Distributed photovoltaic consumption capability improving method and system based on load flow calculation

Abstract

The invention relates to a distributed photovoltaic consumption capability improving method and system which can realize effective regulation and control of distributed photovoltaic output and optimal configuration of power grid resources and improve the consumption level of distributed photovoltaic, and the method comprises the following steps: data acquisition and calculation: periodically acquiring power grid operation parameters; generating a line system coloring topological graph on the basis of a system diagram model constructed by a power grid frame, and determining a line power flow trend; displaying the collected data and the calculation result in the corresponding trend positions in the coloring topological graph of the line system by using different colors; constructing an optimal scheduling model of distributed photovoltaic, a power grid tie line and a power grid operation mode, and providing a power grid operation mode scheduling strategy; power grid operation parameters in the distributed photovoltaic absorption process are monitored in real time, and the line power flow display color during distributed photovoltaic power generation is adjusted; when reverse overload of the transformer occurs, the reverse overload is displayed in a coloring topological graph of a line system and a prompt tone is given out, a scheduling strategy is adjusted in time, and stable operation of the system is ensured.

Description

Technical Field

[0001] This invention belongs to the field of power system operation and control technology, specifically relating to a method and system for improving the distributed photovoltaic absorption capacity based on power flow calculation. Background Technology

[0002] The contradictions between the surge in installed capacity and the insufficient adaptation of the distribution network, the imperfect market mechanism, and the lagging development of energy storage are becoming increasingly prominent. The phenomenon of "curtailment" in some areas has become the core bottleneck restricting its sustainable development. Furthermore, the output of distributed photovoltaic power is highly intermittent and volatile, and is significantly affected by natural factors such as light intensity, temperature, and weather. This has led to challenges to the stable operation of the power grid after its large-scale grid connection, and the problem of insufficient photovoltaic absorption capacity is becoming increasingly prominent.

[0003] Currently, distributed photovoltaic (PV) power consumption faces the following main problems: First, PV output fluctuates greatly, making it difficult for the distribution network to balance active power in real time. Second, the distribution network has limited regulation capabilities. The topology and equipment parameter design of traditional distribution networks do not fully consider the situation of large-scale distributed PV access. The active power generated by distributed PV cannot be consumed at the same level, leading to problems such as voltage exceeding limits and backflow in some areas. During backflow, the copper loss of the main transformer increases, causing certain losses. At peak backflow, in order to ensure grid frequency security, light and wind curtailment occurs, resulting in a large loss of distributed PV power generation. Third, there is insufficient source-load coordination. There is a lack of effective coordination mechanism between user-side electricity load and PV output, making it impossible to fully utilize user-side flexibility resources to smooth out PV fluctuations. Summary of the Invention

[0004] The technical problem to be solved by this invention is to overcome the defects of poor grid stability and insufficient distributed photovoltaic power absorption capacity caused by existing technologies. It provides a method and system for improving the distributed photovoltaic power absorption capacity, which can realize intelligent power flow calculation, intuitively display power flow direction, and assist regulators in optimizing grid operation mode. This enables effective regulation of distributed photovoltaic power output and optimized allocation of grid resources, thereby improving the absorption level of distributed photovoltaic power.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A method for improving the distributed photovoltaic (PV) grid integration capacity based on power flow calculation, comprising the following steps: S1. Data Acquisition and Calculation: Periodically collect power grid operating parameters, including real-time current values ​​of primary distributed photovoltaic power stations, system node voltages, real-time current values ​​of system lines, and bus voltage values; calculate the active power load P of the lines. L Reactive load Q L Distributed photovoltaic active power output P and reactive power output Q; S2. Based on the system diagram model of the power grid construction, a colored topology map of the line system is generated, with red representing load absorption and green representing the power flow of distributed photovoltaic power generation, to determine the direction of power flow in the line system. The collected data and calculation results are displayed in the corresponding power flow direction position in the colored topology map of the line system using the corresponding color. S3. With the goal of maximizing distributed photovoltaic (PV) absorption and minimizing grid losses, considering system node voltage upper and lower limits, line power flow limits, reverse overload capacity constraints, and adjustable load adjustment range constraints, an optimized scheduling model for distributed PV, grid interconnection lines, and grid operation modes is obtained. By comparing and analyzing line active power load and distributed PV active power output, a grid operation mode scheduling strategy is provided. S4. Real-time monitoring of grid operation parameters during distributed photovoltaic (PV) integration. The line power flow is displayed in green when PV is generating electricity and in red when the load is being absorbed. When PV is fed back, the line power flow is displayed in purple. When a transformer reverse overload occurs, an overload signal will pop up in the line system color topology diagram, displaying the overload value and the normal limit, accompanied by a prompt sound. When the above situations occur, the abnormal information will be fed back to the optimization scheduling model to adjust the scheduling strategy in a timely manner and ensure the stable operation of the system.

[0006] Furthermore, the active power load P of the line L The calculation formula is:

[0007] Among them U L I is the system line voltage. L For system line current, The power factor of the system; Line power generation load calculation: ; Among them, I fd P represents the generating load current of the line; e For equipment capacity; K d This is the demand factor, i.e., the demand factor for the group of electrical equipment. Represented as average power factor; U N Rated voltage; Line reactive load Q L The calculation formula is: ; Among them U L I is the system line voltage. L For system line current, This is the sine value of the system power factor angle; Internet load calculation:

[0008] Among them, I sw Represented as the grid load current of the line; I zy This is expressed as the station load current of the clean energy station; Busbar load calculation:

[0009] Among them, I m Let I be the bus load current of a 66 kV busbar. This system has N lines, named 1, 2, 3, ..., n. n This represents the total load current of line n in the system, where n is the line name; The formula for calculating the active power output P of distributed photovoltaic power is:

[0010] Among them U pv I is the line voltage on the grid-connected side of the photovoltaic system. pv This refers to the line current on the grid-connected side of the photovoltaic system. The power factor of the photovoltaic system; The formula for calculating the reactive power output Q of distributed photovoltaic power is:

[0011] Among them U pv I is the line voltage on the grid-connected side of the photovoltaic system. pv This refers to the line current on the grid-connected side of the photovoltaic system. This is the sine value of the power factor angle of the photovoltaic system.

[0012] Furthermore, the upper and lower limit constraints of the system node voltage are:

[0013] Where U is the system node voltage, U min U is the minimum system voltage. max Maximum system voltage; The conditions for the aforementioned power flow limit agreement are:

[0014] This represents the minimum permissible power flow for line l; This represents the maximum permissible power flow for line l; This refers to the actual power flow of line l. The reverse overload capacity constraint condition is:

[0015] Where S is the actual reverse power flow capacity of the transformer, S eThis refers to the rated capacity of the transformer.

[0016] Furthermore, the grid operation mode dispatch strategy is as follows: when the photovoltaic output exceeds the load demand, priority is given to the absorption of distributed photovoltaic power within the system by adjusting the grid operation mode at the power receiving end of the substation; when the photovoltaic output still exceeds the load demand, if the distributed photovoltaic power has other power supply lines, the distributed photovoltaic power is transmitted to the 66 kV system of other 220 kV substations; if there are no other power supply lines, the distributed photovoltaic power is further absorbed by controlling the closing of the 66 kV bus tie switch; when the photovoltaic output is less than the load demand, no adjustment is made, and the load change is monitored in real time.

[0017] Furthermore, the power grid operating parameters are collected every 5 minutes via NB-IoT communication.

[0018] A distributed photovoltaic (PV) grid integration capacity enhancement system based on power flow calculation includes: The data acquisition and calculation module periodically collects power grid operating parameters and calculates the active power load P of the lines. L Reactive load Q L Distributed photovoltaic active power output P and reactive power output Q; The line system diagram topology coloring module, based on the system diagram model of the power grid construction, uses red to represent load absorption and green to represent the power flow of distributed photovoltaic power generation, generating a line system coloring topology diagram and determining the direction of line power flow; The optimization scheduling module aims to maximize distributed photovoltaic (PV) absorption and minimize grid losses. It considers system node voltage limits, line power flow limits, and reverse overload capacity constraints to obtain an optimized scheduling model for distributed PV, adjustable loads, grid interconnections, and grid operation modes. By comparing and analyzing line active power load and distributed PV active power output, it provides grid operation mode scheduling strategies. The monitoring and early warning module monitors the grid operation parameters in real time during the distributed photovoltaic (PV) integration process and displays the corresponding colors in the line power flow during distributed PV power generation. When a transformer reverse overload occurs, an overload signal will pop up in the topology diagram and display the overload value and normal limit, accompanied by an alarm sound. When the above situations occur, the abnormal information will be fed back to the optimization scheduling model to adjust the scheduling strategy in a timely manner and ensure the stable operation of the system.

[0019] Compared with the prior art, the present invention has the following beneficial effects: This invention ensures the scientific nature of dispatching decisions, effectively mitigates fluctuations in distributed photovoltaic (PV) output, improves the efficiency of distributed PV power flow calculation, enhances the absorption capacity of distributed PV, provides a more intuitive display of power flow trends, assists dispatchers in optimizing grid operation, and achieves effective control over distributed PV output and optimized allocation of grid resources, thereby improving the absorption level of distributed PV. By fully utilizing the flexibility of energy storage systems and adjustable loads, it optimizes the allocation of distribution network resources, significantly enhances the absorption capacity of distributed PV, and ensures the safe and stable operation of the power grid. Attached Figure Description

[0020] Figure 1 This is a flowchart of the present invention; Figure 2 This is a system structure diagram of the present invention; Figure 3 This is a topology coloring model of the circuit system diagram in an embodiment of the present invention. Detailed Implementation

[0021] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments: like Figure 1 As shown, a method for improving the distributed photovoltaic (PV) grid integration capacity based on power flow calculation is described, with the following steps: S1. Data Acquisition and Calculation: Periodically collect power grid operating parameters, including real-time current values ​​of primary distributed photovoltaic power stations, system node voltages, real-time current values ​​of system lines, and bus voltage values; calculate the active power load P of the lines. L Reactive load Q L Distributed photovoltaic active power output P and reactive power output Q; S2. Based on the system diagram model of the power grid construction, a colored topology map of the line system is generated, with red representing load absorption and green representing the power flow of distributed photovoltaic power generation, to determine the direction of power flow in the line system. The collected data and calculation results are displayed in the corresponding power flow direction position in the colored topology map of the line system using the corresponding color. S3. With the goal of maximizing distributed photovoltaic (PV) absorption and minimizing grid losses, considering system node voltage limits, line power flow limits, reverse overload capacity constraints, and adjustable load regulation range constraints, an optimized scheduling model for distributed PV, grid interconnections, and grid operation modes is obtained. By comparing and analyzing line active power load and distributed PV active power output, a grid operation mode scheduling strategy is provided: When PV output exceeds load demand, priority is given to PV absorption within the system by adjusting the grid operation mode at the substation receiving end; when PV output still exceeds load demand, if distributed PV has other power supply lines, the distributed PV power is transmitted to other 220 kV substations' 66 kV systems; if there are no other power supply lines, distributed PV absorption is further achieved by controlling the closing of the 66 kV bus tie switch; when PV output is less than load demand, no adjustment is made, and load changes are monitored in real time. S4. Real-time monitoring of grid operation parameters during distributed photovoltaic (PV) integration. The line power flow is displayed in green when PV is generating electricity and in red when the load is being absorbed. When PV is fed back, the line power flow is displayed in purple. When a transformer reverse overload occurs, an overload signal will pop up in the line system color topology diagram, displaying the overload value and the normal limit, accompanied by a prompt sound. When the above situations occur, the abnormal information will be fed back to the optimization scheduling model to adjust the scheduling strategy in a timely manner and ensure the stable operation of the system.

[0022] Furthermore, the active power load P of the line L The calculation formula is: Line active load P L The calculation formula is: ; Among them U L I is the system line voltage. L For system line current, The power factor of the system; Line power generation load calculation: ; Among them, I fd P represents the generating load current of the line; e For equipment capacity; K d This is the demand factor, i.e., the demand factor for the group of electrical equipment. Represented as average power factor; U N Rated voltage; Line reactive load Q L The calculation formula is: ; Among them U L I is the system line voltage.L For system line current, This is the sine value of the system power factor angle; Internet load calculation: ; Among them, I sw Represented as the grid load current of the line; I zy This is expressed as the station load current of the clean energy station; Busbar load calculation: ; Among them, I m Let I be the bus load current of a 66 kV busbar. This system has N lines, named 1, 2, 3, ..., n. n This represents the total load current of line n in the system, where n is the line name; The formula for calculating the active power output P of distributed photovoltaic power is: ; Among them U pv I is the line voltage on the grid-connected side of the photovoltaic system. pv This refers to the line current on the grid-connected side of the photovoltaic system. The power factor of the photovoltaic system; The formula for calculating the reactive power output Q of distributed photovoltaic power is:

[0023] Among them U pv I is the line voltage on the grid-connected side of the photovoltaic system. pv This refers to the line current on the grid-connected side of the photovoltaic system. This is the sine value of the power factor angle of the photovoltaic system.

[0024] Furthermore, the upper and lower limit constraints of the system node voltage are: ; Where U is the system node voltage, U min U is the minimum system voltage. max Maximum system voltage; The conditions for the aforementioned power flow limit agreement are: ; This represents the minimum permissible power flow for line l; This represents the maximum permissible power flow for line l; This refers to the actual power flow of line l. The reverse overload capacity constraint condition is: ; Where S is the actual reverse power flow capacity of the transformer, S e This refers to the rated capacity of the transformer.

[0025] Furthermore, the power grid operating parameters are collected every 5 minutes via NB-IoT communication.

[0026] like Figure 2 As shown, a distributed photovoltaic (PV) grid integration capacity enhancement system based on power flow calculation includes: The data acquisition and calculation module periodically collects power grid operating parameters and calculates the active power load P of the lines. L Reactive load Q L Distributed photovoltaic active power output P and reactive power output Q; The line system diagram topology coloring module, based on the system diagram model of the power grid construction, uses red to represent load absorption and green to represent the power flow of distributed photovoltaic power generation, generating a line system coloring topology diagram and determining the direction of line power flow; The optimization scheduling module aims to maximize the absorption of distributed photovoltaic power and minimize grid losses. It considers the upper and lower limits of system node voltage, line power flow limits, and reverse overload capacity constraints to obtain an optimized scheduling model for distributed photovoltaic power, adjustable loads, grid interconnections, and grid operation modes. By comparing and analyzing the active power load of lines and the active power output of distributed photovoltaic power, an optimized scheduling strategy is obtained. The monitoring and early warning module monitors the grid operation parameters in real time during the distributed photovoltaic (PV) integration process and displays the corresponding colors in the line power flow during distributed PV power generation. When a transformer reverse overload occurs, an overload signal will pop up in the topology diagram and display the overload value and normal limit, accompanied by an alarm sound. When the above situations occur, the abnormal information will be fed back to the optimization scheduling model to adjust the scheduling strategy in a timely manner and ensure the stable operation of the system.

[0027] Figure 3The diagram shows the 66kV system busbars of a 220kV substation. Substation 1 is connected to both 66kV busbars I and II, with two main transformers absorbing loads of 3.0MW and 2.0MW respectively. Substation 2 is connected to 66kV busbar II, absorbing 2.0MW of load. Substation 3 is connected to 66kV busbar I, absorbing 3.0MW of load. Photovoltaic power stations 1 and 2 are connected to 66kV busbar II, generating 3.0MW and 8MW respectively. The power flow indicator is green when distributed photovoltaic power generation is in operation, red when load is absorbed, and purple when distributed photovoltaic power is fed back. Since the power generation of photovoltaic power station 2 exceeds the load absorbed by substation 2, 6.0MW of distributed photovoltaic power is fed back to the 66kV busbar II. Additionally, photovoltaic power station 1 generates 3.0MW, which can be absorbed by the #2 main transformer of substation 1. Therefore, the 66kV busbar II will feed back 7.0MW of power to the main transformer. At this point, priority is given to distributed photovoltaic (PV) consumption within the system. By adjusting the grid operation mode at the receiving end of the substation, the power supply line of substation 3 is converted to receive PV power from substation 2 for distributed PV consumption. If the PV output is still greater than the load demand, then the PV power supply of substation 2 is converted to the 66 kV system of the 220 kV substation. If there are no other power supply lines, then distributed PV consumption is further achieved by controlling the closing of the 66 kV bus tie switch.

Claims

1. A method for improving distributed photovoltaic power consumption capacity based on power flow calculation, characterized by the steps of As follows: S1, data acquisition and calculation, periodically acquiring power grid operation parameters, the power grid operation parameters including real-time current value of primary distributed photovoltaic power station, system node voltage, system line real-time current value and bus voltage value, calculating line active load P L , reactive load Q L , distributed photovoltaic active output P and reactive output Q; S2, based on the system diagram model of the grid framework construction, the load consumption is represented by red color and the distributed photovoltaic power generation power flow is represented by green color, a line system coloring topological graph is generated to determine the line power flow direction; the collected data and the calculation results are displayed in the corresponding power flow direction position of the line system coloring topological graph by using corresponding colors; S3, taking the maximum distributed photovoltaic consumption and the minimum grid loss as the target, considering the system node voltage upper and lower limit, the line power flow limit, the reverse overload capacity constraint and the adjustable load adjustment range constraint, an optimal scheduling model of the distributed photovoltaic, the grid tie line and the grid operation mode is obtained; by comparing and analyzing the line active load and the distributed photovoltaic active output, a grid operation mode scheduling strategy is provided; S4, real-time monitoring of the grid operation parameters in the distributed photovoltaic consumption process, the line power flow is displayed as green color when the distributed photovoltaic generates power, and as red color when the load is consumed, and the line power flow is displayed as purple color when the distributed photovoltaic is sent back; when the transformer is reversely overloaded, an overload signal will be popped up in the line system coloring topological graph and the overload value and the normal limit value are displayed, accompanied by a prompt sound; when the above-mentioned situations occur, the abnormal information is fed back to the optimal scheduling model, and the scheduling strategy is adjusted in time to ensure the stable operation of the system.

2. The method of claim 1, wherein the method is characterized in that, Line active load P L The calculation formula is: ； where U L is the system line voltage, I L is the system line current, is the power factor of the system; Line power generation load calculation: where I fd is the generating load current of the line; P e is the device capacity; K d is the need factor, i.e. the need factor of the group of electrical devices; denotes the average power factor; U N is the rated voltage; Line reactive load Q L The formula for calculating Q is: where U L is the system line voltage, I L is the system line current, is the sine of the system power factor angle; Line on-grid load calculation: wherein, I sw represents the on-grid load current of the line; I zy represents the station load current of the clean energy station; Bus load calculation: wherein I m is the bus load current of a 66 kV bus, the system has N lines, the names of which are 1, 2, 3,..., n, I n represents the total line load current of line n in the system, n is the line name; The calculation formula of the distributed photovoltaic active output P is: where U pv is the line voltage at the grid-connection side of the photovoltaic system, I pv is the line current at the grid-connection side of the photovoltaic system, is the power factor of the photovoltaic system; The calculation formula of the distributed photovoltaic reactive output Q is: where U pv is the line voltage at the grid-connection side of the photovoltaic system, I pv is the line current at the grid-connection side of the photovoltaic system, is the sine value of the power factor angle of the photovoltaic system.

3. The method of claim 1, wherein the method is characterized by, The system node voltage upper and lower limit constraint condition is: where U is the system node voltage, U min is the system voltage minimum, U max is the system voltage maximum; The line power flow limit condition is: is the minimum allowed power flow for line l; is the maximum allowed power flow for line l; is the actual operating power flow for line l; The reverse overload capacity constraint condition is: where S is the actual reverse flow capacity of the transformer, S e is the rated capacity of the transformer.

4. The method of claim 1, wherein the method is characterized by, The grid operation mode scheduling strategy is: when the photovoltaic output is greater than the load demand, the distributed photovoltaic consumption in the system is preferentially carried out, the grid operation mode of the power receiving end of the transformer substation is adjusted, and the distributed photovoltaic consumption is carried out; when the photovoltaic output is still greater than the load demand, if the distributed photovoltaic has other power lines, the distributed photovoltaic power is sent to other 220kV transformer substations 66kV system, if there is no other power line, the distributed photovoltaic consumption is further carried out through the control of 66kV bus tie switch mode; when the photovoltaic output is less than the load demand, no adjustment is made, and the load change situation is real-time monitored.

5. The method of claim 1, wherein the method is characterized by, The collection of the grid operation parameters is collected through the NB-IoT communication mode every 5 minutes.

6. The system for improving the distributed photovoltaic power consumption capacity based on the power flow calculation according to any one of claims 1-5, characterized in that, It comprises: A data acquisition and calculation module periodically acquires power grid operation parameters and calculates line active load P L , reactive load Q L , and active output P and reactive output Q of the distributed photovoltaic power A line system diagram topological coloring module, based on the system diagram model of the grid framework construction, the load consumption is represented by red color and the distributed photovoltaic power generation power flow is represented by green color, a line system coloring topological graph is generated to determine the line power flow direction; An optimal scheduling module, taking the maximum distributed photovoltaic consumption and the minimum grid loss as the target, considering the system node voltage upper and lower limit, the line power flow limit, the reverse overload capacity constraint condition, an optimal scheduling model of the distributed photovoltaic, the adjustable load, the grid tie line and the grid operation mode is obtained; by comparing and analyzing the line active load and the distributed photovoltaic active output, a grid operation mode scheduling strategy is provided; The monitoring and early warning module monitors the power grid operation parameters in real time during the distributed photovoltaic consumption process and displays corresponding colors in the line power flow during the distributed photovoltaic power generation. When the transformer reverse overload occurs, the overload signal will pop up in the topology diagram and display the overload value and the normal limit value, accompanied by a prompt sound. When the above situation occurs, the abnormal information is fed back to the optimization scheduling model, the scheduling strategy is adjusted in time, and the stable operation of the system is ensured.

Images