Method and device for configuring hybrid energy storage system

Abstract

The invention discloses a method and device for configuring a hybrid energy storage system, and the method comprises the steps: giving an operation model of the hybrid energy storage system according to the operation characteristics of the hybrid energy storage system; establishing a target function containing the economical efficiency of the power system by combining a peak regulation scene and a fluctuation stabilization scene; determining a configuration optimization constraint for the hybrid energy storage system according to the energy storage demand of the power system in combination with the operation model of the hybrid energy storage system; and optimizing the configuration of the hybrid energy storage system based on the objective function in combination with the configuration optimization constraint, and giving an optimization result. According to the method, the operation models of the gravity energy storage subsystem and the electrochemical energy storage subsystem are established, the target function with the economic benefit of the power system as the core is established according to the scene of peak regulation and fluctuation stabilization, and the configuration of the hybrid energy storage system is completed in combination with the set configuration optimization constraint. The performance of the hybrid energy storage system and the economic benefit of the power system are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of hybrid energy storage optimization, and specifically relates to a method and device for configuring a hybrid energy storage system. Background Art

[0002] The output power of renewable energy power plants is characterized by randomness and volatility, which has a negative impact on the stability and security of the power system. Therefore, large-scale access to renewable energy puts forward higher requirements for peak load regulation of the power system and smoothing of wind and solar fluctuations.

[0003] For example, patent CN117767376A discloses a hybrid energy storage system capacity optimization configuration method and system, which determines a grid-connected fluctuation capacity limit with the best smoothing effect from multiple grid-connected fluctuation capacity limits for any day of the wind power output scenario with the largest number of days, and then determines the power curve of the hybrid energy storage system in the annual wind power output data set based on the grid-connected fluctuation capacity limit; comprehensively considers the average annual cost of the hybrid energy storage system, the opportunity compensation cost of wind power fluctuations, the power curve of the hybrid energy storage system and various constraints, and constructs a hybrid energy storage system capacity configuration model; with the goal of minimizing costs, solves the hybrid energy storage system capacity configuration model, and determines the optimal flywheel rated capacity and lithium battery rated capacity. By finding the optimal capacity configuration of the hybrid energy storage system, the defects of the existing hybrid energy storage system energy storage are improved, so as to maximize the benefits of the hybrid energy storage system in smoothing wind power fluctuations.

[0004] As an "energy-type" energy storage, gravity energy storage has the advantages of long cycle charging and discharging service life, high safety, large capacity, no pollution, and large-scale construction. It is suitable for peak load regulation in power systems, black start of microgrids, and other scenarios. As a new energy storage technology, the hybrid energy storage system with gravity energy storage can combine other types of energy storage with gravity energy storage, comprehensively utilize the advantages of multiple energy storage technologies, and make up for the shortcomings of single gravity energy storage.

[0005] However, due to the problems of slow response speed and low energy density of gravity energy storage, how to balance the configuration of gravity energy storage and other energy storage in the hybrid energy storage system to improve the performance of the hybrid energy storage system and the economic benefits of the power system is a problem that needs to be solved at present. Summary of the invention

[0006] In view of the defects existing in the above-mentioned prior art, the present invention provides a method for configuring a hybrid energy storage system, comprising:

[0007] According to the operation characteristics of the hybrid energy storage system, the operation model of the hybrid energy storage system is given, wherein the hybrid energy storage system includes a gravity energy storage subsystem and an electrochemical energy storage subsystem;

[0008] Combine the peak load regulation and fluctuation smoothing scenarios to establish an objective function including the economic efficiency of the power system;

[0009] According to the energy storage demand of the power system and in combination with the operation model of the hybrid energy storage system, the configuration optimization constraints for the hybrid energy storage system are determined, wherein the configuration optimization constraints include gravity charging and discharging constraints determined based on the power system;

[0010] Based on the objective function and combined with the configuration optimization constraints, the configuration of the hybrid energy storage system is completed.

[0011] In a possible implementation, according to the operating characteristics of the hybrid energy storage system, an operating model of the hybrid energy storage system is provided, including:

[0012] For the electrochemical energy storage subsystem, combined with the working state of the electrochemical energy storage subsystem, an operation model of the electrochemical energy storage subsystem is constructed, wherein the operation model of the electrochemical energy storage subsystem includes the correlation between the storage capacity, charge and discharge power, charge and discharge efficiency and charge state of the electrochemical energy storage subsystem;

[0013] For the gravity energy storage subsystem, combined with the working state of the gravity energy storage subsystem, an operation model of the gravity energy storage subsystem is constructed, wherein the operation model of the gravity energy storage subsystem includes the correlation between the storage capacity, charge and discharge power, charge and discharge efficiency and charge state of the gravity energy storage subsystem.

[0014] In a possible implementation, the peak load regulation and fluctuation smoothing scenarios are combined to establish an objective function including the economic performance of the power system, including:

[0015] For peak load shaving scenarios, determine the peak load shaving benefits and energy storage operation and maintenance costs;

[0016] Determine the contact line fluctuation penalty for fluctuation smoothing scenarios;

[0017] According to the grid-connected revenue, peak-shaving revenue, energy storage operation and maintenance cost and interconnection line fluctuation penalty, an objective function is established, where the objective function is the configuration result of the maximum total economic benefit of the hybrid energy storage system.

[0018] In a possible implementation manner, the tie line fluctuation penalty is specifically expressed as:

[0019] C2=(P g,t -P g,t-1 ) 2 c l Δt

[0020] Among them, C2 is the tie line fluctuation penalty, which is the economic cost paid due to the power fluctuation of the tie line, P g,t is the power of the tie line in period t, P g,t-1is the power of the tie line in period t-1, c l is the tie line fluctuation penalty coefficient, and Δt is the duration of period t.

[0021] In a possible implementation, according to the energy storage demand of the power system and in combination with the operation model of the hybrid energy storage system, the configuration optimization constraints for the hybrid energy storage system are determined, including:

[0022] According to the energy storage demand of the power system, combined with the operation model of the electrochemical energy storage subsystem and the operation model of the gravity energy storage subsystem, the power constraint and the state of charge constraint of the power system are determined;

[0023] Determine electrochemical charge and discharge constraints based on the operation model of the electrochemical energy storage subsystem;

[0024] Based on the operation model of the gravity energy storage subsystem, the gravity charging and discharging constraints and the gravity climbing constraints are determined, where the gravity climbing constraints are specifically expressed as:

[0025]

[0026] Where K is the climbing rate of the gravity energy storage subsystem, P GB (t-1) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during the period t-1, P GB (t) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during period t, and Δt is the duration of period t.

[0027] In a possible implementation manner, the power constraint of the power system is specifically expressed as:

[0028] P p,t +P ES,t +P BG,t =P g,t

[0029] Among them, P p,t is the actual power of other types of power generation in the power system during period t, P BG,t is the actual power of the gravity energy storage subsystem in period t, P ES,t is the actual power of the electrochemical energy storage subsystem in period t, P g,t is the power of the tie line in period t, P g,t Used to reflect the energy storage demand of the power system.

[0030] In a possible implementation, the gravity charge and discharge constraint is specifically expressed as:

[0031]

[0032] Among them, P GB(t) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during period t, is the minimum charging power of the gravity energy storage subsystem, is the maximum charging power of the gravity energy storage subsystem, is the minimum discharge power of the gravity energy storage subsystem, is the maximum discharge power of the gravity energy storage subsystem.

[0033] In a possible implementation, the minimum charging power and the maximum charging power of the gravity energy storage subsystem are specifically expressed as:

[0034]

[0035] in, is the maximum power that the gravity energy storage subsystem can absorb from the power system during period t, is the minimum power that the gravity energy storage subsystem can absorb from the power system in period t, n is the number of gravity energy storage units that have been put into operation in the gravity energy storage subsystem, Δt is the evaluation period, d gra is the adjustable power of the gravity energy storage subsystem during the evaluation period, P single is the power change corresponding to a single weight block in the gravity energy storage unit of the gravity energy storage subsystem, ΔT gra is the time period required for the weight block to switch, N gra,n is the number of weight blocks in the nth gravity energy storage unit in the gravity energy storage subsystem.

[0036] In a possible implementation, based on the objective function and in combination with the configuration optimization constraint, the configuration of the hybrid energy storage system is optimized and an optimization result is given, including:

[0037] Initialize the energy storage capacity and rated power of the gravity energy storage subsystem and the energy storage capacity and rated power of the electrochemical energy storage subsystem;

[0038] Determine the inertia weight, iteration threshold, learning factor, and social learning factor;

[0039] According to the objective function and the configuration optimization constraints, iterate and obtain the iterative result;

[0040] Determine the fitness corresponding to the iteration result according to the configuration capacity and rated power of the gravity energy storage subsystem and the configuration capacity and rated power of the electrochemical energy storage subsystem corresponding to the iteration result;

[0041] When the fitness reaches the fitness threshold or the number of iterations exceeds the iteration threshold, the optimization result is determined, and the optimization result includes the maximum total economic benefit of the hybrid energy storage system, the configuration capacity and rated power of the gravity energy storage subsystem, and the configuration capacity and rated power of the electrochemical energy storage subsystem.

[0042] The present invention also discloses a device for configuring a hybrid energy storage system, comprising:

[0043] A model determination module is used to provide an operation model of the hybrid energy storage system according to the operation characteristics of the hybrid energy storage system, wherein the hybrid energy storage system includes a gravity energy storage subsystem and an electrochemical energy storage subsystem;

[0044] Function building module, used to combine peak load regulation and fluctuation smoothing scenarios to build an objective function including power system economics;

[0045] A constraint determination module, used to determine the configuration optimization constraints for the hybrid energy storage system according to the energy storage demand of the power system and in combination with the operation model of the hybrid energy storage system, wherein the configuration optimization constraints include gravity charging and discharging constraints determined based on the power system;

[0046] The optimization analysis module is used to complete the configuration of the hybrid energy storage system based on the objective function and combined with the configuration optimization constraints.

[0047] The method for configuring a hybrid energy storage system provided by the present invention has at least the following beneficial effects:

[0048] By establishing the operation models of the gravity energy storage subsystem and the electrochemical energy storage subsystem, and based on the peak shaving and fluctuation smoothing scenarios, an objective function with the economic benefits of the power system as the core is established. Combined with the set configuration optimization constraints, the configuration of the hybrid energy storage system is completed, achieving improvements in the performance of the hybrid energy storage system and the economic benefits of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A flow chart of a method for configuring a hybrid energy storage system provided by an embodiment of the present invention;

[0050] Figure 2 A flow chart of establishing an objective function including power system economics provided by an embodiment of the present invention;

[0051] Figure 3 A flow chart of a particle swarm optimization algorithm provided by an embodiment of the present invention;

[0052] Figure 4 A diagram showing the fluctuation smoothing effect of the hybrid energy storage system provided by an embodiment of the present invention;

[0053] Figure 5 A structural diagram of a device for configuring a hybrid energy storage system provided in an embodiment of the present invention.

[0054] Among them, 201 is a model determination module; 202 is a function establishment module; 203 is a constraint determination module; 204 is an optimization analysis module. DETAILED DESCRIPTION

[0055] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only 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 making creative work are within the scope of protection of the present invention.

[0056] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0057] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0058] Building a new power system with clean energy as the main body is the trend of future development. However, while the large-scale application of clean energy brings huge economic and environmental benefits to the power system, it has also become a major problem in building a new power system. Due to the intermittent and random characteristics of clean energy, the output power of new energy power fields is random and volatile, which affects the quality of electricity and the stability of power supply. Therefore, the emergence of hybrid energy storage systems solves the problem that a single energy storage technology cannot meet the needs of complex power systems, achieves technical and economic complementarity, and is the development trend of the energy storage industry.

[0059] At present, energy storage device systems such as batteries, supercapacitors, and flywheel energy storage have been widely used in the integration and power smoothing of renewable energy generation. Batteries are common energy storage units with higher energy density, suitable for large-capacity energy storage but relatively slow ramp charging and discharging processes; supercapacitors are power storage units with higher power density and lower energy volume, but their power exchange regulation is more flexible. Considering the trade-off between economic cost and technical capabilities, most studies use battery energy storage technology or supercapacitor energy storage technology to reduce the volatility of wind power output. Compared with energy storage methods such as batteries, mechanical energy storage systems have the advantages of long life cycle and environmental friendliness, and have been widely used in power smoothing, quality regulation and voltage recovery of wind turbine systems.

[0060] Hybrid energy storage systems can not only improve the flexibility and efficiency of energy storage, but also show higher adaptability in different application scenarios. For example, battery energy storage can provide fast-response short-term power supply, while gravity energy storage is suitable for long-term, large-scale energy storage. Through the combination of the two, hybrid energy storage systems can provide more stable and reliable solutions in terms of power system peak regulation, wind and solar fluctuations, and promotion of new energy consumption, further promoting energy transformation and sustainable development.

[0061] Gravity energy storage belongs to mechanical energy storage, and its energy storage medium is mainly solid matter and water. The basic principle of gravity energy storage is to raise and lower the energy storage medium based on the height difference, so as to complete the charging and discharging process of the energy storage system. Gravity energy storage uses the surplus electric energy generated by new energy to lift the gravity block for "charging", and then put down the gravity block when the power consumption is at its peak, and use gravity to do work to "discharge", thereby providing power for the power system.

[0062] However, the application of gravity energy storage is still in its infancy. The research focus of gravity energy storage is mainly on the control strategy within the gravity energy storage system and the grid-connected control strategy of a single unit. There are still obvious deficiencies in the capacity configuration of gravity energy storage, especially the research on capacity optimization configuration combining gravity energy storage with other energy storage technologies is relatively lacking, which is not conducive to improving the performance and economy of hybrid energy storage systems containing gravity energy storage. Therefore, in order to improve the performance and economic benefits of hybrid energy storage systems containing gravity energy storage, the present invention proposes a method for configuring a hybrid energy storage system, by analyzing the operating characteristics of the hybrid energy storage system, constructing an operating model of the hybrid energy storage system, and then combining the peak load and fluctuation smoothing scenarios and the energy storage requirements of the power system under different operating scenarios, establishing an objective function and configuration optimization constraints, based on which the configuration of the hybrid energy storage system is optimized to obtain an optimization result.

[0063] like Figure 1 As shown, the present invention provides a method for configuring a hybrid energy storage system, the specific steps comprising:

[0064] S101: According to the operating characteristics of the hybrid energy storage system, an operating model of the hybrid energy storage system is provided.

[0065] Specifically, the hybrid energy storage system includes a gravity energy storage subsystem and an electrochemical energy storage subsystem. For the electrochemical energy storage subsystem, combined with the working state of the electrochemical energy storage subsystem, an operation model of the electrochemical energy storage subsystem is constructed, wherein the operation model of the electrochemical energy storage subsystem includes the relationship between the storage capacity, charge and discharge power, charge and discharge efficiency, and charge state of the electrochemical energy storage subsystem. The working state of the electrochemical energy storage subsystem includes the charging state and the discharging state. According to the working state of the electrochemical energy storage subsystem, the operation model of the electrochemical energy storage subsystem is specifically expressed as:

[0066]

[0067] In the formula, E ES (t+1) is the storage capacity of the electrochemical energy storage subsystem in the t+1 period, E ES (t) is the storage capacity of the electrochemical energy storage subsystem in period t, is the charging power of the electrochemical energy storage subsystem during the period t under charging state, is the charging efficiency of the electrochemical energy storage subsystem during the period t under the charging state, is the discharge power of the electrochemical energy storage subsystem in the period t under the discharge state, is the discharge efficiency of the electrochemical energy storage subsystem in the period t under the discharge state, SOC ES (t+1) is the state of charge of the electrochemical energy storage subsystem at time t+1, SOC ES (t) is the charge state of the electrochemical energy storage subsystem in time period t, E ESN is the rated capacity of the electrochemical energy storage subsystem, and Δt is the duration of the period t.

[0068] For the gravity energy storage subsystem, combined with the working state of the gravity energy storage subsystem, the operation model of the gravity energy storage subsystem is constructed, wherein the operation model of the gravity energy storage subsystem includes the relationship between the storage capacity, charging and discharging power, charging and discharging efficiency and charge state of the gravity energy storage subsystem. The working state of the gravity energy storage subsystem includes the charging state and the discharging state. According to the working state of the gravity energy storage subsystem, the operation model of the gravity energy storage subsystem is specifically expressed as follows:

[0069]

[0070] In the formula, E GB (t+1) is the storage capacity of the gravity energy storage subsystem in the t+1 period, E GB (t) is the storage capacity of the gravity energy storage subsystem in period t, is the charging power of the gravity energy storage subsystem in the charging state during the period t, is the charging efficiency of the gravity energy storage subsystem in the charging state within the period t, is the discharge power of the gravity energy storage subsystem in the period t under the discharge state, is the discharge efficiency of the gravity energy storage subsystem in the period t under the discharge state, SOC GB (t+1) is the charge state of the gravity energy storage subsystem at time t+1, SOC GB (t) is the charge state of the gravity energy storage subsystem in time period t, E GBN is the rated capacity of the gravity energy storage subsystem, and Δt is the duration of period t.

[0071] The power system includes power generation, transmission, transformation, distribution and power consumption, as well as secondary facilities such as regulation and control, relay protection, safety automatic devices, metering devices, dispatching automation and power communication required to ensure its normal operation. The main structure of the power system is mainly composed of power sources (such as hydropower stations, thermal power plants, nuclear power plants and other power plants), substations (such as step-up substations, load center substations, etc.), transmission and distribution lines and load centers. The power supply points are connected to each other through transmission lines to realize the exchange and regulation of electric energy between different regions, thereby improving the safety and economy of power supply. The function of the power system is to convert the primary energy of nature into electric energy through power generation devices, and then supply the electric energy to each user through transmission, transformation and distribution.

[0072] In a power system that includes renewable energy generation, the large-scale access of renewable energy leads to poor frequency stability of the power system, so energy storage systems with frequency regulation capabilities have become a rigid demand. Hybrid energy storage systems can maximize the advantages of different energy storage systems, provide short-term high power and long-term energy output, and thus achieve universal application of hybrid energy storage systems at lower investment and operating costs.

[0073] By connecting the hybrid energy storage system to the power system, the hybrid energy storage system can store electricity when the power system load is low, and release electricity when the power system load is peak, providing the power system with stable voltage and frequency output, and enhancing the stability and reliability of the power system. There is a close complementary relationship between the power system and the hybrid energy storage system, which together constitute the flexibility and stability of the power system.

[0074] S102: Combine the peak load regulation and fluctuation smoothing scenarios to establish an objective function including the economic efficiency of the power system.

[0075] Specifically, Figure 2 As shown in the figure, for the peak load shaving scenario, the peak load shaving revenue and the energy storage operation and maintenance cost are determined. For the fluctuation smoothing scenario, the interconnection line fluctuation penalty is determined. According to the grid-connected revenue, peak load shaving revenue, energy storage operation and maintenance cost and interconnection line fluctuation penalty, an objective function is established, where the objective function is the configuration result of the maximum total economic benefit of the hybrid energy storage system.

[0076] It is important to understand that peak load regulation refers to the process in which the power system adjusts the output of generators according to changes in power load to maintain power balance and keep the system frequency stable. This is because electricity cannot be stored in large quantities, and the generation and use of electricity are synchronized. The power generation department must generate the same amount of electricity as required, so the power load in the power system often changes.

[0077] Since the power load is uneven, the power system is often overloaded during peak power consumption. At this time, it is necessary to use generators other than normal operation to adjust the peak power consumption to meet the demand. These generators are called peak-shaving units. The requirements for peak-shaving units are that they are easy to start and stop, and easy to adjust synchronously when connected to the grid.

[0078] Power system fluctuation suppression refers to reducing power, voltage and frequency fluctuations in the power system through various technologies and means to ensure the stable operation of the power system. Power system fluctuations refer to power fluctuations caused by mismatch between power generation and power consumption, voltage fluctuations caused by the loss of supply and demand balance of reactive power in the power system, and frequency fluctuations caused by the loss of balance of active power. Power fluctuations can lead to voltage instability, equipment damage, and reduced power supply quality, which can seriously affect the normal production and life of power users. Voltage fluctuations can affect the normal operation of equipment and the stability of the power system. Frequency fluctuations can affect voltage, and in severe cases, can have a bad impact on the operation of generators.

[0079] Fluctuation smoothing can be achieved through the complementarity of multiple energy sources and optimized scheduling. By combining wind energy, solar energy with hydropower, thermal power generation, etc., and taking advantage of the characteristics of different energy generation, complementary operation can be achieved. At the same time, prediction technology is used to accurately predict the power generation of renewable energy so that scheduling arrangements can be made in advance. Fluctuation smoothing can also be achieved through energy storage technology. The energy storage system can store energy when there is excess power generation and release energy when there is insufficient power generation, thereby smoothing power fluctuations. Through these methods and technologies, the fluctuations of the power system can be effectively smoothed, ensuring the stable operation of the power system and meeting the needs of users.

[0080] The specific income from Internet access is as follows:

[0081]

[0082] Where F1 is the income from renewable energy generation in the power system, P g,t is the power of the tie line in period t, P c,t is the charging power of the hybrid energy storage system in period t, P d,t is the discharge power of the hybrid energy storage system in period t, c1 is the on-grid electricity price of renewable energy power generation in the power system, and Δt is the duration of period t. In a specific example, Δt is one hour.

[0083] Peak load regulation benefits refer to the economic benefits of the hybrid energy storage system that charges during low load periods and discharges during peak load periods, using time-of-use electricity prices to participate in peak-valley arbitrage. Specifically, it can be expressed as:

[0084]

[0085] Where F2 is the peak load benefit of the hybrid energy storage system, P d,t is the discharge power of the hybrid energy storage system in period t, P c,t is the charging power of the hybrid energy storage system in period t, c2 is the time-of-use electricity price, and Δt is the duration of period t. When calculating the peak-shaving benefit, the present invention uses the difference between the discharge power and the charging power of the hybrid energy storage system as the total peak-shaving power.

[0086] Energy storage operation and maintenance costs refer to the dynamic cost investment incurred by the necessary inspection and maintenance of related facilities to ensure the stable operation of the hybrid energy storage system, which is specifically expressed as:

[0087] C1=(P d,t +P c,t )c ope Δt

[0088] In the formula, C1 is the energy storage operation and maintenance cost, c ope Operation and maintenance costs for each energy storage unit.

[0089] Tie-line fluctuation penalty refers to the economic cost due to tie-line power fluctuation, which is specifically expressed as:

[0090] C2=(P g,t -P g,t-1 ) 2 c l Δt

[0091] Among them, C2 is the tie line fluctuation penalty, which is the economic cost paid due to the power fluctuation of the tie line, P g,t is the power of the tie line in period t, P g,t-1 is the power of the tie line in period t-1, c l is the tie line fluctuation penalty coefficient, and Δt is the duration of period t.

[0092] Tie-line fluctuation penalty refers to the need to punish power fluctuations that exceed a certain range during power system operation, affecting the stability and power supply quality of the power system. This penalty mechanism is intended to encourage power system operators to take measures to reduce tie-line power fluctuations and ensure stable operation of the power system.

[0093] In the power system, the interconnection line is the line connecting the power grids in different regions, and its power fluctuation will affect the stability of the entire system. The power fluctuation of the interconnection line is due to the uncertainty of renewable energy power generation, the uncertainty of the load side of the power system, and the insufficient regulation capacity of the power system. The output of wind and photovoltaic power generation is affected by weather conditions, and there is a large deviation between the predicted value and the actual value, which will cause the power fluctuation of the interconnection line. The construction of the power system has brought about a new electricity consumption mode, the characteristics of the load side have changed, and the total demand has continued to grow, which will increase the risk of power fluctuation of the interconnection line. The regulation capacity of the power system mainly depends on coal-fired power, gas-fired power, pumped storage and hydropower stations with regulation capacity, but the start-stop restrictions, regulation speed and output range of these power sources limit the regulation capacity of the power system.

[0094] In order to reduce the power fluctuation of the interconnection line, power system operators usually use energy storage equipment, dynamic adjustment mechanism and other means. By configuring energy storage equipment, the fluctuation of renewable energy power generation can be smoothed and the sudden change of interconnection line power can be reduced. The interconnection line plan can also be adjusted according to the predicted output of renewable energy to ensure timely adjustment when the reserve is insufficient, so as to give full play to the mutual assistance ability of the interconnected power grid.

[0095] By setting up a tie line fluctuation penalty mechanism, operators are encouraged to take measures to reduce tie line power fluctuations, thereby improving the overall stability of the power system. By reducing tie line power fluctuations, the risks of the system caused by power imbalance are reduced, and the safety and quality of power supply are guaranteed.

[0096] The objective function is specifically expressed as:

[0097] minC=-(F1+F2)+(C1+C2)

[0098] In the formula, F1 is the grid-connected income of the hybrid energy storage system, F2 is the peak-shaving income of the hybrid energy storage system, C1 is the energy storage operation and maintenance cost, and C2 is the interconnection line fluctuation penalty.

[0099] S103: Determine configuration optimization constraints for the hybrid energy storage system based on the energy storage demand of the power system and in combination with an operation model of the hybrid energy storage system.

[0100] Specifically, the configuration optimization constraints include power system power constraints, state of charge constraints of the hybrid energy storage system, electrochemical charge and discharge constraints, gravity charge and discharge constraints, and gravity climbing constraints. According to the energy storage demand of the power system, combined with the operation model of the electrochemical energy storage subsystem and the operation model of the gravity energy storage subsystem, the power system power constraints and state of charge constraints are determined. Based on the operation model of the electrochemical energy storage subsystem, the electrochemical charge and discharge constraints are determined. Based on the operation model of the gravity energy storage subsystem, the gravity charge and discharge constraints and the gravity climbing constraints are determined.

[0101] Furthermore, the power constraint of the power system is specifically expressed as:

[0102] P p,t +P ES,t +P BG,t =P g,t

[0103] Among them, P p,t is the actual power of other types of power generation in the power system during period t, P BG,t is the actual power of the gravity energy storage subsystem in period t, P ES,t is the actual power of the electrochemical energy storage subsystem in period t, P g,t is the power of the tie line in period t, P g,t Used to reflect the energy storage demand of the power system. In a specific implementation, other types of power generation include wind power generation, photovoltaic power generation, etc.

[0104] Furthermore, the state of charge constraint of the hybrid energy storage system is specifically expressed as:

[0105]

[0106] In the formula, SOC t+1 is the state of charge of the hybrid energy storage system at time t+1, SOC t is the state of charge of the hybrid energy storage system in period t, SOC min is the minimum state of charge of the hybrid energy storage system, SOC max is the maximum state of charge of the hybrid energy storage system, η c is the charging efficiency of the hybrid energy storage system, η d is the discharge efficiency of the hybrid energy storage system, E N is the rated capacity of the hybrid energy storage system.

[0107] Furthermore, the electrochemical charge and discharge constraints are specifically expressed as:

[0108]

[0109] Where P ES (t) is the charging and discharging power allocated to the electrochemical energy storage subsystem by the hybrid energy storage system, is the maximum charging power of the electrochemical energy storage subsystem, is the maximum discharge power of the electrochemical energy storage subsystem.

[0110] Furthermore, the gravity charge and discharge constraint is specifically expressed as:

[0111]

[0112] Where P GB(t) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during period t, is the minimum charging power of the gravity energy storage subsystem, is the maximum charging power of the gravity energy storage subsystem, is the minimum discharge power of the gravity energy storage subsystem, is the maximum discharge power of the gravity energy storage subsystem.

[0113] Among them, the minimum charging power and maximum charging power of the gravity energy storage subsystem are specifically expressed as:

[0114]

[0115] In the formula, is the maximum power that the gravity energy storage subsystem can absorb from the power system during period t, is the minimum power that the gravity energy storage subsystem can absorb from the power system in period t, n is the number of gravity energy storage units that have been put into operation in the gravity energy storage subsystem, Δt is the evaluation period, d gra is the adjustable power of the gravity energy storage subsystem during the evaluation period, P single is the power change corresponding to a single weight block in the gravity energy storage unit of the gravity energy storage subsystem, ΔT gra is the time period required for the weight block to switch, N gra,n is the number of weight blocks in the nth gravity energy storage unit in the gravity energy storage subsystem.

[0116] Among them, the minimum discharge power and maximum discharge power of the gravity energy storage subsystem are specifically expressed as:

[0117]

[0118] In the formula, is the maximum power that the gravity energy storage subsystem can send to the power system during period t, is the minimum power that the gravity energy storage subsystem can send to the power system in period t, n is the number of gravity energy storage units that have been put into operation in the gravity energy storage subsystem, Δt is the evaluation period, d gra is the adjustable power of the gravity energy storage subsystem during the evaluation period, P single is the power change corresponding to a single weight block in the gravity energy storage unit of the gravity energy storage subsystem, N gra,n is the number of weight blocks in the nth gravity energy storage unit in the gravity energy storage subsystem.

[0119] Furthermore, the gravity climbing constraint is specifically expressed as:

[0120]

[0121] Where K is the climbing rate of the gravity energy storage subsystem, P GB (t-1) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during the period t-1, P GB (t) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during period t, and Δt is the duration of period t.

[0122] S104: Based on the objective function and in combination with the configuration optimization constraints, complete the configuration of the hybrid energy storage system.

[0123] Specifically, the energy storage capacity and rated power of the gravity energy storage subsystem and the energy storage capacity and rated power of the electrochemical energy storage subsystem are initialized. The inertia weight, the iteration number threshold, the learning factor and the social learning factor are determined. According to the objective function and the configuration optimization constraints, iterations are performed to obtain iteration results. According to the configuration capacity and rated power of the gravity energy storage subsystem and the configuration capacity and rated power of the electrochemical energy storage subsystem corresponding to the iteration results, the fitness corresponding to the iteration results is determined. When the fitness reaches the fitness threshold or the number of iterations exceeds the iteration number threshold, the optimization result is determined, and the optimization result includes the maximum total economic benefit of the hybrid energy storage system, the configuration capacity and rated power of the gravity energy storage subsystem, and the configuration capacity and rated power of the electrochemical energy storage subsystem. Among them, the energy storage capacity refers to the total energy storage capacity of the gravity energy storage subsystem or the electrochemical energy storage subsystem, usually expressed in kilowatt-hours or megawatt-hours. The energy storage capacity reflects the total energy that the energy storage system can store. Configuration capacity refers to the maximum energy storage capacity that the gravity energy storage subsystem or electrochemical energy storage subsystem can provide to the power system load at a certain moment or within a certain period of time, usually expressed in kilowatts or megawatts. Configuration capacity is determined by factors such as the operating status of the gravity energy storage subsystem or electrochemical energy storage subsystem, the charging and discharging status of the battery, and load demand.

[0124] In a specific implementation, the overall economic optimization of the power system and the hybrid energy storage system is taken as the goal, and the particle swarm algorithm is used to solve the optimization result of the hybrid energy storage system. Figure 3 ,First, initialize the parameters in the particle swarm algorithm, including:

[0125] Determine the number of particles and the threshold of the number of iterations, where the number of particles is 4. The particles specifically have the energy storage capacity and rated power of the gravity energy storage subsystem and the energy storage capacity and rated power of the electrochemical energy storage subsystem. The initial values ​​of the 4 particles are positions and velocities randomly generated in the search space, and the historical optimal position and global optimal position of each particle are recorded.

[0126] The iteration number threshold is set according to actual needs or experience.

[0127] Set the inertia weight. The inertia weight plays a role in balancing the global exploration and local development capabilities in the particle swarm algorithm. The inertia weight determines the impact of the previous moment's speed on the next move. By adjusting the inertia weight, the convergence speed and global search ability of the algorithm can be controlled. A larger inertia weight is conducive to global exploration and increases the diversity of the population, while a smaller inertia weight can improve the algorithm's local mining ability and speed up the convergence speed.

[0128] Set the learning factor and social learning factor. The learning factor indicates the degree to which the particle moves to its own historical optimal position, and the social learning factor indicates the degree to which the particle moves to the global optimal position. The learning factor is used to adjust the weight of the particle's update speed based on individual experience, and determines the degree to which the particle pays attention to the individual optimal solution during the search process. A larger learning factor can increase the particle's global search ability, but may cause the particle to oscillate in the search space; a smaller learning factor can increase the particle's local search ability, but may cause it to fall into the local optimal solution. The social learning factor is used to adjust the weight of the particle's update speed based on group experience, and determines the degree to which the particle pays attention to the group optimal solution during the search process. A larger social learning factor can increase the particle's global search ability and help the particle make better use of group information, but it may also cause the particle to oscillate in the search space; a smaller social learning factor can increase the particle's local search ability, but may cause it to fall into the local optimal solution. According to different optimization scenarios, the values ​​of the learning factor and the social learning factor can be manually adjusted at different stages of the particle swarm algorithm to balance the capabilities of global search and local search; the parameters can also be adjusted according to the convergence of the particle swarm algorithm, for example, a larger learning factor and social learning factor can be used in the early stage of the particle swarm algorithm to speed up the global search, and a smaller learning factor and social learning factor can be used in the later stage of the particle swarm algorithm for fine search.

[0129] Secondly, perform iterative solution, including:

[0130] In each iteration, the configuration capacity and rated power of the corresponding electrochemical energy storage subsystem and gravity energy storage subsystem are calculated according to the energy storage capacity and rated power of the current particle;

[0131] For different time periods, determine the power system power constraints, charge state constraints of the hybrid energy storage system, electrochemical charge and discharge constraints, gravity charge and discharge constraints, and gravity climbing constraints corresponding to the time period;

[0132] According to the objective function, the optimization solution is performed. In each iteration, according to the configuration capacity and rated power of the current particle, its fitness is solved and calculated. If the solution is successful, the total cost of the current particle is recorded, that is, the value of the objective function corresponding to the current particle is determined. If the solution fails, the fitness is set to infinity and the optimization iteration process is exited. In a specific example, the YALMIP toolbox and Gurobi solver can be used for optimization solution. In other examples, other methods can be used for solution without limitation. If the solution is successful, continue to update the historical optimal position and global optimal position of the particle as well as the speed and position of each particle, recalculate the fitness, and complete the iteration.

[0133] Finally, when the iteration stop condition is met, the optimization result is obtained, which includes the maximum total economic benefit of the hybrid energy storage system, the configuration capacity and rated power of the gravity energy storage subsystem, and the configuration capacity and rated power of the electrochemical energy storage subsystem.

[0134] In a specific example, the hybrid energy storage system is connected to a wind-solar combined power station A, which includes a wind power generation system with a maximum power of X1 MW and a photovoltaic power generation system with a peak capacity of X2 MW.

[0135] The on-grid electricity price and time-of-use electricity price of a wind-solar combined power station A are shown in Table 1, and the operating parameters of the hybrid energy storage system are shown in Table 2.

[0136] Table 1 On-grid electricity price

[0137]

[0138] Table 2 Operation parameters of hybrid energy storage system

[0139]

[0140] According to the operating parameters of the hybrid energy storage system mentioned above, combined with the established configuration optimization constraints and objective function, the hybrid energy storage system is optimized and solved, and the optimization results of the hybrid energy storage system are shown in Table 3, and the various costs and benefits involved in the objective function are shown in Table 4. In the results of this example, the costs of the hybrid energy storage system are positive, such as energy storage operation and maintenance costs and tie line fluctuation penalties, and the benefits of the system are negative, such as grid-connected benefits and peak-shaving benefits.

[0141] Table 3 Optimization results of hybrid energy storage system

[0142]

[0143] Table 4 Costs and benefits

[0144]

[0145] By analyzing the output of energy storage, it can be seen that the overall trend of the output of the hybrid energy storage system is to perform two charging operations and two discharging operations within 24 hours a day. From the perspective of peak load regulation, during the flat and valley period of time-of-use electricity prices, energy storage uses the surplus electricity of wind-solar combined power station A for charging operations, effectively storing low-priced electricity to prepare for subsequent power supply, while reducing the power abandonment phenomenon of wind-solar combined power station A; during T2:00-T3:00 and T4:00-T5:00 every day, that is, the peak period of time-of-use electricity prices, the power demand of the power system rises sharply, and the hybrid energy storage system performs discharge operations to sell electricity to the power system to meet the power demand of the power system. Therefore, the hybrid energy storage system not only meets the peak load regulation needs of the power system through charging and discharging operations, but also realizes peak-valley arbitrage.

[0146] The fluctuation smoothing effect of the hybrid energy storage system is as follows Figure 4 As shown in the figure, by comparing the interconnection line power before and after optimization, it can be seen that the interconnection line power fluctuation of the power system after optimization is significantly smaller. When the output of wind-solar combined power station A is unstable, the hybrid energy storage system can effectively adjust the power of the power system interconnection line by absorbing or releasing electric energy, thereby reducing its power fluctuation. Therefore, the hybrid energy storage system plays a significant role in smoothing the interconnection line power fluctuation and improving the stability of the power system.

[0147] In order to verify the economy and effectiveness of the optimization results of the hybrid energy storage system, this example sets up three schemes for comparison. The specific schemes are as follows:

[0148] Option 1: The power system is connected to the hybrid energy storage system;

[0149] Option 2: The power system is only connected to the gravity energy storage subsystem;

[0150] Option 3: The power system is only connected to the electrochemical energy storage subsystem.

[0151] The system costs and benefits of the three solutions are compared, as shown in Table 5.

[0152] Table 5 Comparison of costs and benefits of the three schemes

[0153]

[0154] In summary, the method for configuring a hybrid energy storage system provided by the present invention can not only charge during low load periods and discharge during peak load periods to achieve peak load regulation and peak-valley arbitrage in the power system, but also smooth out power fluctuations in the interconnection line and perform fluctuation suppression, thereby maximizing the total economic benefits of the power system while reducing the interconnection line fluctuation penalty.

[0155] Reference Figure 5 , an embodiment of the present invention provides a device for configuring a hybrid energy storage system, comprising:

[0156] A model determination module 201 is used to provide an operation model of the hybrid energy storage system according to the operation characteristics of the hybrid energy storage system, wherein the hybrid energy storage system includes a gravity energy storage subsystem and an electrochemical energy storage subsystem;

[0157] Function establishment module 202, used to establish an objective function including power system economics in combination with peak load regulation and fluctuation smoothing scenarios;

[0158] The constraint determination module 203 is used to determine the configuration optimization constraints for the hybrid energy storage system according to the energy storage demand of the power system and in combination with the operation model of the hybrid energy storage system, wherein the configuration optimization constraints include the gravity charging and discharging constraints determined based on the power system;

[0159] The optimization analysis module 204 is used to complete the configuration of the hybrid energy storage system based on the objective function and in combination with the configuration optimization constraints.

[0160] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0161] Although preferred embodiments of the present invention have been described, additional changes and modifications may be made to these embodiments by those skilled in the art once the basic inventive concepts are known. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for configuring a hybrid energy storage system, characterized in that: include: According to the operation characteristics of the hybrid energy storage system, the operation model of the hybrid energy storage system is given, wherein the hybrid energy storage system includes a gravity energy storage subsystem and an electrochemical energy storage subsystem; Combine the peak load regulation and fluctuation smoothing scenarios to establish an objective function including the economic efficiency of the power system; According to the energy storage demand of the power system and in combination with the operation model of the hybrid energy storage system, the configuration optimization constraints for the hybrid energy storage system are determined, wherein the configuration optimization constraints include gravity charging and discharging constraints determined based on the power system; Based on the objective function and combined with the configuration optimization constraints, the configuration of the hybrid energy storage system is completed.

2. The method for configuring a hybrid energy storage system according to claim 1, characterized in that: According to the operation characteristics of the hybrid energy storage system, an operation model of the hybrid energy storage system is provided, including: For the electrochemical energy storage subsystem, combined with the working state of the electrochemical energy storage subsystem, an operation model of the electrochemical energy storage subsystem is constructed, wherein the operation model of the electrochemical energy storage subsystem includes the correlation between the storage capacity, charge and discharge power, charge and discharge efficiency and charge state of the electrochemical energy storage subsystem; For the gravity energy storage subsystem, combined with the working state of the gravity energy storage subsystem, an operation model of the gravity energy storage subsystem is constructed, wherein the operation model of the gravity energy storage subsystem includes the correlation between the storage capacity, charge and discharge power, charge and discharge efficiency and charge state of the gravity energy storage subsystem.

3. The method for configuring a hybrid energy storage system according to claim 1, characterized in that: The above scenario combines peak load regulation and fluctuation smoothing to establish an objective function containing the economic efficiency of the power system, including: For peak load shaving scenarios, determine the peak load shaving benefits and energy storage operation and maintenance costs; Determine the contact line fluctuation penalty for fluctuation smoothing scenarios; According to the grid-connected revenue, peak-shaving revenue, energy storage operation and maintenance cost and interconnection line fluctuation penalty, an objective function is established, where the objective function is the configuration result of the maximum total economic benefit of the hybrid energy storage system.

4. The method for configuring a hybrid energy storage system according to claim 3, characterized in that: The tie line fluctuation penalty is specifically expressed as: C2=(P g,t -P g,t-1 ) 2 c l Δt Among them, C2 is the tie line fluctuation penalty, which is the economic cost paid due to the power fluctuation of the tie line, P g,t is the power of the tie line in period t, P g,t-1 is the power of the tie line in period t-1, c l is the tie line fluctuation penalty coefficient, and Δt is the duration of period t.

5. The method for configuring a hybrid energy storage system according to claim 1, characterized in that: The configuration optimization constraints for the hybrid energy storage system are determined based on the energy storage demand of the power system and in combination with the operation model of the hybrid energy storage system, including: According to the energy storage demand of the power system, combined with the operation model of the electrochemical energy storage subsystem and the operation model of the gravity energy storage subsystem, the power constraint and the state of charge constraint of the power system are determined; Determine electrochemical charge and discharge constraints based on the operation model of the electrochemical energy storage subsystem; Based on the operation model of the gravity energy storage subsystem, the gravity charging and discharging constraints and the gravity climbing constraints are determined, where the gravity climbing constraints are specifically expressed as: Where K is the climbing rate of the gravity energy storage subsystem, P GB (t-1) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during the period t-1, P GB (t) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during period t, and Δt is the duration of period t.

6. The method for configuring a hybrid energy storage system according to claim 5, characterized in that: The power constraint of the power system is specifically expressed as: P p,t +P ES,t +P BG,t =P g,t Among them, P p,t is the actual power of other types of power generation in the power system during period t, P BG,t is the actual power of the gravity energy storage subsystem in period t, P ES,t is the actual power of the electrochemical energy storage subsystem in period t, P g,t is the power of the tie line in period t, P g,t Used to reflect the energy storage demand of the power system.

7. The method for configuring a hybrid energy storage system according to claim 5, characterized in that: The gravity charge and discharge constraint is specifically expressed as: Among them, P GB (t) is the charging power or discharging power allocated to the gravity energy storage subsystem by the hybrid energy storage system during period t, is the minimum charging power of the gravity energy storage subsystem, is the maximum charging power of the gravity energy storage subsystem, is the minimum discharge power of the gravity energy storage subsystem, is the maximum discharge power of the gravity energy storage subsystem.

8. The method for configuring a hybrid energy storage system according to claim 7, characterized in that: The minimum charging power and maximum charging power of the gravity energy storage subsystem are specifically expressed as: in, is the maximum power that the gravity energy storage subsystem can absorb from the power system during period t, is the minimum power that the gravity energy storage subsystem can absorb from the power system in period t, n is the number of gravity energy storage units that have been put into operation in the gravity energy storage subsystem, Δt is the evaluation period, d gra is the adjustable power of the gravity energy storage subsystem during the evaluation period, P single is the power change corresponding to a single weight block in the gravity energy storage unit of the gravity energy storage subsystem, ΔT gra is the time period required for the weight block to switch, N gra,n is the number of weight blocks in the nth gravity energy storage unit in the gravity energy storage subsystem.

9. The method for configuring a hybrid energy storage system according to claim 1, characterized in that: Based on the objective function and in combination with the configuration optimization constraints, the configuration of the hybrid energy storage system is optimized and the optimization results are given, including: Initialize the energy storage capacity and rated power of the gravity energy storage subsystem and the energy storage capacity and rated power of the electrochemical energy storage subsystem; Determine the inertia weight, iteration threshold, learning factor, and social learning factor; According to the objective function and the configuration optimization constraints, iterate and obtain the iterative result; Determine the fitness corresponding to the iteration result according to the configuration capacity and rated power of the gravity energy storage subsystem and the configuration capacity and rated power of the electrochemical energy storage subsystem corresponding to the iteration result; When the fitness reaches the fitness threshold or the number of iterations exceeds the iteration threshold, the optimization result is determined, and the optimization result includes the maximum total economic benefit of the hybrid energy storage system, the configuration capacity and rated power of the gravity energy storage subsystem, and the configuration capacity and rated power of the electrochemical energy storage subsystem.

10. A device configured with a hybrid energy storage system, characterized in that: A method for configuring a hybrid energy storage system according to any one of claims 1 to 9, comprising: A model determination module is used to provide an operation model of the hybrid energy storage system according to the operation characteristics of the hybrid energy storage system, wherein the hybrid energy storage system includes a gravity energy storage subsystem and an electrochemical energy storage subsystem; Function building module, used to combine peak load regulation and fluctuation smoothing scenarios to build an objective function including power system economics; A constraint determination module, used to determine the configuration optimization constraints for the hybrid energy storage system according to the energy storage demand of the power system and in combination with the operation model of the hybrid energy storage system, wherein the configuration optimization constraints include gravity charging and discharging constraints determined based on the power system; The optimization analysis module is used to complete the configuration of the hybrid energy storage system based on the objective function and combined with the configuration optimization constraints.

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