IDC power utilization guarantee method and system

Abstract

The invention provides an IDC power utilization guarantee method and system, and relates to the technical field of electric power systems.A lithium battery energy storage system is built into an independent voltage source to be connected with a target power grid in parallel, and power utilization strategy analysis is conducted on IDC load requirements, electricity price information of the target power grid and characteristic information of the lithium battery energy storage system; and analyzing the power grid operation data set, the IDC load data set and the energy storage system operation data set based on the IDC power utilization strategy to obtain IDC power utilization strategy parameters to carry out IDC power utilization guarantee monitoring, and carrying out dynamic feedback adjustment. The technical problems that in the prior art, an electricity utilization strategy is not flexible, and real-time monitoring and dynamic adjustment are lacked, so that IDC electricity utilization guarantee efficiency is low, and safety is low are solved. The technical effect of double guarantee of power utilization efficiency optimization and power supply safety of the data center is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and particularly to a method and system for ensuring power supply for IDC. Background Art

[0002] With the rapid development of technologies such as cloud computing, big data, and artificial intelligence, Internet Data Centers (IDCs) have become important infrastructure for supporting the digital economy. The operation of IDCs highly depends on the power system. It has a large power consumption load and high continuity requirements. Once the power supply is interrupted or the power quality fluctuates, it will directly affect the operation stability of server equipment, and even cause serious business interruptions and economic losses.

[0003] The power supply systems of traditional IDCs usually rely on the combination of the power grid and lead-acid batteries or cold standby diesel generators to achieve main and standby power supplies. Although such solutions can ensure power supply continuity to a certain extent, they have limitations in many aspects during actual operation: First, they cannot flexibly cope with scenarios such as electricity price fluctuations and peak electricity consumption, resulting in a continuous increase in operating costs; second, they lack real-time load perception and energy dynamic allocation capabilities, and it is difficult to meet modern power supply requirements such as high-frequency load fluctuations, rapid regulation, and participation in power grid frequency modulation; moreover, traditional standby power sources such as diesel generators have problems such as slow start-up response, high operating noise, and serious environmental pollution, which do not conform to the development direction of green and low-carbon; while lead-acid batteries have defects such as low energy density, short service life, and high maintenance costs, and it has gradually become difficult to meet the high reliability and intelligent requirements of the new generation of IDCs.

[0004] There are technical problems in the prior art that the power consumption strategy is not flexible, and there is a lack of real-time monitoring and dynamic regulation, resulting in low efficiency and low safety in ensuring power supply for IDC. Summary of the Invention

[0005] This application provides a method and system for ensuring power supply for IDC, which is used to solve the technical problems in the prior art that the power consumption strategy is not flexible, and there is a lack of real-time monitoring and dynamic regulation, resulting in low efficiency and low safety in ensuring power supply for IDC.

[0006] In view of the above problems, this application provides a method and system for ensuring power supply for IDC.

[0007] In the first aspect of the present application, a method for ensuring power supply for an IDC is provided. The method includes: designing a lithium battery energy storage system, building the lithium battery energy storage system into an independent voltage source, and connecting the independent voltage source in parallel with the target power grid; obtaining the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system; performing an electricity consumption strategy analysis on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the IDC electricity consumption strategy, where the IDC electricity consumption strategy includes a charge-discharge strategy, a frequency modulation strategy, and a voltage sag response strategy; monitoring and obtaining the power grid operation data set, the IDC load data set, and the energy storage system operation data set in real time, analyzing the power grid operation data set, the IDC load data set, and the energy storage system operation data set based on the IDC electricity consumption strategy to obtain the IDC electricity consumption strategy parameters; performing IDC power supply guarantee monitoring based on the IDC electricity consumption strategy parameters, and dynamically feedback-adjusting the IDC electricity consumption strategy parameters according to the electricity consumption monitoring data.

[0008] In the second aspect of the present application, an IDC power supply guarantee system is provided. The system includes: an energy storage system design module for designing a lithium battery energy storage system, building the lithium battery energy storage system into an independent voltage source, and connecting the independent voltage source in parallel with the target power grid; a data acquisition module for obtaining the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system; an electricity consumption strategy analysis module for performing an electricity consumption strategy analysis on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the IDC electricity consumption strategy, where the IDC electricity consumption strategy includes a charge-discharge strategy, a frequency modulation strategy, and a voltage sag response strategy; a data analysis module for monitoring and obtaining the power grid operation data set, the IDC load data set, and the energy storage system operation data set in real time, analyzing the power grid operation data set, the IDC load data set, and the energy storage system operation data set based on the IDC electricity consumption strategy to obtain the IDC electricity consumption strategy parameters; an electricity consumption monitoring module for performing IDC power supply guarantee monitoring based on the IDC electricity consumption strategy parameters, and dynamically feedback-adjusting the IDC electricity consumption strategy parameters according to the electricity consumption monitoring data.

[0009] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0010] By designing a lithium battery energy storage system, the lithium battery energy storage system is built into an independent voltage source, and the independent voltage source is connected in parallel with the target power grid. Obtain the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system, conduct an electricity consumption strategy analysis on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system, and determine the IDC electricity consumption strategy. The IDC electricity consumption strategy includes charge and discharge strategies, frequency modulation strategies, and voltage sag response strategies. Real-time monitor and obtain the power grid operation data set, the IDC load data set, and the energy storage system operation data set. Analyze the power grid operation data set, the IDC load data set, and the energy storage system operation data set based on the IDC electricity consumption strategy to obtain IDC electricity consumption strategy parameters. Conduct IDC electricity consumption guarantee monitoring based on the IDC electricity consumption strategy parameters, and perform dynamic feedback adjustment on the IDC electricity consumption strategy parameters according to the electricity consumption monitoring data. It achieves the technical effects of improving the intelligent level of the electricity consumption strategy, enhancing the stability of system operation, realizing the optimization of electricity consumption efficiency, and providing dual guarantees for the power supply security of the data center. Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0012] Figure 1 Schematic flowchart of an IDC power consumption guarantee method provided by this application;

[0013] Figure 2 Schematic structural diagram of an IDC power consumption guarantee system provided by this application.

[0014] Description of the reference numerals: Energy storage system design module 11, data acquisition module 12, electricity consumption strategy analysis module 13, data analysis module 14, electricity consumption monitoring module 15. Detailed Embodiments

[0015] This application provides an IDC power consumption guarantee method and system, which are used to solve the technical problems in the prior art, such as inflexible electricity consumption strategies, lack of real-time monitoring and dynamic adjustment, resulting in low IDC power consumption guarantee efficiency and low security. It achieves the technical effects of improving the intelligent level of the electricity consumption strategy, enhancing the stability of system operation, realizing the optimization of electricity consumption efficiency, and providing dual guarantees for the power supply security of the data center.

[0016] Next, the technical solutions in the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited by the exemplary embodiments described herein. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention. Additionally, it should be noted that for the convenience of description, only the parts related to the present invention are shown in the drawings rather than all of them.

[0017] Embodiment 1, as Figure 1 shown, the present application provides a method for ensuring power supply for IDC, and the method includes:

[0018] Design a lithium battery energy storage system, build the lithium battery energy storage system into an independent voltage source, and connect the independent voltage source in parallel with the target power grid.

[0019] Furthermore, the design of the lithium battery energy storage system includes: selecting lithium battery materials and planning battery packs based on the IDC load demand and backup duration to obtain lithium battery material information and battery pack arrangement parameters; designing the energy storage system according to the lithium battery material information and battery pack arrangement parameters to determine the energy storage system design parameters; performing monitoring coverage analysis on each battery cell in the energy storage system design parameters to obtain an energy storage system monitoring network; configuring the energy storage system based on the energy storage system design parameters and the energy storage system monitoring network to obtain the lithium battery energy storage system.

[0020] Specifically, an IDC (Internet Data Center) is a physical facility dedicated to providing network resource hosting, data storage, and computing services, and it belongs to a high-energy-consuming electrical load. To ensure power supply in the IDC scenario, a lithium battery energy storage system is first designed, and based on the IDC load requirements and backup power duration, a preliminary plan for the energy storage system is made. The IDC load requirements refer to the power requirements of the data center at different time periods, which directly determine the capacity requirements of the energy storage system and the response mechanism of the power supply strategy, including the daily power consumption scale of the target IDC, the power requirements of critical loads, etc. The daily power consumption scale refers to the total amount of electricity required for the IDC under normal operation, including the power consumption requirements of servers, network devices, cooling systems, lighting, office equipment, etc. The power requirements of critical loads refer to the power requirements of equipment or systems that need to be prioritized for power supply in case of emergencies such as power outages, such as servers, storage devices, network core devices, etc. Historical power consumption data is obtained from the IDC's electricity meter records, including daily, monthly, and annual power consumption, peak power, average power, etc. By analyzing the historical power consumption data, the daily power consumption scale and load fluctuation patterns are obtained. The power of the main equipment in the IDC is measured or the technical specification sheets of the equipment are consulted to obtain the rated power of each equipment. According to the actual operating conditions and load rates of the equipment, the actual power consumption of the equipment is calculated to obtain the power requirements of critical loads. The backup power duration refers to the minimum duration required to maintain operation in case of emergencies such as power outages, and it is determined according to the business requirements and operation strategies of the IDC. For example, a large IDC may require stable operation for more than 2 hours after the mains power outage. By analyzing the load requirements and backup power duration, the required battery capacity and type are obtained, and a suitable lithium battery material type and battery pack plan are selected to obtain lithium battery material information. For example, lithium battery material types include lithium iron phosphate, ternary lithium, etc. The material information of the lithium battery includes the chemical composition and energy density of the battery cells, etc. The battery pack planning and configuration scheme includes the capacity of a single battery cell, the number of battery cells, the series-parallel connection method of the battery pack, etc. Series connection determines the output voltage, and parallel connection determines the output current and total capacity, forming detailed battery pack arrangement parameters.

[0021] Based on the material properties and arrangement structure, a comprehensive energy storage system design is carried out, and specific energy storage system design parameters are output, including the configuration of the battery management system (BMS), the design of the thermal management system, the electrical connection scheme, and safety protection measures, etc. These design parameters ensure the efficient and stable operation of the energy storage system and can meet the actual application requirements of the IDC. After the design is completed, in order to ensure the reliability and safety of the energy storage system, a monitoring coverage analysis is carried out on each battery cell in the energy storage system design parameters, and a comprehensive and reliable energy storage system monitoring network is established. The monitoring coverage refers to the ability of the system to monitor core parameters such as temperature, voltage, current, and internal resistance for each battery cell or battery module. By real-time monitoring of key parameters such as the voltage, current, and temperature of the battery cells, potential faults or abnormal conditions can be detected and processed in a timely manner, ensuring the safety and stability of the lithium battery energy storage system during long-term operation. Furthermore, based on the determined energy storage system design parameters and the established energy storage system monitoring network, the actual configuration of the energy storage system is carried out to obtain a lithium battery energy storage system with high performance matching, strong safety, and comprehensive monitoring. And this lithium battery energy storage system is built into an independent voltage source, enabling the energy storage system to have the ability to stably output voltage independently, without relying on the voltage change of the power grid, ensuring that the energy storage system can independently supply power to the IDC in the case of power grid fluctuations or even interruptions. Subsequently, this independent voltage source is connected to the target power grid in parallel to achieve a dual-guarantee power supply structure of the main power grid and backup energy storage, improving the reliability of the lithium battery energy storage system, and thus ensuring the power continuity and data security of the IDC during power grid anomalies.

[0022] Obtain the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system.

[0023] Specifically, obtain the IDC load demand. The IDC load demand refers to the total amount of electricity required by the Internet data center during daily operation and emergency situations, which directly determines the capacity demand of the energy storage system and the response mechanism of the power supply strategy, and is one of the core bases for strategy formulation. The electricity price information refers to the power supply price structure in the area where the target IDC is located. Obtain the time-of-use electricity price policy from the local power company or electricity contract to master the electricity price difference for each hour segment. Also, comprehensively collect and obtain the characteristic information of the lithium battery energy storage system. The characteristic information of the energy storage system determines the power supply capacity boundary and the adaptation range of the regulation strategy of the system, including multiple aspects such as electrical characteristic parameters, cycle life and efficiency, thermal management and safety thresholds. By obtaining the IDC load demand, electricity price information, and the characteristic information of the lithium battery energy storage system, a comprehensive and multi-dimensional basis is provided for the determination of the electricity consumption strategy, ensuring that the subsequent electricity consumption strategy can not only meet the power demand of the IDC, but also be economically feasible, while maintaining an efficient and safe operating state.

[0024] Conduct power consumption strategy analysis on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the IDC power consumption strategy, where the IDC power consumption strategy includes charge-discharge strategies, frequency modulation strategies, and voltage sag response strategies.

[0025] Furthermore, the determination of the IDC power consumption strategy includes: constructing a load power consumption strategy library, which includes the power supply energy information of different loads and the corresponding power consumption strategy sets; traversing and matching in the load power consumption strategy library based on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the charge-discharge strategy, frequency modulation strategy, and voltage sag response strategy of the energy storage system; and forming the determined IDC power consumption strategy based on the charge-discharge strategy, frequency modulation strategy, and voltage sag response strategy of the energy storage system.

[0026] Specifically, classify the loads in the IDC to obtain the IDC load types, including server loads, cooling system loads, lighting loads, office equipment loads, etc. Each load type has its specific power consumption characteristics and requirements. Based on the load type and power supply energy information, obtain the corresponding power consumption strategy sets. Organize the collected load types, power supply energy information, and power consumption strategy sets into the form of a database or knowledge base to form a load power consumption strategy library. The load power consumption strategy library is a structured knowledge base for storing the power supply energy information of various different loads and the corresponding power consumption strategy sets. Conduct power consumption strategy analysis and matching based on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system. Input the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system into the load power consumption strategy library for traversing and matching to determine the charge-discharge strategy, frequency modulation strategy, and voltage sag response strategy of the energy storage system. The charge-discharge strategy, that is, when to charge to reserve electric energy and when to discharge to supply loads or assist the power grid, is used to improve energy utilization efficiency and reduce operating costs; the frequency modulation strategy, that is, how to adjust the output frequency of the energy storage system to stabilize the power grid voltage and frequency, is used to respond to power grid frequency fluctuations and maintain system stability; the voltage sag response strategy, that is, when the power grid voltage drops briefly, how the energy storage system quickly responds to ensure continuous power supply to the IDC. Integrate these three aspects of strategies, the charge-discharge strategy, frequency modulation strategy, and voltage sag response strategy of the energy storage system, to form a complete IDC power consumption strategy, ensuring that while the IDC meets the load demand, it can effectively utilize the electricity price difference to reduce costs and give full play to the advantages of the lithium battery energy storage system to improve the flexibility and reliability of energy use.

[0027] Further, the determination of the charge-discharge strategy of the energy storage system includes: taking the target power grid as the active power source and the lithium battery energy storage system as the backup power source to obtain a parallel power consumption strategy; based on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system, performing similarity matching with the load power consumption strategy library to determine the peak shaving and valley filling strategy and the demand response strategy; and obtaining the charge-discharge strategy based on the parallel power consumption strategy, the peak shaving and valley filling strategy, and the demand response strategy.

[0028] Specifically, the target power grid in the area where the IDC is located is set as the active power source, that is, the power grid is used as the main source of power supply for the IDC, responsible for meeting the basic and most of the power demands. The lithium battery energy storage system is set as the backup power source, which plays a role when the power grid supply is insufficient or during peak electricity price periods, and is used for specific strategy scenarios or emergency switching. Through this setting, the basic framework of the parallel power consumption strategy is formed. The parallel power consumption strategy means that the power grid and the energy storage system are connected in parallel in the architecture, and the power supply roles can be dynamically switched according to the strategy. That is, the power grid and the energy storage system work in parallel, complementing each other, supporting the automatic switching or coordinated power supply between the mains power and the energy storage, ensuring that the energy storage system can replenish energy immediately in case of peak electricity prices, abnormal voltages, or sudden power outages, achieving double guarantees of system reliability and flexibility, so as to improve the flexibility and economy of power supply.

[0029] Based on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system, these three types of information are input into the pre-constructed load power consumption strategy library for similarity matching analysis. The similarity matching analysis can use the rule matching method or the scoring algorithm based on index weights to compare the matching degrees of the load characteristics, electricity price patterns, and energy storage capabilities of the current scenario with the existing strategies in the strategy library, determine the strategy case most similar to the current situation, and determine the peak shaving and valley filling strategy and the demand response strategy. The peak shaving and valley filling strategy means using the energy storage system to charge during low electricity price periods and discharge during high electricity price periods to smooth the load fluctuations of the power grid and reduce the electricity cost. The demand response strategy is to flexibly adjust the electricity consumption behavior of the data center according to the power supply and demand situation of the power grid and the electricity price signal, such as reducing unnecessary loads during peak electricity price periods to respond to the dispatching requirements of the power grid and improve the stability and efficiency of the power grid. Finally, based on the parallel power consumption strategy and the peak shaving and valley filling strategy and the demand response strategy determined by similarity matching, the charge-discharge strategy is obtained. The charge-discharge strategy is a specific operation plan generated after comprehensively considering the electricity price, load, and system capabilities, guiding when and how the energy storage system performs energy conversion. This strategy not only considers the parallel working mechanism of the power grid and the energy storage system, but also makes full use of the electricity price information, the characteristics of the energy storage system, and the load demand of the data center, realizing the economy, flexibility, and stability of power supply, and ensuring the power supply stability and data security of the IDC.

[0030] Real-time monitoring is used to obtain the power grid operation dataset, the IDC load dataset, and the energy storage system operation dataset. Based on the IDC power consumption strategy, the power grid operation dataset, the IDC load dataset, and the energy storage system operation dataset are analyzed to obtain the IDC power consumption strategy parameters.

[0031] Furthermore, obtaining the IDC power consumption strategy parameters includes: performing strategy analysis on the power grid operation dataset, the IDC load dataset, and the energy storage system operation dataset based on the IDC power consumption strategy to obtain the selection threshold of the power consumption strategy parameters; constructing a power consumption evaluation fitness function according to the IDC power consumption demand target; and using the power consumption evaluation fitness function to perform global optimization within the selection threshold of the power consumption strategy parameters to determine the IDC power consumption strategy parameters.

[0032] Specifically, through sensors such as voltage sensors, current sensors, power sensors, monitoring platforms, and communication interfaces, etc., the power grid operation dataset, the IDC load dataset, and the energy storage system operation dataset are obtained in real-time. The power grid operation dataset includes the real-time voltage, current, frequency, electricity price fluctuations, power supply stability, etc. of the power grid. The IDC load dataset reflects the load conditions of the data center at different time points, including the current total load power, the distribution of critical loads and non-critical loads, the load change trend, etc. The energy storage system operation dataset records key indicators such as the charge and discharge status, remaining capacity, charge and discharge efficiency, etc. of the energy storage system. Then, according to the IDC power consumption strategy including the charge and discharge strategy, the frequency modulation strategy, and the voltage sag response strategy, the power grid operation dataset, the IDC load dataset, and the energy storage system operation dataset are analyzed. For example, for the charge and discharge strategy, parameters such as the battery pack status and charge and discharge efficiency in the energy storage system operation dataset are analyzed, and combined with the electricity price information in the power grid operation dataset, the optimal charge and discharge timing and charge and discharge depth of the energy storage system are determined, thereby obtaining the selection threshold of the charge and discharge strategy parameters, such as the upper and lower limits of the state of charge of the battery pack. For the frequency modulation strategy, the frequency fluctuation situation in the power grid operation dataset is analyzed, and combined with the load change trend in the IDC load dataset, the future frequency demand is predicted. Based on the response speed and regulation ability of the energy storage system, the participation degree and regulation amount of the energy storage system in the frequency modulation process are determined, and the selection threshold of the frequency modulation strategy parameters is obtained, such as the response time and regulation power range of the energy storage system. For the voltage sag response strategy, the voltage sag events in the power grid operation dataset are analyzed, and combined with the distribution of sensitive devices in the IDC load dataset, the impact of voltage sags on IDC operation is evaluated. According to the fast response characteristics of the energy storage system, the compensation strategy and compensation amount of the energy storage system in the voltage sag event are determined, and the selection threshold of the voltage sag response strategy parameters is obtained, such as the response time, compensation voltage range, and compensation duration of the energy storage system. Through analysis, the selection threshold of the power consumption strategy parameters is obtained, and the selection threshold of the power consumption strategy parameters defines the reasonable value range of the power consumption strategy parameters.

[0033] Then, according to the IDC power demand target, a power consumption evaluation fitness function is constructed, and the power consumption evaluation fitness function is used to evaluate the pros and cons of the power consumption strategy parameters. For example, the power consumption evaluation fitness function comprehensively considers multiple factors such as the power consumption cost of the data center, the stability of the power grid, and the service life of the energy storage system to ensure that the selected power consumption strategy parameters can meet the power demand of the data center while taking into account the operating benefits of the power grid and the energy storage system. The power consumption evaluation fitness function F = w1×power consumption cost+w2×power supply stability score+w3×battery loss penalty term, where w1, w2, and w3 are weight coefficients, which are flexibly adjusted according to the focus of IDC operations. Finally, using the constructed power consumption evaluation fitness function, with the help of intelligent optimization algorithms such as genetic algorithms, particle swarm optimization, simulated annealing, etc., a global optimization is performed within the strategy parameter threshold range, and multiple candidate parameter combinations are randomly generated. Substitute them into the fitness function to calculate the score, and select the combination with the highest fitness (i.e., the best effect) as the final strategy parameter, i.e., the IDC power consumption strategy parameter. By analyzing and determining the IDC power consumption strategy parameters, we can not only ensure the scientificity and rationality of the IDC power consumption strategy, but also improve the energy utilization efficiency of the data center and reduce electricity costs. At the same time, we take into account the stability of the power grid and the service life of the energy storage system to achieve safe and stable operation of the data center.

[0034] Furthermore, the determination of the IDC power consumption strategy parameters includes: randomly selecting multiple power consumption strategy parameters within the power consumption strategy parameter selection threshold; performing fitness evaluation on the multiple power consumption strategy parameters using the power consumption evaluation fitness function to obtain multiple strategy parameter fitnesses; and performing global iterative optimization within the power consumption strategy parameter selection threshold based on the multiple strategy parameter fitnesses to determine the IDC power consumption strategy parameters.

[0035] Specifically, in the process of determining the IDC power consumption strategy parameters, first, within the selected threshold range of the power consumption strategy parameters that have been obtained, multiple power consumption strategy parameters are randomly selected as candidates. The power consumption strategy parameters specifically refer to the key variables that affect the effects of charge-discharge, frequency modulation, and voltage sag response strategies, such as the charge-discharge depth, response time, and regulation power range of the energy storage system. Using a pre-defined power consumption evaluation fitness function, the fitness evaluation of these randomly selected multiple power consumption strategy parameters is carried out. The fitness function is a standard for measuring the quality of the strategy parameters. By quantifying and scoring the strategy parameters, the fitness values of multiple strategy parameters are obtained. The higher the value, the better the overall effect of the strategy. Based on the fitness values of these strategy parameters, global iterative optimization is carried out within the selected threshold range of the power consumption strategy parameters. By continuously adjusting the strategy parameters, the fitness function is made to reach the maximum value or meet specific optimization objectives. The finally selected set of parameters is the optimal IDC power consumption strategy parameters under the current operating environment and strategy logic. These parameters will directly guide the formulation and implementation of the charge-discharge, frequency modulation, and voltage sag response strategies of the IDC, thereby improving the energy efficiency, economy, and stability of the IDC and ensuring the effectiveness and feasibility of the strategy.

[0036] Based on the IDC power consumption strategy parameters, IDC power consumption guarantee monitoring is carried out, and the IDC power consumption strategy parameters are dynamically feedback-adjusted according to the power consumption monitoring data.

[0037] Specifically, after determining the IDC power consumption strategy parameters, the IDC power consumption guarantee monitoring stage is entered. In this stage, according to the determined IDC power consumption strategy parameters, the IDC power consumption strategy is executed. During the execution process, the power consumption guarantee monitoring of the overall power consumption process is carried out. Through the deployed sensors and monitoring platform, key data such as the power grid status, IDC load changes, and energy storage system operation conditions are collected in real time. The monitoring content includes the power usage status of the IDC, including key electrical parameters such as current, voltage, and power factor, as well as the charge and discharge status of the energy storage system and the strategy execution effects such as frequency modulation response. During the monitoring process, power consumption monitoring data is continuously collected, and these data are used to reflect the execution effect of the IDC power consumption strategy. And the collected power consumption monitoring data is analyzed, comparing the actual execution effect with the strategy expectation to identify strategy deviations, such as whether there are problems such as insufficient discharge, electricity price response errors, or frequency modulation lags. Based on this deviation analysis, dynamic feedback regulation is triggered. Dynamic feedback regulation means that according to the real-time monitored data, the power consumption strategy parameters are adjusted in a timely manner to ensure that the IDC power consumption strategy can always adapt to the actual power consumption demand and environmental changes. For example, if it is found that the charge and discharge efficiency of the energy storage system is not high, we can adjust parameters such as the charge and discharge depth or response time to improve the utilization efficiency of the energy storage system. Through IDC power consumption guarantee monitoring and dynamic feedback regulation, it is possible to ensure that the IDC power consumption strategy always remains in an optimal state, timely respond to various power consumption situations and environmental changes, ensure stable power supply, reduce operation and maintenance costs, and extend the service life of energy storage equipment.

[0038] Further, the dynamic feedback regulation of the IDC power consumption strategy parameters according to the power consumption monitoring data includes: optimizing and analyzing the power consumption monitoring data to obtain the optimization direction of the strategy parameters; optimizing the IDC power consumption strategy parameters according to the optimization direction of the strategy parameters, and performing power consumption dynamic feedback regulation through the optimized IDC power consumption strategy parameters.

[0039] Specifically, based on the continuously collected power consumption monitoring data, optimize and analyze the power consumption strategy parameters currently being executed, that is, compare and evaluate the real-time or periodically collected data with the expected effects of the strategy, identify operation deviations and inefficient or abnormal performances in strategy execution, and then clarify the optimization direction of the strategy parameters. For example, when the monitoring data shows that the SOC of the energy storage system is frequently lower than the set threshold, or the electricity price during the charging period is higher than the expected low valley range, the system can judge that there is a mismatch in the current charge and discharge strategy parameters and needs to adjust the charging time window or the lowest SOC threshold; another example is that during frequent frequency modulation, the response time of the energy storage is relatively long, and it may be necessary to optimize the response trigger time or power configuration. After determining the optimization direction, make targeted adjustments to the corresponding IDC power consumption strategy parameters, that is, update parameters such as the upper limit of charge and discharge power, frequency modulation response rate, and voltage compensation duration according to the optimization direction to form a new strategy parameter configuration. Put the optimized strategy parameters into actual operation and continue to track the execution effect in real time through the monitoring mechanism, so as to build a data-driven dynamic feedback regulation closed loop for power consumption, ensure that the IDC power consumption strategy can respond to actual power consumption needs and environmental changes in real time, and achieve the dual guarantee of optimal power consumption efficiency and power supply security of the data center.

[0040] In summary, the IDC power consumption guarantee method provided by the embodiments of the present application has the following technical effects:

[0041] 1. The lithium battery energy storage system is built into an independent voltage source and is connected in parallel with the power grid, which can independently supply power to the IDC, ensure the power supply safety of the IDC, and can also avoid problems such as data damage and data loss caused by unstable power supply networks due to voltage sags and excessive frequency fluctuations.

[0042] 2. The IDC is a high-energy-consuming power consumption load. Adopting a new model architecture to obtain the IDC power consumption strategy can reduce the power consumption cost and achieve the dual guarantee of optimal power consumption efficiency and power supply security of the data center.

[0043] 3. By designing a lithium battery energy storage system, it can replace lead-acid backup power and can also replace diesel generator emergency power supply, reduce carbon emissions during the operation of diesel generators, reduce noise pollution, reduce secondary investment in large diesel generators, save investment costs, and can also conduct peak-valley arbitrage to achieve the purpose of increasing efficiency.

[0044] 4. By constructing an intelligent feedback mechanism from strategy execution to dynamic optimization, it can ensure that the IDC power consumption strategy can continuously adapt to changes in the power grid environment, load fluctuations, and the aging trend of the energy storage system, making the IDC power consumption strategy more flexible and efficient in adapting to various situations, thereby improving power consumption efficiency, reducing operating costs, and ensuring the stable operation of the IDC.

[0045] Embodiment 2, based on the same inventive concept as an IDC power consumption guarantee method in the foregoing embodiment, such asFigure 2 As shown, the present application provides an IDC power supply guarantee system, where the system includes:

[0046] A energy storage system design module 11, which is used to design a lithium battery energy storage system, build the lithium battery energy storage system into an independent voltage source, and the independent voltage source is connected in parallel with the target power grid; a data acquisition module 12, which is used to acquire the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system; a power consumption strategy analysis module 13, which is used to perform power consumption strategy analysis on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the IDC power consumption strategy, and the IDC power consumption strategy includes charge and discharge strategies, frequency modulation strategies, and voltage sag response strategies; a data analysis module 14, which monitors and acquires the power grid operation data set, the IDC load data set, and the energy storage system operation data set in real time, and analyzes the power grid operation data set, the IDC load data set, and the energy storage system operation data set based on the IDC power consumption strategy to obtain IDC power consumption strategy parameters; a power consumption monitoring module 15, which is used to perform IDC power supply guarantee monitoring based on the IDC power consumption strategy parameters, and perform dynamic feedback adjustment on the IDC power consumption strategy parameters according to the power consumption monitoring data.

[0047] Further, the energy storage system design module 11 is also used to perform the following steps: select lithium battery materials and plan the battery pack based on the IDC load demand and the backup power duration to obtain lithium battery material information and battery pack arrangement parameters; design the energy storage system according to the lithium battery material information and the battery pack arrangement parameters to determine the energy storage system design parameters; perform monitoring coverage analysis on each battery cell in the energy storage system design parameters to obtain an energy storage system monitoring network; configure the energy storage system based on the energy storage system design parameters and the energy storage system monitoring network to obtain the lithium battery energy storage system.

[0048] Further, the power consumption strategy analysis module 13 is also used to perform the following steps: construct a load power consumption strategy library, and the load power consumption strategy library includes the power supply energy information of different loads and the corresponding power consumption strategy sets; traverse and match in the load power consumption strategy library based on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the charge and discharge strategies, frequency modulation strategies, and voltage sag response strategies of the energy storage system; based on the charge and discharge strategies, frequency modulation strategies, and voltage sag response strategies of the energy storage system, form and determine the IDC power consumption strategy.

[0049] Further, the power consumption strategy analysis module 13 is further configured to perform the following steps: taking the target power grid as the active power source and the lithium battery energy storage system as the standby power source to obtain a parallel power consumption strategy; based on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system, performing similarity matching with the load power consumption strategy library to determine the peak shaving and valley filling strategy and the demand response strategy; and obtaining the charge and discharge strategy based on the parallel power consumption strategy and the peak shaving and valley filling strategy and the demand response strategy.

[0050] Further, the data analysis module 14 is further configured to perform the following steps: performing strategy analysis on the power grid operation data set, the IDC load data set, and the energy storage system operation data set based on the IDC power consumption strategy to obtain the threshold for selecting power consumption strategy parameters; constructing a power consumption evaluation fitness function according to the IDC power consumption demand target; and performing global optimization within the threshold for selecting power consumption strategy parameters by using the power consumption evaluation fitness function to determine the IDC power consumption strategy parameters.

[0051] Further, the data analysis module 14 is further configured to perform the following steps: randomly selecting multiple power consumption strategy parameters within the threshold for selecting power consumption strategy parameters; performing fitness evaluation on the multiple power consumption strategy parameters by using the power consumption evaluation fitness function to obtain the fitness of multiple strategy parameters; and performing global iterative optimization within the threshold for selecting power consumption strategy parameters based on the fitness of multiple strategy parameters to determine the IDC power consumption strategy parameters.

[0052] Further, the power consumption monitoring module 15 is further configured to perform the following steps: performing optimized analysis on the power consumption monitoring data to obtain the optimization direction of the strategy parameters; optimizing the IDC power consumption strategy parameters according to the optimization direction of the strategy parameters, and performing power consumption dynamic feedback regulation by using the optimized IDC power consumption strategy parameters.

[0053] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0054] This specification and the drawings are only exemplary descriptions of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and deformations to the present application without departing from the scope of the present application. Thus, if these modifications and deformations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and deformations.

Claims

1. An IDC power supply guarantee method, characterized in that, The method includes: Design a lithium battery energy storage system, build the lithium battery energy storage system into an independent voltage source, and connect the independent voltage source in parallel with the target power grid; Obtain the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system; Conduct an electricity consumption strategy analysis on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the IDC electricity consumption strategy, where the IDC electricity consumption strategy includes charge and discharge strategies, frequency modulation strategies, and voltage sag response strategies; Real-time monitor and obtain the power grid operation data set, the IDC load data set, and the energy storage system operation data set, and analyze the power grid operation data set, the IDC load data set, and the energy storage system operation data set based on the IDC electricity consumption strategy to obtain the IDC electricity consumption strategy parameters; Conduct IDC power consumption guarantee monitoring based on the IDC electricity consumption strategy parameters, and perform dynamic feedback adjustment on the IDC electricity consumption strategy parameters according to the power consumption monitoring data.

2. The IDC power supply guarantee method according to claim 1, wherein The design of the lithium battery energy storage system includes: Select lithium battery materials and plan the battery pack based on the IDC load demand and the backup power duration to obtain lithium battery material information and battery pack arrangement parameters; Design the energy storage system according to the lithium battery material information and the battery pack arrangement parameters to determine the energy storage system design parameters; Conduct a monitoring coverage analysis on each battery cell in the energy storage system design parameters to obtain the energy storage system monitoring network; Configure the energy storage system based on the energy storage system design parameters and the energy storage system monitoring network to obtain the lithium battery energy storage system.

3. The IDC power supply guarantee method according to claim 1, characterized in that, The determination of the IDC electricity consumption strategy includes: Construct a load electricity consumption strategy library, where the load electricity consumption strategy library includes the power supply energy information of different loads and the corresponding electricity consumption strategy sets; Traverse and match in the load electricity consumption strategy library based on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the charge and discharge strategy, frequency modulation strategy, and voltage sag response strategy of the energy storage system; Based on the charge and discharge strategy, frequency modulation strategy, and voltage sag response strategy of the energy storage system, form and determine the IDC electricity consumption strategy.

4. The IDC power supply guarantee method according to claim 3, characterized in that, The determination of the charge and discharge strategy of the energy storage system includes: Take the target power grid as the active power source and the lithium battery energy storage system as the backup power source to obtain a parallel electricity consumption strategy; Based on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system, perform a similarity match with the load electricity consumption strategy library to determine the peak shaving and valley filling strategy and the demand side response strategy; Based on the parallel electricity consumption strategy and the peak shaving and valley filling strategy and the demand side response strategy, obtain the charge and discharge strategy.

5. The IDC power supply guarantee method according to claim 1, wherein The obtaining of the IDC electricity consumption strategy parameters includes: Conduct a strategy analysis on the power grid operation data set, the IDC load data set, and the energy storage system operation data set based on the IDC electricity consumption strategy to obtain the threshold for selecting the electricity consumption strategy parameters; Construct an electricity consumption evaluation fitness function according to the IDC electricity consumption demand target; Perform global optimization within the threshold for selecting the power consumption strategy parameters by using the power consumption evaluation fitness function to determine the IDC power consumption strategy parameters.

6. The IDC power supply guarantee method according to claim 5, characterized in that The determination of the IDC power consumption strategy parameters includes: Randomly select multiple power consumption strategy parameters within the threshold for selecting the power consumption strategy parameters; Use the power consumption evaluation fitness function to evaluate the fitness of the multiple power consumption strategy parameters to obtain the fitness of multiple strategy parameters; Based on the fitness of the multiple strategy parameters, perform global iterative optimization within the threshold for selecting the power consumption strategy parameters to determine the IDC power consumption strategy parameters.

7. The IDC power supply guarantee method according to claim 6, wherein The dynamic feedback adjustment of the IDC power consumption strategy parameters according to the power consumption monitoring data includes: Perform optimized analysis on the power consumption monitoring data to obtain the optimization direction of the strategy parameters; Optimize the IDC power consumption strategy parameters according to the optimization direction of the strategy parameters, and perform power consumption dynamic feedback adjustment through the optimized IDC power consumption strategy parameters.

8. An IDC power supply guarantee system, characterized in that, The steps for implementing the IDC power consumption guarantee method according to any one of claims 1 to 7 include: A energy storage system design module, which is used to design a lithium battery energy storage system, build the lithium battery energy storage system into an independent voltage source, and connect the independent voltage source in parallel with the target power grid; A data acquisition module, which is used to acquire the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system; A power consumption strategy analysis module, which is used to perform power consumption strategy analysis on the IDC load demand, the electricity price information of the target power grid, and the characteristic information of the lithium battery energy storage system to determine the IDC power consumption strategy, and the IDC power consumption strategy includes charge and discharge strategies, frequency modulation strategies, and voltage sag response strategies; A data analysis module, which monitors and acquires the power grid operation data set, the IDC load data set, and the energy storage system operation data set in real time, and analyzes the power grid operation data set, the IDC load data set, and the energy storage system operation data set based on the IDC power consumption strategy to obtain the IDC power consumption strategy parameters; A power consumption monitoring module, which is used to perform IDC power consumption guarantee monitoring based on the IDC power consumption strategy parameters, and perform dynamic feedback adjustment on the IDC power consumption strategy parameters according to the power consumption monitoring data.

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