A power plant optimal scheduling method based on carbon-electric multi-time joint decision

Abstract

The application discloses a power plant optimal scheduling method based on carbon-electric multi-time joint decision-making. The method comprises the following steps: establishing a carbon-electric multi-time joint decision-making system; inputting power transaction data and operation data of the power plant into a power transaction pre-out clearing model to output a pre-out clearing power supply cost parameter; inputting carbon transaction data and operation data of the power plant into a carbon transaction pre-out clearing model to output a carbon quota cost parameter of the power plant participating in the carbon transaction; inputting the pre-out clearing power supply cost parameter, the carbon quota cost parameter and the operation data of the power plant into a multi-time joint decision-making model to output an out clearing amount of the power plant and a carbon quota quantity; and arranging the out power of the power plant to realize the optimal scheduling of the power plant. The power generation and the carbon quota are considered as a whole, the carbon transaction and the power transaction decision-making of the power plant are cooperatively optimized, the optimal scheduling of the power plant can be effectively guided, the smooth completion of the carbon transaction is ensured, and the carbon emission amount is reduced.

Description

TECHNICAL FIELD

[0001] The application relates to a power plant optimal scheduling method, in particular to a power plant optimal scheduling method based on carbon-electricity multi-time joint decision. BACKGROUND

[0002] In recent years, power trading and carbon trading are accelerating. In view of the fact that the production of electric energy is often accompanied by the generation of carbon emissions, power plants are faced with the assessment of carbon emissions. Therefore, the power plants tend to consider the joint consideration of power generation and carbon emissions when scheduling.

[0003] Existing researches mostly assume that the carbon quota cost parameter is a fixed value, quantitatively evaluate the carbon emission cost parameter according to the emission characteristics of the unit, and consider the carbon emission cost in the revenue model of the power plant, so as to guide the optimal scheduling of the power plant. This method assumes that the carbon quota cost parameter is a fixed value, but in reality, the carbon quota cost parameter in carbon trading is volatile. The existing researches do not consider the existence of the initial carbon quota of the power plant in the decision-making, and often assume that the amount of electricity generated is inputted with the amount of carbon quota, but in reality, the power plant will obtain the initial carbon quota allocated at the beginning of the year, and the initial carbon quota makes the scheduling scheme easy to lose optimality.

[0004] Under the coordination of carbon trading and power trading, a power plant optimal scheduling method based on carbon-electricity multi-time joint decision is proposed. The power generation and carbon quota are considered together to guide the optimal scheduling of the power plant, which is beneficial to ensure the completion rate of carbon trading and reduce the social carbon emission. SUMMARY

[0005] In order to solve the problems in the background art, the application proposes a power plant optimal scheduling method based on carbon-electricity multi-time joint decision. The method of the application considers the power generation behavior and the carbon emission behavior together by establishing a carbon-electricity multi-time joint decision model of the power plant, so as to ensure the completion rate of carbon trading and reduce the social carbon emission.

[0006] The technical scheme adopted by the application is as follows:

[0007] The power plant optimal scheduling method of the application comprises the following steps:

[0008] Step 1: Establish a carbon-electricity multi-time joint decision system of the power plant considering carbon-electricity joint constraints, which comprises a power trading pre-out clearing model considering power trading constraints, a carbon trading pre-out clearing model considering carbon trading constraints, and a multi-time joint decision model considering multi-time joint decision constraints of the power plant participating in power trading and carbon trading.

[0009] Step 2: Obtain the power transaction data of the power plant participating in the power transaction and the operation data of the power plant, input the power transaction data and the operation data of the power plant into the power transaction pre-out clearing model considering the power transaction constraint, and the power transaction pre-out clearing model outputs the pre-out clearing power supply cost parameter of the power plant participating in the power transaction.

[0010] Step 3: Obtain the carbon transaction data of the power plant participating in the carbon transaction, input the carbon transaction data and the operation data of the power plant into the carbon transaction pre-out clearing model considering the carbon transaction constraint, and the carbon transaction pre-out clearing model outputs the carbon quota cost parameter of the power plant participating in the carbon transaction.

[0011] Step 4: Input the pre-out clearing power supply cost parameter obtained in step 2, the carbon quota cost parameter obtained in step 3, and the operation data of the power plant into the multi-time joint decision model considering the multi-time joint decision constraint, and the multi-time joint decision model outputs the clearing amount of the power plant and the carbon quota amount.

[0012] Step 5: Finally, the carbon-electric multi-time joint decision system considering the carbon-electric joint constraint outputs the pre-out clearing power supply cost parameter, the carbon quota cost parameter, the clearing amount of the power plant, and the carbon quota amount to arrange the output of the power plant, and realizes the optimal scheduling of the power plant.

[0013] The cost is related to the power supply of the power plant and the amount of carbon quota.

[0014] In step 1, the power plant is located in a power system, the power system includes a plurality of nodes, transmission lines, power plants and loads, each node is connected through each transmission line, each power plant and load is located at a respective node in the power system; the power plant includes a plurality of generator units. The power plant is specifically a coal-fired power plant or a gas-fired power plant.

[0015] In step 2, the power transaction pre-out clearing model considering the power transaction constraint is specifically as follows:

[0016]

[0017] Wherein, θ t represents the operation time of the lth power plant in the power system at t period; represents the offer of the kth segment of the power of the dth load in the power system in the power transaction at t period; represents the clearing amount of the bth segment of the power of the ith generator unit of the lth power plant in the power system at t period; lib represents the offer of the bth segment of the power of the ith generator unit of the lth power plant in the power system at t period; represents the clearing amount of the bth segment of the power of the ith generator unit of the lth power plant in the power system at t period; is positive, it means that the power plant transmits power to the power grid, and if it is negative, it means that the power plant transmits power from the power grid; the segment refers to the segmented linear method commonly used in power transaction to simplify the calculation complexity.

[0018] The power transaction constraint is specifically as follows:

[0019]

[0020]

[0021]

[0022]

[0023]

[0024]

[0025] wherein, B nm represents the susceptance of the transmission line between the nth and mth nodes in the power system; δ nt represents the phase angle of the nth node in the power system at time period t, δ mt represents the phase angle of the mth node in the power system at time period t; represents the maximum power value of the line flow from the nth node to the mth node on the transmission line between the nth node and the mth node in the power system; represents the maximum clearing amount of the bth segment of the power of the ith generator set of the lth power plant in the power system at time period t; represents the maximum bid amount of the kth segment of the power in the power transaction of the dth load in the power system at time period t; λ nt represents the pre-clearing power supply cost parameter of the nth node in the power system at time period t; π represents the circular constant; d ∈ Ψ n represents when the dth load in the power system is located on the nth node, i ∈ Ψ n represents when the ith generator set of the lth power plant in the power system is located on the nth node, w ∈ Ψ n represents when the wth generator set of the lth power plant in the power system is located on the nth node, m ∈ Θ n represents that the mth node in the power system is a downstream node of the nth node.

[0026] λ nt is the dual variable of the formula .

[0027] The operation data of the power plant input by the power transaction pre-out clearing model is the operation time θ of the lth power plant in the power system at the tth time period t The power transaction data of the power plant participating in the power transaction input by the power transaction pre-out clearing model includes the bid of the kth segment of the power of the dth load in the power system in the power transaction and the bid of the kth segment of the power of the dth load in the power system in the power transaction at the tth time period The pre-out clearing power supply cost parameter of the power plant participating in the power transaction output by the power transaction pre-out clearing model is the pre-out clearing power supply cost parameter λ of the nth node in the power system at the tth time period nt .

[0028] In the step 3, the carbon transaction pre-out clearing model considering the carbon transaction constraint is specifically as follows:

[0029]

[0030] Wherein, represents the input bid of the carbon quota of the lth power plant in the power system at the tth time period in the carbon transaction, represents the input bid of the carbon quota of the lth power plant in the power system at the tth time period in the carbon transaction, Γ c represents the input side of the carbon quota of the carbon transaction; represents the output bid of the carbon quota of the lth power plant in the power system at the tth time period in the carbon transaction, represents the output bid of the carbon quota of the lth power plant in the power system at the tth time period in the carbon transaction, Γ s represents the output side of the carbon quota of the carbon transaction; represents the output bid of the carbon quota of the other industry subject o in the carbon transaction at the tth time period, and the other industry subject o specifically includes high-carbon-emission industry subjects such as steel, petrochemical, chemical, building material and non-ferrous metal; represents the output bid of the carbon quota of the other industry subject o in the carbon transaction at the tth time period.

[0031] The carbon transaction constraint is specifically as follows:

[0032]

[0033]

[0034]

[0035]

[0036] Wherein, μ t represents the carbon quota cost parameter of the carbon transaction pre-out clearing at the tth time period; C ltC represents the carbon quota balance of the lth power plant in the power system at the beginning of the carbon trading in period t; C represents the maximum output bid of the carbon quota of the other industry subject o in the carbon trading.

[0037] μ t is the dual variable of the formula .

[0038] The operation data of the power plant input by the carbon trading pre-clearing model includes the operation time θ t of the lth power plant in the power system in period t; the carbon trading data of the power plant participating in the carbon trading input by the carbon trading pre-clearing model includes the input bid of the carbon quota of the lth power plant in the power system in period t in the carbon trading, the output bid of the carbon quota of the lth power plant in the power system in period t in the carbon trading, and the output bid of the carbon quota of the other industry subject o in the carbon trading in period t The carbon quota cost parameter of the power plant participating in the carbon trading output by the carbon trading pre-clearing model is the carbon quota cost parameter μ t of the carbon trading pre-clearing in period t.

[0039] The carbon quota balance C lt of the lth power plant in the power system at the beginning of the carbon trading in period t is specifically as follows:

[0040]

[0041] Wherein, C represents the initial allocated total carbon quota of the lth power plant in the power system; i∈Ω l B represents that the ith power unit belongs to the lth power plant in the power system; lit C represents the cumulative carbon emission of the ith power unit of the lth power plant in the power system in period t.

[0042] The operation data of the power plant input by the carbon trading pre-clearing model further includes the initial allocated total carbon quota of the lth power plant in the power system

[0043] The power plant obtains the initial carbon quota at the beginning of the year, and the power plant allocates the total carbon quota to different short time scales, and makes transaction decisions at different times in the carbon trading according to the power generation situation and the balance. Considering the relationship between the carbon quota bid and the power generation in the current period and the initial carbon quota decomposition, the power plant knows the power generation situation in the first t-1 periods of the year, i.e. the clearing amount, and can obtain the carbon quota use situation of itself in period t, i.e. the carbon quota balance at the beginning of the carbon trading.

[0044] In the step 4, the multi-time joint decision model of the power plant participating in the power transaction and the carbon transaction considering the multi-time joint decision constraint is as follows:

[0045]

[0046] Wherein, φ l represents the objective function of the multi-time joint decision model; n:i∈Ψ n represents the node where the nth power plant in the power system is located; a lib represents the cost coefficient of the bth segment of the power of the ith generator unit of the nth power plant in the power system in the tth period.

[0047] The multi-time joint decision constraint is as follows:

[0048]

[0049]

[0050]

[0051]

[0052]

[0053]

[0054] Wherein, α li(b-1) represents the bid of the b-1th segment of the power of the ith generator unit of the nth power plant in the power system in the tth period in the power transaction; ETq lt represents the carbon quota quantity of the nth power plant in the power system in the tth period in the carbon transaction; represents the carbon emission factor of the ith generator unit of the nth power plant in the power system; σ lt represents the carbon quota decomposition factor of the nth power plant in the power system in the tth period in the carbon transaction.

[0055] The operation data of the power plant input by the multi-time joint decision model includes the operation time θ t of the nth power plant in the power system in the tth period, and the initial allocated total carbon quota of the nth power plant in the power system The clearing quantity of the power plant output by the multi-time joint decision model is specifically the clearing quantity of the bth segment of the power of the ith generator unit of the nth power plant in the power system in the tth period The carbon quota quantity of the power plant output by the multi-time joint decision model is specifically the carbon quota quantity of the nth power plant in the power system in the tth period in the carbon transaction ETqlt .

[0056] In step 5, the carbon-electricity combined constraint is specifically as follows:

[0057]

[0058]

[0059]

[0060]

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[0085] wherein, and represent the dual variables of the formula ; represents the maximum bid of the kth segment of the power of the dth load in the power system in the power transaction; and represent the dual variables of the formula , and represent the dual variables of the formula , represents the maximum power value of the line flow from the mth node to the nth node on the transmission line between the mth node and the nth node in the power system; and represent the dual variables of the formula ; and represent the dual variables of the formula ; represents the dual variables of the formula ; represents the maximum input bid of the carbon quota of the lth power plant in the power system in the carbon transaction in the time period t; represents the maximum output bid of the carbon quota of the lth power plant in the power system in the carbon transaction in the time period t; represents the dual variables of the formula ; and represent the dual variables of the formula ; and represent the dual variables of the formula .

[0086] The carbon-electricity combined constraint is the KKT condition of the power transaction and carbon transaction pre-out clearing problem, that is, the problem to be solved is converted into a single-layer optimization problem, and a solver can be used to directly solve the carbon-electricity combined constraint to obtain the final output result.

[0087] The beneficial effects of the present application are:

[0088] This invention presents a novel method for optimizing the dispatch of power plants, enabling coordinated optimization of carbon trading and electricity trading decisions. It effectively guides power plant dispatch optimization. Furthermore, it can enhance the activity of carbon trading, ensure its smooth completion, and reduce overall carbon emissions. Attached Figure Description

[0089] Figure 1 This is a logic block diagram of the method of the present invention;

[0090] Figure 2 This is a schematic diagram of the clearing volume of each power plant in this invention. Detailed Implementation

[0091] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0092] like Figure 1 As shown, the power plant optimization scheduling method of the present invention includes the following steps:

[0093] Step 1: Establish a carbon-electricity multi-time joint decision-making system for power plants that considers carbon-electricity joint constraints. The carbon-electricity multi-time joint decision-making system includes an electricity trading pre-clearing model that considers electricity trading constraints, a carbon trading pre-clearing model that considers carbon trading constraints, and a multi-time joint decision-making model that considers multi-time joint decision-making constraints for power plants participating in electricity trading and carbon trading.

[0094] In step 1, the power plant is located within the power system, which includes several nodes, transmission lines, power plants, and loads. The nodes are connected by transmission lines, and each power plant and load is located at its respective node within the power system. The power plant includes several generator units. Specifically, the power plant may be a coal-fired power plant or a gas-fired power plant, etc.

[0095] Step 2: Obtain power trading data and power plant operation data of power plants participating in power trading. Input the power trading data and power plant operation data into the power trading pre-clearing model that considers power trading constraints. The power trading pre-clearing model outputs the pre-clearing power supply cost parameters of power plants participating in power trading.

[0096] In step 2, the pre-clearing model for electricity trading, considering electricity trading constraints, is as follows:

[0097]

[0098] Where, θ t This represents the operating time of the l-th power plant in the power system during time period t; This represents the bid price for the k-th segment of power for the d-th load in the power trading system. the kth segment of the bid of the power of the dth load in the power system in the time period t; α lib the bth segment of the bid of the power of the ith generator set of the lth power plant in the power system in the time period t; the bth segment of the clearing quantity of the power of the ith generator set of the lth power plant in the power system in the time period t; is positive if the power plant transmits power to the grid and is negative if the power plant transmits power from the grid; the segment refers to the segmented linear method usually adopted in power transaction to simplify the complexity of calculation.

[0099] The power transaction constraint is specifically as follows:

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106] wherein, B nm represents the susceptance of the transmission line between the nth and mth nodes in the power system; δ nt represents the phase angle of the nth node in the power system in the time period t, δ mt represents the phase angle of the mth node in the power system in the time period t; represents the maximum power value of the line flow from the nth node to the mth node on the transmission line between the nth and mth nodes in the power system; represents the maximum clearing quantity of the bth segment of the power of the ith generator set of the lth power plant in the power system in the time period t; represents the maximum bid of the kth segment of the power of the dth load in the power system in the time period t; λ nt represents the pre-clearing power supply cost parameter of the nth node in the power system in the time period t; π represents the circular constant; d ∈ Ψ n represents when the dth load in the power system is located on the nth node, i ∈ Ψ n represents when the ith generator set of the lth power plant in the power system is located on the nth node, w ∈ Ψ n represents when the wth generator set of the lth power plant in the power system is located on the nth node, m ∈ Θ nThe mth node in the power system is a downstream node of the nth node.

[0107] λ nt is a dual variable of the formula .

[0108] The operation data of the power plant input by the power transaction pre-out clearing model is an operation time θ t of the lth power plant in the power system at the tth period; the power transaction data of the power plant participating in the power transaction input by the power transaction pre-out clearing model includes a bid of a kth segment of power of the dth load in the power system in the power transaction and a bid of a kth segment of power of the dth load in the power system in the power transaction at the tth period The pre-out clearing power supply cost parameter of the power plant participating in the power transaction output by the power transaction pre-out clearing model is a pre-out clearing power supply cost parameter λ nt of the nth node in the power system at the tth period.

[0109] Step 3: Obtain carbon transaction data of the power plant participating in the carbon transaction, input the carbon transaction data and the operation data of the power plant into the carbon transaction pre-out clearing model considering the carbon transaction constraint, and output a carbon quota cost parameter of the power plant participating in the carbon transaction by the carbon transaction pre-out clearing model.

[0110] In step 3, the carbon transaction pre-out clearing model considering the carbon transaction constraint is as follows:

[0111]

[0112] wherein, represents an input bid of a carbon quota of the lth power plant in the power system in the carbon transaction at the tth period, represents an input bid of a carbon quota of the lth power plant in the power system in the carbon transaction at the tth period, Γ c represents an input side of the carbon quota of the carbon transaction; represents an output bid of a carbon quota of the lth power plant in the power system in the carbon transaction at the tth period, represents an output bid of a carbon quota of the lth power plant in the power system in the carbon transaction at the tth period, Γ s represents an output side of the carbon quota of the carbon transaction; represents an output bid of a carbon quota of other industry subjects o except the power industry in the carbon transaction at the tth period, and the other industry subjects o specifically include high-carbon-emission industry subjects such as iron and steel, petrochemical, chemical industry, building materials and non-ferrous metal industry; represents an output bid of a carbon quota of the other industry subjects o in the carbon transaction at the tth period.

[0113] The carbon transaction constraint is specifically as follows:

[0114]

[0115]

[0116]

[0117]

[0118] wherein μ t represents the carbon quota price parameter of the carbon trading pre-clearing in period t; C lt represents the carbon quota balance of the lth power plant in the power system in the initial stage of the carbon trading in period t; represents the maximum output bid of the carbon quota of the other industry subject o in the carbon trading.

[0119] μ t is the dual variable of the formula .

[0120] The operation data of the power plant input by the carbon trading pre-clearing model includes the operation time θ t of the lth power plant in the power system in period t; the carbon trading data of the power plant participating in the carbon trading input by the carbon trading pre-clearing model includes the input bid u l c t of the carbon quota of the lth power plant in the power system in period t in the carbon trading, the output bid u l s t of the carbon quota of the lth power plant in the power system in period t in the carbon trading, and the output bid uos t of the carbon quota of the other industry subject o in the carbon trading in period t; the carbon quota price parameter of the power plant participating in the carbon trading output by the carbon trading pre-clearing model is the carbon quota price parameter μ t of the carbon trading pre-clearing in period t.

[0121] The carbon quota balance C lt of the lth power plant in the power system in the initial stage of the carbon trading in period t is specifically as follows:

[0122]

[0123] wherein, represents the total carbon quota of the initial allocation of the lth power plant in the power system; i∈Ω l represents that the ith generator belongs to the lth power plant in the power system; B lit represents the cumulative carbon emission of the ith generator of the lth power plant in the power system in period t.

[0124] The operation data of the power plant inputted in the carbon transaction pre-clearing model further comprises an initial total carbon quota of the lth power plant in the power system

[0125] The initial carbon quota obtained by the power plant at the beginning of a year, the power plant allocates the total carbon quota to different short time scales, and according to the power generation and the balance, the power plant makes transaction decisions at different times in the carbon transaction. By comprehensively considering the relationship between the carbon quota and the power generation in the current period and the initial carbon quota decomposition, the power plant can obtain the carbon quota usage in period t, i.e., the carbon quota balance in the early stage of carbon transaction, according to the power generation in the first t-1 periods of the year, i.e., the clearing amount.

[0126] Step 4: inputting the pre-clearing power supply cost parameters obtained in step 2, the carbon quota cost parameters obtained in step 3 and the operation data of the power plant into the multi-time joint decision model considering multi-time joint decision constraints, and outputting the clearing amount and the carbon quota amount of the power plant by the multi-time joint decision model.

[0127] In step 4, the multi-time joint decision model of the power plant participating in the power transaction and the carbon transaction considering multi-time joint decision constraints is as follows:

[0128]

[0129] Wherein, φ l represents the objective function of the multi-time joint decision model; n:i∈Ψ n represents that when n is the node where the ith generator set of the lth power plant in the power system is located; a lib represents the cost coefficient of the bth segment of the power of the ith generator set of the lth power plant in the power system in period t.

[0130] The multi-time joint decision constraint is as follows:

[0131]

[0132]

[0133]

[0134]

[0135]

[0136]

[0137] Wherein, α li(b-1)ETq represents the offer of the b-1 segment of the power of the i th power generating unit of the l th power plant in the power system in the time period t in the power transaction; ETq lt ETq represents the amount of carbon quota of the l th power plant in the power system in the time period t in the carbon transaction; σ represents the carbon emission factor of the i th power generating unit of the l th power plant in the power system; lt ETq represents the carbon quota decomposition factor of the l th power plant in the power system in the time period t in the carbon transaction.

[0138] The operation data of the power plant input by the multi-time joint decision model includes the operation time θ of the l th power plant in the power system in the time period t t and the initial allocated total carbon quota of the l th power plant in the power system The cleared quantity of the power plant output by the multi-time joint decision model is specifically the cleared quantity of the b th segment of the power of the i th power generating unit of the l th power plant in the power system in the time period t The carbon quota amount of the power plant output by the multi-time joint decision model is specifically the carbon quota amount ETq of the l th power plant in the power system in the time period t in the carbon transaction lt .

[0139] Step 5: Finally, the carbon-electric multi-time joint decision system considering the carbon-electric joint constraint outputs the pre-clearing power supply cost parameter, the carbon quota cost parameter, the cleared quantity of the power plant and the carbon quota amount to arrange the output of the power plant, and realizes the optimal dispatch of the power plant.

[0140] The cost is specifically related to the amount of electricity and the amount of carbon quota of the pre-clearing power supply of the power plant.

[0141] In step 5, the carbon-electric joint constraint is specifically as follows:

[0142]

[0143]

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[0169]

[0170] wherein, and denote the dual variables of the equation denotes the maximum offer of the kth segment of power of the dth load in the power system in the power transaction; and denote the dual variables of the equation and denote the dual variables of the equation ​​​Pmax,mn represents a maximum power value of line flow from the mth node to the nth node on a transmission line between the mth node and the nth node in the power system; and Pmax,mn represents a maximum power value of line flow from the mth node to the nth node on a transmission line between the mth node and the nth node in the power system; represents a dual variable of the formula and represents a dual variable of the formula represents a dual variable of the formula represents a dual variable of the formula represents a dual variable of the formula Pmax,l represents a maximum input competitive amount of a carbon quota of the lth power plant in the power system in the carbon transaction in the time period t; Pmax,l represents a maximum output competitive amount of a carbon quota of the lth power plant in the power system in the carbon transaction in the time period t; represents a dual variable of the formula represents a dual variable of the formula represents a dual variable of the formula represents a dual variable of the formula and represents a dual variable of the formula represents a dual variable of the formula

[0171] The carbon-electricity combined constraint is a KKT condition of the power transaction and the carbon transaction pre-out clearing problem, that is, the problem to be solved is converted into a single-layer optimization problem, and a solver can be used to directly solve the carbon-electricity combined constraint to obtain a final output result.

[0172] The embodiments of the present application are as follows:

[0173] Taking an IEEE30 node power system as an example, the power system includes 30 power nodes and 41 transmission lines. Six power plants are connected with power nodes 1, 2, 5, 8, 11 and 13, and the power plants on the power nodes 5, 8, 11 and 13 are coal-fired power plants (C1, C2, C3 and C4), and the remaining power plants are gas-fired power plants (G1 and G2). In the carbon transaction, in addition to the six power plants, three other industry subjects are also included, and the data of the power plant parameters, the initial quota of each subject in the carbon transaction, the carbon emission factor and the like are shown in Table 1.

[0174] Table 1: IEEE30 power system data

[0175]

[0176]

[0177] As Figure 2As shown, the annual power generation of each power plant, i.e. the clearing amount, is displayed. The coal-fired power plant will run out of the initial allocated carbon quota faster due to its higher carbon emission factor, at this time, more power generation will have to pay the carbon quota cost parameter, so the clearing amount will decrease under carbon trading. This shows that the introduction of carbon trading will reduce the survival space of coal-fired units, and will select power plants with smaller carbon emissions, thereby driving the reduction of carbon emissions of power energy.

[0178] The following Table 2 shows the carbon quota decomposition factor of each power plant under typical 10 scenarios. The method proposed by the present application can adjust the carbon quota decomposition factor according to the pre-clearing situation of carbon trading. Power plants input carbon quota when the carbon quota cost parameter is low, and try not to use their own initial quota, when the carbon quota cost parameter is high, power plants prefer to use the initial quota allocated, thereby reducing their own reporting amount in carbon trading.

[0179] Table 2 Carbon quota decomposition factor under typical 10 scenarios

[0180] Power plant T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 C1 0 0.069 0.137 0.137 0.164 0.164 0.11 0.11 0.055 0.055 C2 0 0 0.139 0.215 0.147 0.147 0.098 0.098 0.078 0.078 C3 0 0 0 0.09 0.152 0.152 0.202 0.202 0.101 0.101 C4 0 0 0 0 0.341 0.341 0 0.09 0.114 0.114 G1 0 0 0 0 0.292 0.292 0.027 0.195 0.097 0.097 G2 0 0 0.061 0 0.235 0.235 0.156 0.156 0.078 0.078

[0181] The following Table 3 is the social carbon emission amount. When considering carbon-electric multi-time joint decision, power plants can optimize their decomposition factors, so they have more optimization space, and the carbon emission amount is reduced.

[0182] Table 3 Social carbon emission amount

[0183] Carbon emissions (million tons CO2) 87.93

Claims

1. A method for optimal scheduling of power plants based on carbon-electric multi-time joint decision, characterized in that: The method comprises the following steps: Step 1: establishing a carbon-electric multi-time joint decision system of a power plant considering carbon-electric joint constraints, the carbon-electric multi-time joint decision system comprising a power transaction pre-out clearing model considering power transaction constraints, a carbon transaction pre-out clearing model considering carbon transaction constraints, and a multi-time joint decision model of the power plant participating in power transaction and carbon transaction considering multi-time joint decision constraints; Step 2: obtaining power transaction data of the power plant participating in power transaction and operation data of the power plant, inputting the power transaction data and the operation data of the power plant into the power transaction pre-out clearing model considering power transaction constraints, and outputting pre-out clearing power supply cost parameters of the power plant participating in power transaction by the power transaction pre-out clearing model; Step 3: obtaining carbon transaction data of the power plant participating in carbon transaction, inputting the carbon transaction data and the operation data of the power plant into the carbon transaction pre-out clearing model considering carbon transaction constraints, and outputting carbon quota cost parameters of the power plant participating in carbon transaction by the carbon transaction pre-out clearing model; Step 4: inputting the pre-out clearing power supply cost parameters obtained in Step 2, the carbon quota cost parameters obtained in Step 3, and the operation data of the power plant into the multi-time joint decision model considering multi-time joint decision constraints, and outputting clearing quantity and carbon quota quantity of the power plant by the multi-time joint decision model; Step 5: finally outputting the pre-out clearing power supply cost parameters, the carbon quota cost parameters, the clearing quantity and the carbon quota quantity of the power plant by the carbon-electric multi-time joint decision system considering carbon-electric joint constraints to arrange power output of the power plant, and realizing optimized scheduling of the power plant. In Step 2, the power transaction pre-out clearing model considering power transaction constraints is as follows: where θ t denotes the operating time of the lth power plant in the power system at time period t; denotes the bid of the kth segment of power of the dth load in the power system in the power transaction at time period t; denotes the bid of the kth segment of power of the dth load in the power system in the power transaction at time period t; a lib denotes the bid of the bth segment of power of the ith generator set of the lth power plant in the power system at time period t; denotes the solution of the bth segment of power of the ith generator set of the lth power plant in the power system at time period t; In Step 3, the carbon transaction pre-out clearing model considering carbon transaction constraints is as follows: wherein, denotes the input bid of the carbon quota of the lth power plant in the power system in the carbon trading at time period t, denotes the input bid of the carbon quota of the lth power plant in the power system in the carbon trading at time period t, Γ c denotes the input side of the carbon quota of the carbon trading; denotes the output bid of the carbon quota of the lth power plant in the power system in the carbon trading at time period t, denotes the output bid of the carbon quota of the lth power plant in the power system in the carbon trading at time period t, Γ s denotes the output side of the carbon quota of the carbon trading; denotes the output bid of the carbon quota of the other industry subject o in the carbon trading at time period t, denotes the output bid of the carbon quota of the other industry subject o in the carbon trading at time period t, In Step 4, the multi-time joint decision model of the power plant participating in power transaction and carbon transaction considering multi-time joint decision constraints is as follows: wherein φ l represents a target function of a multi-time joint decision model; n: i∈Ψ n represents a node where the nth generator group of the lth power plant in the power system is located; a lib represents a cost coefficient of the bth segment of the power of the ith generator group of the lth power plant in the power system at the tth time period.

2. The method of claim 1, wherein the method is characterized by: In Step 1, the power plant is located in a power system, the power system comprising a plurality of nodes, power transmission lines, power plants and loads, the nodes being connected by the power transmission lines, each power plant and load being located at a respective node in the power system; and the power plant comprising a plurality of generator units.

3. The method of claim 2, wherein the method is characterized by: The power transaction constraints are as follows: wherein, B nm represents the susceptance of the transmission line between the nth and the mth nodes in the power system; δ nt represents the phase angle of the nth node in the power system at time period t, δ mt represents the phase angle of the mth node in the power system at time period t; represents the maximum power value of the line flow from the nth node to the mth node on the transmission line between the nth and the mth nodes in the power system; represents the maximum clearing amount of the bth segment of the power of the ith generator unit of the lth power plant in the power system at time period t; represents the maximum bidding amount of the kth segment of the power of the dth load in the power system at time period t; λ nt represents the pre-clearing supply cost parameter of the nth node in the power system at time period t; π represents the circular constant; d e n represents when the dth load in the power system is located on the nth node, i e n represents when the ith generator unit of the lth power plant in the power system is located on the nth node, w e n represents when the wth generator unit of the lth power plant in the power system is located on the nth node, m e n represents that the mth node in the power system is a downstream node of the nth node; The operation data of the power plant input by the power transaction pre-out clearing model is an operation time θ of the lth power plant in the power system at the tth time period t The power transaction data of the power plant participating in the power transaction input by the power transaction pre-out clearing model includes a bid of a kth segment of power of the dth load in the power system in the power transaction and a bid of a kth segment of power of the dth load in the power system in the power transaction at the tth time period The pre-out clearing power supply cost parameter of the power plant participating in the power transaction output by the power transaction pre-out clearing model is a pre-out clearing power supply cost parameter λ of an n th node in the power system at the tth time period nt .

4. The method of claim 2, wherein the method is characterized by: The carbon transaction constraints are as follows: wherein μ t represents the carbon quota cost parameter of the carbon trading pre-out in the time period t; C lt represents the carbon quota surplus of the lth power plant in the power system at the initial stage of the carbon trading in the time period t; represents the maximum output competitive quantity of the carbon quota of the other industry subject o in the carbon trading. The operation data of the power plant input by the carbon transaction pre-clearing model includes an operation time θ of the lth power plant in the power system at a t period t The carbon transaction data of the power plant participating in the carbon transaction input by the carbon transaction pre-clearing model includes an input bid of a carbon quota of the lth power plant in the power system at a t period in the carbon transaction An output bid of a carbon quota of the lth power plant in the power system at a t period in the carbon transaction And an output bid of a carbon quota of a subject o other than the power industry in the carbon transaction at a t period The carbon quota cost parameter of the power plant participating in the carbon transaction output by the carbon transaction pre-clearing model is a carbon quota cost parameter μ of the carbon transaction pre-clearing at a t period t .

5. The method of claim 4, wherein the method is characterized by: The period t power system in the first power plant in the carbon trading initial carbon quota balance C lt , as follows: wherein, represents the initial allocated total carbon quota of the lth power plant in the power system; i e Ω l represents the lth power plant in the power system to which the ith generator belongs; B lit represents the cumulative carbon emission of the ith generator of the lth power plant in the power system at time period t; The operation data of the power plant input by the carbon trading pre-clearing model further includes the initial allocated total carbon quota of the lth power plant in the power system 6. The method of claim 2, wherein the method is characterized by: The multi-time joint decision constraints are as follows: wherein, a li(b-1) represents the offer of the b-1th segment of power of the ith generator unit of the lth power plant in the power system in the time period t in the power transaction; ETq lt represents the amount of carbon quota of the lth power plant in the power system in the time period t in the carbon transaction; represents the carbon emission factor of the ith generator unit of the lth power plant in the power system; σ lt represents the carbon quota decomposition factor of the lth power plant in the power system in the time period t in the carbon transaction; The operation data of the power plant input by the multi-time joint decision model includes an operation time θ of the lth power plant in the power system at a tth time period t and an initial allocated total carbon quota of the lth power plant in the power system The clearing quantity of the power plant output by the multi-time joint decision model is specifically a clearing quantity of a bth segment of a power of an ith generator set of the lth power plant in the power system at a tth time period The carbon quota quantity of the power plant output by the multi-time joint decision model is specifically a carbon quota quantity ETq of the lth power plant in the power system at a tth time period in carbon trading lt .

7. The method of claim 2, wherein the method is characterized by: In Step 5, the carbon-electric joint constraints are as follows: wherein, and denote the dual variables of the formula ; denotes the maximum offer of the kth segment of power of the dth load in the power system in the power transaction; and denote the dual variables of the formula , and denote the dual variables of the formula , denotes the maximum power value of the line flow from the mth node to the nth node on the transmission line between the mth node and the nth node in the power system; and denote the dual variables of the formula ; and denote the dual variables of the formula ; denote the dual variables of the formula ; denotes the maximum input bid of the carbon quota of the lth power plant in the power system in the carbon transaction at time period t; the maximum output bid of the carbon quota of the lth power plant in the power system in the carbon transaction at time period t; denote the dual variables of the formula ; and denote the dual variables of ; and denote the dual variables of .

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