Optimal configuration method based on multiple energy storage models

Abstract

The invention discloses an optimal configuration method based on multiple energy storage models. The method comprises the following steps: acquiring environment data and load data; constructing a micro-grid model according to the environment data and the load data, wherein the micro-grid model comprises the following steps: selecting equipment to configure distributed energy and an energy storage device; configuring basic parameters for each device; setting constraint conditions, and calculating model loss according to a preset objective function; the constraint condition comprises a distributed energy output constraint and an energy storage constraint; updating capacity configuration parameters of the energy storage device according to the model loss; according to the new energy output, the optimal configuration can be found in different types of energy storage devices by taking the minimum sum of the loss of the abandoned electric quantity and the cost of the energy storage battery as an objective function and considering the capacity of the energy storage battery and the maximum power constraint of charging and discharging.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrid energy storage configuration, and more specifically, to an optimal configuration method based on multiple energy storage models. Background Art

[0002] At present, energy storage technology is an effective means to alleviate the grid connection pressure of large-scale renewable energy. Energy storage technology can be used to solve the problems of discontinuous and uncontrollable power generation of renewable energy such as wind energy and solar energy, and ensure its controllable grid connection and on-demand distribution at ultra-short-term and real-time scales.

[0003] However, with the expansion of the installed capacity of large-scale renewable energy, high-performance energy storage devices need to be configured. In a microgrid, multiple distributed energy sources and energy storage devices often need to be configured according to requirements.

[0004] Therefore, how to quickly configure the optimal energy storage strategy based on multiple energy storage models is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides an optimal configuration method based on multiple energy storage models, which can, according to the output of new energy, take the sum of the curtailment loss and the energy storage battery cost as the objective function, consider the energy storage battery capacity and the constraints of the maximum charge and discharge power, and find the optimal configuration among different types of energy storage devices.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] An optimal configuration method based on multiple energy storage models, comprising the following steps:

[0008] Obtain environmental data and load data.

[0009] Construct a microgrid model according to the environmental data and the load data, including: selecting equipment to configure distributed energy sources and energy storage devices; configuring basic parameters for each device.

[0010] Set constraint conditions, and calculate the model loss according to a preset objective function; the constraint conditions include distributed energy output constraints and energy storage constraints;

[0011] The objective function is: minL = f + C NPC

[0012] f = C ES + E NE,aban × C NE,aban

[0013] C ES = C lnv + C M + Cpel

[0014]

[0015] LCC = C I + C O + C M + C D

[0016] Among them, C ES is the energy storage cost, E NE,aban is the amount of abandoned new energy, C NE,aban is the loss cost per unit of abandoned electricity; C lnv is the investment cost, C M is the maintenance cost, C pel is the charging cost; LCC is the life cycle cost, C I is the equipment purchase cost, C O is the equipment operation cost, C D is the equipment disposal cost; C NPC is the total net present value cost; LCC(m) represents the life cycle cost in the m-th year, including the initial investment cost, replacement cost, operation and maintenance costs, etc.; B(m) is the income in the m-th year, C E,m is the environmental pollution penalty cost, and r0 is the discount rate;

[0017] Update the capacity configuration parameters of the energy storage device according to the model loss.

[0018] Furthermore, the distributed energy includes a photovoltaic power generation system and / or a hydroelectric power generation system; the energy storage device includes an electrochemical energy storage, a hydrogen energy storage, and / or a pumped-storage system.

[0019] Furthermore, the distributed energy output constraints include:

[0020] Photovoltaic charge and discharge constraint: -P ES < P pel < P ES ; among them, P ES represents the maximum energy storage power, and P pel represents the actual energy storage power;

[0021] Photovoltaic output constraint: P PV,min < P PV < P PV,max ; among them, P PV is the output power of the photovoltaic power generation system, P PV,min is the lower limit of photovoltaic output, and P PV,max is the upper limit of photovoltaic output;

[0022] Hydroelectric output constraint: P PR,min < P PR<P PR,max ; where P PR is the output power of the photovoltaic power generation system, P PR,min is the lower limit of photovoltaic output, P PR,max is the upper limit of photovoltaic output

[0023] The energy storage constraint includes:

[0024]

[0025] where Y batn represents the rated capacity of the battery pack, Y batn,max represents the maximum rated capacity allowed for installation of the battery pack; P batn represents the rated power of the battery pack, P batn,max represents the maximum rated power allowed for installation of the battery pack; E represents the rated energy storage capacity, E max represents the maximum rated capacity allowed for installation; η PR represents the pumping - generation efficiency, η PR,min represents the lower limit of the pumping - generation efficiency, η PR,max is the upper limit of the pumping - generation efficiency.

[0026] Furthermore, by importing environmental data, calculate the output power of the photovoltaic power generation system; the environmental data includes solar radiation intensity and temperature; calculate the output power of the photovoltaic power generation system according to the light radiation and temperature:

[0027]

[0028] where Y PV represents the rated capacity of the photovoltaic array, f PV represents the derating factor, G T represents the solar radiation incident on the photovoltaic array within the current time step, G T,STC represents the incident radiation under standard test conditions; α P represents the power temperature coefficient, T c represents the photovoltaic cell temperature in the current time step, T c,STC represents the photovoltaic cell temperature under standard test conditions.

[0029] Furthermore, the pumping - generation efficiency is:

[0030]

[0031] where E P represents the pumped - water volume, E T represents the generated - electricity volume;

[0032] The pumped - water volume of the hydro - power generation system is:

[0033]

[0034] Among them, E P represents the pumped water power, H P represents the average pumping head, V S represents the regulated water volume, η P represents the pumping efficiency of the water pump;

[0035] The generated power of the hydropower system is:

[0036]

[0037] Among them, E T represents the generated power, H T represents the average generating head, η T represents the operating efficiency of the generator;

[0038] The energy storage capacity of the pumped - storage system is:

[0039] E = 9.81ρ water V res h head η

[0040] η = η T η P

[0041] Among them, E represents the energy storage capacity, ρ water represents the density of water, V res represents the reservoir volume, h head represents the head height, and η represents the efficiency of energy conversion.

[0042] Furthermore, the operating efficiency of the generator is:

[0043] η T = η1η2η3η4

[0044] Among them, η1, η 2、 η3, η4 respectively represent the operating efficiencies of the water conveyance system, water turbine, generator, and main transformer under the generating condition;

[0045] The pumping efficiency of the water pump is:

[0046] η P = η5η6η7η8

[0047] Among them, η5, η6, η7, η8 respectively represent the operating efficiencies of the water conveyance system, water turbine, generator, and main transformer under the pumping condition.

[0048] Furthermore, constructing the micro - grid model also includes:

[0049] The distributed energy source, power grid, and load are all connected to the AC bus, and the energy storage device is connected to the DC bus; the AC bus and the DC bus are connected through a bidirectional converter.

[0050] Furthermore, in the microgrid model, the distributed energy source includes a hydropower system; the energy storage device includes a parallel reservoir; the constraint conditions include constraining the water supply sequence of each reservoir according to the non-storage water volume of each reservoir.

[0051] Furthermore, the specific method of constraining the water supply sequence of each reservoir according to the non-storage water volume of each reservoir is as follows:

[0052] Calculate the K value according to the non-storage water volume of each reservoir, and select the reservoir with a smaller K value for priority water supply;

[0053]

[0054] Among them, W 不蓄 represents the non-storage water volume, F represents the reservoir area, and H represents the drawdown depth.

[0055] Through the above technical solutions, it can be seen that compared with the prior art, the present invention discloses an optimal configuration method based on a multi-energy storage model. The present invention can, with the sum of the curtailment loss and the energy storage battery cost as the objective function according to the output of the distributed energy source, consider the energy storage battery capacity and the constraints of the maximum charge and discharge power, and find the optimal configuration among different types of energy storage devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0057] Figure 1 It is a schematic diagram of an optimal configuration method based on a multi-energy storage model provided by the present invention.

[0058] Figure 2 It is a schematic diagram of the microgrid model structure of the electric-hydrogen hybrid energy storage in the embodiment of the present invention.

[0059] Figure 3 It is a schematic diagram of the microgrid model structure of the electrochemical energy storage in the embodiment of the present invention.

[0060] Figure 4 It is a working principle diagram of the pumped-storage energy storage in the implementation of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0061] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0062] An embodiment of the present invention discloses an optimal configuration method based on a multi-energy storage model, as Figure 1 , including the following steps:

[0063] S1: Obtain environmental data and load data;

[0064] S2: Construct a microgrid model according to the environmental data and the load data, including: selecting equipment to configure distributed energy and energy storage devices; configuring basic parameters for each device;

[0065] S3: Set constraint conditions and calculate the model loss according to a preset objective function; the constraint conditions include distributed energy output constraints and energy storage constraints;

[0066] The objective function is: minL = f + C NPC

[0067] f = C ES + E NE,aban × C NE,aban

[0068] C ES = C lnv + C M + C pel

[0069]

[0070] LCC = C I + C O + C M + C D

[0071] Among them, C ES is the energy storage cost, E NE,aban is the abandoned new energy power, C NE,aban is the unit abandoned power loss cost; C lnv is the investment cost, C M is the maintenance cost, C pel is the charging cost; LCC is the life cycle cost, C I is the equipment purchase cost, C O is the equipment operation cost, C D is the equipment disposal cost; C NPCis the total net present value cost; LCC(m) represents the life cycle cost in the m-th year, including the initial investment cost, replacement cost, operation and maintenance cost, etc.; B(m) is the revenue in the m-th year, and C E,m is the environmental pollution penalty cost, and r0 is the discount rate.

[0072] Update the capacity configuration parameters of the energy storage device according to the model loss.

[0073] In this embodiment, the investment cost refers to the cost required for the construction of the energy storage system, including the total costs generated by design, hardware, software, engineering, procurement, construction, etc. The initial investment cost consists of the initial investment capacity and the initial investment power cost.

[0074] C lnv = C p W p + C E Q E

[0075] In the formula, C p is the unit power investment cost; W p is the nominal power capacity; C E is the unit capacity investment cost; Q E is the nominal energy storage capacity.

[0076] The maintenance cost refers to the expenses generated during the annual operation and maintenance of the energy storage system, mainly including the operation and maintenance cost and the operation labor cost.

[0077]

[0078] In the formula, C P-M is the annual unit power maintenance cost; C lab is the annual labor operation cost; N is the operation cycle of the energy storage system.

[0079] The charging cost refers to all the expenses required for the energy storage system to charge from the power grid or renewable energy power sources. The energy storage system needs to charge and discharge during operation. The charging process requires taking power from the power grid or renewable energy, thus generating expenses. The level of the expenses depends on the electricity price and the amount of electricity charged. The charging duration of pumped-storage energy storage is generally 4h, while the charging duration of a large number of new energy storage systems is generally between 0.5 and 3h.

[0080] The net present value cost refers to the present value of all costs for installing and operating components within the project life cycle minus the present value of the revenue obtained.

[0081] To further implement the above technical solution, the distributed energy includes a photovoltaic power generation system and / or a hydraulic power generation system; the energy storage device includes an electrochemical energy storage, a hydrogen energy storage, and / or a pumped storage system. In addition, when constructing a microgrid model, a load and a power grid also need to be configured; the distributed energy, the power grid, and the load are all connected to the AC bus, and the energy storage device is connected to the DC bus; the AC bus and the DC bus are connected through a bidirectional converter.

[0082] In one embodiment, a microgrid energy storage model with an electro-hydrogen hybrid energy storage can be constructed. A hydrogen energy storage system is introduced into the AC-DC hybrid microgrid system, the distributed energy is photovoltaic power generation, the energy storage system includes a lithium battery and a hydrogen energy storage system, and the structure of the grid-connected microgrid system is as Figure 2 , and a microgrid model containing a photovoltaic power generation system, a hydrogen energy storage, a storage battery, a bidirectional converter, a power grid, and an AC load is created in the system. Among them, the storage battery and the hydrogen energy storage system are on the DC bus, the power grid and the photovoltaic power generation system are connected to the AC bus, and the bidirectional converter is between the AC bus and the DC bus, which can not only complete the exchange of alternating current and direct current, but also realize the charging and discharging of the battery.

[0083] In this embodiment, when only considering the configuration with electrochemical energy storage, the model is reconfigured, and the system structure is as Figure 3 .

[0084] To further implement the above technical solution, the distributed energy output constraints include:

[0085] Photovoltaic charge and discharge constraint: -P ES <P pel <P ES ; where P ES represents the maximum energy storage power, and P pel represents the actual energy storage power;

[0086] Photovoltaic output constraint: P PV,min <P PV <P PV,max ; where P PV is the output power of the photovoltaic power generation system, P PV,min is the lower limit of the photovoltaic output, and P PV,max is the upper limit of the photovoltaic output;

[0087] Hydraulic output constraint: P PR,min <P PR <P PR,max ; where P PR is the output power of the photovoltaic power generation system, P PR,min is the lower limit of the photovoltaic output, and P PR,max is the upper limit of the photovoltaic output

[0088] The energy storage constraints include:

[0089]

[0090] Among them, Y batn represents the rated capacity of the battery pack, and Y batn,max represents the maximum rated capacity allowed for the battery pack to be installed; P batn represents the rated power of the battery pack, and P batn,max represents the maximum rated power allowed for the battery pack to be installed; E represents the rated energy storage capacity, and E max represents the maximum rated capacity allowed for installation; η PR represents the pumped-storage power generation efficiency, and η PR,min represents the lower limit of the pumped-storage power generation efficiency, and η PR,max The upper limit of the pumped-storage power generation efficiency.

[0091] In this embodiment, a photovoltaic power generation system is adopted. It is necessary to obtain the light radiation according to historical data to calculate the output of the photovoltaic power generation system, and its output power is:

[0092]

[0093] Among them, Y PV represents the rated capacity of the photovoltaic array, f PV represents the derating factor, G T represents the solar radiation incident on the photovoltaic array within the current time step, and G T,STC represents the incident radiation under standard test conditions; α P represents the power temperature coefficient, T c represents the photovoltaic cell temperature in the current time step, and T c,STC represents the photovoltaic cell temperature under standard test conditions.

[0094] In one embodiment, a microgrid energy storage model for pumped-storage can be constructed. The working principle of pumped-storage is as Figure 4 , and the pumped-storage power station, that is, the hydraulic power generation system, can realize the water cycle between the upper reservoir and the lower reservoir. When there is excess power, the electric energy sent from the power grid is used to drive the motor through the transformer to pump the water in the downstream reservoir to the upstream reservoir, and the electric energy can be converted into the water potential energy of the water body to achieve energy storage; when there is a power shortage, the water body in the upstream reservoir is then released to the downstream through the water potential energy, and at the same time, the water turbine drives the water turbine generator set to generate electricity and convert it into electric energy to the transformer.

[0095] In this embodiment, in a single cycle, the pumped water volume of the hydraulic power generation system is:

[0096]

[0097] Among them, E P represents the pumped water volume, H PDenotes the average pumping head, V S Denotes the regulated water volume, η P Denotes the pumping efficiency of the water pump; η T = η1η2η3η4; η1, η2, η3, and η4 respectively denote the operating efficiencies of the water conveyance system, water turbine, generator, and main transformer under the power generation condition.

[0098] The generated electricity of the hydropower system is:

[0099]

[0100] Where, E T Denotes the generated electricity, H T Denotes the average generating head, η T Denotes the operating efficiency of the generator; η P = η5η6η7η8; η5, η6, η7, and η8 respectively denote the operating efficiencies of the water conveyance system, water turbine, generator, and main transformer under the pumping condition.

[0101] The energy storage capacity of the reservoir in the pumped-storage system is:

[0102] E = 9.81ρ water V res h head η

[0103] η = η T η P

[0104] Where, E denotes the energy storage capacity, ρ water Denotes the density of water, V res Denotes the reservoir volume, h head Denotes the head height, and η denotes the efficiency of energy conversion.

[0105] To further implement the above technical solution, when multiple regulated hydropower and pumped-storage systems in parallel operate jointly, the water supply sequence of each reservoir can be restricted according to the non-storage water volume of each reservoir to achieve the scheduling of the parallel reservoir system and ensure the operation benefits.

[0106] When Systems A and B operate jointly, the total non-storage output that the two power stations can produce is the sum of the non-storage outputs of the two power stations, and then the reservoir water release supplementary output can be obtained.

[0107] When the supplementary output is borne by Power Station A, the flow rate that needs to be released is:

[0108]

[0109] When the supplementary treatment is borne by Power Station B, the flow rate that needs to be released is:

[0110]

[0111] It is deduced that:

[0112] From the above formula, we can know that the drawdown depth of the reservoir will affect the power generation head, and then the non-storage power loss of the two reservoirs is obtained as follows:

[0113] dE 不蓄、甲 =0.00272W 不蓄、甲 dH 甲i η 甲

[0114] dE 不蓄、乙 =0.00272W 不蓄、乙 dH 乙i η 乙

[0115] Where W 不蓄、甲 and W 不蓄、乙 are the non-storage capacity of reservoir A and reservoir B in the water supply period after time period i; η 甲 and η 乙 They represent the power generation efficiency of power stations A and B respectively.

[0116] In order to minimize the loss of non-storage power in the two hydropower stations, the reservoir with less loss will be given priority in water supply. Therefore, the conditions for the priority release of water from Reservoir A are:

[0117]

[0118] In summary, this embodiment uses K to constrain the water supply sequence of each reservoir, and selects reservoirs with smaller K values ​​for priority water supply.

[0119]

[0120] Among them, W 不蓄 represents the amount of water not stored, F represents the reservoir area, and H represents the drawdown depth.

[0121] In this embodiment, the constraint conditions also include not exceeding the maximum energy storage and the scheduling interval.

[0122] Specifically, the maximum energy storage line is determined according to the power generation output of the power station. The maximum energy storage refers to the total energy storage when all reservoirs are fully stored, which can be calculated by the effective water storage capacity and the corresponding available head when the reservoir is fully stored. The theoretical power generation of each regulating reservoir of the cascade hydropower station group when it is discharged to the dead water level can be calculated from top to bottom based on the water level of each reservoir as the upper limit of normal operation, such as the normal water storage level or the flood season operation level, as the maximum energy storage line.

[0123] N=A×H×Q

[0124] Among them, N represents the power generation output, A is the output coefficient, H represents the head, and Q represents the flow rate.

[0125] The function of the upper dispatch line is to increase the output of the hydropower station as early as possible before the reservoir is full in a wet year, reduce the wasted water, and fill the reservoir before the beginning of the dry season. After determining the typical year series of monthly flow combinations that meet the design guarantee rate, in order to fill all reservoirs at the end of the storage period, starting from the condition that all reservoirs are full at the end of the storage period, calculate in reverse chronological order according to the guaranteed output of the hydropower station group. Each calculation period should consider the storage and water supply sequence determined by the discrimination coefficient and the requirements to meet various constraint conditions, and calculate the total stored energy of the hydropower station group at the beginning of the period. In this way, calculate in reverse chronological order from the end of the storage period to the beginning of the water supply period, and then take its upper envelope, that is, the connection of each point of the total stored energy of the hydropower station group as the upper dispatch line of the total dispatch diagram of the hydropower station group.

[0126] The function of the lower dispatch line is to reduce the output of the hydropower station group as early as possible within the allowable range in a dry year outside the guarantee rate, to avoid a large drop in output that the system cannot bear near the end of the water supply period. The method of drawing the lower dispatch line is basically the same as that of the upper dispatch line. Select the typical year series with the monthly guarantee rate meeting the requirements. Starting from the condition that all reservoirs are full at the end of the storage period, calculate the system guaranteed output of the hydropower station group, and at the same time consider the water supply and storage sequence and various constraint conditions determined by the discrimination coefficient. Calculate in reverse chronological order from the end of the storage period to the beginning of the water supply period, and the total stored energy of the hydropower station at each period can be obtained. Connect the points representing the total stored energy and then take its upper envelope to obtain the lower dispatch line.

[0127] The various embodiments in this specification are described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. For the same and similar parts among the various embodiments, reference can be made to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and reference can be made to the description of the method part for related parts.

[0128] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An optimal configuration method based on a multi-energy storage model, characterized in that It includes the following steps: Obtain environmental data and load data; Construct a microgrid model based on the environmental data and the load data, including: select device configurations for distributed energy and energy storage devices; configure basic parameters for each device; Set constraint conditions and calculate the model loss according to a preset objective function; the constraint conditions include distributed energy output constraints and energy storage constraints; The objective function is: minL = f + C NPC f = C ES + E NE,aban × C NE，aban C ES = C lnv + C M + C pel LCC = C I + C O + C M + C D Among them, C ES is the energy storage cost, E NE，aban is the amount of abandoned new energy power, C NE，aban is the cost of loss per unit of abandoned power; C lnv is the investment cost, C M is the maintenance cost, C pel is the charging cost; LCC is the life cycle cost, C I is the equipment purchase cost, C O is the equipment operation cost, C D is the equipment disposal cost; C NPC is the total net present value cost; LCC(m) represents the life cycle cost in the m-th year, including the initial investment cost, replacement cost, operation and maintenance costs, etc.; B(m) is the income in the m-th year, C E，m is the environmental pollution discharge penalty cost, and r0 is the discount rate; Update the capacity configuration parameters of the energy storage device according to the model loss.

2. The optimal configuration method based on a multi-energy storage model according to claim 1, wherein The distributed energy includes a photovoltaic power generation system and / or a hydroelectric power generation system; the energy storage device includes an electrochemical energy storage, a hydrogen energy storage, and / or a pumped-storage system.

3. The optimal configuration method based on a multi-energy storage model according to claim 2, wherein The distributed energy output constraints include: Photovoltaic charge and discharge constraint: -P ES <P pel <P ES ; where P ES represents the maximum energy storage power, and P pel represents the actual energy storage power; Photovoltaic output constraint: P PV，min < P PV < P PV，max ; where, P PV is the output power of the photovoltaic power generation system, P PV，min is the lower limit of photovoltaic output, P PV，max is the upper limit of photovoltaic output; Hydraulic output constraint: P PR，min <P PR <P PR，max ; where, P PR is the output power of the photovoltaic power generation system, P PR，min is the lower limit of photovoltaic output, P PR，max is the upper limit of photovoltaic output; The energy storage constraints include: Among them, Y batn represents the rated capacity of the battery pack, and Y batn，max represents the maximum rated capacity allowed for installation of the battery pack; P batn represents the rated power of the battery pack, and P batn，max represents the maximum rated power allowed for installation of the battery pack; E represents the rated energy storage capacity, and E max represents the maximum rated capacity allowed for installation; η PR represents the pumping - generation efficiency, and η PR，min represents the lower limit of the pumping - generation efficiency, and η PR，max the upper limit of the pumping - generation efficiency.

4. The optimal configuration method based on a multi-energy storage model according to claim 3, wherein Calculate the output power of the photovoltaic power generation system by importing environmental data; The environmental data includes solar radiation intensity and temperature; calculate the output power of the photovoltaic power generation system according to the light radiation and temperature: Among them, Y PV represents the rated capacity of the photovoltaic array, f PV represents the derating factor, G T represents the solar radiation incident on the photovoltaic array within the current time step, G T,STC represents the incident radiation under standard test conditions; α P represents the power temperature coefficient, T c represents the photovoltaic cell temperature in the current time step, T c,STC represents the photovoltaic cell temperature under standard test conditions.

5. The optimal configuration method based on a multi-energy storage model according to claim 3, characterized in that The pumped-storage power generation efficiency is: Among them, E P represents the pumped water power, and E T represents the generated power; The pumped water volume of the hydroelectric power generation system is: Among them, E P represents the pumping power consumption, H P represents the average pumping head, V S represents the regulated water volume, η P represents the pumping efficiency of the water pump; The generated electricity volume of the hydroelectric power generation system is: Among them, E T represents the generated electricity, H T represents the average generating head, η T represents the operating efficiency of the generator; The energy storage capacity of the pumped-storage system is: E = 9.81ρ water V res h head η η = η T η P Among them, E represents the energy storage capacity, ρ water represents the density of water, V res represents the reservoir volume, h head represents the head height, and η represents the efficiency of energy conversion.

6. The optimal configuration method based on a multi-energy storage model according to claim 5, wherein The operating efficiency of the generator is: η T = η1η2η3η4 Wherein, η1, η2, η3, and η4 respectively represent the operating efficiencies of the water conveyance system, the water turbine, the generator, and the main transformer under the power generation condition; The pumping efficiency of the water pump is: η P = η5η6η7η8 Wherein, η5, η6, η7, and η8 respectively represent the operating efficiencies of the water conveyance system, the water turbine, the generator, and the main transformer under the pumping condition.

7. The optimal configuration method based on a multi-energy storage model according to claim 1 or 2, characterized in that The constructing of the microgrid model further includes: Connect the configured distributed grid model and load model energy to the AC bus; connect the configured energy storage device to the DC bus; the AC bus and the DC bus are connected through a bidirectional converter.

8. The optimal configuration method based on a multi-energy storage model according to claim 2, characterized in that In the microgrid model, the distributed energy includes a hydroelectric power generation system; the energy storage device includes a parallel reservoir; the constraint conditions include, according to the non-storage water volume of each reservoir, restricting the water supply sequence of each reservoir.

9. The optimal configuration method based on a multi-energy storage model according to claim 8, characterized in that The restricting the water supply sequence of each reservoir according to the non-storage water volume of each reservoir is specifically: Calculate the K value according to the non-storage water volume of each reservoir and select the reservoir with a smaller K value for priority water supply; Among them, W 不蓄 represents the non-storage water volume, F represents the reservoir area, and H represents the drawdown depth.

10. The optimal configuration method based on a multi-energy storage model according to claim 8, wherein The constraint conditions further include not exceeding the maximum energy storage and the scheduling interval.

Images