CN104850899A - Method for calculating optimal consumption of carbon emission paid quota for coal-fired power plant - Google Patents

Abstract

A method for calculating optimal consumption of carbon emission paid quota for coal-fired power plant comprises the steps of S1: selecting factors which have large influences on carbon emission, the factors being weather, coal type, load and operating parameters; S2: modeling; S3: assuming a carbon emission quota quantity purchased each time and a carbon emission quota ultimate bargain price auctioned each time; S4: constructing function relationships among the carbon emission quota quantity required to be purchased each time, the carbon emission bargain price of each time and an ultimate carbon emission paid quota total quantity consumed, and establishing a mathematical model; and S5: solving a value which enables the coal-fired power plant carbon emission paid quota total quantity consumed W within a year to be minimum by using a penalty function method for solving the optimum control of a non-linear control system, to obtain a coal-fired power plant carbon emission paid quota optimal consumption plan. With adoption of the method provided by the present invention, the optimal consumption of carbon emission paid quota for coal-fired power plant is calculated, possibilities and theoretical foundations are provided for reducing costs, and the method is also applicable to steel, petrochemical and concrete industries.

Description

The computing method of a kind of coal-burning power plant carbon emission paid quota optimal Consumption scheme

Technical field

The present invention relates to the computing method of a kind of coal-burning power plant carbon emission paid quota optimal Consumption scheme.

Background technology

Along with the impact of greenhouse gases on global climate manifests day by day, carbon dioxide is as one of main greenhouse gases causing greenhouse effect, and its reduction of discharging problem has become the problem of global focus the most.Climate resources is as the global public resource of one, and any country and individual carry certain responsibility and corresponding duties of cutting emissions to climate change problem.In order to alleviate the impact that can not be ignored that climate warming brings to human economy and society, every country has all put into effect a series of relevant policies successively in the emission reduction work of greenhouse gases in the world, multinomial measure is taken, for the emission reduction work of greenhouse gases makes positive effort from many aspects.

After Kyoto Protocol, developed country sets up carbon emission exchange in succession, and developing country, also by Clean Development Mechanism, incorporates International Carbon market more and more.As maximum developing country and discharge big country of the world, Chinese Government has made the formal commitment in the climate Conference forward direction whole world, Copenhagen the emission reduction targets of carbon dioxide intensity decline 40-45% of the year two thousand twenty China per GDP, and propose the target of the carbon dioxide strength ratio reduction by 17% in 2010 realizing per GDP by 2015 further in " 12 " planning, and decompose each province and city as the binding indicator to set up carbon emission trade market.

Carbon transaction is a kind of policy instrument for reducing carbon dioxide isothermal chamber gas discharging, limits exactly to the total emission volumn of greenhouse gases, between each economic entity, then distributes the Emission Right of restriction and carry out the bargain transaction of Emission Right.Up to the present, China has successively started Beijing, Shenzhen, Guangdong, Shanghai, Tianjin, Hubei, 7, Chongqing carbon emission transaction pilot.Carbon emission allocation of quota to be freely assigned as master, introduces paying-allocation in the early stage in good time, and progressively improves the ratio of paying-allocation.At present, the free quota ratio of Guangdong Province's electric power enterprise is 95%, and paid quota ratio is 5%, paid quota portion in principle one fraction of the year four times with form granting of bidding, enterprise independently can determine whether buy.For embodying quota in the scarcity of different times and value, provide reserve price and carry out ladder and rise, it is 25 yuan/ton, 30 yuan/ton, 35 yuan/ton, 40 yuan/ton that reserve price of bidding for four times is drafted respectively.

For needing the enterprise participating in carbon emission transaction, while actively finding the technology outlet effectively reducing carbon emission amount, how under present stage carbon emission mechanism of exchange, find carbon emission paid quota optimal Consumption scheme, the consumption of current carbon emission quota is dropped to minimum also significant, also can provide guiding suggestion for the production of enterprise and reduce the consumer cost of carbon emission simultaneously.

Summary of the invention

Technical matters to be solved by this invention, just be to provide the computing method of a kind of coal-burning power plant carbon emission paid quota optimal Consumption scheme, considering in the factors situation affecting coal-burning power plant's carbon emission paid quota consumption total value, calculate the optimal Consumption scheme of the paid quota of coal-burning power plant's carbon emission, reduce the carbon emission cost of coal-burning power plant to a certain extent.

Solve the problems of the technologies described above, the present invention adopts following technical scheme:

Computing method for coal-burning power plant's carbon emission paid quota optimal Consumption scheme, is characterized in that comprising the following steps:

S1, chooses the factor larger on the impact of carbon emission amount: weather, coal, load and operational factor;

S2, modeling

S2-1, utilizes support vector machine, sets up weather, coal, load, relational model between operational factor and coal-burning power plant's carbon emission amount;

Meter weather, coal, load and operational factor are that sample is designated as x _i, coal-burning power plant's CO2 emissions are output parameter y _i; The constrained input Parametric Representation of sample is { x _i, y _i} ⁿ, x _ibe i-th group of input parameter, y _ibe i-th group of output parameter, n is sample size;

Adopt support vector machine method modeling, select radial basis function as the kernel function of support vector machine:

$K(x_i,x_j)=\mathrm{\φ}\left(x_i\right)\·\mathrm{\φ}\left(x_j\right)=\exp \left|(-\frac{{\left|\right|x_i-x_j\left|\right|}^2}{2{\mathrm{\σ}}^2})\right|---\left(1\right)$

Parameter σ is the width of radial basis function, and φ (x) is mapping function, if decision function is f (x _i)=w φ (x _i)+b, f (x _i) be model predication value, w is weight coefficient vector, and b is intercept;

Structure based principle of minimization risk determination decision function parameter w, b, be equivalent to and solve following optimization problem:

$\min R=c\·\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{{\mathrm{\ξ}}_i}^2+\frac{1}{2}\·{\left|\right|w\left|\right|}^2$

C is regularization parameter, ξ _ifor training set predicated error vector;

Solve this optimization problem by Lagrange method, definition Lagrange multiplier is α=[α ₁, α ₂..., α _n], have:

According to optimal conditions:

$\frac{\∂L}{\∂w}=0,\frac{\∂L}{\∂b}=0,\frac{\∂L}{\∂{\mathrm{\ξ}}_i}=0,\frac{\∂L}{\∂{\mathrm{\α}}_i}=0,---\left(4\right)$

Draw:

$\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_i=0---\left(6\right)$

2cξ _i＝α _i(7)

Formula (5) and formula (7) are substituted into formula (8):

$y_i=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}({\mathrm{\α}}_j\·K(x_i,x_j))+b+\frac{1}{2c}{\mathrm{\α}}_i---\left(10\right)$

By formula (6) and (10) synthesizing linear system of equations as follows:

According to training sample set (x _i, y _i), i=1,2 ..., n, solution matrix (11), obtains model parameter [b α ₁α ₂α _n]; The decision function finally determined is:

$f\left(x\right)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_i\·K(x,x_i)+b---\left(12\right);$

S2-2, calculates the carbon emission total amount of coal-burning power plant in the middle of a year in conjunction with corresponding input parameter according to output function;

Input weather, coal, load and operational factor influence factor x _i, calculate and export coal-burning power plant CO2 emissions y _i;

S2-3, calculates according to the ratio of the paid quota granting of corresponding carbon emission then and needs the carbon emission quota quantities of purchase and be designated as A;

A＝y _i×5％；

S3, supposes that the carbon emission quota quantities that every first phase is bought are a respectively ₁, a ₂, a ₃, a ₄, the final transaction value of carbon emission quota that each issue auction obtains is P ₁, P ₂, P ₃, P ₄; Wherein:

P＝P(m ₁、m ₂、m ₃......)；

M ₁, m ₂, m ₃... represent the factor affecting the final transaction value of carbon quota, comprise each issue carbon emission rationing transaction reserve price, each issue auction declaration form bit quantity and each issue auction and declare the time;

S4, constructs the carbon emission quota amount of each issue needs purchase and the funtcional relationship of each issue carbon emission transaction value and the paid quota total quantity consumed of final carbon emission, founding mathematical models:

a ₁+a ₂+a ₃+a ₄＝A

a ₁·P ₁+a ₂·P ₂+a ₃·P ₃+a ₄·P ₄＝W

P＝P(m ₁、m ₂、m ₃......)

S5, utilizes the penalty function method solving nonlinear control system optimum control to solve to make a when coal-burning power plant's carbon emission paid quota consumption total value W is minimum in the middle of a year ₁, a ₂, a ₃, a ₄numerical value, obtain coal-burning power plant's carbon emission paid quota optimal Consumption scheme.

This method by affect coal-burning power plant's carbon emission paid quota consumption total value factors by mathematical modeling and mathematical method fully comprehensive, the coal-burning power plant's carbon emission paid quota optimal Consumption scheme measured, provides possibility and theoretical foundation for reducing coal-burning power plant's carbon emission consumer cost; Meanwhile, the abundant refinement of factors of coal-burning power plant's carbon emission paid quota consumption total value will be affected, make coal-burning power plant's carbon emission paid quota optimal Consumption scheme of finally doping more accurate, practical.

Compared with prior art, the present invention has the following advantages:

The present invention is by calculating coal-burning power plant's carbon emission paid quota optimal Consumption scheme, possibility and theoretical foundation is provided for reducing coal-burning power plant's carbon emission consumer cost, be not only applicable to coal-burning power plant, be applicable to the industry such as iron and steel, petrochemical industry, cement needing to participate in carbon emission transaction simultaneously.

Accompanying drawing explanation

Fig. 1 is the Integral Thought calculating carbon emission paid quota optimal Consumption scheme;

Fig. 2 utilizes support vector machine to set up the relational model between parameter and coal-burning power plant's carbon emission amount such as weather, coal, load, operational factor;

Fig. 3 is the relational model of the final transaction value of carbon quota that the factors such as each issue carbon emission rationing transaction reserve price, each issue auction declaration form bit quantity and each issue auction obtain;

Fig. 4 is the carbon emission quota amount of each issue needs purchase and the relational model of each issue carbon emission transaction value and the paid quota total quantity consumed of final carbon emission.

In figure, weather, coal, load, operational factor etc. are input variable, and output variable is coal-burning power plant's carbon emission amount.

Embodiment

Below in conjunction with accompanying drawing, by embodiment, the invention will be further described.

As shown in Figure 1,2,3, 4, the computing method embodiment of coal-burning power plant of the present invention carbon emission paid quota optimal Consumption scheme, specifically comprises the following steps:

S1, chooses the factor larger on the impact of carbon emission amount: weather, coal, load and operational factor;

S2, modeling

S2-1, utilizes support vector machine, sets up weather, coal, load, relational model between operational factor and coal-burning power plant's carbon emission amount;

Meter weather, coal, load and operational factor are that sample is designated as x _i, coal-burning power plant's CO2 emissions are output parameter y _i; The constrained input Parametric Representation of sample is { x _i, y _i} ⁿ, x _ibe i-th group of input parameter, y _ibe i-th group of output parameter, n is sample size;

Adopt support vector machine method modeling, select radial basis function as the kernel function of support vector machine:

$K(x_i,x_j)=\mathrm{\φ}\left(x_i\right)\·\mathrm{\φ}\left(x_j\right)=\exp \left|(-\frac{{\left|\right|x_i-x_j\left|\right|}^2}{2{\mathrm{\σ}}^2})\right|---\left(1\right)$

Parameter σ is the width of radial basis function, and φ (x) is mapping function, if decision function is f (x _i)=w φ (x _i)+b, f (x _i) be model predication value, w is weight coefficient vector, and b is intercept;

Structure based principle of minimization risk determination decision function parameter w, b, be equivalent to and solve following optimization problem:

$\min R=c\·\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{{\mathrm{\ξ}}_i}^2+\frac{1}{2}\·{\left|\right|w\left|\right|}^2$

C is regularization parameter, ξ _ifor training set predicated error vector;

Solve this optimization problem by Lagrange method, definition Lagrange multiplier is α=[α ₁, α ₂..., α _n], have:

According to optimal conditions:

$\frac{\∂L}{\∂w}=0,\frac{\∂L}{\∂b}=0,\frac{\∂L}{\∂{\mathrm{\ξ}}_i}=0,\frac{\∂L}{\∂{\mathrm{\α}}_i}=0,---\left(4\right)$

Draw:

$\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_i=0---\left(6\right)$

2cξ _i＝α _i(7)

Formula (5) and formula (7) are substituted into formula (8):

$y_i=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}({\mathrm{\α}}_j\·K(x_i,x_j))+b+\frac{1}{2c}{\mathrm{\α}}_i---\left(10\right)$

By formula (6) and (10) synthesizing linear system of equations as follows:

According to training sample set (x _i, y _i), i=1,2 ..., n, solution matrix (11), obtains model parameter [b α ₁α ₂α _n]; The decision function finally determined is:

$f\left(x\right)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_i\·K(x,x_i)+b---\left(12\right);$

S2-2, calculates the carbon emission total amount of coal-burning power plant in the middle of a year in conjunction with corresponding input parameter according to output function;

Input weather, coal, load and operational factor influence factor x _i, calculate and export coal-burning power plant CO2 emissions y _i;

S2-3, calculates according to the ratio of the paid quota granting of corresponding carbon emission then and needs the carbon emission quota quantities of purchase and be designated as A;

A＝y _i×5％；

S3, supposes that the carbon emission quota quantities that every first phase is bought are a respectively ₁, a ₂, a ₃, a ₄, the final transaction value of carbon emission quota that each issue auction obtains is P ₁, P ₂, P ₃, P ₄; Wherein:

P＝P(m ₁、m ₂、m ₃......)；

M ₁, m ₂, m ₃... represent the factor affecting the final transaction value of carbon quota, comprise each issue carbon emission rationing transaction reserve price, each issue auction declaration form bit quantity and each issue auction and declare the time;

S4, constructs the carbon emission quota amount of each issue needs purchase and the funtcional relationship of each issue carbon emission transaction value and the paid quota total quantity consumed of final carbon emission, founding mathematical models:

a ₁+a ₂+a ₃+a ₄＝A

a ₁·P ₁+a ₂·P ₂+a ₃·P ₃+a ₄·P ₄＝W

P＝P(m ₁、m ₂、m ₃......)

S5, utilizes the penalty function method solving nonlinear control system optimum control to solve to make a when coal-burning power plant's carbon emission paid quota consumption total value W is minimum in the middle of a year ₁, a ₂, a ₃, a ₄numerical value, obtain coal-burning power plant's carbon emission paid quota optimal Consumption scheme.

Claims (1)

1. computing method for coal-burning power plant's carbon emission paid quota optimal Consumption scheme, is characterized in that comprising the following steps:

S1, chooses the factor larger on the impact of carbon emission amount: weather, coal, load and operational factor;

S2, modeling

S2-1, utilizes support vector machine, sets up weather, coal, load, relational model between operational factor and coal-burning power plant's carbon emission amount;

Meter weather, coal, load and operational factor are that sample is designated as x _i, coal-burning power plant's CO2 emissions are output parameter y _i; The constrained input Parametric Representation of sample is { x _i, y _i} ⁿ, x _ibe i-th group of input parameter, y _ibe i-th group of output parameter, n is sample size;

Adopt support vector machine method modeling, select radial basis function as the kernel function of support vector machine:

$K(x_i,x_j)=\mathrm{\φ}\left(x_i\right)\·\mathrm{\φ}\left(x_j\right)=\exp \left|\left(\frac{{\left|\right|x_i-x_j\left|\right|}^2}{2{\mathrm{\σ}}^2}\right)\right|---\left(1\right);$

Parameter σ is the width of radial basis function, and φ (x) is mapping function, if decision function is f (x _i)=w φ (x _i)+b, f (x _i) be model predication value, w is weight coefficient vector, and b is intercept;

Structure based principle of minimization risk determination decision function parameter w, b, be equivalent to and solve following optimization problem:

$\min R=c\·\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{{\mathrm{\ξ}}_i}^2+\frac{1}{2}\·{\left|\right|w\left|\right|}^2$

C is regularization parameter, ξ _ifor training set predicated error vector;

Solve this optimization problem by Lagrange method, definition Lagrange multiplier is α=[α ₁, α ₂..., α _n], have:

According to optimal conditions:

$\frac{\∂L}{\∂w}=0,\frac{\∂L}{\∂b}=0,\frac{\∂L}{\∂{\mathrm{\ξ}}_i}=0,\frac{\∂L}{\∂{\mathrm{\α}}_i}=0,---\left(4\right);$

Draw:

$\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_i=0---\left(6\right);$

2cξ _i＝α _i(7)；

Formula (5) and formula (7) are substituted into formula (8):

$y_i=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}({\mathrm{\α}}_j\·K(x_i,x_j))+b+\frac{1}{2c}{\mathrm{\α}}_i---\left(10\right);$

By formula (6) and (10) synthesizing linear system of equations as follows:

According to training sample set (x _i, y _i), i=1,2 ..., n, solution matrix (11), obtains model parameter [b α ₁α ₂α _n]; The decision function finally determined is:

$f\left(x\right)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_i\·K(x,x_i)+b---\left(12\right);$

S2-2, calculates the carbon emission total amount of coal-burning power plant in the middle of a year in conjunction with corresponding input parameter according to output function;

Input weather, coal, load and operational factor influence factor x _i, calculate and export coal-burning power plant CO2 emissions y _i;

S2-3, calculates according to the ratio of the paid quota granting of corresponding carbon emission then and needs the carbon emission quota quantities of purchase and be designated as A;

A＝y _i×5％；

S3, supposes that the carbon emission quota quantities that every first phase is bought are a respectively ₁, a ₂, a ₃, a ₄, the final transaction value of carbon emission quota that each issue auction obtains is P ₁, P ₂, P ₃, P ₄; Wherein:

P＝P(m ₁、m ₂、m ₃......)；

M ₁, m ₂, m ₃... represent the factor affecting the final transaction value of carbon quota, comprise each issue carbon emission rationing transaction reserve price, each issue auction declaration form bit quantity and each issue auction and declare the time;

S4, constructs the carbon emission quota amount of each issue needs purchase and the funtcional relationship of each issue carbon emission transaction value and the paid quota total quantity consumed of final carbon emission, founding mathematical models:

a ₁+a ₂+a ₃+a ₄＝A；

a ₁·P ₁+a ₂·P ₂+a ₃·P ₃+a ₄·P ₄＝W

P＝P(m ₁、m ₂、m ₃......)

S5, utilizes the penalty function method solving nonlinear control system optimum control to solve to make a when coal-burning power plant's carbon emission paid quota consumption total value W is minimum in the middle of a year ₁, a ₂, a ₃, a ₄numerical value, obtain coal-burning power plant's carbon emission paid quota optimal Consumption scheme.