CN114243691A - Low-carbon optimized scheduling method for power system - Google Patents

Low-carbon optimized scheduling method for power system Download PDF

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CN114243691A
CN114243691A CN202111536654.2A CN202111536654A CN114243691A CN 114243691 A CN114243691 A CN 114243691A CN 202111536654 A CN202111536654 A CN 202111536654A CN 114243691 A CN114243691 A CN 114243691A
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carbon
power
power generation
generation end
low
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程维杰
程韧俐
马伟哲
李祝昆
周招鹤
杨帆
何晓峰
郑晓辉
宋俊文
刘振兴
刘金生
陈择栖
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Shenzhen Power Supply Co ltd
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Abstract

The invention provides a low-carbon optimal scheduling method for an electric power system. The method comprises the following steps: acquiring basic data and load data of a power generation end in a power system; inputting the obtained basic data and load data into a pre-established low-carbon economic dispatching model for solving to obtain a low-carbon economic dispatching scheme, wherein the low-carbon economic dispatching model comprises a target function and corresponding constraint conditions, the minimum sum of the comprehensive operation cost of the power generation end is used as the minimum sum, the comprehensive operation cost of the power generation end comprises the power generation energy consumption cost of the power generation end and the carbon transaction cost of the power generation end, and the carbon transaction cost of the power generation end is obtained by constructing a carbon transaction cost model based on the carbon emission amount and the carbon emission quota of the power generation end and calculating; and performing optimized dispatching on the power system according to the low-carbon economic dispatching scheme. The invention can reduce the carbon emission while reducing the system operation cost, and has important promotion effect on the development of low-carbon economy.

Description

Low-carbon optimized scheduling method for power system
Technical Field
The invention relates to the technical field of operation regulation and control of an electric power system, in particular to a low-carbon optimal scheduling method for the electric power system.
Background
With the massive utilization of fossil fuels, the global warming problem is increasingly intensified, and the promotion of low-carbon economy is a consensus all over the world. At present, the electric power industry is the main energy consumption industry of China and the largest carbon emission department, and the electric power industry also shows huge emission reduction potential while facing severe emission reduction challenges. In order to achieve the strategic goal of reducing the intensity of carbon emissions, a series of measures need to be taken to advance the low carbon development of electric power systems.
The method for low-carbon of the power system mainly comprises two aspects of policy and technology. A carbon transaction mechanism, a green certificate transaction mechanism and the like can be established in the policy aspect, new energy technologies such as wind power and photovoltaic can be developed in the technical aspect, and the emission reduction target of the power system is realized through the cooperation of the carbon transaction mechanism and the green certificate transaction mechanism.
Currently, the introduction of a carbon trading mechanism into an electric power system is an important research method for realizing low-carbon operation, and the carbon trading is a market mechanism which can trade carbon emission by establishing a legal carbon emission right and utilizing a market. Under the carbon trading mechanism, a supervision department aims at controlling the total carbon emission amount, distributes carbon emission amount for each economic subject according to a certain rule, allows each economic subject to trade the carbon emission amount, and makes and adjusts a production plan according to the distribution amount. If the carbon emission is less than the distribution limit in a specified period, the surplus limit can be sold and benefited; if the carbon emissions are greater than the allocated credit, an excess credit must be purchased. The carbon trading mechanism utilizes market means to control the carbon emission, and can greatly stimulate the enthusiasm of enterprises for emission reduction.
The carbon emission responsibility allocation method is also a research point, and considering the unbalanced energy distribution in China, a large amount of large-scale trans-regional power scheduling exists in the power industry to meet the power supply, and the allocation of the carbon emission responsibility in the power industry should reflect the actual situation of regional large-scale power scheduling, so that the carbon emission allocation scheme adopting the common bearing principle is beneficial to promoting the emission reduction cooperation and economic coordination development among the regions, and the carbon trading market and the power market are linked to achieve the aim of reducing the carbon emission.
Disclosure of Invention
The technical problem to be solved by the embodiments of the present invention is to provide a low-carbon optimal scheduling method for an electric power system, which can reduce the carbon emission while reducing the system operation cost.
In order to solve the above technical problem, an embodiment of the present invention provides a low-carbon optimal scheduling method for an electric power system, including:
step S1, acquiring basic data and load data of a power generation end in the power system;
step S2, inputting the obtained basic data and load data into a pre-established low-carbon economic dispatching model for solving, and obtaining a low-carbon economic dispatching scheme, wherein the low-carbon economic dispatching model comprises a target function and corresponding constraint conditions, the minimum sum of the comprehensive operation cost of the power generation end is used as the minimum sum, the comprehensive operation cost of the power generation end comprises the power generation energy consumption cost of the power generation end and the carbon transaction cost of the power generation end, and the carbon transaction cost of the power generation end is obtained by calculating and constructing a carbon transaction cost model based on the carbon emission amount and the carbon emission quota of the power generation end;
and step S3, performing optimized dispatching on the power system according to the low-carbon economic dispatching scheme.
Further, in step S2, in the carbon transaction cost model, the carbon transaction cost at the power generation end at time t is represented as:
Figure BDA0003413272570000021
ΔMt＝D-EM
in the formula, FTThe carbon transaction cost of the power generation end at the time t, D is the carbon emission of the power generation end in the time t, and EMCarbon emission quota for generator end at t period, KCDMFor unit transaction price, KpPenalty paid for excess fraction of unit carbon emissions; Δ MCDM,tCarbon credits obtained by transactions at time t; Δ MCDM,t' is the carbon credit sold on the market by trading at time t; Δ MP,tCarbon credits obtained by paying a penalty for time t.
Further, a power generation end of the power system is provided with a thermal power generating unit, a photovoltaic power station and a wind power plant, and the carbon emission quota of the power generation end in the time period t is calculated by the following formula:
Figure BDA0003413272570000022
in the formula: eMCarbon emission preparation for power generation end in t periodEta is the unit electric quantity emission distribution, alpha and beta are the correction coefficients of the photovoltaic power generation carbon quota and the wind power generation carbon quota at the moment t respectively, and PG,i,tThe scheduling output, K, of the ith thermal power generating unit at the moment tPV,j,tFor the jth photovoltaic power station stand-by coefficient at time t, PPV,j,tScheduling output, K, for the jth photovoltaic power station at time tW,k,tIs the kth wind farm standby coefficient at the moment t, PW,k,tFor the scheduling contribution, N, of the kth wind farm at time tGNumber of sets of live-wire in electric power system, NPVNumber of photovoltaic power stations in the power system, NWThe number of wind fields in the power system.
Further, the carbon emission amount of the power generation end for the t period is obtained by:
calculating node carbon potentials of all nodes in the power system by adopting a recursion algorithm of the carbon emission flow of the power system, and determining a node carbon potential distribution vector;
according to the node carbon potential distribution vector, combining a common apportionment principle, calculating to obtain the carbon emission flow rate of the power generation end;
the obtained carbon emission flow rate of the power generation end is multiplied by the duration of the t period to obtain the carbon emission amount of the power generation end for the t period.
Further, the carbon emission amount of the power generation end for the t period is calculated by the following formula:
D＝Dr+Dg
Dr＝ADi×EFi
Dg＝ADe×EFe
in the formula, DrCarbon emissions for fossil fuel combustion, DgTo purchase carbon emissions using electricity generation, ADiActivity number, EF, of the ith fossil fueliCarbon dioxide emission factor, AD, for the ith fossil fueleTo purchase the amount of electricity used, EFeIs a power grid emission factor.
Further, the power generation energy consumption cost of the power generation end comprises the operation cost of a power generation end unit, the start-up and shutdown cost of the unit and the light abandoning cost; the objective function in the low-carbon economic dispatching model is as follows:
F＝min(FY+FK+FQ+FT)
in the formula: f represents that the sum of the comprehensive operation cost of the power generation end is minimum, and FYExpressed as the generator-side unit operating cost, FKIndicating the cost of starting and stopping the unit, FQRepresenting cost of waste light, FTRepresents a carbon transaction cost;
the constraints include power constraints and low carbon constraints.
Further, in the objective function:
the generator-side unit running cost FYExpressed as:
Figure BDA0003413272570000041
in the formula: pG,i,tActive power generated by the ith thermal power generating unit at the moment t, ai、bi、ciIs an economic parameter of the operation cost of the ith thermal power generating unit i, PPV,j,tActive power, η, generated at time t for the jth photovoltaic plantPV,jFor the unit electricity operating cost, P, of the jth photovoltaic power plantW,k,tActive power, eta, generated for the kth wind farm at time tW,kFor the operating cost per unit of electricity of the kth wind farm, NGNumber of sets of live-wire in electric power system, NPVNumber of photovoltaic power stations in the power system, NW24 represents that the operation cycle of the low-carbon economic dispatching model is 24 time periods for the number of wind power fields in the power system;
the unit start-up and shut-down costs FKExpressed as:
Figure BDA0003413272570000042
in the formula: vi,tFor the start-stop state of ith thermal power generating unit at t period, wherein: u shapei,t＝1，Ui,t-1When the value is 0, then V i,t1, or else Vi,t＝0，Ui,tIs as followsThe starting and stopping states of the i thermal power generating units in the t period are 0 for stopping and 1 for starting; sT,i,tFor the startup cost of the home page i, SD,i,tFor downtime costs;
the light abandoning cost FQExpressed as:
FQ＝CPVEPV,t
in the formula: cPVPenalty charge for unit abandon of light, EPV,tAnd (4) setting the expected light abandon amount at the time t.
Further, the electric power constraint conditions include system power balance constraint, thermal power unit capacity upper and lower limit constraint, thermal power unit climbing constraint, photovoltaic capacity upper and lower limit constraint, wind power capacity upper and lower limit constraint and rotation reserve amount constraint, wherein:
the system power balance constraint is expressed as:
Figure BDA0003413272570000043
in the formula: pL,tIs the system load at time t, PG,i,tIs the output of the ith thermal power generating unit at the moment t, PPV,j,tIs the output of the jth photovoltaic power station at the moment t, PW,k,tIs the output of the kth wind farm at time t, NGNumber of sets of live-wire in electric power system, NPVNumber of photovoltaic power stations in the power system, NWThe number of wind fields in the power system;
the upper and lower capacity limit constraints of the thermal power generating unit are represented as follows:
Pmin,G≤PG,t≤Pmax,G
in the formula: pmin,G、Pmax,GUpper and lower limits of output, P, for each thermal power unitG,tThe output of each thermal power generating unit is at the moment t;
the ramp constraint of the thermal power generating unit is represented as:
Figure BDA0003413272570000051
in the formula: pRUR,iLimiting the starting up and climbing of the ith thermal power generating unit; pRDR,iLimiting shutdown and climbing of the ith thermal power generating unit;
the photovoltaic capacity upper and lower bound constraints are expressed as:
Pmin,PV≤PPV,t≤Pmax,PV
in the formula: pmin,PV、Pmax,PVFor the upper and lower limits of the output of the photovoltaic power station, PPV,tThe output of the photovoltaic power station at the moment t is obtained;
the wind power capacity upper and lower limit constraints are expressed as:
Pmin,W≤PW,t≤Pmax,W
in the formula: pmin,W、Pmax,WFor the upper and lower limits of the wind power plant output, PW,tThe output of the wind power plant at the moment t is obtained;
the rotational reserve constraint is expressed as:
Figure BDA0003413272570000052
in the formula: pG,i,tmaxThe maximum output at the moment t of the ith thermal power generating unit PG,i,tminThe minimum output at the moment t of the ith thermal power generating unit ul、dlUpper and lower rotation reserve rates, u, respectively, increased due to load prediction errorp、dpUpper and lower rotational reserve rates, u, respectively, increased by photovoltaic contribution prediction errorw、dwRespectively the upper and lower rotational reserve rates increased by the wind power output prediction error.
Further, the low carbon constraints include carbon trade credit constraints and carbon emission reduction target constraints, wherein:
the carbon trading credit constraint is expressed as:
ΔMCDM,t≤MCDM,t,max
in the formula: Δ MCDM,tCarbon credits, M, obtained by trading at time tCDM,t,maxThe maximum displacement reduction capacity which can be reached by the power generation end;
the carbon reduction target constraint is expressed as:
MC,t≤MD,t+ΔMCDM,t
in the formula: mC,tAnd MD,tRespectively representing the total carbon emission amount and the distribution emission amount of the power generation end at the time t; Δ MCDM,tIs the carbon credit obtained by the transaction at time t.
Further, in step S2, solving the low-carbon economic dispatch model specifically includes: and solving the low-carbon economic dispatching model by utilizing a digital optimization technology CPLEX to obtain the low-carbon economic dispatching scheme.
The embodiment of the invention has the following beneficial effects: according to the low-carbon optimal scheduling method for the power system, disclosed by the embodiment of the invention, the carbon distribution and the transaction cost are considered, the low-carbon economic scheduling model with the aim of minimizing the sum of the comprehensive operation costs of the power generation end is constructed, so that the low-carbon economic scheduling scheme is obtained, the power system is optimally scheduled according to the low-carbon economic scheduling scheme, the operation cost of the system can be reduced, the carbon emission can be reduced, and the method has an important promotion effect on the development of low-carbon economy.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a low-carbon optimal scheduling method for an electric power system according to an embodiment of the present invention.
FIG. 2 is a flow chart of a recursion algorithm for a power system carbon emission stream of an embodiment of the present invention.
Detailed Description
The following description of the embodiments refers to the accompanying drawings, which are included to illustrate specific embodiments in which the invention may be practiced.
The embodiment of the invention provides a low-carbon optimal scheduling method of an electric power system, which considers carbon distribution and transaction cost, and establishes a low-carbon economic scheduling model aiming at minimizing the sum of comprehensive operation cost of a power generation end, so as to obtain a scheduling scheme of the electric power system, reduce the operation cost of the system and reduce the carbon emission.
As shown in fig. 1, the low-carbon optimal scheduling method for the power system according to the embodiment of the present invention may include the following steps:
step S1, acquiring basic data and load data of a power generation end in the power system;
step S2, inputting the acquired basic data and load data of the power generation end into a pre-established low-carbon economic dispatching model for solving, and acquiring a low-carbon economic dispatching scheme, wherein the low-carbon economic dispatching model comprises a target function and corresponding constraint conditions which take the minimum sum of the comprehensive operation cost of the power generation end as a minimum, the comprehensive operation cost of the power generation end comprises the power generation energy consumption cost of the power generation end and the carbon transaction cost of the power generation end, and the carbon transaction cost of the power generation end is acquired by calculating and constructing a carbon transaction cost model based on the carbon emission amount and the carbon emission quota of the power generation end;
and step S3, performing optimized dispatching on the power system according to the low-carbon economic dispatching scheme.
Further, the basic data of the power generation end in step S1 may include energy data, correction data, spare coefficients, emission quotas, cost data, constraints, and the like of the power generation end and each power generation unit thereof.
In step S2, the integrated operation cost of the power generation end includes a power generation energy consumption cost of the power generation end and a carbon trading cost of the power generation end, and the carbon trading cost of the power generation end is calculated by constructing a carbon trading cost model based on the carbon emission amount and the carbon emission quota of the power generation end. The carbon transaction cost can be calculated by multiplying the difference between the carbon emission amount of the power generation end and the carbon emission quota by the carbon transaction unit price, so that the embodiment of the invention constructs a carbon transaction cost model based on the carbon transaction mechanism, and the carbon transaction cost of the power generation end at the time t in the model is represented as:
Figure BDA0003413272570000071
in the formula, FTThe carbon transaction cost of the power generation end at the time t, D is the carbon emission of the power generation end in the time t, and EMCarbon emission quota for the generation side, KCDMFor unit transaction price, KpPenalty paid for excess fraction of unit carbon emissions; Δ MCDM,tCarbon credits obtained by transactions at time t; Δ MCDM,t' is the carbon credit sold on the market by trading at time t; Δ MP,tCarbon credits obtained by paying a penalty for time t.
To determine the carbon emission of the power generation end during the period t, in one embodiment, the invention calculates the carbon emission of the power generation end by using a carbon flow tracking theory. Further, the calculating the carbon emission amount of the power generation end by using the carbon flow tracking theory may specifically include:
step S21, calculating node carbon potentials of all nodes in the power system by adopting a recursion algorithm of the carbon emission flow of the power system, and determining a node carbon potential distribution vector;
step S22, calculating and obtaining the carbon emission flow rate of the power generation end according to the node carbon potential distribution vector and by combining a common allocation principle;
step S23, the obtained carbon emission flow rate of the power generation end is multiplied by the duration of the t period, obtaining the carbon emission amount of the power generation end within the t period.
The above steps S21-S23 are further explained. In step S21, as shown in fig. 2, nodes with unknown carbon potentials are sequentially polled by using a recursion algorithm of the carbon emission flow of the power system and using the adjacency characteristics in the node carbon potential calculation, and the node carbon potentials of all the nodes in the whole system are calculated through several recursion processes. The method comprises the following specific steps:
step S21-1, setting recursion times k, and enabling the initial value of k to be 1; setting a set pikThe initial value of (A) is a set formed by all nodes except the suspended node in the power grid, NkHas an initial value of N1N-M, whereinkRepresents a set of nodes with unknown carbon potential before the k recursion begins, NkRepresenting the number of nodes with unknown carbon potential, wherein N is the total number of nodes in the power grid, and M is the number of suspended nodes;
step S21-2, according to the set IIkSequentially polling each node according to the number of the middle node, and setting the initial value of the node sequence j to be 1;
step S21-3, polling the II setkFinding the injection node set of the jth node
Figure BDA0003413272570000081
If set
Figure BDA0003413272570000082
If the carbon potential of all the nodes is known, calculating the carbon potential of the node j, and then entering the step S21-4; if set
Figure BDA0003413272570000083
If the carbon potential of the node is unknown, skipping the node, and entering the next step S21-4;
step S21-4, judging whether all nodes have been polled, i.e. whether j is less than NkIf j is less than NkIf j is j +1, repeating the step S21-3, and continuing to poll the next node; otherwise, go to step S21-5;
step S21-5, let k equal to k +1, update the set ΠkAnd size N thereofkIf N is presentkIf 0, the carbon potentials of all the nodes are obtained, and the process proceeds to step S21-6; otherwise, the step S21-2 is entered for next recursion;
and step S21-6, according to the obtained carbon potentials of all nodes, other variables such as branch carbon flow rate and load carbon flow rate in the power grid can be solved.
After the node carbon potentials of all the nodes are obtained through calculation, the node carbon potential distribution vector E is determinedN. And quantitatively allocating the system emission based on the node carbon potential distribution vector according to a common allocation principle, namely, the load carbon emission is borne by each load, and the carbon emission caused by branch loss is quantitatively allocated by the contribution of each unit to the system network loss.
First, the carbon flow rate vector R is loadedLIs RL＝PL×ENIn which P isLIs divided into loadAnd (6) arranging a matrix.
Secondly, for carbon emission caused by branch power loss, the carbon emission flow rate distribution is represented by an N-order square matrix R1Indicating that in the matrix, if the node i and the node j are connected by a line, and the active loss value on the line is PijAnd R is the carbon flow rate of the corresponding power generation endlijR; otherwise RlijFor all diagonal elements R ═ 0lji0. From this, R is1＝diag(EN)PlWherein P islIs a branch active loss matrix, PlThe matrix is specifically defined as: if the node i and the node j are connected by a line, an active power flow flowing into the node j from the node i exists, and the network loss value on the line ij is P, then PlijP; otherwise, Plij＝0。
Because the power Pa of the service power and the carbon emission intensity E of the unitGAs is known, the plant power carbon flow rate can therefore be expressed as:
Ra＝diag(EG)Pa。
the carbon emission corresponding to the network loss born by the unit is as follows:
RG,k-1＝eG,kPG,k-1 (2)
in the formula: rG,k-1Carbon emission flow rate required to be assumed for the unit k, eG,kCarbon emission intensity, P, for unit kG,k-1The active network loss borne by the unit k. Active network loss P borne by the unit kG,k-1Comprises the following steps:
Figure BDA0003413272570000091
in the formula:
Figure BDA0003413272570000092
is an N-dimensional unit column vector with the jth element being 1 and the rest components being 0NFor a column vector with all elements 1, AdIs an upstream distribution matrix of the system.
The combined vertical type (2) and the formula (3) are used for obtaining the carbon emission flow rate R caused by active loss borne by the unit kG,k-1Comprises the following steps:
Figure BDA0003413272570000101
after the carbon flow rate of the plant power and the carbon emission flow rate caused by active loss born by the unit are calculated, the carbon emission flow rate is multiplied by the time length of the t time period, so that the carbon emission of the power generation end of the power system in the t time period can be obtained, and a basis is provided for calculating the carbon transaction cost.
The above only exemplifies an embodiment of calculating the carbon emission amount of the power generation end, and the method of calculating the carbon emission amount of the power generation end is not limited thereto. For example, the carbon emission amount of the power generation end can also be determined by the following formula, that is, the carbon emission amount D of the power generation end in the t period is expressed as:
D＝Dr+Dg
Dr＝ADi×EFi
Dg＝ADe×EFe
in the formula, DrCarbon emissions for fossil fuel combustion, DgTo purchase carbon emissions using electricity generation, ADiActivity number, EF, of the ith fossil fueliCarbon dioxide emission factor, AD, for the ith fossil fueleTo purchase the amount of electricity used, EFeIs a power grid emission factor.
The carbon emission quota of the power generation end can be determined by the following formula, that is, if the power generation end of the power system is provided with a thermal power generating unit, a photovoltaic power station and a wind power plant, the carbon emission quota can be calculated by the following formula:
Figure BDA0003413272570000102
in the formula: eMThe carbon emission quota is eta which is the unit electric quantity emission allocation quota and can be determined by a regional power grid baseline emission factor specified by the national institute of development and improvement committee, alpha and beta are correction coefficients of the carbon quota of photovoltaic power generation and wind power generation at the time t, and P isG,i,tFor the ith thermal power generating unit at the moment tDispatch contribution of, KPV,j,tFor the jth photovoltaic power station stand-by coefficient at time t, PPV,j,tScheduling output, K, for the jth photovoltaic power station at time tW,k,tIs the kth wind farm standby coefficient at the moment t, PW,k,tFor the scheduling contribution, N, of the kth wind farm at time tGNumber of sets of live-wire in electric power system, NPVNumber of photovoltaic power stations in the power system, NWThe number of wind fields in the power system.
After the carbon emission amount and the carbon emission quota of the power generation end are determined based on the method, a carbon trading cost model, namely an expression (1), can be obtained.
In the embodiment of the present invention, the power generation energy consumption cost of the power generation end may include the operation cost of the power generation end unit, the start and stop cost of the unit, and the light abandoning cost, so in step S2, in the low-carbon economic dispatch model, the objective function is:
F＝min(FY+FK+FQ+FT)
in the formula: f represents that the sum of the comprehensive operation cost of the power generation end is minimum, and FYExpressed as the generator-side unit operating cost, FKIndicating the cost of starting and stopping the unit, FQRepresenting cost of waste light, FTRepresenting the carbon transaction cost.
Wherein the generator-side unit running cost FYExpressed as:
Figure BDA0003413272570000111
in the formula: pG,i,tActive power generated by the ith thermal power generating unit at the moment t, ai、bi、ciIs an economic parameter of the operation cost of the ith thermal power generating unit i, PPV,j,tActive power, η, generated at time t for the jth photovoltaic plantPV,jFor the unit electricity operating cost, P, of the jth photovoltaic power plantW,k,tActive power, eta, generated for the kth wind farm at time tW,kFor the operating cost per unit of electricity of the kth wind farm, NGNumber of sets of live-wire in electric power system, NPVFor lighting in electric power systemsNumber of photovoltaic power stations, NW24 represents that the operation cycle of the low-carbon economic dispatching model is 24 time periods for the number of wind power fields in the power system;
cost of starting and stopping machine set FKExpressed as:
Figure BDA0003413272570000112
in the formula: vi,tFor the start-stop state of ith thermal power generating unit at t period, wherein: u shapei,t＝1，Ui,t-1When the value is 0, then V i,t1, or else Vi,t＝0，Ui,tThe method comprises the following steps that (1) the starting and stopping state of the ith thermal power generating unit in a time period t is represented as 0, and starting is represented as 1; sT,i,tFor the startup cost of the home page i, SD,i,tFor downtime costs;
cost of discarding light FQExpressed as:
FQ＝CPVEPV,t
in the formula: cPVPenalty charge for unit abandon of light, EPV,tAnd (4) setting the expected light abandon amount at the time t.
The constraint conditions comprise an electric power constraint condition and a low-carbon constraint condition, wherein the electric power constraint condition can comprise a system power balance constraint and a unit constraint, and the low-carbon constraint condition can comprise a carbon trade limit constraint and a carbon emission reduction target constraint.
Specifically, the system power balance constraint is expressed as:
Figure BDA0003413272570000121
in the formula: pL,tIs the system load at time t, PG,i,tIs the output of the ith thermal power generating unit at the moment t, PPV,j,tIs the output of the jth photovoltaic power station at the moment t, PW,k,tIs the output of the kth wind farm at time t, NGNumber of sets of live-wire in electric power system, NPVNumber of photovoltaic power stations in the power system, NWThe number of wind fields in the power system.
The unit constraints can comprise thermal power unit capacity upper and lower limit constraints, thermal power unit climbing constraints, photovoltaic capacity upper and lower limit constraints, wind power capacity upper and lower limit constraints and rotation standby quantity constraints.
The thermal power generating unit capacity upper and lower limit constraints are expressed as follows:
Pmin,G≤PG,t≤Pmax,G
in the formula: pmin,G、Pmax,GUpper and lower limits of output, P, for each thermal power unitG,tAnd the output of each thermal power generating unit at the moment t.
The ramp constraint of the thermal power generating unit is represented as:
Figure BDA0003413272570000122
in the formula: pRUR,iLimiting the starting up and climbing of the ith thermal power generating unit; pRDR,iAnd limiting the shutdown and climbing of the ith thermal power generating unit.
The photovoltaic capacity upper and lower bound constraints are expressed as:
Pmin,PV≤PPV,t≤Pmax,PV
in the formula: pmin,PV、Pmax,PVFor the upper and lower limits of the output of the photovoltaic power station, PPV,tAnd the output of the photovoltaic power station at the moment t is obtained.
The wind power capacity upper and lower limit constraints are expressed as:
Pmin,W≤PW,t≤Pmax,W
in the formula: pmin,W、Pmax,WFor the upper and lower limits of the wind power plant output, PW,tAnd outputting power for the wind power plant at the moment t.
The rotational reserve constraint is expressed as:
Figure BDA0003413272570000131
in the formula: pG,i,tmaxThe maximum output at the moment t of the ith thermal power generating unit PG,i,tminFor the ith ignition powerMinimum output of unit at time t, ul、dlUpper and lower rotation reserve rates, u, respectively, increased due to load prediction errorp、dpUpper and lower rotational reserve rates, u, respectively, increased by photovoltaic contribution prediction errorw、dwRespectively the upper and lower rotational reserve rates increased by the wind power output prediction error.
The carbon trading credit constraint is expressed as:
ΔMCDM,t≤MCDM,t,max
in the formula: Δ MCDM,tCarbon credits, M, obtained by trading at time tCDM,t,maxThe maximum displacement reduction capacity which can be achieved by the power generation end. For the carbon transaction mechanism, the maximum emission reduction amount which can be achieved by the power generation end is limited by capital and technical levels.
The carbon reduction target constraint is expressed as:
MC,t≤MD,t+ΔMCDM,t
in the formula: mC,tAnd MD,tRespectively representing the total carbon emission amount and the distribution emission amount of the power generation end at the time t; Δ MCDM,tIs the carbon credit obtained by the transaction at time t.
On the basis of the low-carbon economic dispatching model taking the minimum sum of the comprehensive operation costs of the power generation end as the objective function, the low-carbon economic dispatching model is further solved to obtain a low-carbon economic dispatching scheme.
In one embodiment, the low-carbon economic dispatch model is solved by using a digital optimization technology CPLEX, but the method is not limited to the solution. Therefore, thermal power generating units, photovoltaic power stations, wind power plants and load data are input, constraint conditions and objective functions are set according to the low-carbon economic dispatching model, and a low-carbon economic dispatching scheme with the minimum total comprehensive operation cost of the power generation end can be obtained by solving through a digital optimization technology CPLEX.
Then, in step S3, the power system is optimally scheduled according to the low-carbon economic scheduling scheme.
As can be seen from the above description, according to the low-carbon optimal scheduling method for the power system, a carbon transaction cost model is established according to a carbon transaction mechanism, and the carbon emission transaction cost is determined by combining a system operation state, wherein a carbon emission flow tracking method based on a recursion algorithm can be adopted to calculate the carbon potential of system nodes and the distribution of the carbon emission flow; then combining the carbon emission trading cost as a low-carbon constraint condition with power constraint conditions such as a power balance condition, a unit output upper and lower limit constraint, a rotation reserve quantity constraint and the like to construct a scheduling model taking the minimum sum of the comprehensive operation cost of the power generation end as a target function; and finally, solving the model by adopting optimization software such as CPLEX to obtain a low-carbon economic dispatching scheme.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.

Claims (10)

1. A low-carbon optimal scheduling method for an electric power system is characterized by comprising the following steps:
step S1, acquiring basic data and load data of a power generation end in the power system;
step S2, inputting the obtained basic data and load data into a pre-established low-carbon economic dispatching model for solving, and obtaining a low-carbon economic dispatching scheme, wherein the low-carbon economic dispatching model comprises a target function and corresponding constraint conditions, the minimum sum of the comprehensive operation cost of the power generation end is used as the minimum sum, the comprehensive operation cost of the power generation end comprises the power generation energy consumption cost of the power generation end and the carbon transaction cost of the power generation end, and the carbon transaction cost of the power generation end is obtained by calculating and constructing a carbon transaction cost model based on the carbon emission amount and the carbon emission quota of the power generation end;
and step S3, performing optimized dispatching on the power system according to the low-carbon economic dispatching scheme.
2. The power system low-carbon optimal scheduling method of claim 1, wherein in the step S2, in the carbon transaction cost model, the carbon transaction cost at the power generation end at time t is represented as:
Figure FDA0003413272560000011
ΔMt＝D-EM
in the formula, FTThe carbon transaction cost of the power generation end at the time t, D is the carbon emission of the power generation end in the time t, and EMCarbon emission quota for generator end at t period, KCDMFor unit transaction price, KpPenalty paid for excess fraction of unit carbon emissions; Δ MCDM,tCarbon credits obtained by transactions at time t; Δ MCDM,t' is the carbon credit sold on the market by trading at time t; Δ MP,tCarbon credits obtained by paying a penalty for time t.
3. The low-carbon optimal scheduling method for the power system as claimed in claim 2, wherein a thermal power generating unit, a photovoltaic power station and a wind power plant are arranged at a power generation end of the power system, and the carbon emission quota of the power generation end in the t period is calculated by the following formula:
Figure FDA0003413272560000012
in the formula: eMIs carbon emission quota of a power generation end in a time period t, eta is unit electric quantity emission allocation quota, alpha and beta are carbon quota correction coefficients of photovoltaic power generation and wind power generation at the time t respectively, and PG,i,tThe scheduling output, K, of the ith thermal power generating unit at the moment tPV,j,tFor the jth photovoltaic power station stand-by coefficient at time t, PPV,j,tScheduling output, K, for the jth photovoltaic power station at time tW,k,tIs the kth wind farm standby coefficient at the moment t, PW,k,tFor the scheduling contribution, N, of the kth wind farm at time tGNumber of sets of live-wire in electric power system, NPVNumber of photovoltaic power stations in the power system, NWFor wind fields in electric power systemsNumber of the cells.
4. The low-carbon optimal scheduling method for the power system as claimed in claim 2, wherein the carbon emission of the power generation end in the t period is obtained by the following steps:
calculating node carbon potentials of all nodes in the power system by adopting a recursion algorithm of the carbon emission flow of the power system, and determining a node carbon potential distribution vector;
according to the node carbon potential distribution vector, combining a common apportionment principle, calculating to obtain the carbon emission flow rate of the power generation end;
the obtained carbon emission flow rate of the power generation end is multiplied by the duration of the t period to obtain the carbon emission amount of the power generation end for the t period.
5. The power system low-carbon optimal scheduling method of claim 2, wherein the carbon emission of the t-period power generation end is calculated by the following formula:
D＝Dr+Dg
Dr＝ADi×EFi
Dg＝ADe×EFe
in the formula, DrCarbon emissions for fossil fuel combustion, DgTo purchase carbon emissions using electricity generation, ADiActivity number, EF, of the ith fossil fueliCarbon dioxide emission factor, AD, for the ith fossil fueleTo purchase the amount of electricity used, EFeIs a power grid emission factor.
6. The power system low-carbon optimal scheduling method of any one of claims 2-5, wherein the power generation energy consumption cost of the power generation end comprises a power generation end unit operation cost, a unit start-up and shut-down cost and a light abandoning cost; the objective function in the low-carbon economic dispatching model is as follows:
F＝min(FY+FK+FQ+FT)
in the formula: f represents that the sum of the comprehensive operation cost of the power generation end is minimum, and FYTo representFor the operating costs of the generator-side units, FKIndicating the cost of starting and stopping the unit, FQRepresenting cost of waste light, FTRepresents a carbon transaction cost;
the constraints include power constraints and low carbon constraints.
7. The power system low-carbon optimal scheduling method of claim 6, wherein in the objective function:
the generator-side unit running cost FYExpressed as:
Figure FDA0003413272560000031
in the formula: pG,i,tActive power generated by the ith thermal power generating unit at the moment t, ai、bi、ciIs an economic parameter of the operation cost of the ith thermal power generating unit i, PPV,j,tActive power, η, generated at time t for the jth photovoltaic plantPV,jFor the unit electricity operating cost, P, of the jth photovoltaic power plantW,k,tActive power, eta, generated for the kth wind farm at time tW,kFor the operating cost per unit of electricity of the kth wind farm, NGNumber of sets of live-wire in electric power system, NPVNumber of photovoltaic power stations in the power system, NW24 represents that the operation cycle of the low-carbon economic dispatching model is 24 time periods for the number of wind power fields in the power system;
the unit start-up and shut-down costs FKExpressed as:
Figure FDA0003413272560000032
in the formula: vi,tFor the start-stop state of ith thermal power generating unit at t period, wherein: u shapei,t＝1，Ui,t-1When the value is 0, then Vi,t1, or else Vi,t＝0，Ui,tThe on-off state of the ith thermal power generating unit in the time period t is represented by 0, the shutdown is represented,1 represents starting up; sT,i,tFor the startup cost of the home page i, SD,i,tFor downtime costs;
the light abandoning cost FQExpressed as:
FQ＝CPVEPV,t
in the formula: cPVPenalty charge for unit abandon of light, EPV,tAnd (4) setting the expected light abandon amount at the time t.
8. The low-carbon optimal scheduling method for the power system according to claim 7, wherein the power constraint conditions include system power balance constraint, thermal power unit capacity upper and lower limit constraint, thermal power unit climbing constraint, photovoltaic capacity upper and lower limit constraint, wind power capacity upper and lower limit constraint and rotation reserve amount constraint, wherein:
the system power balance constraint is expressed as:
Figure FDA0003413272560000041
in the formula: pL,tIs the system load at time t, PG,i,tIs the output of the ith thermal power generating unit at the moment t, PPV,j,tIs the output of the jth photovoltaic power station at the moment t, PW,k,tIs the output of the kth wind farm at time t, NGNumber of sets of live-wire in electric power system, NPVNumber of photovoltaic power stations in the power system, NWThe number of wind fields in the power system;
the upper and lower capacity limit constraints of the thermal power generating unit are represented as follows:
Pmin,G≤PG,t≤Pmax,G
in the formula: pmin,G、Pmax,GUpper and lower limits of output, P, for each thermal power unitG,tThe output of each thermal power generating unit is at the moment t;
the ramp constraint of the thermal power generating unit is represented as:
Figure FDA0003413272560000042
in the formula: pRUR,iLimiting the starting up and climbing of the ith thermal power generating unit; pRDR,iLimiting shutdown and climbing of the ith thermal power generating unit;
the photovoltaic capacity upper and lower bound constraints are expressed as:
Pmin,PV≤PPV,t≤Pmax,PV
in the formula: pmin,PV、Pmax,PVFor the upper and lower limits of the output of the photovoltaic power station, PPV,tThe output of the photovoltaic power station at the moment t is obtained;
the wind power capacity upper and lower limit constraints are expressed as:
Pmin,W≤PW,t≤Pmax,W
in the formula: pmin,W、Pmax,WFor the upper and lower limits of the wind power plant output, PW,tThe output of the wind power plant at the moment t is obtained;
the rotational reserve constraint is expressed as:
Figure FDA0003413272560000051
in the formula: pG,i,tmaxThe maximum output at the moment t of the ith thermal power generating unit PG,i,tminThe minimum output at the moment t of the ith thermal power generating unit ul、dlUpper and lower rotation reserve rates, u, respectively, increased due to load prediction errorp、dpUpper and lower rotational reserve rates, u, respectively, increased by photovoltaic contribution prediction errorw、dwRespectively the upper and lower rotational reserve rates increased by the wind power output prediction error.
9. The power system low carbon optimal scheduling method of claim 6, wherein the low carbon constraints comprise a carbon trade credit constraint and a carbon emission reduction target constraint, wherein:
the carbon trading credit constraint is expressed as:
ΔMCDM,t≤MCDM,t,max
in the formula: Δ MCDM,tCarbon credits, M, obtained by trading at time tCDM,t,maxThe maximum displacement reduction capacity which can be reached by the power generation end;
the carbon reduction target constraint is expressed as:
MC,t≤MD,t+ΔMCDM,t
in the formula: mC,tAnd MD,tRespectively representing the total carbon emission amount and the distribution emission amount of the power generation end at the time t; Δ MCDM,tIs the carbon credit obtained by the transaction at time t.
10. The power system low-carbon optimal scheduling method of claim 1, wherein in the step S2, solving the low-carbon economic scheduling model specifically comprises:
and solving the low-carbon economic dispatching model by utilizing a digital optimization technology CPLEX to obtain the low-carbon economic dispatching scheme.
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