CN-121998377-A - Campus molten salt energy storage quantitative management system and method based on distributed control

CN121998377ACN 121998377 ACN121998377 ACN 121998377ACN-121998377-A

Abstract

The invention discloses a park molten salt energy storage quantitative management system and method based on distributed control, and relates to the technical field of energy management. The system comprises a load sensing and classifying module, a demand quantization analysis module, an energy storage configuration rule construction module and a partition configuration and scheduling module, wherein the method comprises the steps of obtaining park load data through a distributed acquisition terminal, extracting characteristics and completing load classification, calculating energy utilization gaps based on classification results, constructing a three-dimensional quantization index system, establishing a quantization mapping relation between load indexes and energy storage parameters to form a regional configuration rule base, calculating matching parameters according to rules, generating a configuration scheme and realizing partition quantization configuration and collaborative scheduling. The method realizes accurate classification of the load, quantitative analysis of the demand and automatic matching of the energy storage parameters, improves the molten salt energy storage configuration precision and the energy utilization efficiency of the park, and is suitable for a distributed energy management scene of the park.

Inventors

HE JIA
LI NA
Cao Xiazhen
ZHANG HONGCHEN
WANG LIANG
WANG SHAOHUA
FENG MAN
ZHU JIADONG
WANG LING
LI YUAN
QIAN JING
DAI HUIHUI

Assignees

中建安装集团有限公司

Dates

Publication Date: 20260508
Application Date: 20260403

Claims (10)

1. The park molten salt energy storage quantitative management method based on distributed control is characterized by comprising the following steps of: s1, acquiring real-time energy utilization data of park load in a continuous period through a distributed acquisition terminal, and extracting load demand characteristics; S2, carrying out demand quantitative analysis on various types of loads according to the real-time energy utilization data and the characteristic parameters to obtain the daily maximum energy utilization gap quantity, the gap duration and the fluctuation frequency of unit time, constructing a three-dimensional quantitative index system and forming a load energy utilization demand characteristic database; S3, establishing a quantized mapping relation between a three-dimensional quantized index and energy storage configuration parameters according to independent energy utilization boundaries of all load areas under distributed control and by combining operation configuration requirements of molten salt energy storage, so as to form a regional energy storage configuration rule; S4, respectively calculating matching parameters of molten salt energy storage in each region according to the regional energy storage configuration rule, generating a regional energy storage configuration scheme, and carrying out quantitative configuration and regional collaborative scheduling management on the molten salt energy storage in the park based on the regional energy storage configuration scheme.
2. The method for quantitatively managing molten salt energy storage in a park based on distributed control as set forth in claim 1, wherein S1 comprises the following steps: According to a preset sampling time interval, collecting real-time energy utilization power of each load node of a park in a continuous statistical period through a distributed collecting terminal to form original energy utilization power time sequence data; Extracting load demand characteristic parameters based on the smoothed energy power time sequence data, wherein the load demand characteristic parameters comprise daily average energy power, energy use period concentration coefficients and energy use power fluctuation coefficients; The method comprises the steps of presetting a period concentration coefficient threshold value and a fluctuation coefficient threshold value, and dividing the load into a continuous load, a period concentration load and a random fluctuation load based on the magnitude relation of the period concentration coefficient, the energy consumption power fluctuation coefficient and the corresponding threshold value.
3. The method for quantitatively managing molten salt energy storage in a park based on distributed control according to claim 2, wherein the step S2 comprises the following steps: For each type of load obtained by division, based on corresponding smooth energy power time sequence data, counting rated energy power of each type of load in a counting period, calculating energy power gaps every moment, and judging that energy gaps exist when the energy power gaps are larger than zero; counting the energy utilization power gaps at each moment of a single day to obtain the maximum energy utilization gap quantity of the day, counting all the moments of the energy utilization gaps of the single day, accumulating to obtain the duration of the gaps, and calculating the fluctuation frequency of unit time according to the state jump condition of the energy utilization gaps; The three-dimensional quantitative index system of each type of load is constructed by taking the maximum daily energy gap amount, the gap duration and the fluctuation frequency of unit time as cores, and the three-dimensional quantitative index, the load demand characteristic parameters and the smooth energy power data of each type of load are uniformly stored to form a load energy demand characteristic database.
4. The method for quantitatively managing molten salt energy storage of a park based on distributed control according to claim 3, wherein the step S3 comprises the following steps: dividing a park into a plurality of independent load areas according to a distributed control architecture, and determining independent energy boundaries of each area and three-dimensional quantization indexes of corresponding load types; Establishing a quantization association rule between a three-dimensional quantization index and energy storage configuration parameters by combining operation configuration requirements of the molten salt energy storage system: Determining the minimum effective molten salt amount according to the daily maximum energy gap amount, the gap duration and the molten salt heat storage conversion coefficient, determining the rated heat release power according to the ratio of the daily maximum energy gap amount to the gap duration, the power adjustment coefficient and the standard heat release reference duration; Carrying out weighted summation on the minimum effective molten salt amount by adopting a weighted superposition rule on an independent load region containing multiple load types, taking the maximum value of rated heat release power and the minimum value of heat exchange matching coefficient to obtain a region comprehensive energy storage configuration parameter; And uniformly integrating the quantization mapping relation, the weighted superposition rule and the distributed area boundary constraint to form a regional energy storage configuration rule base.
5. The method for quantitatively managing molten salt energy storage in a park based on distributed control as set forth in claim 4, wherein the step S4 comprises the following steps: Based on three-dimensional quantization indexes and load type parameters corresponding to each independent load area, respectively calculating to obtain energy storage matching parameters corresponding to each single load type according to a regional energy storage configuration rule base, wherein the energy storage matching parameters comprise minimum effective fused salt heat storage capacity, rated heat release power and heat exchange matching coefficients; Carrying out comprehensive treatment on energy storage matching parameters corresponding to various loads according to a weighted superposition rule on an independent load region containing various load types to obtain comprehensive energy storage matching parameters of the region, wherein the comprehensive energy storage matching parameters comprise region comprehensive minimum effective fused salt heat storage quantity, region comprehensive rated heat release power and region comprehensive heat exchange matching coefficients; Converting the comprehensive energy storage matching parameters into physical configuration indexes which can be implemented by engineering, and generating a regional energy storage configuration scheme based on the physical configuration indexes; according to a regional energy storage configuration scheme, performing regional quantization configuration on a park molten salt energy storage system under a distributed control architecture; Based on quantitative configuration, the real-time energy utilization state, the demand fluctuation and the three-dimensional quantitative index change of each independent load area are combined, the area cooperative scheduling management is executed, and the complementary adjustment and the cooperative energy supply of the multi-area energy storage resources are realized.
6. The park molten salt energy storage quantitative management system based on distributed control is applied to the park molten salt energy storage quantitative management method based on distributed control as claimed in any one of claims 1 to 5, and is characterized by comprising a load sensing and classifying module, a demand quantitative analysis module, an energy storage configuration rule building module and a partition configuration and scheduling module; The load sensing and classifying module acquires real-time energy utilization data of the load of the park through the distributed acquisition terminal, extracts load demand characteristics and finishes load type division; The demand quantitative analysis module carries out demand quantitative analysis on various types of loads, constructs a three-dimensional quantitative index system and forms a load energy demand characteristic database; The energy storage configuration rule construction module establishes a quantization mapping relation between a three-dimensional quantization index and energy storage configuration parameters based on independent energy consumption boundaries to form a regional energy storage configuration rule base; And the partition configuration and scheduling module calculates energy storage matching parameters of each region according to the regional energy storage configuration rule, generates a regional energy storage configuration scheme and executes quantitative configuration and regional collaborative scheduling management.
7. The park molten salt energy storage quantification management system based on distributed control of claim 6, wherein the load sensing and classifying module comprises a data acquisition processing unit and a load classifying unit; The data acquisition processing unit acquires real-time energy consumption power according to a preset sampling interval, and performs moving average smoothing processing on original power time sequence data to obtain smoothed energy consumption power time sequence data; The load classification unit extracts load demand characteristic parameters based on the smooth power data, and divides the load into a continuous load, a period-concentrated load and a random fluctuation load according to a preset threshold.
8. The system for quantitatively managing molten salt energy storage in a park based on distributed control according to claim 6, wherein the demand quantitative analysis module comprises a gap calculation unit and an index construction unit; The gap calculating unit calculates rated energy supply power of each type of load in a statistical period, calculates energy consumption gaps every moment and obtains daily maximum energy consumption gap quantity, gap duration and fluctuation frequency of unit time; The index construction unit constructs a three-dimensional quantitative index system according to the daily maximum energy gap quantity, the gap duration and the unit time fluctuation frequency to form a load energy demand characteristic database.
9. The system for quantitatively managing molten salt energy storage in a park based on distributed control according to claim 6, wherein the energy storage configuration rule building module comprises a region dividing unit and a mapping rule unit; The region dividing unit divides independent load regions according to a distributed control architecture and determines energy boundaries of each region and corresponding three-dimensional quantization indexes; And the mapping rule unit establishes a quantization association rule of the three-dimensional quantization index, the minimum effective molten salt amount, the rated heat release power and the heat exchange matching coefficient, and performs weighted superposition calculation on the multi-load type region to form a regional energy storage configuration rule base.
10. The campus molten salt energy storage quantification management system based on distributed control of claim 6, wherein the partition configuration and scheduling module comprises a parameter calculation unit and a scheduling execution unit; The parameter calculation unit calculates energy storage matching parameters of each area according to the regional energy storage configuration rule base, converts the matching parameters into physical configuration indexes and generates a regional energy storage configuration scheme; And the scheduling execution unit executes the zonal quantitative configuration according to the zonal energy storage configuration scheme, and performs zone cooperative scheduling by combining the real-time energy utilization state, so as to realize the complementary adjustment and cooperative energy supply of the multi-zone energy storage resources.

Description

Campus molten salt energy storage quantitative management system and method based on distributed control Technical Field The invention relates to the technical field of energy management, in particular to a park molten salt energy storage quantitative management system and method based on distributed control. Background The park is used as an energy consumption core scene, and the large-scale configuration of the energy storage system becomes a key means for improving the clean energy consumption rate and optimizing the energy utilization structure. The fused salt energy storage has the advantages of long-term storage, high safety, environmental friendliness and the like, and is increasingly widely applied to the scenes of cooling, heating, power and the like in a park, and the scenes of renewable energy source matched storage and the like. However, current campus molten salt energy storage system configurations are generally faced with technical pain points with insufficient load suitability. The park usually covers various loads such as industry, business, house and the like, the energy intensity and time sequence characteristic difference of different loads are obvious, the industrial load is mainly based on stable industrial steam demand, the cold load period of the commercial load is concentrated, the peak-valley difference is large, and the house load fluctuates in a double peak mode of 'going to work from the morning to the evening'. The traditional configuration scheme does not subdivide load types, and a rough mode of integral load peak accumulation or fixed allocation and storage proportion is adopted to determine the molten salt energy storage capacity and rated power, so that the precise quantitative association of load characteristics and energy storage parameters is lacking. The rough configuration causes redundancy or deficiency of an energy storage system, namely excessive energy storage is configured for industrial loads with gentle fluctuation to cause equipment resource waste, capacity is configured for commercial loads with concentrated time periods to be insufficient, peak energy utilization gaps cannot be covered, key parameters such as energy utilization duration, fluctuation frequency and the like of different loads are ignored, energy storage power is not matched with storage duration, and efficiency exertion is limited. Disclosure of Invention The invention aims to provide a park molten salt energy storage quantitative management system and method based on distributed control, which are used for solving the problems in the background technology. In order to solve the technical problems, the invention provides the following technical scheme: The park molten salt energy storage quantitative management method based on distributed control comprises the following steps: s1, acquiring real-time energy utilization data of park load in a continuous period through a distributed acquisition terminal, and extracting load demand characteristics; S2, carrying out demand quantitative analysis on various types of loads according to the real-time energy utilization data and the characteristic parameters to obtain the daily maximum energy utilization gap quantity, the gap duration and the fluctuation frequency of unit time, constructing a three-dimensional quantitative index system and forming a load energy utilization demand characteristic database; S3, establishing a quantized mapping relation between a three-dimensional quantized index and energy storage configuration parameters according to independent energy utilization boundaries of all load areas under distributed control and by combining operation configuration requirements of molten salt energy storage, so as to form a regional energy storage configuration rule; S4, respectively calculating matching parameters of molten salt energy storage in each region according to the regional energy storage configuration rule, generating a regional energy storage configuration scheme, and carrying out quantitative configuration and regional collaborative scheduling management on the molten salt energy storage in the park based on the regional energy storage configuration scheme. Further, S1 includes the following: According to a preset sampling time interval, collecting real-time energy utilization power of each load node of a park in a continuous statistical period through a distributed collecting terminal to form original energy utilization power time sequence data; Extracting load demand characteristic parameters based on the smoothed energy power time sequence data, wherein the load demand characteristic parameters comprise daily average energy power, energy use period concentration coefficients and energy use power fluctuation coefficients; The method comprises the steps of presetting a period concentration coefficient threshold value and a fluctuation coefficient threshold value, and dividing the load into a continuous load, a period concentratio