Photovoltaic access method and system based on distributed photovoltaic open capacity index

Abstract

The application discloses a kind of photovoltaic access methods based on distributed photovoltaic openable capacity index, comprising the following steps: constructing distributed photovoltaic openable capacity evaluation index system of power distribution network, and the weight of each index is calculated;Obtain power distribution network topology model and load prediction result;Distributed photovoltaic prediction result is calculated;The matching degree of short-term and long-term openable capacity is calculated, to judge whether distributed photovoltaic development is reasonable;Distributed photovoltaic openable capacity evaluation index result is calculated;According to first-come-first-served mechanism, the distributed photovoltaic openable capacity index of power distribution network is dynamically updated, and the orderly access of distributed photovoltaic is guided to be completed.The application further discloses a system for implementing the photovoltaic access method based on the distributed photovoltaic openable capacity index.The method comprehensively considers the influencing factors of the distributed photovoltaic openable capacity of the power distribution network, and takes into account the short-term and long-term dynamic evaluation of the distributed photovoltaic openable capacity of the power distribution network, reduces the impact of the distributed photovoltaic access on the power distribution network, and improves the stability of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution automation, and in particular to a photovoltaic access method and system based on a distributed photovoltaic open capacity index. Background Art

[0002] Distributed photovoltaics (PV) refers to a small-scale power generation system that utilizes dispersed resources and is typically connected to a grid voltage of 35 kilovolts or lower. It uses PV panels to directly convert solar energy into electricity. Its characteristic operating mode is that users generate and consume power on their own, with excess power being fed into the grid, and the distribution system provides balancing and regulation.

[0003] Distributed photovoltaic power generation follows the principles of adapting to local conditions, ensuring clean and efficient operation, decentralized layout, and local utilization. It fully utilizes local solar energy resources to replace and reduce fossil energy consumption. It boasts low output power, minimal pollution, and significant environmental benefits. It can be installed near commercial areas in rural areas, pastoral areas, mountainous areas, and large, medium, and small cities, enabling the coexistence of power generation and consumption.

[0004] With the widespread integration of high-penetration distributed photovoltaic power generation into distribution network substations, these substations are facing operational issues such as overloading and overloading of active power, as well as reactive power safety issues such as busbar voltage exceeding limits. Currently, there is a lack of an effective evaluation index system for the available capacity of distributed photovoltaic power generation in distribution networks. Differences in short-term and medium- to long-term considerations lead to inconsistent evaluation results, making it difficult to scientifically and effectively publish a dynamic index for the available capacity of distributed photovoltaic power generation in distribution networks on a first-come, first-served basis. This hinders the scientific and orderly integration of distributed photovoltaic power generation. Summary of the Invention

[0005] One of the purposes of the present invention is to provide a photovoltaic access method based on the distributed photovoltaic open capacity index, establish an evaluation system for the open capacity of distributed photovoltaic in the distribution network, evaluate medium- and long-term indicators and short-term impacts, dynamically calculate the open capacity index, realize first-come, first-served open capacity evaluation, and guide the scientific and orderly access of distributed photovoltaics.

[0006] A second object of the present invention is to provide a system for implementing the photovoltaic access method based on the distributed photovoltaic open capacity index.

[0007] The present invention provides a photovoltaic access method based on a distributed photovoltaic open capacity index, comprising the following steps:

[0008] S1. Construct an evaluation index system for the open capacity of distributed photovoltaic power generation in distribution networks and calculate the weight of each index;

[0009] S2. Obtain the distribution network topology model and load forecast results based on the PMS system and dispatch automation system;

[0010] S3. Based on the distribution network topology model and load forecast results obtained in step S2, the distributed photovoltaic forecast results are calculated based on the distribution network open capacity assessment scenario;

[0011] S4. Based on the distributed PV forecast results obtained in step S3, calculate the matching degree of short-term and long-term available capacity. Based on the obtained matching degree, determine whether the distributed PV development is reasonable. If reasonable, proceed to the next step. If not, adjust the load development plan or the distributed PV access location, and then return to step S3.

[0012] S5. Calculate the distributed photovoltaic open capacity index based on the weights of each indicator in the distribution network distributed photovoltaic open capacity evaluation index system obtained in step S1 and the distributed photovoltaic prediction results obtained in step S3;

[0013] S6. Based on the distributed photovoltaic open capacity index obtained in step S5 and the growth trend of distributed photovoltaic open capacity, dynamically update the distributed photovoltaic open capacity index of the distribution network to guide the orderly access of distributed photovoltaics.

[0014] Step S1 specifically includes: establishing an evaluation index system for the open capacity of distributed photovoltaic power generation in the distribution network, and systematically evaluating the operation level of the distribution network substation; calculating the weight of each index in the evaluation index system for the open capacity of distributed photovoltaic power generation in the distribution network based on the analytic hierarchy process and entropy weight method;

[0015] The first-level indicators of the evaluation index system for the open capacity of distributed photovoltaic power distribution networks include growth, reliability, power quality, economy, matching and safety;

[0016] Growth includes the secondary indicator of the growth rate of distributed photovoltaic open capacity; the growth rate of distributed photovoltaic open capacity is the ratio of the current distribution network open capacity to the connected distributed photovoltaic capacity;

[0017] Reliability includes the secondary indicator system average power outage duration; the system average power outage duration is the average power outage duration of the system obtained by Monte Carlo simulation method using typical distributed photovoltaic and load operation curves after the current distribution network is connected to distributed photovoltaic according to the current open capacity method;

[0018] The power quality includes secondary indicators such as voltage qualification rate, three-phase unbalance rate and harmonic distortion rate; the voltage qualification rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves; the three-phase unbalance rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves; the harmonic distortion rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves;

[0019] Economic efficiency includes the secondary indicator line loss rate. The line loss rate is calculated by using typical distributed photovoltaic and load operation curves after the current distribution network is connected to distributed photovoltaic according to the current open capacity.

[0020] The matching degree includes the secondary indicators of short-term open capacity and medium- and long-term open capacity ratio; short-term open capacity refers to the current open capacity of distributed photovoltaics; medium- and long-term open capacity refers to the evaluation of the medium- and long-term open capacity of distributed photovoltaics based on the load forecast results;

[0021] Safety includes secondary indicators: maximum reverse ratio and maximum load rate. The maximum reverse ratio is the maximum reverse ratio of the transformer or line; the maximum load rate is the maximum load rate of the transformer or line;

[0022] The analytic hierarchy process comprises the following steps:

[0023] Construct a pairwise comparison matrix and use the following formula:

[0024]

[0025] a ij >0(i<j)

[0026] a ii =1

[0027]

[0028] Among them, A is the pairwise comparison matrix; a ij is the pairwise comparison matrix element, a ij The size of reflects the importance of the i-th indicator compared to the j-th indicator; a ij The value range of is {1,3,5,7,9}, representing the comparison results of “equal”, “slightly”, “obvious”, “strong” and “extreme” respectively; a ij The value is the average of the opinions of several independent experts;

[0029] Calculate the maximum eigenvalue λ of the pairwise comparison matrix A max and the corresponding eigenvector W;

[0030] Calculate the consistency index CI and random consistency index CR using the following formula:

[0031]

[0032] Where n is the order of the pairwise comparison matrix A; RI is the average random consistency index;

[0033] When the random consistency index CR is less than 0.1, the consistency requirement is met;

[0034] The value of the average random consistency index RI corresponds one-to-one to the order n of the pairwise comparison matrix A, specifically:

[0035] When n=1, RI=0;

[0036] When n=2, RI=0;

[0037] When n=3, RI=0.52;

[0038] When n=4, RI=0.89;

[0039] When n=5, RI=1.12;

[0040] When n=6, RI=1.26;

[0041] When n=7, RI=1.36;

[0042] When n=8, RI=1.41;

[0043] When n=9, RI=1.46;

[0044] When n=10, RI=1.49;

[0045] If the pairwise comparison matrix A meets the consistency judgment requirements, the eigenvector W is normalized to obtain the judgment weight of each indicator;

[0046] If the pairwise comparison matrix A does not meet the consistency judgment requirements, communicate with independent experts and correct a ij until the consistency check passes.

[0047] The entropy weight method includes the following steps:

[0048] First, the original data of the indicators in the evaluation index system of the open capacity of distributed photovoltaic power distribution network are standardized to ensure that each indicator is at the same level and expressed using the following formula:

[0049]

[0050] Among them, x is the indicator data; mean(x) is the sample mean; std(x) is the sample standard deviation; z is the standardized indicator data;

[0051] Calculate the information entropy value of each indicator and evaluate the degree of dispersion using the following formula:

[0052]

[0053] Among them, e i is the entropy value of the i-th indicator; n is the number of observations of the i-th indicator; V ij is the observed value of the jth sample of the i-th indicator; e i The value range of is [0,1], which reflects the difference of the i-th indicator. The closer it is to 1, the lower the difference of the indicator.

[0054] Calculate the corresponding weight according to the information entropy value of each indicator, using the following formula

[0055]

[0056] Among them, ω i is the weight of the i-th indicator; m is the total number of indicators.

[0057] Step S3 is specifically as follows:

[0058] Obtain open capacity assessment scenarios for distribution networks, including load history curves, distributed photovoltaic history curves, distribution network power flow calculation models, and typical fault sets;

[0059] Based on the distribution network open capacity assessment scenario and the current load situation, set the maximum tolerance values ​​of the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; using the distribution network topology model obtained in step S2, proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, and obtain the current maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system;

[0060] Based on the load forecast result obtained in step S2, a short- to medium-term load forecast curve and a long-term load forecast curve are obtained; wherein the short- to medium-term load forecast curve is a load forecast curve for 1 to 3 months, and the long-term load forecast curve is a load forecast curve for more than 3 months;

[0061] Based on the distribution network open capacity assessment scenario and the medium- and short-term load forecast curve, set the maximum tolerance values ​​for the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; using the distribution network topology model obtained in step S2, proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, thereby obtaining the medium- and short-term maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system;

[0062] Based on the distribution network open capacity assessment scenario and the long-term load forecast curve, set the maximum tolerance values ​​of the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; use the distribution network topology model obtained in step S2 to proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, thereby obtaining the long-term maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system.

[0063] Step S4 is specifically as follows:

[0064] Based on the distributed photovoltaic prediction results obtained in step S3, the impact of short-term load and distributed photovoltaic changes on the distribution network flow is evaluated, and the matching degree of short-term and long-term available capacity is calculated using the following formula:

[0065]

[0066] Among them, S 中短期 The distributed photovoltaic capacity that can be opened within 1 to 3 months; S 长期 The distributed photovoltaic capacity can be opened for more than 3 months;

[0067] If I≤1, the load development plan and the distributed photovoltaic access location are relatively reasonable, and the next step is entered;

[0068] If I>1, adjust the load development plan and the distributed photovoltaic access location, and return to step S3.

[0069] Step S5 is specifically as follows:

[0070] According to the weights of the indicators obtained in step S1 and the prediction results of the indicators of the distribution network distributed photovoltaic open capacity evaluation index system corresponding to the current maximum distributed photovoltaic open capacity obtained in step S3, the weighted sum of the indicators is performed to obtain the distributed photovoltaic open capacity index in the current state.

[0071] Step S6 specifically includes: announcing the growth trend of the distributed photovoltaic open capacity according to the distributed photovoltaic open capacity index obtained in step S5; the growth trend of the distributed photovoltaic open capacity is judged according to the distributed photovoltaic open index range:

[0072] When the current distributed photovoltaic open capacity index is greater than 1, the growth trend of distributed photovoltaic open capacity is good;

[0073] When the current distributed photovoltaic open capacity index is greater than 0.5 and less than or equal to 1, the growth trend of distributed photovoltaic open capacity is moderate;

[0074] When the current distributed photovoltaic open capacity index is less than or equal to 0.5, the growth trend of distributed photovoltaic open capacity is tense;

[0075] When the growth trend of distributed photovoltaic open capacity is good, a first-come, first-served strategy will be adopted for current distributed photovoltaic installation and access, promoting the rapid development of distributed photovoltaic access; when the growth trend of distributed photovoltaic open capacity is moderate, a first-come, first-served strategy will be adopted, but at the same time, the dynamic update and monitoring of the index will be strengthened; when the growth trend of distributed photovoltaic open capacity is tense, the open capacity will be dynamically updated, giving priority to promoting the development of regions with similar medium- and long-term distributed photovoltaic open capacity;

[0076] At preset time intervals, based on the current distributed photovoltaic installation status, steps S3 to S6 are repeated to revise and update the open capacity index of distributed photovoltaics in the distribution network, so as to achieve orderly access of distributed photovoltaics in accordance with the first-come, first-served principle.

[0077] The present invention also provides a system for implementing the photovoltaic access method based on the distributed photovoltaic open capacity index, comprising an indicator construction and weight calculation module, a model acquisition module, a distributed photovoltaic prediction module, an open capacity matching degree calculation module, a distributed photovoltaic open capacity index calculation module, and a photovoltaic access module;

[0078] The indicator construction and weight calculation module constructs the open capacity evaluation indicator system of distributed photovoltaic power distribution network, calculates the weight of each indicator, and uploads the data to the model acquisition module;

[0079] The model acquisition module obtains the distribution network topology model and load forecast results based on the PMS system and dispatch automation system, and uploads the data to the distributed photovoltaic prediction module;

[0080] The distributed photovoltaic prediction module uses the distribution network topology model based on the received data and the distribution network open capacity assessment scenario to calculate the distributed photovoltaic prediction results and upload the data to the open capacity matching calculation module;

[0081] The open capacity matching calculation module calculates the matching degree of the medium-, short-, and long-term open capacity based on the received data, and judges whether the distributed photovoltaic development is reasonable based on the obtained matching degree. If it is reasonable, it proceeds to the next module. If it is not reasonable, it adjusts the load development plan or the distributed photovoltaic access location, then returns to the distributed photovoltaic prediction module, and uploads the data to the distributed photovoltaic open capacity index calculation module;

[0082] The distributed photovoltaic open capacity index calculation module calculates the distributed photovoltaic open capacity index based on the received data and uploads the data to the photovoltaic access module;

[0083] The photovoltaic access module dynamically updates the open capacity index of distributed photovoltaics in the distribution network based on the received data and in a first-come, first-served mechanism, guiding the orderly access of distributed photovoltaics.

[0084] The present invention discloses a photovoltaic access method and system based on the distributed photovoltaic open capacity index, which comprehensively considers the influencing factors of the distributed photovoltaic open capacity of the distribution network, takes into account the short-term and medium-term dynamic evaluation of the distributed photovoltaic open capacity of the distribution network, and obtains the distributed photovoltaic open capacity index until the distributed photovoltaic is accessed in an orderly manner, thereby reducing the impact of the distributed photovoltaic access on the distribution network and improving the stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] Figure 1 Schematic diagram of the process of the present invention;

[0086] Figure 2 Schematic diagram of the structure of the system of the present invention. DETAILED DESCRIPTION

[0087] The present invention provides a photovoltaic access method based on distributed photovoltaic open capacity index, the flow diagram of which is as follows: Figure 1 As shown, the following steps are included:

[0088] S1. Construct an evaluation index system for the open capacity of distributed photovoltaic power generation in the distribution network and calculate the weight of each index, specifically:

[0089] Establish an evaluation index system for the open capacity of distributed photovoltaic power generation in distribution networks and conduct a systematic evaluation of the operation level of distribution network substations; calculate the weights of each indicator in the evaluation index system for the open capacity of distributed photovoltaic power generation in distribution networks based on the analytic hierarchy process and entropy weight method;

[0090] The first-level indicators of the evaluation index system for the open capacity of distributed photovoltaic power distribution networks include growth, reliability, power quality, economy, matching and safety;

[0091] Growth includes the secondary indicator of the growth rate of distributed photovoltaic open capacity; the growth rate of distributed photovoltaic open capacity is the ratio of the current distribution network open capacity to the connected distributed photovoltaic capacity;

[0092] Reliability includes the secondary indicator system average power outage duration; the system average power outage duration is the average power outage duration of the system obtained by Monte Carlo simulation method using typical distributed photovoltaic and load operation curves after the current distribution network is connected to distributed photovoltaic according to the current open capacity method;

[0093] The power quality includes secondary indicators such as voltage qualification rate, three-phase unbalance rate and harmonic distortion rate; the voltage qualification rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves; the three-phase unbalance rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves; the harmonic distortion rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves;

[0094] Economic efficiency includes the secondary indicator line loss rate. The line loss rate is calculated by using typical distributed photovoltaic and load operation curves after the current distribution network is connected to distributed photovoltaic according to the current open capacity.

[0095] The matching degree includes the secondary indicators of short-term open capacity and medium- and long-term open capacity ratio; short-term open capacity refers to the current open capacity of distributed photovoltaics; medium- and long-term open capacity refers to the evaluation of the medium- and long-term open capacity of distributed photovoltaics based on the load forecast results;

[0096] Safety includes secondary indicators: maximum reverse ratio and maximum load rate. The maximum reverse ratio is the maximum reverse ratio of the transformer or line; the maximum load rate is the maximum load rate of the transformer or line;

[0097] The analytic hierarchy process comprises the following steps:

[0098] Construct a pairwise comparison matrix and use the following formula:

[0099]

[0100] a ij >0(i<j)

[0101] aii =1

[0102]

[0103] Among them, A is the pairwise comparison matrix; a ij is the pairwise comparison matrix element, a ij The size of reflects the importance of the i-th indicator compared to the j-th indicator; a ij The value range of is {1,3,5,7,9}, representing the comparison results of “equal”, “slightly”, “obvious”, “strong” and “extreme” respectively; a ij The value is the average of the opinions of several independent experts;

[0104] Calculate the maximum eigenvalue λ of the pairwise comparison matrix A max and the corresponding eigenvector W;

[0105] Calculate the consistency index CI and random consistency index CR using the following formula:

[0106]

[0107] Where n is the order of the pairwise comparison matrix A; RI is the average random consistency index;

[0108] When the random consistency index CR is less than 0.1, the consistency requirement is met;

[0109] The value of the average random consistency index RI corresponds one-to-one to the order n of the pairwise comparison matrix A, specifically:

[0110] When n=1, RI=0;

[0111] When n=2, RI=0;

[0112] When n=3, RI=0.52;

[0113] When n=4, RI=0.89;

[0114] When n=5, RI=1.12;

[0115] When n=6, RI=1.26;

[0116] When n=7, RI=1.36;

[0117] When n=8, RI=1.41;

[0118] When n=9, RI=1.46;

[0119] When n=10, RI=1.49;

[0120] If the pairwise comparison matrix A meets the consistency judgment requirements, the eigenvector W is normalized to obtain the judgment weight of each indicator;

[0121] If the pairwise comparison matrix A does not meet the consistency judgment requirements, communicate with independent experts and correct a ij until the consistency check passes.

[0122] The entropy weight method includes the following steps:

[0123] First, the original data of the indicators in the evaluation index system of the open capacity of distributed photovoltaic power distribution network are standardized to ensure that each indicator is at the same level and expressed using the following formula:

[0124]

[0125] Among them, x is the indicator data; mean(x) is the sample mean; std(x) is the sample standard deviation; z is the standardized indicator data;

[0126] Calculate the information entropy value of each indicator and evaluate the degree of dispersion using the following formula:

[0127]

[0128] Among them, e i is the entropy value of the i-th indicator; n is the number of observations of the i-th indicator; V ij is the observed value of the jth sample of the i-th indicator; e i The value range of is [0,1], which reflects the difference of the i-th indicator. The closer it is to 1, the lower the difference of the indicator.

[0129] Calculate the corresponding weight according to the information entropy value of each indicator, using the following formula

[0130]

[0131] Among them, ω i is the weight of the i-th indicator; m is the total number of indicators.

[0132] S2. Obtain the distribution network topology model and load forecast results based on the PMS system and dispatch automation system;

[0133] S3. Based on the distribution network topology model and load forecast results obtained in step S2, and based on the distribution network open capacity assessment scenario, the distributed photovoltaic forecast results are calculated, specifically:

[0134] Obtain open capacity assessment scenarios for distribution networks, including load history curves, distributed photovoltaic history curves, distribution network power flow calculation models, and typical fault sets;

[0135] Based on the distribution network open capacity assessment scenario and the current load situation, set the maximum tolerance values ​​of the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; using the distribution network topology model obtained in step S2, proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, and obtain the current maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system;

[0136] Based on the load forecast result obtained in step S2, a short- to medium-term load forecast curve and a long-term load forecast curve are obtained; wherein the short- to medium-term load forecast curve is a load forecast curve for 1 to 3 months, and the long-term load forecast curve is a load forecast curve for more than 3 months;

[0137] Based on the distribution network open capacity assessment scenario and the medium- and short-term load forecast curve, set the maximum tolerance values ​​for the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; using the distribution network topology model obtained in step S2, proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, thereby obtaining the medium- and short-term maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system;

[0138] Based on the distribution network open capacity assessment scenario and the long-term load forecast curve, set the maximum tolerance values ​​of the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; use the distribution network topology model obtained in step S2 to proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, thereby obtaining the long-term maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system.

[0139] S4. Based on the distributed photovoltaic prediction results obtained in step S3, calculate the matching degree of the medium-term, short-term and long-term open capacity, and judge whether the distributed photovoltaic development is reasonable based on the obtained matching degree. If it is reasonable, proceed to the next step; if it is not reasonable, adjust the load development plan or distributed photovoltaic access location, and then return to step S3. Specifically:

[0140] Based on the distributed photovoltaic prediction results obtained in step S3, the impact of short-term load and distributed photovoltaic changes on the distribution network flow is evaluated, and the matching degree of short-term and long-term available capacity is calculated using the following formula:

[0141]

[0142] Among them, S 中短期 The distributed photovoltaic capacity that can be opened within 1 to 3 months; S 长期 The distributed photovoltaic capacity can be opened for more than 3 months;

[0143] If I≤1, the load development plan and the distributed photovoltaic access location are relatively reasonable, and the next step is entered;

[0144] If I>1, adjust the load development plan and the distributed photovoltaic access location, and return to step S3.

[0145] S5. Based on the weights of the indicators in the evaluation index system of the distributed photovoltaic open capacity of the distribution network obtained in step S1 and the distributed photovoltaic prediction results obtained in step S3, the distributed photovoltaic open capacity evaluation index results are calculated, specifically:

[0146] According to the weights of the indicators obtained in step S1 and the prediction results of the indicators of the distribution network distributed photovoltaic open capacity evaluation index system corresponding to the current maximum distributed photovoltaic open capacity obtained in step S3, the weighted sum of the indicators is performed to obtain the distributed photovoltaic open capacity index in the current state.

[0147] S6. Based on the distributed photovoltaic open capacity index obtained in step S5 and the growth trend of distributed photovoltaic open capacity, dynamically update the distributed photovoltaic open capacity index of the distribution network to guide the orderly access of distributed photovoltaics, specifically:

[0148] According to the distributed photovoltaic open capacity index obtained in step S5, the growth trend of the distributed photovoltaic open capacity is announced; the growth trend of the distributed photovoltaic open capacity is judged according to the distributed photovoltaic open index range:

[0149] When the current distributed photovoltaic open capacity index is greater than 1, the growth trend of distributed photovoltaic open capacity is good;

[0150] When the current distributed photovoltaic open capacity index is greater than 0.5 and less than or equal to 1, the growth trend of distributed photovoltaic open capacity is moderate;

[0151] When the current distributed photovoltaic open capacity index is less than or equal to 0.5, the growth trend of distributed photovoltaic open capacity is tense;

[0152] When the growth trend of distributed photovoltaic open capacity is good, a first-come, first-served strategy will be adopted for current distributed photovoltaic installation and access, promoting the rapid development of distributed photovoltaic access; when the growth trend of distributed photovoltaic open capacity is moderate, a first-come, first-served strategy will be adopted, but at the same time, the dynamic update and monitoring of the index will be strengthened; when the growth trend of distributed photovoltaic open capacity is tense, the open capacity will be dynamically updated, giving priority to promoting the development of regions with similar medium- and long-term distributed photovoltaic open capacity;

[0153] At preset time intervals, based on the current distributed photovoltaic installation status, steps S3 to S6 are repeated to revise and update the open capacity index of distributed photovoltaics in the distribution network, so as to achieve orderly access of distributed photovoltaics in accordance with the first-come, first-served principle.

[0154] The present invention also provides a system for implementing the photovoltaic access method based on the distributed photovoltaic open capacity index, the structural diagram of which is shown in FIG. Figure 2 As shown, it includes indicator construction and weight calculation module, model acquisition module, distributed photovoltaic prediction module, open capacity matching degree calculation module, distributed photovoltaic open capacity index calculation module, and photovoltaic access module;

[0155] The indicator construction and weight calculation module constructs the open capacity evaluation indicator system of distributed photovoltaic power distribution network, calculates the weight of each indicator, and uploads the data to the model acquisition module;

[0156] The model acquisition module obtains the distribution network topology model and load forecast results based on the PMS system and dispatch automation system, and uploads the data to the distributed photovoltaic prediction module;

[0157] The distributed photovoltaic prediction module uses the distribution network topology model based on the received data and the distribution network open capacity assessment scenario to calculate the distributed photovoltaic prediction results and upload the data to the open capacity matching calculation module;

[0158] The open capacity matching calculation module calculates the matching degree of the medium-, short-, and long-term open capacity based on the received data, and judges whether the distributed photovoltaic development is reasonable based on the obtained matching degree. If it is reasonable, it proceeds to the next module. If it is not reasonable, it adjusts the load development plan or the distributed photovoltaic access location, then returns to the distributed photovoltaic prediction module, and uploads the data to the distributed photovoltaic open capacity index calculation module;

[0159] The distributed photovoltaic open capacity index calculation module calculates the distributed photovoltaic open capacity index based on the received data and uploads the data to the photovoltaic access module;

[0160] The photovoltaic access module dynamically updates the distribution network's distributed photovoltaic open capacity index based on the received data and the growth trend of the distributed photovoltaic open capacity according to a first-come, first-served mechanism, guiding the orderly access of distributed photovoltaics.

Claims

1. A photovoltaic access method based on distributed photovoltaic open capacity index, characterized in that: The following steps are involved: S1. Construct an evaluation index system for the open capacity of distributed photovoltaic power generation in distribution networks and calculate the weights of each index; S2. Obtain distribution network topology model and load forecast results based on the PMS system and dispatch automation system; S3. Based on the distribution network topology model obtained in step S2 and the distribution network open capacity assessment scenario, the distributed photovoltaic forecast results are calculated; S4. Based on the distributed PV forecast results obtained in step S3, calculate the matching degree of short-term and long-term available capacity. Based on the obtained matching degree, determine whether the distributed PV development is reasonable. If so, proceed to the next step. If not, adjust the load development plan or the distributed PV access location, and then return to step S3. S5. Calculate the distributed photovoltaic open capacity index based on the weights of each indicator in the distribution network distributed photovoltaic open capacity evaluation index system obtained in step S1 and the distributed photovoltaic prediction results obtained in step S3; S6. Based on the distributed photovoltaic open capacity index obtained in step S5, announce the growth trend of distributed photovoltaic open capacity, dynamically update the distributed photovoltaic open capacity index of the distribution network, and guide the orderly access of distributed photovoltaic; Step S4 is specifically as follows: Based on the prediction results of the indicators of the evaluation index system for the open capacity of distributed photovoltaic power distribution network corresponding to different distributed photovoltaic addition situations obtained in step S3, the impact of short-term load and distributed photovoltaic changes on the power flow of the distribution network is evaluated, and the matching degree of the short-term and long-term open capacity is calculated using the following formula: in, The available capacity of distributed photovoltaics within 1 to 3 months; The distributed photovoltaic capacity can be opened for more than 3 months; like , then the load development plan and the distributed photovoltaic access location are relatively reasonable, and proceed to the next step; like , then adjust the load development plan and the distributed photovoltaic access location, and return to step S3.

2. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 1 is characterized in that: Step S1 is specifically as follows: establishing an evaluation index system for the open capacity of distributed photovoltaic power generation in the distribution network, and systematically evaluating the operation level of the distribution network substation; and calculating the weight of each index in the evaluation index system for the open capacity of distributed photovoltaic power generation in the distribution network based on the analytic hierarchy process and the entropy weight method.

3. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 2 is characterized in that: The first-level indicators of the evaluation index system for the open capacity of distributed photovoltaic power distribution networks include growth, reliability, power quality, economy, matching and safety; Growth includes the secondary indicator of the growth rate of distributed photovoltaic open capacity; the growth rate of distributed photovoltaic open capacity is the ratio of the current distribution network open capacity to the connected distributed photovoltaic capacity; Reliability includes the secondary indicator system average power outage duration; the system average power outage duration is the average power outage duration of the system obtained by Monte Carlo simulation method using typical distributed photovoltaic and load operation curves after the current distribution network is connected to distributed photovoltaic according to the current open capacity method; The power quality includes secondary indicators such as voltage qualification rate, three-phase unbalance rate and harmonic distortion rate; the voltage qualification rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves; the three-phase unbalance rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves; the harmonic distortion rate is obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity, using typical distributed photovoltaic and load operation curves; Economic efficiency includes the secondary indicator line loss rate. The line loss rate is calculated by using typical distributed photovoltaic and load operation curves after the current distribution network is connected to distributed photovoltaic according to the current open capacity. The matching degree includes the secondary indicators of short-term open capacity and medium- and long-term open capacity ratio; short-term open capacity refers to the current open capacity of distributed photovoltaics; medium- and long-term open capacity refers to the evaluation of the medium- and long-term open capacity of distributed photovoltaics based on the load forecast results; Safety includes the secondary indicators of maximum reverse transmission ratio and maximum load rate; the maximum reverse transmission ratio is the maximum reverse transmission ratio of the transformer or line; the maximum load rate is the maximum load rate of the transformer or line.

4. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 2, characterized in that: The analytic hierarchy process comprises the following steps: Construct a pairwise comparison matrix and use the following formula: in, is a pairwise comparison matrix; is the pairwise comparison matrix element, The size reflects the Compared with the first The importance of the indicator; The value range is , representing the comparison results of "equal", "slightly", "obvious", "strong" and "extreme" respectively; The value is the average of the opinions of several independent experts; Calculate the pairwise comparison matrix The maximum eigenvalue of and the corresponding eigenvector ; Calculating consistency index and random consistency index , expressed using the following formula: in, is a pairwise comparison matrix The order of is the average random consistency index; When the random consistency index When it is less than 0.1, the consistency requirement is met; Average random consistency index The value of the pairwise comparison matrix The order of One-to-one correspondence, specifically: when hour, ; when hour, ; when hour, ; when hour, ; when hour, ; when hour, ; when hour, ; when hour, ; when hour, ; when hour, ; If the pairwise comparison matrix Satisfy the consistency judgment requirements, and the feature vector Perform normalization processing to obtain the judgment weight of each indicator; If the pairwise comparison matrix If the consistency determination requirements are not met, communicate with independent experts and make corrections until the consistency check passes.

5. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 2 is characterized in that: The entropy weight method includes the following steps: First, the original data of the indicators in the evaluation index system of the open capacity of distributed photovoltaic power distribution network are standardized to ensure that each indicator is at the same level and expressed using the following formula: Among them, x is the indicator data; is the sample mean; is the sample standard deviation; z is the standardized indicator data; Calculate the information entropy value of each indicator and evaluate the degree of dispersion using the following formula: in, For the The entropy value of each indicator; For the The number of observations for each indicator; For the The first indicator The observed value of a sample; The value range is , reflecting the The closer the difference between the indicators is to 1, the lower the difference between the indicators is. Calculate the corresponding weight according to the information entropy value of each indicator, using the following formula in, For the The weight of each indicator; is the total number of indicators.

6. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 1, characterized in that: Step S3 is specifically as follows: Obtain open capacity assessment scenarios for distribution networks, including load history curves, distributed photovoltaic history curves, distribution network power flow calculation models, and typical fault sets; Based on the distribution network open capacity assessment scenario and the current load situation, set the maximum tolerance values ​​of the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; using the distribution network topology model obtained in step S2, proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, and obtain the current maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system; Based on the load forecast result obtained in step S2, a short- to medium-term load forecast curve and a long-term load forecast curve are obtained; wherein the short- to medium-term load forecast curve is a load forecast curve for 1 to 3 months, and the long-term load forecast curve is a load forecast curve for more than 3 months; Based on the distribution network open capacity assessment scenario and the medium- and short-term load forecast curve, set the maximum tolerance values ​​for the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; using the distribution network topology model obtained in step S2, proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, thereby obtaining the medium- and short-term maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system; Based on the distribution network open capacity assessment scenario and the long-term load forecast curve, set the maximum tolerance values ​​of the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system; use the distribution network topology model obtained in step S2 to proportionally increase the distributed photovoltaic access capacity until the average power outage duration, voltage qualification rate, three-phase unbalance, harmonic distortion rate, and line loss rate of the indicator system reach the maximum tolerance values ​​or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint values, thereby obtaining the long-term maximum distributed photovoltaic open capacity and the corresponding prediction results of each indicator of the distribution network distributed photovoltaic open capacity evaluation indicator system.

7. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 1, characterized in that: Step S5 is specifically as follows: According to the weights of the indicators obtained in step S1 and the prediction results of the indicators of the distribution network distributed photovoltaic open capacity evaluation index system corresponding to the current maximum distributed photovoltaic open capacity obtained in step S3, the weighted sum of the indicators is performed to obtain the distributed photovoltaic open capacity index in the current state.

8. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 1, characterized in that: Step S6 specifically includes: announcing the growth trend of the distributed photovoltaic open capacity according to the distributed photovoltaic open capacity index obtained in step S5; the growth trend of the distributed photovoltaic open capacity is judged according to the distributed photovoltaic open index range: When the current distributed photovoltaic open capacity index is greater than 1, the growth trend of distributed photovoltaic open capacity is good; When the current distributed photovoltaic open capacity index is greater than 0.5 and less than or equal to 1, the growth trend of distributed photovoltaic open capacity is moderate; When the current distributed photovoltaic open capacity index is less than or equal to 0.5, the growth trend of distributed photovoltaic open capacity is tense; When the growth trend of distributed photovoltaic open capacity is good, a first-come, first-served strategy will be adopted for current distributed photovoltaic installation and access, promoting the rapid development of distributed photovoltaic access; when the growth trend of distributed photovoltaic open capacity is moderate, a first-come, first-served strategy will be adopted, but at the same time, the dynamic update and monitoring of the index will be strengthened; when the growth trend of distributed photovoltaic open capacity is tense, the open capacity will be dynamically updated, giving priority to promoting the development of regions with similar medium- and long-term distributed photovoltaic open capacity; At preset time intervals, based on the current distributed photovoltaic installation status, steps S3 to S6 are repeated to revise and update the open capacity index of distributed photovoltaics in the distribution network, so as to achieve orderly access of distributed photovoltaics in accordance with the first-come, first-served principle.

9. A system for implementing the photovoltaic access method based on the distributed photovoltaic open capacity index according to any one of claims 1 to 8, characterized in that: It includes indicator construction and weight calculation module, model acquisition module, distributed photovoltaic prediction module, open capacity matching calculation module, distributed photovoltaic open capacity index calculation module, and photovoltaic access module; The indicator construction and weight calculation module constructs the open capacity evaluation indicator system of distributed photovoltaic power distribution network, calculates the weight of each indicator, and uploads the data to the model acquisition module; The model acquisition module obtains the distribution network topology model and load forecast results based on the PMS system and dispatch automation system, and uploads the data to the distributed photovoltaic prediction module; The distributed photovoltaic prediction module uses the distribution network topology model based on the received data and the distribution network open capacity assessment scenario to calculate the distributed photovoltaic prediction results and upload the data to the open capacity matching calculation module; The open capacity matching calculation module calculates the matching degree of the medium-, short-, and long-term open capacity based on the received data, and judges whether the distributed photovoltaic development is reasonable based on the obtained matching degree. If it is reasonable, it proceeds to the next module. If it is not reasonable, it adjusts the load development plan or the distributed photovoltaic access location, then returns to the distributed photovoltaic prediction module, and uploads the data to the distributed photovoltaic open capacity index calculation module; The distributed photovoltaic open capacity index calculation module calculates the distributed photovoltaic open capacity index based on the received data and uploads the data to the photovoltaic access module; The photovoltaic access module dynamically updates the open capacity index of distributed photovoltaics in the distribution network based on the received data and in a first-come, first-served mechanism, guiding the orderly access of distributed photovoltaics.

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