CN117578606A - Heavy overload early warning method for distributed photovoltaic access distribution network substation - Google Patents
Heavy overload early warning method for distributed photovoltaic access distribution network substation Download PDFInfo
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Abstract
The invention relates to a heavy overload early warning method for a distributed photovoltaic access power distribution network substation. Firstly, analyzing output synchronous rate coefficients of distributed photovoltaics in a power distribution network area in a larger output period, analyzing and obtaining a photovoltaic output average coefficient of a month through the number of sunny days in a target month, and calculating the probability that the average value of the photovoltaic output synchronous rate coefficients in the daily analysis period is larger than the average value of the output coefficients of the month in the sunny days of the month; then calculating to obtain the value range of the component capacity of the regional power grid targeted annual distributed photovoltaic development and the critical development capacity of the distributed photovoltaic based on the future regional power grid distributed photovoltaic and load development conditions and by considering the capacity and the capacity ratio of the distributed photovoltaic direct current side; then analyzing the load rate conditions of the power distribution network transformer substation in different scenes, and carrying out early warning on the overload or overload of the transformer substation in different scenes; and finally, providing regional power grid distributed photovoltaic development efficiency indexes to represent regional distributed photovoltaic development efficiency.
Description
Technical Field
The invention relates to a heavy overload early warning method for a distributed photovoltaic access power distribution network substation.
Background
With the access of high proportion of renewable energy sources and the complexity of user electricity behavior, source-load randomness and volatility present great challenges for power system planning, operation and scheduling. The novel power distribution system taking new energy as a main body is characterized in that the proportion of new energy sources with strong uncertainty such as wind, light and the like is greatly increased due to revolutionary change of a power supply structure, the proportion of fossil fuel power sources with strong flexibility is greatly reduced, and the power supply system adapts to the new requirement that the high uncertainty of the power supply becomes a construction elastic power grid.
Due to the intermittent and fluctuating characteristics of the self-output of the distributed photovoltaic, the power distribution network capability and the power quality face a great challenge along with the increasing proportion of the distributed photovoltaic to be connected into the power distribution network. The high-proportion distributed photovoltaic access has great influence on the safe and stable operation of the power distribution network, and a series of problems such as overload safety risk of the distribution transformer, power flow inverted transmission of the power grid, overhigh terminal voltage and the like easily occur. Therefore, in order to ensure safe and stable operation of the system and improve the distributed photovoltaic digestion capability, a power distribution network digestion evaluation analysis method and a power distribution network heavy overload early warning method of large-scale distributed photovoltaic access are required to be researched.
Disclosure of Invention
The invention aims to provide the distribution network transformer substation heavy overload early warning method based on the distribution network distributed photovoltaic development condition, which can early warn the distribution network transformer substation heavy load or overload under different distribution photovoltaic development scales, can provide theoretical basis for power grid planning personnel in distribution network distributed photovoltaic access analysis work, and has very important engineering practice significance.
In order to achieve the above purpose, the technical scheme of the invention is as follows: the method comprises the steps of firstly analyzing output synchronous rate coefficients of distributed photovoltaics in a power distribution network region in a period with larger output based on historical operation data, analyzing the number of days of sunny days in a target month to obtain a photovoltaic output average coefficient of the month, and calculating the probability that the average value of the photovoltaic output synchronous rate coefficients in the analysis period of each day is larger than the average value of the output coefficients of the month in the sunny days of the month; then calculating to obtain the value range of the component capacity of the regional power grid targeted annual distributed photovoltaic development and the critical development capacity of the distributed photovoltaic based on the future regional power grid distributed photovoltaic and load development conditions and by considering the capacity and the capacity ratio of the distributed photovoltaic direct current side; then analyzing the load rate conditions of the power distribution network transformer substation in different scenes, and carrying out early warning on the overload or overload of the transformer substation in different scenes; and finally, providing regional power grid distributed photovoltaic development efficiency indexes to represent regional distributed photovoltaic development efficiency.
In an embodiment of the present invention, the specific implementation manner of analyzing the output time coefficient of the distributed photovoltaic in the power distribution network area in the period with larger output time, analyzing the number of days of a sunny day in a target month to obtain the average output coefficient of the photovoltaic in the month, and calculating the probability that the average value of the photovoltaic output time coefficient in the analysis period per day is greater than the average value of the output coefficients in the month in the sunny day of the month is as follows:
the photovoltaic output coefficient of the study period is analyzed and studied on sunny days, and the photovoltaic output coefficient is shown in the following formula:
α＝{α 1 ，α 2 ，…，α i ,…,α 16 }i∈(1,16) (1)
wherein, alpha represents a synchronous rate coefficient set of the photovoltaic output in a larger period of photovoltaic output, and alpha i Representing the corresponding time rate coefficient of the ith data point of the regional photovoltaic output, P PV,i Represents the regional photovoltaic output corresponding to the ith data point, S inverter,i Representing the alternating current side capacity of the regional photovoltaic inverter corresponding to the ith data point;
and calculating the average value of the photovoltaic output synchronous rate coefficients in the corresponding time period, wherein the average value is shown in the following formula:
wherein alpha is ave Average value of the synchronous rate coefficient of the distributed photovoltaic output in a larger period of photovoltaic output is represented;
and analyzing the average coefficient of the photovoltaic output of the month according to the number of days of the sunny day of the statistical data, wherein the average coefficient is shown in the following formula:
wherein alpha is month,ave Representing the average value alpha of output coefficients of distributed photovoltaic in the regional power grid in the current month ave,j Representing the average value of the photovoltaic output synchronous rate coefficients in the analysis period on the j-th sunny day of the month, and m represents the number of days of the sunny day of the month;
then calculating that the average value of the photovoltaic output synchronous rate coefficients in the daily analysis period is larger than the average value alpha of the output coefficients in the current month in the sunny day of the current month month,ave Probability p (alpha) ave,j ＞α month,ave ) The following formula is shown:
wherein N represents that the average value of the photovoltaic output synchronous rate coefficients in the analysis time periods in the m sunny days of the month is larger than the average value alpha of the output coefficients in the same month month,ave Is a number of days.
In an embodiment of the present invention, the specific implementation manner of calculating the value range of the component capacity of the regional power grid target annual distributed photovoltaic development and the specific implementation manner of the distributed photovoltaic critical development capacity under different scenes based on the future regional power grid distributed photovoltaic and load development conditions and considering the distributed photovoltaic direct current side capacity and the capacity ratio is as follows:
the power balance equation when the power distribution network substation is on the network is as follows:
P sub ＝P PV -P load -P ESS +P resource (6)
wherein P is sub Representing the network power of a power distribution network substation, P PV Representing regional grid distributed photovoltaic output power, P load Representing regional grid load, P ESS Representing stored energy charging power in regional power grid, P resource Representing the output power of other power sources except the distributed photovoltaic power sources in the regional power grid;
the load factor of the power distribution network substation is shown as follows:
wherein S is sub The rated capacity of the power distribution network transformer substation is represented, wherein beta is more than or equal to 80% and less than or equal to 100% of the rated capacity represents the overload of the transformer substation, and beta is more than 100% of the rated capacity represents the overload of the transformer substation;
based on future regional power grid distributed photovoltaic and load development conditions, considering regional distributed photovoltaic output coefficients to consider that the energy storage scale and other power output conditions are not changed, and the formula (6) becomes:
P sub ＝α month,ave S inverter -P load -P cont (8)
wherein P is cont Representing the integrated output power values of the energy storage and other power supplies, and considering the integrated output power values as a constant when the energy storage scale and the output conditions of other power supplies are unchanged;
the proportion eta of the distributed light Fu Rong is 1, namely the ratio of the capacity of the photovoltaic direct-current component to the rated capacity of the alternating-current side of the inverter is 1, and the capacity proportion is shown as follows:
wherein S is PV,DC Representing the capacity of the photovoltaic direct current component;
bringing formula (9) into formula (8) yields:
alpha based on analysis of historical operating data month,ave Substation load P obtained through prediction load P calculated from the operation data cont The relation between the transformer station internet load rate and the capacity ratio of the distributed photovoltaic direct current side is obtained through the following formula:
wherein S' PV,DC The capacity of the component for the target annual distributed photovoltaic development of the regional power grid is represented, and eta' represents the capacity ratio value adopted in the subsequent distributed photovoltaic development.
In an embodiment of the present invention, the specific implementation manner of analyzing the load factor situation of the substation of the power distribution network in different scenes and performing early warning on the overload or overload of the substation in different scenes is as follows:
assume that the corresponding regional power grid theory can develop a distributed photovoltaic capacity of S PV,DC,N Calculating according to beta=100% to obtain the critical development capacity S of the distributed photovoltaic PV,DC,critical The method comprises the steps of carrying out a first treatment on the surface of the Based on the capacity-to-distribution ratio of the distributed photovoltaic of the target year, the regional power grid load condition, the energy storage and other power output conditions and the power distribution network transformer substation load rate (11), the method comprises the following steps of:
scene: when P sub ≤0.8S sub When beta is less than or equal to 80%, calculating to obtain the component capacity S 'of the regional power grid for the target annual distributed photovoltaic development' PV,DC Is a value range of (a); therefore, the distributed photovoltaic development capacity which enables the transformer substation not to have heavy load is calculated under the condition of given capacity ratio; as can be seen from the formula (5), the average value of the photovoltaic output synchronous rate coefficient in the daily analysis period is larger than the average value alpha of the output coefficient in the same month month,ave The probability of (a) is p (alpha) ave,j ＞α month,ave )；
If max { S' PV,DC }＜min{S PV,DC,N -S PV,DC ,S PV,DC,critical Along with the development of future distributed photovoltaics, the corresponding power distribution network transformer substation cannot have the condition of internet surfing and heavy load;
if max { S' PV,DC }≥min{S PV,DC,N -S PV,DC ,S PV,DC,critical It is believed that with the development of future distributed photovoltaics, there is p (α ave,j ＞α month,ave ) The probability of (1) can cause the occurrence of network surfing heavy load or overload condition of the corresponding power distribution network substation;
scene: when 0.8S sub ≤P sub ≤S sub Namely, when beta is more than or equal to 80% and less than or equal to 100%, calculating to obtain the component capacity S 'of the regional power grid for the target annual distributed photovoltaic development' PV,DC Is a value range of (a);
if max { S' PV,DC }＜min{S PV,DC,N -S PV,DC ,S PV,DC,critical Then with the development of future distributed photovoltaics, the corresponding distribution network becomesThe power station cannot be in an internet overload condition;
if max { S' PV,DC }≥min{S PV,DC,N -S PV,DC ,S PV,DC,critical It is believed that with the development of future distributed photovoltaics, there is p (α ave,j ＞α month,ave ) The probability of (1) can cause the occurrence of an internet surfing overload condition of a corresponding power distribution network substation.
Scene: when P sub ＞S sub When beta is more than 100%, calculating to obtain the component capacity S 'of the target annual distributed photovoltaic development of the corresponding regional power grid' PV,DC In the value range, the corresponding power distribution network substation must have the condition of internet surfing overload.
In an embodiment of the present invention, the regional power grid distributed photovoltaic development efficiency index δ is as follows:
the larger the index value delta is, the higher the regional distributed photovoltaic development efficiency is.
Compared with the prior art, the invention has the following beneficial effects: the method of the invention is based on the distributed photovoltaic development condition of the distribution network, and can early warn the heavy load or overload of the distribution network substation under different distributed photovoltaic development scales, thereby providing theoretical basis for power grid planning personnel in the distributed photovoltaic access analysis work of the distribution network, and having very important engineering practice significance.
Drawings
Fig. 1 is a graph of the output characteristics of a distributed photovoltaic autumn under typical load day.
Fig. 2 is a graph of the power coefficient under a typical load day for a distributed photovoltaic.
Fig. 3 is a graph of substation distributed photovoltaic output and load characteristics.
Fig. 4 is a load characteristic of a substation after it withholds distributed photovoltaics and other power sources.
Detailed Description
The technical scheme of the invention is specifically described below with reference to the accompanying drawings.
The invention provides a heavy overload early warning method for a distributed photovoltaic access power distribution network substation, which is based on historical operation data, and comprises the steps of firstly analyzing output synchronous rate coefficients of distributed photovoltaic in a power distribution network area in a period with larger output, analyzing and obtaining a photovoltaic output average coefficient of a month by aiming at the number of sunny days in a month, and calculating the probability that the average value of the photovoltaic output synchronous rate coefficients in the analyzed period is larger than the average value of the output coefficients in the month; then calculating to obtain the value range of the component capacity of the regional power grid targeted annual distributed photovoltaic development and the critical development capacity of the distributed photovoltaic based on the future regional power grid distributed photovoltaic and load development conditions and by considering the capacity and the capacity ratio of the distributed photovoltaic direct current side; then analyzing the load rate conditions of the power distribution network transformer substation in different scenes, and carrying out early warning on the overload or overload of the transformer substation in different scenes; and finally, providing regional power grid distributed photovoltaic development efficiency indexes to represent regional distributed photovoltaic development efficiency.
The following is a specific implementation procedure of the method of the invention.
1. With the large-scale development of distributed photovoltaic, a scene that the distributed photovoltaic is connected to the network to cause heavy overload of a main transformer of the power distribution network may exist in a future power grid in an afternoon operation mode. The large photovoltaic output is concentrated at 11 am to 3 pm in the usual period, and the photovoltaic output coefficient of the study period during sunny days is analyzed as shown in the following formula. The data points are spaced 15 minutes apart for a total of 16 data points.
α＝{α 1 ，α 2 ，…，α i ,…,α 16 }i∈(1,16) (1)
Wherein, alpha represents a synchronous rate coefficient set of the photovoltaic output in a larger period of photovoltaic output, and alpha i Representing the corresponding time rate coefficient of the ith data point of the regional photovoltaic output, P PV,i Representing the regional photovoltaic output corresponding to the ith data point,S inverter,i and the alternating current side capacity of the regional photovoltaic inverter corresponding to the ith data point is shown.
2. The average value of the photovoltaic output synchronous rate coefficient in this period is calculated as shown in the following formula.
Wherein alpha is ave And the average value of the synchronous rate coefficient of the distributed photovoltaic output in a larger photovoltaic output period is represented.
3. And analyzing the average coefficient of the photovoltaic output of the month according to the number of days of the sunny day of the statistical data, wherein the average coefficient is shown in the following formula.
Wherein alpha is month,ave Representing the average value alpha of output coefficients of distributed photovoltaic in the regional power grid in the current month ave,j And (3) representing the average value of the photovoltaic output synchronous rate coefficients in the analysis period on the j-th sunny day of the month, and m represents the number of days of the sunny day of the month.
Then calculating that the average value of the photovoltaic output synchronous rate coefficients in the analysis period per day is larger than the average value alpha of the output coefficients in the current month in the sunny day of the month month,ave Probability p (alpha) ave,j ＞α month,ave ) As shown in the following formula.
Wherein N represents that the average value of the photovoltaic output synchronous rate coefficients in the analysis time periods in the m sunny days of the month is larger than the average value alpha of the output coefficients in the same month month,ave Is a number of days.
4. The power balance equation when the power distribution network substation is on the internet is shown as follows.
P sub ＝P PV -P load -P ESS +P resource (6)
Wherein P is sub Representing the network power of a power distribution network substation, P PV Representing regional grid distributed photovoltaic output power, P load Representing regional grid load, P ESS Representing stored energy charging power in regional power grid, P resource Representing the output power of other power sources except the distributed photovoltaic power sources in the regional power grid.
5. The power distribution network transformer substation load rate is shown in the following formula.
Wherein S is sub And representing rated capacity of the power distribution network substation. Wherein beta is more than or equal to 80% and less than or equal to 100% represents overload of the transformer substation, and beta is more than 100% represents overload of the transformer substation.
6. Based on future regional power grid distributed photovoltaic and load development conditions, considering regional distributed photovoltaic output coefficients to consider that the energy storage scale and other power output conditions do not change greatly, the formula (6) can be changed into:
P sub ＝α month,ave S inverter -P load -P cont (8)
wherein P is cont Representing the integrated output power value of the stored energy and other power sources, and is considered as a constant when the energy storage scale and other power source output conditions do not change greatly.
7. The existing distributed light Fu Rong proportion eta is generally 1, namely the ratio of the capacity of the photovoltaic direct current component to the rated capacity of the alternating current side of the inverter is 1, and the capacity proportion is shown in the following formula.
Wherein S is PV,DC Representing the capacity of the photovoltaic dc module.
8. Further bringing formula (9) into formula (8) yields:
9. alpha based on analysis of historical operating data month,ave Substation load P obtained through prediction load P calculated from the operation data cont The relation between the network load rate of the transformer substation and the capacity ratio of the distributed photovoltaic direct current side can be obtained through the following formula, and the relation is shown in the following formula.
Wherein S' PV,DC The capacity of the component for the target annual distributed photovoltaic development of the regional power grid is represented, and eta' represents the capacity ratio value adopted in the subsequent distributed photovoltaic development.
10. Assume that the regional power grid theory can develop a distributed photovoltaic capacity of S PV,DC,N The critical development capacity S of the distributed photovoltaic can be calculated according to beta=100% PV,DC,critical . Based on the capacity-to-distribution ratio of the distributed photovoltaic of the target year, the regional power grid load condition, the energy storage and other power output conditions and the power distribution network transformer substation load rate (11), the method comprises the following steps of:
scene: when P sub ≤0.8S sub When beta is less than or equal to 80%, the component capacity S 'of the regional power grid for the target annual distributed photovoltaic development can be calculated' PV,DC Is a range of values. Therefore, the distributed photovoltaic development capacity which enables the transformer substation not to have heavy load can be calculated under the condition of given capacity ratio. As can be seen from the formula (5), the average value of the photovoltaic output synchronous rate coefficient in the daily analysis period is larger than the average value alpha of the output coefficient in the same month month,ave The probability of (a) is p (alpha) ave,j ＞α month,ave )。
If max { S' PV,DC }＜min{S PV,DC,N -S PV,DC ,S PV,DC,critical Along with the development of future distributed photovoltaics, the power distribution network substation cannot have the condition of internet surfing heavy load;
if max { S' PV,DC }≥min{S PV,DC,N -S PV,DC ,S PV,DC,critical It is believed that with the development of future distributed photovoltaics, there is p (α ave,j ＞α month,ave ) The probability of (1) can cause the network loading heavy load or overload condition of the distribution network substation.
Scene: when 0.8S sub ≤P sub ≤S sub Namely, when beta is more than or equal to 80% and less than or equal to 100%, the component capacity S 'of the regional power grid for the target annual distributed photovoltaic development can be calculated' PV,DC Is a range of values.
If max { S' PV,DC }＜min{S PV,DC,N -S PV,DC ,S PV,DC,critical Along with the development of future distributed photovoltaics, the power distribution network substation cannot have an internet overload condition;
if max { S' PV,DC }≥min{S PV,DC,N -S PV,DC ,S PV,DC,critical It is believed that with the development of future distributed photovoltaics, there is p (α ave,j ＞α month,ave ) The probability of (1) can cause the network overload condition of the distribution network substation.
Scene: when P sub ＞S sub When beta is more than 100%, the component capacity S 'of the regional power grid for the target annual distributed photovoltaic development can be calculated' PV,DC Is a range of values. In this range, the distribution network substation must have an online overload condition.
11. Therefore, a regional power grid distributed photovoltaic development efficiency index delta is proposed, as shown in the following formula.
The larger the index value delta is, the higher the regional distributed photovoltaic development efficiency is.
Examples of implementation.
Taking a power distribution network transformer substation in a certain provincial area as an example, the transformer substation is provided with 2 main transformers, the rated power transformation capacity is 63MVA, and the rated power transformation capacity of the main transformer substation is 126MVA. The transformer substation is generally on line with distributed photovoltaic in the afternoon operation mode in autumn every year. At present, the distributed photovoltaic capacity connected with the transformer substation is 330MW, the rated capacity of the alternating-current side of the distributed photovoltaic inverter is 300MW, and the proportion of the distributed light Fu Rong is 1.1. Besides distributed photovoltaic, other power sources of 100MW are also configured under the transformer substation, and energy storage is not configured. Fig. 1 shows the output characteristic curve of the distributed photovoltaic connected to the transformer substation under a typical load day in autumn.
The output coefficient of the distributed light Fu Zaishang from 11 pm to 3 pm can be calculated and obtained according to the data of the upper graph, as shown in fig. 2.
From this alpha can be calculated ave =0.57. The month of the typical day is 16 days in the same month, and a sunny day appears, and according to the operation data of 16 days, the following steps are obtained: alpha month,ave ＝0.62。
Then calculating that the average value of the photovoltaic output synchronous rate coefficients in the analysis period per day is larger than the average value alpha of the output coefficients in the current month in the sunny day of the month month,ave Probability p (alpha) ave,j ＞α month,ave ) As shown in the following formula.
According to the actual condition of the transformer substation, the distribution type photovoltaic and load characteristic curves under the transformer substation are shown in fig. 3.
The load characteristics of the substation after withholding the distributed photovoltaic and other power sources are shown in fig. 4.
The analytical calculation can be performed according to the formulas (8) to (10):
thus, the formula (11) can be changed to:
to increase the synchronous rate of distributed photovoltaic and the peak load period during the afternoonIs used for the output of the electric motor, in the future, the capacitance ratio of the access distributed photovoltaic of the transformer substation is 1.2, thereby improving the output coefficient of the distributed photovoltaic. Thus when the substation is fully loaded on the internet, i.e. P sub =126 MW, the continuously developed distributed photovoltaic critical capacity is S PV,DC,critical =114 MW. The distributed photovoltaic capacity which can be developed by the regional power grid theory is S PV,DC,N ＝400MW。
Thus, when the distributed photovoltaic actually developed capacity S 'in the future' PV,DC When the power distribution network transformer substation is less than or equal to 65MW, the condition of surfing the Internet and heavy load can not occur.
When the practical development capacity of the distributed photovoltaic is 65-S 'or less in the future' PV,DC When the power distribution network is less than or equal to 114MW, 56.25% probability can cause the condition of network overload of the power distribution network substation.
The regional power grid distributed photovoltaic development efficiency is 1, and the formula is shown below. Therefore, the distributed photovoltaic in the area where the transformer substation is located can be fully developed in the future, and the development efficiency is high.
The method provided by the invention is based on the distributed photovoltaic development condition of the power distribution network, and can be used for carrying out early warning on the overload or the overload of the distribution network substation under different distributed photovoltaic development scales, so that theoretical basis can be provided for power grid planning personnel in the distributed photovoltaic access analysis work of the power distribution network, and the method has very important engineering practice significance.
The above is a preferred embodiment of the present invention, and all changes made according to the technical solution of the present invention belong to the protection scope of the present invention when the generated functional effects do not exceed the scope of the technical solution of the present invention.
Claims (5)
1. The method is characterized in that based on historical operation data, the output synchronous rate coefficient of the distributed photovoltaic in a power distribution network area in a period with larger output is analyzed, the average coefficient of the photovoltaic output in a month is obtained through analysis on the number of sunny days in a target month, and the probability that the average value of the photovoltaic output synchronous rate coefficient in the analyzed period is larger than the average value of the output coefficient in the month is calculated in the sunny days of the month; then calculating to obtain the value range of the component capacity of the regional power grid targeted annual distributed photovoltaic development and the critical development capacity of the distributed photovoltaic based on the future regional power grid distributed photovoltaic and load development conditions and by considering the capacity and the capacity ratio of the distributed photovoltaic direct current side; then analyzing the load rate conditions of the power distribution network transformer substation in different scenes, and carrying out early warning on the overload or overload of the transformer substation in different scenes; and finally, providing regional power grid distributed photovoltaic development efficiency indexes to represent regional distributed photovoltaic development efficiency.
2. The method for early warning heavy overload of a distributed photovoltaic access power distribution network substation according to claim 1, wherein the specific implementation manner of analyzing the output synchronous rate coefficient of the distributed photovoltaic in the power distribution network area in a period with larger output is as follows, analyzing the number of days of sunny days in a target month to obtain the average photovoltaic output coefficient of the month, and calculating the probability that the average value of the photovoltaic output synchronous rate coefficient in the analyzed period is larger than the average value of the output coefficients in the month in the sunny days of the month:
the photovoltaic output coefficient of the study period is analyzed and studied on sunny days, and the photovoltaic output coefficient is shown in the following formula:
α＝{α 1 ，α 2 ，…，α i ,…,α 16 } i∈(1,16) (1)
wherein, alpha represents a synchronous rate coefficient set of the photovoltaic output in a larger period of photovoltaic output, and alpha i Representing the corresponding time rate coefficient of the ith data point of the regional photovoltaic output, P PV,i Represents the regional photovoltaic output corresponding to the ith data point, S inverter,i Representing the alternating current side capacity of the regional photovoltaic inverter corresponding to the ith data point;
and calculating the average value of the photovoltaic output synchronous rate coefficients in the corresponding time period, wherein the average value is shown in the following formula:
wherein alpha is ave Average value of the synchronous rate coefficient of the distributed photovoltaic output in a larger period of photovoltaic output is represented;
and analyzing the average coefficient of the photovoltaic output of the month according to the number of days of the sunny day of the statistical data, wherein the average coefficient is shown in the following formula:
wherein alpha is month,ave Representing the average value alpha of output coefficients of distributed photovoltaic in the regional power grid in the current month ave,j Representing the average value of the photovoltaic output synchronous rate coefficients in the analysis period on the j-th sunny day of the month, and m represents the number of days of the sunny day of the month;
then calculating that the average value of the photovoltaic output synchronous rate coefficients in the daily analysis period is larger than the average value alpha of the output coefficients in the current month in the sunny day of the current month month,ave Probability p (alpha) ave,j ＞α month,ave ) The following formula is shown:
wherein N represents that the average value of the photovoltaic output synchronous rate coefficients in the analysis time periods in the m sunny days of the month is larger than the average value alpha of the output coefficients in the same month month,ave Is a number of days.
3. The method for early warning heavy overload of a distributed photovoltaic access distribution network substation according to claim 2, wherein the specific implementation manner of calculating the value range of the component capacity of the regional power grid targeted annual distributed photovoltaic development and the specific implementation manner of the distributed photovoltaic critical development capacity under different scenes based on the future regional power grid distributed photovoltaic and load development conditions and considering the distributed photovoltaic direct current side capacity and the capacity ratio is as follows:
the power balance equation when the power distribution network substation is on the network is as follows:
P sub ＝P PV -P load -P ESS +P resource (6)
wherein P is sub Representing the network power of a power distribution network substation, P PV Representing regional grid distributed photovoltaic output power, P load Representing regional grid load, P ESS Representing stored energy charging power in regional power grid, P resource Representing the output power of other power sources except the distributed photovoltaic power sources in the regional power grid;
the load factor of the power distribution network substation is shown as follows:
wherein S is sub The rated capacity of the power distribution network transformer substation is represented, wherein beta is more than or equal to 80% and less than or equal to 100% of the rated capacity represents the overload of the transformer substation, and beta is more than 100% of the rated capacity represents the overload of the transformer substation;
based on future regional power grid distributed photovoltaic and load development conditions, considering regional distributed photovoltaic output coefficients to consider that the energy storage scale and other power output conditions are not changed, and the formula (6) becomes:
P sub ＝α month,ave S inverter -P load -P cont (8)
wherein P is cont Representing the integrated output power values of the energy storage and other power supplies, and considering the integrated output power values as a constant when the energy storage scale and the output conditions of other power supplies are unchanged;
the proportion eta of the distributed light Fu Rong is 1, namely the ratio of the capacity of the photovoltaic direct-current component to the rated capacity of the alternating-current side of the inverter is 1, and the capacity proportion is shown as follows:
wherein S is PV,DC Representing the capacity of the photovoltaic direct current component;
bringing formula (9) into formula (8) yields:
alpha based on analysis of historical operating data month,ave Substation load P obtained through prediction load P calculated from the operation data cont The relation between the transformer station internet load rate and the capacity ratio of the distributed photovoltaic direct current side is obtained through the following formula:
wherein S' PV,DC The capacity of the component for the target annual distributed photovoltaic development of the regional power grid is represented, and eta' represents the capacity ratio value adopted in the subsequent distributed photovoltaic development.
4. The method for pre-warning heavy overload of a power distribution network substation through distributed photovoltaic access according to claim 3, wherein the specific implementation modes of analyzing the load rate conditions of the power distribution network substation in different scenes and pre-warning heavy load or overload of the substation in different scenes are as follows:
assume that the corresponding regional power grid theory can develop a distributed photovoltaic capacity of S PV,DC,N Calculating according to beta=100% to obtain the critical development capacity S of the distributed photovoltaic PV,DC,critical The method comprises the steps of carrying out a first treatment on the surface of the Based on the capacity-to-distribution ratio of the distributed photovoltaic of the target year, the regional power grid load condition, the energy storage and other power output conditions and the power distribution network transformer substation load rate (11), the method comprises the following steps of:
scene: when P sub ≤0.8S sub I.e., beta is less than or equal to 80 percent,calculating to obtain the component capacity S 'of the regional power grid for the target annual distributed photovoltaic development' PV,DC Is a value range of (a); therefore, the distributed photovoltaic development capacity which enables the transformer substation not to have heavy load is calculated under the condition of given capacity ratio; as can be seen from the formula (5), the average value of the photovoltaic output synchronous rate coefficient in the daily analysis period is larger than the average value alpha of the output coefficient in the same month month,ave The probability of (a) is p (alpha) ave,j ＞α month,ave )；
If max { S' PV,DC }＜min{S PV,DC,N -S PV,DC ,S PV,DC,critical Along with the development of future distributed photovoltaics, the corresponding power distribution network transformer substation cannot have the condition of internet surfing and heavy load;
if max { S' PV,DC }≥min{S PV,DC,N -S PV,DC ,S PV,DC,critical It is believed that with the development of future distributed photovoltaics, there is p (α ave,j ＞α month,ave ) The probability of (1) can cause the occurrence of network surfing heavy load or overload condition of the corresponding power distribution network substation;
scene: when 0.8S sub ≤P sub ≤S sub Namely, when beta is more than or equal to 80% and less than or equal to 100%, calculating to obtain the component capacity S 'of the regional power grid for the target annual distributed photovoltaic development' PV,DC Is a value range of (a);
if max { S' PV,DC }＜min{S PV,DC,N -S PV,DC ,S PV,DC,critical Along with the development of future distributed photovoltaics, the corresponding power distribution network transformer substation cannot have the internet overload condition;
if max { S' PV,DC }≥min{S PV,DC,N -S PV,DC ,S PV,DC,critical It is believed that with the development of future distributed photovoltaics, there is p (α ave,j ＞α month,ave ) The probability of (1) can cause the occurrence of an internet surfing overload condition of a corresponding power distribution network substation.
Scene: when P sub ＞S sub When beta is more than 100%, calculating to obtain the component capacity S 'of the target annual distributed photovoltaic development of the corresponding regional power grid' PV,DC In the value range, the corresponding power distribution network substation must have the condition of internet surfing overload.
5. The method for early warning of heavy overload of a distributed photovoltaic access power distribution network substation according to claim 4, wherein the distributed photovoltaic development efficiency index delta of the regional power grid is shown in the following formula:
the larger the index value delta is, the higher the regional distributed photovoltaic development efficiency is.
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