Energy storage configuration method and device

Abstract

The present invention provides an energy storage configuration method and device, wherein the method comprises: obtaining a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of the renewable energy power generation consumed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units and the net output power of the battery energy storage system contained in the model of the battery energy storage system, and the energy storage capacity configuration model is solved with the minimum energy storage capacity as the goal, so that the energy storage capacity can be obtained, and according to the energy storage capacity, a battery energy storage system that meets the safe operation requirements of the power grid in an uncertain environment can be reasonably constructed, thereby reducing the cost of building the battery energy storage system.

Description

Technical Field

[0001] The present invention relates to the field of new energy technologies, and in particular to an energy storage configuration method and device. Background Art

[0002] At present, equipment for generating electricity through new energy sources such as wind power generation or photovoltaic power generation has been widely connected to the power grid. While promoting the low-carbon transformation of the power system, it also brings huge challenges to the grid dispatching based on the principle of power balance. Generally, new energy power generation has strong uncertainty and volatility, and traditional thermal power units are limited by their own ramp rate and cannot smooth out the fluctuations of new energy power generation in real time, resulting in real-time power imbalance in the power system, which easily threatens the reliable supply of the total load of the power grid and endangers the safe operation of the power grid. For this reason, the existing technology uses battery energy storage to deal with it. Since large-capacity energy storage batteries have the ability to adjust quickly, they are considered to be an effective means to support the operation of the power grid and promote the access of new energy. However, the cost of battery energy storage is high, the operation control is relatively complex, and it is not easy to build in large quantities. Summary of the invention

[0003] The present invention provides an energy storage configuration method and device to solve the defects of the prior art that battery energy storage is high in cost, complex in operation and control, and difficult to build in large quantities, so as to reasonably construct a battery energy storage system that meets the requirements of safe operation of the power grid in an uncertain environment and reduce the cost of building the battery energy storage system.

[0004] The present invention provides an energy storage configuration method, comprising:

[0005] Acquire a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance principle of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of renewable energy power generation absorbed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system;

[0006] With the goal of minimizing the energy storage capacity, the energy storage capacity configuration model is solved to obtain the energy storage capacity, and the energy storage capacity is used to construct a battery energy storage system of the power grid according to the energy storage capacity.

[0007] According to an energy storage configuration method provided by the present invention, the energy storage capacity configuration model is constructed in the following manner:

[0008] Based on the historical data of the power grid, an uncertainty set of the total power of renewable energy generation in the power grid and the total load of the power grid is constructed, wherein the uncertainty set includes a reference power corresponding to the total power of renewable energy generation and a reference power corresponding to the total load of the power grid, the maximum absolute deviation of the total power of renewable energy generation and the corresponding reference power is a preset deviation, and the maximum absolute deviation of the total load of the power grid and the corresponding reference power is the preset deviation;

[0009] Determine the power of the renewable energy power generation to be absorbed, wherein the power of the renewable energy power generation to be absorbed is less than or equal to the total power of the renewable energy power generation in the uncertain set;

[0010] Constructing a model of the non-new energy unit;

[0011] Constructing a model of the battery energy storage system;

[0012] Based on the power balance principle of the power grid, determine that the sum of the total power of the non-new energy units contained in the model of the non-new energy units, the power of the new energy power generation consumed, and the net output power of the battery energy storage system contained in the model of the battery energy storage system is equal to the total load of the power grid, and obtain the energy storage capacity configuration model.

[0013] According to an energy storage configuration method provided by the present invention, the model of the battery energy storage system also includes the remaining power of the battery energy storage system; the energy storage capacity configuration model is solved with the minimum energy storage capacity as the goal to obtain the energy storage capacity, including:

[0014] Constructing an initial set of key poles based on a reference power corresponding to the total power generated by the renewable energy and a reference power corresponding to the total load of the power grid;

[0015] Taking the critical pole set as input, the dispatching strategy as a variable, and the minimum energy storage capacity as a goal, solving the energy storage capacity configuration model to obtain the energy storage capacity, wherein the dispatching strategy includes the total power of the non-new energy units, the power of the new energy generation consumed, the net output power of the battery energy storage system, and the remaining power of the battery energy storage system;

[0016] After solving the energy storage capacity with the key pole set as input, the energy storage capacity is input into the objective function with the maximum infeasibility of the scheduling strategy as the goal, and the objective function is solved to obtain the poles in the uncertainty set. When the value of the objective function is greater than zero, the solved poles in the uncertainty set are added to the key pole set and the key pole set is continued to be input into the energy storage capacity configuration model; when the value of the objective function is equal to zero, the energy storage capacity is used as the final result of the solution.

[0017] According to an energy storage configuration method provided by the present invention, the uncertainty set of the total power of renewable energy generation in the power grid and the total load of the power grid is constructed based on the historical data of the power grid, including: based on the historical data of T time periods of several typical days, determining the reference power corresponding to the total power of photovoltaic power generation in any time period of the T time periods, the reference power corresponding to the total power of wind power generation, and the reference power corresponding to the total load of the power grid, and constructing the following uncertainty set:

[0018]

[0019]

[0020] Wherein, Ξ represents the uncertain set, t period represents any period in T periods, t∈{1,2,…,T}, represents the total power of wind power generation during period t, represents the total photovoltaic power generation during period t, represents the total load of the power grid during period t, ξ t represents the uncertainty in the uncertainty set during period t, which is and The transpose of the matrix formed is, represents the reference power corresponding to the total power of wind power generation in period t, Indicates the reference power corresponding to the total photovoltaic power generation power in period t, represents the reference power corresponding to the total load of the power grid during time period t, and Γ represents the preset deviation.

[0021] According to an energy storage configuration method provided by the present invention, the model of the non-new energy unit includes:

[0022] G min ≤G t ≤G max ,t=1,2,…,T

[0023] G t -G t-1 ≤R UP

[0024] G t-1 -G t ≤R DOWN

[0025] Among them, G t represents the total power of the thermal power unit in period t, period t-1 represents the period before period t, G max Represents the upper limit of the total power of the thermal power unit, G min Represents the lower limit of the total power of the thermal power unit, R UPrepresents the threshold of the upward climbing rate of the thermal power unit in the adjacent t period and t-1 period, R DOWN It represents the threshold value of the downward climbing rate of the thermal power unit in the adjacent time period t and time period t-1.

[0026] According to an energy storage configuration method provided by the present invention, the model of the battery energy storage system includes:

[0027] -S max ≤S t ≤S max ,t=1,2,…,T

[0028] E t =E t-1 -S t

[0029] 0≤E t ≤E max

[0030] Among them, S max represents the power capacity of the battery energy storage system, E max represents the energy capacity of the battery energy storage system, S t represents the net output power of the battery energy storage system during period t, E t Represents the remaining power of the battery energy storage system in period t, which is the remaining power E of the previous period t-1 t-1 With S t The difference.

[0031] According to an energy storage configuration method provided by the present invention, based on the power balance of the power grid, determining that the sum of the total power of the non-new energy units contained in the model of the non-new energy units, the power of the new energy power generation consumed, and the net output power of the battery energy storage system contained in the model of the battery energy storage system is equal to the total load of the power grid, and obtaining the energy storage capacity configuration model includes:

[0032] Based on the power balance principle of the power grid, a power balance model of the power grid is constructed:

[0033]

[0034]

[0035]

[0036] in, represents the power of the wind power generation absorbed, represents the power of the photovoltaic power generation absorbed;

[0037] Based on the power balance model of the power grid, the energy storage capacity configuration model is constructed with the minimum energy storage capacity as the goal, and the energy storage capacity includes S max and E max .

[0038] The present invention also provides an energy storage configuration device, comprising:

[0039] A model acquisition module, used to acquire a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance principle of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of renewable energy power generation absorbed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system;

[0040] The capacity acquisition module is used to solve the energy storage capacity configuration model with the goal of minimizing the energy storage capacity to obtain the energy storage capacity, and the energy storage capacity is used to construct the battery energy storage system of the power grid according to the energy storage capacity.

[0041] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any of the energy storage configuration methods described above is implemented.

[0042] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the energy storage configuration method described in any one of the above is implemented.

[0043] The energy storage configuration method provided by the present invention can obtain a constructed energy storage capacity configuration model, which is constructed based on the power balance of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of the renewable energy power generation consumed, the total power of the non-new energy units contained in the model of the non-new energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system. The energy storage capacity configuration model is solved with the minimum energy storage capacity as the goal, and the energy storage capacity can be obtained. According to the energy storage capacity, a battery energy storage system that meets the safe operation requirements of the power grid in an uncertain environment can be reasonably constructed. In this way, the cost of building a battery energy storage system can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 It is one of the flow diagrams of the energy storage configuration method provided by the present invention;

[0046] Figure 2 This is the second flow chart of the energy storage configuration method provided by the present invention;

[0047] Figure 3 It is a structural schematic diagram of the energy storage configuration device provided by the present invention;

[0048] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] like Figure 1 As shown, this embodiment provides an energy storage configuration method, which can be executed by an electronic device such as a computer, a handheld computer or a mobile phone, or the software and / or hardware therein, and at least includes the following steps:

[0051] Step 101, obtaining a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance of the power grid according to an uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of the renewable energy power generation absorbed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system.

[0052] Step 102: With the minimum energy storage capacity as the goal, solve the energy storage capacity configuration model to obtain the energy storage capacity, and the energy storage capacity is used to construct a battery energy storage system of the power grid according to the energy storage capacity.

[0053] In the scenario of this embodiment, the power grid includes both renewable energy power generation and non-renewable energy power generation.

[0054] Among them, renewable energy power generation can include photovoltaic power generation, wind power generation, etc. Here, the total power of renewable energy power generation can reflect the output of renewable energy power generation.

[0055] The power of renewable energy generation consumed refers to the part of the total power of renewable energy generation that is actually consumed.

[0056] Non-renewable energy power generation can include traditional thermal power generation, hydropower generation, etc. Correspondingly, non-renewable energy units are units that perform non-renewable energy power generation. The model of non-renewable energy generator units is used to characterize the operation of non-renewable energy generator units.

[0057] In practical applications, the output of renewable energy power generation is uncertain and fluctuates dramatically over time. The load of the power grid is affected by user actions and also has a certain degree of uncertainty. In order to cope with the uncertainty and volatility of renewable energy power generation, a battery energy storage system can be set up. The battery energy storage system can store and release electrical energy, thereby cooperating with renewable energy power generation to achieve power balance. The model of the battery energy storage system is used to characterize the operation of the battery energy storage system. Here, power balance is the balance between supply and demand in the power system. The grid structure and flow are ignored here, and only the balance between supply and demand in the power system is considered. Based on this, in this embodiment, an uncertain set of the total power of renewable energy power generation and the total load of the power grid is set. The uncertain set is a set of uncertain parameters. Here, the uncertain parameters include the total power of renewable energy power generation and the total load of the power grid, which can reflect the possible fluctuation range of the total power of renewable energy power generation and the total load of the power grid.

[0058] Considering the high cost of battery energy storage systems, the complexity of operation and control, and the difficulty of large-scale construction, before building a battery energy storage system for the power grid, the minimum energy storage capacity of the battery energy storage system that needs to be configured for the power grid can be pre-calculated. To this end, an energy storage capacity configuration model can be constructed to obtain the minimum energy storage capacity. Then, based on the minimum energy storage capacity, a matching battery energy storage system is built for the power grid, and the power grid is dispatched, which can reduce the cost of building a battery energy storage system.

[0059] In this embodiment, a constructed energy storage capacity configuration model can be obtained. The energy storage capacity configuration model is constructed based on the power balance of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of the absorbed renewable energy power generation, the total power of the non-new energy units contained in the model of the non-new energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system. The energy storage capacity configuration model is solved with the minimum energy storage capacity as the goal, and the energy storage capacity can be obtained. According to the energy storage capacity, a battery energy storage system that meets the safe operation requirements of the power grid in an uncertain environment can be reasonably constructed. In this way, the cost of building a battery energy storage system can be reduced.

[0060] In an exemplary embodiment, if Figure 2 As shown, the energy storage capacity configuration model is constructed in the following manner:

[0061] Step 201: Based on the historical data of the power grid, an uncertainty set of the total power of renewable energy generation in the power grid and the total load of the power grid is constructed, wherein the uncertainty set includes a reference power corresponding to the total power of renewable energy generation and a reference power corresponding to the total load of the power grid, the maximum absolute deviation of the total power of renewable energy generation and the corresponding reference power is a preset deviation, and the maximum absolute deviation of the total load of the power grid and the corresponding reference power is the preset deviation.

[0062] If the renewable energy power generation includes wind power generation and photovoltaic power generation, illustratively, constructing the uncertainty set of the total power of renewable energy power generation in the power grid and the total load of the power grid based on the historical data of the power grid may specifically include: determining the reference power corresponding to the total power of photovoltaic power generation in any time period of the T time periods, the reference power corresponding to the total power of wind power generation, and the reference power corresponding to the total load of the power grid based on the historical data of T time periods of several typical days, and constructing the following uncertainty set:

[0063]

[0064]

[0065] Wherein, Ξ represents the uncertain set, t period represents any period in T periods, t∈{1,2,…,T}, represents the total power of wind power generation during period t, represents the total photovoltaic power generation during period t, represents the total load of the power grid during period t, ξ t represents the uncertainty in the uncertainty set during period t, which is and The transpose of the matrix formed is, represents the reference power corresponding to the total power of wind power generation in period t, Indicates the reference power corresponding to the total photovoltaic power generation power in period t, represents the reference power corresponding to the total load of the power grid during time period t, and Γ represents the preset deviation.

[0066] For example, the typical days can be selected from each quarter of a year, and the time granularity is set to hours. In any time period t, the total power of wind power generation based on the typical days t is averaged to obtain Based on the average of the total power of the photovoltaic power generation in several typical days and time periods, we can get And the total load based on several typical days t period is averaged to obtain

[0067] In implementation, the value of the preset deviation Γ can be set according to the user's risk preference. The larger the preset deviation, the more conservative the uncertainty set, and vice versa. Since the conditions in the uncertainty set Ξ are all linear, the uncertainty set Ξ can be expressed in the following form:

[0068] Ξ={ξ|Hξ≤J} (3)

[0069] in:

[0070] ξ=[ξ 1 ξ 2 ;…;ξ T ] (4)

[0071]

[0072]

[0073] Where ξ represents the uncertainty of all time periods ξ t The matrix formed, H and J are coefficient matrices, H includes the coefficients of each time period t , J includes the coefficient J of each period t .

[0074] In this embodiment, the reference power corresponding to the total power of renewable energy generation in each time period and the reference power corresponding to the total load of the power grid can describe the reference curves of renewable energy output and total power grid load, and define the maximum offset parameters (i.e., preset deviations) between the actual curve of renewable energy output and the actual curve of total power grid load and the corresponding reference curves. Based on this, the uncertainty set of the total power of renewable energy generation and the total load of the power grid is obtained, which can accurately describe the possible fluctuation range of the renewable energy power and the total load level of the power grid.

[0075] Step 202: Determine the power of the renewable energy power generation to be consumed, wherein the power of the renewable energy power generation to be consumed is less than or equal to the total power of the renewable energy power generation in the uncertain set. An example is as follows:

[0076]

[0077]

[0078] in, represents the power of the wind power generation absorbed, Represents the power of the photovoltaic power generation absorbed.

[0079] In actual applications, it is not mandatory for all renewable energy power generation to be absorbed by the power grid. In some cases, the power of renewable energy power generation actually absorbed may be less than the total power of renewable energy power generation, and the unabsorbed part may be discarded.

[0080] Step 203, construct a model of the non-new energy unit. The model of the non-new energy unit includes the total power of the non-new energy unit. The total power of the non-new energy unit reflects the total output of the non-new energy unit. The model of the non-new energy unit also includes the constraint conditions of the total power of the non-new energy unit. Among them, the constraint conditions of the total power of the non-new energy unit include the upper and lower limits of the total power of the thermal power unit, and the climbing constraint of the thermal power unit.

[0081] Exemplarily, the model of the non-new energy unit includes:

[0082] G min ≤G t ≤G max ,t=1,2,…,T (9)

[0083] G t -G t-1 ≤R UP (10)

[0084] G t-1 -G t ≤R DOWN (11)

[0085] Among them, G t represents the total power of the thermal power unit in period t, period t-1 represents the period before period t, G max Represents the upper limit of the total power of the thermal power unit, G min Represents the lower limit of the total power of the thermal power unit, R UP represents the threshold of the upward climbing rate of the thermal power unit in the adjacent t period and t-1 period, R DOWN It represents the threshold value of the downward climbing rate of the thermal power unit in the adjacent time period t and time period t-1.

[0086] In practical applications, the total output of thermal power units in any period of time cannot exceed the upper limit G determined by the total installed capacity of thermal power units. max , nor can it be lower than the lower limit G determined by the physical conditions of the thermal power unit operation. min . The total installed capacity refers to the sum of the rated active powers of the actually installed generating units. Formulas (10) and (11) are the ramp constraints of thermal power units. The former means that if the output of the thermal power units in two adjacent periods shows an upward trend, the increased power shall not exceed the threshold R of the upward ramp rate of the thermal power units. UP, accordingly, the latter means that if the output of the thermal power unit in two adjacent periods shows a downward trend, the reduced power shall not exceed the threshold R of the downward climbing rate of the thermal power unit. DOWN In this embodiment, the operation of the thermal power unit is described from multiple perspectives, including the total output of the thermal power unit, the upper and lower limits of the total output, and the ramp constraint, which can comprehensively and accurately reflect the operation of the thermal power unit and facilitate obtaining accurate energy storage capacity.

[0087] Step 204: construct a model of the battery energy storage system. The model of the battery energy storage system includes the net output power of the battery energy storage system. The model of the battery energy storage system also includes constraints on the net output power of the battery energy storage system, such as the power capacity of the battery energy storage system. The model of the battery energy storage system also includes the remaining power of the battery energy storage system and constraints on the remaining power, such as the energy capacity of the battery energy storage system.

[0088] Exemplarily, the model of the battery energy storage system includes:

[0089] -S max ≤S t ≤S max ,t=1,2,…,T (12)

[0090] E t =E t-1 -S t (13)

[0091] 0≤E t ≤E max (14)

[0092] Among them, S max represents the power capacity of the battery energy storage system, E max represents the energy capacity of the battery energy storage system, S t represents the net output power of the battery energy storage system during period t, E t Represents the remaining power of the battery energy storage system in period t, which is the remaining power E of the previous period t-1 t-1 With S t The difference.

[0093] In practical applications, if S t is positive, the battery energy storage system discharges to the grid; if S tIf it is negative, the battery energy storage system absorbs electric energy from the power grid. Formula (12) reflects the range of the net output power of the battery energy storage system, formula (13) reflects the change of the remaining power of the battery energy storage system, and formula (14) reflects the range of the remaining power of the battery energy storage system. In this embodiment, the battery energy storage system is described in multiple aspects by the net output power of the battery energy storage system and its constraints and the remaining power and its constraints, which can accurately reflect the operation of the battery energy storage system and facilitate the acquisition of more accurate energy storage capacity.

[0094] Step 205: Based on the power balance principle of the power grid, determine that the sum of the total power of the non-new energy units contained in the model of the non-new energy units, the power of the new energy power generation consumed, and the net output power of the battery energy storage system contained in the model of the battery energy storage system is equal to the total load of the power grid, and obtain the energy storage capacity configuration model.

[0095] In this embodiment, the uncertain sets of the total power of renewable energy power generation and the total load of the power grid, the model of non-renewable energy units and the model of the battery energy storage system are respectively constructed. In combination with the power balance principle of the power grid, the total power of non-renewable energy units included in the model of non-renewable energy units, the power of renewable energy power generation consumed, and the relationship between the net output power and the remaining power of the battery energy storage system included in the model of the battery energy storage system and the total load of the power grid are established, thereby constructing an energy storage capacity configuration model constrained by power balance. This model can accurately configure matching energy storage capacity for the power grid to build a battery energy storage system that meets the safe operation requirements of the power grid in an uncertain environment.

[0096] Exemplarily, based on the power balance of the power grid, determining that the sum of the total power of the non-new energy units contained in the model of the non-new energy units, the power of the new energy power generation consumed, and the net output power of the battery energy storage system contained in the model of the battery energy storage system is equal to the total load of the power grid, and obtaining the energy storage capacity configuration model may specifically include:

[0097] The first step is to construct a power balance model of the power grid based on the power balance principle of the power grid:

[0098]

[0099] In practical applications, load shedding in power grids will have serious impacts, so load shedding is generally not allowed. Based on this, according to the robust optimization method, a mathematical description of the robust power balance principle that any value in the uncertain set can achieve power balance is established, that is, the power balance model of the power grid.

[0100] In practice, the energy storage capacity vector x can be defined as [S max ; Emax ], the scheduling vector y representing the scheduling strategy = [y 1 ;y 2 ;…;y T ],in The equation of the power balance model of the power grid can be replaced by two inequalities in opposite directions. Since all the conditions in formula (15) are linear, the power balance model of formula (15) can be converted into a matrix form:

[0101] Ax+By≤b+Fξ (16)

[0102] Among them, A is the coefficient matrix of x, B is the coefficient matrix of y, F is the coefficient matrix of ξ, b is the coefficient matrix of the constant term, A, B, F and b are the coefficient matrices obtained in the process of converting formula (15) into matrix form, that is, formula (16). The specific method of converting into matrix form can refer to the relevant technology. Further, if the uncertainty set is taken into account, the power balance in the robust sense can be described as follows: for any realization in the uncertainty set, formula (16) can be satisfied, and the power balance model of the power grid is also:

[0103]

[0104] The second step is to construct the energy storage capacity configuration model based on the power balance model of the power grid with the minimum energy storage capacity as the goal, and the energy storage capacity includes S max and E max .

[0105] Exemplarily, based on the power balance model of formula (17), the following energy storage capacity configuration model is constructed:

[0106]

[0107]

[0108] Among them, c′ is a coefficient, which is the transpose of the coefficient c. Through this model, we can find an optimal or most economical energy storage capacity, that is, the minimum energy storage capacity, so that under this energy storage capacity, for any uncertain realization ξ in the uncertain set Ξ={ξ|Hξ≤J}, we can find at least one feasible scheduling strategy y.

[0109] Exemplarily, the model of the battery energy storage system further includes the remaining power of the battery energy storage system; solving the energy storage capacity configuration model with the minimum energy storage capacity as the goal to obtain the energy storage capacity may specifically include:

[0110] The first step is to construct an initial set of key poles based on the reference power corresponding to the total power of the new energy generation and the reference power corresponding to the total load.

[0111] The initial critical pole set includes the reference power corresponding to the total power of the new energy generation and the reference power corresponding to the total load.

[0112] The second step is to solve the energy storage capacity configuration model with the key pole set as input, the scheduling strategy as variable, and the minimum energy storage capacity as the goal to obtain the energy storage capacity. The scheduling strategy includes the total power of the non-new energy units, the power of the new energy generation consumed, the net output power of the battery energy storage system, and the remaining power of the battery energy storage system. The specific implementation is as follows:

[0113]

[0114] stAx+By n ≤b+Fξ n ,ξ n ∈Ω (19)

[0115] Among them, Ω is the critical pole set, ξ n represents the nth critical point, y n Represents the scheduling strategy corresponding to the nth critical pole.

[0116] After solving the energy storage capacity with the key pole set as input, the energy storage capacity is input into the objective function with the maximum infeasibility of the scheduling strategy as the goal, and the objective function is solved to obtain the poles in the uncertainty set. When the value of the objective function is greater than zero, the solved poles in the uncertainty set are added to the key pole set and the key pole set is continuously input into the energy storage capacity configuration model; when the value of the objective function is equal to zero, the energy storage capacity is used as the final result of the solution. The objective function specifically includes:

[0117]

[0118] stB′λ=0,-1≤λ≤0,ξ∈Ξ (20)

[0119] Among them, (λ * ,ξ * ) represents the objective function, λ′ is the coefficient of the objective function, λ′ is the transpose of λ, B′ is the transpose of B, λ * and * is the solution of the objective function, ξ * is the pole in the uncertainty set. During initialization, If the optimal value of the objective function (i.e., the scheduling strategy with the largest infeasibility) is greater than 0, then Ω=Ω∪{ξ *}, if the optimal value is zero, the logic stops and the current energy storage capacity is taken as the final result.

[0120] Among them, the infeasibility of the scheduling strategy is used to measure the amount of additional resources that need to be provided in order to make all poles in the uncertainty set have a dispatchable strategy under the energy storage capacity. Correspondingly, the above key poles are the poles that make the scheduling strategy infeasibility the largest. When the scheduling strategy infeasibility is zero, the optimal solution can be obtained, because based on the energy storage capacity at this time, no additional resources are required.

[0121] In this embodiment, a decomposition algorithm for solving the energy storage capacity configuration model is provided, and the energy storage capacity is solved in combination with the key poles in the uncertainty set. The key poles are obtained by combining the infeasibility of the scheduling strategy. The solved energy storage capacity can meet various scheduling requirements. Therefore, the energy storage capacity that meets the safe operation requirements of the power grid in an uncertain environment can be solved more accurately, further reducing the cost of building a battery energy storage system.

[0122] The energy storage configuration device provided by the present invention is described below. The energy storage configuration device described below and the energy storage configuration method described above can be referenced to each other.

[0123] like Figure 3 As shown, this embodiment provides an energy storage configuration device, including:

[0124] The model acquisition module 301 is used to acquire a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance principle of the power grid according to the uncertain set of the total power of the renewable energy power generation in the power grid and the total load of the power grid, the power of the renewable energy power generation absorbed, the total power of the non-renewable energy units included in the model of the non-renewable energy units, and the net output power of the battery energy storage system included in the model of the battery energy storage system;

[0125] The capacity acquisition module 302 is used to solve the energy storage capacity configuration model with the goal of minimizing the energy storage capacity to obtain the energy storage capacity, and the energy storage capacity is used to construct the battery energy storage system of the power grid according to the energy storage capacity.

[0126] In an exemplary embodiment, the model acquisition module 301 is further used to:

[0127] Based on the historical data of the power grid, an uncertainty set of the total power of renewable energy generation in the power grid and the total load of the power grid is constructed, wherein the uncertainty set includes a reference power corresponding to the total power of renewable energy generation and a reference power corresponding to the total load of the power grid, the maximum absolute deviation of the total power of renewable energy generation and the corresponding reference power is a preset deviation, and the maximum absolute deviation of the total load and the corresponding reference power is the preset deviation;

[0128] Determine the power of the renewable energy power generation to be absorbed, wherein the power of the renewable energy power generation to be absorbed is less than or equal to the total power of the renewable energy power generation in the uncertain set;

[0129] Constructing a model of the non-new energy unit;

[0130] Constructing a model of the battery energy storage system;

[0131] Based on the power balance principle of the power grid, determine that the sum of the total power of the non-new energy units contained in the model of the non-new energy units, the power of the new energy power generation consumed, and the net output power of the battery energy storage system contained in the model of the battery energy storage system is equal to the total load of the power grid, and obtain the energy storage capacity configuration model.

[0132] In an exemplary embodiment, the capacity acquisition module is specifically configured to:

[0133] Constructing an initial set of key poles based on a reference power corresponding to the total power generated by the renewable energy and a reference power corresponding to the total load of the power grid;

[0134] Taking the critical pole set as input, the dispatching strategy as a variable, and the minimum energy storage capacity as a goal, solving the energy storage capacity configuration model to obtain the energy storage capacity, wherein the dispatching strategy includes the total power of the non-new energy units, the power of the new energy generation consumed, the net output power of the battery energy storage system, and the remaining power of the battery energy storage system;

[0135] After solving the energy storage capacity with the key pole set as input, the energy storage capacity is input into the objective function with the maximum infeasibility of the scheduling strategy as the goal, and the objective function is solved to obtain the poles in the uncertainty set. When the value of the objective function is greater than zero, the solved poles in the uncertainty set are added to the key pole set and the key pole set is continued to be input into the energy storage capacity configuration model; when the value of the objective function is equal to zero, the energy storage capacity is used as the final result of the solution.

[0136] In an exemplary embodiment, the model acquisition module 301 is specifically used to: determine the reference power corresponding to the total power of photovoltaic power generation, the reference power corresponding to the total power of wind power generation, and the reference power corresponding to the total load of the power grid in any period of T periods based on the historical data of T periods of several typical days, and construct the following uncertainty set:

[0137]

[0138]

[0139] Wherein, Ξ represents the uncertain set, t period represents any period in T periods, t∈{1,2,…,T}, represents the total power of wind power generation during period t, represents the total photovoltaic power generation during period t, represents the total load of the power grid during period t, ξ t represents the uncertainty in the uncertainty set during period t, which is and The transpose of the matrix formed is, represents the reference power corresponding to the total power of wind power generation in period t, Indicates the reference power corresponding to the total photovoltaic power generation power in period t, represents the reference power corresponding to the total load of the power grid during time period t, and Γ represents the preset deviation.

[0140] In an exemplary embodiment, the model of the non-new energy unit includes:

[0141] G min ≤G t ≤G max ,t=1,2,…,T

[0142] G t -G t-1 ≤R UP

[0143] G t-1 -G t ≤R DOWN

[0144] Among them, G t represents the total power of the thermal power unit in period t, period t-1 represents the period before period t, G max Represents the upper limit of the total power of the thermal power unit, G min Represents the lower limit of the total power of the thermal power unit, R UP represents the threshold of the upward climbing rate of the thermal power unit in the adjacent t period and t-1 period, R DOWN It represents the threshold value of the downward climbing rate of the thermal power unit in the adjacent time period t and time period t-1.

[0145] In an exemplary embodiment, the model of the battery energy storage system includes:

[0146] -S max ≤S t ≤S max ,t=1,2,…,T

[0147] E t =E t-1 -S t

[0148] 0≤E t ≤E max

[0149] Among them, S max represents the power capacity of the battery energy storage system, E max represents the energy capacity of the battery energy storage system, S t represents the net output power of the battery energy storage system during period t, E t Represents the remaining power of the battery energy storage system in period t, which is the remaining power E of the previous period t-1 t-1 With S t The difference.

[0150] In an exemplary embodiment, the model acquisition module 301 is specifically used to:

[0151] Based on the power balance principle of the power grid, a power balance model of the power grid is constructed:

[0152]

[0153]

[0154]

[0155] in, represents the power of the wind power generation absorbed, represents the power of the photovoltaic power generation absorbed;

[0156] Based on the power balance model of the power grid, the energy storage capacity configuration model is constructed with the minimum energy storage capacity as the goal, and the energy storage capacity includes S max and E max .

[0157] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the energy storage configuration method, which includes:

[0158] Acquire a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance principle of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of renewable energy power generation absorbed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system;

[0159] With the goal of minimizing the energy storage capacity, the energy storage capacity configuration model is solved to obtain the energy storage capacity, and the energy storage capacity is used to construct a battery energy storage system of the power grid according to the energy storage capacity.

[0160] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0161] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, and when the program instructions are executed by a computer, the computer can execute the energy storage configuration method provided by the above methods, the method comprising:

[0162] Acquire a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance principle of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of renewable energy power generation absorbed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system;

[0163] With the goal of minimizing the energy storage capacity, the energy storage capacity configuration model is solved to obtain the energy storage capacity, and the energy storage capacity is used to construct a battery energy storage system of the power grid according to the energy storage capacity.

[0164] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method is implemented to perform the above-mentioned energy storage configuration method, the method comprising:

[0165] Acquire a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance principle of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of renewable energy power generation absorbed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system;

[0166] With the goal of minimizing the energy storage capacity, the energy storage capacity configuration model is solved to obtain the energy storage capacity, and the energy storage capacity is used to construct a battery energy storage system of the power grid according to the energy storage capacity.

[0167] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0168] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0169] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for energy storage configuration, characterized in that: include: Acquire a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance principle of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of renewable energy power generation absorbed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system; With the minimum energy storage capacity as the goal, solving the energy storage capacity configuration model to obtain the energy storage capacity, and the energy storage capacity is used to construct a battery energy storage system of the power grid according to the energy storage capacity; The energy storage capacity configuration model is constructed in the following way: Based on the historical data of the power grid, an uncertainty set of the total power of renewable energy generation in the power grid and the total load of the power grid is constructed, wherein the uncertainty set includes a reference power corresponding to the total power of renewable energy generation and a reference power corresponding to the total load of the power grid, the maximum absolute deviation of the total power of renewable energy generation and the corresponding reference power is a preset deviation, and the maximum absolute deviation of the total load of the power grid and the corresponding reference power is the preset deviation; Determine the power of the renewable energy power generation to be absorbed, wherein the power of the renewable energy power generation to be absorbed is less than or equal to the total power of the renewable energy power generation in the uncertain set; Constructing a model of the non-new energy unit; Constructing a model of the battery energy storage system; Based on the power balance principle of the power grid, determine that the sum of the total power of the non-new energy units contained in the model of the non-new energy units, the power of the new energy power generation consumed, and the net output power of the battery energy storage system contained in the model of the battery energy storage system is equal to the total load of the power grid, and obtain the energy storage capacity configuration model; The model of the battery energy storage system also includes the remaining power of the battery energy storage system; the energy storage capacity configuration model is solved with the minimum energy storage capacity as the goal to obtain the energy storage capacity, including: Constructing an initial set of key poles based on a reference power corresponding to the total power generated by the renewable energy and a reference power corresponding to the total load of the power grid; Taking the critical pole set as input, the dispatching strategy as a variable, and the minimum energy storage capacity as a goal, solving the energy storage capacity configuration model to obtain the energy storage capacity, wherein the dispatching strategy includes the total power of the non-new energy units, the power of the new energy generation consumed, the net output power of the battery energy storage system, and the remaining power of the battery energy storage system; After solving the energy storage capacity with the key pole set as input, input the energy storage capacity into the objective function with the maximum infeasibility of the scheduling strategy as the goal, solve the objective function to obtain the poles in the uncertainty set, and when the value of the objective function is greater than zero, add the solved poles in the uncertainty set to the key pole set and continue to input the key pole set into the energy storage capacity configuration model; when the value of the objective function is equal to zero, use the energy storage capacity as the final result of the solution; The method of constructing the total power of renewable energy generation in the power grid and the uncertainty set of the total load of the power grid based on the historical data of the power grid includes: Historical data for each period of time, determine The reference power corresponding to the total power of photovoltaic power generation, the reference power corresponding to the total power of wind power generation and the reference power corresponding to the total load of the power grid in any period of time are constructed, and the following uncertain set is constructed: ； in, represents the uncertain set, Time period display Any time period in the time period, , express The total power of wind power generation during the period, express The total photovoltaic power generation power in the period, express The total load of the power grid during the period, Indicates the uncertainty concentration The uncertainty of the time period is , and The transpose of the matrix formed is, express The reference power corresponding to the total wind power generation power in the period, express The reference power corresponding to the total power of photovoltaic power generation in the period, express The reference power corresponding to the total load of the power grid during the period, represents the preset deviation; The models of the non-new energy units include: ； in, express The total power of thermal power units during the period, Time period display The period before the period, represents the upper limit of the total power of the thermal power unit, represents the lower limit of the total power of the thermal power unit, Indicates adjacent Time period and The threshold of the upward climbing rate of the thermal power unit in the period, Indicates adjacent Time period and The threshold value of the downward ramp rate of the thermal power unit in the time period; The model of the battery energy storage system includes: ； in, represents the power capacity of the battery energy storage system, represents the energy capacity of the battery energy storage system, express The net output power of the battery energy storage system during the period, express The remaining power of the battery energy storage system in the period is Remaining power during the period and The difference between The power balance based on the power grid determines that the sum of the total power of the non-new energy units contained in the model of the non-new energy units, the power of the new energy power generation consumed, and the net output power of the battery energy storage system contained in the model of the battery energy storage system is equal to the total load of the power grid, and obtains the energy storage capacity configuration model, including: Based on the power balance principle of the power grid, a power balance model of the power grid is constructed: ； in, represents the power of the wind power generation absorbed, represents the power of the photovoltaic power generation absorbed; Based on the power balance model of the power grid, the energy storage capacity configuration model is constructed with the minimum energy storage capacity as the goal, and the energy storage capacity includes and .

2. An energy storage configuration device applied to the energy storage configuration method according to claim 1, characterized in that: include: A model acquisition module, used to acquire a constructed energy storage capacity configuration model, wherein the energy storage capacity configuration model is constructed based on the power balance principle of the power grid according to the uncertain set of the total power of renewable energy power generation in the power grid and the total load of the power grid, the power of renewable energy power generation absorbed, the total power of the non-renewable energy units contained in the model of the non-renewable energy units, and the net output power of the battery energy storage system contained in the model of the battery energy storage system; The capacity acquisition module is used to solve the energy storage capacity configuration model with the goal of minimizing the energy storage capacity to obtain the energy storage capacity, and the energy storage capacity is used to construct the battery energy storage system of the power grid according to the energy storage capacity.

3. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the energy storage configuration method as claimed in claim 1 is implemented.

4. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the energy storage configuration method as claimed in claim 1 is implemented.

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