Energy storage adjustment method and device of virtual power plant, storage medium and electronic equipment

Abstract

The invention discloses an energy storage adjusting method and device of a virtual power plant, a storage medium and electronic equipment, and belongs to the technical field of power systems.The method comprises the steps that an adjusting model and constraint conditions for an energy storage system are established, and the adjusting model takes the minimum capacity of the energy storage system as an objective function; the constraint condition comprises a power balance constraint condition of the virtual power plant, and a variable in the power balance constraint condition comprises a power purchase deviation value between power grid input power of a real-time market and power grid input power of a day-ahead market; constructing a deviation constraint condition and a deviation standard-exceeding constraint condition aiming at the electricity purchasing deviation value; and determining the energy storage adjustment data of the energy storage system according to the adjustment model, the deviation constraint condition and the deviation standard-exceeding constraint condition, thereby effectively avoiding the capacity waste of the energy storage system caused by low-probability extreme weather, and controlling the increase of the electricity price cost caused by the deviation electric quantity. And the electricity price cost in the operation process of the power grid and the construction cost in the planning process achieve a better balance.

Description

Technical Field

[0001] The present application belongs to the technical field of power systems, and in particular, relates to a method, device, storage medium and electronic equipment for regulating energy storage in a virtual power plant. Background Art

[0002] The volatility and intermittency of renewable energy generation will reduce the stability of power system operation. Virtual power plants have attracted much attention due to their good effect in solving the problem of large-scale renewable energy generation access to the grid due to their aggregation of energy storage systems.

[0003] In order to gradually promote the market-oriented reform of the power market, improve the operating efficiency and economic benefits of the power system, and promote the consumption and utilization of new energy, the construction of a power spot pilot project is proposed. The construction of the power spot pilot project subdivides the market transaction time scale, including the day-ahead market and the real-time market. Among them, there is a large price fluctuation risk in the real-time market, and the communication and control system of the industrial plant is relatively complete. Through the coordination of the energy storage system and the flexible load, the power consumption curve of the entire plant is highly consistent with the day-ahead market curve. Therefore, the various components in the industrial plant are very suitable for aggregation into an organic whole to form an industrial plant virtual power plant connected to the large power grid, which can effectively solve the needs of industrial users with large power consumption, high power cost, and high power supply reliability, realize the effective consumption of renewable energy and meet the peak load demand of the system, and at the same time, it can also significantly reduce the emission of industrial gases, which plays a positive role in improving air quality and achieving green and low-carbon development.

[0004] However, the energy storage system in the existing virtual power plant is prone to waste of energy storage system capacity when the power grid is operating, which is not conducive to improving the economic efficiency of industrial plants. Summary of the invention

[0005] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a method, device, storage medium, electronic device and computer program product for regulating energy storage of a virtual power plant, which can achieve a better balance between the electricity price cost during operation and the construction cost during planning.

[0006] In a first aspect, the present application provides an energy storage regulation method for a virtual power plant, wherein the virtual power plant includes an energy storage system connected to a power grid, a photovoltaic system, a traditional power generation system, and a flexible load, and the energy storage regulation method includes:

[0007] Establishing a regulation model and constraints for the energy storage system, wherein the regulation model takes the minimum capacity of the energy storage system as an objective function, the constraints include the power balance constraints of the virtual power plant, the energy storage operation constraints of the energy storage system, the operation power constraints of the traditional power generation system, and the demand response constraints of the flexible loads, and the variables in the power balance constraints include the power purchase deviation value between the grid input power in the real-time market and the grid input power in the day-ahead market;

[0008] Constructing deviation constraint conditions and deviation exceeding constraint conditions for the power purchase deviation value;

[0009] The energy storage regulation data of the energy storage system is determined according to the regulation model, the deviation constraint condition and the deviation exceeding constraint condition.

[0010] In some embodiments, determining the energy storage regulation data of the energy storage system according to the regulation model, the deviation constraint condition and the deviation exceeding constraint condition includes:

[0011] Under the constraint conditions, the deviation constraint conditions and the deviation exceeding constraint conditions, the objective function is solved to obtain energy storage regulation data of the energy storage system.

[0012] In some embodiments, the deviation constraints include:

[0013] |ΔP D (t)|≤α·P DAM (t);

[0014] Among them, ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, P DAM (t) is the grid input power at time t in the day-ahead market, and α is the maximum allowable proportion of the absolute value of the power purchase deviation at time t to the grid input power in the day-ahead market at the same time.

[0015] In some embodiments, the deviation exceeding constraint condition includes:

[0016] R≤β;

[0017] Among them, R is the deviation exceeding the standard ratio at time t, R = N / 8760, N is ΔP D (t)>α·P DAM (t), and β is the maximum allowable value of the deviation excess ratio.

[0018] In some embodiments, the power balance constraint condition includes:

[0019] Pload (t)-P IL (t) = P DAM (t)+P PV (t)-P ch (t)+P diesel (t)+ΔP D (t);

[0020] P load (t)-P IL (t) = P DAM (t)+P PV (t)+P dis (t)+P diesel (t)+ΔP D (t);

[0021] Among them, the first formula represents that the energy storage system is in a charging state, and the second formula represents that the energy storage system is in a discharging state, P pv (t) is the output power of the photovoltaic system at time t, P ch (t) is the charging power of the energy storage system at time t, P dis (t) is the discharge power of the energy storage system at time t, P diesel (t) is the output power of the conventional power generation system at time t, ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, ΔP D (t) = P RTM (t)-P DAM (t), P RTM (t) is the grid input power at time t in the real-time market, P DAM (t) is the grid input power at time t in the day-ahead market power purchase plan, P IL (t) is the power of the flexible load participating in demand response at time t, P load (t) is the power of the total load of the virtual power plant participating in demand response at time t.

[0022] In some embodiments, the energy storage operation constraints include:

[0023]

[0024] Among them, S OC (t) is the state of charge of the energy storage system at time t, S OC (t) = SOC0 – (P dis(t) ·dt) / E N +(P ch(t) ·dt) / E N, SOC0 is the initial state of charge of the energy storage system, E N is the capacity of the energy storage system, is the lower limit of the state of charge of the energy storage system, is the upper limit value of the state of charge of the energy storage system, is the lower limit of the charging power of the energy storage system, is the upper limit of the charging power of the energy storage system, is the lower limit of the discharge power of the energy storage system, is the upper limit of the discharge power of the energy storage system.

[0025] In a second aspect, the present application provides an energy storage regulating device for a virtual power plant, wherein the virtual power plant includes an energy storage system, a photovoltaic system, a traditional power generation system and a flexible load connected to a power grid, and the energy storage regulating device includes:

[0026] Establishing a module for establishing a regulation model and constraints for the energy storage system, wherein the regulation model takes the minimum capacity of the energy storage system as an objective function, the constraints include the power balance constraints of the virtual power plant, the energy storage operation constraints of the energy storage system, the operation power constraints of the traditional power generation system, and the demand response constraints of the flexible load, and the variables in the power balance constraints include the power purchase deviation value between the grid input power of the real-time market and the grid input power of the day-ahead market;

[0027] A construction module, used for constructing a deviation constraint condition and a deviation exceeding constraint condition for the power purchase deviation value;

[0028] A determination module is used to determine the energy storage regulation data of the energy storage system according to the regulation model, the deviation constraint condition and the deviation exceeding constraint condition.

[0029] In some embodiments, the determining module is specifically used to:

[0030] Under the constraint conditions, the deviation constraint conditions and the deviation exceeding constraint conditions, the objective function is solved to obtain energy storage regulation data of the energy storage system.

[0031] In some embodiments, the deviation constraints include:

[0032] |ΔP D (t)|≤α·P DAM (t);

[0033] Where ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, P DAM(t) is the grid input power at time t in the day-ahead market, and α is the maximum allowable proportion of the absolute value of the power purchase deviation at time t to the grid input power in the day-ahead market at the same time.

[0034] In some embodiments, the deviation exceeding constraint condition includes:

[0035] R≤β;

[0036] Among them, R is the deviation exceeding the standard ratio at time t, R = N / 8760, N is ΔP D (t)>α·P DAM (t), and β is the maximum allowable value of the deviation excess ratio.

[0037] In some embodiments, the power balance constraint condition includes:

[0038] P load (t)-P IL (t) = P DAM (t)+P PV (t)-P ch (t)+P diesel (t)+ΔP D (t);

[0039] P load (t)-P IL (t) = P DAM (t)+P PV (t)+P dis (t)+P diesel (t)+ΔP D (t);

[0040] Among them, the first formula represents that the energy storage system is in a charging state, and the second formula represents that the energy storage system is in a discharging state, P pv (t) is the output power of the photovoltaic system at time t, P ch (t) is the charging power of the energy storage system at time t, P dis (t) is the discharge power of the energy storage system at time t, P diesel (t) is the output power of the conventional power generation system at time t, ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, ΔP D (t) = P RTM (t)-P DAM (t), P RTM (t) is the grid input power at time t in the real-time market, P DAM (t) is the grid input power at time t in the day-ahead market power purchase plan, P IL(t) is the power of the flexible load participating in demand response at time t, P load (t) is the power of the total load of the virtual power plant participating in demand response at time t.

[0041] In some embodiments, the energy storage operation constraints include:

[0042]

[0043] Among them, S OC (t) is the state of charge of the energy storage system at time t, S OC (t) = SOC0 – (P dis(t) ·dt) / E N +(P ch(t) ·dt) / E N , SOC0 is the initial state of charge of the energy storage system, E N is the capacity of the energy storage system, is the lower limit of the state of charge of the energy storage system, is the upper limit value of the state of charge of the energy storage system, is the lower limit of the charging power of the energy storage system, is the upper limit of the charging power of the energy storage system, is the lower limit of the discharge power of the energy storage system, is the upper limit of the discharge power of the energy storage system.

[0044] In a third aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the energy storage regulation method for a virtual power plant as described in any one of the above items.

[0045] In a fourth aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the energy storage regulation method for a virtual power plant as described in any one of the above items is implemented.

[0046] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the energy storage regulation method of a virtual power plant as described in any one of the above items.

[0047] The energy storage regulation method, device, storage medium, electronic device and computer program product of the virtual power plant provided in the embodiments of the present application establish a regulation model and constraints for the energy storage system. The regulation model takes the minimum capacity of the energy storage system as the objective function. The constraints include the power balance constraints of the virtual power plant, the energy storage operation constraints of the energy storage system, the operation power constraints of the traditional power generation system and the demand response constraints of the flexible load. The variables in the power balance constraints include the power purchase deviation value between the grid input power of the real-time market and the grid input power of the day-ahead market; construct deviation constraints and deviation exceeding constraints for the power purchase deviation value; determine the energy storage regulation data of the energy storage system according to the regulation model, the deviation constraints and the deviation exceeding constraints for the power purchase deviation value, that is, when optimizing the energy storage system, introduce deviation constraints and deviation exceeding constraints for the power purchase deviation value, thereby effectively avoiding the waste of energy storage system capacity caused by low-probability extreme weather, and controlling the increase in electricity price cost caused by deviation electricity, so as to achieve a better balance between the electricity price cost in the grid operation process and the construction cost in the planning process. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0049] Figure 1 It is a flow chart of the energy storage regulation method of the virtual power plant provided in the embodiment of the present application;

[0050] Figure 2 is a schematic diagram of the topological structure of a virtual power plant provided in an embodiment of the present application;

[0051] Figure 3 It is a structural schematic diagram of an energy storage regulating device of a virtual power plant provided in an embodiment of the present application;

[0052] Figure 4 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0053] Figure 5 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0054] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0055] Explanation of common terms in this application:

[0056] Virtual power plant (VPP): refers to the aggregation of distributed energy resources (DER) such as distributed generators (DG), energy storage systems, controllable loads, electric vehicles, etc. through advanced control, metering, communication and other technologies, and unified management and scheduling through virtualization technology to form a unified virtual energy system. As a special power plant, it can serve as a "positive power plant" to supply power to the system for peak load regulation, and as a "negative power plant" to increase load absorption and coordinate system valley filling.

[0057] Electricity spot market: that is, payment and delivery, physical delivery in a short period of time. It mainly includes the day-ahead market and the real-time market. Among them, the market operator organizes the day-ahead market on a daily basis, based on the day-ahead transaction declaration of market entities, and taking into account the operation of the power grid and physical constraints, to meet the day-ahead market load demand and reserve demand, with the goal of minimizing power generation costs / maximizing social welfare, to conduct centralized optimization and clearing of the day-ahead market, and form the day-ahead market clearing results. On the operation day, the market operator, based on the declaration of market entities, on the basis of the determination of the unit combination, takes into account the actual operation status of the power grid and physical constraints, meets the ultra-short-term load forecast and reserve demand, and takes into account the minimum power generation cost, to conduct real-time market clearing, and form the real-time market clearing results.

[0058] Embodiments of the present application provide a method, device, storage medium, electronic device, and computer program product for regulating energy storage in a virtual power plant.

[0059] See also Figure 1 and Figure 2 , Figure 1 is a flow chart of a method for regulating energy storage in a virtual power plant provided in an embodiment of the present application, Figure 2 Schematic diagram of the topology of a virtual power plant provided in an embodiment of the present application. The energy storage regulation method of the virtual power plant is applied to an electronic device, which can be implemented as a server or a terminal device.

[0060] Among them, Figure 2In the paper, the virtual power plant (industrial virtual power plant) includes energy storage systems, photovoltaic systems, traditional power generation systems and flexible loads connected to the power grid. The virtual power plant also includes other loads, and the traditional power generation system mainly includes diesel generators. According to energy demand, energy flows inside the virtual power plant under the premise of meeting power balance and energy storage system performance constraints. The function of the energy storage system is to smooth the fluctuation of photovoltaic power output, so that the amount of electricity absorbed by the virtual power plant from the power grid is as close as possible to the purchased electricity cleared in the day-ahead market, avoiding the occurrence of peak loads, while smoothing the volatility of photovoltaic power output and easing the output requirements for diesel generators. This is crucial to avoid the risk of price fluctuations in the real-time market, increase the penetration rate of photovoltaics in virtual power plants without causing frequency instability, and ensure voltage quality. Since the configuration cost of the energy storage system is very high, excessive energy storage capacity configuration is not conducive to improving the economic efficiency of the industrial virtual power plant, and some long-term idle energy storage will cause great waste. Therefore, it is necessary to reduce the installation capacity of the energy storage system on the basis of avoiding the risk of real-time market price fluctuations as much as possible.

[0061] Specifically, the energy storage adjustment method of the virtual power plant may include the following steps 101-103, wherein:

[0062] 101. Establish a regulation model and constraints for the energy storage system. The regulation model takes the minimum capacity of the energy storage system as the objective function. The constraints include the power balance constraints of the virtual power plant, the energy storage operation constraints of the energy storage system, the operating power constraints of the traditional power generation system, and the demand response constraints of the flexible load. The variables in the power balance constraints include the power purchase deviation value between the grid input power in the real-time market and the grid input power in the day-ahead market.

[0063] That is, a regulation model is constructed, and the regulation model takes the lowest construction cost of the energy storage system in the industrial plant as the optimization goal, that is, the total capacity E of the configured energy storage system N Minimum is the optimization goal, and the objective function is: f = min E N The constraints adopted are as follows:

[0064] ① Constraints on the operating status of the energy storage system

[0065] During the operation of the energy storage system, the charge and discharge power will affect the service life of the energy storage system. The physical characteristics of the battery itself also limit the upper and lower limits of its charge and discharge power, and the state of charge must also be within the specified upper and lower limits. That is, the energy storage operation constraints that need to be met include:

[0066]

[0067] Among them, formula (1) is the constraint of charge state, formula (2) is the constraint of charge and discharge power, SOC (t) is the charge state of the energy storage system at time t, S OC (t) = SOC0 – (P dis(t) ·dt) / E N +(P ch(t) ·dt) / E N , SOC0 is the initial state of charge of the energy storage system, E N is the capacity of the energy storage system, is the lower limit of the state of charge of the energy storage system, is the upper limit of the state of charge of the energy storage system, is the lower limit of the charging power of the energy storage system, is the upper limit of the charging power of the energy storage system, is the lower limit of the discharge power of the energy storage system, is the upper limit of the discharge power of the energy storage system.

[0068] ② Constraints on the operating power of traditional power generation systems (diesel generators)

[0069] Considering only the upper and lower limits of the output of the diesel generator, the operating power constraints that need to be met include:

[0070]

[0071] In formula (3), is the lower limit of output power of traditional power generation system (diesel generator), It is the upper limit of output power of traditional power generation system (diesel generator).

[0072] ③ Constraints on flexible loads for demand response

[0073] Flexible loads are interruptible loads. During the operation of the microgrid system in industrial plants, in order to take into account the comfort of the staff, the power of the flexible loads participating in demand response needs to be controlled within a reasonable range, that is, the demand response constraints that need to be met include:

[0074] 0≤P IL (t)≤μ·P load (t); (4)

[0075] In formula (4), P IL (t) is the power of the flexible load participating in demand response at time t, P load (t) is the power of the total load of the virtual power plant participating in demand response at time t, and μ is the maximum proportion of the flexible load participating in demand response at time t to the total load at the same time.

[0076] ④Power balance constraints

[0077] Depending on the charging and discharging state of the energy storage system, the power balance constraint condition of the industrial plant that needs to be met at any time is the following formula (5) or (6):

[0078] P load (t)-P IL (t) = P DAM (t)+P PV (t)-P ch (t)+P diesel (t)+ΔP D (t); (5)

[0079] P load (t)-P IL (t) = P DAM (t)+P PV (t)+P dis (t)+P diesel (t)+ΔP D (t); (6)

[0080] Among them, the first formula (formula (5)) represents that the energy storage system is in a charging state, and the second formula (formula (6)) represents that the energy storage system is in a discharging state. pv (t) is the output power of the photovoltaic system at time t, P ch (t) is the charging power of the energy storage system at time t, P dis (t) is the discharge power of the energy storage system at time t, P diesel (t) is the output power of the traditional power generation system (diesel generator) at time t, ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, ΔP D (t) = P RTM (t)-P DAM (t), P RTM (t) is the grid input power at time t in the real-time market, P DAM (t) is the grid input power at time t in the day-ahead market power purchase plan, P IL (t) is the power of the flexible load participating in demand response at time t, P load (t) is the total load of the virtual power plant participating in demand response at time t.

[0081] The virtual power plant formulates a day-ahead power purchase curve based on its own load demand, grid peak load demand, and time-of-use electricity prices, tiered electricity prices, etc., and determines the grid input power (i.e., clearing volume) P at any time in the day-ahead market. DAM (t). ΔP D(t) A positive value indicates that power is further absorbed from the grid on the basis of the day-ahead market clearing amount, while a negative value indicates that the photovoltaic power generation is excessive and the surplus power is connected to the grid. Figure 2 , when the grid is running, if the sum of the market clearing volume and the photovoltaic output is greater than the load demand, the flexible load that was reduced by demand response will be restored first, then the diesel generator output will be adjusted to a suitable state, and finally the remaining part will be charged to the energy storage system. If there is still a surplus (ΔP D If the sum of the market power and the photovoltaic power output is less than the load demand, the energy storage system is first discharged to adjust, then the diesel generator output is increased, and finally the flexible load is reduced through demand response. If it is still not satisfied (ΔP D (t) is a positive value), the real-time market electricity purchase volume will be increased to make it greater than the day-ahead market clearing volume.

[0082] 102. Construct deviation constraints and deviation exceeding constraints for power purchase deviation values.

[0083] Among them, in the bidding and clearing process of the day-ahead market, the power purchase curve is often fully optimized, and the price fluctuations in the real-time market will have an adverse impact on the economic operation of the industrial plant. Therefore, the interconnection line power curve should be as close as possible to the curve obtained by the day-ahead market clearing, that is, the deviation of the power purchase amount between the real-time market and the day-ahead market should be limited to a certain range. The deviation constraints that need to be met include:

[0084] |ΔP D (t)|≤α·P DAM (t); (7)

[0085] In formula (7), ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, P DAM (t) is the grid input power at time t in the day-ahead market, and α is the maximum allowable proportion of the absolute value of the power purchase deviation at time t to the grid input power in the day-ahead market at the same time.

[0086] Usually, in most cases, the electricity price in the real-time market is generally higher than the electricity price in the day-ahead market, and each region has its own penalty method for demand-side deviation electricity. D The existence of (t) has a significant impact on the economic efficiency of industrial plant operations. Because the microgrid system of the industrial virtual power plant is connected to the power grid, the photovoltaic power generation system is allowed to operate with surplus power on the grid. Therefore, negative deviations can be avoided by reasonably formulating a day-ahead market power purchase strategy. Considering the positive deviation, from the perspective of electricity price cost, when ΔP DWhen (t) is 0, it means that there is no deviation in power, which is most beneficial to reducing operating costs. However, during the operation of industrial virtual power plants, there may be a large difference between load peaks and valleys. During peak load periods, especially when there are short-term peak loads, if ΔP is always pursued, D If (t) is 0, the configuration capacity of the energy storage system will be greatly increased, which will significantly increase the construction cost, and even cause the increased construction cost to be far higher than the electricity price cost saved in the power market. Therefore, ΔP can be appropriately increased. D The allowable value of (t) is increased (equivalent to increasing the allowable value of α) to reduce the capacity pressure of the energy storage system.

[0087] At the same time, due to the inevitable occurrence of several days of extreme weather in a year, the photovoltaic output is extremely low. In this case, the allowable value of α set in formula (7) corresponds to the additional power purchase in the real-time market, which is far from making up for the shortage of photovoltaic output, that is, (1+α)·P DAM The power value of (t) cannot cover the necessary load in the industrial virtual power plant. At this time, there are generally two ways to do it, one is to increase the allowable value of α, and the other is to increase the configuration capacity of the energy storage system. However, both methods have their own shortcomings.

[0088] Among them, if the method of increasing the allowable value of α is adopted, the allowable value of α will increase significantly due to the sharp drop in photovoltaic output. When the energy storage system is optimized according to the newly obtained α, the energy storage capacity E in the optimization result will be N Too small, so it can neither absorb photovoltaic power well when photovoltaic power is sufficient, aggravating the phenomenon of abandoned light, nor make up for the power shortage well when photovoltaic power is insufficient, resulting in the need for a larger ΔP D (t), resulting in an increase in electricity price costs. If the configuration capacity of the energy storage system is increased, the capacity of the energy storage system needs to be greatly increased when optimizing the configuration of the energy storage system according to α under normal circumstances, resulting in huge additional construction costs. And because the probability of such extreme weather is very low, the energy storage system capacity increased to compensate for these extremely rare extreme weather cannot be effectively used most of the time in a year, resulting in a huge waste of capacity.

[0089] Therefore, the deviation exceeding standard ratio R is introduced as a constraint, that is, the deviation exceeding standard constraint conditions that need to be met include:

[0090] R≤β; (8)

[0091] In formula (8), R is the deviation exceeding the standard ratio at time t, R = N / 8760, N is ΔP D (t)>α·P DAM (t), and β is the maximum allowable value of the deviation excess ratio.

[0092] 103. According to the regulation model, the deviation constraint condition and the deviation exceeding constraint condition, determine the energy storage regulation data of the energy storage system.

[0093] In some embodiments, the above step 103 specifically includes:

[0094] Under the constraint condition, the deviation constraint condition and the deviation exceeding constraint condition, the objective function is solved to obtain energy storage regulation data of the energy storage system.

[0095] The energy storage regulation data includes the charging and discharging power of the energy storage system. After the energy storage regulation data are determined, the energy storage system is configured and optimized according to these data.

[0096] It should be pointed out that by limiting the values ​​of α and β within a reasonable range, the energy storage system can be optimized during grid operation to effectively avoid the waste of energy storage system capacity caused by low-probability extreme weather and control the increase in electricity price costs caused by deviation in electricity volume, thereby achieving a better balance between the electricity price cost during operation and the construction cost during planning.

[0097] As can be seen from the above, the energy storage regulation method of the virtual power plant provided in the embodiment of the present application establishes a regulation model and constraints for the energy storage system. The regulation model takes the minimum capacity of the energy storage system as the objective function. The constraints include the power balance constraints of the virtual power plant, the energy storage operation constraints of the energy storage system, the operating power constraints of the traditional power generation system, and the demand response constraints of the flexible load. The variables in the power balance constraints include the power purchase deviation value between the grid input power in the real-time market and the grid input power in the day-ahead market; construct deviation constraints and deviation exceeding constraints for the power purchase deviation value; determine the energy storage regulation data of the energy storage system according to the regulation model, the deviation constraints and the deviation exceeding constraints for the power purchase deviation value, that is, when optimizing the energy storage system, introduce deviation constraints and deviation exceeding constraints for the power purchase deviation value, so as to effectively avoid the waste of energy storage system capacity caused by low-probability extreme weather, and control the increase in electricity price cost caused by deviation electricity, so as to achieve a better balance between the electricity price cost in the grid operation process and the construction cost in the planning process.

[0098] According to the method described in the above embodiment, the embodiment of the present application also provides an energy storage adjustment device for a virtual power plant, which is used to execute the steps in the energy storage adjustment method for a virtual power plant. Figure 3 , Figure 32 is a schematic diagram of the structure of the energy storage regulating device of the virtual power plant provided in the embodiment of the present application. The energy storage regulating device 200 is applied to an electronic device, and the electronic device can be implemented as a user terminal or a server. Specifically, the energy storage regulating device 200 includes an establishment module 201, a construction module 202 and a determination module 203, wherein:

[0099] Establishing module 201, for establishing a regulation model and constraints for the energy storage system, wherein the regulation model takes the minimum capacity of the energy storage system as the objective function, and the constraints include the power balance constraints of the virtual power plant, the energy storage operation constraints of the energy storage system, the operation power constraints of the traditional power generation system, and the demand response constraints of the flexible load, and the variables in the power balance constraints include the power purchase deviation value between the grid input power of the real-time market and the grid input power of the day-ahead market;

[0100] A construction module 202 is used to construct a deviation constraint condition and a deviation exceeding constraint condition for a power purchase deviation value;

[0101] The determination module 203 is used to determine the energy storage regulation data of the energy storage system according to the regulation model, the deviation constraint condition and the deviation exceeding constraint condition.

[0102] In some embodiments, the determination module 203 is specifically used to:

[0103] Under the constraint condition, the deviation constraint condition and the deviation exceeding constraint condition, the objective function is solved to obtain energy storage regulation data of the energy storage system.

[0104] In some embodiments, the deviation constraint includes:

[0105] |ΔP D (t)|≤α·P DAM (t);

[0106] Among them, ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, P DAM (t) is the grid input power at time t in the day-ahead market, and α is the maximum allowable proportion of the absolute value of the power purchase deviation at time t to the grid input power in the day-ahead market at the same time.

[0107] In some embodiments, the deviation exceeding constraint condition includes:

[0108] R≤β;

[0109] Among them, R is the deviation exceeding the standard ratio at time t, R = N / 8760, N is ΔP D (t)>α·P DAM(t), and β is the maximum allowable value of the deviation excess ratio.

[0110] In some embodiments, the power balance constraint includes:

[0111] P load (t)-P IL (t) = P DAM (t)+P PV (t)-P ch (t)+P diesel (t)+ΔP D (t);

[0112] P load (t)-P IL (t) = P DAM (t)+P PV (t)+P dis (t)+P diesel (t)+ΔP D (t);

[0113] Among them, the first formula represents that the energy storage system is in a charging state, and the second formula represents that the energy storage system is in a discharging state. pv (t) is the output power of the photovoltaic system at time t, P ch (t) is the charging power of the energy storage system at time t, P dis (t) is the discharge power of the energy storage system at time t, P diesel (t) is the output power of the traditional power generation system (diesel generator) at time t, ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, ΔP D (t) = P RTM (t)-P DAM (t), P RTM (t) is the grid input power at time t in the real-time market, P DAM (t) is the grid input power at time t in the day-ahead market power purchase plan, P IL (t) is the power of the flexible load participating in demand response at time t, P load (t) is the total load of the virtual power plant participating in demand response at time t.

[0114] In some embodiments, the energy storage operation constraints include:

[0115]

[0116] Among them, S OC (t) is the charge state of the energy storage system at time t, S OC(t) = SOC0 – (P dis(t) ·dt) / E N +(P ch(t) ·dt) / E N , SOC0 is the initial state of charge of the energy storage system, E N is the capacity of the energy storage system, is the lower limit of the state of charge of the energy storage system, is the upper limit of the state of charge of the energy storage system, is the lower limit of the charging power of the energy storage system, is the upper limit of the charging power of the energy storage system, is the lower limit of the discharge power of the energy storage system, is the upper limit of the discharge power of the energy storage system.

[0117] It should be noted that the specific details of each module unit in the energy storage regulation device 200 of the above-mentioned virtual power plant have been described in detail in the embodiment of the above-mentioned energy storage regulation method, and will not be repeated here.

[0118] In some embodiments, the energy storage regulating device of the virtual power plant in the embodiments of the present application may be an electronic device, or a component in an electronic device, such as an integrated circuit or a chip. The electronic device may be a terminal device. Exemplarily, the electronic device may be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and may also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), etc., which is not specifically limited in the embodiments of the present application.

[0119] In some embodiments, Figure 4 As shown, an embodiment of the present application also provides an electronic device 300, including a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the program is executed by the processor 301, each process of the energy storage regulation method embodiment of the above-mentioned virtual power plant is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0120] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0121] Figure 5 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of the present application.

[0122] The electronic device 400 includes but is not limited to: a radio frequency unit 401, a network module 402, an audio output unit 403, an input unit 404, a sensor 405, a display unit 406, a user input unit 407, an interface unit 408, a memory 409, a processor 410 and other components.

[0123] Those skilled in the art will appreciate that the electronic device 400 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 410 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 5 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0124] It should be understood that in the embodiment of the present application, the input unit 404 may include a graphics processor (Graphics Processing Unit, GPU) 4041 and a microphone 4042, and the graphics processor 4041 processes the image data of the static picture or video obtained by the image capture device (such as a camera) in the video capture mode or the image capture mode. The display unit 406 may include a display panel 4061, and the display panel 4061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 407 includes a touch panel 4071 and at least one of other input devices 4072. The touch panel 4071 is also called a touch screen. The touch panel 4071 may include two parts: a touch detection device and a touch controller. Other input devices 4072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0125] The memory 409 can be used to store software programs and various data. The memory 409 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, an image playback function, etc.), etc. In addition, the memory 409 may include a volatile memory or a non-volatile memory, or the memory 409 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory 409 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0126] The processor 410 may include one or more processing units; the processor 410 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the modem processor may not be integrated into the processor 410.

[0127] An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned virtual power plant energy storage regulation method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0128] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0129] An embodiment of the present application also provides a computer program product, including a computer program, which implements the energy storage regulation method of the virtual power plant when executed by a processor.

[0130] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0131] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0132] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0133] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0134] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0135] In the description of the present application, “plurality” means two or more.

[0136] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0137] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for regulating energy storage in a virtual power plant, characterized in that: The virtual power plant includes an energy storage system, a photovoltaic system, a traditional power generation system and a flexible load connected to the power grid, and the energy storage regulation method includes: Establishing a regulation model and constraints for the energy storage system, wherein the regulation model takes the minimum capacity of the energy storage system as an objective function, the constraints include the power balance constraints of the virtual power plant, the energy storage operation constraints of the energy storage system, the operation power constraints of the traditional power generation system, and the demand response constraints of the flexible loads, and the variables in the power balance constraints include the power purchase deviation value between the grid input power in the real-time market and the grid input power in the day-ahead market; Constructing deviation constraint conditions and deviation exceeding constraint conditions for the power purchase deviation value; The energy storage regulation data of the energy storage system is determined according to the regulation model, the deviation constraint condition and the deviation exceeding constraint condition.

2. The energy storage adjustment method of a virtual power plant according to claim 1, characterized in that: The step of determining the energy storage regulation data of the energy storage system according to the regulation model, the deviation constraint condition and the deviation exceeding constraint condition comprises: Under the constraint conditions, the deviation constraint conditions and the deviation exceeding constraint conditions, the objective function is solved to obtain energy storage regulation data of the energy storage system.

3. The energy storage adjustment method of a virtual power plant according to claim 1, characterized in that: The deviation constraints include: |ΔP D (t)|≤α·P DAM (t); Among them, ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, P DAM (t) is the grid input power at time t in the day-ahead market, and α is the maximum allowable proportion of the absolute value of the power purchase deviation at time t to the grid input power in the day-ahead market at the same time.

4. The energy storage adjustment method of a virtual power plant according to claim 3 is characterized in that: The deviation exceeding standard constraint conditions include: R≤β； Among them, R is the deviation exceeding the standard ratio at time t, R = N / 8760, N is ΔP D (t)>α·P DAM (t), and β is the maximum allowable value of the deviation excess ratio.

5. The energy storage adjustment method of a virtual power plant according to claim 1, characterized in that: The power balance constraints include: P load (t)-P IL (t)=P DAM (t)+P PV (t)-P ch (t)+P diesel (t)+ΔP D (t); P load (t)-P IL (t)=P DAM (t)+P PV (t)+P dis (t)+P diesel (t)+ΔP D (t); Among them, the first formula represents that the energy storage system is in a charging state, and the second formula represents that the energy storage system is in a discharging state, P pv (t) is the output power of the photovoltaic system at time t, P ch (t) is the charging power of the energy storage system at time t, P dis (t) is the discharge power of the energy storage system at time t, P diesel (t) is the output power of the conventional power generation system at time t, ΔP D (t) is the power purchase deviation between the grid input power at time t in the real-time market and the grid input power at time t in the day-ahead market, ΔP D (t) = P RTM (t)-P DAM (t), P RTM (t) is the grid input power at time t in the real-time market, P DAM (t) is the grid input power at time t in the day-ahead market power purchase plan, P IL (t) is the power of the flexible load participating in demand response at time t, P load (t) is the power of the total load of the virtual power plant participating in demand response at time t.

6. The energy storage adjustment method of a virtual power plant according to claim 5, characterized in that: The energy storage operation constraints include: Among them, S OC (t) is the state of charge of the energy storage system at time t, S OC (t) = SOC0 – (P dis(t) ·dt) / E N +(P ch(t) ·dt) / E N , SOC0 is the initial state of charge of the energy storage system, E N is the capacity of the energy storage system, is the lower limit of the state of charge of the energy storage system, is the upper limit value of the state of charge of the energy storage system, is the lower limit of the charging power of the energy storage system, is the upper limit of the charging power of the energy storage system, is the lower limit of the discharge power of the energy storage system, is the upper limit of the discharge power of the energy storage system.

7. An energy storage adjustment device for a virtual power plant, characterized in that: The virtual power plant includes an energy storage system, a photovoltaic system, a traditional power generation system and a flexible load connected to the power grid, and the energy storage regulating device includes: Establishing a module for establishing a regulation model and constraints for the energy storage system, wherein the regulation model takes the minimum capacity of the energy storage system as an objective function, the constraints include the power balance constraints of the virtual power plant, the energy storage operation constraints of the energy storage system, the operation power constraints of the traditional power generation system, and the demand response constraints of the flexible load, and the variables in the power balance constraints include the power purchase deviation value between the grid input power of the real-time market and the grid input power of the day-ahead market; A construction module, used for constructing a deviation constraint condition and a deviation exceeding constraint condition for the power purchase deviation value; A determination module is used to determine the energy storage regulation data of the energy storage system according to the regulation model, the deviation constraint condition and the deviation exceeding constraint condition.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the energy storage regulation method of a virtual power plant as described in any one of claims 1-6 is implemented.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the energy storage regulation method of the virtual power plant as described in any one of claims 1-6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the energy storage regulation method of a virtual power plant as described in any one of claims 1-6 is implemented.

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