CN117650551A

CN117650551A - New energy source outgoing energy storage capacity accumulation type configuration method, device, equipment and medium

Info

Publication number: CN117650551A
Application number: CN202311845629.1A
Authority: CN
Inventors: 李鹏; 杨尉薇; 刘淑军; 张孜毅; 王博; 杨本均; 张美俊; 张小龙; 王鹏磊
Original assignee: China Three Gorges Corp; China Three Gorges Renewables Group Co Ltd
Current assignee: China Three Gorges Corp; China Three Gorges Renewables Group Co Ltd
Priority date: 2023-12-27
Filing date: 2023-12-27
Publication date: 2024-03-05

Abstract

The application provides a new energy outgoing energy storage capacity accumulation type configuration method, device, equipment and medium, comprising the following steps: acquiring an initial value of the energy storage capacity, and inputting the initial value into an energy storage optimal configuration model to obtain new energy consumption; the energy storage optimal configuration model aims at calculating the maximum value of the new energy consumption; inputting the new energy consumption into an intermediate variable transfer model to obtain a transfer variable, and inputting the transfer variable into an energy storage optimization configuration model and the intermediate variable transfer model to perform iterative calculation until the calculation requirement of a preset period is completed, and determining the new energy utilization rate; the intermediate variable transfer model is used for restraining the energy storage capacity and the running state of the unit; after the new energy utilization rate is determined to be inconsistent with the index requirement, an energy storage capacity calibration value is obtained, an accumulated value is calculated based on the energy storage capacity calibration value, iterative calculation is performed again by using the accumulated value until the new energy utilization rate is consistent with the index requirement, and a target energy storage capacity is output, so that reasonable energy storage capacity can be calculated in an optimized mode, and the configuration efficiency is improved.

Description

New energy source outgoing energy storage capacity accumulation type configuration method, device, equipment and medium

Technical Field

The application relates to the technical field of new energy power, in particular to a new energy output energy storage capacity accumulation type configuration method, device, equipment and medium.

Background

The new energy is the main driving force of the current power industry, has multiple advantages of environmental protection, reproducibility and the like, and brings with it a plurality of challenges, such as insufficient controllability, large volatility, limited regulation capability and the like. By effectively planning the energy storage capacity of the new energy, the new energy with unstable and large fluctuation can quickly and stably respond to the fluctuation of the power demand, thereby reducing unnecessary risks.

In the prior art, a calculation method for improving the planning efficiency of the energy storage capacity of large-scale new energy output is constructed to ensure that the utilization efficiency of the new energy is improved to the maximum extent and the cost of energy storage planning is reduced, and the calculation method generally predicts and plans the capacity based on historical operation data of an electric power system.

However, due to the random fluctuation characteristic of the new energy, in order to ensure that the calculation result is more in line with the actual situation and a more reasonable and effective result is obtained, the method needs to perform data analysis and calculation for a long period of time, and the solving time is long, so that the energy storage planning efficiency is greatly reduced.

Disclosure of Invention

The application provides a new energy outgoing energy storage capacity accumulation type configuration method, device, equipment and medium, which are used for solving the problems that the existing capacity is predicted and planned based on historical operation data of a power system, data analysis and calculation in a long time period are needed, the solving time is long, and the energy storage planning efficiency is greatly reduced.

In a first aspect, the present application provides a new energy output energy storage capacity accumulation configuration method, where the method includes:

acquiring an input energy storage capacity initial value, a target new energy utilization index, wind power theoretical output, photovoltaic theoretical output and a target power load, and inputting the energy storage capacity initial value and the target power load into an energy storage optimal configuration model constructed in advance to obtain new energy consumption of a first period; the target power load is the sum of the total power of the unit, the output of new energy and the charge-discharge power; the objective function of the energy storage optimal configuration model aims at calculating the maximum value of the new energy consumption; the energy storage optimal configuration model is used for restraining new energy output and power grid transmission requirements; the wind power theoretical output is used for limiting the upper limit of wind power output in the energy storage optimal configuration model; the photovoltaic theoretical output is used for limiting the upper limit of the photovoltaic output in the energy storage optimal configuration model;

Inputting the new energy consumption of the first period into an intermediate variable transmission model constructed in advance to obtain a transmission variable of the first period, and inputting the transmission variable of the first period into an energy storage optimal configuration model and the intermediate variable transmission model constructed in advance to perform iterative calculation until the calculation requirement of a preset period is completed to obtain a plurality of new energy consumption, wind power actual output and photovoltaic actual output in the preset period; the intermediate variable transfer model is used for restraining the energy storage capacity and the running state of the unit;

determining a new energy utilization rate based on the new energy consumption, the wind power actual output and the photovoltaic actual output, and acquiring an energy storage capacity calibration value after determining that the new energy utilization rate does not accord with the target new energy utilization rate index;

calculating the sum of the energy storage capacity calibration value and the energy storage capacity initial value to obtain an accumulated value, and carrying out iterative calculation again based on an energy storage optimal configuration model and an intermediate variable transfer model which are established in advance by the accumulated value until the obtained new energy utilization rate accords with the target new energy utilization rate index, and outputting the target energy storage capacity; the target energy storage capacity is an accumulated value.

Optionally, determining the new energy utilization rate based on the plurality of new energy consumption amounts, the wind power actual output and the photovoltaic actual output includes:

calculating the sum of a plurality of new energy consumption amounts in the preset period to obtain a new energy consumption total amount, calculating the sum of forces by utilizing a plurality of wind power actual forces and photovoltaic actual forces in the preset period to obtain a new energy output total amount, and calculating to obtain a new energy utilization rate based on the new energy consumption total amount and the new energy output total amount.

Optionally, the new energy output comprises wind power actual output and photovoltaic actual output; the construction process of the energy storage optimization configuration model comprises the following steps:

dividing a new energy power grid into a plurality of subareas, and setting a first constraint condition of new energy output of each subarea; the first constraint condition is that the actual wind power output of each partition is smaller than or equal to the theoretical wind power output, and the theoretical photovoltaic output of each partition is smaller than or equal to the theoretical photovoltaic output;

setting a second constraint condition of thermal power unit output, a third constraint condition of thermal power unit running state, a fourth constraint condition of pumped storage unit running state, a fifth constraint condition of pumped storage unit power, a sixth constraint condition of pumped storage unit storage capacity, a seventh constraint condition of lithium battery charge and discharge power, an eighth constraint condition of lithium battery charge and discharge depth and a ninth constraint condition of lithium battery energy storage capacity, and forming constraint conditions required by power grid transmission;

Constructing an energy storage optimization configuration model based on the first constraint condition and the constraint condition of the power grid transmission requirement;

the second constraint condition is used for constraining the optimized power of the thermal power generating unit; the third constraint condition is used for constraining the starting and/or stopping states of the plurality of units corresponding to the thermal power unit and the time of the plurality of units in the starting and/or stopping states; the fourth constraint condition is used for constraining the water pumping or discharging state of the water pumping energy storage unit; the fifth constraint condition is used for constraining the pumping power and the water discharging power of the pumped storage unit; the sixth constraint condition is used for constraining the capacity of the reservoir of the pumped storage unit; the seventh constraint condition is used for constraining the charging state and the discharging state of the lithium battery; the eighth constraint condition is used for constraining the residual electric quantity of the lithium battery; the ninth constraint condition is used for constraining the energy storage capacity of the lithium battery.

Optionally, the formula corresponding to the second constraint condition is:

0≤P _h (s,t,j)≤[TP _max (j)-TP _min (j)]·X(s,t,j)

TP(s,t,j)＝TP _min (j)·X(s,t,j)+P _h (s,t,j)

wherein TP _max (j) The upper limit of the output force of a j-th unit in the thermal power unit is represented; TP (Transmission protocol) _min (j) Representing thermal powerThe lower limit of the output force of the jth unit in the units; x (s, t, j) represents the running state of the jth unit in the thermal power unit at the jth period; TP (s, t, j) represents the output of the jth unit in the jth period at the t moment in the thermal power unit; p (P) _h (s, t, j) represents the optimized power of the jth unit in the thermal power unit at the jth period;

the formula corresponding to the third constraint condition is:

and, in addition, the method comprises the steps of,

Y(s,t,j)+Z(s,t+1,j)+Z(s,t+2,j)+...+Z(s,t+k,j)≤1

Z(s,t,j)+Y(s,t+1,j)+Y(s,t+2,j)+...+Y(s,t+k,j)≤1

wherein X (s, t, j) represents the running state of the jth unit in the thermal power unit at the jth period, 0 represents that the unit is shut down, and 1 represents that the unit is running; y (s, t, j) represents a starting state of a jth unit in a thermal power unit at a jth period, 0 represents a non-starting state, and 1 represents a starting state; z (s, t, j) represents a shutdown state of a jth unit in a thermal power unit at a jth period, 0 represents a non-shutdown state, and 1 represents a shutdown state; t+k represents the time t+k, k being the minimum time step of the start-up or stop of the unit.

Optionally, the formula corresponding to the fourth constraint condition is:

a(s,t,j)+b(s,t,j)≤1

wherein a (s, t, j) represents the pumping state of the jth unit in the pumping energy storage unit at the jth period; b (s, t, j) represents the water discharge state of the jth unit in the pump storage unit at the t moment;

the formula corresponding to the fifth constraint condition is:

wherein TP _CX (s, t, j) represents the optimized power of the jth unit in the pump storage unit at the jth period;representing the maximum pumping power of a jth unit in the pumping energy storage unit; / >Representing the minimum pumping power of a j-th unit in the pumping energy storage unit; />Representing the maximum water discharge power of a jth unit in the pumped storage unit;representing the minimum water discharge power of a jth unit in the pumped storage unit;

the formula corresponding to the sixth constraint condition is:

Cap _min (j)≤Cap _initial (s,t-1,j)-TP(s,t,j)≤Cap _max (j)

wherein, cap _max (j) Representing the upper limit of the capacity of a jth unit in the pumped storage unit; cap (Cap) _min (j) Representing the lower limit of the capacity of a jth unit in the pumped storage unit; cap (Cap) _initial (s, t, j) represents the initial capacity of the jth set of the pumped-storage set at the jth time of the jth period.

Optionally, the formula corresponding to the seventh constraint condition is:

c(s,t)+d(s,t)≤1

wherein c (s, t) represents a state of charge at the t-th moment of the s-th cycle of the battery pack, 0 represents a state of non-charge, and 1 represents a state of charge in progress; d (s, t) represents a discharge state at the t-th time of the s-th cycle of the battery pack, 0 represents a non-discharge state, and 1 represents a discharge state;representing the maximum charging power of the battery pack at the t-th moment; />Representing the maximum discharge power of the battery pack at the t-th moment; TP (Transmission protocol) _bat (s, t) represents the charge and discharge power of the battery pack at the t-th time of the s-th cycle;

the formula corresponding to the eighth constraint condition is:

SOC _min ≤SOC(t)≤SOC _max

wherein SOC is _min Representing the minimum value of the residual electric quantity of the battery pack; SOC (State of Charge) _max Representing the maximum value of the residual electric quantity of the battery pack; SOC (t) represents the residual capacity of the battery pack at the t-th moment; SOC (State of Charge) _min And SOC (System on chip) _max Determining according to an application scene;

the formula corresponding to the ninth constraint condition is:

E _min ≤E _bat ≤E _max

wherein E is _bat Representing the energy storage capacity of the battery pack; e (E) _min Representing the corresponding minimum energy storage capacity of the battery pack; e (E) _max Indicating the corresponding maximum energy storage capacity of the battery pack.

Optionally, the transmission variables comprise the optimized power of the thermal power unit, the running state of the thermal power unit, the optimized power of the pumped storage unit, the running state of the pumped storage unit, the initial storage capacity of the pumped storage unit, the charge and discharge power of the lithium battery and the initial capacity of the lithium battery; the construction process of the intermediate variable transfer model comprises the following steps:

setting the optimized power of the thermal power generating unit to meet a first preset condition, and setting the running state of the thermal power generating unit to meet a second preset condition; the first preset condition is that the optimized power of the thermal power unit in the current period is consistent with the optimized power of the thermal power unit output to the next period; the second preset condition is the running state, the stopping state and the starting state of each unit in the thermal power unit in the current period, and the running state, the stopping state and the starting state of each unit in the next period are consistent;

Setting the optimized power of the pumped storage unit to meet a third preset condition, setting the running state of the pumped storage unit to meet a fourth preset condition, and setting the initial storage capacity of the pumped storage unit to meet a fifth preset condition; the third preset condition is that the optimized power of the pumped storage unit in the current period is consistent with the optimized power of the pumped storage unit output to the next period; the fourth preset condition is the pumping state and the water discharging state of the pumping energy storage unit in the current period, and the pumping state and the water discharging state of the pumping energy storage unit in the period output to the next period are consistent; the fifth preset condition is that the initial storage capacity of the pumped storage unit in the current period is consistent with the initial storage capacity of the pumped storage unit output to the next period;

setting the charge and discharge power of the lithium battery to meet a sixth preset condition, and setting the initial capacity of the lithium battery to meet a seventh preset condition; the sixth preset condition is that the charge and discharge power of the lithium battery in the current period is consistent with the charge and discharge power of the lithium battery in the next period; the seventh preset condition is that the energy storage capacity of the lithium battery in the current period is consistent with the energy storage capacity of the lithium battery output to the next period;

And constructing an intermediate variable transfer model based on the first preset condition, the second preset condition, the third preset condition, the fourth preset condition, the fifth preset condition, the sixth preset condition and the seventh preset condition.

Optionally, the method further comprises:

and outputting an initial value of the energy storage capacity when the new energy utilization rate is determined to be in accordance with the target new energy utilization rate index.

In a second aspect, the present application provides a new energy delivery energy storage capacity accumulation configuration device, where the device includes:

the acquisition module is used for acquiring an input energy storage capacity initial value, a target new energy utilization index, wind power theoretical output, photovoltaic theoretical output and a target power load, and inputting the energy storage capacity initial value and the target power load into an energy storage optimal configuration model constructed in advance to obtain new energy consumption of a first period; the target power load is the sum of the total power of the unit, the output of new energy and the charge-discharge power; the objective function of the energy storage optimal configuration model aims at calculating the maximum value of the new energy consumption; the energy storage optimal configuration model is used for restraining new energy output and power grid transmission requirements; the wind power theoretical output is used for limiting the upper limit of wind power output in the energy storage optimal configuration model; the photovoltaic theoretical output is used for limiting the upper limit of the photovoltaic output in the energy storage optimal configuration model;

The input module is used for inputting the new energy consumption of the first period into an intermediate variable transfer model constructed in advance to obtain a transfer variable of the first period, and inputting the transfer variable of the first period into an energy storage optimal configuration model and the intermediate variable transfer model constructed in advance to perform iterative calculation until the calculation requirement of a preset period is completed to obtain a plurality of new energy consumption, wind power actual output and photovoltaic actual output in the preset period; the intermediate variable transfer model is used for restraining the energy storage capacity and the running state of the unit;

the determining module is used for determining new energy utilization rate based on the new energy consumption, the wind power actual output and the photovoltaic actual output, and acquiring an energy storage capacity calibration value after determining that the new energy utilization rate does not accord with the target new energy utilization rate index;

the accumulation module is used for calculating the sum of the energy storage capacity calibration value and the energy storage capacity initial value to obtain an accumulated value, and carrying out iterative calculation again based on an energy storage optimal configuration model and an intermediate variable transfer model which are established in advance on the basis of the accumulated value until the obtained new energy utilization rate accords with the target new energy utilization rate index, and outputting the target energy storage capacity; the target energy storage capacity is an accumulated value.

In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively coupled to the processor;

the memory stores computer-executable instructions;

the processor executes computer-executable instructions stored by the memory to implement the method of any one of the first aspects.

In a fourth aspect, the present application provides a computer-readable storage medium storing computer-executable instructions for implementing the method of any one of the first aspects when executed by a processor.

In summary, the application provides a new energy outgoing energy storage capacity accumulation configuration method, device, equipment and medium, which can check whether different energy storage capacities meet new energy utilization requirements time by time on the premise of giving initial energy storage capacity by taking the maximum value of new energy consumption as a target and continuously iterating the check to calculate the energy storage capacity meeting the given new energy utilization index through an energy storage optimal configuration model and an intermediate variable transfer model which are constructed in advance and comprise physical constraints on a plurality of units; the method for optimizing the energy storage capacity through the two model designs ensures that the model operation results are more in line with the actual conditions, and meanwhile, the more reasonable energy storage capacity can be optimized and calculated, and the efficiency of planning and configuring the capacity is remarkably improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.

Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present application;

fig. 2 is a schematic flow chart of a new energy output energy storage capacity accumulation configuration method according to an embodiment of the present application;

fig. 3 is a schematic flow chart of a specific new energy output energy storage capacity accumulation configuration method provided in an embodiment of the present application;

fig. 4 is a schematic structural diagram of a new energy output energy storage capacity accumulating configuration device according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Specific embodiments thereof have been shown by way of example in the drawings and will herein be described in more detail. These drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments.

Detailed Description

In order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second", etc. are used to distinguish the same item or similar items having substantially the same function and effect. For example, the first device and the second device are merely for distinguishing between different devices, and are not limited in their order of precedence. It will be appreciated by those of skill in the art that the words "first," "second," and the like do not limit the amount and order of execution, and that the words "first," "second," and the like do not necessarily differ.

In this application, the terms "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.

In the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a alone, a and B together, and B alone, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b, or c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.

The new energy is the main driving force of the current power industry, has multiple advantages of environmental protection, renewable performance and the like, however, the new energy also brings non-negligible challenges, such as insufficient controllability, large volatility, limited regulation capacity and the like. By effectively planning the energy storage capacity of the new energy, the new energy with unstable and large fluctuation can quickly and stably respond to the fluctuation of the power demand, and unnecessary risks are reduced.

However, the configuration and planning of the energy storage system are complex engineering problems, and face the problems of multiple influencing factors, large data volume and the like, which provide great challenges for system computing resources, planning work efficiency and effects, so that an urgent need exists to construct an efficient computing method so as to ensure that the utilization efficiency of new energy sources is improved to the maximum extent and reduce the cost of energy storage planning.

In one possible implementation, the configuration of the energy storage system is performed by constructing a calculation method for improving the planning efficiency of the energy storage capacity delivered by the large-scale new energy source, and the calculation method generally predicts and plans the capacity based on historical operation data of the electric power system.

It will be appreciated that long periods of data analysis calculations can lead to substantial reductions in model planning efficiency.

Aiming at the problems, the application provides a new energy source output energy storage capacity accumulation type configuration method, which is based on an accumulation type time-by-time iteration calculation method of energy storage capacity planning efficiency to configure the energy storage capacity; specifically, through an energy storage optimization configuration model and an intermediate variable transfer model which are constructed in advance and comprise physical constraints on a plurality of units, on the premise of giving initial energy storage capacity, taking the maximum value of new energy consumption as a target, checking whether different energy storage capacities meet the requirement of new energy utilization rate or not time by time, and continuously iterating the check to calculate the energy storage capacity meeting the given new energy utilization rate index; the method for optimizing the energy storage capacity through the two model designs ensures that the model operation results are more in line with the actual conditions, and meanwhile, the more reasonable energy storage capacity can be optimized and calculated, and the efficiency of planning and configuring the capacity is remarkably improved.

Exemplary, fig. 1 is a schematic diagram of an application scenario provided in an embodiment of the present application, where, as shown in fig. 1, the application scenario may be applied to large-scale new energy output energy storage capacity planning; the application scene comprises: a user's terminal device 101 and a data processing system 102; wherein, the data processing system 102 is provided with an energy storage optimization configuration model and an intermediate variable transfer model which are constructed in advance; the energy storage optimal configuration model is used for restraining new energy output and power grid transmission requirements and aims at the maximum new energy consumption; the intermediate variable transfer model is used for restraining the energy storage capacity and the running state of the unit.

Specifically, taking an example of constructing an energy storage optimization configuration model including optimizing physical constraints such as a thermal power unit, a pumped storage unit, a lithium battery and the like time by time, the terminal equipment 101 of a user can input an initial value of energy storage capacity and a new energy utilization index, and further, after receiving the initial energy storage capacity and the new energy utilization index, the data processing system 102 inputs the initial energy storage capacity into the energy storage optimization configuration model and an intermediate variable model to check whether the energy storage capacities of different lithium batteries meet the new energy utilization index time by time; the method comprises the steps of inputting initial energy storage capacity into an energy storage optimal configuration model to obtain new energy consumption of a first week, inputting the new energy consumption of the first week into an intermediate variable transmission model to obtain a transmission variable of the first week, further inputting the transmission variable of the first week into the energy storage optimal configuration model and the intermediate variable transmission model to obtain a transmission variable of a second week, and so on, continuously iterating calculation, repeating calculation until the annual calculation is completed, and further checking whether the new energy utilization rate obtained by calculation is smaller than a new energy utilization rate index; if yes, adding a certain amount of energy storage capacity, and continuing to perform iterative calculation until the calculated new energy utilization rate meets the new energy utilization rate index, namely, the new energy utilization rate index is greater than or equal to the new energy utilization rate index, and further, outputting a target energy storage capacity meeting the new energy utilization rate index, wherein the target energy storage capacity is more economic energy storage capacity.

The new energy utilization index is the new energy utilization rate meeting the application scene and the user requirement and is used for determining the output target energy storage capacity.

It should be noted that, in the embodiment of the present application, the period for calculating the new energy consumption and the transmission variable each time is not particularly limited, and may be one week, two weeks or one month; alternatively, the preset period of the iterative calculation may be one year, or may be one quarter or two years, which is not specifically limited in the embodiment of the present application, and the foregoing is merely an example.

Optionally, after the data processing system 102 outputs the target energy storage capacity, it may be sent to the user's terminal device 101 for visual display.

Alternatively, the Terminal device may be various electronic devices having a display screen and supporting web browsing, and the Terminal device may also be referred to as a Terminal (Terminal), a User Equipment (UE), a Mobile Station (MS), a Mobile Terminal (MT), or the like. The terminal device may be a mobile phone, a smart television, a wearable device, a smart speaker, a smart security device, a smart gateway, a tablet computer (Pad), a computer with wireless transceiving function, a Virtual Reality (VR) terminal device, an augmented Reality (Augmented Reality, AR) terminal device, a wireless terminal in industrial control (industrial control), a wireless terminal in self-driving (self-driving), a wireless terminal in teleoperation (remote medical surgery), a wireless terminal in smart grid (smart grid), a wireless terminal in transportation security (transportation safety), a wireless terminal in smart city (smart city), a wireless terminal in smart home (smart home), etc. Such terminal devices include, but are not limited to, smartphones, tablet computers, laptop portable computers, desktop computers, and the like.

The following describes the technical solutions of the present application and how the technical solutions of the present application solve the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 2 is a flow chart of a new energy outgoing energy storage capacity accumulation type configuration method provided in an embodiment of the present application, as shown in fig. 2, an execution main body of the new energy outgoing energy storage capacity accumulation type configuration method is a data processing system, and the new energy outgoing energy storage capacity accumulation type configuration method includes the following steps:

s201, acquiring an input energy storage capacity initial value, a target new energy utilization index, wind power theoretical output, photovoltaic theoretical output and a target power load, and inputting the energy storage capacity initial value and the target power load into an energy storage optimal configuration model constructed in advance to obtain new energy consumption of a first period; the target power load is the sum of the total power of the unit, the output of new energy and the charge-discharge power; the objective function of the energy storage optimal configuration model aims at calculating the maximum value of the new energy consumption; the energy storage optimal configuration model is used for restraining new energy output and power grid transmission requirements; the wind power theoretical output is used for limiting the upper limit of wind power output in the energy storage optimal configuration model; the photovoltaic theoretical output is used for limiting the upper limit of the photovoltaic output in the energy storage optimal configuration model.

In this embodiment of the present application, the objective function targets the maximum new energy consumption, and the corresponding formula is:

f(s)＝max{grossnewenergy(s)}

wherein f(s) represents an objective function; grossnewenergy(s) the grid-connected total power of the new energy source, namely the total power of the power grid, in each period; new energy output at the t moment of the s-th period of the nth partition is represented by new energy (s, t, n); the value of t is 1-168, namely the corresponding time is one week; the period refers to one week, and may also refer to other predefined periods, which are not specifically limited in the embodiments of the present application.

It should be noted that partitioning refers to dividing a power grid into a plurality of areas according to a predefined rule; the predefined rules may refer to different locations of the areas, different power requirements, etc., which are not specifically limited in the embodiments of the present application.

In this step, the data processing system may obtain an initial value of the energy storage capacity manually entered And determining new energy utilization index eta to be reached _set As a condition of loop calculation for judging whether the flow is continued; the new energy utilization index is set according to the following formula:

Σnewernergy (s, t, n) represents the total new energy consumption of the base energy storage system, namely the sum of new energy output; theoryNewenergy (s, t, n) represents the nth partition at the s-th week Theoretical new energy output at the t-th moment; η (eta) _set And the set new energy utilization index is indicated.

Further, acquiring a wind power theoretical output force (s, t, n) input by a user as an output upper limit of wind power per hour in an energy storage optimal configuration model; obtaining a photovoltaic theoretical output force input by a user:

TheoryPVpower(s,t,n)，

the theoretical output of the photovoltaic is used as the upper limit of output of the photovoltaic per hour in the energy storage optimal configuration model; furthermore, a target power Load (s, t, n) is required to be set and used as the Load quantity required by each hour in the energy storage optimal configuration model, the data are further input into the energy storage optimal configuration model, the computer is used for carrying out simulation calculation on the data of the first period, the output of each unit is ensured to be within the constraint range, and the new energy consumption quantity of the first period is calculated and obtained; the formula corresponding to the target power load is as follows:

newenergy(s,t,n)＝Load(s,t,n)-TP _gross (s,t,n)-TP _bat (s,t,n)

wherein TP _gross (s, t, n) represents the total power of the units at the time t of the s-th period of the nth partition, namely the sum of the total power of all conventional units; load (s, t, n) represents a target power Load at the time t of the s-th cycle of the n-th partition; TP (Transmission protocol) _bat (s, t, n) represents the charge/discharge power at the time t of the nth section s-th cycle.

It should be noted that all conventional units may refer to thermal power units, pumped storage units, and units in lithium batteries.

Alternatively, considering the transmission power between the areas of the partitions, the power load balance must be partition balanced in the unit of area, and the balance equation is given by:

TP _gross (s,t,n)+newenergy(s,t,n)+Linepower(s,t,i)+TP _bat (s,t,n)＝Load(s,t,n)

wherein, lineface (s, t, i) represents the transmission capacity of the ith transmission line in the s-th period of the nth partition, namely the transmission power; and the transmission capacity constraint between regions is expressed by the following equation:

-Linepower _max (i)≤Linepower(i)≤Linepower _max (i)

-Linepower _max (i) Representing the lower limit of the transmission power of the ith transmission line; linepower _max (i) Representing the upper limit of the transmission power of the ith transmission line; linepower (i) represents the transmission power of the ith transmission line, and is considered to be generated when the load is applied to the outside and when the load is applied to the inside.

Therefore, the energy storage optimal configuration model needs to meet the load curve constraint, namely the load curve of the power generated by the clean energy base, the grid sink power and the channel; wherein, the net sinking power is positive; the network sink power is transmission power transmitted between the plurality of partitions.

S202, inputting the new energy consumption of the first period into an intermediate variable transfer model constructed in advance to obtain a transfer variable of the first period, and inputting the transfer variable of the first period into an energy storage optimal configuration model and the intermediate variable transfer model constructed in advance to perform iterative calculation until the calculation requirement of a preset period is completed to obtain a plurality of new energy consumption, wind power actual output and photovoltaic actual output in the preset period; the intermediate variable transfer model is used for restraining the energy storage capacity and the running state of the unit.

In the embodiment of the application, the transmission variables include the optimized power of the thermal power unit, the running state of the thermal power unit, the optimized power of the pumped storage unit, the running state of the pumped storage unit, the initial storage capacity of the pumped storage unit, the charge and discharge power of the lithium battery and the initial capacity of the lithium battery; the optimized power may refer to an adjustable optimized power compared to a real transmission power; the operating conditions may include a shutdown condition, an on-operating condition, an off-start condition, an on-start condition, a shutdown condition, and an on-shutdown condition.

The preset period is a time period preset in advance for calculating new energy consumption so as to meet scene requirements, and specific numerical values corresponding to the preset period are not limited in the embodiment of the application, for example, the preset period can be one year; the first period may refer to a period of one week, and be the first week, or may refer to a first period of a preset period of time, such as the first month, which is not specifically limited in the embodiment of the present application.

In the step, the new energy consumption of the first period is input into an intermediate variable transmission model constructed in advance, a computer is used for extracting data variables such as an operation state, an energy storage capacity and the like which need to be transmitted, the consistency of annual operation of the unit is ensured through the transmission of the transmission variables, and correspondingly, the transmission variables can be stored for output.

Further, the stored transfer variables are input into an energy storage optimal configuration model, and the iterative computation of S201-S202 is repeated by a computer by combining the previous known parameter limits, namely the wind power theoretical output, the photovoltaic theoretical output and the target power load until the computation requirement of a preset period, such as the data simulation computation requirement of the whole year, is completed, so that the data of new energy consumption, the wind power actual output, the photovoltaic actual output and the like of each period of the whole year are obtained.

And S203, determining a new energy utilization rate based on the new energy consumption, the wind power actual output and the photovoltaic actual output, and acquiring an energy storage capacity calibration value after determining that the new energy utilization rate does not accord with the target new energy utilization rate index.

In this embodiment of the present application, the energy storage capacity calibration value is a certain amount of energy storage capacity, and a specific value corresponding to the energy storage capacity calibration value is preset in advance.

In the step, the annual new energy consumption is calculated according to the obtained annual new energy consumption in each period, and the annual new energy theoretical output sum is calculated based on the annual wind power actual output and the photovoltaic actual output, further, the annual new energy utilization rate is calculated according to the annual new energy total consumption and the annual new energy theoretical output sum, namely the new energy utilization rate eta, which is the new energy utilization rate calculated in a time-by-time iterative mode.

Further, checking the new energy utilization rate, i.e. checking whether the new energy utilization rate accords with the set target new energy utilization rate index eta _set The method comprises the steps of carrying out a first treatment on the surface of the If the bar is not satisfiedParts, i.e. eta < eta _set Acquiring the energy storage capacity calibration value delta E _bat 。

S204, calculating the sum of the energy storage capacity calibration value and the energy storage capacity initial value to obtain an accumulated value, and carrying out iterative calculation again based on an energy storage optimal configuration model and an intermediate variable transfer model which are established in advance on the basis of the accumulated value until the obtained new energy utilization rate meets the target new energy utilization rate index, and outputting the target energy storage capacity; the target energy storage capacity is an accumulated value.

In this step, the energy storage capacity E to be currently planned _bat On the basis of (a) a certain amount of energy storage capacity calibration value delta E is increased _bat Obtaining accumulated values, i.e.If the accumulated value is the sum of the energy storage capacity calibration value and the initial value of the energy storage capacity, i.e. +.>Further, a +>Inputting the energy storage capacity as a new set into the S201 again, repeating the S201-S202, and continuing to carry out loop iteration verification until the condition eta is more than or equal to eta is met _set The obtained new energy utilization rate accords with the target new energy utilization rate index, and then the target energy storage capacity is output, namely the finally planned energy storage capacity is finished, and the cycle is ended.

Therefore, the embodiment of the application aims at the maximum new energy consumption, performs time-by-time simulation iterative verification on the energy storage configuration capacity, can obtain the target energy storage capacity meeting the given new energy utilization rate, greatly improves the planning efficiency, and enables the energy storage capacity configuration planning to be more reasonable.

In the step, the sum of a plurality of new energy consumption amounts in a preset period is calculated, and a formula corresponding to the total new energy consumption amount is obtained as follows:

grossnewenergy＝∑newenergy(s,t,n)

the gross new energy represents the total amount of new energy consumption, and further, the sum of the forces is calculated by utilizing a plurality of wind power actual forces and photovoltaic actual forces in a preset period, and a formula corresponding to the total sum of the new energy forces is obtained as follows:

TheoryNewenergy'(s,t,n)＝Windpower(s,t,n)+PVpower(s,t,n)

grossTNew＝∑TheoryNewenergy(s,t,n)

Wherein grossTNew represents the sum of new energy output, the fourth (s, t, n) represents the actual new energy output at the t-th moment of the s-th period of the nth partition, and Windpower (s, t, n) represents the actual wind power output at the t-th moment of the s-th period of the nth partition; PVpower (s, t, n) represents the actual photovoltaic output at time t of the s-th cycle of the n-th zone.

Further, a formula corresponding to the new energy utilization rate obtained based on calculation of the total new energy consumption amount and the total new energy output amount is as follows:

therefore, the embodiment of the application can iteratively calculate the new energy utilization rate time by time, so that the calculation result is more in line with the actual situation, and the calculation accuracy is further improved.

In the embodiment of the application, the new energy output is constrained according to the theoretical output curve of the new energy actual output less than or equal to the new energy output on the premise of known premise, namely

0≤Windpower(s,t,n)≤TheoryWindpower(s,t,n)

0≤PVpower(s,t,n)≤TheoryPVpower(s,t,n)

The Windpower (s, t, n) represents the actual wind power output at the t moment of the s-th period of the nth partition; PVpower (s, t, n) represents the actual photovoltaic output at time t of the s-th cycle of the n-th partition; the TheoryWinddpower (s, t, n) represents the theoretical wind power output at the t moment of the s-th period of the nth partition; the photovoltaic power (s, t, n) represents the photovoltaic theoretical output at the t moment of the s-th period of the nth partition; it should be noted that, the wind power theoretical output and the photovoltaic theoretical output are known values, and specific values corresponding to the values are not limited in the embodiment of the present application.

In the step, the output constraint of the thermal power unit, namely the constraint on the optimized power of the thermal power unit is carried out; by the specific expression of the total power of the conventional aggregate: TP (s, t, j) =tp _min (j)·X(s，t，j)+P _h (s, t, j) the expression for optimizing power can be derived as: TP (s, t, j) -TP _min (j)·X(s，t，j)＝P _h (s, t, j), further, constraint is applied to the upper and lower limits of the optimized power, and the second constraint condition corresponds to the constraint.

Optionally, the formula corresponding to the second constraint condition is:

0≤P _h (s,t,j)≤[TP _max (j)-TP _min (j)]·X(s,t,j)

TP(s,t,j)＝TP _min (j)·X(s,t,j)+P _h (s,t,j)

wherein TP _max (j) The upper limit of the output force of a j-th unit in the thermal power unit is represented; TP (Transmission protocol) _min (j) The lower limit of the output force of a j-th unit in the thermal power unit is represented; x (s, t, j) represents the running state of the jth unit in the thermal power unit at the jth period; TP (s, t, j) represents the output of the jth unit in the jth period at the t moment in the thermal power unit; p (P) _h And (s, t, j) represents the optimized power of the jth unit in the jth period.

Constraint is carried out on the start-stop state logic of the thermal power unit and the minimum start-stop time of the thermal power unit, and a third constraint condition is correspondingly adopted; the formula corresponding to the third constraint condition is:

and, in addition, the method comprises the steps of,

Y(s,t,j)+Z(s,t+1,j)+Z(s,t+2,j)+...+Z(s,t+k,j)≤1

Z(s,t,j)+Y(s,t+1,j)+Y(s,t+2,j)+...+Y(s,t+k,j)≤1

wherein X (s, t, j) represents the running state of the jth unit in the thermal power unit at the jth period, 0 represents that the unit is shut down, and 1 represents that the unit is running; y (s, t, j) represents a starting state of a jth unit in a thermal power unit at a jth period, 0 represents a non-starting state, and 1 represents a starting state; z (s, t, j) represents a shutdown state of a jth unit in a thermal power unit at a jth period, 0 represents a non-shutdown state, and 1 represents a shutdown state; and t+k represents the time t+k, k is the minimum time step of starting or stopping the machine set, k is a preset value in advance, and the specific numerical value corresponding to k is not limited in the embodiment of the application.

Therefore, the energy storage optimization configuration model can better optimize the energy storage capacity by restraining the optimized power of the thermal power generating unit, the starting and/or stopping states of the plurality of units corresponding to the thermal power generating unit and the time of the plurality of units in the starting and/or stopping states, and planning is more reasonable, so that the expected effect is achieved.

Furthermore, in order to meet the power grid transmission requirement, the energy storage system further needs to restrict the pumped storage unit, namely the pumping or water discharging state of the pumped storage unit, the pumping power and the water discharging power of the pumped storage unit and the capacity of a reservoir of the pumped storage unit.

Specifically, the pumping or water discharging state of the pumped storage unit is restrained, namely the logic state of pumping water is restrained, and the fourth restraint condition is correspondingly adopted.

Optionally, the formula corresponding to the fourth constraint condition is:

a(s,t,j)+b(s,t,j)≤1

wherein a (s, t, j) represents the pumping state of the jth unit in the pumping energy storage unit at the jth period; b (s, t, j) represents the water discharge state of the jth unit in the pump storage unit at the jth period.

And the pumping power and the water discharge power of the pumped storage unit are restrained, and a fifth restraint condition is correspondingly adopted.

Optionally, the formula corresponding to the fifth constraint condition is:

wherein TP _CX (s, t, j) represents the optimized power of the jth unit in the pump storage unit at the jth period;representing the maximum pumping power of a jth unit in the pumping energy storage unit; />Representing the minimum pumping power of a j-th unit in the pumping energy storage unit; />Representing the maximum water discharge power of a jth unit in the pumped storage unit;and the minimum water discharge power of a j-th unit in the pumped storage units is shown.

It should be noted that, the maximum pumping power, the minimum pumping power, the maximum water discharge power and the minimum water discharge power are preset values in advance according with practical application scenes, and the specific values corresponding to the values are not limited in the embodiment of the present application.

And (3) restraining the capacity of the reservoir of the pumped storage unit, and correspondingly, a sixth constraint condition.

Optionally, the formula corresponding to the sixth constraint condition is:

Cap _min (j)≤Cap _initial (s,t-1,j)-TP(s,t,j)≤Cap _max (j)

It should be noted that, the upper capacity limit and the lower capacity limit are preset values in advance, which conform to the actual application scenario, and the specific values corresponding to the values are not limited in the embodiment of the present application.

Therefore, the energy storage optimization configuration model can better optimize the energy storage capacity through constraining the pumping and water discharging states, pumping power, water discharging power and the capacity of the pumping energy storage unit reservoir, and planning is more reasonable so as to achieve the expected effect.

Furthermore, in order to meet the power grid transmission requirement, the embodiment of the application also needs to carry out energy storage constraint on the lithium battery, namely, constraint on the charging state, the discharging state and the residual electric quantity of the lithium battery as well as the energy storage capacity of the lithium battery.

Specifically, the charging state and the discharging state of the lithium battery are constrained, namely, the charging and discharging power of the lithium battery is constrained, and a seventh constraint condition is correspondingly adopted.

Optionally, the formula corresponding to the seventh constraint condition is:

c(s,t)+d(s,t)≤1

wherein c (s, t) represents a state of charge at the t-th moment of the s-th cycle of the battery pack, 0 represents a state of non-charge, and 1 represents a state of charge in progress; d (s, t) represents a discharge state at the t-th time of the s-th cycle of the battery pack, 0 represents a non-discharge state,1 represents a discharging state;representing the maximum charging power of the battery pack at the t-th moment; />Representing the maximum discharge power of the battery pack at the t-th moment; TP (Transmission protocol) _bat (s, t) represents the charge and discharge power at the t-th time of the s-th cycle of the battery. />

It should be noted that, the maximum charging power and the maximum discharging power are preset values in advance, which conform to the actual application scenario, and the specific values corresponding to the values are not limited in the embodiment of the present application.

And constraining the residual electric quantity of the lithium battery, namely constraining the charge and discharge depth of the lithium battery, and correspondingly, an eighth constraint condition.

Optionally, the formula corresponding to the eighth constraint condition is:

SOC _min ≤SOC(t)≤SOC _max

wherein SOC is _min Representing the minimum value of the residual electric quantity of the battery pack; SOC (State of Charge) _max Representing the maximum value of the residual electric quantity of the battery pack; SOC (t) represents the residual capacity of the battery pack at the t-th moment; SOC (State of Charge) _min And SOC (System on chip) _max According to the application scene determination, the specific numerical values corresponding to the application are not limited.

And restraining the energy storage capacity of the lithium battery, and correspondingly, a ninth constraint condition.

Optionally, the formula corresponding to the ninth constraint condition is:

E _min ≤E _bat ≤E _max

It should be noted that, the minimum energy storage capacity and the maximum energy storage capacity are preset values in advance, which are in accordance with practical application scenarios, and the specific values corresponding to the values are not limited in the embodiment of the present application.

Therefore, the embodiment of the application can ensure that the energy storage optimization configuration model optimizes the energy storage capacity better by restraining the charging state, the discharging state, the residual electric quantity and the energy storage capacity of the lithium battery, and calculates the energy storage capacity which is more economical, so that the planning is more reasonable, and the expected effect is achieved.

In some embodiments, the energy storage at the moment of electricity rejection is also constrained, since the total electricity rejection power is equal to the theoretical new energy output minus the actual new energy output, i.e.:

Abandonedpower(s,t,n)＝TheoryNewenergy(s,t,n)-newenergy(s,t,n)

therefore, the constraint conditions for constraining the energy storage only at the time of discarding electricity are:

-TP _bat (t)≤TheoryNewenergy(s,t,n)

wherein, abandonedpower (s, t, n) represents the total power of the energy storage system of the base.

In summary, the energy storage optimization configuration model is constructed through the first constraint condition and the constraint condition of the power grid transmission requirement, so that the running condition of the model can be ensured to be more in line with the actual condition, the feasibility of the model is improved, and the energy storage capacity is optimized and calculated more reasonably than other algorithms.

In this embodiment of the present application, the process for constructing the intermediate variable transfer model includes: the method comprises the steps of setting the transmission process of the optimized power of the thermal power unit, setting the transmission process of the start-stop state of the thermal power unit, setting the transmission process of the optimized power of the pumped storage unit, setting the transmission process of the pumped storage capacity of the pumped storage unit, setting the transmission process of the charge-discharge power of the lithium battery and setting the transmission process of the energy storage capacity of the lithium battery.

Specifically, since the thermal power unit is limited by climbing constraint, that is, the output of the thermal power unit cannot be greatly suddenly changed within a certain period of time, in order to ensure the continuity of unit operation, the optimized power participated by the thermal power unit in the current period can be stored and output to the next period for consideration and calculation of the next period, that is:

P _hZ (s,t,j)＝P _h (s,t,j)

wherein P is _hZ (s, t, j) represents that the optimized power of the last cycle of the thermal power generating unit is output to the optimized power of the jth unit at the t moment of the current cycle, and the optimized power is stored for calling.

Because the thermal power unit is limited by the physical characteristics of the unit, the energy consumption of the unit and the operation cost in the operation process, the unit can not be started and stopped frequently, and therefore, the two start and stop operations of the same unit need to be separated by a certain time, and the constraint of the minimum start and stop time of the thermal power unit needs to be considered.

In some embodiments, the thermal power generating unit operation state of the previous cycle is output to the present cycle through a transmission variable, and is used in consideration and calculation of the next cycle, namely:

wherein X (s+1, t, j) represents the operation state of the jth unit at the (t) th time of the (s+1) th period, namely the operation state of the jth unit output to the next period; y (s+1, t, j) represents the starting state of the jth machine set at the jth moment in the (s+1) th period, namely the starting state of the jth machine set at the jth moment output to the next period; z (s+1, t, j) represents the shutdown state of the jth unit at the (t) th period of the (s+1) th period, namely, the shutdown state of the jth unit output to the next period at the (t) th period.

Since the transfer function of pumped storage is related to the storage capacity, if the last time of the previous period is 168, the last time of the previous period is 165, further, the output of the last time of the previous period is subtracted from the remaining storage capacity of the last time of the previous period, and the remaining storage capacity of the last time of the previous period is equal to the storage capacity of the initial time of the s+1 period, in order to ensure the continuity of unit operation, the optimized power participated by the pumped storage unit of the previous period can be stored and output to the present period, so as to call and calculate, namely:

TP _CXZ (s+1,t,j)＝TP _CX (s,t,j)

wherein TP _CX (s, t, j) represents the optimized power of the jth unit in the pump storage unit at the jth period; TP (Transmission protocol) _CXZ (s, t, j) represents the optimized power output of the jth unit in the pumped storage unit in the previous period to the present period, and correspondingly, TP _CXZ (s+1, t, j) represents the optimized power output to the jth unit of the next cycle at the time t, and is stored for recall.

Because the pumped storage unit is limited by the physical characteristics of the unit, the energy consumption of the unit and the running cost in the running process, the unit can not be started and stopped frequently, and therefore, the two start and stop operations of the same unit need to be separated by a certain time, and the constraint of the minimum start and stop time of the pumped storage unit needs to be considered.

In some embodiments, the pump-around unit operating state of the previous cycle is output to the present cycle by passing the variable for use in consideration and calculation of the next cycle, namely:

a _Z (s+1,t,j)＝a(s,t,j)

b _Z (s+1,t,j)＝b(s,t,j)

wherein a (s, t, j) represents the pumping state of the jth unit in the pumping energy storage unit at the jth period; a, a _Z (s, t, j) represents that the pumping state of the jth unit in the pumping energy storage unit in the previous period is output to the period, and correspondingly, a _Z (s+1, t, j) represents the pumping state of the jth machine set at the t moment output to the jth machine set in the next period, and stores the pumping state for calling; b (s, t, j) represents the water discharge state of the jth unit in the pumped storage unit at the jth period, b _Z (s, t, j) represents that the water discharge state of the jth unit in the pumping energy storage unit in the previous period is output to the period, and correspondingly, b _Z (s+1, t, j) represents the output to the followingAnd the water discharge state of the jth machine set at the t moment of one period is stored for calling.

Further, a transfer process of setting the pumped storage reservoir capacity comprises the following steps:

Cap _initialZ (s+1,t,j)＝Cap _initial (s,t,j)

wherein, cap _initial (s, t, j) represents the initial capacity of the jth unit in the pump storage unit at the jth period and the t moment, cap _initialZ (s, t, j) represents the initial storage capacity output in the pumped storage unit of the previous period to the current period, and corresponds to Cap _initialZ (s+1, t, j) represents the state of water discharged at the t-th moment of the j-th unit output to the next cycle, and stores it for calling.

Further, a transfer process of the charge and discharge power of the lithium battery is set, comprising:

TP _batZ (s+1,t)＝TP _bat (s,t)

wherein TP _bat (s, t) represents the charge and discharge power at the t moment of the s-th period, namely the energy storage output; TP (Transmission protocol) _batZ (s, t) represents the charge-discharge power output of the previous cycle to the present cycle, corresponding to TP _batZ (s+1, t) represents the charge-discharge power output to the t-th time of the next cycle, and is stored for recall.

Further, a transfer process for setting the energy storage capacity of the lithium battery includes:

E _batZ (s+1,t)＝E _bat (s,t)

E _bat (s, t) represents the energy storage capacity of the lithium battery at the t-th moment of the s-th period; e (E) _batZ (s, t) represents the energy storage capacity of the previous period to be output to the present period, corresponding to E _batZ (st+1, t) represents the energy storage capacity output to the t-th time of the next cycle, and is stored for recall.

Therefore, the embodiment of the application sets up the transfer process of the optimized power of the thermal power unit, the start-stop state of the thermal power unit, the optimized power of the pumped storage unit, the pumping water logic state of the pumped storage unit, the pumped storage capacity of the pumped storage unit, the charge and discharge power of the lithium battery and the energy storage capacity of the lithium battery, builds the intermediate variable transfer model, ensures the continuity that the thermal power unit, the pumped storage unit and the units in the lithium battery can run across the period, and improves the running stability.

Optionally, the method further comprises:

In the step, if the calculated annual new energy utilization rate eta meets the condition, namely eta is more than or equal to eta _set And outputting the currently planned energy storage capacity as the finally planned energy storage capacity to finish the optimization process.

Optionally, after the final planned energy storage capacity is obtained, the energy storage capacity may be visually displayed for the user to view or apply.

Therefore, the embodiment of the application can be configured to obtain reasonable energy storage capacity, and the capacity planning and configuration efficiency is improved.

In combination with the foregoing embodiments, fig. 3 is a schematic flow chart of a specific new energy outgoing energy storage capacity accumulation configuration method provided in the embodiments of the present application, as shown in fig. 3, where the new energy outgoing energy storage capacity accumulation configuration method includes the following steps:

step 1: an energy storage optimization configuration model (model 1) and an intermediate variable transfer model (model 2) are built in advance, and an energy storage initial value (energy storage capacity initial value), parameter limitation and a new energy utilization index (target new energy utilization index) are set.

Step 2: the data are input into the model 1, the computer is used for carrying out simulation calculation on the data of the first period, the output of each unit is ensured to be within the constraint range, and the new energy consumption of the first period is obtained through calculation.

Step 3: and (3) inputting the data in the step (2) into a model (2), extracting data variables such as an operation state, an energy storage capacity and the like which need to be transmitted by using a computer, ensuring the consistency of annual operation of the unit through the transmission of the transmission variables, and storing the transmission variables for output.

Step 4: and (3) inputting the data stored in the step (3) into the model (1), and repeating the iterative computation of the step (2) and the step (3) by using a computer in combination with parameter limits set in advance until the annual data simulation computation is completed, so as to obtain the new energy consumption of each period of the whole year.

Step 5: and (3) calculating the annual new energy consumption and annual new energy theoretical output sum according to the annual new energy consumption in each period obtained in the step (4), and calculating the ratio of the annual new energy consumption to the annual new energy theoretical output sum to obtain the new energy utilization rate.

Step 6: judging whether the new energy utilization rate meets the condition, if so, outputting the final energy storage capacity and the new energy utilization rate; if not, adding a certain amount of energy storage capacity (energy storage capacity calibration value) to obtain an accumulated value, inputting the accumulated value into the step 2 again, and repeating the steps to continue the loop iteration calibration until the condition is met; the condition may be set such that the new energy utilization is greater than or equal to the target new energy utilization index.

Compared with the traditional optimization calculation method, by utilizing the new energy output energy storage capacity accumulation type configuration method, the running time and the memory occupation can be reduced, and as shown in the table 1, the calculation efficiency and the calculation result of the traditional optimization calculation method and the calculation result of the method are compared.

TABLE 1

	Example 1	EXAMPLE 2
			Calculation time(s)	17317.158	79.056
Memory occupation (k bit)	816230.4	227532.8
			Results-planning Capacity (MW, h)	1125	1270
results-New energy utilization ratio of day-to-day operation according to planned energy storage	81.4％	81.9％
			Results-percentage increase in New energy utilization compared to random Access energy storage operation	10％	10.4％

In the method of the present application, as shown in table 1, on the premise of ensuring the optimization quality, compared with the conventional optimization calculation method, the method of the present application greatly reduces the operation time and the memory occupation, thereby improving the operation efficiency, and also improving the optimization quality.

In the foregoing embodiments, the new energy output energy storage capacity accumulation configuration method provided in the embodiments of the present application is described, and in order to implement each function in the method provided in the embodiments of the present application, an electronic device as an execution body may include a hardware structure and/or a software module, and each function may be implemented in the form of a hardware structure, a software module, or a hardware structure and a software module. Some of the functions described above are performed in a hardware configuration, a software module, or a combination of hardware and software modules, depending on the specific application of the solution and design constraints.

For example, fig. 4 is a schematic structural diagram of a new energy output energy storage capacity accumulation configuration device according to an embodiment of the present application, where the device 400 includes: an acquisition module 401, an input module 402, a determination module 403 and an accumulation module 404; the obtaining module 401 is configured to obtain an input energy storage capacity initial value, a target new energy utilization index, a wind power theoretical output, a photovoltaic theoretical output and a target power load, and input the energy storage capacity initial value and the target power load into an energy storage optimization configuration model constructed in advance to obtain new energy consumption of a first period; the target power load is the sum of the total power of the unit, the output of new energy and the charge-discharge power; the objective function of the energy storage optimal configuration model aims at calculating the maximum value of the new energy consumption; the energy storage optimal configuration model is used for restraining new energy output and power grid transmission requirements; the wind power theoretical output is used for limiting the upper limit of wind power output in the energy storage optimal configuration model; the photovoltaic theoretical output is used for limiting the upper limit of the photovoltaic output in the energy storage optimal configuration model;

the input module 402 is configured to input the new energy consumption of the first period into an intermediate variable transmission model that is built in advance, obtain a transmission variable of the first period, and input the transmission variable of the first period into an energy storage optimization configuration model and an intermediate variable transmission model that are built in advance to perform iterative computation until a computation requirement of a preset period is completed, so as to obtain a plurality of new energy consumption, wind power actual output and photovoltaic actual output in the preset period; the intermediate variable transfer model is used for restraining the energy storage capacity and the running state of the unit;

The determining module 403 is configured to determine a new energy utilization rate based on the plurality of new energy consumption amounts, the wind power actual output and the photovoltaic actual output, and obtain an energy storage capacity calibration value after determining that the new energy utilization rate does not conform to the target new energy utilization rate index;

the accumulation module 404 is configured to calculate a sum of the energy storage capacity calibration value and an energy storage capacity initial value to obtain an accumulated value, and perform iterative calculation again based on an energy storage optimal configuration model and an intermediate variable transfer model that are constructed in advance on the basis of the accumulated value until the obtained new energy utilization rate meets the target new energy utilization rate index, and output a target energy storage capacity; the target energy storage capacity is an accumulated value.

Optionally, the determining module 403 is specifically configured to:

Optionally, the new energy output comprises wind power actual output and photovoltaic actual output; the device 400 further comprises a construction module of an energy storage optimization configuration model; the building module of the energy storage optimization configuration model is used for:

Optionally, the formula corresponding to the second constraint condition is:

0≤P _h (s,t,j)≤[TP _max (j)-TP _min (j)]·X(s,t,j)

TP(s,t,j)＝TP _min (j)·X(s,t,j)+P _h (s,t,j)

wherein TP _max (j) The upper limit of the output force of a j-th unit in the thermal power unit is represented; TP (Transmission protocol) _min (j) The lower limit of the output force of a j-th unit in the thermal power unit is represented; x (s, t, j) represents the running state of the jth unit in the thermal power unit at the jth period; TP (s, t, j) represents the output of the jth unit in the jth period at the t moment in the thermal power unit; p (P) _h (s, t, j) represents the optimized power of the jth unit in the thermal power unit at the jth period;

the formula corresponding to the third constraint condition is:

and, in addition, the method comprises the steps of,

Y(s,t,j)+Z(s,t+1,j)+Z(s,t+2,j)+...+Z(s,t+k,j)≤1

Z(s,t,j)+Y(s,t+1,j)+Y(s,t+2,j)+...+Y(s,t+k,j)≤1

Optionally, the formula corresponding to the fourth constraint condition is:

a(s,t,j)+b(s,t,j)≤1

The formula corresponding to the fifth constraint condition is:

/>

wherein TP _CX (s, t, j) represents the optimized power of the jth unit in the pump storage unit at the jth period;representing the maximum pumping power of a jth unit in the pumping energy storage unit; />Representing the minimum pumping power of a j-th unit in the pumping energy storage unit; />Representing the maximum water discharge power of a jth unit in the pumped storage unit;representing the minimum water discharge power of a jth unit in the pumped storage unit;

the formula corresponding to the sixth constraint condition is:

Cap _min (j)≤Cap _initial (s,t-1,j)-TP(s,t,j)≤Cap _max (j)

Optionally, the formula corresponding to the seventh constraint condition is:

c(s,t)+d(s,t)≤1

wherein c (s, t) represents a state of charge at the t-th moment of the s-th cycle of the battery pack, 0 represents a state of non-charge, and 1 represents a state of charge in progress; d (s, t) represents a discharge state at the t-th time of the s-th cycle of the battery pack, 0 represents a non-discharge state, and 1 represents a discharge state;representing the maximum charging power of the battery pack at the t-th moment; / >Representing the maximum discharge power of the battery pack at the t-th moment; TP (Transmission protocol) _bat (s, t) represents the charge and discharge power of the battery pack at the t-th time of the s-th cycle;

the formula corresponding to the eighth constraint condition is:

SOC _min ≤SOC(t)≤SOC _max

wherein SOC is _min Representing the minimum value of the residual electric quantity of the battery pack; SOC (State of Charge) _max Indicating the most residual capacity of the battery packA large value; SOC (t) represents the residual capacity of the battery pack at the t-th moment; SOC (State of Charge) _min And SOC (System on chip) _max Determining according to an application scene;

the formula corresponding to the ninth constraint condition is:

E _min ≤E _bat ≤E _max

Optionally, the transmission variables comprise the optimized power of the thermal power unit, the running state of the thermal power unit, the optimized power of the pumped storage unit, the running state of the pumped storage unit, the initial storage capacity of the pumped storage unit, the charge and discharge power of the lithium battery and the initial capacity of the lithium battery; the apparatus 400 further includes a building module for an intermediate variable transfer model; the construction module of the intermediate variable transfer model is used for:

Optionally, the apparatus 400 further comprises an output module; the output module is used for:

The specific implementation principle and effect of the new energy output energy storage capacity accumulation type configuration device provided in the embodiment of the present application can be referred to the relevant description and effect corresponding to the above embodiment, and will not be repeated here.

The embodiment of the application also provides a schematic structural diagram of an electronic device, and fig. 5 is a schematic structural diagram of an electronic device provided in the embodiment of the application, as shown in fig. 5, the electronic device may include: a processor 501 and a memory 502 communicatively coupled to the processor; the memory 502 stores a computer program; the processor 501 executes the computer program stored in the memory 502, so that the processor 501 performs the method described in any one of the embodiments above.

Wherein the memory 502 and the processor 501 may be connected by a bus 503.

Embodiments of the present application also provide a computer-readable storage medium storing computer program execution instructions that, when executed by a processor, are configured to implement a method as described in any of the foregoing embodiments of the present application.

The embodiment of the application also provides a chip for executing instructions, wherein the chip is used for executing the method in any of the previous embodiments executed by the electronic equipment in any of the previous embodiments of the application.

Embodiments of the present application also provide a computer program product comprising a computer program which, when executed by a processor, performs a method as described in any of the preceding embodiments of the present application, as performed by an electronic device.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules is merely a logical function division, and there may be additional divisions of actual implementation, e.g., multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.

The modules illustrated as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

In addition, each functional module in each embodiment of the present application may be integrated in one processing unit, or each module may exist alone physically, or two or more modules may be integrated in one unit. The units formed by the modules can be realized in a form of hardware or a form of hardware and software functional units.

The integrated modules, which are implemented in the form of software functional modules, may be stored in a computer readable storage medium. The software functional modules described above are stored in a storage medium and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or processor to perform some of the steps of the methods described in various embodiments of the present application.

It should be appreciated that the processor may be a central processing unit (Central Processing Unit, CPU for short), other general purpose processors, digital signal processor (Digital Signal Processor, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present application may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.

The Memory may include a high-speed random access Memory (Random Access Memory, abbreviated as RAM), and may further include a Non-volatile Memory (NVM), such as at least one magnetic disk Memory, and may also be a U-disk, a removable hard disk, a read-only Memory, a magnetic disk, or an optical disk.

The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, the buses in the drawings of the present application are not limited to only one bus or one type of bus.

The storage medium may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random-Access Memory (SRAM), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read Only Memory, EEPROM), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.

An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuits, ASIC for short). It is also possible that the processor and the storage medium reside as discrete components in an electronic device or a master device.

It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all alternative embodiments, and that the acts and modules referred to are not necessarily required in the present application.

It should be further noted that, although the steps in the flowchart are sequentially shown as indicated by arrows, the 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 a portion of the steps in the flowcharts may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order in which the sub-steps or stages are performed is not necessarily sequential, and may be performed in turn or alternately with at least a portion of the sub-steps or stages of other steps or other steps.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments. The technical features of the foregoing embodiments may be arbitrarily combined, and for brevity, all of the possible combinations of the technical features of the foregoing embodiments are not described, however, all of the combinations of the technical features should be considered as being within the scope of the disclosure.

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

The foregoing is merely a specific implementation of the embodiments of the present application, but the protection scope of the embodiments of the present application is not limited thereto, and any changes or substitutions within the technical scope disclosed in the embodiments of the present application should be covered by the protection scope of the embodiments of the present application. Therefore, the protection scope of the embodiments of the present application shall be subject to the protection scope of the claims.

Claims

1. The method for configuring the accumulation type energy storage capacity of new energy source delivery is characterized by comprising the following steps:

2. The method of claim 1, wherein determining a new energy utilization based on the plurality of new energy consumption amounts, the wind power actual output, and the photovoltaic actual output comprises:

3. The method of claim 1, wherein the new energy output comprises a wind power actual output and a photovoltaic actual output; the construction process of the energy storage optimization configuration model comprises the following steps:

4. A method according to claim 3, wherein the second constraint corresponds to the formula:

0≤P _h (s,t,j)≤[TP _max (j)-TP _min (j)]·X(s,t,j)

TP(s,t,j)＝TP _min (j)·X(s,t,j)+P _h (s,t,j)

the formula corresponding to the third constraint condition is:

and, in addition, the method comprises the steps of,

Y(s,t,j)+Z(s,t+1,j)+Z(s,t+2,j)+...+Z(s,t+k,j)≤1

Z(s,t,j)+Y(s,t+1,j)+Y(s,t+2,j)+...+Y(s,t+k,j)≤1

5. A method according to claim 3, wherein the fourth constraint corresponds to the formula:

a(s,t,j)+b(s,t,j)≤1

the formula corresponding to the fifth constraint condition is:

the formula corresponding to the sixth constraint condition is:

Cap _min (j)≤Cap _initial (s,t-1,j)-TP(s,t,j)≤Cap _max (j)

wherein, cap _max (j) Representing the upper limit of the capacity of a jth unit in the pumped storage unit; cap (Cap) _min (j) Representing the lower limit of the capacity of a jth unit in the pumped storage unit; cap (Cap) _initial (s, t, j) represents the jth period t of the jth unit in the pumped storage unitInitial capacity of the etch.

6. A method according to claim 3, wherein the seventh constraint corresponds to the formula:

c(s,t)+d(s,t)≤1

wherein c (s, t) represents a state of charge at the t-th moment of the s-th cycle of the battery pack, 0 represents a state of non-charge, and 1 represents a state of charge in progress; d (s, t) represents a discharge state at the t-th time of the s-th cycle of the battery pack, 0 represents a non-discharge state, and 1 represents a discharge state; Representing the maximum charging power of the battery pack at the t-th moment; />Representing the maximum discharge power of the battery pack at the t-th moment; TP (Transmission protocol) _bat (s, t) represents the charge and discharge power of the battery pack at the t-th time of the s-th cycle;

the formula corresponding to the eighth constraint condition is:

SOC _min ≤SOC(t)≤SOC _max

the formula corresponding to the ninth constraint condition is:

E _min ≤E _bat ≤E _max

7. The method of claim 1, wherein the transfer variables comprise an optimal power of the thermal power generation unit, an operational state of the thermal power generation unit, an optimal power of the pumped storage unit, an operational state of the pumped storage unit, an initial storage capacity of the pumped storage unit, a charge-discharge power of the lithium battery, and an initial capacity of the lithium battery; the construction process of the intermediate variable transfer model comprises the following steps:

8. The method according to any one of claims 1-7, further comprising:

9. A new energy delivery energy storage capacity accumulation type configuration device, characterized in that the device comprises:

10. An electronic device, comprising: a processor, and a memory communicatively coupled to the processor;

the memory stores computer-executable instructions;

the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1-8.

11. A computer readable storage medium storing computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-8.