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

Abstract

The invention discloses a photovoltaic access method based on a distributed photovoltaic openable capacity index, and the method comprises the following steps: constructing a distributed photovoltaic openable capacity evaluation index system of a power distribution network, and carrying out the calculation to obtain the weight of each index; obtaining a power distribution network topology model and a load prediction result; calculating to obtain a distributed photovoltaic prediction result; calculating the matching degree of the medium-short-term and long-term openable capacities, and judging whether the distributed photovoltaic development is reasonable or not; calculating a distributed photovoltaic openable capacity evaluation index result; and dynamically updating the distributed photovoltaic openable capacity index of the power distribution network according to a first-arrival first-arrival mechanism, and guiding to complete ordered access of the distributed photovoltaic. The invention also discloses a system for realizing the photovoltaic access method based on the distributed photovoltaic openable capacity index. According to the method, influence factors of the distributed photovoltaic openable capacity of the power distribution network are comprehensively considered, short-term and medium-and-long-term dynamic evaluation of the distributed photovoltaic openable capacity of the power distribution network is considered, the influence of distributed photovoltaic access on the power distribution network is reduced, and the stability of the power distribution network is improved.

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 photovoltaic refers to a power generation system with a smaller installed capacity that uses decentralized resources and is usually connected to a power grid with a voltage level of less than 35 kV or lower. It uses photovoltaic modules to directly convert solar energy into electrical energy. Its operating mode is characterized by self-generation and self-use on the user side, excess electricity being connected to the grid, and balanced regulation in the distribution system.

[0003] Distributed photovoltaic power generation follows the principles of adapting measures to local conditions, clean and efficient, decentralized layout, and nearby utilization, making full use of local solar energy resources to replace and reduce fossil energy consumption. It has the characteristics of low output power, low pollution, and outstanding environmental benefits. It can be built near rural areas, pastoral areas, mountainous areas, and commercial areas of large, medium and small cities to achieve coexistence of power generation and electricity consumption.

[0004] With the large-scale access of high-penetration distributed photovoltaic power to distribution network substations, distribution network substations are facing active operation problems such as heavy load and overload, and reactive safety problems such as bus voltage exceeding the limit. At present, there is a lack of effective evaluation index system for the open capacity of distributed photovoltaic power in distribution network. There are differences in the consideration factors of the open capacity of distribution network in the short-term and medium-term, and the evaluation results are also different. It is difficult to scientifically and effectively release the dynamic index of the open capacity of distributed photovoltaic power in distribution network according to the principle of "first come, first served", which is not conducive to guiding the scientific and orderly access of distributed photovoltaic power. 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 the first-come-first-served open capacity evaluation, and guide the scientific and orderly access of distributed photovoltaics.

[0006] A second objective 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. Based on the PMS system and dispatching automation system, obtain the distribution network topology model and load forecast results;

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

[0011] S4. According to 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 development of distributed photovoltaic 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 the distributed photovoltaic access location, and then return to step S3;

[0012] S5. Calculate the distributed photovoltaic open capacity index according to the weights of each indicator of the distribution network distributed photovoltaic open capacity evaluation index system obtained in step S1 and the distributed photovoltaic prediction result 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, the distributed photovoltaic open capacity index of the distribution network is dynamically updated to guide the orderly access of distributed photovoltaics.

[0014] 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; 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;

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

[0016] Growth includes the secondary indicator distributed photovoltaic open capacity growth ratio; the distributed photovoltaic open capacity growth ratio 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 after the current distribution network is connected to distributed photovoltaics according to the current open capacity mode, using typical distributed photovoltaics and load operation curves;

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

[0019] Economic efficiency includes the secondary indicator line loss rate; the line loss rate is the line loss rate of the distribution network obtained by statistical calculation 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;

[0020] The matching degree includes the ratio of short-term open capacity to medium- and long-term open capacity, which are the secondary indicators. Short-term open capacity refers to the current open capacity of distributed photovoltaics. Medium- and long-term open capacity refers to the open capacity of distributed photovoltaics in the medium and long term, which is evaluated based on the load forecast results.

[0021] Safety includes the secondary indicators of maximum reverse transmission ratio and maximum load rate. The maximum reverse transmission ratio is the maximum transmission 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 a 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 comprises 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 ith indicator; n is the number of observations of the ith indicator; V ij is the observed value of the jth sample of the ith 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 ith indicator; m is the total number of indicators.

[0057] Step S3 is specifically as follows:

[0058] Obtain the open capacity assessment scenarios of the distribution network, 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; use the distribution network topology model obtained in step S2 to increase the distributed photovoltaic access capacity in proportion 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 value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the current maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The prediction results of each indicator;

[0060] Based on the load forecasting result obtained in step S2, a short- to medium-term load forecasting curve and a long-term load forecasting curve are obtained; wherein the short- to medium-term load forecasting curve is a load forecasting curve for 1 to 3 months, and the long-term load forecasting curve is a load forecasting 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 ​​of the average power outage duration, voltage qualification rate, three-phase imbalance, harmonic distortion rate and line loss rate of the indicator system; use the distribution network topology model obtained in step S2 to increase the distributed photovoltaic access capacity in proportion until the average power outage duration, voltage qualification rate, three-phase imbalance, harmonic distortion rate and line loss rate of the indicator system reach the maximum tolerance value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the medium- and short-term maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The forecast results of each indicator;

[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 increase the distributed photovoltaic access capacity in proportion 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 value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the long-term maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The prediction results of each indicator.

[0063] Step S4 is specifically as follows:

[0064] According to 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 open 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 available capacity for distributed photovoltaic power generation for more than 3 months;

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

[0068] If I>1, the load development plan and the distributed photovoltaic access location are adjusted, and the process returns 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: according to the distributed photovoltaic open capacity index obtained in step S5, announcing the growth trend of distributed photovoltaic open capacity; the growth trend of distributed photovoltaic open capacity is judged according to the distributed photovoltaic open index interval:

[0072] When the index of the currently available distributed photovoltaic capacity is greater than 1, the growth trend of the available distributed photovoltaic 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 the open capacity of distributed photovoltaics is good, a first-come-first-served strategy will be adopted for the current distributed photovoltaic access, promoting the rapid development of distributed photovoltaic access; when the growth trend of the open capacity of distributed photovoltaics 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 the open capacity of distributed photovoltaics is tense, the open capacity will be dynamically updated, giving priority to promoting the development of regions close to the open capacity of distributed photovoltaics in the medium and long term;

[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, including 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 generation in the 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 according to 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-term, short-term and long-term open capacity based on the received data, and judges whether the development of distributed photovoltaics is reasonable based on the obtained matching degree. If it is reasonable, it will enter the next module. If it is unreasonable, it will adjust the load development plan or the distributed photovoltaic access location, and then return to the distributed photovoltaic prediction module, and upload 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 according to the received data and the first-come-first-served mechanism, and guides the orderly access of distributed photovoltaics.

[0084] The present invention discloses a photovoltaic access method and system based on a distributed photovoltaic open capacity index, which comprehensively considers the influencing factors of the open capacity of the distributed photovoltaic power distribution network, takes into account the short-term and medium-term dynamic evaluation of the open capacity of the distributed photovoltaic power distribution network, and obtains the distributed photovoltaic open capacity index until the distributed photovoltaic power 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 It is a schematic diagram of the process of the present invention;

[0086] Figure 2 It is a 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 a distributed photovoltaic open capacity index, and its flow chart 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 distribution networks and calculate the weight of each index, which is as follows:

[0089] Establish an evaluation index system for the open capacity of distributed photovoltaic power generation in distribution networks, and systematically evaluate the operation level of distribution network substations; calculate the weights of each index 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 generation in the distribution network include growth, reliability, power quality, economy, matching and safety;

[0091] Growth includes the secondary indicator distributed photovoltaic open capacity growth ratio; the distributed photovoltaic open capacity growth ratio 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 after the current distribution network is connected to distributed photovoltaics according to the current open capacity mode, using typical distributed photovoltaics and load operation curves;

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

[0094] Economic efficiency includes the secondary indicator line loss rate; the line loss rate is the line loss rate of the distribution network obtained by statistical calculation 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;

[0095] The matching degree includes the ratio of short-term open capacity to medium- and long-term open capacity, which are the secondary indicators. Short-term open capacity refers to the current open capacity of distributed photovoltaics. Medium- and long-term open capacity refers to the open capacity of distributed photovoltaics in the medium and long term, which is evaluated based on the load forecast results.

[0096] Safety includes the secondary indicators of maximum reverse transmission ratio and maximum load rate. The maximum reverse transmission ratio is the maximum transmission 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 a 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 comprises 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 ith indicator; n is the number of observations of the ith indicator; V ij is the observed value of the jth sample of the ith 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 ith indicator; m is the total number of indicators.

[0132] S2. Based on the PMS system and dispatching automation system, obtain the distribution network topology model and load forecast results;

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

[0134] Obtain the open capacity assessment scenarios of the distribution network, 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; use the distribution network topology model obtained in step S2 to increase the distributed photovoltaic access capacity in proportion 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 value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the current maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The prediction results of each indicator;

[0136] Based on the load forecasting result obtained in step S2, a short- to medium-term load forecasting curve and a long-term load forecasting curve are obtained; wherein the short- to medium-term load forecasting curve is a load forecasting curve for 1 to 3 months, and the long-term load forecasting curve is a load forecasting 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 ​​of the average power outage duration, voltage qualification rate, three-phase imbalance, harmonic distortion rate and line loss rate of the indicator system; use the distribution network topology model obtained in step S2 to increase the distributed photovoltaic access capacity in proportion until the average power outage duration, voltage qualification rate, three-phase imbalance, harmonic distortion rate and line loss rate of the indicator system reach the maximum tolerance value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the medium- and short-term maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The forecast results of each indicator;

[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 increase the distributed photovoltaic access capacity in proportion 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 value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the long-term maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The prediction results of each indicator.

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

[0140] According to 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 open 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 available capacity for distributed photovoltaic power generation for more than 3 months;

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

[0144] If I>1, the load development plan and the distributed photovoltaic access location are adjusted, and the process returns to step S3.

[0145] S5. According to the weights of each indicator of the evaluation index system of the open capacity of the distributed photovoltaic power distribution network obtained in step S1 and the distributed photovoltaic prediction result obtained in step S3, the evaluation index result of the open capacity of the distributed photovoltaic power distribution network is calculated, which is 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, the distributed photovoltaic open capacity index of the distribution network is dynamically updated 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 distributed photovoltaic open capacity is announced; the growth trend of distributed photovoltaic open capacity is judged according to the distributed photovoltaic open index range:

[0149] When the index of the currently available distributed photovoltaic capacity is greater than 1, the growth trend of the available distributed photovoltaic 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 the open capacity of distributed photovoltaics is good, a first-come-first-served strategy will be adopted for the current distributed photovoltaic access, promoting the rapid development of distributed photovoltaic access; when the growth trend of the open capacity of distributed photovoltaics 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 the open capacity of distributed photovoltaics is tense, the open capacity will be dynamically updated, giving priority to promoting the development of regions close to the open capacity of distributed photovoltaics in the medium and long term;

[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, and its structural schematic diagram is as follows: Figure 2 As shown, it includes 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;

[0155] The indicator construction and weight calculation module constructs the open capacity evaluation indicator system of distributed photovoltaic power generation in the 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 according to 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-term, short-term and long-term open capacity based on the received data, and judges whether the development of distributed photovoltaics is reasonable based on the obtained matching degree. If it is reasonable, it will enter the next module. If it is unreasonable, it will adjust the load development plan or the distributed photovoltaic access location, and then return to the distributed photovoltaic prediction module, and upload 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 distributed photovoltaic open capacity index according to the received data and the growth trend of distributed photovoltaic open capacity according to the first-come-first-served mechanism, and guides 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 weight of each index; S2. Based on the PMS system and dispatching automation system, obtain the distribution network topology model and load forecast results; S3. According to the distribution network topology model obtained in step S2, based on the distribution network open capacity assessment scenario, the distributed photovoltaic prediction results are calculated; S4. According to 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 development of distributed photovoltaic 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 the distributed photovoltaic access location, and then return to step S3; S5. Calculate the distributed photovoltaic open capacity index according to the weights of each indicator of the distribution network distributed photovoltaic open capacity evaluation index system obtained in step S1 and the distributed photovoltaic prediction result obtained in step S3; S6. Based on the distributed photovoltaic open capacity index obtained in step S5, the growth trend of distributed photovoltaic open capacity is announced, the distributed photovoltaic open capacity index of the distribution network is dynamically updated, and the orderly access of distributed photovoltaic is guided.

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 generation in the distribution network include growth, reliability, power quality, economy, matching and safety; Growth includes the secondary indicator distributed photovoltaic open capacity growth ratio; the distributed photovoltaic open capacity growth ratio 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 after the current distribution network is connected to distributed photovoltaics according to the current open capacity mode, using typical distributed photovoltaics and load operation curves; The power quality includes the secondary indicators of voltage qualification rate, three-phase unbalance rate and harmonic distortion rate; the voltage qualification rate is the voltage qualification rate of the distribution network obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity mode, using typical distributed photovoltaic and load operation curves; the three-phase unbalance rate is the three-phase unbalance rate of the distribution network obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity mode, using typical distributed photovoltaic and load operation curves; the harmonic distortion rate is the harmonic distortion rate of the distribution network obtained by statistical calculation after the current distribution network is connected to distributed photovoltaic according to the current open capacity mode, using typical distributed photovoltaic and load operation curves; Economic efficiency includes the secondary indicator line loss rate; the line loss rate is the line loss rate of the distribution network obtained by statistical calculation 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 matching degree includes the ratio of short-term open capacity to medium- and long-term open capacity, which are the secondary indicators. Short-term open capacity refers to the current open capacity of distributed photovoltaics. Medium- and long-term open capacity refers to the open capacity of distributed photovoltaics in the medium and long term, which is evaluated 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 is characterized in that: The analytic hierarchy process comprises the following steps: Construct a pairwise comparison matrix and use the following formula: a ij >0(i<j) a ii ＝1 Among them, A is a 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; Calculate the maximum eigenvalue λ of the pairwise comparison matrix A max and the corresponding eigenvector W; Calculate the consistency index CI and random consistency index CR using the following formula: Where n is the order of the pairwise comparison matrix A; RI is the average random consistency index; When the random consistency index CR is less than 0.1, the consistency requirement is met; The value of the average random consistency index RI corresponds one-to-one to the order n of the pairwise comparison matrix A, specifically: When n=1, RI=0; When n=2, RI=0; When n=3, RI=0.52; When n=4, RI=0.89; When n=5, RI=1.12; When n=6, RI=1.26; When n=7, RI=1.36; When n=8, RI=1.41; When n=9, RI=1.46; When n=10, RI=1.49; If the pairwise comparison matrix A meets the consistency judgment requirements, the eigenvector W is normalized to obtain the judgment weight of each indicator; 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.

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 comprises 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; mean(x) is the sample mean; std(x) 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: Among them, e i is the entropy value of the ith indicator; n is the number of observations of the ith indicator; V ij is the observed value of the jth sample of the ith 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. Calculate the corresponding weight according to the information entropy value of each indicator, using the following formula Among them, ω i is the weight of the ith indicator; m is the total number of indicators.

6. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 1 is characterized in that: Step S3 is specifically as follows: Obtain the open capacity assessment scenarios of the distribution network, 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; use the distribution network topology model obtained in step S2 to increase the distributed photovoltaic access capacity in proportion 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 value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the current maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The prediction results of each indicator; Based on the load forecasting result obtained in step S2, a short- to medium-term load forecasting curve and a long-term load forecasting curve are obtained; wherein the short- to medium-term load forecasting curve is a load forecasting curve for 1 to 3 months, and the long-term load forecasting curve is a load forecasting 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 ​​of the average power outage duration, voltage qualification rate, three-phase imbalance, harmonic distortion rate and line loss rate of the indicator system; use the distribution network topology model obtained in step S2 to increase the distributed photovoltaic access capacity in proportion until the average power outage duration, voltage qualification rate, three-phase imbalance, harmonic distortion rate and line loss rate of the indicator system reach the maximum tolerance value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the medium- and short-term maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The forecast results of each indicator; 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 increase the distributed photovoltaic access capacity in proportion 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 value or the maximum reverse transmission ratio and maximum load rate of the indicator reach the maximum constraint value, and obtain the long-term maximum distributed photovoltaic open capacity and the corresponding distribution network distributed photovoltaic open capacity evaluation indicator system The prediction results of each indicator.

7. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 1 is characterized in that: Step S4 is specifically as follows: According to the prediction results of each indicator of the evaluation index system of the distributed photovoltaic open capacity of the 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 distribution network flow is evaluated, and the matching degree of the medium-term, short-term and long-term open capacity is calculated. The following formula is used for calculation: Among them, S 中短期 The distributed photovoltaic capacity that can be opened within 1 to 3 months; S 长期 The available capacity for distributed photovoltaic power generation for more than 3 months; If I≤1, the load development plan and the distributed photovoltaic access location are relatively reasonable, and proceed to the next step; If I>1, the load development plan and the distributed photovoltaic access location are adjusted, and the process returns to step S3.

8. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 1 is 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.

9. The photovoltaic access method based on the distributed photovoltaic open capacity index according to claim 1 is characterized in that: Step S6 specifically includes: according to the distributed photovoltaic open capacity index obtained in step S5, announcing the growth trend of distributed photovoltaic open capacity; the growth trend of distributed photovoltaic open capacity is judged according to the distributed photovoltaic open index interval: When the index of the currently available distributed photovoltaic capacity is greater than 1, the growth trend of the available distributed photovoltaic 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 the open capacity of distributed photovoltaics is good, a first-come-first-served strategy will be adopted for the current distributed photovoltaic access, promoting the rapid development of distributed photovoltaic access; when the growth trend of the open capacity of distributed photovoltaics 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 the open capacity of distributed photovoltaics is tense, the open capacity will be dynamically updated, giving priority to promoting the development of regions close to the open capacity of distributed photovoltaics in the medium and long term; 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.

10. A system for implementing the photovoltaic access method based on the distributed photovoltaic open capacity index as described in any one of claims 1 to 9, characterized in that: 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; The indicator construction and weight calculation module constructs the open capacity evaluation indicator system of distributed photovoltaic power generation in the 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 according to 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-term, short-term and long-term open capacity based on the received data, and judges whether the development of distributed photovoltaics is reasonable based on the obtained matching degree. If it is reasonable, it will enter the next module. If it is unreasonable, it will adjust the load development plan or the distributed photovoltaic access location, and then return to the distributed photovoltaic prediction module, and upload 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 according to the received data and the first-come-first-served mechanism, and guides the orderly access of distributed photovoltaics.

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