CN115293561A - Low-carbon planning method and device for power system considering carbon emission flow - Google Patents
Low-carbon planning method and device for power system considering carbon emission flow Download PDFInfo
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Abstract
The invention relates to a low-carbon planning method and a low-carbon planning device for a power system considering carbon emission flow, wherein the method comprises the steps of constructing a double-layer low-carbon planning model based on a pre-constructed low-carbon investment planning model and a pre-constructed load side demand response model; and solving the double-layer low-carbon planning model and outputting a low-carbon planning result. The invention provides a double-layer low-carbon planning model of an electric power system, which takes carbon price as a price signal based on the step carbon price on the demand side and considers the carbon emission responsibility allocation and the demand side active response, and achieves the purposes of reducing the carbon emission and the carbon emission cost.
Description
Technical Field
The invention belongs to the technical field of power markets, and particularly relates to a low-carbon planning method and device for a power system considering carbon emission flow.
Background
In an electric power system, the carbon dioxide emission generated by power generation of a coal-fired unit is very high, and the carbon emission is directly caused by a power generation side intuitively, so that in the low-carbon planning of the electric power system, the carbon emission constraint of the power generation side is mainly considered, the installed capacity of the traditional coal-fired unit is reduced, the installed capacity of a new energy unit is expanded, and the purpose of reducing the carbon emission of the system is achieved; when power supply planning is carried out, a carbon trading mechanism is introduced into part of technologies, carbon trading cost is added into an optimization target, the carbon responsibility of a power generation enterprise is restrained, and the purpose of reducing system carbon emission is achieved; aiming at the power transmission link, a full life cycle carbon emission evaluation model is provided, and carbon emission cost of power transmission equipment is considered, so that carbon emission reduction is realized. In addition, in the partial technology, when power planning is carried out, loads on a user side are adjusted through demand response, some rigid loads become adjustable flexible resources to participate in the operation of a power system, and the adjustment and the correction of a load curve are realized, so that the electric energy use efficiency is improved, and the carbon emission caused by unnecessary investment is reduced.
The current technology is based on different optimization targets, and low-carbon planning models are researched on a power supply side and a load side, but for the existing low-carbon planning models on the power supply side, although a better theoretical support effect can be achieved on reduction of carbon emission of a power system, a guidance effect is difficult to achieve on the aspect of guiding power utilization of a user, and no research is conducted on how to consider demand response in system planning. For the existing load side demand response model, although the user side load can be adjusted through demand response, the low-carbon benefit of the demand response in power planning is not considered, and even though the demand side management is verified to be capable of effectively reducing the carbon emission of the system, the carbon emission responsibility of the demand side demand response model is still born by the power generation side.
Therefore, the existing low-carbon planning model does not return the carbon emission responsibility to the user side, and the carbon emission responsibility of each load node cannot be reasonably shared to reduce the carbon emission and the carbon emission cost.
Disclosure of Invention
In view of this, the present invention provides a low-carbon planning method and apparatus for a power system considering carbon emission flow, so as to solve the problem that the carbon emission responsibility of each load node cannot be reasonably shared to reduce the carbon emission amount and the carbon emission cost in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme: a power system low carbon planning method considering carbon emission flow comprises the following steps:
constructing a double-layer low-carbon planning model based on a pre-constructed low-carbon investment planning model and a pre-constructed load side demand response model;
and solving the double-layer low-carbon planning model and outputting a low-carbon planning result.
Further, the low-carbon investment planning model comprises: the method comprises the following steps of taking the lowest sum of investment cost and operation cost of the power system as a first objective function and a first constraint condition corresponding to the first objective function;
the first objective function is min C Total ＝C Inv +C Ope
Wherein, C Total For the overall cost of the system, C InV For system investment cost, C ope The cost of system operation;
the first constraint condition comprises:
and (3) constraint of installed capacity:
wherein, the first and the second end of the pipe are connected with each other,
is the upper limit of the machine set g,
is the installed upper limit of the wind power plant w,
is the installed upper limit of the photovoltaic power station p,
the installation upper limit of the energy storage equipment e;
and (3) new energy power generation ratio constraint:
wherein N is T Is a period of time, N WT Is the total number of wind power plant equipment, N PV Is the total number of photovoltaic power plant installations, P WT For generating power for wind turbines, P PV Generating power for a photovoltaic power plant, N N Is the total number of nodes of the grid, rho New Is the ratio of the new energy to the electricity generation,
predicting a curve for the load demand of the node i;
and (3) grid frame constraint:
F l，t ＝B l (θ Bgn，l，t -θ End，l，t )-F l Max ≤F l，t ≤F l Max -π≤θ i，t ≤π
wherein omega G，i Set of units, omega, for node i WT，i For a set of wind farms, Ω PV，i Set of photovoltaic power stations, omega ES，i Is a set of energy storage devices, P G，g，t Is the generated output of the unit g at the time t, P wT，w，t For the power generation output of the wind farm w at time t, P PV，p，t For the generated output of the photovoltaic power station p at the time t,
and
respectively the discharging power and the charging power of the energy storage equipment e, and BI is the susceptance of the branch circuit l; f l，t ，θ Bgn，l，t ，θ End，l，t The phase angles of the power flow, the head end and the tail end nodes of the branch circuit l at the time t are theta i，t The phase angle of the node i;
the traditional unit operation simulation constraint:
0≤P G，g，t ≤Q G，g
wherein, the first and the second end of the pipe are connected with each other,
the maximum rates of the lower climbing and the upper climbing of the unit g are respectively, and the upper mode is respectively the output and climbing restraint of the unit;
and (3) new energy output constraint:
0≤P WT，w，t ≤γ WT，w，t Q WT，w
0≤P PV，p，t ≤γ PV，pt Q PV，p
wherein, gamma is WT，w，t Per unit output prediction curve and gamma for wind power plant omega PV，w，t The per-unit output prediction curve of the photovoltaic power station p is obtained;
energy storage operation restraint:
0≤S e，t ≤H e Q ES，e
wherein S is e，t The state of charge of the energy storage device e at time t;
respectively the charging efficiency and the discharging efficiency, H, of the energy storage device e e For the time period of energy storage of the energy storage device e,
an initial energy storage level of the energy storage device e;
system standby constraints:
wherein r is New ，r Load Are respectively asAnd the new energy power generation and the load demand standby rate.
Further, solving the low-carbon investment planning model, and outputting unit output, wind-solar output and branch power flow data;
and constructing a load side demand response model based on the unit output, the wind and light output and the branch power flow data.
Further, the load side demand response model includes: a second objective function targeting a minimum sum of the load-side carbon emission cost and the demand response cost, and a second constraint condition corresponding to the second objective function;
the second objective function is such that,
wherein, C CE，i，t Cost of carbon emissions for node i at time t, C DR In order to meet the unit cost of demand response,
respectively the load up-regulation power and the load down-regulation power of the node i at the time t,
the second constraint includes:
and (3) load regulation constraint:
wherein D is DR，i，t The load demand after the node i responds at the time t;
carbon emissions are constrained by the equation:
E i，t ＝I N，i，t D DR，i，t
I L，l，t ＝I N，i，t ，l∈Ω i-
wherein, I N，i，t Is the carbon potential of node I at time t, I L，i，t Carbon flow density at node l at time t, I G，g，t Carbon emission intensity for coal-fired unit g, I WT，W，t Intensity of carbon emission for wind farm w, I PV，P，t Is the carbon emission intensity of the photovoltaic power plant p.
Further, the solving the double-layer low-carbon planning model and outputting a low-carbon planning result includes:
solving the low-carbon investment planning model, and outputting unit output, wind-solar output and branch power flow data;
judging whether to perform power demand response or not based on the unit output, the wind-solar output and the branch power flow data to obtain a judgment result;
and outputting a low-carbon planning result according to the judgment result.
Further, the outputting a low-carbon planning result according to the judgment result includes:
if the judgment result is that demand response is carried out, solving the demand response model based on the unit output, the wind and light output and the branch power flow data to obtain optimized and adjusted load data, inputting the optimized and adjusted load data into an investment planning model and solving again to output an optimal planning result;
otherwise, directly outputting the investment planning result with the lowest sum of the system investment cost and the operation cost as a low-carbon planning result.
Further, the carbon emission cost is
Wherein, E i，t Is a node at time ti carbon emissions; c CE，1 、C CE，2 、C CE，3 、C CE，4 The unit cost for the step carbon emission; e Bnd，1 、E Bnd，2 、E Bnd，3 Is the boundary amount of the carbon emission price interval.
Further, the solving the low-carbon investment planning model includes:
inputting input parameters of the low-carbon investment planning model;
the input parameters comprise planning parameters, line parameters, unit parameters, a wind and light prediction curve, a load prediction curve and a carbon emission coefficient.
The embodiment of the application provides a power system low carbon planning device who takes into account carbon emission and flow includes:
the building module is used for building a double-layer low-carbon planning model based on a pre-built low-carbon investment planning model and a pre-built load side demand response model;
and the solving module is used for solving the double-layer low-carbon planning model and outputting a low-carbon planning result.
By adopting the technical scheme, the invention can achieve the following beneficial effects:
the invention provides a low-carbon planning method and device for a power system considering carbon emission flow. The method is based on the step carbon price on the demand side, the carbon price is used as a price signal, a power system double-layer low-carbon planning model considering carbon emission responsibility allocation and demand side active response is provided, and the purposes of reducing carbon emission and carbon emission cost are achieved.
Drawings
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 schematic diagram illustrating the steps of a power system low carbon planning method of the present invention that accounts for carbon emission flow;
FIG. 2 is a schematic flow chart of a method for low carbon planning of an electrical power system that accounts for carbon emission flows in accordance with the present invention;
fig. 3 is a schematic structural diagram of a power system low-carbon planning apparatus considering carbon emission flow according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the background of low-carbon energy, implementing low-carbon planning of a power system mainly based on clean energy is an important approach to achieve the goal of "double-carbon". The low-carbon power system is an innovation of the traditional power system, is a necessary trend of sustainable development of the power system, can ensure that the environmental protection performance of the power system is greatly improved while the power system is stably operated, saves a large amount of funds, and enables the economic benefit and the social benefit of the power industry to be unified.
It should be noted that the definition of the carbon emission flow of the power system is: in an electrical power system, a virtual network flow exists as a kind of adherence to a power flow, representing carbon emissions resulting from maintaining the power network flow. It can be further understood that: in the power system, carbon dioxide is generated from the power generation side and flows out, enters the power network along with the power generation power, flows in the net rack depending on tide, and finally flows into the load side. Superficially, carbon dioxide is emitted directly into the air from the power generation side, and is essentially consumed by the load side users through the carbon emission stream.
Carbon flowThe rate is the amount of carbon emitted by the injection node or by the branch in a unit of time, in tCO 2 /h。
The carbon flow density can be divided into branch carbon flow density and node carbon flow density, the node carbon flow density is also called node carbon potential and is expressed by tCO 2 /kWh。
A specific power system low-carbon planning method and apparatus considering carbon emission flow provided in the embodiments of the present application will be described with reference to the drawings.
As shown in fig. 1, the power system low-carbon planning method considering carbon emission flow provided in the embodiment of the present application includes:
s101, constructing a double-layer low-carbon planning model based on a pre-constructed low-carbon investment planning model and a pre-constructed load side demand response model;
the modeling mode of the low-carbon investment planning model is based on a time sequence model of 8760h all year round, and a unit clustering linearization method is adopted to model the traditional unit. Specifically, the low-carbon investment planning model takes a first objective function with the lowest sum of the investment cost and the operation cost of the power system as a target and a first constraint condition corresponding to the first objective function;
the first objective function is min C Total ＝C Inv +C Ope
Wherein, C Total For the overall cost of the system, C Inv For system investment cost, C ope The system operating cost;
the first constraint condition comprises:
and (3) constraint of installed capacity:
wherein the content of the first and second substances,
is the upper limit of the machine set g,
is the installed upper limit of the wind power plant w,
is the installed upper limit of the photovoltaic power station p,
the installation upper limit of the energy storage equipment e;
and (3) new energy power generation ratio constraint:
wherein N is T Is a period of time, N WT For the total number of wind power plant equipment, N PV Is the total number of photovoltaic power plant devices, P WT For generating power for wind turbines, P PV Generating power for a photovoltaic power plant, N N As total number of grid nodes, ρ New The proportion of the new energy to generate electricity,
predicting a curve for the load demand of the node i;
and (3) grid frame constraint:
F l，t ＝B l (θ Bgn，l，t -θ End，l，t )-F l Max ≤F l，t ≤F l Max -π≤θ i，t ≤π
wherein omega G，I Set of units, omega, being node i WT，i For a set of wind farms, Ω PV，I Set of photovoltaic power stations, omega ES，i Is a set of energy storage devices, P G，g，t Is the generated output of the unit g at the time t, P WT，w，t For the power generation output of the wind farm w at time t, P PV，p，t For the generated output of the photovoltaic power station p at the time t,
and
respectively the discharge power and the charge power of the energy storage device e, B l Is the susceptance of branch l; f l，t ，θ Bgn，l，t ，θ End，l，t The phase angles of the power flow, the head end and the tail end nodes of the branch 1 at the time t are theta i，t The phase angle of the node i;
the traditional unit operation simulation constraint:
0≤P G，g，t ≤Q G，g
wherein, the first and the second end of the pipe are connected with each other,
maximum rates of downward climbing and upward climbing of the unit g are respectively, and the upper formula is respectively the output and climbing constraints of the unit;
and (3) new energy output constraint:
0≤P WT，w，t ≤γ WT，w，t Q WT，w
0≤P PV，p，t ≤γ PV，p，t Q PV，p
wherein, γ WT，w，t Per unit output prediction curve and gamma for wind power plant omega PV，w，t The per-unit output prediction curve of the photovoltaic power station p is obtained;
energy storage operation restraint:
0≤S e，t ≤H e Q ES，e
wherein S is e，t The state of charge of the energy storage device e at time t;
respectively the charging efficiency and the discharging efficiency, H, of the energy storage device e e For the time period of energy storage of the energy storage device e,
is the initial energy storage level of the energy storage device e;
system standby constraints:
wherein r is New ，r Load Respectively serving as new energy power generation and load demand standby rates
After a low-carbon investment planning model is built, the low-carbon investment planning model is solved to obtain unit output, wind and light output and branch power flow data, and then a load side demand response model is built based on the unit output, the wind and light output and the branch power flow data.
The load side demand response model is based on a carbon emission flow theory, and is modeled by applying a load side stepped carbon valence mechanism, and specifically, the load side demand response model comprises: a second objective function targeting a minimum sum of the load-side carbon emission cost and the demand response cost, and a second constraint condition corresponding to the second objective function;
the second objective function is such that,
wherein, C CE，i，t Cost of carbon emissions for node i at time t, C DR In order to meet the unit cost of demand response,
respectively the load up-regulation power and the load down-regulation power of the node i at the time t;
wherein the carbon emission cost is calculated by
Wherein E is i，t The carbon emission at the node i at the time t; c CE，1 、C CE，2 、C CE，3 、C CE，4 The unit cost for the step carbon emission; e Bnd，1 、E Bnd，2 、E Bnd，3 Is the boundary amount of the carbon emission price interval;
the second constraint includes:
and (3) load regulation constraint:
wherein D is DR，i，t The load demand after the node i responds at the time t;
carbon emissions are constrained by the equation:
E i，t ＝I N，i，t D DR，i，t
I L，l，t ＝I N，i，t ，l∈Ω i-
wherein, I N，i，t Is the carbon potential of node I at time t, I L，i，t Carbon flow density of node l at time t, I G，g，t Carbon emission intensity for coal-fired unit g, I WT，W，t Intensity of carbon emission for wind farm w, I PV，P，t Is the carbon emission intensity of the photovoltaic power plant p.
And S102, solving the double-layer low-carbon planning model and outputting a low-carbon planning result.
In some embodiments, as shown in fig. 2, the solving the two-tier low-carbon planning model and outputting a low-carbon planning result includes:
s1021, inputting input parameters of the low-carbon investment planning model;
s1022, solving the low-carbon investment planning model;
s1023, outputting the output of the unit, the wind-solar output and the branch power flow data;
s1024, judging whether to perform power demand response or not based on the unit output, the wind-solar output and the branch power flow data to obtain a judgment result;
and S1025, outputting a low-carbon planning result according to the judgment result.
In some embodiments, the outputting a low-carbon planning result according to the determination result includes:
s10241, if the judgment result is the demand response, solving the demand response model based on the unit output, the wind and light output and the branch power flow data,
s10242, obtaining optimized and adjusted load data,
inputting the optimized and adjusted load data into an investment planning model and solving again;
and outputting an optimal planning result, otherwise, directly outputting an investment planning result which takes the lowest sum of the system investment cost and the operation cost into consideration as a low-carbon planning result.
The solving of the low-carbon investment planning model comprises:
inputting input parameters of the low-carbon investment planning model;
the input parameters comprise planning parameters, line parameters, unit parameters, a wind and light prediction curve, a load prediction curve and a carbon emission coefficient.
The working principle of the power system low-carbon planning method considering the carbon emission flow is as follows: as shown in fig. 2, in the double-layer low-carbon planning model provided by the present application, the low-carbon investment planning model is located at the upper layer, the load-side demand response model is located at the lower layer, the distribution of the system load is adjusted through the demand response by the lower layer model, and the adjusted load data needs to be updated to the upper layer model and solved again to optimize the planning result.
Specifically, input parameters are input into a low-carbon investment planning model for solving, and the input parameters comprise planning parameters, line parameters, unit parameters, a wind-light prediction curve, a load prediction curve, a carbon emission coefficient and other data; then, solving the upper-layer investment planning model, outputting the unit output, the wind-solar output and the branch power flow, judging whether demand response is carried out or not, and directly outputting an investment planning result considering the lowest sum of the system investment cost and the operation cost if the demand response judgment is not needed; and if the demand response is considered, the output result of the investment planning model is used as the input of the demand response model, the demand response model with carbon price as a price signal is solved, and the load is optimized and adjusted. And finally, updating the responded load data into an upper layer model, solving the investment planning model again (the load response is not considered again in the re-solving process, and only one solution is required), outputting the optimal planning result at the moment, and calculating the carbon emission amount and the carbon emission cost of the load side.
The carbon emission responsibility of the power system is reduced to the user side based on the carbon emission flow theory so as to reasonably share the carbon emission responsibility of each load node. The method is based on the step carbon price on the demand side, the carbon price is used as a price signal, and a power system double-layer planning model considering carbon emission responsibility allocation and demand side active response is provided. The first layer is a traditional investment decision planning model, and mainly optimizes the capacity of traditional units, wind power plants, photovoltaic power stations and energy storage equipment in the system; and on the basis of the upper low-carbon investment planning model, the second layer utilizes the calculated power flow and the unit output to calculate the carbon emission responsibility based on the carbon emission flow theory, and then combines the carbon price on the demand side to optimally adjust the load curve by taking the minimum sum of the carbon emission cost and the demand response cost as the target so as to achieve the aim of reducing the carbon emission and the carbon emission cost.
By the technical scheme provided by the application, the carbon emission responsibility on the user side is reasonably and effectively shared; the solving efficiency of a planning model for simulating the running state of the power system for 8760h all the year is improved by introducing a unit clustering linearization technology; the user side is guided to optimize and adjust the load demand, the system load distribution is reasonably adjusted through demand response on the premise that the total load demand is not changed, the utilization rate of new energy can be effectively improved, new energy consumption is promoted, the investment cost and the operation cost of an electric power system are saved, and the total carbon emission amount and the carbon emission cost of the system are obviously reduced.
As shown in fig. 3, the present application provides a low carbon planning apparatus for a power system with consideration of carbon emission flow, comprising:
the building module is used for building a double-layer low-carbon planning model based on a pre-built low-carbon investment planning model and a pre-built load side demand response model;
and the solving module is used for solving the double-layer low-carbon planning model and outputting a low-carbon planning result.
The working principle of the power system low-carbon planning device considering the carbon emission flow provided by the application is that the construction module 201 constructs a double-layer low-carbon planning model based on a pre-constructed low-carbon investment planning model and a pre-constructed load side demand response model; the solving module 202 solves the double-layer low-carbon planning model and outputs a low-carbon planning result.
In summary, the present invention provides a power system low-carbon planning method and device considering carbon emission flow, which provides a power system double-layer low-carbon planning model considering carbon emission responsibility allocation and demand side active response based on demand side stepped carbon price and using the carbon price as a price signal, so as to achieve the purpose of reducing carbon emission and carbon emission cost.
It is to be understood that the embodiments of the method provided above correspond to the embodiments of the apparatus described above, and the corresponding specific contents may be referred to each other, which is not described herein again.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present invention, and shall cover the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (9)
1. A power system low-carbon planning method considering carbon emission flow is characterized by comprising the following steps:
constructing a double-layer low-carbon planning model based on a pre-constructed low-carbon investment planning model and a pre-constructed load side demand response model;
and solving the double-layer low-carbon planning model and outputting a low-carbon planning result.
2. The method of claim 1, wherein the low carbon investment planning model comprises: the method comprises the following steps of taking the lowest sum of investment cost and operation cost of the power system as a first objective function and a first constraint condition corresponding to the first objective function;
the first mentionedAn objective function of, minC Total ＝C Inv +C Ope
Wherein, C Total For the overall cost of the system, C Inv For system investment cost, C ope The system operating cost;
the first constraint includes:
and (3) constraint of installed capacity:
wherein the content of the first and second substances,
is the upper limit of the machine set g,
is the installed upper limit of the wind power plant w,
is the installed upper limit of the photovoltaic power station p,
the installation upper limit of the energy storage equipment e;
and (3) new energy power generation ratio constraint:
wherein N is T Is a period of time, N WT For the total number of wind power plant equipment, N PV Is the total number of photovoltaic power plant devices, P WT For generating power for wind turbines, P PV Generating power for a photovoltaic power plant, N N Is the total number of nodes of the grid, rho New The proportion of the new energy to generate electricity,
predicting a curve for the load demand of the node i;
and (3) grid restraint:
F l，t ＝B l (θ Bgn，l，t -θ End，l，t )
-F l Max ≤F l，t ≤F l Max
-π≤θ i，t ≤π
wherein omega G，i Set of units, omega, being node i WT，i For a set of wind farms, Ω PV，i Set of photovoltaic power stations, omega ES，i Is a set of energy storage devices, P G，g，t Is the generated output of the unit g at the time t, P wT，w，t For the power generation output of the wind farm w at time t, P PV，p，t For the generated output of the photovoltaic power station p at the time t,
and
respectively the discharge power and the charge power of the energy storage device e, B l Is the susceptance of branch l; f l，t ，θ Bgn，l，t ，θ End，l，t The phase angles of the power flow, the head end and the tail end nodes of the branch 1 at the time t are theta i，t The phase angle of the node i;
the traditional unit operation simulation constraint:
0≤P G，gt ≤Q G，g
wherein the content of the first and second substances,
maximum rates of downward climbing and upward climbing of the unit g are respectively, and the upper formula is respectively the output and climbing constraints of the unit;
and (3) new energy output constraint:
0≤P WT，w，t ≤γ WT，w，t Q WT，w
0≤P PV，p，t ≤γ PV，p，t Q PV，p
wherein, γ WT，w，t Per unit output prediction curve and gamma for wind power plant omega PV，w，t The per-unit output prediction curve of the photovoltaic power station p is obtained;
energy storage operation restraint:
0≤S e，t ≤H e Q ES，e
wherein S is e，t The state of charge of the energy storage device e at time t;
respectively the charging efficiency and the discharging efficiency, H, of the energy storage device e e For the energy storage duration of the energy storage device e,
is the initial energy storage level of the energy storage device e;
system standby constraints:
wherein r is New ，r Load Respectively the new energy power generation and the load demand utilization rate.
3. The method of claim 2,
solving the low-carbon investment planning model, and outputting unit output, wind-solar output and branch power flow data;
and constructing a load side demand response model based on the unit output, the wind and light output and the branch power flow data.
4. The method of claim 1, wherein the load side demand response model comprises: a second objective function targeting a minimum sum of the load-side carbon emission cost and the demand response cost, and a second constraint condition corresponding to the second objective function;
the second objective function is such that,
wherein, C CE，i，t Cost of carbon emissions for node i at time t, C DR In order to meet the unit cost of demand response,
respectively the load up-regulation power and the load down-regulation power of the node i at the moment t;
the second constraint includes:
and (3) load adjustment constraint:
wherein D is DR，i，t The load demand after the node i responds at the time t;
carbon emissions are constrained by the equation:
E i，t ＝I N，i，t D DRi，t
I L，l，t ＝I N，i，t ，l∈Ω i-
wherein, I N，i，t Is the carbon potential of node I at time t, I L，i，t Carbon flow density at node l at time t, I G，g，t Carbon emission intensity for coal-fired unit g, I WT，W，t Carbon emission for wind farm wStrength, I PV，P，t Is the carbon emission intensity of the photovoltaic power plant p.
5. The method of claim 1, wherein solving the two-tier low-carbon planning model and outputting a low-carbon planning result comprises:
solving the low-carbon investment planning model, and outputting unit output, wind-solar output and branch power flow data;
judging whether to perform power demand response or not based on the unit output, the wind-solar output and the branch power flow data to obtain a judgment result;
and outputting a low-carbon planning result according to the judgment result.
6. The method of claim 5, wherein outputting a low carbon planning result according to the determination result comprises:
if the judgment result is that demand response is carried out, solving the demand response model based on the unit output, the wind and light output and the branch power flow data to obtain optimized and adjusted load data, inputting the optimized and adjusted load data into an investment planning model and solving again to output an optimal planning result;
otherwise, directly outputting the investment planning result with the lowest sum of the system investment cost and the operation cost as a low-carbon planning result.
7. The method of claim 4, wherein the carbon emission cost is
Wherein E is i，t Carbon emission at a node i at time t; c CE，1 、C CE，2 、C CE，3 、C CE，4 The unit cost for the step carbon emission; e Bnd，1 、E Bnd，2 、E Bnd，3 Is the boundary amount of the carbon emission price interval.
8. The method of claim 5, wherein solving the low carbon investment planning model comprises:
inputting input parameters of the low-carbon investment planning model;
the input parameters comprise planning parameters, line parameters, unit parameters, a wind and light prediction curve, a load prediction curve and a carbon emission coefficient.
9. A power system low carbon planning device considering carbon emission flow is characterized by comprising:
the building module is used for building a double-layer low-carbon planning model based on a pre-built low-carbon investment planning model and a pre-built load side demand response model;
and the solving module is used for solving the double-layer low-carbon planning model and outputting a low-carbon planning result.
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| CN115907155B (en) * | 2022-11-22 | 2023-07-18 | 南方电网能源发展研究院有限责任公司 | Generator set planning method and device for introducing carbon emission cost |
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