Small hydropower dynamic compensation peak shaving control method for distributed photovoltaic rich feeder

Abstract

The application discloses a kind of small hydropower dynamic compensation peak shaving control methods for distributed photovoltaic enrichment feeder, comprising: predicting the photovoltaic output of distributed photovoltaic enrichment feeder next day each time point, feeder load small hydropower inflow flow;With small hydropower reference power generation power, calculate the photovoltaic power of each time point of feeder and load cut-off power, calculate small hydropower dynamic compensation price, establish small hydropower power generation income model;Calculate the feasible output interval of each time point next day;Small hydropower optimization operation model is constructed, and the small hydropower optimal output plan of each time point next day is obtained by solving small hydropower optimization operation model;Based on the actual water level of current time and small hydropower optimal output plan, calculate the maximum and minimum of water level of each time point subsequently;When water level maximum or minimum exceeds preset safety threshold range, trigger adaptive correction mechanism.The application has the advantages of realizing small hydropower water resource efficient utilization and the like.

Description

Technical Field

[0001] This invention mainly relates to the field of power distribution network operation and control technology, specifically to a dynamic compensation and peak-shaving control method for small hydropower stations with distributed photovoltaic enrichment feeders. Background Technology

[0002] With the widespread adoption of distributed photovoltaic (PV) systems, numerous distributed PV units are densely connected to distribution network feeders, forming distributed PV-rich feeders. These feeders exhibit significant intraday operational contradictions: during the day, PV output is high, far exceeding the local load demand of the feeder, leading to difficulties in PV integration and backflow issues; at night, PV output disappears, and coupled with peak residential and industrial loads, the feeders are prone to severe overload, seriously affecting the safe and stable operation of the distribution network.

[0003] Small hydropower, as a common adjustable power source in distribution networks, has the advantages of fast response and flexible adjustment, and is an important support for resolving operational conflicts in photovoltaic-rich feeders. However, currently, small hydropower plants operate under a fixed electricity price model, with an operational strategy of "generating power whenever water is available," without linkage with the operating status of distribution network feeders, thus failing to realize their peak-shaving potential. Therefore, there is an urgent need for a small hydropower control method that can balance photovoltaic absorption, feeder peak shaving, and water resource protection. This method should guide small hydropower plants to dynamically adjust their output through a scientific compensation mechanism, solving the operational pain points of distributed photovoltaic-rich feeders, while avoiding water waste and improving the economic efficiency and safety of distribution network operation. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention provides a dynamic compensation and peak-shaving control method for small hydropower stations oriented towards distributed photovoltaic enrichment feeders, which enables efficient utilization of water resources in small hydropower stations.

[0005] To solve the above-mentioned technical problems, the technical solution proposed by this invention is as follows: A dynamic compensation and peak-shaving control method for small hydropower plants with distributed photovoltaic enrichment feeders includes the following steps: S1. Based on historical data and weather forecast information, predict the photovoltaic output of the distributed photovoltaic enrichment feeder at various time points the following day. Feeder load Small hydropower water flow Combined with the benchmark power generation capacity of small hydropower and feeder capacity Calculate the photovoltaic curtailment power at each time point of the feeder. and load shedding power ; S2. Based on photovoltaic curtailment power and load shedding power Combined with the fixed on-grid electricity price for small hydropower Unit power load shedding cost Unit distributed photovoltaic curtailment cost Calculate the dynamic compensation price for small hydropower. Establish a price that takes into account dynamic compensation. Small hydropower generation revenue model Small hydropower generation revenue model The output is the actual power generation of small hydropower. The corresponding electricity generation revenue; S3. Based on predicted small hydropower inflow Reservoir water level constraints and ecological flow Considering the technical constraints of the generating units, calculate the feasible output range for each time point on the following day. ; S4. Small hydropower generation revenue model The optimization objective is to maximize the cumulative value at each time point on the following day, within a feasible output range. As a decision variable Given the constraints on the range of values, an optimal operation model for small hydropower is constructed, and the optimal power output plan for small hydropower at each time point on the following day is obtained by solving the optimal operation model for small hydropower. ; S5. In real-time operation, based on the actual water level at the current moment. Optimal output plan for small hydropower Combined with the water flow of small hydropower stations Calculate the maximum water level at each subsequent time point. and minimum value ; When the water level reaches its maximum value or minimum value When the value exceeds the preset safety threshold, an adaptive correction mechanism is triggered to adjust the profit model. The objective is to maximize the cumulative value during the remaining time period, within the feasible output range. Under constraints, a revised output plan is re-solved for subsequent time points, replacing the optimal output plan. The subsequent part will enable dynamic and coordinated adjustment of small hydropower output.

[0006] Preferably, in step S1, the photovoltaic curtailment power... and load shedding power The calculation formula is:

[0007] .

[0008] Preferably, in step S2, the price is dynamically compensated. Specifically:

[0009] In the formula, and This is the preset compensation coefficient.

[0010] Preferably, in step S2, the actual power generation revenue model of small hydropower... Specifically: .

[0011] Preferably, in step S3, the lower limit of the output range Specifically:

[0012] in, The density of water, It is the acceleration due to gravity. This is the current water level. It refers to the power generation efficiency of the water turbine. It is ecological flow. This is to prevent the water level from exceeding the warning level. Minimum discharge flow rate, It is the minimum technical output; Upper limit of output range Specifically:

[0013] in, This is to prevent the water level from falling below the dead water level. Maximum discharge flow rate; It represents the greatest technological contribution.

[0014] Preferably, the maximum discharge flow rate and minimum discharge flow The constraints are:

[0015]

[0016]

[0017] In the formula, The area corresponding to the water level; for The actual discharge flow at any given moment; for The water flow rate at any given time; The unit time interval.

[0018] Preferably, the maximum water level in step S5 and minimum value The calculation formula is:

[0019]

[0020] for The actual water level at that moment; For a point in time.

[0021] Preferably, in step S5, when the water level reaches its maximum value... or minimum value When the preset safety threshold is exceeded, the adaptive correction mechanism is triggered as follows: Set adaptive correction trigger conditions:

[0022] In the formula, To adaptively correct the trigger flag, The set safety factor; like This indicates that the water level may exceed the limit during the remaining period, triggering adaptive correction.

[0023] The present invention also discloses a computer-readable storage medium having a computer program stored thereon, the computer program performing the steps of the method described above when run by a processor.

[0024] This invention further discloses a dynamic compensation and peak-shaving control system for small hydropower plants with distributed photovoltaic enrichment feeders, comprising a memory and a processor connected to each other. The memory stores a computer program, which executes the steps of the method described above when run by the processor.

[0025] Compared with the prior art, the advantages of the present invention are as follows: This invention aims to address the challenges of daytime photovoltaic (PV) absorption and nighttime overload in distributed photovoltaic (PV) feeders during peak load periods. First, it predicts the feeder's operating status at 9:00 AM the following day and calculates PV curtailment and load shedding power when small hydropower plants do not implement peak-shaving control. Second, it determines the dynamic compensation price for small hydropower peak shaving and establishes a small hydropower revenue model. Then, based on predicted inflow data, reservoir water level constraints, ecological flow requirements, and unit technical constraints, it determines the feasible output range for small hydropower plants at 9:00 AM the following day. Based on this, it formulates a power output plan for the following day. Finally, during real-time operation, it adaptively modifies the subsequent power output plan, considering water level safety margins, to ensure water level safety. This invention achieves dynamic synergy between PV absorption, feeder peak shaving, efficient water resource utilization, and reservoir safety through optimized small hydropower control, demonstrating strong practicality and high feasibility.

[0026] This invention is applicable to distribution network feeders with dense distributed photovoltaic (PV) grids, solving the problems of difficulty in absorbing PV power during peak PV generation periods and overloading of feeders during nighttime peak load periods, while also enabling efficient utilization of small hydropower water resources. Attached Figure Description

[0027] Figure 1 This is a flowchart of a small hydropower dynamic compensation and peak-shaving control method for distributed photovoltaic enriched feeders, according to an embodiment of the present invention. Detailed Implementation

[0028] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0029] like Figure 1 As shown in the figure, the dynamic compensation and peak-shaving control method for small hydropower stations with distributed photovoltaic enrichment feeders provided by this invention includes the following steps: S1. Based on historical data (such as photovoltaic output and load curves for the same period in the past week) and meteorological forecast information (such as the next day's radiance and temperature), predict the photovoltaic output of the distributed photovoltaic enrichment feeder at 96 points the next day. Feeder load Small hydropower water flow Among them, 96 points the next day refers to 96 discrete moments obtained by dividing a 24-hour day into 15-minute intervals. ; Combined with the benchmark power generation of small hydropower Calculate the photovoltaic curtailment power at each time point of the feeder. and load shedding power :

[0030]

[0031] In the formula, It refers to the feeder capacity.

[0032] S2. Based on photovoltaic curtailment power and load shedding power Calculate the dynamic compensation price for small hydropower. Establish a small hydropower generation revenue model that considers dynamic compensation.

[0033] Among them, dynamic compensation price It is based on the fixed electricity price of small hydropower, guiding the adjustment of small hydropower output according to the feeder operation status at different times; among which, dynamic compensation price Specifically:

[0034] In the formula, and These are the unit power load cut-off cost and the unit distributed photovoltaic curtailment cost, respectively. and This is the preset compensation coefficient.

[0035] Based on the aforementioned dynamic compensation price, a model for the actual power generation revenue of small hydropower is established, specifically: when photovoltaic power is curtailed (i.e.... Small hydropower plants receive compensation for the portion of their actual power generation that is less than the benchmark power generation capacity; when the load is cut off (i.e. The portion of small hydropower generation exceeding the benchmark generation capacity is compensated, specifically as follows:

[0036] In the formula, This refers to the actual power generation capacity of small hydropower stations. It is a fixed on-grid electricity price for small hydropower.

[0037] S3. Based on the predicted inflow data of small hydropower stations, reservoir water level constraints, ecological flow requirements, and unit technical constraints, calculate the feasible output range at 96:00 the following day. ; Among them, the lower limit of the power output range The critical power generation capacity to meet ecological flow, minimum technical output, and reservoir capacity safety is as follows:

[0038] In the formula, The density of water, It is the acceleration due to gravity. This is the current water level. It refers to the power generation efficiency of the water turbine. It is ecological flow. This is to prevent the water level from exceeding the warning level. Minimum discharge flow rate, It is the minimum technical output.

[0039] Upper limit of output range To meet maximum technical output and dead water level The constrained critical power generation capacity is:

[0040] In the formula, This is to prevent the water level from falling below the dead water level. Maximum discharge flow rate; It represents the greatest technological contribution.

[0041] The feasible discharge flow rate needs to meet the constraints of maximum and minimum discharge capacity, namely:

[0042]

[0043]

[0044] In the formula, This represents the area corresponding to the water level.

[0045] S4. With the goal of maximizing the revenue from small hydropower generation, establish an optimized operation model for small hydropower and optimize the output plan for 96 points the following day, namely:

[0046] S5. An adaptive correction mechanism based on water level safety margin: when the water level is in a dangerous range, the power output plan is dynamically fine-tuned according to the water level deviation. Under normal circumstances, no correction is triggered, thus achieving dynamic coordination of power output in different time periods.

[0047] Specifically, based on the actual water level at the current moment Small hydropower output plan and water inflow forecast Calculate the maximum water level for all subsequent times. and minimum value ,Right now:

[0048]

[0049] To prevent the water level from exceeding the warning level Or below the dead water level Set the adaptive correction trigger condition:

[0050] In the formula, To adaptively adjust the trigger flag; To set the safety factor, .

[0051] like This indicates that the water level may exceed the limit during the remaining period, triggering an adaptive correction. The correction method is: the actual water level at previous times. As the initial state, with the profit model exist The objective is to maximize the cumulative value up to time 96, within the feasible output range. To constrain this, we need to recalculate the output plan for each subsequent time step, i.e.:

[0052] The revised power output plan obtained from the solution replaces the instructions for the corresponding time periods in the original plan and is issued to the small hydropower stations for execution; if If the original plan remains unchanged, no correction will be triggered. Through the above adaptive mechanism, multi-objective optimization can be achieved by dynamically coordinating photovoltaic power consumption, feeder peak shaving, and power generation revenue while ensuring reservoir safety.

[0053] This invention aims to address the challenges of daytime photovoltaic (PV) absorption and nighttime overload in distributed photovoltaic (PV) feeders during peak load periods. First, it predicts the feeder's operating status at 9:00 AM the following day and calculates PV curtailment and load shedding power when small hydropower plants do not implement peak-shaving control. Second, it determines the dynamic compensation price for small hydropower peak shaving and establishes a small hydropower revenue model. Then, based on predicted inflow data, reservoir water level constraints, ecological flow requirements, and unit technical constraints, it determines the feasible output range for small hydropower plants at 9:00 AM the following day. Based on this, it formulates a power output plan for the following day. Finally, during real-time operation, it adaptively modifies the subsequent power output plan, considering water level safety margins, to ensure water level safety. This invention achieves dynamic synergy between PV absorption, feeder peak shaving, efficient water resource utilization, and reservoir safety through optimized small hydropower control, demonstrating strong practicality and high feasibility.

[0054] This invention is applicable to distribution network feeders with dense distributed photovoltaic (PV) grids, solving the problems of difficulty in absorbing PV power during peak PV generation periods and overloading of feeders during nighttime peak load periods, while also enabling efficient utilization of small hydropower water resources.

[0055] The present invention also discloses a computer-readable storage medium having a computer program stored thereon, the computer program performing the steps of the method described above when run by a processor.

[0056] This invention further discloses a dynamic compensation and peak-shaving control system for small hydropower plants with distributed photovoltaic enrichment feeders, comprising a memory and a processor connected to each other. The memory stores a computer program, which executes the steps of the method described above when run by the processor.

[0057] The medium and system of the present invention, corresponding to the methods described above, also have the advantages described above.

[0058] The present invention can implement all or part of the processes in the methods of the above embodiments, or it can be implemented by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium includes: any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. The memory is used to store computer programs and / or modules. The processor implements various functions by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may include high-speed random access memory, as well as non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital (SD) cards, flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0059] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A dynamic compensation and peak-shaving control method for small hydropower stations with distributed photovoltaic enrichment feeders, characterized in that, Including the following steps: S1. Based on historical data and weather forecast information, predict the photovoltaic output of the distributed photovoltaic enrichment feeder at various time points the following day. Feeder load Small hydropower water flow Combined with the benchmark power generation capacity of small hydropower and feeder capacity Calculate the photovoltaic curtailment power at each time point of the feeder. and load shedding power ; S2. Based on photovoltaic power curtailment and load shedding power Combined with the fixed on-grid electricity price for small hydropower Unit power load shedding cost Unit distributed photovoltaic curtailment cost Calculate the dynamic compensation price for small hydropower. Establish a price that takes into account dynamic compensation. Small hydropower generation revenue model Small hydropower generation revenue model The output is the actual power generation of small hydropower. The corresponding electricity generation revenue; S3. Based on predicted small hydropower inflow Reservoir water level constraints and ecological flow Considering the technical constraints of the generating units, calculate the feasible output range for each time point on the following day. ; S4. Small hydropower generation revenue model The optimization objective is to maximize the cumulative value at each time point on the following day, within a feasible output range. As a decision variable Given the constraints on the range of values, an optimal operation model for small hydropower is constructed, and the optimal power output plan for small hydropower at each time point on the following day is obtained by solving the optimal operation model for small hydropower. ; S5. In real-time operation, based on the actual water level at the current moment. Optimal output plan for small hydropower Combined with the water flow of small hydropower stations Calculate the maximum water level at each subsequent time point. and minimum value ; When the water level reaches its maximum value or minimum value When the value exceeds the preset safety threshold, an adaptive correction mechanism is triggered to adjust the profit model. The objective is to maximize the cumulative value during the remaining time period, within the feasible output range. Under constraints, a revised output plan is re-solved for subsequent time points, replacing the optimal output plan. The subsequent part will enable dynamic and coordinated adjustment of small hydropower output.

2. The method for dynamic compensation and peak-shaving control of small hydropower stations for distributed photovoltaic enrichment feeders according to claim 1, characterized in that, In step S1, the photovoltaic curtailment power and load shedding power The calculation formula is: 。 3. The method for dynamic compensation and peak-shaving control of small hydropower stations for distributed photovoltaic enrichment feeders according to claim 1, characterized in that, In step S2, the price is dynamically compensated. Specifically: In the formula, and This is the preset compensation coefficient.

4. The method for dynamic compensation and peak-shaving control of small hydropower stations for distributed photovoltaic enrichment feeders according to claim 1, 2, or 3, characterized in that, In step S2, the actual power generation revenue model of small hydropower Specifically: 。 5. The method for dynamic compensation and peak-shaving control of small hydropower stations for distributed photovoltaic enrichment feeders according to claim 1, 2, or 3, characterized in that, In step S3, the lower limit of the output range Specifically: in, The density of water, It is the acceleration due to gravity. This is the current water level. It refers to the power generation efficiency of the water turbine. It is ecological flow. This is to prevent the water level from exceeding the warning level. Minimum discharge flow rate, It is the minimum technical output; Upper limit of output range Specifically: in, This is to prevent the water level from falling below the dead water level. Maximum discharge flow rate; It represents the greatest technological contribution.

6. The method for dynamic compensation and peak-shaving control of small hydropower stations for distributed photovoltaic enrichment feeders according to claim 5, characterized in that, Maximum discharge flow and minimum discharge flow The constraints are: In the formula, The area corresponding to the water level; for The actual discharge flow at any given moment; for The water flow rate at any given time; The unit time interval.

7. The method for dynamic compensation and peak-shaving control of small hydropower stations for distributed photovoltaic enrichment feeders according to claim 6, characterized in that, Maximum water level in step S5 and minimum value The calculation formula is: for The actual water level at that moment; For a point in time.

8. The method for dynamic compensation and peak-shaving control of small hydropower stations for distributed photovoltaic enrichment feeders according to claim 6, characterized in that, In step S5, when the water level reaches its maximum value... or minimum value When the preset safety threshold is exceeded, the adaptive correction mechanism is triggered as follows: Set adaptive correction trigger conditions: In the formula, To adaptively correct the trigger flag, The set safety factor; like This indicates that the water level may exceed the limit during the remaining period, triggering adaptive correction.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program, when run by a processor, performs the steps of the method as described in any one of claims 1-8.

10. A dynamic compensation and peak-shaving control system for small hydropower plants with distributed photovoltaic enrichment feeders, comprising an interconnected memory and a processor, wherein the memory stores a computer program, characterized in that, The computer program, when run by a processor, performs the steps of the method as described in any one of claims 1-8.

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