Basin cascade chain type automatic voltage control and coordinated regulation method

Abstract

The application discloses a kind of river basin cascade chain hydroelectric automatic voltage control coordination regulation method, it is related to voltage regulation technical field.The application accurately solves the problem of reactive power pulling and voltage gradient anomaly of chain hydroelectricity, improves reasonable voltage gradient operation rate, avoids internal reactive power invalid consumption.Through the three-level coordination of "provincial dispatching-collective control-power station", replace traditional independent response mode, greatly improve voltage instruction tracking accuracy and AVC examination compliance rate.Simulation verification and index check, enhance the safety and stability of hydroelectric system, optimize reactive power output distribution to reduce loss, adapt to the characteristics of chain structure.Provide high adaptability control framework for large-scale hydroelectricity grid connection, help clean energy efficient consumption and modern power grid stable operation.

Description

Technical Field

[0001] This invention relates to the field of voltage regulation technology, and in particular to a method for automatic voltage control and coordinated regulation of a cascade hydropower system in a river basin. Background Technology

[0002] With the continuous development and construction of cascade hydropower projects in river basins, multiple hydropower stations in the same basin and adjacent cascades are often connected to the power system in a chain structure, forming chain-structured cascade hydroelectric power plants (CC-HPPs) and their sending-end networks, such as... Figure 1 As shown in the diagram, in the CC-HPPs structure, multiple hydropower stations are connected sequentially via transmission lines and centrally connected to the regional hub substation. This structure is characterized by close upstream and downstream hydropower production and operation relationships, large system capacity, and the presence of power crossings, posing new challenges to the coordinated operation and comprehensive management of hydropower in the basin.

[0003] When CC-HPPs are implemented in the closed-loop response regulation of the existing power dispatch automation system's Automatic Voltage Control (AVC), the AVC master station of this functional module primarily aims to serve the overall optimization of the power grid, with the goal of stabilizing the voltage of the central busbar at the regional hub substation. It calculates the voltage setpoints for the high-voltage busbars of each substation and distributes them to the AVC substations at each substation for execution and evaluation. Because this system dispatch model lacks a multi-substation collaborative mechanism and control method from a single substation "point" to a chain-structure "domain," it easily encounters regulation problems such as reactive power imbalances between substations and unreasonable voltage gradients between the beginning and end of the chain of hydropower stations, significantly impacting the stability and economy of hydropower safe production. Therefore, further research is warranted on using the AVC collaborative regulation (Co-regulation) method to conduct regional overall collaborative reactive power and voltage optimization regulation of the chain of hydropower stations and their sending-end networks.

[0004] However, while existing automatic voltage control systems achieve voltage stability at regional central substations by setting target voltage values, their control logic does not fully consider the strong coupling characteristics and individual operational constraints inherent in chain-like structures. This leads to issues such as large inter-station reactive power flows, abnormal voltage gradients, and inaccurate tracking of target voltage values ​​in chain-like hydropower stations during automatic voltage control responses. Therefore, in the current automatic voltage control process, the cascade chain-like hydropower areas in the basin not only fail to accurately respond to voltage commands to meet assessment requirements, but also experience unnecessary inter-station reactive power losses while tracking voltage command values. This further reflects the insufficient adaptability of current automatic voltage control to chain-like hydropower areas, necessitating more targeted reactive power and voltage regulation methods to address the complex reactive power and voltage control problems in chain-like hydropower. Summary of the Invention

[0005] The purpose of this invention is to provide a coordinated regulation method for automatic voltage control in cascade hydropower in a river basin, in order to improve the technical problems of existing automatic voltage control (AVC) systems in cascade hydropower in a river basin, which lack a coordinated mechanism for the electrical coupling characteristics of the chain structure, resulting in internal circulation consumption of reactive power between stations, unreasonable voltage gradient distribution, and affecting the stability of grid voltage and the economic efficiency of operation.

[0006] To achieve the above-mentioned objectives, the embodiments of the present invention provide the following technical solutions:

[0007] A method for automatic voltage control and coordinated regulation of a cascade hydropower project in a river basin, comprising:

[0008] It receives and operates voltage commands issued by the power grid AVC central station, and collects actual operating data of each hydropower station in the cascade chain hydropower network of the basin.

[0009] Based on the topology of the cascade chain hydropower network in the basin and the actual operation data of each hydropower station, the power flow equation is constructed and solved, and the time-varying sensitivity matrix is ​​calculated.

[0010] Based on the time-varying sensitivity matrix, a multi-constraint optimization mathematical model is constructed. The SQP algorithm is used to solve the multi-constraint optimization mathematical model to generate a coordinated reactive power regulation command.

[0011] Based on the collaborative reactive power regulation command, the reactive power output of each hydropower station is virtually adjusted and power flow simulation is performed to output optimized power flow and voltage results;

[0012] Based on the optimized power flow and voltage results, reactive power and voltage operation evaluation indicators are calculated; based on the reactive power and voltage operation evaluation indicators, coordinated reactive power regulation commands are issued to the AVC substations of each hydropower station for coordination.

[0013] Firstly, this invention quantifies the coupling relationship between nodes through reactive power-voltage sensitivity analysis. Combined with a multi-constraint optimization model and the SQP solution algorithm, it can significantly alleviate the reactive power pull problem between stations in the operation of cascade chain hydropower in a watershed and avoid ineffective consumption of reactive power within the region. At the same time, it effectively corrects voltage gradient anomalies, significantly improves the reasonable voltage gradient operation rate, ensures a reasonable voltage reduction distribution from the end to the access point in the chain structure, and eliminates the hidden danger of unreasonable power loss within the power.

[0014] Secondly, to change the traditional mode in which each hydropower station responds independently to the grid's AVC commands, this invention uses a three-level coordinated integrated control system of "provincial dispatch-centralized control-power station" to enable each hydropower station to respond to voltage commands in a coordinated manner under the overall system planning. This significantly reduces the deviation between the operating voltage and the given voltage, reduces AVC reverse adjustment actions, ensures that each hydropower station accurately tracks the voltage target value, significantly improves the grid's AVC assessment compliance rate, solves the problem of low voltage response in the traditional mode, and improves the voltage control response accuracy and assessment compliance rate.

[0015] Thirdly, due to the risks of reactive power imbalance between hydropower stations, equipment overload caused by voltage anomalies, and unstable operation, this invention verifies the reactive power and voltage operation by designing a reactive power and voltage operation evaluation index to ensure the rationality of the coordinated reactive power regulation command and enhance the safety and economy of the hydropower system operation; at the same time, it optimizes the reactive power output distribution of each power station in the region, improves the system operating power factor, reduces transmission losses, and enhances the overall economic efficiency of the cascade hydropower operation in the basin.

[0016] Fourthly, this invention addresses the unique structure of cascade chain hydropower in a river basin, characterized by "electrical interconnection and power transmission." To overcome the gap in the collaborative regulation of traditional AVC from "point" to "domain," it constructs a specialized regional voltage joint regulation system (RVCS, an automatic voltage control and collaborative regulation method for cascade chain hydropower in a river basin). This system ensures that the control mode is highly compatible with the characteristics of the chain structure, solving the problem of insufficient adaptability of traditional AVC to chain hydropower and providing an effective solution for the cluster control of hydropower with similar topologies. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A schematic diagram of a typical cascade chain hydropower structure in a river basin;

[0019] Figure 2 This is a flowchart of the method in Embodiment 1 of the present invention;

[0020] Figure 3 This is a schematic diagram of the equivalent circuit model of chain hydropower in Embodiment 1 of the present invention;

[0021] Figure 4 This is a deployment diagram of the RVCS system in Embodiment 1 of the present invention;

[0022] Figure 5 This is a control cycle diagram of the RVCS in Embodiment 1 of the present invention;

[0023] Figure 6 This is a diagram of the three-station chain hydropower flow model in Embodiment 2 of the present invention;

[0024] Figure 7 This is a graph showing the reactive power pulling amplitude in scenario 1 of embodiment 2 of the present invention;

[0025] Figure 8 This is a graph showing the reactive power pulling amplitude in scenario 2 of embodiment 2 of the present invention;

[0026] Figure 9 This is a voltage deviation curve for scenario 1 in embodiment 2 of the present invention;

[0027] Figure 10 This is a voltage deviation curve for scenario 2 in embodiment 2 of the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0029] Example 1:

[0030] Please see Figure 2 This embodiment provides a method for automatic voltage control and coordinated regulation of cascade chain hydropower in a watershed. Figure 2The execution entity of the method shown can be a software and / or hardware device. The execution entity of this application can include, but is not limited to, at least one of the following: user equipment, network equipment, etc. User equipment can include, but is not limited to, computers, smartphones, personal digital assistants (PDAs), and the aforementioned electronic devices. Network equipment can include, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Cloud computing is a type of distributed computing, consisting of a super virtual computer composed of a group of loosely coupled computers. This embodiment does not impose any limitations on this.

[0031] A method for automatic voltage control and coordinated regulation of a cascade hydropower system in a river basin, comprising:

[0032] S1. Receive and execute voltage commands issued by the power grid AVC central station, and collect actual operating data of each hydropower station in the cascade chain hydropower network of the basin; the actual operating data includes the real-time voltage of the high-voltage bus node, the current reactive power output of the generator node, and the access point voltage regulation dead zone given by the power grid AVC central station.

[0033] Specifically, in each adjustment process, the first stage, which lasts from 0 to 2 minutes, is used for the power station at the connection point to adjust in response to the voltage command of the power grid AVC.

[0034] At the start of the control cycle, the power grid AVC master station (provincial dispatch level) sends the voltage setpoint of the centralized grid-connected access point of the cascade chain hydropower area to the regional voltage control system of the basin's centralized control center based on the global optimal power flow calculation. Within the following two minutes (phase one), the regional voltage control system instructs the AVC substations of the access point power stations to adjust their reactive power output to track the voltage setpoint. Simultaneously, it collects real-time operating parameters of all power stations within the entire cascade chain hydropower network of the basin.

[0035] S2. Based on the topology of the cascade chain hydropower network in the basin and the actual operation data of each hydropower station, construct the power flow equation and solve it to calculate the time-varying sensitivity matrix of the chain hydropower area.

[0036] S2 includes:

[0037] S2-1. Based on the topology and connection relationship of the cascade chain hydropower network in the watershed, construct the equivalent circuit model of the chain hydropower.

[0038] For details, please refer to Figure 1 Typical structure of cascade chain hydropower in a river basin (topology and connection relationship), constructed as follows Figure 3 The diagram shows the equivalent circuit model of a chain hydropower network consisting of n hydropower stations in a river basin.

[0039] exist Figure 3 In the chain-like hydropower equivalent circuit model, there are 2n+1 nodes. The first n nodes (nodes 1 to n) are the high-voltage busbar nodes of each hydropower station, and are considered as PQ nodes where P and Q are both 0. The second n nodes (nodes n+1 to 2n) are the generator port nodes of each hydropower station, serving as PV nodes. Node 2n+1 (node ​​0) is the high-voltage busbar node of the hub substation, directly connected to the external infinite system, and serves as the balancing node.

[0040] S2-2. Based on the equivalent circuit model of chain hydropower, construct the nodal power equation set for each node;

[0041] The formula corresponding to the set of nodal power equations is:

[0042] ;

[0043] in, , Let represent any two interconnected nodes in the chain-like hydropower equivalent circuit model. Represents a node , Interconnected, , Representing nodes respectively Active power and reactive power , Representing nodes respectively , voltage amplitude, , Representing the elements of the admittance matrix The real and imaginary parts, Represents a node , voltage phase angle difference, , Let these represent the cosine function and the sine function, respectively. This represents the summation function.

[0044] S2-3. Based on the nodal power equations of each node, the power flow equations of the cascade chain hydropower network in the basin are constructed by Taylor series. The power flow equations are divided to generate block matrix power flow equations.

[0045] Specifically, based on the nodal power equations of each node, the unbalanced power of the system is solved, resulting in the power flow equations. By using Taylor series expansion and neglecting higher-order terms, a linear power flow calculation equation set (power flow equations) containing a total of 3n equations is obtained, as follows:

[0046] ;

[0047] in, , , , Representing node 1 and node 2 respectively ,node ,node The change in active power, , Representing node 1 and node 2 respectively The change in reactive power, , , , Representing node 1 and node 2 respectively ,node ,node The change in phase angle, , Representing node 1 and node 2 respectively The change in voltage amplitude.

[0048] , All indicate the first The active power of the nth node is related to the nth node. The partial derivative matrix of the phase angles of each node, and so on, shows that... , , , , , , , , , , , , , , , Definition. , All indicate the first The reactive power of the nth node is related to the nth node. The partial derivative matrix of the phase angles of each node, and so on, shows that... , , , , , , , definition. Indicates the first The active power of the nth node is related to the nth node. The partial derivative matrix of the voltage magnitude at each node, and so on, can be derived as follows: , , , , , , , definition. Indicates the first The reactive power of the nth node is related to the nth node. The partial derivative matrix of the voltage magnitude at each node, and so on, can be derived as follows: , , , definition.

[0049] When the power flow equations are written in block matrix form, the block matrix power flow equations can be expressed as:

[0050] ;

[0051] in, This represents the change in active power. This represents the change in reactive power. , , , Let represent the partial derivative matrices of active power with respect to phase angle, active power with respect to voltage magnitude, reactive power with respect to phase angle, and reactive power with respect to voltage magnitude, respectively. , These represent the change in phase angle and the change in voltage amplitude, respectively.

[0052] S2-4. Set the power flow objective function and, based on the actual operating data of each hydropower station, perform a linear transformation on the block matrix power flow equation to generate a time-varying sensitivity matrix.

[0053] S2-4 includes:

[0054] S2-4-1. Set the power flow objective function;

[0055] Specifically, the PQ deviation (active and reactive power deviation) of the traditional power flow objective function focuses more on ensuring the stable operation of each node in the power grid. However, it is not adapted to the strong coupling characteristics of chained hydropower, and is prone to problems such as low power factor and internal reactive power pull due to unbalanced reactive power distribution, even though the node is stable and meets the target.

[0056] Therefore, this embodiment introduces power factor deviation into the power flow objective function, which retains the role of PQ deviation in ensuring node stability while also specifically optimizing reactive power distribution and power quality in chained hydropower. This ensures that the objective function for power flow calculation meets overall stability requirements while also aligning with the economic efficiency and grid performance standards of actual operation, thus improving adaptability and practicality. The formula corresponding to the power flow objective function is:

[0057] ;

[0058] ;

[0059] in, , , They represent the first In the nth iteration The active power deviation, reactive power deviation, and voltage amplitude squared deviation of each hydropower station Represents the maximum value function. Represents absolute value. Indicates the convergence threshold. Indicates power factor deviation. Indicates the first Reactive power deviation of a hydropower station , They represent the first The active and reactive power of each hydropower station.

[0060] The aforementioned power flow objective function focuses on minimizing the reactive power output of other hydropower stations within the region, enabling rapid optimization of reactive power distribution and reduction of losses. However, it does not differentiate between regulation priorities. When the voltage gradient health benefits of more than half of the hydropower stations in a chain are less than 0 (gradient reversed), pursuing only the minimum reactive power will lead to a longer voltage gradient correction cycle. Since a reasonable gradient is the primary prerequisite for the safe operation of chain hydropower (its priority is higher than reactive power optimization), a variant of the objective function is added.

[0061] If under normal operating conditions (H>0 for half or less of the power plants), the power flow objective function is still used to optimize reactive power output.

[0062] If H < 0 for more than half of the power plants, switch to the variant power flow objective function. By incorporating voltage gradient health into the objective and giving it high weight, prioritize the rapid correction of the reverse voltage gradient, and then take reactive power optimization into account to avoid the internal reactive power vicious cycle.

[0063] Based on the voltage gradient health status from the previous coordination, calculate the variant power flow objective function. The corresponding formula is:

[0064] ;

[0065] ;

[0066] ;

[0067] in, , These represent the first weight and the second weight, respectively. This represents the gradient health penalty term. This represents the reactive power optimization term. The discrete Laplace operator represents the voltage gradient. Represents a symbolic function. Represents a constant. This represents the voltage gradient health threshold. Indicates the first Reference reactive power of each hydropower station This represents the steepness coefficient.

[0068] The denominator in the gradient health penalty term is the Sigmoid function, used to implement state-sensitive weight switching and the steepness coefficient. The value is 5, which is used to control the sensitivity of switching. When the voltage gradient health is less than the voltage gradient health threshold, the denominator approaches 1, and the gradient health penalty term increases; conversely, the denominator increases rapidly, and the gradient health penalty term decreases.

[0069] In addition, the first weight The corresponding formula is:

[0070] ;

[0071] Second weight The corresponding formula is:

[0072] ;

[0073] in, , These represent the first and second basic weights, respectively. Represents a constant. Indicates the first The voltage gradient health of each hydropower station. The more hydropower stations in the power grid with a voltage gradient health of <0, the better. The larger the value, the more the objective function focuses on gradient correction; as gradient health improves, Decrease By increasing the power flow objective function, the variable power flow objective function gradually transitions to reactive power optimization.

[0074] In emergency situations where voltage gradient reversal occurs in most power plants, this embodiment can intelligently switch the optimization objective from "minimizing reactive power output" to "prioritizing rapid correction of voltage gradient" through a gradient health-weighted penalty term and an adaptive weighting mechanism. This restores a reasonable voltage distribution within 1-2 adjustment cycles, avoiding reactive power inner loops and system instability. Once the gradient is healthy, it automatically and smoothly transitions to economic reactive power allocation, achieving an adaptive balance between safety correction and economic optimization. It is also fully compatible with existing models and solution processes, and can significantly improve the operational resilience and control accuracy of chain hydropower systems without the need for additional hardware.

[0075] S2-4-2. Based on the actual operating data of each hydropower station, calculate the active power deviation, reactive power deviation, voltage amplitude square deviation, and power factor deviation of each node in the current iteration.

[0076] Active power deviation is the difference between the actual active power at a node and the theoretical active power calculated using the nodal power equations. Reactive power deviation is the difference between the actual reactive power at a node and the theoretical reactive power calculated using the nodal power equations. Voltage amplitude square deviation is the difference between the actual squared value of the given voltage amplitude at a node and the theoretical squared value. Power factor deviation is the difference between the actual power factor at a node and the expected power factor.

[0077] S2-4-3. Based on the active power deviation, reactive power deviation, voltage amplitude square deviation, and power factor deviation of each node in the current iteration, determine whether the current iteration has converged through the power flow objective function; if yes, proceed to S2-4-5; otherwise, proceed to S2-4-4.

[0078] Substitute the active power deviation, reactive power deviation, voltage amplitude square deviation, and power factor deviation of each node in the current iteration into the power flow objective function. If the power flow function value of the current iteration is less than the convergence threshold, it means that the current iteration has converged and enters S2-4-5; otherwise, the current iteration has not converged and enters S2-4-4.

[0079] S2-4-4 Calculate the Jacobian matrix, phase angle correction, and voltage magnitude correction for each node based on the block matrix power flow equation; Calculate the phase angle correction for each node. and voltage amplitude correction Update the voltage and phase angle of each node and return to S2-4-2; the nodes in S2-4-4 refer to the high-voltage bus nodes of each hydropower station.

[0080] In power flow calculations for chain-type hydropower networks, calculating the Jacobian matrix and node corrections are core iterative steps. Traditional update methods employ the conventional Newton-Raphson method. However, while the conventional Newton-Raphson method uses a uniform correction step size, in the highly coupled and voltage gradient-sensitive structure of chain-type networks, this can lead to insufficient correction for nodes with abnormal gradients and overcorrection for normal nodes, causing oscillations. Furthermore, it can also result in slow convergence, voltage gradient oscillations, or even divergence, especially when the voltage gradients of adjacent nodes are no longer reasonable.

[0081] To address the issues of "blind averaging," slow convergence, and lack of physical guidance in traditional update methods such as the Newton-Raphson method, this embodiment proposes an adaptive weighted correction method based on voltage gradient health assessment to update the voltage and phase angle of each node.

[0082] S2-4-4 includes:

[0083] A1. Calculate the Jacobian matrix under the current iteration based on the block matrix power flow equation. ;

[0084] A2. Based on the system of linear equations:

[0085] ;

[0086] Solve the problem to generate a phase angle correction vector containing the phase angle corrections of all nodes. and the voltage magnitude correction vector containing the voltage magnitude corrections for all nodes. ;in, , These represent the active power deviation vector and reactive power deviation vector of all nodes in the current iteration, respectively.

[0087] A3. Based on the phase angle correction vector and the voltage amplitude correction vector, calculate the voltage gradient health of the high-voltage bus nodes between two adjacent stations. The corresponding formula is:

[0088] ;

[0089] in, Indicates the first The adjacent iteration in the nth iteration The first hydropower station and the first Voltage gradient health between high-voltage busbar nodes of a hydropower station , They represent the first The adjacent iteration in the nth iteration The first hydropower station and the first The voltage amplitude of each hydropower station, , They represent the first The adjacent iteration in the nth iteration The first hydropower station and the first The rated operating voltage amplitude of each hydropower station;

[0090] A4. Based on the health status of each voltage gradient, set the adaptive voltage weight for each hydropower station. The corresponding formula is:

[0091] ;

[0092] in, Indicates the first Adaptive voltage weighting for individual hydropower stations , , , Both represent constants.

[0093] In this embodiment, , , , The values ​​are 1.5, 1.2, 1.0, and 0.8. This is because... When the value is less than zero, it indicates that the gradient of the hydropower station is reversed, which will cause reactive power to flow in the opposite direction from downstream to upstream, forming an internal consumption cycle. This will not be able to effectively support the operation of the power grid and may even cause a sharp drop in voltage stability. Therefore, strong correction is required. The corresponding adaptive voltage weight is set to 1.5, which is the maximum value among the constants, so that the voltage of the hydropower station can quickly get out of the reverse state in the iteration, prioritize the recovery of the gradient direction, and avoid staying at the ill-conditioned point.

[0094] when When the value range is (0, 0.5), it indicates that although the gradient of the hydropower station is positive, it is less than half of the rated value (weak). This means that the line voltage drop is too small, and the line capacity cannot be fully utilized. The reactive power required by the power grid cannot be effectively transmitted through this chain structure. Moreover, when the gradient is weak, the power grid is highly sensitive to disturbances such as load fluctuations and unit commissioning and decommissioning, and is prone to sliding into an unreasonable state. Therefore, it is necessary to allocate a larger adaptive voltage weight, i.e., take a value of 1.2, to avoid excessive aggression leading to oscillation, and to ensure that the gradient quickly leaves the weak state.

[0095] when When the value of is in the range of [0.5, 1), it indicates that the gradient direction of the hydropower station is correct (the upstream voltage is higher than the downstream voltage) and has reached more than half of the rated gradient. The power grid will not experience reactive power backflow or severe circulating current, and is in a basically safe operating range. However, the current gradient has not reached the rated design value (reasonable but insufficient), which means that the line voltage drop is not fully utilized, the reactive power transmission capacity is not optimal, and it may lead to the downstream power station needing to generate more reactive power to support the local voltage. There is room for improvement in the overall reactive power factor. Therefore, the corresponding adaptive voltage weight is set to 1, and the standard iteration step size of the Newton-Raphson method is adopted to ensure that there is no emergency risk to the power grid, avoid oscillations introduced by over-adjustment, and gradually optimize the gradient to a state closer to the rated value.

[0096] when A gradient of 1 or higher indicates that the hydropower station's voltage gradient has reached or exceeded the design value (good), signifying a very smooth reactive power transmission channel and strong support capacity. However, a larger gradient is not always better. An excessively large gradient means that the upstream voltage may be too high, approaching or even exceeding the equipment's allowable upper limit, threatening insulation safety; or the downstream voltage may be too low, requiring the downstream power station to generate more reactive power for compensation, increasing the equipment burden; it may also mask potential regulation conflicts. Therefore, the corresponding adaptive voltage weight is set to 0.8, actively reducing the correction step size to achieve a "damping" effect, preventing over-adjustment, enhancing stability, and protecting the regulation margin.

[0097] A5. According to the formula:

[0098] ;

[0099] ;

[0100] Update the voltage and phase angle of each node. Among these, Indicates the first In the nth iteration The voltage of the hydroelectric power station , They represent the updated number of... Voltage and phase angle of the high-voltage busbar node of a hydropower station. , They represent the first In the nth iteration Phase angle and phase angle deviation of a hydropower station.

[0101] In summary, this embodiment calculates the voltage gradient health index between high-voltage buses of adjacent power stations in real time, diagnoses four states of voltage gradient: "reverse," "weak," "reasonable but insufficient," and "good." Based on the diagnostic results, it dynamically assigns differentiated adaptive weights to target and weight the node voltage correction, achieving precise adjustment where "the more severe the problem, the greater the correction; the better the state, the more cautious the correction." This method deeply integrates physical operating rules into the numerical iteration kernel, significantly accelerating the convergence speed of power flow calculations and effectively enhancing the numerical stability of the iteration process. More importantly, it fundamentally ensures that the obtained power flow solution naturally conforms to the voltage gradient distribution required for the safe and economical operation of chained hydropower. This provides a solid and reliable mathematical foundation for subsequent high-precision sensitivity analysis and collaborative optimization, achieving a full-chain collaborative performance improvement from "basic algorithm" to "upper-level optimization." Therefore, the adaptive weighted correction method based on voltage gradient health assessment updates the phase angle and voltage, which can solve the problem of "blind uniform correction" in the traditional Newton-Raphson power flow algorithm in the strongly coupled special structure of the cascade hydropower in the basin (due to the failure to consider the physical constraint that the voltage gradient must decrease reasonably, the iteration convergence is slow, the numerical oscillation or even divergence is caused, and the final solution may not be physically reasonable).

[0102] S2-4-5. Calculate the slack node power of each node using the nodal power equations. Based on the slack node power, determine whether a PV node exists. If so, set the PV node as a PQ node, update the node data and transformer operating data, recalculate the variable node admittance matrix, and return to S2-4-1. Otherwise, proceed to S2-4-6.

[0103] S2-4-6. Perform matrix transformation on the block matrix power flow equation, set the active power change to 0, and generate a full-dimensional Jacobian matrix; calculate the time-varying sensitivity matrix based on the full-dimensional Jacobian matrix.

[0104] Specifically, after modifying the PV nodes, the constructed power flow equations containing PV nodes can be expressed as:

[0105] ;

[0106] Because the coupling between active power and voltage is low, the effect of active power on node voltage is often neglected in the analysis, that is, let If the value is 0, the time-varying sensitivity matrix can be obtained by transforming the block matrix power flow equation. :

[0107] ;

[0108] in, , All indicate the first The node is the first The reactive-voltage sensitivity of each node can be seen from the formula. , , The meaning of parameters such as... This represents the reactive-voltage sensitivity between node 1 and node n. This represents the reactive-voltage sensitivity of nodes 1~n to nodes n+1~2n. This represents the reactive-voltage sensitivity of nodes n+1 to 2n to nodes 1 to n. This represents the reactive power-voltage sensitivity between nodes n+1 and 2n.

[0109] Furthermore, in the chain-type hydroelectric structure, nodes n+1 to 2n are generator nodes, possessing adjustable power characteristics. Therefore, in its reactive power voltage sensitivity matrix, only... , Matrices have practical physical meaning. The matrix represents the impact of changes in the generator node power of a certain power station on the voltage of the high-voltage bus nodes of various power stations in the region; The matrix represents the impact of changes in the generator node power of a certain power station on the voltage of the generator bus nodes of all power stations in the region. Therefore, when reactive power regulation is implemented in all power stations within the region, it can be achieved through a time-varying sensitivity matrix. Calculate the high-voltage busbar that causes any hydroelectric power station in the region. voltage gradient .

[0110] Given that system parameters change with operating conditions, before utilizing sensitivity for reactive power regulation, the current real-time operating parameters must be incorporated into the power flow model to construct the Jacobian matrix for the corresponding time point, thereby ensuring the accuracy of sensitivity calculations. Specifically, if the current regulation time is... Then it should be based on time. Calculation of time-varying sensitivity matrix for system parameters In the next adjustment, it needs to be updated to the time. The system parameters are used to recalculate the time-varying sensitivity matrix for the next time step. The instantaneous sensitivity matrix will dynamically change as the adjustment cycle progresses, exhibiting a " → → The temporal evolution characteristics of "". Therefore, at the current moment Voltage variation at the high-voltage busbar node of any hydropower station x in the following region It can be represented as:

[0111] ;

[0112] in, Indicates the first The reactive voltage sensitivity of the generator port node of a hydropower station to the high-voltage bus node of station x. Indicates the first Reactive power regulation at the generator port nodes of a hydropower station. This represents the time-varying sensitivity matrix of the previous moment.

[0113] Therefore, the reactive power-voltage sensitivity matrix (time-varying sensitivity matrix) obtained by S2-4 can quantify the impact of reactive power output changes of each power station in the region on the high-voltage bus voltage, providing a quantitative analysis basis for the study of reactive power and voltage control strategies in the region.

[0114] S3. Based on the time-varying sensitivity matrix, a multi-constraint optimization mathematical model is constructed. The multi-constraint optimization mathematical model is solved by the SQP algorithm to generate a coordinated reactive power regulation command.

[0115] S3 includes:

[0116] S3-1. Construct the optimization objective function; Only the hydropower station at the access point responds to AVC control to meet the voltage demand of the regional central point and ensure the safety and stability of the power grid. The remaining hydropower stations in the region are optimized with the minimum reactive power output as the objective function. The corresponding formula is:

[0117] ;

[0118] in, Indicates the first The current reactive power output of the hydropower station Indicates the first The weighting coefficient of each hydropower station This represents the minimum value function.

[0119] By constructing the relevant constraints on the impact of reactive power regulation on the grid connection point voltage of each station using reactive power-voltage sensitivity, and solving the optimal reactive power output operating state of each station in the region under the premise of ensuring the AVC control effect and safety stability of the grid.

[0120] S3-2. Based on the time-varying sensitivity matrix, calculate the voltage gradient of the high-voltage bus nodes of each hydropower station; determine whether the voltage gradient is reasonable. If the voltage amplitude of each power station decreases sequentially from n to 1, it is a reasonable gradient, and generate the judgment result.

[0121] S3-3. Based on the actual operation data and judgment results of each hydropower station, construct a system that satisfies the voltage change constraint at the centralized access point of the chain hydropower station and the voltage gradient difference constraint of each high-voltage bus of the chain hydropower station.

[0122] The chain-type hydropower structure ultimately connects to the power system via a substation that is connected to the power grid through only one high-voltage side node of the power plant. According to the voltage drop theory in power system analysis, the node voltage is affected by reactive power flow and voltage between nodes. To ensure the stability of the bus voltage at the substation connected to the power system, regional reactive power optimization should be carried out under the premise of satisfying the grid AVC regulation. Therefore, the impact of regional reactive power optimization on the bus voltage at the grid connection point needs to be considered. By controlling the impact on voltage within the AVC regulation dead zone, the regulation of the grid connection point voltage by the system AVC is ensured. Thus, the formula corresponding to satisfying the voltage change constraint at the centralized connection point of the chain-type hydropower is:

[0123] ;

[0124] in, Indicates the first Reactive-voltage sensitivity of each generator port node to the first high-voltage bus node Indicates the first Reactive power of each generator port node This indicates the dead zone voltage value of the power grid AVC regulation.

[0125] To satisfy the voltage gradient difference constraint between the high-voltage busbars of each station in a chain-type hydropower plant, the chain-type hydropower plant transmits power to the power system through only one high-voltage side node. Based on the power transmission direction, the high-voltage busbar voltage of each power plant in the chain-type hydropower plant should maintain a decreasing gradient from node n to node 1; otherwise, unreasonable power consumption will occur within the chain-type hydropower structure. When the high-voltage busbar voltage between two adjacent stations is at 2 minutes during the regulation cycle... > When the gradient is reasonable, that is, when the judgment result is reasonable, then according to:

[0126] ;

[0127] By imposing constraints, it can be ensured that the voltage gradient between the two stations remains in a reasonable direction after adjustment. Among these constraints, This indicates the time before adjustment in each adjustment cycle. This represents the voltage gradient between two adjacent stations at 5 minutes in the optimized regulation cycle. , These represent the voltages at node n and node n-1, respectively.

[0128] If the judgment result is unreasonable, then according to:

[0129] ;

[0130] ;

[0131] ;

[0132] By imposing constraints, it can be ensured that the adjusted voltage gradient between the two stations tends to a reasonable gradient after multiple cycles. Among these constraints, This represents the voltage gradient between two adjacent stations at 2 minutes into the adjustment cycle before optimization. Indicates the first The generator port node and the first Reactive power-voltage sensitivity between high-voltage bus nodes Indicates the first Reactive power of each generator port node Indicates the first Current voltage of each high-voltage bus node Indicates the first The generator port node and the first Reactive power-voltage sensitivity between high-voltage bus nodes Indicates the first Reactive power of each generator port node Indicates the first The voltage of each high-voltage bus node.

[0133] The structural characteristics of chain hydropower, namely "centralized access and power ride-through," determine that voltage stability at the access point is the core of grid security, and reasonable reduction of voltage gradient is the key to avoiding internal reactive power pull. Based on voltage drop theory and the principle of reactive power-voltage coupling at nodes, this embodiment introduces voltage change constraints at the centralized access point (to control voltage fluctuations within the AVC dead zone) and voltage gradient difference constraints at each station's high-voltage bus (to ensure that voltage decreases from the end to the access point). This can accurately respond to grid AVC commands, ensure voltage stability at the grid connection point, and eliminate the technical problems of reactive power reverse flow and internal circulation consumption between stations, thus balancing grid security and operational economy.

[0134] S3-4. Based on the actual operating data of each hydropower station, construct single-station voltage-reactive power output constraints; the single-station voltage-reactive power output constraints include single-station adjustment step size constraints, single-station voltage upper and lower limit constraints, and single-station reactive power upper and lower limit constraints.

[0135] The formula corresponding to the single-station adjustment step size constraint is:

[0136] ;

[0137] The formula corresponding to the upper and lower limit constraints of the single-station voltage is:

[0138] ;

[0139] The formulas corresponding to the upper and lower limits of reactive power output constraints at a single station are as follows:

[0140] ;

[0141] in, Indicates the first Voltage regulation step size of each high-voltage bus node , They represent the first Upper and lower operating voltage limits for each high-voltage busbar node. , They represent the first The upper limit and lower limit of reactive power output of each generator port node.

[0142] S3-5. Based on satisfying the voltage change constraints at the centralized access point of the chain hydropower, the voltage gradient difference constraints of each station's high-voltage bus, and the voltage-reactive power output constraints of a single station, a multi-constraint optimization mathematical model is constructed.

[0143] S3-6. Based on the optimization objective function, the multi-constraint optimization mathematical model is solved using the SQP algorithm to generate coordinated reactive power regulation commands.

[0144] Specifically, based on the preset optimization objective function, the sequential quadratic programming (SQP) algorithm is used to iteratively solve a multi-constraint optimization mathematical model that includes constraints on voltage changes at the centralized access point of chain hydropower stations, voltage gradient differences between high-voltage busbars at each station, upper and lower limits of voltage and reactive power output at a single station, and adjustment step size constraints. This directly generates a coordinated reactive power regulation command that includes the reactive power optimization adjustment of each hydropower station's generator busbar node.

[0145] S4. Based on the coordinated reactive power regulation command, the reactive power output of each hydropower station is virtually adjusted and power flow simulation is performed to output the optimized power flow and voltage results.

[0146] Specifically, based on the coordinated reactive power regulation instructions obtained in the previous solution, the reactive power output adjustment amount corresponding to the generator bus nodes of each hydropower station is extracted. In the power system simulation model, the current actual reactive power output of each hydropower station is superimposed with the adjustment amount to complete the virtual modification of reactive power output, and the parameters are updated only at the model level.

[0147] Subsequently, power flow calculation algorithms (such as the Newton-Raphson method) are invoked, combined with basic data such as the topology and admittance matrix of the cascade chain hydropower network in the basin, and the adjusted reactive power output is used as input to iteratively calculate the voltage amplitude, phase angle and power distribution of each node and each branch until the active power deviation, reactive power deviation and voltage constraints meet the convergence threshold. Finally, the optimized power flow and voltage results, including the high-voltage bus voltage of each substation and the power flow of the transmission branches, are output as the basis for subsequent reactive power and voltage operation evaluation.

[0148] S5. Based on the optimized power flow and voltage results, calculate the reactive power and voltage operation evaluation index; based on the reactive power and voltage operation evaluation index, issue coordinated reactive power regulation commands to the AVC substations of each hydropower station for coordination. The reactive power and voltage operation evaluation index includes the absolute value of reactive power pull amplitude and the reasonable voltage gradient operation rate.

[0149] Specifically, traditional AVC systems, when dealing with cascade hydropower projects in a river basin, can only observe the total reactive power output of the power grid and cannot detect the internal losses (inter-station reactive power internal ineffective cycles) between individual hydropower stations. Furthermore, conventional voltage qualification rate assessments only focus on whether the voltage at each point falls within the dead zone, ignoring the overall stability of the power grid operation. Therefore, this embodiment proposes the absolute value of reactive power pull amplitude and the reasonable voltage gradient operation rate. The absolute value of reactive power pull amplitude quantifies the severity of inter-station reactive power internal ineffective cycles, while the reasonable voltage gradient operation rate is used to statistically determine the proportion of time the voltage gradient remains reasonable, continuously monitoring the overall health of the power grid.

[0150] The reactive power generated by some power stations and absorbed by others within a chain hydropower area is defined as the absolute value of reactive power pull flow. This characterizes the intensity of the reactive pulling. A value of 0 indicates that all stations within the chain hydropower area simultaneously generate or absorb reactive power, and there is no reactive power pull phenomenon. Therefore, the formula corresponding to the absolute value of the reactive power pull amplitude is:

[0151] ;

[0152] In the formula, This indicates that a power plant cannot simultaneously absorb and generate reactive power. For the first The reactive power output of a hydropower station; For the first The amount of reactive power absorbed by a hydroelectric power station.

[0153] In chain-type hydropower, the high-voltage bus voltage from the terminal power station to the first (connection point) power station should exhibit a reasonable gradient that decreases sequentially. The percentage of operating time within this reasonable voltage gradient is defined as the chain-type hydropower reasonable voltage gradient operating rate. Therefore, the reasonable voltage gradient operating rate The corresponding formula is:

[0154] ;

[0155] In the formula: This represents the total duration during which the voltage deviation is positive within the operating period. This represents the total operating time. The closer this value is to 1, the longer it operates with a reasonable voltage gradient, which is more conducive to the safe and stable operation of the power grid.

[0156] After the power flow simulation outputs the optimization results, based on the preset reactive power and voltage operation evaluation indicators, core quantitative data are extracted from the optimization results, including the voltage gradient difference of each station's high-voltage bus, the total reactive power loss in the region, the voltage deviation rate of the centralized access point, the compliance rate of the upper and lower limits of reactive power output of a single station, and the system operating power factor.

[0157] Next, these optimized index values ​​are compared with the baseline operating data (or preset qualified thresholds) before optimization. If the core judgment conditions of "the reactive power output of each station is lower than the baseline value, the voltage gradient difference is within a reasonable decreasing range, the voltage deviation of the centralized access point is within the allowable range of the assessment, and the voltage and reactive power output of all individual stations are within the limits" are met, the optimization effect is considered to be good. If any index fails to meet the standard (such as abnormal voltage gradient or increased reactive power loss), the optimization is judged to be unsuccessful, the termination instruction is issued, and the solution is returned to be recalculated.

[0158] When the optimization effect is deemed good, the coordinated reactive power adjustment command (including the reactive power adjustment amount of each hydropower station generator bus node) is encapsulated into a standardized control message and sent through the communication link between the RVCS substation of the basin control center and the AVC substation of each power plant; at the same time, the execution feedback of each substation is collected in real time to confirm the command reception and action execution status, and to ensure that the adjustment action is accurately implemented.

[0159] In this embodiment, by precisely transforming the two problems that traditional AVC cannot quantify—inter-station reactive power consumption and voltage distribution structure distortion—into observable and optimizable mathematical objects, the absolute value of reactive power pull amplitude and reasonable voltage gradient operation rate are proposed. This enables a profound understanding and closed-loop control of the chain hydropower operation status. The reactive power and voltage operation evaluation indicators not only serve as the target guide for the optimization model, driving the solution process to directly address the core issues, but also act as a strict verification standard before the instructions are issued. This ensures that only coordinated instructions that can significantly improve the degree of reactive power pull and the health of the voltage gradient are executed, thereby eliminating ineffective regulation at its root. Ultimately, by continuously minimizing the reactive power pull amplitude and maximizing the reasonable voltage gradient operation rate, not only is the safety (suppressing circulating current and stabilizing voltage structure) and economy (reducing network losses and improving transmission efficiency) of the power grid operation significantly improved, but the overall coordination of the basin hydropower cluster and its support capability for the main grid are also fundamentally enhanced, realizing a technological leap from "passively responding to point-like instructions" to "actively optimizing regional operation."

[0160] The method in this embodiment can be integrated into a Regional Voltage Control System (RVCS), such as... Figure 4As shown, by deploying RVCS substations in the basin control center of chain hydropower, a coordinated integrated control mode of "provincial dispatch-centralized control-power station" can be realized in conjunction with the power grid AVC for cascade chain hydropower in the basin.

[0161] In the RVCS control mode, the power grid AVC master station, aiming for optimal power flow, calculates the high-voltage bus voltage U0 of the hub substation in the chained hydropower area and sends it to the regional coordination secondary voltage controller. The regional coordination secondary voltage controller, aiming to maintain U0 at the hub substation, converts the reactive power demand for the chained hydropower area into a setpoint U1 for the high-voltage bus voltage at the access point through reactive power-voltage sensitivity and sends it to the RVCS substation of the basin control center. The RVCS substation, aiming to maintain the access point voltage U1 and optimize reactive power output within the region, establishes an inter-station collaborative reactive power optimization model through sensitivity, calculating Q2 to Q... n The strategy is implemented by issuing the AVC substations to all power stations within the region. This will change the control mode of each power station within the chained hydropower region from independent response to the grid's AVC to a system where each station responds to the grid via its RVCS (Reactive Power Control System). Then, all stations within the region will jointly respond to the RVCS under coordinated constraints, thereby achieving a coordinated response between the provincial dispatch center, centralized control system, and power stations. This will enable the chained hydropower region to meet the grid's reactive power requirements while improving its internal operating power factor.

[0162] like Figure 5 As shown, the RVCS control cycle adopts the same 5-minute time level as the AVC. RVCS optimization calculations and adjustments are performed during the period following the start of each AVC control cycle in the power grid. Phase 1: 0-2 minutes, the access point power station responds to the voltage command from the power grid AVC and adjusts using the same method as S1. Phase 2: 2-3 minutes, the access point power station completes its adjustment and accepts the power grid AVC assessment. Simultaneously, the RVCS uses this period to collect operating parameters within the region and calculates the optimized adjustment amounts for the remaining power stations in the region, preparing for issuance; this phase uses the same method as S2 to S4. Phase 3: 3-5 minutes, after the access point power station's assessment, the remaining power stations in the region receive and execute the RVCS's optimized adjustment commands. The process stops at 5 minutes and begins the next adjustment cycle; this phase uses the same method as S5.

[0163] In summary, this invention precisely addresses the issues of reactive power strain and voltage gradient anomalies in chain-type hydropower, improving the operational rate of reasonable voltage gradients and avoiding internal reactive power waste. By employing a three-level collaborative approach involving the provincial dispatch center, centralized control system, and power plant, it replaces the traditional independent response mode, significantly improving voltage command tracking accuracy and AVC (Active Voltage Control) compliance. Simulation verification and indicator validation enhance the safety and stability of the hydropower system, optimize reactive power output allocation to reduce losses, and adapt to the characteristics of chain-type structures. It provides a highly adaptable control framework for large-scale hydropower grid connection, contributing to the efficient consumption of clean energy and the stable operation of modern power grids.

[0164] Example 2:

[0165] This embodiment is based on Embodiment 1. A simulation analysis is performed using a chain hydropower system consisting of adjacent cascade hydropower stations "P, S, Z" in a certain river basin and its actual operating data as an example. A power flow model was established based on its physical wiring and the actual parameters shown in Tables 1 to 3. The established power flow model is as follows: Figure 6 As shown.

[0166] Table 1 Equivalent Generator Parameter Table

[0167]

[0168] Table 2 Parameter Table for a Single Transformer

[0169]

[0170] Table 3 Transmission Line Parameter Table

[0171]

[0172] In the actual operation of this chain hydropower station with AVC closed-loop control at multiple stations, inter-station reactive power pull phenomena occurred repeatedly. Two actual operating scenarios with relatively obvious reactive power pull phenomena were selected as Scenario 1 and Scenario 2, date 1 (21:00-22:00) and date 2 (11:00-12:00), respectively. Continuous power flow simulations were performed with adjustment methods applied during reactive power pull in Scenario 1 and before reactive power pull occurred in Scenario 2. The simulation results were then analyzed from the perspectives of mitigating inter-station reactive power pull and correcting voltage gradients.

[0173] The simulation results of the absolute value A of reactive power pull during the simulation period for scenarios 1 and 2 are as follows: Figure 7 and Figure 8 As shown. In Scenario 1, approximately 60 Mvar of reactive power was pulled during the period from 21:00 to 21:40. The adjustment method was implemented at 21:00, and the pull amplitude was significantly reduced in the first adjustment cycle, with continuous optimization in subsequent cycles. In Scenario 2, approximately 50 Mvar of reactive power was pulled between 11:15 and 12:00. The adjustment method was implemented in advance at 11:00, and the large-scale reactive power pull was successfully prevented through two rounds of regulation.

[0174] Evaluation amplitude of reactive power pull between stations throughout the entire simulation scenario The comparison results are shown in Table 4.

[0175] Table 4. Optimization results of reactive power traction in various scenarios

[0176]

[0177] As shown in Table 4, both applying adjustment methods when and before the reactive power pull phenomenon occurs can reduce the amplitude of reactive power pull by more than 90%, but the control effect is better when applied before the phenomenon occurs.

[0178] The voltage deviation during the simulation periods of Scenario 1 and Scenario 2 is as follows: Figure 9 and Figure 10 As shown. The inter-station operating voltage is " > "and" > A reasonable gradient is denoted as 1 in the voltage deviation graph, and conversely, it is denoted as -1.

[0179] In Scenario 1, the voltage gradient fluctuated significantly in the first 0.5 hours due to the use of adjustment methods to control reactive power pull. However, after multiple rounds of optimization, the unreasonable voltage gradient in the latter 0.5 hours was significantly reduced. In the actual operation of Scenario 2, there were only a few unreasonable voltage gradient operation points throughout the entire period, and the overall reasonable voltage gradient operation rate remained at a high level. In the simulation operation, reasonable voltage gradient operation was maintained throughout the entire period.

[0180] Reasonable voltage gradient operating rate for each simulation scenario The comparison with the actual values ​​is shown in Table 5. As can be seen from the table, when the reactive power pull phenomenon occurs, the control of the voltage gradient requires multiple cycles of continuous adjustment to achieve a certain corrective effect. However, when the RVCS is activated before the phenomenon occurs, the voltage gradient is better controlled and maintained.

[0181] Table 5. Voltage gradient optimization results for each scenario

[0182]

[0183] In summary, the adjustment method presented in this embodiment is highly effective in optimizing reactive power pull and voltage gradient. This strategy can reduce inter-station reactive power pull by up to 97.76%. Furthermore, unreasonable voltage gradients are also improved, with the reasonable voltage gradient operation rate increasing by up to 16.67%. Especially when adjustment is performed before reactive power pull occurs, the voltage gradient maintenance rate is significantly improved, and stability is significantly enhanced. Overall, simulation results verify the optimization potential of the proposed adjustment method in a watershed cascade hydropower system, particularly its effectiveness when implemented before reactive power pull occurs, contributing to improved system operational economy and stability.

[0184] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0185] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for automatic voltage control and coordinated regulation of a cascade hydropower system in a river basin, characterized in that, include: It receives and operates voltage commands issued by the power grid AVC central station, and collects actual operating data of each hydropower station in the cascade chain hydropower network of the basin. Based on the topology of the cascade chain hydropower network in the basin and the actual operation data of each hydropower station, the power flow equation is constructed and solved, and the time-varying sensitivity matrix is ​​calculated. Based on the time-varying sensitivity matrix, a multi-constraint optimization mathematical model is constructed. The SQP algorithm is used to solve the multi-constraint optimization mathematical model to generate a coordinated reactive power regulation command. Based on the collaborative reactive power regulation command, the reactive power output of each hydropower station is virtually adjusted and power flow simulation is performed to output optimized power flow and voltage results; Based on the optimized power flow and voltage results, the reactive power and voltage operation evaluation index is calculated. Based on the reactive power and voltage operation evaluation index, the coordinated reactive power regulation command is issued to the AVC substation of each hydropower station for coordination. The calculation of the time-varying sensitivity matrix includes: Based on the topology and connection relationships of the cascade chain hydropower network in the watershed, an equivalent circuit model of the chain hydropower is constructed; based on the equivalent circuit model of the chain hydropower, a set of nodal power equations for each node is constructed. Based on the nodal power equations of each node, the power flow equations of the cascade chain hydropower network in the basin are constructed by Taylor series. The power flow equations are then divided to generate block matrix power flow equations. Set the power flow objective function and, based on the actual operating data of each hydropower station, perform a linear transformation on the block matrix power flow equation to generate a time-varying sensitivity matrix. The generation of the time-varying sensitivity matrix includes: Set the power flow objective function; based on the actual operating data of each hydropower station, calculate the active power deviation, reactive power deviation, voltage amplitude squared deviation, and power factor deviation of each node in the current iteration; Based on the active power deviation, reactive power deviation, voltage amplitude squared deviation, and power factor deviation of each node in the current iteration, the current iteration is judged to be converged by the power flow objective function. If it is converged, the power of the balancing node of each node is calculated by the node power equation set. Otherwise, the Jacobian matrix, the phase angle correction and voltage amplitude correction of each node are calculated based on the block matrix power flow equation, and the iteration is repeated. Based on the power of each balancing node, determine whether a PV node exists; if so, set the PV node as a PQ node, update the node data and transformer operation data, and iterate again; otherwise, perform a matrix transformation on the block matrix power flow equation, set the active power change to 0, and generate a full-dimensional Jacobian matrix; based on the full-dimensional Jacobian matrix, calculate the time-varying sensitivity matrix. The calculation of the Jacobian matrix, phase angle correction, and voltage magnitude correction at each node based on the block matrix power flow equation, followed by iterative processing, includes: Calculate the Jacobian matrix for the current iteration based on the block matrix power flow equation; Based on the system of linear equations: ； Solve the problem to generate a phase angle correction vector containing the phase angle corrections of all nodes. and the voltage magnitude correction vector containing the voltage magnitude corrections for all nodes. ;in, , Let these represent the active power deviation vector and reactive power deviation vector of all nodes in the current iteration, respectively. This represents the Jacobian matrix in the current iteration; Based on the phase angle correction vector and the voltage magnitude correction vector, the voltage gradient health of the high-voltage bus nodes between two adjacent stations is calculated using the following formula: ； in, Indicates the first The adjacent iteration in the nth iteration The first hydropower station and the first Voltage gradient health between high-voltage busbar nodes of a hydropower station , They represent the first The adjacent iteration in the nth iteration The first hydropower station and the first The voltage amplitude of each hydropower station, , They represent the first The adjacent iteration in the nth iteration The first hydropower station and the first The rated operating voltage amplitude of each hydropower station; Based on the health status of each voltage gradient, an adaptive voltage weight is set for each hydropower station, and the corresponding formula is: ； in, Indicates the first Adaptive voltage weighting for individual hydropower stations , , , Both represent constants; According to the formula: ； ； Update the voltage and phase angle of each node; where, Indicates the first In the nth iteration The voltage of the hydroelectric power station , They represent the updated number of... Voltage and phase angle of the high-voltage busbar node of a hydropower station. , They represent the first In the nth iteration Phase angle and phase angle deviation of each hydropower station Indicates the first The voltage amplitude correction vector of a hydropower station.

2. The automatic voltage control and coordinated regulation method for a cascade hydropower project in a river basin according to claim 1, characterized in that, The actual operating data includes the real-time voltage of the high-voltage bus node, the current reactive power output of the generator node, and the dead zone of the access point voltage regulation given by the power grid AVC central station.

3. The automatic voltage control and coordinated regulation method for a cascade hydropower project in a river basin according to claim 1, characterized in that, The chain-like hydropower equivalent circuit model includes 2 n+ 1 node; node 1 to node n For each hydropower station, there are PQ nodes; node n+ 1 to Node 2 n For each hydropower station's PV nodes; nodes 2n +1 is the balanced node.

4. The automatic voltage control and coordinated regulation method for a cascade chain hydropower project in a river basin according to claim 1, characterized in that, The generation of coordinated reactive power regulation instructions includes: Construct an optimization objective function; calculate the voltage gradient of the high-voltage bus nodes of each hydropower station based on the time-varying sensitivity matrix; determine whether the voltage gradient is reasonable and generate the judgment result; Based on the actual operation data and judgment results of each hydropower station, a system is constructed that satisfies the voltage change constraint at the centralized access point of the chain hydropower and the voltage gradient difference constraint of each high-voltage bus of the chain hydropower station. Based on the actual operating data of each hydropower station, a single-station voltage-reactive power output constraint is constructed. Based on satisfying the voltage change constraints at the centralized access point of chain hydropower, the voltage gradient difference constraints of each high-voltage bus of chain hydropower stations, and the voltage-reactive power output constraints of a single station, a multi-constraint optimization mathematical model is constructed. Based on the objective function, the SQP algorithm is used to solve the multi-constraint optimization mathematical model and generate coordinated reactive power regulation commands.

5. The automatic voltage control and coordinated regulation method for a cascade chain hydropower project in a river basin according to claim 4, characterized in that, The formula that satisfies the voltage variation constraint at the centralized access point of chained hydropower: ； in, Indicates the first Reactive-voltage sensitivity of each generator port node to the first high-voltage bus node Indicates the first Reactive power of each generator port node This indicates the dead zone voltage value of the power grid AVC regulation; The formula corresponding to the constraint of voltage gradient difference between high-voltage busbars at each station of a chain hydropower project is as follows: ； ； ； ； in, This represents the voltage gradient between two adjacent stations at 2 minutes during the adjustment cycle before optimization. Indicates the first The generator port node and the first Reactive power-voltage sensitivity between high-voltage bus nodes Indicates the first Reactive power of each generator port node Indicates the first Current voltage of each high-voltage bus node Indicates the first The generator port node and the first Reactive power-voltage sensitivity between high-voltage bus nodes Indicates the first Reactive power of each generator port node Indicates the first The voltage of each high-voltage bus node.

6. The automatic voltage control and coordinated regulation method for a cascade chain hydropower project in a river basin according to claim 4, characterized in that, The formula corresponding to the single-station adjustment step size constraint is: ； The formula corresponding to the upper and lower limit constraints of the single-station voltage is: ； The formulas corresponding to the upper and lower limits of reactive power output constraints at a single station are as follows: ； in, Indicates the first Voltage regulation step size of each high-voltage bus node , They represent the first Upper and lower operating voltage limits for each high-voltage busbar node. , They represent the first The upper limit and lower limit of reactive power output of each generator port node.

7. The automatic voltage control and coordinated regulation method for a cascade chain hydropower project in a river basin according to claim 4, characterized in that, The generation of coordinated reactive power regulation instructions includes: Based on the preset optimization objective function, the sequential quadratic programming (SQP) algorithm is used to iteratively solve a multi-constraint optimization mathematical model that includes constraints on voltage changes at the centralized access point of chain hydropower stations, voltage gradient difference constraints on high-voltage busbars of each station, upper and lower limits of voltage and reactive power output of a single station, and adjustment step size constraints. This directly generates a coordinated reactive power regulation command that includes the reactive power optimization adjustment of each hydropower station generator busbar node.

8. The automatic voltage control and coordinated regulation method for a cascade hydropower project in a river basin according to claim 1, characterized in that, The output optimized power flow and voltage results include: The power flow calculation algorithm is invoked, and combined with the topology and admittance matrix of the cascade chain hydropower network in the basin, the adjusted reactive power output is used as input to iteratively calculate the voltage amplitude, phase angle and power distribution of each node and each branch until the active power deviation, reactive power deviation and voltage constraint meet the convergence threshold. The output includes the optimized power flow and voltage results of each power station's high-voltage bus voltage and transmission branch power flow.

9. The automatic voltage control and coordinated regulation method for a cascade chain hydropower project in a river basin according to claim 1, characterized in that, The reactive power and voltage operation evaluation indicators include the absolute value of reactive power pull amplitude and the reasonable voltage gradient operation rate.

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