Distributed photovoltaic fair scheduling method and system based on equal weight regulation factor

Abstract

A fair dispatch method and system for distributed photovoltaic (PV) power based on the weighted control factor is proposed. Before the start of the current control cycle, the weighted control factor of each distributed PV unit is calculated. The ratio of the total control target power of the distributed PV group to the total adjustable capacity of all distributed PV units is obtained. If the ratio is not less than a preset threshold, a full participation control mode is adopted. If the ratio is less than the preset threshold, a rotating control mode is adopted. In the full participation control mode, the total control target power is evenly distributed among all distributed PV units. In the rotating control mode, each distributed PV unit is arranged in ascending order of weighted control factor, and distributed PV units with equal weighted control factors are arranged in ascending order of their last control time. The total control target power is allocated to the distributed PV units selected based on the arrangement results. Before the start of the next control cycle, the weighted control factor is updated to reduce negative impacts on users and improve user satisfaction.

Description

Technical Field

[0001] This invention belongs to the field of power system control technology, specifically relating to a distributed photovoltaic fair dispatch method and system based on the equal weight control factor. Background Technology

[0002] With the transformation of the global energy structure and the increasing awareness of environmental protection, distributed photovoltaic (DPV) power generation systems have developed rapidly worldwide due to their advantages such as being clean, renewable, and readily absorbed by the grid. Their installed capacity and power generation account for a gradually increasing proportion of the total power structure. However, the intermittent and fluctuating nature of DPV, as well as the potential mismatch between its power output and grid load characteristics, pose new challenges to the stable operation of the power grid. Especially during special periods such as holidays when daytime electricity load is low and renewable energy output is high, and under special circumstances such as power outages due to major infrastructure projects, when all conventional absorption methods (such as deep peak shaving from large hydropower and thermal power, pumped storage, etc.) are exhausted and DPV still cannot fully absorb the power, the power grid needs to regulate DPV to ensure grid safety and stability. Currently, this regulation is mainly reflected in peak shaving demand, that is, reducing the output of DPV to match the grid load.

[0003] Existing distributed photovoltaic (PV) group regulation and control methods typically allocate the total regulation target proportionally to all participating PV entities based on their installed capacity. This model is logically simple, easy to implement, and to some extent ensures fairness in regulation. However, this model involving all users has significant drawbacks: 1) Frequent adjustments cause inconvenience to users: The output of renewable energy fluctuates significantly, leading to frequent grid control demands. Under the current model, all distributed photovoltaic users need to participate in each control operation. This means that the inverters on the user side receive frequent control commands, preventing them from reaching full power output.

[0004] 2) Frequent power limitation alarms: When the inverter cannot operate at full capacity due to grid regulation, it will trigger power limitation alarm signals. These alarm signals will frequently appear on the user's monitoring interface or in notifications, causing confusion for many distributed photovoltaic users, especially low-voltage individual users who have little understanding of the power system, and may even mislead users into thinking that the equipment has malfunctioned.

[0005] 3) Increased operational pressure and complaint risks for power grid companies: Frequent alarms and the resulting user inconvenience will inevitably lead to more inquiries and complaints from users to power grid companies, increasing the operating costs of power grid companies and the pressure of user communication, which is not conducive to the healthy development of distributed photovoltaic power and the harmonious operation of the power grid. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a distributed photovoltaic fair dispatch method and system based on a weighted control factor. It introduces a minimum adjustment threshold and a weighted control factor, determines whether to adopt alternating control based on the relationship between the actual control target and the minimum adjustment threshold, and formulates an alternating control mechanism based on the weighted control factor. This achieves more refined and intelligent distributed photovoltaic group dispatch and control, thereby reducing negative impacts on users and improving user satisfaction while ensuring grid safety and stability.

[0007] The present invention adopts the following technical solution.

[0008] This invention proposes a distributed photovoltaic fair scheduling method based on a weighted control factor, comprising: Before the start of the current regulation cycle, the power, regulation duration and installed capacity of each distributed photovoltaic power generation unit during each regulation period within the preset evaluation cycle are obtained from the historical database in order to calculate the average weight regulation factor of each distributed photovoltaic power generation unit. At the start of the current control cycle, the ratio of the total control target power of the distributed photovoltaic cluster to the total adjustable capacity of all distributed photovoltaics is obtained; if the ratio is not less than the preset threshold, the full participation control mode is adopted; if the ratio is less than the preset threshold, the alternating control mode is adopted. When adopting the full participation control mode, the total control target power is evenly distributed to all distributed photovoltaic power. When adopting the alternating control mode, the distributed photovoltaic (PV) units are arranged in ascending order of their average control factor, and the distributed PV units with equal average control factors are arranged in ascending order of their last control time. The total control target power is allocated to the distributed PV units selected based on the arrangement results. The amount of power and duration of regulation for each distributed photovoltaic power generation unit in the current regulation cycle are stored in the historical database, and the average weight regulation factor for each distributed photovoltaic power generation unit is updated before the start of the next regulation cycle.

[0009] For a distributed photovoltaic system, the ratio of power to installed capacity during each regulation within a preset evaluation period is used as the regulation ratio for each regulation. The product of the regulation ratio and the regulation duration for each regulation is accumulated to obtain the average weight regulation factor for each distributed photovoltaic system.

[0010] The preset evaluation periods include: one week, one month, and one quarter.

[0011] The preset threshold is 20%.

[0012] When adopting the full participation control mode, the total control target power is distributed equally to all distributed photovoltaic power in the same proportion, and corresponding control instructions are issued to all distributed photovoltaic power.

[0013] When using the alternating control mode, the order of priority is selected based on the ranking results. One distributed photovoltaic; The total adjustable capacity of each distributed photovoltaic system is not less than the total controllable target power, and The difference between the total adjustable capacity of distributed photovoltaic power generation and the total control target power shall not exceed a preset margin, which is set at 10% of the total control target power. It is a positive integer.

[0014] Set the total control target power according to the selected The adjustable capacity of each distributed photovoltaic system is allocated proportionally to the selected... Corresponding control instructions were issued to each distributed photovoltaic system.

[0015] When adopting the alternating control mode, when selecting the distributed photovoltaic system with the smallest average control factor, grid constraint verification is added, including: 1) Verify whether the voltage at the connection point of the distributed photovoltaic system with the smallest average weight control factor is within the allowable range; 2) Verify whether the feeder containing the distributed photovoltaic system with the smallest average weight control factor is overloaded; When all of the above constraints are met, the distributed photovoltaic (PV) with the smallest average weight control factor is selected first. If at least one constraint is not met, the distributed PV is skipped, and the next distributed PV with the smallest average weight control factor is selected.

[0016] The cumulative number of skipped distributed photovoltaic (PV) units is used to calculate the compensation amount before the weighted control factor ranking is performed in the next control cycle, based on the number of skipped distributed PV units, as shown in the following formula:

[0017] In the formula, This represents the compensation amount for the weighted control factor of distributed photovoltaic power within a preset period. The preset compensation coefficient, , This represents the cumulative number of skips for distributed photovoltaic power generation. If the difference between the average weight control factor and the compensation amount of the distributed photovoltaic system is greater than 0, then the average weight control factor of each distributed photovoltaic system is updated using the difference.

[0018] The weighted sum of the ratio of the actual photovoltaic response power to the control command power and the ratio of the actual photovoltaic response time to the ideal response time within the current control cycle is used as the control efficiency evaluation index. The reciprocal of the control efficiency evaluation index is used to correct the product of the control ratio and the control duration in the next control cycle. The corrected products are accumulated to obtain the updated average weight control factor.

[0019] In another aspect, this invention proposes a distributed photovoltaic fair dispatch system based on a weighted control factor, comprising: The average weight control factor module is used to obtain the power, control duration and installed capacity of each distributed photovoltaic power generation unit from the historical database before the start of the current control cycle, in order to calculate the average weight control factor of each distributed photovoltaic power generation unit. The control mode switching module is used to obtain the ratio of the total control target power of the distributed photovoltaic group to the total adjustable capacity of all distributed photovoltaics at the beginning of the current control cycle; if the ratio is not less than the preset threshold, the full participation control mode is adopted; if the ratio is less than the preset threshold, the alternating control mode is adopted. The control mode execution module is used to distribute the total control target power equally among all distributed photovoltaic (PV) ... The weighted regulation factor module is also used to store the amount of power regulated and the duration of regulation for each distributed photovoltaic power generation in the current regulation cycle into the historical database, and to update the weighted regulation factor for each distributed photovoltaic power generation before the start of the next regulation cycle.

[0020] The present invention is also a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the method.

[0021] The present invention is also a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0022] The beneficial effects of the present invention are as follows: compared with the prior art, the present invention quantifies the historical control burden of each distributed photovoltaic power generation unit through the weighted control factor, and designs a dual-mode fair scheduling mechanism based on this, thereby achieving long-term fairness guarantee in the group control of distributed photovoltaic power generation units, which has significant technological progress and engineering application value.

[0023] Compared to existing technologies, this invention provides a more refined and intelligent group control strategy, improving the flexibility and efficiency of power grid regulation. This invention constructs a distributed photovoltaic (PV) system that allows for rotating participation in grid peak shaving. By implementing batch-based rotational regulation, it significantly reduces the regulation frequency for individual users while ensuring effective regulation, thus mitigating user annoyance and complaints caused by frequent inverter alarms. By setting a weighted regulation factor, it ensures that all distributed PV projects participating in group control, regardless of installed capacity, have a fair regulation burden over a certain time scale, preventing excessive regulation of a few projects and achieving regulation fairness among different users. This facilitates the construction of longer-term and more stable user relationships, encourages more distributed PV users to participate in group control, and ensures the energy balance of the power system and the safe and stable operation of the power grid. Attached Figure Description

[0024] Figure 1 This is a flowchart of a distributed photovoltaic fair scheduling method based on the average weight control factor proposed in this invention; Figure 2 This is a schematic diagram of the distributed photovoltaic system architecture in an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0026] This invention provides a distributed photovoltaic fair scheduling method based on the average weight control factor, such as... Figure 1 As shown, it includes the following steps: Step 1: Before the start of the current regulation cycle, obtain the power, regulation duration and installed capacity of each distributed photovoltaic power generation unit from the historical database for each regulation during the preset evaluation cycle. Use the ratio of power to installed capacity during each regulation as the regulation ratio for each regulation. Accumulate the product of the regulation ratio and regulation duration for each regulation to obtain the average weight regulation factor for each distributed photovoltaic power generation unit.

[0027] Specifically, for each distributed photovoltaic system, within a preset historical period (such as a week, a month, or a quarter), the records of each instance of regulation (power reduction) are iterated, and the following calculations are performed for each regulation: The first step is to calculate the power control ratio for this regulation: divide the actual power reduction amount of this regulation by the installed capacity (rated power) of the photovoltaic project to obtain a ratio between 0 and 1.

[0028] The second step is to multiply the power control ratio calculated in the first step by the duration of the control (i.e., the time from when the control command takes effect to when it is lifted, usually in minutes or hours) to obtain the weighted control amount for that control.

[0029] The third step is to sum the weighted control amounts of all control records within the preset period to obtain the average weighted control factor of the distributed photovoltaic system.

[0030] Specifically, the weighted control factor for each distributed photovoltaic system within a preset period:

[0031]

[0032] In the formula, This is the weighted control factor for distributed photovoltaic power generation within a preset period. For the first time within the preset period The adjustment ratio during the second adjustment, For the first time within the preset period Power quantity during the second regulation For the installed capacity of distributed photovoltaic power, For the first time within the preset period Power regulation duration during the second regulation The number of adjustments within a preset period.

[0033] Before the start of each regulation cycle, the system first calculates the weighted regulation factor for all distributed photovoltaic (PV) systems based on regulation records in the historical database. The weighted regulation factor quantifies the historical regulation burden of each distributed PV system by accumulating (power reduction / installed capacity) × duration for each regulation. This allows the dispatch system to prioritize PV systems with lighter burdens for regulation, achieving fair rotation among projects in long-term operation and solving the fairness problem of bias in traditional methods.

[0034] Step 2: At the start of the current control cycle, obtain the total control target power of the distributed photovoltaic group and the total adjustable capacity of all distributed photovoltaics; when the ratio of the total control target power to the total adjustable capacity is not less than the preset threshold, the full participation control mode is adopted; when the ratio of the total control target power to the total adjustable capacity is less than the preset threshold, the alternating control mode is adopted.

[0035] Specifically, the total control target of the distributed photovoltaic cluster is received from the power dispatch center. The total control target includes, but is not limited to, the total control target power.

[0036] Specifically, the operational data of each distributed photovoltaic system participating in the group dispatch and control includes, but is not limited to, real-time output, adjustable capacity, operating status, and installed capacity.

[0037] Then, the control mode is selected based on the ratio of current control demand to total adjustable capacity; finally, the control command is executed and the average weight control factor is updated. Specifically, the ratio of the total control target power to the total adjustable capacity is used as the control ratio, and the preset threshold is preferably 20%.

[0038] Step 3: When adopting the full participation control mode, the total control target power is distributed equally to all distributed photovoltaics in the same proportion, and corresponding control instructions are issued to all distributed photovoltaics.

[0039] Step 4: When using the rotating control mode, the distributed photovoltaic (PV) systems are arranged in ascending order of their average control factor, and those with equal average control factors are arranged in ascending order of their last control time. Based on the arrangement, the system with the highest ranking is selected. Distributed photovoltaic power; the total control target power will be adjusted according to the selected... The adjustable capacity of each distributed photovoltaic system is allocated proportionally to the selected... Corresponding control instructions were issued to each distributed photovoltaic system.

[0040] The distributed photovoltaic (PV) systems are sorted according to their average weighting control factors, with priority given to those with smaller average weighting control factors (i.e., relatively less control). When the average weighting control factors are the same, they are sorted according to preset secondary sorting rules, such as selecting the project with the longest last adjustment time, in order to achieve a fair rotation that takes into account the installed capacity.

[0041] The smaller the average weighting control factor, the lighter the relative regulation burden borne by the distributed photovoltaic (PV) in the past cycle. The fairness of existing technologies is only reflected in the allocation ratio of a single dispatch, without considering the cumulative regulation burden borne by each PV in historical cycles. A PV that has been frequently reduced in a preset past cycle is in an equal competitive position with a PV that has never been reduced, failing to ensure fair rotation of installed capacity. This invention, however, accumulates historical regulation records (regulation power ratio × regulation duration each time), quantifies the historical regulation burden of each PV using the average weighting control factor, and uses the average weighting control factor as the priority basis for the next dispatch in a specific rotational regulation mode, achieving cumulative fairness across cycles.

[0042] Furthermore, in the alternating control mode, when selecting the distributed photovoltaic system with the smallest average control factor, grid constraint verification is added, including: 1) Verify whether the voltage at the connection point of the distributed photovoltaic system with the smallest average weight control factor is within the allowable range; 2) Verify whether the feeder containing the distributed photovoltaic system with the smallest average weight control factor is overloaded; When all the above constraints are met, the distributed photovoltaic (PV) photovoltaic (PV) photovoltaic system with the smallest average weight control factor is selected first. If at least one constraint is not met, the PV is skipped, and the next PV with the smallest average weight control factor is selected. However, under the above constraints, some PVs may be skipped due to "unfavorable grid location" (such as being located at voltage-sensitive nodes or feeder ends). Therefore, the number of skipped PVs is accumulated, and the compensation amount is calculated based on the number of skipped PVs before the average weight control factor ranking is performed in the next control cycle, as shown in the following formula:

[0043] In the formula, This represents the compensation amount for the weighted control factor of distributed photovoltaic power within a preset period. The preset compensation coefficient, , This represents the cumulative number of skips for distributed photovoltaic systems.

[0044] If the difference between the average weight control factor and the compensation amount of the distributed photovoltaic system is greater than 0, the average weight control factor of each distributed photovoltaic system is updated using the difference. By introducing the compensation amount to update the average weight control factor as a sorting criterion, photovoltaic systems that are frequently skipped will receive a higher priority in subsequent control, thus avoiding permanent neglect due to poor grid location.

[0045] Meanwhile, the dual-mode adaptive switching mechanism (using alternating regulation when the regulation ratio is <20%) further reduces the impact of fair scheduling on photovoltaic owners.

[0046] Specifically, based on the sorting results, the one that appears first in the sorting is selected. One distributed photovoltaic, The total adjustable capacity of each distributed photovoltaic system is not less than the total controllable target power, and The difference between the total adjustable capacity of distributed photovoltaic systems and the total controllable target power shall not exceed a preset margin. In this embodiment, the preset margin is set at 10% of the total controllable target power. It is a positive integer.

[0047] After receiving instructions, each distributed photovoltaic project adjusts its output via inverters. The system monitors the actual output changes and feeds the adjustment results back to the power dispatch center.

[0048] Step 5: Store the power output and duration of each distributed photovoltaic power generation unit in the historical database during the current regulation cycle, and update the weighted regulation factor of each distributed photovoltaic power generation unit before the start of the next regulation cycle.

[0049] The weighted control factor of this invention contains a negative feedback coupling mechanism. When a photovoltaic project is regulated in the current regulation cycle, its weighted control factor increases, and its priority for the next scheduling cycle automatically decreases, thus automatically giving regulation opportunities to other photovoltaic projects, achieving automatic rotation and long-term load balancing among projects. Furthermore, the negative feedback coupling mechanism of the weighted control factor and the rotating regulation mode form a mutually reinforcing symbiotic relationship. The rotating regulation mode provides the execution platform for precise adjustment of the negative feedback coupling mechanism, while the negative feedback coupling mechanism enables the rotating regulation mode to acquire the intelligent characteristic of automatic convergence.

[0050] Furthermore, the average weighted control factor cannot reflect control costs, such as communication delays and response accuracy. Therefore, when updating the average weighted control factor of each distributed photovoltaic system before the start of the next control cycle, a control efficiency evaluation index is introduced. This index is calculated by weighting the ratio of the actual photovoltaic response power to the control command power and the ratio of the actual photovoltaic response time to the ideal response time within the current control cycle. The reciprocal of this index is used to correct the product of the control ratio and the control duration in the next control cycle. The corrected products are then summed to obtain the updated average weighted control factor, as shown in the following formula:

[0051]

[0052]

[0053] In the formula, This refers to the average weight control factor updated within a preset period for distributed photovoltaic power generation. For the first time within the preset period The adjustment ratio during the second adjustment, For the first time within the preset period Power quantity during the second regulation For the installed capacity of distributed photovoltaic power, For the first time within the preset period Power regulation duration during the second regulation The number of adjustments within a preset period, To regulate efficiency evaluation indicators, , This is a weighting coefficient; in this example, the value is 0.5. This represents the actual photovoltaic response power during the current regulation cycle. This refers to the photovoltaic control command power during the current control cycle. This refers to the actual response time of photovoltaic systems during the current regulation cycle. This represents the ideal response time for photovoltaics.

[0054] For photovoltaic systems with lower regulation efficiency evaluation indicators, the updated average weight regulation factor is artificially increased, thus placing them lower in the ranking and reducing the number of times they are invoked. However, after a long period of inactivity, their historical contribution decreases, and the average weight regulation factor decreases again, returning them to a higher ranking position and being invoked once more. This forms a dynamic balance of the average weight regulation factor. Furthermore, it enables photovoltaic monitoring and early warning based on the adaptive adjustment mechanism of the average weight regulation factor. When the average weight regulation factor of a photovoltaic system shows a downward trend in the ranking over multiple consecutive regulation cycles, the regulation efficiency evaluation indicators can be analyzed to identify factors that deteriorate the photovoltaic regulation cost, thereby issuing an early warning and improving the photovoltaic operating performance.

[0055] The method proposed in this invention is Figure 2 The system shown can be applied to this, taking a group control system containing 4 distributed photovoltaic power stations (DPV1 to DPV4) as an example. The system simulates 10 control requests within a week and tracks the decision-making and execution results of each round of control in real time.

[0056] The installed capacity and adjustable capacity of each power station (assuming they are always online and the adjustable capacity equals the installed capacity) are as follows: DPV1 is 50kW, DPV2 is 100kW, DPV3 is 30kW, DPV4 is 20kW, and the total adjustable capacity is 200kW. The preset evaluation period is one week, and the threshold is 20%. To reflect the starting point of the fairness evolution, this embodiment sets that at the beginning of a new week, the weighted control factor of each power station is reset to zero, and the initial value of "last control time" is recorded as 0 (indicating that it has not yet participated in control). Furthermore, it is assumed that during the control process, each photovoltaic power station meets the grid constraint verification and the control efficiency evaluation index is at an ideal value.

[0057] When the weighted control factors are the same, the systems are arranged in ascending order of the last control time (the older the better). If the time is still the same, the systems are arranged in descending order of adjustable capacity to meet the control target with as few power plants as possible. The preset margin is 10% of the total control target power. If, during actual selection, the difference between the total adjustable capacity and the target power exceeds the margin due to the excessive capacity of a single power plant, the system will still execute with the smallest power plant combination to ensure timely control response.

[0058] A total of 10 control requests are planned within a week. The timing, duration, and total target power of these requests are shown in Table 1. Table 1: Weekly Regulation Demand Table

[0059] First adjustment (Monday 9:00-10:00, 30kW, rotating): Initially, all station factors are 0, and the last control time is 0. Power ranking: DPV2 (100kW) > DPV1 (50kW) > DPV3 (30kW) > DPV4 (20kW). DPV2 is selected, as its adjustable capacity is 100kW ≥ 30kW. Although the difference of 70kW exceeds the margin of 3kW, it cannot be reduced; therefore, DPV2 is chosen as the participating station. DPV2 is allocated to reduce 30kW. The control ratio for this operation is 0.3, with a weighting of 0.3 × 1h = 0.3. Update: DPV2 factor 0.3, last control time 10h; other factors 0, time 0.

[0060] Second round of regulation (Monday 14:00-14:30, 10kW, rotating): The current average weighted control factors are: DPV1(0), DPV3(0), DPV4(0) < DPV2(0.3). The three stations with a factor of 0 all had a previous time of 0. Ranked by capacity, DPV1(50) > DPV3(30) > DPV4(20). DPV1 is selected, with a capacity of 50kW ≥ 10kW, and 10kW is allocated. The control ratio is 0.2, and the weighting is 0.2 × 0.5h = 0.1. Update: DPV1 factor 0.1, time 14.5h; everything else remains unchanged.

[0061] Third adjustment (Tuesday 10:00-11:00, 50kW, all employees): The proportion must be 25% or higher than the threshold, with full participation. Allocation based on capacity proportions: DPV1: 12.5kW, DPV2: 25kW, DPV3: 7.5kW, DPV4: 5kW. The control ratio for each station is 0.25, with a weighted average of 0.25 × 1h = 0.25. Update factors: DPV1 = 0.35, DPV2 = 0.55, DPV3 = 0.25, DPV4 = 0.25; the last time for all stations is updated to 34 hours.

[0062] Fourth adjustment (Wednesday 12:00-13:00, 25kW, rotating): Factor ranking: DPV3 (0.25), DPV4 (0.25) < DPV1 (0.35) < DPV2 (0.55). DPV3 and DPV4 have the same factor, and both lasted for 34 hours. Based on capacity, DPV3 (30) > DPV4 (20). DPV3 is selected, with a capacity of 30 ≥ 25. The difference of 5kW is slightly greater than the margin of 2.5kW but still applicable, so 25kW is allocated. The control ratio is 0.833, and the weighted average is 0.833 × 1h = 0.833. Update: DPV3 factor = 1.083, time 61h; other times remain unchanged.

[0063] Fifth adjustment (Wednesday 15:00-15:30, 40kW, all employees): The proportion is 20%, with full participation. Allocation: DPV1: 10kW, DPV2: 20kW, DPV3: 6kW, DPV4: 4kW. The control ratio for each station is 0.2, with a weighted average of 0.2 × 0.5h = 0.1. Update factors: DPV1 = 0.45, DPV2 = 0.65, DPV3 = 1.183, DPV4 = 0.35; the last time for all stations was updated to 63.5h.

[0064] The 6th adjustment (Thursday 8:00-9:30, 35kW, rotating): Factor ranking: DPV4 (0.35) < DPV1 (0.45) < DPV2 (0.65) < DPV3 (1.183). Selecting DPV4 (20kW) results in insufficient cumulative output; adding DPV1 (50kW) brings the cumulative output to 70kW ≥ 35kW, therefore DPV4 and DPV1 are selected. Capacity allocation: DPV4: 35 × (20 / 70) = 10kW, DPV1: 35 × (50 / 70) = 25kW. The control ratio is 0.5 for both, and the weighting is 0.5 × 1.5h = 0.75. Update factors: DPV4 = 1.10, DPV1 = 1.20; DPV4 and DPV1 were last updated at 81.5h, while the others remain at 63.5h.

[0065] The 7th adjustment (Thursday 20:00-21:00, 20kW, rotating): Factor ranking: DPV2 (0.65) < DPV4 (1.10) < DPV3 (1.183) < DPV1 (1.20). DPV2 capacity ≥ 20kW, allocated 20kW. Control ratio 0.2, weighted 0.2 × 1h = 0.2. Update: DPV2 factor = 0.85, time updated to 93h; everything else remains unchanged.

[0066] Eighth adjustment (Friday 9:00-10:00, 60kW, all employees): Allocation: DPV1: 15kW, DPV2: 30kW, DPV3: 9kW, DPV4: 6kW. Weighting is 0.3 for all. Update factors: DPV1=1.50, DPV2=1.15, DPV3=1.483, DPV4=1.40; last time updated to 106h for all.

[0067] Ninth adjustment (Saturday 12:00-12:30, 15kW, rotating): Factor ranking: DPV2 (1.15) < DPV4 (1.40) < DPV3 (1.483) < DPV1 (1.50). DPV2 capacity 100 ≥ 15, allocated 15kW. Weighting 0.075. Update: DPV2 factor = 1.225, time 132.5h.

[0068] 10th adjustment (Sunday 16:00-17:00, 45kW, all staff): Allocation: DPV1: 11.25kW, DPV2: 22.5kW, DPV3: 6.75kW, DPV4: 4.5kW. Weighted average for all is 0.225. Update factors: DPV1=1.725, DPV2=1.45, DPV3=1.708, DPV4=1.625; last updated time for all was 161h.

[0069] The above 10 weekly control operations were calculated in parallel using the traditional "allocation based on installed capacity ratio" method. The cumulative weighted control factor (final value) and the number of control operations participated in by each power station under the two methods are compared as follows:

[0070] From the perspective of the final weighted control factor, although there are some differences in the factors of each station under the method of this invention (1.45~1.725), this is the result of dynamic evolution within a short period of one week, and the difference is significantly smaller than the cumulative load deviation that may be caused by the capacity differences of each station. In contrast, the factors of the traditional method are completely consistent, which seems "fair" but in fact does not consider the accumulation of historical load and the minimum user disturbance. While ensuring fairness over a long period, this invention reduces the number of cumulative control actions from 40 times per station to 23 times per station, a reduction of 42.5%, which significantly reduces the triggering frequency and impact range of inverter power limitation alarms.

[0071] The dynamic process of allocating regulatory opportunities reveals that DPV2, due to its low initial factor and large capacity, was selected multiple times in the first few rounds of regulation. However, its factor increased with each participation, reaching 1.225 after the 9th regulation, thus reducing its subsequent priority. DPV1 and DPV3, on the other hand, were protected in the medium term, avoiding continuous over-calling. Throughout the process, the negative feedback coupling mechanism of the weighted regulatory factors continued to function, with factors at each station chasing each other and converging towards an equilibrium level. If this process continues for several weeks or months, the regulatory burden on each station will automatically converge to almost equal levels, achieving fair scheduling across cycles.

[0072] In summary, this embodiment fully verifies the effectiveness of the dual-mode fair scheduling method proposed in this invention in continuous multi-round control scenarios. It not only reduces the disturbance to users from a single control, but also ensures fairness over a long period through the dynamic feedback of the weighted control factor, significantly improving the user-friendliness and engineering practicality of distributed photovoltaic group control.

[0073] In another aspect, this invention proposes a distributed photovoltaic fair dispatch system based on a weighted control factor, comprising: The average weight control factor module is used to obtain the power, control duration and installed capacity of each distributed photovoltaic power generation unit from the historical database before the start of the current control cycle, in order to calculate the average weight control factor of each distributed photovoltaic power generation unit. The control mode switching module is used to obtain the ratio of the total control target power of the distributed photovoltaic group to the total adjustable capacity of all distributed photovoltaics at the beginning of the current control cycle; if the ratio is not less than the preset threshold, the full participation control mode is adopted; if the ratio is less than the preset threshold, the alternating control mode is adopted. The control mode execution module is used to distribute the total control target power equally among all distributed photovoltaic (PV) ... The weighted regulation factor module is also used to store the amount of power regulated and the duration of regulation for each distributed photovoltaic power generation in the current regulation cycle into the historical database, and to update the weighted regulation factor for each distributed photovoltaic power generation before the start of the next regulation cycle.

[0074] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0075] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0076] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0077] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A distributed photovoltaic fair dispatch method based on a weighted control factor, characterized in that, include: Before the start of the current regulation cycle, the power, regulation duration and installed capacity of each distributed photovoltaic power generation unit during each regulation period within the preset evaluation cycle are obtained from the historical database. The ratio of the power to the installed capacity during each regulation period within the preset evaluation cycle is used as the regulation ratio for each regulation period. The products of the regulation ratio and the regulation duration for each regulation period are accumulated to calculate the average weight regulation factor for each distributed photovoltaic power generation unit. At the start of the current regulation cycle, obtain the ratio of the total regulation target power of the distributed photovoltaic cluster to the total adjustable capacity of all distributed photovoltaics. If the ratio is not less than the preset threshold, the full participation control mode is adopted; if the ratio is less than the preset threshold, the alternating control mode is adopted. When adopting the full participation control mode, the total control target power is evenly distributed to all distributed photovoltaic power. When the rotating control mode is adopted, the distributed photovoltaic power plants are arranged in order of increasing average weight control factor, and the distributed photovoltaic power plants with the same average weight control factor are arranged in order of the most recent control time. The total control target power is allocated to the distributed photovoltaic power selected based on the arrangement results; The amount of power and duration of regulation for each distributed photovoltaic power generation unit in the current regulation cycle are stored in the historical database, and the average weight regulation factor for each distributed photovoltaic power generation unit is updated before the start of the next regulation cycle.

2. The distributed photovoltaic fair dispatch method based on the equal weight control factor according to claim 1, characterized in that, The preset evaluation periods include: one week, one month, and one quarter.

3. The distributed photovoltaic fair dispatch method based on the equal weight control factor according to claim 1, characterized in that, The preset threshold is 20%.

4. The distributed photovoltaic fair dispatch method based on the equal weight control factor according to claim 1, characterized in that, When adopting the full participation control mode, the total control target power is distributed equally to all distributed photovoltaic power in the same proportion, and corresponding control instructions are issued to all distributed photovoltaic power.

5. The distributed photovoltaic fair dispatch method based on the equal weight control factor according to claim 1, characterized in that, When using the alternating control mode, the order of priority is selected based on the ranking results. One distributed photovoltaic; The total adjustable capacity of each distributed photovoltaic system shall not be less than the total controllable target power, and The difference between the total adjustable capacity of distributed photovoltaic power generation and the total control target power shall not exceed a preset margin, which is set at 10% of the total control target power. It is a positive integer.

6. The distributed photovoltaic fair dispatch method based on the equal weight control factor according to claim 5, characterized in that, Set the total control target power according to the selected The proportional relationship between the adjustable capacities of individual distributed photovoltaic systems is used to allocate power to the selected... Corresponding control instructions were issued to each distributed photovoltaic system.

7. The distributed photovoltaic fair dispatch method based on the equal weight control factor according to claim 5, characterized in that, When adopting the alternating control mode, when selecting the distributed photovoltaic system with the smallest average control factor, grid constraint verification is added, including: 1) Verify whether the voltage at the connection point of the distributed photovoltaic system with the smallest average weight control factor is within the allowable range; 2) Verify whether the feeder containing the distributed photovoltaic system with the smallest average weight control factor is overloaded; When all of the above constraints are met, the distributed photovoltaic (PV) with the smallest average weight control factor is selected first. If at least one constraint is not met, the distributed PV is skipped, and the next distributed PV with the smallest average weight control factor is selected.

8. The distributed photovoltaic fair dispatch method based on the equal weight control factor according to claim 7, characterized in that, The cumulative number of skipped distributed photovoltaic (PV) units is used to calculate the compensation amount before the weighted control factor ranking is performed in the next control cycle, based on the number of skipped distributed PV units, as shown in the following formula: In the formula, This represents the compensation amount for the weighted control factor of distributed photovoltaic power within a preset period. The preset compensation coefficient, , This represents the cumulative number of skips for distributed photovoltaic power generation. If the difference between the average weight control factor and the compensation amount of the distributed photovoltaic system is greater than 0, then the average weight control factor of each distributed photovoltaic system is updated using the difference.

9. The distributed photovoltaic fair dispatch method based on the equal weight control factor according to claim 1, characterized in that, The weighted sum of the ratio of the actual photovoltaic response power to the control command power and the ratio of the actual photovoltaic response time to the ideal response time within the current control cycle is used as the control efficiency evaluation index. The reciprocal of the control efficiency evaluation index is used to correct the product of the control ratio and the control duration in the next control cycle. The corrected products are accumulated to obtain the updated average weight control factor.

10. A distributed photovoltaic fair dispatch system based on a weighted control factor, used to implement the distributed photovoltaic fair dispatch method based on a weighted control factor as described in any one of claims 1 to 9, characterized in that, include: The average weight control factor module is used to obtain the power, control duration and installed capacity of each distributed photovoltaic power generation unit from the historical database before the start of the current control cycle. The ratio of the power to the installed capacity during each control cycle is used as the control ratio for each control cycle. The average weight control factor for each distributed photovoltaic power generation unit is calculated by summing the products of the control ratio and the control duration for each control cycle. The control mode switching module is used to obtain the ratio of the total control target power of the distributed photovoltaic group to the total adjustable capacity of all distributed photovoltaics at the beginning of the current control cycle. If the ratio is not less than the preset threshold, a full participation control mode will be adopted; If the ratio is less than the preset threshold, the alternating control mode is adopted; The control mode execution module is used to distribute the total control target power equally among all distributed photovoltaic (PV) ... The weighted regulation factor module is also used to store the amount of power regulated and the duration of regulation for each distributed photovoltaic power generation in the current regulation cycle into the historical database, and to update the weighted regulation factor for each distributed photovoltaic power generation before the start of the next regulation cycle.

11. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-9.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-9.

Images