Voltage regulation and control method and system for low-voltage flexible interconnection power distribution system

Abstract

The invention relates to the technical field of voltage regulation and control of a power distribution system, and particularly discloses a voltage regulation and control method and system of a low-voltage flexible interconnection power distribution system. On-load voltage regulating transformer and capacitor bank action decisions considering robustness and economical efficiency can be made, and the influence of uncertainty of renewable resources on voltage stability can be effectively dealt with; the SOP voltage reactive droop control parameter optimization model is constructed by taking the minimum node voltage deviation and the system network loss as targets, and the SOP voltage reactive droop control parameter optimization model based on intraday rolling optimization can ensure that the node voltage is stable in the real-time voltage control stage of the SOP, and also considers global network loss optimization, so that the global performance of the system is improved. According to the method, dynamic characteristics and interaction influences among different voltage regulating devices are considered, sequential cooperative control among various resources is realized through day-ahead and intra-day distributed optimization and centralized local multi-stage voltage control, and the voltage out-of-limit problem of the flexible interconnection power distribution system is effectively solved. And the system voltage control effect is improved.

Description

Technical Field

[0001] This invention relates to the field of voltage regulation technology for power distribution systems, specifically to a voltage regulation method and system for a low-voltage flexible interconnected power distribution system. Background Technology

[0002] With the large-scale integration of distributed renewable energy and the increasing diversification of load demands, traditional low-voltage distribution networks are prone to problems such as bidirectional power flow and voltage exceeding limits. Although low-voltage distribution networks can regulate system voltage levels through methods such as switching on-load tap changers and capacitor banks, network reconfiguration, and distributed active-reactive power control, problems such as poor resource coordination, slow response speed, and limited voltage regulation effect still exist. Flexible interconnected distribution systems based on SoftOpenPoint (SOP), as a new generation of distribution network technology, can guarantee millisecond-level dynamic power response, achieve precise control between feeder power flows, and support flexible system networking, greatly improving system operational flexibility. However, compared with traditional distribution networks, the voltage control problem of SOP-based flexible interconnected distribution systems becomes more complex. This is mainly reflected in the unclear coordination mechanism between SOP and traditional voltage regulating equipment, and the lack of a unified control framework.

[0003] Existing voltage control methods for distribution networks largely rely on the collaborative efforts of traditional voltage regulating resources to ensure voltage security. However, for flexible interconnected distribution systems with System-on-Place (SOP) devices, relying solely on traditional voltage regulating resources not only wastes the voltage regulation potential of SOP devices but also fails to achieve efficient voltage regulation of the distribution network. To address these issues, some scholars have proposed voltage regulation models that coordinate SOPs with traditional distributed voltage regulating resources. However, most of these models fail to fully consider the differences in regulation characteristics and response speeds between SOPs and various distributed resources, resulting in an unclear collaborative framework and hindering efficient voltage management. Furthermore, some voltage regulation models struggle to balance conservatism and economy when dealing with fluctuations in renewable energy output, leading to low economic efficiency in voltage management and making it impossible to achieve efficient, reliable, and low-cost voltage management for SOP-based flexible interconnected distribution systems. Therefore, domestic and international scholars have conducted preliminary research on how to address the voltage management problem in flexible interconnected distribution systems. Although SOP devices can achieve millisecond-level power response and possess significant voltage regulation potential, a framework for effective sequential collaboration between SOPs and traditional voltage regulating resources is still lacking. Meanwhile, there is still a lack of effective solutions for balancing the economic efficiency and robustness of voltage management in the face of fluctuations in the output of wind and solar renewable resources.

[0004] Therefore, it is necessary to introduce a voltage management model for flexible interconnected power distribution systems that sequentially coordinates SOP with traditional voltage regulation resources, revealing the coordination mechanism between resources and achieving efficient, reliable, and low-cost voltage management. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the existing technology and provide a high-efficiency, reliable and low-cost voltage regulation method and system for low-voltage flexible interconnected power distribution systems.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0007] A voltage regulation method for a low-voltage flexible interconnected power distribution system includes:

[0008] In the day-ahead centralized voltage control phase, a day-ahead centralized voltage control model is established with the goal of minimizing operating costs and node voltage deviations.

[0009] Based on the aforementioned centralized voltage control model, a two-stage sub-Blu-ray bar optimization model is constructed with the goal of minimizing the operating cost of discrete regulating equipment, node voltage deviation, and system network loss.

[0010] During the intraday rolling optimization phase, with the goal of minimizing system network losses and node voltage deviation, an intraday rolling optimization model is established to control the output power of wind turbine inverters, photovoltaic inverters, and SOPs, and to obtain the SOP power reference value for rolling optimization.

[0011] In the real-time voltage control phase, an optimization model for the SOP voltage reactive power droop control parameters is established.

[0012] By combining the current global state information of the power distribution system, the fixed-point voltage parameters of the SOP voltage reactive droop control parameter optimization model are dynamically optimized to obtain the dynamically optimized SOP voltage reactive droop control parameters.

[0013] The reactive power output of the SOP is adjusted in real time by dynamically optimizing the reactive power droop control parameters of the SOP voltage and the voltage deviation of the SOP power injection node.

[0014] The dynamically optimized SOP voltage reactive power droop control parameters are stored in the SOP device for real-time dynamic adjustment of the local voltage by the SOP.

[0015] As a further improvement to the above technical solution:

[0016] The objective function of the current centralized voltage control model It satisfies the following expression: ;

[0017] In the formula, For operating costs, For voltage deviation, and These represent the probabilities corresponding to scenario 1 and scenario 2, respectively.

[0018] As a further improvement to the above technical solution:

[0019] The operating costs Including network loss costs Capacitor bank loss cost and on-load tap-changing transformer loss cost It satisfies the following expression: ;

[0020] The voltage deviation Satisfy the following expression: ;

[0021] In the formula, i represents a node in the power distribution system. For time period, For the scene; For the scene The corresponding probability, For the scene middle The square of the voltage at time node i. For the set of nodes in the power distribution system, This is the lower bound of the node voltage. This is the upper bound of the node voltage;

[0022] The network loss cost Satisfy the following expression: ;

[0023] In the formula, l represents a branch of the power distribution system. For the scene middle The square of the current in branch l at time t, This represents the resistance of branch l. This refers to the collection of all branches in the power distribution system.

[0024] The capacitor bank loss cost Satisfy the following expression: ;

[0025] In the formula, This represents the operating cost coefficient for on-load tap-changing transformers. For the scene middle The corresponding tap position of the on-load tap-changing transformer is always available;

[0026] The loss cost of the on-load tap-changing transformer Satisfy the following expression: ;

[0027] In the formula, This represents the cost factor for using capacitor banks. For the scene middle The number of capacitors switched on at any given time.

[0028] As a further improvement to the above technical solution:

[0029] The constraints of the day-ahead centralized voltage control model include power flow constraints, voltage safety constraints, renewable resource output constraints, SOP constraints, and wind and solar renewable resource output constraints.

[0030] As a further improvement to the above technical solution:

[0031] Based on the aforementioned centralized voltage control model, a two-stage sub-Blule bar optimization model is constructed with the objective of minimizing the operating cost of discrete regulating equipment, node voltage deviation, and system network loss. This model includes:

[0032] Rewriting equations (1.1)-(1.6) in a min-max-min compact form yields a two-stage sub-Bruker optimization model, satisfying the following expression: ;

[0033] In the formula, , These are the 0-1 variables for the first-stage sub-Brussels bar optimization model and the second-stage sub-Brussels bar optimization model, respectively. For continuous variables in the second-stage sub-Bruker optimization model; , , , , All are constant coefficient matrices, representing the corresponding matrix or vector form of the variables; Represents a fuzzy set of renewable energy output;

[0034] The first stage is a BLU rod optimization model, with the control strategies of on-load tap-changing transformers and capacitor banks as decision variables.

[0035] The second stage is a bibliometric optimization model, which uses the probability distribution of uncertain renewable energy output scenarios and SOP response power as variables, but does not contain binary variables.

[0036] The first-stage sub-Brussels bar optimization model and the second-stage sub-Brussels bar optimization model are solved iteratively until the two-stage sub-Brussels bar optimization model converges, including:

[0037] The optimal decision variables obtained by the first-stage sub-Brussels bar optimization model are passed to the second-stage sub-Brussels bar optimization model. The second-stage sub-Brussels bar optimization model solves the worst-case probability distribution and returns it to the first-stage sub-Brussels bar optimization model.

[0038] As a further improvement to the above technical solution:

[0039] The objective function of the intraday rolling optimization model It satisfies the following expression: ;

[0040] In the formula, To optimize the set of time periods for rolling updates; Let be the current in branch ij; Let be the impedance of branch ij; A set of nodes that connect to SOPs; The power loss of the m-th SOP device; i and j represent different nodes in the power distribution system.

[0041] As a further improvement to the above technical solution:

[0042] The constraints of the intraday rolling optimization model include: system power flow constraints, safety constraints, renewable resource output constraints, and SOP constraints; and the day-ahead centralized voltage control model used to control on-load tap-changing transformers and capacitor banks in the day-ahead centralized voltage control stage is used as the constraint for intraday rolling optimization.

[0043] As a further improvement to the above technical solution:

[0044] The establishment of the SOP voltage reactive power droop control parameter optimization model includes:

[0045] Based on the SOP power reference, short-term renewable resources, and load forecast data obtained during the intraday rolling optimization phase, and using fixed-point voltage parameters , , and Establish an optimization model for the control parameters of SOP voltage reactive power droop, using these as decision variables;

[0046] The objective function of the SOP voltage reactive power droop control parameter optimization model It satisfies the following expression: ;

[0047] The SOP voltage reactive power droop control parameter optimization model simultaneously satisfies the constraints of the intraday rolling optimization model as well as the following constraints:

[0048] SOP reactive power capacity constraint satisfies the following expression: ;

[0049] In the formula, This represents the maximum reactive power at port i of the SOP device at time t. Indicates the apparent capacitance of SOP devices. This represents the reference active power at port i of the SOP device at time t. This represents the maximum reactive power at port j of the SOP device at time t. This represents the reference amount of active power at port j of the SOP device at time t.

[0050] The SOP reactive voltage control rule constraint satisfies the following expression: ; ; ;

[0051] In the formula, This is the SOP voltage reactive power droop control function. Let i be the reactive power reference value at port i of the SOP device at time t. Let be the reactive power of port i of the SOP device at time t; , , and Let be the fixed-point voltage at time t;

[0052] Based on the current global state information of the power distribution system, the fixed-point voltage in equation (1.11) is adjusted. , , , The solution is performed to obtain the dynamically optimized SOP voltage reactive power droop control parameters;

[0053] The global status information includes the output of wind and solar renewable resources in the power distribution system, the voltage information of each node, the load information, and the power information of each branch.

[0054] As a further improvement to the above technical solution:

[0055] The reactive power output of the SOP is adjusted in real time by dynamically optimizing the reactive power droop control parameters of the SOP voltage and the voltage deviation of the SOP power injection node, satisfying the following expression; ; ;

[0056] In the formula, Let i be the reactive power adjustment at port i of SOP at time t. Let i be the active power output value of port i at time t. The optimal voltage level achievable by each node under a specific set of reactive power droop control parameters is obtained by solving the SOP voltage reactive power droop control parameter optimization model. This represents the optimal voltage level that can be achieved by adjusting a certain set of reactive power droop control parameters, considering system network losses. Specifically refers to the reference voltage of the SOP reactive power injection node;

[0057] At the same time, during this stage This refers to the optimal active power output of the SOP obtained from the intraday rolling optimization phase.

[0058] The present invention also provides a computer system, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the voltage regulation method for a low-voltage flexible interconnected power distribution system as described above.

[0059] Compared with the prior art, the advantages of the present invention are as follows:

[0060] (1) The present invention provides a voltage regulation method for a low-voltage flexible interconnected distribution system. In the day-ahead stage, a data-driven two-stage discrete bar optimization model is constructed with the objectives of minimizing the operating cost of discrete regulating equipment, node voltage deviation, and system network loss. In the intraday stage, a dynamic rolling optimization model for SOP voltage reactive power droop control parameters is constructed with the objectives of minimizing node voltage deviation and system network loss. In the real-time stage, dynamic voltage control is achieved by adjusting the reactive power output of SOP through optimized control rules. Considering the dynamic characteristics and interactive effects between different voltage regulating equipment, sequential collaborative control between various resources is achieved through day-ahead and intraday distributed optimization and centralized local multi-level voltage control, effectively solving the voltage over-limit problem of flexible interconnected distribution systems.

[0061] (2) The present invention can give full play to the fast and slow adjustment characteristics of various controllable resources and improve the voltage control effect of the system; the day-ahead voltage regulation model based on the split-blown bar optimization can formulate the on-load tap-changing transformer and capacitor bank operation decision that takes into account both robustness and economy, and effectively cope with the impact of the uncertainty of renewable resources on voltage stability; the SOP voltage reactive power droop control parameter optimization model based on intraday rolling optimization can ensure the voltage stability of the node in the real-time voltage control stage of SOP, while also taking into account the global network loss optimization, and improve the overall system performance. Attached Figure Description

[0062] Figure 1 This is a framework diagram of a voltage regulation method for a low-voltage flexible interconnected power distribution system according to an embodiment of the present invention.

[0063] Figure 2 This is an optimized SOP voltage reactive voltage droop control curve according to an embodiment of the present invention. Detailed Implementation

[0064] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0065] like Figure 1 As shown, this embodiment provides a voltage regulation method for a low-voltage flexible interconnected power distribution system, including:

[0066] In the day-ahead centralized voltage control phase, a day-ahead centralized voltage control model is established with the goal of minimizing operating costs and node voltage deviations.

[0067] The objective function of the current centralized voltage control model It satisfies the following expression: ;

[0068] In the formula, For operating costs, For voltage deviation, and These represent the probabilities corresponding to scenario 1 and scenario 2, respectively.

[0069] In this embodiment, the operating cost Main consideration: Network loss cost Capacitor bank loss cost and the cost of losses in on-load tap-changing transformers It satisfies the following expression: ;

[0070] The voltage deviation Satisfy the following expression: ;

[0071] In the formula, i represents a node in the power distribution system. For time period, For the scene; For the scene The corresponding probability, For the scene middle The square of the voltage at time node i. For the set of nodes in the power distribution system, This is the lower bound of the node voltage. This is the upper bound of the node voltage;

[0072] The network loss cost Satisfy the following expression: ;

[0073] In the formula, l represents a branch of the power distribution system. For the scene middle The square of the current in branch l at time t, This represents the resistance of branch l. This refers to the collection of all branches in the power distribution system.

[0074] The capacitor bank loss cost Satisfy the following expression: ;

[0075] In the formula, This represents the operating cost coefficient for on-load tap-changing transformers. For the scene middle The corresponding tap position of the on-load tap-changing transformer is always available;

[0076] The loss cost of the on-load tap-changing transformer Satisfy the following expression: ;

[0077] In the formula, This represents the cost factor for using capacitor banks. For the scene middle The number of capacitors switched on at any given time.

[0078] The constraints of the day-ahead centralized voltage control model include power flow constraints, voltage safety constraints, renewable resource output constraints, SOP constraints, and wind and solar renewable resource output constraints.

[0079] Based on the aforementioned centralized voltage control model, and with the objectives of minimizing the operating costs of discrete regulating equipment, node voltage deviations, and system network losses, a two-stage sub-Bruker optimization model is constructed, specifically:

[0080] Rewriting equations (1.1)-(1.6) in a min-max-min compact form yields a two-stage sub-Bruker optimization model, satisfying the following expression: ;

[0081] In the formula, , These are the 0-1 variables for the first-stage sub-Brussels bar optimization model and the second-stage sub-Brussels bar optimization model, respectively. For continuous variables in the second-stage sub-Bruker optimization model; , , , , All are constant coefficient matrices, representing the corresponding matrix or vector form of the variables; Represents a fuzzy set of renewable energy output;

[0082] The first stage is a BLU rod optimization model, with the control strategies of on-load tap-changing transformers and capacitor banks as decision variables.

[0083] The second stage is a bibliometric optimization model, which uses the probability distribution of uncertain renewable energy output scenarios and SOP response power as variables, but does not contain binary variables.

[0084] The first-stage sub-Brussels bar optimization model and the second-stage sub-Brussels bar optimization model are solved iteratively until the two-stage sub-Brussels bar optimization model converges, including:

[0085] The optimal decision variables obtained by the first-stage sub-Brussels bar optimization model are passed to the second-stage sub-Brussels bar optimization model. The second-stage sub-Brussels bar optimization model solves the worst-case probability distribution and returns it to the first-stage sub-Brussels bar optimization model.

[0086] In the day-ahead centralized voltage control phase: Centralized voltage control based on the overall state information of the flexible interconnected distribution system requires establishing a centralized optimization problem, consuming significant computational resources and making it impossible to perform orderly and coordinated control of flexible resources at a minute-level time resolution. Simultaneously, discrete control devices such as on-load tap-changing transformers and capacitor banks cannot be continuously adjusted on a time scale, and their adjustment speed is slower compared to inverters and SOPs, making them more suitable for developing detailed control plans day-ahead. Therefore, this embodiment establishes a centralized voltage control model with 1-hour time intervals in the day-ahead phase. This phase provides hourly control schemes for on-load tap-changing transformers and capacitor banks, which are then applied to intraday voltage control.

[0087] During the intraday rolling optimization phase, with the goal of minimizing system network losses and node voltage deviation, an intraday rolling optimization model is established to control the output power of wind turbine inverters, photovoltaic inverters, and SOPs, and to obtain the SOP power reference value for rolling optimization.

[0088] The objective function of the intraday rolling optimization model It satisfies the following expression: ;

[0089] In the formula, To optimize the set of time periods for rolling updates; Let be the current in branch ij; Let be the impedance of branch ij; A set of nodes that connect to SOPs; The power loss of the m-th SOP device; i and j represent different nodes in the power distribution system.

[0090] The constraints of the intraday rolling optimization model include: system power flow constraints, safety constraints, renewable resource output constraints, and SOP constraints; and the day-ahead centralized voltage control model used to control on-load tap-changing transformers and capacitor banks in the day-ahead centralized voltage control stage is used as the constraint for intraday rolling optimization.

[0091] Intraday Rolling Optimization Phase: The active and reactive power output of photovoltaic inverters, wind turbine inverters, and SOP devices respond quickly, making them suitable for minute-level control within a single day. Furthermore, during this intraday phase, renewable resource output forecasts and load forecasts at 15-minute intervals are more accurate, facilitating more precise control of the reactive power output of photovoltaic and wind turbine inverters. Therefore, in the real-time voltage control phase of the flexible interconnected distribution system, an intraday rolling optimization model with 15-minute intervals is established. The decision variables are the active and reactive power output of each port of the SOP, and the active and reactive power output of the photovoltaic and wind turbines. The optimization objective is to minimize system network losses and node voltage deviations, thereby controlling the output power of the wind turbine inverters, photovoltaic inverters, and SOPs.

[0092] In the real-time voltage control phase, an optimization model for the SOP voltage reactive power droop control parameters is established, specifically:

[0093] The reactive power droop control curve of the i-side voltage of SOP is as follows: Figure 2 As shown, the basic control laws are the same on the j-side, but the i-side is used as an example for analysis and modeling. This represents the maximum reactive power that can be injected at port i of the Standard Operating Procedure (SOP). The slopes of the two segments of the standard SOP voltage-reactive power droop curve and the fixed-point voltage are also considered. , , , , , The constant voltage droop curve prevents the Standard Operating Procedure (SOP) from reaching its maximum reactive power capacity during real-time voltage control, resulting in reduced local active power output and voltage exceeding limits, leading to poor economy and robustness. Furthermore, using this type of standard voltage droop control curve for real-time voltage control only considers the voltage regulation of the current node, neglecting the impact on the voltage of other nodes in the system, which is detrimental to the overall voltage stability of the system.

[0094] Therefore, this embodiment proposes a dynamic optimization method for SOP voltage reactive power droop control parameters with centralized setting and local control. A dynamic parameter optimization model is established based on the SOP output active and reactive power obtained from intraday rolling optimization, as well as short-term renewable resources and load forecast data. The decision variables are... , , , The optimization model is solved with the goal of minimizing the voltage deviation of the centralized nodes, so as to achieve dynamic optimization of the reactive power droop control parameters of the SOP voltage.

[0095] Based on the SOP power reference, short-term renewable resources, and load forecast data obtained during the intraday rolling optimization phase, and using fixed-point voltage parameters , , and Establish an optimization model for the control parameters of SOP voltage reactive power droop, using these as decision variables;

[0096] The objective function of the SOP voltage reactive power droop control parameter optimization model It satisfies the following expression: ;

[0097] The SOP voltage reactive power droop control parameter optimization model simultaneously satisfies the constraints of the intraday rolling optimization model as well as the following constraints:

[0098] SOP reactive power capacity constraint satisfies the following expression: ;

[0099] In the formula, This represents the maximum reactive power at port i of the SOP device at time t. Indicates the apparent capacitance of SOP devices. This represents the reference active power at port i of the SOP device at time t. This represents the maximum reactive power at port j of the SOP device at time t. This represents the reference amount of active power at port j of the SOP device at time t.

[0100] The SOP reactive voltage control rule constraint satisfies the following expression: ; ; ;

[0101] In the formula, This is the SOP voltage reactive power droop control function. Let i be the reactive power reference value at port i of the SOP device at time t. Let be the reactive power of port i of the SOP device at time t; , , and Let be the fixed-point voltage at time t; Equation (1.11) describes the SOP reactive droop control rule, but unlike the standard SOP droop control, its fixed-point voltage is... , , , These are variables to be optimized. By performing centralized rolling optimization on them, the real-time voltage control of SOP can balance the stability of the system's centralized voltage and the reduction of system network losses.

[0102] By combining the current global state information of the power distribution system, the fixed-point voltage parameters of the SOP voltage reactive power droop control parameter optimization model are dynamically optimized to obtain the dynamically optimized SOP voltage reactive power droop control parameters; the global state information includes the output of wind and solar renewable resources in the power distribution system, the voltage information of each node, the load information, and the power information of each branch.

[0103] The reactive power output of the SOP is adjusted in real time by dynamically optimizing the reactive power droop control parameters of the SOP voltage and the voltage deviation of the SOP power injection node, as shown in the following expression: ; ;

[0104] In the formula, , , The optimal voltage level achievable by each node under a specific set of reactive power droop control parameters is obtained by solving the SOP voltage reactive power droop control parameter optimization model. This represents the optimal voltage level that can be achieved by adjusting a certain set of reactive power droop control parameters, considering system network losses. Specifically refers to the reference voltage of the SOP reactive power injection node;

[0105] At the same time, during this stage This refers to the optimal active power output of SOP obtained during the intraday rolling optimization phase. This method can ensure that the active power output of SOP is not reduced during the real-time voltage regulation phase, minimizing system network losses, while also fully tapping the reactive power control potential of SOP to maintain system voltage stability.

[0106] The dynamically optimized SOP voltage reactive power droop control parameters are stored in the SOP device for real-time dynamic adjustment of the local voltage by the SOP.

[0107] In this embodiment, considering the deviation in SOP voltage-reactive power droop control power allocation caused by the high impedance characteristics of low-voltage distribution transformer areas, an SOP droop control rule optimization model is established based on rolling optimization results. The SOP control rules are dynamically optimized with the objectives of minimizing global node voltage deviation and network loss. During the real-time voltage control phase, the voltage fluctuations caused by load fluctuations within the distribution system on the low-voltage distribution transformer area are considered. Reactive power injection is adjusted in real-time through SOP to ensure that the node voltage remains within the safe operating range. This multi-level voltage regulation model achieves hierarchical sequential coordination of voltage regulation resources in low-voltage distribution transformer areas, resulting in efficient and highly reliable voltage regulation.

[0108] Real-time voltage control phase: During the intraday real-time voltage control phase, this embodiment proposes a dynamic tuning method for SOP voltage reactive power droop control parameters. Based on the active and reactive power outputs of SOP obtained through rolling optimization as power reference quantities, and combined with the current centralized voltage information of the distribution system, the fixed-point voltage parameters of the droop curve are dynamically tuned every 15 minutes to obtain a dynamically optimized SOP reactive power droop control curve. It is worth noting that although the control parameters tuned here are used for SOP real-time voltage control, the impact of the parameters on centralized voltage and network losses is considered during the parameter tuning process, which is a centralized parameter optimization. Therefore, during the SOP real-time reactive power droop control phase, the reactive power output of SOP can both regulate the local voltage and reduce system network losses, maintaining centralized voltage stability.

[0109] This embodiment also provides a computer system, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the voltage regulation method for a low-voltage flexible interconnected power distribution system as described above.

[0110] The computer system can be a mobile phone, desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device may include, but is not limited to, a processor and memory. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0111] The above description is merely a preferred embodiment of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. For those skilled in the art, improvements and modifications obtained without departing from the inventive concept should also be considered within the scope of protection of the present invention.

Claims

1. A voltage regulation method for a low-voltage flexible interconnected power distribution system, characterized in that, include: In the day-ahead centralized voltage control phase, a day-ahead centralized voltage control model is established with the goal of minimizing operating costs and node voltage deviations. Based on the aforementioned centralized voltage control model, a two-stage sub-Blu-ray bar optimization model is constructed with the goal of minimizing the operating cost of discrete regulating equipment, node voltage deviation, and system network loss. During the intraday rolling optimization phase, with the goal of minimizing system network losses and node voltage deviation, an intraday rolling optimization model is established to control the output power of wind turbine inverters, photovoltaic inverters, and SOPs, and to obtain the SOP power reference value for rolling optimization. In the real-time voltage control phase, an optimization model for the SOP voltage reactive power droop control parameters is established. By combining the current global state information of the power distribution system, the fixed-point voltage parameters of the SOP voltage reactive droop control parameter optimization model are dynamically optimized to obtain the dynamically optimized SOP voltage reactive droop control parameters. The reactive power output of the SOP is adjusted in real time by dynamically optimizing the reactive power droop control parameters of the SOP voltage and the voltage deviation of the SOP power injection node. The dynamically optimized SOP voltage reactive power droop control parameters are stored in the SOP device for real-time dynamic adjustment of the local voltage by the SOP.

2. The voltage regulation method for a low-voltage flexible interconnected power distribution system according to claim 1, characterized in that, The objective function of the current centralized voltage control model It satisfies the following expression: ； In the formula, For operating costs, For voltage deviation, and These represent the probabilities corresponding to scenario 1 and scenario 2, respectively.

3. The voltage regulation method for a low-voltage flexible interconnected power distribution system according to claim 2, characterized in that, The operating costs Including network loss costs Capacitor bank loss cost and on-load tap-changing transformer loss cost It satisfies the following expression: ； The voltage deviation Satisfy the following expression: ； In the formula, i represents a node in the power distribution system. For time period, For the scene; For the scene The corresponding probability, For the scene middle The square of the voltage at time node i. For the set of nodes in the power distribution system, This is the lower bound of the node voltage. This is the upper bound of the node voltage; The network loss cost Satisfy the following expression: ； In the formula, l represents a branch of the power distribution system. For the scene middle The square of the current in branch l at time t, This represents the resistance of branch l. This refers to the collection of all branches in the power distribution system. The capacitor bank loss cost Satisfy the following expression: ； In the formula, This represents the operating cost coefficient for on-load tap-changing transformers. For the scene middle The corresponding tap position of the on-load tap-changing transformer is always available; The loss cost of the on-load tap-changing transformer Satisfy the following expression: ； In the formula, This represents the cost factor for using capacitor banks. For the scene middle The number of capacitors switched on at any given time.

4. The voltage regulation method for a low-voltage flexible interconnected power distribution system according to claim 1 or 2, characterized in that, The constraints of the day-ahead centralized voltage control model include power flow constraints, voltage safety constraints, renewable resource output constraints, SOP constraints, and wind and solar renewable resource output constraints.

5. The voltage regulation method for a low-voltage flexible interconnected power distribution system according to claim 3, characterized in that, Based on the aforementioned centralized voltage control model, a two-stage sub-Blule bar optimization model is constructed with the objective of minimizing the operating cost of discrete regulating equipment, node voltage deviation, and system network loss. This model includes: Rewriting equations (1.1)-(1.6) in a min-max-min compact form yields a two-stage sub-Bruker optimization model, satisfying the following expression: ； In the formula, , These are the 0-1 variables for the first-stage sub-Brussels bar optimization model and the second-stage sub-Brussels bar optimization model, respectively. For continuous variables in the second-stage sub-Bruker optimization model; , , , , All are constant coefficient matrices, representing the corresponding matrix or vector form of the variables; Represents a fuzzy set of renewable energy output; The first stage is a BLU rod optimization model, with the control strategies of on-load tap-changing transformers and capacitor banks as decision variables. The second stage is a bibliometric optimization model, which uses the probability distribution of uncertain renewable energy output scenarios and SOP response power as variables, but does not contain binary variables. The first-stage sub-Brussels bar optimization model and the second-stage sub-Brussels bar optimization model are solved iteratively until the two-stage sub-Brussels bar optimization model converges, including: The optimal decision variables obtained by the first-stage sub-Brussels bar optimization model are passed to the second-stage sub-Brussels bar optimization model. The second-stage sub-Brussels bar optimization model solves the worst-case probability distribution and returns it to the first-stage sub-Brussels bar optimization model.

6. The voltage regulation method for a low-voltage flexible interconnected power distribution system according to claim 5, characterized in that, The objective function of the intraday rolling optimization model It satisfies the following expression: ； In the formula, To optimize the set of time periods for rolling updates; Let be the current in branch ij; Let be the impedance of branch ij; A set of nodes that connect to SOPs; The power loss of the m-th SOP device; i and j represent different nodes in the power distribution system.

7. The voltage regulation method for a low-voltage flexible interconnected power distribution system according to claim 6, characterized in that, The constraints of the intraday rolling optimization model include: system power flow constraints, safety constraints, renewable resource output constraints, and SOP constraints; and the day-ahead centralized voltage control model used to control on-load tap-changing transformers and capacitor banks in the day-ahead centralized voltage control stage is used as the constraint for intraday rolling optimization.

8. The voltage regulation method for a low-voltage flexible interconnected power distribution system according to claim 7, characterized in that, The establishment of the SOP voltage reactive power droop control parameter optimization model includes: Based on the SOP power reference, short-term renewable resources, and load forecast data obtained during the intraday rolling optimization phase, and using fixed-point voltage parameters , , and Establish an optimization model for the control parameters of SOP voltage reactive power droop, using these as decision variables; The objective function of the SOP voltage reactive power droop control parameter optimization model It satisfies the following expression: ； The SOP voltage reactive power droop control parameter optimization model simultaneously satisfies the constraints of the intraday rolling optimization model as well as the following constraints: SOP reactive power capacity constraint satisfies the following expression: ； In the formula, This represents the maximum reactive power at port i of the SOP device at time t. Indicates the apparent capacitance of SOP devices. This represents the reference active power at port i of the SOP device at time t. This represents the maximum reactive power at port j of the SOP device at time t. This represents the reference amount of active power at port j of the SOP device at time t. The SOP reactive voltage control rule constraint satisfies the following expression: ； ； ； In the formula, This is the SOP voltage reactive power droop control function. Let i be the reactive power reference value at port i of the SOP device at time t. Let be the reactive power of port i of the SOP device at time t; , , and Let be the fixed-point voltage at time t; Based on the current global state information of the power distribution system, the fixed-point voltage in equation (1.11) is adjusted. , , , The solution is performed to obtain the dynamically optimized SOP voltage reactive power droop control parameters; The global status information includes the output of wind and solar renewable resources in the power distribution system, the voltage information of each node, the load information, and the power information of each branch.

9. The voltage regulation method for a low-voltage flexible interconnected power distribution system according to claim 8, characterized in that, The reactive power output of the SOP is adjusted in real time by dynamically optimizing the reactive power droop control parameters of the SOP voltage and the voltage deviation of the SOP power injection node, satisfying the following expression; ； ； In the formula, Let i be the reactive power adjustment at port i of SOP at time t. Let i be the active power output value of port i at time t. The optimal voltage level achievable by each node under a specific set of reactive power droop control parameters is obtained by solving the SOP voltage reactive power droop control parameter optimization model. This represents the optimal voltage level that can be achieved by adjusting a certain set of reactive power droop control parameters, considering system network losses. Specifically refers to the reference voltage of the SOP reactive power injection node; At the same time, during this stage This refers to the optimal active power output of the SOP obtained from the intraday rolling optimization phase.

10. A computer system, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the voltage regulation method for a low-voltage flexible interconnected power distribution system as described in any one of claims 1-9.

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