Source network load storage collaborative planning method and system considering dynamic carbon emission factor of unit

Abstract

The invention provides a source network load storage collaborative planning method and system considering a unit dynamic carbon emission factor, and the method comprises the steps: obtaining the historical operation data and type information of a coal power unit in a to-be-planned region, and building a dynamic carbon emission factor model of the coal power unit in the to-be-planned region based on the historical operation data; based on each operation scene, the output of each aggregated coal power unit combination, the online capacity and the dynamic carbon emission factor model, determining the total carbon emission in the to-be-planned area under the planning duration; constructing a source network load storage low-carbon power system collaborative planning optimization model based on the objective function and the constraint condition; and obtaining the output and installed capacity of each type of unit in the to-be-planned region as decision variables, inputting the decision variables into the established source-grid-load-storage low-carbon power system collaborative planning optimization model, and performing solving to obtain a source-grid-load-storage collaborative optimization configuration scheme of the to-be-planned region. According to the technical scheme provided by the invention, the planning precision and the calculation solving efficiency are improved.

Description

Technical Field

[0001] This application relates to the field of power system operation optimization technology, and in particular to a source-grid-load-storage coordinated planning method and system that considers the dynamic carbon emission factor of generating units. Background Technology

[0002] Traditional power system planning methods generally use fixed carbon emission factors to estimate system carbon emissions. This method simplifies the carbon emission characteristics of coal-fired power units, estimating their carbon emissions linearly with power generation, resulting in relatively coarse planning models. However, with the increasing penetration of new energy sources, especially the large-scale integration of fluctuating and intermittent power sources such as wind and solar power, the operating mode of traditional thermal power units has changed significantly. Thermal power units are gradually shifting from being the primary power source to auxiliary and regulating power sources in the power system, undertaking more frequent peak-shaving and frequency regulation tasks, and their operating load rates are dynamically changing. In this context, fixed carbon emission factors cannot accurately reflect the true carbon emission characteristics of coal-fired power units under dynamic operating conditions. Specifically, the carbon emissions of thermal power units are closely related to their operating status, especially under low load or frequent start-stop conditions, where carbon emissions per unit of power generation may be significantly higher than under full-load operation. Because traditional models ignore the impact of unit load rate on carbon emissions, this leads to biases in carbon emission estimation, making system planning unable to effectively capture the emission characteristics of coal-fired power units at different load levels. Therefore, in power systems with a high proportion of renewable energy penetration, there is an urgent need to propose a scheme that can accurately characterize the dynamic carbon emission characteristics of thermal power units and develop a source-grid-load-storage coordinated planning scheme based on dynamic carbon emission factors. Summary of the Invention

[0003] This application provides a source-grid-load-storage coordinated planning method and system that considers the dynamic carbon emission factor of the unit, so as to at least solve the technical problem that the fixed carbon emission factor cannot accurately reflect the real carbon emission characteristics of coal-fired power units under dynamic operating conditions, resulting in the deviation of carbon emission estimation and the inability to accurately carry out source-grid-load-storage coordinated planning.

[0004] The first aspect of this application proposes a source-grid-load-storage coordinated planning method that considers the dynamic carbon emission factor of generating units. The method includes:

[0005] Obtain historical operating data and type information of coal-fired power units in the area to be planned, and construct a dynamic carbon emission factor model of coal-fired power units in the area to be planned based on the historical operating data. The operating data includes the load rate of coal-fired power units and the carbon emission per unit of electricity generated by coal-fired power units.

[0006] acquire each operation scene of a planning time length, an output and an online capacity of each aggregated coal-fired unit combination in the region to be planned, and determine a total carbon emission amount in the region to be planned under the planning time length based on the each operation scene, the output and the online capacity of the each aggregated coal-fired unit combination, and the dynamic carbon emission factor model;

[0007] build a target function with a minimum investment cost, a variable operation cost and a fixed operation cost of a power system as a target, build a source-grid-load-storage low-carbon power system collaborative planning optimization model based on the target function and constraint conditions with investment constraints, operation constraints, aggregated coal-fired unit capacity constraints, and total carbon emission amount constraints as the constraint conditions;

[0008] acquire an output and an installed capacity of each type of unit in the region to be planned as a decision variable, input the output and the installed capacity of each type of unit in the region to be planned into a pre-established source-grid-load-storage low-carbon power system collaborative planning optimization model, and solve the source-grid-load-storage low-carbon power system collaborative planning optimization model through a solver to obtain a source-grid-load-storage collaborative optimization configuration scheme of the region to be planned;

[0009] wherein the each type of unit includes a coal-fired unit, a hydroelectric unit, a wind power unit, a photovoltaic unit, and an energy storage unit;

[0010] the operation constraints include output constraints, ramp rate constraints, abandoned wind and light rate constraints, state of charge constraints, node power balance, and charging and discharging efficiency constraints.

[0011] Preferably, a calculation formula of the dynamic carbon emission factor model of the coal-fired unit in the region to be planned is as follows:

[0012]

[0013] x=P / Cap ol

[0014] wherein y is a carbon emission amount of the coal-fired unit per unit of electricity, x is a load rate of the coal-fired unit, P is an output of the aggregated coal-fired unit, Cap ol is an online capacity of the aggregated coal-fired unit, is a first regression parameter, is a second regression parameter.

[0015] Further, a calculation formula of the total carbon emission amount in the region to be planned under the planning time length is as follows:

[0016]

[0017] wherein E Gen is the total carbon emission amount, and p sWeight of the s-th scenario, N s Total number of aggregated scenarios, N GP Total number of aggregated coal unit groups, N T Total number of aggregated time points, P gp,s,t Output of the gp-th aggregated coal unit group in the s-th scenario at time t, Cap ol,gp,s,t On-line capacity of the gp-th aggregated coal unit group in the s-th scenario at time t.

[0018] Further, the calculation formula of the objective function is as follows:

[0019] min C Sys = C Inv + C Fix + C Oper

[0020] In the formula, C Sys Total cost of the power system, C Inv Total investment cost of units and lines, C Fix Total maintenance cost of units and lines, C Oper Total operation cost of the power system.

[0021] Further, the calculation formula of the investment constraint is as follows:

[0022]

[0023] O pv + O wp ≥ r install (O pv + O wp + O gp + O hp )

[0024] ∑P pv + ∑P wp ≥ r output (D-D cut )

[0025] In the formula, O u Installed capacity of the u-th unit, Maximum installed capacity of the u-th unit, gp for coal, hp for hydropower, wp for wind power, pv for photovoltaic, store for energy storage, line for line, O pv Device capacity of the photovoltaic unit, O wp Installed capacity of the wind power unit, O gp Installed capacity of the coal power unit, O hp Installed capacity of the hydropower unit, r install Minimum proportion of new energy installed capacity, Ppv P is the output of the photovoltaic unit wp D is the total load, D cut r is the cut load output is the proportion of new energy output not lower than the total output

[0026] The calculation formula of the output constraint is as follows:

[0027]

[0028] In the formula, P u is the output of the u-th unit

[0029] The calculation formula of the ramp rate constraint is as follows:

[0030]

[0031] In the formula, P gp,t+1 is the output of the coal-fired unit at t+1, P gp,t is the output of the coal-fired unit at t, η gp is the ramp rate of the coal-fired unit

[0032] The calculation formula of the wind and light curtailment rate constraint is as follows:

[0033]

[0034] In the formula, N wp is the total number of wind power units, N pv is the total number of photovoltaic units, is the amount of electricity curtailed by the wind power unit at t, is the amount of electricity curtailed by the photovoltaic unit at t, χ is the maximum wind and light curtailment rate is the predicted output of the wind power unit at t, is the predicted output of the photovoltaic unit at t;

[0035] The calculation formula of the state of charge constraint is as follows:

[0036] SOC store,min ≤ SOC store,t ≤ B store O store

[0037] In the formula, SOC store,min is the minimum state of charge of the energy storage unit, SOC store,t is the state of charge of the energy storage unit at t, B store is the energy storage duration of the energy storage unit, O store is the installed capacity of the energy storage unit

[0038] The calculation formula of the charging and discharging efficiency constraint is as follows:

[0039]

[0040] SOCt-1 store,t-1 is the state of charge of the energy storage unit at time t-1, η store is the charge and discharge efficiency of the energy storage unit;

[0041] The calculation formula of the node power balance is as follows:

[0042]

[0043] SOCt is the discharge power of the energy storage unit at time t, is the charge power of the energy storage unit at time t, D n,t is the load of node n at time t, is the load shedding of node n at time t, is the outgoing power of line l at time t, is the incoming power of line l at time t;

[0044] The calculation formula of the aggregated coal-fired power unit capacity constraint is as follows:

[0045]

[0046] Cap ol,t is the online capacity of the coal-fired power unit at time t, Cap ol,t-1 is the online capacity of the coal-fired power unit at time t-1, Cap op,t is the startup capacity of the coal-fired power unit at time t, Cap cl,t is the shutdown capacity of the coal-fired power unit at time t, T on is the startup time, Cap op,t-j is the startup capacity of the coal-fired power unit at time t-j, T off is the shutdown time, Cap cl,t-j is the shutdown capacity of the coal-fired power unit at time t-j;

[0047] The calculation formula of the total carbon emission constraint is as follows:

[0048] E Gen ≤ E Lim

[0049] E Lim is the carbon emission limit value.

[0050] The second aspect embodiment of the present application proposes a source-grid-load-storage collaborative planning system considering the dynamic carbon emission factor of the unit, comprising:

[0051] The first obtaining module is configured to obtain historical operation data and type information of coal power units in a region to be planned, and construct a dynamic carbon emission factor model of the coal power units in the region to be planned based on the historical operation data, wherein the operation data comprises a load rate of the coal power units and carbon emission per unit of power of the coal power units;

[0052] The second obtaining module is configured to obtain each operation scenario of a planning time length, output and online capacity of each aggregated coal power unit combination in the region to be planned, and determine overall carbon emission in the region to be planned under the planning time length based on the each operation scenario, the output and online capacity of the each aggregated coal power unit combination, and the dynamic carbon emission factor model;

[0053] The constructing module is configured to construct a target function with a minimum investment cost, variable operation cost and fixed operation cost of a power system as a target, construct a source-grid-load-storage low-carbon power system collaborative planning optimization model based on the target function and constraint conditions of investment constraints, operation constraints, aggregated coal power unit capacity constraints and overall carbon emission constraints;

[0054] The optimization module is configured to obtain output and installed capacity of each type of unit in the region to be planned as a decision variable, input the output and installed capacity of each type of unit in the region to be planned into a pre-established source-grid-load-storage low-carbon power system collaborative planning optimization model, and solve the source-grid-load-storage low-carbon power system collaborative planning optimization model by a solver to obtain a source-grid-load-storage collaborative optimization configuration scheme of the region to be planned.

[0055] The each type of unit comprises coal power units, hydropower units, wind power units, photovoltaic units and energy storage units.

[0056] The operation constraints comprise output constraints, ramp rate constraints, abandoned wind and light rate constraints, state of charge constraints, node power balance constraints and charging and discharging efficiency constraints.

[0057] Preferably, the dynamic carbon emission factor model of the coal power units in the region to be planned has the following calculation formula:

[0058]

[0059] x=P / Cap ol

[0060] In the formula, y is carbon emission per unit of power of the coal power units, x is the load rate of the coal power units, P is output of an aggregated coal power unit group, Cap ol is online capacity of the aggregated coal power unit group, is a first regression parameter, is a second regression parameter.

[0061] Further, the calculation formula of the total carbon emission in the to-be-planned area under the planning duration is as follows:

[0062]

[0063] In the formula, E Gen is the total carbon emission, p s is the weight of the s-th scenario, N s is the total number of scenarios, N GP is the number of aggregated coal-fired generating units, N T is the total number of aggregated time points in the planning duration, P gp,s,t is the output of the gp-th aggregated coal-fired generating unit combination in the s-th scenario at the t-th time point, Cap ol,gp,s,t is the online capacity of the gp-th aggregated coal-fired generating unit combination in the s-th scenario at the t-th time point.

[0064] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method of the first aspect.

[0065] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the method of the first aspect.

[0066] The technical scheme provided by the embodiments of the present application at least brings the following beneficial effects:

[0067] The application provides a source-grid-load-storage collaborative planning method and system considering a dynamic carbon emission factor of a unit, and the method comprises the following steps: obtaining historical operation data and type information of coal-fired units in a region to be planned, and constructing a dynamic carbon emission factor model of the coal-fired units in the region to be planned based on the historical operation data, wherein the operation data comprises a load rate of the coal-fired units and carbon emission of the coal-fired units per unit of electricity; obtaining output and online capacity of each aggregated coal-fired unit combination in the region to be planned in each operation scenario in a planning period, and determining total carbon emission in the region to be planned in the planning period based on the dynamic carbon emission factor model, the output and the online capacity of each aggregated coal-fired unit combination in each operation scenario; constructing a target function with the minimum investment cost, variable operation cost and fixed operation cost of a power system as the target, constructing a constraint condition with investment constraints, operation constraints, aggregated coal-fired unit capacity constraints and total carbon emission constraints, constructing a source-grid-load-storage low-carbon power system collaborative planning optimization model based on the target function and the constraint condition; obtaining output and installed capacity of each type of unit in the region to be planned as a decision variable, inputting the output and installed capacity of each type of unit in the region to be planned into the source-grid-load-storage low-carbon power system collaborative planning optimization model established in advance, and solving the source-grid-load-storage low-carbon power system collaborative planning optimization model by a solver to obtain a source-grid-load-storage collaborative optimization configuration scheme of the region to be planned; wherein the each type of unit comprises a coal-fired unit, a hydropower unit, a wind power unit, a photovoltaic unit and an energy storage unit; and the operation constraints comprise output constraints, ramp rate constraints, abandoned wind and light rate constraints, state of charge constraints, node power balance constraints and charging and discharging efficiency constraints. The technical scheme provided by the application improves the planning accuracy and calculation solving efficiency.

[0068] Additional aspects and advantages of the application will be made apparent by the following description and the appended claims. BRIEF DESCRIPTION OF DRAWINGS

[0069] The above and / or additional aspects and advantages of the application will become apparent and be made clear to those skilled in the art from the following description and the appended claims, taken in conjunction with the accompanying drawings.

[0070] Figure 1 A flowchart of a source-grid-load-storage collaborative planning method considering a dynamic carbon emission factor of a unit according to an embodiment of the application is provided;

[0071] Figure 2 A structural diagram of a source-grid-load-storage collaborative planning system considering a dynamic carbon emission factor of a unit according to an embodiment of the application is provided. DETAILED DESCRIPTION

[0072] Embodiments of the present application are described below in detail with reference to the accompanying drawings, wherein the same or similar components or components having the same or similar functions are denoted by the same or similar reference numerals throughout. The embodiments described below by reference to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as limiting the present application.

[0073] The source-grid-load-storage collaborative planning method and system considering the dynamic carbon emission factor of a unit provided by the present application, the method comprising: obtaining historical operation data and type information of coal-fired units in a region to be planned, and constructing a dynamic carbon emission factor model of the coal-fired units in the region to be planned based on the historical operation data, wherein the operation data comprises a load rate of the coal-fired units and a carbon emission per unit of electricity of the coal-fired units; obtaining the output and online capacity of each aggregated coal-fired unit combination in the region to be planned for each operation scenario of a planning period, and determining the total carbon emission in the region to be planned for the planning period based on the dynamic carbon emission factor model, the output and online capacity of each aggregated coal-fired unit combination, and each operation scenario; constructing an objective function with the minimum investment cost, variable operation cost and fixed operation cost of the power system as the target, constructing a constraint condition with investment constraints, operation constraints, aggregated coal-fired unit capacity constraints, and total carbon emission constraints, constructing a source-grid-load-storage low-carbon power system collaborative planning optimization model based on the objective function and the constraint condition; obtaining the output and installed capacity of each type of unit in the region to be planned as a decision variable, inputting the output and installed capacity of each type of unit in the region to be planned into the source-grid-load-storage low-carbon power system collaborative planning optimization model established in advance, and solving the source-grid-load-storage low-carbon power system collaborative planning optimization model through a solver to obtain a source-grid-load-storage collaborative optimization configuration scheme for the region to be planned; wherein the each type of unit comprises a coal-fired unit, a hydropower unit, a wind power unit, a photovoltaic unit, and an energy storage unit; the operation constraints comprise output constraints, ramp rate constraints, wind and light curtailment rate constraints, state of charge constraints, node power balance constraints, and charging and discharging efficiency constraints. The technical solution provided by the present application improves the planning accuracy and calculation and solving efficiency.

[0074] The source-grid-load-storage collaborative planning method and system considering the dynamic carbon emission factor of a unit of the embodiments of the present application are described below with reference to the accompanying drawings.

[0075] Embodiment one

[0076] Figure 1 A flowchart of a source-grid-load-storage collaborative planning method considering the dynamic carbon emission factor of a unit according to one embodiment of the present application is shown in Figure 1 as shown, the method comprises:

[0077] Step 1: Obtain historical operation data and type information of coal-fired power units in the region to be planned, and construct a dynamic carbon emission factor model of the coal-fired power units in the region to be planned based on the historical operation data, wherein the operation data includes load rate of the coal-fired power units and carbon emission per unit of electricity of the coal-fired power units;

[0078] In the embodiment of the present disclosure, the calculation formula of the dynamic carbon emission factor model of the coal-fired power units in the region to be planned is as follows:

[0079]

[0080] x = P / Cap ol

[0081] In the formula, y is the carbon emission per unit of electricity of the coal-fired power units, x is the load rate of the coal-fired power units, P is the output of a group of aggregated coal-fired power units, Cap ol is the online capacity of the group of aggregated coal-fired power units, is the first regression parameter, is the second regression parameter.

[0082] It should be noted that based on the data of carbon emission and specific load rate of different types of coal-fired power units (300 MW, 600 MW, 1000 MW), a reverse proportional function relationship is constructed to form a dynamic carbon emission factor model that can describe the carbon emission of coal-fired power units, wherein a reverse proportional linear regression modeling method of least squares is used.

[0083] Step 2: Obtain the output and online capacity of each aggregated coal-fired power unit combination in the region to be planned for each operation scenario in the planning period, and determine the total carbon emission in the region to be planned in the planning period based on the operation scenario, the output and online capacity of each aggregated coal-fired power unit combination, and the dynamic carbon emission factor model;

[0084] In the embodiment of the present disclosure, the calculation formula of the total carbon emission in the region to be planned in the planning period is as follows:

[0085]

[0086] In the formula, E Gen is the total carbon emission, p s is the weight of the s-th scenario, N s is the total number of aggregated scenarios, N GP is the number of aggregated coal-fired power unit combinations, N T is the total number of time points after aggregation in the planning period, P gp,s,t is the output of the gp-th coal-fired power unit combination after aggregation in the s-th scenario at t time point, Cap ol,gp,s,t is the online capacity of the gp-th coal-fired power unit combination after aggregation in the s-th scenario at t time point.

[0087] It should be noted that, wherein f(P gp,s,t / Cap ol,gp,s,t ) = y.

[0088] Step 3: A target function is constructed with the minimum investment cost, variable operation cost and fixed operation cost of the power system as the target, investment constraints, operation constraints, capacity constraints and total carbon emission constraints as the constraint conditions, and a source-grid-load-storage low-carbon power system collaborative planning optimization model is constructed based on the target function and the constraint conditions;

[0089] The operation constraints include output constraints, ramp rate constraints, wind and light curtailment rate constraints, state of charge constraints, node power balance constraints and charging and discharging efficiency constraints.

[0090] In the embodiments of the present disclosure, the calculation formula of the target function is as follows:

[0091] min C Sys = C Inv + C Fix + C Oper

[0092] In the formula, C Sys is the total cost of the power system, C Inv is the total investment cost of the units and lines, C Fix is the total maintenance cost of the units and lines, and C Oper is the total operation cost of the power system.

[0093] In the embodiments of the present disclosure, the calculation formula of the investment constraints is as follows:

[0094]

[0095] O pv + O wp ≥ r install (O pv + O wp + O gp + O hp )

[0096] ∑P pv + ∑P wp ≥ r output (D-D cut )

[0097] In the formula, O u is the installed capacity of the u-th unit, is the maximum installed capacity of the u-th unit, gp is coal power, hp is hydropower, wp is wind power, pv is photovoltaic, store is energy storage, line is line, and Opv P is the installed capacity of photovoltaic units, O wp P is the installed capacity of wind power units, O gp P is the installed capacity of coal power units, O hp P is the installed capacity of hydro power units, r install P is the minimum proportion of new energy installed capacity, P pv P is the output of photovoltaic units, P wp P is the output of wind power units, D is the total load, D cut P is the load shedding, r output P is the proportion of new energy output not less than the total output;

[0098] The calculation formula of the output constraint is as follows:

[0099]

[0100] In the formula, P u P is the output of the u-th unit;

[0101] The calculation formula of the ramp rate constraint is as follows:

[0102]

[0103] In the formula, P gp,t+1 P is the output of coal power units at t+1, P gp,t P is the output of coal power units at t, η gp P is the ramp rate of coal power units;

[0104] The calculation formula of the wind and light curtailment rate constraint is as follows:

[0105]

[0106] In the formula, N wp N is the total number of wind power units, N pv N is the total number of photovoltaic units, P is the amount of wind power units curtailed at t, P is the amount of photovoltaic units curtailed at t, χ is the maximum wind and light curtailment rate, P is the predicted output per unit of wind power units at t, P is the predicted output per unit of photovoltaic units at t;

[0107] The calculation formula of the state of charge constraint is as follows:

[0108] SOC store,min ≤ SOC store,t ≤ B store O store

[0109] In the formula, SOC store,minThe minimum state of charge (SOC) of the energy storage unit. store,t Let B be the state of charge of the energy storage unit at time t. store For the energy storage duration of the energy storage unit, O store The installed capacity of the energy storage unit;

[0110] The formula for calculating the charge / discharge efficiency constraint is as follows:

[0111]

[0112] In the formula, SOC store,t-1 Let η be the state of charge of the energy storage unit at time t-1. store For the charging and discharging efficiency of energy storage units;

[0113] The formula for calculating the node power balance is as follows:

[0114]

[0115] In the formula, Let be the discharge power of the energy storage unit at time t. Let D be the charging power of the energy storage unit at time t. n,t Let n be the load at time t. Let t be the load shedding at node n. Let be the feed power of line l at time t. Let be the feed power of line l at time t;

[0116] The formula for calculating the capacity constraint of the coal-fired power unit is as follows:

[0117]

[0118] In the formula, Cap ol,t Cap is the online capacity of the coal-fired power unit at time t. ol,t-1 Cap represents the online capacity of the coal-fired power unit at time t-1. op,t Cap is the operating capacity of the coal-fired power unit at time t. cl,t Let T be the shutdown capacity of the coal-fired power unit at time t. on For boot time, Cap op,t-j Let T be the operating capacity of the coal-fired power unit at time tj. off For shutdown time, Cap cl,t-j The shutdown capacity of the coal-fired power unit at time tj;

[0119] The formula for calculating the overall carbon emission constraint is as follows:

[0120]

[0121] In the formula, E Lim This represents the carbon emission limit.

[0122] Step 4: Obtain the output and installed capacity of each type of unit in the region to be planned as a decision variable, and input the output and installed capacity of each type of unit in the region to be planned into the pre-established source-grid-energy storage low-carbon power system collaborative planning optimization model, and solve the source-grid-energy storage low-carbon power system collaborative planning optimization model through a solver to obtain the source-grid-energy storage collaborative optimization configuration scheme of the region to be planned.

[0123] The types of units include coal-fired units, hydropower units, wind power units, photovoltaic units and energy storage units.

[0124] Specifically, the installed capacity and to-be-installed capacity boundary of each type of unit in the region to be planned, grid structure related data and load data are obtained, and the output and to-be-installed capacity of each type of unit in the region to be planned are input as planning decision variables into the pre-established source-grid-energy storage low-carbon power system collaborative planning optimization model, and the source-grid-energy storage low-carbon power system collaborative planning optimization model is solved through a solver to obtain the source-grid-energy storage collaborative optimization configuration scheme of the region to be planned.

[0125] It should be noted that the CPLEX solver can efficiently solve the source-grid-energy storage low-carbon power system collaborative planning optimization model.

[0126] The source-grid-energy storage collaborative planning method considering the dynamic carbon emission factor of the unit provided by the application establishes an inverse proportional relationship between the carbon emission of the coal-fired unit and the load rate, which can effectively evaluate the carbon emission of the coal-fired unit under different load rates. At the same time, the linear feature of the source-grid-energy storage collaborative planning model is maintained, and the solving efficiency is improved. In addition, the application increases the diversity of unit selection in the planning model, providing a more refined and scientific and reasonable solution for future low-carbon planning of the power system, and has wide practical application potential and popularization value.

[0127] In summary, the source-grid-energy storage collaborative planning method considering the dynamic carbon emission factor of the unit provided by the embodiment greatly improves the planning calculation solving efficiency on the basis of ensuring the accuracy of the dynamic carbon emission factor description, and is suitable for large-scale, multi-time period low-carbon power system planning, and provides strong support for power grid development planning decision.

[0128] Embodiment two

[0129] Figure 2 The structure diagram of a source-grid-energy storage collaborative planning system considering the dynamic carbon emission factor of the unit provided according to an embodiment of the application is shown in Figure 2 The system comprises:

[0130] The first obtaining module 100 is configured to obtain historical operation data and type information of coal power units in a region to be planned, and construct a dynamic carbon emission factor model of the coal power units in the region to be planned based on the historical operation data, wherein the operation data comprises a load rate of the coal power units and carbon emission per unit of power of the coal power units.

[0131] The calculation formula of the dynamic carbon emission factor model of the coal power units in the region to be planned is as follows:

[0132]

[0133] x = P / Cap ol

[0134] In the formula, y is the carbon emission per unit of power of the coal power units, x is the load rate of the coal power units, P is the output of a group of aggregated coal power units, Cap ol is the online capacity of the group of aggregated coal power units, is a first regression parameter, is a second regression parameter.

[0135] The second obtaining module 200 is configured to obtain each operation scenario of a planning duration, the output and online capacity of each group of aggregated coal power units in the region to be planned, and determine the total carbon emission in the region to be planned under the planning duration based on the each operation scenario, the output and online capacity of each group of aggregated coal power units, and the dynamic carbon emission factor model.

[0136] The calculation formula of the total carbon emission in the region to be planned under the planning duration is as follows:

[0137]

[0138] In the formula, E Gen is the total carbon emission, p s is a weight of the s-th scenario, N s is a total number of aggregated scenarios, N GP is a number of groups of aggregated coal power units, N T is a total number of aggregated time points under the planning duration, P gp,s,t is the output of the gp-th group of aggregated coal power units under the s-th scenario at the t-th time point, Cap ol,gp,s,t is the online capacity of the gp-th group of aggregated coal power units under the s-th scenario at the t-th time point.

[0139] The construction module 300 is used for constructing a target function with the minimum investment cost, variable operation cost and fixed operation cost of the power system as the target, constructing a source network load storage low-carbon power system collaborative planning optimization model based on the target function and the constraint conditions, the constraint conditions including investment constraints, operation constraints, aggregated coal-fired power unit capacity constraints and total carbon emission constraints.

[0140] The operation constraints include output constraints, ramp rate constraints, wind or light curtailment rate constraints, state of charge constraints, node power balance constraints and charging and discharging efficiency constraints.

[0141] It should be noted that the calculation formula of the target function is as follows:

[0142] min C Sys =C Inv +C Fix +C Oper

[0143] In the formula, C Sys is the total cost of the power system, C Inv is the total investment cost of the units and lines, C Fix is the total maintenance cost of the units and lines, and C Oper is the total operation cost of the power system.

[0144] The calculation formula of the investment constraints is as follows:

[0145]

[0146] O pv +O wp ≥r install (O pv +O wp +O gp +O hp )

[0147] ∑P pv +∑P wp ≥r output (D-D cut )

[0148] In the formula, O u is the installed capacity of the u-th unit, is the maximum installed capacity of the u-th unit, gp is coal-fired power, hp is hydropower, wp is wind power, pv is photovoltaic power, store is energy storage, line is line, O pv is the installed capacity of the photovoltaic unit, O wp is the installed capacity of the wind power unit, O gp is the installed capacity of the coal-fired power unit, O hp is the installed capacity of the hydropower unit, and r installP is the minimum proportion of new energy installed capacity pv P is the output of photovoltaic units wp D is the total load, D cut r is the load shedding output P is the proportion of new energy output not less than the total output

[0149] The calculation formula of the output constraint is as follows:

[0150]

[0151] P is the output of the u-th unit u

[0152] The calculation formula of the ramp rate constraint is as follows:

[0153]

[0154] P is the output of the u-th unit gp,t+1 P is the output of the coal-fired unit at t+1 gp,t P is the output of the coal-fired unit at t gp η is the ramp rate of the coal-fired unit

[0155] The calculation formula of the wind and light curtailment rate constraint is as follows:

[0156]

[0157] N is the total number of wind power units wp N is the total number of wind power units pv N is the total number of photovoltaic units χ is the maximum wind and light curtailment rate χ is the maximum wind and light curtailment rate P is the predicted output of the wind power unit at t P is the predicted output of the photovoltaic unit at t

[0158] The calculation formula of the state of charge constraint is as follows:

[0159] SOC store,min ≤SOC store,t ≤B store O store

[0160] SOC store,min is the minimum state of charge of the energy storage unit store,t SOC is the state of charge of the energy storage unit at t store B is the energy storage duration of the energy storage unit store O is the installed capacity of the energy storage unit

[0161] ​The calculation formula of the charge-discharge efficiency constraint is as follows:

[0162]

[0163] In the formula, SOC store,t-1 is the state of charge of the energy storage unit at time t-1, η store is the charge-discharge efficiency of the energy storage unit;

[0164] The calculation formula of the node power balance is as follows:

[0165]

[0166] In the formula, is the discharge power of the energy storage unit at time t, is the charge power of the energy storage unit at time t, D n,t is the load of node n at time t, is the load shedding of node n at time t, is the outgoing power of line l at time t, is the incoming power of line l at time t;

[0167] The calculation formula of the aggregated coal-fired power unit capacity constraint is as follows:

[0168]

[0169] In the formula, Cap ol,t is the online capacity of the coal-fired power unit at time t, Cap ol,t-1 is the online capacity of the coal-fired power unit at time t-1, Cap op,t is the startup capacity of the coal-fired power unit at time t, Cap cl,t is the shutdown capacity of the coal-fired power unit at time t, T on is the startup time, Cap op,t-j is the startup capacity of the coal-fired power unit at time t-j, T off is the shutdown time, Cap cl,t-j is the shutdown capacity of the coal-fired power unit at time t-j;

[0170] The calculation formula of the total carbon emission constraint is as follows:

[0171] E Gen ≤E Lim

[0172] In the formula, E Lim is the carbon emission limit value.

[0173] The optimization module 400 is configured to obtain the output and installed capacity of each type of unit in the region to be planned as a decision variable, and input the output and installed capacity of each type of unit in the region to be planned into a pre-established source-grid-storage low-carbon power system collaborative planning optimization model, and solve the source-grid-storage low-carbon power system collaborative planning optimization model through a solver to obtain a source-grid-storage collaborative optimization configuration scheme of the region to be planned.

[0174] The types of units include coal-fired units, hydropower units, wind power units, photovoltaic units and energy storage units.

[0175] In summary, the source-grid-storage collaborative planning system considering the dynamic carbon emission factor of units proposed in the embodiment improves the planning accuracy and calculation and solving efficiency.

[0176] Embodiment three

[0177] To achieve the above-mentioned embodiments, the present disclosure further proposes an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to realize the method of embodiment one.

[0178] Embodiment four

[0179] To achieve the above-mentioned embodiments, the present disclosure further proposes a computer readable storage medium having a computer program stored thereon, wherein the program is executed by a processor to realize the method of embodiment one.

[0180] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example" or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0181] Any processes or methods described in the flow charts or otherwise described herein can be understood as representing modules, segments, or portions of code that include one or more executable instructions for implementing the specified logical functions or steps, and the preferred embodiments of the application include additional or fewer steps, in other orders, with other functionality, in implementations of these preferred embodiments of the application. Thus, any of the steps, options, aspects, components, etc. discussed herein can be included or deleted in other embodiments of the application, and yet still be deemed to fall within the scope of the present application.

[0182] Although the embodiments of the present application have been shown and described above, it should be understood by those ordinary skilled in the art that the above embodiments are exemplary and cannot be construed as limiting the present application, and those ordinary skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A source-grid-load-storage collaborative planning method considering unit dynamic carbon emission factors, characterized in that, The method comprises: acquiring historical operation data and type information of coal power units in a region to be planned, and constructing a dynamic carbon emission factor model of the coal power units in the region to be planned based on the historical operation data, wherein the operation data comprises a load rate of the coal power units and carbon emission per unit of electricity of the coal power units; acquiring each operation scenario, output and online capacity of each aggregated coal power unit combination in the region to be planned within a planning time length, and determining overall carbon emission in the region to be planned within the planning time length based on the each operation scenario, output and online capacity of the each aggregated coal power unit combination and the dynamic carbon emission factor model; constructing a target function with the minimum investment cost, variable operation cost and fixed operation cost of a power system as a target, constructing a source-grid-load-storage low-carbon power system collaborative planning optimization model based on the target function and constraint conditions of investment constraints, operation constraints, aggregated coal power unit capacity constraints and overall carbon emission constraints; acquiring output and installed capacity of each type of unit in the region to be planned as a decision variable, inputting the output and installed capacity of each type of unit in the region to be planned into the source-grid-load-storage low-carbon power system collaborative planning optimization model established in advance, and solving the source-grid-load-storage low-carbon power system collaborative planning optimization model by a solver to obtain a source-grid-load-storage collaborative optimization configuration scheme of the region to be planned; wherein the each type of unit comprises coal power units, hydropower units, wind power units, photovoltaic units and energy storage units; the operation constraints comprise output constraints, ramp rate constraints, abandoned wind and light rate constraints, state of charge constraints, node power balance constraints and charging and discharging efficiency constraints.

2. The method of claim 1, wherein, The calculation formula of the dynamic carbon emission factor model of the coal power units in the region to be planned is as follows: x = P / Cap ol In the formula, y is the carbon emission per unit of electricity of the coal-fired generating unit, x is the load rate of the coal-fired generating unit, P is the output of the group of coal-fired generating units after aggregation, Cap ol is the online capacity of the group of coal-fired generating units after aggregation, is the first regression parameter, is the second regression parameter.

3. The method of claim 2, wherein, The calculation formula of the overall carbon emission in the region to be planned within the planning time length is as follows: In the formula, E Gen is the total carbon emissions, p s is the weight of the s-th scenario, N s is the total number of aggregated scenarios, N GP is the number of aggregated coal-fired unit groups, N T is the total number of aggregated time points in the planning period, P gp,s,t is the output of the gp-th aggregated coal-fired unit combination in the s-th scenario at time t, Cap ol,gp,s,t is the online capacity of the gp-th aggregated coal-fired unit combination in the s-th scenario at time t.

4. The method of claim 3, wherein, The calculation formula of the target function is as follows: minC Sys = C Inv + C Fix + C Oper where C Sys is the total cost of the power system, C Inv is the total cost of the investment in units and lines, C Fix is the total maintenance cost of units and lines, C Oper is the total operating cost of the power system.

5. The method of claim 4, wherein, The calculation formula of the investment constraints is as follows: O pv +O wp ≥r install (O pv +O wp +O gp +O hp ) ∑P pv +∑P wp ≥r output (D-D cut ) wherein O u is the installed capacity of the u-th unit, is the installed capacity of the u-th unit, gp is coal power, hp is hydropower, wp is wind power, pv is photovoltaic, store is energy storage, line is line, O pv is the installed capacity of the u-th unit, O wp is the installed capacity of the u-th unit, O gp is the installed capacity of the u-th unit, O hp is the installed capacity of the u-th unit, r install is the minimum proportion of new energy installed capacity, P pv is the output of the photovoltaic unit, P wp is the output of the wind power unit, D is the total load, D cut is the load shedding, r output is the proportion of new energy output not less than the total output; The calculation formula of the output constraints is as follows: In the formula, P u is the output of the u-th unit. The calculation formula of the ramp rate constraints is as follows: In the formula, P gp,t+1 is the output of the coal-fired generating unit at time t+1, P gp,t is the output of the coal-fired generating unit at time t, η gp is the ramp rate of the coal-fired generating unit. The calculation formula of the abandoned wind and light rate constraints is as follows: where N wp is the total number of wind turbines, N pv is the total number of photovoltaic units, is the wind turbine curtailment at time t, is the photovoltaic curtailment at time t, χ is the maximum wind and photovoltaic curtailment rate, is the wind turbine predicted power at time t, is the photovoltaic predicted power at time t. The calculation formula of the state of charge constraints is as follows: SOC store,min ≤ SOC store,t ≤ B store O store In the formula, SOC store,min is the minimum value of the state of charge of the energy storage unit, SOC store,t is the state of charge of the energy storage unit at time t, B store is the energy storage duration of the energy storage unit, O store is the installed capacity of the energy storage unit; The calculation formula of the charging and discharging efficiency constraints is as follows: In the formula, SOC store,t-1 is the state of charge of the energy storage unit at time t-1, η store is the charge and discharge efficiency of the energy storage unit; and the calculation formula of the node power balance is as follows: wherein, is the discharging power of the energy storage unit at time t, is the charging power of the energy storage unit at time t, D n,t is the load at node n at time t, is the load shedding at node n at time t, is the feed-out power of line 1 at time t, is the feed-in power of line 1 at time t; The calculation formula of the aggregated coal power unit capacity constraints is as follows: Cap ol,t Cap ol,t-1 Cap op,t Cap cl,t Cap on Cap op,t-j Cap off Cap cl,t-j Cap The calculation formula of the overall carbon emission constraints is as follows: E Gen ≤E Lim In the formula, E Lim is a carbon emission limit value.

6. A source-grid-load-storage collaborative planning system considering unit dynamic carbon emission factors, characterized in that, The system comprises: a first acquisition module configured to acquire historical operation data and type information of coal power units in a region to be planned, and construct a dynamic carbon emission factor model of the coal power units in the region to be planned based on the historical operation data, wherein the operation data comprises a load rate of the coal power units and carbon emission per unit of electricity of the coal power units; a second acquisition module configured to acquire each operation scenario, output and online capacity of each aggregated coal power unit combination in the region to be planned within a planning time length, and determine overall carbon emission in the region to be planned within the planning time length based on the each operation scenario, output and online capacity of the each aggregated coal power unit combination and the dynamic carbon emission factor model; The construction module is configured to construct a target function with the minimum investment cost, variable operation cost and fixed operation cost of the power system as a target, to construct a source-grid-load-storage low-carbon power system collaborative planning optimization model based on the target function and constraint conditions, with investment constraints, operation constraints, aggregated coal-fired power unit capacity constraints and total carbon emission constraints as the constraint conditions; The optimization module is configured to obtain the output and installed capacity of each type of unit in the region to be planned as a decision variable, input the output and installed capacity of each type of unit in the region to be planned into the pre-established source-grid-load-storage low-carbon power system collaborative planning optimization model, and solve the source-grid-load-storage low-carbon power system collaborative planning optimization model through a solver to obtain a source-grid-load-storage collaborative optimization configuration scheme of the region to be planned. The various types of units include coal-fired power units, hydropower units, wind power units, photovoltaic units and energy storage units. The operation constraints include output constraints, ramp rate constraints, abandoned wind and light rate constraints, state of charge constraints, node power balance constraints and charge and discharge efficiency constraints.

7. The system of claim 6, wherein, The calculation formula of the dynamic carbon emission factor model of the coal-fired power unit in the region to be planned is as follows: x = P / Cap ol In the formula, y is the carbon emission per unit of electricity of the coal-fired generating unit, x is the load rate of the coal-fired generating unit, P is the output of the group of coal-fired generating units after aggregation, Cap ol is the online capacity of the group of coal-fired generating units after aggregation, is the first regression parameter, is the second regression parameter.

8. The system of claim 7, wherein, The calculation formula of the total carbon emission in the region to be planned under the planning time length is as follows: In the formula, E Gen is the total carbon emissions, p s is the weight of the s-th scene, N s is the total number of scenes, N GP is the number of coal-fired generating units after aggregation, N T is the total number of time points after aggregation of the planning duration, P gp,s,t is the output of the gp-th coal-fired generating unit combination in the s-th scene at time t after aggregation, Cap ol,gp,s,t is the online capacity of the gp-th coal-fired generating unit combination in the s-th scene at time t after aggregation.

9. An electronic device, comprising: The computer program is stored in the memory and executable on the processor, and the processor executes the program to implement the method of any one of claims 1-5. The program is executed by the processor to implement the method of any one of claims 1-5.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, ​

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