CN116823020A - Comprehensive evaluation method for low-carbon operation of transformer area considering load side carbon reduction potential - Google Patents
Comprehensive evaluation method for low-carbon operation of transformer area considering load side carbon reduction potential Download PDFInfo
- Publication number
- CN116823020A CN116823020A CN202310600433.XA CN202310600433A CN116823020A CN 116823020 A CN116823020 A CN 116823020A CN 202310600433 A CN202310600433 A CN 202310600433A CN 116823020 A CN116823020 A CN 116823020A
- Authority
- CN
- China
- Prior art keywords
- carbon
- node
- low
- index
- area
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 316
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 209
- 238000011156 evaluation Methods 0.000 title claims abstract description 83
- 230000009467 reduction Effects 0.000 title claims abstract description 74
- 238000000034 method Methods 0.000 claims abstract description 99
- 230000008901 benefit Effects 0.000 claims abstract description 10
- 238000004146 energy storage Methods 0.000 claims description 47
- 230000005611 electricity Effects 0.000 claims description 25
- 239000011159 matrix material Substances 0.000 claims description 23
- 239000000243 solution Substances 0.000 claims description 23
- 230000006399 behavior Effects 0.000 claims description 20
- 230000004044 response Effects 0.000 claims description 20
- 238000004364 calculation method Methods 0.000 claims description 15
- 238000006467 substitution reaction Methods 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000010248 power generation Methods 0.000 claims description 8
- 230000005540 biological transmission Effects 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 7
- 230000008859 change Effects 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 230000000694 effects Effects 0.000 claims description 4
- 230000004907 flux Effects 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims description 3
- 239000007924 injection Substances 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 claims description 3
- 238000003672 processing method Methods 0.000 claims description 3
- 238000004445 quantitative analysis Methods 0.000 claims description 3
- 238000012546 transfer Methods 0.000 claims description 3
- 238000010276 construction Methods 0.000 description 12
- 238000012423 maintenance Methods 0.000 description 8
- 238000005265 energy consumption Methods 0.000 description 7
- 230000033228 biological regulation Effects 0.000 description 6
- 230000009466 transformation Effects 0.000 description 4
- 238000003763 carbonization Methods 0.000 description 3
- 238000007599 discharging Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000002776 aggregation Effects 0.000 description 2
- 238000004220 aggregation Methods 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 239000003245 coal Substances 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 239000000295 fuel oil Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000006386 neutralization reaction Methods 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- XOFYZVNMUHMLCC-ZPOLXVRWSA-N prednisone Chemical compound O=C1C=C[C@]2(C)[C@H]3C(=O)C[C@](C)([C@@](CC4)(O)C(=O)CO)[C@@H]4[C@@H]3CCC2=C1 XOFYZVNMUHMLCC-ZPOLXVRWSA-N 0.000 description 1
- 238000000513 principal component analysis Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a comprehensive evaluation method for low-carbon operation of a platform area considering load side carbon reduction potential, which comprises the following steps: step 1: calculating the node carbon potential of the node where the platform area is located; step 2: calculating the maximum carbon emission reduction capacity of the load side of the platform area; step 3: constructing a low-carbon platform region evaluation index; step 4: index pretreatment; step 5: determining comprehensive weights by adopting an index comprehensive weighting method; step 6: calculating an evaluation result by adopting a good-bad solution distance method; the method has the advantages of bringing the load side carbon reduction potential into an evaluation system, establishing low-carbon area evaluation indexes and establishing a comprehensive evaluation method.
Description
Technical Field
The invention belongs to the technical field of low-carbon operation of a low-voltage distribution network area of an electric power system, and particularly relates to a comprehensive evaluation method for low-carbon operation of an area taking load side carbon reduction potential into consideration.
Background
When the low-carbon evaluation of the transformer area is carried out, the key is that the carbon emission is calculated for the energy consumption condition of the user side, and the sources of various load carbons are clarified; the traditional method for calculating the carbon emission of the electric power system mainly considers from a macroscopic level, cannot realize accurate calculation of the carbon emission caused by electricity consumption of a user, such as a carbon emission flow (Carbon Emission Flow, CEF) theory, the carbon emission flow can be regarded as a virtual flow accompanying active power flow in an electric power network, carbon emission generated on a power generation side is transferred to the electricity consumption side, and node carbon potential of a system node can be obtained according to system power flow distribution of a certain time node, so that the carbon emission amount of the system is calculated; for example, the low-carbon demand response is used for guiding the electricity consumption behavior of the user, and the influence of the electricity consumption behavior of the user on carbon emission is considered from the user side; and then, a low-carbon effect evaluation system and a quantitative calculation method of the intelligent power distribution network are adopted; the method provides meaningful references for calculation of the carbon emission and the carbon reduction potential of the area, but a specific calculation method of the carbon emission flow of the area is not proposed; as the power grid gradually changes to low-carbonization, the evaluation of low-carbonization of the power grid gradually becomes a research hot spot, and the environmental benefit of the power distribution network is analyzed by the traditional method such as a combined evaluation method of using balanced principal component analysis; and for example, the advanced regional electric energy substitution potential is evaluated by using a better and worse solution distance method for improving the degree of association, and the evaluation method based on the cloud model and the probability degree is used for the comprehensive evaluation of the urban power distribution network, and then, if an evaluation index system considering three aspects of economy, energy consumption and environment is established, comprehensively evaluating the advantages and disadvantages of the distributed energy system scheme; the method evaluates the low-carbon characteristics of the power grid from different sides, but does not relate to the metering of carbon emission, and does not evaluate the carbon neutralization potential of the transformer area from the perspective of the load side; therefore, it is necessary to provide a comprehensive evaluation method for low-carbon operation of a low-carbon region, which takes the carbon reduction potential of the load side into an evaluation system, establishes a low-carbon region evaluation index and establishes a comprehensive evaluation method.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a comprehensive evaluation method for low-carbon operation of a low-carbon area, which is used for bringing the carbon reduction potential of a load side into an evaluation system, establishing low-carbon area evaluation indexes and establishing a comprehensive evaluation method.
The purpose of the invention is realized in the following way: a comprehensive evaluation method for low-carbon operation of a platform area considering load side carbon reduction potential comprises the following steps:
step 1: calculating the node carbon potential of the node where the platform area is located;
step 2: calculating the maximum carbon emission reduction capacity of the load side of the platform area;
step 3: constructing a low-carbon platform region evaluation index;
step 4: index pretreatment;
step 5: determining comprehensive weights by adopting an index comprehensive weighting method;
step 6: and calculating an evaluation result by adopting a good-bad solution distance method.
The step 1 specifically comprises the following steps: compared to the transmission network, most distribution networks are of a radiating topology, in an open-loop operating state, which makes no circulation in the network; the method adopts a direct algorithm of carbon emission flow to calculate, and specifically comprises the following steps:
step 1.1: according to a direct solution of carbon emission, a main network system in which a station area is located is assumed to have N nodes, wherein M nodes have loads, and K nodes have generator sets;
step 1.2: firstly, solving the tide distribution of the whole network in a certain time period, and generating the following various matrixes on the basis of the tide distribution, so as to obtain the carbon potential of each node of the system;
step 1.3: wherein, the branch flow distribution matrix P B ＝(P Bij ) N×N Describing active power flow distribution on a branch connecting each node in the system; unit injection distribution matrix P G ＝(P Gkj ) K×N Describing the connection relation between the generator set and the nodes and the active output condition of the generator set; load distribution matrix P L ＝(P Lmj ) M×N Describing the connection relation between the load and the node and the active load quantity; node active flux matrix P N ＝(P Nij ) N×N Describing the active power flow inflow of the node, and not considering the outflow of the node;
step 1.4: the carbon potential of the nodes in the system can be obtained, the carbon potential of each node of the main network can be calculated, and the carbon emission of each node can be obtained by combining the active power flow flowing through each node in the time period;
step 1.5: the whole power distribution network can be regarded as a load node in the main network, so that the carbon potential of each node in the power distribution network can be calculated by calculating the carbon potential of the node connected with the main network; similarly, the platform region can be regarded as a load node in the power distribution network, and the carbon emission of the platform region can be obtained according to the load quantity of the platform region and the carbon potential of the node;
step 1.6: when the distributed power supply and the energy storage equipment do not exist in the station areas, the electric energy source of any station area node is the tidal current inflow of the power distribution network, and the carbon potential of the station area node is equal to the carbon potential of the node connected with the main network of the power distribution network;
step 1.7: when the distributed power supply and the energy storage equipment exist in the platform area, the node carbon potential of the platform area is influenced by the output of the new energy and the energy storage discharge, so that a carbon emission flow model of the energy storage equipment needs to be considered;
step 1.8: when the energy storage is in a charging state, the energy storage can be regarded as a load, and the accumulated electric quantity and the carbon flow can be obtained by calculating the carbon potential of the node of the station area and the charging power thereof;
step 1.9: when the energy storage is in a discharge state, the energy storage can be regarded as a generator set, the calculation method of the carbon emission flow of the platform region transfers the carbon emission generated on the power generation side to the load side through the flow of active power flow, and the carbon emission of the platform region in a period of time can be obtained according to the node carbon potential and the load of the platform region.
The step 2 specifically comprises the following steps: based on the method for calculating the carbon emission flow of the platform area in the step 1, different carbon emission amounts can be generated by different electricity utilization behaviors of users on the load side; based on the information, the low-carbon demand response mechanism can enable a user to effectively sense different carbon emission information generated by different electricity utilization behaviors, and the platform region guides the user to reasonably change own electricity utilization behaviors by releasing the information to the user, so that low-carbon operation of the platform region is realized; the carbon emission generated by the electricity consumption behaviors before and after the user responds is compared, the effect of low-carbon demand response can be quantified, and the electricity consumption behaviors of the user are optimized by taking the maximum carbon reduction of the platform area as an objective function in a period of time, so that the carbon reduction potential of the load side of the platform area can be obtained.
The step 3 specifically comprises the following steps: selecting proper indexes as the basis and key for low-carbon assessment of the transformer area, selecting easily-obtained basic data of the transformer area to reflect the low-carbon operation level of the transformer area in combination with the maximum carbon reduction amount calculation method of the transformer area in the step 2, taking the carbon reduction potential of the transformer area as a direct index, and taking the new energy output ratio, the comprehensive line loss rate, the load rate and the electric energy substitution amount as indirect indexes in order to improve the applicability and feasibility of the low-carbon assessment method of the transformer area.
The step 4 specifically comprises the following steps: the low-carbon evaluation index of the platform area is divided into a forward index and a reverse index, wherein the forward index has benefit attribute, and the larger the value is, the better the value is; the reverse index has cost attribute, and the smaller the value is, the better the value is; the reverse index is required to be subjected to forward processing, the reverse index is converted into a forward index, the influence of the index dimension on the evaluation result is eliminated, the index value is required to be subjected to dimensionless processing, and the index values are normalized to the [0,1] interval by using an extremum processing method.
The step 5 specifically comprises the following steps: in order to comprehensively reflect the influence of expert experience and index data values on weights, a subjective weight is determined by adopting a hierarchical analysis method, an objective weight is determined by adopting an entropy weight method, and finally the subjective weight and the objective weight are linearly combined to determine the comprehensive weight.
The Analytic Hierarchy Process (AHP) in the step 6 combines qualitative judgment with quantitative analysis through hierarchical structure and ratio analysis, so that the effectiveness of decision making is improved; the target layer is a low-carbon level evaluation of the area, the criterion layer is an evaluation index, and the scheme layer is a typical area of different areas; according to the definition of information entropy, the smaller the entropy value of a certain index, the more information it provides, the greater the contribution to the evaluation, the greater the weight should be, and vice versa.
The entropy weight method in the step 6 is to determine the weight by obtaining the entropy value of index information; the comprehensive weighting method combines the analytic hierarchy process and the weight determined by the entropy weighting method linearly, so that the weight setting of each index is more objective and reasonable, and the expert experience and the information of the data can be considered.
The step 6 specifically comprises the following steps: the best and inferior solution distance method is to calculate the distance between each scheme and the optimal solution and the best and inferior solutions to obtain an evaluation result, and the determined comprehensive weight is incorporated into the best and inferior solution distance method, namely the TOPSIS method to determine the final score of each scheme.
The invention has the beneficial effects that: the invention relates to a comprehensive assessment method for low-carbon operation of a transformer area considering carbon reduction potential of a load side, which aims to bring the carbon reduction potential of the load side of a low-voltage distribution transformer area into a transformer area low-carbon assessment index system to establish an assessment index and a comprehensive assessment method of the low-carbon transformer area; the invention relates to a comprehensive assessment method for low-carbon operation of a low-voltage distribution transformer area considering load side carbon reduction potential, which comprises the following steps: calculating the node carbon potential of the node where the platform area is located; calculating the maximum carbon emission reduction capacity of the load side of the platform area; constructing a low-carbon platform region evaluation index; index pretreatment; determining comprehensive weights by adopting an index comprehensive weighting method; calculating an evaluation result by adopting a good-bad solution distance method; the invention can effectively evaluate the low-carbon operation level of the platform area and provides a direction for planning construction and low-carbon transformation of operation maintenance of the platform area; in the aspect of planning and construction, the planning capacity and construction scale of a renewable generator set and energy storage can be increased, distributed energy grid-connected power generation is guided, an electric vehicle charging pile is constructed, and the peak regulation and carbon reduction potential of the electric vehicle are exerted; in the aspect of operation and maintenance, the line loss rate of the system is reduced, a user is guided to actively participate in demand side response and electric energy replacement, adjustable resources are aggregated, and the low-carbon operation level of a platform area is improved; the method has the advantages of bringing the load side carbon reduction potential into an evaluation system, establishing low-carbon area evaluation indexes and establishing a comprehensive evaluation method.
Drawings
Fig. 1 is a diagram of a low-carbon mesa structure according to the present invention.
FIG. 2 is a flow chart of the comprehensive evaluation of the low-carbon area of the present invention.
Fig. 3 is a topology diagram of a power distribution network of the present invention.
Fig. 4 is a graph of the carbon potential and the energy storage capacity of the grid nodes of the present invention.
Fig. 5 is a plot of zone load for the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Example 1
1-5, a comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential, the method comprising the following steps:
step 1: calculating the node carbon potential of the node where the platform area is located;
step 2: calculating the maximum carbon emission reduction capacity of the load side of the platform area;
step 3: constructing a low-carbon platform region evaluation index;
step 4: index pretreatment;
step 5: determining comprehensive weights by adopting an index comprehensive weighting method;
step 6: and calculating an evaluation result by adopting a good-bad solution distance method.
The step 1 specifically comprises the following steps: compared to the transmission network, most distribution networks are of a radiating topology, in an open-loop operating state, which makes no circulation in the network; the method adopts a direct algorithm of carbon emission flow to calculate, and specifically comprises the following steps:
step 1.1: according to a direct solution of carbon emission, a main network system in which a station area is located is assumed to have N nodes, wherein M nodes have loads, and K nodes have generator sets;
step 1.2: firstly, solving the tide distribution of the whole network in a certain time period, and generating the following various matrixes on the basis of the tide distribution, so as to obtain the carbon potential of each node of the system;
step 1.3: wherein, the branch flow distribution matrix P B ＝(P Bij ) N×N Describing active power flow distribution on a branch connecting each node in the system; unit injection distribution matrix P G ＝(P Gkj ) K×N Describing the connection relation between the generator set and the nodes and the active output condition of the generator set; load distribution matrix P L ＝(P Lmj ) M×N Describing the connection relation between the load and the node and the active load quantity; node active flux matrix P N ＝(P Nij ) N×N Describing the active power flow inflow of the node, and not considering the outflow of the node;
step 1.4: the carbon potential of the nodes in the system can be obtained, the carbon potential of each node of the main network can be calculated, and the carbon emission of each node can be obtained by combining the active power flow flowing through each node in the time period;
step 1.5: the whole power distribution network can be regarded as a load node in the main network, so that the carbon potential of each node in the power distribution network can be calculated by calculating the carbon potential of the node connected with the main network; similarly, the platform region can be regarded as a load node in the power distribution network, and the carbon emission of the platform region can be obtained according to the load quantity of the platform region and the carbon potential of the node;
step 1.6: when the distributed power supply and the energy storage equipment do not exist in the station areas, the electric energy source of any station area node is the tidal current inflow of the power distribution network, and the carbon potential of the station area node is equal to the carbon potential of the node connected with the main network of the power distribution network;
step 1.7: when the distributed power supply and the energy storage equipment exist in the platform area, the node carbon potential of the platform area is influenced by the output of the new energy and the energy storage discharge, so that a carbon emission flow model of the energy storage equipment needs to be considered;
step 1.8: when the energy storage is in a charging state, the energy storage can be regarded as a load, and the accumulated electric quantity and the carbon flow can be obtained by calculating the carbon potential of the node of the station area and the charging power thereof;
step 1.9: when the energy storage is in a discharge state, the energy storage can be regarded as a generator set, the calculation method of the carbon emission flow of the platform region transfers the carbon emission generated on the power generation side to the load side through the flow of active power flow, and the carbon emission of the platform region in a period of time can be obtained according to the node carbon potential and the load of the platform region.
In this embodiment, (1) design of low-carbon region architecture: in the power system, because of numerous power utilization users, a power company generally manages the power utilization users in the power supply range by taking a power supply area as a minimum unit, an area topology framework is a basis for analyzing the low-carbon characteristics of the area, and a low-carbon area containing renewable energy sources, energy storage and flexible resources on the load side is shown in a figure 1; on the power supply side, besides the electric energy transmitted to the distribution network by the main network, the distributed power supplies such as photovoltaic, wind power, energy storage and the like additionally arranged on the low-voltage side of the distribution transformer are used for providing electric energy, and the transformer area realizes access management of new energy devices such as photovoltaic, energy storage and the like by collecting real-time data such as a photovoltaic inverter, an intelligent internet-of-things electric energy meter and the like; on the load side, the proportion of flexible loads with regulation and control capability, such as electric vehicles, air conditioners and the like, namely FL is synchronously increased, and the platform region performs overall management on flexible resources on the load side through information communication, power electronics and automatic control technologies; in summary, the running state of the source-network-load-storage of the station area is coordinated and controlled, so that the running efficiency of the system can be effectively improved, the utilization of clean energy is promoted, and the low-carbonization running of the station area is realized;
(2) calculation of carbon reduction potential of the station area: node active fluxMatrix P N ＝(P Nij ) N×N Describing the active power flow inflow of the node, and not considering the outflow of the node; for node i:wherein I is + A branch set which is an active power flow flowing into a node i; p (P) Bs Active power for branch s; p (P) Gi The output of the generator set at the node i is output; thus, the carbon potential of the node in the system can be obtained: />Wherein ρ is s Unit kgCO for carbon flow density of branch s 2 /(kW·h)；e Gi For the carbon emission intensity of the generator set at the node i, kgCO 2 /(kW.h); when the energy storage is in a charging state, the energy storage can be regarded as a load, and the accumulated electric quantity and the carbon flow can be obtained by calculating the carbon potential of the node of the station area and the charging power thereof; when the energy storage is in a discharging state, the energy storage can be regarded as a generator set, and the discharging carbon potential of the energy storage can be calculated by the following formula:in the formula e s (T) is the node carbon potential when energy storage and discharge are carried out after T charging periods; f (F) 0 、Q 0 The residual carbon flow and the residual electric quantity when the energy storage is switched to the charging state last time are respectively; η is the energy storage charging and discharging efficiency; p (P) t 、e t Charging power and carbon potential of the t-th charging period respectively; Δt is the period length;
set G-table distributed renewable energy generator set in the table area, wherein the carbon emission intensity of the generator set can be regarded as 0,S energy storage equipment in a discharge state, and then the node carbon potential of the table area is as follows:in the formula e l,t The node carbon potential of the first station area in the t period is the node carbon potential of the first station area in the t period; p (P) n,t 、P g,t 、P s,t Active power injected into a power grid at a t period, active output of a g-th distributed generator set and active output of energy storage equipment in a discharge state at a s-th stageDischarging; e, e n,t 、e s,t The carbon potential of the main network node and the discharge carbon potential of the energy storage device in the t period are respectively;
calculating the carbon reduction potential of the platform area by taking a day as a unit, wherein the objective function is as follows:wherein DeltaE is D Carbon emission reduction for a day for a bay; omega is the power user set in the station area; t (T) d Is the total time of day; />Load decrease and load increase of the user in the t period after the low-carbon demand response is implemented respectively;
in addition, the following constraint conditions are satisfied, and formulas (1) - (2) represent the maximum and minimum constraints of the user load adjustment amount; equation (3) indicates that the load increase of the user during a certain period cannot exceed the difference between the maximum rated load and the baseline load during that period; equation (4) indicates that the user's load reduction in a certain period cannot exceed the baseline load for that period; equation (5) indicates that the user cannot be in the load increasing and load decreasing states at the same time for a certain period of time; equation (6) represents the total load change constraint in one day before and after the user electricity behavior adjustment;
in (1) the->0-1 variables representing increase and decrease of user load in the t-th period, respectively; />Maximum rated load for the t-th period; p (P) L,t Baseline load for period t;respectively isThe upper limit of the load increment and decrement that can be adjusted by the user in each period; />Is the maximum value of the total load change in a day;
after the maximum carbon reduction amount of one day of the platform area is obtained, the maximum carbon reduction amount of one year of the platform area is obtained by accumulating the maximum carbon reduction amounts:wherein DeltaE is Y The carbon reduction is the maximum annual carbon reduction of the station area; t (T) Y Is the total period of one year.
The step 2 specifically comprises the following steps: based on the method for calculating the carbon emission flow of the platform area in the step 1, different carbon emission amounts can be generated by different electricity utilization behaviors of users on the load side; based on the information, the low-carbon demand response mechanism can enable a user to effectively sense different carbon emission information generated by different electricity utilization behaviors, and the platform region guides the user to reasonably change own electricity utilization behaviors by releasing the information to the user, so that low-carbon operation of the platform region is realized; the carbon emission generated by the electricity consumption behaviors before and after the user responds is compared, the effect of low-carbon demand response can be quantified, and the electricity consumption behaviors of the user are optimized by taking the maximum carbon reduction of the platform area as an objective function in a period of time, so that the carbon reduction potential of the load side of the platform area can be obtained.
The step 3 specifically comprises the following steps: selecting proper indexes as the basis and key for low-carbon assessment of the transformer area, selecting easily-obtained basic data of the transformer area to reflect the low-carbon operation level of the transformer area in combination with the maximum carbon reduction amount calculation method of the transformer area in the step 2, taking the carbon reduction potential of the transformer area as a direct index, and taking the new energy output ratio, the comprehensive line loss rate, the load rate and the electric energy substitution amount as indirect indexes in order to improve the applicability and feasibility of the low-carbon assessment method of the transformer area.
In this embodiment, the comprehensive evaluation method for the low-carbon area includes: firstly, the following description is made on the low-carbon index of the station area:
first, the carbon reduction potential of the region (X 1 ): the transformer area can guide users to adjust electricity consumption behaviors to reduce carbon emission and excavate load through a low-carbon demand response strategyThe regulatory potential of various regulatable resources is laterally selected, so that the carbon reduction potential delta E of the station area is selected Y As an index for intuitively reflecting the low carbon level of the user side of the platform area;
secondly, the new energy output ratio (X) 2 ): the installed capacity and the absorption rate of the grid-connected distributed new energy are key factors influencing the low-carbon operation of the platform area, the carbon emission intensity of the distributed new energy unit is zero, and the output of the new energy unit should be arranged preferentially in order to improve the utilization efficiency of the new energy and reduce the carbon emission of the platform area; the new energy output ratio of the station area represents the ratio of the output of photovoltaic, fans and the like to the total power supply quantity of the station area, and can reflect the low carbon level of the power supply side of the station area; the new energy output ratio can be expressed by the following formula:wherein P is pv,t 、P w,t Photovoltaic and fan output in the station area of the t period are respectively carried out;
thirdly, the line loss rate (X) 3 ): the carbon emission generated in the power transmission process is closely related to the operation mode and the transmission technology of the power grid, so that the line loss rate is reduced, and the carbon emission generated in the power transmission process can be reduced; the line loss rate is the ratio of the power loss of the line of the station area to the total power supply of the station area in the power transmission process, and is used for reflecting the economical efficiency and low carbon property of the operation of the station area; the station line loss rate η may be expressed as:wherein P is 1 The total power supply quantity of the transformer area; p (P) 2 The total electricity consumption of the users in the platform area is achieved;
fourth, load factor (X) 4 ): the load factor is the ratio of the average load to the peak load of the platform area and is used for measuring the load fluctuation condition of the platform area in the annual time; the higher the load rate is, the annual load is relatively flat, otherwise, the load fluctuation is obvious; according to the research, the coal consumption of the coal-fired unit is reduced by about 2.3 g/(kW.h) every time the load rate is increased by one percentage point; the annual load rate calculation formula of the platform area is as follows:wherein P is avg Average month electricity consumption for the load of the platform area; p (P) max The power consumption is the maximum monthly power consumption for the load of the platform area;
fifth, the energy substitution (X) 5 ): the electric energy substitution refers to substituting the electric energy for other energy consumption forms such as fire coal, fuel oil and the like in the fields of heating, traffic and the like, and has positive significance for reducing carbon emission and environmental pollution; the power substitution amount is defined as an increase in the power consumption amount in the τ year from the reference year, and may be expressed as:wherein D is e,τ Is the electric energy replacement quantity in the tau th year; y is Y e,τ Actual electric energy consumption is tau; y is Y τ The total energy consumption of the terminal in the tau period; t (T) B Is the reference year; />The total energy consumption is the reference annual energy consumption; />Is the electricity consumption of the reference year.
The step 4 specifically comprises the following steps: the low-carbon evaluation index of the platform area is divided into a forward index and a reverse index, wherein the forward index has benefit attribute, and the larger the value is, the better the value is; the reverse index has cost attribute, and the smaller the value is, the better the value is; the reverse index is required to be subjected to forward processing, the reverse index is converted into a forward index, the influence of the index dimension on the evaluation result is eliminated, the index value is required to be subjected to dimensionless processing, and the index values are normalized to the [0,1] interval by using an extremum processing method.
In this embodiment, the index data is preprocessed: forward treatment: x is x * =m-x, where x * Is a reverse index value after forward conversion; m is the maximum value in the index; x is the original reverse index value; dimensionless treatment:wherein, in the formula, x uv Is an element in the original matrix X; m is M v 、m v Respectively x uv Maximum and minimum of (2), M v ＝max{x uv },m v ＝min{x uv }；z uv Is an element in the normalized matrix Z.
The step 5 specifically comprises the following steps: in order to comprehensively reflect the influence of expert experience and index data values on weights, a subjective weight is determined by adopting a hierarchical analysis method, an objective weight is determined by adopting an entropy weight method, and finally the subjective weight and the objective weight are linearly combined to determine the comprehensive weight.
The Analytic Hierarchy Process (AHP) in the step 6 combines qualitative judgment with quantitative analysis through hierarchical structure and ratio analysis, so that the effectiveness of decision making is improved; the target layer is a low-carbon level evaluation of the area, the criterion layer is an evaluation index, and the scheme layer is a typical area of different areas; according to the definition of information entropy, the smaller the entropy value of a certain index, the more information it provides, the greater the contribution to the evaluation, the greater the weight should be, and vice versa.
The entropy weight method in the step 6 is to determine the weight by obtaining the entropy value of index information; the comprehensive weighting method combines the analytic hierarchy process and the weight determined by the entropy weighting method linearly, so that the weight setting of each index is more objective and reasonable, and the expert experience and the information of the data can be considered.
The step 6 specifically comprises the following steps: the best and inferior solution distance method is to calculate the distance between each scheme and the optimal solution and the best and inferior solutions to obtain an evaluation result, and the determined comprehensive weight is incorporated into the best and inferior solution distance method, namely the TOPSIS method to determine the final score of each scheme.
In this embodiment, it is assumed that there are U evaluation schemes (zones), V evaluation indexes, and the original matrix x= (X) is subjected to index preprocessing uv ) U×V Conversion to normalized matrix z= (Z) uv ) U×V Then calculating the comprehensive weight of the index; the subjective weight is determined as follows:
(1) constructing a judgment matrix: and comparing the indexes of the same level in pairs, and constructing a judgment matrix according to the importance: a= (a) ef ) V×V Wherein a is ef Representing the importance degree between every two indexes, taking the value of a by adopting a scale method, and a ef ＝1a ef ＞0,a ee ＝1；
(2) Consistency test: in order to eliminate decision errors caused by expert experience as much as possible, consistency test needs to be performed on the judgment matrix:wherein CI is a consistency index; lambda (lambda) max Judging the maximum eigenvalue of the matrix; CR is a consistency ratio; RI is the average random consistency index; and (3) taking a value and referring to: when CR < 0.1, it is considered valid, otherwise it should be modified so that it meets the requirements;
(3) and (5) calculating subjective weight: calculating subjective weight of the index by using a geometric average method:
the step of determining the objective weight is as follows:
(1) calculating a probability matrix: probability matrix p= (P uv ) U×V The element in (b) represents the specific gravity of the u-th station area under the v-th index:
(2) calculating information entropy: for the v index, the information entropy is:
(3) calculating objective weights:and linearly combining the subjective weight and the objective weight to obtain a comprehensive weight: />Wherein omega is v The comprehensive weight of the v index; α is a subjective weight coefficient, α=0.5;
(4) calculating the comprehensive evaluation result of each area: for the normalized matrix z= (Z) uv ) U×V Defining a maximum value and a minimum value as:in the method, in the process of the invention,v＝1,2,...,V；
(5) the distances between each evaluation scheme and the maximum and minimum values are calculated respectively:
(6) calculating the final score of each scheme:
in summary, a comprehensive evaluation method of the low-carbon area is established, and a specific flow is shown in fig. 2.
The invention relates to a comprehensive assessment method for low-carbon operation of a transformer area considering carbon reduction potential of a load side, which aims to bring the carbon reduction potential of the load side of a low-voltage distribution transformer area into a transformer area low-carbon assessment index system to establish an assessment index and a comprehensive assessment method of the low-carbon transformer area; the invention relates to a comprehensive assessment method for low-carbon operation of a low-voltage distribution transformer area considering load side carbon reduction potential, which comprises the following steps: calculating the node carbon potential of the node where the platform area is located; calculating the maximum carbon emission reduction capacity of the load side of the platform area; constructing a low-carbon platform region evaluation index; index pretreatment; determining comprehensive weights by adopting an index comprehensive weighting method; calculating an evaluation result by adopting a good-bad solution distance method; the invention can effectively evaluate the low-carbon operation level of the platform area and provides a direction for planning construction and low-carbon transformation of operation maintenance of the platform area; in the aspect of planning and construction, the planning capacity and construction scale of a renewable generator set and energy storage can be increased, distributed energy grid-connected power generation is guided, an electric vehicle charging pile is constructed, and the peak regulation and carbon reduction potential of the electric vehicle are exerted; in the aspect of operation and maintenance, the line loss rate of the system is reduced, a user is guided to actively participate in demand side response and electric energy replacement, adjustable resources are aggregated, and the low-carbon operation level of a platform area is improved; the method has the advantages of bringing the load side carbon reduction potential into an evaluation system, establishing low-carbon area evaluation indexes and establishing a comprehensive evaluation method.
Example 2
1-5, a comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential, the method comprising the following steps:
step 1: calculating the node carbon potential of the node where the platform area is located;
step 2: calculating the maximum carbon emission reduction capacity of the load side of the platform area;
step 3: constructing a low-carbon platform region evaluation index;
step 4: index pretreatment;
step 5: determining comprehensive weights by adopting an index comprehensive weighting method;
step 6: and calculating an evaluation result by adopting a good-bad solution distance method.
In this embodiment, the calculation analysis: in order to verify the rationality and applicability of the method, 6 typical areas of three different areas of city, suburban area and rural area in Henan are selected for carrying out carbon reduction potential analysis and low carbon level evaluation, and are named A1, A2, B1, B2, C1 and C2 respectively; basic data and information of each area are obtained according to the evaluation index;
taking a typical day of urban area A1 as an example, the carbon reduction potential of the urban area A1 is analyzed: the network structure of the distribution network where the station area is located is shown in fig. 3, wherein a node 1 is connected with an upper-level main network, the node carbon potential value of each period is given, the station area A1 is connected with a node 7, and the node carbon potential of the main network of the node 1, the station area photovoltaic and the energy storage capacity are shown in fig. 4; firstly, calculating node carbon potential of a platform area according to the node carbon potential of a main network and the output conditions of photovoltaic and energy storage equipment, and sending the information to a user as a low-carbon demand response signal by the platform area, wherein the load change curve and the carbon emission reduction amount of the platform area before and after the response are calculated on the premise that 10% of load can participate in the low-carbon demand response, and the final result is shown in figure 5;
as can be seen from the figure, on the power supply side, in the period of low carbon potential of the main network node, the electric energy of the station area is mainly transmitted by the power distribution network, and the energy storage equipment is in a charging state; in a period of higher carbon potential of the main network node, the energy storage equipment is in a discharge state, and the carbon potential of the platform area is reduced relative to that of the main network; on the load side, after receiving the low-carbon demand response signal, the user reduces the carbon emission generated by self electricity consumption in the festivalThe power consumption behavior of the point carbon potential high period is transferred to the node carbon potential low period for working, and the carbon emission reduction of the platform area in the typical day is 47kgCO 2 ；
Six typical bays were evaluated for low carbon: firstly, collecting basic data and related information of a platform area according to formulated platform area evaluation indexes, and carrying out corresponding calculation and pretreatment; the values of all index data after pretreatment are shown in table 1; as can be seen from the data in table 1, compared with suburban areas and rural areas, urban areas are developed in regional economy, and the urban areas are more in flexible control resources such as electric vehicles and temperature control loads owned by residents at the user side, can be more actively involved in low-carbon demand response, and have large low-carbon control potential; the rural areas are distributed in load along the lines, the controllable resource aggregation difficulty is high, the aggregation potential is low, the rural areas are longer in power supply distance, and the line loss rate is high; the indexes such as the new energy output ratio, the load rate, the electric energy substitution quantity and the like have different numerical characteristics due to different actual conditions of the areas;
TABLE 1 index values of each of the pretreated values
Secondly, calculating subjective weight and objective weight of each index, and obtaining comprehensive weight as shown in table 2; the weight result shows that the carbon reduction potential of the platform region is a key index for evaluating the low carbon level of the platform region, and the correlation with the regulation potential of the user-side regulatable resource of the platform region is larger; secondly, the output duty ratio of the distributed new energy is larger, which indicates the influence of the power supply side on the low carbon level of the station area; the proportion of the line loss rate of the transformer area is smaller, which indicates that the index is mainly related to the power grid architecture and the power supply distance, and the adjustability is smaller, so the index is not used as a main evaluation index; in addition, the comprehensive weight is the index X due to the comprehensive reflection of expert experience judgment and the difference of the data of each evaluation object 1 、X 2 、X 5 The weight of X is reduced compared with subjective method 3 、X 4 The method has the advantages that the method can eliminate errors caused by expert experience to a certain extent, so that the setting of indexes is moreScientific and objective;
table 2 weights of the various indices
Finally, final scores and ranks for evaluating the low carbon levels of each plot are calculated as shown in table 3; the results show that the low-carbon operation levels of the station areas A1 and A2 are good, and the low-carbon operation levels of the station areas B2 and C1 are poor; the load rate of the station area B2 is small, the service time of electric equipment needs to be reasonably adjusted, and peak-valley difference is reduced; the carbon reduction potential, the line loss rate and the electric energy substitution quantity of the station area C1 are smaller, a power supply structure needs to be optimized, the power supply radius is reduced, and the load side demand response potential is improved;
TABLE 3 Low carbon evaluation results for each zone
In order to further examine the effectiveness of the method, the low carbon level of the station area in different time dimensions is verified, taking the urban station area A1 as an example, and the evaluation scores in different scenes are calculated on the assumption that three index values of the station area, namely the carbon reduction potential, the new energy output ratio and the electric energy substitution amount, are changed in different periods, wherein specific data and calculation results are shown in table 4; the result shows that with the development of economy and society, the installation proportion of new energy is increased year by year, the permeability of new energy is increased year by year, electric vehicles on the load side and the like are more and more popular, the potential of flexible resource participation in demand response is more and more large, and with the development of science and technology and the deep penetration of a low-carbon concept, the electric energy substitution quantity is increased year by year; thus, the low-carbon evaluation score of the platform area also shows a gradually rising situation;
TABLE 4 index values at different times
By combining the analysis, the index system and the evaluation method provided by the invention can effectively evaluate the low-carbon operation level of the platform area, and provide a direction for planning construction and low-carbon transformation of operation maintenance of the platform area; in the aspect of planning and construction, the planning capacity and construction scale of a renewable generator set and energy storage can be increased, distributed energy grid-connected power generation is guided, an electric vehicle charging pile is constructed, and the peak regulation and carbon reduction potential of the electric vehicle are exerted; in the aspect of operation and maintenance, the line loss rate of the system is reduced, a user is guided to actively participate in demand side response and electric energy replacement, adjustable resources are aggregated, and the low-carbon operation level of a platform area is improved.
The invention relates to a comprehensive assessment method for low-carbon operation of a transformer area considering carbon reduction potential of a load side, which aims to bring the carbon reduction potential of the load side of a low-voltage distribution transformer area into a transformer area low-carbon assessment index system to establish an assessment index and a comprehensive assessment method of the low-carbon transformer area; the invention relates to a comprehensive assessment method for low-carbon operation of a low-voltage distribution transformer area considering load side carbon reduction potential, which comprises the following steps: calculating the node carbon potential of the node where the platform area is located; calculating the maximum carbon emission reduction capacity of the load side of the platform area; constructing a low-carbon platform region evaluation index; index pretreatment; determining comprehensive weights by adopting an index comprehensive weighting method; calculating an evaluation result by adopting a good-bad solution distance method; the invention can effectively evaluate the low-carbon operation level of the platform area and provides a direction for planning construction and low-carbon transformation of operation maintenance of the platform area; in the aspect of planning and construction, the planning capacity and construction scale of a renewable generator set and energy storage can be increased, distributed energy grid-connected power generation is guided, an electric vehicle charging pile is constructed, and the peak regulation and carbon reduction potential of the electric vehicle are exerted; in the aspect of operation and maintenance, the line loss rate of the system is reduced, a user is guided to actively participate in demand side response and electric energy replacement, adjustable resources are aggregated, and the low-carbon operation level of a platform area is improved; the method has the advantages of bringing the load side carbon reduction potential into an evaluation system, establishing low-carbon area evaluation indexes and establishing a comprehensive evaluation method.
Claims (9)
1. A comprehensive evaluation method for low-carbon operation of a transformer area considering load side carbon reduction potential is characterized by comprising the following steps of: the method comprises the following steps:
step 1: calculating the node carbon potential of the node where the platform area is located;
step 2: calculating the maximum carbon emission reduction capacity of the load side of the platform area;
step 3: constructing a low-carbon platform region evaluation index;
step 4: index pretreatment;
step 5: determining comprehensive weights by adopting an index comprehensive weighting method;
step 6: and calculating an evaluation result by adopting a good-bad solution distance method.
2. The comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential as claimed in claim 1, wherein the comprehensive assessment method comprises the following steps: the step 1 specifically comprises the following steps: compared to the transmission network, most distribution networks are of a radiating topology, in an open-loop operating state, which makes no circulation in the network; the method adopts a direct algorithm of carbon emission flow to calculate, and specifically comprises the following steps:
step 1.1: according to a direct solution of carbon emission, a main network system in which a station area is located is assumed to have N nodes, wherein M nodes have loads, and K nodes have generator sets;
step 1.2: firstly, solving the tide distribution of the whole network in a certain time period, and generating the following various matrixes on the basis of the tide distribution, so as to obtain the carbon potential of each node of the system;
step 1.3: wherein, the branch flow distribution matrix P B ＝(P Bij ) N×N Describing active power flow distribution on a branch connecting each node in the system; unit injection distribution matrix P G ＝(P Gkj ) K×N Describing the connection relation between the generator set and the nodes and the active output condition of the generator set; load distribution matrix P L ＝(P Lmj ) M×N Describing the connection relation between load and node and the likeWork load amount; node active flux matrix P N ＝(P Nij ) N×N Describing the active power flow inflow of the node, and not considering the outflow of the node;
step 1.4: the carbon potential of the nodes in the system can be obtained, the carbon potential of each node of the main network can be calculated, and the carbon emission of each node can be obtained by combining the active power flow flowing through each node in the time period;
step 1.5: the whole power distribution network can be regarded as a load node in the main network, so that the carbon potential of each node in the power distribution network can be calculated by calculating the carbon potential of the node connected with the main network; similarly, the platform region can be regarded as a load node in the power distribution network, and the carbon emission of the platform region can be obtained according to the load quantity of the platform region and the carbon potential of the node;
step 1.6: when the distributed power supply and the energy storage equipment do not exist in the station areas, the electric energy source of any station area node is the tidal current inflow of the power distribution network, and the carbon potential of the station area node is equal to the carbon potential of the node connected with the main network of the power distribution network;
step 1.7: when the distributed power supply and the energy storage equipment exist in the platform area, the node carbon potential of the platform area is influenced by the output of the new energy and the energy storage discharge, so that a carbon emission flow model of the energy storage equipment needs to be considered;
step 1.8: when the energy storage is in a charging state, the energy storage can be regarded as a load, and the accumulated electric quantity and the carbon flow can be obtained by calculating the carbon potential of the node of the station area and the charging power thereof;
step 1.9: when the energy storage is in a discharge state, the energy storage can be regarded as a generator set, the calculation method of the carbon emission flow of the platform region transfers the carbon emission generated on the power generation side to the load side through the flow of active power flow, and the carbon emission of the platform region in a period of time can be obtained according to the node carbon potential and the load of the platform region.
3. The comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential as claimed in claim 2, wherein the comprehensive assessment method is characterized by comprising the following steps of: the step 2 specifically comprises the following steps: based on the method for calculating the carbon emission flow of the platform area in the step 1, different carbon emission amounts can be generated by different electricity utilization behaviors of users on the load side; based on the information, the low-carbon demand response mechanism can enable a user to effectively sense different carbon emission information generated by different electricity utilization behaviors, and the platform region guides the user to reasonably change own electricity utilization behaviors by releasing the information to the user, so that low-carbon operation of the platform region is realized; the carbon emission generated by the electricity consumption behaviors before and after the user responds is compared, the effect of low-carbon demand response can be quantified, and the electricity consumption behaviors of the user are optimized by taking the maximum carbon reduction of the platform area as an objective function in a period of time, so that the carbon reduction potential of the load side of the platform area can be obtained.
4. A method for comprehensive assessment of low-carbon operation of a district taking into account load side carbon reduction potential as defined in claim 3, wherein: the step 3 specifically comprises the following steps: selecting proper indexes as the basis and key for low-carbon assessment of the transformer area, selecting easily-obtained basic data of the transformer area to reflect the low-carbon operation level of the transformer area in combination with the maximum carbon reduction amount calculation method of the transformer area in the step 2, taking the carbon reduction potential of the transformer area as a direct index, and taking the new energy output ratio, the comprehensive line loss rate, the load rate and the electric energy substitution amount as indirect indexes in order to improve the applicability and feasibility of the low-carbon assessment method of the transformer area.
5. The comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential as claimed in claim 1, wherein the comprehensive assessment method comprises the following steps: the step 4 specifically comprises the following steps: the low-carbon evaluation index of the platform area is divided into a forward index and a reverse index, wherein the forward index has benefit attribute, and the larger the value is, the better the value is; the reverse index has cost attribute, and the smaller the value is, the better the value is; the reverse index is required to be subjected to forward processing, the reverse index is converted into a forward index, the influence of the index dimension on the evaluation result is eliminated, the index value is required to be subjected to dimensionless processing, and the index values are normalized to the [0,1] interval by using an extremum processing method.
6. The comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential as claimed in claim 1, wherein the comprehensive assessment method comprises the following steps: the step 5 specifically comprises the following steps: in order to comprehensively reflect the influence of expert experience and index data values on weights, a subjective weight is determined by adopting a hierarchical analysis method, an objective weight is determined by adopting an entropy weight method, and finally the subjective weight and the objective weight are linearly combined to determine the comprehensive weight.
7. The comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential as claimed in claim 6, wherein the comprehensive assessment method comprises the following steps: the Analytic Hierarchy Process (AHP) in the step 5 combines qualitative judgment with quantitative analysis through hierarchical structure and ratio analysis, so that the effectiveness of decision making is improved; the target layer is a low-carbon level evaluation of the area, the criterion layer is an evaluation index, and the scheme layer is a typical area of different areas; according to the definition of information entropy, the smaller the entropy value of a certain index, the more information it provides, the greater the contribution to the evaluation, the greater the weight should be, and vice versa.
8. The comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential as claimed in claim 7, wherein the comprehensive assessment method comprises the following steps: the entropy weight method in the step 5 is to determine the weight by obtaining the entropy value of index information; the comprehensive weighting method combines the analytic hierarchy process and the weight determined by the entropy weighting method linearly, so that the weight setting of each index is more objective and reasonable, and the expert experience and the information of the data can be considered.
9. The comprehensive assessment method for low-carbon operation of a platform area considering load side carbon reduction potential as claimed in claim 1, wherein the comprehensive assessment method comprises the following steps: the step 6 specifically comprises the following steps: the best and inferior solution distance method is to calculate the distance between each scheme and the optimal solution and the best and inferior solutions to obtain an evaluation result, and the determined comprehensive weight is incorporated into the best and inferior solution distance method, namely the TOPSIS method to determine the final score of each scheme.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310600433.XA CN116823020A (en) | 2023-05-25 | 2023-05-25 | Comprehensive evaluation method for low-carbon operation of transformer area considering load side carbon reduction potential |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310600433.XA CN116823020A (en) | 2023-05-25 | 2023-05-25 | Comprehensive evaluation method for low-carbon operation of transformer area considering load side carbon reduction potential |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116823020A true CN116823020A (en) | 2023-09-29 |
Family
ID=88123186
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310600433.XA Pending CN116823020A (en) | 2023-05-25 | 2023-05-25 | Comprehensive evaluation method for low-carbon operation of transformer area considering load side carbon reduction potential |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116823020A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117371650A (en) * | 2023-10-09 | 2024-01-09 | 国网江苏省电力有限公司连云港供电分公司 | Accurate carbon metering method and system for power distribution network considering load side electric energy substitution |
-
2023
- 2023-05-25 CN CN202310600433.XA patent/CN116823020A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117371650A (en) * | 2023-10-09 | 2024-01-09 | 国网江苏省电力有限公司连云港供电分公司 | Accurate carbon metering method and system for power distribution network considering load side electric energy substitution |
| CN117371650B (en) * | 2023-10-09 | 2024-06-07 | 国网江苏省电力有限公司连云港供电分公司 | Accurate carbon metering method and system for power distribution network considering load side electric energy substitution |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Guo et al. | Optimal operation of regional integrated energy system considering demand response | |
| CN109919478B (en) | Comprehensive energy microgrid planning method considering comprehensive energy supply reliability | |
| Yang et al. | Multi-time scale optimal scheduling of regional integrated energy systems considering integrated demand response | |
| Li et al. | Improving wind power integration by regenerative electric boiler and battery energy storage device | |
| Ju et al. | A Tri-dimensional Equilibrium-based stochastic optimal dispatching model for a novel virtual power plant incorporating carbon Capture, Power-to-Gas and electric vehicle aggregator | |
| CN108123492A (en) | A kind of generation schedule optimization method a few days ago for considering thermoelectricity electricity accumulation of heat combined adjusting peak | |
| CN103151797A (en) | Multi-objective dispatching model-based microgrid energy control method under grid-connected operation mode | |
| CN108376996B (en) | Practical power distribution network distributed photovoltaic receiving capacity estimation method | |
| CN116402307A (en) | Power grid planning capacity analysis method considering operation characteristics of schedulable flexible resources | |
| CN116823020A (en) | Comprehensive evaluation method for low-carbon operation of transformer area considering load side carbon reduction potential | |
| Liang et al. | Capacity configuration optimization of wind-solar combined power generation system based on improved grasshopper algorithm | |
| Liu et al. | Multi-objective optimal scheduling of community integrated energy system considering comprehensive customer dissatisfaction model | |
| Gao et al. | Multi-energy sharing optimization for a building cluster towards net-zero energy system | |
| Li et al. | Integrated energy system for low-carbon economic operation optimization: Pareto compromise programming and master-slave game | |
| Deng et al. | Real-coded quantum optimization-based bi-level dispatching strategy of integrated power and heat systems | |
| Tang et al. | Multi-time-scale optimal scheduling of integrated energy system considering demand response | |
| Yu et al. | Day-ahead optimal dispatch of integrated energy system considering wind power forecasting and integrated demand response | |
| CN115940284B (en) | Operation control strategy of new energy hydrogen production system considering time-of-use electricity price | |
| CN114612021B (en) | Multi-granularity-attribute-considered thermal load cooperative regulation and control method | |
| Ma et al. | Evaluation model for economic operation of active distribution network orienting to energy internet | |
| Wang et al. | Optimal Operation of Regional Integrated Energy System Considering Integrated Demand Response and Exergy Efficiency | |
| CN112270432B (en) | Energy management method of comprehensive energy system considering multi-subject benefit balance | |
| Zhang et al. | A Two‐Stage Optimization Model of Capacity Allocation and Regulation Operation for Virtual Power Plant | |
| Chen et al. | A multi-objective joint planning of transmission channel and energy storage system considering economy and flexibility | |
| CN106300443B (en) | A kind of three for reducing abandonment layer cogeneration microgrid energy control method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication |