Power system carbon emission time sequence production simulation pre-evaluation method and system

Abstract

The invention discloses a power system carbon emission time sequence production simulation pre-evaluation method, and discloses a system with the power system carbon emission time sequence production simulation pre-evaluation method, a terminal and a medium. According to the power system carbon emission time sequence production simulation pre-evaluation method, a provincial power system carbon emission time sequence simulation model considering source network load storage interaction characteristics is established, and carbon emission situation research and judgment on power systems in key regions, provincial levels and above in a carbon peak reaching critical period are enhanced; and the accuracy of predicting the total amount of power carbon emission in provinces and regions in the future is improved, so that low-carbon planning of a power system is effectively guided.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power system carbon emission pre-evaluation, and particularly relates to a power system carbon emission time sequence production simulation pre-evaluation method and system. BACKGROUND

[0002] The power industry is the main force of carbon emission reduction, and its carbon emission accounts for about 40% of the total carbon emission of the whole society. At present, China has entered the critical period of carbon peak, and the optimization of power system planning scheme and peak reduction path is crucial to the progress of "double carbon" of the power industry and even the whole society. It is urgent to break through the carbon emission time sequence simulation technology of the power system, establish a provincial power grid carbon emission time sequence simulation model considering the peak shaving consumption characteristics of fossil energy units and the source-grid-load-storage interaction characteristics, strengthen the judgment of the carbon emission situation of key areas, provincial and above power systems in the critical period of carbon peak, improve the accuracy of future provincial and regional power carbon emission total quantity prediction, and effectively guide the low-carbon planning of the power system.

[0003] In order to effectively quantify and evaluate the carbon emission of the power system, the carbon emission characteristics of fossil energy units and the source-grid-load-storage interaction characteristics need to be considered, and the modeling and solving of the power system carbon emission time sequence simulation need to be researched. At present, the research on the carbon emission simulation of the provincial scale power system mainly focuses on the optimization of new energy consumption, economy or safety of power time sequence balance. On the basis of the system operation mode result, the carbon dioxide emission is calculated according to the fossil energy unit power generation, specific consumption characteristics and carbon emission factor. The existing technology researches the low-carbon economic dispatch of deep peak shaving of pumped storage auxiliary coal-fired units considering the carbon emission characteristics of deep peak shaving, adopts the piecewise linearization method to realize the mixed integer nonlinear model, and can realize the optimization dispatch of IEEE39 node system for daily period. However, the modeling method of each unit in the literature is difficult to support the annual full period optimization simulation of the provincial and above scale. SUMMARY

[0004] The present application aims at at least solving one of the problems in the prior art. To this end, the present application provides a power system carbon emission time sequence production simulation pre-evaluation method, which can establish a provincial power system carbon emission time sequence simulation model considering the source-grid-load-storage interaction characteristics, strengthen the judgment of the carbon emission situation of key areas, provincial and above power systems in the critical period of carbon peak, improve the accuracy of future provincial and regional power carbon emission total quantity prediction, and effectively guide the low-carbon planning of the power system.

[0005] The present application also provides a system, a terminal and a medium with the power system carbon emission time sequence production simulation pre-evaluation method.

[0006] The power system carbon emission time sequence production simulation pre-evaluation method according to the first aspect of the present application is characterized by comprising the following steps:

[0007] a carbon emission time sequence simulation pre-evaluation model of a power system is constructed with the minimum carbon emission as a target;

[0008] According to the simulation pre-evaluation model, a new energy consumption maximum unit combination optimization model is obtained by optimizing the simulation pre-evaluation model with the maximum new energy consumption as a target, and a unit combination and start-stop arrangement of the power system are obtained based on the new energy consumption maximum unit combination optimization model;

[0009] The new energy consumption maximum unit combination optimization model is optimized with the minimum unit output of the carbon emission as a target, and a linearization optimization model is obtained by using a piecewise linearization method for piecewise linearization, and a unit output plan is determined according to the linearization optimization model and the unit combination and start-stop arrangement;

[0010] The unit combination and start-stop arrangement and the unit output plan are combined to obtain a power system production simulation result.

[0011] The power system carbon emission time sequence production simulation pre-evaluation method according to the embodiment of the present application has at least the following beneficial effects: the present application proposes a power system carbon emission time sequence production simulation pre-evaluation model with the minimum carbon emission as a target, and constructs a power system carbon emission time sequence simulation two-stage optimization framework based on target decoupling, respectively establishes a unit combination optimization model with the maximum new energy consumption and establishes a unit output optimization model with the minimum carbon emission,

[0012] According to some embodiments of the present application, in the step of constructing the power system carbon emission time sequence simulation pre-evaluation model with the minimum carbon emission as a target, the objective function of the simulation pre-evaluation model is:

[0013]

[0014] In the formula, P g,t is the power generation power of the gth fossil energy unit at the t period; β g (t) is the average fuel consumption per unit of electricity of the thermal power unit at the corresponding power operating point, that is, the specific consumption characteristic; NCV g,r (t) is the average low heat value of the fossil fuel used by the gth thermal power unit in the t period; CC g,r is the carbon content per unit heat value of the fossil fuel used by the gth thermal power unit; OF g,r is the carbon oxidation rate of the fuel.

[0015] According to some embodiments of the present application, the constraint conditions of the simulation pre-evaluation model include load balance constraints, fossil energy unit output operation constraints, fossil energy unit climbing operation constraints, fossil energy unit start-stop operation state constraints, fossil energy unit minimum start-stop time constraints, power grid line transmission capacity constraints, system reserve capacity constraints, new energy output constraints, and annual total carbon emission constraints, wherein:

[0016] The load balance constraints satisfy:

[0017]

[0018] In the formula, m represents the grid partition sequence number; N represents the number of grid partitions; g represents the clustering fossil energy unit sequence number; N G,n is the total clustering number of fossil energy units in region n; represents the new energy output power of region n at time period t;

[0019] The fossil energy unit output operation constraints satisfy:

[0020]

[0021] In the formula: are the upper and lower limits of the output of the gth fossil energy unit in region n; X g,n (t) is the operation state of the gth fossil energy unit in region n at time period t, which is a binary variable, 0 indicating that the unit has been stopped, and 1 indicating that the unit is running; ΔP g,n (t) is the power of the gth fossil energy unit in region n at time period t participating in optimization;

[0022] The fossil energy unit climbing operation constraints satisfy:

[0023] P g,n (t+1)-P g,n (t)≤ΔP g,up

[0024] P g,n (t)-P g,n (t+1)≤ΔP g,down

[0025] In the formula: ΔP g,up and ΔP g,down respectively represent the up-climbing rate and the down-climbing rate of the fossil energy unit;

[0026] The fossil energy unit start-stop operation state constraints satisfy:

[0027]

[0028] In the formula: Y g (t) and Z​g (t) is the start-up state and shutdown state of the g-type unit at time t, both of which are binary variables. For Y, 0 indicates not in the start-up state, and 1 indicates being started up; for Z, 0 indicates not in the shutdown state, and 1 indicates being shut down; this constraint is a logical constraint of the start-up and shutdown and running state of the unit, which ensures that each state variable is logical in the process of unit combination;

[0029] The minimum start-up and shutdown time constraint of the fossil energy unit is satisfied:

[0030] Y g (t) + Z g (t+1) + Z g (t+2) +... + Z g (t+k)≤1

[0031] Z g (t) + Y g (t+1) + Y g (t+2) +... + Y g (t+k)≤1

[0032] In the formula: k is determined by the minimum start-up or shutdown time parameter of the unit, which reflects the time step of the minimum start-up or shutdown. This constraint mainly considers the constraints of physical characteristics, energy consumption and operation cost of the unit, and the unit cannot be frequently started and stopped;

[0033] The transmission capacity constraint of the power grid line satisfies:

[0034]

[0035] In the formula, represents the line transmission section limit between region n and region m;

[0036] The system reserve capacity constraint satisfies:

[0037]

[0038] In the formula: R P and R N are positive and negative rotating reserves, respectively; is the reliable capacity of new energy generation in region n, which refers to the conventional unit capacity that can be replaced by new energy under a certain confidence level;

[0039] The new energy output constraint satisfies:

[0040]

[0041] In the formula: refers to the theoretical time series output of the wind farm in region n at time period t, The regional n photovoltaic power station photovoltaic theoretical time series output at the t time period;

[0042] Annual total carbon emission constraint E n Satisfies:

[0043]

[0044] In the formula, E n Is the annual total carbon emission constraint.

[0045] According to some embodiments of the present application, the step of obtaining the unit combination and start-stop arrangement of the power system based on the new energy consumption maximum optimization model, when the unit combination with the maximum new energy consumption is optimized as the target, the objective function satisfies:

[0046]

[0047] In the formula: n is the grid region serial number, Pn(t) is the power generation output of the regional n wind farm at the t time period, Pn(t) is the power generation output of the regional n photovoltaic power station at the t time period.

[0048] According to some embodiments of the present application, the step of obtaining the unit combination and start-stop arrangement of the power system based on the new energy consumption maximum optimization model, when the unit combination with the maximum new energy consumption is optimized as the target, the constraint condition includes:

[0049] Load balance constraint:

[0050]

[0051] In the formula: m represents the grid partition serial number; N represents the number of grid partitions; g is the cluster thermal power unit serial number; N G,n Is the total cluster number of the thermal power unit in the region n; Pn(t) is the new energy output of the region n at the t time period; P g,n (t) is the output of the gth thermal power unit in the region n at the t time period; Pn(t) is the load in the region n; Pnm(t) is the power exchange between the region n and the region m; Pnm(t) is the power exchange between the region n and the region m;

[0052] Fossil energy unit output operation constraint:

[0053]

[0054] In the formula: are the upper and lower limits of the gth type of thermal power unit output in the region n; X g,n (t) is the running state of the gth type of thermal power unit in the region n at time t, which is a binary variable, 0 indicating that the unit has been shut down, and 1 indicating that the unit is running; ΔP g,n (t) is the power of the gth type of thermal power unit in the region n participating in optimization at time t;

[0055] Fossil energy unit climbing operation constraint:

[0056] P g,n (t+1)-P g,n (t)≤ΔP g,up

[0057] P g,n (t)-P g,n (t+1)≤ΔP g,down

[0058] In the formula: ΔP g,up and ΔP g,down respectively represent the upper and lower climbing rates of the thermal power unit;

[0059] Fossil energy unit start-stop operation state constraint:

[0060]

[0061] In the formula: Y g (t) and Z g (t) are the start and stop states of the gth type of unit at time t, both of which are binary variables. For Y, 0 indicates not in the start state, and 1 indicates being started; for Z, 0 indicates not in the stop state, and 1 indicates being stopped; this constraint is a logical constraint of the unit start-stop and running state, which ensures that the state variables are logical in the process of unit combination;

[0062] Fossil energy unit minimum start-stop time constraint:

[0063] Y g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1

[0064] Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1

[0065] wherein k is determined by the minimum start-up or shut-down time parameter of the unit, which reflects the time step of the minimum start-up or shut-down, and the constraint is mainly considered to be restricted by the physical characteristics of the unit, the energy consumption and the operation cost of the unit, and the unit cannot be frequently started and stopped;

[0066] The transmission capacity constraint of the power grid line:

[0067]

[0068] wherein, represents the line transmission section limit between the region n and the region m;

[0069] The system reserve capacity constraint:

[0070]

[0071] wherein: R P and R N are positive and negative rotating reserves respectively; is the reliable capacity of the new energy generation in the region n, which refers to the conventional unit capacity that can be replaced by the new energy under a certain confidence level;

[0072] The new energy output constraint:

[0073]

[0074] wherein: refers to the theoretical time series output of the wind farm in the region n at the t period, refers to the photovoltaic theoretical time series output of the photovoltaic power station in the region n at the t period.

[0075] According to some embodiments of the present application, the new energy consumption maximum optimization model is optimized with the minimum carbon emission unit output as the target, and a linear optimization model is obtained by using the piecewise linearization method for stage linearization, and in the step of determining the unit output plan according to the linear optimization model and the unit combination and start-up and shut-down arrangement, the optimization is performed with the minimum carbon emission unit output as the target, and the objective function satisfies:

[0076]

[0077] wherein: P g,t is the power generation of the gth fossil energy unit at the t period; β g (t) is the average fuel consumption per unit of electricity of the thermal power unit at the corresponding power operating point, that is, the specific consumption characteristic; NCV g,r (t) is the average low heat value of the fossil fuel used by the gth thermal power unit at the t period; CC g,rThe unit heat value carbon content of the fossil fuel used by the gth thermal power unit; OF g,r The carbon oxidation rate of the fuel.

[0078] According to some embodiments of the present application, the new energy consumption maximum optimization model is optimized with the minimum carbon emission unit output as the target, and a piecewise linearization method is used for stage linearization to obtain a linear optimization model. In the step of determining the unit output plan according to the linear optimization model and the unit combination and start-stop arrangement, when optimization is performed with the minimum carbon emission unit output as the target, the constraint conditions include:

[0079] Load balance constraint:

[0080]

[0081] In the formula, m represents the grid partition sequence number; N represents the number of grid partitions; g represents the cluster thermal power unit sequence number; N G,n The total cluster number of thermal power units in region n; Pn(t) represents the new energy output of region n at time period t; P g,n Pn,g(t) represents the output of the gth type of thermal power unit in region n at time period t; Ln represents the load in region n; Pnm represents the power exchange between region n and region m; Pn,m(t) represents the outgoing power of the tie line of region n at time period t;

[0082] Fossil energy unit output operation constraint:

[0083]

[0084] In the formula: Pn,g,max and Pn,g,min represent the upper limit and lower limit of the output of the gth type of thermal power unit in region n; X g,n Pn,g(t) is the operation state of the gth type of thermal power unit in region n at time period t, which is a binary variable, 0 representing that the unit has been shut down, and 1 representing that the unit is running; ΔP g,n Pn,g(t) is the power of the gth type of thermal power unit in region n at time period t participating in optimization;

[0085] Fossil energy unit ramp constraint:

[0086] Pn,g(t+1)-Pn,g(t)≤ΔPn,g g,n Pn,g(t+1)-Pn,g(t)≤ΔPn,g g,n Pn,g(t+1)-Pn,g(t)≤ΔPn,g g,up

[0087] Pn,g(t+1)-Pn,g(t)≤ΔPn,g g,n Pn,g(t+1)-Pn,g(t)≤ΔPn,g g,n Pn,g(t+1)-Pn,g(t)≤ΔPn,g g,down

[0088] In the formula: ΔPg,up and ΔP g,down respectively represent the up-ramp rate and the down-ramp rate of the thermal power unit;

[0089] The transmission capacity constraint of the power grid line:

[0090]

[0091] In the formula, represents the line transmission section limit between the region n and the region m;

[0092] The new energy output constraint:

[0093]

[0094]

[0095] In the formula: refers to the theoretical time series output of the wind power plant in the region n at the t period, refers to the photovoltaic theoretical time series output of the photovoltaic power station in the region n at the t period;

[0096] The total annual carbon emission E n constraint:

[0097]

[0098] In the formula, E n is the total annual carbon emission constraint.

[0099] According to some embodiments of the present application, the new energy consumption maximum optimization model is optimized with the minimum carbon emission unit output as the target, and a piecewise linearization method is used for stage-by-stage linearization to obtain a linearization optimization model. In the step of determining the unit output plan according to the linearization optimization model and the unit combination and start-stop arrangement, after stage-by-stage linearization is performed by using the piecewise linearization method to obtain a linearization optimization model, the objective function of the linearization optimization model satisfies:

[0100]

[0101] The constraint conditions further include:

[0102]

[0103] In the formula, b k is the division point when the model is piecewise linearized, and is respectively z k , w k is an auxiliary point introduced when the model is linearized, and corresponds to b k

[0104] ​The power system carbon emission timing production simulation pre-evaluation system according to the second aspect of the embodiments of the present application comprises:

[0105] a model construction module, which is capable of constructing a power system carbon emission timing simulation pre-evaluation model with the minimum carbon emission as a target;

[0106] a first optimization module, which is capable of optimizing the simulation pre-evaluation model to obtain a new energy consumption maximum optimization model with the maximum new energy consumption as a target according to the simulation pre-evaluation model, and obtaining a unit combination and start-stop arrangement of the power system based on the new energy consumption maximum optimization model;

[0107] a second optimization module, which is capable of optimizing the new energy consumption maximum optimization model to obtain a linearization optimization model with the minimum unit output as a target, and performing stage linearization by using a piecewise linearization method, and determining a unit output plan according to the linearization optimization model and the unit combination and start-stop arrangement;

[0108] a simulation evaluation module, which is capable of combining the unit combination and start-stop arrangement and the unit output plan to obtain a power system production simulation result.

[0109] According to some embodiments of the present application, in the model construction module, a target function of the simulation pre-evaluation model is:

[0110]

[0111] wherein, P g,t is a power generation of the gth fossil energy unit at the t period; β g (t) is an average fuel consumption per unit of electricity of the thermal power unit at the corresponding power operating point, that is, a specific consumption characteristic; NCV g,r (t) is an average low heat value of the fossil fuel used by the gth thermal power unit at the t period; CC g,r is a unit heat value carbon content of the fossil fuel used by the gth thermal power unit; OF g,r is a carbon oxidation rate of the fuel.

[0112] According to some embodiments of the present application, the constraint conditions of the simulation pre-evaluation model comprise a load balance constraint, a fossil energy unit output operation constraint, a fossil energy unit climbing operation constraint, a fossil energy unit start-stop operation state constraint, a fossil energy unit minimum start-stop time constraint, a power grid line transmission capacity constraint, a system reserve capacity constraint, a new energy output constraint, and an annual total carbon emission constraint, wherein:

[0113] the load balance constraint satisfies:

[0114]

[0115] wherein: m represents the grid partition sequence number; N represents the number of grid partitions; g represents the cluster sequence number of thermal power units; N G,n represents the total number of clusters of thermal power units in region n; represents the new energy output power of region n at time period t;

[0116] The fossil energy unit output operation constraint is satisfied:

[0117]

[0118] wherein: represents the upper limit and lower limit of the gth thermal power unit output in region n; X g,n (t) represents the operation state of the gth thermal power unit in region n at time period t, which is a binary variable, 0 indicating that the unit has been shut down, and 1 indicating that the unit is running; ΔP g,n (t) represents the power of the gth thermal power unit in region n at time period t participating in optimization;

[0119] The fossil energy unit climbing operation constraint is satisfied:

[0120] P g,n (t+1)-P g,n (t)≤ΔP g,up

[0121] P g,n (t)-P g,n (t+1)≤ΔP g,down

[0122] wherein: ΔP g,up and ΔP g,down respectively represent the up-climbing rate and down-climbing rate of the thermal power unit;

[0123] The fossil energy unit start-stop operation state constraint is satisfied:

[0124]

[0125] wherein: Y g (t) and Z g (t) are the start state and stop state of the gth unit at time t, both of which are binary variables. For Y, 0 indicates not in the start state, and 1 indicates being started; for Z, 0 indicates not in the stop state, and 1 indicates being stopped; this constraint is a logical constraint of the unit start-stop and operation state, which ensures that the state variables are logical in the process of unit combination;

[0126] The fossil energy unit minimum start-stop time constraint is satisfied:

[0127] Y​g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1

[0128] Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1

[0129] where k is determined by the minimum start-up or shut-down time of the unit, which reflects the time step of the minimum start-up or shut-down, and the constraint mainly considers the constraints of physical characteristics, energy consumption and operation cost of the unit, and the unit cannot be frequently started and stopped;

[0130] The transmission capacity constraint of the power grid line satisfies:

[0131]

[0132] wherein, represents the line transmission section limit between the region n and the region m;

[0133] The system reserve capacity constraint satisfies:

[0134]

[0135] wherein: R P and R N are positive and negative rotating reserves, respectively; is the reliable capacity of new energy power generation in the region n, which refers to the conventional unit capacity that can be replaced by new energy under a certain confidence level;

[0136] The new energy output constraint satisfies:

[0137]

[0138] wherein: refers to the theoretical time series output of the wind farm in the region n at the t period, refers to the theoretical time series output of the photovoltaic power station in the region n at the t period;

[0139] The annual total carbon emission constraint E n satisfies:

[0140]

[0141] wherein, E n is the annual total carbon emission constraint.

[0142] According to some embodiments of the present application, in the first optimization module, when the unit combination with the largest new energy consumption is taken as the target for optimization, the objective function satisfies:

[0143]

[0144] wherein n represents the grid area serial number, represents the power generation output of the wind power plant in area n at time period t, represents the power generation output of the photovoltaic power plant in area n at time period t.

[0145] According to some embodiments of the present application, in the first optimization module, when the unit combination with the largest new energy consumption is taken as the target for optimization, the constraint conditions include:

[0146] Load balance constraint:

[0147]

[0148] wherein m represents the grid partition serial number; N represents the number of grid partitions; g represents the clustering thermal power unit serial number; N G,n represents the total clustering number of thermal power units in area n; represents the new energy output of area n at time period t; P g,n (t) represents the output of the gth thermal power unit in area n at time period t; represents the load in area n; represents the power exchange between area n and area m; represents the power sent out by the tie line of area n at time period t;

[0149] Fossil energy unit output operation constraint:

[0150]

[0151] wherein: represents the upper and lower limits of the output of the gth thermal power unit in area n; X g,n (t) represents the operation state of the gth thermal power unit in area n at time period t, which is a binary variable, 0 representing that the unit has been shut down, and 1 representing that the unit is running; ΔP g,n (t) represents the power of the gth thermal power unit in area n participating in optimization at time period t;

[0152] Fossil energy unit climbing operation constraint:

[0153] P g,n (t+1)-P g,n (t)≤ΔP g,up

[0154] P g,n (t)-P g,n(t+1)≤ΔP g,down

[0155] where ΔP g,up and ΔP g,down represent the up-ramp rate and down-ramp rate of thermal power units, respectively;

[0156] Fossil energy unit start-up and shut-down state constraints:

[0157]

[0158] where Y g (t) and Z g (t) are the start-up state and shut-down state of the g-th unit at time t, both of which are binary variables. For Y, 0 means not in start-up state, and 1 means in start-up state; for Z, 0 means not in shut-down state, and 1 means in shut-down state; this constraint is a logical constraint of the start-up and shut-down states of the units, which ensures that the state variables are logical in the process of unit commitment;

[0159] Fossil energy unit minimum start-up and shut-down time constraints:

[0160] Y g (t) + Z g (t+1) + Z g (t+2) +... + Z g (t+k)≤1

[0161] Z g (t) + Y g (t+1) + Y g (t+2) +... + Y g (t+k)≤1

[0162] where k is determined by the minimum start-up or shut-down time parameter of the unit, which reflects the time step of the minimum start-up or shut-down, and this constraint mainly considers the constraints of physical characteristics, energy consumption and operation cost of the unit, which cannot be frequently started or shut down;

[0163] Transmission capacity constraints of power grid lines:

[0164]

[0165] where, represents the transmission section limit between region n and region m;

[0166] System reserve capacity constraints:

[0167]

[0168] where R P and R NPositive and negative rotation standby, respectively; The reliable capacity of new energy generation in the region n refers to the conventional unit capacity that can be replaced by new energy under a certain confidence level.

[0169] New energy output constraint:

[0170]

[0171] In the formula: Refers to the theoretical time series output of the wind farm in region n at period t, Refers to the theoretical time series output of the photovoltaic power station in region n at period t.

[0172] According to some embodiments of the present application, in the second optimization module, when the unit output with the minimum carbon emission is optimized as the target, the objective function satisfies:

[0173]

[0174] In the formula: P g,t is the power generation of the gth fossil energy unit at period t; β g (t) is the average fuel consumption per unit of electricity of the thermal power unit at the corresponding power operating point, that is, the specific consumption characteristic; NCV g,r (t) is the average low heat value of the fossil fuel used by the gth thermal power unit at period t; CC g,r is the carbon content per unit heat value of the fossil fuel used by the gth thermal power unit; OF g,r is the carbon oxidation rate of the fuel.

[0175] According to some embodiments of the present application, in the second optimization module, when the unit output with the minimum carbon emission is optimized as the target, the constraint conditions include:

[0176] Load balancing constraint:

[0177]

[0178] In the formula: m represents the grid partition number; N represents the number of grid partitions; g is the cluster thermal power unit number; N G,n is the total cluster number of thermal power units in region n; represents the new energy output of region n at period t; P g,n (t) represents the output of the gth thermal power unit in region n at period t; is the load in region n; is the power exchange between region n and region m; represents the power transmission of the tie line of region n at period t;

[0179] Fossil energy unit output operation constraint:

[0180]

[0181] In the formula: are the upper and lower limits of the gth type of thermal power unit output in region n; X g,n (t) is the operating state of the nth gth type of thermal power unit in the region at time t, which is a binary variable, 0 indicating that the unit has been shut down, and 1 indicating that the unit is running; ΔP g,n (t) is the power of the nth gth type of thermal power unit in the region participating in optimization at time t;

[0182] Fossil energy unit climbing constraint:

[0183] P g,n (t+1)-P g,n (t)≤ΔP g,up

[0184] P g,n (t)-P g,n (t+1)≤ΔP g,down

[0185] In the formula: ΔP g,up and ΔP g,down respectively represent the climbing rate and the climbing rate of the thermal power unit;

[0186] Power grid line transmission capacity constraint:

[0187]

[0188] In the formula, represents the line transmission section limit between region n and region m;

[0189] New energy output constraint:

[0190]

[0191] In the formula: represents the theoretical time series output of the wind farm in region n at time t, represents the theoretical time series output of the photovoltaic power station in region n at time t;

[0192] Annual total carbon emissions E n constraint:

[0193]

[0194] In the formula, E n is the annual total carbon emission constraint.

[0195] According to some embodiments of the present application, in the second optimization module, the piecewise linearization method is used for piecewise linearization, and after a linearization optimization model is obtained, the objective function of the linearization optimization model satisfies:

[0196]

[0197] The constraint condition further includes:

[0198]

[0199] In the formula, b k is a division point when the model is piecewise linearized, and b z k , w k is an auxiliary point introduced by linearization of the model, and b k corresponds.

[0200] According to the terminal of the third aspect of the embodiment of the present application, the terminal comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to realize the power system carbon emission timing production simulation pre-evaluation method.

[0201] According to the computer readable storage medium of the fourth aspect of the embodiment of the present application, the medium stores computer executable instructions, and the computer executable instructions are used to execute the power system carbon emission timing production simulation pre-evaluation method.

[0202] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter in the description of embodiments of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0203] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description of embodiments of the present application, taken in conjunction with the accompanying drawings, in which:

[0204] Figure 1 is a schematic diagram of the steps of the power system carbon emission timing production simulation pre-evaluation method of the embodiment of the present application;

[0205] Figure 2 is a structural block diagram of the power system carbon emission timing production simulation pre-evaluation system provided by the embodiment of the present application. DETAILED DESCRIPTION

[0206] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0207] In the description of the present application, it should be understood that the orientation description, such as the orientation or position relationship indicated by up, down, front, back, left, right and the like, is based on the orientation or position relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0208] In the description of the present application, one or more is understood as one or more, more than two is understood as more than two, greater than, less than, more than, etc. are understood as not including the number, above, below, etc. are understood as including the number. If the first, second is described, it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the sequence of technical features indicated.

[0209] In the description of the present application, unless otherwise explicitly limited, the words such as setting, installing, connecting and the like should be broadly understood, and those skilled in the art can reasonably determine the specific meaning of the above words in the present application in combination with the specific content of the technical scheme.

[0210] Embodiment one,

[0211] To solve the problem that the existing simulation model is difficult to support annual full-time optimization simulation of a province and above, the present application provides a power system carbon emission time sequence production simulation pre-evaluation method, as shown in the formula (1), the method at least includes: Figure 1

[0212] Step S100, a power system carbon emission time sequence simulation pre-evaluation model is constructed with the minimum carbon emission as the target.

[0213] Based on the time sequence production simulation technology, the per-period power balance and carbon emission calculation are combined, the power system carbon emission time sequence simulation pre-evaluation model considering the source-grid-load-storage interaction characteristics is established with the minimum carbon emission as the target;

[0214] Objective function:

[0215]

[0216] In the formula, P g,t is the power generation of the gth fossil energy unit at t period; β g (t) is the average power generation fuel consumption of the thermal power unit at the corresponding power operating point, that is, the specific consumption characteristic; NCV g,r (t) is the average low heat value of the fossil fuel used by the gth thermal power unit in t period; CC g,r ​The unit heat value of fossil fuel used by the gth thermal power unit; OF g,r The carbon oxidation rate of the fuel.

[0217] The constraint conditions include:

[0218] (1) Load balance constraint

[0219]

[0220] In the formula: m represents the grid partition number; N represents the number of grid partitions; g is the cluster thermal power unit number; N G,n The total cluster number of thermal power units in region n; Pn(t) represents the new energy output of region n at time period t; P g,n (t) represents the output of the gth type of thermal power unit in region n at time period t; Pn represents the load in region n; Pnm represents the power exchange between region n and region m; Pn,m(t) represents the outgoing power of the tie line of region n at time period t.

[0221] (2) Fossil energy unit output operation constraint

[0222]

[0223] In the formula: Pn,g represents the upper and lower limits of the output of the gth type of thermal power unit in region n; X g,n (t) is the operating state of the gth type of thermal power unit in region n at time period t, which is a binary variable, 0 indicating that the unit has been shut down, and 1 indicating that the unit is running; ΔP g,n (t) is the power of the gth type of thermal power unit in region n at time period t participating in optimization.

[0224] (3) Fossil energy unit climbing operation constraint

[0225] Pn,g(t+1)-Pn,g(t)≤ΔPn,g g,n Pn,g(t)-Pn,g(t+1)≤-ΔPn,g g,n g,up (5)

[0226] Pn,g(t+1)-Pn,g(t)≥-ΔPn,g g,n Pn,g(t)-Pn,g(t+1)≥ΔPn,g g,n g,down (6)

[0227] In the formula: ΔPn,g g,up and ΔPn,g g,down respectively represent the up-climbing rate and down-climbing rate of the thermal power unit.

[0228] (4) Fossil energy unit start-stop operation state constraint

[0229] ​​

[0230] wherein Y g (t) and Z g (t) are the start-up state and shut-down state of the g-type unit t, both of which are binary variables. For Y, 0 represents not in the start-up state, and 1 represents being in the start-up state; for Z, 0 represents not in the shut-down state, and 1 represents being in the shut-down state; this constraint is a logical constraint of the start-up and shut-down and operation state of the unit, which ensures that each state variable is logical in the process of unit combination.

[0231] (5) Minimum start-up and shut-down time constraint of fossil energy unit

[0232] Y g (t) + Z g (t+1) + Z g (t+2) +... + Z g (t+k)≤1 (8)

[0233] Z g (t) + Y g (t+1) + Y g (t+2) +... + Y g (t+k)≤1 (9)

[0234] wherein k is determined by the minimum start-up or shut-down time parameter of the unit, which reflects the time step of the minimum start-up or shut-down. This constraint mainly considers the constraints of physical characteristics, energy consumption and operation cost of the unit, and the unit cannot be frequently started and stopped.

[0235] (6) Transmission capacity constraint of power grid line

[0236]

[0237] wherein, represents the transmission cross-section limit of the line between the region n and the region m.

[0238] (7) System reserve capacity constraint

[0239]

[0240] wherein R P and R N are the positive and negative rotating reserves, respectively; is the reliable capacity of the new energy generation in the region n, which refers to the conventional unit capacity that can be replaced by the new energy under a certain confidence level.

[0241] (8) New energy output constraint

[0242]

[0243] In the formula: denotes the theoretical time series output of the wind farm in region n at the t period, denotes the photovoltaic theoretical time series output of the photovoltaic power station in region n at the t period.

[0244] (9) Annual total carbon emission constraint E n satisfies:

[0245]

[0246] In the formula, E n is the annual total carbon emission constraint.

[0247] Step S200, according to the simulation pre-evaluation model, a unit combination with maximum new energy consumption is taken as a target to optimize the simulation pre-evaluation model, to obtain a new energy consumption maximum optimization model, and based on the new energy consumption maximum optimization model, a unit combination and start-stop arrangement of the power system are obtained. Specifically as follows:

[0248] 1. Objective function

[0249] Taking the maximum new energy consumption as a target, the objective function is as follows:

[0250]

[0251] In the formula: n denotes the grid region serial number, denotes the power generation output of the wind farm in region n at the t period, P n pv denotes the power generation output of the photovoltaic power station in region n at the t period.

[0252] 2. Constraint condition

[0253] (1) Load balance constraint

[0254]

[0255] In the formula: m represents the grid partition serial number; N represents the number of grid partitions; g is the cluster thermal power unit serial number; N G,n is the total cluster number of thermal power units in region n; denotes the new energy output of region n at the t period; P g,n (t) denotes the output of the gth type of thermal power unit in region n at the t period; is the load in region n; is the power exchange between region n and region m; denotes the outgoing power of the tie line of region n at the t period.

[0256] (2) Fossil energy unit output operation constraint

[0257]

[0258] In the formula: are the upper and lower limits of the gth fossil-fired generating unit in region n; X g,n (t) is the operation state of the gth fossil-fired generating unit in region n at time t, which is a binary variable, 0 indicating that the unit has been shut down and 1 indicating that the unit is running; ΔP g,n (t) is the power of the gth fossil-fired generating unit in region n participating in optimization at time t.

[0259] (3) Fossil-fired generating unit ramping operation constraint

[0260] P g,n (t+1)-P g,n (t)≤ΔP g,up (20)

[0261] P g,n (t)-P g,n (t+1)≤ΔP g,down (21)

[0262] In the formula: ΔP g,up and ΔP g,down respectively represent the up-ramping rate and down-ramping rate of the fossil-fired generating unit.

[0263] (4) Fossil-fired generating unit start-up and shut-down operation state constraint

[0264]

[0265] In the formula: Y g (t) and Z g (t) are the start-up state and shut-down state of the gth unit at time t, both of which are binary variables. For Y, 0 indicates that it is not in the start-up state and 1 indicates that it is in the start-up state; for Z, 0 indicates that it is not in the shut-down state and 1 indicates that it is in the shut-down state; this constraint is a logical constraint of the start-up and shut-down states of the unit, which ensures that the state variables are logical during unit combination.

[0266] (5) Fossil-fired generating unit minimum start-up and shut-down time constraint

[0267] Y g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1 (23)

[0268] Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1 (24)

[0269] In the formula, k is determined by the minimum unit start-up or shutdown time parameter, which reflects the time step of the minimum start-up or shutdown. This constraint mainly considers the constraints of physical characteristics, energy consumption and operation cost of the unit, and the unit cannot be frequently started and stopped.

[0270] (6) Transmission capacity constraint of power grid line

[0271]

[0272] In the formula, represents the line transmission section limit between region n and region m.

[0273] (7) System reserve capacity constraint

[0274]

[0275] In the formula: R P and R N are positive and negative rotating reserves, respectively. is the credible capacity of new energy power generation in region n, which refers to the conventional unit capacity that can be replaced by new energy under a certain confidence level.

[0276] (8) New energy output constraint

[0277]

[0278] In the formula: refers to the theoretical time series output of the wind farm in region n at period t, refers to the theoretical time series output of the photovoltaic power station in region n at period t.

[0279] The new energy consumption maximum optimization model established based on the above process realizes the unit commitment decision optimization with a week as a period for the unit commitment of the power system, and obtains the corresponding unit commitment and start-stop arrangement.

[0280] Step S300, optimize the new energy consumption maximum optimization model with the minimum carbon emission unit output as the target, and use the piecewise linearization method for stage linearization to obtain a linear optimization model, and determine the unit output plan according to the linear optimization model and the unit commitment and start-stop arrangement. Specifically, it includes:

[0281] Step S301, optimize the new energy consumption maximum optimization with the minimum carbon emission unit output as the target:

[0282] 1. Objective function

[0283] With the minimum carbon emission as the target, according to formula (2), the objective function of the unit output optimization mathematical model is as follows:

[0284]

[0285] 2, constraint condition

[0286] (1) Load balance constraint

[0287]

[0288] (2) Fossil energy unit output operation constraint

[0289]

[0290] (3) Fossil energy unit climbing constraint

[0291] P g,n (t+1)-P g,n (t)≤ΔP g,up (34)

[0292] P g,n (t)-P g,n (t+1)≤ΔP g,down (35)

[0293] (4) Power grid line transmission capacity constraint

[0294]

[0295] (5) New energy output constraint

[0296]

[0297] (6) E n Total annual carbon emission constraint

[0298]

[0299] In the formula, E n Total annual carbon emission constraint.

[0300] Step S302, using piecewise linearization method for stage linearization, get linearization optimization model.

[0301] The power system carbon emission time sequence simulation pre-evaluation model composed of the above formula (30) to formula (39) is a mixed integer nonlinear model, considering the obvious piecewise curve characteristics of the specific consumption characteristics of fossil energy units, the piecewise linearization method is used to convert it into a mixed integer linear model, piecewise linearization is a piecewise approximation approximation method, which has the advantages of simple solution and wide application range, and can effectively solve the problems of high variable dimension and large iteration number, the present application is according to 10% P g,maxSegmenting the to-be-optimized model into linearization intervals for linearization, and dividing points b k respectively Introducing z k , w k Linearizing the model, converting the target into formula (40), and adding the constraint condition of formula (41).

[0302]

[0303]

[0304] Step S303, determining the unit output plan according to the linearization optimization model and the unit combination and the start-stop arrangement thereof.

[0305] Inputting the unit combination and the start-stop arrangement thereof obtained in step S200 into the linearization optimization model to obtain the corresponding unit output plan.

[0306] Step S400, combining the unit combination and the start-stop arrangement thereof and the unit output plan to obtain the power system production simulation result.

[0307] In the unit combination decision-making stage, a new energy consumption maximum optimization model is used for simulation to obtain the corresponding unit combination and start-stop arrangement.

[0308] In the unit output optimization stage, a linearization optimization carbon emission minimum model is used for simulation to obtain the unit output plan.

[0309] Combining the unit combination and the start-stop arrangement thereof and the unit output plan to obtain the power system production simulation result.

[0310] Embodiment two,

[0311] Another embodiment of the application provides a power system carbon emission time sequence production simulation pre-evaluation system, the system 20 comprises:

[0312] The model construction module 201 can construct a power system carbon emission time sequence simulation pre-evaluation model with the minimum carbon emission as the target;

[0313] The first optimization module 202 optimizes the simulation pre-evaluation model with the maximum new energy consumption as the target according to the simulation pre-evaluation model, obtains a new energy consumption maximum optimization model, and obtains the unit combination and the start-stop arrangement thereof of the power system based on the new energy consumption maximum optimization model;

[0314] The second optimization module 203 optimizes the new energy consumption maximum optimization model with the minimum carbon emission of the unit output as the target, and linearizes the model by using a piecewise linearization method to obtain a linearized optimization model, and determines the unit output plan according to the linearized optimization model and the unit combination and start-stop arrangement;

[0315] The simulation evaluation module 204 can combine the unit combination and start-stop arrangement and the unit output plan to obtain a power system production simulation result.

[0316] Further, in the model construction module, the objective function of the simulation pre-evaluation model is:

[0317]

[0318] In the formula, P g,t is the power generation of the gth fossil energy unit at the t period; β g (t) is the average fuel consumption per unit of electricity of the thermal power unit at the corresponding power operating point, that is, the specific consumption characteristic; NCV g,r (t) is the average low heat value of the fossil fuel used by the gth thermal power unit in the t period; CC g,r is the carbon content per unit heat value of the fossil fuel used by the gth thermal power unit; OF g,r is the carbon oxidation rate of the fuel.

[0319] Further, the constraint conditions of the simulation pre-evaluation model include load balance constraints, fossil energy unit output operation constraints, fossil energy unit climbing operation constraints, fossil energy unit start-stop operation state constraints, fossil energy unit minimum start-stop time constraints, power grid line transmission capacity constraints, system reserve capacity constraints, new energy output constraints, and annual total carbon emission constraints, wherein:

[0320] The load balance constraint satisfies:

[0321]

[0322] In the formula, m represents the grid partition number; N represents the number of grid partitions; g is the clustering thermal power unit number; N G,n is the total clustering number of thermal power units in the region n; represents the new energy output of the region n at the t period;

[0323] outgoing power;

[0324] The fossil energy unit output operation constraint satisfies:

[0325]

[0326] In the formula, is the upper limit and lower limit of the gth type of thermal power unit in region n; X g,n (t) is the operation state of the gth type of thermal power unit in region n at time t, which is a binary variable, 0 represents that the unit has been shut down, and 1 represents that the unit is running; ΔP g,n (t) is the power of the gth type of thermal power unit in region n at time t participating in optimization;

[0327] The fossil energy unit climbing operation constraint is satisfied:

[0328] P g,n (t+1)-P g,n (t)≤ΔP g,up (46)

[0329] P g,n (t)-P g,n (t+1)≤ΔP g,down (47)

[0330] In the formula: ΔP g,up and ΔP g,down respectively represent the up-climbing rate and down-climbing rate of the thermal power unit;

[0331] The fossil energy unit start-stop operation state constraint is satisfied:

[0332]

[0333] In the formula: Y g (t) and Z g (t) are the start state and stop state of the gth type of unit at time t, both of which are binary variables. For Y, 0 represents not in the start state, and 1 represents being started; for Z, 0 represents not in the stop state, and 1 represents being stopped; this constraint is a logical constraint of the unit start-stop and operation state, which ensures that the state variables are logical in the process of unit combination;

[0334] The fossil energy unit minimum start-stop time constraint is satisfied:

[0335] Y g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1 (49)

[0336] Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1 (50)

[0337] In the formula, k is determined by the minimum unit start-up or shutdown time parameter, which reflects the time step of minimum start-up or shutdown. This constraint mainly considers the constraints of physical characteristics, energy consumption and operation cost of the unit, and the unit cannot be frequently started and stopped;

[0338] The power grid line transmission capacity constraint is satisfied:

[0339]

[0340] In the formula, represents the line transmission section limit between region n and region m;

[0341] The system reserve capacity constraint is satisfied:

[0342]

[0343] In the formula: R P and R N are positive and negative rotating reserves, respectively; is the reliable capacity of new energy generation in region n, which refers to the conventional unit capacity that can be replaced by new energy under a certain confidence level;

[0344] The new energy output constraint is satisfied:

[0345]

[0346] In the formula: represents the theoretical time series output of the wind farm in region n at period t, represents the theoretical time series output of the photovoltaic power station in region n at period t;

[0347] The annual total carbon emission constraint E n is satisfied:

[0348]

[0349] In the formula, E n is the annual total carbon emission constraint.

[0350] Further, in the first optimization module 202, the unit combination with the largest new energy consumption is optimized as the target, and the objective function satisfies:

[0351]

[0352] In the formula: n represents the grid region number, represents the power generation output of the wind farm in region n at period t, represents the power generation output of the photovoltaic power station in region n at period t.

[0353] Further, in the second optimization module 203, when the carbon emission minimum unit output is optimized, the objective function satisfies:

[0354]

[0355] P g (t) = β g (t) * CC g (t) * OF g (t) * NCV g (t) / (1000 * CC g (t) ), (1) g,t P g (t) is the power of the gth fossil energy unit at time t; β g (t) is the average fuel consumption per unit of electricity of the thermal power unit at the corresponding power operating point, that is, the specific consumption characteristic; NCV g,r (t) is the average low heat value of the fossil fuel used by the gth thermal power unit in the time period t; CC g,r is the carbon content per unit heat value of the fossil fuel used by the gth thermal power unit; OF g,r is the carbon oxidation rate of the fuel.

[0356] Embodiments of the application also provide a terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the power system carbon emission timing production simulation pre-evaluation method.

[0357] Specifically, the processor can be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in combination with the disclosure. The processor can also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of DSP and microprocessor, etc.

[0358] Specifically, the processor is connected with the memory through a bus, and the bus can include a channel for transmitting information. The bus can be a PCI bus or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc.

[0359] The memory can be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, an optical disk storage (including a compact disk, a laser disk, an optical disk, a digital versatile disk, a Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium capable of carrying or storing desired program codes in the form of instructions or data structures and capable of being accessed by a computer, but not limited thereto.

[0360] Optionally, the memory is used to store the code of the computer program for executing the scheme of the application, and the processor is used to control the execution. The processor is used to execute the application program code stored in the memory to implementFigure 2 The power system carbon emission time-series production simulation pre-evaluation system provided by the embodiment shown.

[0361] Another embodiment of the present application provides a computer readable storage medium storing computer executable instructions for executing the above Figure 1 The power system carbon emission time-series production simulation pre-evaluation method shown.

[0362] The device embodiments described above are only schematic, wherein the units described as separate components can or can not be physically separate, i.e., can be located in one place or can be distributed on a plurality of network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0363] Those skilled in the art can understand that all or some steps of the method disclosed above and the system can be implemented as software, firmware, hardware and appropriate combinations thereof. Some or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software can be distributed on a computer readable medium, which can include computer storage media (or non-transitory media) and communication media (or transitory media). As known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. In addition, as known to those skilled in the art, communication media generally includes computer readable instructions, data structures, program modules or other data in a modulated data signal carrier or other transmission mechanism, and can include any information delivery medium.

[0364] The above is a specific description of the preferred embodiments of the present application, but the present application is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or replacements without departing from the spirit of the present application, and these equivalent modifications or replacements are all included in the scope defined by the claims of the present application.

Claims

1. A method for pre-assessment of carbon emission time-series production simulation in a power system, characterized in that, Includes the following steps: With the goal of minimizing carbon emissions, a time-series simulation and pre-assessment model for carbon emissions in the power system is constructed. Based on the simulation pre-evaluation model, the simulation pre-evaluation model is optimized with the unit combination that maximizes renewable energy consumption as the objective, to obtain the renewable energy consumption maximization optimization model, and the unit combination and its start-up and shutdown arrangements of the power system are obtained based on the renewable energy consumption maximization optimization model. The optimization model for maximizing the absorption of new energy sources is optimized with the goal of minimizing the unit output. The model is then linearized in stages using a piecewise linearization method to obtain a linearized optimization model. Based on the linearized optimization model and the unit combination and its start-up and shutdown arrangements, the unit output plan is determined. By combining the unit combination and its start-up and shutdown arrangements with the unit output plan, the power system production simulation results are obtained.

2. The method according to claim 1, characterized in that, In the step of constructing a time-series simulation pre-assessment model for power system carbon emissions with the goal of minimizing carbon emissions, the objective function of the simulation pre-assessment model is: In the formula: P g,t β represents the power generation capacity of the g-th fossil fuel unit during time period t; g (t) represents the average fuel consumption per unit of electricity generated by the thermal power unit at the corresponding power operating point, i.e., the specific fuel consumption characteristic; NCV g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t; CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit; OF g,r The carbon oxidation rate of the fuel.

3. The method according to claim 2, characterized in that, The constraints of the simulation pre-evaluation model include load balance constraints, fossil fuel unit output operation constraints, fossil fuel unit ramp-up operation constraints, fossil fuel unit start-up and shutdown operation status constraints, fossil fuel unit minimum start-up and shutdown time constraints, power grid transmission capacity constraints, system reserve capacity constraints, renewable energy output constraints, and annual total carbon emission constraints, among which: Load balance constraints are satisfied: In the formula: m represents the power grid partition number; N represents the number of power grid partitions; g is the clustered thermal power unit number; N G,n The total number of clusters of thermal power units within region n; This represents the output of new energy sources in region n during time period t. External power transmission; Fossil fuel power unit output operation constraints are satisfied: In the formula: X represents the upper and lower limits of the output of the g-th type of thermal power unit within region n; g,n (t) represents the operating status of the nth type g thermal power unit in the region during time period t. It is a binary variable, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. ΔP g,n (t) represents the power of the nth type g thermal power unit in the region participating in the optimization during time period t; Fossil fuel power units meet the following constraints during ramp-up operation: P g,n (t+1)-P g,n (t)≤ΔP g,up P g,n (t)-P g,n (t+1)≤ΔP g,down Where: ΔP g,up and ΔP g,down These represent the uphill and downhill ramp rates of thermal power units, respectively. Fossil fuel power unit start-up and shutdown operation constraints are satisfied: In the formula: Y g (t) and Z g (t) represents the start-up and shutdown states of the g-th unit at time t, both of which are binary variables. For Y, 0 indicates that it is not in the start-up state, and 1 indicates that it is starting up; for Z, 0 indicates that it is not in the shutdown state, and 1 indicates that it is shutting down. This constraint is a logical constraint on the start-up, shutdown, and operation states of the unit, ensuring that each state variable is logically consistent during the unit combination process. The minimum start-up and shutdown time constraints for fossil fuel power units are satisfied as follows: Y g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1 Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1 In the formula: k is determined by the minimum start-up or shutdown time parameter of the unit, which reflects the minimum start-up or shutdown time step. This constraint is mainly due to the constraints of the unit's physical characteristics, energy consumption and operating costs, and the unit cannot be frequently started and stopped. The power grid transmission capacity constraint is satisfied as follows: In the formula, This represents the line transmission section limit between region n and region m; The system's reserve capacity constraint is satisfied: In the formula: R P and R N They are for positive and negative rotation respectively; The credible capacity of renewable energy generation within region n refers to the capacity of conventional generating units that can be replaced by renewable energy under a certain confidence level. New energy output constraints are met: In the formula: P n W (t) refers to the theoretical time series power output of wind farm n in region during time period t. This refers to the theoretical time series output of photovoltaic power plants in region n during period t. Annual carbon emission limit E n satisfy: In the formula, E n This serves as a constraint on the total annual carbon emissions.

4. The method according to claim 1, characterized in that, In the step of optimizing the simulation pre-evaluation model based on the simulation pre-evaluation model with the unit combination that maximizes renewable energy consumption as the objective, to obtain the renewable energy consumption-maximizing optimization model, and obtaining the unit combination and its start-up and shutdown schedule of the power system based on the renewable energy consumption-maximizing optimization model, the objective function satisfies the following when optimizing with the unit combination that maximizes renewable energy consumption as the objective: In the formula: n refers to the power grid area number, P n w (t) refers to the power generation output of wind farm n in region during time period t. This refers to the power output of a photovoltaic power station in region n during time period t.

5. The method according to claim 4, characterized in that, In the step of optimizing the simulation pre-evaluation model based on the simulation pre-evaluation model with the unit combination that maximizes renewable energy consumption as the objective, to obtain the optimized model for maximizing renewable energy consumption, and obtaining the unit combination and its start-up and shutdown schedule of the power system based on the optimized model for maximizing renewable energy consumption, the constraints when optimizing with the unit combination that maximizes renewable energy consumption as the objective include: Load balance constraints: In the formula: m represents the power grid partition number; N represents the number of power grid partitions; g is the clustered thermal power unit number; N G,n The total number of clusters of thermal power units within region n; P represents the renewable energy output of region n during time period t; g,n (t) represents the output of the g-th type thermal power unit in region n during time period t; The load within region n; For power exchange between region n and region m; This represents the power transmitted by the tie line in region n during time period t. Fossil fuel power unit output constraints: In the formula: X represents the upper and lower limits of the output of the g-th type of thermal power unit within region n; g,n (t) represents the operating status of the nth type g thermal power unit in the region during time period t. It is a binary variable, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. ΔP g,n (t) represents the power of the nth type g thermal power unit in the region participating in the optimization during time period t; Constraints on ramp-up operation of fossil fuel units: P g,n (t+1)-P g,n (t)≤ΔP g,up P g,n (t)-P g,n (t+1)≤ΔP g,down Where: ΔP g,up and ΔP g,down These represent the uphill and downhill ramp rates of thermal power units, respectively. Fossil fuel power unit start-up and shutdown operation constraints: In the formula: Y g (t) and Z g (t) represents the start-up and shutdown states of the g-th unit at time t, both of which are binary variables. For Y, 0 indicates that it is not in the start-up state, and 1 indicates that it is starting up; for Z, 0 indicates that it is not in the shutdown state, and 1 indicates that it is shutting down. This constraint is a logical constraint on the start-up, shutdown, and operation states of the unit, ensuring that each state variable is logically consistent during the unit combination process. Minimum start-up and shutdown time constraints for fossil fuel power units: Y g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1 Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1 In the formula: k is determined by the minimum start-up or shutdown time parameter of the unit, which reflects the minimum start-up or shutdown time step. This constraint is mainly due to the constraints of the unit's physical characteristics, energy consumption and operating costs, and the unit cannot be frequently started and stopped. Power grid transmission capacity constraints: In the formula, This represents the line transmission section limit between region n and region m; System backup capacity constraints: In the formula: R P and R N They are for positive and negative rotation respectively; The credible capacity of renewable energy generation within region n refers to the capacity of conventional generating units that can be replaced by renewable energy under a certain confidence level. Constraints on new energy output: In the formula: P n W (t) refers to the theoretical time series power output of wind farm n in region during time period t, P n PV (t) refers to the theoretical time series output of photovoltaic power station n in region during time period t.

6. The method according to claim 1, characterized in that, The optimization model for maximizing new energy consumption, which aims to achieve the lowest possible unit output with minimal carbon emissions, is then optimized using a piecewise linearization method to obtain a linearized optimization model. In the step of determining the unit output plan based on this linearized optimization model and the unit combination and its start-up and shutdown schedule, when optimizing with the lowest possible unit output, the objective function satisfies: In the formula: P g,t β represents the power generation capacity of the g-th fossil fuel unit during time period t; g (t) represents the average fuel consumption per unit of electricity generated by the thermal power unit at the corresponding power operating point, i.e., the specific fuel consumption characteristic; NCV g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t; CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit; OF g,r The carbon oxidation rate of the fuel.

7. The method according to claim 6, characterized in that, In the step of optimizing the new energy consumption maximization optimization model with the goal of minimizing carbon emissions and performing staged linearization using a piecewise linearization method to obtain a linearized optimization model, and determining the unit output plan based on the linearized optimization model and the unit combination and its start-up and shutdown arrangements, the constraints when optimizing with the goal of minimizing carbon emissions include: Load balance constraints: In the formula: m represents the power grid partition number; N represents the number of power grid partitions; g is the clustered thermal power unit number; N G,n The total number of clusters of thermal power units within region n; P represents the renewable energy output of region n during time period t; g,n (t) represents the output of the g-th type thermal power unit in region n during time period t; The load within region n; For power exchange between region n and region m; This represents the power transmitted by the tie line in region n during time period t. Fossil fuel power unit output constraints: In the formula: X represents the upper and lower limits of the output of the g-th type of thermal power unit within region n; g,n (t) represents the operating status of the nth type g thermal power unit in the region during time period t. It is a binary variable, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. ΔP g,n (t) represents the power of the nth type g thermal power unit in the region participating in the optimization during time period t; Fossil fuel power unit ramp-up constraints: P g,n (t+1)-P g,n (t)≤ΔP g,up P g,n (t)-P g,n (t+1)≤ΔP g,down Where: ΔP g,up and ΔP g,down These represent the uphill and downhill ramp rates of thermal power units, respectively. Power grid transmission capacity constraints: In the formula, This represents the line transmission section limit between region n and region m; Constraints on new energy output: In the formula: P n W (t) refers to the theoretical time series power output of wind farm n in region during time period t, P n PV (t) refers to the theoretical time series output of photovoltaic power station n in region during time period t; Annual carbon emissions E n constraint: In the formula, E n This serves as a constraint on the total annual carbon emissions.

8. The method according to claim 7, characterized in that, The optimization model for maximizing new energy consumption, with the goal of minimizing unit output with carbon emissions, is then optimized using a piecewise linearization method for staged linearization to obtain a linearized optimization model. In the step of determining the unit output plan based on the linearized optimization model and the unit combination and its start-up and shutdown arrangements, the objective function of the linearized optimization model, after staged linearization using a piecewise linearization method, satisfies the following: The constraints also include: In the formula, b k The points used to perform piecewise linearization of the model are respectively z k w k Auxiliary points are introduced to linearize the model, and b k correspond.

9. A power system carbon emission time-series production simulation and pre-assessment system, characterized in that, include: The model building module can construct a time-series simulation and pre-assessment model of carbon emissions in the power system with the goal of minimizing carbon emissions; The first optimization module can optimize the simulation pre-evaluation model based on the simulation pre-evaluation model with the unit combination that maximizes new energy consumption as the target, to obtain the optimization model that maximizes new energy consumption, and obtain the unit combination and its start-up and shutdown arrangements of the power system based on the optimization model that maximizes new energy consumption. The second optimization module can optimize the new energy consumption maximization optimization model with the goal of minimizing the unit output of carbon emissions, and use the piecewise linearization method to perform staged linearization to obtain a linearized optimization model. Based on the linearized optimization model and the unit combination and its start-up and shutdown arrangements, the unit output plan is determined. The simulation evaluation module can combine the unit combination and its start-up and shutdown arrangements with the unit output plan to obtain the power system production simulation results.

10. The system according to claim 9, characterized in that, In the model building module, the objective function of the simulation pre-evaluation model is: In the formula: P g,t β represents the power generation capacity of the g-th fossil fuel unit during time period t; g (t) represents the average fuel consumption per unit of electricity generated by the thermal power unit at the corresponding power operating point, i.e., the specific fuel consumption characteristic; NCV g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t; CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit; OF g,r The carbon oxidation rate of the fuel.

11. The system according to claim 10, characterized in that, The constraints of the simulation pre-evaluation model include load balance constraints, fossil fuel unit output operation constraints, fossil fuel unit ramp-up operation constraints, fossil fuel unit start-up and shutdown operation status constraints, fossil fuel unit minimum start-up and shutdown time constraints, power grid transmission capacity constraints, system reserve capacity constraints, renewable energy output constraints, and annual total carbon emission constraints, among which: Load balance constraints are satisfied: In the formula: m represents the power grid partition number; N represents the number of power grid partitions; g is the clustered thermal power unit number; N G,n The total number of clusters of thermal power units within region n; P represents the renewable energy output of region n during time period t; g,n (t) represents the output of the g-th type thermal power unit in region n during time period t; The load within region n; For power exchange between region n and region m; This represents the power transmitted by the tie line in region n during time period t. Fossil fuel power unit output operation constraints are satisfied: In the formula: X represents the upper and lower limits of the output of the g-th type of thermal power unit within region n; g,n (t) represents the operating status of the nth type g thermal power unit in the region during time period t. It is a binary variable, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. ΔP g,n (t) represents the power of the nth type g thermal power unit in the region participating in the optimization during time period t; Fossil fuel power units meet the following constraints during ramp-up operation: P g,n (t+1)-P g,n (t)≤ΔP g,up P g,n (t)-P g,n (t+1)≤ΔP g,down Where: ΔP g,up and ΔP g,down These represent the uphill and downhill ramp rates of thermal power units, respectively. Fossil fuel power unit start-up and shutdown operation constraints are satisfied: In the formula: Y g (t) and Z g (t) represents the start-up and shutdown states of the g-th unit at time t, both of which are binary variables. For Y, 0 indicates that it is not in the start-up state, and 1 indicates that it is starting up; for Z, 0 indicates that it is not in the shutdown state, and 1 indicates that it is shutting down. This constraint is a logical constraint on the start-up, shutdown, and operation states of the unit, ensuring that each state variable is logically consistent during the unit combination process. The minimum start-up and shutdown time constraints for fossil fuel power units are satisfied as follows: Y g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1 Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1 In the formula: k is determined by the minimum start-up or shutdown time parameter of the unit, which reflects the minimum start-up or shutdown time step. This constraint is mainly due to the constraints of the unit's physical characteristics, energy consumption and operating costs, and the unit cannot be frequently started and stopped. The power grid transmission capacity constraint is satisfied as follows: In the formula, This represents the line transmission section limit between region n and region m; The system's reserve capacity constraint is satisfied: In the formula: R P and R N They are for positive and negative rotation respectively; The credible capacity of renewable energy generation within region n refers to the capacity of conventional generating units that can be replaced by renewable energy under a certain confidence level. New energy output constraints are met: In the formula: P n W (t) refers to the theoretical time series power output of wind farm n in region during time period t, P n PV (t) refers to the theoretical time series output of photovoltaic power station n in region during time period t; Annual carbon emission limit E n satisfy: In the formula, E n This serves as a constraint on the total annual carbon emissions.

12. The system according to claim 9, characterized in that, In the first optimization module, when optimizing the unit combination that maximizes new energy consumption, the objective function satisfies: In the formula: n refers to the power grid area number, P n w (t) refers to the power generation output of wind farm n in region during time period t, P n PV (t) refers to the power output of the photovoltaic power station in region n during time period t.

13. The system according to claim 12, characterized in that, In the first optimization module, when optimizing the unit combination that maximizes new energy consumption as the target, the constraints include: Load balance constraints: In the formula: m represents the power grid partition number; N represents the number of power grid partitions; g is the clustered thermal power unit number; N G,n The total number of clusters of thermal power units within region n; P represents the renewable energy output of region n during time period t; g,n (t) represents the output of the g-th type thermal power unit in region n during time period t; The load within region n; For power exchange between region n and region m; This represents the power transmitted by the tie line in region n during time period t. Fossil fuel power unit output constraints: In the formula: X represents the upper and lower limits of the output of the g-th type of thermal power unit within region n; g,n (t) represents the operating status of the nth type g thermal power unit in the region during time period t. It is a binary variable, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. ΔP g,n (t) represents the power of the nth type g thermal power unit in the region participating in the optimization during time period t; Constraints on ramp-up operation of fossil fuel units: P g,n (t+1)-P g,n (t)≤ΔP g,up P g,n (t)-P g,n (t+1)≤ΔP g,down Where: ΔP g,up and ΔP g,down These represent the uphill and downhill ramp rates of thermal power units, respectively. Fossil fuel power unit start-up and shutdown operation constraints: In the formula: Y g (t) and Z g (t) represents the start-up and shutdown states of the g-th unit at time t, both of which are binary variables. For Y, 0 indicates that it is not in the start-up state, and 1 indicates that it is starting up; for Z, 0 indicates that it is not in the shutdown state, and 1 indicates that it is shutting down. This constraint is a logical constraint on the start-up, shutdown, and operation states of the unit, ensuring that each state variable is logically consistent during the unit combination process. Minimum start-up and shutdown time constraints for fossil fuel power units: Y g (t)+Z g (t+1)+Z g (t+2)+...+Z g (t+k)≤1 Z g (t)+Y g (t+1)+Y g (t+2)+...+Y g (t+k)≤1 In the formula: k is determined by the minimum start-up or shutdown time parameter of the unit, which reflects the minimum start-up or shutdown time step. This constraint is mainly due to the constraints of the unit's physical characteristics, energy consumption and operating costs, and the unit cannot be frequently started and stopped. Power grid transmission capacity constraints: In the formula, This represents the line transmission section limit between region n and region m; System backup capacity constraints: In the formula: R P and R N They are for positive and negative rotation respectively; The credible capacity of renewable energy generation within region n refers to the capacity of conventional generating units that can be replaced by renewable energy under a certain confidence level. Constraints on new energy output: In the formula: P n W (t) refers to the theoretical time series power output of wind farm n in region during time period t, P n PV (t) refers to the theoretical time series output of photovoltaic power station n in region during time period t.

14. The system according to claim 9, characterized in that, In the second optimization module, when optimizing for the unit output with the lowest carbon emissions, the objective function satisfies: In the formula: P g,t β represents the power generation capacity of the g-th fossil fuel unit during time period t; g (t) represents the average fuel consumption per unit of electricity generated by the thermal power unit at the corresponding power operating point, i.e., the specific fuel consumption characteristic; NCV g,r (t) represents the average lower heating value of the fossil fuel used by the g-th thermal power unit during the time period t; CC g,r The carbon content per unit calorific value of the fossil fuel used by the g-th thermal power unit; OF g,r The carbon oxidation rate of the fuel.

15. The system according to claim 14, characterized in that, In the second optimization module, when optimizing for the unit output with the lowest carbon emissions, the constraints include: Load balance constraints: In the formula: m represents the power grid partition number; N represents the number of power grid partitions; g is the clustered thermal power unit number; N G,n The total number of clusters of thermal power units within region n; P represents the renewable energy output of region n during time period t; g,n (t) represents the output of the g-th type thermal power unit in region n during time period t; The load within region n; For power exchange between region n and region m; This represents the power transmitted by the tie line in region n during time period t. Fossil fuel power unit output constraints: In the formula: X represents the upper and lower limits of the output of the g-th type of thermal power unit within region n; g,n (t) represents the operating status of the nth type g thermal power unit in the region during time period t. It is a binary variable, where 0 indicates that the unit has been shut down and 1 indicates that the unit is running. ΔP g,n (t) represents the power of the nth type g thermal power unit in the region participating in the optimization during time period t; Fossil fuel power unit ramp-up constraints: P g,n (t+1)-P g,n (t)≤ΔP g,up P g,n (t)-P g,n (t+1)≤ΔP g,down Where: ΔP g,up and ΔP g,down These represent the uphill and downhill ramp rates of thermal power units, respectively. Power grid transmission capacity constraints: In the formula, This represents the line transmission section limit between region n and region m; Constraints on new energy output: In the formula: P n W (t) refers to the theoretical time series power output of wind farm n in region during time period t, P n PV (t) refers to the theoretical time series output of photovoltaic power station n in region during time period t; Annual carbon emissions E n constraint: In the formula, E n This serves as a constraint on the total annual carbon emissions.

16. The system according to claim 15, characterized in that, In the second optimization module, a piecewise linearization method is used to perform staged linearization. After obtaining the linearized optimization model, the objective function of the linearized optimization model satisfies: The constraints also include: In the formula, b k The points used to perform piecewise linearization of the model are respectively z k w k Auxiliary points are introduced to linearize the model, and b k correspond.

17. A terminal, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method of any one of claims 1 to 8.

18. A computer-readable storage medium storing computer-executable instructions for performing the method of any one of claims 1 to 8.

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