Embedded DC operation optimization method for improving section power transmission capability
By performing N-1 fault simulation and deep reinforcement learning algorithm optimization on embedded DC lines, the problem of uneven power flow distribution affecting the cross-sectional power transmission capacity was solved, thereby improving the overall power transmission capacity and reducing network losses.
Patent Information
- Application Number
- CN202511739928.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-25
- Publication Date
- 2026-02-10
AI Technical Summary
The cross-sectional power transmission capacity is affected by the uneven distribution of power flow, resulting in a high load rate of one or several AC lines, making it difficult to further improve the overall power transmission capacity.
By performing N-1 fault simulation on embedded DC lines, an objective function is constructed. Then, a deep reinforcement learning algorithm is used to optimize the transmission power of the embedded DC lines, improve the uneven power flow distribution of AC lines, and reduce the load rate.
It effectively improved the cross-sectional power transmission capacity, improved the problem of uneven load rate of AC lines, and reduced network losses.
Smart Images
Figure CN121507897A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to power system safety and stability analysis and control technology, and in particular discloses an embedded DC operation optimization method to improve the cross-sectional transmission capacity. Background Technology
[0002] With the increasing proportion of new energy sources in the energy structure and the continuous expansion of the AC power grid, there is an urgent need to improve the operational flexibility and cross-sectional transmission capacity of provincial / regional AC power grids. However, if AC transmission technology is used to enhance this capacity, AC power flow is difficult to control effectively, and the overall transmission capacity improvement is limited due to factors such as short-circuit current. Therefore, the Jiangsu power grid proposed "embedding" DC transmission within the provincial AC power grid, constructing and putting into operation the Yangzhou-Zhenjiang ±200 kV ±200 kV "embedded" DC transmission project at its north-to-south power transmission cross-river section, thereby improving the cross-sectional transmission capacity.
[0003] However, the transmission capacity of a transmission section is affected by the power flow balance of the multiple AC lines contained within it. If the power flow distribution is uneven, and one or more AC lines experience heavy power flow and high load rates, it will be difficult to further increase the overall transmission capacity of the section. In this case, if the embedded DC transmission power of the same transmission section can be optimized and adjusted to reduce the load rate of each AC line, more room for increasing transmission capacity can be released. This allows for further improvement of the overall transmission power of the section when needed, which is a technical problem that urgently needs to be solved in this field. Summary of the Invention
[0004] This application addresses the shortcomings of the aforementioned background technology by providing an embedded DC operation optimization method to improve the cross-sectional power transmission capacity, thus solving the technical problem of insufficient cross-sectional power transmission capacity caused by uneven power flow distribution in current research.
[0005] This application provides an embedded DC operation optimization method to improve the transmission capacity of a transmission section. The transmission section includes an embedded DC line and multiple AC lines. The optimization method includes:
[0006] Perform N-1 fault simulation on the AC line of the transmission section where the embedded DC is located. If the transmission section has line overload after the N-1 fault simulation, start the embedded DC operation strategy optimization.
[0007] Taking into account the transmission line load rate and network loss, an objective function for optimizing the embedded DC operation strategy is constructed.
[0008] A deep reinforcement learning algorithm is used to optimize and determine the transmission power within the power range of embedded DC transmission.
[0009] Optionally, N-1 fault simulation is performed on other AC lines of the transmission section where the embedded DC is located. If the transmission section experiences line overload after the N-1 fault simulation, the embedded DC operation strategy optimization is initiated, including:
[0010] Based on the AC line transmission power and grid structure, determine the AC line that is in the same transmission section as the embedded DC power transmission direction;
[0011] Choose one of the AC lines located in the same transmission section as the detection AC line, and set a three-phase grounding permanent short circuit fault on the busbar on one side of the detection AC circuit and disconnect the line 0.1s after the fault as the N-1 fault simulation;
[0012] Calculate the load rate of the remaining AC lines that are in the same transmission section as the embedded DC line after the detected AC line is disconnected;
[0013] Select any one of the AC lines other than the detection AC line as a new detection circuit, perform the N-1 fault simulation, and calculate the load rate of the remaining AC lines that are in the same transmission section as the embedded DC after the new detection AC line is cut off, until all the AC lines are traversed.
[0014] If any AC line experiences a load rate exceeding a set threshold after the faulty line is disconnected, the embedded DC operation strategy optimization will be initiated.
[0015] Optionally, the set threshold is 1.0.
[0016] Optionally, taking into account transmission line load rate and network loss, the objective function for optimizing the embedded DC operation strategy is constructed, including:
[0017] Taking into account transmission line load rate and network loss, the objective function for optimizing the embedded DC operation strategy is as follows:
[0018]
[0019] in, Represents the objective function value. This indicates the maximum load rate of each AC line in the transmission section. This represents the total network loss of the AC and DC lines at the aforementioned transmission section. The weighting coefficient represents the load rate.
[0020] Optionally, the maximum load rate of each AC line is calculated using a first formula, which is as follows:
[0021]
[0022] Among them, P i P represents the power transmitted by the i-th AC line. rated_i Let represent the rated capacity of the i-th AC line, and n represent the number of AC lines.
[0023] Optionally, the total network loss of the AC and DC transmission lines at the transmission section is calculated using a second formula, which is as follows:
[0024]
[0025] Among them, Q i U represents the reactive power transmitted by the AC line described in the i-th clause. Ni R represents the rated voltage of the AC line described in clause i. i P represents the resistance of the AC line described in the i-th clause. d U represents the power transmitted by the embedded DC line. d R represents the rated voltage of the embedded DC circuit. d This represents the resistance of the embedded DC circuit.
[0026] Optionally, the total network loss of the AC and DC transmission lines at the transmission section further includes: calculating the total network loss of the AC and DC transmission lines at the transmission section using the second formula. The data is normalized to the range of [0,1] so that the total network loss of the AC and DC transmission lines at the transmission section is consistent with the load rate range of the AC line.
[0027] Optionally, the weighting coefficient of the load rate The value of depends on the overload condition of the AC line during the N-1 fault simulation before optimization, and is determined according to the third formula, which is as follows:
[0028]
[0029] Where k represents the maximum number of AC lines whose fault concentration load rate exceeds 1.0.
[0030] Alternatively, when k=1, The value is 0.5; when k=n-1, The value is 1.0.
[0031] Optionally, a deep reinforcement learning algorithm is employed to optimize and determine the transmission power within the transmission power range of the embedded DC, including:
[0032] The embedded DC line transmits power P d The value range is [0.3pu, 1.2pu], in P dWithin the range of values, the TD3 deep reinforcement learning algorithm is used to optimize the power P transmitted by the embedded DC line. d The correction amount is mapped to an action, and the power flow calculation results and the current embedded DC line transmission power are mapped to a state. The reward function of the algorithm is constructed in conjunction with the objective function, and the reward function is as follows:
[0033]
[0034] in, The objective function value is given for any given initial power supply to the embedded DC line.
[0035] The technical solution provided in this application embodiment, the embedded DC operation optimization method for improving the cross-sectional power transmission capacity provided in this embodiment, can improve the problem of uneven power flow distribution of each AC line in the transmission section by optimizing and adjusting the transmission power of the embedded DC, while taking into account both the improvement of transmission capacity and network loss, and can effectively improve the transmission capacity of the section. Attached Figure Description
[0036] Figure 1 This is a schematic diagram of a power transmission section with embedded DC provided in an embodiment of this application. Figure 1 This is a schematic diagram of a power transmission section with embedded DC provided in an embodiment of this application;
[0037] Figure 2 This is a flowchart illustrating an embedded DC operation optimization method for improving the transmission capacity of a power transmission section, provided in an embodiment of this application.
[0038] Figure 3 for Figure 2 The flowchart shown is a schematic diagram of step S1 in the embedded DC operation optimization method for improving the transmission capacity of a transmission section. Detailed Implementation
[0039] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0040] Figure 1 This is a schematic diagram of a power transmission section with embedded DC, provided in an embodiment of this application. A power transmission section, also known as a power flow section or section power flow, is an important concept in power system security and stability analysis. It refers to a set of transmission lines with similar electrical distances and the same active power flow direction under ground-state power flow conditions, undertaking the function of inter-regional power flow transmission and having transmission limits. This section typically connects the power source center and the load center. When a single component fails, the overall power flow changes relatively little, requiring real-time monitoring of its transmission capacity to ensure system safety. Its division methods include dividing power supply area tie-line groups according to geographical location, or forming monitoring and control groups according to safety constraints. For example, such as... Figure 1The transmission section shown contains 5 AC lines and 1 DC line. It should be noted that in practical applications, the number of AC lines is determined according to specific transmission requirements.
[0041] Figure 2 This is a flowchart illustrating an embedded DC operation optimization method for improving cross-sectional power transmission capacity provided in an embodiment of this application. Figure 1 and Figure 2 As shown, this embodiment provides an embedded DC operation optimization method for improving the transmission capacity of a transmission section. The transmission section includes embedded DC lines and multiple AC lines. The embedded DC operation optimization method for improving the transmission capacity of a transmission section provided in this embodiment includes:
[0042] S1: Perform N-1 fault simulation on the AC line of the transmission section where the embedded DC is located. If the transmission section is overloaded after the N-1 fault simulation, start the embedded DC operation strategy optimization.
[0043] Specifically, N-1 fault simulation is mainly used to evaluate the stability and safety of a power system when a single component fails. By simulating the system's operating state after a component failure, it verifies whether the constraints such as voltage and current are met.
[0044] S2: Taking into account the transmission line load rate and network loss, construct the objective function for optimizing the embedded DC operation strategy.
[0045] S3: Employ a deep reinforcement learning algorithm to optimize and determine the transmission power within the power range of embedded DC transmission.
[0046] The embedded DC operation optimization method for improving the cross-sectional power transmission capacity provided in this embodiment can improve the problem of uneven power flow distribution of AC lines in the transmission section by optimizing and adjusting the transmission power of the embedded DC, while taking into account both the improvement of transmission capacity and network loss, and can effectively improve the transmission capacity of the section.
[0047] Figure 3 for Figure 2 The flowchart shown is a schematic diagram of step S1 in the embedded DC operation optimization method for improving the cross-sectional power transmission capacity. (See attached diagram.) Figure 3 As shown, in the embedded DC operation optimization method for improving cross-sectional power transmission capacity provided in this embodiment, step S1 includes:
[0048] S11: Based on the AC line transmission power and grid structure, determine the AC lines that are in the same transmission section as the embedded DC power transmission lines. Figure 1 Taking the power transmission section shown as an example, there are 5 AC lines in the same power transmission section as the embedded DC line.
[0049] S12: Select any AC line from those in the same transmission section as the test AC line. Simulate an N-1 fault by setting a three-phase permanent ground fault on the busbar of the test AC circuit side and disconnecting the line 0.1 seconds after the fault. Figure 1 Taking the power transmission section shown as an example, an AC line can be randomly selected as the test AC line, or an AC line can be selected from left to right or from right to left as the test AC line.
[0050] S13: Calculate the load rate of the remaining AC lines that are in the same transmission section as the embedded DC line after the detected AC line is disconnected.
[0051] S14: Select any AC line other than the detection AC line as the new detection circuit, perform N-1 fault simulation, and calculate the load rate of the remaining AC lines that are in the same transmission section as the embedded DC line after the new detection AC line is cut off, until all AC lines are traversed.
[0052] S15: If any AC line experiences a load rate exceeding a set threshold after the faulty line is disconnected, the embedded DC operation strategy optimization is initiated. Specifically, the set threshold is 1.0.
[0053] In the embedded DC operation optimization method for improving the cross-section power transmission capacity provided in this embodiment, a three-phase grounding permanent short-circuit fault is set on the busbar on the AC circuit side and the line is disconnected 0.1s after the fault as an N-1 fault simulation. This method can accurately determine whether the AC circuit of the power transmission section is overloaded, thereby enabling timely activation of the embedded DC operation strategy optimization.
[0054] In the embedded DC operation optimization method for improving the cross-sectional power transmission capacity provided in this embodiment, step S2 specifically includes: taking into account the transmission line load rate and network loss, constructing the objective function for embedded DC operation strategy optimization as follows:
[0055]
[0056] in, Represents the objective function value. This indicates the maximum load rate of each AC line in the power transmission section. This represents the total network loss of AC and DC transmission lines across the transmission section. The weighting coefficient represents the load rate.
[0057] Specifically, the maximum load rate of each AC line is calculated using the first formula, which is as follows:
[0058]
[0059] Among them, Pi P represents the power transmitted by the i-th AC line. rated_i Let represent the rated capacity of the i-th AC line, and n represent the number of AC lines.
[0060] Specifically, the total network loss of AC and DC transmission lines at the transmission section is calculated using the second formula, which is as follows:
[0061]
[0062] Among them, Q i U represents the reactive power transmitted by the i-th AC line. Ni R represents the rated voltage of the i-th AC line. i Let P represent the resistance of the i-th AC line. d U represents the power transmitted by the embedded DC line. d R represents the rated voltage of the embedded DC circuit. d This indicates the resistance of an embedded DC circuit.
[0063] Furthermore, based on the second formula, the total network loss of AC and DC transmission lines at the transmission section also includes: the total network loss of AC and DC transmission lines at the transmission section calculated using the second formula. The data is normalized to the range of [0, 1] so that the total network loss of AC and DC transmission lines is consistent with the load rate range of AC lines.
[0064] Specifically, the weighting factor of the load rate The value of depends on the overload condition of the AC line during the N-1 fault simulation before optimization, and is determined according to the third formula, which is as follows:
[0065]
[0066] Where k represents the maximum number of AC lines whose fault concentration load rate exceeds 1.0.
[0067] Furthermore, when k=1, The value is 0.5; when k=n-1, The value is 1.0.
[0068] In the embedded DC operation optimization method for improving the cross-sectional power transmission capacity provided in this embodiment, step S3 specifically includes: the embedded DC line transmitting power P d The value range is [0.3pu, 1.2pu], in P d Within the range of values, the TD3 deep reinforcement learning algorithm is used to optimize the power transmission P of the embedded DC line. dThe correction quantity is mapped to an action, and the power flow calculation results and the current embedded DC line transmission power are mapped to a state. The reward function of the algorithm is constructed in conjunction with the objective function. The reward function is as follows:
[0069]
[0070] in, The objective function value is given for any given initial power supply to the embedded DC line.
[0071] In the embedded DC operation optimization method for improving the transmission capacity of a transmission section provided in this embodiment, the reward function of the algorithm is constructed through the objective function, and the transmission power is determined by optimizing within the transmission power range of the embedded DC based on the reward function. In this way, the problem of uneven power flow distribution of each AC line in the transmission section can be improved by optimizing and adjusting the transmission power of the embedded DC. At the same time, it takes into account both the factors of improving transmission capacity and network loss, and can effectively improve the transmission capacity of the section.
[0072] For ease of understanding, this application also provides actual data and structure of a provincial power grid, and performs fault simulation based on the PSD-BPA simulation platform. The above-mentioned schematic diagram of the "North-to-South Power Transmission" section of the provincial power grid, including embedded DC transmission, is shown in the figure. Figure 1 As shown in Table 1, the initial embedded DC transmission power is 180MW, and the rated capacities of the other five AC lines in the transmission section are 3600MW, 3500MW, 3200MW, 3100MW, and 3000MW, respectively. The load rates of each AC line are shown in Table 1.
[0073] Table 1. AC line load rate before optimization
[0074] Exchange Line 1 AC Line 2 Exchange Line 3 Exchange Line 4 Exchange Line 5 26.79% 28.52% 71.39% 50.51% 53.32%
[0075] The embedded DC transmission power was optimized using the technical solution of this invention, increasing its transmission power from 180MW to 450MW. The load rate of each AC line is shown in Table 2. Comparing the results in Tables 1 and 2, it can be seen that the load rate of each AC line decreased after optimization, with the maximum load rate decreasing from 71.39% to 65.98%. This effectively improved the power flow distribution balance of the transmission section and further enhanced the transmission capacity of the section.
[0076] Table 2. Optimized AC line load rate
[0077] Exchange Line 1 AC Line 2 Exchange Line 3 Exchange Line 4 Exchange Line 5 26.09% 28.16% 65.98% 50.21% 51.99%
[0078] As shown in Tables 1 and 2, the load rates of each AC line before and after optimization are reduced. This helps to improve the uneven power flow distribution of each AC line in the transmission section. At the same time, it takes into account both the improvement of transmission capacity and network loss, and can effectively improve the transmission capacity of the section.
[0079] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.
[0080] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.
[0081] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this application.
Claims
1. An embedded DC operation optimization method for improving cross-sectional power transmission capacity, characterized in that, The power transmission section includes an embedded DC line and multiple AC lines, and the optimization method includes: Perform N-1 fault simulation on the AC line of the transmission section where the embedded DC is located. If the transmission section is overloaded after the N-1 fault simulation, start the embedded DC operation strategy optimization. Taking into account the transmission line load rate and network loss, an objective function for optimizing the embedded DC operation strategy is constructed. A deep reinforcement learning algorithm is used to optimize and determine the transmission power within the power range of embedded DC transmission.
2. The embedded DC operation optimization method for improving cross-sectional power transmission capacity according to claim 1, characterized in that, Perform N-1 fault simulation on other AC lines in the transmission section where the embedded DC is located. If the transmission section experiences line overload after the N-1 fault simulation, initiate embedded DC operation strategy optimization, including: Based on the AC line transmission power and grid structure, determine the AC line that is in the same transmission section as the embedded DC power transmission direction; Choose one of the AC lines located in the same transmission section as the detection AC line, and set a three-phase grounding permanent short circuit fault on the busbar on one side of the detection AC circuit and disconnect the line 0.1s after the fault as the N-1 fault simulation; Calculate the load rate of the remaining AC lines that are in the same transmission section as the embedded DC line after the detected AC line is disconnected; Select any one of the AC lines other than the detection AC line as a new detection circuit, perform the N-1 fault simulation, and calculate the load rate of the remaining AC lines that are in the same transmission section as the embedded DC after the new detection AC line is cut off, until all the AC lines are traversed. If any AC line experiences a load rate exceeding a set threshold after the faulty line is disconnected, the embedded DC operation strategy optimization will be initiated.
3. The embedded DC operation optimization method for improving cross-sectional power transmission capacity according to claim 2, characterized in that, The set threshold is 1.
0.
4. The embedded DC operation optimization method for improving cross-sectional power transmission capacity according to claim 3, characterized in that, Taking into account transmission line load rate and network loss, the objective function for optimizing the embedded DC operation strategy is constructed, including: Taking into account transmission line load rate and network loss, the objective function for optimizing the embedded DC operation strategy is as follows: ； in, Represents the objective function value. This indicates the maximum load rate of each AC line in the transmission section. This represents the total network loss of the AC and DC lines at the aforementioned transmission section. The weighting coefficient represents the load rate.
5. The embedded DC operation optimization method for improving cross-sectional power transmission capacity according to claim 4, characterized in that, The maximum load rate of each AC line is calculated using a first formula, which is as follows: ； Among them, P i P represents the power transmitted by the i-th AC line. rated_i Let represent the rated capacity of the i-th AC line, and n represent the number of AC lines.
6. The embedded DC operation optimization method for improving cross-sectional power transmission capacity according to claim 5, characterized in that, The total network loss of the AC and DC transmission lines at the transmission section is calculated using the second formula, which is as follows: ； Among them, Q i U represents the reactive power transmitted by the AC line described in the i-th clause. Ni R represents the rated voltage of the AC line described in clause i. i P represents the resistance of the AC line described in the i-th clause. d U represents the power transmitted by the embedded DC line. d R represents the rated voltage of the embedded DC circuit. d This represents the resistance of the embedded DC circuit.
7. The embedded DC operation optimization method for improving cross-sectional power transmission capacity according to claim 6, characterized in that, The total network loss of AC and DC transmission lines at the transmission section also includes: The total network loss of the AC and DC transmission lines at the transmission section calculated using the second formula. The data is normalized to the range of [0,1] so that the total network loss of the AC and DC transmission lines at the transmission section is consistent with the load rate range of the AC line.
8. The embedded DC operation optimization method for improving cross-sectional power transmission capacity according to claim 6, characterized in that, The weighting coefficient of the load rate The value of depends on the overload condition of the AC line during the N-1 fault simulation before optimization, and is determined according to the third formula, which is as follows: ； Where k represents the maximum number of AC lines whose fault concentration load rate exceeds 1.
0.
9. The embedded DC operation optimization method for improving cross-sectional power transmission capacity according to claim 8, characterized in that, When k=1, The value is 0.5; when k=n-1, The value is 1.
0.
10. The embedded DC operation optimization method for improving the cross-sectional transmission capacity according to any one of claims 6-9, characterized in that, A deep reinforcement learning algorithm is used to optimize and determine the transmission power within the power range of embedded DC transmission, including: The embedded DC line transmits power P d The value range is [0.3pu, 1.2pu], in P d Within the range of values, the TD3 deep reinforcement learning algorithm is used to optimize the power P transmitted by the embedded DC line. d The correction amount is mapped to an action, and the power flow calculation results and the current embedded DC line transmission power are mapped to a state. The reward function of the algorithm is constructed in conjunction with the objective function, and the reward function is as follows: ； in, The objective function value is given for any given initial power supply to the embedded DC line.