A data industrial park dual-storage collaborative energy supply system and a method for operating the same

Abstract

This application provides a dual-storage collaborative energy supply system for a data industry park and its operation method, relating to the field of integrated energy system optimization and control technology. The system includes a collaborative dispatch controller, an electric energy storage unit, and a cold storage unit cooled by a cold source. The method includes: generating an upper-level control plan based on state information, with economic or peak-shaving objectives, containing planning curves for the cold source and electric energy storage; calculating a dynamic power adjustment margin that can respond to real-time fluctuations based on the plan and the power capacity of the electric energy storage; allocating constrained real-time power commands to the electric energy storage based on the system's real-time power deviation and this margin, ensuring that its deviation does not exceed the margin, and controlling the electric energy storage accordingly, while simultaneously controlling the cold source to operate according to the upper-level plan. The dynamic margin mechanism isolates the conflict between long-cycle economic dispatch and short-term rapid adjustment, maintaining real-time power balance of the system while ensuring economic objectives, thus balancing operational economy, power supply stability, and equipment lifespan.

Description

Technical Field

[0001] This application belongs to the field of integrated energy system optimization and control technology, specifically involving a dual-storage collaborative energy supply system for a data industrial park and its operation method. Background Technology

[0002] Energy supply systems, especially integrated energy systems that incorporate renewable energy, electrical energy storage, and cold energy storage, play a crucial role in achieving efficient energy utilization and low-carbon operation. These systems typically involve two different timescales of regulation needs: one is economical dispatching and load shifting on an hourly or even longer timescale (such as using peak-valley pricing for peak shaving and valley filling); the other is rapid power balancing and power quality support on a second- to minute-scale basis (such as smoothing out fluctuations in renewable energy output and ensuring power supply to critical loads).

[0003] To address these needs, existing technologies typically employ hierarchical or collaborative optimization strategies. For example, some solutions develop economical operating plans for cooling and power systems at the day-ahead scheduling level and utilize resources such as energy storage and adjustable loads at the real-time adjustment level to smooth power fluctuations. However, these methods still face a significant challenge in implementation: the coupling conflict between control objectives at different time scales. Specifically, to achieve hourly economic objectives (such as cooling load shifting and reducing peak power consumption), the upper-level scheduling plan allocates specific charging and discharging schedules to energy storage units to coordinate with the operation of the cooling source. However, when the system faces second-level power fluctuations during real-time operation, allowing energy storage units to freely respond to these fluctuations may cause their actual state of charge (SOC) and output trajectory to deviate from the preset plan, thereby weakening or even undermining the achievement of the upper-level economic objectives. Conversely, if the rapid adjustment capability of energy storage units is excessively restricted to strictly guarantee the economic plan, the real-time power balance and power quality of the system will be difficult to guarantee. This dynamic contradiction between the rigid demands of upper-level planning and the flexibility of rapid adjustment at the lower level often leads to a dilemma in the overall operation of the system, where "ensuring economic efficiency" and "ensuring stability" are mutually reinforcing, making it difficult to balance long-term operational benefits with short-term power supply quality.

[0004] While some existing two-layer optimization schemes attempt to coordinate different resources, their lower-level control usually allows for simultaneous adjustment of cold source power and electrical energy storage output, or only aims at minimizing cost and fluctuations for unified optimization. They do not establish clear, dynamic boundaries in the control logic to isolate control commands at different time scales, thus failing to fundamentally solve the above-mentioned coupling conflict problem. Summary of the Invention

[0005] This application provides a dual-storage collaborative energy supply system for a data industry park and its operation method to solve one of the aforementioned technical problems.

[0006] The technical solution adopted in this application is as follows:

[0007] This application provides a dual-storage collaborative energy supply system for a data industry park, including:

[0008] Cooperative scheduling controller, the cooperative scheduling controller being used for:

[0009] The status information of the energy supply system is obtained, the energy supply system including a power network, an electric energy storage unit connected to the power network, and a cold storage unit connected to the power network and providing cold energy through a cold source;

[0010] Based on the status information, a first control plan is generated with a preset optimization objective. The first control plan includes at least the operating power plan of the cold source.

[0011] Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power adjustment margin.

[0012] Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin.

[0013] The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

[0014] According to one embodiment of this application, the first control plan is generated based on the state information with a preset optimization objective. The first control plan includes at least the operating power plan of the cold source, with the optimization objective being to minimize the system operating cost or peak power. The first control plan includes the power reference curve of the cold source and the planned power support curve of the energy storage unit.

[0015] According to one embodiment of this application, the dynamic power regulation margin is calculated as follows: β(t) = min{ P_max - P_plan(t), P_plan(t) - P_min}, where P_max is the rated maximum discharge power of the energy storage unit, P_min is its rated maximum charging power, P_plan(t) is the planned power support curve value of the energy storage unit at time t, and the discharge power is defined as positive and the charging power is defined as negative.

[0016] According to one embodiment of this application, the step of allocating a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power regulation margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin, includes:

[0017] Based on the planned power value of the energy storage unit at the current moment and the real-time power deviation, the initial real-time power target of the energy storage unit is determined.

[0018] Based on the rated maximum discharge power and rated maximum charging power of the energy storage unit, the initial real-time power target is subjected to a first limiting process to obtain an intermediate power value;

[0019] Based on the dynamic power adjustment margin, the intermediate power value is subjected to a second limiting process to obtain the constrained real-time power command, so that the deviation of the constrained real-time power command from the planned power value does not exceed the dynamic power adjustment margin.

[0020] According to one embodiment of this application, the energy supply system is a data industry park energy supply system, the power network is a park public bus, and the status information includes the output forecast of renewable energy power generation devices connected to the park public bus and the park load forecast.

[0021] According to one embodiment of this application, the system further includes an uninterruptible power supply or static switching device connected between the campus public bus and the critical IT load. The collaborative scheduling controller is further configured to: in the process of allocating a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power adjustment margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power adjustment margin, when the absolute value of the real-time power deviation exceeds the dynamic power adjustment margin, trigger the uninterruptible power supply or static switching device to provide millisecond-level power support to maintain the continuous power supply to the critical IT load.

[0022] A second aspect of this application provides a method for the coordinated power supply operation of dual energy storage in a data industry park, applied to the aforementioned system. The method is executed by a coordinated scheduling controller and includes the following steps:

[0023] Based on the status information of the energy supply system, a first control plan is generated with a preset optimization target. The first control plan includes at least the operating power plan of the cold source.

[0024] Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power adjustment margin.

[0025] Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin.

[0026] The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

[0027] According to one embodiment of this application, the dynamic power regulation margin is calculated as follows: β(t) = min{ P_max - P_plan(t), P_plan(t) - P_min}, where P_max is the rated maximum discharge power of the energy storage unit, P_min is its rated maximum charging power, and P_plan(t) is the planned power value of the energy storage unit in the first control plan at time t.

[0028] According to one embodiment of this application, the step of allocating a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power regulation margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin, includes:

[0029] Based on the planned power value of the energy storage unit at the current moment and the real-time power deviation, the initial real-time power target of the energy storage unit is determined.

[0030] Based on the rated maximum discharge power and rated maximum charging power of the energy storage unit, the initial real-time power target is subjected to a first limiting process to obtain an intermediate power value;

[0031] Based on the dynamic power adjustment margin, the intermediate power value is subjected to a second limiting process to obtain the constrained real-time power command, so that the deviation of the constrained real-time power command from the planned power value does not exceed the dynamic power adjustment margin.

[0032] A third aspect of this application provides an electronic device including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method as described.

[0033] Due to the adoption of the above technical solution, the beneficial effects achieved by this application are as follows:

[0034] This application establishes a clear and quantifiable boundary between the first control plan (especially the cold source operation power plan) generated by the upper-level optimization and the real-time power allocation at the lower level by introducing a core mechanism of dynamic power regulation margin. This margin clarifies the maximum capacity range that the energy storage unit can use to respond to real-time power fluctuations without interfering with the upper-level plan. The lower-level allocation steps strictly limit the deviation of the real-time power command of the energy storage unit within this margin, thereby ensuring the rigid execution of the upper-level economic / peak shaving plan in terms of control logic, while reserving deterministic operating space for the lower-level rapid power support, effectively resolving the target coupling conflict between long-term economic dispatch and short-term stable operation.

[0035] Because the coordinated planning of the upper-level cold source and energy storage (the first control plan) is effectively guaranteed, the system can make full use of the cold storage units to transfer the cold load during different time periods and optimize the charging and discharging strategies of the energy storage to achieve peak shaving and valley filling, thereby significantly reducing the overall system operating cost or peak demand. At the same time, the lower-level distribution ensures the instantaneous balance of the common bus power and voltage stability through rapid and controlled adjustment within the dynamic margin, improving the adaptability to renewable energy fluctuations and load changes, and achieving a balance between economy and stability.

[0036] In traditional control methods, energy storage units may engage in irregular deep charging and discharging due to frequent responses to various fluctuations, or operate under suboptimal conditions to accommodate multiple objectives. This invention provides a "flexible constraint" on its real-time output through dynamic power adjustment margins, ensuring smooth adjustments only within its "capacity margin" while prioritizing the execution of upper-level plans. This avoids impacting the energy reserves reserved for economic objectives due to short-term fluctuations, reduces unnecessary and redundant charge-discharge cycles, helps extend the lifespan of the energy storage unit, and lowers its total lifecycle cost.

[0037] The dynamic power regulation margin is a time-varying variable, dynamically calculated based on the upper-level plan and the real-time power capacity of the energy storage, and can adapt to changes in the system's operating state. This enables the control system to not only possess clear coordination rules but also flexible adjustment elasticity, better cope with prediction errors and uncertainties, and embody the advanced characteristics of intelligent collaborative control. Attached Figure Description

[0038] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0039] Figure 1 A flowchart illustrating a dual-storage collaborative energy supply operation method for a data industry park, provided as an embodiment of this application;

[0040] Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0041] Figure label:

[0042] 810, Processor; 820, Communication interface; 830, Memory; 840, Communication bus. Detailed Implementation

[0043] To more clearly illustrate the overall concept of this application, a detailed explanation is provided below with reference to the accompanying drawings.

[0044] Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application may also be implemented in other ways different from those described herein. Therefore, the scope of protection of this application is not limited to the specific embodiments disclosed below. It should be noted that, unless otherwise specified, the embodiments of this application and the features thereof can be combined with each other.

[0045] In this application, unless otherwise expressly specified and limited, the "above" or "below" of the second feature can mean that the first and second features are in direct contact, or that the first and second features are in indirect contact through an intermediate medium. In the description of this specification, references to terms such as "an embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples.

[0046] Example 1

[0047] like Figure 1 As shown, a dual-storage collaborative energy supply system for a data industrial park includes:

[0048] Cooperative scheduling controller, the cooperative scheduling controller being used for:

[0049] The status information of the energy supply system is obtained. The energy supply system includes a power network, an electric energy storage unit connected to the power network, and a cold storage unit connected to the power network and providing cooling capacity through a cold source.

[0050] Specifically, this step refers to the collaborative dispatch controller collecting or receiving data sets reflecting the current operating status, configuration, and external environment of each component of the energy supply system. The status information specifically includes: 1) real-time electrical parameters of the power network, such as common bus voltage, frequency, and total load power; 2) real-time operating status of energy storage units, including their current charge / discharge power, remaining capacity (SOC), rated power upper and lower limits, and health status; 3) operating status of cold storage units and their associated cold sources, including the start / stop status of the cold source (such as a chiller unit), real-time cooling power, and the current cold storage capacity and temperature of the cold storage equipment; 4) predictive or planned data related to system operation, such as short-term output forecasts of renewable energy (such as photovoltaic and wind power), predicted curves of park electricity and cooling loads, and electricity price information. This information is acquired through sensors, measurement and control units, or the upper-level energy management system (EMS) deployed on each device side and transmitted to the collaborative dispatch controller via a communication network, forming the data basis for its optimization calculations and real-time decision-making.

[0051] For example, in a specific implementation applied to a data industry park, the collaborative scheduling controller obtains status information in the following ways: The controller collects the voltage and frequency values ​​of the 10kV common bus connecting each data center and distributed energy source in real time through the park's Supervisory Control and Data Acquisition (SCADA) system. Simultaneously, the controller obtains real-time data from the battery management system (BMS) of the lithium iron phosphate battery storage array within the park, including its current discharge power of 200kW, SOC of 65%, rated maximum discharge power P_max of 500kW, and rated maximum charging power P_min of -400kW (negative values ​​indicate charging). For the cold storage system, the controller obtains information from the chiller controller and the cold storage tank temperature sensors, indicating that both chillers are currently operating at 70% load, with a total cooling capacity of 1400kW, the cold storage tank has 40% remaining capacity, and the outlet water temperature is 6℃. Furthermore, the controller receives the photovoltaic power generation forecast curve for the next 24 hours, the power consumption forecast curve for the IT load of each data center, and time-of-use electricity price signals from the park's energy management platform. All of the above data is updated every 5 seconds and aggregated to the collaborative scheduling controller via industrial Ethernet, providing comprehensive state awareness for its subsequent optimization and coordinated control.

[0052] Based on the status information, a first control plan is generated with a preset optimization objective. The first control plan includes at least the operating power plan of the cold source.

[0053] Specifically, this step refers to the collaborative scheduling controller calculating, based on the acquired comprehensive state information and through built-in or external optimization algorithms, a system coordinated operation plan for a certain future time period (e.g., the next 24 hours), i.e., the first control plan. The preset optimization objectives are typically economic or technical goals, such as minimizing the total system operating cost, minimizing peak power purchased from the upper-level grid (peak shaving), or maximizing the local consumption rate of renewable energy. The core of generating this plan lies in coordinating the operating sequence of the energy storage unit and the cold storage unit, where the cold storage unit possesses a strong load shifting capability due to its thermal inertia. Therefore, the first control plan must at least include the planned operating power of the cold source (e.g., refrigeration unit) at various future time segments, i.e., the "cold source operating power plan." This plan indicates when and at what power the cold source will operate, so that ice or refrigeration can be prepared in advance and stored in the cold storage equipment during periods of low electricity prices or renewable energy surplus, thereby reducing cold source power consumption during periods of high electricity prices or power shortages and achieving time-shifting of the cooling load. In addition, the first control plan usually generates a "planned power support curve for the energy storage unit" in conjunction with the cold source plan. This curve specifies the planned charging and discharging power of the energy storage to meet the overall economic objectives, such as charging during peak photovoltaic power generation periods and discharging during peak load periods at night.

[0054] For example, in a data park implementation with the optimization objective of minimizing daily operating costs, the collaborative scheduling controller performs optimization calculations based on the acquired next-day photovoltaic output forecast, IT load and air conditioning cooling load forecast, and time-of-use electricity price information. The generated first control plan covers 00:00 to 24:00 the next day, with a time resolution of 15 minutes. This plan explicitly includes: 1) Cooling source operating power plan: It is planned that two chiller units will operate at full load of 800kW during the off-peak electricity price period at night (00:00-08:00), storing most of the generated cooling capacity in ice storage tanks; during the normal electricity price period during the day (08:00-12:00, 14:00-18:00), they will operate at a lower load of 400kW, partially meeting the real-time cooling demand, with the remaining portion supplemented by the release of cooling from the ice storage tanks; during the peak electricity price period (12:00-14:00, 18:00-22:00), they will be completely shut down, and the entire cooling load of the park will be borne by the ice storage tanks. 2) Planned Power Support Curve for Energy Storage: The planned energy storage system charges at 250kW during peak photovoltaic output hours (10:00-14:00) to store inexpensive electricity; and discharges at 300kW during peak load and electricity price hours (18:00-20:00) to replace purchasing electricity from the grid. This plan aims to minimize the park's total electricity costs through peak-shifting via cold storage and valley filling.

[0055] Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power regulation margin.

[0056] Specifically, this step refers to, under the premise that the first control plan has clearly defined the planned charging and discharging power values ​​(i.e., the planned power support curve) of the energy storage unit at each future time, and in combination with the inherent physical power limitations of the energy storage unit, calculating the upper limit of the power space that can be additionally used to respond to real-time power fluctuations (such as sudden changes in renewable energy output or load changes) at each time without interfering with or deviating from the predetermined plan. This upper limit of space is the regulation capability range, and is quantified as a dynamic power regulation margin that changes over time. The power capability of the energy storage unit is defined by its rated parameters, mainly including the rated maximum discharge power and the rated maximum charging power, which represent the positive limit of its output power and the negative limit of its absorption power from the grid, respectively. The core of calculating the dynamic power regulation margin is to first determine the distances of the planned power value at each time from its positive physical limit (maximum discharge power) and negative physical limit (maximum charging power), and then take the smaller of the two as the margin at that time. This calculation ensures that regardless of whether the real-time power command requires the energy storage unit to increase discharge or charge based on the plan (i.e., responding to positive or negative power deviations), the actual output variation is strictly limited within this margin range, thereby ensuring that its actual operating trajectory will not impact the planning framework set for the upper-level economic objectives.

[0057] For example: Continuing from the previous embodiment, assume that the first control plan specifies that the planned power value P_plan of the energy storage at 14:00 on a certain day is -100kW (a negative value indicates a planned charge of 100kW), and that the rated maximum discharge power P_max of the energy storage unit is 500kW, and the rated maximum charging power P_min is -400kW (i.e., the maximum absorbable power is 400kW). Based on this, calculate the dynamic power regulation margin β at 14:00: First, calculate the margin between the planned value and the discharge limit, which is P_max - P_plan = 500 - (-100) = 600kW; then calculate the margin between the planned value and the charging limit, which is P_plan - P_min = (-100) - (-400) = 300kW. Taking the smaller of the two, we get β(14:00) = 300kW. This means that at 14:00, to ensure the 100kW charging plan can be executed, the actual power of the energy storage unit can be dynamically adjusted within the range of [-400kW, +200kW] based on the planned value of -100kW to respond to real-time demand. However, the absolute magnitude of the adjustment (i.e., the deviation between the real-time power command and the planned value of -100kW) cannot exceed 300kW. For example, it can be adjusted to a maximum discharge of 200kW (deviation +300kW) or to a maximum charge of -400kW (deviation -300kW), but it cannot exceed this range, otherwise it will disrupt the preset economical charging plan. This margin changes over time. For example, at 20:00, if the planned value P_plan is +300kW (discharge), then the margin β(20:00) = min(500-300, 300-(-400)) = min(200, 700) = 200kW.

[0058] Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin.

[0059] Specifically, this step refers to the coordinated dispatch controller calculating and issuing a final real-time power command to the energy storage unit based on the difference between the actual total power and the planned total power monitored by the energy supply system in real-time operation (i.e., real-time power deviation), and in conjunction with the pre-calculated dynamic power adjustment margin. The generation of this command must adhere to a core constraint: the deviation of the command value from the predetermined planned power value in the first control plan must not exceed the corresponding dynamic power adjustment margin at that moment. The specific process includes: first, superimposing the real-time power deviation onto the planned power value of the energy storage unit to form an initial real-time power target without considering margin constraints. Subsequently, this initial target undergoes dual limiting processing. The first limiting is based on the physical power capability (rated maximum charge / discharge power) of the energy storage unit, ensuring that the command does not exceed the equipment hardware limits. The second limiting is based on the dynamic power adjustment margin, ensuring that the absolute deviation between the command value and the planned value is limited within the margin range. After this constrained allocation, the energy storage unit can respond to the real-time power imbalance demand of the system within its capacity, and strictly ensure that its actual output trajectory will not disrupt the first control plan formulated by the upper layer, thereby achieving decoupling and synergy between short-term power regulation and long-term economic planning.

[0060] For example: Continuing from the previous example, at 14:00, the planned power value P_plan for energy storage in the first control plan is -100kW (100kW charging), and the dynamic power adjustment margin β at this time is 300kW. Assume that the system's real-time monitoring detects a sudden decrease in photovoltaic output, resulting in a +250kW power deficit on the park's public bus (i.e., a real-time power deviation ΔP of +250kW). First, calculate the initial real-time power target: P_rt = P_plan + ΔP = -100kW + 250kW = +150kW (i.e., a target discharge of 150kW). Next, perform constrained allocation: first, physical limits are applied, assuming the equipment power upper and lower limits are P_max = 500kW and P_min = -400kW, with the target +150kW falling within this range. Then, margin constraint limits are applied, calculating the deviation between the planned value -100kW and the target value +150kW as 250kW, which is less than the margin of 300kW; therefore, this deviation is allowed. Ultimately, the constrained real-time power command P_final issued by the coordinated dispatch controller to the energy storage unit is +150kW. This command changes the energy storage unit from a planned charge of 100kW to an actual discharge of 150kW, compensating for the insufficient photovoltaic output by adding a net 250kW of discharge power. This 250kW change does not exceed the 300kW margin, therefore it does not affect the basic charging plan set to coordinate with the cold source operation. If the real-time power deviation ΔP is +400kW, the initial target is +300kW, which deviates from the planned value of -100kW by 400kW, exceeding the 300kW margin. In this case, the final constrained command value will be limited to the planned value plus the margin, i.e., -100kW + 300kW = +200kW, only responding to the 300kW power deficit. The remaining 100kW deficit must be addressed by other system mechanisms (such as backup power).

[0061] The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

[0062] Specifically, this step refers to the coordinated scheduling controller outputting the two types of commands generated to the corresponding controlled equipment actuators. For the cold source, the controller, based on the predetermined cold source operating power plan in the first control plan, sends control signals containing target power values ​​or start / stop states to the refrigeration unit or its variable frequency drive at the corresponding time points, driving the cold source to operate according to the planned curve. For the energy storage unit, the controller, based on the constrained real-time power command after real-time calculation and constraint processing, sends control signals containing target charging and discharging power values ​​to the energy storage converter, driving the energy storage unit to adjust its output in real time according to the command. The output of the control signal can be periodic or event-triggered, and usually includes monitoring and feedback of the execution results, such as confirming whether the equipment operates according to the command and whether the actual operating parameters are consistent with the command, thereby forming a closed-loop control to ensure that the overall system operating state meets the long-term economic goals of the first control plan, while maintaining real-time power balance through constrained rapid adjustment of energy storage.

[0063] For example, in one specific embodiment, the collaborative scheduling controller sends the generated first control plan (time resolution 15 minutes) to the chiller group control system before midnight every day. For instance, the plan indicates that both chillers will operate at full load of 800kW between 04:00 and 08:00. At 04:00, the controller sends a start command and a power setpoint of 800kW to the start / stop controllers of both chillers. The units start and operate at the set power, while simultaneously feeding back the actual operating power to the controller. For the energy storage unit, the controller performs closed-loop control with a second-level cycle. Assume that at a certain time 14:00:05, the controller calculates the constrained real-time power command for that time to be +150kW (discharge). The controller immediately sends the power setpoint command +150kW to the energy storage converter via the Modbus TCP protocol. After receiving the command, the converter adjusts its power electronic switching state within milliseconds, enabling the battery pack to discharge to the grid at a power of 150kW. The actual discharge power value (e.g., +148kW) is then fed back to the controller via a communication link. The controller continuously compares the planned value, the commanded value, and the actual value to ensure that the actual output of the energy storage unit always tracks real-time power demand within the dynamic power regulation margin constraint, while the cooling source operates strictly according to the hourly plan.

[0064] According to one embodiment of this application, the first control plan is generated based on the state information with a preset optimization objective. The first control plan includes at least the operating power plan of the cold source, with the optimization objective being to minimize the system operating cost or peak power. The first control plan includes the power reference curve of the cold source and the planned power support curve of the energy storage unit.

[0065] Specifically, based on the collected state information, the collaborative scheduling controller uses a preset optimization model and algorithm to calculate and generate a system collaborative operation plan for future scheduling cycles (e.g., the next 24 hours), namely the first control plan. The "preset optimization objective" is clearly defined as minimizing the total system operating cost or minimizing the peak power obtained from the grid (i.e., peak shaving). To achieve this objective, the core of the optimization calculation lies in coordinating the operating strategies of the energy storage unit (energy-type, fast-response) and the cold storage unit (which achieves thermal energy storage and time shifting through cold source power consumption). Therefore, the generated first control plan must at least specify the "cold source operating power plan," which is specifically embodied in a time series curve, namely the "cold source power baseline curve," which specifies the planned start-stop status and operating power value of the cold source (such as a chiller unit or heat pump) at various time segments in the future (e.g., every 15 minutes). At the same time, to coordinate with the operation of the cold source and jointly achieve the overall optimization objective, the first control plan also simultaneously generates the "planned power support curve of the energy storage unit." This curve specifies the planned charging and discharging power values ​​of energy storage at various times within the same dispatch cycle. Its formulation requires comprehensive consideration of electricity price signals, renewable energy output forecasts, load forecasts, and cold source operation plans. The aim is to further achieve peak shaving and valley filling, smooth net load fluctuations, or reduce electricity purchase costs through the planned charging and discharging of energy storage. These two curves together constitute the upper-level optimization instructions. The cold source power baseline curve aims to shift electrical load using cold storage characteristics, while the planned power support curve for energy storage performs time-shifting and optimization of the electrical energy itself. The two work together to achieve the preset economic or technical objectives.

[0066] According to one embodiment of this application, the dynamic power regulation margin is calculated as follows: β(t) = min{ P_max - P_plan(t), P_plan(t) - P_min}, where P_max is the rated maximum discharge power of the energy storage unit, P_min is its rated maximum charging power, P_plan(t) is the planned power support curve value of the energy storage unit at time t, and the discharge power is defined as positive and the charging power is defined as negative.

[0067] Specifically, this step defines the specific calculation method for the dynamic power regulation margin β(t). Here, P_max represents the rated maximum discharge power of the energy storage unit, which is a positive value; P_min represents its rated maximum charging power, which is a negative value. P_plan(t) represents the planned power value pre-set for the energy storage unit at time t in the first control plan. This value follows the same sign convention: a positive value represents planned discharge, and a negative value represents planned charging. During calculation, the difference between the current planned power value P_plan(t) and its upper limit of discharge capacity P_max (P_max - P_plan(t)), and the difference between it and its lower limit of charging capacity P_min (P_plan(t) - P_min) are first calculated. These two differences represent the space for the energy storage unit to further increase discharge power and the space for further increase in charging power (i.e., more negative) under the current plan, respectively. Finally, the smaller of these two differences is taken as the dynamic power regulation margin β(t) at that time. The purpose of this calculation method is to ensure that, regardless of whether the real-time system demand requires increased discharge or increased charging, the actual power variation of the energy storage unit is uniformly limited within a conservative margin range that does not interfere with the plan. This margin is a function that varies with time t, and its value is dynamically determined by the planned power and the physical limits of the equipment at each moment.

[0068] According to one embodiment of this application, the step of allocating a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power regulation margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin, includes:

[0069] Based on the planned power value of the energy storage unit at the current moment and the real-time power deviation, the initial real-time power target of the energy storage unit is determined.

[0070] Based on the rated maximum discharge power and rated maximum charging power of the energy storage unit, the initial real-time power target is subjected to a first limiting process to obtain an intermediate power value;

[0071] Based on the dynamic power adjustment margin, the intermediate power value is subjected to a second limiting process to obtain the constrained real-time power command, so that the deviation of the constrained real-time power command from the planned power value does not exceed the dynamic power adjustment margin.

[0072] Specifically, based on the planned power value of the energy storage unit at the current moment and the real-time power deviation, the initial real-time power target of the energy storage unit is determined. This step means that at the current control moment, the collaborative dispatch controller first reads the planned power value pre-set for the energy storage unit in the first control plan and uses this planned power value as the basic output target for the current moment. Simultaneously, the collaborative dispatch controller obtains the real-time power deviation of the energy supply system at that moment. The real-time power deviation reflects the power difference between the actual operating state and the planned operating state of the system. This difference may originate from inconsistencies between the actual output of renewable energy and the predicted value, fluctuations in park load, or other operational disturbances. Based on the planned power value and the real-time power deviation, the collaborative dispatch controller forms the initial real-time power target that the energy storage unit should prioritize responding to at the current moment. The initial real-time power target represents the theoretically target power level that the energy storage unit should achieve if only compensation for the current real-time power deviation is considered, without temporarily considering the power boundary and planned constraints of the energy storage unit.

[0073] Based on the rated maximum discharge power and rated maximum charging power of the energy storage unit, the initial real-time power target is subjected to a first limiting process to obtain an intermediate power value. This step ensures that the initial real-time power target does not exceed the physical capabilities of the energy storage unit itself. Since the energy storage unit is limited by its rated parameters during actual operation, its discharge power cannot exceed the rated maximum discharge power, and its charging power cannot exceed the allowable range corresponding to the rated maximum charging power. Therefore, the collaborative scheduling controller needs to first perform boundary constraint processing on the initial real-time power target. When the initial real-time power target is within the allowable charging and discharging power range of the energy storage unit, the intermediate power value can remain unchanged. When the initial real-time power target exceeds the range limited by the rated maximum discharge power or the rated maximum charging power, it is truncated to the corresponding power boundary. The intermediate power value obtained after this first limiting process represents the target power value that the energy storage unit can achieve at the current moment, provided that the physical power capabilities of the equipment are met.

[0074] Based on the dynamic power adjustment margin, the intermediate power value undergoes a second limiting process to obtain the constrained real-time power command, ensuring that the deviation of the constrained real-time power command from the planned power value does not exceed the dynamic power adjustment margin. The purpose of this step is to further ensure that, while already satisfying the physical power boundaries of the equipment, the real-time adjustment behavior of the energy storage unit will not excessively impact the planned operation schedule at the current moment. The dynamic power adjustment margin represents the maximum range of deviation that the energy storage unit is allowed to deviate from the planned value under the current planned power value constraint. The collaborative scheduling controller compares the intermediate power value with the planned power value at the current moment to determine whether the deviation of the intermediate power value from the planned power value is within the range allowed by the dynamic power adjustment margin. When the deviation does not exceed the dynamic power adjustment margin, the intermediate power value can be directly used as the constrained real-time power command; when the deviation exceeds the dynamic power adjustment margin, the intermediate power value needs to be further tightened to the boundary range defined by the dynamic power adjustment margin, so as to obtain the final constrained real-time power command issued to the energy storage unit.

[0075] Through the above processing, the collaborative scheduling controller can respond to real-time power deviations in the power supply system while simultaneously considering the equipment capacity constraints and planned execution constraints of the energy storage units. In other words, the constrained real-time power commands enable the energy storage units to appropriately adjust to real-time power fluctuations in the system, while ensuring that this adjustment remains within the allowable range of the current planned operation framework. This prevents the energy storage units from deviating excessively from planned values ​​and affecting the execution effect of the upper-level control plan. Thus, a coordinated and unified approach can be achieved between real-time power balance requirements and planned scheduling objectives.

[0076] According to one embodiment of this application, the energy supply system is a data industry park energy supply system, the power network is a park public bus, and the status information includes the output forecast of renewable energy power generation devices connected to the park public bus and the park load forecast.

[0077] Specifically, this step clarifies a specific application scenario for this application: the energy supply system of a data industry park. The power network specifically refers to the "park common bus," which distributes electricity to all buildings and facilities within the park, and all major power generation and consumption equipment is connected to this bus. In this scenario, the status information particularly emphasizes the importance of predictive data, specifically including two types of key predictive information: first, the "output forecast" of renewable energy power generation devices (such as photovoltaic power generation systems and wind turbines) connected to the park common bus in a specific future period (e.g., the expected power generation curve); second, the "park load forecast" for the entire park in the same period in the future, i.e., the total power demand curve. This load typically covers IT equipment load, lighting, air conditioning systems (including the portion supplying power to chiller units), and other auxiliary facilities. This predictive information is the core input data for generating the first control plan and performing economically optimized scheduling, enabling the controller to proactively arrange the coordinated operation strategy of the cold storage unit and the electric energy storage unit to cope with the intermittency of renewable energy and the volatility of the load.

[0078] According to one embodiment of this application, the system further includes an uninterruptible power supply or static switching device connected between the campus public bus and the critical IT load. The collaborative scheduling controller is further configured to: in the process of allocating a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power adjustment margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power adjustment margin, when the absolute value of the real-time power deviation exceeds the dynamic power adjustment margin, trigger the uninterruptible power supply or static switching device to provide millisecond-level power support to maintain the continuous power supply to the critical IT load.

[0079] Specifically, an uninterruptible power supply (UPS) or static transfer switch is additionally configured between the park's public bus and critical IT loads (such as data center servers) that have extremely high requirements for power supply continuity. In addition to executing the main control process, the collaborative scheduling controller is also tasked with monitoring and triggering this backup power supply. Specifically, during the core step of "allocating constrained real-time power commands to the energy storage unit based on real-time power deviation and dynamic power adjustment margin," the controller continuously compares the absolute value of the real-time power deviation with the current calculated dynamic power adjustment margin β(t). When the absolute value of the real-time power deviation exceeds β(t), it indicates that the current power imbalance demand has exceeded the allowable adjustment margin of the energy storage unit while ensuring the upper-level plan is met. At this time, the controller immediately generates a trigger signal and sends it to the control unit of the UPS or static transfer switch. Upon receiving a trigger signal, the backup equipment will be activated within milliseconds. For example, the uninterruptible power supply (UPS) will invert its battery energy, or a static transfer switch will instantly switch the load to the backup power line, thus providing instantaneous power deficit support for critical IT loads. The purpose of this mechanism is to ensure that when the system encounters severe power disturbances exceeding the "flexible" adjustment capabilities of the energy storage system, the power supply to critical loads is absolutely uninterrupted by activating the faster backup power supply, thereby pursuing economical and coordinated operation without sacrificing the highest priority of power supply reliability.

[0080] A second aspect of this application provides a method for the coordinated power supply operation of dual energy storage in a data industry park, applied to the aforementioned system. The method is executed by a coordinated scheduling controller and includes the following steps:

[0081] Based on the status information of the energy supply system, a first control plan is generated with a preset optimization target. The first control plan includes at least the operating power plan of the cold source.

[0082] Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power adjustment margin.

[0083] Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin.

[0084] The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

[0085] According to one embodiment of this application, the dynamic power regulation margin is calculated as follows: β(t) = min{ P_max - P_plan(t), P_plan(t) - P_min}, where P_max is the rated maximum discharge power of the energy storage unit, P_min is its rated maximum charging power, and P_plan(t) is the planned power value of the energy storage unit in the first control plan at time t.

[0086] According to one embodiment of this application, the step of allocating a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power regulation margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin, includes:

[0087] Based on the planned power value of the energy storage unit at the current moment and the real-time power deviation, the initial real-time power target of the energy storage unit is determined.

[0088] Based on the rated maximum discharge power and rated maximum charging power of the energy storage unit, the initial real-time power target is subjected to a first limiting process to obtain an intermediate power value;

[0089] Based on the dynamic power adjustment margin, the intermediate power value is subjected to a second limiting process to obtain the constrained real-time power command, so that the deviation of the constrained real-time power command from the planned power value does not exceed the dynamic power adjustment margin.

[0090] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in any of the first aspects above.

[0091] Figure 2 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 2 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 may call logical instructions in the memory 830 to execute the method in any of the embodiments of the first aspect described above, the method including:

[0092] Based on the status information of the energy supply system, a first control plan is generated with a preset optimization target. The first control plan includes at least the operating power plan of the cold source.

[0093] Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power adjustment margin.

[0094] Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin.

[0095] The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

[0096] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0097] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being able to be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer being able to perform the methods provided by the above methods, the method comprising:

[0098] Based on the status information of the energy supply system, a first control plan is generated with a preset optimization target. The first control plan includes at least the operating power plan of the cold source.

[0099] Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power adjustment margin.

[0100] Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin.

[0101] The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

[0102] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the methods provided by the above methods, the method comprising:

[0103] Based on the status information of the energy supply system, a first control plan is generated with a preset optimization target. The first control plan includes at least the operating power plan of the cold source.

[0104] Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power adjustment margin.

[0105] Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin.

[0106] The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

[0107] Example 2

[0108] This embodiment illustrates the specific application of the proposed solution in a data industry park, with the optimization objective of minimizing the total operating cost the following day.

[0109] In a specific application scenario, the rated voltage of the park's public busbar is 10kV. The park is equipped with distributed photovoltaic power generation devices, energy storage units, a cold source, and a cold storage unit. The energy storage unit is a lithium iron phosphate battery energy storage system with a rated maximum discharge power of 500kW and a maximum absorption power limit corresponding to the rated maximum charging power of 400kW. The cold source consists of two parallel-operated electric chiller units with a total cooling power limit of 1600kW. The cold storage unit is an ice storage device with a rated cold storage capacity of 6400kWh. The collaborative dispatch controller receives time-of-use electricity price information for the next 24 hours, the park's comprehensive electricity load forecast curve, the cold load forecast curve, and the photovoltaic output forecast curve, and generates a first control plan with the optimization objective of minimizing the total electricity purchase cost for the next day.

[0110] In this first control plan, the operating power of the cooling source is planned as follows: During the off-peak electricity price period from 00:00 to 07:00, the two chiller units will operate at a total power of 1400kW. After meeting the real-time cooling load of the park, the remaining cooling capacity will be stored in the cold storage unit. During the high-output photovoltaic period from 10:00 to 15:00, the chiller units will operate at a total power of 800kW. During the peak electricity price period from 18:00 to 21:00, the chiller units will operate at 400kW, and the remaining cooling load will be borne by the cold storage unit releasing cooling capacity. Simultaneously, the first control plan also includes a planned power support curve for the energy storage unit. From 11:00 to 14:00, the energy storage unit will operate according to a charging plan of 250kW, and from 18:00 to 20:00, the energy storage unit will operate according to a discharging plan of 300kW.

[0111] Taking 12:00 as an example, at this time, the first control plan stipulates that the energy storage unit is in a planned charging state with a planned charging power of 250kW. Based on the planned operating status at this time and the rated maximum charge / discharge capacity of the energy storage unit, the coordinated dispatch controller determines the range of adjustment capabilities that the energy storage unit can use to respond to real-time power changes under the current plan constraints. This range of adjustment capabilities represents the dynamic power regulation margin at the current time, meaning the maximum range of deviation the energy storage unit is allowed from the planned value without disrupting the established charging plan at this time.

[0112] If, at any given moment, cloud cover causes the actual photovoltaic output to decrease by 100kW compared to the predicted value, resulting in a 100kW real-time power deficit on the park's public bus, the collaborative dispatch controller first determines the initial real-time power target for the energy storage unit based on the planned charging power and this real-time power deficit. Subsequently, the collaborative dispatch controller first applies a first limiting process to the initial real-time power target based on the rated maximum discharge power and rated maximum charging power of the energy storage unit to ensure that the target does not exceed the equipment's physical capabilities. Then, based on the current dynamic power adjustment margin, a second limiting process is applied to the target after the first limiting process to ensure that the deviation of the final issued real-time power command from the planned power value does not exceed the allowable adjustment range at the current moment.

[0113] In this scenario, the coordinated dispatch controller ultimately issues a constrained real-time power command to the energy storage unit, lower than the originally planned charging power. This causes the energy storage unit to adjust from its planned higher charging state to a lower charging state, thereby releasing some regulation capacity to compensate for the power deficit caused by the decrease in photovoltaic output. Simultaneously, the cold source continues to operate according to the power plan in the first control plan. Thus, without compromising the overall economic goals of low-cost charging at midday and cold energy transfer, real-time response to power fluctuations on the common bus is achieved.

[0114] Example 3

[0115] This embodiment illustrates the specific application of the proposed solution in a data industry park, with the optimization objective of minimizing the peak power drawn from the power grid by the park.

[0116] In a specific application scenario, the park's public bus is a 10kV distribution bus, and the park's load includes server rack load, cooling station load, lighting load, and auxiliary power load. The park's monthly electricity demand is relatively high, so the collaborative dispatch controller sets minimizing the peak power taken from the grid by the park as the optimization objective, and generates a first control plan based on the park's comprehensive electricity load forecast, cooling load forecast, photovoltaic output forecast, and energy storage status information for the next day.

[0117] In this first control plan, to reduce the power consumption from the grid during the afternoon peak hours, the operating power of the cooling source is planned as follows: from 01:00 to 06:00, the chiller units operate at higher power and store cold energy in the cold storage unit; from 13:00 to 17:00, the chiller units reduce their operating power, and the cold storage unit takes over most of the cooling load of the park. Correspondingly, the planned power support curve of the energy storage unit is set as follows: from 13:00 to 17:00, the energy storage unit maintains a higher planned discharge power to directly reduce the peak power consumption of the park from the public grid.

[0118] Taking 15:00 as an example, the first control plan stipulates that the energy storage unit is in a planned discharge state, and the planned discharge power at this time is already close to its rated maximum discharge power. The collaborative dispatch controller determines the dynamic power regulation margin for the current time based on the current planned discharge level and the rated maximum charge / discharge capacity of the energy storage unit. Since the energy storage unit is already in a high discharge state at this time, its room for further increasing discharge is small, while the adjustment space for reducing discharge or switching to charging is relatively large. To ensure that regardless of the direction of real-time power changes in the system, the actual power deviation of the energy storage unit will not disrupt the peak shaving plan, the collaborative dispatch controller uses the stricter of these constraints as the allowable deviation range for the current time.

[0119] If, at any given moment, the computational load within the park experiences a brief decrease, and the actual photovoltaic output exceeds the predicted value, resulting in a real-time power surplus on the common bus, the collaborative scheduling controller, based on the current planned discharge power and this real-time power surplus, determines the initial real-time power target for the energy storage unit. Subsequently, the collaborative scheduling controller first performs a first limiting process on the initial real-time power target based on the rated maximum discharge power and the rated maximum charging power, and then performs a second limiting process based on the current dynamic power adjustment margin, resulting in a constrained real-time power command.

[0120] In this scenario, the coordinated dispatch controller issues a real-time power command to the energy storage unit, which is lower than the originally planned discharge power but still maintains a discharge state. This allows the energy storage unit to respond to the system's real-time power surplus while maintaining a high level of discharge, thus continuing to meet the peak shaving target. At the same time, the cold source continues to operate according to the low-power plan in the first control plan, and the cold storage unit continues to release cold energy to bear the park's cooling load.

[0121] If a larger real-time power surplus occurs at another time, the coordinated dispatch controller only allows the energy storage units to adjust their output within the range permitted by the dynamic power regulation margin, and does not allow them to deviate too much from the original planned discharge level, in order to maintain the priority of peak shaving control. In this way, the park can maintain a lower peak power intake from the grid during the afternoon peak period.

[0122] Example 4

[0123] This embodiment illustrates a specific application scenario where the energy supply system is a data industry park energy supply system, the power network is a park public bus, and the status information includes renewable energy power generation device output forecasts and park load forecasts.

[0124] In a specific application scenario, a 10kV public busbar is installed within the data industry park. The park's rooftop distributed photovoltaic power generation system, energy storage units, cooling station system, and loads from multiple data center buildings are all connected to this public busbar. The distributed photovoltaic power generation system has an installed capacity of 2MWp; the energy storage units are battery energy storage systems with a rated power of 500kW and a rated capacity of 1MWh; and the cooling station system includes electric chillers and ice storage units. The park's main loads include server loads, precision air conditioning loads, lighting loads, and power loads.

[0125] The collaborative dispatch controller obtains and updates the following status information through the park monitoring system: voltage, frequency, real-time active power and reactive power of the park's public bus; current charging and discharging power, state of charge, rated maximum discharge power, rated maximum charging power and health status information of the energy storage units; start-up and shutdown status of the cold source, real-time operating power, remaining cold storage capacity of the cold storage unit and cold load demand information; photovoltaic output forecast curve for the next 24 hours; comprehensive electricity load forecast curve for the park for the next 24 hours; and cold load forecast curve for the park for the next 24 hours.

[0126] For example, at 09:00 on a certain operating day, the coordinated dispatch controller receives the following forecast information: photovoltaic output will be high from 11:00 to 14:00, and the overall electricity load and cooling load of the park will also be at a high level. Based on the above status information, the coordinated dispatch controller generates a first control plan, determining that during the period from 11:00 to 14:00, the higher photovoltaic output will be used to schedule the energy storage unit for planned charging, and the operating power of the cold source will be appropriately increased to meet the real-time cooling load and supplement the cooling capacity of the cold storage unit; during the period from 18:00 to 21:00, the power purchased by the grid side will be reduced through planned discharge of the energy storage and release of cold from the cold storage unit.

[0127] Taking 11:30 as an example, if the first control plan determines that the cold source will remain in normal operation and the energy storage unit will be in the planned charging state, then the coordinated dispatch controller will determine the dynamic power regulation margin for the current time based on the planned charging power at that time and the rated maximum charging and discharging capacity of the energy storage unit. This dynamic power regulation margin is used to characterize the maximum range by which the energy storage unit is allowed to deviate from the planned value without disrupting the current planned charging schedule.

[0128] If cloud cover at 11:30 causes the actual photovoltaic output to be lower than the predicted value, resulting in a real-time power deficit, the coordinated scheduling controller determines the initial real-time power target of the energy storage unit based on the planned charging status and the real-time power deficit at that time. Then, based on the rated maximum discharge power and rated maximum charging power of the energy storage unit, the initial real-time power target is subjected to a first limiting process. Finally, based on the dynamic power adjustment margin at the current time, the target after the first limiting process is subjected to a second limiting process to obtain the final constrained real-time power command.

[0129] In this scenario, the coordinated dispatch controller issues a real-time power command to the energy storage unit, lower than the originally planned charging power, so that it reduces its charging power while still charging to offset the bus power deficit caused by the decline in photovoltaic power. At the same time, the cold source continues to operate according to the first control plan, and the cold storage unit stores cold according to the plan. Thus, a dual-storage coordinated energy supply control based on renewable energy forecasting and park load forecasting is realized in the park's public bus scenario.

[0130] Example 5

[0131] This embodiment illustrates the linkage protection method between the system and the uninterruptible power supply or static switching switch when the real-time power deviation exceeds the dynamic power adjustment margin.

[0132] In a specific application scenario, an uninterruptible power supply (UPS) and a static transfer switch are installed between the campus public bus and critical IT loads. The critical IT loads include data center server clusters, core switching equipment, and storage devices. The UPS provides millisecond-level power support to the critical IT loads in the event of a significant transient power shortage or short-term anomaly on the main power supply side. The static transfer switch quickly switches the critical IT loads to a backup power supply path under predetermined abnormal conditions. The coordinated dispatch controller is communicatively connected to the energy storage unit, the UPS, and the static transfer switch.

[0133] Under normal operating conditions, the coordinated dispatch controller controls the operation of the cold source according to the first control plan and allocates constrained real-time power commands to the energy storage unit based on the real-time power deviation and dynamic power adjustment margin. For example, at a certain moment, the first control plan stipulates that the energy storage unit is in a planned discharge state, and the current planned discharge power is at a moderately high level. The coordinated dispatch controller determines the dynamic power adjustment margin at the current moment based on the current planned power value and the rated maximum charge and discharge capacity of the energy storage unit.

[0134] If a set of high-power cooling auxiliary equipment in the park suddenly starts, causing a significant real-time power deficit on the common bus, but this deficit is still within the allowable range of the current dynamic power regulation margin, the coordinated dispatch controller first determines the initial real-time power target of the energy storage unit based on the planned discharge power and this real-time power deficit; then, it performs a first limiting process based on the rated maximum discharge power and rated maximum charging power of the energy storage unit; subsequently, it performs a second limiting process based on the current dynamic power regulation margin, obtaining the final constrained real-time power command. In this case, the energy storage unit can independently provide real-time power support, therefore the coordinated dispatch controller does not need to trigger the uninterruptible power supply or static switching switch.

[0135] In another abnormal operating condition, if the park's public bus experiences a larger instantaneous power deficit due to external power supply fluctuations and the simultaneous startup of large-capacity loads, and this real-time power deficit exceeds the current dynamic power regulation margin, the coordinated dispatch controller will still first allocate constrained real-time power commands to the energy storage units in the manner described above, allowing the energy storage units to provide as much power support as possible within their allowable deviation range. Simultaneously, the coordinated dispatch controller sends a trigger signal to the uninterruptible power supply (UPS), which provides instantaneous support for the remaining power difference to the critical IT loads; or, it sends an action signal to the static switching switch, causing the static switching switch to switch the critical IT loads to the backup power supply path within milliseconds to maintain continuous power supply to the critical IT loads. After the public bus power stabilizes, the coordinated dispatch controller system returns to its normal dual-storage coordinated control operation state according to the first control plan and dynamic power regulation margin.

[0136] In this way, the system forms a layered protection mechanism in which the energy storage unit undertakes normal flexible regulation, and the uninterruptible power supply or static switching device undertakes rigid protection of critical loads under abnormal operating conditions. Without disrupting the planned operation objectives of the upper level, it improves the power supply continuity of critical IT loads and the overall stability of the park's energy supply system.

[0137] For any parts not mentioned in this application, existing technologies may be used or referenced.

[0138] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0139] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A dual-storage collaborative energy supply system for a data industrial park, characterized in that, include: Cooperative scheduling controller, the cooperative scheduling controller being used for: The status information of the energy supply system is obtained, the energy supply system including a power network, an electric energy storage unit connected to the power network, and a cold storage unit connected to the power network and providing cold energy through a cold source; Based on the status information, a first control plan is generated with a preset optimization objective. The first control plan includes at least the operating power plan of the cold source. Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power adjustment margin. Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin. The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

2. The energy supply system collaborative control system according to claim 1, characterized in that, Based on the state information, a first control plan is generated with a preset optimization objective. The first control plan includes at least the operating power plan of the cold source, with the optimization objective being to minimize the system operating cost or peak power. The first control plan includes the power reference curve of the cold source and the planned power support curve of the energy storage unit.

3. The energy supply system collaborative control system according to claim 2, characterized in that, The dynamic power regulation margin is calculated as follows: β(t) = min{ P_max - P_plan(t), P_plan(t) - P_min}, where P_max is the rated maximum discharge power of the energy storage unit, P_min is its rated maximum charging power, and P_plan(t) is the planned power support curve value of the energy storage unit at time t. Discharge power is defined as positive, and charging power is defined as negative.

4. The energy supply system collaborative control system according to claim 3, characterized in that, The step of allocating a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power regulation margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin, includes: Based on the planned power value of the energy storage unit at the current moment and the real-time power deviation, the initial real-time power target of the energy storage unit is determined. Based on the rated maximum discharge power and rated maximum charging power of the energy storage unit, the initial real-time power target is subjected to a first limiting process to obtain an intermediate power value; Based on the dynamic power adjustment margin, the intermediate power value is subjected to a second limiting process to obtain the constrained real-time power command, so that the deviation of the constrained real-time power command from the planned power value does not exceed the dynamic power adjustment margin.

5. The energy supply system coordinated control system according to any one of claims 1-4, characterized in that, The energy supply system is the energy supply system of the data industry park, the power network is the park's public bus, and the status information includes the output forecast of renewable energy power generation devices connected to the park's public bus and the park's load forecast.

6. The energy supply system collaborative control system according to claim 5, characterized in that, The system also includes an uninterruptible power supply (UPS) or static switching switch connected between the campus public bus and the critical IT load. The collaborative scheduling controller is further configured to: allocate a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power adjustment margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power adjustment margin; when the absolute value of the real-time power deviation exceeds the dynamic power adjustment margin, trigger the UPS or static switching switch to provide millisecond-level power support to maintain the continuous power supply to the critical IT load.

7. A method for the coordinated operation of dual energy storage in a data industrial park, applied to the system described in any one of claims 1-6, characterized in that, The method is executed by the cooperative scheduling controller and includes the following steps: Based on the status information of the energy supply system, a first control plan is generated with a preset optimization target. The first control plan includes at least the operating power plan of the cold source. Based on the first control plan and the power capability of the energy storage unit, the range of adjustment capability that the energy storage unit can use to respond to real-time power changes under the constraints of the first control plan is determined. The range of adjustment capability is characterized as a time-varying dynamic power adjustment margin. Based on the real-time power deviation of the power supply system and the dynamic power regulation margin, a constrained real-time power command is assigned to the energy storage unit, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin. The cold source is controlled to operate according to the first control plan, and the electrical energy storage unit is controlled according to the constrained real-time power command.

8. The method according to claim 7, characterized in that, The dynamic power regulation margin is calculated as follows: β(t) = min{ P_max - P_plan(t), P_plan(t) - P_min}, where P_max is the rated maximum discharge power of the energy storage unit, P_min is its rated maximum charging power, and P_plan(t) is the planned power value of the energy storage unit in the first control plan at time t.

9. The method according to claim 8, characterized in that, The step of allocating a constrained real-time power command to the energy storage unit based on the real-time power deviation of the power supply system and the dynamic power regulation margin, such that the deviation of the real-time power command of the energy storage unit does not exceed the dynamic power regulation margin, includes: Based on the planned power value of the energy storage unit at the current moment and the real-time power deviation, the initial real-time power target of the energy storage unit is determined. Based on the rated maximum discharge power and rated maximum charging power of the energy storage unit, the initial real-time power target is subjected to a first limiting process to obtain an intermediate power value; Based on the dynamic power adjustment margin, the intermediate power value is subjected to a second limiting process to obtain the constrained real-time power command, so that the deviation of the constrained real-time power command from the planned power value does not exceed the dynamic power adjustment margin.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method as described in any one of claims 7-9.

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