A method and system for prospective section over-limit control of a power transmission and distribution network containing new energy

Abstract

This invention discloses a forward-looking section over-limit control method and system for transmission-distribution networks incorporating renewable energy. The control method comprises the following steps: obtaining the predicted renewable energy output data using existing data-driven distributed photovoltaic cluster output prediction methods; assuming full renewable energy generation, constructing a scenario where renewable energy is fully connected to the grid; using the Matpower tool to perform power flow calculations to determine the predicted section over-limit situation; establishing a forward-looking section over-limit control model and determining the objective function and constraints, the objective function being to minimize the sum of curtailment cost and over-limit penalty cost; using a CPLEX solver to solve the objective function in a rolling manner over time periods, deriving the optimized photovoltaic curtailment plan and energy storage charging and discharging strategy; and issuing power adjustment commands. This invention, by establishing a multi-time period optimization model, coordinates photovoltaic curtailment and energy storage charging and discharging, significantly reducing the risk of section over-limit, improving grid security, and increasing renewable energy utilization.

Description

Technical Field

[0001] This invention belongs to the field of power system dispatching and control technology, specifically a forward-looking cross-section over-limit control method and system for power transmission and distribution networks containing new energy sources, applicable to the safe and stable operation of power grids with high penetration of new energy sources. Background Technology

[0002] When a surge in renewable energy generation leads to a strained power balance and insufficient load reserves across the grid, grid dispatchers need to analyze the renewable energy absorption capacity while considering grid security, and set renewable energy absorption targets through the automatic renewable energy generation control function of the dispatch master station. Traditional renewable energy absorption methods based on manual analysis are relatively crude, prone to deviating from the optimal renewable energy absorption capacity, and involve a large workload, adjusting only based on current information and unable to predict future over-limit risks. Existing optimization dispatch methods are computationally complex and difficult to meet the needs of online applications. There is an urgent need for a forward-looking optimization dispatch method that can coordinate photovoltaic curtailment and energy storage charging and discharging in advance, and fully considers safety to solve the above problems. Summary of the Invention

[0003] The purpose of this invention is to address the problems existing in the prior art by providing a forward-looking cross-section over-limit control method and system for transmission and distribution networks containing new energy sources.

[0004] The objective of this invention is achieved through the following technical solution:

[0005] A forward-looking control method for cross-section over-limit control in transmission and distribution networks incorporating new energy sources, comprising the following steps:

[0006] S1. Obtain the output data of new energy prediction using existing data-driven distributed photovoltaic cluster output prediction methods;

[0007] S2. Set the new energy to full power generation, input the predicted output data of new energy obtained in step S1 into the transmission-distribution network model, and construct the scenario of full grid connection of new energy in the transmission-distribution network.

[0008] S3. Based on the scenario of full grid connection of new energy in the transmission and distribution network constructed in step S2, use the matpower tool to perform power flow calculations to obtain the predicted cross-section over-limit situation.

[0009] S4. Based on the predicted cross-section exceedance situation obtained in step S3, run the forward scheduling program, establish a forward-looking cross-section exceedance control model, and determine the objective function and constraints. The objective function is to minimize the sum of the cost of wasted light and the cost of exceedance penalty.

[0010] S5. Use the cplex solver to solve the objective function in a rolling manner according to time periods to obtain the optimized photovoltaic curtailment plan and energy storage charging and discharging strategy;

[0011] S6. Issue power adjustment command.

[0012] The transmission-distribution network model in step S2 includes a high-voltage power grid, a low-voltage distribution network, a low-voltage power grid, and power tie lines. Specifically, the high-voltage power grid is based on the IEEE standard 39-node system network structure, and the low-voltage distribution network is based on the IEEE standard 14-node system network structure. The low-voltage distribution network is connected to the high-voltage power grid through power tie lines and accesses the respective power generation and consumption equipment contained in the low-voltage power grid. The transmission-distribution network model is formed by the power generation and consumption equipment at the end of the low-voltage power grid from the high-voltage power grid to the low-voltage power grid.

[0013] The power flow calculation program of the matpower tool in step S3 uses the Newton-Raphson method to perform power flow calculation. The Newton-Raphson method is an iterative method for solving nonlinear equation systems. It establishes a power flow calculation correction equation and iterates repeatedly to make the solution locally linearized.

[0014] In the Newton-Raphson method, for a power system with n nodes, each PQ node and PV node has:

[0015]

[0016] In the formula, , Let i be the active power imbalance and reactive power imbalance at node i in the power correction equation. , Let i be the active power and reactive power. , Let the voltages at nodes i and j be . Let be the real and imaginary parts of the element in the i-th row and j-th column of the nodal admittance matrix. Let be the imaginary part of the element in the i-th row and j-th column of the nodal admittance matrix. Let be the voltage phase difference between node i and node j; by repeatedly solving the modified equation until convergence, the power flow of the power system can be obtained.

[0017] The objective function of the prospective cross-section over-limit control model in step S4 is:

[0018]

[0019] In the formula, This is the penalty coefficient for discarded light. Let be the amount of solar power curtailed at photovoltaic power station i at time t. This is the penalty coefficient for exceeding the limit. The cross-section at time t is limited.

[0020] The constraints of the forward-looking cross-sectional limit control model in step S4 include upper and lower limits of photovoltaic output, dynamic equations of energy storage SOC and limits of charging and discharging power, and power balance constraints.

[0021] The upper and lower limits of photovoltaic output are as follows:

[0022]

[0023] In the formula, For the output of photovoltaic unit i at time t, For the minimum output of photovoltaic power station i, This is the maximum output of photovoltaic unit i.

[0024] The aforementioned energy storage SOC dynamic equation and charge / discharge power limit constraints are as follows:

[0025]

[0026]

[0027] In the formula, Let t be the energy storage state. The energy storage charging coefficient, The charging state at time t. The discharge state at time t. The energy storage discharge coefficient, This is the maximum charging power. This represents the maximum discharge power.

[0028] The power balance constraint is as follows:

[0029]

[0030] In the formula, The output value of unit l, including new energy sources. Let m be the load value of line m. This represents the line loss value.

[0031] A system for a forward-looking section over-limit control method for transmission and distribution networks incorporating new energy sources, the system comprising:

[0032] The predictive power flow analysis module uses existing data-driven distributed photovoltaic cluster output prediction methods to obtain the predicted output data of new energy sources; it sets the new energy to full power generation, inputs the predicted output data of new energy sources into the transmission-distribution network model, and constructs a scenario where new energy sources are fully connected to the grid; it uses the Matpower tool to perform power flow calculations to obtain the predicted cross-section over-limit situation.

[0033] The forward-looking rolling optimization module runs a forward-looking scheduling program to establish a forward-looking cross-section over-limit control model and its objective function and constraints. The objective function is to minimize the sum of curtailment cost and over-limit penalty cost. The cplex solver is used to solve the optimized photovoltaic curtailment plan and energy storage charging and discharging strategy in rolling solutions according to time periods.

[0034] The instruction execution module issues power adjustment instructions based on the optimization results.

[0035] The present invention has the following advantages over the prior art:

[0036] This invention eliminates risk points before limit exceedances occur by adjusting energy storage status and photovoltaic output in advance, while coordinating resources in both regions to achieve forward-looking optimized scheduling of new energy output. Through forward-looking optimized scheduling, an active safety control mode of "predicting limit exceedances and preventing them in advance" is realized, which significantly improves the safety of the power system. At the same time, by reducing the amount of new energy curtailed, the utilization rate of new energy is improved. Attached Figure Description

[0037] Appendix Figure 1 A flowchart of a forward-looking section over-limit control method for power transmission and distribution networks containing new energy sources, provided by the present invention;

[0038] Appendix Figure 2 The IEEE standard 39-node system network structure diagram provided for this invention;

[0039] Appendix Figure 3 The IEEE standard 14-node system network structure diagram provided for this invention

[0040] Appendix Figure 4 A graph showing the difference in network losses between artificial power curtailment and forward-looking dispatch in the upper-level power grid model provided by this invention;

[0041] Appendix Figure 5 The present invention provides a power flow variation diagram over time for 56 over-limit lines in the scenario of full grid connection of new energy in the power transmission and distribution network.

[0042] Appendix Figure 6 The power flow variation diagram over time for line 57 in the scenario of full grid connection of new energy in the transmission and distribution network provided by the present invention;

[0043] Appendix Figure 7 The power flow variation diagram of over-limit line 59 under the scenario of full grid connection of new energy in the transmission and distribution network provided by the present invention;

[0044] Appendix Figure 8 The power flow variation diagram of over-limit lines under the scenario of full grid connection of new energy in the transmission and distribution network provided by the present invention;

[0045] Appendix Figure 9The power flow variation diagram of over-limit line 61 under the scenario of full grid connection of new energy in the transmission and distribution network provided by the present invention;

[0046] Appendix Figure 10 The diagram showing the power flow variation over time of the original over-limit line 56 after the power transmission and distribution network receives and executes the forward-looking dispatching command, as provided by the present invention.

[0047] Appendix Figure 11 The diagram provided by the present invention shows the power flow variation over time of the original over-limit line 57 after the transmission and distribution network receives and executes the forward-looking dispatching command;

[0048] Appendix Figure 12 The diagram provided by the present invention shows the power flow variation over time of the original over-limit line 59 after the power transmission and distribution network receives and executes the forward-looking dispatching command;

[0049] Appendix Figure 13 The diagram provided by the present invention shows the power flow variation over time of the original over-limit line 60 after the power transmission and distribution network receives and executes the forward-looking dispatching command;

[0050] Appendix Figure 14 The diagram provided by the present invention shows the power flow variation over time of the original over-limit line 61 after the transmission and distribution network receives and executes the forward-looking dispatching command. Detailed Implementation

[0051] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that the invention will be thorough and complete, and the concept of the exemplary embodiments will be fully conveyed to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and therefore their detailed description will be omitted.

[0052] The terms “a,” “one,” “the,” and “the” are used to indicate the existence of one or more elements / components / etc.; the terms “including” and “having” are used to indicate an open-ended meaning of inclusion and that other elements / components / etc. may exist in addition to the listed elements / components / etc.

[0053] This invention provides a forward-looking section over-limit control method for power transmission and distribution networks containing new energy sources. The steps of this control method are as follows:

[0054] S1. Obtain the power output data of new energy prediction using existing data-driven distributed photovoltaic cluster power output prediction methods.

[0055] S2. Set the new energy to full power generation, input the predicted output data of new energy obtained in step S1 into the transmission-distribution network model, and construct the scenario of full grid connection of new energy in the transmission-distribution network.

[0056] The transmission-distribution network model includes a high-voltage grid, a low-voltage distribution network, a low-voltage grid, and power tie lines. Specifically, the high-voltage grid is represented by the IEEE standard 39-node system network structure, and the low-voltage distribution network is represented by the IEEE standard 14-node system network structure. The low-voltage distribution network is connected to the high-voltage grid through power tie lines and accesses the respective power generation and consumption equipment contained in the low-voltage grid. The transmission-distribution network model is formed by the transmission from the high-voltage grid to the low-voltage grid and then to the power generation and consumption equipment at the end.

[0057] S3. Based on the scenario of full grid connection of new energy in the transmission and distribution network constructed in step S2, use the matpower tool to perform power flow calculations to obtain the predicted cross-section over-limit situation.

[0058] The power flow calculation program in the MATLAB tool uses the Newton-Raphson method to perform power flow calculations. The Newton-Raphson method is an iterative method for solving nonlinear equation systems. It establishes a power flow calculation correction equation and iterates repeatedly to make the solution locally linearized.

[0059] In the Newton-Raphson method, for a power system with n nodes, each PQ node and PV node has:

[0060]

[0061] In the formula, , Let i be the active power imbalance and reactive power imbalance at node i in the power correction equation. , Let i be the active power and reactive power. , Let the voltages at nodes i and j be . Let be the real and imaginary parts of the element in the i-th row and j-th column of the nodal admittance matrix. Let be the imaginary part of the element in the i-th row and j-th column of the nodal admittance matrix. Let be the voltage phase difference between node i and node j. By repeatedly solving the modified equations until convergence, the power flow of the power system can be obtained.

[0062] S4. Based on the predicted cross-section exceedance situation obtained in step S3, run the forward scheduling program, establish a forward-looking cross-section exceedance control model, and determine the objective function and constraints. The objective function is to minimize the sum of the cost of wasted light and the cost of exceedance penalty.

[0063] The objective function of the forward-looking cross-section over-limit control model is:

[0064]

[0065] In the formula, This is the penalty coefficient for discarded light. Let be the amount of solar power curtailed at photovoltaic power station i at time t. This is the penalty coefficient for exceeding the limit. The cross-section at time t is limited.

[0066] The constraints of the forward-looking cross-sectional limit control model include upper and lower limits of photovoltaic output, dynamic equations of energy storage SOC and limits of charging and discharging power, and power balance constraints.

[0067] Among them, the upper and lower limits of photovoltaic power output are constrained as follows:

[0068]

[0069] In the formula, For the output of photovoltaic unit i at time t, For the minimum output of photovoltaic power station i, This is the maximum output of photovoltaic unit i.

[0070] The dynamic equations for energy storage SOC and the limits for charge and discharge power are as follows:

[0071]

[0072]

[0073] In the formula, Let t be the energy storage state. The energy storage charging coefficient, The charging state at time t. The discharge state at time t. The energy storage discharge coefficient, This is the maximum charging power. This represents the maximum discharge power.

[0074] The power balance constraint is:

[0075]

[0076] In the formula, The output value of unit l, including new energy sources. Let m be the load value of line m. This represents the line loss value.

[0077] S5. Use the cplex solver to solve the objective function in a rolling manner according to time periods to obtain the optimized photovoltaic curtailment plan and energy storage charging and discharging strategy;

[0078] For example, the forward-looking cross-section over-limit control model is used to solve the optimization result once at 1-hour intervals for a total of 24 hours. The optimization result is output as the optimized output of photovoltaic power at that time point, i.e., the scheduling target value.

[0079] S6. Issue power adjustment commands based on the optimization results.

[0080] The control method provided by this invention is compared with the traditional manual power curtailment strategy to demonstrate the superiority of this invention. The manual power curtailment strategy refers to the method provided by this invention, which, in the scenario of full grid connection of renewable energy in the transmission and distribution network, manually partially disconnects renewable energy units at the moment the limit is exceeded, thereby eliminating the limit exceedance.

[0081] A system for a forward-looking section over-limit control method for transmission and distribution networks incorporating new energy sources, the system comprising:

[0082] The predictive power flow analysis module uses existing data-driven distributed photovoltaic cluster output prediction methods to obtain the predicted output data of new energy sources; it sets the new energy to full power generation, inputs the predicted output data of new energy sources into the transmission-distribution network model, and constructs a scenario where new energy sources are fully connected to the grid; it uses the Matpower tool to perform power flow calculations to obtain the predicted cross-section over-limit situation.

[0083] The forward-looking rolling optimization module runs a forward-looking scheduling program to establish a forward-looking cross-section over-limit control model and its objective function and constraints. The objective function is to minimize the sum of curtailment cost and over-limit penalty cost. The cplex solver is used to solve the optimized photovoltaic curtailment plan and energy storage charging and discharging strategy in rolling solutions according to time periods.

[0084] The instruction execution module issues power adjustment instructions based on the optimization results.

[0085] Specific calculation examples

[0086] Using the IEEE standard 39-bus system network structure as a high-voltage power grid, the topology is as follows: Figure 2 As shown, its voltage level is 345kV, with a total of 39 nodes and 46 branches; it uses the IEEE standard 14-node system network structure as the low-voltage distribution network, and the topology is as follows. Figure 3 As shown, its voltage level is 23kV, and it has 14 nodes and 20 branches. The low-voltage distribution network is connected to the high-voltage grid via power tie lines. Low-voltage grid 1 and low-voltage grid 2 each contain their own power generation and consumption equipment, namely: photovoltaic (PV), energy storage (ES), and controlled source (CS). From the high-voltage grid to the low-voltage grid and then to the power generation and consumption equipment at the terminal, a multi-voltage level transmission-distribution network model is formed. The two tie lines are counted as branches. This power system model has a total of 67 nodes and 88 branches.

[0087] The predicted output data of new energy sources is used as the basis for a forward-looking control method and system for cross-section overruns in transmission and distribution networks that include new energy sources. Compared with artificial power curtailment strategies, a comparative analysis of the amount of new energy curtailment was conducted, and the results are shown in Table 1 below:

[0088] Table 1. Comparison of Curtailment Amount from New Energy Sources Due to Artificial Power Curtailment and Curtailment Amount from Forward-Looking Section Exceedance Control Method

[0089]

[0090] During periods 3-9, full power generation is optimal both before and after. During periods 10-12, energy storage is near full charge, limiting charging capacity. Changes in forecast values ​​cause overlapping power flows across sections during this period, necessitating a slight reduction in power curtailment to ensure safety compared to manual curtailment strategies. During periods 13-16, full power generation is optimal both before and after. During periods 16-18, load demand and renewable energy output decrease, while photovoltaic and energy storage, after being controlled to exceed limits, still generate output, leading to increased curtailment. Calculations based on the table show that the total curtailment is reduced by 4.01% compared to manual curtailment strategies.

[0091] The optimized calculation results of the upper-layer network loss are as follows: Figure 4 As shown, in period 2, the forward-looking cross-sectional limit control predicted the photovoltaic output and issued an early warning, initiating energy storage charging ahead of schedule. The charging process increased line current, leading to a slight increase in upper-level grid losses. In period 3, as actual photovoltaic output began, the forward-looking cross-sectional limit control adjusted the power flow distribution in advance based on predictions, causing energy storage to switch from charging to discharging, reducing transmission losses. Starting in period 4, photovoltaic output increased significantly. Due to the improved local consumption of new energy sources thanks to the forward-looking cross-sectional limit control, the upper-level grid losses steadily decreased.

[0092] The power flow variation over time of some over-limit lines in the scenario of full grid connection of new energy in the transmission and distribution network, such as Figures 5-9 As shown, during certain periods, power lines exceed their limits due to increased electricity load and the lack of reasonable dispatching strategies; that is, the power flowing through the lines exceeds the limit. However, the forward-looking cross-section limit control method and system for transmission and distribution networks incorporating renewable energy, as presented in this invention, enables forward-looking dispatching to fully utilize the time-shifting capability of energy storage, transferring excess photovoltaic energy from midday to evening peak use. Simultaneously, it optimizes the trade-off between curtailment and limit exceeding at the system level, achieving the overall optimal dispatching effect. The dispatching effect is as follows: Figures 10-14 As shown in the figure, the power flow of some previously over-limit lines changes over time after the transmission and distribution network receives and executes forward-looking dispatch instructions. Figures 5-9 The comparison shows that the power of the originally over-limit line was successfully eliminated after the forward scheduling command was executed.

[0093] This invention eliminates risk points before limit exceedances occur by adjusting energy storage status and photovoltaic output in advance, while coordinating resources in both regions to achieve forward-looking optimized scheduling of new energy output. Through forward-looking optimized scheduling, an active safety control mode of "predicting limit exceedances and preventing them in advance" is realized, which significantly improves the safety of the power system. At the same time, by reducing the amount of new energy curtailed, the utilization rate of new energy is improved.

[0094] In this embodiment of the invention, the term "multiple" refers to two or more, unless otherwise explicitly defined. The terms "install," "connect," and "fix" should be interpreted broadly. For example, "connect" can mean a fixed connection, a detachable connection, or an integral connection. Those skilled in the art can understand the specific meaning of the above terms in this embodiment of the invention based on the specific circumstances.

[0095] In the description of the embodiments of the present invention, it should be understood that the terms "upper" and "lower" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the device or unit referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of the present invention.

[0096] In the description of this specification, the terms "an embodiment," "a preferred embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0097] The above embodiments are merely illustrative of the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solutions based on the technical concept proposed in this invention shall fall within the scope of protection of this invention. Technologies not covered in this invention can be implemented using existing technologies.

Claims

1. A forward-looking section over-limit control method for transmission and distribution networks containing new energy sources, characterized in that: The control method involves the following steps: S1. Obtain the output data of new energy prediction using existing data-driven distributed photovoltaic cluster output prediction methods; S2. Set the new energy to full power generation, input the predicted output data of new energy obtained in step S1 into the transmission-distribution network model, and construct the scenario of full grid connection of new energy in the transmission-distribution network. S3. Based on the scenario of full grid connection of new energy in the transmission and distribution network constructed in step S2, use the matpower tool to perform power flow calculations to obtain the predicted cross-section over-limit situation. S4. Based on the predicted cross-section exceedance situation obtained in step S3, run the forward scheduling program, establish a forward-looking cross-section exceedance control model, and determine the objective function and constraints. The objective function is to minimize the sum of the cost of wasted light and the cost of exceedance penalty. S5. Use the cplex solver to solve the objective function in a rolling manner according to time periods to obtain the optimized photovoltaic curtailment plan and energy storage charging and discharging strategy; S6. Issue power adjustment command.

2. The forward-looking section over-limit control method for transmission and distribution networks containing new energy sources according to claim 1, characterized in that: The transmission-distribution network model in step S2 includes a high-voltage power grid, a low-voltage distribution network, a low-voltage power grid, and power tie lines. Specifically, the high-voltage power grid is based on the IEEE standard 39-node system network structure, and the low-voltage distribution network is based on the IEEE standard 14-node system network structure. The low-voltage distribution network is connected to the high-voltage power grid through power tie lines and accesses the respective power generation and consumption equipment contained in the low-voltage power grid. The transmission-distribution network model is formed by the power generation and consumption equipment at the end of the low-voltage power grid from the high-voltage power grid to the low-voltage power grid.

3. The forward-looking section over-limit control method for transmission and distribution networks containing new energy sources according to claim 1, characterized in that: The power flow calculation program of the matpower tool in step S3 uses the Newton-Raphson method to perform power flow calculation. The Newton-Raphson method is an iterative method for solving nonlinear equation systems. It establishes a power flow calculation correction equation and iterates repeatedly to make the solution locally linearized.

4. The forward-looking section over-limit control method for transmission and distribution networks containing new energy sources according to claim 3, characterized in that: In the Newton-Raphson method, for a power system with n nodes, each PQ node and PV node has: In the formula, , Let i be the active power imbalance and reactive power imbalance at node i in the power correction equation. , Let i be the active power and reactive power. , Let the voltages at nodes i and j be . Let be the real and imaginary parts of the element in the i-th row and j-th column of the nodal admittance matrix. Let be the imaginary part of the element in the i-th row and j-th column of the nodal admittance matrix. Let be the voltage phase difference between node i and node j.

5. The forward-looking section over-limit control method for transmission and distribution networks containing new energy sources according to claim 1, characterized in that: The objective function of the prospective cross-section over-limit control model in step S4 is: In the formula, This is the penalty coefficient for discarded light. Let be the amount of solar power curtailed at photovoltaic power station i at time t. This is the penalty coefficient for exceeding the limit. The cross-section at time t is limited.

6. The forward-looking section over-limit control method for transmission and distribution networks containing new energy sources according to claim 1, characterized in that: The constraints of the forward-looking cross-sectional limit control model in step S4 include upper and lower limits of photovoltaic output, dynamic equations of energy storage SOC and limits of charging and discharging power, and power balance constraints.

7. The forward-looking section over-limit control method for transmission and distribution networks containing new energy sources according to claim 6, characterized in that: The upper and lower limits of photovoltaic output are as follows: In the formula, For the output of photovoltaic unit i at time t, For the minimum output of photovoltaic power station i, This is the maximum output of photovoltaic unit i.

8. The forward-looking section over-limit control method for transmission and distribution networks containing new energy sources according to claim 6, characterized in that: The aforementioned energy storage SOC dynamic equation and charge / discharge power limit constraints are as follows: In the formula, Let t be the energy storage state. The energy storage charging coefficient, The charging state at time t. The discharge state at time t. The energy storage discharge coefficient, This is the maximum charging power. This represents the maximum discharge power.

9. The forward-looking section over-limit control method for transmission and distribution networks containing new energy sources according to claim 6, characterized in that: The power balance constraint is as follows: In the formula, The output value of unit l, including new energy sources, Let m be the load value of line m. This represents the line loss value.

10. A system used in the forward-looking section over-limit control method for transmission and distribution networks containing new energy sources as described in any one of claims 1-9, characterized in that: The system includes: The predictive power flow analysis module uses existing data-driven distributed photovoltaic cluster output prediction methods to obtain the predicted output data of new energy sources; it sets the new energy to full power generation, inputs the predicted output data of new energy sources into the transmission-distribution network model, and constructs a scenario where new energy sources are fully connected to the grid; it uses the Matpower tool to perform power flow calculations to obtain the predicted cross-section over-limit situation. The forward-looking rolling optimization module runs a forward-looking scheduling program to establish a forward-looking cross-section over-limit control model and its objective function and constraints. The objective function is to minimize the sum of curtailment cost and over-limit penalty cost. The cplex solver is used to solve the optimized photovoltaic curtailment plan and energy storage charging and discharging strategy in rolling solutions according to time periods. The instruction execution module issues power adjustment instructions based on the optimization results.

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