Flexible resource allocation and dispatching methods for new energy power systems that take into account resilience factors

Abstract

The application discloses a new energy power system flexible resource configuration scheduling method considering comprehensive resilience factors, S1, initial power parameter setting, setting initial flexible resource configuration; S2, constructing a comprehensive scenario set through historical power parameters and a probability model; S3, performing resilience evaluation on a power system in a current flexible resource configuration state, first, establishing a flexible resource model, then, establishing a power system resilience evaluation model, calculating a loss load amount under different scenario conditions, and an expected value of power shortage under a current flexible resource configuration proportion k. The application calculates resilience indexes of different scenarios through a DC optimal power flow optimization model of the flexible resource, adjusts the flexible resource configuration proportion according to a comparison result of the indexes and a set value, and arranges a promotion priority according to development costs of different flexible resources. The application realizes flexible resource configuration considering resilience requirements, and effectively improves the resilience of the power system.

Description

Technical Field

[0001] This invention relates to the field of power technology, and in particular to a flexible resource allocation and scheduling method for new energy power systems that integrates resilience factors. Background Technology

[0002] In recent years, frequent extreme weather events worldwide have seriously threatened the safe operation of power systems. Global climate and the environment have deteriorated dramatically in recent years, with frequent extreme weather events such as droughts, floods, hurricanes, extreme heat, and extreme cold, leading to continuously escalating disaster losses. As the most important infrastructure, the energy and power system is severely affected by extreme weather. Extreme weather not only causes a surge in load in a short period, but the sudden deterioration of operating conditions also increases the failure rate of equipment on the generation side and transmission lines. Natural disasters accompanying extreme weather can also damage critical facilities such as power plants, transmission lines, electrical equipment, and dispatch communications. Therefore, research on the resilience of power systems, describing these extremely low-probability but extremely high-damage failures caused by extreme weather, has attracted much attention. Improving the resilience of power systems can be achieved through the adjustment capabilities of various flexible resources within the system. However, the current level of flexibility in my country's power system is insufficient, and the coordinated response capability of flexible power sources and load resources is limited. Therefore, there is an urgent need for flexible resource allocation and dispatch methods to meet the needs of new power systems for flexible resource allocation. At the same time, it is necessary to fully consider the investment and construction costs of different types of flexible resources, prioritize the construction and development of flexible power sources, and deeply explore the potential of load resources to achieve more effective demand response. Summary of the Invention

[0003] One objective of this invention is to propose a flexible resource allocation and scheduling method for new energy power systems that integrates resilience factors. This invention achieves flexible resource allocation that takes into account resilience requirements, thereby effectively improving the resilience of the power system.

[0004] A flexible resource allocation and scheduling method for a new energy power system based on comprehensive resilience factors according to an embodiment of the present invention includes the following steps:

[0005] S1. Initial power parameter settings, setting initial flexible resource configuration;

[0006] S2. Construct a comprehensive scenario set using historical power parameters and probability models;

[0007] S3. Conduct a resilience assessment of the power system under the current flexible resource allocation status. First, establish a flexible resource model, then establish a power system resilience assessment model, calculate the load shedding under different scenario conditions, and the expected value of power shortage under the current flexible resource allocation ratio k.

[0008] S4. Determine whether the expected power shortage meets the resilience requirements and adjust the flexible resource allocation ratio accordingly.

[0009] Optionally, S1 specifically includes:

[0010] S11. Input the basic parameters of power system transmission line data, traditional power source data and load data;

[0011] S12. Set the expected power shortage value (EENS) for the power system resilience index. set EENS set This represents the expected value of load loss that can be tolerated under extreme system conditions;

[0012] S13. Set the initial flexible resource allocation ratio k0, where k0 represents the ratio of the initial flexible resource capacity to the conventional power supply installed capacity.

[0013] Optionally, the feature is that each scenario h of the comprehensive scenario set H includes grid fault conditions and new energy output.

[0014] Optionally, the power system resilience assessment model specifically includes:

[0015] Using the optimal DC power flow model of the power system as the model for assessing grid resilience, the load shedding and expected power shortage at each node are calculated. The objective function is:

[0016]

[0017] Among them, f h This represents the sum of conventional generating costs, flexible load demand response costs, energy storage operating costs, and load shedding costs for the power system in state h; n g n ED n d and n es These represent the number of conventional generating units, grid nodes, flexible loads, and energy storage systems in the power system, respectively; GC r，h () represents the power generation cost of the r-th generator unit in the power system under the h-th state; CC i，h () represents the load reduction cost of the i-th power node in the power system under the h-th state; DC d，h () represents the demand response cost of the d-th flexible load in the power system under the h-th state; SCe s，h () represents the operating cost of the es-th energy storage system in the power system under the h-th state of the power system; This represents the active power output of the r-th generator unit in the power system during time period t, under the h-th state of the power system. This represents the load reduction amount of the i-th power node in the power system during time period t, under the h-th state of the power system. This represents the demand response power of the d-th flexible load in the power system during time period t, under the h-th state of the power system. and These represent the charging and discharging power of the battery energy storage station es during time period t in the h-th state of the power system;

[0018] Operating constraints, power balance constraints for each node:

[0019]

[0020] Where EL represents the set of branches connected to node i; PD i，t f represents the load power of node i during time period t under normal grid operation. lt This represents the power flow of line l at time t under normal power grid operation.

[0021] Relationship between line power flow and node phase angle:

[0022]

[0023] Where, θ it θ jt Let x represent the phase angles of nodes i and j at time t during normal operation, respectively. l This represents the impedance of line l.

[0024] Power constraints on transmission lines:

[0025]

[0026] Among them, f l，max This represents the maximum power transmitted by line l;

[0027] Node phase angle constraint:

[0028]

[0029] Where, θ i，max This represents the maximum allowable deviation of the power angle at node i;

[0030] Flexible load resource power upper and lower limit constraints:

[0031]

[0032] Constraints related to energy storage devices:

[0033] The operation of energy storage devices depends primarily on their state of charge, and the charging and discharging process is represented as follows:

[0034]

[0035] In the formula: This indicates the state of charge of the battery energy storage power station es during time period t; and x represents the charging and discharging power of the battery energy storage power station es during time period t; es，t η is a 0-1 variable representing the battery's energy storage state, where 0 represents the charging state and 1 represents the discharging state. ch and η dis For the charge and discharge efficiency of battery energy storage power stations; C ES This refers to the rated capacity of the energy storage.

[0036] To ensure the stable operation of energy storage systems, their state of charge is limited to a certain range:

[0037]

[0038] In the formula: and These are the upper and lower limits of the es state of charge of the energy storage power station, respectively.

[0039] Upper and lower limits of charging and discharging power constraints for battery energy storage power stations:

[0040]

[0041] in, and These represent the upper and lower power limits of the battery energy storage station during charging and discharging, respectively.

[0042] Ramp-up constraints for various adjustment resources:

[0043]

[0044] Among them, Rp r，max , Rp d，max These represent the maximum ramp rate of conventional unit r, the maximum ramp rate of energy storage system es during charging, the maximum ramp rate of energy storage system es during discharging, and the maximum ramp rate of flexible load d in response, respectively.

[0045] Shear load constraint:

[0046]

[0047] Optionally, S4 specifically includes:

[0048] The power grid resilience index is represented by the expected power shortage value. Based on the load shedding, the expected power shortage value index is calculated using the following formula:

[0049]

[0050] Where, ph Let h represent the probability of scenario h occurring in the power system, and T represent the duration of the fault under extreme conditions. This represents the load reduction amount of the i-th power node in the power system during time period t under the h-th scenario.

[0051] Compare the expected power shortage (EENS) with the required power shortage (EENS). set The size, if EENS < EEMS set If the conditions are met, it means that the current flexible resource allocation meets the resilience requirements, and the process ends; if ENS > ENS set If so, the flexible resource allocation needs to be adjusted, and the process should be returned to S3;

[0052] Based on the initial value k0, increase Δk to obtain a new flexible resource allocation ratio k, and calculate the required increase in flexible resource capacity ΔC based on the Δk value. f Adjust the corresponding flexible resource parameters:

[0053] k = k0 + Δk;

[0054] ΔC f =C t Δ k .

[0055] The beneficial effects of this invention are:

[0056] This invention proposes a flexible resource allocation and scheduling method for new energy power systems that considers resilience factors. This method considers grid fault scenarios and new energy output scenarios under different extreme weather conditions. It calculates resilience indicators for different scenarios using a DC optimal power flow optimization model that considers flexible resources. Then, based on the comparison results between the indicators and set values, it adjusts the allocation ratio of flexible resources and prioritizes their development according to their development costs. This achieves flexible resource allocation that considers resilience requirements, effectively improving the resilience of the power system. Attached Figure Description

[0057] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0058] Figure 1 This is a flowchart of a flexible resource allocation and scheduling method for a new energy power system that integrates resilience factors, as proposed in this invention. Detailed Implementation

[0059] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0060] refer to Figure 1 A flexible resource allocation and scheduling method for a new energy power system that integrates resilience factors includes the following steps:

[0061] S1. Initial power parameter settings, setting initial flexible resource configuration;

[0062] S2. Construct a comprehensive scenario set using historical power parameters and probability models;

[0063] S3. Conduct a resilience assessment of the power system under the current flexible resource allocation status. First, establish a flexible resource model, then establish a power system resilience assessment model, calculate the load shedding under different scenario conditions, and the expected value of power shortage under the current flexible resource allocation ratio k.

[0064] S4. Determine whether the expected power shortage meets the resilience requirements and adjust the flexible resource allocation ratio accordingly.

[0065] In this embodiment, S1 specifically includes:

[0066] S11. Input the basic parameters of power system transmission line data, traditional power source data and load data;

[0067] S12. Set the expected power shortage value (EENS) for the power system resilience index. set EENS set This represents the expected value of load loss that can be tolerated under extreme system conditions;

[0068] S13. Set the initial flexible resource allocation ratio k0, where k0 represents the ratio of the initial flexible resource capacity to the conventional power supply installed capacity.

[0069] In this embodiment, the characteristic is that each scenario h in the comprehensive scenario set H includes grid fault conditions and new energy output.

[0070] In this embodiment, the power system resilience assessment model specifically includes:

[0071] Using the optimal DC power flow model of the power system as the model for assessing grid resilience, the load shedding and expected power shortage at each node are calculated. The objective function is:

[0072]

[0073] Among them, f h This represents the sum of conventional generating costs, flexible load demand response costs, energy storage operating costs, and load shedding costs for the power system in state h; n g n ED n d and n esThese represent the number of conventional generating units, grid nodes, flexible loads, and energy storage systems in the power system, respectively; GC r，h () represents the power generation cost of the r-th generator unit in the power system under the h-th state; CC i，h () represents the load reduction cost of the i-th power node in the power system under the h-th state; DC d，h () represents the demand response cost of the d-th flexible load in the power system under the h-th state; SC es，h () represents the operating cost of the es-th energy storage system in the power system under the h-th state of the power system; This represents the active power output of the r-th generator unit in the power system during time period t, under the h-th state of the power system. This represents the load reduction amount of the i-th power node in the power system during time period t, under the h-th state of the power system. This represents the demand response power of the d-th flexible load in the power system during time period t, under the h-th state of the power system. and These represent the charging and discharging power of the battery energy storage station es during time period t in the h-th state of the power system;

[0074] Operating constraints, power balance constraints for each node:

[0075]

[0076] Where EL represents the set of branches connected to node i; PD i，t f represents the load power of node i during time period t under normal grid operation. lt This represents the power flow of line l at time t under normal power grid operation.

[0077] Relationship between line power flow and node phase angle:

[0078]

[0079] Where, θ it θ jt Let x represent the phase angles of nodes i and j at time t during normal operation, respectively. l This represents the impedance of line l.

[0080] Power constraints on transmission lines:

[0081]

[0082] Among them, f l，max This represents the maximum power transmitted by line l;

[0083] Node phase angle constraint:

[0084]

[0085] Where, θ i，max This represents the maximum allowable deviation of the power angle at node i;

[0086] Flexible load resource power upper and lower limit constraints:

[0087]

[0088] Constraints related to energy storage devices:

[0089] The operation of energy storage devices depends primarily on their state of charge, and the charging and discharging process is represented as follows:

[0090]

[0091] In the formula: This indicates the state of charge of the battery energy storage power station es during time period t; and x represents the charging and discharging power of the battery energy storage power station es during time period t; es，t η is a 0-1 variable representing the battery's energy storage state, where 0 represents the charging state and 1 represents the discharging state. ch and η dis For the charge and discharge efficiency of battery energy storage power stations; C ES This refers to the rated capacity of the energy storage.

[0092] To ensure the stable operation of energy storage systems, their state of charge is limited to a certain range:

[0093]

[0094] In the formula: and These are the upper and lower limits of the es state of charge of the energy storage power station, respectively.

[0095] Upper and lower limits of charging and discharging power constraints for battery energy storage power stations:

[0096]

[0097] in, and These represent the upper and lower power limits of the battery energy storage station during charging and discharging, respectively.

[0098] Ramp-up constraints for various adjustment resources:

[0099]

[0100] Among them, Rp r，max , Rp d，max These represent the maximum ramp rate of conventional unit r, the maximum ramp rate of energy storage system es during charging, the maximum ramp rate of energy storage system es during discharging, and the maximum ramp rate of flexible load d in response, respectively.

[0101] Shear load constraint:

[0102]

[0103] In this embodiment, S4 specifically includes:

[0104] The power grid resilience index is represented by the expected power shortage value. Based on the load shedding, the expected power shortage value index is calculated using the following formula:

[0105]

[0106] Where, p h Let h represent the probability of scenario h occurring in the power system, and T represent the duration of the fault under extreme conditions. This represents the load reduction amount of the i-th power node in the power system during time period t under the h-th scenario.

[0107] Compare the expected power shortage (EENS) with the required power shortage (EENS). set The size, if EENS < EENS set If the conditions are met, it means that the current flexible resource allocation meets the resilience requirements, and the process ends; if EENSvEENS set If so, the flexible resource allocation needs to be adjusted, and the process should be returned to S3;

[0108] Based on the initial value k0, increase Δk to obtain a new flexible resource allocation ratio k, and calculate the required increase in flexible resource capacity ΔC based on the Δk value. f Adjust the corresponding flexible resource parameters:

[0109] k = k0 + Δk;

[0110] ΔC f =C t Δ k .

[0111] This invention proposes a flexible resource allocation and scheduling method for new energy power systems that considers resilience factors. This method considers grid fault scenarios and new energy output scenarios under different extreme weather conditions. It calculates resilience indicators for different scenarios using a DC optimal power flow optimization model that considers flexible resources. Then, based on the comparison results between the indicators and set values, it adjusts the allocation ratio of flexible resources and prioritizes their development according to their development costs. This achieves flexible resource allocation that considers resilience requirements, effectively improving the resilience of the power system.

[0112] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for flexible resource configuration and scheduling of new energy power system with comprehensive toughness factors, characterized in that, Comprise the following steps: S1, initial power parameter setting, setting initial flexible resource configuration; S2, constructing a comprehensive scenario set through historical power parameters and probability models; S3, the power system is resiliently evaluated under the current flexible resource configuration condition, a flexible resource model is first established, then a power system resilience evaluation model is established, and the loss of load is calculated under different scene conditions, and the current flexible resource configuration proportion the expected value of power shortage under the condition S4, judging whether the power shortage expectation value meets the resilience requirement, adjusting the flexible resource configuration proportion; The power system resilience evaluation model specifically comprises: Taking the power system DC optimal power flow model as the model for evaluating the resilience of the power grid, the load reduction amount and the power shortage expectation value of each node are calculated, and the objective function is ； wherein, denotes the sum of the conventional generation cost, the flexible load demand response cost, the energy storage operation cost and the load shedding cost of the power system in the th state; , , and denote the number of conventional generation units, the number of grid nodes, the number of flexible loads and the number of energy storage systems in the power system, respectively; denotes the generation cost of the th generation unit in the power system in the th state; denotes the load shedding cost of the th grid node in the power system in the th state; denotes the demand response cost of the th flexible load in the power system in the th state; denotes the operation cost of the th energy storage system in the power system in the th state; denotes the active power output of the th generation unit in the power system in the th state during the th time period; denotes the load shedding amount of the th grid node in the power system in the th state during the th time period; denotes the demand response power of the th flexible load in the power system in the th state during the th time period; and denote the charge and discharge power of the th battery energy storage station in the power system in the th state during the th time period; Running constraints, power balance constraints of each node: ； wherein the set EL represents the set of branches connected to the node ; represents the load power of the node at the time interval under normal operation of the power grid, represents the power flow of the line at the time instant under normal operation of the power grid; The relationship between line power flow and node phase angle: ； wherein , respectively represent the phase angles of the nodes and at the time in normal operating state, represent the impedance of the line ; Power transmission line power constraint: ； wherein indicates a line maximum value of the transmitted power; Node phase angle constraint: ； wherein representing a node maximum value of the power angle deviation allowed; Flexible load resource power upper and lower limit constraint: ； Energy storage device related constraint: The operation of the energy storage device mainly depends on its state of charge, and the charging and discharging process is represented as: ； wherein: denotes the battery energy storage plant at the state of charge within the time period; and denotes the battery energy storage plant at the charge and discharge power within the time period; is a 0-1 variable indicating the state of the battery energy storage, 0 indicating a charging state and 1 indicating a discharging state; and denote the charge and discharge efficiency of the battery energy storage plant; is the energy storage rated capacity; In order to realize the stable operation of the energy storage system, the state of charge is limited within a certain range: ； wherein: and are energy storage plants upper and lower state of charge limits; Battery energy storage power station charging and discharging power upper and lower limit constraint: ； ； in, , , and These represent battery energy storage power stations. The upper and lower limits of power during charging and the upper and lower limits of power during discharging; The climbing constraint of various types of regulation resources: ； ； ； ； wherein, , , , represent the conventional unit ramp rate maximum, energy storage system ramp rate maximum, energy storage system ramp rate maximum, flexible load ramp rate maximum; Load shedding constraints: ; The S4 specifically comprises: The power grid resilience index is represented by the power shortage expectation value, and the power shortage expectation value index is calculated based on the load reduction amount by the following formula: ； wherein, represents a probability of a scenario of the power system occurring, represents a fault duration under an extreme condition, represents a load curtailment amount of a first power node in the power system under a first scenario of the power system, a first power node in the power system;​​​ Comparative power shortage expectation value With the power requirement value , if , the condition is met, indicating that the current flexible resource configuration meets the resilience demand, and the process ends; if , the flexible resource configuration needs to be adjusted, and returns to S3; On the basis of initial values promote Get new flexible resource configuration ratio According to Value calculation of the required increase of flexible resource capacity Adjust the corresponding flexible resource parameters: ； 。 2.The method of claim 1, wherein, The S1 specifically comprises: S11, inputting the basic parameters of power system transmission line data, traditional power supply data and load data; S12, setting the power system resilience index value of the power requirement , represents the expected value of the loss of load allowed under extreme conditions of the system; S13, set initial flexible resource configuration ratio , represents the ratio of initial flexible resource capacity to conventional power installed capacity.

3. The method of claim 1, wherein the method is characterized by: The comprehensive scenario set Each scenario of the comprehensive scenario set includes grid failure conditions and new energy output.

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