New energy station configuration energy storage optimization control method based on multi-time scale power prediction

Abstract

The invention provides a new energy station configuration energy storage optimization control method based on multi-time scale power prediction. The method comprises the following steps: step 1, reading operation information of a new energy station; 2, according to the operation information of the new energy station, establishing an objective function of charging and discharging of the energy storage system, solving the objective function, and generating a charging and discharging plan of the energy storage system in the next day; 3, performing rolling correction on the charge and discharge plan of the energy storage system in the day by combining the charge and discharge plan of the energy storage system in the next day and the output power fluctuation condition of the grid-connected point; and step 4, outputting the intra-day energy storage system charging and discharging plan after rolling correction to an energy storage control system, and performing control optimization of new energy station configuration energy storage. An objective function is established through the time-of-use electricity price and the power fluctuation condition of the station, an optimal energy storage charging and discharging plan can be obtained, and comprehensive optimization control over energy storage of new energy station distribution construction is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of power generation control for new energy power stations, and particularly to an optimized control method for energy storage configured in a new energy power station based on multi-time scale power prediction. Background Art

[0002] New energy power generation inherently has intermittency, randomness, and volatility, which pose great challenges to system regulation. To promote the effective consumption of new energy and ensure the safe and stable operation of the new power system, the fast regulation ability and energy time-shifting characteristics of energy storage devices have become important means to complement new energy. For this reason, when building new energy power stations in most regions of the country, it is required that new energy power stations be equipped with a certain capacity of energy storage devices. At present, generally, the required energy storage capacity is 10% - 20% of the installed capacity of the new energy power station, and the duration ranges from 1 hour to 4 hours. This measure also makes up for the deficiencies of new energy power generation characteristics to a certain extent.

[0003] However, with the gradual commissioning of the energy storage configured in various places, some problems have emerged. In most regions of the country, policies can often only ensure that the energy storage configured for new energy can achieve "one charge and one discharge" or "two charges and two discharges", with relatively single usage scenarios and low utilization rates of energy storage devices. At the same time, the economy and its flexible regulation ability of the configured energy storage are not considered.

[0004] Under such circumstances, an optimized control method for energy storage configured in a new energy power station based on multi-time scale power prediction is explored. Through short-term power prediction and ultra-short-term power prediction of the new energy power station, considering the time-of-use electricity price policy and power fluctuation conditions of the power station, an objective function is established, and the optimal charging and discharging plan of the configured energy storage is solved to optimize the control of the energy storage configured in the new energy power station. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide an optimized control method for energy storage configured in a new energy power station based on multi-time scale power prediction to solve at least the above problems.

[0006] The technical solution adopted by the present invention is as follows:

[0007] An optimized control method for energy storage configured in a new energy power station based on multi-time scale power prediction, the method comprising the following steps:

[0008] Step 1: Read the operation information of the new energy power station;

[0009] Step 2: According to the operation information of the new energy power station, establish an objective function for the charging and discharging of the energy storage system, solve the objective function, and generate the charging and discharging plan of the energy storage system for the next day;

[0010] Step 3: Combine the charging and discharging plan of the energy storage system for the next day and the output power fluctuation of the grid connection point, and perform rolling correction on the charging and discharging plan of the in-day energy storage system;

[0011] Step 4: Output the rolling corrected charging and discharging plan of the in-day energy storage system to the energy storage control system for control optimization of the energy storage built in the new energy power station.

[0012] Furthermore, the operation information of the new energy power station in Step 1 includes: short-term power prediction of the new energy power station, ultra-short-term power prediction, theoretical available power, energy storage system power, and state of charge of the energy storage system.

[0013] Furthermore, based on the operation information of the new energy power station in Step 2, the specific objective function for establishing the charging and discharging of the energy storage system is: establish the charging and discharging objective function of the energy storage system according to the short-term power prediction information, time-of-use electricity price information and time-of-use electricity price constraints of the new energy power station, the state of charge and state-of-charge constraints of the energy storage system, and the charging and discharging constraint curtailment plan.

[0014] Furthermore, the specific formula for establishing the charging and discharging objective function of the energy storage system is:

[0015]

[0016] Among them, C sell represents the electricity sales revenue of the whole station; λ(t) represents the time-of-use electricity price at time t; P g (t) represents the total power of the grid connection point at time t; Δt represents the control period;

[0017]

[0018] Among them, C loss represents the loss cost during the charging and discharging process of the energy storage system; K c (t), K d (t) respectively represent the charging and discharging states of the energy storage system, which are Boolean variables; P b (t) represents the charging and discharging power of the energy storage system at time t; η c , η d respectively represent the charging and discharging efficiencies of the energy storage system;

[0019]

[0020] Among them, C limit represents the loss cost of the reduced power generation of the new energy power station after curtailment; P avail (t) represents the theoretical available power of the new energy power station; P limit (t) represents the curtailment power of the new energy power station caused by non-station factors such as blocked transmission channels or difficult consumption;

[0021] max J = C sell -C loss -C limit

[0023] Furthermore, the time-of-use electricity price calculation formula is:

[0024] λ(t) = λ1I1(t) + λ2I2(t) + λ3I3(t)

[0025] where λ1, λ2, and λ3 represent the electricity prices during peak hours, normal hours, and valley hours respectively; I1(t), I2(t), and I3(t) represent whether it is in the peak hour, normal hour, and valley hour respectively, and are Boolean variables;

[0026] The calculation formula for the total power at the grid connection point at time t is:

[0027] P g (t) = P n (t) + P b (t)

[0028] where the P n (t) represents the output power of the new energy power station at time t; P b (t) represents the charge and discharge power of the energy storage system at time t;

[0029] The calculation formula for the state of charge of the energy storage system is:

[0030] Charging process:

[0031] SOC(t) = SOC(t - Δt) + K c (t)η c P b (t)Δt

[0032] where SOC(t) represents the state of charge at time t; SOC(t - Δt) represents the state of charge at time t - Δt;

[0033] Discharging process:

[0034] SOC(t) = SOC(t - Δt) + K d (t)P b (t)Δt / η d

[0036] Furthermore, the constraints of the time-of-use electricity price are:

[0037] I1(t) + I2(t) + I3(t) ≤ 1

[0038] The constraints on the charge and discharge power of the energy storage system and the constraints on the conversion of its charge and discharge states are:

[0039] -P b_max ≤P b (t)≤P b_max

[0040] K c (t)+K d (t)≤1

[0041] Among them, P b_max represents the maximum charging power of the energy storage system;

[0042] The state of charge constraint of the energy storage system is:

[0043] SOC min ≤SOC(t)≤SOC max

[0044] Among them, SOC min and SOC max represent the minimum and maximum state of charge allowed for the energy storage system respectively.

[0045] Furthermore, in step 2, solving the objective function to generate the charging and discharging plan of the energy storage system for the next day is specifically: bringing the short-term power prediction value and the limited power P limit (t) into the objective function, and solving the objective function to obtain the charging and discharging plan of the energy storage system for the next day Among them, the short-term power prediction value is the theoretical available power of the new energy power station.

[0046] Furthermore, step 3 is specifically: after entering the intraday operation, according to the ultra-short-term power prediction information of the new energy power station every 15 minutes, combined with the charging and discharging plan of the energy storage system for the next day and the grid-connected output power fluctuation situation, construct a new objective function to perform rolling correction on the intraday charging and discharging plan of the energy storage system.

[0047] Furthermore, the specific formula for constructing the new objective function is:

[0048]

[0049] Among them, represents the new charging and discharging plan of the energy storage system optimized considering the ultra-short-term power prediction result and the power fluctuation at the grid connection point; (P g (t)-P g (t - 1)) 2 represents the square difference between the power generation power P g (t) at the current time t and the power generation power P g (t - 1) at the previous time t - 1.

[0050] Furthermore, step 4 is specifically as follows: the daily energy storage system charging and discharging plan after rolling correction in step 3 is delegated to the energy storage control system for execution, so as to complete the comprehensive optimization control of the energy storage equipped with the new energy site.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] The present invention provides a method for optimizing and controlling energy storage equipped with new energy stations based on multi-time scale power prediction, which combines the station time-of-use electricity price, power fluctuation, short-term power prediction, state of charge, charging and discharging constraints, and power restriction plan through the constructed objective function, and obtains the optimal energy storage charging and discharging plan by solving the objective function, which can take into account the economic efficiency of accessory energy storage and realize the comprehensive optimization control of energy storage equipped with new energy stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0054] Figure 1 It is a flow chart of the overall method provided by the present invention. DETAILED DESCRIPTION

[0055] The technical solution of the present invention is further elaborated in detail below in conjunction with the drawings and specific embodiments of the specification. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In the following description, the expression "some embodiments" is related to a subset of all possible embodiments, but it should be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0056] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.

[0057] It should be understood that the present invention can be implemented in different forms and should not be construed as limited to the embodiments presented herein. On the contrary, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the present invention to those skilled in the art. And the purpose of the terms used herein is only to describe specific embodiments and not to limit the present invention. When used herein, the singular forms "a", "an" and "the" are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms "comprising" and / or "including", when used in this specification, determine the presence of the stated features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups. When used herein, the term "and / or" includes any and all combinations of the related listed items.

[0058] It should be further noted that when an element is referred to as "fixed to" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "inner", "outer", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation.

[0059] To thoroughly understand the present invention, detailed structures will be presented in the following description to illustrate the technical solutions proposed by the present invention. The optional embodiments of the present invention are described in detail below. However, in addition to these detailed descriptions, the present invention can also have other implementations.

[0060] Referring to Figure 1 , the present invention provides an optimized control method for energy storage configured in a new energy power station based on multi-time scale power prediction. The method includes the following steps:

[0061] Step 1: Read the operation information of the new energy power station;

[0062] The operation information of the new energy power station includes: short-term power prediction, ultra-short-term power prediction, theoretical available power, energy storage system power, and state of charge of the energy storage system of the new energy power station.

[0063] Exemplarily, the information obtained further includes the day-ahead electricity price data of the new energy power station.

[0064] Step 2: According to the operation information of the new energy power station, establish an objective function for the charge and discharge of the energy storage system, solve the objective function, and generate the charge and discharge plan of the energy storage system for the next day;

[0065] In step 2, based on the operation information of the new energy power station, the objective function for the charge and discharge of the energy storage system is specifically established as follows: According to the short-term power prediction information, time-of-use electricity price information, and time-of-use electricity price constraints of the new energy power station, the state of charge and state-of-charge constraints of the energy storage system, and the charge and discharge constraints and power curtailment plan, the objective function for the charge and discharge of the energy storage system is established.

[0066] Exemplarily, by combining the short-term power, time-of-use electricity price, state of charge, charge and discharge constraints, and power curtailment plan, the objective function for the charge and discharge of the energy storage system is established. By solving the objective function, the optimal charge and discharge plan of the energy storage can be obtained, and the optimal control of the energy storage configured in the new energy power station can be better realized.

[0067] The specific formula for establishing the objective function of the energy storage system's charge and discharge is as follows:

[0068]

[0069] Among them, C sell represents the electricity sales revenue of the entire station; λ(t) represents the time-of-use electricity price at time t; P g (t) represents the total power at the grid connection point at time t; Δt represents the control period;

[0070]

[0071] Among them, C loss represents the loss cost during the charge and discharge process of the energy storage system; K c (t), K d (t) respectively represent the charge and discharge states of the energy storage system, which are Boolean variables; P b (t) represents the charge and discharge power of the energy storage system at time t; η c , η d respectively represent the charge and discharge efficiencies of the energy storage system;

[0072]

[0073] Among them, C limit represents the loss cost of the reduced power generation of the new energy power station after power curtailment; P avail (t) represents the theoretical available power of the new energy power station; P limit (t) represents the power curtailment power of the new energy power station caused by factors other than the power station itself, such as blocked transmission channels or difficult power consumption;

[0074] max J = C sell -C loss -C limit

[0076] Exemplarily, by comprehensively considering the electricity sales revenue of the new energy power station, the loss cost of the energy storage system, and the curtailment cost, an optimal charging and discharging plan can be obtained.

[0077] The formula for time-of-use electricity price is:

[0078] λ(t) = λ1I1(t) + λ2I2(t) + λ3I3(t)

[0079] Where λ1, λ2, and λ3 represent the electricity price during peak hours, normal hours, and valley hours respectively; I1(t), I2(t), and I3(t) represent whether it is during peak hours, normal hours, and valley hours respectively, and are Boolean variables.

[0080] The constraints for time-of-use electricity price are:

[0081] I1(t) + I2(t) + I3(t) ≤ 1

[0082] The formula for the total power at the grid connection point at time t is:

[0083] P g (t) = P n (t) + P b (t)

[0084] Where the P n (t) represents the output power of the new energy power station at time t; P b (t) represents the charging and discharging power of the energy storage system at time t.

[0085] The constraints for the charging and discharging power of the energy storage system and its charging and discharging state conversion constraints are:

[0086] -P b_max ≤ P b (t) ≤ P b_max

[0087] K c (t) + K d (t) ≤ 1

[0088] Where P b_max represents the maximum charging power of the energy storage system;

[0089] The formula for the state of charge of the energy storage system is:

[0090] Charging process:

[0091] SOC(t) = SOC(t - Δt) + K c (t)η c P b (t)Δt

[0092] Discharging process:

[0093] SOC(t) = SOC(t - Δt) + K d (t)P b (t)Δt / η d

[0094] The state of charge constraint of the energy storage system is:

[0095] SOC min ≤ SOC(t) ≤ SOC max

[0096] where SOC min and SOC max represent the minimum and maximum state of charge allowed for the energy storage system, respectively.

[0097] In step 2, solving the objective function to generate the charging and discharging plan of the energy storage system for the next day is specifically as follows: Substitute the short - term power prediction value and the power limit P limit (t) into the objective function, and solve the objective function to obtain the charging and discharging plan of the energy storage system for the next day where the short - term power prediction value is the theoretical available power of the new - energy power station.

[0098] Exemplarily, substituting the short - term power prediction value and the power limit into the objective function for solution can more accurately match the power generation of the new - energy power station with the grid demand, effectively reduce the phenomena of wind and light abandonment caused by inaccurate power prediction, and improve the utilization rate of new energy.

[0099] Step 3: Combine the charging and discharging plan of the energy storage system for the next day and the output power fluctuation situation at the grid connection point, and perform rolling correction on the charging and discharging plan of the energy storage system within the day;

[0100] Step 3 is specifically as follows: After entering the within - day operation, according to the ultra - short - term power prediction information of the new - energy power station every 15 minutes, combine the charging and discharging plan of the energy storage system for the next day and the output power fluctuation situation at the grid connection point to construct a new objective function, and perform rolling correction on the charging and discharging plan of the energy storage system within the day.

[0101] The specific formula for constructing the new objective function is:

[0102]

[0103] where represents the optimized new charging and discharging plan of the energy storage system considering the ultra - short - term power prediction result and the power fluctuation at the grid connection point; (P g (t) - P g (t - 1)) 2 represents the power generation at the current time t, Pg (t) and the power generation power P at the previous moment t-1 g The squared difference between (t-1).

[0104] Step 4: Output the rolling revised daily energy storage system charging and discharging plan to the energy storage control system to optimize the control of energy storage equipped with new energy sites.

[0105] Step 4 is specifically as follows: the daily energy storage system charging and discharging plan after rolling correction in step 3 is delegated to the energy storage control system for execution, thereby completing the comprehensive optimization control of energy storage equipped with new energy stations.

[0106] For example, the rolling revised daily energy storage system charge and discharge plan can be adjusted in each time period, and the energy storage control system of the new energy station completes the comprehensive optimization control of the energy storage built in the new energy station by executing the rolling revised daily energy storage system charge and discharge plan. By executing the optimized plan, the operating efficiency and economic benefits of the energy storage system can be improved, while ensuring the stable operation of the new energy station.

[0107] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing the control of energy storage in renewable energy stations based on multi-time scale power prediction, characterized in that: The method comprises the following steps: Step 1: Read the operation information of the new energy station; Step 2: According to the operation information of the new energy station, establish the objective function of the energy storage system charging and discharging, solve the objective function, and generate the energy storage system charging and discharging plan for the next day; Step 3: Combine the energy storage system’s charging and discharging plan for the next day and the output power fluctuation of the grid connection point to make rolling corrections to the energy storage system’s charging and discharging plan for the day; Step 4: Output the rolling revised daily energy storage system charging and discharging plan to the energy storage control system to optimize the control of energy storage equipped with new energy sites.

2. According to claim 1, a method for optimizing control of energy storage built at new energy stations based on multi-time scale power prediction is characterized in that: The operation information of the new energy station in step 1 includes: short-term power forecast, ultra-short-term power forecast, theoretical available power, energy storage system power, and energy storage system charge state of the new energy station.

3. The method for optimizing the control of energy storage installed at a new energy station based on multi-time scale power prediction according to claim 2 is characterized in that: In step 2, the objective function of charging and discharging of the energy storage system is established based on the operating information of the new energy station. Specifically, the objective function of charging and discharging of the energy storage system is established based on the short-term power forecast information of the new energy station, the time-of-use electricity price information and time-of-use electricity price constraints, the charge state and charge state constraints of the energy storage system, and the charge and discharge constraint power restriction plan.

4. The method for optimizing control of energy storage equipped with new energy stations based on multi-time scale power prediction according to claim 3 is characterized in that: The specific formula for establishing the charging and discharging objective function of the energy storage system is: Among them, C sell represents the electricity sales revenue of the entire station; λ(t) represents the time-of-use electricity price at time t; P g (t) represents the total power of the grid-connected point at time t; Δt represents the control period; Among them, C loss Represents the loss cost of the energy storage system during charging and discharging; K c (t), K d (t) respectively represent the charging and discharging state of the energy storage system, which is a Boolean variable; P b (t) represents the charging and discharging power of the energy storage system at time t; η c ,η d They represent the efficiency of charging and discharging of the energy storage system respectively; Among them C limit P represents the loss cost of less power generation from new energy stations after power restriction; avail (t) represents the theoretical available power of the new energy station; P limit (t) indicates the power limit of the new energy station due to the obstruction of the transmission channel or the difficulty of consumption caused by factors other than the station itself; maxJ=C sell -C loss -C limit .

5. The method for optimizing control of energy storage equipped with new energy stations based on multi-time scale power prediction according to claim 4 is characterized in that: The calculation formula for time-of-use electricity price is: λ(t)=λ1I1(t)+λ2I2(t)+λ3I3(t) Among them, λ1, λ2, and λ3 represent the peak period electricity price, the normal period electricity price, and the valley period electricity price respectively; I1(t), I2(t), and I3(t) represent whether it is in the peak period, the normal period, and the valley period respectively, and are Boolean variables; The total power calculation formula of the grid connection point at time t is: P g (t)=P n (t)+P b (t) Among them, the P n (t) represents the output power of the new energy station at time t; P b (t) represents the charging and discharging power of the energy storage system at time t; The calculation formula of the energy storage system state of charge is: Charging process: SOC(t)=SOC(t-Δt)+K c (t)η c P b (t)Δt Wherein, SOC(t) represents the state of charge at time t; SOC(t-Δt) represents the state of charge at time t-Δt; Discharge process: SOC(t)=SOC(t-Δt)+K d (t)P b (t)Δt / η d 。 6. The method for optimizing control of energy storage built at new energy stations based on multi-time scale power prediction according to claim 5 is characterized in that: The constraints of time-of-use electricity prices are: I1(t)+I2(t)+I3(t)≤1 The constraints on the charging and discharging power of the energy storage system and its charging and discharging state transition constraints are: -P b_max ≤P b (t)≤P b_max K c (t)+K d (t)≤1 Among them, P b_max Indicates the maximum charging power of the energy storage system; The state of charge constraint of the energy storage system is: SOC min ≤SOC(t)≤SOC max Among them, SOC min , SOC max They respectively represent the minimum state of charge and maximum state of charge allowed by the energy storage system.

7. The method for optimizing and controlling the energy storage installed at a new energy station based on multi-time scale power prediction according to claim 6 is characterized in that: In step 2, the objective function is solved to generate the next day's energy storage system charging and discharging plan: With power cut-off P limit (t) is brought into the objective function, and the objective function is solved to obtain the charging and discharging plan of the energy storage system for the next day. Among them, the short-term power forecast value It is the theoretical available power of the new energy station.

8. The method for optimizing and controlling energy storage installed at a new energy station based on multi-time scale power prediction according to claim 7 is characterized in that: Step 3 is as follows: After entering the intraday operation, based on the ultra-short-term power forecast information of the new energy station every 15 minutes, combined with the next day's energy storage system charging and discharging plan and grid-connected output power fluctuations, a new objective function is constructed to make rolling corrections to the intraday energy storage system charging and discharging plan.

9. The method for optimizing and controlling energy storage installed at a new energy station based on multi-time scale power prediction according to claim 8 is characterized in that: The specific formula for constructing a new objective function is: in, It indicates that the energy storage system optimizes the new energy storage system charging and discharging plan by considering the ultra-short-term power forecast results and the power fluctuation of the grid connection point; (P g (t)-P g (t-1)) 2 Represents the power generation P at the current time t g (t) and the power generation power P at the previous moment t-1 g The squared difference between (t-1).

10. The method for optimizing control of energy storage built at new energy stations based on multi-time scale power prediction according to claim 9 is characterized in that: Step 4 is specifically as follows: the daily energy storage system charging and discharging plan after rolling correction in step 3 is delegated to the energy storage control system for execution, thereby completing the comprehensive optimization control of energy storage equipped with new energy sites.

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