CN115630743A - Carbon-reduction micro-grid day-ahead energy optimization method based on source network load storage interaction - Google Patents
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Abstract
The invention discloses a carbon reduction micro-grid day-ahead energy optimization method based on source network load storage interaction. According to the carbon-reducing micro-grid day-ahead energy optimization method based on the source network charge-storage interaction, the source network power supply information corresponding to the designated power utilization area and the information such as the power consumption and the production capacity corresponding to the designated power utilization area are obtained, so that the area power utilization stability weight, the source network power supply type carbon reduction weight, the source network power supply energy storage carbon reduction weight and the source network power supply line carbon reduction weight are set, the comprehensive carbon reduction weight factor corresponding to each source network power supply end is obtained through comprehensive analysis, the optimal carbon-reducing power generation mode corresponding to the designated power utilization area is output, the problem that the carbon-reducing optimization degree of the power generation side in the prior art can not meet the carbon-reducing optimization requirement is effectively solved, the multi-dimensional analysis of the carbon-reducing optimization of the power generation side is achieved, the carbon-reducing optimization effect of the power generation side is greatly improved, and the power supply stability hidden danger and the power supply safety hidden danger of the power grid are avoided to the greatest extent.
Description
Technical Field
The invention belongs to the technical field of power grid carbon reduction optimization management, and relates to a carbon reduction micro-grid energy optimization method before day based on source grid load storage interaction.
Background
With the development and progress of the society, the demand for electric power also shows a trend of straight rising, and under the background, the carbon emission of electric power production also keeps rising, and certain interference is caused to the environment, and especially, the power generation mode of non-clean energy such as firepower is still used as the main power generation mode, so that carbon reduction optimization is urgent.
The main influence factors of the carbon emission in the power production comprise emission factors, energy structures, power structures and other aspects, and the carbon reduction optimization for the power production is mainly concentrated on the power utilization side at present, namely, the carbon reduction optimization is mainly used for reducing the power consumption to control the generated energy, so that the carbon reduction optimization is realized, the optimization degree of the power generation side obviously does not meet the carbon reduction optimization requirement, and the carbon reduction optimization requirement is embodied in the following layers:
1. at present, the carbon reduction optimization level of the power generation side is mainly focused on an energy use level, namely the use amount of clean power generation energy is increased and the use amount of non-clean energy such as coal is reduced, but the use environment, the use scene and the like of the clean energy are obviously higher than those of the non-clean energy, the large-scale replacement cannot be realized, the carbon reduction optimization effect of the power generation side cannot be improved, and the power supply stability and the power supply potential safety hazard are increased;
2. generally, a mode that multi-path power supply is needed for power generation in one region, namely a single power generation mode may not meet power supply requirements, wherein a power generation distribution problem is involved, carbon emission of different power generation modes is obviously different, for example, the carbon emission of wind power generation is obviously lower than that of thermal power generation, and the analysis of the power distribution problem on the power generation side at present is mainly based on the power generation capacity and the power generation cost level without integrating carbon emission factors, so that the rationality and feasibility of power generation distribution are insufficient, and the carbon emission in the power generation process cannot be reduced;
3. when current when carrying out the analysis to the electricity generation side, do not combine the power consumption steady state of power consumption side to carry out the analysis, but only according to the economic condition of power consumption side, also do not combine the loss of different power generation modes and the carbon emission problem in the transmission and distribution lines simultaneously, the analysis foundation is comparatively unilateral, has certain limitation, can't improve the reliability and the precision of electric wire netting operation carbon reduction optimization analysis result, also can't provide clear direction for the carbon reduction optimization in the electric wire netting operation.
Disclosure of Invention
In view of this, in order to solve the problems proposed in the background art, a method for optimizing the energy before day of the carbon-reduction microgrid based on the source network load storage interaction is proposed;
the purpose of the invention can be realized by the following technical scheme:
the invention provides a carbon-reduction micro-grid day-ahead energy optimization method based on source network load storage interaction, which comprises the following steps:
firstly, acquiring power supply information of an area source network: acquiring corresponding source network power supply information in a specified power utilization area, wherein the source network power supply information is power supply amount, power generation raw material usage amount and power supply parameters corresponding to each source network power supply end in each month in a set period, and the source network power supply ends are sequentially numbered as 1,2,... I,. N according to a set sequence;
secondly, acquiring regional power grid information: obtaining the rated power consumption currently set in the appointed power utilization area and recording as D Rated value Meanwhile, acquiring the corresponding electricity consumption and production of the designated electricity utilization area in each month in the set period;
thirdly, setting a region power utilization stability weight: setting a regional power utilization stability weighting factor based on the power consumption and the production amount of the designated power utilization region corresponding to each month in the set period, and recording as epsilon;
fourthly, setting the carbon reduction weight of the power supply type of the source network: extracting power supply types from power supply parameters corresponding to the power supply ends of the source networks, further setting carbon subtraction weight factors corresponding to the power supply types of the power supply ends of the source networks, and recording the weight factors as eta i I is denoted as source net power supply end number, i =1,2.
Fifthly, setting the weight of carbon reduction in power supply and energy storage of the source network: extracting the power generation amount and the power supply amount corresponding to each month of each power supply end of the source network in a set period, thereby setting the weight factor of energy storage and carbon reduction corresponding to each power supply end of the source network and recording the weight factor as tau i ；
Sixthly, carbon reduction weight setting of a source network power supply line: extracting the length of the power supply line and the corresponding operating power and number of various devices arranged in the power supply line from the power supply parameters corresponding to the power supply ends of the source networks, thereby setting the carbon reduction weight factor of the power supply line corresponding to the power supply end of each source network and recording the weight factor as mu i ；
And seventhly, performing source network power supply carbon reduction optimization analysis: and performing power supply carbon reduction optimization analysis on the specified power utilization area to obtain an optimal carbon reduction power generation mode corresponding to the specified power utilization area, and feeding back the optimal carbon reduction power generation mode to a power generation management center corresponding to the specified power utilization area.
Preferably, the power supply parameters corresponding to the power supply terminals of each source network specifically include a power supply type, a number of power supply units, a model of each power supply unit, a set power supply amount of each power supply unit, a length of a power supply line, a model of the power supply line, and corresponding operating powers of various devices and corresponding numbers of various devices installed in the power supply line.
Preferably, the performing regional power utilization stabilization weight factor setting includes the following steps:
comparing the power consumption corresponding to each month in a set period of the designated power consumption area, screening out the highest power consumption and the lowest power consumption, calculating the average power consumption corresponding to the designated power consumption area by an average value calculation method, and designating the designated power consumption areaThe highest electricity consumption, the lowest electricity consumption and the average electricity consumption corresponding to the electricity utilization areas are respectively marked as D max 、D min And
comparing the production capacity of the designated electricity utilization area in each month in a set period, screening out the highest production capacity and the lowest production capacity, and respectively recording the maximum production capacity and the lowest production capacity as L max And L min ；
By analysis of formulas
Analyzing to obtain a power utilization stability weighting factor epsilon corresponding to the designated power utilization area, wherein a1, a2, a3 and a4 are respectively expressed as correction coefficients corresponding to set maximum power utilization difference, minimum power utilization difference, rated power utilization difference and production difference, and delta D 0 、ΔD 1 And Δ L are respectively expressed as a set allowable maximum power consumption difference, an allowable minimum power consumption difference, and an allowable production float value, and e is a natural number.
Preferably, the setting of the carbon-reduction weight factor of the power supply type corresponding to the power supply terminal of each source network comprises the following steps:
extracting the power supply type corresponding to each source network power supply end, thereby locating the unit power generation carbon emission amount of the power supply type corresponding to each source network power supply end from the information base and recording the unit power generation carbon emission amount as C i ；
Extracting the generated energy and the usage amount of the power generation raw materials corresponding to each month of each source network power supply end in a set period, calculating the average generated energy and the average usage amount of the power generation raw materials corresponding to each source network power supply end through an average value, and recording the average generated energy corresponding to each source network power supply end as F i ；
Based on the average power generation raw material usage amount corresponding to each source network power supply end, locating the theoretical power generation amount corresponding to the average power generation raw material usage amount of each source network power supply end from the information base, and recording the theoretical power generation amount as F i ′；
Extracting the number of power supply units and the model number of each power supply unit corresponding to each power supply end of the power supply network, and determining the model number of each power supply unit corresponding to each power supply end of the power supply network based on the power supply end of each power supply networkLocating power supply reference carbon emission amount C corresponding to each power supply unit model in each source network power supply end from the information base' ir R denotes a power supply unit number, r =1,2.. G;
extracting the set power supply quantity corresponding to each power supply unit of each power supply end of the power supply network, and recording as G i r ；
Based on analytical formulae
Analyzing to obtain a carbon reduction weight factor eta of the power supply type corresponding to each power supply end of the source network i A5, a6, a7, a8 are respectively expressed as the ratio weight corresponding to the set carbon emission amount, the power generation conversion rate, the number of power supply units, and the carbon emission amount of the power supply units, k 0 i 、k 1 i Respectively representing the reference carbon rejection ratio, the reference power generation conversion rate, M, corresponding to the set power supply type corresponding to the ith source network power supply terminal i Is the number of power supply unit groups corresponding to the power supply end of the ith source network, M' i And the number of the carbon-reduction reference power supply sets corresponding to the power supply type of the power supply end of the set ith source network is determined.
Preferably, the setting of the energy storage and carbon reduction weight factor corresponding to each power supply end of the power supply network comprises the following steps:
and subtracting the generated energy corresponding to each month of each power supply end of the power supply network in the set period from the power consumption corresponding to each month of the designated power consumption area in the set period to obtain the stored power corresponding to each month of each power supply end of the power supply network in the set period, and recording the stored power as K i t And t is a month number, and t =1,2
According to analytical formulae
Analyzing to obtain the energy storage carbon reduction weight factor tau of the power supply end of each source network i ，ψ i 、ζ i Respectively expressed as a set energy storage evaluation correction coefficient, an energy storage difficulty coefficient, K 'corresponding to the ith source network power supply end' i And storing the reference electric quantity corresponding to the set power supply end of the ith power supply network.
Preferably, the setting of the carbon-reduction weight factor of the power supply line corresponding to the power supply end of each source network comprises the following steps:
accumulating to obtain the accumulated operating power of the power supply line corresponding to each source network power supply end, and recording as P, based on the operating power corresponding to each type of equipment and the corresponding number of each type of equipment in the power supply line corresponding to each source network power supply end i ；
By analytical formulae
Analyzing to obtain the running power carbon-reduction weight factor of the power supply circuit corresponding to the power supply end of each source network
P i ' respectively representing the carbon emission factor of the power supply type corresponding to the set ith source network power supply terminal and the carbon emission amount allowed by the operation of the equipment;
extracting the model of the power supply line corresponding to each power supply end of the source network, and positioning the power consumption of the unit power supply distance of the power supply line model corresponding to each power supply end of the source network from the information base;
extracting the length of a power supply line corresponding to each source network power supply end, and calculating the theoretical power loss corresponding to each source network power supply end by the theoretical power loss calculation formula of theoretical power loss = power supply line length multiplied by unit power supply distance power loss plus compensation power loss, and recording as S i ；
Extracting the power generation amount and the power supply amount of each source network power supply end in each month in a set period, obtaining the power generation loss amount of each source network power supply end in each month in the set period by making a difference, further obtaining the average power loss amount corresponding to each source network power supply end by calculating in a mean value calculation mode, and recording as S' i ；
By analytical formulae
Analyzing to obtain loss weight factors omega of corresponding power supply lines of power supply ends of each source network i σ is the estimated correction coefficient for line loss, Δ S i The allowable loss difference of the power supply type corresponding to the power supply end of the set ith source network is set;
and analyzing and obtaining the carbon reduction weight factor of the power supply line corresponding to the power supply end of each source network based on the running power carbon reduction weight factor and the loss weight factor of the power supply line corresponding to the power supply end of each source network.
Preferably, the specific calculation formula of the carbon-reduction weight factor of the power supply line corresponding to the power supply end of each source network is
Wherein b1 and b2 respectively represent carbon reduction weight factors corresponding to set line operation and line loss.
Preferably, before performing power supply carbon reduction optimization analysis on the specified power utilization area, the method further comprises analyzing the corresponding comprehensive carbon reduction weight of each power supply terminal of the power supply network, and the specific analysis process is as follows:
substituting the carbon reduction weight factor of the power supply type, the energy storage carbon reduction weight factor and the power supply line carbon reduction weight factor corresponding to the power supply end of each source network into an analysis formula
In the method, the comprehensive carbon-reducing weight factor lambda corresponding to each power supply terminal of the source network is obtained through analysis i And phi 1, phi 2 and phi 3 respectively represent compensation factors corresponding to the set carbon reduction of the power supply type, the carbon reduction of the stored energy and the carbon reduction of the power supply line.
Preferably, the power supply carbon reduction optimization analysis is performed on the specified power utilization area, and the specific analysis process includes the following steps:
extracting unit carbon discharge amount of power supply types corresponding to the power supply terminals of the source networks in the specified power utilization area and power generation amount corresponding to the power supply terminals of the source networks in each month in a set period, and screening out the maximum power generation amount corresponding to the power supply terminals of the source networks from the unit carbon discharge amount and marking the maximum power generation amount as F max i By means of a calculation formula
R 0 Calculating the comprehensive carbon emission amount of power generation corresponding to the specified power utilization area for the set allowable error carbon emission amount;
importing the comprehensive carbon emission amount of power generation corresponding to the specified power utilization area, the comprehensive carbon reduction weight factor corresponding to each source network power supply end in the specified power utilization area and the unit carbon emission amount of the power supply type corresponding to each source network power supply end into a power supply carbon reduction preference model, and outputting the target power supply amount corresponding to each source network power supply end;
and obtaining the expected generated energy corresponding to each source network power supply end in the specified power utilization area based on the target power supply amount corresponding to each source network power supply end, and using the expected generated energy as the optimal carbon reduction power generation mode corresponding to the specified power utilization area.
Preferably, the power supply carbon reduction preference model is specifically expressed as
Q represents a power supply carbon reduction value index, f i A target power supply amount corresponding to the power supply end of the ith source network, (f) 1 +f′ 1 )+(f 2 +f′ 2 )....+(f i +f′ i )+....(f n +f′ n )＝D Rated value +D Compensation ，D Compensation To compensate for the set power consumption, f i ' is the predicted power loss of the power supply line corresponding to the power supply end of the set ith power supply network, and x is the set carbon removal optimization correction factor.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a carbon-reduction micro-grid day-ahead energy optimization method based on source network charge storage interaction, which comprises the steps of obtaining corresponding source network power supply information in a specified power utilization area and corresponding information such as power consumption and production capacity of the specified power utilization area, and accordingly setting a regional power utilization stability weight, a source network power supply type carbon reduction weight, a source network power supply energy storage carbon reduction weight and a source network power supply line carbon reduction weight, comprehensively analyzing to obtain comprehensive carbon reduction weight factors corresponding to each source network power supply end, and further outputting an optimal carbon reduction power generation mode corresponding to the specified power utilization area, so that on one hand, the problem that the carbon reduction optimization degree of the power generation side in the prior art can not meet the carbon reduction optimization requirement is effectively solved, and through analyzing the power supply types, the energy storage conditions and the power supply line conditions of different source network power supply ends, multi-dimensional analysis of carbon reduction optimization of the power generation side is realized, further the carbon reduction optimization effect of the power generation side is greatly improved, and the hidden danger of power supply stability and the hidden danger of power supply of the power grid are avoided to the greatest extent; on the other hand, by setting the carbon reduction weight in each power supply end of the source network, the reasonability, the scientificity and the feasibility of power generation distribution of the designated power utilization area are effectively improved, the carbon emission in the power generation process of each source network is reduced as much as possible, the limitation and the one-sidedness in the current analysis mode are broken through multi-dimensional analysis, the reliability and the accuracy of the carbon reduction optimization analysis result of the power grid operation are ensured, and the basis of definite direction and reliable decision is provided for the carbon reduction optimization in the power grid operation.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart illustrating the steps of the method of the present invention.
Detailed Description
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Referring to fig. 1, the invention provides a method for optimizing energy before day of a carbon-reduction microgrid based on source network load storage interaction, which comprises the following steps:
firstly, acquiring power supply information of an area source network: acquiring corresponding source network power supply information in a designated power utilization area, wherein the source network power supply information is power supply amount, power generation raw material usage amount and power supply parameters corresponding to each source network power supply end in each month in a set period, and the source network power supply ends are numbered as 1,2,... I,. N in sequence according to a set sequence;
specifically, the power supply parameters corresponding to the power supply end of each source network specifically include power supply type, number of power supply units, model of each power supply unit, set power supply amount of each power supply unit, length of a power supply line, model of the power supply line, corresponding operating power of various devices arranged in the power supply line, and corresponding number of various devices;
it should be noted that each power supply end of the power grid includes, but is not limited to, a fire power supply end, a photovoltaic power supply end, a hydro-energy power supply end, and a wind-energy power supply end;
secondly, acquiring regional power grid information: obtaining the rated power consumption currently set in the appointed power utilization area and recording as D Rated value Simultaneously acquiring the corresponding electricity consumption and the corresponding production of each month in a set period of the designated electricity utilization area;
thirdly, setting a region power utilization stability weight: setting a regional power utilization stability weighting factor based on the power consumption and the production quantity corresponding to each month in a set period of the specified power utilization region, and recording as epsilon;
exemplarily, the regional electric stability weight factor setting is performed, and the specific setting process includes the following steps:
comparing the power consumption corresponding to the appointed power consumption area in each month in a set period, screening out the highest power consumption and the lowest power consumption, calculating the average power consumption corresponding to the appointed power consumption area by an average value calculation method, and respectively recording the highest power consumption, the lowest power consumption and the average power consumption corresponding to the appointed power consumption area as D max 、D min And
comparing the production capacity of the designated electricity utilization area in each month in a set period, screening out the highest production capacity and the lowest production capacity, and respectively recording the maximum production capacity and the lowest production capacity as L max And L min ；
By analytical formulae
Analyzing to obtain a power utilization stability weighting factor epsilon corresponding to the designated power utilization area, wherein a1, a2, a3 and a4 are respectively expressed as correction coefficients corresponding to set maximum power utilization difference, minimum power utilization difference, rated power utilization difference and production difference, and delta D 0 、ΔD 1 And DeltaL is respectively expressed as a set allowable maximum power utilization difference, an allowable minimum power utilization difference and an allowable production floating value, and e is a natural number;
fourthly, carbon reduction weight setting of the power supply type of the source network: extracting power supply types from power supply parameters corresponding to the power supply ends of the source networks, further setting carbon subtraction weight factors corresponding to the power supply types of the power supply ends of the source networks, and recording the weight factors as eta i I is denoted as source net power supply end number, i =1,2.
Exemplarily, the carbon reduction weight factor of the power supply type corresponding to the power supply terminal of each source network is set, and the specific setting process includes the following steps:
extracting the power supply type corresponding to each source network power supply terminal, thereby locating the unit power generation carbon emission amount of the power supply type corresponding to each source network power supply terminal from the information base and recording the unit power generation carbon emission amount as C i ；
Extracting the power generation amount and the power generation raw material usage amount corresponding to each month of each source network power supply end in a set period, calculating the average power generation amount and the average power generation raw material usage amount corresponding to each source network power supply end through an average value, and recording the average power generation amount corresponding to each source network power supply end as F i ；
Based on the average power generation raw material usage amount corresponding to each source network power supply end, locating the theoretical power generation amount corresponding to the average power generation raw material usage amount of each source network power supply end from the information base, and recording the theoretical power generation amount as F i ′；
Extracting the number of power supply sets corresponding to the power supply terminals of each power supply networkAnd each power supply unit model number, and positioning a power supply reference exhaust carbon quantity, marked as C ', corresponding to each power supply unit model number in each power supply end of the source network from the information base based on each power supply unit model number corresponding to each power supply end of the source network' ir R denotes a power supply unit number, r =1, 2.... G;
extracting the set power supply quantity corresponding to each power supply unit from each power supply end of the power supply network, and recording as G i r ；
Based on analytical formulae
Analyzing to obtain the carbon reduction weight factor eta of the power supply type corresponding to each power supply end of the source network i A5, a6, a7, a8 are respectively expressed as the ratio weight corresponding to the set carbon emission amount of power generation, power generation conversion rate, number of power supply units and carbon emission amount of power supply units, k 0 i 、k 1 i Respectively representing the reference carbon rejection ratio, the reference power generation conversion rate, M, corresponding to the set power supply type corresponding to the power supply end of the ith source network i Is the number of power supply unit groups corresponding to the power supply end of the ith source network, M' i The number of the carbon reduction reference power supply sets corresponding to the set power supply type of the ith source network power supply end;
it should be noted that, the higher the power generation conversion rate, the lower the carbon emission, the more power supply units and the higher the power of the power supply units, the higher the energy consumption of the power supply units, and thus the higher the carbon emission;
fifthly, setting the weight of carbon reduction in power supply and energy storage of the source network: extracting the power generation amount and the power supply amount corresponding to each month of each power supply end of the source network in a set period, thereby setting the weight factor of energy storage and carbon reduction corresponding to each power supply end of the source network and recording the weight factor as tau i ；
Exemplarily, setting an energy storage and carbon reduction weight factor of each power supply end of the power supply network, wherein the specific setting process comprises the following steps:
and subtracting the generated energy corresponding to each month of each power supply end of the power supply network in the set period from the power consumption corresponding to each month of the designated power consumption area in the set period to obtain the stored power corresponding to each month of each power supply end of the power supply network in the set period, and recording the stored power as K i t And t is a month number, and t =1,2
Extracting the power generation amount corresponding to each month of each source network power supply end in a set period and the power consumption amount corresponding to each month of a designated power consumption area in the set period, and calculating the difference to obtain the corresponding stored power amount of each source network power supply end in each month of the set period and recording the difference as K i t And t is represented as a month number, and t =1,2
According to analytical formula
Analyzing to obtain the energy storage carbon reduction weight factor tau of the power supply end of each source network i ，ψ i 、ζ i Respectively expressed as a set energy storage evaluation correction coefficient, an energy storage difficulty coefficient, K 'corresponding to the ith source network power supply end' i And storing the electric quantity for the reference corresponding to the set ith power supply end of the source network.
In a specific embodiment, the energy storage modes include chemical energy storage, mechanical energy storage and electromagnetic energy storage, and the larger the capacity of the stored electric quantity is, the larger the generated energy of the power grid can be reduced, so that the carbon reduction effect can be realized, and especially for clean power generation energy such as wind power and photovoltaic, the more the stored electric energy is, the limitation in the power generation environment can be relieved, namely when the wind power is insufficient or the illumination is insufficient, the power supply can be ensured, and the electric power waste rate is reduced;
sixthly, carbon reduction weight setting of a source network power supply line: extracting the length of the power supply line and the corresponding operating power and number of various devices arranged in the power supply line from the power supply parameters corresponding to the power supply ends of the source networks, and setting the power supply end pairs of the source networksThe power supply line minus the carbon weight factor is recorded as mu i ；
Exemplarily, the setting of the energy storage and carbon reduction weight factor corresponding to the power supply terminal of each source network comprises the following steps:
accumulating to obtain the accumulated operating power of the power supply line corresponding to each source network power supply end, and recording as P, based on the operating power corresponding to each type of equipment and the corresponding number of each type of equipment in the power supply line corresponding to each source network power supply end i ；
By analysis of formulas
Analyzing to obtain the running power carbon-reduction weight factor of the power supply circuit corresponding to the power supply end of each source network
P i ' respectively representing the carbon emission factor of the power supply type corresponding to the set ith source network power supply terminal and the carbon emission amount allowed by the operation of the equipment;
it should be noted that, the operation of the device in the power supply end of the source network is taken as an example for one month, that is, the calculated carbon emission amount of the device in the power supply line corresponding to each power supply end of the source network in one month, and the allowed carbon emission amount of the device in operation is also taken as a reference period for one month;
extracting the model of the power supply line corresponding to each power supply end of the source network, and positioning the power consumption of the unit power supply distance of the power supply line model corresponding to each power supply end of the source network from the information base;
it should be noted that the power supply line model refers to the model of a power supply cable in the power supply line;
extracting the length of a power supply line corresponding to each source network power supply end, and calculating theoretical power loss corresponding to each source network power supply end through a theoretical power loss calculation formula, namely theoretical power loss = power supply line length x unit power supply distance power loss + compensation power loss, and recording the theoretical power loss as S i ；
Extracting the corresponding generated energy and power supply amount of each source network power supply end in each month in the set period, and obtaining the difference between the generated energy and the power supply amount of each source network power supply end in each month in the set periodCalculating the average power loss corresponding to each power supply end of the source network by means of mean value calculation, and recording as S' i ；
It should be noted that the power supply amount corresponding to each source network power supply end refers to the amount of power actually supplied to a specified power utilization area by each source network power supply end, and the power generation loss includes power transmission line loss and power distribution line loss, and belongs to comprehensive loss, which is expressed in order to simplify the present invention;
by analytical formulae
Analyzing to obtain loss weight factors omega of corresponding power supply lines of power supply ends of each source network i σ is the estimated correction coefficient of line loss, Δ S i The allowable loss difference of the power supply type corresponding to the power supply end of the set ith source network is set;
based on the running power carbon-reducing weight factor and the loss weight factor of the power supply circuit corresponding to the power supply end of each source network, analyzing the formula
Analyzing to obtain the weight factor mu of the carbon reduction of the power supply line corresponding to the power supply end of each source network i B1 and b2 respectively represent carbon reduction weight factors corresponding to set line operation and line loss;
and seventhly, performing source network power supply carbon reduction optimization analysis: and performing power supply carbon reduction optimization analysis on the specified power utilization area to obtain an optimal carbon reduction power generation mode corresponding to the specified power utilization area, and feeding back the optimal carbon reduction power generation mode to a power generation management center corresponding to the specified power utilization area.
Specifically, before performing power supply carbon reduction optimization analysis on the specified power utilization area, the method further comprises analyzing the corresponding comprehensive carbon reduction weight of each power supply end of the power supply network, wherein the specific analysis process is as follows:
extracting carbon reduction weight factors of power supply types, energy storage carbon reduction weight factors and power supply line carbon reduction weight factors corresponding to power supply terminals of each source network, and analyzing the weight factors by using an analysis formula
Analyzing to obtain the corresponding comprehensive carbon reduction weight factor lambda of each power supply end of each source network i Phi 1, phi 2 and phi 3 respectively represent compensation factors corresponding to carbon reduction of a set power supply type, energy storage carbon reduction and carbon reduction of a power supply circuit;
further, the power supply carbon reduction optimization analysis is carried out on the specified power utilization area, and the specific analysis process comprises the following steps:
a1, extracting unit carbon discharge amount of power supply types corresponding to each source network power supply end in a specified power utilization area and power generation amount corresponding to each month of each source network power supply end in a set period, and screening out maximum power generation amount corresponding to each source network power supply end from the unit carbon discharge amount and marking the maximum power generation amount as F max i By means of a calculation formula
R 0 Calculating the comprehensive carbon emission amount of power generation corresponding to the specified power utilization area for the set allowable error carbon emission amount;
a2, introducing the comprehensive carbon removal amount of power generation corresponding to the specified power utilization area, the comprehensive carbon reduction weight factor corresponding to each source network power supply end in the specified power utilization area and the unit carbon removal amount of the power supply type corresponding to each source network power supply end into a power supply carbon reduction preferred model, and outputting the target power supply amount corresponding to each source network power supply end, wherein the power supply carbon reduction preferred model is specifically represented as
Q represents a power supply carbon reduction value index, f i A target power supply amount corresponding to the power supply end of the ith source network, (f) 1 -f′ 1 )+(f 2 +-f′ 2 )....+(f i -f′ i )+....(f n -f′ n )＝D Rated value +D Compensation ，D Compensation To compensate for the set power consumption, f i The method comprises the following steps of setting predicted power consumption of a power supply line corresponding to a power supply end of an ith power supply network, and setting x as a set carbon-discharging optimization correction factor;
it should be noted that, the expected power consumption setting mode of the power supply line corresponding to each power supply end of the power supply network is as follows: the power generation amount and the power supply amount of each source network power supply end in each month in a set period are subjected to difference to obtain the power generation loss amount of each source network power supply end in each month in the set period, the maximum power generation loss amount corresponding to each source network power supply end is screened out and is used as the predicted power loss amount of the power supply line corresponding to each source network power supply end;
it should be noted that 1 *f 1 *C 1 +λ 2 *f 2 *C 2 +...λ i *f i *C i +...+λ n *f n *C n The larger the value is, the higher the comprehensive carbon emission amount of each source network power supply end corresponding to the specified power utilization area is, the lower the power supply carbon reduction value corresponding to each source network power supply end is, otherwise, the higher the power supply carbon reduction value corresponding to each source network power supply end is, and the stronger the feasibility is;
and A3, obtaining the expected generated energy corresponding to each source network power supply end in the specified power utilization area based on the target power supply amount corresponding to each source network power supply end, and using the expected generated energy as the optimal carbon-reducing power generation mode corresponding to the specified power utilization area.
Understandably, the specific process for acquiring the expected generated energy corresponding to each power supply terminal of the power supply network in the designated power utilization area is as follows: and extracting target power supply amount corresponding to each source network power supply end of the specified power utilization area and predicted power loss amount of a power supply line corresponding to each source network power supply end, and calculating the predicted power generation amount corresponding to each source network power supply end of the specified power utilization area through a calculation formula, namely the predicted power generation amount = the target power supply amount + the predicted power loss amount + the set floating power amount.
According to the method and the device, the corresponding source network power supply information in the designated power utilization area and the corresponding power consumption, production and other information of the designated power utilization area are obtained, so that the regional power utilization stability weight, the source network power supply type carbon reduction weight, the source network power supply energy storage carbon reduction weight and the source network power supply line carbon reduction weight are set, the comprehensive carbon reduction weight factor corresponding to each source network power supply end is obtained through comprehensive analysis, the optimal carbon reduction power generation mode corresponding to the designated power utilization area is output, on one hand, the problem that the carbon reduction optimization degree of the power generation side in the prior art obviously cannot meet the carbon reduction optimization requirement is solved, on the other hand, the multi-dimensional analysis of the carbon reduction optimization of the power generation side is realized through analyzing the power supply types, the energy storage condition and the power supply line condition of different source network power supply ends, the carbon reduction optimization effect of the power generation side is greatly improved, and meanwhile, the power supply stability hidden danger and the power supply safety are avoided to the power grid to the greatest extent; on the other hand, by setting the carbon reduction weight in each power supply end of the source network, the reasonability, the scientificity and the feasibility of power generation distribution of the designated power utilization area are effectively improved, the carbon emission in the power generation process of each source network is reduced as much as possible, the limitation and the one-sidedness in the current analysis mode are broken through multi-dimensional analysis, the reliability and the accuracy of the carbon reduction optimization analysis result of the power grid operation are ensured, and the basis of definite direction and reliable decision is provided for the carbon reduction optimization in the power grid operation.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
1. A carbon reduction micro-grid day-ahead energy optimization method based on source network load storage interaction is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps of firstly, obtaining power supply information of an area source network: acquiring corresponding source network power supply information in a designated power utilization area, wherein the source network power supply information is power supply amount, power generation raw material usage amount and power supply parameters corresponding to each source network power supply end in each month in a set period, and the source network power supply ends are numbered as 1,2,... I,. N in sequence according to a set sequence;
secondly, acquiring regional power grid information: obtaining the rated power consumption currently set in the appointed power utilization area and recording as D Rated value Simultaneously acquiring the corresponding electricity consumption and the corresponding production of each month in a set period of the designated electricity utilization area;
thirdly, setting a regional power utilization stability weight: setting a regional power utilization stability weighting factor based on the power consumption and the production quantity corresponding to each month in a set period of the specified power utilization region, and recording as epsilon;
fourthly, carbon reduction weight setting of the power supply type of the source network: extracting power supply types from power supply parameters corresponding to the power supply ends of the source networks, further setting carbon subtraction weight factors corresponding to the power supply types of the power supply ends of the source networks, and recording the weight factors as eta i I denotes a source network power supply terminal number, i =1, 2.... N;
fifthly, setting the weight of carbon reduction in power supply and energy storage of the source network: extracting the generated energy and the power supply amount corresponding to each month of each power supply end of the source network in a set period, thereby setting the energy storage and carbon reduction weight factor corresponding to each power supply end of the source network and recording the weight factor as tau i ；
Sixthly, carbon reduction weight setting of a source network power supply line: extracting the length of the power supply line and the corresponding operating power and number of various devices arranged in the power supply line from the power supply parameters corresponding to the power supply ends of the source networks, setting the carbon reduction weight factor of the power supply line corresponding to the power supply end of each source network, and recording the weight factor as mu i ；
And seventhly, performing source network power supply carbon reduction optimization analysis: and performing power supply carbon reduction optimization analysis on the specified power utilization area to obtain an optimal carbon reduction power generation mode corresponding to the specified power utilization area, and feeding back the optimal carbon reduction power generation mode to a power generation management center corresponding to the specified power utilization area.
2. The method for optimizing the energy of the carbon-reducing microgrid before the day based on the source network load storage interaction is characterized in that: the power supply parameters corresponding to the power supply end of each source network specifically comprise power supply types, the number of power supply units, the types of the power supply units, the set power supply amount of each power supply unit, the length of a power supply line, the types of the power supply line, the corresponding operating power of various devices arranged in the power supply line and the corresponding number of the various devices.
3. The method for optimizing the energy of the carbon-reducing microgrid before the day based on the source network load storage interaction is characterized in that: the regional power utilization stabilization weight factor setting is carried out, and the specific setting process comprises the following steps:
comparing the power consumption corresponding to the appointed power consumption area in each month in a set period, screening out the highest power consumption and the lowest power consumption, calculating the average power consumption corresponding to the appointed power consumption area by an average value calculation method, and respectively recording the highest power consumption, the lowest power consumption and the average power consumption corresponding to the appointed power consumption area as D max 、D min And
comparing the production capacity of the designated electricity utilization area in each month in a set period, screening out the highest production capacity and the lowest production capacity, and respectively recording the maximum production capacity and the lowest production capacity as L max And L min ；
By analysis of formulas
Analyzing to obtain a power utilization stability weighting factor epsilon corresponding to the designated power utilization area, wherein a1, a2, a3 and a4 are respectively expressed as correction coefficients corresponding to set maximum power utilization difference, minimum power utilization difference, rated power utilization difference and production difference, and delta D 0 、ΔD 1 And Δ L are respectively expressed as a set allowable maximum power consumption difference, an allowable minimum power consumption difference, and an allowable production float value, and e is a natural number.
4. The method for optimizing the energy of the carbon-reducing microgrid before the day based on the source network load storage interaction is characterized in that: the method comprises the following steps of setting a carbon reduction weight factor of a power supply type corresponding to each power supply end of a source network, wherein the specific setting process comprises the following steps:
extracting the power supply type corresponding to each source network power supply terminal, thereby locating the unit power generation carbon emission amount of the power supply type corresponding to each source network power supply terminal from the information base and recording the unit power generation carbon emission amount as C i ；
Extracting the generated energy and the usage amount of the power generation raw materials corresponding to each month of each source network power supply end in a set period, calculating the average generated energy and the average usage amount of the power generation raw materials corresponding to each source network power supply end through an average value, and supplying power to each source networkThe average power generation amount corresponding to the end is recorded as F i ；
Based on the average power generation raw material usage amount corresponding to each source network power supply end, locating the theoretical power generation amount corresponding to the average power generation raw material usage amount of each source network power supply end from the information base, and recording the theoretical power generation amount as F i ′；
Extracting the number of power supply unit sets corresponding to each source network power supply end and each power supply unit model, and positioning power supply reference carbon emission quantity corresponding to each power supply unit model in each source network power supply end from the information base and recording the carbon emission quantity as C 'based on each power supply unit model corresponding to each source network power supply end' ir R denotes a power supply unit number, r =1, 2.... G;
extracting the set power supply quantity corresponding to each power supply unit of each power supply end of the power supply network, and recording as G i r ；
Based on analytical formulae
Analyzing to obtain the carbon reduction weight factor eta of the power supply type corresponding to each power supply end of the source network i A5, a6, a7, a8 are respectively expressed as the ratio weight corresponding to the set carbon emission amount, the power generation conversion rate, the number of power supply units, and the carbon emission amount of the power supply units, k 0 i 、k 1 i Respectively representing the reference carbon rejection ratio, the reference power generation conversion rate, M, corresponding to the set power supply type corresponding to the ith source network power supply terminal i The number of power supply units corresponding to the power supply terminal of the ith power supply network, M i ' the number of the carbon-reduction reference power supply machine sets corresponding to the set power supply type of the ith source network power supply end.
5. The method for optimizing the energy before the day of the carbon-reducing microgrid based on source network load storage interaction is characterized in that: the method comprises the following steps of setting energy storage and carbon reduction weight factors corresponding to power supply terminals of each source network, wherein the specific setting process comprises the following steps:
the generated energy corresponding to each month of each power supply end in the set period and the power consumption corresponding to each month of the designated power utilization area in the set period are differed to obtain the power consumption corresponding to each month of each power supply end in the set periodStores the quantity of electricity and marks as K i t And t is represented as a month number, and t =1,2
According to analytical formula
Analyzing to obtain the weight factor tau of the stored energy and the carbon reduction of the power supply end of each source network i ，ψ i 、ζ i Respectively representing the energy storage evaluation correction coefficient and the energy storage difficulty coefficient K 'corresponding to the set ith source network power supply end' i And storing the electric quantity for the reference corresponding to the set ith power supply end of the source network.
6. The method for optimizing the energy of the carbon-reducing microgrid before the day based on the source network load storage interaction is characterized in that: the method comprises the following steps of setting a carbon reduction weight factor of a power supply circuit corresponding to each power supply end of a power supply network, wherein the specific setting process comprises the following steps:
accumulating to obtain the accumulated operating power of the power supply line corresponding to each source network power supply end, and recording as P, based on the operating power corresponding to each type of equipment and the corresponding number of each type of equipment in the power supply line corresponding to each source network power supply end i ；
By analysis of formulas
Analyzing to obtain the running power carbon-reduction weight factor of the power supply circuit corresponding to the power supply end of each source network
P i ' respectively representing the carbon emission factor of the power supply type corresponding to the set ith source network power supply terminal and the carbon emission amount allowed by the operation of the equipment;
extracting the model of the power supply line corresponding to each power supply end of the source network, and positioning the power consumption of the unit power supply distance of the power supply line model corresponding to each power supply end of the source network from the information base;
extracting the length of a power supply line corresponding to each source network power supply end, and calculating theoretical power loss corresponding to each source network power supply end through a theoretical power loss calculation formula, namely theoretical power loss = power supply line length x unit power supply distance power loss + compensation power loss, and recording the theoretical power loss as S i ；
Extracting the corresponding generated energy and power supply amount of each source network power supply end in each month in a set period, obtaining the corresponding generated power loss amount of each source network power supply end in each month in the set period by making a difference, further obtaining the corresponding average loss electric quantity of each source network power supply end by calculating in a mean value calculation mode, and recording as S' i ；
By analytical formulae
Analyzing and obtaining loss weight factor omega of power supply circuit corresponding to each power supply end of each source network i σ is the estimated correction coefficient for line loss, Δ S i The allowable loss difference of the power supply type corresponding to the power supply end of the set ith source network is set;
and analyzing and obtaining the carbon reduction weight factor of the power supply line corresponding to each source network power supply end based on the running power carbon reduction weight factor and the loss weight factor of the power supply line corresponding to each source network power supply end.
7. The method for optimizing the energy of the carbon-reducing microgrid before the day based on the source network load storage interaction is characterized in that: the carbon reduction weight factor of the power supply circuit corresponding to each power supply end of the power supply network is specifically calculated by the formula
Wherein b1 and b2 respectively represent carbon reduction weight factors corresponding to set line operation and line loss.
8. The method for optimizing the energy of the carbon-reducing microgrid ahead of day based on source network load storage interaction of claim 4, wherein the method comprises the following steps: before carrying out power supply carbon reduction optimization analysis on the designated power utilization area, analyzing the corresponding comprehensive carbon reduction weight of each power supply end of the power grid, wherein the specific analysis process is as follows:
substituting the carbon reduction weight factors of the power supply types, the energy storage carbon reduction weight factors and the power supply line carbon reduction weight factors corresponding to the power supply ends of the source networks into an analysis formula
In the method, the comprehensive carbon-reducing weight factor lambda corresponding to each power supply terminal of the source network is obtained through analysis i Phi 1, phi 2 and phi 3 respectively represent compensation factors corresponding to carbon reduction of the set power supply type, energy storage and power supply line.
9. The method for optimizing the energy of the carbon-reduction microgrid ahead of day based on source network load storage interaction of claim 8, characterized in that: the method comprises the following steps of performing power supply carbon reduction optimization analysis on a specified power utilization area, wherein the specific analysis process comprises the following steps:
extracting unit carbon discharge amount of power supply types corresponding to each source network power supply end in the specified power utilization area and power generation amount corresponding to each source network power supply end in each month in a set period, screening out maximum power generation amount corresponding to each source network power supply end from the unit carbon discharge amount and recording the maximum power generation amount as F max i By means of a calculation formula
R 0 Calculating the comprehensive carbon emission amount of power generation corresponding to the specified power utilization area for the set allowable error carbon emission amount;
leading the comprehensive carbon removal amount of power generation corresponding to the specified power utilization area, the comprehensive carbon removal weight factor corresponding to each source network power supply end in the specified power utilization area and the unit carbon removal amount of the power supply type corresponding to each source network power supply end into a power supply carbon removal optimal model, and outputting the target power supply amount corresponding to each source network power supply end;
and obtaining the predicted generating capacity corresponding to each source network power supply end in the specified power utilization area based on the target power supply amount corresponding to each source network power supply end, and using the predicted generating capacity as the optimal carbon-reduction power generation mode corresponding to the specified power utilization area.
10. The method for optimizing the energy of the carbon-reduction microgrid ahead of day based on source network load storage interaction of claim 9, characterized in that: the power supply carbon reduction optimal model is specifically expressed as
Q represents a power supply carbon reduction value index, f i A target power supply amount corresponding to the power supply end of the ith source network, (f) 1 +f 1 ′)+(f 2 +f′ 2 )....+(f i +f i ′)+....(f n +f′ n )＝D Rated value +D Compensation ，D Compensation To compensate for the set power consumption, f i ' is the predicted power loss of the power supply line corresponding to the power supply end of the set ith power supply network, and x is the set carbon removal optimization correction factor.
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