Unit commitment method and system for large-scale new energy consumption-oriented power system

Abstract

The application discloses a kind of large-scale new energy consumption-oriented power system unit planning method and system, comprising: determining the reconstruction optimization target of each regional power grid in power system;Build the power balance constraint condition of each regional power grid, reserve capacity constraint condition, thermal power unit operation constraint condition, transmission power constraint condition;Based on the reconstruction optimization target, power balance constraint suite, reserve capacity constraint condition, thermal power unit operation constraint condition and transmission power constraint condition are solved, determine the thermal power unit reconstruction state variable of each region;Based on the thermal power unit reconstruction state variable, power system unit is planned.The method of the application constructs new type power system unit flexibility reconstruction model in partition, solves the thermal power unit reconstruction state variable of each region, can efficiently and accurately realize the planning of power system unit, guarantee the stable operation of power system.

Description

Technical Field

[0001] This invention relates to the field of new energy technology, and more specifically, to a power system unit planning method and system for large-scale new energy consumption. Background Technology

[0002] To achieve carbon peaking by 2030 and strive for carbon neutrality by 2060, renewable energy still needs to achieve leapfrog development in the next 30 years.

[0003] To enhance the absorption capacity of large-scale new energy sources in regional power grids, the problem can be addressed by constructing new electrochemical energy storage power stations and pumped storage power stations, among other flexible resources. However, this approach suffers from high investment costs and long project cycles. Therefore, in the construction of my country's new power system, an alternative solution has been proposed: considering the current situation where conventional thermal power units account for the largest share of capacity, and addressing the common issues of high minimum technical output and slow ramp-up rates in thermal power units, corresponding flexibility modifications are carried out to tap their potential as a flexible resource.

[0004] Therefore, a power system unit planning method is needed to accommodate large-scale renewable energy consumption. Summary of the Invention

[0005] This invention proposes a power system unit planning method and system for large-scale renewable energy consumption, in order to solve the problem of how to plan power system units.

[0006] To address the aforementioned problems, according to one aspect of the present invention, a power system unit planning method for large-scale renewable energy consumption is provided, the method comprising:

[0007] Determine the transformation and optimization objectives for each regional power grid within the power system;

[0008] Construct power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints for each regional power grid;

[0009] Based on the aforementioned transformation and optimization objectives, power balance constraint suite, reserve capacity constraint conditions, thermal power unit operation constraint conditions, and transmission power constraint conditions, the state variables of thermal power unit transformation in each region are determined by solving the problem.

[0010] The power system units are planned based on the state variables of the thermal power unit retrofit.

[0011] Preferably, determining the transformation and optimization objectives of each regional power grid in the power system includes:

[0012]

[0013] Among them, F m Cost of retrofitting units within sub-region m; The number of thermal power units within sub-region m; Let i be the state variable for the modification of the i-th thermal power unit within sub-region m; Let $ be the minimum output modification cost for the i-th thermal power unit within sub-region m. Let $\frac{i}{m}$ be the cost of upgrading the ramp rate of the $i$-th thermal power unit within sub-region $m$.

[0014] Preferably, the power balance constraint condition includes:

[0015]

[0016] in, This refers to the number of thermal power units. Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t.

[0017] Preferably, the standby capacity constraint includes:

[0018]

[0019] in, Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; The number of thermal power units within sub-region m; This represents the upper limit of the output of the i-th thermal power unit within subregion m; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t; Let m be the reserve capacity requirement at time t within subregion m.

[0020] Preferably, the operating constraints of the thermal power unit include:

[0021] Upper and lower limits of thermal power unit generating capacity constraints:

[0022]

[0023] Thermal power unit output ramp-up constraints:

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030]

[0031] Minimum continuous start-up and shutdown operating time constraints for thermal power units:

[0032]

[0033]

[0034] Constraints on the state variables and coupling relationships of thermal power units:

[0035]

[0036]

[0037]

[0038] in, Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m before its renovation. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m after its modification. This represents the upper limit of the generating power of the i-th thermal power unit within sub-region m; The power increase rate limit for the i-th thermal power unit within sub-region m before its modification; The power increase rate limit for the i-th thermal power unit within sub-region m after modification; The power reduction rate limit for the i-th thermal power unit within sub-region m before its modification; The power reduction rate limit for the i-th thermal power unit within sub-region m after modification; The starting power limit for the i-th thermal power unit within sub-region m; The shutdown power limit for the i-th thermal power unit within sub-region m; Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within sub-region m after completing the shutdown process; where . Let be the minimum continuous operating time of the i-th thermal power unit in subregion m. Let be the minimum continuous downtime of the i-th thermal power unit in subregion m; Let be the state variable indicating whether the i-th thermal power unit in subregion m is to be upgraded; Let be the stable operating state variable of the i-th thermal power unit in subregion m at time t; Let be the state variable for the i-th thermal power unit in subregion m to complete the start-up process; Let be the state variable for the i-th thermal power unit in subregion m to complete the shutdown process.

[0039] Preferably, the transmission power constraint includes:

[0040]

[0041]

[0042]

[0043] in, Let m be the purchased or exported power of subregion m at time t. Let m be the number of external connection lines to subregion m. The upper limit of the transmission power at the interface of the u-th external tie line in subregion m; Let be the power transmitted from subregion f to subregion m at time t; N represents the power transferred from subregion m to subregion f at time t. mf The number of communication lines between subregions m and f; This represents the maximum transmission power of the h-th sub-regional connection line between sub-regions m and f.

[0044] Preferably, the process of solving for the state variables of the thermal power unit renovation in each region based on the renovation optimization objective, power balance constraint suite, reserve capacity constraint, thermal power unit operation constraint, and transmission power constraint includes:

[0045] Constructing a partition-optimized Lagrangian function for brightness enhancement based on the alternating direction multiplier method, including:

[0046]

[0047]

[0048] Based on the aforementioned Lagrange function, the retrofit optimization objective, the power balance constraint suite, the reserve capacity constraint, the thermal power unit operation constraint, and the transmission power constraint, the state variables of the thermal power unit retrofit for each region are determined.

[0049] Among them, L ρ For the augmented Lagrangian function, N G Ω represents the number of all subregions. m Let λ be the set of variables for subregion m. m Here, ρ is the Lagrange multiplier, and ρ is the iteration step size. Let be the power input from subregion f to subregion m at time t within subregion m; Let be the power input from subregion m to subregion f at time t; Let m be the purchased or exported power of subregion m at time t; Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within subregion m to complete the shutdown process; Let be the auxiliary variable for the state of the i-th thermal power unit within subregion m;

[0050] The iterative solution process based on the alternating direction multiplier method decomposes the optimization solution into multiple sub-regions, enabling the interaction and iteration of coupled information within these sub-regions.

[0051]

[0052]

[0053] Wherein, the superscript k represents the k-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method, and the superscript (k-1) represents the (k-1)-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method; The k-th iteration value of the variable set in subregion m, F m Let m be the function for the cost of upgrading units within sub-region m. and For the Lagrange multiplier λ m The values ​​of the (k-1)th and kth iterations, The number of subregions connected to subregion m; Let be the power variable input from subregion f to subregion m at time t within subregion m; Let be the (k-1)th iteration value of the power input from sub-region f to sub-region m at time t. Let f be the (k-1)th iteration value of the power input from sub-region m to sub-region f at time t;

[0054] Convergence criterion for iterative process based on alternating direction multiplier method:

[0055]

[0056] Among them, gap m Let ε be the iterative residual of subregion m. m is the convergence threshold for subregion m.

[0057] According to another aspect of the present invention, a power system unit planning system for large-scale renewable energy consumption is provided, the system comprising:

[0058] The transformation and optimization target determination unit is used to determine the transformation and optimization targets of each regional power grid in the power system;

[0059] The constraint construction unit is used to construct the power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints for each regional power grid.

[0060] The retrofit state variable determination unit is used to solve the retrofit optimization target, power balance constraint suite, reserve capacity constraint, thermal power unit operation constraint and transmission power constraint to determine the thermal power unit retrofit state variables for each region.

[0061] The planning unit is used to plan the power system units based on the state variables of the thermal power unit renovation.

[0062] Preferably, the optimization target determination unit determines the transformation and optimization targets for each regional power grid in the power system, including:

[0063]

[0064] Among them, F m Cost of retrofitting units within sub-region m; The number of thermal power units within sub-region m; Let i be the state variable for the modification of the i-th thermal power unit within sub-region m; Let $ be the minimum output modification cost for the i-th thermal power unit within sub-region m. Let $\frac{i}{m}$ be the cost of upgrading the ramp rate of the $i$-th thermal power unit within sub-region $m$.

[0065] Preferably, the power balance constraint condition includes:

[0066]

[0067] in, This refers to the number of thermal power units. Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t.

[0068] Preferably, the standby capacity constraint includes:

[0069]

[0070] in, Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; The number of thermal power units within sub-region m; This represents the upper limit of the output of the i-th thermal power unit within subregion m; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t; Let m be the reserve capacity requirement at time t within subregion m.

[0071] Preferably, the operating constraints of the thermal power unit include:

[0072] Upper and lower limits of thermal power unit generating capacity constraints:

[0073]

[0074] Thermal power unit output ramp-up constraints:

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082] Minimum continuous start-up and shutdown operating time constraints for thermal power units:

[0083]

[0084]

[0085] Constraints on the state variables and coupling relationships of thermal power units:

[0086]

[0087]

[0088]

[0089] in, Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m before its renovation. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m after its modification. This represents the upper limit of the generating power of the i-th thermal power unit within sub-region m; The power increase rate limit for the i-th thermal power unit within sub-region m before its modification; The power increase rate limit for the i-th thermal power unit within sub-region m after modification; The power reduction rate limit for the i-th thermal power unit within sub-region m before its modification; The power reduction rate limit for the i-th thermal power unit within sub-region m after modification; The starting power limit for the i-th thermal power unit within sub-region m; The shutdown power limit for the i-th thermal power unit within sub-region m; Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within sub-region m after completing the shutdown process; where . Let be the minimum continuous operating time of the i-th thermal power unit in subregion m. Let be the minimum continuous downtime of the i-th thermal power unit in subregion m; Let be the state variable indicating whether the i-th thermal power unit in subregion m is to be upgraded; Let be the stable operating state variable of the i-th thermal power unit in subregion m at time t; Let be the state variable for the i-th thermal power unit in subregion m to complete the start-up process; Let be the state variable for the i-th thermal power unit in subregion m to complete the shutdown process.

[0090] Preferably, the transmission power constraint includes:

[0091]

[0092]

[0093]

[0094] in, Let m be the purchased or exported power of subregion m at time t. Let m be the number of external connection lines to subregion m. The upper limit of the transmission power at the interface of the u-th external tie line in subregion m; Let be the power transmitted from subregion f to subregion m at time t; N represents the power transferred from subregion m to subregion f at time t. mf The number of communication lines between subregions m and f; This represents the maximum transmission power of the h-th sub-regional connection line between sub-regions m and f.

[0095] Preferably, the retrofit state variable determination unit solves the retrofit optimization objective, power balance constraint suite, reserve capacity constraint, thermal power unit operation constraint, and transmission power constraint to determine the thermal power unit retrofit state variables for each region, including:

[0096] Constructing a partition-optimized Lagrangian function for brightness enhancement based on the alternating direction multiplier method, including:

[0097]

[0098]

[0099] Based on the aforementioned Lagrange function, the retrofit optimization objective, the power balance constraint suite, the reserve capacity constraint, the thermal power unit operation constraint, and the transmission power constraint, the state variables of the thermal power unit retrofit for each region are determined.

[0100] Among them, L ρ For the augmented Lagrangian function, N G Ω represents the number of all subregions. m Let λ be the set of variables for subregion m. m Let ρ be the Lagrange multiplier and ρ be the iteration step size. Let be the power input from subregion f to subregion m at time t within subregion m; Let be the power input from subregion m to subregion f at time t; Let m be the purchased or exported power of subregion m at time t; Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within subregion m to complete the shutdown process; Let be the auxiliary variable for the state of the i-th thermal power unit within subregion m;

[0101] The iterative solution process based on the alternating direction multiplier method decomposes the optimization solution into multiple sub-regions, enabling the interaction and iteration of coupled information across these sub-regions.

[0102]

[0103]

[0104] Wherein, the superscript k represents the k-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method, and the superscript (k-1) represents the (k-1)-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method; The k-th iteration value of the variable set in subregion m, F m Let m be the function for the cost of upgrading units within sub-region m. and For the Lagrange multiplier λ m The values ​​of the (k-1)th and kth iterations, The number of subregions connected to subregion m; Let be the power variable input from subregion f to subregion m at time t within subregion m; Let be the (k-1)th iteration value of the power input from sub-region f to sub-region m at time t. Let f be the (k-1)th iteration value of the power input from sub-region m to sub-region f at time t;

[0105] Convergence criterion for iterative process based on alternating direction multiplier method:

[0106]

[0107] Among them, gap m Let ε be the iterative residual of subregion m. m is the convergence threshold for subregion m.

[0108] Based on another aspect of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the steps in a power system unit planning method for large-scale renewable energy consumption.

[0109] According to another aspect of the present invention, the present invention provides an electronic device, comprising:

[0110] The aforementioned computer-readable storage medium; and

[0111] One or more processors for executing a program in the computer-readable storage medium.

[0112] This invention provides a power system unit planning method and system for large-scale renewable energy consumption, comprising: determining the transformation and optimization objectives of each regional power grid in the power system; constructing power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints for each regional power grid; solving the transformation and optimization objectives, power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints to determine the thermal power unit transformation state variables for each region; and planning the power system units based on the thermal power unit transformation state variables. The method of this invention constructs a novel power system unit flexibility retrofit model by partitioning the system. The model aims to minimize retrofit costs and comprehensively considers the impact of operating and retrofit states on unit operating capacity, constructing multidimensional constraints. To address the issue of multiplier terms for operating and retrofit states in the model, a multiplier term linearization method based on auxiliary variables is proposed. To address the problem of high-dimensionality regional model variables and constraints, leading to significant solution difficulties, a partitioned optimization method based on the alternating direction multiplier method is proposed. This method determines the thermal power unit retrofit state variables for each region and plans the power system units based on these thermal power unit retrofit state variables. This approach enables efficient and accurate planning of power system units, ensuring the stable operation of the power system. Attached Figure Description

[0113] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0114] Figure 1 This is a flowchart of a power system unit planning method 100 for large-scale renewable energy consumption according to an embodiment of the present invention;

[0115] Figure 2 This is a schematic diagram of the structure of a power system unit planning system 200 for large-scale renewable energy consumption according to an embodiment of the present invention. Detailed Implementation

[0116] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0117] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0118] This invention constructs a novel power system unit flexibility retrofit model by partitioning the system. The model aims to minimize retrofit costs and comprehensively considers the impact of both operating and retrofit states on unit operating capacity, constructing multidimensional constraints. To address the issue of multiplier terms for operating and retrofit states in the model, a multiplier term linearization method based on auxiliary variables is proposed. Furthermore, to address the problem of high-dimensionality regional model variables and constraints, leading to significant solution difficulties, a partitioned optimization method based on the alternating direction multiplier method is proposed. This method determines the thermal power unit retrofit state variables for each region and plans the power system units based on these thermal power unit retrofit state variables. This approach enables efficient and accurate planning of power system units, ensuring the stable operation of the power system.

[0119] Figure 1 This is a flowchart of a power system unit planning method 100 for large-scale renewable energy consumption according to an embodiment of the present invention. Figure 1 As shown, the power system unit planning method 100 for large-scale new energy consumption provided by the embodiment of the present invention starts from step 101, in which the transformation and optimization targets of each regional power grid in the power system are determined.

[0120] Preferably, the determination of the transformation and optimization objectives for each regional power grid in the power system includes:

[0121]

[0122] Among them, F m Cost of retrofitting units within sub-region m; The number of thermal power units within sub-region m; Let i be the state variable for the modification of the i-th thermal power unit within sub-region m; Let $ be the minimum output modification cost for the i-th thermal power unit within sub-region m. Let $\frac{i}{m}$ be the cost of upgrading the ramp rate of the $i$-th thermal power unit within sub-region $m$.

[0123] In this invention, the power system is first divided into regions, and for any region, a regional power grid unit flexibility transformation and optimization target is constructed, which is to minimize the transformation cost.

[0124] The transformation and optimization objectives for any regional power grid are determined using the following methods:

[0125]

[0126] Among them, F m Cost of retrofitting units within sub-region m; The number of thermal power units within sub-region m; Let i be the state variable for the modification of the i-th thermal power unit within sub-region m; Let $ be the minimum output modification cost for the i-th thermal power unit within sub-region m. Let $\frac{i}{m}$ be the cost of upgrading the ramp rate of the $i$-th thermal power unit within sub-region $m$.

[0127] In step 102, the power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints of each regional power grid are constructed.

[0128] Preferably, the power balance constraint condition includes:

[0129]

[0130] in, This refers to the number of thermal power units. Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t.

[0131] Preferably, the standby capacity constraint includes:

[0132]

[0133] in, Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; The number of thermal power units within sub-region m; This represents the upper limit of the output of the i-th thermal power unit within subregion m; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t; Let m be the reserve capacity requirement at time t within subregion m.

[0134] Preferably, the operating constraints of the thermal power unit include:

[0135] Upper and lower limits of thermal power unit generating capacity constraints:

[0136]

[0137] Thermal power unit output ramp-up constraints:

[0138]

[0139]

[0140]

[0141]

[0142]

[0143]

[0144]

[0145] Minimum continuous start-up and shutdown operating time constraints for thermal power units:

[0146]

[0147]

[0148] Constraints on the state variables and coupling relationships of thermal power units:

[0149]

[0150]

[0151]

[0152] in, Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m before its renovation. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m after its modification; This represents the upper limit of the generating power of the i-th thermal power unit within sub-region m; The power increase rate limit for the i-th thermal power unit within sub-region m before its modification; The power increase rate limit for the i-th thermal power unit within sub-region m after modification; The power reduction rate limit for the i-th thermal power unit within sub-region m before its modification; The power reduction rate limit for the i-th thermal power unit within sub-region m after modification; The starting power limit for the i-th thermal power unit within sub-region m; The shutdown power limit for the i-th thermal power unit within sub-region m; Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within sub-region m that has completed the shutdown process; where . Let be the minimum continuous operating time of the i-th thermal power unit in subregion m. Let be the minimum continuous downtime of the i-th thermal power unit in subregion m; Let be the state variable indicating whether the i-th thermal power unit in subregion m is to be upgraded; Let be the stable operating state variable of the i-th thermal power unit in subregion m at time t; Let be the state variable for the i-th thermal power unit in subregion m to complete the start-up process; Let be the state variable for the i-th thermal power unit in subregion m to complete the shutdown process.

[0153] Preferably, the transmission power constraint includes:

[0154]

[0155]

[0156]

[0157] in, Let m be the purchased or exported power of subregion m at time t. Let m be the number of external connection lines to subregion m. The upper limit of the transmission power at the interface of the u-th external tie line in subregion m; Let be the power transmitted from subregion f to subregion m at time t; N represents the power transferred from subregion m to subregion f at time t. mf The number of communication lines between subregions m and f; This represents the maximum transmission power of the h-th sub-regional connection line between sub-regions m and f.

[0158] In this invention, power balance constraints are constructed for the flexibility retrofitting of power grid units in each region. The constraints for regional power balance are mainly reflected in the power supply and demand balance relationship at each time point.

[0159]

[0160] In the formula, P C,i,t P represents the power generation of the i-th thermal power unit at time t; W,j,t Let N be the power generation of the j-th wind farm at time t; W P represents the number of wind farms in the regional power grid. S,k,t Let N be the power generation of the k-th photovoltaic system at time t; S P represents the number of photovoltaic systems in the regional power grid. O,t P represents the power of purchased electricity at time t. L,t Let t be the load power at time t.

[0161] Constructing regional power grid reserve capacity constraints:

[0162]

[0163] In the formula, u C,i,t Let P be the stable operating state variable of the i-th thermal power unit at time t; C,i,max P represents the upper limit of the output of the i-th thermal power unit; R,t Let t be the reserve capacity requirement at time t.

[0164] Regarding the construction of operating constraints for thermal power units: These constraints reflect the unit's output, ramp-up capability, and start-up / shutdown time requirements. Reducing the minimum stable combustion load of thermal power units can improve the absorption of renewable energy output, while enhancing the unit's ramp-up capability can balance the rapid random fluctuations of renewable energy.

[0165] 1. Construct upper and lower limits for the power generation capacity of thermal power units:

[0166] u C,i,t [(1-v C,i )P C,i,min +v C,i P′ C,i,min ]≤P C,i,t ≤u C,i,t P C,i,max (4)

[0167] In the formula, v C,iLet P be the state variable indicating whether the i-th thermal power unit needs to be upgraded. C,i,min P represents the lower limit of the power generation capacity of the i-th thermal power unit before its retrofit; C ' ,i,min This represents the lower limit of the generated power output after the upgrade; P C,i,max This represents the upper limit of the power generation capacity of the i-th thermal power unit.

[0168] 2. Constructing output ramp-up constraints for thermal power units:

[0169] P C,i,t -P C,i,t-1 ≤u C,i,t [(1-v C,i )P C,i,up +v C,i P′ C,i,up ]+y C,i,t P C,i,start (5)

[0170] P C,i,t-1 -P C,i,t ≤u C,i,t [(1-v C,i )P C,i,down +v C,i P′ C,i,down ]+z C,i,t P C,i,shut (6)

[0171] In the formula, P C,i,up P′ represents the power increase rate limit before the i-th thermal power unit is upgraded. C,i,up P represents the power increase rate limit after the i-th thermal power unit is upgraded; C,i,down P′ represents the power reduction rate limit for the i-th thermal power unit before its retrofit; C,i,down P is the power reduction rate limit for the i-th thermal power unit after modification; C,i,start P is the starting power limit for the i-th thermal power unit; C,i,shut For the shutdown power limit of the i-th thermal power unit; y C,i,t z represents the state variable for the i-th thermal power unit to complete the start-up process. C,i,t Let be the state variable for the i-th thermal power unit to complete the shutdown process.

[0172] 3. Establish minimum continuous start-up and shutdown operating time constraints for thermal power units:

[0173]

[0174]

[0175] In the formula, T on,i T represents the minimum continuous operating time of the i-th thermal power unit. off,iLet be the minimum continuous downtime of the i-th thermal power unit.

[0176] 4. Construct state variable constraints for thermal power units. The self-constraints and coupling relationships of the state variables of thermal power units are as follows:

[0177] y C,i,t -z C,i,t =u C,i,t -u C,i,t-1 (9)

[0178] y C,i,t +z C,i,t ≤1 (10)

[0179] y C,i,t ,z C,i,t ,u C,i,t ,v C,i ∈{0,1} (11)

[0180] 5. Construct regional transmission power constraints.

[0181] Considering the cross-sectional transmission power limit of the interconnection lines between the regional power grid and the external power grid, the overall power purchased or transmitted from outside the region is subject to the following constraints:

[0182]

[0183] In the formula, P O,t N represents the purchased or transmitted power at time t. O P represents the number of external connection lines. O,u,max This represents the upper limit of the transmission power at the u-th external contact line interface.

[0184] 6. Considering the presence of variable multiplication terms in the model, auxiliary variables are added to linearize the model.

[0185] Considering the v in the upper and lower limits of unit output and the ramping constraint C,i and u C,i,t The multipliers cannot be solved directly. Therefore, we use an auxiliary variable to linearize the multipliers. The auxiliary variable is:

[0186] l C,i,t =u C,i,t v C,i (13)

[0187] Simultaneously, add constraints to this auxiliary variable:

[0188] l C,i,t ≤u C,i,t (14)

[0189] l C,i,t ≤v C,i (15)

[0190] l C,i,t ≥u C,i,t +v C,i -1 (16)

[0191] l C,i,t ∈{0,1} (17)

[0192] Then the unit output upper and lower limit constraints and ramp constraints (step 4) formulas (4) to (6) are transformed into:

[0193] (u C,i,t -l C,i,t )P C,i,min +l C,i,t P′ C,i,min ≤P C,i,t ≤u C,i,t P C,i,max (18)

[0194] P C,i,t -P C,i,t-1 ≤(u C,i,t -l C,i,t )P C,i,up +l C,i,t P′ C,i,up +y C,i,t P C,i,start (19)

[0195] P C,i,t-1 -P C,i,t ≤(u C,i,t -l C,i,t )P C,i,down +l C,i,t P′ C,i,down +z C,i,t P C,i,shut (20)

[0196] If the power grid is partitioned, similarly, the constraints for constructing any sub-region m can be obtained as follows:

[0197] 1. Power balance constraints, including:

[0198]

[0199] in, This refers to the number of thermal power units. Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t.

[0200] 2. Reserve capacity constraints, including:

[0201]

[0202] in, Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; The number of thermal power units within sub-region m; This represents the upper limit of the output of the i-th thermal power unit within subregion m; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t; Let m be the reserve capacity requirement at time t within subregion m.

[0203] 3. Operating constraints of thermal power units, including:

[0204] Upper and lower limits of thermal power unit generating capacity constraints:

[0205]

[0206] Thermal power unit output ramp-up constraints:

[0207]

[0208]

[0209]

[0210]

[0211]

[0212]

[0213]

[0214] Minimum continuous start-up and shutdown operating time constraints for thermal power units:

[0215]

[0216]

[0217] Constraints on the state variables of thermal power units and their coupling relationships:

[0218]

[0219]

[0220]

[0221] in, Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m before its renovation. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m after its modification; This represents the upper limit of the generating power of the i-th thermal power unit within sub-region m; The power increase rate limit for the i-th thermal power unit within sub-region m before its modification; The power increase rate limit for the i-th thermal power unit within sub-region m after modification; The power reduction rate limit for the i-th thermal power unit within sub-region m before its modification; The power reduction rate limit for the i-th thermal power unit within sub-region m after modification; The starting power limit for the i-th thermal power unit within sub-region m; The shutdown power limit for the i-th thermal power unit within sub-region m; Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within sub-region m after completing the shutdown process; where . Let be the minimum continuous operating time of the i-th thermal power unit in subregion m. Let be the minimum continuous downtime of the i-th thermal power unit in subregion m; Let be the state variable indicating whether the i-th thermal power unit in subregion m is to be upgraded; Let be the stable operating state variable of the i-th thermal power unit in subregion m at time t; Let be the state variable for the i-th thermal power unit in subregion m to complete the start-up process; Let be the state variable for the i-th thermal power unit in subregion m to complete the shutdown process.

[0222] 4. Transmission power constraints, including:

[0223]

[0224]

[0225]

[0226] in, Let m be the purchased or exported power of subregion m at time t. Let m be the number of external connection lines to subregion m. The upper limit of the transmission power at the interface of the u-th external tie line in subregion m; Let be the power transmitted from subregion f to subregion m at time t; N represents the power transferred from subregion m to subregion f at time t. mf The number of communication lines between subregions m and f; This represents the maximum transmission power of the h-th sub-regional connection line between sub-regions m and f.

[0227] For example, if a power system is divided into two sub-regions, A and B, then the optimization objective of the model for sub-region A can be:

[0228]

[0229] In the formula, F A This represents the cost of upgrading units within sub-region A; variables with the superscript A are the corresponding variables within sub-region A.

[0230] Since the original region is divided into sub-regions, there is a power connection between the two sub-regions. Therefore, the power balance constraint formula (2) in sub-region A is transformed into:

[0231]

[0232] In the formula, P t A Let t be the power received by sub-region A from sub-region B.

[0233] The reserve capacity constraint formula (3) is transformed into:

[0234]

[0235] The regional transmission power constraint formula (12) is transformed into:

[0236]

[0237] P t A +P 0,t =0 (25)

[0238]

[0239] In the formula, P 0,t N represents the power transmitted from sub-region A to sub-region B at time t. AB P represents the number of communication lines between sub-regions A and B. AB,h,max This represents the maximum transmission power of the h-th sub-regional connection line.

[0240] In summary, equations (21) to (26) and the constraints in the thermal power unit operation constraints can constitute the flexible transformation planning model for sub-region A.

[0241] The optimization objective for subregion B is:

[0242]

[0243] In the formula, F B This refers to the cost of upgrading units within sub-region B; the variable with the superscript B is the corresponding variable within sub-region B.

[0244] The charge balance constraint within sub-region B is transformed into:

[0245]

[0246] Reserve capacity constraints transformed into

[0247]

[0248] The regional transmission power constraint is transformed into:

[0249]

[0250] P t B -P 0,t =0 (31)

[0251]

[0252] In summary, equations (27) to (32), along with the constraints in the thermal power unit operation constraints, constitute the flexible transformation planning model for sub-region B.

[0253] In step 103, the state variables of the thermal power unit renovation are determined by solving the aforementioned renovation and optimization objectives, power balance constraint suite, reserve capacity constraint conditions, thermal power unit operation constraint conditions, and transmission power constraint conditions.

[0254] Preferably, the process of solving for the state variables of the thermal power unit renovation in each region based on the renovation optimization objective, power balance constraint suite, reserve capacity constraint, thermal power unit operation constraint, and transmission power constraint includes:

[0255] Constructing a partition-optimized Lagrangian function for brightness enhancement based on the alternating direction multiplier method, including:

[0256]

[0257]

[0258] Based on the aforementioned Lagrange function, the retrofit optimization objective, the power balance constraint suite, the reserve capacity constraint, the thermal power unit operation constraint, and the transmission power constraint, the state variables of the thermal power unit retrofit for each region are determined.

[0259] Among them, L ρ For the augmented Lagrangian function, N G Ω represents the number of all subregions. m Let λ be the set of variables for subregion m. m Let ρ be the Lagrange multiplier and ρ be the iteration step size. Let be the power input from subregion f to subregion m at time t within subregion m; Let be the power input from subregion m to subregion f at time t; Let m be the purchased or exported power of subregion m at time t; Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within subregion m to complete the shutdown process; Let be the auxiliary variable for the state of the i-th thermal power unit within subregion m;

[0260] The iterative solution process based on the alternating direction multiplier method decomposes the optimization solution into multiple sub-regions, enabling the interaction and iteration of coupled information across these sub-regions.

[0261]

[0262]

[0263] Wherein, the superscript k represents the k-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method, and the superscript (k-1) represents the (k-1)-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method; The k-th iteration value of the variable set in subregion m, F m Let m be the function for the cost of upgrading units within sub-region m. and For the Lagrange multiplier λ m The values ​​of the (k-1)th and kth iterations, The number of subregions connected to subregion m; Let be the power variable input from subregion f to subregion m at time t within subregion m; Let be the (k-1)th iteration value of the power input from sub-region f to sub-region m at time t. Let f be the (k-1)th iteration value of the power input from sub-region m to sub-region f at time t;

[0264] Convergence criterion for iterative process based on alternating direction multiplier method:

[0265]

[0266] Among them, gap m Let ε be the iterative residual of subregion m. m is the convergence threshold for subregion m.

[0267] In step 104, the power system units are planned based on the state variables of the thermal power unit renovation.

[0268] In this invention, considering the large dimensionality of variables and constraints and the high difficulty of solving when the regional power grid contains a large number of thermal power units, a partition optimization method based on the alternating direction multiplier method is proposed, including:

[0269] Constructing a partition-optimized Lagrangian function for brightness enhancement based on the alternating direction multiplier method, including:

[0270]

[0271]

[0272] Based on the aforementioned Lagrange function, the retrofit optimization objective, the power balance constraint suite, the reserve capacity constraint, the thermal power unit operation constraint, and the transmission power constraint, the state variables of the thermal power unit retrofit for each region are determined.

[0273] Among them, L ρ For the augmented Lagrangian function, N G Ω represents the number of all subregions. m Let λ be the set of variables for subregion m. m Let ρ be the Lagrange multiplier and ρ be the iteration step size. Let be the power input from subregion f to subregion m at time t within subregion m; Let be the power input from subregion m to subregion f at time t; Let m be the purchased or exported power of subregion m at time t; Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within subregion m to complete the shutdown process; Let be the auxiliary variable for the state of the i-th thermal power unit within subregion m;

[0274] The iterative solution process based on the alternating direction multiplier method decomposes the optimization solution into multiple sub-regions, enabling the interaction and iteration of coupled information across these sub-regions.

[0275]

[0276]

[0277] Wherein, the superscript k represents the k-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method, and the superscript (k-1) represents the (k-1)-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method; The k-th iteration value of the variable set in subregion m, F m Let m be the function for the cost of upgrading units within sub-region m. and For the Lagrange multiplier λ m The values ​​of the (k-1)th and kth iterations, The number of subregions connected to subregion m; Let be the power variable input from subregion f to subregion m at time t within subregion m; Let be the (k-1)th iteration value of the power input from sub-region f to sub-region m at time t. Let f be the (k-1)th iteration value of the power input from sub-region m to sub-region f at time t;

[0278] Convergence criterion for iterative process based on alternating direction multiplier method:

[0279]

[0280] Among them, gap m Let ε be the iterative residual of subregion m. m is the convergence threshold for subregion m.

[0281] The planning scheme of this invention is to determine the state variable v of each unit to determine whether it needs to undergo flexibility modification. C,i However, because the planning takes into account the timing impact of new energy power generation, i.e., operational needs, the planning model also includes operational-related variables y. C,i,t ,z C,i,t ,u C,i,t P O,t and P C,i,t There is also an auxiliary variable l that increases due to the presence of multipliers. C,i,t However, these six variables are auxiliary variables in the planning model, and their solutions do not belong to the planning scheme. Therefore, after determining the state variables of the thermal power unit retrofit in each region, the power system units can be planned directly based on these thermal power unit retrofit state variables.

[0282] Continuing with regions A and B as examples, for the unit flexibility modification model of the two sub-regions, an augmented Lagrangian function based on the alternating direction multiplier method for zonal optimization is constructed:

[0283]

[0284]

[0285]

[0286] In the formula, L ρ For the augmented Lagrangian function, Ω A Let Ω be the set of variables in region A. B Let be the set of variables in region B, λ1 and λ2 be Lagrange multipliers, and ρ be the iteration step size.

[0287] The iterative solution process based on the alternating direction multiplier method can decompose the optimization solution into two independent sub-regions, and through coupling variables P 0,t Enables interaction and iteration of coupled information between two sub-regions.

[0288] The objective function of the k-th solution in subregion A is transformed into The objective function of the k-th solution in subregion A is transformed into The sub-region constraints remain unchanged, as do those in 7-1. Therefore, Ω A and Ω BThe formulas for the k-th iteration solution are abstracted as equations (36) and (37).

[0289]

[0290]

[0291] Subregion coupling variable P 0,t The formula for the k-th iteration solution is:

[0292]

[0293] The formula for the k-th iteration solution of the parameters λ1 and λ2 related to the Lagrange augmented function is:

[0294]

[0295]

[0296] In the formula, the superscript (k) represents the k-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method, and the superscript (k-1) represents the (k-1)-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method.

[0297] Convergence criterion for iterative process based on alternating direction multiplier method:

[0298]

[0299]

[0300]

[0301] In the formula, gap1, gap2 and gap3 are the iterative residuals within subregion A, within subregion B and within the coupling variable itself, respectively, and ε1, ε2 and ε3 are the convergence thresholds within subregion A, within subregion B and within the coupling variable itself, respectively.

[0302] Finally, the power system units are planned based on the state variables of the thermal power unit transformation obtained from the solution.

[0303] Figure 2 This is a schematic diagram of a power system unit planning system 200 for large-scale renewable energy consumption according to an embodiment of the present invention. Figure 2 As shown, the power system unit planning system 200 for large-scale new energy consumption provided by the embodiments of the present invention includes: a retrofit and optimization target determination unit 201, a constraint condition construction unit 202, a retrofit state variable determination unit 203, and a planning unit 204.

[0304] Preferably, the transformation and optimization target determination unit 201 is used to determine the transformation and optimization targets of each regional power grid in the power system.

[0305] Preferably, the optimization target determination unit 201 determines the transformation and optimization targets of each regional power grid in the power system, including:

[0306]

[0307] Among them, F m Cost of retrofitting units within sub-region m; The number of thermal power units within sub-region m; Let i be the state variable for the modification of the i-th thermal power unit within sub-region m; Let $ be the minimum output modification cost for the i-th thermal power unit within sub-region m. Let $\frac{i}{m}$ be the cost of upgrading the ramp rate of the $i$-th thermal power unit within sub-region $m$.

[0308] Preferably, the power balance constraint condition includes:

[0309]

[0310] in, This refers to the number of thermal power units. Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t.

[0311] Preferably, the constraint construction unit 202 is used to construct the power balance constraint, reserve capacity constraint, thermal power unit operation constraint, and transmission power constraint for each regional power grid.

[0312] Preferably, the standby capacity constraint includes:

[0313]

[0314] in, Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; The number of thermal power units within sub-region m; This represents the upper limit of the output of the i-th thermal power unit within subregion m; Let be the power generation capacity of the j-th wind farm within sub-region m at time t; The number of wind farms in the power grid within sub-region m; Let be the power generation of the k-th photovoltaic system within sub-region m at time t; Let m be the number of photovoltaic systems in the power grid within sub-region m. Let be the power of the purchased electricity within sub-region m at time t; The number of subregions connected to subregion m; Let be the power received by subregion m from subregion f at time t; Let be the load power within subregion m at time t; Let m be the reserve capacity requirement at time t within subregion m.

[0315] Preferably, the operating constraints of the thermal power unit include:

[0316] Upper and lower limits of thermal power unit generating capacity constraints:

[0317]

[0318] Thermal power unit output ramp-up constraints:

[0319]

[0320]

[0321]

[0322]

[0323]

[0324]

[0325]

[0326] Minimum continuous start-up and shutdown operating time constraints for thermal power units:

[0327]

[0328]

[0329] Constraints on the state variables and coupling relationships of thermal power units:

[0330]

[0331]

[0332]

[0333] in, Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m before its renovation. This represents the lower limit of the power generation capacity of the i-th thermal power unit within sub-region m after its modification. This represents the upper limit of the generating power of the i-th thermal power unit within sub-region m; The power increase rate limit for the i-th thermal power unit within sub-region m before its modification; The power increase rate limit for the i-th thermal power unit within sub-region m after modification; The power reduction rate limit for the i-th thermal power unit within sub-region m before its modification; The power reduction rate limit for the i-th thermal power unit within sub-region m after modification; The starting power limit for the i-th thermal power unit within sub-region m; The shutdown power limit for the i-th thermal power unit within sub-region m; Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within sub-region m after completing the shutdown process; where . Let be the minimum continuous operating time of the i-th thermal power unit in subregion m. Let be the minimum continuous downtime of the i-th thermal power unit in subregion m; Let be the state variable indicating whether the i-th thermal power unit in subregion m is to be upgraded; Let be the stable operating state variable of the i-th thermal power unit in subregion m at time t; Let be the state variable for the i-th thermal power unit in subregion m to complete the start-up process; Let be the state variable for the i-th thermal power unit in subregion m to complete the shutdown process.

[0334] Preferably, the transmission power constraint includes:

[0335]

[0336]

[0337]

[0338] in, Let m be the purchased or exported power of subregion m at time t. Let m be the number of external connection lines to subregion m. The upper limit of the transmission power at the interface of the u-th external tie line in subregion m; Let be the power transmitted from subregion f to subregion m at time t; N represents the power transferred from subregion m to subregion f at time t. mf The number of communication lines between subregions m and f; This represents the maximum transmission power of the h-th sub-regional connection line between sub-regions m and f.

[0339] Preferably, the modification state variable determination unit 203 is used to solve the modification optimization target, power balance constraint suite, reserve capacity constraint, thermal power unit operation constraint and transmission power constraint to determine the thermal power unit modification state variables for each region.

[0340] Preferably, the retrofit state variable determination unit 203 solves the retrofit optimization objective, power balance constraint suite, reserve capacity constraint, thermal power unit operation constraint, and transmission power constraint to determine the thermal power unit retrofit state variables for each region, including:

[0341] Constructing a partition-optimized Lagrangian function for brightness enhancement based on the alternating direction multiplier method, including:

[0342]

[0343]

[0344] Based on the aforementioned Lagrange function, the retrofit optimization objective, the power balance constraint suite, the reserve capacity constraint, the thermal power unit operation constraint, and the transmission power constraint, the state variables of the thermal power unit retrofit for each region are determined.

[0345] Among them, L ρ For the augmented Lagrangian function, N G Ω represents the number of all subregions. m Let λ be the set of variables for subregion m. m Let ρ be the Lagrange multiplier and ρ be the iteration step size. Let be the power input from subregion f to subregion m at time t within subregion m; Let be the power input from subregion m to subregion f at time t; Let m be the purchased or exported power of subregion m at time t; Let be the power generation capacity of the i-th thermal power unit within sub-region m at time t; Let i be the state variable indicating whether the i-th thermal power unit within subregion m should be upgraded. Let be the stable operating state variable of the i-th thermal power unit within sub-region m at time t; Let be the state variable for the i-th thermal power unit within sub-region m to complete the start-up process; Let be the state variable for the i-th thermal power unit within subregion m to complete the shutdown process; Let be the auxiliary variable for the state of the i-th thermal power unit within subregion m;

[0346] The iterative solution process based on the alternating direction multiplier method decomposes the optimization solution into multiple sub-regions, enabling the interaction and iteration of coupled information across these sub-regions.

[0347]

[0348]

[0349] Wherein, the superscript k represents the k-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method, and the superscript (k-1) represents the (k-1)-th calculation result of the corresponding variable in the iterative process based on the alternating direction multiplier method; The k-th iteration value of the variable set in subregion m, F m Let m be the function for the cost of upgrading units within sub-region m. and For the Lagrange multiplier λ m The values ​​of the (k-1)th and kth iterations, The number of subregions connected to subregion m; Let be the power variable input from subregion f to subregion m at time t within subregion m; Let be the (k-1)th iteration value of the power input from sub-region f to sub-region m at time t. Let f be the (k-1)th iteration value of the power input from sub-region m to sub-region f at time t;

[0350] Convergence criterion for iterative process based on alternating direction multiplier method:

[0351]

[0352] Among them, gap m Let ε be the iterative residual of subregion m. m is the convergence threshold for subregion m.

[0353] Preferably, the planning unit 204 is used to plan the power system units based on the thermal power unit retrofit state variables.

[0354] The power system unit planning system 200 for large-scale renewable energy consumption in this embodiment corresponds to the power system unit planning method 100 for large-scale renewable energy consumption in another embodiment of this invention, and will not be described again here.

[0355] Based on another aspect of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the steps in a power system unit planning method for large-scale renewable energy consumption.

[0356] According to another aspect of the present invention, the present invention provides an electronic device, comprising:

[0357] The aforementioned computer-readable storage medium; and

[0358] One or more processors for executing a program in the computer-readable storage medium.

[0359] The invention has been described with reference to a few embodiments. However, as will be known to those skilled in the art, and as defined in the appended claims, other embodiments besides those disclosed above fall equivalently within the scope of the invention.

[0360] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the art, unless otherwise expressly defined herein. All references to “a / the / the [device, component, etc.]” ​​are openly interpreted as at least one instance of said device, component, etc., unless otherwise expressly stated. The steps of any method disclosed herein need not be performed in the exact order disclosed unless explicitly stated otherwise.

[0361] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0362] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0363] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0364] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0365] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A power system unit planning method for large-scale renewable energy consumption, characterized in that, The method includes: Determine the transformation and optimization objectives for each regional power grid within the power system; Construct power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints for each regional power grid; Based on the aforementioned transformation and optimization objectives, power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints, the state variables of thermal power unit transformation in each region are determined by solving the problems. Based on the aforementioned thermal power unit retrofit state variables, the power system units are planned; The process of solving for the state variables of thermal power unit renovation in each region based on the renovation and optimization objectives, power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints includes: Constructing an augmented Lagrangian function based on the alternating direction multiplier method for partition optimization, including: Based on the aforementioned Lagrange function, the renovation and optimization objective, the power balance constraint, the reserve capacity constraint, the thermal power unit operation constraint, and the transmission power constraint, the state variables of the thermal power unit renovation in each region are determined by solving the problem. in, For the augmented Lagrangian function, The number of all sub-regions, sub-region m The set of variables in the region For Lagrange multipliers, This is the iteration step size; sub-region m internal t Time sub-region m From sub-region f Input power; for t Time sub-region f From sub-region m Input power; sub-region m exist t The power of outbound purchases or deliveries at any given time; sub-region m Internal i One thermal power unit t Power generation at any given moment; sub-region m Internal i The state variable of whether a thermal power unit is to be upgraded; sub-region m Internal i One thermal power unit t The stable operating state variables at any given time; sub-region m Internal i The state variables of a thermal power unit completing the start-up process; sub-region m Internal i The state variables of a thermal power unit completing the shutdown process; sub-region m Internal i Auxiliary variables for the state of each thermal power unit; The iterative solution process based on the alternating direction multiplier method decomposes the optimization solution into multiple sub-regions, enabling the interaction and iteration of coupled information across these sub-regions. ， ， Wherein, the superscript k indicates the k-th iteration of the corresponding variable in the iterative process based on the alternating direction multiplier method. k The result of this calculation, superscript This indicates the corresponding variable in the iterative process based on the alternating direction multiplier method. The results of this calculation; subregion m The k-th iteration value of the variable set of the region. sub-region m Internal unit modification cost function, and Lagrange multipliers The values ​​of the (k-1)th and kth iterations, For sub-regions m Number of sub-regions connected; sub-region m internal t Time sub-region m From sub-region f The power variable input; for t Time sub-region m From sub-region f The input power value at the (k-1)th iteration. for t Time sub-region f From sub-region m The (k-1)th iteration value of the input power; Convergence criterion for iterative process based on alternating direction multiplier method: ， in, sub-region m The iterative residual, sub-region m The convergence threshold.

2. The method according to claim 1, characterized in that, The determination of the transformation and optimization objectives for each regional power grid in the power system includes: ， in, sub-region m Internal unit modification costs; sub-region m Number of internal thermal power units; sub-region m Inner i State variables of the thermal power unit renovation; sub-region m Inner i Minimum output modification cost for a thermal power unit; sub-region m Inner i Cost of upgrading the ramp rate of a thermal power unit.

3. The method according to claim 1, characterized in that, The power balance constraint conditions include: ， in, This refers to the number of thermal power units. sub-region m Internal i One thermal power unit t Power generation at any given moment; sub-region m Internal j A wind farm in t Power generation at any given moment; sub-region m Number of wind farms within the internal power grid; sub-region m Internal k A photovoltaic system in t Power generation at any given moment; sub-region m Number of photovoltaic systems in the internal power grid; sub-region m Internal and external power consumption t Power at any given moment; For sub-regions m Number of sub-regions connected; for t Time sub-region m From sub-region f Received power; sub-region m internal t Load power at any given time.

4. The method according to claim 1, characterized in that, The standby capacity constraints include: ， in, sub-region m Internal i One thermal power unit t The stable operating state variables at any given time; sub-region m Number of internal thermal power units; sub-region m Internal i The maximum output of each thermal power unit; sub-region m Internal j A wind farm in t Power generation at any given moment; sub-region m Number of wind farms within the internal power grid; sub-region m Internal k A photovoltaic system in t Power generation at any given moment; sub-region m Number of photovoltaic systems in the internal power grid; sub-region m Internal and external power consumption t Power at any given moment; For sub-regions m Number of sub-regions connected; for t Time sub-region m From sub-region f Received power; sub-region m internal t Load power at any given time; sub-region m internal t The required reserve capacity at any time.

5. The method according to claim 1, characterized in that, The operating constraints of the thermal power unit include: Upper and lower limits of thermal power unit generating capacity constraints: ， Thermal power unit output ramp-up constraints: ， ， ， ， ， ， ， Minimum continuous start-up and shutdown operating time constraints for thermal power units: ， ， Constraints on the state variables of thermal power units and their coupling relationships: ， ， ， in, sub-region m Internal i The state variable of whether a thermal power unit is to be upgraded; sub-region m Internal i The lower limit of power generation capacity of each thermal power unit before renovation; sub-region m Internal i Lower limit of power generation capacity of each thermal power unit after renovation; sub-region m Internal i Maximum power generation capacity of each thermal power unit; sub-region m Internal i The power increase rate limit of each thermal power unit before its renovation; sub-region m Internal i The power increase rate limit after the modification of a thermal power unit; sub-region m Internal i The power reduction rate limit of each thermal power unit before its renovation; sub-region m Internal i Limitation on the rate of power reduction of each thermal power unit after modification; sub-region m Internal i Starting power limit for individual thermal power units; sub-region m Internal i Power shutdown limit for individual thermal power units; sub-region m Internal i One thermal power unit t The stable operating state variables at any given time; sub-region m Internal i The state variables of a thermal power unit completing the start-up process; sub-region m Internal i The state variables of each thermal power unit completing the shutdown process; among them. sub-region m No. i Minimum continuous operating time for each thermal power unit sub-region m No. i Minimum continuous downtime of each thermal power unit; sub-region m No. i The state variable of whether a thermal power unit is to be upgraded; sub-region m No. i One thermal power unit t The stable operating state variables at any given time; sub-region m No. i The state variables of a thermal power unit completing the start-up process; sub-region m No. i The state variables of a thermal power unit completing the shutdown process.

6. The method according to claim 1, characterized in that, The transmission power constraint conditions include: ， ， ， in, sub-region m exist t Power of outbound purchase or delivery at any time sub-region m Number of external communication lines sub-region m No. u Maximum power limit for external communication line interface transmission; for t From the sub-region f Transported to sub-region m The power; for t From the sub-region m Transported to sub-region f The power; sub-region m and f The number of communication lines between them; sub-region m and f Between h The maximum transmission power of the strip area connection line.

7. A power system unit planning system for large-scale renewable energy consumption, characterized in that, The system includes: The transformation and optimization target determination unit is used to determine the transformation and optimization targets of each regional power grid in the power system; The constraint construction unit is used to construct the power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints for each regional power grid. The retrofit state variable determination unit is used to solve the retrofit optimization target, power balance constraint, reserve capacity constraint, thermal power unit operation constraint and transmission power constraint to determine the thermal power unit retrofit state variables for each region. The planning unit is used to plan the power system units based on the state variables of the thermal power unit retrofit. The modification state variable determination unit, based on the modification optimization objective, power balance constraints, reserve capacity constraints, thermal power unit operation constraints, and transmission power constraints, solves to determine the thermal power unit modification state variables for each region, including: Constructing an augmented Lagrangian function based on the alternating direction multiplier method for partition optimization, including: Based on the aforementioned Lagrange function, the renovation and optimization objective, the power balance constraint, the reserve capacity constraint, the thermal power unit operation constraint, and the transmission power constraint, the state variables of the thermal power unit renovation in each region are determined by solving the problem. in, For the augmented Lagrangian function, The number of all sub-regions, sub-region m The set of variables in the region For Lagrange multipliers, This is the iteration step size; sub-region m internal t Time sub-region m From sub-region f Input power; for t Time sub-region f From sub-region m Input power; sub-region m exist t The power of outbound purchases or deliveries at any given time; sub-region m Internal i One thermal power unit t Power generation at any given moment; sub-region m Internal First i The state variable of whether a thermal power unit is to be upgraded; sub-region m Internal i One thermal power unit t The stable operating state variables at any given time; sub-region m Internal First i The state variables of a thermal power unit completing the start-up process; sub-region m Internal i The state variables of a thermal power unit completing the shutdown process; sub-region m Internal First i Auxiliary variables for the state of each thermal power unit; The iterative solution process based on the alternating direction multiplier method decomposes the optimization solution into multiple sub-regions, enabling the interaction and iteration of coupled information across these sub-regions. ， ， Wherein, the superscript k indicates the k-th iteration of the corresponding variable in the iterative process based on the alternating direction multiplier method. k The result of this calculation, superscript This indicates the corresponding variable in the iterative process based on the alternating direction multiplier method. The results of this calculation; subregion m The k-th iteration value of the variable set of the region. sub-region m Internal unit modification cost function, and Lagrange multipliers The values ​​of the (k-1)th and kth iterations, For sub-regions m Number of sub-regions connected; sub-region m internal t Time sub-region m From sub-region f The power variable input; for t Time sub-region m From sub-region f The input power value at the (k-1)th iteration. for t Time sub-region f From sub-region m The (k-1)th iteration value of the input power; Convergence criterion for iterative process based on alternating direction multiplier method: ， in, sub-region m The iterative residual, sub-region m The convergence threshold.

8. The system according to claim 7, characterized in that, The optimization target determination unit determines the transformation and optimization targets for each regional power grid in the power system, including: ， in, sub-region m Internal unit modification costs; sub-region m Number of internal thermal power units; sub-region m Inner i State variables of the thermal power unit renovation; sub-region m Inner i Minimum output modification cost for a thermal power unit; sub-region m Inner i Cost of upgrading the ramp rate of a thermal power unit.

9. The system according to claim 7, characterized in that, The power balance constraint conditions include: ， in, This refers to the number of thermal power units. sub-region m Internal First i One thermal power unit t Power generation at any given moment; sub-region m Internal First j A wind farm in t Power generation at any given moment; sub-region m Number of wind farms within the internal power grid; sub-region m Internal First k A photovoltaic system in t Power generation at any given moment; sub-region m Number of photovoltaic systems in the internal power grid; sub-region m Internal and external power consumption t Power at any given moment; For sub-regions m Number of sub-regions connected; for t Time sub-region m From sub-region f Received power; sub-region m internal t Load power at any given time.

10. The system according to claim 7, characterized in that, The standby capacity constraints include: ， in, sub-region m Internal First i One thermal power unit t The stable operating state variables at any given time; sub-region m Number of internal thermal power units; sub-region m Internal First i The maximum output of each thermal power unit; sub-region m Internal First j A wind farm in t Power generation at any given moment; sub-region m Number of wind farms within the internal power grid; sub-region m Internal First k A photovoltaic system in t Power generation at any given moment; sub-region m Number of photovoltaic systems in the internal power grid; sub-region m Internal and external power consumption t Power at any given moment; For sub-regions m Number of sub-regions connected; for t Time sub-region m From sub-region f Received power; sub-region m internal t Load power at any given time; sub-region m internal t The required reserve capacity at any time.

11. The system according to claim 7, characterized in that, The operating constraints of the thermal power unit include: Upper and lower limits of thermal power unit generating capacity constraints: ， Thermal power unit output ramp-up constraints: ， ， ， ， ， ， ， Minimum continuous start-up and shutdown operating time constraints for thermal power units: ， ， Constraints on the state variables of thermal power units and their coupling relationships: ， ， ， in, sub-region m Internal First i The state variable of whether a thermal power unit is to be upgraded; sub-region m Internal First i The lower limit of power generation capacity of each thermal power unit before renovation; sub-region m Internal First i Lower limit of power generation capacity of each thermal power unit after renovation; sub-region m Internal First i Maximum power generation capacity of each thermal power unit; sub-region m Internal First i The power increase rate limit of each thermal power unit before its renovation; sub-region m Internal First i The power increase rate limit after the modification of a thermal power unit; sub-region m Internal First i The power reduction rate limit of each thermal power unit before its renovation; sub-region m Internal First i Limitation on the rate of power reduction of each thermal power unit after modification; sub-region m Internal First i Starting power limit for individual thermal power units; sub-region m Internal First i Power shutdown limit for individual thermal power units; sub-region m Internal First i One thermal power unit t The stable operating state variables at any given time; sub-region m Internal First i The state variables of a thermal power unit completing the start-up process; sub-region m Internal First i The state variables of each thermal power unit completing the shutdown process; among them. sub-region m No. i Minimum continuous operating time for each thermal power unit sub-region m No. i Minimum continuous downtime of each thermal power unit; sub-region m No. i The state variable of whether a thermal power unit is to be upgraded; sub-region m No. i One thermal power unit t The stable operating state variables at any given time; sub-region m No. i The state variables of a thermal power unit completing the start-up process; sub-region m No. i The state variables of a thermal power unit completing the shutdown process.

12. The system according to claim 7, characterized in that, The transmission power constraint conditions include: ， ， ， in, sub-region m exist t Power of outbound purchase or delivery at any time sub-region m Number of external communication lines sub-region m No. u Maximum power limit for external communication line interface transmission; for t From the sub-region f Transported to sub-region m The power; for t From the sub-region m Transported to sub-region f The power; sub-region m and f The number of communication lines between them; sub-region m and f Between h The maximum transmission power of the strip area connection line.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1-6.

14. An electronic device, characterized in that, include: The computer-readable storage medium as described in claim 13; as well as One or more processors for executing a program in the computer-readable storage medium.

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