dc converter, and the ac-dc converter can support the power distribution system by absorbing or emitting a certain amount of active output power and reactive output power.
The application sets the output power of the energy storage system to the distribution system as the positive direction, namely, the output power is the positive direction when the energy storage system is operated as a power supply, the active and reactive characteristics of the energy storage system are comprehensively considered, and the charge and discharge power constraint is shown as formulas (3), (4) and (5):
-P max，i ≤P i (t)≤P max，i (4)；
-Q max，i ≤Q i (t)≤Q max，i (5)；
in the formula ,Pi (t) is the active power output power value of the ith node at the moment t, and is positive when the energy storage is discharged and negative when the energy storage is charged; q (Q) i (t) is the reactive power output value of the ith node at the moment t; s is S Ei 、P max，i and Qmax，i The upper limits of the access power capacity, the active power and the reactive power of the energy storage system converter are respectively set.
S3, calculating a node sensitivity coefficient, and dividing all nodes into different blocks according to the node sensitivity. The sensitivity coefficient N of any node is defined as:
in the above formula, α and β are sensitivity coefficient weights, satisfying α+β=1. P (P) i (delta t) is the active output power variation of the ith node in delta t time; q (Q) i (delta t) is the reactive output power variation of the ith node in delta t time; s is S i (Δt) is the energy deviation of the ith node in Δt time, S i (Δt) can be expressed as:
s4, superposing the energy storage energy of each time period to obtain the energy storage energy capacity F of each block shown in a formula (8);
wherein ,Ft Is the initial capacity of the stored energy, where t=1, 2, …, T.
S5, constructing a confirmation relation of the configuration capacity shown in the formula (9), and determining the configuration capacity of each block.
Min(γ 1 ·S max +γ 2 ·F) (9)；
wherein ,γ1 、γ 2 As the weight parameter, F is the energy storage capacity, S max The maximum capacity of the stored energy power, namely the maximum charge and discharge power,
s6, selecting the maximum configuration capacity in the block as the configuration capacity of the energy storage system.
As shown in fig. 2, the present application further provides an energy storage capacity configuration system including a photovoltaic power distribution network, including:
and the objective function determining module is used for determining a photovoltaic energy storage objective function. According to the operation strategy of energy storage, under the condition of ensuring that the energy storage system operates in the optimal operation state, the energy is as close to or kept in the node energy amplitude optimization section as possible, and the node numbers of the alternating current subsystem and the direct current subsystem are respectively N ac and Ndc The method comprises the steps of carrying out a first treatment on the surface of the the active output power value and the reactive output power value of the node i at the moment t are respectively P i(t) and Qi (t)。
And the constraint module is used for calculating the charge and discharge power constraint after the energy storage system is connected to the power distribution system.
The node sensitivity coefficient calculation module is used for calculating the sensitivity coefficient of each node and dividing all the nodes into different blocks according to the node sensitivity.
And the energy storage energy capacity of the blocks is used for superposing the energy storage energy of each time period to obtain the energy storage energy capacity of each block.
When the energy storage system is connected with the power distribution system, the energy storage system is connected with the power distribution system through the bidirectional ac-dc converter, and the ac-dc converter can support the power distribution system by absorbing or emitting a certain amount of active output power and reactive output power.
Compared with the traditional alternating current power distribution system, the power distribution system is an alternating current/direct current hybrid power distribution system, the load in the network can be distributed more reasonably, an alternating current distributed power supply and the load are connected into an alternating current subsystem node of the alternating current/direct current hybrid power distribution system, and the direct current distributed power supply and the load are connected into a direct current subsystem node of the alternating current/direct current hybrid power distribution network, so that the unnecessary investment of an electric power conversion device is reduced, and meanwhile, the system loss and the harmonic content are reduced, and the running economy and the electric energy quality of the system are improved.
And the regional capacity configuration module is used for constructing a confirmation relation of the configuration capacity and determining the configuration capacity of each block.
The energy storage system capacity allocation module is used for selecting the maximum allocation capacity in the block as the energy storage system allocation capacity.
In the preferred embodiment, the energy storage capacity configuration system of the photovoltaic power distribution network further establishes an energy storage capacity double-layer optimization system, wherein the outer layer system is used for solving the energy storage capacity configuration method, and the inner layer system is used for solving the system operation condition under the planning of the energy storage capacity.
The outer layer optimization model transmits the energy storage capacity, rated power and an initial value of the SOC to the inner layer optimization model; and the inner layer optimization model performs operation optimization of the alternating current-direct current hybrid power distribution network under the energy storage parameters given by the outer layer, obtains the operation power of energy storage and VSC, the system loss cost and the energy storage energy income, returns to the outer layer optimization model, and performs alternate solving through the inner layer optimization and the outer layer optimization.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted across a computer-readable storage medium. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.
While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (3)
1. An energy storage capacity configuration system including a photovoltaic power distribution network, comprising:
the objective function determining module is used for approaching or maintaining energy in the node energy amplitude optimizing section under the condition of ensuring that the energy storage system operates in an optimal operation state, and setting a photovoltaic energy storage objective function as follows:
F＝min(λ 1 C 1 -λ 2 C 2 +λ 3 S) (1)；
wherein ,
in the formula ,C1 C for energy loss of energy storage system 2 For energy storage system energy income, S is energy deviation, lambda 1 、λ 2 and λ3 The weight coefficients are respectively the energy loss of the energy storage system, the energy income of the energy storage system and the energy deviation; n (N) ac and Ndc The number of nodes of the alternating current subsystem and the direct current subsystem is respectively; p (P) i(t) and Qi (t) respectively an active output power value and a reactive output power value of a node i at the moment t;
the constraint module is used for calculating the constraint of the charging and discharging power after the energy storage system is connected to the power distribution system;
the node sensitivity coefficient calculation module is used for calculating the sensitivity coefficient of each node and dividing all the nodes into different blocks according to the node sensitivity;
the sensitivity coefficient N of any node is defined as:
in the above formula, α and β are sensitivity coefficient weights, satisfying α+β=1; p (P) i (delta t) is the active output power variation of the ith node in delta t time; q (Q) i (delta t) is the reactive output power variation of the ith node in delta t time; s is S i (Δt) is the energy deviation of the ith node in Δt time, S i (Δt) is expressed as:
the energy storage energy capacity of the blocks is used for superposing the energy storage energy of each time period to obtain the energy storage energy capacity of each block;
calculating the energy storage capacity F of each block according to a formula (8);
wherein ,Ft Initial capacity for stored energy, where t=1, 2,;
the regional capacity configuration module is used for constructing a confirmation relation of configuration capacity and determining the configuration capacity of each block; the constraint relation of the configuration capacity is as follows:
Min(α 1 ·S max +α 2 ·F)；
wherein ,α1 、α 2 As the weight parameter, F is the energy storage capacity, S max For the maximum capacity of the stored energy power,
the energy storage system capacity allocation module is used for selecting the maximum allocation capacity in the block as the energy storage system allocation capacity;
the energy storage capacity configuration system further comprises an energy storage capacity double-layer optimization system, wherein the outer layer system is used for solving the energy storage capacity configuration method, and the inner layer system is used for solving the system operation condition under the planning of the energy storage capacity; the outer layer optimization model transmits the energy storage capacity, rated power and an initial value of the SOC to the inner layer optimization model; and the inner layer optimization model performs operation optimization of the alternating current-direct current hybrid power distribution network under the energy storage parameters given by the outer layer, obtains the operation power of energy storage and VSC, the system loss cost and the energy storage energy income, returns to the outer layer optimization model, and performs alternate solving through the inner layer optimization and the outer layer optimization.
2. The energy storage capacity allocation system according to claim 1, wherein when the energy storage system is connected to the power distribution system, the energy storage system is connected to the power distribution system through a bi-directional ac-dc converter that supports the power distribution system by absorbing or emitting active and reactive output power.
3. The energy storage capacity allocation system according to claim 2, wherein the energy storage system outputs power to the power grid in a positive direction, and the charge and discharge power constraints are as follows:
-P max,i ≤P i (t)≤P max,i ；
-Q max,i ≤Q i (t)≤Q max,i ；
in the formula ,Pi (t) is the active power output power value of the ith node at the moment t, and is positive when the energy storage is discharged and negative when the energy storage is charged; q (Q) i (t) is the reactive power output value of the ith node at the moment t; s is S Ei 、P max,i and Qmax,i Respectively is energy storageThe upper limit of access power capacity, active power and reactive power of the system converter.
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| CN114243760A (en) * | 2021-11-25 | 2022-03-25 | 国网浙江省电力有限公司杭州供电公司 | Photovoltaic energy storage coordination configuration method suitable for power distribution network |
| CN114548597A (en) * | 2022-03-03 | 2022-05-27 | 国网浙江省电力有限公司双创中心 | Optimization method for alternating current-direct current hybrid optical storage and distribution power grid |
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