Optimal configuration method of grid-forming energy storage considering photovoltaic support

Abstract

The present application belongs to the technical field of power system energy storage planning, and specifically discloses a network-constructing type energy storage optimal configuration method considering photovoltaic support, obtains power distribution network data and identifies fault scenarios, calculates the reactive power-voltage sensitivity of photovoltaic nodes to key nodes to quantify the effective degree of voltage support; calculates the effective reactive power support amount of photovoltaic and performs reliability evaluation, simultaneously establishes a frequency and voltage support model to obtain energy storage demand; establishes an active / reactive power coupling safety margin model of energy storage converter to quantify the energy storage capacity released by photovoltaic support; establishes an optimal configuration model with the minimum annual total cost as the target, and obtains an energy storage configuration scheme by iterative solution. The present application quantifies the photovoltaic transient support capability as the energy storage capacity release amount, which effectively reduces the energy storage configuration cost while ensuring transient safety.

Description

Technical Field

[0001] This invention belongs to the field of power system energy storage planning technology, specifically relating to a method for optimizing the configuration of grid-type energy storage that takes into account photovoltaic support. Background Technology

[0002] With the widespread integration of distributed photovoltaic (PV) systems, electric vehicles, and various power electronic devices into distribution networks, the operational mode of these networks is shifting from traditional unidirectional power receiving networks to highly coupled active distribution systems with high-level source-load-storage integration. For distribution networks connected to the upper-level grid via weak tie lines, when a tie line is broken due to a fault, the local distribution network rapidly switches to islanded operation. The system loses the inertia and voltage support of the main grid, potentially leading to frequency drops, voltage sags, or even instability. Grid-based energy storage, capable of autonomously establishing voltage and frequency references through virtual synchronous machine control, is a crucial means of addressing transient stability issues after islanding switching.

[0003] Existing energy storage optimization methods typically focus on economic operation during grid connection, distributed photovoltaic (PV) integration, or steady-state voltage constraints. Some studies consider transient voltage support in energy storage configuration, ensuring voltage safety after faults through transient voltage amplitude and recovery time constraints. Other studies employ an iterative solution approach of "master optimization - transient verification - cutting plane feedback," verifying the feasibility of candidate solutions through scenario-by-scenario transient verification. Regarding PV utilization, existing methods usually set apparent power constraints on PV inverters, incorporating them as adjustable resources into the optimization model.

[0004] However, existing technologies still have the following shortcomings: they do not take the frequency change rate after the tie line is disconnected, the lowest frequency point, the voltage recovery time, the transient end state of charge, and the islanding continuous operation capability as unified capacity constraints; they have not established a time-series coordination mechanism of "grid-based energy storage construction - photovoltaic switching to transient auxiliary support - photovoltaic support releasing energy storage active power margin"; they have not formed key quantitative indicators such as the effective reactive power support of photovoltaics, the safety margin of energy storage active / reactive power coupling, and the release of energy storage capacity for capacity planning; and they lack quantification of photovoltaic support availability, response delay, support saturation, and differences in node voltage sensitivity, making "taking photovoltaic auxiliary support" easily degenerate into general active / reactive power constraints. Summary of the Invention

[0005] The purpose of this invention is to solve the problem that existing grid-type energy storage configuration schemes cannot meet the requirements of transient safety and economy, and to propose an optimized configuration method for grid-type energy storage that takes into account photovoltaic support.

[0006] The technical solution of this invention is as follows: This invention provides a method for optimizing the configuration of grid-based energy storage that takes into account photovoltaic support, including: Step 1: Obtain basic data of the distribution network and a set of fault scenarios for weak tie lines. Identify the island range for each tie line fault scenario, and select a set of key nodes and a set of photovoltaic candidate supports. Calculate the reactive power-voltage sensitivity of each photovoltaic node to the key nodes, obtain the voltage support effectiveness of each photovoltaic node, and construct a set of uncertain scenarios for photovoltaic transient auxiliary support. Step 2: Establish an energy storage economic dispatch model for the grid-connected operation phase, solve for the state parameters before each fault occurs, and use them as the initial state for transient calculation of tie-line faults; establish a timing switching model and a photovoltaic transient auxiliary support state model after the tie-line is disconnected; calculate the photovoltaic effective reactive power support based on the voltage support effectiveness, the apparent capacity constraint of the photovoltaic inverter, and the uncertain scenario set; evaluate the credibility of the photovoltaic effective reactive power support to obtain the lower bound of the photovoltaic effective support that meets the given confidence level; establish a grid-type energy storage transient frequency support model and a transient voltage recovery model to obtain the energy storage active power support requirements that meet frequency security and the system reactive power support requirements that meet voltage security, respectively. Step 3: Establish an active / reactive power coupling safety margin model for the energy storage converter. Unify the active power support demand of the energy storage, the reactive power support demand of the system, and the apparent capacity constraint of the energy storage converter into the transient feasible region, and calculate the coupling safety margin of the energy storage converter. Based on the reduced reactive power support of the photovoltaic system and the reduced reactive power output demand of the energy storage, calculate the active power margin that the energy storage can additionally use for frequency support under the apparent capacity constraint of the energy storage converter, and convert the active power margin into the capacity release of the rated power and rated energy of the energy storage. Step 4: With the goal of minimizing the annualized total cost of grid-based energy storage, establish an energy storage optimization configuration model based on the effective support lower bound of photovoltaics, the capacity release, the active power support requirement of energy storage, the reactive power support requirement of the system, and the coupling safety margin. Solve the energy storage optimization configuration model using an iterative solution method to obtain the final energy storage configuration scheme.

[0007] The beneficial effects of this invention are: 1. The grid-based energy storage optimization configuration method of the present invention, which considers photovoltaic (PV) support, establishes a PV effective reactive power support model and incorporates node voltage sensitivity, inverter apparent capacity margin, response delay, communication availability, low-voltage ride-through state, and support saturation into the calculation to obtain a lower bound of PV effective support that can be used for energy storage capacity planning. Compared with only considering the adjustable range of PV reactive power, the present invention can more accurately quantify the true contribution of PV to the voltage recovery of critical nodes during fault transient phases. The established active / reactive power coupling safety margin model of the energy storage converter unifies the energy storage active power frequency regulation demand, energy storage reactive power voltage regulation demand, PV effective reactive power support, and energy storage converter apparent capacity constraints into the same transient feasible domain. This model can directly determine whether grid-based energy storage experiences apparent capacity saturation during fault transient phases due to simultaneous output of active and reactive power, avoiding insufficient transient support capacity caused by configuring only based on active power or steady-state capacity.

[0008] 2. The grid-type energy storage optimization configuration method of the present invention, which takes into account photovoltaic support, reduces the reactive power output demand of energy storage through effective reactive power support of photovoltaics, calculates the active power margin that energy storage can additionally use for frequency support under apparent capacity constraints, and converts it into the capacity release amount of rated power and rated energy of energy storage, so that "photovoltaic auxiliary support" directly serves energy storage capacity planning, rather than just staying at the level of photovoltaic participation in voltage regulation. Attached Figure Description

[0009] Figure 1 The diagram shows a power distribution network with weak interconnections. Figure 2 The diagram shows the transient reactive power-voltage support characteristics of a photovoltaic inverter. Figure 3 The flowchart shown is a method for optimizing the configuration of grid-type energy storage that takes into account photovoltaic support. Detailed Implementation

[0010] Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the drawings are merely exemplary and are intended to illustrate the principles and spirit of the invention, and are not intended to limit the scope of the invention.

[0011] This invention provides a method for optimizing the configuration of grid-based energy storage that takes into account photovoltaic (PV) support. The core of this method lies in constructing a calculation process during the capacity planning stage: "fault triggering - grid-based energy storage network construction - PV inverter follow-up support - active / reactive power coupling margin verification - PV support reliability verification - capacity iterative correction." This process determines the grid-based energy storage's access location, rated active power, rated energy capacity, inverter rated apparent capacity, transient support reserved power, transient support reserved energy, and optional PV transient support control parameters. This enables the distribution network to quickly complete frequency and voltage support after a tie-line fault, and reduces energy storage configuration costs while ensuring transient safety and the sustainability of subsequent islanded operation.

[0012] The method of this invention is applicable to distribution network systems containing distributed photovoltaic power, grid-connected energy storage, various types of loads, and weak interconnections. Please refer to [link / reference]. Figure 1 and Figure 2 , Figure 1 The diagram shown is of a power distribution network containing weak interconnections. Figure 2 The diagram shown illustrates the transient reactive power-voltage support characteristics of a photovoltaic inverter. Figure 2 The horizontal axis represents the photovoltaic (PV) node voltage, and the vertical axis represents the reactive power output of the PV inverter, with reactive power injection into the distribution network being positive. The PV inverter outputs maximum reactive power when the node voltage is not higher than V1; when the node voltage is between V1 and V... ref Between these points, the reactive power output decreases linearly with increasing voltage according to the droop characteristic, and at V... ref The value is zero at the node; when the node voltage is at V ref Between V2 and V2, the inverter gradually transitions from zero reactive power to reactive power absorption; when the node voltage is not lower than V2, the reactive power output remains at the maximum negative reactive power. This characteristic enables the photovoltaic inverter to provide reactive power support at low voltages and absorb reactive power at high voltages, while limiting its output amplitude through apparent capacity constraints.

[0013] The method of this invention can be implemented by a computer program. The inputs are the distribution network topology, line impedance, node load, photovoltaic access node, photovoltaic capacity, energy storage candidate access location, time-of-use tariff, energy storage cost, photovoltaic inverter control parameters, grid-type energy storage control parameters, tie line fault scenarios and transient safety thresholds. The outputs are the rated active power, rated energy capacity, inverter rated apparent capacity, transient support reserved power, support reserved energy and optional photovoltaic support parameters of the grid-type energy storage.

[0014] Please see Figure 3 , Figure 3 The flowchart shown is a method for optimizing the configuration of grid-based energy storage that takes into account photovoltaic support. Figure 3 As shown, the grid-type energy storage optimization configuration method considering photovoltaic support according to an embodiment of the present invention includes the following steps: Step 1: Obtain basic data of the distribution network and a set of fault scenarios for weak tie lines. Identify the island range for each tie line fault scenario, and select a set of key nodes and a set of photovoltaic candidate supports. Calculate the reactive power-voltage sensitivity of each photovoltaic node to the key nodes, obtain the voltage support effectiveness of each photovoltaic node, and construct a set of uncertain scenarios for photovoltaic transient auxiliary support.

[0015] In this embodiment, the basic data of the distribution network includes equipment parameters and control parameters. For example, it includes distribution network topology, line impedance, node load, photovoltaic access nodes and capacity, candidate energy storage access locations, time-of-use tariffs, energy storage costs, photovoltaic inverter control parameters, and grid-based energy storage control parameters. Based on the basic data of the distribution network, a network model, a load model, a photovoltaic inverter model, a grid-based energy storage candidate configuration model, and a set of weak tie-line fault scenarios are formed.

[0016] In this embodiment, for each tie-line fault scenario, the distribution network topology is updated based on the set of disconnected lines after the fault, the island range formed after the fault is identified, and the set of key nodes is determined based on the load importance level, the degree of node voltage exceeding the limit, reactive power voltage sensitivity, and electrical distance.

[0017] Specifically, for the first In a single tie-line fault scenario, the distribution network topology is updated based on the set of disconnected lines after the fault, and the extent of islanding formed after the fault is identified. For each node within the islanded area, the set of critical nodes is determined based on load importance level, node voltage exceedance degree, reactive power and voltage sensitivity, and electrical distance. .

[0018] In this embodiment, key nodes can be identified comprehensively through the following indicators: ; In the formula, For nodes Key indicators of degree As a load importance level indicator, For nodes Electrical distance metrics between candidate nodes of grid-type energy storage This is an indicator of node voltage exceeding limits risk. This is a sensitivity indicator of node voltage to reactive power support. , , , For weighting coefficients. When When the value exceeds the set threshold, the node will be... It was identified as a key node.

[0019] In this embodiment, the reactive power-voltage sensitivity of each photovoltaic node to the key node is calculated to obtain the voltage support effectiveness of each photovoltaic node. This specifically includes the following steps: S11: For the first The photovoltaic node and the first For each key node, the reactive power-voltage sensitivity is calculated based on the power flow Jacobian matrix as follows: ; in, For the first Voltage amplitude at key nodes, For the first Reactive power injection of each photovoltaic node.

[0020] S12: Normalize all photovoltaic nodes within the island range to obtain the first... The photovoltaic node for the first The relative voltage support effectiveness of each key node is as follows: ; in, Indicates the first The photovoltaic node for the first The relative voltage support effectiveness of key nodes This is a candidate support set for photovoltaics.

[0021] S13: For multiple key nodes, a weighted sum is calculated based on the importance weight of each key node to obtain the [number of nodes]. Voltage support effectiveness of individual photovoltaic nodes: ; in, For the set of key nodes, For the first The importance weight of each key node.

[0022] In this embodiment, the set of uncertain scenarios for photovoltaic transient auxiliary support includes: photovoltaic output uncertainty, photovoltaic inverter capacity margin uncertainty, communication / detection delay uncertainty, low voltage ride-through state, support unavailability state caused by partial shading, and photovoltaic support saturation state.

[0023] Specifically, there are uncertainties in photovoltaic (PV) active power output, meaning that the actual PV output at the time of the fault is affected by sunlight and temperature; uncertainties in PV inverter capacity margin, meaning that the proportion of PV inverter already used for active power output at the time of the fault determines the remaining reactive capacity; uncertainties in communication / detection delay, meaning the delay from the occurrence of the fault to the PV detecting the islanding signal; uncertainties in low voltage ride-through state, meaning whether PV enters low voltage ride-through mode due to voltage drop, thus limiting output; uncertainties in support unavailability state caused by partial shading, meaning that some PV cannot output normally due to shading; and uncertainties in PV support saturation state, meaning whether the PV inverter has reached its apparent capacity limit.

[0024] Step 2: Establish an energy storage economic dispatch model for grid-connected operation, solve for the state parameters before each fault occurs, and use them as the initial state for transient calculation of tie-line faults; establish a time-series switching model and a photovoltaic transient auxiliary support state model after the tie-line is disconnected; calculate the photovoltaic effective reactive power support based on the voltage support effectiveness, the apparent capacity constraint of the photovoltaic inverter, and the uncertain scenario set; evaluate the credibility of the photovoltaic effective reactive power support to obtain the lower bound of the photovoltaic effective support that meets the given confidence level; establish a grid-type energy storage transient frequency support model and a transient voltage recovery model to obtain the energy storage active power support requirements that meet frequency security and the system reactive power support requirements that meet voltage security, respectively.

[0025] In this embodiment, the state parameters at the moment before each fault occurs are solved, including: energy storage state of charge, energy storage active / reactive power output, photovoltaic active power output, node voltage, and line power flow.

[0026] In this embodiment, the timing switching model after the tie line is disconnected is as follows: after the tie line trips, the grid-type energy storage first establishes a local frequency and voltage reference; after the photovoltaic inverter detects the islanding support signal and completes synchronization, it switches from maximum power point tracking control to transient auxiliary support mode.

[0027] In this embodiment, the photovoltaic transient auxiliary support state model includes six states that proceed sequentially: normal grid-connected state, islanding detection state, synchronization waiting state, transient support state, support saturation state, and support withdrawal state. Specifically, in the normal grid-connected state, the photovoltaic inverter operates under maximum power point tracking control; in the islanding detection state, the photovoltaic inverter detects a disconnection signal on the tie line and maintains this for a first preset time delay; in the synchronization waiting state, the photovoltaic inverter synchronizes with the reference voltage and frequency established by the grid-connected energy storage and maintains this for a second preset time delay; in the transient support state, the photovoltaic inverter outputs reactive power and limits the rate of change of active power according to reactive power-voltage droop control; in the support saturation state, the photovoltaic inverter limits reactive power and / or active power output when it reaches its apparent capacity limit; in the support withdrawal state, the photovoltaic inverter gradually withdraws from support and returns to normal control after the voltage recovers above the threshold.

[0028] It should be noted that different states correspond to different reactive power support commands, active power ramping limits, and support durations.

[0029] In this embodiment, the photovoltaic reactive power output is jointly determined by the node voltage deviation, voltage support effectiveness, inverter apparent capacity margin, support response delay, and communication availability, and is converted into an effective reactive power support amount for key voltage nodes.

[0030] Specifically, the effective reactive power support of photovoltaics is calculated based on the voltage support validity, the apparent capacity constraint of the photovoltaic inverter, and the uncertain scenario set. The reliability of the effective reactive power support of photovoltaics is then assessed to obtain the lower bound of the effective reactive power support that meets a given confidence level. This includes the following steps: S21: The reactive power output of the photovoltaic inverter during the transient period is calculated using the reactive power-voltage droop control method as follows: ; in, This refers to the reactive power output of a single photovoltaic inverter during the transient period. This refers to the reactive power-voltage droop factor of photovoltaic systems. for After the timeline failure Voltage of the photovoltaic access node under a transient step size This is the voltage reference value for the photovoltaic inverter.

[0031] S22: The active and reactive power output of the photovoltaic system satisfies the apparent capacity constraint of the photovoltaic inverter as follows: ; In the formula, This refers to the rated apparent power capacity of the photovoltaic inverter. This refers to the active power output of a single photovoltaic inverter during the transient period; photovoltaics can participate in transient voltage support without exceeding the equipment capacity, and reduce the impact of their active power disturbances on the system frequency.

[0032] S23: Based on the voltage support effectiveness, the apparent capacity constraint of the photovoltaic inverter, and the communication / detection availability determined based on the uncertain scenario set, the effective reactive power support of photovoltaics to key nodes within the islanded area is calculated as follows: ; In the formula, This represents the effective reactive power support for photovoltaic systems. For photovoltaic candidate support set, This refers to the reactive power output of a single photovoltaic inverter during the transient period.

[0033] S24: Conduct a credibility assessment of the effective reactive power support of photovoltaic power, using either robust constraint or chance constraint methods. Using the effective lower bound of photovoltaic (PV) support in the calculation of energy storage capacity, the effective lower bound of PV support is obtained. The calculation process is expressed as follows: ; in, This is the lower bound of the effective support for photovoltaics obtained after the credibility assessment. For uncertainties in photovoltaic output, latency, communication status, and support availability, For the first An uncertain set under a faulty connection scenario To allow for failure probability.

[0034] Optionally, a photovoltaic active power transient smoothing model can be established to ensure that the rate of change of photovoltaic active power does not exceed a set threshold within a preset time window after the tie line is disconnected, thereby reducing frequency disturbances caused by sudden changes in photovoltaic active power.

[0035] In this embodiment, a transient frequency support model and a transient voltage recovery model for grid-type energy storage are established to obtain the active power support requirements for energy storage to meet frequency security and the reactive power support requirements for the system to meet voltage security, respectively. This includes the following steps: S31: Establish a transient frequency support model for grid-type energy storage, use the equivalent frequency equation of virtual synchronous machine to calculate the frequency dynamics after the fault, and obtain the active power support requirements of energy storage to meet the frequency security requirements; the frequency dynamics include: frequency change rate, frequency minimum point, quasi-steady-state frequency deviation and frequency recovery time.

[0036] In this embodiment, after the grid-type energy storage adopts virtual synchronous machine control, the system frequency dynamics can be described by the equivalent frequency equation. At the initial moment of the fault, the primary frequency regulation has not yet fully activated, and the system frequency change rate is mainly determined by inertia. When the system enters the primary frequency regulation-dominated stage, the quasi-steady-state frequency deviation is determined by the equivalent power deficit and the frequency regulation coefficient.

[0037] Specifically, S31 includes: S311: The system frequency dynamics are described using the equivalent frequency equation of a virtual synchronous machine. ; In the formula, For frequency deviation, The virtual inertia time constant, This is the system's baseline capacity; The damping coefficient is... As the reference frequency, This refers to the actual active power output of the energy storage AC side during the transient phase. Active power output of photovoltaic power during the transient phase. This represents the total active power of the load during the transient phase. This refers to the total active power loss during the transient phase.

[0038] S312: The rate of frequency change at the initial moment of the fault is determined by inertia support: ; In the formula, This refers to the reactive power deficit of the system when a fault occurs.

[0039] S313: The quasi-steady-state frequency deviation after the system enters the primary frequency modulation-dominated phase is: ; In the formula, This refers to the equivalent power deficit in the later stage of the transient state. This is the primary frequency regulation coefficient for energy storage.

[0040] S314: Based on the comparison results of the frequency change rate, the lowest frequency point, the quasi-steady-state frequency deviation and the recovery time of the corresponding frequency with their respective thresholds, the energy storage active power support requirements to meet frequency security are obtained.

[0041] S32: Establish a transient voltage recovery model and obtain the system reactive power support requirements to meet voltage safety through transient discrete power flow calculation.

[0042] In this embodiment, instead of employing complex electromagnetic transient simulation, voltage safety is evaluated at the capacity planning level through network power flow calculations under transient discrete timescales. The node voltage under each transient step is calculated using the power flow calculation function of the distribution network. The reactive power output of energy storage and photovoltaics during the transient phase jointly affects the node voltage recovery process.

[0043] Specifically, S32 includes: S321: In the Under each transient step, the node voltage is calculated using the distribution network power flow calculation function based on the active power injection vector and reactive power injection vector of each node in the system. ; In the formula, and These are the active power injection vector and reactive power injection vector for each node in the system, respectively. This is a function for calculating power flow in a distribution network.

[0044] S322: The voltage recovery trajectory of each key node is obtained by calculating the transient step size. Based on the comparison results of the voltage amplitude and voltage recovery time of the key nodes with their respective thresholds, the system reactive power support requirements that meet the voltage safety requirements are obtained.

[0045] Step 3: Establish an active / reactive power coupling safety margin model for the energy storage converter, unify the active power support demand of energy storage, the reactive power support demand of the system, and the apparent capacity constraint of the energy storage converter into the transient feasible region, and calculate the coupling safety margin of the energy storage converter; based on the reduced reactive power support of photovoltaics and the reduced reactive power output demand of energy storage, calculate the active power margin that energy storage can additionally use for frequency support under the apparent capacity constraint of the energy storage converter, and convert the active power margin into the capacity release of the rated power and rated energy of the energy storage.

[0046] Specifically, in the first Under each transient step, the effective reactive power support from photovoltaics is first subtracted from the system's reactive power support demand to obtain the remaining reactive power support demand to be borne by energy storage. This remaining reactive power demand, along with the energy storage's active power support demand, is then substituted into the apparent capacity constraint of the energy storage converter. The coupling safety margin is represented by the difference between the converter's allowed apparent capacity and the actual combined active and reactive apparent power. When photovoltaics provides reactive power support, the reactive power output demand of energy storage decreases, and the released converter capacity can be converted into an additional active power support margin. This margin can be expressed as the difference between the upper limit of the energy storage's allowed active power output before and after photovoltaic support. Further conservative values ​​satisfying the safety constraints under each fault scenario and transient step are taken to obtain the energy storage's rated power capacity release. This active power margin is then integrated or discretely accumulated over the duration of transient support. Combined with the energy storage's charge / discharge efficiency and state of charge constraints, the rated energy storage capacity release is obtained.

[0047] Step 4: With the goal of minimizing the annualized total cost of grid-based energy storage, establish an energy storage optimization configuration model based on the effective support lower bound of photovoltaics, capacity release, active power support requirements of energy storage, reactive power support requirements of the system, and coupling safety margin. Use an iterative solution method to solve the energy storage optimization configuration model to obtain the final energy storage configuration scheme.

[0048] In this embodiment, with the goal of minimizing the annualized total cost of grid-based energy storage, an optimal configuration model for grid-based energy storage is established by constraining the rated power, rated energy, apparent capacity of the converter, state of charge of the energy storage, transient frequency safety, transient voltage safety, photovoltaic support reliability, active / reactive coupling safety margin of the energy storage, power balance of islanded operation, and continuous islanded operation capability.

[0049] Specifically, the objective function of the energy storage optimization configuration model is: ; in, For total cost, For investment costs, For maintenance costs, To calculate the operating revenue. The expressions for each item are as follows: ; ; ; ; In the formula, Investment cost per unit of rated power for energy storage; The rated energy investment cost for an energy storage unit; This refers to the rated active power of the energy storage. This refers to the rated energy capacity of the energy storage. This is the capital recovery factor; The annual discount rate; The economic lifespan in years for an energy storage project; This is the annual maintenance cost coefficient; Total number of grid-connected economic dispatch periods; superscript Indicates the grid connection and operation phase; and The first The discharge revenue electricity price and the charging electricity purchase price for each time period; and The first Energy storage discharge power and charging power for each time period; The length of a single scheduling period.

[0050] In this embodiment, the constraints of the energy storage optimization configuration model include: transient voltage amplitude constraints, voltage recovery time constraints, frequency minimum point constraints, frequency change rate constraints, quasi-steady-state frequency deviation constraints, frequency recovery time constraints, active and reactive power balance constraints of each node during islanded operation, line capacity constraints, node voltage constraints, energy storage state of charge constraints, energy storage power output constraints, apparent power constraints of energy storage converters, as well as the lower bound constraint of effective photovoltaic support and the coupling safety margin constraints.

[0051] The transient voltage amplitude constraint is expressed as: ; In the formula, For nodes In the Voltage amplitude of a transient step and For nodes The lower and upper limits of transient voltage. For a set of nodes, This is the set of transient step sizes.

[0052] The voltage recovery time constraint is expressed as: ; In the formula, The time required for the critical node voltage to recover to the specified range. This is the maximum allowable voltage recovery time.

[0053] The minimum frequency constraint is expressed as: ; In the formula, For the first The system frequency of a transient step size The lowest frequency point, The lowest permissible frequency.

[0054] The frequency change rate constraint is expressed as: ; In the formula, For the first The rate of change of frequency of each transient step size This represents the upper limit of the absolute value of the rate of change of frequency.

[0055] Quasi-steady-state frequency deviation constraint, expressed as: ; In the formula, For quasi-steady-state frequency deviation, This represents the upper limit of the permissible quasi-steady-state frequency deviation.

[0056] The frequency recovery time constraint is expressed as: ; In the formula, The time required for the frequency to recover to the specified range. The maximum allowed frequency recovery time.

[0057] The active and reactive power balance constraints of each node during islanded operation are expressed as follows: ; In the formula, superscript This indicates the ongoing operation phase of the isolated island. and For nodes The active and reactive power injection of photovoltaic power; and For energy storage discharge and charging power; For energy storage reactive power output, and To meet the active and reactive power demands of the load, and To distribute to nodes The active and reactive power losses, This is a set of isolated runtime segments.

[0058] Line capacity constraints and node voltage constraints are expressed as follows: ; In the formula, and For the line During the isolated period The trend of meritorious and ineffective actions This represents the maximum apparent power of the line in operation. For the set of routes, For nodes During the isolated period The voltage amplitude.

[0059] Energy storage state of charge constraints are expressed as: ; In the formula, and The upper and lower limits of the energy storage state of charge. For grid connection scheduling period The state of charge; For the first A transient step of charged state; For island runtime segment The state of charge.

[0060] Energy storage power output constraints are expressed as: ; In the formula, For the first The first fault scenario The active power output is measured in transient steps; positive values ​​indicate discharge injection, and negative values ​​indicate charge absorption. This refers to the rated active power of the energy storage.

[0061] The apparent power constraint of the energy storage converter is expressed as: .

[0062] In the formula, and These represent the active and reactive power outputs of energy storage at any stage of grid-connected operation, transient process, and islanded operation, respectively. The rated apparent capacity of the configured energy storage.

[0063] In this embodiment, the energy storage optimization configuration model is solved using an iterative solution method of "main optimization-transient verification-cut plane feedback". The main optimization model outputs candidate energy storage capacity and photovoltaic support parameters. The transient verification model calculates frequency, voltage, photovoltaic support status and energy storage coupling safety margin for each scenario. If the verification does not meet the requirements, capacity correction constraints are generated according to the reasons for failure, and the solution is returned to the main optimization model to be solved again until the changes in rated power, rated energy and apparent capacity of the energy storage and the converter in two adjacent iterations are all less than the given threshold, and all transient safety constraints are satisfied, thus obtaining the final energy storage configuration scheme.

[0064] Specifically, the iterative solution process includes the following steps: Step A: Establish the master optimization model with the goal of minimizing the annualized total cost of energy storage, and solve for the energy storage access location, rated active power, rated energy capacity, and rated apparent capacity of the converter as candidate solutions.

[0065] In this embodiment, the master optimization model is a relaxed form of the energy storage optimization configuration model when the transient safety constraints are not explicitly expressed. The cutting plane constraints generated by the transient verification gradually approximate the complete constraint set, and the objective function of the master optimization model is consistent with the objective function of the energy storage optimization configuration model.

[0066] Step B: Perform scenario-by-scenario transient verification on the candidate solutions output by the master optimization model. The transient verification includes frequency security constraints, voltage security constraints, photovoltaic support status, photovoltaic effective reactive power support, coupling safety margin of energy storage converter, and end value of energy storage state of charge.

[0067] In this embodiment, frequency safety constraints include: frequency rate of change, frequency minimum point, quasi-steady-state frequency difference, and frequency recovery time. Voltage safety constraints include: critical node voltage amplitude and voltage recovery time.

[0068] Step C: If a candidate scheme satisfies the constraints of the energy storage optimization configuration model and all security constraints of the transient verification, then the scheme is taken as the current feasible scheme, and the upper limit of the energy storage capacity is reduced.

[0069] Step D: If the candidate scheme does not meet the frequency security constraints of the transient verification, then generate active power support correction constraints to increase the lower limit of the rated power of energy storage or increase the transient active power reserve of energy storage.

[0070] Step E: If the candidate scheme does not meet the voltage safety constraint of the transient verification, determine whether the effective reactive power support of the photovoltaic is lower than the lower limit of the effective photovoltaic support; if so, reduce the value of the lower limit of the effective photovoltaic support or increase the reactive power reserve of the energy storage; if not, increase the rated apparent capacity of the energy storage converter.

[0071] Step F: If the coupling safety margin of the energy storage converter is less than the set threshold, then generate a coupling feasible region correction constraint and return to the main optimization model to solve it again. The coupling feasible region correction constraint is: ; In the formula, and The configured energy storage is respectively in the first Active and reactive power output of energy storage under a transient step size This is the converter's usable capacity reduction factor after considering temperature and overload time factors under fault scenarios. The rated apparent capacity of the configured energy storage, This represents the minimum permissible coupling safety margin.

[0072] Step G: If the transient end-of-life energy storage state of charge is insufficient or the islanded continuous operation cannot meet the requirements, then raise the lower limit of the rated energy of the energy storage or adjust the energy storage state of charge reservation strategy before the fault.

[0073] Step H: When the changes in rated active power, rated energy capacity, and rated apparent capacity of the converter in two consecutive iterations are all less than the set threshold, and all safety constraints of the transient verification are met, the final energy storage configuration scheme is output.

[0074] In this embodiment, the final energy storage configuration scheme output includes: the access location of the grid-type energy storage, rated active power, rated energy capacity, rated apparent capacity of the converter, reserved power for transient support, reserved energy for transient support, available set of photovoltaic transient auxiliary support, photovoltaic support control parameters, and frequency and voltage safety verification results under various typical fault scenarios.

[0075] The grid-based energy storage optimization configuration method considering photovoltaic support in this invention simultaneously takes into account transient frequency safety, transient voltage recovery, energy storage converter coupling margin, photovoltaic support reliability, and islanded continuous operation capability. This method can simultaneously ensure rapid frequency support, voltage recovery, and subsequent islanded power supply sustainability after a tie-line fault. Employing an iterative solution method of "main optimization-transient verification-cut plane feedback," when the transient verification detects frequency exceeding limits, voltage recovery failure, insufficient photovoltaic support, insufficient energy storage coupling margin, or insufficient SOC end-point, it can generate targeted capacity correction constraints based on the cause of the failure, rather than simply increasing the total energy storage capacity. This reduces energy storage redundancy while ensuring transient safety.

[0076] Furthermore, to illustrate the effectiveness of the method of the present invention, a comparison was made between different configuration methods under typical examples. The comparison results are shown in Table 1, which presents the comparison results of different configuration methods under typical examples.

[0077] Table 1

[0078] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations are intended to cover non-exclusive inclusion, such that an article or device comprising a list of elements includes not only those elements but also other elements not expressly listed. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device comprising said element. Terms such as "connected" or "linked" are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect. The orientations or positional relationships indicated by terms such as "upper," "lower," "left," and "right" are based on the orientations or positional relationships shown in the accompanying drawings and are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention.

[0079] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0080] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for optimizing the configuration of grid-type energy storage considering photovoltaic support, characterized in that, include: Step 1: Obtain basic data of the distribution network and a set of fault scenarios for weak tie lines. Identify the island range for each tie line fault scenario, and select a set of key nodes and a set of photovoltaic candidate supports. Calculate the reactive power-voltage sensitivity of each photovoltaic node to the key nodes, obtain the voltage support effectiveness of each photovoltaic node, and construct a set of uncertain scenarios for photovoltaic transient auxiliary support. Step 2: Establish an energy storage economic dispatch model for the grid-connected operation phase, solve for the state parameters before each fault occurs, and use them as the initial state for transient calculation of tie-line faults; establish a timing switching model and a photovoltaic transient auxiliary support state model after the tie-line is disconnected; calculate the photovoltaic effective reactive power support based on the voltage support effectiveness, the apparent capacity constraint of the photovoltaic inverter, and the uncertain scenario set; evaluate the credibility of the photovoltaic effective reactive power support to obtain the lower bound of the photovoltaic effective support that meets the given confidence level; establish a grid-type energy storage transient frequency support model and a transient voltage recovery model to obtain the energy storage active power support requirements that meet frequency security and the system reactive power support requirements that meet voltage security, respectively. Step 3: Establish an active / reactive power coupling safety margin model for the energy storage converter. Unify the active power support demand of the energy storage, the reactive power support demand of the system, and the apparent capacity constraint of the energy storage converter into the transient feasible region, and calculate the coupling safety margin of the energy storage converter. Based on the reduced reactive power support of the photovoltaic system and the reduced reactive power output demand of the energy storage, calculate the active power margin that the energy storage can additionally use for frequency support under the apparent capacity constraint of the energy storage converter, and convert the active power margin into the capacity release of the rated power and rated energy of the energy storage. Step 4: With the goal of minimizing the annualized total cost of grid-based energy storage, establish an energy storage optimization configuration model based on the effective support lower bound of photovoltaics, the capacity release, the active power support requirement of energy storage, the reactive power support requirement of the system, and the coupling safety margin. Solve the energy storage optimization configuration model using an iterative solution method to obtain the final energy storage configuration scheme.

2. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 1, characterized in that, In step 1, the reactive power-voltage sensitivity of each photovoltaic node to the key node is calculated to obtain the voltage support effectiveness of each photovoltaic node, including: S11: For the first The photovoltaic node and the first For each key node, the reactive power-voltage sensitivity is calculated based on the power flow Jacobian matrix as follows: ； in, For the first Voltage amplitude at key nodes, For the first Reactive power injection of each photovoltaic node; S12: Normalize all photovoltaic nodes within the island range to obtain the first... The photovoltaic node for the first The relative voltage support effectiveness of each key node is as follows: ； in, Indicates the first The photovoltaic node for the first The relative voltage support effectiveness of key nodes For photovoltaic candidate support set; S13: For multiple key nodes, a weighted sum is calculated based on the importance weight of each key node to obtain the [number of nodes]. Voltage support effectiveness of individual photovoltaic nodes: ； in, For the set of key nodes, For the first The importance weight of each key node.

3. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 1, characterized in that, The set of uncertain scenarios for photovoltaic transient auxiliary support includes: photovoltaic output uncertainty, photovoltaic inverter capacity margin uncertainty, communication / detection delay uncertainty, low voltage ride-through state, support unavailability state caused by partial shading, and photovoltaic support saturation state.

4. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 1, characterized in that, In step 2, the photovoltaic transient auxiliary support state model includes six states that it goes through in sequence: normal grid connection state, islanding detection state, synchronization waiting state, transient support state, support saturation state, and support exit state. In the normal grid-connected state, the photovoltaic inverter operates under maximum power point tracking control; in the islanding detection state, the photovoltaic inverter detects a disconnection signal on the tie line and maintains this for a first preset time delay; in the synchronization waiting state, the photovoltaic inverter synchronizes with the reference voltage and frequency established by the grid-connected energy storage and maintains this for a second preset time delay; in the transient support state, the photovoltaic inverter outputs reactive power and limits the rate of change of active power according to reactive power-voltage droop control; in the support saturation state, the photovoltaic inverter limits reactive power and / or active power output when it reaches the apparent capacity limit; in the support withdrawal state, the photovoltaic inverter gradually withdraws from support and returns to normal control after the voltage recovers to above the threshold.

5. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 1, characterized in that, In step 2, the effective reactive power support of the photovoltaic system is calculated based on the voltage support validity, the apparent capacity constraint of the photovoltaic inverter, and the uncertain scenario set. The reliability of the effective reactive power support is then assessed to obtain a lower bound for the effective photovoltaic support that satisfies a given confidence level, including: S21: The reactive power output of the photovoltaic inverter during the transient period is calculated using the reactive power-voltage droop control method as follows: ； in, This refers to the reactive power output of a single photovoltaic inverter during the transient period. This refers to the reactive power-voltage droop factor of photovoltaic systems. for After the timeline failure Voltage of the photovoltaic access node under a transient step size This is the voltage reference value for the photovoltaic inverter; S22: The active and reactive power output of the photovoltaic system satisfies the apparent capacity constraint of the photovoltaic inverter as follows: ； In the formula, This refers to the rated apparent power capacity of the photovoltaic inverter. This represents the active power output of a single photovoltaic inverter during the transient period. S23: Based on the voltage support effectiveness, the apparent capacity constraint of the photovoltaic inverter, and the communication / detection availability determined based on the uncertain scenario set, the effective reactive power support of the photovoltaic system to the key nodes within the islanded area is calculated as follows: ； In the formula, This represents the effective reactive power support for photovoltaic systems. For photovoltaic candidate support set, This refers to the reactive power output of a single photovoltaic inverter during the transient period. S24: Conduct a credibility assessment of the aforementioned effective reactive power support quantity of photovoltaic power, using either robust constraint or chance constraint methods. The effective lower bound of photovoltaic support is used in the calculation of energy storage capacity to obtain the effective lower bound of photovoltaic support. The calculation process is expressed as follows: ； in, This is the lower bound of the effective support for photovoltaics obtained after the credibility assessment. For uncertainties in photovoltaic output, latency, communication status, and support availability, For the first An uncertain set under a faulty connection scenario To allow for failure probability.

6. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 1, characterized in that, In step 2, a transient frequency support model and a transient voltage recovery model for grid-type energy storage are established to obtain the active power support requirements for energy storage to meet frequency security and the reactive power support requirements for the system to meet voltage security, respectively, including: S31: Establish the transient frequency support model of the grid-type energy storage, and use the equivalent frequency equation of the virtual synchronous machine to calculate the frequency dynamics after the fault, so as to obtain the energy storage active power support requirements that meet the frequency security requirements; the frequency dynamics include: frequency change rate, frequency minimum point, quasi-steady-state frequency deviation and frequency recovery time. S32: Establish the transient voltage recovery model and obtain the system reactive power support requirements that meet voltage safety through transient discrete power flow calculation.

7. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 6, characterized in that, S31 includes: S311: The system frequency dynamics are described using the equivalent frequency equation of the virtual synchronizer. ； In the formula, For frequency deviation, The virtual inertia time constant, This is the system's baseline capacity; The damping coefficient is... As the reference frequency, This refers to the actual active power output of the energy storage AC side during the transient phase. Active power output of photovoltaic power during the transient phase. This represents the total active power of the load during the transient phase. This refers to the total active power loss during the transient phase. S312: The rate of frequency change at the initial moment of the fault is determined by inertia support: ； In the formula, This refers to the reactive power deficit of the system when a fault occurs. S313: The quasi-steady-state frequency deviation after the system enters the primary frequency modulation-dominated phase is: ； In the formula, This refers to the equivalent power deficit in the later stage of the transient state. This refers to the primary frequency regulation coefficient for energy storage. S314: Based on the comparison results of the frequency change rate, the lowest frequency point, the quasi-steady-state frequency deviation and the recovery time of the corresponding frequency with their respective thresholds, the energy storage active power support requirements that meet the frequency security requirements are obtained.

8. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 6, characterized in that, S32 includes: S321: In the Under each transient step, the node voltage is calculated using the distribution network power flow calculation function based on the active power injection vector and reactive power injection vector of each node in the system. ； In the formula, and These are the active power injection vector and reactive power injection vector for each node in the system, respectively. This is a function for calculating power flow in a distribution network. S322: The voltage recovery trajectory of each key node is obtained by calculating the transient step size. Based on the comparison results of the voltage amplitude and voltage recovery time of the key nodes with their respective thresholds, the system reactive power support requirements that meet the voltage safety requirements are obtained.

9. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 1, characterized in that, The objective function of the energy storage optimization configuration model is: ； in, For total cost, For investment costs, For maintenance costs, For operating revenue; The constraints of the energy storage optimization configuration model include: transient voltage amplitude constraints, voltage recovery time constraints, frequency minimum point constraints, frequency change rate constraints, quasi-steady-state frequency deviation constraints, frequency recovery time constraints, active and reactive power balance constraints of each node during islanded operation, line capacity constraints, node voltage constraints, energy storage state of charge constraints, energy storage power output constraints, apparent power constraints of energy storage converters, as well as the effective support lower bound constraint of photovoltaics and the coupling safety margin constraints.

10. The method for optimizing the configuration of grid-type energy storage considering photovoltaic support according to claim 1, characterized in that, In step 4, the energy storage optimization configuration model is solved using the "master optimization-transient verification-cut plane feedback" iterative solution method to obtain the final energy storage configuration scheme, including: Step A: Establish the master optimization model with the goal of minimizing the annualized total cost of energy storage, and solve for the energy storage access location, rated active power, rated energy capacity, and rated apparent capacity of the converter as candidate solutions; Step B: Perform scenario-by-scenario transient verification on the candidate solutions output by the master optimization model. The transient verification includes frequency security constraints, voltage security constraints, photovoltaic support status, photovoltaic effective reactive power support, coupling security margin of the energy storage converter, and end value of energy storage state of charge. Step C: If the candidate scheme satisfies the constraints of the energy storage optimization configuration model and all the security constraints of the transient verification, then the scheme is taken as the current feasible scheme, and the upper limit of the energy storage capacity is reduced. Step D: If the candidate scheme does not meet the frequency security constraint of the transient verification, then generate the active power support correction constraint to increase the lower bound of the rated power of energy storage or increase the transient active power reserve of energy storage. Step E: If the candidate scheme does not meet the voltage safety constraint of the transient verification, then determine whether the effective reactive power support of the photovoltaic is lower than the lower limit of the effective photovoltaic support; if yes, then reduce the value of the lower limit of the effective photovoltaic support or increase the reactive power reserve of the energy storage; if no, then increase the rated apparent capacity of the energy storage converter. Step F: If the coupling safety margin of the energy storage converter is less than a set threshold, then a coupling feasible region correction constraint is generated, and the main optimization model is returned to be solved again. The coupling feasible region correction constraint is: ； In the formula, and The configured energy storage is respectively in the first Active and reactive power output of energy storage under a transient step size This is the converter's usable capacity reduction factor after considering temperature and overload time factors under fault scenarios. The rated apparent capacity of the configured energy storage, This represents the minimum permissible coupling safety margin. Step G: If the transient end-of-life energy storage state of charge is insufficient or the islanded continuous operation cannot meet the requirements, then raise the lower limit of the rated energy of the energy storage or adjust the energy storage state of charge reservation strategy before the fault. Step H: When the changes in the rated active power, rated energy capacity, and rated apparent capacity of the converter in two consecutive iterations are all less than the set threshold, and all safety constraints of the transient verification are satisfied, the final energy storage configuration scheme is output.

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