A distributed power supply management system and method

Abstract

The present invention relates to the field of electric energy management technology, and in particular to a distributed power supply management system and method, the system comprising: a data acquisition module for collecting power supply area data and power grid data; a priority analysis module for analyzing the priority coefficient of each power supply area; a power distribution module for distributing power to each power supply area; an energy efficiency monitoring module for analyzing the power grid energy efficiency state; a correlation analysis module for constructing the correlation coefficient between the power grid input power and the power grid energy efficiency according to the analysis result of the power grid energy efficiency state in the management cycle, and adjusting the power distribution process of each power supply area in the next management cycle; a fluctuation analysis module for analyzing the fluctuation state of the voltage according to the power grid voltage collected in the management cycle, and optimizing the adjustment process of the power distribution process of each power supply area in the next management cycle according to the analysis result. The present invention improves the management efficiency of distributed power supply.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy management, and in particular to a distributed power supply management system and method. Background Art

[0002] With the development of the power market, especially the development of distributed power sources, the operation mode and dispatching strategy of the power grid need to be innovated and changed. The integration of distributed power sources enables small power generation units, energy storage devices and consumer devices to be interconnected with the main power grid, and the traditional centralized dispatching mode is gradually changing to decentralized power dispatching. This change provides new opportunities for more efficient power utilization and resource allocation, but also brings greater challenges, especially in terms of real-time, coordination and intelligent dispatching.

[0003] Chinese patent publication number CN104377694A discloses a distributed power supply management system and method, including an information acquisition module, a power management mechanism, a GIS distribution module and a controller, wherein the information acquisition module, the power management mechanism and the GIS distribution module are respectively interconnected with the controller signal; by dividing the power grid into multiple areas for a specific area, regional power and power quality monitoring is implemented, so that power distribution can be adjusted autonomously to improve stability and reliability; the power supply information is integrated into the GIS distribution module so that it can be displayed intuitively on the controller, which is worthy of promotion and application; it can be seen that when distributing power, the scheme only analyzes the power, and there are problems of low power distribution efficiency and high power resource consumption. Summary of the invention

[0004] An object of the present invention is to provide a distributed power management system and method to solve at least one of the problems existing in the prior art.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A distributed power management system, comprising:

[0007] Data acquisition module, used to collect energy supply area data and power grid data;

[0008] The priority analysis module is used to analyze the priority coefficient of each energy supply area according to the soil moisture, water pump flow and maximum power of each energy supply area collected during the monitoring period;

[0009] The power distribution module is used to distribute power to each energy supply area according to the analysis results of the load demand of each energy supply area and the priority coefficient of each energy supply area collected during the monitoring period;

[0010] Energy efficiency monitoring module, used to analyze the energy efficiency of the power grid according to the power distribution results of each energy supply area and the power grid output power during the monitoring period, and analyze the energy efficiency status of the power grid according to the analysis results;

[0011] The correlation analysis module is used to construct the correlation coefficient between the grid input power and the grid energy efficiency according to the analysis results of the grid energy efficiency status within the management cycle, and adjust the power distribution process of each energy supply area in the next management cycle;

[0012] The fluctuation analysis module is used to analyze the voltage fluctuation state according to the grid voltage collected during the management period, and optimize the adjustment process of the power distribution process of each energy supply area in the next management period according to the analysis results.

[0013] Furthermore, the priority analysis module includes a soil moisture analysis unit, which is used to compare the soil moisture of each energy supply area with the preset humidity s0, and analyze the abnormality of the soil moisture based on the comparison result. The abnormality of the soil moisture includes normal and abnormal. If the soil moisture of the i-th energy supply area in the current monitoring period is abnormal, the humidity priority coefficient of the i-th energy supply area is set to Ysi1; if the soil moisture of the i-th energy supply area in the current monitoring period is normal, the humidity priority coefficient of the i-th energy supply area is set to Ysi2.

[0014] Furthermore, the priority analysis module also includes a load analysis unit, which is used to compare the maximum power of the water pumps in each energy supply area collected with a preset power threshold p0. If pi≤p0, the load analysis unit sets the load priority coefficient of the i-th energy supply area to Ypi1; if pi>p0, the load analysis unit sets the load priority coefficient of the i-th energy supply area to Ypi2;

[0015] The priority analysis module also includes a flow analysis unit, which is used to compare the water pump flow of each energy supply area collected during the monitoring period with the preset flow L0, and analyze the water pump flow state according to the comparison result. The water pump flow state includes a normal state and a high flow state. If the water pump flow state of the i-th energy supply area in the current monitoring period is a normal state, the flow priority coefficient of the i-th energy supply area is set to YLi1; if the water pump flow state of the i-th energy supply area in the current monitoring period is a high flow state, the flow priority coefficient of the i-th energy supply area is set to YLi2.

[0016] Furthermore, the priority analysis module also includes a priority analysis unit, which constructs a priority coefficient for each energy supply area based on the construction results of the humidity priority coefficient, load priority coefficient and flow priority coefficient of each energy supply area, and sets the priority coefficient of the i-th energy supply area to YXi.

[0017] Furthermore, the power distribution module is used to analyze the abnormality of load demand based on the load demand of each energy supply area collected during the monitoring period. The abnormality of load demand includes normal and abnormal. If the load demand in the current monitoring period is normal, the power distribution of the i-th energy supply area is set to Di1; if the load demand in the current monitoring period is abnormal, the power distribution of the i-th energy supply area is set to Di2.

[0018] Furthermore, the energy efficiency monitoring module is used to analyze the energy efficiency N of the power grid according to the power distribution results of each power supply area during the monitoring period and the power grid output power, and compare the energy efficiency N of the power grid with the preset energy efficiency α to analyze the power grid energy efficiency status, which includes normal and low energy efficiency.

[0019] Furthermore, the correlation analysis module includes an abnormality analysis unit, which is used to analyze the abnormality of the power grid energy efficiency within the management period according to the analysis result of the power grid energy efficiency state within the management period, and the abnormality of the power grid energy efficiency includes normal and abnormal.

[0020] Furthermore, the correlation analysis module also includes a correlation analysis unit, which is used to construct a correlation coefficient G between the grid input power and the grid energy efficiency according to the analysis results of the abnormality of the grid energy efficiency within the management period, and adjust the power distribution process of each power supply area in the next management period according to the correlation coefficient between the grid input power and the grid energy efficiency. If G<0, the correlation analysis unit sets the preset proportional coefficient to η1; if G=0, no adjustment is made; if G>0, the correlation analysis unit sets the preset proportional coefficient to η2.

[0021] Furthermore, the fluctuation analysis module is used to construct a fluctuation coefficient of the grid voltage according to the grid voltage collected during the management period and set it to B, and compare the fluctuation coefficient B of the grid voltage with the preset fluctuation coefficient B0, and analyze the fluctuation state of the grid voltage according to the comparison result. The fluctuation state of the grid voltage includes a stable state and an abnormal state. If the fluctuation state of the grid voltage in the current management period is an abnormal state, when G>0, the preset adjustment ratio is set to β1.

[0022] On the other hand, the present invention also provides a distributed power management method, comprising:

[0023] Step S1: Collecting energy supply area data and power grid data;

[0024] Step S2: analyzing the priority coefficient of each energy supply area according to the soil moisture, water pump flow rate and maximum power of each energy supply area collected during the monitoring period;

[0025] Step S3: Allocate power to each energy supply area according to the load demand of each energy supply area collected during the monitoring period and the analysis result of the priority coefficient of each energy supply area;

[0026] Step S4: Analyze the energy efficiency of the power grid according to the power distribution results of each energy supply area and the power grid output power during the monitoring period, and analyze the power grid energy efficiency status according to the analysis results;

[0027] Step S5: constructing the correlation coefficient between the grid input power and the grid energy efficiency according to the analysis result of the grid energy efficiency status in the management cycle, and adjusting the power distribution process of each energy supply area in the next management cycle;

[0028] Step S6: Analyze the voltage fluctuation state according to the grid voltage collected during the management period, and optimize the adjustment process of the power distribution process of each energy supply area in the next management period according to the analysis result.

[0029] The beneficial effects of the present invention are as follows: The distributed power management system described in this embodiment forms an efficient, intelligent and flexible power dispatching solution by combining multiple modules such as data collection, priority analysis, power distribution and energy efficiency monitoring. The system can dynamically adjust the distribution of water resources and electricity according to the real-time collected data, and the monitoring module can track the grid load in real time. Through priority analysis and dynamic scheduling, the system can automatically provide decision support for different energy supply areas, reduce manual intervention, and improve the scientificity and timeliness of decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of 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 work.

[0031] Figure 1 Schematic diagram of the structure of the distributed power management system of this embodiment.

[0032] Figure 2 Schematic diagram of the structure of the priority analysis module of this embodiment.

[0033] Figure 3 Schematic diagram of the structure of the correlation analysis module in this embodiment.

[0034] Figure 4 Schematic diagram of the distributed power management method of this embodiment. DETAILED DESCRIPTION

[0035] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0036] It should be noted that, although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0037] See also Figure 1 As shown, it is a schematic diagram of the structure of the distributed power management system of this embodiment, the system includes:

[0038] The data acquisition module is used to collect energy supply area data and power grid data, wherein the energy supply area data includes soil moisture, water pump flow, maximum water pump power and load demand of each energy supply area, and the power grid data includes maximum power grid load, power grid voltage and power grid output power. The energy supply area is farmland with irrigation demand. In this embodiment, no specific limitation is made on the collection method of energy supply area data and power grid data, and technicians in this field can set it freely, as long as the collection requirements of energy supply area data and power grid data are met. Among them, the soil moisture can be collected by a soil moisture sensor, the water pump flow and the maximum water pump power can be collected interactively, the load demand of the energy supply area can be collected by a smart meter, the maximum power grid load can be collected interactively, and the power grid voltage and power grid output power can be collected by a smart meter.

[0039] Please continue reading Figure 1 As shown, the system also includes a priority analysis module, which is connected to the data acquisition module, and the priority analysis module is used to analyze the priority coefficient of each energy supply area according to the soil moisture, water pump flow and maximum power of each energy supply area collected during the monitoring period; it can be understood that the setting of the monitoring period is not specifically limited in this embodiment, and technical personnel in this field can set it freely, as long as the setting requirements of the monitoring period are met, wherein the monitoring period can be set to 5 minutes.

[0040] Specifically, the soil moisture, water pump flow rate and maximum water pump power of each energy supply area collected during the monitoring period described in this embodiment are collected at the beginning of the monitoring period.

[0041] See also Figure 2 As shown, the priority analysis module includes:

[0042] The soil moisture analysis unit is used to compare the soil moisture of each energy supply area with the preset humidity s0, and analyze the abnormality of soil moisture according to the comparison results to determine the actual needs of crops, and construct the humidity priority coefficient of each energy supply area according to the analysis results, where:

[0043] If si≤s0, the soil moisture analysis unit determines that the soil moisture of the i-th energy supply area in the current monitoring period is abnormal, and sets the moisture priority coefficient of the i-th energy supply area to Ysi1, setting Ysi1=(s0-si) / s0, si is the soil moisture of the i-th energy supply area in the current monitoring period;

[0044] If si>s0, the soil moisture analysis unit determines that the soil moisture of the i-th energy supply area in the current monitoring period is normal, and sets the humidity priority coefficient of the i-th energy supply area to Ysi2, setting: Ysi2=0; through scientific analysis of soil moisture, the actual needs of crops can be judged to improve the accuracy of the energy supply area priority coefficient analysis, thereby improving the accuracy of power distribution in the power grid, and ultimately improving the management efficiency of distributed power sources.

[0045] It is understandable that the setting of the preset humidity is not specifically limited in this embodiment, and those skilled in the art can freely set it as long as the value requirement of the preset humidity is met. Among them, when the crop is wheat, the optimal value of s0 is 45%.

[0046] Please continue reading Figure 2 As shown, the priority analysis module also includes:

[0047] The load analysis unit is used to compare the collected maximum power of the water pumps in each energy supply area with the preset power threshold p0, and construct the load priority coefficient according to the comparison result to quantify the load priority of the energy supply area, where:

[0048] If pi≤p0, the load analysis unit sets the load priority coefficient of the i-th energy supply area to Ypi1, setting: Ypi1=0, pi is the maximum power of the water pump in the i-th energy supply area;

[0049] If pi>p0, the load analysis unit sets the load priority coefficient of the i-th energy supply area to Ypi2, and sets: Ypi2=ln[5×(pi-p0) / p0+1] / ln6; by analyzing the maximum power of the energy supply area and the preset power threshold, the system can reasonably allocate resources to improve the accuracy of the energy supply area priority coefficient analysis, thereby improving the accuracy of power distribution in the power grid.

[0050] It can be understood that the setting of the preset humidity is not specifically limited in this embodiment, and those skilled in the art can freely set it as long as the value requirement of the preset humidity is met, wherein the optimal value of p0 is 6kW.

[0051] Please continue reading Figure 2 As shown, the priority analysis module also includes:

[0052] The flow analysis unit is used to compare the water pump flow of each energy supply area collected during the monitoring period with the preset flow L0, and analyze the water pump flow state according to the comparison result, and construct a flow priority coefficient according to the water pump flow state to quantify the priority of the water pump flow, where:

[0053] If Li≤L0, the flow analysis unit determines that the water pump flow state of the i-th energy supply area in the current monitoring period is normal, and sets the flow priority coefficient of the i-th energy supply area to YLi1, setting: YLi1=0, Li is the water pump flow of the i-th energy supply area;

[0054] If Li>L0, the flow analysis unit determines that the water pump flow state of the i-th energy supply area in the current monitoring period is a high flow state, and sets the flow priority coefficient of the i-th energy supply area to YLi2, setting: YLi2=exp[3×(Li-L0) / L0-3]; by quantifying the priority of the water pump flow, the accuracy of the energy supply area priority coefficient analysis is improved, thereby improving the accuracy of power distribution in the power grid.

[0055] It can be understood that the setting of the preset flow rate is not specifically limited in this embodiment, and those skilled in the art can freely set it as long as the value requirement of the preset flow rate is met, wherein the optimal value of L0 is 25m³ / h.

[0056] Please continue reading Figure 2 As shown, the priority analysis module also includes:

[0057] A priority analysis unit is connected to the soil moisture analysis unit, the load analysis unit and the flow analysis unit. The priority analysis unit constructs the priority coefficient of each energy supply area according to the construction results of the moisture priority coefficient, the load priority coefficient and the flow priority coefficient of each energy supply area to improve the scientific nature of power dispatching, wherein:

[0058] The priority analysis unit sets the priority coefficient of the ith energy supply area as YXi, and sets: YXi=x1×humidity priority coefficient of the ith energy supply area+x2×load priority coefficient of the ith energy supply area+x3×flow priority coefficient of the ith energy supply area, x1 is the humidity weight, x2 is the load weight, x3 is the flow weight, x1+x2+x3=1; by combining the three important indicators of humidity, load and flow, an effective comprehensive evaluation model of the energy supply area is constructed, thereby improving the scientific nature of power dispatching.

[0059] It can be understood that the present embodiment does not specifically limit the setting of each weight, and those skilled in the art can freely set it as long as the setting requirements of each weight are met, among which the best value of x1 is 0.5, the best value of x2 is 0.3, and the best value of x3 is 0.2.

[0060] Please continue reading Figure 1 As shown, the system further includes a power distribution module, which is connected to the priority analysis module, and the power distribution module is used to analyze the abnormality of the load demand according to the load demand of each energy supply area collected during the monitoring period, so as to flexibly adjust the power distribution according to the load demand change of the energy supply area, and distribute power to each energy supply area according to the analysis result and the analysis result of the priority coefficient of each energy supply area, wherein:

[0061] like , the power distribution module determines that the load demand in the current monitoring period is normal, and sets the power distribution of the i-th energy supply area to Di1, setting: Di1=Fi;

[0062] like , the power distribution module determines that the load demand in the current monitoring period is abnormal, and sets the power distribution of the i-th energy supply area to Di2, setting:

[0063] ;

[0064] Among them, Fi is the load demand of the i-th energy supply area in the current monitoring period, PZ is the maximum load of the power grid, η is the preset proportional coefficient, and I is the number of energy supply areas; by optimizing the power allocation strategy, excessive waste of resources can be avoided and the overall operating efficiency can be improved; through real-time monitoring and adjustment of power demand, the safety and stability of the system can be improved.

[0065] Specifically, the load demand of each energy supply area collected during the monitoring period in this embodiment is collected at the beginning of the monitoring period.

[0066] It can be understood that the present embodiment does not specifically limit the setting of the preset proportional coefficient, and those skilled in the art can freely set it as long as the value requirement of the preset proportional coefficient is met, wherein the optimal value of η is 0.8.

[0067] Please continue reading Figure 1 As shown, the system also includes an energy efficiency monitoring module, which is connected to the power distribution module. The energy efficiency monitoring module is used to analyze the energy efficiency N of the power grid according to the power distribution results of each energy supply area and the power grid output power within the monitoring period, and set: ; DiE is the power distribution result of the i-th energy supply area, E=1,2;

[0068] The energy efficiency monitoring module compares the energy efficiency N of the power grid with the preset energy efficiency α, and analyzes the energy efficiency status of the power grid according to the comparison result, so as to evaluate the energy efficiency of the system in real time and provide data support for further optimization. If N≤α, the energy efficiency monitoring module determines that the energy efficiency status of the power grid in the current monitoring period is low energy efficiency. If N>α, the energy efficiency monitoring module determines that the energy efficiency status of the power grid in the current monitoring period is normal. By monitoring the energy efficiency status, the system can make timely adjustments and optimizations, provide a good feedback mechanism for the maintenance of the power system, achieve energy saving and consumption reduction, and improve the management efficiency of distributed power sources.

[0069] Wherein, z is the number of grid output power data collected during the monitoring period, and Pscj is the j-th grid output power collected during the monitoring period.

[0070] It can be understood that the present embodiment does not specifically limit the setting of the preset energy efficiency, and those skilled in the art can freely set it as long as the value requirement of the preset energy efficiency is met, wherein the optimal value of α is 0.85.

[0071] Please continue reading Figure 1 As shown, the system also includes a correlation analysis module, which is connected to the energy efficiency monitoring module, and the correlation analysis module is used to analyze the abnormality of the power grid energy efficiency within the management period according to the analysis results of the power grid energy efficiency status within the management period, and is also used to construct the correlation coefficient between the power grid input power and the power grid energy efficiency according to the analysis results, and adjust the power distribution process of each power supply area in the next management period according to the correlation coefficient between the power grid input power and the power grid energy efficiency; it can be understood that in this embodiment, the setting of the management period is not specifically limited, and technical personnel in this field can set it freely, as long as the setting requirements of the management period are met, wherein the setting of the management period should be greater than the setting of the monitoring period, and the management period can be set to 30 days.

[0072] Specifically, the grid input power is the sum of the power distributed by the grid to each energy supply area.

[0073] See also Figure 3 As shown, the correlation analysis module includes:

[0074] An abnormality analysis unit is used to analyze the abnormality of the power grid energy efficiency within the management period according to the analysis result of the power grid energy efficiency state within the management period. If n1 / R≤u1, the abnormality analysis unit determines that the power grid energy efficiency of the current management period is normal; if n1 / R>u1, the abnormality analysis unit determines that the power grid energy efficiency of the current management period is abnormal; by summarizing the previous energy efficiency data of the power grid, reasonable power dispatching is made, system operation is standardized, and the efficiency of the entire energy supply area is improved;

[0075] Among them, n1 is the number of monitoring cycles in which the power grid energy efficiency status is low energy efficiency within the management cycle, R is the number of monitoring cycles within the management cycle, and u1 is the preset abnormality ratio.

[0076] It can be understood that the present embodiment does not specifically limit the setting of the preset abnormality ratio, and those skilled in the art can freely set it as long as the value requirement of the preset abnormality ratio is met, wherein the best value of u1 is 0.1.

[0077] Please continue reading Figure 3 As shown, the correlation analysis module also includes:

[0078] A correlation analysis unit is connected to the abnormality analysis unit. The correlation analysis unit is used to construct a correlation coefficient G between the grid input power and the grid energy efficiency according to the analysis result of the abnormality of the grid energy efficiency within the management period, so as to establish an intuitive and clear statistical relationship model, which provides an important quantitative basis for subsequent decision-making, making the synergistic relationship between power supply and energy efficiency under different circumstances clearer. Setting:

[0079] ;

[0080] Wherein, Pr is the input power of the grid in the rth monitoring period within the management period, and Nr is the grid energy efficiency in the rth monitoring period within the management period;

[0081] The correlation analysis unit adjusts the power distribution process of each energy supply area in the next management period according to the correlation coefficient between the grid input power and the grid energy efficiency, wherein:

[0082] If G<0, the correlation analysis unit sets the preset proportionality coefficient to η1, setting η1=η×{1-β×[3×G 2 -2×(-G) 3 ]};

[0083] If G=0, no adjustment is made;

[0084] If G>0, the correlation analysis unit sets the preset proportionality coefficient to η2, setting η2=η×{1+β×[3×G 2 -2×G 3]}, when η2≥η0, the value of η2 is η0, and η0 is the preset ratio threshold; the power distribution process is dynamically optimized by analyzing the results. For the case of G<0, the preset ratio coefficient can be automatically adjusted to deal with negative correlation events; and for the case of G>0, the power output capacity can be timely increased to meet the needs of a higher energy efficiency state;

[0085] Among them, β is the preset adjustment ratio.

[0086] It can be understood that the present embodiment does not specifically limit the setting of the preset adjustment ratio and the preset ratio threshold, and those skilled in the art can freely set them as long as the value requirements of the preset adjustment ratio and the preset ratio threshold are met, where the optimal value of β is 0.2, and the optimal value of η0 is 0.95.

[0087] Specifically, the input power of the power grid in the rth monitoring period in this embodiment is the sum of the power distribution of the power grid to each energy supply area in the rth monitoring period.

[0088] Please continue reading Figure 1 As shown, the system also includes a fluctuation analysis module, which is connected to the correlation analysis module, and the fluctuation analysis module is used to analyze the voltage fluctuation state according to the grid voltage collected during the management period, and optimize the adjustment process of the power distribution process of each energy supply area in the next management period according to the analysis result, wherein:

[0089] The fluctuation analysis module sets the fluctuation coefficient of the grid voltage to B, and sets:

[0090] ,

[0091] ;

[0092] Wherein, Vm is the mth grid voltage data collected in the management cycle, M is the number of grid voltage data collected in the management cycle, and VP is the average value of the number of grid voltages collected in the management cycle;

[0093] The fluctuation analysis module compares the fluctuation coefficient B of the grid voltage with the preset fluctuation coefficient B0, and analyzes the fluctuation state of the grid voltage according to the comparison result, and optimizes the adjustment process of the power distribution process of each energy supply area in the next management cycle according to the analysis result; if B≤B0, the fluctuation analysis module determines that the fluctuation state of the grid voltage in the current management cycle is a stable state and no optimization is performed; if B>B0, the fluctuation analysis module determines that the fluctuation state of the grid voltage in the current management cycle is an abnormal state, and when G>0, the preset adjustment ratio is set to β1, and β1=β×exp[-(B-B0)] is set; by analyzing the fluctuation state of the grid voltage, the problem of voltage instability can be discovered in time, and when the fluctuation state is abnormal, the power distribution strategy can be adjusted to ensure the irrigation effect of the energy supply area and enhance the system resilience.

[0094] It can be understood that the present embodiment does not specifically limit the setting of the preset fluctuation coefficient, and those skilled in the art can freely set it as long as the value requirement of the preset fluctuation coefficient is met, wherein the best value of B0 is 0.15.

[0095] See also Figure 4 As shown, it is a flow chart of the distributed power management method of this embodiment, and the method includes:

[0096] Step S1: Collecting energy supply area data and power grid data;

[0097] Step S2: analyzing the priority coefficient of each energy supply area according to the soil moisture, water pump flow rate and maximum power of each energy supply area collected during the monitoring period;

[0098] Step S3: Allocate power to each energy supply area according to the load demand of each energy supply area collected during the monitoring period and the analysis result of the priority coefficient of each energy supply area;

[0099] Step S4: Analyze the energy efficiency of the power grid according to the power distribution results of each energy supply area and the power grid output power during the monitoring period, and analyze the power grid energy efficiency status according to the analysis results;

[0100] Step S5: constructing the correlation coefficient between the grid input power and the grid energy efficiency according to the analysis result of the grid energy efficiency status in the management cycle, and adjusting the power distribution process of each energy supply area in the next management cycle;

[0101] Step S6: Analyze the voltage fluctuation state according to the grid voltage collected during the management period, and optimize the adjustment process of the power distribution process of each energy supply area in the next management period according to the analysis result.

[0102] Specifically, the distributed power management system and method described in this embodiment are applied in large-scale smart agricultural parks, such as greenhouses and planting bases. By deploying a variety of sensors to monitor data such as soil moisture and water flow in real time, precise scheduling is achieved in combination with the power distribution system to ensure the sustainability of agricultural production.

[0103] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the embodiments here. All obvious changes or modifications derived from the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. A distributed power management system, characterized in that: include: Data acquisition module, used to collect energy supply area data and power grid data; The priority analysis module is used to analyze the priority coefficient of each energy supply area according to the soil moisture, water pump flow and maximum power of each energy supply area collected during the monitoring period; The power distribution module is used to distribute power to each energy supply area according to the analysis results of the load demand of each energy supply area and the priority coefficient of each energy supply area collected during the monitoring period; Energy efficiency monitoring module, used to analyze the energy efficiency of the power grid according to the power distribution results of each energy supply area and the power grid output power during the monitoring period, and analyze the energy efficiency status of the power grid according to the analysis results; The correlation analysis module is used to construct the correlation coefficient between the grid input power and the grid energy efficiency according to the analysis results of the grid energy efficiency status within the management cycle, and adjust the power distribution process of each energy supply area in the next management cycle; The fluctuation analysis module is used to analyze the voltage fluctuation state according to the grid voltage collected during the management period, and optimize the adjustment process of the power distribution process of each energy supply area in the next management period according to the analysis results; The priority analysis module includes a soil moisture analysis unit, which is used to compare the soil moisture of each energy supply area with the preset humidity s0, and analyze the abnormality of the soil moisture according to the comparison result. The abnormality of the soil moisture includes normal and abnormal. If the soil moisture of the i-th energy supply area in the current monitoring period is abnormal, the humidity priority coefficient of the i-th energy supply area is set to Ysi1, and Ysi1=(s0-si) / s0 is set, si is the soil moisture of the i-th energy supply area in the current monitoring period; if the soil moisture of the i-th energy supply area in the current monitoring period is normal, the humidity priority coefficient of the i-th energy supply area is set to Ysi2, and Ysi2=0 is set; The priority analysis module also includes a load analysis unit, which is used to compare the collected maximum power of the water pumps in each energy supply area with the preset power threshold p0. If pi≤p0, the load analysis unit sets the load priority coefficient of the i-th energy supply area to Ypi1, and sets: Ypi1=0; if pi>p0, the load analysis unit sets the load priority coefficient of the i-th energy supply area to Ypi2, and sets: Ypi2=ln[5×(pi-p0) / p0+1] / ln6, where pi is the maximum power of the water pump in the i-th energy supply area; The priority analysis module also includes a flow analysis unit, which is used to compare the water pump flow of each energy supply area collected during the monitoring period with the preset flow L0, and analyze the water pump flow state according to the comparison result. The water pump flow state includes a normal state and a high flow state. If the water pump flow state of the i-th energy supply area in the current monitoring period is a normal state, the flow priority coefficient of the i-th energy supply area is set to YLi1, and the setting is: YLi1=0; if the water pump flow state of the i-th energy supply area in the current monitoring period is a high flow state, the flow priority coefficient of the i-th energy supply area is set to YLi2, and the setting is: YLi2=exp[3×(Li-L0) / L0-3], Li is the water pump flow of the i-th energy supply area; The priority analysis module also includes a priority analysis unit, which constructs a priority coefficient of each energy supply area according to the construction results of the humidity priority coefficient, the load priority coefficient and the flow priority coefficient of each energy supply area, and sets the priority coefficient of the ith energy supply area to YXi, and sets: YXi=x1×humidity priority coefficient of the ith energy supply area+x2×load priority coefficient of the ith energy supply area+x3×flow priority coefficient of the ith energy supply area, x1 is the humidity weight, x2 is the load weight, and x3 is the flow weight; The correlation analysis module includes a correlation analysis unit, which is used to construct a correlation coefficient G between the grid input power and the grid energy efficiency according to the analysis result of the abnormality of the grid energy efficiency within the management period, and set: R is the number of monitoring cycles within the management cycle, Pr is the input power of the grid in the rth monitoring cycle within the management cycle, and Nr is the grid energy efficiency in the rth monitoring cycle within the management cycle; The correlation analysis unit adjusts the power distribution process of each energy supply area in the next management period according to the correlation coefficient between the grid input power and the grid energy efficiency. If G < 0, the correlation analysis unit sets the preset proportional coefficient to η1, setting η1 = η×{1-β×[3×G 2 -2×(-G) 3 ]}; if G = 0, no adjustment is performed; if G > 0, the correlation analysis unit sets the preset proportional coefficient to η2, setting η2 = η × {1 + β × [3 × G 2 -2×G 3 ]}, β is the preset adjustment ratio, and η is the preset proportional coefficient.

2. The distributed power management system according to claim 1, characterized in that: The power distribution module is used to analyze the abnormality of load demand based on the load demand of each energy supply area collected during the monitoring period. The abnormality of load demand includes normal and abnormal. If the load demand in the current monitoring period is normal, the power distribution of the i-th energy supply area is set to Di1; if the load demand in the current monitoring period is abnormal, the power distribution of the i-th energy supply area is set to Di2.

3. The distributed power management system according to claim 2, characterized in that: The energy efficiency monitoring module is used to analyze the energy efficiency N of the power grid according to the power distribution results of each power supply area during the monitoring period and the power grid output power, and compare the energy efficiency N of the power grid with the preset energy efficiency α to analyze the energy efficiency status of the power grid, which includes normal and low energy efficiency.

4. The distributed power management system according to claim 3, characterized in that: The correlation analysis module includes an abnormality analysis unit, which is used to analyze the abnormality of the power grid energy efficiency within the management period according to the analysis result of the power grid energy efficiency state within the management period, and the abnormality of the power grid energy efficiency includes normal and abnormal.

5. The distributed power management system according to claim 4, characterized in that: The fluctuation analysis module is used to construct a fluctuation coefficient of the grid voltage according to the grid voltage collected during the management period and set it to B, and compare the fluctuation coefficient B of the grid voltage with the preset fluctuation coefficient B0, and analyze the fluctuation state of the grid voltage according to the comparison result. The fluctuation state of the grid voltage includes a stable state and an abnormal state. If the fluctuation state of the grid voltage in the current management period is an abnormal state, when G>0, the preset adjustment ratio is set to β1.

6. A distributed power management method, applied to the distributed power management system according to any one of claims 1 to 5, characterized in that: include: Step S1: Collecting energy supply area data and power grid data; Step S2: analyzing the priority coefficient of each energy supply area according to the soil moisture, water pump flow rate and maximum power of each energy supply area collected during the monitoring period; Step S3: Allocate power to each energy supply area according to the load demand of each energy supply area collected during the monitoring period and the analysis result of the priority coefficient of each energy supply area; Step S4: Analyze the energy efficiency of the power grid according to the power distribution results of each energy supply area and the power grid output power during the monitoring period, and analyze the power grid energy efficiency status according to the analysis results; Step S5: constructing the correlation coefficient between the grid input power and the grid energy efficiency according to the analysis result of the grid energy efficiency status in the management cycle, and adjusting the power distribution process of each energy supply area in the next management cycle; Step S6: Analyze the voltage fluctuation state according to the grid voltage collected during the management period, and optimize the adjustment process of the power distribution process of each energy supply area in the next management period according to the analysis result.

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