CN108985532B - Network source load scheduling evaluation system and method based on carbon emission - Google Patents

Network source load scheduling evaluation system and method based on carbon emission Download PDF

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CN108985532B
CN108985532B CN201710406692.3A CN201710406692A CN108985532B CN 108985532 B CN108985532 B CN 108985532B CN 201710406692 A CN201710406692 A CN 201710406692A CN 108985532 B CN108985532 B CN 108985532B
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蒋传文
胡静哲
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Abstract

A network source load scheduling evaluation system and method based on carbon emission are disclosed, wherein basic information of a power grid, basic information of a power supply and basic information of a load of a power system are collected firstly, then a price demand response model, an excitation demand response model and a network source load coordination scheduling model are established, a scheduling strategy set is obtained by solving through an NSGA-II algorithm, and then a complex power flow tracking algorithm is adopted to calculate the carbon emission amount of each node and branch in the scheduling strategy set; and finally, calculating economic indexes and environmental indexes for the scheduling strategy set, establishing a network source load scheduling index system, realizing the scheduling and interaction effect of comprehensively evaluating network source load coordination scheduling from the aspects of economy and environment, providing more comprehensive data support for scheduling evaluators, including two indexes of a power side and a load side, and clearly reflecting the contribution degree of the power side and the load side to the scheduling strategy.

Description

Network source load scheduling evaluation system and method based on carbon emission
Technical Field
The invention relates to a technology in the field of electric power, in particular to a system and a method for network source load scheduling evaluation based on carbon emission.
Background
With the increasing concern of energy problems and climate change problems, the realization of low-carbon development and the reduction of excessive consumption of fossil energy are gradually common targets of various countries and industries. With the development of large-scale renewable energy networking and demand response technologies, the load side is no longer used as a rigid power receiving end, but gradually develops into a flexible load which can be scheduled by a power supply network, so that network-source-load, namely, power grid-power supply-load coordination scheduling is a necessary trend of future power grid development.
At present, an evaluation method capable of comprehensively evaluating the low-carbon benefits generated by network-source-load coordinated scheduling does not exist, and the evaluation of the network-source-load coordinated scheduling is mainly focused on the aspect of economic benefits.
Disclosure of Invention
The invention provides a network source load scheduling evaluation system and method based on carbon emission, aiming at the defects that the evaluation method of the prior art on the carbon emission is single, the system index is lacked, the influence of reactive power on the carbon emission is ignored, the comprehensive index of the correlation and difference between the carbon emission at the user side is not measured, the regional carbon emission index at the power supply side is not measured, the correlation index of the carbon emission and the cost is not measured, and the like.
The invention is realized by the following technical scheme:
the invention relates to a network source load scheduling evaluation system based on carbon emission, which comprises: information acquisition module, scheduling module, carbon flow track module and index evaluation module, wherein: the information acquisition module is connected with a power grid and acquires network structure and operation information, the scheduling module obtains a scheduling strategy set through an NSGA-II algorithm and is respectively connected with the carbon flow tracking module and the index evaluation module and transmits scheduling strategy set information, the carbon flow tracking module is connected with the index evaluation module and obtains and outputs carbon flow information through a complex power flow tracking algorithm, and the index evaluation module outputs various indexes.
The network source load scheduling evaluation method of the system comprises the steps of firstly collecting basic information of a power grid, basic information of a power supply and basic information of loads of a power system, then establishing a price demand response model, an excitation demand response model and a network source load coordination scheduling model, solving through an NSGA-II algorithm to obtain a scheduling strategy set, and then calculating the carbon emission of each node and branch in the scheduling strategy set by adopting a complex power flow tracking algorithm; and finally, calculating the economic index and the environmental index of the scheduling strategy set.
The price demand response model is
Figure BDA0001311107580000021
Wherein: cPFor electricity charges after load transfer, DPnew，t＝DPold，t+dup，t+ddown，t，λtIs the time of use electricity price at time t.
The excitation demand response model is
Figure BDA0001311107580000022
Wherein: dI，t＝DInew，t-DIold，t，CIIs the load shedding compensation cost, gamma unit load shedding compensation cost, dI，tThe cutting load at time t.
The network source load coordination scheduling model is
Figure BDA0001311107580000023
Wherein: f. of1To coordinate scheduling costs, CGIn order to reduce the running cost of the conventional unit,
Figure BDA0001311107580000024
egen，irepresents the carbon emission, P, of the conventional unit ii，tThe output of the conventional unit i at the time t is shown, and NG shows the number of the conventional units.
The carbon emission is obtained by the following steps:
1) computing node injected power
Figure BDA0001311107580000025
Wherein: siInjecting power for the node i; sjiIs the complex power of line j-i; sGen，iIs the power injected directly into the i node by the generator;
2) calculating the injection power vector S ═ H of each node-1SGenWherein:
Figure BDA0001311107580000026
SGenthe output vector of each generator of the system is taken as the output vector;
3) calculating carbon emissions for node k
Figure BDA0001311107580000027
And carbon emissions on lines p-q
Figure BDA0001311107580000028
The economic indicators comprise: scheduling cost, carbon emission cost fraction, load cost fraction, and power supply cost fraction.
The scheduling cost Cm＝f1 mCarbon emission cost ratio
Figure BDA0001311107580000029
Ratio of load cost
Figure BDA00013111075800000210
Power supply cost ratio cS，m＝1-cL，m。
The environment indexes comprise a load side environment index and a power supply side environment index.
The load side environmental indexes comprise: maximum load carbon emission
Figure BDA0001311107580000031
Carbon emission ratio at maximum load
Figure BDA0001311107580000032
Mean value of carbon emissions loaded
Figure BDA0001311107580000033
Standard deviation of carbon emission under load
Figure BDA0001311107580000034
And line carbon emission losses
Figure BDA0001311107580000035
The power supply side environment indexes comprise: maximum regional carbon emission
Figure BDA0001311107580000036
Maximum area carbon emission ratio
Figure BDA0001311107580000037
Regional carbon emission mean
Figure BDA0001311107580000038
And regional carbon emission standard deviation
Figure BDA0001311107580000039
Drawings
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a schematic diagram of the system of the present invention;
FIG. 3 is an example baseline load curve;
fig. 4 is an embodiment scheduling policy set pareto.
Detailed Description
As shown in fig. 1, the network resource load scheduling evaluation method in this embodiment includes the following steps:
1) the IEEE30 system was used as the detection system, and the reference load curve for one day is shown in fig. 3. The generator carbon emission intensity (t/MW) is shown in Table 1.
TABLE 1
Generator 1 Generator 2 Generator 3 Generator 4 Generator 5 Generator 6
0.95 0.5 1.06 0.95 1.06 1.06
2) And establishing a price demand response model and an excitation demand response model.
3) And establishing a network source load coordination scheduling model, and solving through an NSGA-II algorithm to obtain a scheduling strategy set, wherein the pareto frontier of the scheduling strategy set is shown in figure 4.
4) And calculating the carbon emission of each node and branch in the scheduling strategy set by adopting a complex power flow tracking algorithm.
5) Taking the scheduling policy (65017$, 3504t) as an example, the generator region: the 1, 2, 3 and 4 machine sets belong to the area 1; and 5, 6, the unit belongs to the area 2, and the economic index and the environmental index of the unit are calculated.
The economic indicators are shown in table 2.
TABLE 2
Cost of dispatch Carbon emission cost ratio Ratio of load cost Power supply cost ratio
2709.051283 0.160721412 1.097831888 0.839278588
The load side environmental index is shown in table 3.
TABLE 3
Figure BDA0001311107580000041
The power source side environment index is shown in table 4.
TABLE 4
Maximum regional carbon emission Maximum area carbon emission ratio Regional carbon emission mean
103.7657947 2.412694891 73.38702433
Compared with the prior art, the network source load dispatching index system is established, the dispatching and interaction effects of comprehensive evaluation of network source load coordinated dispatching in the aspects of economy and environment are achieved, more comprehensive data support can be provided for dispatching evaluation personnel, the power supply side and the load side are included, and the contribution degree of the power supply side and the load side to the dispatching strategy can be clearly reflected.
The foregoing embodiments may be modified in many different ways by those skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

Claims (8)

1. A network source load scheduling evaluation method of a network source load scheduling evaluation system based on carbon emission is characterized in that the network source load scheduling evaluation system comprises: information acquisition module, scheduling module, carbon flow track module and index evaluation module, wherein: the information acquisition module is connected with a power grid and acquires network structure and operation information, the scheduling module obtains a scheduling strategy set through an NSGA-II algorithm and is respectively connected with the carbon flow tracking module and the index evaluation module and transmits scheduling strategy set information, the carbon flow tracking module is connected with the index evaluation module and obtains and outputs carbon flow information through a complex power flow tracking algorithm, and the index evaluation module outputs various indexes;
the network source load scheduling evaluation method comprises the steps of firstly collecting basic information of a power grid, basic information of a power supply and basic information of a load of a power system, then establishing a price demand response model, an excitation demand response model and a network source load coordination scheduling model, solving through an NSGA-II algorithm to obtain a scheduling strategy set, and then calculating the carbon emission of each node and branch in the scheduling strategy set by adopting a complex power flow tracking algorithm; and finally, calculating the economic index and the environmental index of the scheduling strategy set.
2. The carbon emission-based grid source load scheduling evaluation method according to claim 1, wherein the price demand response model is
Figure FDA0002955815750000011
Wherein: cPFor electricity charges after load transfer, DPnew,t＝DPold,t+dup,t+ddown,t，λtIs the time of use electricity price at time t.
3. The carbon emission-based grid source load scheduling evaluation method according to claim 2, wherein the excitation demand response model is
Figure FDA0002955815750000012
Wherein: dI,t＝DInew,t-DIold,t，CIIs the load shedding compensation cost, gamma unit load shedding compensation cost, dI,tThe cutting load at time t.
4. The carbon emission-based grid source load scheduling evaluation method according to claim 3, wherein the grid source load coordination scheduling model is
Figure FDA0002955815750000013
Wherein: f. of1To coordinate scheduling costs, CGIn order to reduce the running cost of the conventional unit,
Figure FDA0002955815750000014
egen,irepresents the carbon emission, P, of the conventional unit ii,tThe output of the conventional unit i at the time t is shown, and NG shows the number of the conventional units.
5. The method for evaluating carbon emission-based grid source load scheduling as claimed in claim 4, wherein the carbon emission is obtained by the following steps:
1) computing node injected power
Figure FDA0002955815750000021
Wherein: siInjecting power for the node i; sjiIs the complex power of line j-i; sGen,iIs the power injected directly into the i node by the generator;
2) calculating the injection power vector S ═ H of each node-1SGenWherein:
Figure FDA0002955815750000022
SGenthe output vector of each generator of the system is taken as the output vector;
3) calculating carbon emissions for node k
Figure FDA0002955815750000023
And carbon emissions on lines p-q
Figure FDA0002955815750000024
6. The carbon emission-based grid source load scheduling evaluation method according to claim 5, wherein the economic indicators comprise: scheduling cost, carbon emission cost fraction, load cost fraction, and power supply cost fraction.
7. The method as claimed in claim 6, wherein the scheduling cost C is a scheduling costm＝f1 mCarbon emission cost ratio
Figure FDA0002955815750000025
Ratio of load cost
Figure FDA0002955815750000026
Power supply cost ratio cS,m＝1-cL,m。
8. The carbon emission-based grid source load scheduling evaluation method according to claim 1, wherein the environmental indicators include a load-side environmental indicator and a power-supply-side environmental indicator, wherein: the load-side environmental index includes: maximum load carbon emission
Figure FDA0002955815750000027
Carbon emission ratio at maximum load
Figure FDA0002955815750000028
Mean value of carbon emissions loaded
Figure FDA0002955815750000029
Standard deviation of carbon emission under load
Figure FDA00029558157500000210
And line carbon emission losses
Figure FDA00029558157500000211
The power supply side environmental indexes include: maximum regional carbon emission
Figure FDA00029558157500000212
Maximum area carbon emission ratio
Figure FDA00029558157500000213
Regional carbon emission mean
Figure FDA00029558157500000214
And regional carbon emission standard deviation
Figure FDA0002955815750000031
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