Power generation planning method, system and device considering carbon emission reduction and storage medium

Abstract

The invention relates to the technical field of electric power, in particular to a power generation planning method, system and device considering carbon emission reduction and a storage medium. Comprising the steps of constructing a power generation cost model, calculating a carbon dioxide emission tax and a total government subsidy, determining power generation cost of the government under different carbon emission reduction strategies, modeling behaviors of the government and a power plant by using a Nash-Cournot model, finding a Nash equilibrium point in the Nash-Cournot model by using a PSO optimization algorithm, and determining the power generation cost of the government according to the Nash equilibrium point. And obtaining the number of various units corresponding to the Nash equilibrium point, the energy type and the generating capacity of each engine unit. Costs and carbon emission costs of different power generation modes in a power system are evaluated, related policies such as carbon dioxide emission tax and subsidy are considered, the power generation costs under different policies are calculated, the reliability of power generation cost calculation is improved, government and power plant behaviors are modeled by using a Nap-Cournot model, and the power generation cost calculation efficiency is improved. And finding a Nash equilibrium point in the Nash-Cournot model by adopting a PSO (Particle Swarm Optimization) algorithm so as to determine an optimal power generation combination scheme.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a method, system, device and storage medium for power generation planning taking carbon emission reduction into consideration. Background Art

[0002] The restructuring and regulation of the power industry in recent decades has brought fundamental changes to the practice of power system planning. Generation expansion planning (GEP) has been one of the most discussed topics in internationally recognized power industry journals. GEP is a large-scale, nonlinear, discrete, dynamic, and highly constrained optimization problem that determines which generating units should be built within the planning scope and when they should be put into operation so that the installed capacity meets the forecast demand. In the past few years, carbon emission reduction has been an attractive topic. Existing studies have considered few factors in the process of power generation planning and carbon emission reduction, resulting in inaccurate power generation planning results under carbon emission reduction and no practical reference. Summary of the invention

[0003] In order to overcome the technical problem of inaccurate power generation planning results considering carbon emission reduction in the prior art, the present invention proposes a power generation planning method, system, device and storage medium considering carbon emission reduction.

[0004] The technical solution adopted by the present invention to achieve the above-mentioned purpose is: a power generation planning method considering carbon emission reduction, comprising:

[0005] Constructing power generation cost model;

[0006] Calculate CO2 emissions taxes and total government subsidies;

[0007] Determine the government's power generation costs under different carbon emission reduction strategies based on the constructed power generation cost model and the calculated carbon dioxide emission tax and total government subsidies;

[0008] The Nash-Cournot model is used to model the behavior of the government and power plants based on the power generation costs under different carbon emission reduction strategies;

[0009] The PSO optimization algorithm is used to find the Nash equilibrium point in the Nash-Cournot model to obtain the number NU of each type of unit, the energy category k and the power generation CU of each engine unit corresponding to the Nash equilibrium point.

[0010] Preferably, the construction of the power generation cost model comprises the following steps:

[0011] Calculate the cost of power generation planning:

[0012]

[0013]

[0014] Among them, Cost inv represents the investment cost, k represents the energy category, q represents the maximum number of energy categories, i represents the planning time period, p represents the maximum planning duration, CU represents the power generation of each generator set, IC represents the investment cost of each unit, NU represents the number of each type of unit, r represents the dimension of the input data sequence, Cost gen represents the power generation cost, FC represents the variable power generation cost of each unit, cumNU represents the cumulative total number of units, TW represents the theoretical working hours of each unit, CapF represents the capacity factor of each unit, Cost O&M represents the operation and maintenance cost, OMC represents the operation and maintenance cost of each unit;

[0015] The objective function of the power generation cost model is constructed. The expression of the objective function is:

[0016] min{Cost GEP =Cost inv +Cost gen +Cost O&M}

[0017] Among them, Cost GEP Cost represents the system cost of considering power generation planning problems. inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost;

[0018] Constraints for building a power generation cost model:

[0019] Spare margin constraints:

[0020] R min <R(i)<R max i=1,...,p

[0021] Among them, R represents the reserve margin, R min and R max They represent the minimum and maximum values ​​of the reserve margin, respectively, i represents the planned time period, and p represents the maximum value of the planned duration;

[0022] Constraints on the maximum number of new units;

[0023]

[0024] in, Indicates the capacity of the units that may be added in each time period. Indicates the maximum unit capacity that may be added in each time period;

[0025] Total capacity constraints for each time period:

[0026] (1+R min )×Demand peak (i)≤CCap total (i)≤(1+R max )×Demand peak (i)

[0027] i=1,...,p

[0028] Among them, R min and R max They represent the minimum and maximum values ​​of the reserve margin, i represents the planned time period, p represents the maximum planned duration, and Demand peak Indicates the system peak demand capacity during this period, CCap tolal Indicates the total capacity constraint for each time period;

[0029] The total capacity calculation expression for each period is:

[0030]

[0031] Among them, CCap tolal represents the total capacity of each time period, k represents the energy category, q represents the maximum number of energy categories, i represents the planned time period, p represents the maximum planning duration, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

[0032] Preferably, the carbon dioxide emission tax and the total government subsidy are calculated, wherein the carbon dioxide emission tax calculation expression is:

[0033]

[0034] Among them, Tax carbon represents the carbon dioxide emission tax, i represents the planning time period, p represents the maximum planning time, ET represents the carbon dioxide emission cost, CO2 gen represents the carbon dioxide emissions, CU represents the power generation of each engine unit, and cumNU represents the cumulative total of the number of units;

[0035] The total government subsidy calculation expression is:

[0036]

[0037] Among them, Subside government represents the total government subsidy, i represents the planning period, p represents the maximum planning duration, S govrepresents the government subsidy per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

[0038] Preferably, the government's electricity generation costs under different carbon emission reduction strategies are as follows:

[0039] Strategy 1: Without considering carbon dioxide emission tax and government subsidies, the power generation cost function expression at this time is:

[0040] Cost Strategy1 =Cost inv +Cost gen +Cost O&M

[0041] Among them, Cost Strategy1 represents the power generation cost under strategy 1, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost;

[0042] Strategy 2: Considering the carbon dioxide emission tax as a penalty factor for non-renewable energy power plants, the power generation cost function expression at this time is:

[0043] Cost Strategy2 =Cost inv +Cost gen +Cost O&M +Tax carbon

[0044] Among them, Cost Strategy2 represents the power generation cost under strategy 2, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon represents a carbon dioxide emission tax;

[0045] Strategy 3: Considering the total government subsidy as an incentive for renewable energy power plants, the power generation cost function expression at this time is:

[0046] Cost Strategy3 =Cost inv +Cost gen +Cost O&M -Subside government

[0047] Among them, Cost Strategy3 represents the power generation cost under strategy three, Cost invIndicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates operation and maintenance costs, Subside government represents total government subsidies;

[0048] Strategy 4: Considering both the carbon dioxide emission tax and the total government subsidy, the power generation cost function expression at this time is:

[0049] Cost Strategy4 =Cost inv +Cost gen +Cost O&M +Tax carbon -Subside government

[0050] Among them, Cost Strategy4 represents the power generation cost under strategy 4, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon Subside government represents total government subsidies.

[0051] Preferably, in the Nash-Cournot model, each power plant is regarded as a gaming party, and the goal of the power plant is to maximize revenue. The government is regarded as another gaming party, and the purpose of the government is to minimize the system cost of considering the power generation planning problem and reduce carbon emissions by levying carbon taxes and providing subsidies. The expression of the Nash-Cournot model is:

[0052] Π s =Rev s -Cost s s=1,...,4

[0053] Among them, s represents the power generation profit under a certain strategy, Rev s represents the income from selling electricity under the sth strategy, Cost s represents the power generation cost under the s-th strategy;

[0054] Among them, the income from selling electricity in the case of the sth strategy is Rev s The calculation expression is:

[0055]

[0056] Among them, Rev srepresents the income from selling electricity under the sth strategy, i represents the planning time period, p represents the maximum planning duration, EP represents the price of electricity per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

[0057] Preferably, the particle velocity update expression when the PSO optimization algorithm searches for the Nash equilibrium point is:

[0058]

[0059] in, represents the velocity of particle i in j-dimensional space in the next iteration, represents the speed of particle i in the j-dimensional space in the current iteration, w represents the inertia weight, t represents the current iteration number, R1 and R2 represent random numbers between 0 and 1, c1 and c2 represent the individual learning factor and the group learning factor respectively, Indicates the position of particle i in the j-dimensional space in the current iteration, represents the personal best position of particle i in the j-dimensional space in the current iteration, Indicates the global optimal position of particle i in the j-dimensional space in the current iteration;

[0060] The expression of particle position update when the PSO optimization algorithm searches for the Nash equilibrium point is:

[0061]

[0062] in, Indicates the position of particle i in j-dimensional space in the next iteration, Indicates the position of particle i in the j-dimensional space in the current iteration, Indicates the velocity of particle i in j-dimensional space in the current iteration.

[0063] A power generation planning system considering carbon emission reduction, comprising:

[0064] Constructing a power generation cost model module, used to construct a power generation cost model;

[0065] CO2 emission tax and total government subsidies calculation module, used to calculate CO2 emission tax and total government subsidies;

[0066] The power generation cost analysis module is used to determine the power generation cost of the government under different carbon emission reduction strategies based on the constructed power generation cost model and the calculated carbon dioxide emission tax and total government subsidies;

[0067] The Nash-Cournot model building module is used to model the behavior of governments and power plants using the Nash-Cournot model based on the government's power generation costs under different carbon emission reduction strategies;

[0068] The solution module is used to find the Nash equilibrium point in the Nash-Cournot model using the PSO optimization algorithm to obtain the number NU of various units, the energy category k and the power generation CU of each engine group corresponding to the Nash equilibrium point.

[0069] Preferably, constructing the power generation cost model comprises the following steps:

[0070] Calculate the cost of power generation planning:

[0071]

[0072]

[0073] Among them, Cost inv represents the investment cost, k represents the energy category, q represents the maximum number of energy categories, i represents the planning time period, p represents the maximum planning duration, CU represents the power generation of each generator set, IC represents the investment cost of each unit, NU represents the number of each type of unit, r represents the dimension of the input data sequence, Cost gen represents the power generation cost, FC represents the variable power generation cost of each unit, cumNU represents the cumulative total number of units, TW represents the theoretical working hours of each unit, CapF represents the capacity factor of each unit, Cost O&M represents the operation and maintenance cost, OMC represents the operation and maintenance cost of each unit;

[0074] The objective function of the power generation cost model is constructed. The expression of the objective function is:

[0075] min{Cost GEP =Cost inv +Cost gen +Cost O&M}

[0076] Among them, Cost GEP Cost represents the system cost of considering power generation planning problems. inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost;

[0077] Constraints for building a power generation cost model:

[0078] Spare margin constraints:

[0079] R min <R(i)<R max i=1,...,p

[0080] Among them, R represents the reserve margin, R min and R max They represent the minimum and maximum values ​​of the reserve margin, respectively, i represents the planned time period, and p represents the maximum value of the planned duration;

[0081] Constraints on the maximum number of new units;

[0082]

[0083] in, Indicates the capacity of the units that may be added in each time period. Indicates the maximum unit capacity that may be added in each time period;

[0084] Total capacity constraints for each time period:

[0085] (1+R min )×Demand peak (i)≤CCap total (i)≤(1+R max )×Demand peak (i)

[0086] i=1,...,p

[0087] Among them, R min and R max They represent the minimum and maximum values ​​of the reserve margin, i represents the planned time period, p represents the maximum planned duration, and Demand peak Indicates the system peak demand capacity during this period, CCap tolal Indicates the total capacity constraint for each time period;

[0088] The total capacity calculation expression for each period is:

[0089]

[0090] Among them, CCap tolal represents the total capacity of each time period, k represents the energy category, q represents the maximum number of energy categories, i represents the planned time period, p represents the maximum planning duration, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

[0091] Preferably, the carbon dioxide emission tax and the total government subsidy are calculated, wherein the carbon dioxide emission tax calculation expression is:

[0092]

[0093] Among them, Tax carbon represents the carbon dioxide emission tax, i represents the planning time period, p represents the maximum planning time, ET represents the carbon dioxide emission cost, CO2 gen represents the carbon dioxide emissions, CU represents the power generation of each engine unit, and cumNU represents the cumulative total of the number of units;

[0094] The total government subsidy calculation expression is:

[0095]

[0096] Among them, Subside government represents the total government subsidy, i represents the planning period, p represents the maximum planning duration, S gov represents the government subsidy per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

[0097] Preferably, the government's electricity generation costs under different carbon emission reduction strategies are as follows:

[0098] Strategy 1: Without considering carbon dioxide emission tax and government subsidies, the power generation cost function expression at this time is:

[0099] Cost Strategy1 =Cost inv +Cost gen +Cost O&M

[0100] Among them, Cost Strategy1 represents the power generation cost under strategy 1, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost;

[0101] Strategy 2: Considering the carbon dioxide emission tax as a penalty factor for non-renewable energy power plants, the power generation cost function expression at this time is:

[0102] Cost Strategy2 =Cost inv +Cost gen +Cost O&M +Tax carbon

[0103] Among them, Cost Strategy2 represents the power generation cost under strategy 2, Cost inv Indicates investment cost, Costgen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon represents a carbon dioxide emission tax;

[0104] Strategy 3: Considering the total government subsidy as an incentive for renewable energy power plants, the power generation cost function expression at this time is:

[0105] Cost Strategy3 =Cost inv +Cost gen +Cost O&M -Subside government

[0106] Among them, Cost Strategy3 represents the power generation cost under strategy three, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates operation and maintenance costs, Subside government represents total government subsidies;

[0107] Strategy 4: Considering both the carbon dioxide emission tax and the total government subsidy, the power generation cost function expression at this time is:

[0108] Cost Strategy4 =Cost inv +Cost gen +Cost O&M +Tax carbon -Subside government

[0109] Among them, Cost Strategy4 represents the power generation cost under strategy 4, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon Subside government represents total government subsidies.

[0110] Preferably, in the Nash-Cournot model, each power plant is regarded as a gaming party, and the goal of the power plant is to maximize revenue. The government is regarded as another gaming party, and the purpose of the government is to minimize the system cost of considering the power generation planning problem and reduce carbon emissions by levying carbon taxes and providing subsidies. The expression of the Nash-Cournot model is:

[0111] Π s =Revs -Cost s s=1,...,4

[0112] Among them, s represents the power generation profit under a certain strategy, Rev s represents the income from selling electricity under the sth strategy, Cost s represents the power generation cost under the s-th strategy;

[0113] Among them, the income from selling electricity in the case of the sth strategy is Rev s The calculation expression is:

[0114]

[0115] Among them, Rev s represents the income from selling electricity under the sth strategy, i represents the planning time period, p represents the maximum planning duration, EP represents the price of electricity per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

[0116] Preferably, the particle velocity update expression when the PSO optimization algorithm searches for the Nash equilibrium point is:

[0117]

[0118] in, represents the velocity of particle i in j-dimensional space in the next iteration, represents the speed of particle i in the j-dimensional space in the current iteration, w represents the inertia weight, t represents the current iteration number, R1 and R2 represent random numbers between 0 and 1, c1 and c2 represent the individual learning factor and the group learning factor respectively, Indicates the position of particle i in the j-dimensional space in the current iteration, represents the personal best position of particle i in the j-dimensional space in the current iteration, Indicates the global optimal position of particle i in the j-dimensional space in the current iteration;

[0119] The expression of particle position update when the PSO optimization algorithm searches for the Nash equilibrium point is:

[0120]

[0121] in, Indicates the position of particle i in j-dimensional space in the next iteration, Indicates the position of particle i in the j-dimensional space in the current iteration, Indicates the velocity of particle i in j-dimensional space in the current iteration.

[0122] A power generation planning device taking carbon emission reduction into consideration comprises a memory and a processor, wherein the memory is used to store a computer program, and the computer program is used to execute the above method when loaded by the processor.

[0123] A computer-readable storage medium stores a computer program, wherein the computer program is suitable for executing the above method when loaded by a processor.

[0124] Compared with the prior art, the present invention constructs a power generation cost model to evaluate the cost and carbon emission cost of different power generation methods in the power system. At the same time, relevant policies such as carbon dioxide emission tax and subsidies are taken into account to calculate the power generation cost under different strategies, thereby improving the reliability of power generation cost calculation; the Nash-Cournot model is used to model the behavior of the government and power plants, and the PSO optimization algorithm is used to find the Nash equilibrium point in the Nash-Cournot model to determine the optimal power generation combination scheme, which can reduce carbon emissions while meeting energy demand, thereby helping to protect the environment and mitigate the impact of climate change, promote the development and utilization of renewable energy, and improve the sustainability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0125] Figure 1 It is a flow chart of a power generation planning method taking carbon emission reduction into consideration according to the present invention. DETAILED DESCRIPTION

[0126] A power generation planning method considering carbon emission reduction of the present invention is as follows Figure 1 As shown, including:

[0127] Constructing power generation cost model;

[0128] The construction of the power generation cost model comprises the following steps:

[0129] Calculate the cost of power generation planning:

[0130]

[0131]

[0132] Among them, Cost inv represents the investment cost, k represents the energy category, q represents the maximum number of energy categories, i represents the planning time period, p represents the maximum planning duration, CU represents the power generation of each generator set, IC represents the investment cost of each unit, NU represents the number of each type of unit, r represents the dimension of the input data sequence, Cost genrepresents the power generation cost, FC represents the variable power generation cost of each unit, cumNU represents the cumulative total number of units, TW represents the theoretical working hours of each unit, CapF represents the capacity factor of each unit, Cost O&M represents the operation and maintenance cost, OMC represents the operation and maintenance cost of each unit;

[0133] The objective function of the power generation cost model is constructed. The expression of the objective function is:

[0134] min{Cost GEP =Cost inv +Cost gen +Cost O&M}

[0135] Among them, Cost GEP Cost represents the system cost of considering power generation planning problems. inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost;

[0136] Constraints for building a power generation cost model:

[0137] Spare margin constraints:

[0138] R min <R(i)<R max i=1,...,p

[0139] Among them, R represents the reserve margin, R min and R max They represent the minimum and maximum values ​​of the reserve margin, respectively, i represents the planned time period, and p represents the maximum value of the planned duration;

[0140] Constraints on the maximum number of new units;

[0141]

[0142] in, Indicates the capacity of the units that may be added in each time period. Indicates the maximum unit capacity that may be added in each time period;

[0143] Total capacity constraints for each time period:

[0144] (1+R min )×Demand peak (i)≤CCap total (i)≤(1+R max )×Demand peak (i)

[0145] i=1,...,p

[0146] Among them, R min and R max They represent the minimum and maximum values ​​of the reserve margin, i represents the planned time period, p represents the maximum planned duration, and Demand peak Indicates the system peak demand capacity during this period, CCap tolal Indicates the total capacity constraint for each time period;

[0147] The total capacity calculation expression for each period is:

[0148]

[0149] Among them, CCap tolal represents the total capacity of each time period, k represents the energy category, q represents the maximum number of energy categories, i represents the planned time period, p represents the maximum planning duration, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of generator sets;

[0150] Calculate CO2 emissions taxes and total government subsidies;

[0151] Calculate the carbon dioxide emission tax and total government subsidies, where the carbon dioxide emission tax calculation expression is:

[0152]

[0153] Among them, Tax carbon represents the carbon dioxide emission tax, i represents the planning time period, p represents the maximum planning time, ET represents the carbon dioxide emission cost, CO2 gen represents the carbon dioxide emissions, CU represents the power generation of each engine unit, and cumNU represents the cumulative total of the number of units;

[0154] The total government subsidy calculation expression is:

[0155]

[0156] Among them, Subside government represents the total government subsidy, i represents the planning period, p represents the maximum planning duration, S gov represents the government subsidy per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total of the number of units;

[0157] Determine the government's power generation costs under different carbon emission reduction strategies based on the constructed power generation cost model and the calculated carbon dioxide emission tax and total government subsidies;

[0158] The government's electricity costs under different carbon emission reduction strategies are as follows:

[0159] Strategy 1: Without considering carbon dioxide emission tax and government subsidies, the power generation cost function expression at this time is:

[0160] Cost Strategy1 =Cost inv +Cost gen +Cost O&M

[0161] Among them, Cost Strategy1 represents the power generation cost under strategy 1, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost;

[0162] Strategy 2: Considering the carbon dioxide emission tax as a penalty factor for non-renewable energy power plants, the power generation cost function expression at this time is:

[0163] Cost Strategy2 =Cost inv +Cost gen +Cost O&M +Tax carbon

[0164] Among them, Cost Strategy2 represents the power generation cost under strategy 2, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon represents a carbon dioxide emission tax;

[0165] Strategy 3: Considering the total government subsidy as an incentive for renewable energy power plants, the power generation cost function expression at this time is:

[0166] Cost Strategy3 =Cost inv +Cost gen +Cost O&M -Subside government

[0167] Among them, Cost Strategy3 represents the power generation cost under strategy three, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates operation and maintenance costs, Subside governmentrepresents total government subsidies;

[0168] Strategy 4: Considering both the carbon dioxide emission tax and the total government subsidy, the power generation cost function expression at this time is:

[0169] Cost Strategy4 =Cost inv +Cost gen +Cost O&M +Tax carbon -Subside government

[0170] Among them, Cost Strategy4 represents the power generation cost under strategy 4, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon Subside government represents total government subsidies;

[0171] The Nash-Cournot model is used to model the behavior of the government and power plants based on the power generation costs under different carbon emission reduction strategies;

[0172] In the Nash-Cournot model, each power plant is regarded as a game party, and the goal of the power plant is to maximize revenue. The government is regarded as another game party. The government's purpose is to minimize the system cost of power generation planning issues and reduce carbon emissions by levying carbon taxes and providing subsidies. The expression of the Nash-Cournot model is:

[0173] Π s =Rev s -Cost s s=1,...,4

[0174] Among them, s represents the power generation profit under a certain strategy, Rev s represents the income from selling electricity under the sth strategy, Cost s represents the power generation cost under the s-th strategy;

[0175] Among them, the income from selling electricity in the case of the sth strategy is Rev s The calculation expression is:

[0176]

[0177] Among them, Rev srepresents the income from selling electric energy under the sth strategy, i represents the planning time period, p represents the maximum planning duration, EP represents the price of electric energy per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of generator sets;

[0178] Use the PSO optimization algorithm to find the Nash equilibrium point in the Nash-Cournot model to obtain the number NU of each type of unit, the energy category k and the power generation CU of each engine unit corresponding to the Nash equilibrium point. The number NU of each type of unit, the energy category k and the power generation CU of each engine unit obtained at this time are the power generation planning scheme. Under this power generation plan, the balance between power generation demand and income and carbon emission reduction can be achieved;

[0179] The expression of particle velocity update when the PSO optimization algorithm searches for the Nash equilibrium point is:

[0180]

[0181] in, represents the velocity of particle i in j-dimensional space in the next iteration, represents the speed of particle i in the j-dimensional space in the current iteration, w represents the inertia weight, t represents the current iteration number, R1 and R2 represent random numbers between 0 and 1, c1 and c2 represent the individual learning factor and the group learning factor respectively, Indicates the position of particle i in the j-dimensional space in the current iteration, represents the personal best position of particle i in the j-dimensional space in the current iteration, Indicates the global optimal position of particle i in the j-dimensional space in the current iteration;

[0182] The expression of particle position update when the PSO optimization algorithm searches for the Nash equilibrium point is:

[0183]

[0184] in, Indicates the position of particle i in j-dimensional space in the next iteration, Indicates the position of particle i in the j-dimensional space in the current iteration, Indicates the velocity of particle i in j-dimensional space in the current iteration.

[0185] A power generation planning system considering carbon emission reduction, comprising:

[0186] Constructing a power generation cost model module, used to construct a power generation cost model;

[0187] Building a power generation cost model involves the following steps:

[0188] Calculate the cost of power generation planning:

[0189]

[0190]

[0191] Among them, Cost inv represents the investment cost, k represents the energy category, q represents the maximum number of energy categories, i represents the planning time period, p represents the maximum planning duration, CU represents the power generation of each generator set, IC represents the investment cost of each unit, NU represents the number of each type of unit, r represents the dimension of the input data sequence, Cost gen represents the power generation cost, FC represents the variable power generation cost of each unit, cumNU represents the cumulative total number of units, TW represents the theoretical working hours of each unit, CapF represents the capacity factor of each unit, Cost O&M represents the operation and maintenance cost, OMC represents the operation and maintenance cost of each unit;

[0192] The objective function of the government power generation cost model is constructed. The expression of the objective function is:

[0193] min{Cost GEP =Cost inv +Cost gen +Cost O&M}

[0194] Among them, Cost GEP Cost represents the system cost of considering power generation planning problems. inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost;

[0195] Constraints for constructing the government power generation cost model:

[0196] Spare margin constraints:

[0197] R min <R(i)<R max i=1,...,p

[0198] Among them, R represents the reserve margin, R min and R max They represent the minimum and maximum values ​​of the reserve margin, respectively, i represents the planned time period, and p represents the maximum value of the planned duration;

[0199] Constraints on the maximum number of new units;

[0200]

[0201] in, Indicates the capacity of the units that may be added in each time period. Indicates the maximum unit capacity that may be added in each time period;

[0202] Total capacity constraints for each time period:

[0203] (1+R min )×Demand peak (i)≤CCap total (i)≤(1+R max )×Demand peak (i)

[0204] i=1,...,p

[0205] Among them, R min and R max They represent the minimum and maximum values ​​of the reserve margin, i represents the planned time period, p represents the maximum planned duration, and Demand peak Indicates the system peak demand capacity during this period, CCap tolal Indicates the total capacity constraint for each time period;

[0206] The total capacity calculation expression for each period is:

[0207]

[0208] Among them, CCap tolal represents the total capacity of each time period, k represents the energy category, q represents the maximum number of energy categories, i represents the planned time period, p represents the maximum planning duration, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of generator sets;

[0209] CO2 emission tax and total government subsidies calculation module, used to calculate CO2 emission tax and total government subsidies;

[0210] The calculation expression of carbon dioxide emission tax is:

[0211]

[0212] Among them, Tax carbon represents the carbon dioxide emission tax, i represents the planning time period, p represents the maximum planning time, ET represents the carbon dioxide emission cost, CO2 gen represents the carbon dioxide emissions, CU represents the power generation of each engine unit, and cumNU represents the cumulative total of the number of units;

[0213] The total government subsidy calculation expression is:

[0214]

[0215] Among them, Subside government represents the total government subsidy, i represents the planning period, p represents the maximum planning duration, S gov represents the government subsidy per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

[0216] The power generation cost analysis module is used to determine the power generation cost of the government under different carbon emission reduction strategies based on the constructed power generation cost model and the calculated carbon dioxide emission tax and total government subsidies;

[0217] The government's electricity costs under different carbon emission reduction strategies are as follows:

[0218] Strategy 1: Without considering carbon dioxide emission tax and government subsidies, the power generation cost function expression at this time is:

[0219] Cost Strategy1 =Cost inv +Cost gen +Cost O&M

[0220] Among them, Cost Strategy1 represents the power generation cost under strategy 1, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost;

[0221] Strategy 2: Considering the carbon dioxide emission tax as a penalty factor for non-renewable energy power plants, the power generation cost function expression at this time is:

[0222] Cost Strategy2 =Cost inv +Cost gen +Cost O&M +Tax carbon

[0223] Among them, Cost Strategy2 represents the power generation cost under strategy 2, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon represents a carbon dioxide emission tax;

[0224] Strategy 3: Considering the total government subsidy as an incentive for renewable energy power plants, the power generation cost function expression at this time is:

[0225] Cost Strategy3 =Cost inv +Cost gen +Cost O&M -Subside government

[0226] Among them, Cost Strategy3 represents the power generation cost under strategy three, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates operation and maintenance costs, Subside government represents total government subsidies;

[0227] Strategy 4: Considering both the carbon dioxide emission tax and the total government subsidy, the power generation cost function expression at this time is:

[0228] Cost Strategy4 =Cost inv +Cost gen +Cost O&M +Tax carbon -Subside government

[0229] Among them, Cost Strategy4 represents the power generation cost under strategy 4, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon Subside government represents total government subsidies.

[0230] The Nash-Cournot model building module is used to model the behavior of governments and power plants using the Nash-Cournot model based on the government's power generation costs under different carbon emission reduction strategies;

[0231] In the Nash-Cournot model, each power plant is regarded as a game party, and the goal of the power plant is to maximize revenue. The government is regarded as another game party. The government's purpose is to minimize the system cost of power generation planning issues and reduce carbon emissions by levying carbon taxes and providing subsidies. The expression of the Nash-Cournot model is:

[0232] Π s =Revs -Cost s s=1,...,4

[0233] Among them, s represents the power generation profit under a certain strategy, Rev s represents the income from selling electricity under the sth strategy, Cost s represents the power generation cost under the s-th strategy;

[0234] Among them, the income from selling electricity in the case of the sth strategy is Rev s The calculation expression is:

[0235]

[0236] Among them, Rev s represents the income from selling electric energy under the sth strategy, i represents the planning time period, p represents the maximum planning duration, EP represents the price of electric energy per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of generator sets;

[0237] A solution module is used to find the Nash equilibrium point in the Nash-Cournot model using the PSO optimization algorithm to obtain the number NU of each type of units, the energy category k and the power generation CU of each engine group corresponding to the Nash equilibrium point;

[0238] The expression of particle velocity update when the PSO optimization algorithm searches for the Nash equilibrium point is:

[0239]

[0240] in, represents the velocity of particle i in j-dimensional space in the next iteration, represents the speed of particle i in the j-dimensional space in the current iteration, w represents the inertia weight, t represents the current iteration number, R1 and R2 represent random numbers between 0 and 1, c1 and c2 represent the individual learning factor and the group learning factor respectively, Indicates the position of particle i in the j-dimensional space in the current iteration, represents the personal best position of particle i in the j-dimensional space in the current iteration, Indicates the global optimal position of particle i in the j-dimensional space in the current iteration;

[0241] The expression of particle position update when the PSO optimization algorithm searches for the Nash equilibrium point is:

[0242]

[0243] in, Indicates the position of particle i in j-dimensional space in the next iteration, Indicates the position of particle i in the j-dimensional space in the current iteration, Indicates the velocity of particle i in j-dimensional space in the current iteration;

[0244] A power generation planning device taking carbon emission reduction into consideration comprises a memory and a processor, wherein the memory is used to store a computer program, and the computer program is used to execute the above method when loaded by the processor.

[0245] A computer-readable storage medium stores a computer program, wherein the computer program is suitable for executing the above method when loaded by a processor.

[0246] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0247] The present application is described with reference to the flowcharts of the methods, systems, and computer program products according to the embodiments of the present application. It should be understood that each process in the flowchart, as well as the combination of processes in the flowchart, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart. Figure 1 A device that specifies functions in a process or multiple processes.

[0248] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A function specified in a process or multiple processes.

[0249] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 The steps of a specified function in a process or multiple processes.

[0250] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0251] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for power generation planning considering carbon emission reduction, characterized in that: include: Constructing power generation cost model; Calculate CO2 emissions taxes and total government subsidies; Determine the government's power generation costs under different carbon emission reduction strategies based on the constructed power generation cost model and the calculated carbon dioxide emission tax and total government subsidies; The Nash-Cournot model is used to model the behavior of the government and power plants based on the power generation costs under different carbon emission reduction strategies; The PSO optimization algorithm is used to find the Nash equilibrium point in the Nash-Cournot model to obtain the number NU of each type of unit, the energy category k and the power generation CU of each engine unit corresponding to the Nash equilibrium point.

2. A method for power generation planning considering carbon emission reduction according to claim 1, characterized in that: The construction of the power generation cost model comprises the following steps: Calculate the cost of power generation planning: Among them, Cost inv represents the investment cost, k represents the energy category, q represents the maximum number of energy categories, i represents the planning time period, p represents the maximum planning duration, CU represents the power generation of each generator set, IC represents the investment cost of each unit, NU represents the number of each type of unit, r represents the dimension of the input data sequence, Cost gen represents the power generation cost, FC represents the variable power generation cost of each unit, cumNU represents the cumulative total number of units, TW represents the theoretical working hours of each unit, CapF represents the capacity factor of each unit, Cost O&M represents the operation and maintenance cost, OMC represents the operation and maintenance cost of each unit; The objective function of the power generation cost model is constructed. The expression of the objective function is: min{Cost GEP =Cost inv +Cost gen +Cost O&M } Among them, Cost GEP Cost represents the system cost of considering power generation planning problems. inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost; Constraints for building a power generation cost model: Spare margin constraints: R min <R(i)<R max i=1,...,p Among them, R represents the reserve margin, R min and R max They represent the minimum and maximum values ​​of the reserve margin, respectively, i represents the planned time period, and p represents the maximum value of the planned duration; Constraints on the maximum number of new units; in, Indicates the capacity of the units that may be added in each time period. Indicates the maximum unit capacity that may be added in each time period; Total capacity constraints for each time period: (1+R min )×Demand peak (i)≤CCap total (i)≤(1+R max )×Demand peak (i) i=1,...,p Among them, R min and R max They represent the minimum and maximum values ​​of the reserve margin, i represents the planned time period, p represents the maximum planned duration, and Demand peak Indicates the system peak demand capacity during this period, CCap tolal Indicates the total capacity constraint for each time period; The total capacity calculation expression for each period is: Among them, CCap tolal represents the total capacity of each time period, k represents the energy category, q represents the maximum number of energy categories, i represents the planned time period, p represents the maximum planned duration, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

3. A method for power generation planning considering carbon emission reduction according to claim 1, characterized in that: Calculate the carbon dioxide emission tax and total government subsidies, where the carbon dioxide emission tax calculation expression is: Among them, Tax carbon represents the carbon dioxide emission tax, i represents the planning time period, p represents the maximum planning time, ET represents the carbon dioxide emission cost, CO2 gen represents the carbon dioxide emissions, CU represents the power generation of each engine unit, and cumNU represents the cumulative total of the number of units; The total government subsidy calculation expression is: Among them, Subside government represents the total government subsidy, i represents the planning period, p represents the maximum planning duration, S gov represents the government subsidy per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

4. A method for power generation planning considering carbon emission reduction according to claim 3, characterized in that: The government's electricity costs under different carbon emission reduction strategies are as follows: Strategy 1: Without considering carbon dioxide emission tax and government subsidies, the power generation cost function expression at this time is: Cost Strategy1 =Cost inv +Cost gen +Cost O&M Among them, Cost Strategy1 represents the power generation cost under strategy 1, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M represents the operation and maintenance cost; Strategy 2: Considering the carbon dioxide emission tax as a penalty factor for non-renewable energy power plants, the power generation cost function expression at this time is: Cost Strategy2 =Cost inv +Cost gen +Cost O&M +Tax carbon Among them, Cost Strategy2 represents the power generation cost under strategy 2, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon represents a carbon dioxide emission tax; Strategy 3: Considering the total government subsidy as an incentive for renewable energy power plants, the power generation cost function expression at this time is: Cost Strategy3 =Cost inv +Cost gen +Cost O&M -Subside government Among them, Cost Strategy3 represents the power generation cost under strategy three, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates operation and maintenance costs, Subside government represents total government subsidies; Strategy 4: Considering both the carbon dioxide emission tax and the total government subsidy, the power generation cost function expression at this time is: Cost Strategy4 =Cost inv +Cost gen +Cost O&M +Tax carbon -Subside government Among them, Cost Strategy4 represents the power generation cost under strategy 4, Cost inv Indicates investment cost, Cost gen Cost represents the power generation cost. O&M Indicates the operation and maintenance cost, Tax carbon Subside government represents total government subsidies.

5. A method for power generation planning considering carbon emission reduction according to claim 4, characterized in that: In the Nash-Cournot model, each power plant is regarded as a game party, and the goal of the power plant is to maximize revenue. The government is regarded as another game party. The government's purpose is to minimize the system cost of power generation planning issues and reduce carbon emissions by levying carbon taxes and providing subsidies. The expression of the Nash-Cournot model is: Π s =Rev s -Cost s s=1,...,4 Among them, s represents the power generation profit under a certain strategy, Rev s represents the income from selling electricity under the sth strategy, Cost s represents the power generation cost under the s-th strategy; Among them, the income from selling electricity in the case of the sth strategy is Rev s The calculation expression is: Among them, Rev s represents the income from selling electricity under the sth strategy, i represents the planning time period, p represents the maximum planning duration, EP represents the price of electricity per unit capacity, CU represents the power generation of each generator set, and cumNU represents the cumulative total number of units.

6. A method for power generation planning considering carbon emission reduction according to claim 1, characterized in that: The expression of particle velocity update when the PSO optimization algorithm searches for the Nash equilibrium point is: in, represents the velocity of particle i in j-dimensional space in the next iteration, represents the speed of particle i in the j-dimensional space in the current iteration, w represents the inertia weight, t represents the current iteration number, R1 and R2 represent random numbers between 0 and 1, c1 and c2 represent the individual learning factor and the group learning factor respectively, Indicates the position of particle i in the j-dimensional space in the current iteration, represents the personal best position of particle i in the j-dimensional space in the current iteration, Indicates the global optimal position of particle i in the j-dimensional space in the current iteration; The expression of particle position update when the PSO optimization algorithm searches for the Nash equilibrium point is: in, Indicates the position of particle i in j-dimensional space in the next iteration, Indicates the position of particle i in the j-dimensional space in the current iteration, Indicates the velocity of particle i in j-dimensional space in the current iteration.

7. A power generation planning system considering carbon emission reduction, characterized in that: include: Constructing a power generation cost model module, used to construct a power generation cost model; CO2 emission tax and total government subsidies calculation module, used to calculate CO2 emission tax and total government subsidies; The power generation cost analysis module is used to determine the power generation cost of the government under different carbon emission reduction strategies based on the constructed power generation cost model and the calculated carbon dioxide emission tax and total government subsidies; The Nash-Cournot model building module is used to model the behavior of governments and power plants using the Nash-Cournot model based on the government's power generation costs under different carbon emission reduction strategies; The solution module is used to find the Nash equilibrium point in the Nash-Cournot model using the PSO optimization algorithm to obtain the number NU of various units, the energy category k and the power generation CU of each engine group corresponding to the Nash equilibrium point.

8. A power generation planning device considering carbon emission reduction, characterized in that: The invention comprises a memory and a processor, wherein the memory is used to store a computer program, and the computer program is used to execute the method according to any one of claims 1 to 6 when loaded by the processor.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is suitable for executing the method according to any one of claims 1 to 6 when loaded by a processor.

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