Intelligent optimization energy storage efficient charging and discharging method

Abstract

The invention discloses an intelligent optimization energy storage efficient charging and discharging method. The method comprises the following steps: S1) acquiring parameters of a power system; s2) calculating an average value of 24-hour electricity consumption according to a daily load demand curve of the power system; s3) identifying a whole interval graph formed by enveloping the average value and the daily load demand curve, defining an area above the average value as a positive area, and defining an area below the average value as a negative area; s4) performing charging operation in the negative area region and performing discharging operation in the positive area region according to the pumping and storage parameters and the energy storage parameters; the method comprises the steps of (S1) carrying out pumping and storage treatment on a pumping and storage system, (S2) carrying out pumping and storage treatment on the pumping and storage system, (S5) repeating charging and discharging operations until the total charging and discharging area requirement of the day is met or the maximum operation frequency limit is reached, (S6) forming a new demand curve after all pumping and storage treatment is finished within one day, and (S7) carrying out energy storage treatment on the new demand curve to form an optimized demand curve, optimizing the charging and discharging strategy of the pumping and storage and energy storage system, and reducing the calculated amount.

Description

Technical Field

[0001] This invention belongs to the field of energy storage control technology, specifically relating to an intelligent optimization method for efficient charging and discharging of energy storage. Background Technology

[0002] With the increasing penetration rate of new energy sources, the power grid faces challenges such as increased volatility and insufficient regulation capacity. Energy storage systems, with their flexible charging and discharging characteristics, can effectively smooth fluctuations in new energy output, provide various ancillary services, and enhance grid resilience. However, electrochemical energy storage lacks independent power generation capability; its regulation capacity depends on the power system's own supply and demand balance, meaning it is affected by other regulatory resources. Therefore, research on charging and discharging strategies needs to be conducted to maximize efficiency. Foreign scholars have combined MPC (Multi-Variable Computation) with machine learning to dynamically adjust energy storage charging and discharging plans, achieving multi-timescale optimization. High-frequency, high-precision sensor data acquisition and complex AI algorithms place high demands on computing resources and communication bandwidth, and multi-variable optimization consumes significant computing resources, making it difficult to meet response requirements. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides an intelligent optimization method for efficient charging and discharging of energy storage.

[0004] The specific plan is as follows: A smart optimization method for efficient charging and discharging of energy storage includes the following steps: S1): Obtain power system parameters; the power system parameters include pumped storage parameters, energy storage parameters, and the daily load demand curve Need2 of the power system; The pumped storage parameters include the installed capacity CXg, the pumped storage duration CXh, and the number of daily pumped storage charges CXn. The energy storage parameters include the installed capacity CNg, the duration of energy storage CNh, and the number of daily charging times CNn. S2): Calculate the average 24-hour electricity consumption based on the daily load demand curve Need2 of the power system; S3): Identify the entire interval graph formed by the envelope of the Average and Need2 curves. The area above the Average is defined as the positive area, and the area below the Average is defined as the negative area. Record the envelope area of ​​each positive area and the envelope area of ​​each negative area. S4): Based on the pumping and storage parameters, charging operations are performed in the negative area region and discharging operations are performed in the positive area region. S5): Repeat the charging and discharging operation until the total charging and discharging area requirement for the day is met or the maximum number of operations is reached; S6): After all the pumping and storage processes are completed within a day, a new demand curve Need3 is formed; S7): Energy storage is performed on the Need3 curve after pumped storage treatment to form the final optimized demand curve Need4, where the daily discharge area of ​​energy storage is S. 放 Keep it within the preset percentage range.

[0005] Charging operations in negative area regions include the following steps: M1): Each time a charge is performed, the graph with the largest negative area is selected, and the lowest point is found within the selected negative area. The lowest point is the minimum power value min. M2): Set the loop step size to m. Starting from the lowest point, i.e. the lowest power value min, calculate the power value min+n×m after n loops. Set the horizontal axis corresponding to the power value min+n×m after n loops as "horizontal axis min+n×m". The total area formed by "horizontal axis min+n×m" and the negative area envelope below is S1. M3): Based on the charging completion determination condition, determine whether the current pumping and charging is complete. If not, proceed to step M2; if complete, proceed to step M4. M4): Remove the area below "min + n × m" from the Need2 curve to form a new demand curve, and record the total pumped storage charging area S. 充 The time and location of the charging operation, and the charging height at that time and location.

[0006] The charging completion determination condition includes "charging completion determination condition 1" or "charging completion determination condition 2". Charging is completed when either "charging completion determination condition 1" or "charging completion determination condition 2" is met. The “charging completion judgment condition 1” is: the height between the horizontal axis “min+n×m” and the lowest point reaches the pumping capacity CXg or Average-min; that is, min+n×m≥CXg or min+n×m≥Average-min; The “charging completion judgment condition 2” is: “the horizontal axis min+n×m” and the envelope area S1 below reach the product of the pumping capacity CXg and the pumping time CXh, that is, S1≥CX*CXh. If there are two charging operations per day, the constraint is S1+S2≤CX*CXh, where S2 is the total area formed by the "horizontal axis min+n×m" and the negative area envelope below during the second charging.

[0007] If all positive areas have undergone pumping and discharging operations within a day, the total daily discharge area S 放 It has not yet reached 75% of the total charging area for today, i.e., S放 If < (S1 + S2) * 75%; then discard the previous charging operation result, restart the charging operation for today, and use "charging completion judgment condition 3" instead of "charging completion judgment condition 2" to judge the charging completion. The "charging completion judgment condition 3" is: the envelope area S1 between the horizontal axis "min + n × m" and the area below it reaches 4 / 3 times the total discharge area of ​​the day, that is, S1 ≥ S 放 *4 / 3, If there are two charging operations per day, then the constraint is S1 + S2 ≤ S 放 *4 / 3.

[0008] Performing a discharge operation in the positive area region includes the following steps: N1): During each discharge, select the shape with the largest positive area in the diagram, and find the highest point from the selected positive area. The highest point is the maximum power value (max). N2): Set the loop step size to m. Starting from the highest point, i.e., the maximum power value max, calculate the power value max-n×m after n loops. Define the horizontal axis corresponding to the power value max-n×m after n loops as "horizontal axis max-n×m". The total area formed by "horizontal axis max-n×m" and the positive area envelope above it is S. 放 ; N3): Based on the discharge completion determination condition, determine whether the pumping and discharging is complete. If not, proceed to step N2; if complete, proceed to step N4. N4): Remove the area above "max-n×m" from the Need2 curve to form a new demand curve, and record the total pumped storage and discharge area S. 放 The time and location of the discharge operation, and the discharge height at that time and location.

[0009] The discharge completion determination condition includes "discharge completion determination condition 1" or "discharge completion determination condition 2". Discharge is completed when either "discharge completion determination condition 1" or "discharge completion determination condition 2" is met. The "discharge completion judgment condition 1" is: "the height of the horizontal axis max-n×m and the highest point reaches the pumping capacity CXg or max-Average, that is, max-n×m≥CXg or max-n×m≥max-Average; The "discharge completion judgment condition 2" is: the area S of the upper envelope "horizontal axis max-n×m". 放 The total charging area reached 75% of the total area for the day.

[0010] In step S7), the daily discharge area S of the energy storage 放The area is controlled within a preset percentage range, where the preset percentage is the total area S of the pumped-storage charging. 充 85%, that is, S 放 ≤S 充 *85%.

[0011] This invention discloses an intelligent optimization method for efficient charging and discharging of energy storage. The method involves acquiring power system parameters and daily load demand curves; identifying the positive and negative areas of the demand curve and calculating the envelope area; performing charging operations in the negative area and discharging operations in the positive area; repeating the charging and discharging operations until the total charging and discharging area requirement is met; and forming an optimized demand curve. By identifying the positive and negative areas of the power demand curve, this invention optimizes the configuration of charging and discharging strategies, effectively improving the operating efficiency of the power system and the renewable energy absorption capacity, thus possessing significant engineering application value. Furthermore, by simulating the charging and discharging operations of pumped storage and energy storage, the original power demand curve Need2 is adjusted, ultimately generating new, optimized demand curves Need3 and Need4. This optimizes the charging and discharging strategies of the pumped storage and energy storage systems, reduces computational load, and achieves a rapid response effect. Attached Figure Description

[0012] Figure 1 This is the overall flowchart of the present invention.

[0013] Figure 2 This is a flowchart of a charging operation.

[0014] Figure 3 This is a flowchart of a discharge operation.

[0015] Figure 4 This is a flowchart illustrating the process between a charging operation and a discharging operation.

[0016] Figure 5 This is a schematic diagram of a charging and discharging simulation.

[0017] Figure 6 This is a detailed flowchart of the present invention. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the implementation of the present invention, and not all of it. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0019] like Figures 1 to 6 As shown, an intelligent optimization method for efficient charging and discharging of energy storage includes the following steps: S1): Obtain power system parameters; the power system parameters include pumped storage parameters, energy storage parameters, and the daily load demand curve Need2 of the power system; The pumping parameters include the installed capacity of the pumping unit CXg, the duration of pumping CXh, and the number of daily pumping charges CXn, where the number of daily pumping charges CXn is 1 or 2 times. The energy storage parameters include the installed capacity CNg, the duration of energy storage CNh, and the number of daily charging times CNn. S2): Calculate the average 24-hour electricity consumption based on the daily load demand curve Need2 of the power system; this is used for the subsequent division of "positive / negative areas"; S3): Identify the entire region formed by the envelope of the Average value and the Need2 curve. The area above the Average value is defined as a positive area, which needs to be processed by "discharging". The area below the Average value is defined as a negative area, which needs to be processed by "charging". Record the envelope area of ​​each positive area and the envelope area of ​​each negative area respectively; such as positive 1, positive 2..., negative 1, negative 2..., the envelope area is the overall area of ​​the region.

[0020] S4): Based on the pumping and storage parameters, charging operations are performed in the negative area region and discharging operations are performed in the positive area region. S5): Repeat the charging and discharging operation until the total charging and discharging area requirement for the day is met or the maximum number of operations is reached; S6): After all the pumping and storage processes are completed within a day, a new demand curve Need3 is formed; S7): Energy storage is performed on the Need3 curve after pumped storage treatment to form the final optimized demand curve Need4, where the daily discharge area of ​​energy storage is S. 放 The area is controlled within a preset percentage range, where the preset percentage is the total area S of the pumped-storage charging. 充 85%, that is, S 放 ≤S 充 *85%, the Need4 curve represents the load power after subtracting wind and solar power, local power plants and external power, pumped storage and energy storage, which is the power provided to thermal power.

[0021] like Figure 2 , Figure 5 and Figure 6 As shown, charging operations are performed in the negative area region. The goal of charging is to fill the "negative area" of the demand curve, that is, the part below the average value, and includes the following steps: M1): Select the charging area. Each time you charge, select the shape with the largest negative area in the graph and find the lowest point from the selected negative area. The lowest point is the minimum power value min. M2): Cyclic charging, with a cycle step size of m. The cycle step size m is the charging power increase in each cycle under the charging operation, which is only used in the cycle calculation. Based on the cycle step size m, starting from the lowest point, i.e. the lowest power value min, the power value min+n×m is calculated upwards after n cycles. The horizontal axis corresponding to the power value min+n×m after n cycles is set as "horizontal axis min+n×m". The total area formed by "horizontal axis min+n×m" and the negative area envelope below is S1. The vertical axis of the curve represents power, and the horizontal axis represents time. The area enclosed by the curve and the horizontal axis represents electricity consumption, where electricity consumption = power * time. The portion of the need2 curve below the average value (Average) can be interpreted as requiring less power than the average, allowing for charging of the pumped storage tank. min + n × m represents the power value after the nth cycle, and the portion enclosed by min + n × m and the need2 curve represents the amount of electricity charged to the pumped storage tank. M3): Charging completion condition. Based on the charging completion judgment condition, determine whether the current pumping and charging is completed. If not completed, proceed to step M2; if completed, proceed to step M4. M4): Update the curve, remove the area below "min+n×m" from the Need2 curve to form a new demand curve, and record the total pumped storage charging area S. 充 The charging time and location, and the charging height at that time and location, where the charging height is also the charging power.

[0022] The charging completion determination condition includes "charging completion determination condition 1" or "charging completion determination condition 2". Charging is completed when either "charging completion determination condition 1" or "charging completion determination condition 2" is met. The "charging completion judgment condition 1" is: the height between the horizontal axis "min+n×m" and the lowest point reaches the pumped storage installed capacity CXg or Average-min; that is, min+n×m≥CXg or min+n×m≥Average-min; in other words, the charging power reaches the maximum value of the pumped storage power or the power of the power supply at the minimum value and the average value. The “charging completion judgment condition 2” is: “the horizontal axis min+n×m” and the envelope area S1 below reach the product of the pumping capacity CXg and the pumping time CXh, that is, S1≥CX*CXh. If there are two charging operations per day, the constraint is S1+S2≤CX*CXh, where S2 is the total area formed by the "horizontal axis min+n×m" and the negative area envelope below during the second charging.

[0023] like Figure 4As shown, if all positive areas have undergone pump-storage and discharge operations within a day, the total daily discharge area S 放 It has not yet reached 75% of the total charging area for today, i.e., S 放 If < (S1 + S2) * 75%; then discard the previous charging operation result, restart the charging operation for today, and use "charging completion judgment condition 3" instead of "charging completion judgment condition 2" to judge the charging completion. The "charging completion judgment condition 3" is: the envelope area S1 between the horizontal axis "min + n × m" and the area below it reaches 4 / 3 times the total discharge area of ​​the day, that is, S1 ≥ S 放 *4 / 3, If there are two charging operations per day, then the constraint is S1 + S2 ≤ S 放 *4 / 3.

[0024] like Figure 3 , Figure 5 and Figure 6 As shown, the discharge operation is performed in the positive area region. The goal of the discharge is to reduce the "positive area" of the demand curve, that is, the part above the average value. This includes the following steps: N1): Select the discharge area. Each time you discharge, select the shape with the largest positive area in the diagram and find the highest point from the selected positive area. The highest point is the maximum power value (max). N2): Cyclic discharge, with a cycle step size of m. Starting from the highest point, i.e., the maximum power value max, calculate the power value max-n×m after n cycles downwards. Define the horizontal axis corresponding to the power value max-n×m after n cycles as "horizontal axis max-n×m". The total area formed by "horizontal axis max-n×m" and the positive area envelope above it is S. 放 ;like Figure 2 As shown; N3): Discharge completion condition. Based on the discharge completion judgment condition, determine whether the pumping and discharging is completed. If not completed, proceed to step N2; if completed, proceed to step N4. N4): Update the curve by removing the area above "max-n×m" from the Need2 curve to form a new demand curve, and record the total pumped storage and discharge area S. 放 The time and location of the discharge operation, and the discharge height at that time and location.

[0025] The discharge completion determination condition includes "discharge completion determination condition 1" or "discharge completion determination condition 2". Discharge is completed when either "discharge completion determination condition 1" or "discharge completion determination condition 2" is met. The "discharge completion judgment condition 1" is: "the height of the horizontal axis max-n×m and the highest point reaches the pumping capacity CXg or max-Average, that is, max-n×m≥CXg or max-n×m≥max-Average; The "discharge completion judgment condition 2" is: the area S of the upper envelope "horizontal axis max-n×m". 放 The total charging area reached 75% of the total area for the day.

[0026] The two horizontal axes for charging and discharging replace the curves above and below the horizontal axes, forming a new curve need3. After all pumping / storage operations are completed within a day, curve need3 is formed. Curve need3 is the intermediate demand curve.

[0027] Based on Need3, the curve is further adjusted using energy storage, following similar principles to pumped storage, but the daily discharge area of ​​energy storage must be ≤ 85% of the daily charging area of ​​pumped storage, thus limiting the discharge scale of energy storage. After energy storage processing is completed, a new demand curve, Need4, is finally output.

[0028] This embodiment adjusts the original electricity demand curve Need2 through pumped storage and energy storage charging and discharging operations, generating more reasonable demand curves Need3 and Need4. The overall logic includes data input, charging operation, discharging operation, energy storage processing, and curve generation.

[0029] The intelligent optimization energy storage high-efficiency charging and discharging method acquires power system parameters and daily load demand curves; identifies positive and negative areas of the demand curve and calculates the envelope area; performs charging operations in the negative area and discharging operations in the positive area; repeats the charging and discharging operations until the total charging and discharging area requirement is met; and forms an optimized demand curve.

[0030] By identifying the positive and negative areas of the electricity demand curve, the optimal configuration of charging and discharging strategies can be achieved, effectively improving the operating efficiency of the power system and the capacity for renewable energy absorption, which has significant engineering application value. Furthermore, by simulating the charging and discharging operations of pumped storage and energy storage systems, the original electricity demand curve Need2 is adjusted, ultimately generating new, optimized demand curves Need3 and Need4. This optimizes the charging and discharging strategies of pumped storage and energy storage systems, reduces computational load, and achieves a rapid response technical effect.

[0031] This invention achieves refined management of the electricity demand curve through a closed-loop logic of "input parameters → charging (filling negative areas) → discharging (reducing positive areas) → energy storage optimization → output curve". By utilizing the "charging and discharging" capabilities of pumped storage and energy storage, the fluctuations in the demand curve are adjusted (filling troughs and reducing peaks), ultimately generating a more stable and easily satisfied demand curve Need4.

[0032] The entire process embodies the power dispatch strategy of "supplementing first and then reducing, with energy storage as an auxiliary measure," and ensures the rationality and effectiveness of charging and discharging operations by quantifying constraints such as "area" and "height."

[0033] The technical means disclosed in this invention are not limited to those disclosed in the above embodiments, but also include technical solutions composed of any combination of the above technical features. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications are also considered within the scope of protection of this invention.

Claims

1. A smart optimization method for efficient charging and discharging of energy storage, characterized in that: Includes the following steps: S1): Obtain power system parameters; the power system parameters include pumped storage parameters, energy storage parameters, and the daily load demand curve Need2 of the power system; The pumped storage parameters include the installed capacity CXg, the pumped storage duration CXh, and the number of daily pumped storage charges CXn. The energy storage parameters include the installed capacity CNg, the duration of energy storage CNh, and the number of daily charging times CNn. S2): Calculate the average 24-hour electricity consumption based on the daily load demand curve Need2 of the power system; S3): Identify the entire interval graph formed by the envelope of the Average and Need2 curves. The area above the Average is defined as the positive area, and the area below the Average is defined as the negative area. Record the envelope area of ​​each positive area and the envelope area of ​​each negative area. S4): Based on the pumping and storage parameters, charging operations are performed in the negative area region and discharging operations are performed in the positive area region. S5): Repeated charging and discharging operations until the total charging and discharging area requirement for the day is met or the maximum number of operations is reached; S6): After all pumping and storage processing is completed within a day, a new demand curve Need3 is formed; S7): Energy storage is performed on the Need3 curve after pumped storage treatment to form the final optimized demand curve Need4, where the daily discharge area of ​​energy storage is S. 放 Keep it within the preset percentage range.

2. The intelligent optimization method for efficient charging and discharging of energy storage according to claim 1, characterized in that: Charging operations in negative area regions include the following steps: M1): Each time a charge is performed, the graph with the largest negative area is selected, and the lowest point is found within the selected negative area. The lowest point is the minimum power value min. M2): Set the loop step size to m. Starting from the lowest point, i.e. the lowest power value min, calculate the power value min+n×m after n loops. Set the horizontal axis corresponding to the power value min+n×m after n loops as "horizontal axis min+n×m". The total area formed by "horizontal axis min+n×m" and the negative area envelope below is S1. M3): Based on the charging completion determination condition, determine whether the current pumping and charging is complete. If not, proceed to step M2; if complete, proceed to step M4. M4): Remove the area below "min + n × m" from the Need2 curve to form a new demand curve, and record the total pumped storage charging area S. 充 The time and location of the charging operation, and the charging height at that time and location.

3. The intelligent optimization method for efficient charging and discharging of energy storage according to claim 2, characterized in that: The charging completion determination condition includes "charging completion determination condition 1" or "charging completion determination condition 2". Charging is completed when either "charging completion determination condition 1" or "charging completion determination condition 2" is met. The "charging completion judgment condition 1" is: the height between the horizontal axis "min+n×m" and the lowest point reaches the pumped storage installed capacity CXg or Average-min; that is, min+n×m≥CXg or min+n×m≥Average-min; The "charging completion judgment condition 2" is: the envelope area S1 of "horizontal axis min+n×m" and below reaches the product of the pumping capacity CXg and the pumping duration CXh, that is, S1≥CX*CXh. If there are two charging operations per day, the constraint is S1+S2≤CX*CXh, where S2 is the total area formed by "horizontal axis min+n×m" and the negative area envelope below during the second charging.

4. The intelligent optimization method for efficient charging and discharging of energy storage according to claim 3, characterized in that: If all positive areas have undergone pumping and discharging operations within a day, the total daily discharge area S 放 It has not yet reached 75% of the total charging area for today, i.e., S 放 If < (S1 + S2) * 75%; then discard the previous charging operation result, restart the charging operation for today, and use "charging completion judgment condition 3" instead of "charging completion judgment condition 2" to judge the charging completion. The "charging completion judgment condition 3" is: the envelope area S1 between "horizontal axis min + n × m" and below reaches 4 / 3 times the total discharge area of ​​the day, that is, S1 ≥ S 放 *4 / 3, If there are two charging operations per day, then the constraint is S1 + S2 ≤ S 放 *4 / 3.

5. The intelligent optimization method for efficient charging and discharging of energy storage according to claim 1, characterized in that: Performing a discharge operation in the positive area region includes the following steps: N1): During each discharge, select the shape with the largest positive area in the diagram, and find the highest point from the selected positive area. The highest point is the maximum power value (max). N2): Set the loop step size to m. Starting from the highest point, i.e., the maximum power value max, calculate the power value max-n×m after n loops. Set the horizontal axis corresponding to the power value max-n×m after n loops as "horizontal axis max-n×m". The total area formed by "horizontal axis max-n×m" and the positive area envelope above is S. 放 ; N3): Based on the discharge completion determination condition, determine whether the pumping and discharging is complete. If not, proceed to step N2; if complete, proceed to step N4. N4): Remove the area above "horizontal axis max-n×m" from the Need2 curve to form a new demand curve, and record the total pumped storage and discharge area S. 放 The time and location of the discharge operation, and the discharge height at that time and location.

6. The intelligent optimization method for efficient charging and discharging of energy storage according to claim 5, characterized in that: The discharge completion determination condition includes "discharge completion determination condition 1" or "discharge completion determination condition 2". Discharge is completed when either "discharge completion determination condition 1" or "discharge completion determination condition 2" is met. The "discharge completion judgment condition 1" is: the height of the horizontal axis max-n×m and the highest point reaches the pumping capacity CXg or max-Average, that is, max-n×m≥CXg or max-n×m≥max-Average. The "discharge completion judgment condition 2" is: the area S of the upper envelope and the horizontal axis "max-n×m". 放 The total charging area reached 75% of the total area for the day.

7. The intelligent optimization method for efficient charging and discharging of energy storage according to claim 1, characterized in that: In step S7), the daily discharge area S of the energy storage 放 The area is controlled within a preset percentage range, where the preset percentage is the total area S of the pumped-storage charging. 充 85%, that is, S 放 ≤S 充 *85%.

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