Second-order cone programming-based power distribution network new energy acceptance capability detection method and system

Abstract

The invention discloses a second-order cone programming-based power distribution network new energy acceptance capability detection method. The method comprises the following steps of: constructing two objective functions corresponding to the minimum environmental cost and the minimum comprehensive cost; the node voltage constraint, the current-carrying capacity constraint, the superior power grid power exchange constraint and the power flow constraint are combined as steady-state constraints; the second-order cone programming is applied to the power distribution network, and steady-state constraints are adjusted by using upper relaxation operation to establish a power flow optimization model based on the second-order cone programming; an N-1 safety criterion of the power distribution network is considered from a power distribution network line, and a reliability constraint is established. According to the method, the reliability problem after fault reconstruction of the power distribution network is considered carefully based on the reliability constraint of the N-1 criterion, so that the access scheme is more feasible. The acceptance problem of the power distribution network to the DG is converted into the corresponding second-order cone programming through relaxation, the solution of the original problem is simplified, the excellent property of convex optimization is utilized, and a reference direction is provided for the solution of the corresponding DG access problem.

Description

Technical Field

[0001] The present invention relates to a technology in the field of new energy, specifically a method and system for detecting representative fault line sets in a distribution network based on second-order cone programming. Background Art

[0002] The transformation of the energy structure continues to steadily advance, driven by a reduction in the use of traditional fossil fuels and an increased development of new energy sources, such as wind and photovoltaics. Against this backdrop, distributed generation from renewable energy sources, a clean, safe, flexible, and efficient method of power generation, is increasingly being integrated into urban distribution networks as a supplement to grid power generation.

[0003] However, due to the need for safe operation of distribution networks, renewable energy distributed power sources cannot be freely connected to the distribution network without restrictions. First, the integration of renewable energy distributed power sources into the distribution network changes the traditional one-way energy transmission structure of the distribution network. If the connected capacity is too large, there is a risk of reverse power flow and voltage limit violations. Second, renewable energy distributed power sources have random and fluctuating characteristics, and their output is affected by weather changes, making it unstable. Third, renewable energy distributed power sources contain a large number of power electronic devices, which generate a large proportion of harmonics, affecting the power quality of the grid. Therefore, it is necessary to scientifically evaluate the distribution network's ability to accommodate renewable energy distributed power sources and develop access solutions based on corresponding needs. This is also a current hot topic in the application of renewable energy. Summary of the Invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention proposes a method and system for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming.

[0005] The present invention is achieved through the following technical solutions:

[0006] The present invention relates to a method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming. The method comprises the following steps: constructing two objective functions corresponding to minimum environmental cost and minimum comprehensive cost; combining node voltage constraints, current carrying capacity constraints, upper-level power grid power exchange constraints, and power flow constraints as steady-state constraints; applying second-order cone programming to the distribution network, adjusting the steady-state constraints using upper relaxation operations, and establishing a power flow optimization model based on second-order cone programming; and considering the N-1 safety criterion of the distribution network from the perspective of the distribution network lines, and establishing reliability constraints.

[0007] The present invention relates to a system for implementing the above-mentioned method, comprising: a power flow optimization model establishment unit, a reliability constraint unit and a case analysis unit, wherein: the power flow optimization model establishment unit establishes an objective function, designs corresponding steady-state constraints, applies second-order cone programming, and uses phase angle relaxation and second-order cone relaxation operations to meet the constraint requirements of the second-order cone programming; the reliability constraint unit searches for representative fault lines in a large distribution network based on the N-1 criterion and completes the analysis of the representative fault line set; the case analysis unit analyzes the topology of the computing power system, inputs case-related data, applies the above-mentioned power flow optimization model and reliability constraint analysis, and obtains access plans under the respective goals of minimizing environmental cost and minimizing comprehensive cost. Technical Effects

[0008] Compared to existing technologies, this invention, based on the reliability constraints of the N-1 criterion, carefully considers the reliability issues after distribution network failure reconfiguration, making the access solution more feasible. By relaxing the distribution network's DG admission problem into a corresponding second-order cone programming, it simplifies the solution of the original problem and leverages the excellent properties of convex optimization, providing a reference direction for solving the corresponding DG access problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 Flowchart of the present invention;

[0010] Figure 2 This is the minimum loop diagram of the distribution network in the embodiment;

[0011] Figure 3 is a typical minimum loop graph containing only one tie line in the embodiment;

[0012] Figure 4 Analyze the flow chart for a representative set of faulted lines;

[0013] Figure 5 This is the IEEE 33-node distribution network structure diagram. DETAILED DESCRIPTION

[0014] like Figure 1 As shown, this embodiment specifically includes:

[0015] Step 1) Two objective functions are set from the perspective of environmental protection and cost, with the corresponding goals being minimizing environmental cost and minimizing comprehensive cost respectively.

[0016] Step 2) The node voltage constraint, current carrying capacity constraint, upper grid power exchange constraint and power flow constraint are combined as steady-state constraints.

[0017] Step 3) Use the second-order cone programming method, apply it to the distribution network, and use relaxation operations to adjust the steady-state constraints to establish a power flow optimization model based on second-order cone programming.

[0018] The second-order cone programming method is implemented using, but not limited to, the technology described in the document "Applications of second-order cone programming".

[0019] Step 4) Consider the N-1 safety criterion of the distribution network from the perspective of the distribution network lines and establish reliability constraints.

[0020] In the step 1), the objective function MinC is established with the minimum environmental cost and the minimum comprehensive cost as the corresponding goals. e , MinC=C DG / 365+C OM +C L +C e , including: annual investment cost of connecting new energy to the distribution network The total investment cost is converted into annual construction cost; the maintenance cost required for the normal operation of distributed power generation in one year Costs incurred by network losses in the distribution network during operation Taking into account the corresponding environmental cost and governance costs brought about by the generation of greenhouse gases during the power generation process n is the service life of the distributed power source, which is generally 30 years; r is the discount rate, which is generally 10%. WG 、C PV are the unit capacity investment costs corresponding to wind power distributed power sources and photovoltaic distributed power sources, P WG 、P PV are the capacities of wind power distributed generation and photovoltaic distributed generation connected to the corresponding nodes in the distribution network, N WG 、N PV are the number of nodes installed in the distribution network for wind power distributed generation and photovoltaic distributed generation respectively. om.WG 、C om.PV The maintenance costs required for wind power distributed power and photovoltaic distributed power to maintain normal operation per unit capacity per unit time. t.ij is the current corresponding to line ij within time t after the new energy distributed power source is connected to the distribution network, r ij is the resistance corresponding to line ij, N l is the number of branches, α b is the loss electricity price. gas is the environmental governance cost penalty fee corresponding to the unit mass of greenhouse gas, which is the sum of the environmental discount cost and the emission levy price, and is taken as 0.033 yuan / kg, K DG is the mass of greenhouse gases generated per unit of electricity transmitted by the power grid, which is 639.2 kg / (MW·h), P ij.L is the network loss corresponding to the i-th branch, Pi.Load is the active power required by the i-th load, P i.DG is the output corresponding to the i-th distributed generation, N L and M are the number of loads and the number of connected DGs, respectively, which means that the environmental cost is reflected by imposing corresponding environmental penalties on the part of consumed electricity excluding the part provided by new energy.

[0021] The steady-state constraints include:

[0022] 1) Node voltage upper and lower limit constraints: Among them: U i represents the voltage amplitude of the i-th node, U i max 、U i min are the upper and lower limits allowed for the voltage amplitude of the i-th node respectively.

[0023] 2) Branch current limit constraints: Among them: I ij Indicates the current size of branch ij, I ij max The current limit constraint describes the objective situation that each branch is limited by the actual line capacity.

[0024] 3) Upper-level power grid power exchange constraints: Where: P0 is the active power flowing into the distribution network from the root node, P0 max 、P0 min They are the upper and lower limits of the active power transmitted by the transmission network set for safe operation, Q0 is the reactive power flowing from the upper power grid into the distribution network, and Q0 max 、Q0 min They are the upper and lower limits of reactive power transmitted by the transmission network set for safe operation.

[0025] 4) Branch power flow power conservation constraints: Where: P ij , Q ij are the active power and reactive power flowing on branch ij, r ij 、x ij are the resistance and reactance on branch ij, U i is the voltage at the i-th node, the set u(j) represents the set of all branches with j as the end node, the set v(j) represents the set of all branches with j as the first node, P j and Q j Represent the active injection power and reactive injection power of node j respectively. j.DGrepresents the capacity of the distributed power supply connected to node j, P j.load , Q j.load They represent the active and reactive loads carried by node j respectively. The upper two equations obtain the injection power of each node through flow calculation. The lower two equations constrain the power balance relationship of each node. Taken together, they basically describe the flow power conservation constraints in the distribution network topology.

[0026] 5) Branch Ohm's law constraints: Among them: U i 、U j Represent the voltage amplitude of nodes i and j respectively, P ij , Q ij is the active and reactive power of branch ij, r ij 、x ij is the resistance and reactance of branch ij, I ij The essence of Ohm's law constraint on the current in branch ij is the principle of voltage drop in the distribution network.

[0027] 6) Branch power equality constraint: Among them: I ij is the current amplitude of branch ij, U i is the voltage amplitude of node i, P ij , Q ij are the active and reactive power of branch ij respectively.

[0028] The second-order cone programming is: min{f T x|Ax=b,x∈K}, where: f T x is the objective function, variable x∈R N ; A, b, f are all coefficient constants, where A∈R M*N , b∈R M , c∈R M , the set that satisfies the second-order cone condition A i ∈R M*N , b∈R M , c∈R M In fact, this form is equivalent to an affine transformation of the standard cone: K0 = {(u, t)|||u||≤t}, u = A i x+b i ,

[0029] According to the properties of affine transformation, the convexity of the set after transformation remains unchanged, so the second-order cone is a convex cone like the standard cone.

[0030] The relaxation operation is to relax the original constraint in phase angle, that is, to ignore the phase angle part of the variable and only take the amplitude, specifically including: splitting the complex power into active and reactive parts, removing the phase angle of voltage and current by squaring: replacing the voltage and current with their squares as variables, and the square of the current Voltage squared This completes the phase angle relaxation of the original constraints. The constraints after relaxation include:

[0031] After the constrained phase angle is relaxed, the square of the current is subjected to a second-order cone relaxation: After that, it is further transformed into the standard second-order cone form: It can be seen that after relaxation, the corresponding requirements of the second-order cone constraint are met. After phase angle relaxation and second-order cone relaxation, the original optimization problem becomes a power flow steady-state model. That is, the second-order cone programming model can be solved using algorithms for second-order cone problems.

[0032] like Figure 4 As shown, the N-1 safety criterion for the distribution network specifically includes:

[0033] i) The minimum ring in the distribution network is defined as the smallest ring unit that does not contain any rings in the distribution network topology (including the tie switch circuit), such as Figure 1 As shown in Figure 2, the smallest ring in the distribution network topology must contain a tie switch line that has not yet been put into operation.

[0034] ii) Analyze the line transfer in the N-1 fault for the minimum ring with only one tie switch inside. First, analyze the method of selecting representative fault lines in the minimum ring without DG access. At this time, except for the tie switch inside the minimum ring, all other lines are lines in normal operation of the distribution network, such as Figure 2 As shown in Figure 2. When the smallest ring research object is determined, the corresponding supply transfer plan is also determined.

[0035] iii) When a fault occurs on line E in the O~T3 section, the current before the fault is I f , then the line will complete the power transfer through the tie switch line (T2, T3) after the fault. The following analyzes the possible over-limit situations that may occur after the fault power transfer from the perspectives of current and voltage:

[0036] 1) Current analysis: After the reconfiguration is completed, the line current on the O~T2 segment will bear at least the current flowing on the original line E, that is, the current increases by ΔI=If Considering the current safety constraints, there is a risk of current exceeding the limit on the lines in the O~T2 section.

[0037] 2) Voltage analysis: When the reconfiguration is completed, the terminal node of the flow along the O~T2 segment will no longer be T2, but will extend along the connected tie switch to a certain point T on O~T3. e Since there is no other power supply involved, along T2~T e The node voltage will be further reduced along the basis of T2 voltage. Due to the existence of node voltage constraints, it is necessary to consider T e Risk of voltage being too low and exceeding the limit.

[0038] Considering these two perspectives, the most serious fault occurs on line E3, located near the current inflow point O. Within the O-T3 segment, E3 has the highest current before the fault. Furthermore, since it is closest to the current inflow point O, it is also furthest from the extended end node of the O-T2 segment after the fault, making its end node most susceptible to voltage undershoot. Therefore, line E3 is the representative fault line for the O-T3 segment. Similarly, E1 is the representative fault line for the O-T1 segment. However, due to the presence of an out-of-loop line at T1, the possibility of out-of-loop assistance during the O-T1 segment fault cannot be ruled out. Therefore, E1 cannot represent the fault for the T1-T2 segment. The representative fault line for the T1-T2 segment is E2.

[0039] iv) When DG is connected to the distribution network, we also take a typical minimum ring as the research object and set the DG access point to P. According to the previous theory, E1, E2, and E3 are still representative fault lines. When the O-T1 line fails, there are two situations depending on the output of the DG:

[0040] 1) The DG output is relatively small. Before the fault occurs, the flow direction of the upstream branch of point P remains unchanged. At this time, the maximum current of O~T1 before the fault can only be the larger value between the currents of E1 and E4. Therefore, E4 can be added as one of the representative fault lines in O~T1.

[0041] 2) The DG output is relatively large. Before the fault occurred, the flow direction of the upstream branch of point P changed due to the DG output, flowing from P to O. This indicates that due to the excessive output of the DG, the power generated by the DG alone could have met the load demand of the P-T2 section. At this time, if the fault occurred on the line upstream of point P, there is a possibility that the DG power would be reversed to the O-T3 section via the interconnection line. The affected nodes of the O-T3 section would experience voltage rise, and there is a risk of voltage exceeding the limit. Obviously, if the fault occurs on line E5, it is likely to reversely transmit the most power and the risk of voltage exceeding the limit is the greatest. Therefore, E5 can also be regarded as one of the representative fault lines in the O-T1 section.

[0042] Since the representative fault line set consists of the outgoing branches (edges starting from the nodes) of the nodes whose minimum intra-ring node degree exceeds 2 in the directed graph corresponding to the distribution network operation topology, when the distribution network is connected to the DG, the degree corresponding to the node connected to the DG must be increased by 1.

[0043] After actual experiments, the IEEE 33-node distribution network system is used as an example. The system topology is as follows: Figure 5 As shown in the figure, node 1 is the connection point between the distribution network and the upper-level power grid. The solid line represents the line in normal operation, and the dashed line represents the tie-breaker line. The system base voltage is 12.66 kV, and the power base is 10 MVA. The total active load is 3715 kW, and the total reactive load is 2300 kvar. The wind power distributed generation units are installed at nodes 8, 25, and 32, and the photovoltaic distributed generation units are installed at nodes 7, 24, and 30. The capacity of each wind power distributed generation unit is 100 kW, and the capacity of each photovoltaic distributed generation unit is also 100 kW. The investment costs per unit of wind power and photovoltaic distributed generation units are 500,000 yuan and 900,000 yuan, respectively, which translates to 5,000 yuan and 9,000 yuan per kW of capacity, respectively. The operation and maintenance costs per hour for each kW of wind power and photovoltaic distributed generation units are 0.1 yuan and 0.04 yuan, respectively. The loss electricity price is 0.61 yuan / kWh, referring to the electricity price in Shanghai.

[0044] Let the objective functions be minimizing environmental cost and minimizing comprehensive cost respectively, substitute the relevant data of the example into the steady-state model of power flow based on the second-order cone, and obtain the access scheme corresponding to the objectives as shown in Table 1:

[0045] Table 1

[0046] The analysis of the example results is as follows:

[0047] 1) When analyzing based on minimizing environmental costs, the corresponding number of connected DGs is 37, with a total capacity of 3700kW. However, when analyzing based on minimizing comprehensive costs, the corresponding number of connected DGs is 34, with a total capacity of 3400kW, a difference of 300kW. This indicates that when analyzing based on environmental costs, the distribution network can connect more DG capacity, further leveraging its DG acceptance capacity and, in effect, placing greater emphasis on the positive role played by the integration of renewable energy DG.

[0048] 2) The daily network loss cost for the access solution with an environmental objective is 292.4 yuan less than the daily network loss cost when analyzed with total cost as the objective. This shows that when the analysis is based on the environment, DG access to the distribution network can better reduce network losses. This is also one of the results of accessing more DG while ensuring reliability.

[0049] 3) The comprehensive cost of the analysis based on the environment is only 757.03 yuan higher than that of the analysis based on the comprehensive cost. However, the daily greenhouse gas emissions are reduced by as much as 4908.7 kg. This shows that although the investment and maintenance costs of DGs are higher when analyzed based on environmental costs, the environmental benefits brought by the relatively large number of DGs connected are also more obvious. In the long run, it is obvious that the benefits brought by paying attention to the environment are more substantial.

[0050] The above-mentioned specific implementation can be partially adjusted in different ways by those skilled in the art without departing from the principles and purpose of the present invention. The scope of protection of the present invention shall be based on the claims and shall not be limited by the above-mentioned specific implementation. All implementation schemes within its scope shall be subject to the constraints of the present invention.

Claims

1. A method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming, characterized in that: By constructing two objective functions corresponding to the minimum environmental cost and the minimum comprehensive cost, the node voltage constraint, the current carrying capacity constraint, the upper power grid power exchange constraint and the power flow constraint are combined as steady-state constraints. Second-order cone programming is applied to the distribution network, and the upper relaxation operation is used to adjust the steady-state constraints to establish a power flow optimization model based on second-order cone programming; the N-1 safety criterion of the distribution network is considered from the distribution network line, and reliability constraints are established.

2. The method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming according to claim 1 is characterized in that: The steady-state constraints include: 1) Node voltage upper and lower limit constraints: Among them: U i Represents the voltage amplitude of the i-th node, U i max 、U i min are the upper and lower limits allowed for the voltage amplitude of the i-th node respectively; 2) Branch current limit constraints: Where: I ij Indicates the current size of branch ij, I ij max Indicates the upper limit of the current that branch ij can carry; the current limit constraint describes the objective situation that each branch is limited by the actual line capacity; 3) Upper-level power grid power exchange constraints: Where: P0 is the active power flowing into the distribution network from the root node, P0 max 、P0 min They are the upper and lower limits of the active power transmitted by the transmission network set for safe operation, Q0 is the reactive power flowing from the upper power grid into the distribution network, and Q0 max 、Q0 min They are the upper and lower limits of reactive power transmitted by the transmission network set for safe operation; 4) Branch power flow power conservation constraints: Where: P ij , Q ij are the active power and reactive power flowing on branch ij, r ij 、x ij are the resistance and reactance on branch ij, U i is the voltage at the i-th node, the set u(j) represents the set of all branches with j as the end node, the set v(j) represents the set of all branches with j as the first node, P j and Q j Represent the active injection power and reactive injection power of node j respectively; P j.DG represents the capacity of the distributed power supply connected to node j, P j.load , Q j.load Represents the active and reactive loads carried by node j respectively. The upper two equations obtain the injection power of each node through power flow calculation. The lower two equations constrain the power balance relationship of each node. Taken together, they basically describe the power conservation constraint in the distribution network topology. 5) Branch Ohm's law constraints: Among them: U i 、U j Represent the voltage amplitude of nodes i and j respectively, P ij , Q ij is the active and reactive power of branch ij, r ij 、x ij is the resistance and reactance of branch ij, I ij The essence of Ohm's law constraint for the current in branch ij is the principle of voltage drop in the distribution network; 6) Branch power equality constraint: Where: I ij is the current amplitude of branch ij, U i is the voltage amplitude of node i, P ij , Q ij are the active and reactive power of branch ij respectively.

3. The method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming according to claim 1 is characterized in that: The second-order cone programming is: min{f T x|Ax=b,x∈K}, where: f T x is the objective function, variable x∈R N ; A, b, f are all coefficient constants, where: A∈R M*N , b∈R M , c∈R M , the set that satisfies the second-order cone condition i=1,2,...,m,A i ∈R M*N , b∈R M , c∈R M In fact, this form is equivalent to an affine transformation of the standard cone: K0 = {(u, t)|||u||≤t}, u = A i x+b i , According to the properties of affine transformation, the convexity of the set after transformation remains unchanged, so the second-order cone is a convex cone like the standard cone.

4. The method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming according to claim 1 is characterized in that: The relaxation operation is to relax the original constraint in phase angle, that is, to ignore the phase angle part of the variable and only take the amplitude, specifically including: splitting the complex power into active and reactive parts, removing the phase angle of voltage and current by squaring: replacing the voltage and current with their squares as variables, and the square of the current Voltage squared This completes the phase angle relaxation of the original constraints. The constraints after relaxation include:

5. The method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming according to claim 4 is characterized in that: After the constrained phase angle is relaxed, the square of the current is subjected to a second-order cone relaxation: After that, it is further transformed into the standard second-order cone form: It can be seen that after relaxation, the corresponding requirements of the second-order cone constraint are met. After phase angle relaxation and second-order cone relaxation, the original optimization problem becomes a power flow steady-state model. That is, the second-order cone programming model, which uses the algorithm for the second-order cone problem to solve it.

6. The method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming according to claim 1 is characterized in that: The N-1 safety criterion for the distribution network specifically includes: i) The minimum ring in the distribution network is defined as the smallest ring unit that does not contain any rings in the distribution network topology. The minimum ring in the distribution network topology must contain a tie switch circuit that has not yet been put into operation; ii) Analyzing line transfer during N-1 faults in a minimum ring with only one tie switch: First, we analyze the method for selecting representative fault lines within the minimum ring without DG access. In this case, except for the tie switch within the minimum ring, all other lines are in normal operation of the distribution network. Once the minimum ring is determined, the corresponding transfer plan is determined. iii) When a fault occurs on line E in the O~T3 section, the current before the fault is I f , then the line will complete the power transfer through the tie switch line (T2, T3) after the fault; iv) When DG is connected to the distribution network, a typical minimum ring is also taken as the research object, and the DG access point is set as P. According to the previous theory, E1, E2, and E3 are still representative fault lines.

7. The method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming according to claim 6 is characterized in that: The possible over-limit situations that may occur after a faulty power supply is switched include: 1) Current analysis: After the reconfiguration is completed, the line current on the O~T2 segment will bear at least the current flowing on the original line E, that is, the current increases by ΔI=I f ,Considering the current safety constraints, there is a risk of exceeding the current limit on the lines in the O~T2 section; 2) Voltage analysis: When the reconfiguration is completed, the terminal node of the flow along the O~T2 segment will no longer be T2, but will extend along the connected tie switch to a certain point T on O~T3. e Since there is no other power supply involved, along T2~T e The node voltage will be further reduced along the basis of T2 voltage. Due to the existence of node voltage constraints, it is necessary to consider T e Risk of voltage being too low and exceeding the limit; The most serious fault situation is line E3 near the current inflow point O. Among the lines in the O-T3 section, E3 has the largest current before the fault. Moreover, since it is closest to the current inflow point O, the extended end node of the O-T2 section is also the farthest after the fault. Its end node is also most likely to have the risk of voltage exceeding the limit due to excessive low voltage. Therefore, line E3 is the representative fault line in the O-T3 section. Similarly, E1 is the representative fault line in the O-T1 section. Due to the existence of an out-of-loop line at point T1, the possible help of the out-of-loop during the fault of the O-T1 section cannot be ruled out. Therefore, E1 does not represent the fault of the T1-T2 section line. The representative fault line of the T1-T2 section should be E2.

8. The method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming according to claim 6 is characterized in that: The output level of the DG includes: 1) The DG output is relatively small. Before the fault occurs, the flow direction of the upstream branch of point P remains unchanged. At this time, the maximum current of O~T1 before the fault can only be the larger value between the currents of E1 and E4. Therefore, E4 is added as one of the representative fault lines in O~T1; 2) The DG output is relatively large. Before the fault occurred, the flow direction of the upstream branch of point P changed due to the DG output, flowing from P to O. This shows that due to the excessive output of the DG, the power generated by the DG alone has already met the load demand of the P-T2 section. At this time, if the line where the fault occurs is located upstream of point P, there is a possibility that the DG power will be reversed to the O-T3 section through the interconnection line. The voltage of the affected nodes in the O-T3 section will rise, and there is a risk of excessive voltage exceeding the limit. Obviously, if the E5 line has a fault, it is likely to reverse the power and the risk of voltage exceeding the limit is also the greatest. Therefore, E5 is also one of the representative fault lines in O-T1.

9. The method for detecting the new energy acceptance capacity of a distribution network based on second-order cone programming according to any one of claims 1 to 8, wherein: include: Step 1) Two objective functions are set from the perspective of environmental protection and cost, with the minimum environmental cost and the minimum comprehensive cost as the corresponding goals respectively. The objective function MinC is established with the minimum environmental cost and the minimum comprehensive cost as the corresponding goals. e , MinC=C DG / 365+C OM +C L +C e , including: annual investment cost of connecting new energy to the distribution network The total investment cost is converted into annual construction cost; the maintenance cost required for the normal operation of distributed power generation in one year Costs incurred by network losses in the distribution network during operation Taking into account the corresponding environmental cost and governance costs brought about by the generation of greenhouse gases during the power generation process n is the service life of distributed power generation, r is the discount rate, C WG 、C PV are the unit capacity investment costs corresponding to wind power distributed power sources and photovoltaic distributed power sources, P WG 、P PV are the capacities of wind power distributed generation and photovoltaic distributed generation connected to the corresponding nodes in the distribution network, N WG 、N PV are the number of nodes installed in the distribution network for wind power distributed generation and photovoltaic distributed generation, C om.WG 、C om.PV are the maintenance costs required for wind power distributed power generation and photovoltaic distributed power generation to maintain normal operation per unit capacity per unit time, I t.ij is the current corresponding to line ij within time t after the new energy distributed power source is connected to the distribution network, r ij is the resistance corresponding to line ij, N l is the number of branches, α b is the loss electricity price, C gas is the environmental governance cost penalty fee corresponding to the unit mass of greenhouse gas, which is the sum of the environmental discount cost and the emission levy price. DG is the mass of greenhouse gases generated per unit of electricity delivered by the grid, P ij.L is the network loss corresponding to the i-th branch, P i.Load is the active power required by the i-th load, P i.DG is the output corresponding to the i-th distributed generation, N L and M are the number of loads and the number of connected DGs, respectively, which means that the environmental cost is reflected by imposing corresponding environmental penalties on the consumed electricity excluding the part provided by renewable energy; Step 2) combining node voltage constraints, current carrying capacity constraints, upper grid power exchange constraints, and power flow constraints as steady-state constraints; Step 3) using the second-order cone programming method, applying it to the distribution network, and using relaxation operations to adjust the steady-state constraints to establish a power flow optimization model based on the second-order cone programming; Step 4) Consider the N-1 safety criterion of the distribution network from the perspective of the distribution network lines and establish reliability constraints.

10. A distribution network new energy acceptance capacity detection system based on second-order cone programming that implements the method according to any one of claims 1 to 9, characterized in that: include: The power flow optimization model establishment unit, the reliability constraint unit and the case analysis unit, among which: the power flow optimization model establishment unit establishes the objective function, designs the corresponding steady-state constraints, applies the second-order cone programming, and uses phase angle relaxation and second-order cone relaxation operations to meet the constraints of the second-order cone programming; the reliability constraint unit finds the representative fault lines in the large distribution network based on the N-1 criterion, and completes the analysis of the representative fault line set; the case analysis unit analyzes the computing system topology, inputs the case-related data, applies the aforementioned power flow optimization model and reliability constraint analysis, and obtains the access plan under the respective goals of minimizing environmental cost and minimizing comprehensive cost.

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