A management method and system for base station energy storage equipment with adaptive output voltage
By constructing a voltage distribution balance model and multi-objective optimization function, the problem that the output voltage of the base station energy storage equipment cannot be adjusted adaptively is solved, and the stable operation of the equipment and energy consumption are achieved to ensure the power supply quality.
Patent Information
- Application Number
- CN202510560412.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-30
- Publication Date
- 2025-07-11
- Estimated Expiration
- 2045-04-30
AI Technical Summary
The output voltage of the existing base station energy storage equipment cannot be adaptively regulated according to the working conditions of the electrical equipment in the base station, resulting in low equipment working efficiency, possible damage and increased risk of communication interruption, and there is a large loss during the energy conversion process.
By obtaining the critical static weight and dynamic voltage requirement function of base station electrical equipment, a voltage distribution balance model is constructed, and the multi-objective optimization function is optimized to generate voltage regulation instructions to realize the time-sharing voltage regulation management of energy storage equipment.
Accurately adapt to the voltage requirements of different equipment, ensure stable operation of the equipment, reduce energy consumption, realize dynamic and flexible adjustment, and ensure stable and reliable power supply quality.
Smart Images

Figure CN120090213B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of equipment management, and is a method and system for managing a base station energy storage device with an adaptive output voltage. Background Art
[0002] With the rapid development of communication technology, the number of base stations is increasing continuously, putting forward higher requirements for the stability and reliability of base station power supply. In the base station power supply system, energy storage devices play a crucial role. When the mains power is interrupted or the voltage is unstable due to weather reasons, the energy storage devices can provide continuous power support for the base station. However, the output voltage of existing base station energy storage devices is often fixed and cannot be adaptively adjusted according to the actual power consumption requirements of the base station and the voltage conditions of the mains power. In some cases, the fixed output voltage may not meet the voltage requirements of different devices in the base station, resulting in low working efficiency or even damage to the devices; when the mains voltage fluctuates greatly, the energy storage device cannot adjust the output voltage in time, which may affect the normal operation of the base station and increase the risk of communication interruption. In addition, there may be relatively large losses in the energy conversion process of the energy storage device with a fixed output voltage, reducing the energy utilization efficiency. Summary of the Invention
[0003] The technical problem to be solved by the present invention is that in the prior art, the present invention solves the problem that the output voltage of the base station energy storage device in the prior art cannot be adaptively regulated according to the working conditions of the electrical equipment in the base station, and proposes a method and system for managing a base station energy storage device with an adaptive output voltage.
[0004] In order to achieve the above object, the technical solution of a method for managing a base station energy storage device with an adaptive output voltage according to the present invention includes the following steps:
[0005] S1: Obtain the criticality static weight of the base station electrical equipment according to the equipment attributes and historical voltage demand data of the base station electrical equipment;
[0006] S2: Obtain the dynamic voltage demand function curve of the base station electrical equipment, the energy consumption function curve of the base station power supply system, and the independent conversion loss function curve of the power supply source;
[0007] S3: According to S2, construct a voltage distribution balance model of the energy storage device, and at the same time obtain the safe voltage range of the base station electrical equipment as a constraint condition of the voltage distribution balance model;
[0008] S4: Optimize the voltage distribution balance model through a multi-objective optimization function to obtain an equilibrium distribution scheme;
[0009] S5: Input the balanced distribution plan into the energy storage device management model to generate a set of voltage regulation instructions, and complete the time-sharing voltage regulation management of the energy storage device according to the set of voltage regulation instructions.
[0010] Specifically, S1 includes:
[0011] S11: Obtain the attribute list of the base station power consumption equipment, and calculate the static weight of the criticality of the base station power consumption equipment according to the historical voltage demand data under different working modes of the base station power consumption equipment;
[0012] Preferably, the calculation strategy of the static weight of the criticality is specifically:
[0013] ;
[0014] Among them, is the static weight of the criticality; is the adaptive coefficient;
[0015] is the current harmonic distortion rate of the power consumption equipment;
[0016] is the heating rate inside the cabinet of the power consumption equipment; is the service priority;
[0017] are the real-time information throughput and the maximum information throughput of the power consumption equipment respectively;
[0018] S12: Based on the dynamic voltage demand curves corresponding to each power consumption equipment in the static weight of the criticality of the power consumption equipment, obtain the voltage sensitivity coefficient and the power consumption curve of the corresponding power consumption equipment.
[0019] Preferably, the calculation strategy of the voltage sensitivity coefficient of the power consumption equipment is:
[0020] ; Among them, is the voltage sensitivity coefficient of the power consumption equipment;
[0021] It should be noted that The power consumption curve corresponding to the power consumption equipment represents the power consumption of the power consumption equipment at different working voltages.
[0022] Specifically, S2 includes:
[0023] S21: Define the time window parameters of the target power supply of the energy storage device according to the communication guarantee level and the importance weight of the power consumption equipment ; Among them, represents the minimum guarantee start time of the critical power consumption equipment with the highest service priority, represents the longest switching delay of the energy storage device;
[0024] S22: Obtain the reference value of the dynamic voltage regulation rate according to the stable time window of the target power supply and the safe voltage range of the electrical equipment.
[0025] Preferably, the stable time window of the target power supply is specifically:
[0026] ; where is the stable time window of the target power supply;
[0027] Preferably, the calculation strategy of the reference value of the dynamic voltage regulation rate is:
[0028] ;
[0029] where is the reference value of the dynamic voltage regulation rate;
[0030] is the safe voltage range of the electrical equipment;
[0031] S23: Take the time derivative of the dynamic voltage demand function of the base station electrical equipment to obtain the instantaneous voltage demand gradient of each electrical equipment. Preset the instantaneous voltage demand fluctuation threshold, and screen the time points at which the instantaneous voltage demand gradient of each electrical equipment exceeds the instantaneous voltage demand fluctuation threshold as the voltage regulation trigger signal points.
[0032] Specifically, S2 further includes:
[0033] S24: Classify the historical cooperative voltage regulation strategies, voltage regulation margins and corresponding energy consumption characteristics of the mains power and energy storage devices through a clustering algorithm according to the historical cooperative voltage regulation strategies, voltage regulation margins and corresponding energy consumption characteristics of the mains power and energy storage devices to obtain several historical operation scenarios;
[0034] Assign initial voltage values to several historical operation scenarios and determine the initial power supply voltage value of the mains power supply;
[0035] Preferably, ;
[0036] is the initial power supply voltage value of the mains power supply;
[0037] where The power consumption of the mains power at voltage V. It should be noted that the higher the voltage, the greater the energy consumption;
[0038] is the current voltage and the deviation from the standard voltage It should be noted that the greater the deviation, the more unstable the power supply
[0039] Direction coefficient; if = 0, it means the power supply scheme pursues power saving; if is very large, it means the power supply scheme gives priority to ensuring power supply stability;
[0040] S25: Continuously monitor the dynamic voltage demand function of the base station power consumption equipment. When the voltage regulation trigger signal point is monitored, calculate the voltage regulation urgency through the fuzzy decision layer , and determine the initial power supply scheme through the average value of the voltage regulation urgency of the base station power consumption equipment;
[0041] When <0.3, only fine-tune the mains power through PID control and continue to execute step S26
[0042] When 0.3 ≤ <0.7, enable the pre-synchronization of the energy storage device and execute step S28 simultaneously;
[0043] When ≥ 0.7, force the collaborative voltage regulation mechanism of the mains power and the energy storage device and execute step S28 simultaneously;
[0044] Preferably, the calculation strategy of the voltage regulation urgency is:
[0045] ;
[0046] Where is the voltage regulation urgency of the i-th power consumption equipment;
[0047] is the deviation value between the power consumption demand and the actual power supply, is the baseline of the power consumption demand deviation;
[0048] Record the energy consumption evolution variables generated by the dynamic switching process and the independent conversion loss evolution variables of the power supply source, and update the energy consumption function curve of the base station power supply system and the independent conversion loss function curve of the power supply source.
[0049] Specifically, S2 further includes:
[0050] S26: Calculate the voltage regulation margin of the mains power based on the voltage demand change gradient and the dynamic voltage regulation rate reference value, and predict the voltage demand change amount of the base station power consumption equipment at the same time;
[0051] Select the depletion critical point according to the voltage regulation margin of the mains power and the prediction result of the voltage demand change amount;
[0052] Preferably, the calculation strategy of the voltage regulation margin is:
[0053] is the maximum adjustable voltage of the mains power;
[0054] is the output voltage of the current power supply;
[0055] Preferably, the voltage demand change of the base station electrical equipment is predicted specifically as:
[0056] ;
[0057] is the voltage demand change gradient of the base station electrical equipment; is the prediction time step;
[0058] Preferably, when it indicates that the critical point of the depletion of the mains power voltage regulation margin is reached;
[0059] S27: Trigger the energy storage device to enter the parallel power supply mode at the critical point of the depletion of the mains power voltage regulation margin, and establish a cooperative working mechanism between the mains power and the energy storage device;
[0060] S28: According to the static weight of the criticality of the base station electrical equipment, initially allocate the supply voltages of the mains power and the energy storage device under the cooperative working mechanism;
[0061] Preferably, the initial allocation of the supply voltage is specifically:
[0062] , ;
[0063] wherein, are respectively the initial supply voltages of the mains power and the energy storage device;
[0064] is the real-time demand voltage of the electrical equipment; is the total demand voltage of the base station electrical equipment;
[0065] S29: Construct a voltage distribution balance model for the energy storage device, specifically:
[0066] ;
[0067] wherein, is the voltage distribution balance;
[0068] is the nominal voltage of the electrical equipment; is the actual power of the power supply;
[0069] is the rated power of the base station power supply system; is the voltage matching balance weight.
[0070] It should be noted that is the voltage matching term; is the power consumption term of the power supply;
[0071] It should be noted that the voltage matching term is used to ensure that the actual voltage of each electrical device is as close as possible to its required voltage;
[0072] Specifically, in S4, the construction of the multi-objective optimization function is as follows: According to the voltage regulation efficiency, energy consumption cost, and weight distribution of the power supply priority of the mains power energy and energy storage devices, a multi-objective optimization function is constructed, and under the constraint conditions, Pareto solution selection is performed. The multi-objective optimization function is specifically:
[0073] ;
[0074] Among them, are the required voltage and nominal voltage of the electrical device respectively.
[0075] It should be noted that the multi-objective optimization function is used to minimize the voltage fluctuation of the base station electrical device;
[0076] It should be noted that the constraint conditions include: ; ;
[0077] Among them, is the safe voltage range of the electrical device; are the initial supply voltages of the mains power energy and energy storage devices respectively; represents the longest switching delay of the energy storage device; is the stable time window of the target power supply;
[0078] Specifically, the balanced distribution scheme further includes: calculating the dynamic weight of criticality, which is used to balance the voltage supply ratio of different priority electrical devices during the power supply period.
[0079] Preferably, the generation method of the dynamic weight of criticality includes:
[0080] ;
[0081] Among them, is the dynamic weight of criticality;
[0082] is the normal operation duration of the electrical device after the last communication failure;
[0083] The longest normal operation duration and the shortest normal operation duration of the electrical equipment after a communication failure;
[0084] The average normal operation duration of the base station electrical equipment after the last communication failure;
[0085] The real-time energy efficiency ratio of the electrical equipment; The nominal energy efficiency ratio of the electrical equipment;
[0086] The average energy efficiency ratio of the base station electrical equipment;
[0087] Specifically, in S5, the energy storage device management model includes: a state perception layer, which is established based on the power supply quality evaluation index. The perception parameters of the state perception layer include: the mains fluctuation characteristic parameter, the energy storage device capacity attenuation rate, and the voltage deviation degree of the base station electrical equipment;
[0088] The power supply quality evaluation index The calculation strategy is specifically:
[0089] ;
[0090] Among them, are respectively the mains fluctuation evaluation index, the energy storage device attenuation evaluation index, and the electrical equipment voltage deviation evaluation index.
[0091] Preferably, the calculation strategy of the mains fluctuation evaluation index is: ;
[0092] Among them, is the mains fluctuation rate; is the nominal voltage;
[0093] Preferably, the calculation strategy of the energy storage device attenuation evaluation index is: ;
[0094] Among them, m is the attenuation sensitivity index of the energy storage device; is the energy storage device capacity attenuation rate;
[0095] Preferably, the calculation strategy of the electrical equipment voltage deviation evaluation index is specifically:
[0096] ;
[0097] Among them, are respectively the static weight of criticality and the dynamic weight of criticality;
[0098] is the normalized deviation between the actual voltage and the required voltage of the ith electrical equipment.
[0099] Specifically, in S5, the energy storage device management model also includes: real-time monitoring of power supply quality, and when the power supply quality evaluation index recovers to a preset quality safety threshold, triggering a power supply state migration mechanism to gradually reduce the output proportion of the energy storage device.
[0100] In addition, the present invention provides a base station energy storage device management system with adaptive output voltage, including the following modules:
[0101] Equipment weight determination module, demand data acquisition module, model building module, balanced allocation solution module and management and control module;
[0102] The device weight determination module obtains the criticality static weight of the base station electrical equipment according to the device attributes and historical voltage demand data of the base station electrical equipment;
[0103] The demand data acquisition module is used to obtain the dynamic voltage demand function curve of the base station power equipment, the energy consumption function curve of the base station power supply system and the independent conversion loss function curve of the power supply source;
[0104] The model building module is used to build a voltage distribution balance model for energy storage equipment, and at the same time obtain the safe voltage range of the base station electrical equipment as a constraint condition of the voltage distribution balance model;
[0105] The balanced allocation scheme module optimizes the voltage distribution balance model through a multi-objective optimization function to obtain a balanced allocation scheme;
[0106] The management and control module inputs the balanced allocation plan into the energy storage device management model, generates a voltage control instruction set, and completes the time-sharing voltage control management of the energy storage device according to the voltage control instruction set.
[0107] Compared with the prior art, the technical effects of the present invention are as follows:
[0108] 1. The present invention obtains the static weight of the criticality of the base station power equipment, combines it with the dynamic voltage demand function curve, etc., to construct and optimize the voltage distribution balance model, which can accurately adapt to the voltage requirements of different equipment, ensure that the actual voltage of each power equipment is as close to the required voltage as possible, ensure the stable operation of the equipment, and reduce the risk of performance degradation or failure due to voltage deviation.
[0109] 2. The present invention takes into account the voltage regulation efficiency and energy consumption cost of AC power and energy storage equipment, constructs a multi-objective optimization function for Pareto solution selection, and can effectively reduce the energy consumption of the base station power supply system. By comparing the voltage matching items and power consumption items of different allocation schemes, a lower energy consumption scheme is selected. For example, in the voltage distribution of AC power and energy storage equipment, unnecessary power consumption is reduced, saving operating costs.
[0110] 3. The present invention introduces dynamic weights of criticality, and balances the voltage supply ratios of devices with different priorities during the power supply period according to factors such as the operating time and energy efficiency ratio after a communication failure of the device, thereby achieving dynamic and flexible adjustment. At the same time, the state perception layer monitors parameters such as mains fluctuations, energy storage device attenuation, and device voltage deviation in real time based on the power supply quality evaluation index. When the power supply quality changes, the corresponding mechanism is triggered, such as the power supply source state migration mechanism, to automatically adjust the output ratio of the energy storage device to ensure stable and reliable power supply quality. BRIEF DESCRIPTION OF THE DRAWINGS
[0111] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:
[0112] Figure 1 A schematic flow chart of a method for managing a base station energy storage device with adaptive output voltage according to the present invention;
[0113] Figure 2 A data flow diagram of a base station energy storage device management method with adaptive output voltage according to the present invention;
[0114] Figure 3 It is a structural schematic diagram of a base station energy storage equipment management system with adaptive output voltage according to the present invention. DETAILED DESCRIPTION
[0115] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.
[0116] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.
[0117] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.
[0118] Embodiment 1:
[0119] like Figure 1 and Figure 2 As shown, a base station energy storage device management method with adaptive output voltage according to an embodiment of the present invention is as follows: Figure 1 As shown, the specific steps are as follows:
[0120] S1: Obtain the criticality static weight of the base station power equipment according to the equipment attributes and historical voltage demand data of the base station power equipment;
[0121] S1 includes:
[0122] S11: Obtain a list of attributes of the base station power equipment, and calculate the criticality static weight of the base station power equipment according to the historical voltage demand data of the base station power equipment under different working modes;
[0123] In one specific implementation, the calculation strategy of the criticality static weight is specifically:
[0124] ;
[0125] in, is the criticality static weight;
[0126] is the harmonic distortion rate of the current of the electrical equipment;
[0127] is the temperature rise rate inside the electrical equipment cabinet; For business priorities;
[0128] It should be noted that is an adaptive coefficient; illustratively, in this embodiment, Online update via Kalman filter;
[0129] They are the real-time information throughput and maximum information throughput of the electrical equipment respectively;
[0130] S12: Based on the dynamic voltage demand curve corresponding to each electrical device in the static weight of the criticality of the electrical device, a voltage sensitivity coefficient and a power consumption curve of the electrical device are obtained.
[0131] In one specific embodiment, the calculation strategy for the voltage sensitivity coefficient of the electrical device is as follows:
[0132] ; where is the voltage sensitivity coefficient of the electrical device;
[0133] It should be noted that corresponds to the power consumption curve of the electrical device, representing the power consumption of the electrical device at different operating voltages.
[0134] S2: Obtain the dynamic voltage demand function curve of the base station electrical device, the energy consumption function curve of the base station power supply system, and the independent conversion loss function curve of the power supply source;
[0135] S21: Define the time window parameter for the target power supply of the energy storage device according to the communication guarantee level and the importance weight of the electrical device ; where represents the minimum guarantee start time of the critical electrical device with the highest service priority, represents the longest switching delay of the energy storage device;
[0136] S22: Obtain the reference value of the dynamic voltage regulation rate according to the stable time window of the target power supply and the safe voltage range of the electrical device;
[0137] In one specific embodiment, the stable time window of the target power supply is specifically:
[0138] ; where is the stable time window of the target power supply;
[0139] In one specific embodiment, the calculation strategy for the reference value of the dynamic voltage regulation rate is:
[0140] ;
[0141] where is the reference value of the dynamic voltage regulation rate;
[0142] is the safe voltage range of the electrical device;
[0143] S23: Differentiate the dynamic voltage demand function of the base station electrical device with respect to time to obtain the instantaneous voltage demand gradient of each electrical device, preset the instantaneous voltage demand fluctuation threshold, and screen the time points at which the instantaneous voltage demand gradient of each electrical device exceeds the instantaneous voltage demand fluctuation threshold as the voltage regulation trigger signal points.
[0144] S24: Classify the historical cooperative voltage regulation strategies, voltage regulation margins, and corresponding energy consumption characteristics of the mains power and energy storage devices through a clustering algorithm (K-means) according to the historical cooperative voltage regulation strategies, voltage regulation margins, and corresponding energy consumption characteristics of the mains power and energy storage devices, to obtain several historical operation scenarios;
[0145] Exemplarily, in this embodiment, several historical operation scenarios include: classifying the historical load data into scenarios such as "stable mode" or "peak mode or night mode".
[0146] Assign initial voltage values to several historical operation scenarios, and determine the initial power supply voltage value of the mains power supply;
[0147] In one specific implementation,
[0148] Among them, The power consumption of the mains power at voltage V. It should be noted that the higher the voltage, the greater the energy consumption;
[0149] Is the deviation between the current voltage and the standard voltage. It should be noted that the greater the deviation, the more unstable the power supply;
[0150] Direction coefficient; if = 0, it means that the power supply scheme pursues power saving; if Is very large, it means that the power supply scheme gives priority to ensuring power supply stability;
[0151] S25: Continuously monitor the dynamic voltage demand function of the base station electrical equipment. When it is monitored that, it should be noted that when reaching the voltage regulation trigger signal point, calculate the voltage regulation urgency through the fuzzy decision-making layer, and determine the initial power supply scheme based on the average value of the voltage regulation urgency of the base station electrical equipment;
[0152] When <0.3, only fine-tune the mains power through PID control (adjust within a small range of PID control parameters), and continue to execute step S26
[0153] When 0.3 ≤ <0.7, enable energy storage device pre-synchronization (reduce switching delay), and simultaneously execute step S28;
[0154] When ≥ 0.7, enforce the cooperative voltage regulation mechanism of the mains power and energy storage devices (sacrifice energy efficiency for stability), and simultaneously execute step S28;
[0155] In one specific implementation, the calculation strategy of the voltage regulation urgency is:
[0156] ;
[0157] Among them, is the voltage regulation urgency of the i-th electrical equipment;
[0158] is the deviation value between the power consumption demand and the actual power supply, is the baseline of the power consumption demand deviation;
[0159] Record the energy consumption evolution variable generated by the dynamic switching process and the independent conversion loss evolution variable of the power supply source, and update the energy consumption function curve of the base station power supply system and the independent conversion loss function curve of the power supply source.
[0160] S26: Based on the voltage demand change gradient and the dynamic voltage regulation rate reference value, calculate the voltage regulation margin of the mains power energy, and at the same time predict the change amount of the voltage demand of the base station electrical equipment;
[0161] Select the depletion critical point according to the voltage regulation margin of the mains power energy and the prediction result of the change amount of the voltage demand;
[0162] In one specific implementation manner, the voltage regulation margin The calculation strategy is:
[0163] is the maximum adjustable voltage of the mains power energy (defined by the safe voltage range of the electrical equipment)
[0164] is the output voltage of the current power supply source;
[0165] In one specific implementation manner, the prediction of the change amount of the voltage demand of the base station electrical equipment is specifically:
[0166] ;
[0167] is the voltage demand change gradient of the base station electrical equipment; is the prediction time step;
[0168] In one specific implementation manner, when it means reaching the depletion critical point of the voltage regulation margin of the mains power energy;
[0169] S27: Trigger the energy storage device to enter the parallel power supply mode at the depletion critical point of the voltage regulation margin of the mains power energy, and establish a collaborative working mechanism between the mains power energy and the energy storage device;
[0170] S28: According to the static weight of the criticality of the base station electrical equipment, initially allocate the supply voltages of the mains power energy and the energy storage device under the collaborative working mechanism;
[0171] In one of the specific embodiments, the initial distribution of the supply voltage is specifically as follows:
[0172] , ;
[0173] Among them, are respectively the initial supply voltages of the mains power energy and the energy storage device;
[0174] is the real-time demand voltage of the electrical equipment; is the total demand voltage of the base station electrical equipment;
[0175] S29: Construct a voltage distribution balance degree model for the energy storage device, specifically as follows:
[0176] ;
[0177] Among them, is the nominal voltage of the electrical equipment; is the actual power of the power supply;
[0178] is the rated power of the base station power supply system; is the voltage matching balance weight.
[0179] It should be noted that is the voltage matching item; is the power consumption item of the power supply;
[0180] It should be noted that the voltage matching item is used to ensure that the actual voltage of each electrical equipment is as close as possible to its demand voltage;
[0181] S3: According to S2, construct a voltage distribution balance degree model for the energy storage device, and at the same time obtain the safe voltage range of the base station electrical equipment as the constraint condition of the voltage distribution balance degree model;
[0182] S4: Optimize the voltage distribution balance degree model through a multi-objective optimization function to obtain an equilibrium distribution scheme;
[0183] In S4, the construction of the multi-objective optimization function is specifically as follows: According to the voltage regulation efficiency, energy consumption cost and weight distribution of the power supply priority of the mains power energy and the energy storage device, construct a multi-objective optimization function, and under the constraint conditions, perform Pareto solution selection. The multi-objective optimization function is specifically as follows:
[0184] ;
[0185] Among them, are respectively the demand voltage and the nominal voltage of the electrical equipment.
[0186] It should be noted that the multi-objective optimization function is used to minimize the voltage fluctuation of the base station power-consuming equipment;
[0187] It should be noted that the constraint conditions include: ; ;
[0188] Exemplarily, in this embodiment, it should be noted that the process of solving the Pareto optimal solution includes: inputting a three-dimensional optimization space (equipment energy consumption, voltage fluctuation, and dynamic weight of criticality), combining constraint conditions (stable time window of target power supply and safe voltage range of power-consuming equipment), outputting a set of non-dominated solutions (Pareto front), and obtaining an equilibrium allocation scheme.
[0189] Exemplarily, in this embodiment, a strategy for obtaining an allocation scheme of the supply voltage of the mains power and energy storage equipment under a collaborative working mechanism is given;
[0190] Exemplarily, in this embodiment, the base station power-consuming equipment includes equipment A and equipment B. Among them, the static weight of the criticality of equipment A is 0.8, and the required voltage is 48V. The static weight of the criticality of equipment B is 0.2, and the required voltage is 47V;
[0191] Exemplarily, in this embodiment, the nominal voltage of the equipment is 48V, and the rated power of the base station power supply system is 1000W;
[0192] Exemplarily, in this embodiment, the voltage matching balance weight ;
[0193] Exemplarily, in this embodiment, the total required voltage of the base station power-consuming equipment is 48V, that is ;
[0194] Exemplarily, in this embodiment, the independent conversion loss function curve of the power supply is obtained by fitting the historical working day log of the power supply;
[0195] The non-linear loss coefficients of the voltage conversion of the mains power and energy storage equipment are obtained according to the independent conversion loss function curve of the power supply. Exemplarily, in this embodiment, the non-linear loss coefficient of the voltage conversion of the mains power is 10, and the non-linear loss coefficient of the voltage conversion of the energy storage equipment is 20; Exemplarily, in this embodiment, the independent conversion loss function curve of the mains power is: ;
[0196] The independent conversion loss function curve of the energy storage equipment is: ;
[0197] It should be noted that for the mains power, the mains power is supplied through an AC-DC converter or a voltage regulator module. Its voltage conversion loss is non-linear, and its loss mainly comes from the conduction loss and switching loss of the switching device. These losses are proportional to the square of the current, that is, the greater the voltage deviation, the square growth of the conversion loss (such as the Buck / Boost circuit);
[0198] It should be noted that for the energy storage device, usually a lithium battery pack, its output voltage will decrease with the depth of discharge. When the battery discharges, the internal resistance loss of the energy storage device is proportional to the square of the current. Therefore, in this embodiment, the independent conversion loss function curve of the energy storage device is approximately linear.
[0199] The voltage regulation margin of the mains power is 47.8V, specifically:[[]]
[0200] ;
[0201] ;
[0202] Exemplarily, in this embodiment, the current allocation scheme is: 47.8V of mains power and 0.2V of energy storage device;
[0203] Construct a voltage distribution balance model for the energy storage device,
[0204] Calculate and obtain the voltage matching term and the power supply power consumption term of the current allocation scheme respectively;
[0205] The calculation strategy of the voltage matching term includes:
[0206] ;
[0207] The calculation strategy of the power supply power consumption term includes:
[0208] ;
[0209] Obtain the voltage distribution fitness according to the voltage matching term and the power supply power consumption term of the current allocation scheme, specifically:
[0210] ;
[0211] Construct a multi-objective optimization function, and perform Pareto solution selection under the constraint conditions, specifically:
[0212] Calculate the voltage fluctuation penalty value under the current allocation scheme;
[0213] ;
[0214] Exemplarily, in this embodiment, when the allocation scheme is adjusted to 47.5V of mains power energy and 0.5V of energy storage device, repeat the above steps to synchronously calculate the voltage matching term and the power supply power consumption term of the adjusted allocation scheme. Among them, the voltage matching term of the adjusted allocation scheme is specifically:
[0215] ;
[0216] The power supply power consumption term of the adjusted allocation scheme is specifically:
[0217] ;
[0218] Obtain the voltage allocation fitness according to the voltage matching term and the power supply power consumption term of the adjusted allocation scheme, specifically:
[0219] ;
[0220] Synchronously calculate the voltage fluctuation penalty value under the adjusted allocation scheme;
[0221] ;
[0222] Exemplarily, in this embodiment, perform Pareto front analysis, as shown in the following table:
[0223]
[0224] According to the above table, the current scheme (solution 1, mains power energy 47.8V and energy storage device 0.2V) is superior to solution 2 in terms of voltage allocation fitness, power consumption and voltage fluctuation penalty value. Therefore, in this embodiment, solution 1 is the Pareto optimal solution.
[0225] S5: Input the balanced allocation scheme into the energy storage device management model to generate a set of voltage regulation instructions, and complete the time-sharing voltage regulation management of the energy storage device according to the set of voltage regulation instructions.
[0226] The balanced allocation scheme further includes: calculating the criticality dynamic weight, which is used to balance the voltage supply ratio of different priority electrical equipment during the power supply period.
[0227] In one specific implementation, the method for generating the criticality dynamic weight includes:
[0228] ;
[0229] Among them, is the criticality dynamic weight;
[0230] is the normal operation duration of the electrical equipment after the last communication failure;
[0231] The longest and shortest normal operation durations of the electrical equipment after a communication failure;
[0232] The average normal operation duration of the base station electrical equipment after the last communication failure;
[0233] The real-time energy efficiency ratio of the electrical equipment; The nominal energy efficiency ratio of the electrical equipment;
[0234] The average energy efficiency ratio of the base station electrical equipment;
[0235] Exemplarily, in this embodiment, it should be noted that the longer the normal operation duration of the electrical equipment after the last communication failure, the higher the reliability of the electrical equipment, the lower the probability of failure, and the higher the priority of the power supply to supply power to it.
[0236] In S5, the energy storage device management model includes: a state perception layer, which is established based on the power supply quality evaluation index. The perception parameters of the state perception layer include: the mains fluctuation characteristic parameter, the energy storage device capacity attenuation rate, and the voltage deviation degree of the base station electrical equipment;
[0237] The calculation strategy of the power supply quality evaluation index is specifically:
[0238] ;
[0239] Among them, They are respectively the mains fluctuation evaluation index, the energy storage device attenuation evaluation index, and the electrical equipment voltage deviation evaluation index.
[0240] In one specific embodiment, the calculation strategy of the mains fluctuation evaluation index is: ;
[0241] Among them, is the mains fluctuation rate; is the nominal voltage;
[0242] In one specific embodiment, the calculation strategy of the energy storage device attenuation evaluation index is: ;
[0243] Among them, m is the attenuation sensitivity index of the energy storage device; is the energy storage device capacity attenuation rate;
[0244] Exemplarily, in this embodiment, the attenuation sensitivity index m of the energy storage device = 0.05;
[0245] In one specific implementation, the calculation strategy of the voltage deviation evaluation index of the electrical equipment is specifically as follows:
[0246] ;
[0247] in, They are static weight of criticality and dynamic weight of criticality respectively;
[0248] is the normalized deviation between the actual voltage and the required voltage of the ith electrical equipment.
[0249] In S5, the energy storage device management model also includes: real-time monitoring of power supply quality, and when the power supply quality evaluation index recovers to a preset quality safety threshold, triggering a power supply state migration mechanism to gradually reduce the output proportion of the energy storage device.
[0250] Embodiment 2:
[0251] like Figure 3 As shown, a base station energy storage device management system with adaptive output voltage according to an embodiment of the present invention is as follows: Figure 3 As shown, it includes the following modules:
[0252] Equipment weight determination module, demand data acquisition module, model building module, balanced allocation solution module and management and control module;
[0253] The device weight determination module obtains the criticality static weight of the base station electrical equipment according to the device attributes and historical voltage demand data of the base station electrical equipment;
[0254] The demand data acquisition module is used to obtain the dynamic voltage demand function curve of the base station power equipment, the energy consumption function curve of the base station power supply system and the independent conversion loss function curve of the power supply source;
[0255] The model building module is used to build a voltage distribution balance model for energy storage equipment, and at the same time obtain the safe voltage range of the base station electrical equipment as a constraint condition of the voltage distribution balance model;
[0256] The balanced allocation scheme module optimizes the voltage distribution balance model through a multi-objective optimization function to obtain a balanced allocation scheme;
[0257] The management and control module inputs the balanced allocation plan into the energy storage device management model, generates a voltage control instruction set, and completes the time-sharing voltage control management of the energy storage device according to the voltage control instruction set.
[0258] Embodiment three:
[0259] This embodiment provides an electronic device, including: a processor and a memory, wherein, a computer program that can be called by the processor is stored in the memory;
[0260] The processor executes the above-mentioned management method for a base station energy storage device with adaptive output voltage by calling the computer program stored in the memory.
[0261] This electronic device may have relatively large differences due to different configurations or performances, and can include one or more processors (Central Processing Units, CPU) and one or more memories. Among them, at least one computer program is stored in the memory, and this computer program is loaded and executed by the processor to implement the management method for a base station energy storage device with adaptive output voltage provided by the above method embodiment. This electronic device can also include other components for implementing device functions. For example, this electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for data input and output. This embodiment will not be elaborated here.
[0262] Embodiment 4:
[0263] This embodiment proposes a computer-readable storage medium, on which a rewritable computer program is stored;
[0264] When the computer program runs on a computer device, it causes the computer device to execute the above-mentioned management method for a base station energy storage device with adaptive output voltage.
[0265] For example, the computer-readable storage medium can be a read-only memory (abbreviation: ROM), a random access memory (abbreviation: RAM), a compact disc read-only memory (abbreviation: CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.
[0266] It should be understood that in various embodiments of the present application, the magnitudes of the serial numbers of the above processes do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
[0267] It should be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.
[0268] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from a website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.
[0269] Those of ordinary skill in the art will realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed in the present invention can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.
[0270] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.
[0271] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only one way, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.
[0272] The unit described as a separating component may or may not be physically separated, and the component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0273] In addition, each functional unit in various embodiments of the present invention may be integrated into one processing unit, may exist separately as individual physical units, or two or more units may be integrated into one unit.
[0274] In the description of this specification, the descriptions with reference to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in a suitable manner in any one or more embodiments or examples.
[0275] The above has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification is only to illustrate the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.
Claims
1. A management method for a base station energy storage device with adaptive output voltage, characterized in that, Including: S1: Obtain the static weight of criticality of base station electrical equipment according to the equipment attributes and historical voltage demand data of base station electrical equipment; S2: Obtain the dynamic voltage demand function curve of base station electrical equipment, calculate the reference value of dynamic voltage regulation rate according to the static weight of criticality, evaluate the urgency of voltage regulation through the reference value of dynamic voltage regulation rate, and update the energy consumption function curve of the base station power supply system and the independent conversion loss function curve of the power supply source based on the evaluation results; S3: According to S2, construct a voltage distribution balance model for energy storage equipment, and at the same time obtain the safe voltage range of base station electrical equipment as a constraint condition for the voltage distribution balance model; S4: Construct a multi-objective optimization function according to the voltage regulation efficiency, energy consumption cost and weight distribution of power supply priority of mains power energy and energy storage equipment, optimize the voltage distribution balance model through the multi-objective optimization function, and obtain an equilibrium distribution plan; S5: Input the equilibrium distribution plan into the energy storage equipment management model, generate a set of voltage regulation instructions, and complete the time-sharing voltage regulation management of the energy storage equipment according to the set of voltage regulation instructions.
2. The method for managing a base station energy storage device with adaptive output voltage according to claim 1, characterized in that S2 Including: S21: Define the time window parameters for the target power supply of the energy storage device according to the communication guarantee level and the importance weight of the electrical equipment ; where represents the minimum guarantee start time of the critical electrical equipment with the highest service priority, represents the longest switching delay of the energy storage device; S22: Obtain the reference value of dynamic voltage regulation rate according to the stable time window of target power supply and the safe voltage range of electrical equipment; S23: Differentiate the dynamic voltage demand function of base station electrical equipment with respect to time to obtain the instantaneous voltage demand gradient of each electrical equipment, preset the instantaneous voltage demand fluctuation threshold, and screen the time points when the instantaneous voltage demand gradient of each electrical equipment exceeds the instantaneous voltage demand fluctuation threshold as voltage regulation trigger signal points.
3. The method for managing a base station energy storage device with an adaptive output voltage according to claim 2, wherein, S2 also includes: S24: Classify the historical cooperative voltage regulation strategies, voltage regulation margins and corresponding energy consumption characteristics of mains power energy and energy storage equipment through a clustering algorithm according to the historical cooperative voltage regulation strategies, voltage regulation margins and corresponding energy consumption characteristics of mains power energy and energy storage equipment, and obtain several historical operation scenarios; Assign initial voltage values to several historical operation scenarios, and determine the initial power supply voltage value of the mains power supply.
4. The management method of a base station energy storage device with adaptive output voltage according to claim 3, characterized in that, S2 also includes: S25: Continuously monitor the dynamic voltage demand function of base station electrical equipment. When a voltage regulation trigger signal point is detected, calculate the urgency of voltage regulation through the fuzzy decision layer, and determine the initial power supply plan according to the average value of the voltage regulation urgency of base station electrical equipment; When <0.3, finely adjust the mains power through PID control, and continue to execute step S26; When 0.3 ≤ < 0.7, enable the pre-synchronization of the energy storage device and simultaneously execute step S28; When ≥ 0.7, the forced coordinated voltage regulation mechanism of the mains power energy and the energy storage device is implemented, and step S28 is executed simultaneously; Among them, is the pressure regulation urgency; Record the energy consumption evolution variables generated by dynamic switching processing and the independent conversion loss evolution variables of the power supply source, and update the energy consumption function curve of the base station power supply system and the independent conversion loss function curve of the power supply source; S26: Calculate the voltage regulation margin of mains power energy based on the voltage demand change gradient and the reference value of dynamic voltage regulation rate, and at the same time predict the voltage demand change amount of base station electrical equipment; Screen out the depletion critical point according to the voltage regulation margin of mains power energy and the prediction result of voltage demand change amount; S27: Trigger the energy storage equipment to enter the parallel power supply mode at the depletion critical point of the voltage regulation margin of mains power energy, and establish a cooperative working mechanism between mains power energy and energy storage equipment; S28: According to the static weight of criticality of base station electrical equipment, initially allocate the supply voltages of mains power energy and energy storage equipment under the cooperative working mechanism; S29: Construct a voltage distribution balance model for energy storage equipment, specifically: ; Among them, is the voltage distribution balance degree; is the static weight of criticality; is the real-time required voltage of the electrical equipment; is the rated voltage of the electrical equipment; is the actual power of the power supply; is the rated power of the base station power supply system; is the voltage matching balance weight, and n is the total number of electrical equipment.
5. The management method of a base station energy storage device with adaptive output voltage according to claim 4, characterized in that, In S4, the construction of the multi-objective optimization function is specifically as follows: according to the voltage regulation efficiency, energy consumption cost of the mains power energy and energy storage device, and the weight distribution of the power supply priority of the electrical equipment, a multi-objective optimization function is constructed, and under the constraint conditions, Pareto solution selection is carried out. The multi-objective optimization function is specifically as follows: ; wherein, is the voltage sensitivity coefficient of the electrical equipment; are respectively the required voltage and the nominal voltage of the electrical equipment.
6. The management method of a base station energy storage device with adaptive output voltage according to claim 5, characterized in that, The balanced allocation scheme also includes: calculating a criticality dynamic weight, where the criticality dynamic weight is used to balance the voltage supply ratio of electrical equipment with different priorities during a power supply period.
7. The method for managing a base station energy storage device with an adaptive output voltage according to claim 6, wherein In S5, the energy storage device management model includes: a state perception layer, the state perception layer is established based on the power supply quality evaluation index, and the perception parameters of the state perception layer include: mains power fluctuation characteristic parameters, energy storage device capacity attenuation rate and voltage deviation of base station power equipment; The power supply quality evaluation index The specific calculation strategy is as follows: ; Among them, are the mains voltage fluctuation evaluation index, the energy storage device attenuation evaluation index, and the electrical equipment voltage deviation evaluation index respectively.
8. A method for managing a base station energy storage device with adaptive output voltage according to claim 7, characterized in that In S5, the energy storage device management model also includes: real-time monitoring of power supply quality, and when the power supply quality evaluation index recovers to a preset quality safety threshold, triggering a power supply state migration mechanism to gradually reduce the output proportion of the energy storage device.
9. A base station energy storage device management system with an adaptive output voltage, which is implemented based on a base station energy storage device management method with an adaptive output voltage according to any one of claims 1-8, characterized in that The system includes the following modules: Equipment weight determination module, demand data acquisition module, model building module, balanced allocation plan module and management and control module; The device weight determination module obtains the criticality static weight of the base station electrical equipment according to the device attributes and historical voltage demand data of the base station electrical equipment; The demand data acquisition module is used to obtain the dynamic voltage demand function curve of the base station power equipment, the energy consumption function curve of the base station power supply system and the independent conversion loss function curve of the power supply source; The model building module is used to build a voltage distribution balance model for energy storage equipment, and at the same time obtain the safe voltage range of the base station electrical equipment as a constraint condition of the voltage distribution balance model; The balanced allocation scheme module optimizes the voltage distribution balance model through a multi-objective optimization function to obtain a balanced allocation scheme; The management and control module inputs the balanced allocation plan into the energy storage device management model, generates a voltage control instruction set, and completes the time-sharing voltage control management of the energy storage device according to the voltage control instruction set.
Citation Information
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