A method and system for site selection and capacity determination of a medium voltage flexible interconnection switch in a power distribution network
By constructing a full life-cycle cost objective function and a mixed-integer second-order cone programming model to optimize the location and capacity of flexible interconnection switches, the problems of location robustness and cost coordination in existing technologies are solved. This achieves a balance between economy and safety under high new energy penetration rates, extends equipment life, and reduces operating costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SUZHOU SUXIN POWER DESIGN CONSULTING CO LTD
- Filing Date
- 2026-03-04
- Publication Date
- 2026-06-05
AI Technical Summary
Existing flexible interconnection switch location and capacity determination methods lack robustness analysis of location selection during the dynamic evolution of penetration rate in the context of high proportion of distributed power access. They fail to effectively coordinate the high initial investment of equipment with the full life cycle operation and maintenance and network loss costs, resulting in limited overall economic efficiency of planning schemes over long-term time scales.
A total lifecycle cost objective function is constructed, which includes fixed installation costs, operation and maintenance costs, annual network loss costs, annual loss costs, and risk cost penalties. The location and capacity determination of flexible interconnection switches are optimized through a mixed integer second-order cone programming model. Considering the volatility of new energy sources and the thermal reliability of equipment, power flow constraints, operational safety constraints, and junction temperature constraints are established.
It achieves a balance between economy and safety in medium-voltage flexible interconnection switches in distribution networks with high renewable energy penetration, reduces equipment overload risk and system operation uncertainty, extends equipment lifespan, and optimizes total life cycle cost.
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Figure CN122154200A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of power distribution network optimization technology, and specifically relates to a method and system for site selection and capacity determination of medium-voltage flexible interconnection switches in power distribution networks. Background Technology
[0002] With the advancement of the national "dual carbon" goals, distributed generation (DG), represented by distributed photovoltaic (PV) and wind power (WT), is being massively integrated into medium-voltage distribution networks. However, traditional distribution networks are passive networks designed for unidirectional power flow. The widespread integration of DG, especially its intermittent, fluctuating, and random power output, poses a severe challenge to the safe and stable operation of distribution networks.
[0003] First, high-penetration distributed generation (DG) connections can easily lead to voltage overshooting at some nodes or cause severe voltage spikes during light-load periods. Second, when DG output exceeds local load, power backflow (power flow reversal) occurs, rendering existing relay protection configurations ineffective and threatening grid safety. Third, the temporal and spatial mismatch between power sources and loads exacerbates power imbalances between feeders, increasing system network losses.
[0004] To address these challenges, medium-voltage flexible interconnection switch (SOP) technology has emerged. SOPs typically employ a back-to-back voltage source converter (B2B VSC) topology and are power electronic devices capable of flexibly interconnecting multiple medium-voltage feeders. With its flexible controllability and rapid response (microsecond-level adjustment), it enables flexible transfer of active power and independent compensation and support of reactive power between feeders. Therefore, SOPs are considered one of the key technologies for building new smart distribution networks, improving the absorption capacity of new energy sources, and enhancing the carrying capacity of distribution networks.
[0005] However, the fixed installation cost of SOP equipment is high, and its planning and layout in the distribution network (i.e., site selection and capacity determination) plays a decisive role in its technical and economic benefits. If the site selection is inappropriate or the capacity configuration is unreasonable, it will not only fail to effectively solve the above-mentioned technical problems, but will also cause huge waste of assets.
[0006] Currently, existing methods for optimizing the location and capacity of flexible interconnected switches include: Patent application CN113013868A provides a four-terminal soft switch location and capacity optimization method based on the influence of power supply capacity. This method establishes an optimized configuration model considering the influence of power supply capacity, an annual loss calculation model, and a power supply capacity assessment model, and solves these models using second-order cone programming and particle swarm optimization algorithms. This achieves continuous adjustment and load balancing of the power flow of the four feeders, effectively improving the power supply capacity and equipment utilization efficiency of the distribution network. Patent application CN115528682A discloses an optimized control method based on the loss characteristics of key equipment in flexible interconnected distribution networks, based on SOP and transformer... The fitting analysis of loss characteristics leads to the construction of a node loss sensitivity calculation model and a two-layer optimization model for SOP (Standard Operating Procedure) occupancy, which can accurately optimize the transformer loss, which accounts for a large proportion, significantly reduce the overall system loss, and achieve precise control of network power flow. Meanwhile, patent application CN118886633A provides a method and system for flexible soft-switching location and occupancy in distribution networks based on hybrid second-order cone programming. This method combines an improved sparrow algorithm with second-order cone programming to solve a flexible soft-switching location and occupancy planning model that aims to minimize daily overall operating costs. This allows for a more accurate measurement of the economics of different configuration schemes, achieving coordination and complementarity among system devices and significantly reducing operating costs and system losses.
[0007] However, existing SOP configuration methods based on mathematical programming mostly focus on short-term operational optimization under specific renewable energy penetration rates or typical daily scenarios. With the continuous integration of high-proportion distributed power sources, existing technologies still face the following bottlenecks: First, they lack robustness analysis of site selection during the dynamic evolution of penetration rates. Existing methods are mostly based on static scenarios and fail to identify installation locations that maintain optimal performance when penetration rates jump significantly from low to high. Second, existing models often focus on daily operating costs, failing to effectively balance the high initial investment in equipment with the cross-year maintenance and network loss costs throughout the entire lifecycle, thus limiting the overall economic viability of the planning scheme over the long term. Summary of the Invention
[0008] To address the technical problems in existing technologies, such as the lack of robustness analysis for site selection during penetration rate evolution and the focus on short-term operational benefits while neglecting the comprehensive cost over the entire life cycle, this invention provides a method and system for site selection and capacity determination of medium-voltage flexible interconnected switches in distribution networks. The method includes: constructing a mathematical model of the distribution network containing multiple candidate installation locations for flexible interconnected switchgear; constructing an optimization objective function for the distribution network mathematical model, considering the fixed installation cost, operation and maintenance cost, annual network loss cost, annual loss cost, and risk cost penalty term of the flexible interconnected switchgear, with the goal of minimizing the total cost over the entire life cycle of the distribution network; establishing constraints on the distribution network mathematical model during its operating cycle; transforming the constructed distribution network mathematical model into a mixed-integer second-order cone programming model; and solving the model using an optimization solver to obtain the site selection and capacity determination schemes for the flexible interconnected switchgear. This invention, by constructing a model incorporating multi-dimensional cost and risk constraints, achieves optimal site selection and capacity determination of medium-voltage flexible interconnected switches in distribution networks while considering the fluctuations in renewable energy and the thermal reliability of equipment, thus balancing economic efficiency and safety.
[0009] The present invention adopts the following technical solution: The first aspect of the present invention provides a method for site selection and capacity determination of medium-voltage flexible interconnection switches in a distribution network, comprising: A mathematical model of a distribution network with multiple candidate installation locations for flexible interconnected switchgear is constructed. With the goal of minimizing the total lifecycle cost of the distribution network, the model considers the fixed installation cost, operation and maintenance cost, annual network loss cost, annual loss cost, and risk cost penalty term of the flexible interconnected switchgear. The risk cost penalty term is calculated based on the impact of distributed power generation output changes on the transmission power of the flexible interconnected switchgear. Establish constraints for the mathematical model of the distribution network during its operating cycle. These constraints include: power flow constraints, operational safety constraints, distributed generation output constraints, flexible interconnection switchgear operation constraints, and junction temperature constraints. The power flow constraints and the operational constraints of the flexible interconnected switchgear are transformed into standard second-order cone forms, and the constructed distribution network mathematical model is transformed into a mixed-integer second-order cone programming model. An optimization solver is used to solve the model to obtain the location scheme and capacity scheme of the flexible interconnected switchgear.
[0010] Preferably, the specific calculation process for the fixed installation cost of flexible interconnection switchgear is as follows: Based on the service life of the flexible interconnected switchgear and the predefined cost-return rate, the cost-return coefficient of the flexible interconnected switchgear during its service life is calculated; the fixed cost per unit capacity of the flexible interconnected switchgear is multiplied by the cost-return coefficient and the rated capacity of all flexible interconnected switchgear in the distribution network, and then divided by the predefined unit conversion coefficient to obtain the fixed installation cost of the flexible interconnected switchgear.
[0011] Preferably, the specific calculation process for operation and maintenance costs is as follows: The operation and maintenance cost of the flexible interconnected switchgear is obtained by multiplying the fixed cost per unit capacity of the flexible interconnected switchgear by a predefined operation and maintenance cost coefficient and the rated capacity of all flexible interconnected switchgear in the distribution network, and then dividing by a predefined unit conversion coefficient.
[0012] Preferably, the specific calculation process for annual network loss cost is as follows: For each operating day under any typical scenario, the resistance of each branch of the distribution network in each time period of the corresponding operating day is multiplied by the square of the corresponding current, then multiplied by the electricity price of the corresponding time period and summed to obtain the network loss cost for the corresponding operating day of the corresponding typical scenario; the annual operating days of each typical scenario are multiplied by the corresponding network loss cost, then divided by the predefined unit conversion factor and summed to obtain the annual network loss cost.
[0013] Preferably, the specific calculation process for annual depreciation cost is as follows: For each operating day under any typical scenario, the absolute value of the transmission power of each flexible interconnection switch installed in the distribution network during each time period of the corresponding operating day is multiplied by the loss coefficient, then multiplied by the electricity price of the corresponding time period and summed to obtain the loss cost for the corresponding operating day of the corresponding typical scenario; the annual operating days of each typical scenario are multiplied by the corresponding loss cost, then divided by the predefined unit conversion coefficient and summed to obtain the annual loss cost.
[0014] Preferably, the specific calculation process for the risk cost penalty item is as follows: For any flexible interconnected switchgear in any typical scenario, the change in distributed power output at each moment in the corresponding scenario is used as the denominator, and the change in transmission power of the corresponding device under the change in distributed power output is used as the numerator. The squares of the ratio of the numerator to the denominator at each time period are summed to obtain the sensitivity coefficient of the corresponding flexible interconnected switchgear in the corresponding scenario. The sensitivity coefficient is multiplied by the probability of the corresponding scenario and summed to obtain the total sensitivity coefficient of all flexible interconnected switchgear in all scenarios. The total sensitivity coefficient is multiplied by a predefined risk cost coefficient to obtain the risk cost penalty term.
[0015] Preferably, the operational constraints of the flexible interconnection switchgear include active power balance constraints, active power loss constraints, reactive power upper and lower limit constraints, capacity constraints, equipment installation constraints, and equipment capacity correlation constraints. The junction temperature constraints of flexible interconnection switchgear include: junction temperature safety constraints and aging loss constraints; among them, the junction temperature of flexible interconnection switchgear is calculated based on the constructed junction temperature dynamic equation by substituting the ambient temperature, active power loss of flexible interconnection switchgear and equivalent thermal resistance at different time periods.
[0016] Preferably, the equipment capacity association constraint for any candidate installation location satisfies: When no flexible interconnection switchgear is installed at the corresponding candidate installation location, the equipment capacity at the corresponding location is 0; When flexible interconnected switchgear is installed at the corresponding candidate installation location, the lower limit of the equipment capacity at the corresponding location is the product of the predefined minimum configuration capacity and the new energy penetration rate and the predefined baseline configuration capacity under different scenarios, and the upper limit of the equipment capacity at the corresponding location is the predefined maximum configuration capacity.
[0017] Preferably, the junction temperature safety constraint is that the real-time junction temperature of the flexible interconnect switchgear meets the requirement that the junction temperature of the flexible interconnect switchgear in each time period does not exceed the predefined maximum junction temperature threshold. The aging loss constraint is that the daily aging loss factor shall not exceed the maximum allowable lifespan loss quota for a single day; the calculation process for the daily aging loss factor is as follows: For any given time period, the junction temperature of the flexible interconnected switchgear during that time period is used as the numerator, the predefined maximum junction temperature threshold is used as the denominator, the ratio of the numerator to the denominator is used as the base, and the predefined lifespan index of the flexible interconnected switchgear is used as the exponent to obtain the loss amplification factor of the equipment temperature rise. The time length of the corresponding period is multiplied by the loss amplification factor, divided by the lifespan of the flexible interconnected switchgear, and then summed to obtain the daily aging loss factor of the equipment.
[0018] A second aspect of the present invention provides a location and capacity determination system for medium-voltage flexible interconnection switches in a distribution network, and uses a location and capacity determination method for medium-voltage flexible interconnection switches in a distribution network, comprising: An optimization objective function construction module is used to build a mathematical model of the distribution network with multiple candidate installation locations for flexible interconnected switchgear. With the goal of minimizing the total lifecycle cost of the distribution network, the objective function of the mathematical model is constructed, considering the fixed installation cost, operation and maintenance cost, annual network loss cost, annual loss cost, and risk cost penalty term of the flexible interconnected switchgear. The risk cost penalty term is calculated based on the impact of distributed power generation output changes on the transmission power of the flexible interconnected switchgear. The constraint setting module establishes the constraint conditions of the distribution network mathematical model during the operating cycle. The constraint conditions include: power flow constraints, operation safety constraints, distributed generation output constraints, flexible interconnection switchgear operation constraints, and junction temperature constraints. The site selection and capacity determination module transforms power flow constraints and flexible interconnected switchgear operation constraints into standard second-order cone forms, and converts the constructed distribution network mathematical model into a mixed-integer second-order cone programming model. An optimization solver is used to solve the model to obtain the site selection and capacity determination schemes for the flexible interconnected switchgear.
[0019] A third aspect of the present invention provides a computer device including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of an addressing and capacity determination method for a medium-voltage flexible interconnection switch in a power distribution network.
[0020] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of an addressing and capacity determination method for a medium-voltage flexible interconnection switch in a power distribution network.
[0021] Compared with the prior art, the beneficial effects of the present invention include at least the following: 1. This invention achieves multi-dimensional comprehensive optimization of the location and capacity determination of medium-voltage flexible interconnection switches in distribution networks by constructing a total life-cycle cost objective function that includes fixed installation costs, operation and maintenance costs, annual network loss costs, annual loss costs, and risk cost penalties. Compared to planning methods that only consider initial investment or single operating costs, this invention can coordinate the relationship between equipment investment and operating benefits from a long-term operational perspective, effectively reducing the overall operating cost of the distribution network.
[0022] 2. This invention quantifies the impact of distributed power generation output variations on the transmission power of flexible interconnected switches into a sensitivity coefficient, and incorporates a risk cost penalty term into the optimization objective function, thus considering the impact of renewable energy volatility on equipment operational stability during the planning stage. By comprehensively evaluating the risk levels under different operating scenarios through a scenario probability weighting method, the resulting site selection and capacity determination schemes are not only economical but also possess stronger anti-disturbance capabilities and adaptability to high renewable energy penetration, effectively reducing the risk of equipment overload and system operational uncertainty caused by renewable energy output fluctuations.
[0023] 3. Based on traditional power flow and capacity constraints, this invention further introduces junction temperature safety constraints and aging loss constraints for flexible interconnected switchgear, and transforms power flow constraints and equipment operation constraints into a standard second-order cone form, ultimately forming a mixed-integer second-order cone programming model for solution. On the one hand, the solvability and solution efficiency of the model are improved through the second-order cone convex optimization form; on the other hand, the junction temperature safety constraints and lifetime aging constraints avoid the problem of accelerated lifespan decay caused by long-term high-temperature operation of equipment, significantly improving the reliability and service life of equipment operation. Attached Figure Description
[0024] Figure 1 A flowchart illustrating a method for selecting and calibrating a medium-voltage flexible interconnection switch in a distribution network, provided by the present invention; Figure 2 This is a schematic diagram of the back-to-back voltage source converter (B2BVSC) topology of the medium-voltage flexible interconnection switch (SOP) in an embodiment of the present invention. Figure 3 This is a schematic diagram of the IEEE 33-node system and SOP candidate locations in an embodiment of the present invention; Figure 4 This is a daily curve of wind and solar power output and load under a 90% penetration scenario in an embodiment of the present invention; Figure 5 This is a three-dimensional voltage distribution diagram under a 90% penetration rate scenario in an embodiment of the present invention. Detailed Implementation
[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.
[0026] Example 1 Embodiment 1 of the present invention provides a method for site selection and capacity determination of medium-voltage flexible interconnection switches in a distribution network, see reference. Figure 1 This includes the following steps: S1. Construct a mathematical model of the distribution network containing multiple candidate installation locations for medium-voltage flexible interconnected switchgear (SOP) equipment; with the goal of minimizing the total cost of the distribution network throughout its entire life cycle, consider the fixed installation cost, operation and maintenance cost, annual network loss cost, annual loss cost, and risk cost penalty term of the flexible interconnected switchgear, and construct the optimization objective function of the distribution network mathematical model; among which, the risk cost penalty term is calculated based on the impact of the output change of distributed power sources on the transmission power of the flexible interconnected switchgear.
[0027] In this embodiment, the following is adopted: Figure 2 The B2B VSC model shown adopts a back-to-back voltage source converter topology in SOP and establishes its mathematical model in the dq rotating coordinate system. The mathematical model also includes its control strategy, which adopts a dual closed-loop vector control. The outer loop adopts the PQ-UdcQ control mode to accurately control the active power and maintain the DC bus voltage stability, while the inner loop adopts current decoupling control.
[0028] Establish a mathematical model of SOP in the dq coordinate system: ; in, , These are the d-axis and q-axis components of the grid voltage, respectively. , These are the d-axis and q-axis components of the grid current, respectively. , VSC represents the control voltage components on the d and q axes; L is the inductance; R is the resistance. ω is the rotational angular velocity of the dp coordinate system; t is time. and It is a cross-coupling term; Establish Figure 3 The IEEE 33-node distribution network model shown.
[0029] As a preferred implementation method, the specific construction process of the optimization objective function is as follows: Based on the service life of the flexible interconnection switchgear and a predefined cost-return rate, the cost-return coefficient of the flexible interconnection switchgear over its service life is calculated. The fixed installation cost of the flexible interconnection switchgear is then obtained by multiplying the unit capacity fixed cost by the cost-return coefficient and the rated capacity of all flexible interconnection switchgear in the distribution network, and then dividing by a predefined unit conversion factor. The specific formula is as follows: ; In the formula, The fixed installation cost of the SOP equipment, i.e., the annualized fixed cost of the SOP; The cost-return ratio for SOPs is 0.08. The service life of the SOP equipment is set at 20 years. This represents the cost-return ratio of SOP equipment over its service life. The fixed cost per unit capacity is set at 1000 yuan / kVA in this embodiment; The rated capacity of the s-th SOP device is expressed in MVA. This represents the total number of SOP (Standard Operating Procedure) devices installed in the power distribution network. This represents the sum of the rated capacities of all SOP equipment that are finally determined; dividing by 10 in the formula represents the unit conversion factor from kVA to MVA; The operation and maintenance cost of the flexible interconnected switchgear is obtained by multiplying the unit capacity fixed cost of the flexible interconnected switchgear by a predefined operation and maintenance cost coefficient and the rated capacity of all flexible interconnected switchgear in the distribution network, and then dividing by a predefined unit conversion coefficient. The specific formula is as follows: ; In the formula, The maintenance cost of SOP equipment is the annualized maintenance expenditure of SOP. This is the operation and maintenance cost coefficient, with a value of 0.03; dividing by 10 in the formula represents the unit conversion factor from kVA to MVA; For each operating day under any typical scenario, the resistance of each branch of the distribution network in each time period of the corresponding operating day is multiplied by the square of the corresponding current, then multiplied by the electricity price of the corresponding time period, and summed to obtain the network loss cost for the corresponding operating day of the corresponding typical scenario; the annual network loss cost is obtained by multiplying the annual operating days of each typical scenario by the corresponding network loss cost, dividing by a predefined unit conversion factor, and summing; specifically expressed as: ; In the formula, The annual network loss cost is the cost incurred by all branches of the distribution network during operation due to current flowing through resistance. Active power loss The corresponding electricity cost; Represented by node The set of branches for the terminal node; The set of all branches (or lines) in the distribution network; in this embodiment, the total number of branches in the distribution network is 32; t is the time period index. The total number of time periods within the running cycle is 24 in this embodiment; k is the scene index; This represents the total number of typical scenarios; For scenario k, the annual operating days are the total number of operating days in the year. The electricity price for time period t is expressed in yuan / kWh; dividing by 10 in the formula represents the unit conversion factor from kVA to MVA. For each operating day under any typical scenario, the absolute value of the transmission power of each flexible interconnection switchgear installed in the distribution network during each time period of the corresponding operating day is multiplied by the loss coefficient, then multiplied by the electricity price of the corresponding time period, and summed to obtain the loss cost for the corresponding operating day under the corresponding typical scenario; the annual loss cost is obtained by multiplying the annual operating days of each typical scenario by the corresponding loss cost, dividing by a predefined unit conversion coefficient, and summing; specifically expressed as: ; In the formula, Annual loss cost refers to the power loss generated by the SOP equipment itself (such as VSC converter) during operation. This is the loss coefficient, with a value of 0.05; Let t be the transmission power of the s-th SOP device in time period t under typical scenario k, that is, the active power injected by the device into the access node to which it belongs, in MVA; dividing by 10 in the formula represents the unit conversion factor from kVA to MVA; For any flexible interconnected switchgear in any typical scenario, the change in distributed power output at each moment in the corresponding scenario is used as the denominator, and the change in transmission power of the corresponding device under the change in distributed power output is used as the numerator. The squares of the ratios of the numerator and denominator at each time point are summed to obtain the sensitivity coefficient of the corresponding flexible interconnected switchgear in the corresponding scenario. The sensitivity coefficient is multiplied by the probability of the corresponding scenario and summed to obtain the total sensitivity coefficient of all flexible interconnected switchgear in all scenarios. The total sensitivity coefficient is multiplied by a predefined risk cost coefficient to obtain the risk cost penalty term. The specific formula is as follows: ; In the formula, This is a risk cost penalty item, representing the risk cost arising from changes in the transmission power of SOP equipment due to variations in the output of distributed power sources. The risk cost coefficient represents the unit conversion factor corresponding to the change in the sensitivity coefficient, and the unit is yuan. Scenario probability represents the probability of this scenario occurring within a year; For the scene Next The change in transmission power of the s-th SOP device in time period is determined by substituting the change in output of distributed power sources in the corresponding time period into the power flow equation. Indicates in the scene Next The change in active power injected into the distribution network by distributed generation during a given period, i.e., the change in output of distributed generation. The optimization objective function is obtained by adding the fixed cost of SOP equipment installation, the operation and maintenance cost of SOP equipment, the annual network loss cost, the annual depreciation cost, and the risk cost penalty term; specifically expressed as: ; In the formula, To optimize the objective function, namely the total cost of the distribution network throughout its entire life cycle.
[0030] In this embodiment, the risk costs arising from changes in the transmission power of the SOP equipment due to variations in the output of distributed power sources include additional operating costs, maintenance costs, and equipment replacement costs. For example, high sensitivity means that the SOP equipment needs to frequently or significantly adjust its power to smooth out fluctuations in distributed power sources, which accelerates equipment aging and indirectly increases future maintenance and replacement costs. It also means that the node voltage of the distribution network is more likely to exceed limits under distributed power source fluctuations, requiring additional backup capacity or control measures, which directly increases operating costs. The risk cost coefficient in this embodiment is obtained by multiplying a predefined baseline cost by an empirically set coefficient.
[0031] S2. Establish the constraints of the distribution network mathematical model during the operating cycle. The constraints include: power flow constraints, operation safety constraints, distributed power output constraints, flexible interconnection switchgear operation constraints, and junction temperature constraints.
[0032] As a preferred implementation, the power flow constraints for the 32 branches and 33 nodes in this embodiment are established as follows: ; In the formula, Represented by node The set of branches for the terminal node; It is the collection of all branches (or lines) in the distribution network; For the node Flow to Node The active power; Let be the resistance of branch ij; Let be the current flowing through branch ij; For nodes Net injected power; For the node Flow to Node The active power; This represents the node. Connected adjacent nodes (i.e., downstream nodes); For nodes The set of branches adjacent to its neighboring nodes; For the node Flow to Node reactive power; The reactance of branch ij; For the node Flow to Node reactive power; , Let be the voltages at nodes i and j, respectively.
[0033] The operational safety constraints are: ; ; In the formula, express Time Node The voltage amplitude; This parameter represents the lower limit of the allowable deviation of the node voltage. In a specific embodiment, its value is taken as a per-unit value of 0.95. This parameter represents the upper limit of allowable deviation of the node voltage. In a specific embodiment, its value is taken as a per-unit value of 1.05. This represents the upper limit of the current amplitude that is allowed to flow through the branch.
[0034] As a preferred implementation method, distributed generation (DG) output constraints are established to accurately simulate the operating characteristics of wind turbines and photovoltaic power generation systems under different penetration rate scenarios. The specific constraint formulas are as follows:
[0035] In the formula, Indicates in Time-based access nodes The active power injected by the distributed power source; Access node for time period t The predicted value of the active power injected by the distributed generation; Indicates in Time-based access nodes The reactive power injected by the distributed power source; Indicates in The active power output of distributed power sources is predicted based on preset wind speed and solar radiation forecast data for a given time period. Indicates in Time period nodes The power factor angle of the distributed power source is specified in this embodiment. The distributed power source operates at a constant power factor or adjusts within a preset range according to the grid voltage regulation requirements. Indicates access node The upper limit of the rated installed capacity of distributed power sources, i.e., the upper limit of apparent power. In this embodiment, time-series prediction curves are used. The actual active power output of the DG is limited for each time period, and its operating state is ensured not to exceed the rated thermal stability capacity of the equipment through apparent power constraints. By introducing this constraint into the model, and in conjunction with the active and reactive power regulation capabilities of the flexible interconnection switch (SOP), it is possible to effectively absorb the fluctuations of distributed power sources, thereby maintaining the voltage stability of the distribution network under different penetration scenarios.
[0036] The SOP execution constraints are established as follows: ; In the formula, the first term is the active power balance constraint; for Time-of-use flexible interconnection switch (SOP) injection node The active power; for Time period and node Active power losses generated by interconnected flexible switch (SOP) converters (VSC); The second item is the active power loss constraint; For nodes Loss factor of connected flexible interconnected switch (SOP) converters (VSC); The third item is the upper and lower limits constraint of reactive power; , These are the minimum and maximum values of reactive power, respectively. The fourth item is the capacity constraint; Injecting nodes for flexible interconnected switches (SOPs) The rated capacity of the side converter (VSC) is the apparent power limit; The fifth item is the SOP (Standard Operating Procedure) equipment installation constraints. The binary decision variable representing the w-th SOP candidate installation location is denoted as a 0 / 1 variable, where 0 indicates that the SOP equipment is not installed at the corresponding location, and 1 indicates that it is installed. This represents the total number of candidate installation locations. This represents the total number of SOP devices installed in the distribution network; in this embodiment, it is taken as 3. The sixth item is the SOP equipment capacity-related constraint; when When, the constraint becomes This mandates that the SOP equipment capacity at that location be 0; when When, the constraint becomes This means that the minimum configuration capacity of the SOP must be adjusted according to the new energy penetration rate in scenario k. Increased with the increase; The minimum configuration capacity of the SOP device is 0.1 MVA in this embodiment; The baseline configuration capacity for SOP equipment is set by those skilled in the art based on experience; The maximum configuration capacity of the SOP device is 1.5 MVA in this embodiment.
[0037] As a preferred embodiment, the junction temperature constraint of the flexible interconnection switchgear includes: junction temperature safety constraint and aging loss constraint; specifically: To account for the impact of operating power on the lifespan of the insulated-gate bipolar transistors (IGBTs) inside the converter of flexible interconnected switchgear, a dynamic equation for junction temperature based on a first-order RC equivalent thermal circuit model is established. Based on the ambient temperature, active power loss, and equivalent thermal resistance of the flexible interconnected switchgear at different times, the junction temperature of the flexible interconnected switchgear is calculated for different time periods. The specific junction temperature calculation formula is as follows: ; In the formula, express Time-based access nodes The junction temperature of the IGBTs inside the SOP equipment; express The ambient temperature over a period of time is an external input parameter that changes over time. express Active power loss of SOP equipment connected to node i during time period; It represents the equivalent thermal resistance of the SOP equipment converter, reflecting the resistance to heat dissipation from the junction region to the environment; It represents the thermal time constant, reflecting the inertia of temperature changes in the equipment; The duration of each time period; Under any operating scenario, the junction temperature safety constraint, i.e., the real-time junction temperature of the SOP device, must meet the requirement that the junction temperature of the flexible interconnect switchgear in each time period does not exceed the predefined maximum junction temperature threshold; specifically: ; In the formula, This indicates the maximum junction temperature threshold that the IGBT can operate at, usually 125°C or 150°C. It allows SOP devices to be moderately overloaded in low ambient temperatures or for short periods of time, but will automatically reduce operating power in high-temperature environments to protect the hardware from burning out. To ensure the asset value of the Standard Operating Procedure (SOP) over its 20-year lifespan, an aging loss constraint based on junction temperature is introduced: For any given time period, the junction temperature of the flexible interconnection switchgear during that period is used as the numerator, the predefined highest junction temperature threshold is used as the denominator, the ratio of the numerator to the denominator is used as the base, and the predefined lifespan index of the flexible interconnection switchgear is used as the exponent to obtain the loss amplification factor of the equipment's temperature rise. The time length of the corresponding period is multiplied by the loss amplification factor, divided by the lifespan of the flexible interconnection switchgear, and then summed to obtain the daily aging loss factor of the equipment. A predefined maximum allowable lifespan loss quota is used, and the aging loss constraint is that the daily aging loss factor does not exceed the maximum allowable lifespan loss quota. Specifically, this is expressed as follows: ; In the formula, The lifespan index of the equipment is determined by the materials of the core components of the SOP equipment; 365 represents the number of days in a year and is used to convert the lifespan of the SOP equipment into time periods. This indicates the maximum allowable lifespan loss quota per day; this constraint ensures that the SOP will not be prematurely damaged due to frequent high-temperature operation when new energy sources fluctuate drastically.
[0038] S3. Transform the power flow constraints and the operation constraints of the flexible interconnected switchgear into a standard second-order cone form, and transform the constructed distribution network mathematical model into a mixed-integer second-order cone programming model; use an optimization solver to solve the model to obtain the location scheme and capacity scheme of the flexible interconnected switchgear.
[0039] As a preferred implementation method, the second-order cone relaxation (SOCR) technique is used to solve the constructed distribution network mathematical model. The specific process is as follows: Non-convex nonlinear constraints (such as power flow constraints and SOP capacity constraints) are transformed into standard second-order cone forms, specifically as follows: Will Transform into ; Will Transform into ; Will Transform into ; The junction temperature dynamic equation Transform into a linear difference equation ; After transformation, the mathematical model of the distribution network becomes a mixed-integer second-order cone programming (MISOCP) problem. The CPLEX solver is then used to solve it, yielding the SOP (Standard Operating Procedure) equipment location scheme and SOP equipment capacity scheme. .
[0040] This embodiment selects Figure 3 The IEEE 33-node system shown is a distribution network to be planned. The system has a base voltage of 12.66 kV, 32 branches, a total active load of 3715 kW, and a reactive load of 2300 kVar. Photovoltaic generators (PV) are installed at nodes 7, 13, and 27, and wind turbines (WT) are installed at nodes 10, 16, 17, 30, and 33. Five SOP candidate installation locations (i.e., flexible interconnection switch locations) are set: TS1 (12-22), TS2 (25-29), TS3 (8-21), TS4 (9-15), and TS5 (18-33). Three potential renewable energy access capacity scenarios are set: 30%, 60%, and 90% penetration rate scenarios. A 24-hour normalized wind and solar power output and load curve is generated for each scenario. Taking the 90% penetration rate scenario as an example, its time-series curve is as follows: Figure 4 As shown.
[0041] In three scenarios of 30%, 60%, and 90%, the MISOCP model was programmed using the MATLAB platform and the YALMIP toolkit, and then solved using the CPLEX solver.
[0042] In this embodiment, the solution result for the 30% penetration scenario is as follows: The optimal addresses are (12-22), (25-29), and (18-33); The optimal capacities are: 0.400 MVA (position 1, i.e., TS1), 0.401 MVA (position 2, i.e., TS2), and 0.400 MVA (position 5, i.e., TS5). The cost breakdown is as follows: fixed installation cost of RMB 131,600, operation and maintenance cost of RMB 36,000, annual network loss cost of RMB 303,700, annual SOP loss cost of RMB 127,400, and risk cost penalty of RMB 21,300. The total cost is RMB 620,000. Voltage fluctuations are suppressed. Under low penetration rates, the impact of distributed power source fluctuations on the power grid is relatively small. The SOP adjustment sensitivity is low, so the risk cost accounts for a small proportion.
[0043] The solution for the 60% penetration rate scenario is as follows: The optimal addresses are (12-22), (25-29), and (18-33); The optimal capacity is 0.700 MVA (all locations); The cost breakdown is as follows: fixed installation cost of RMB 230,200, operation and maintenance cost of RMB 63,000, annual network loss cost of RMB 227,100, annual SOP loss cost of RMB 106,500, and risk cost penalty item of RMB 73,400; The total cost is 700,200 yuan. The voltage stability is further improved compared to the 30% scenario. The system's demand for SOP adjustment is increased, and the risk cost rises accordingly.
[0044] The solution for the 90% penetration scenario is as follows: The optimal addresses are (12-22), (25-29), and (18-33); The optimal capacity is 1.000 MVA (all locations); The cost breakdown is as follows: fixed installation cost of RMB 328,600, operation and maintenance cost of RMB 90,000, annual network loss cost of RMB 173,100, annual SOP loss cost of RMB 90,700, and risk cost penalty item of RMB 135,000; Total cost: RMB 817,400. Under extreme conditions of high penetration, risk costs increase significantly.
[0045] Because the mathematical model of the distribution network takes into account life constraints, even if the SOP faces high fluctuation risks, its output is still limited to the safe range of junction temperature, effectively balancing operating efficiency and equipment life.
[0046] like Figure 5 As shown, even at a high permeability of 90%, the system voltage remains stable, verifying the effectiveness of this method. By comparing the voltage distribution under different permeability levels (e.g., ... Figure 5After installing the SOP (Standard Operating Procedure) equipment, the system voltage distribution became more stable, verifying the effectiveness of the SOP in improving the performance of the distribution network. The optimal installation location of the SOP remained consistent under different penetration rates (12-22, 25-29, and 18-33), indicating the robustness of the site selection results. As the penetration rate increased, the optimal configuration capacity of the SOP (from 0.4MVA to 1.0MVA) and the total cost (from 620,000 to 817,400) both gradually increased, but the annual network loss cost (from 303,700 to 173,100) decreased significantly.
[0047] Based on this result, the present invention constructs the capacity in one go according to the long-term capacity (e.g., 100% penetration rate, with a capacity of 1.1 MVA) in the early planning stage (e.g., when the penetration rate is 30%). Although the short-term fixed installation cost is high, from the perspective of the whole life cycle, it can effectively avoid the repeated construction and equipment replacement costs caused by multi-stage expansion, and the long-term operation is more economical.
[0048] Example 2 Embodiment 2 of the present invention provides a location and capacity determination system for medium-voltage flexible interconnection switches in a distribution network, comprising: An optimization objective function construction module is used to build a mathematical model of the distribution network with multiple candidate installation locations for flexible interconnected switchgear. With the goal of minimizing the total lifecycle cost of the distribution network, the objective function of the mathematical model is constructed, considering the fixed installation cost, operation and maintenance cost, annual network loss cost, annual loss cost, and risk cost penalty term of the flexible interconnected switchgear. The risk cost penalty term is calculated based on the impact of distributed power generation output changes on the transmission power of the flexible interconnected switchgear. The constraint setting module establishes the constraint conditions of the distribution network mathematical model during the operating cycle. The constraint conditions include: power flow constraints, operation safety constraints, distributed generation output constraints, flexible interconnection switchgear operation constraints, and junction temperature constraints. The site selection and capacity determination module transforms power flow constraints and flexible interconnected switchgear operation constraints into standard second-order cone forms, and converts the constructed distribution network mathematical model into a mixed-integer second-order cone programming model. An optimization solver is used to solve the model to obtain the site selection and capacity determination schemes for the flexible interconnected switchgear.
[0049] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.
[0050] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.
[0051] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.
[0052] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.
[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.
Claims
1. A method for site selection and capacity determination of medium-voltage flexible interconnection switches in a distribution network, characterized in that, include: A mathematical model of a distribution network with multiple candidate installation locations for flexible interconnected switchgear is constructed. With the goal of minimizing the total lifecycle cost of the distribution network, the model considers the fixed installation cost, operation and maintenance cost, annual network loss cost, annual loss cost, and risk cost penalty term of the flexible interconnected switchgear. The risk cost penalty term is calculated based on the impact of distributed power generation output changes on the transmission power of the flexible interconnected switchgear. Establish constraints for the mathematical model of the distribution network during its operating cycle. These constraints include: power flow constraints, operational safety constraints, distributed generation output constraints, flexible interconnection switchgear operation constraints, and junction temperature constraints. The power flow constraints and the operating constraints of the flexible interconnected switchgear are transformed into standard second-order cone forms, and the constructed distribution network mathematical model is transformed into a mixed integer second-order cone programming model. An optimization solver is used to solve the model to obtain the location scheme and capacity scheme of the flexible interconnected switchgear.
2. The method for site selection and capacity determination of a medium-voltage flexible interconnection switch in a distribution network according to claim 1, characterized in that: The specific calculation process for the fixed installation cost of flexible interconnection switchgear is as follows: Based on the service life of the flexible interconnection switchgear and the predefined cost-return rate, the cost-return coefficient of the flexible interconnection switchgear during its service life is calculated; the fixed cost per unit capacity of the flexible interconnection switchgear is multiplied by the cost-return coefficient and the rated capacity of all flexible interconnection switchgear in the distribution network, and then divided by the predefined unit conversion coefficient to obtain the fixed installation cost of the flexible interconnection switchgear.
3. The method for site selection and capacity determination of a medium-voltage flexible interconnection switch in a distribution network according to claim 1, characterized in that: The specific calculation process for the operation and maintenance costs is as follows: The operation and maintenance cost of the flexible interconnected switchgear is obtained by multiplying the fixed cost per unit capacity of the flexible interconnected switchgear by a predefined operation and maintenance cost coefficient and the rated capacity of all flexible interconnected switchgear in the distribution network, and then dividing by a predefined unit conversion coefficient.
4. The method for site selection and capacity determination of a medium-voltage flexible interconnection switch in a distribution network according to claim 1, characterized in that: The specific calculation process for the annual network loss cost is as follows: For each operating day under any typical scenario, the resistance of each branch of the distribution network in each time period of the corresponding operating day is multiplied by the square of the corresponding current, then multiplied by the electricity price of the corresponding time period and summed to obtain the network loss cost for the corresponding operating day of the corresponding typical scenario; the annual operating days of each typical scenario are multiplied by the corresponding network loss cost, then divided by a predefined unit conversion factor and summed to obtain the annual network loss cost.
5. The method for site selection and capacity determination of a medium-voltage flexible interconnection switch in a distribution network according to claim 1, characterized in that: The specific calculation process for the annual depreciation cost is as follows: For each operating day under any typical scenario, the absolute value of the transmission power of each flexible interconnection switch installed in the distribution network during each time period of the corresponding operating day is multiplied by the loss coefficient, then multiplied by the electricity price of the corresponding time period and accumulated to obtain the loss cost for the corresponding operating day of the corresponding typical scenario; the annual operating days of each typical scenario are multiplied by the corresponding loss cost, then divided by the predefined unit conversion coefficient and accumulated to obtain the annual loss cost.
6. The method for site selection and capacity determination of a medium-voltage flexible interconnection switch in a distribution network according to claim 1, characterized in that: The specific calculation process for the risk cost penalty item is as follows: For any flexible interconnected switchgear in any typical scenario, the change in distributed power output at each moment in the corresponding scenario is used as the denominator, and the change in transmission power of the corresponding device under the change in distributed power output is used as the numerator. The squares of the ratio of the numerator to the denominator at each time period are summed to obtain the sensitivity coefficient of the corresponding flexible interconnected switchgear in the corresponding scenario. The sensitivity coefficient is multiplied by the probability of the corresponding scenario and summed to obtain the total sensitivity coefficient of all flexible interconnected switchgear in all scenarios. The total sensitivity coefficient is multiplied by a predefined risk cost coefficient to obtain the risk cost penalty term.
7. The method for site selection and capacity determination of a medium-voltage flexible interconnection switch in a distribution network according to claim 1, characterized in that: The operational constraints of the flexible interconnection switchgear include active power balance constraints, active power loss constraints, reactive power upper and lower limit constraints, capacity constraints, equipment installation constraints, and equipment capacity correlation constraints. The junction temperature constraints of the flexible interconnection switchgear include: junction temperature safety constraints and aging loss constraints; wherein, the junction temperature of the flexible interconnection switchgear is calculated based on the constructed junction temperature dynamic equation by substituting the ambient temperature at different time periods, the active power loss of the flexible interconnection switchgear, and the equivalent thermal resistance.
8. The method for site selection and capacity determination of a medium-voltage flexible interconnection switch in a distribution network according to claim 7, characterized in that: The equipment capacity association constraint for any candidate installation location satisfies: When no flexible interconnection switchgear is installed at the corresponding candidate installation location, the equipment capacity at the corresponding location is 0; When flexible interconnected switchgear is installed at the corresponding candidate installation location, the lower limit of the equipment capacity at the corresponding location is the product of the predefined minimum configuration capacity and the new energy penetration rate and the predefined baseline configuration capacity under different scenarios, and the upper limit of the equipment capacity at the corresponding location is the predefined maximum configuration capacity.
9. The method for site selection and capacity determination of a medium-voltage flexible interconnection switch in a distribution network according to claim 7, characterized in that: The junction temperature safety constraint is that the real-time junction temperature of the flexible interconnect switchgear must not exceed the predefined maximum junction temperature threshold in each time period. The aging loss constraint is that the daily aging loss factor shall not exceed the maximum allowable lifespan loss quota for a single day; wherein, the calculation process of the daily aging loss factor is as follows: For any given time period, the junction temperature of the flexible interconnected switchgear during that time period is used as the numerator, the predefined maximum junction temperature threshold is used as the denominator, the ratio of the numerator to the denominator is used as the base, and the predefined lifespan index of the flexible interconnected switchgear is used as the exponent to obtain the loss amplification factor of the equipment temperature rise. The time length of the corresponding period is multiplied by the loss amplification factor, divided by the lifespan of the flexible interconnected switchgear, and then summed to obtain the daily aging loss factor of the equipment.
10. A location and capacity determination system for medium-voltage flexible interconnection switches in a distribution network, using the method described in any one of claims 1-9, characterized in that, include: An optimization objective function construction module is used to construct a distribution network mathematical model containing multiple candidate installation locations for flexible interconnected switchgear. With the goal of minimizing the total lifecycle cost of the distribution network, the objective function of the distribution network mathematical model is constructed, considering the fixed installation cost, operation and maintenance cost, annual network loss cost, annual loss cost, and risk cost penalty term of the flexible interconnected switchgear. The risk cost penalty term is calculated based on the impact of distributed power generation output changes on the transmission power of the flexible interconnected switchgear. The constraint setting module establishes the constraint conditions of the distribution network mathematical model during the operating cycle. The constraint conditions include: power flow constraints, operation safety constraints, distributed generation output constraints, flexible interconnection switchgear operation constraints, and junction temperature constraints. The site selection and capacity determination module transforms power flow constraints and flexible interconnected switchgear operation constraints into standard second-order cone forms, and converts the constructed distribution network mathematical model into a mixed-integer second-order cone programming model. An optimization solver is used to solve the model to obtain the site selection and capacity determination schemes for the flexible interconnected switchgear.
11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.
12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.