CN110048421B

CN110048421B - Energy storage device capacity selection method and device

Info

Publication number: CN110048421B
Application number: CN201910438088.8A
Authority: CN
Inventors: 李思亮; 杨洋; 严宁; 齐睿; 裴俊
Original assignee: Windmagics Wuhan Co ltd
Current assignee: Windmagics Wuhan Co ltd
Priority date: 2019-05-24
Filing date: 2019-05-24
Publication date: 2020-11-13
Anticipated expiration: 2039-05-24
Also published as: CN110048421A

Abstract

The embodiment of the invention provides a method and a device for selecting the capacity of an energy storage device. The method comprises the following steps: acquiring historical load data and historical electricity price data of each charging period, and respectively acquiring the maximum energy storage benefit of each charging period after each energy storage device with selectable capacity is added according to a pre-established benefit model, the historical load data and the historical electricity price data of each charging period; for each optional capacity, acquiring the maximum total annual income after the energy storage device with the optional capacity is added according to the maximum energy storage income of each charging period after the energy storage device with the optional capacity is added, and acquiring the total cost for deploying the energy storage device with the optional capacity; and selecting one selectable capacity as a selection result according to preset conditions according to the maximum total annual income after the energy storage device with each selectable capacity is added and the total cost for deploying the energy storage device with each selectable capacity. The method and the device for selecting the capacity of the energy storage device can obtain a more accurate capacity selection result.

Description

Energy storage device capacity selection method and device

Technical Field

The invention relates to the technical field of electric power, in particular to a method and a device for selecting capacity of an energy storage device.

Background

The energy storage device is widely applied to the fields of power generation, power transmission and distribution and user side in a power system. The access of the energy storage device in the power grid plays a crucial role in both peak clipping and valley filling and power grid planning and development. The user side is connected with the energy storage device, so that the capacity planned by the power distribution network side can be reduced, the demand electric charge and the electric quantity electric charge of the user are reduced, and the reliability of power supply is enhanced. The energy storage device is mainly used for managing the electric charge and helps a user to reduce the required electric charge and the electric quantity and the electric charge so as to reduce the total expenditure of the electric charge of the user. The energy storage devices on the consumer side are present in the power grid in both the load-acting operating mode (charging) and the generator-acting operating mode (discharging). In general, the consumer-side energy storage device is operated in a load mode during low load periods and in a generator mode during high load periods. Due to the existence of the peak-valley electricity price, the energy storage device on the user side can perform charging and discharging operation in different periods of time so as to reduce the expense of the user for purchasing electricity.

The current user side energy storage profit mode comprises peak-valley price difference profit, capacity electricity charge management, demand side response, power supply reliability improvement and the like, wherein the peak-valley price difference profit is a main profit mode of most user side energy storage projects, and the peak-valley price difference is greatly influenced by regions and policies. The peak-valley electricity price policy guides the user to actively participate in the electricity demand response through the price lever, the user can actively select to use more electricity in the electricity price low-valley period, and use less electricity in the electricity price peak period, so that the peak clipping and valley filling effects are achieved, and the electricity peak-load demand is reduced.

For the function evaluation of the user-side energy storage device access, the economic benefit after the user-side energy storage device access is generally evaluated so as to evaluate the superiority of the energy storage device. The selection of the capacity of the energy storage device is generally based on the economic benefits generated by accessing energy storage devices of different capacities. However, economic benefits are closely linked to the operating strategy of the energy storage device, and the benefits produced by the energy storage device can only be maximized when the operating strategy is optimized. The prior art cannot obtain the long-term optimal operation strategy of the energy storage device, and generally obtains the long-term (such as one year or several years) economic benefit evaluation result by obtaining the typical 24-hour optimal operation strategy of the energy storage device to evaluate the daily economic benefit. Therefore, a typical 24-hour optimal operation strategy obtained in the prior art may be only a local optimal scheme, but not a global optimal scheme, which results in poor accuracy of an evaluation result of the obtained long-term economic benefit, and further results in that a proper energy storage device capacity cannot be selected, so that the economic benefit actually generated by the energy storage device cannot reach an expectation and resources are wasted.

Disclosure of Invention

The embodiment of the invention provides a method and a device for selecting the capacity of an energy storage device, which are used for overcoming or at least partially overcoming the defect of low accuracy of the conventional method for selecting the capacity of the energy storage device.

In a first aspect, an embodiment of the present invention provides a method for selecting a capacity of an energy storage device, including:

acquiring historical load data and historical electricity price data of each charging period, and respectively acquiring the maximum energy storage benefit of each charging period after each energy storage device with selectable capacity is added according to a pre-established benefit model, the historical load data and the historical electricity price data of each charging period;

for each optional capacity, acquiring the maximum total annual income after the energy storage device with the optional capacity is added according to the maximum energy storage income of each charging period after the energy storage device with the optional capacity is added, and acquiring the total cost for deploying the energy storage device with the optional capacity;

selecting a selectable capacity as a selection result according to a preset condition according to the maximum total annual income after each energy storage device with the selectable capacity is added and the total cost for deploying each energy storage device with the selectable capacity;

the profit model takes the energy storage profit of each charging period after the energy storage device is added as a target to be maximized; the energy storage income comprises demand electric charge income and electric quantity electric charge income.

Preferably, the specific step of obtaining the maximum energy storage benefit of each charging period after the energy storage device with each selectable capacity is added according to the benefit model, the historical load data and the historical electricity price data of each charging period includes:

for any charging period after the energy storage device with any optional capacity is added, acquiring initial maximum power and maximum charging and discharging duration according to any optional capacity, and acquiring the minimum value of the maximum actual load of any charging period after the energy storage device is added according to the initial maximum power and the maximum charging and discharging duration so as to maximize the required electricity charge gain of any charging period;

taking the minimum value of the maximum actual load of the energy storage device in any charging period as the initialization condition of the profit model, and obtaining the time sequence of the charging and discharging power of the energy storage device in any charging period according to the particle swarm algorithm and the profit model so as to maximize the energy storage profit of any charging period;

and acquiring the maximum energy storage benefit of any charging period after the energy storage device with any optional capacity is added according to the time sequence of the charging and discharging power of the energy storage device in any charging period.

Preferably, the time sequence of the charging and discharging power of the energy storage device in any charging period is obtained according to the particle swarm algorithm and the profit model, so that the specific step of maximizing the energy storage profit in any charging period comprises:

if the result of the last iteration according to the particle swarm optimization is judged and known to be in local convergence, optimizing the result of the last iteration, so that the residual electric quantity of the energy storage device at the starting time point and the residual electric quantity of the energy storage device at the ending time point of unit time of the local convergence before and after optimization are the same, and the load after the energy storage device is added in the unit time does not exceed the minimum value of the maximum actual load of any charging period after the energy storage device is added;

and performing the iteration according to the optimized result of the last iteration.

Preferably, the specific steps of obtaining the initial maximum power and the maximum charge-discharge time according to any one of the selectable capacities include:

acquiring initial maximum power and initial maximum charge-discharge duration according to any optional capacity; the product of the initial maximum power and the initial maximum charge-discharge time length is equal to any optional capacity;

and acquiring the maximum charging and discharging time according to the initial maximum charging and discharging time, a preset annual attenuation rate and the number of years of adding the energy storage device corresponding to any charging period.

Preferably, for each optional capacity, the specific step of obtaining the maximum total annual revenue after the energy storage device with the optional capacity is added according to the maximum energy storage revenue in each charging period after the energy storage device with the optional capacity is added includes:

acquiring the annual maximum benefit of the energy storage device with the selectable capacity according to the maximum energy storage benefit of each charging period after the energy storage device with the selectable capacity is added;

and taking the sum of the annual maximum benefits of the energy storage devices with the selectable capacity as the maximum annual total benefit of the energy storage devices with the selectable capacity.

Preferably, the specific step of obtaining the annual maximum profit of the energy storage device with the selectable capacity according to the maximum energy storage profit of each charging period after the energy storage device with the selectable capacity is added includes:

for each year after the energy storage device with the optional capacity is added, acquiring the average value of the maximum energy storage income of each charging period included in each year after the energy storage device with the optional capacity is added;

and taking the product of the average value and the number of the charging periods included in each year as the maximum profit of each year after the energy storage device with the selectable capacity is added.

Preferably, for each selectable capacity, the specific step of obtaining the total cost of deploying the energy storage devices of the selectable capacity comprises:

and acquiring the total cost for deploying the energy storage device with the optional capacity according to the manufacturing cost of the unit capacity and the optional capacity.

In a second aspect, an embodiment of the present invention provides an energy storage device capacity selection apparatus, including:

the charging period income acquisition module is used for acquiring historical load data and historical electricity price data of each charging period and respectively acquiring the maximum energy storage income of each charging period after each energy storage device with selectable capacity is added according to a pre-established income model, the historical load data and the historical electricity price data of each charging period;

the total profit total cost obtaining module is used for obtaining the maximum total profit of the whole year after the energy storage device with the selectable capacity is added according to the maximum energy storage profit of each charging period after the energy storage device with the selectable capacity is added for each selectable capacity, and obtaining the total cost of deploying the energy storage device with the selectable capacity;

the energy storage device capacity selection module is used for selecting a selectable capacity as a selection result according to a preset condition according to the maximum total annual income after each energy storage device with the selectable capacity is added and the total cost for deploying each energy storage device with the selectable capacity;

In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when executing the computer program, the method for selecting a capacity of an energy storage device according to any one of the various possible implementations of the first aspect is implemented.

In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the energy storage device capacity selection method as provided in any one of the various possible implementations of the first aspect.

According to the method and the device for selecting the capacity of the energy storage device, provided by the embodiment of the invention, the time sequence of the charging and discharging power of the energy storage device in the charging period, which enables the user side to obtain the maximum energy storage benefit of each charging period, is obtained, the maximum energy storage benefit of each charging period after the energy storage device with the selectable capacity is added is obtained, and the more accurate maximum energy storage benefit and long-term benefit (the maximum total benefit of the whole year) of each charging period can be obtained, so that the more appropriate capacity of the energy storage device can be selected, and the capacity of the energy storage device which meets the requirements of the user can be selected.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

Fig. 1 is a schematic flow chart of a method for selecting a capacity of an energy storage device according to an embodiment of the present invention;

fig. 2 is a schematic structural diagram of an energy storage device capacity selection device according to an embodiment of the invention;

fig. 3 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In order to overcome the above problems in the prior art, embodiments of the present invention provide a method and an apparatus for selecting a capacity of an energy storage device, where an energy storage device is assumed to be added at a user side at a certain historical time, and based on a historical load, a full-time operation strategy of the energy storage device (a whole charging cycle rather than a certain period of time in the charging cycle) is obtained by obtaining a full-time operation strategy of the energy storage device after the energy storage device is added at the user side and satisfying a constraint condition, so as to obtain a maximum total yield of all years of different energy storage capacities, and thus, an energy storage device with a suitable capacity is selected according to the maximum total yield of all years and a total deployment cost of the energy storage devices with different selectable capacities, and can be added at the current time or.

Fig. 1 is a schematic flow chart of a method for selecting a capacity of an energy storage device according to an embodiment of the present invention. As shown in fig. 1, the method includes: step S101, obtaining historical load data and historical electricity price data of each charging period, and respectively obtaining the maximum energy storage benefit of each charging period after each energy storage device with selectable capacity is added according to a pre-established benefit model, the historical load data and the historical electricity price data of each charging period.

The profit model takes the energy storage profit of each charging period after the energy storage device is added to the maximum as a target; the energy storage profit comprises demand electric power profit and electric quantity electric power profit.

Specifically, the energy storage benefit refers to the reduced electricity charge expenditure after the user side adds the energy storage device.

For the jth charging period (abbreviated as 'jth charging period') after the energy storage device is added, the energy storage income is the required electric charge income S₁And electric quantity and electric charge profit S₂Sum, denoted as R_j。

R_j＝S₁+S₂

The demand electric charge refers to the electric charge measured according to the maximum actual load in the charging period. Therefore, the demand charges profit S₁The gains obtained for reducing the maximum actual load in the billing cycle by adding an energy storage device.

The electric quantity and the electric charge refer to the electric charge measured according to the total electric quantity in the charging period. Because the existing loads on the user side are charged according to the demand electric charge mode, the electric quantity and the electric charge income S can be obtained by reasonably utilizing the peak-to-valley electric charge price difference by controlling the charging and discharging of the energy storage device₂。

For the jth charging period, under the condition that the energy storage device can be charged and discharged in the charging period in the whole period, the influence of the historical load and the charging and discharging power of the energy storage device in the whole period in the charging period is considered, and the required electric charge profit S₁And electric quantity and electric charge profit S₂Are respectively calculated as

Wherein the content of the first and second substances,

the unit of the discharge and charge power (referred to as "charge and discharge power") of the energy storage device at the ith time in the charging period can be kW,

indicating that the energy storage device is discharging,

indicating charging of the energy storage device; alpha represents the unit price of the demand electric charge, the unit is yuan/kW, for example, the value of alpha can be 38 yuan/kW;

indicating the historical load (simply referred to as "historical load") of the user side at the ith moment in the charging period; e.g. of the type_iThe unit price of the electricity quantity and the electricity charge at the ith moment is expressed in unit of yuan/kW.h; m represents the total number of time instants within the charging period.

The charging period is generally month; the time interval between two adjacent moments in the charging period is typically 15 minutes. For example, in the case of a billing period of month (in 30 days) and a time interval of hours, m is 24 × 4 × 30 is 2880.

The unit price of the electricity amount and the electricity fee is the time-of-use electricity price, that is, the peak-to-valley electricity price.

For the jth billing cycle, the profit model maximizes the energy storage profit R_jFor targeting, the objective function of the revenue model is max (R)_j)。

It should be noted that the capacity of the energy storage device is related to the maximum value of the historical load, and the capacity of the energy storage device limits the charging and discharging power and the charging and discharging time of the energy storage device, so that for each optional capacity, the profit model is optimally solved according to the historical load data and the historical electricity price data of each charging period, and the time sequence of the charging and discharging power of the energy storage device in the charging period and the maximum energy storage profit of the charging period after the energy storage device with the optional capacity is added are obtained. And the energy storage device performs charging and discharging in the charging period according to the acquired time sequence of the charging and discharging power of the energy storage device in the charging period, and the user side can obtain the maximum energy storage benefit of the charging period after the energy storage device with the optional capacity is added.

And S102, for each optional capacity, acquiring the maximum total annual income after the energy storage device with the optional capacity is added according to the maximum energy storage income of each charging period after the energy storage device with the optional capacity is added, and acquiring the total cost for deploying the energy storage device with the optional capacity.

Specifically, for each optional capacity, after obtaining the maximum energy storage benefit of each charging period after the energy storage device with the optional capacity is added, the maximum total benefit of the energy storage device with the optional capacity up to now may be obtained according to the maximum energy storage benefit of each charging period after the energy storage device with the optional capacity is added, and the maximum total benefit of the energy storage device with the optional capacity up to now may be obtained as the maximum total benefit of the whole year.

Since energy storage devices can operate for long periods of time and are relatively costly, long term gains, such as years of gains, are generally considered.

According to the maximum energy storage income of each charging period after the energy storage device with the selectable capacity is added, the maximum energy storage income of each charging period can be directly summed to obtain the maximum total income of the energy storage device with the selectable capacity to the present, and any suitable data processing method can be adopted to process the maximum energy storage income of each charging period so as to obtain the maximum total income of the energy storage device with the selectable capacity to the present. In this regard, the embodiments of the present invention are not particularly limited.

For each selectable capacity, a total cost of deploying the energy storage devices of the selectable capacity may be obtained from the selectable capacity.

And S103, selecting a selectable capacity as a selection result according to preset conditions according to the maximum total annual income after each selectable capacity energy storage device is added and the total cost for deploying each selectable capacity energy storage device.

Specifically, one selectable capacity from the selectable capacities may be selected as a result of the energy storage device capacity selection based on preset conditions, a maximum total yearly revenue after adding the energy storage devices of the selectable capacities, and a total cost of deploying the energy storage devices of the selectable capacities.

The preset conditions can be determined according to actual needs, for example: the net profit (which means the total profit minus the total cost) of a given term (e.g. 10 years) is the maximum, the profit rate of a given term is the maximum, or the profit is realized fastest, and the preset rules are not particularly limited by the embodiment of the present invention.

According to the embodiment of the invention, the time sequence of the charging and discharging power of the energy storage device in the charging period, which enables the user side to obtain the maximum energy storage profit of each charging period, is obtained, the maximum energy storage profit of each charging period after the energy storage device with the optional capacity is added is obtained, and the maximum energy storage profit and the long-term profit (the maximum total income over the years) of each charging period can be obtained more accurately, so that the more appropriate capacity of the energy storage device can be selected, and the capacity of the energy storage device which meets the requirements of the user better can be selected.

Based on the content of the above embodiments, the specific step of obtaining the maximum energy storage benefit of each charging period after adding the energy storage device with each selectable capacity according to the benefit model, the historical load data of each charging period and the historical electricity price data includes: for any charging period after the energy storage device with any optional capacity is added, the initial maximum power and the maximum charging and discharging time length are obtained according to any optional capacity, and the minimum value of the maximum actual load of any charging period after the energy storage device is added is obtained according to the initial maximum power and the maximum charging and discharging time length, so that the required electric charge income of any charging period is maximum.

In particular, for any optional capacity W_maxIn order to obtain the maximum energy storage benefit of the jth charging period, the minimum value of the maximum actual load DCT of any charging period after the energy storage device is added is obtained first, so that the required energy charge benefit of the charging period is maximum.

It will be appreciated that if the meter is usedThe historical load at the ith time in the fee cycle is

Because the energy storage device is added, the charging and discharging power of the energy storage device at the ith moment is

Therefore, after the energy storage device is added, the actual load on the user side at the ith moment is

Due to the fact that

Is determined that the capacity of the energy storage device is W_maxIt is also determined that optimization can achieve

When minimum value of

When the minimum value is taken, the demand electric charge profit S₁And max.

The objective function to obtain the minimum DCT is min (DCT | P)_d,P_max,H_max,n)。

Wherein the content of the first and second substances,

a time series representing the historical load of the billing cycle; p_maxRepresents the initial maximum power; h_max,nRepresents a maximum charge-discharge time period; n indicates that the charging period belongs to the nth year after the energy storage device with the optional capacity is added.

Initial maximum power P_max(the positive and negative values are not considered to respectively represent discharging and charging, and only the absolute value is taken), the rated power of the energy storage device is generally 10-40% of the maximum historical load; the maximum charging and discharging duration refers to the maximum duration of charging of the energy storage device under the initial maximum power.

The capacity of the energy storage device limitsCharge and discharge power and duration of the energy storage device, and thus, according to the selectable capacity W_maxSeveral sets of initial maximum power and maximum charge-discharge duration may be obtained. And respectively obtaining the minimum value of the DCT according to each group of initial maximum power and the maximum charging and discharging duration.

Two constraint conditions are provided for obtaining the minimum DCT, and the constraint condition 1 is that the maximum charge-discharge power larger than the DCT cannot exceed P_max(ii) a Constraint 2 is that neither the initial remaining capacity nor the end remaining capacity of any one discharge process (peak clipping) can exceed the limit of the selectable capacity.

It can be understood that the value range of DCT is min (P)_d) To max (P)_d) In the meantime. Wherein, min (P)_d) Finger-shaped

Minimum value of (d), max (P)_d) Finger-shaped

Maximum value of (2).

The operational logic for obtaining the objective function of the minimum DCT includes:

calculate DCT and max (P)_d) The start and stop points therebetween and the required discharge amount;

calculating the maximum residual capacity before discharging, namely the maximum residual capacity of full-load charging in a chargeable period;

and calculating the residual capacity after the single discharge process is finished.

For obtaining the objective function with the minimum DCT, initialization is required first. At initialization, P is added_dAverage value of (i.e. of)

Average of) as an input, the output value being equal to the input value if both of the above two constraints are satisfied; if either of the two constraints is not satisfied, adding a penalty term exceeding the two constraints to the original objective function to output an output value larger than the input value.

According to the initialized objective function, a conjugate gradient method can be adopted to obtain the minimum value of DCT, namely the optimal DCT.

And taking the minimum value of the maximum actual load of any charging period after the energy storage device is added as an initialization condition of the profit model, and acquiring a time sequence of the charging and discharging power of the energy storage device in any charging period according to the particle swarm algorithm and the profit model so as to maximize the energy storage profit of any charging period.

Specifically, for any charging period, the minimum value of the DCT obtained in the above steps is used as an initialization condition of the revenue model.

It will be appreciated that the initialization conditions for the revenue model also include

I.e. neither charging nor discharging.

For the jth charging period (belonging to the nth year after the energy storage device is added), the profit model maximizes the energy storage profit R_jFor targeting, the objective function of the revenue model is max (R)_j)。

The initial condition is that the energy storage device is full at the moment of assumption 0.

SOC₀＝W_n＝P_max×h_max,n

Therein, SOC₀Representing the electric quantity of the energy storage device at the time of the charging period 0; w_nRepresenting the actual capacity of the energy storage device during the billing period.

The optimal solution of the profit model can be obtained by adopting a particle swarm algorithm, and the time sequence of the charging and discharging power of the energy storage device in the charging period is optimized, so that the energy storage profit of the charging period is the maximum.

The constraint conditions of the profit model include actual load constraint, State of Charge (SOC) constraint, and maximum power constraint.

And actual load constraint refers to that the actual load cannot be greater than a load threshold DCT in the optimization process. In the final result, the priority of the demand electric charge and the income is higher than that of the electric quantity and the electric charge and the income.

Load threshold

The remaining capacity constraint refers to the remaining capacity SOC of the energy storage device at any time i (i-th time)_i(State of Charge, SOC) is between 0 and W_nIn between, i.e

0＜SOC_i≤W_n

SOC when energy storage device is charged_i＝SOS_i-1-P_i ^bΔt

When the energy storage device is discharged

Where Δ t represents the time period between two adjacent moments, typically 1 hour.

Maximum power constraint, meaning that the maximum power charged and discharged is within the design range of the accumulator of the energy storage device, i.e.

Adopting any Particle Swarm Optimization (PSO) to carry out maximization solution on the objective function of the profit model to obtain

The optimal solution of (1). Will be provided with

The initial values are 0 for each particle, all particles have an optimum value determined by the optimization function, and each particle has a velocity that determines its direction and distance of change.

For example, a coordinated evolution particle swarm algorithm may be adopted, and other particle swarm algorithms may also be adopted, which is not specifically limited in this embodiment of the present invention.

Since the revenue model contains constraint conditions, the model containing the constraints needs to be transformed into a model without the constraints by using a penalty function method for optimization solution. For the penalty function method, any external penalty function method may be employed.

In the PSO optimizing process, the particle updating points are always ensured to meet the constraint conditions of the revenue model, so that the searching time in the calculation feasible domain is reduced.

Specifically, the time series of the charging and discharging power of the energy storage device in the charging period is obtained, and the time series of the charging and discharging power of the energy storage device in the charging period, the historical load data and the historical electricity price data are substituted into the calculation formula of the energy storage benefit of the charging period, so that the maximum energy storage benefit of the charging period can be obtained.

According to the embodiment of the invention, the minimum value of the maximum actual load is obtained first, the electricity fee income of the required quantity is fixed, and the electricity fee income of the electric quantity is optimized on the basis, so that the maximum energy storage income of the charging period is obtained, the maximum energy storage income and the long-term income (maximum total income of the whole year) of each charging period can be more accurately obtained, and therefore, more appropriate energy storage device capacity can be selected, and the energy storage device capacity which is more in line with the requirement of a user is selected.

Based on the content of each embodiment, according to the particle swarm algorithm and the profit model, the time sequence of the charging and discharging power of the energy storage device in any charging period is obtained, so that the specific steps of maximizing the energy storage profit in any charging period comprise: if the result of the last iteration according to the particle swarm optimization is judged and known to be in local convergence, the result of the last iteration is optimized, so that the residual electric quantity of the energy storage device at the starting time point and the residual electric quantity of the energy storage device at the ending time point of unit time of the local convergence before and after optimization are the same, and the load after the energy storage device is added in the unit time does not exceed the minimum value of the maximum actual load of any charging period after the energy storage device is added; and performing the iteration according to the optimized result of the last iteration.

The particle swarm optimization comprises a plurality of iteration processes, wherein the iteration times are preset iteration times, and can be generally selected to be 20 times.

Specifically, because the optimization is performed over the entire period of time, there are many variables (for example, 2880 variables when m is 2880), the result of one iteration may be in local convergence, and the iteration cannot be continued, but the result of local convergence is not necessarily optimal for the global.

Performing previous iteration according to the particle swarm algorithm, judging whether the result of the previous iteration is in local convergence after the result of the previous iteration is obtained, and judging that the local convergence is realized if the total profit difference of the previous 2 iterations is smaller than a preset value;

if not, directly determining the P after iteration according to the result of the last iteration_i ^bInputting again, and performing the iteration;

if so, optimizing the result of the last iteration by adopting a unit time optimization strategy, specifically optimizing the income in unit time, and completing the iteration according to the optimization result.

It should be noted that the charging period includes a plurality of unit times, and each unit time includes a plurality of time instants. For example, the charging period is a month, the time interval between two adjacent time instants is an hour, and the unit time may be a day.

P to be generated last iteration for the presence of local convergence results_i ^bThe method comprises the steps of sequentially dividing the unit time into segments according to the unit time, and for any unit time segment, the basic principle of a unit time optimization strategy is to keep the maximum actual load of the unit time not to exceed the minimum value of DCT obtained through the previous steps, keep the SOC of the energy storage device at the starting time point and the SOC of the energy storage device at the ending time point of the unit time in the last iteration result (a charge-discharge power curve) unchanged, and optimize the charge-discharge power of each time of the unit time.

Before and after unit time optimization, the integrals of the charging and discharging power curves in unit time are the same, and the SOC of the energy storage device at the ending time point of any segment is unchanged before and after unit time optimization.

The unit time optimization strategy has the advantage that the optimization result of any certain unit time does not influence other results which are not optimized in the step, namely, the local optimization of a single unit time does not conflict with the constraint condition of the profit model, so that the effectiveness of the previous iteration result is influenced. The strategy can effectively avoid the defect of local optimization during multivariate (m-2880) optimization, and can greatly improve the calculation speed.

According to the embodiment of the invention, the iteration result is optimized when the iteration result is locally converged, so that a global optimal solution can be obtained, and a time sequence of charging and discharging power in a whole period can be obtained, thereby obtaining more accurate maximum energy storage income and long-term income (maximum total income over the years) of each charging period, selecting more appropriate energy storage device capacity, and selecting the energy storage device capacity which is more in line with the requirements of users.

Based on the content of the above embodiments, the specific steps of obtaining the initial maximum power and the maximum charge-discharge duration according to any optional capacity include: acquiring initial maximum power and initial maximum charge-discharge duration according to any optional capacity; the product of the initial maximum power and the initial maximum charge-discharge time length is equal to any optional capacity.

It should be noted that the initial maximum charging and discharging duration refers to a maximum duration of charging the energy storage device at the initial maximum power when the energy storage device is deployed for the first time. The product of the initial maximum power and the initial maximum charge-discharge time period is equal to the selectable capacity.

Specifically, for any optional capacity, a plurality of groups of initial maximum power and initial maximum charge-discharge duration can be obtained according to a preset energy storage initial configuration table. Table 1 shows an example of the energy storage initial configuration table.

TABLE 1 initial configuration table for energy storage

Initial maximum power (kW)	Initial maximum charge-discharge time (h)	Selectable capacity (kWh)
			2	1	2
2	2	4
			3	1	3
…	…	…
			50	1	50
50	2	100

And acquiring the maximum charging and discharging time according to the initial maximum charging and discharging time, the preset annual attenuation rate and the number of years of the energy storage device corresponding to any charging period.

Specifically, because the energy storage device generally adopts a storage battery to store energy, the actual capacity of the storage battery can be attenuated along with the increase of the charging and discharging times, and the maximum charging and discharging time can be correspondingly shortened.

The number of years of adding the energy storage device corresponding to the charging period refers to the charging period belonging to the first year after adding the energy storage device with the optional capacity.

For each charging period included in the nth year after the energy storage device with the optional capacity is added, the maximum charging and discharging time length H of the charging period_max,nIs calculated by the formula

H_max,n＝H_max(1-η)^n-1

Wherein H_maxRepresents an initial maximum charge-discharge time period; eta represents a predetermined annual decay rate, generally around 3%.

According to the embodiment of the invention, the maximum charging and discharging time lengths of different charging periods are obtained through the initial maximum charging and discharging time length, the preset annual attenuation rate and the number of years of adding the energy storage device, the attenuation of the battery performance is considered, and more accurate maximum charging and discharging time length can be obtained, so that more accurate maximum energy storage income and long-term income (maximum total income over the years) of each charging period can be obtained, more appropriate energy storage device capacity can be selected, and the energy storage device capacity which is more in line with the requirements of users can be selected.

Based on the content of the above embodiments, for each optional capacity, according to the maximum energy storage benefit of each charging period after the energy storage device with the optional capacity is added, the specific step of obtaining the maximum total annual benefit after the energy storage device with the optional capacity is added includes: and acquiring the annual maximum benefit of the energy storage device with the optional capacity after the energy storage device with the optional capacity is added according to the maximum energy storage benefit of each charging period after the energy storage device with the optional capacity is added.

It should be noted that each year includes a plurality of charging cycles.

For each year after the energy storage device with the selectable capacity is added, the maximum energy storage income of each charging period included in the year can be directly summed to serve as the maximum income of the year after the energy storage device with the selectable capacity is added, and any suitable data processing method can be adopted to process the maximum energy storage income of each charging period included in the year so as to obtain the maximum income of the year after the energy storage device with the selectable capacity is added. In this regard, the embodiments of the present invention are not particularly limited.

And taking the sum of the annual maximum benefits of the energy storage devices with the optional capacity as the maximum annual total benefit of the energy storage devices with the optional capacity.

Specifically, for each optional capacity, the energy storage device added with the optional capacity has been n years so far, and the maximum profit of the energy storage device added with the optional capacity in the 1 st year, the 2 nd year and the nth year is respectively B₁,B₂,…,B_nThen, the maximum total yearly profit B after adding the energy storage device with the selectable capacity can be obtained by the following formula:

B＝B₁+B₂+…+B_n

according to the embodiment of the invention, the maximum annual income of the energy storage device with the optional capacity is obtained according to the maximum energy storage income of each charging period after the energy storage device with the optional capacity is added, the maximum total annual income is obtained according to the maximum annual income, more accurate long-term income (the maximum total annual income) can be obtained, more appropriate energy storage device capacity can be selected, and the energy storage device capacity which is more in line with the requirement of a user is selected.

Based on the content of each embodiment, the specific step of obtaining the annual maximum benefit of the energy storage device with the optional capacity according to the maximum energy storage benefit of each charging period after the energy storage device with the optional capacity is added includes: for each year after the energy storage device with the optional capacity is added, acquiring the average value of the maximum energy storage income of each charging period included in each year after the energy storage device with the optional capacity is added; the product of the average value and the number of billing cycles included per year is taken as the maximum profit per year after adding the energy storage device of selectable capacity.

Specifically, for each year after the energy storage device with the optional capacity is added, the average value of the maximum energy storage profit of each charging period included in the year after the energy storage device with the optional capacity is added can be obtained according to the maximum energy storage profit of each charging period included in the year after the energy storage device with the optional capacity is added; the average is multiplied by the number of billing cycles involved in the year to obtain the maximum revenue for the year after the addition of the energy storage device of selectable capacity.

For example, the billing period is a month, and for each year after the optional capacity storage device is added, the maximum profit for that year is equal to the average of the maximum energy storage profit for 12 months in that year multiplied by 12.

According to the embodiment of the invention, the product of the average value of the maximum energy storage income of each charging period included every year and the number of the charging periods included every year is used as the maximum income of each year, so that the accumulated error of the maximum energy storage income of each charging period can be reduced, more accurate maximum income of each year can be obtained, more accurate long-term income (maximum total income of all years) can be obtained, more appropriate energy storage device capacity can be selected, and the energy storage device capacity which is more in line with the requirement of a user can be selected.

Based on the content of the foregoing embodiments, the specific step of obtaining, for each selectable capacity, the total cost of deploying the energy storage devices with the selectable capacity includes: and acquiring the total cost for deploying the energy storage device with the optional capacity according to the manufacturing cost and the optional capacity of the unit capacity.

Specifically, since the energy storage device generally uses a storage battery for storing energy, the deployment costs of storage batteries with different capacities are different, and the total cost for deploying the energy storage device with the selectable capacity can be obtained according to the following formula:

C₁＝W_maxk_w

wherein, C₁Represents the total cost of deploying a selectable capacity of energy storage devices; w_maxIndicating a selectable capacity; k is a radical of_wThe manufacturing cost of the unit capacity of the energy storage device is generally 1500-2000/(yuan kW.h).

The embodiment of the invention obtains the total cost for deploying the energy storage devices with the selectable capacity through the manufacturing cost and the selectable capacity of the unit capacity, and can reflect the deployment cost of the energy storage devices with different capacities, thereby obtaining more accurate total cost for deploying the energy storage devices and selecting more proper energy storage device capacity.

To facilitate an understanding of the embodiments of the present invention, the following description is given by way of an example.

The historical load data and the historical electricity charge data of a certain business 2018 in 1 month are adopted. Specifically, the time resolution (time interval between two adjacent moments) of the historical load data is 1h, and the initial maximum power P_max500kW, initial maximum charge and discharge time of 0.5hActual load after adding energy storage device

The specific price of the required electric power is 2533kW, the unit price of the required electric power is 44 Yuan/kW, and the electric power (time-of-use electric power) are shown in Table 2.

TABLE 2 TIME-SHARING ELECTRIC CHARGE METER

Time of day	Price (Yuan/kWh)
		0	0.2071
1	0.2071
		2	0.2071
3	0.2071
		4	0.2071
5	0.2071
		6	0.2071
7	0.6172
		8	0.6172
9	0.8959
		10	0.8959
11	0.8959
		12	0.5911
13	0.5911
		14	0.8959
15	0.8959
		16	0.5911
17	0.5911
		18	0.5911
19	0.8959
		20	0.8959
21	0.5911
		22	0.5911
23	0.2071

The minimum value of the obtained DCT is 2397 kW.

By adopting the prior art, the method for acquiring the time sequence of the charge and discharge power, which is suitable for typical 24-hour optimization, is popularized to one month, and the optimized energy storage device SOC only presents 2 charge and discharge cycles in one month. Indicating that the prior art does not achieve results that satisfy engineering experience.

By adopting the method provided by the embodiment of the invention, 3 charge-discharge cycles occur every day, 3 electricity consumption peak price periods exist in the corresponding area every day, the engineering empirical rule is met, the utilization rate of the energy storage device is higher, and the engineering empirical rule is also met.

Therefore, compared with the prior art, the method provided by the embodiment of the invention can obtain a better all-time energy storage device operation strategy, thereby obtaining more accurate maximum energy storage income and long-term income (maximum total income over the years) of each charging period, selecting more appropriate energy storage device capacity and selecting the energy storage device capacity which is more in line with the requirements of users.

Fig. 2 is a schematic structural diagram of an energy storage device capacity selection device according to an embodiment of the present invention. Based on the content of the foregoing embodiments, as shown in fig. 2, the apparatus includes a billing cycle revenue obtaining module 201, a total revenue total cost obtaining module 202, and an energy storage device capacity selecting module 203, where:

a charging period profit obtaining module 201, configured to obtain historical load data and historical electricity price data of each charging period, and respectively obtain the maximum energy storage profit of each charging period after adding each energy storage device with a selectable capacity according to a pre-established profit model, the historical load data of each charging period, and the historical electricity price data;

the total profit total cost obtaining module 202 is configured to, for each selectable capacity, obtain a maximum total profit per year after the energy storage device with the selectable capacity is added according to a maximum energy storage profit in each charging period after the energy storage device with the selectable capacity is added, and obtain a total cost for deploying the energy storage device with the selectable capacity;

the energy storage device capacity selection module 203 is configured to select a selectable capacity as a selection result according to a preset condition according to the maximum total annual revenue after each energy storage device with the selectable capacity is added and the total cost for deploying each energy storage device with the selectable capacity;

Specifically, for each optional capacity, the charging period profit obtaining module 201 performs optimization solution on the profit model according to the historical load data and the historical electricity price data of each charging period, and obtains the time sequence of the charging and discharging power of the energy storage device in the charging period and the maximum energy storage profit of the charging period after the energy storage device with the optional capacity is added. And the energy storage device performs charging and discharging in the charging period according to the acquired time sequence of the charging and discharging power of the energy storage device in the charging period, and the user side can obtain the maximum energy storage benefit of the charging period after the energy storage device with the optional capacity is added.

After the total profit total cost obtaining module 202 obtains, for each selectable capacity, the maximum energy storage profit of each charging period after the energy storage device with the selectable capacity is added, the maximum total profit of the energy storage device with the selectable capacity to the present can be obtained according to the maximum energy storage profit of each charging period after the energy storage device with the selectable capacity is added, and the maximum total profit is taken as the maximum total profit of the past year; for each selectable capacity, a total cost of deploying the energy storage devices of the selectable capacity may be obtained from the selectable capacity.

The energy storage device capacity selection module 203 may select one selectable capacity from the selectable capacities as a result of the energy storage device capacity selection according to preset conditions, a maximum total yearly revenue after adding the energy storage devices of the selectable capacities, and a total cost of deploying the energy storage devices of the selectable capacities.

The specific method and process for implementing the corresponding function by each module included in the energy storage device capacity selection device are described in the above embodiments of the energy storage device capacity selection method, and details are not described herein.

The energy storage device capacity selection device is used for the energy storage device capacity selection method of the previous embodiments. Therefore, the descriptions and definitions in the energy storage device capacity selection methods in the foregoing embodiments can be used for understanding the execution modules in the embodiments of the present invention.

Fig. 3 is a block diagram of an electronic device according to an embodiment of the present invention. Based on the content of the above embodiment, as shown in fig. 3, the electronic device may include: a processor (processor)301, a memory (memory)302, and a bus 303; wherein, the processor 301 and the memory 302 complete the communication with each other through the bus 303; the processor 301 is configured to invoke computer program instructions stored in the memory 302 and executable on the processor 301 to perform the energy storage device capacity selection method provided by the above-mentioned embodiments of the methods, for example, including: acquiring historical load data and historical electricity price data of each charging period, and respectively acquiring the maximum energy storage benefit of each charging period after each energy storage device with selectable capacity is added according to a pre-established benefit model, the historical load data and the historical electricity price data of each charging period; for each optional capacity, acquiring the maximum total annual income after the energy storage device with the optional capacity is added according to the maximum energy storage income of each charging period after the energy storage device with the optional capacity is added, and acquiring the total cost for deploying the energy storage device with the optional capacity; selecting a selectable capacity as a selection result according to a preset condition according to the maximum total annual income after each energy storage device with the selectable capacity is added and the total cost for deploying each energy storage device with the selectable capacity; the profit model takes the energy storage profit of each charging period after the energy storage device is added to the maximum as a target; the energy storage profit comprises demand electric power profit and electric quantity electric power profit.

Another embodiment of the present invention discloses a computer program product, which includes a computer program stored on a non-transitory computer readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the computer can execute the method for selecting capacity of an energy storage device provided by the above-mentioned embodiments of the method, for example, the method includes: acquiring historical load data and historical electricity price data of each charging period, and respectively acquiring the maximum energy storage benefit of each charging period after each energy storage device with selectable capacity is added according to a pre-established benefit model, the historical load data and the historical electricity price data of each charging period; for each optional capacity, acquiring the maximum total annual income after the energy storage device with the optional capacity is added according to the maximum energy storage income of each charging period after the energy storage device with the optional capacity is added, and acquiring the total cost for deploying the energy storage device with the optional capacity; selecting a selectable capacity as a selection result according to a preset condition according to the maximum total annual income after each energy storage device with the selectable capacity is added and the total cost for deploying each energy storage device with the selectable capacity; the profit model takes the energy storage profit of each charging period after the energy storage device is added to the maximum as a target; the energy storage profit comprises demand electric power profit and electric quantity electric power profit.

Furthermore, the logic instructions in the memory 302 may be implemented in software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or make a contribution to the prior art, or may be implemented in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

Another embodiment of the present invention provides a non-transitory computer-readable storage medium, which stores computer instructions, where the computer instructions cause a computer to execute the method for selecting capacity of an energy storage device provided in the above method embodiments, for example, the method includes: acquiring historical load data and historical electricity price data of each charging period, and respectively acquiring the maximum energy storage benefit of each charging period after each energy storage device with selectable capacity is added according to a pre-established benefit model, the historical load data and the historical electricity price data of each charging period; for each optional capacity, acquiring the maximum total annual income after the energy storage device with the optional capacity is added according to the maximum energy storage income of each charging period after the energy storage device with the optional capacity is added, and acquiring the total cost for deploying the energy storage device with the optional capacity; selecting a selectable capacity as a selection result according to a preset condition according to the maximum total annual income after each energy storage device with the selectable capacity is added and the total cost for deploying each energy storage device with the selectable capacity; the profit model takes the energy storage profit of each charging period after the energy storage device is added to the maximum as a target; the energy storage profit comprises demand electric power profit and electric quantity electric power profit.

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. It is understood that the above-described technical solutions may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method of the above-described embodiments or some parts of the embodiments.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A method for selecting a capacity of an energy storage device, comprising:

the profit model takes the energy storage profit of each charging period after the energy storage device is added as a target to be maximized; the energy storage income comprises demand electric charge income and electric quantity electric charge income;

the specific steps of obtaining the maximum energy storage benefit of each charging period after each energy storage device with the optional capacity is added according to the benefit model, the historical load data and the historical electricity price data of each charging period comprise:

2. The energy storage device capacity selection method according to claim 1, wherein the specific step of obtaining the time series of the charging and discharging power of the energy storage device in any charging period according to a particle swarm algorithm and the profit model so that the energy storage profit of any charging period is the maximum includes:

3. The energy storage device capacity selection method according to claim 1, wherein the specific step of obtaining the initial maximum power and the maximum charge-discharge duration according to any one of the selectable capacities comprises:

4. The energy storage device capacity selection method according to claim 1, wherein for each selectable capacity, the specific step of obtaining the maximum total annual revenue after the energy storage devices with the selectable capacity are added according to the maximum energy storage revenue in each charging period after the energy storage devices with the selectable capacity are added comprises:

5. The energy storage device capacity selection method according to claim 4, wherein the specific step of obtaining the annual maximum profit of the energy storage device with the selectable capacity according to the maximum energy storage profit of each charging period after the energy storage device with the selectable capacity is added comprises:

6. The energy storage device capacity selection method of claim 1, wherein the specific step of obtaining, for each selectable capacity, a total cost of deploying the selectable capacity of energy storage devices comprises:

7. An energy storage device capacity selection device, comprising:

8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the program, carries out the steps of the energy storage device capacity selection method according to any of claims 1 to 6.

9. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the energy storage device capacity selection method according to any one of claims 1 to 6.