Maximum demand control method and device for energy storage peak-valley arbitrage charging period

Abstract

The invention discloses a maximum demand control method and device in an energy storage peak-valley arbitrage charging period. The method comprises the steps of collecting total load power data of a user side and real-time operation state data of an energy storage system in real time within a preset valley electricity price charging period, and reading a reference maximum demand reference value which takes effect at the current moment; comparing the collected total load power data with the read standard maximum demand reference value in real time to generate a power over-limit trigger signal; and in response to the power over-limit trigger signal, controlling the energy storage system to execute reverse power output until the discharge energy value output by the energy storage system completely counteracts the accumulated charge energy value input in the current demand metering period. According to the technical scheme, during valley electricity charging, the self-charging electric quantity is counteracted through precise discharging, the maximum demand record of the system does not contain energy storage charging components, therefore, extra electric charge is avoided, and the arbitrage capacity is completely reserved.

Description

Technical Field

[0001] This invention relates to the technical field of power energy storage and demand management, and in particular to a method and device for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage. Background Technology

[0002] With the deepening of electricity market reform and the implementation of time-of-use pricing mechanisms, user-side electrochemical energy storage systems have become an important means for industrial and commercial enterprises to reduce electricity costs and improve energy management flexibility. A typical user-side energy storage system consists of energy storage battery units, an energy storage converter, a step-up transformer, an energy management system, and related electrical equipment. Its core economic operating model typically relies on peak shaving and valley filling, i.e., charging the energy storage batteries during off-peak hours at night and discharging them to supply loads during daytime peak hours, thus profiting from the price difference. A schematic diagram of the energy storage system structure is shown below. Figure 9 As shown. In addition, to control the basic electricity costs that enterprises need to pay each month, which are usually calculated based on the maximum active power demand of the month, energy storage systems are often equipped with maximum demand control functions. By adjusting their own charging and discharging power, the total load power at the grid connection point can be kept below the set demand threshold, thus avoiding high demand costs due to short-term overload.

[0003] However, in actual operation, especially during off-peak hours when energy storage systems are charging, existing maximum demand control strategies have shortcomings. Conventional strategies often employ a combination of fixed thresholds and dynamic tracking. The system sets a baseline demand reference value and monitors the total load in real time during charging periods, i.e., the sum of user load and energy storage charging power. If the total power approaches or exceeds the threshold, it responds by reducing or even zeroing the energy storage charging power. However, this method has a fundamental risk: within a rolling 15-minute demand metering window, if the energy storage charges at a higher power initially, and is forced to reduce power later due to a sudden increase in user load, the total electricity consumption within that window already includes the energy storage's initial charging contribution. This could lead to an unreasonable inflation of the updated maximum actual demand value for the month by the energy storage charging volume, essentially increasing demand charges due to the energy storage's own charging behavior, eroding the revenue gained through peak-valley arbitrage. Current technology cannot ensure that the metered maximum demand value purely reflects the actual user load demand during charging periods, thus constituting a significant uncertainty risk for the return on investment of user-side energy storage projects. How to properly solve the above problems has become an urgent issue for the industry. Summary of the Invention

[0004] This invention provides a method and apparatus for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage systems. This method enables precise demand control during off-peak electricity pricing charging periods, ensuring that the charging power of the energy storage system does not affect the actual recorded maximum demand value. The energy storage system discharges within the same metering window, only offsetting the power required for its own charging. This avoids exceeding demand charges while fully preserving the energy storage capacity for peak-valley arbitrage, achieving optimal economic operation.

[0005] According to a first aspect of the present invention, a method for controlling the maximum demand during peak-valley arbitrage charging periods of energy storage is provided, the method comprising: During the preset off-peak electricity price charging period, the total load power data of the user side and the real-time operating status data of the energy storage system are collected in real time, and the reference value of the current maximum demand is read. The total load power data collected is compared with the reference value of the maximum demand read in real time to generate a power over-limit trigger signal, which indicates whether the current load level has exceeded the demand control threshold. In response to the power over-limit trigger signal, the energy storage system is controlled to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the cumulative charging energy value input in the current demand metering cycle.

[0006] In one embodiment, the cumulative charging energy value input within the current demand metering cycle includes: A time window with a preset billing duration is established as the demand measurement cycle, and the time window slides forward continuously on the time axis according to a preset time step. The system continuously locks onto the current time window and identifies the time interval between the start time of the time window and the current time. Within the identified time interval, the power of the energy storage system when it is in a charging state is integrally calculated to quantify the cumulative charging energy value.

[0007] In one embodiment, controlling the energy storage system to perform reverse power output includes: Calculate the difference between the total load power data and the reference maximum demand value to obtain the demand deviation power value; If the demand deviation power value is less than the rated discharge power of the energy storage system, then the demand deviation power value shall be used as the target discharge power. If the demand deviation power value is greater than or equal to the rated discharge power of the energy storage system, then the rated discharge power shall be used as the target discharge power.

[0008] In one embodiment, it also includes: The discharged amount of the energy storage system during the reverse power output process is accumulated in real time; The discharged power is compared with the accumulated charging energy value in real time; If the comparison result shows that the discharged amount is equal to or greater than the accumulated charging energy value, a discharge termination command is immediately generated to control the energy storage system to stop discharging.

[0009] In one embodiment, it also includes: After stopping the discharge in response to the discharge termination command, continuously monitor whether the total load power data falls back below the reference maximum demand value; If the total load power data is detected to have dropped, then determine whether the current time is still within the off-peak electricity price charging period; If the total load power data is not detected to have dropped, the energy storage system is controlled to switch back to charging mode and operate in maximum demand follow mode.

[0010] In one embodiment, the benchmark maximum demand reference value includes: At the beginning of each billing cycle, an initial demand value predicted based on historical load data is loaded as the benchmark maximum demand reference value. If, during system operation, it is detected that the generated actual maximum demand value has exceeded the current benchmark maximum demand reference value, the actual maximum demand value will be updated to the new benchmark maximum demand reference value and used for subsequent comparisons.

[0011] According to a second aspect of the present invention, a maximum demand control device for energy storage peak-valley arbitrage charging periods is provided, comprising: The acquisition module is used to collect the total load power data of the user side and the real-time operating status data of the energy storage system in real time during the preset off-peak electricity price charging period, and read the reference value of the current maximum demand. The comparison module is used to compare the collected total load power data with the read benchmark maximum demand reference value in real time to generate a power over-limit trigger signal, which indicates whether the current load level has exceeded the demand control threshold. The control module is used to respond to the power over-limit trigger signal and control the energy storage system to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the cumulative charging energy value input in the current demand metering cycle.

[0012] In one embodiment, the acquisition module, the comparison module, and the control module are controlled to execute any of the above-described methods for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage.

[0013] According to a third aspect of the present invention, an electronic device is provided, comprising: a communication interface, a processor, and a memory; The memory is used to store program instructions, which, when executed by the processor that is connected to the memory via the communication interface, implement any of the above-mentioned maximum demand control methods for peak-valley arbitrage charging periods.

[0014] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which computer program instructions are stored, which, when executed by a computer (e.g., a processor in a computer), implement any of the above-described methods for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage.

[0015] In summary, this invention provides a method and apparatus for controlling maximum demand during peak-valley arbitrage charging periods for energy storage. The method includes: during a preset off-peak electricity price charging period, real-time acquisition of total load power data on the user side and real-time operating status data of the energy storage system, and reading the current effective benchmark maximum demand reference value; real-time comparison of the acquired total load power data with the read benchmark maximum demand reference value to generate a power over-limit trigger signal, wherein the power over-limit trigger signal indicates whether the current load level has exceeded the demand control threshold; and in response to the power over-limit trigger signal, controlling the energy storage system to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the accumulated charging energy value input during the current demand metering cycle. The technical solution of this application dynamically suppresses load peaks during off-peak charging through real-time monitoring and control, ensuring that the user's maximum demand does not exceed the limit, thereby avoiding high demand-based electricity charges. The discharge amount can be limited to offset the charging amount during the same period. While achieving demand management, it ensures that the energy storage system's electricity reserves for peak-valley arbitrage are not lost, thus achieving dual optimization of demand control and arbitrage revenue.

[0016] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and drawings.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 A flowchart of a method for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage, provided as an embodiment of the present invention; Figure 2 A flowchart of another method for controlling the maximum demand during peak-valley arbitrage charging periods provided in an embodiment of the present invention; Figure 3 A flowchart of another method for controlling the maximum demand during peak-valley arbitrage charging periods provided as an embodiment of the present invention; Figure 4 A flowchart of another method for controlling the maximum demand during peak-valley arbitrage charging periods provided as an embodiment of the present invention; Figure 5 A flowchart of another method for controlling the maximum demand during peak-valley arbitrage charging periods provided as an embodiment of the present invention; Figure 6 A flowchart of another method for controlling the maximum demand during peak-valley arbitrage charging periods provided as an embodiment of the present invention; Figure 7 A structural diagram of a maximum demand control device for peak-valley arbitrage charging periods provided as an embodiment of the present invention; Figure 8 A structural diagram of an electronic device provided as an embodiment of the present invention; Figure 9 A schematic diagram of the energy storage system structure provided for an embodiment of the present invention; Figure 10 This is a schematic diagram of electrical load and energy storage charging and discharging provided for an embodiment of the present invention. Detailed Implementation

[0020] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0021] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0022] like Figure 1 As shown, the present invention provides a method for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage. This method includes: In step S11, during the preset off-peak electricity price charging period, the total load power data of the user side and the real-time operating status data of the energy storage system are collected in real time, and the reference value of the current maximum demand is read. In step S12, the collected total load power data is compared with the read reference value of the maximum demand in real time to generate a power over-limit trigger signal. The power over-limit trigger signal indicates whether the current load level has exceeded the demand control threshold. In step S13, in response to the power over-limit trigger signal, the energy storage system is controlled to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the cumulative charging energy value input in the current demand metering cycle.

[0023] In one embodiment, a method for controlling the maximum demand during peak-valley arbitrage charging periods in a user-side energy storage power station is described in detail. This method primarily relies on an energy management system deployed within the energy storage power station. Its core objective is to address the technical challenge of exceeding the predetermined maximum demand threshold when the user's internal load suddenly increases during off-peak electricity pricing, leading to additional demand charges. In this embodiment, the control system initiates an initialization procedure to confirm whether the current time falls within a preset off-peak electricity pricing charging period. Once confirmed, the system immediately enters a high-frequency monitoring mode. In this high-frequency monitoring mode, the energy management system collects real-time total load power data at the user-side grid connection point via connected smart meters or sensors. This total load power data reflects the sum of the user's basic electricity load and the current charging power of the energy storage system. A schematic diagram of the electricity load and energy storage charging / discharging is shown below. Figure 10 As shown. Simultaneously, the system will also read real-time operating status data from within the energy storage system, including but not limited to the current charging / discharging status, real-time power values, and remaining battery capacity, to ensure that subsequent control strategies are based on an accurate understanding of the system's current status.

[0024] While collecting data, the system needs to establish a baseline for comparison, namely, reading the current effective maximum demand reference value. The setting of the maximum demand reference value is dynamically adjustable to adapt to demand management needs in different months or under different operating conditions. Specifically, at the beginning of each billing cycle, the system loads an initial demand value predicted based on historical load data, or directly uses the actual maximum demand value of the previous month as the current maximum demand reference value. Throughout the system's operation, the control logic continuously monitors the actual demand. If it detects that the actual maximum demand value has exceeded the currently set maximum demand reference value due to non-energy storage charging factors (such as natural growth in user production load), the system will automatically update this new, larger actual maximum demand value to the latest maximum demand reference value.

[0025] The control system performs millisecond-level real-time comparisons between the collected total load power data from the user side and the reference maximum demand value. This allows it to sensitively detect whether the current load level is approaching or exceeding the preset demand control safety line. In conventional peak-valley arbitrage charging mode, the energy storage system typically charges at a constant or following power. The total load power in this mode includes both the user's basic production and living load and the energy storage system's charging power. If the comparison shows that the total load power data exceeds the reference maximum demand value, it means that without system intervention, the average power during the current demand metering period is highly likely to break the monthly maximum demand record, resulting in unnecessary electricity costs. At this moment, the control algorithm immediately generates a power over-limit trigger signal. This signal is the activation command for switching from the conventional charging following mode to the emergency demand easing mode, indicating that the system must adopt an active energy offsetting strategy to prevent demand from exceeding limits.

[0026] In response to the power over-limit trigger signal, the system immediately enters the reverse power output control phase. This embodiment employs an energy offsetting strategy for the energy storage system's discharge. The controller sends a command to the energy storage converter, controlling the energy storage system to quickly switch from a charging state to a discharging state, executing reverse power output. To accurately quantify the energy to be offset, the system introduces the concept of a time window for the demand metering cycle. The system establishes a time window with a duration consistent with the grid demand metering duration (typically fifteen minutes) and allows this time window to continuously slide forward on the time axis. The system locks onto the current time window in real time and identifies the time interval from the start of the time window to the current time. Within this interval, the system performs time integration calculations on the power of the energy storage system when it is in the charging state, thereby quantifying the cumulative charging energy value of the energy storage system within a specific demand metering cycle.

[0027] To perform reverse power output, the system dynamically adjusts the discharge power based on the deviation between the real-time load and the threshold. It calculates the difference between the total load power data and the reference maximum demand value in real time to obtain the demand deviation power value. If this demand deviation power value is less than the rated discharge power of the energy storage system, the system uses this value as the target discharge power. In this case, the energy storage discharge precisely fills the load gap, achieving balance. If the demand deviation power value fluctuates drastically and is greater than or equal to the rated discharge power of the energy storage system, the system will output at its maximum rated discharge power to reduce the metered load on the grid side to the greatest extent possible. Simultaneously, the system accumulates the discharged electricity during the reverse power output process, continuing to discharge until the discharged energy value completely offsets the accumulated charging energy value input within the current demand metering cycle.

[0028] During the discharge process of the energy storage system, the system continuously compares the real-time accumulated discharged energy with the previously calculated accumulated charging energy value. When the comparison result shows that the discharged energy is equal to or greater than the accumulated charging energy value, it indicates that the energy offset target has been achieved, and the system immediately generates a discharge termination command to control the energy storage system to stop discharging. After discharging stops, the system does not immediately resume charging, but continuously monitors whether the total load power data has fallen below the reference maximum demand value. If the load has fallen and the current time is still during the off-peak electricity price charging period, the system controls the energy storage system to switch back to charging mode and operate in maximum demand following mode to continue peak-valley arbitrage; if the load remains high, the system remains in standby or limits charging, thereby maximizing the retention of energy storage arbitrage capacity while ensuring that the maximum demand is not refreshed.

[0029] In a preferred embodiment, the maximum demand control discharge strategy is implemented during off-peak electricity charging periods as follows: When the real-time load increases and exceeds the reference value for maximum demand, the energy storage begins to discharge.

[0030] After the energy storage starts discharging under the maximum demand strategy, it calculates in real time the demand metering cycle "energy storage discharge - energy storage charging ≤ 0". When the energy storage discharge amount in the real-time demand metering cycle equals the energy storage charging amount, the energy storage stops discharging.

[0031] 1. Start time of energy storage discharge Load power - reference maximum demand > 0 2. Energy storage discharge period Period when load power > reference maximum demand ① Load power - reference maximum demand value < rated energy storage power Energy storage discharge power = load power - reference value for maximum demand The energy storage discharge corresponds to the demand metering cycle. The energy storage discharge amount equals the energy storage charging amount. Energy storage stops discharging.

[0032] ② Load power - reference maximum demand > energy storage rated power (due to excessive load surge) Energy storage discharge power = rated energy storage power From the moment the first slip occurs, the maximum demand value is refreshed, and the energy storage discharge reduces the component of the energy storage charging quantity.

[0033] When the Nth slip occurs and the maximum demand value is refreshed, if the energy storage discharge amount equals the energy storage charging amount within the demand metering cycle, the energy storage stops discharging, and the refreshed maximum demand value has no component of energy storage charging amount.

[0034] 3. Energy storage and discharge power Energy storage discharge power = IF (load power - reference maximum demand value > energy storage rated power, load power - reference maximum demand value, energy storage rated power) 4. End of energy storage discharge When the total energy storage charge and discharge amount for a real-time rolling 15-minute demand metering cycle is 0, the energy storage stops discharging.

[0035] User-side energy storage employs a peak-valley arbitrage control strategy, charging during off-peak electricity price periods. Simultaneously, while charging, a maximum demand follow-up control strategy is implemented, controlling the charging power (minimum is 0) and prohibiting charging beyond the maximum demand.

[0036] Therefore, during the energy storage charging period, as long as the load power exceeds the reference maximum demand value, a maximum demand update will be generated.

[0037] On the surface, it appears that the increase in load power caused the maximum demand update, but the new maximum demand value includes the energy storage charging amount. The energy storage charging amount follows the maximum demand reference value, resulting in an increase in the updated maximum demand value.

[0038] To address the impact of energy storage operation on maximum demand, the maximum demand control strategy is optimized. During the peak-valley arbitrage strategy's energy storage charging period, a maximum demand control discharge priority strategy is simultaneously implemented. This ensures that the energy storage discharges accordingly to offset the charging amount that follows the maximum demand during the 15-minute metering cycle. This ensures that the updated maximum actual demand value during energy storage charging does not contain any component of the energy storage charging amount.

[0039] The control objective of the maximum demand control strategy is the component of the maximum demand value (electricity in a 15-minute demand metering cycle / 0.25 hours) without energy storage charging.

[0040] During the low-price energy storage charging period of the energy storage peak-valley arbitrage strategy, the maximum demand control strategy is prioritized for energy storage discharge. The control target is that the maximum demand value refreshed in the demand metering cycle (energy in 15 minutes of demand metering cycle / 0.25 hours) has no component of energy storage charging, while minimizing discharge: after the maximum demand value is updated and there is no component of energy storage charging, it automatically switches to the peak-valley arbitrage charging strategy; only the amount of electricity charged by the energy storage in the demand metering cycle is released, without excessive discharge.

[0041] The technical solution in this embodiment dynamically suppresses load peaks during off-peak charging through real-time monitoring and control, ensuring that the user's maximum demand does not exceed the limit, thereby avoiding high demand-based electricity charges. The discharge amount can be limited to offset the charging amount during the same period. While achieving demand management, it ensures that the energy storage system's electricity reserves for peak-valley arbitrage are not lost, thus achieving dual optimization of demand control and arbitrage revenue.

[0042] In one embodiment, such as Figure 2 As shown, it also includes the following steps S21-S23: In step S21, a time window with a preset billing duration is established as the demand measurement cycle, and the time window slides forward continuously on the time axis according to the preset time step. In step S22, the time window at the current moment is locked in real time, and the time interval between the start time of the time window and the current moment is identified; In step S23, within the identified time interval, the power of the energy storage system when it is in the charging state is integrally calculated to quantify the cumulative charging energy value.

[0043] In one embodiment, the energy storage system involved in this embodiment is deployed on the industrial and commercial user side, mainly including energy storage battery units, energy storage converter (PCS), step-up transformer, energy management system (EMS), and necessary power monitoring devices. System operation requires pre-configuration of off-peak electricity price charging period parameters, typically set during the low-peak hours of the grid's time-of-use pricing (e.g., 11:00 PM to 7:00 AM the next day). At the hardware deployment level, a high-precision power sensor is installed at the grid connection point to collect real-time total load power data on the user side; the energy storage system is internally configured with a battery management system (BMS) to monitor the battery's state of charge (SOC), charge / discharge power limits, and real-time operating status.

[0044] At the beginning of each calendar month's billing cycle, the system loads an initial demand value derived from the user's historical load data using statistical forecasting methods as a baseline maximum demand reference value. This baseline maximum demand reference value can be preset and adjusted based on factors such as the user's production plan and seasonal load changes. During system operation, a composite strategy combining fixed thresholds and dynamic tracking is employed. If the actual maximum demand value generated in the current month exceeds the current baseline maximum demand reference value, the system automatically updates the actual maximum demand value to the new baseline maximum demand reference value for subsequent real-time comparisons.

[0045] During the preset off-peak electricity pricing charging period, the system collects total load power data from the user side in real time at a preset sampling period (e.g., 1 second). This data represents the sum of the user's own load and the charging power of the energy storage system. The system compares the collected total load power data with the currently effective benchmark maximum demand reference value in real time. When the total load power exceeds the benchmark maximum demand reference value, a power over-limit trigger signal is immediately generated. This power over-limit trigger signal not only indicates that the current load level has exceeded the demand control threshold, but also initiates a preparatory procedure for the energy storage system to switch from charging to discharging. To prevent frequent switching due to instantaneous fluctuations, an appropriate power margin buffer can be set.

[0046] In response to a power over-limit trigger signal, the system immediately controls the energy storage system to perform reverse power output. The discharge power setting follows the demand deviation tracking principle, calculating the difference between the total load power and the reference maximum demand value to obtain the demand deviation power value. If the demand deviation power value is less than the rated discharge power of the energy storage system, this demand deviation power value is used as the target discharge power to achieve precise power compensation; if the demand deviation power value is greater than or equal to the rated discharge power, the rated discharge power is used as the target discharge power to provide maximum demand support. Discharge control not only targets instantaneous power but also focuses on energy balance. The system establishes a 15-minute time window as the demand metering cycle, which slides forward continuously in preset steps (e.g., every 1 minute). The system locks the current time window in real time, identifies the time interval from the start of the window to the current time, and integrates the power of the energy storage system during the charging state within this interval to obtain the cumulative charging energy value. The control objective of reverse power output is to ensure that the discharge energy output by the energy storage system in the current demand metering cycle completely offsets the cumulative charging energy input in that cycle, thereby ensuring that the net energy metering value in the 15-minute demand metering cycle does not contain any energy storage charging component.

[0047] During the reverse power output process of the energy storage system, the system accumulates the discharged electricity in real time and compares it with the aforementioned accumulated charging energy value. When the discharged electricity is detected to be equal to or greater than the accumulated charging energy value, a discharge termination command is immediately generated to control the energy storage system to stop discharging, so as to avoid over-discharge affecting subsequent arbitrage capacity. After the discharge stops, the system continuously monitors the total load power data: if the total load power falls below the reference maximum demand value, and the current time is still during the off-peak electricity price charging period, the system controls the energy storage system to switch back to charging state and continue to operate in maximum demand follow mode; if the total load power does not fall below the reference value, it indicates that the user load remains high, and the energy storage system remains in standby state until the load conditions are met or the time period changes.

[0048] In one embodiment, such as Figure 3 As shown, controlling the energy storage system to perform reverse power output includes the following steps S31-S33: In step S31, the difference between the total load power data and the reference maximum demand value is calculated to obtain the demand deviation power value; In step S32, if the demand deviation power value is less than the rated discharge power of the energy storage system, then the demand deviation power value is used as the target discharge power. In step S33, if the demand deviation power value is greater than or equal to the rated discharge power of the energy storage system, then the rated discharge power is used as the target discharge power.

[0049] In one embodiment, when a power over-limit trigger signal is generated, the energy storage system executes precise calculation and control logic for reverse power output. Closed-loop regulation based on real-time feedback ensures that discharge behavior effectively suppresses instantaneous load peaks on the user side while maintaining operational economy. Specifically, when the energy management system receives the power over-limit trigger signal, its internal computing unit immediately initiates the demand deviation calculation process to obtain the current total load power data on the user side, which represents the instantaneous total active power at the grid connection point; simultaneously, it reads the currently effective benchmark maximum demand reference value, i.e., the power control upper limit set by the user. The system calculates the algebraic difference between these two values ​​to obtain the demand deviation power value. This demand deviation power value quantitatively reflects the specific extent to which the current total load exceeds the control target, and also clarifies the minimum compensation power required to pull the total load back below the benchmark value, thereby providing a precise quantitative benchmark for subsequent power dispatch and avoiding energy storage capacity waste caused by excessive discharge.

[0050] If the demand deviation power value is less than the rated discharge power of the energy storage system, the system enters a precise regulation mode. The system compares the demand deviation power value with the rated discharge power of the energy storage system, which is the maximum power that the energy storage converter and battery pack can sustainably output within a safe range. If the demand deviation power value is less than the rated discharge power, it indicates that the current over-limit is within the full compensation capacity of the energy storage system. In this case, the control system adopts an on-demand output strategy, directly setting the demand deviation power value as the target discharge power command for the energy storage converter. For example, if the load exceeds the benchmark value by 500 kW and the rated power of the energy storage is 1000 kW, the control system commands the converter to output 500 kW of power. In this mode, the energy storage output power tracks load deviation changes in real time, precisely limiting the total load power monitored by the grid side to the benchmark maximum demand reference value, while avoiding excessive power output from the energy storage system. This reduces ineffective energy consumption and ensures its arbitrage capability during subsequent peak periods.

[0051] If the comparison result shows that the demand deviation power value is greater than or equal to the rated discharge power of the energy storage system, the control system prioritizes equipment safety and limits the target discharge power to the rated discharge power of the energy storage system, allowing the energy storage system to discharge at its maximum permissible power. Although this mode may not be able to completely suppress the total load below the benchmark value, it can still reduce the load peak, reduce the refresh range of the maximum demand, and effectively prevent the risk of overload, overheating, or damage caused by commands exceeding the equipment's carrying capacity, ensuring the continuous and stable operation of the system under high load conditions.

[0052] In one embodiment, such as Figure 4 As shown, it also includes the following steps S41-S43: In step S41, the discharged amount of the energy storage system during the reverse power output process is accumulated in real time; In step S42, the discharged energy is compared with the accumulated charging energy value in real time; In step S43, if the comparison result shows that the discharged amount is equal to or greater than the accumulated charging energy value, a discharge termination command is immediately generated to control the energy storage system to stop discharging.

[0053] In one embodiment, this embodiment details how the energy storage system achieves precise control through energy closed-loop control when performing reverse power output. Simultaneously with the control system initiating discharge, the metering module within the energy management system begins high-frequency sampling of the real-time discharge power of the energy storage system and continuously accumulates this data through time integration calculations to generate dynamically updated discharged power.

[0054] The system uses the accumulated charging energy calculated within the current demand metering cycle as a threshold for determining the termination of discharge. The control unit compares the real-time accumulated discharged energy with this threshold at a high frequency to monitor whether the discharge process has achieved the energy offset target.

[0055] When the comparison result shows that the discharged energy is equal to or greater than the accumulated charging energy, the control unit immediately generates a discharge termination command and sends it to the energy storage converter to stop the discharge. This mechanism ensures that the discharge amount is strictly limited to offset the simultaneous charging amount, avoiding additional consumption of energy storage energy, thereby achieving demand control while ensuring the arbitrage capability of the energy storage system during subsequent peak periods.

[0056] In one embodiment, such as Figure 5 As shown, it also includes the following steps S51-S53: In step S51, after stopping the discharge in response to the discharge termination command, the total load power data is continuously monitored to see if it falls below the reference maximum demand value. In step S52, if the total load power data is detected to have dropped, it is determined whether the current time is still within the off-peak electricity price charging period; In step S53, if the total load power data is not detected to have dropped, the energy storage system is controlled to switch back to charging mode and operate in maximum demand follow mode.

[0057] In one embodiment, during monitoring, the system executes branch decision logic based on the changing trend of total load power data. If the monitoring results show that the total load power data on the user side has significantly decreased and stabilized below the baseline maximum demand reference value, this indicates that the load peak that caused the previous demand alarm has been resolved. At this time, the system will further read the system clock to determine whether the current time is still within the preset off-peak electricity price charging period. If it is confirmed that it is still within the off-peak electricity period, the system will lift the restrictions, allowing the energy storage system to resume the normal charging process according to the established peak-valley arbitrage strategy.

[0058] Conversely, if monitoring results show that the total load power data has not decreased and remains higher than or equal to the baseline maximum demand reference value, the control system executes a special reset strategy. Although the load is still high, since the energy storage system has already offset its own charging impact during the current metering cycle through discharge, the system determines that it is unnecessary to continue discharging to compensate for the user's base load and offset its own charging. Therefore, the control system logically switches the energy storage system's operating mode back to charging mode, but at the same time, it forcibly activates the maximum demand follow mode. In this mode, since the real-time monitored load is still higher than the reference value, the maximum demand follow algorithm dynamically limits the allowed charging power to zero (or a very small safe positive value). Physically, this appears as the energy storage system being in a standby, non-charging state, but logically it has returned to the charging standby mode.

[0059] In one embodiment, such as Figure 6 As shown, it also includes the following steps S61-S63: In step S61, at the beginning of each billing cycle, an initial demand value predicted based on historical load data is loaded as the benchmark maximum demand reference value. In step S62, if during system operation, it is detected that the generated actual maximum demand value has exceeded the current benchmark maximum demand reference value, then the actual maximum demand value is updated to a new benchmark maximum demand reference value and used for subsequent comparison.

[0060] In one embodiment, at the beginning of each billing cycle, typically at the start of each calendar month, the energy management system automatically initiates an initialization loading process. The system accesses the historical database, retrieving historical load data and maximum demand records for the user during similar periods. Based on this historical data, the system, in conjunction with a built-in load forecasting algorithm or user-preset production plan parameters, calculates or directly loads a predicted initial demand value.

[0061] The benchmark maximum demand reference value is not fixed; it follows a dynamic update principle of only increasing and never decreasing. That is, within a billing cycle, its value will only be adjusted upwards as the actual maximum demand is updated. The energy management system continuously monitors the actual maximum demand generated at the grid connection point. If, during monitoring, it is found that non-energy storage factors such as the startup of a user's production line or sudden high-load operation of equipment cause the current actual maximum demand value to objectively exceed the currently effective benchmark maximum demand reference value within the system, the control logic will recognize this change. At this time, the system will immediately trigger an update, directly updating this actual maximum demand value to the new benchmark maximum demand reference value. This updated value will be directly used for real-time comparison and power trigger judgment in subsequent time periods, thereby ensuring that the energy storage system's demand control threshold can keep up with the user's highest demand level for the month.

[0062] In one embodiment, Figure 7 This is a block diagram illustrating a maximum demand control device for peak-valley arbitrage charging periods in energy storage, according to an exemplary embodiment. Figure 7 As shown, the maximum demand control device for peak-valley arbitrage charging periods of the energy storage includes an acquisition module 71, a comparison module 72, and a control module 73.

[0063] The acquisition module 71 is used to collect the total load power data of the user side and the real-time operating status data of the energy storage system in real time during the preset off-peak electricity price charging period, and read the reference value of the benchmark maximum demand that is effective at the current moment. The comparison module 72 is used to compare the collected total load power data with the read benchmark maximum demand reference value in real time to generate a power over-limit trigger signal, which indicates whether the current load level has exceeded the demand control threshold. The control module 73 is used to respond to the power over-limit trigger signal and control the energy storage system to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the cumulative charging energy value input in the current demand metering cycle. The acquisition module 71, comparison module 72, and control module 73 included in the block diagram of the maximum demand control device for peak-valley arbitrage charging periods of energy storage are controlled to execute the maximum demand control method for peak-valley arbitrage charging periods of energy storage as described in any of the above embodiments.

[0064] like Figure 8 As shown, the present invention provides an electronic device 800, which includes: a communication interface, a processor 801, and a memory 802; The memory 802 stores program instructions. When executed by the processor 801, which is connected to the memory 802 via the communication interface, the program instructions collect the total load power data and the real-time operating status data of the energy storage system in real time during a preset off-peak electricity price charging period, and read the current effective reference value of the maximum demand. The collected total load power data is compared with the read reference value of the maximum demand in real time to generate a power over-limit trigger signal. The power over-limit trigger signal indicates whether the current load level has exceeded the demand control threshold. In response to the power over-limit trigger signal, the energy storage system is controlled to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the accumulated charging energy value input in the current demand metering cycle.

[0065] This invention provides a computer-readable storage medium storing computer program instructions. When executed by a processor, the computer program instructions collect real-time total load power data and real-time operating status data of the energy storage system during a preset off-peak electricity price charging period, and read the current effective reference value for maximum demand. The collected total load power data is compared in real-time with the read reference value for maximum demand to generate a power over-limit trigger signal, which indicates whether the current load level has exceeded the demand control threshold. In response to the power over-limit trigger signal, the energy storage system is controlled to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the accumulated charging energy value input during the current demand metering cycle.

[0066] It should be understood that the specific features, operations, and details described above regarding the method of the present invention can also be similarly applied to the apparatus and system of the present invention, or vice versa. Furthermore, each step of the method of the present invention described above can be performed by a corresponding component or unit of the apparatus or system of the present invention.

[0067] It should be understood that the various modules / units of the device of the present invention can be implemented wholly or partially through software, hardware, firmware, or a combination thereof. Each module / unit can be embedded in the processor of a computer device in hardware or firmware form or independent of the processor, or it can be stored in the memory of a computer device in software form for the processor to call to execute the operation of each module / unit. Each module / unit can be implemented as an independent component or module, or two or more modules / units can be implemented as a single component or module.

[0068] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores computer instructions executable by the processor, which, when executed by the processor, instruct the processor to perform steps of the methods of embodiments of the present invention. The computer device can be broadly categorized as a server, terminal, or any other electronic device with the necessary computing and / or processing capabilities. In one embodiment, the computer device may include a processor, memory, network interface, communication interface, etc., connected via a system bus. The processor of the computer device can be used to provide the necessary computing, processing, and / or control capabilities. The memory of the computer device may include a non-volatile storage medium and internal memory. The non-volatile storage medium may store an operating system, computer programs, etc. The internal memory can provide an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface and communication interface of the computer device can be used to connect and communicate with external devices via a network. When the computer program is executed by the processor, it performs the steps of the methods of the present invention.

[0069] This invention can be implemented as a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, causes the steps of the methods of embodiments of the invention to be performed. In one embodiment, the computer program is distributed across multiple network-coupled computer devices or processors, such that the computer program is stored, accessed, and executed in a distributed manner by one or more computer devices or processors. A single method step / operation, or two or more method steps / operations, may be executed by a single computer device or processor or by two or more computer devices or processors. One or more method steps / operations may be executed by one or more computer devices or processors, and one or more other method steps / operations may be executed by one or more other computer devices or processors. One or more computer devices or processors may execute a single method step / operation, or execute two or more method steps / operations.

[0070] It will be understood by those skilled in the art that the method steps of the present invention can be performed by a computer program instructing related hardware, such as a computer device or processor. The computer program may be stored in a non-transitory computer-readable storage medium, and its execution causes the steps of the present invention to be performed. Depending on the context, any references herein to memory, storage, databases, or other media may include non-volatile and / or volatile memory. Examples of non-volatile memory include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid-state drive, etc. Examples of volatile memory include random access memory (RAM), external cache memory, etc.

[0071] The technical features described above can be combined arbitrarily. Although not all possible combinations of these technical features are described, any combination of these technical features should be considered to be covered by this specification, provided that such combination does not contain contradictions.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage, characterized in that, include: During the preset off-peak electricity price charging period, the total load power data of the user side and the real-time operating status data of the energy storage system are collected in real time, and the reference value of the current maximum demand is read. The total load power data collected is compared with the reference value of the maximum demand read in real time to generate a power over-limit trigger signal, which indicates whether the current load level has exceeded the demand control threshold. In response to the power over-limit trigger signal, the energy storage system is controlled to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the cumulative charging energy value input in the current demand metering cycle.

2. The method for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage as described in claim 1, characterized in that, The cumulative charging energy value input within the current demand metering cycle includes: A time window with a preset billing duration is established as the demand measurement cycle, and the time window slides forward continuously on the time axis according to a preset time step. The system continuously locks onto the current time window and identifies the time interval between the start time of the time window and the current time. Within the identified time interval, the power of the energy storage system when it is in a charging state is integrally calculated to quantify the cumulative charging energy value.

3. The method for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage as described in claim 2, characterized in that, The control of the energy storage system to perform reverse power output includes: Calculate the difference between the total load power data and the reference maximum demand value to obtain the demand deviation power value; If the demand deviation power value is less than the rated discharge power of the energy storage system, then the demand deviation power value shall be used as the target discharge power. If the demand deviation power value is greater than or equal to the rated discharge power of the energy storage system, then the rated discharge power shall be used as the target discharge power.

4. The method for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage as described in claim 1, characterized in that, Also includes: The discharged amount of the energy storage system during the reverse power output process is accumulated in real time; The discharged power is compared with the accumulated charging energy value in real time; If the comparison result shows that the discharged amount is equal to or greater than the accumulated charging energy value, a discharge termination command is immediately generated to control the energy storage system to stop discharging.

5. The method for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage as described in claim 4, characterized in that, Also includes: After stopping the discharge in response to the discharge termination command, continuously monitor whether the total load power data falls back below the reference maximum demand value; If the total load power data is detected to have dropped, then determine whether the current time is still within the off-peak electricity price charging period; If the total load power data is not detected to have dropped, the energy storage system is controlled to switch back to charging mode and operate in maximum demand follow mode.

6. The method for controlling the maximum demand during peak-valley arbitrage charging periods for energy storage as described in claim 1, characterized in that, The reference value for the maximum demand includes: At the beginning of each billing cycle, an initial demand value predicted based on historical load data is loaded as the benchmark maximum demand reference value. If, during system operation, it is detected that the generated actual maximum demand value has exceeded the current benchmark maximum demand reference value, the actual maximum demand value will be updated to the new benchmark maximum demand reference value and used for subsequent comparisons.

7. A maximum demand control device for energy storage peak-valley arbitrage charging periods, characterized in that, include: The acquisition module is used to collect the total load power data of the user side and the real-time operating status data of the energy storage system in real time during the preset off-peak electricity price charging period, and read the reference value of the current maximum demand. The comparison module is used to compare the collected total load power data with the read benchmark maximum demand reference value in real time to generate a power over-limit trigger signal, which indicates whether the current load level has exceeded the demand control threshold. The control module is used to respond to the power over-limit trigger signal and control the energy storage system to perform reverse power output until the discharge energy value output by the energy storage system completely offsets the cumulative charging energy value input in the current demand metering cycle.

8. The maximum demand control device for peak-valley arbitrage charging periods as described in claim 7, characterized in that: The acquisition module, the comparison module, and the control module are controlled to execute the maximum demand control method for energy storage peak-valley arbitrage charging periods as described in any one of claims 2 to 6.

9. An electronic device, characterized in that, include: Communication interface, processor, memory; The memory is used to store program instructions, which, when executed by the processor that is connected to the memory via the communication interface, enable the electronic device to implement the maximum demand control method for peak-valley arbitrage charging periods as described in any one of claims 1 to 6.

10. A computer-readable storage medium having program instructions stored thereon, characterized in that, When the program instructions are executed by the computer, the computer implements the maximum demand control method for peak-valley arbitrage charging periods as described in any one of claims 1 to 6.

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