Wind and light consumption low-carbon scheduling method and system based on load side green evidence income

Abstract

The invention provides a load side green evidence income-based wind and light consumption low-carbon scheduling method and system, and the method comprises the steps: determining the wind and light renewable energy consumption of a load side according to a power generation side system scheduling cost model; determining a load curve after the power user participates in the load source cooperation based on the load side wind and light renewable energy consumption; according to the load curve and the lowest cost of the system, determining the green proof total income of the wind-light renewable energy power generator and the power consumer participating in the source-load cooperation; based on a pre-constructed Shapley green certificate income distribution model, distributing the green certificate total income, and determining the green certificate income obtained by the power consumers participating in the source-load cooperation; establishing a load-side wind and light consumption low-carbon scheduling model by taking the minimum total cost of the transfer load of the power consumer as a target according to the green evidence income obtained by the power consumer and the electricity price cost of the transfer load; and through the load-side wind and light absorption low-carbon scheduling model, completing load-side wind and light absorption low-carbon scheduling. And wind and light abandoning power of the system is reduced.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and in particular to a method and system for low-carbon dispatching of wind and solar power consumption based on load-side green certificate income. Background Art

[0002] The power generation side is the place where renewable energy is connected to the grid and consumed. Adding electric boilers and other power-to-heat devices on the power generation side to decouple the rigid constraint of "heat determines electricity" of the cogeneration unit, and realizing wind power heating is also an effective way to promote the consumption of renewable energy; in order to further increase the output of wind power heating, on the basis of decoupling the cogeneration unit with the power-to-heat device, the output of the cogeneration unit is further compressed through the heat storage device, which can further reduce the amount of wind power abandoned. However, decoupling the cogeneration unit to promote the consumption of wind and solar power is suitable for winter heating areas. Therefore, exploring a wind and solar power consumption method with a wider range of temporal and spatial applications and increasing the amount of wind and solar power connected to the grid is a need for the green development of the power system.

[0003] The power system has the characteristic of "source follows load", and the actual grid-connected power on the power generation side depends on the actual demand on the load side. Therefore, considering the overall power system, increasing the power demand during the wind and solar power abandonment period on the load side is conducive to increasing the wind and solar power grid connection during the wind and solar power abandonment period on the power generation side. As the actual consumption party of renewable energy, the demand response resources on the load side have great potential in wind and solar power consumption. Further exploring the wind and solar power consumption capacity on the load side is the key to promoting the green development of the power system.

[0004] In the process of renewable energy construction and development, cost factors need to be considered. In order to encourage the construction of wind and solar renewable energy, carbon emission trading (CET) and green certificate trading (GCT) came into being. CET and GCT give economic value to the green attributes of renewable energy generation through market means, and the cost advantage of renewable energy grid connection is more prominent. However, at this stage, my country's GCT market is mainly used for renewable energy power generation subsidies, and the effect is relatively single. It is urgent to expand the application scenarios of GCT to improve the vitality of the GCT market and better play the role of GCT in encouraging renewable energy grid connection and consumption. Summary of the invention

[0005] In view of the above technical problems, the present invention provides a low-carbon dispatching method for wind and solar power consumption based on load-side green certificate income, comprising:

[0006] Determine the consumption of wind and solar renewable energy on the load side based on the system dispatch cost model on the power generation side;

[0007] Based on the wind and solar renewable energy consumption on the load side, determine the load curve after the power user participates in the load-source cooperation; based on the load curve and the minimum system cost, determine the total green certificate income of the wind and solar renewable energy power generators and power users participating in the source-load cooperation;

[0008] Based on the pre-built Shapley value green certificate income distribution model, the total income of the green certificate is distributed to determine the green certificate income obtained by the power users participating in the source-load cooperation;

[0009] According to the green certificate income obtained by the electricity user and the electricity price cost of load transfer, a low-carbon dispatch model for wind and solar power consumption on the load side is established with the goal of minimizing the total cost of load transfer for the electricity user; through the low-carbon dispatch model for wind and solar power consumption on the load side, the low-carbon dispatch of wind and solar power consumption on the load side is completed.

[0010] Furthermore, according to the system dispatch cost model on the power generation side, the consumption of wind and solar renewable energy on the load side is determined, including:

[0011] The system operates with the goal of minimizing the comprehensive cost, including the coal cost of thermal power units, the operation and maintenance cost of wind and solar renewable energy power generation units, the cost of abandoned wind and solar power, the cost of system participation in carbon trading, and the cost of system participation in green certificates. The minimum comprehensive cost objective function min f is as follows:

[0012] minf=min(f f +f w +f s +f qw +f qs + f CET +f GCT ) (1)

[0013] in:

[0014]

[0015] In the formula, f f is the coal burning cost of thermal power units during the dispatch period; w and f s are respectively the wind power operation cost and photovoltaic power generation operation cost during the dispatch period; w and ε s are the unit operating costs of wind power generation and photovoltaic power generation respectively; ν w and ν s are the unit wind abandonment penalty cost and the unit solar abandonment penalty cost respectively; f CET is the cost of participating in CET during the system scheduling period; α CET is the unit carbon emission rights trading price; R is the set of assessed main units; F i is the actual carbon emissions of unit i during the scheduling period; E iis the carbon quota of unit i during the scheduling period; P i (t) is the power generation of unit i in period t; β i is the carbon emission intensity of unit i; γ i is the carbon emission quota coefficient of unit i; T and Δt are the total duration of the scheduling cycle and the unit scheduling duration respectively; f GCT is the cost of the system participating in GCT; α GCT is the unit green certificate transaction cost; N ne and N ob They are the number of green certificates required for the system to meet the renewable energy consumption quota and the number of green certificates obtained by renewable energy power generators; RPS P is the system green certificate quota coefficient; load (t) is the load during period t; λ GCT P is the system green certificate quantity conversion coefficient; i (t) is the grid-connected power of the i-th renewable energy source in period t; n is the number of renewable energy sources;

[0016] The constraints are as follows:

[0017] Power balance constraints

[0018]

[0019] Output constraints of thermal power units

[0020]

[0021] Power constraints of renewable energy grid-connected electricity

[0022]

[0023] Tie line power constraint

[0024]

[0025] In the formula, and They are the output and climbing power upper and lower limits of thermal power unit i; and P s max are the upper limits of grid-connected power of wind turbines and photovoltaic units respectively; P ex (t) is the transmission power of the tie line during period t, and They are the upper and lower limits of the transmission power of the tie line respectively.

[0026] Furthermore, based on the consumption of wind and solar renewable energy on the load side, the load curve after the power user participates in the load-source cooperation is determined, including:

[0027] The load side does not consider the load curve of source-load cooperation and pre-dispatches at the lowest system cost, and announces the wind and solar curtailment periods based on the pre-dispatching results;

[0028] According to the load transfer amount reported by the power user during the wind and solar power abandonment period, the load curve after the power user participates in the load-source cooperation is obtained.

[0029] Furthermore, based on the load curve and the lowest system cost, the total green certificate revenue of wind and solar renewable energy power generators and power users participating in the source-load cooperation is determined, including:

[0030] According to the load curve, a power generation plan is determined with the goal of minimizing system cost;

[0031] Based on the power generation plan, the total green certificate income of wind and solar renewable energy power generators participating in source-load cooperation and power users meeting the assessment requirements is determined.

[0032] Furthermore, based on the pre-constructed Shapley value green certificate income distribution model, the total green certificate income is distributed to determine the green certificate income obtained by the power users participating in the source-load cooperation, including:

[0033] The green certificate income distribution model of Shapley value is as follows:

[0034] According to the definition of Shapley value gain sharing theory, the benefit obtained by each sub-member is determined by the average marginal effect.

[0035]

[0036] in

[0037]

[0038] Where: i is the benefit that member i should get when participating in the cooperation; s is the subset of the alliance of participating entities; S i is the set consisting of all subsets containing member i; |s| is the number of elements in set s; A(s) is the total benefit that all members of set s consisting of sub-alliances can obtain by participating in cooperation; A(s\{i}) is the benefit that the system obtains when member i in set s does not participate in cooperation; A(s)-A(s\{i}) is the marginal contribution of member i in joining the cooperative alliance set s. There are a total of (M-|s|)! (|s|-1)! ways for cooperation to occur; the probability of each occurrence is μ(|s|); M is the number of elements in the set of participating cooperative entities;

[0039] The green certificate income obtained by renewable energy power generators and power users after source-load cooperation is calculated as follows:

[0040]

[0041] In the formula, f r and f l are the green certificate income obtained by renewable energy power generators and electricity users respectively; α GCT is the unit green certificate transaction cost; N ob,0 and N ob,1 are the number of green certificates obtained by renewable energy power generators before and after participating in source-load cooperation; μr and μl are the additional green certificate income distribution coefficients of renewable energy power generators and loads obtained by formula (14).

[0042] Furthermore, based on the green certificate income obtained by the power user and the electricity price cost of the transferred load, with the goal of minimizing the total cost of the power user's transferred load, a low-carbon dispatch model for wind and solar power consumption on the load side is established, including:

[0043] The variables for renewable energy curtailment by electricity users are as follows:

[0044]

[0045] Where P q (t) is the amount of renewable energy abandoned in period t, and Z(t) is a 0-1 variable corresponding to whether renewable energy is abandoned or not. When Z(t) is 1, it means that there is renewable energy abandoned in period t. At this time, increasing the load is conducive to promoting the consumption of renewable energy; when Z(t) is 0, it means that there is no renewable energy abandoned in period t, and the load of this period is transferred to the wind and solar abandonment period;

[0046] The wind and solar power consumption low-carbon dispatch model on the load side is established with the minimum total cost of user load transfer. The objective function is as follows:

[0047]

[0048] Where P move (t) is the change in power load during period t, which is positive when the load increases and negative when the load decreases; h(t) is the electricity price during period t; λ GCT It is the conversion coefficient of the number of green certificates in the system. One green certificate corresponds to 1MWh of wind and solar power generation settlement electricity.

[0049] The constraints are as follows:

[0050] The amount of user load transferred during the period of wind and solar power abandonment should not be higher than the amount of wind and solar power abandoned during the same period:

[0051] P r (t)≤P q (t), Z(t)=1 (18)

[0052] The upper and lower limits of the user's actual transferable load

[0053] 0≤|P move (t)|≤δ max (t)P load (t) (19)

[0054] The total load of power users remains unchanged during the dispatch period

[0055]

[0056] Load cannot increase or decrease constraints at the same time

[0057] P r (t)P d (t)=0 (21)

[0058] Changing the user's electricity consumption behavior will reduce the user's electricity consumption satisfaction. In order to ensure that the user adjusts his or her electricity consumption behavior within an acceptable range, the user's electricity consumption satisfaction constraint should also be considered.

[0059] r min ≤r (22)

[0060] Where P r (t) is the load increase during period t, and P move (t) is related to the equation (23); δ max (t) is the upper limit coefficient of load transfer during period t; r min and the lower limit of user electricity satisfaction during the scheduling period, r is the actual user electricity satisfaction, calculated as shown in formula (24);

[0061]

[0062] The present invention also provides a low-carbon dispatching system for wind and solar power consumption based on load-side green certificate income, including:

[0063] The renewable energy consumption determination module is used to determine the consumption of wind and solar renewable energy on the load side according to the system dispatch cost model on the power generation side;

[0064] A green certificate total revenue determination module is used to determine the load curve after the power user participates in the load-source cooperation based on the wind and solar renewable energy consumption on the load side; and determine the green certificate total revenue of the wind and solar renewable energy power generators and power users participating in the source-load cooperation based on the load curve and the system minimum cost;

[0065] A green certificate revenue allocation module is used to allocate the total green certificate revenue based on the pre-built Shapley value green certificate revenue allocation model to determine the green certificate revenue obtained by the power users participating in the source-load cooperation;

[0066] The low-carbon dispatch module is used to establish a low-carbon dispatch model for wind and solar power consumption on the load side according to the green certificate income obtained by the power user and the electricity price cost of the transferred load, with the goal of minimizing the total cost of the power user's load transfer; and complete the low-carbon dispatch of wind and solar power consumption on the load side through the low-carbon dispatch model for wind and solar power consumption on the load side.

[0067] Furthermore, the green certificate total income determination module includes:

[0068] The load side does not consider the load curve of source-load cooperation and pre-dispatches at the lowest system cost, and announces the wind and solar curtailment periods based on the pre-dispatching results;

[0069] According to the load transfer amount reported by the power user during the wind and solar power abandonment period, the load curve after the power user participates in the load-source cooperation is obtained.

[0070] Furthermore, the green certificate total income determination module includes:

[0071] A power generation plan determination module, used to determine a power generation plan based on the load curve with the goal of minimizing system cost;

[0072] The green certificate total revenue determination submodule determines the total green certificate revenue of wind and solar renewable energy power generators participating in source-load cooperation and power users who meet the assessment requirements based on the power generation plan.

[0073] Furthermore, the green certificate income distribution module includes:

[0074] The green certificate income distribution model construction module is based on the green certificate income distribution model of Shapley value Shapley, specifically:

[0075] According to the definition of Shapley value gain sharing theory, the benefit obtained by each sub-member is determined by the average marginal effect.

[0076]

[0077] in

[0078]

[0079] Where: i is the benefit that member i should get when participating in the cooperation; s is the subset of the alliance of participating entities; S iis the set consisting of all subsets containing member i; |s| is the number of elements in set s; A(s) is the total benefit that all members of set s consisting of sub-alliances can obtain by participating in cooperation; A(s\{i}) is the benefit that the system obtains when member i in set s does not participate in cooperation; A(s)-A(s\{i}) is the marginal contribution of member i in joining the cooperative alliance set s. There are a total of (M-|s|)! (|s|-1)! ways for cooperation to occur; the probability of each occurrence is μ(|s|); M is the number of elements in the set of participating cooperative entities;

[0080] The green certificate income obtained by renewable energy power generators and power users after source-load cooperation is calculated as follows:

[0081]

[0082] In the formula, f r and f l are the green certificate income obtained by renewable energy power generators and electricity users respectively; α GCT is the unit green certificate transaction cost; N ob,0 and N ob,1 are the number of green certificates obtained by renewable energy power generators before and after participating in source-load cooperation; μr and μl are the additional green certificate income distribution coefficients of renewable energy power generators and loads obtained by formula (14).

[0083] The present invention provides a low-carbon scheduling method and system for wind and solar power consumption based on green certificate income on the load side, which establishes a source-load connection based on GCT, unifies the wind and solar power consumption targets on both sides of the source and load through green certificates, guides power users to increase their electricity demand during wind and solar power abandonment periods, and reduces the amount of wind and solar power abandoned in the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a flow chart of a low-carbon dispatching method for wind and solar power consumption based on load-side green certificate income provided by an embodiment of the present invention;

[0085] Figure 2 It is a schematic diagram of the wind and solar power consumption function on the load side involved in the embodiment of the present invention;

[0086] Figure 3 This is a flow chart of wind and solar power consumption in cooperation with source load involved in an embodiment of the present invention;

[0087] Figure 4 This is a schematic diagram of the source-load cooperation and wind-solar consumption principle involved in an embodiment of the present invention;

[0088] Figure 5 is a flow chart of user profit distribution involved in an embodiment of the present invention; Figure 6 It is a load information diagram before and after source-load cooperation under a partial power price mechanism involved in an embodiment of the present invention;

[0089] Figure 7 It is a load information diagram before and after source-load cooperation under the time-of-use electricity price mechanism involved in an embodiment of the present invention;

[0090] Figure 8 It is a structural schematic diagram of a wind and solar power consumption low-carbon scheduling system based on load-side green certificate income provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0091] Many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present invention, so the present invention is not limited to the specific implementation disclosed below.

[0092] In view of the above technical problems, the present invention combines the characteristics of GCT and load-side electricity consumption behavior, and proposes a low-carbon dispatching method for wind and solar power consumption that takes into account the green certificate income and source-load cooperation mechanism on the load side. First, according to the system dispatch cost analysis, it is concluded that increasing the load during the wind and solar power abandonment period can promote the consumption of renewable energy; secondly, power users with load transfer capabilities sign a cooperation agreement with renewable energy power generators, and renewable energy power generators provide power users with wind and solar power grid connection information. Users report load transfer capabilities and adjust electricity consumption behaviors based on the wind and solar power abandonment information provided by renewable energy power generators, promote wind and solar grid connection, increase the green certificate income of renewable energy power generators, and reduce carbon emissions generated by their own electricity consumption; then, the green certificate income brought by load transfer is distributed between renewable energy power generators and power users through the Shapley value method; finally, a load-side low-carbon dispatching model is established according to the source-load cooperation principle and process proposed in the present invention. Through simulation analysis, the role of the source-load cooperation mechanism proposed in the present invention in promoting wind and solar grid connection is verified.

[0093] Example 1

[0094] Specifically, the present invention provides a low-carbon dispatching method for wind and solar power consumption based on load-side green certificate income, such as Figure 1 As shown, the following steps are included:

[0095] Step S101, determining the consumption of wind and solar renewable energy on the load side according to the system dispatch cost model on the power generation side.

[0096] The system dispatch cost model on the power generation side is shown in equations (1)-(12). It is easy to see from the dispatch cost model that under the background of CET and GCT, for the built power generation equipment, when the dispatch plan is arranged with the cost optimization as the goal, wind and solar power generation has lower operating costs and better market benefits. When the load is determined, the system will give priority to wind and solar renewable energy power generation. Figure 2 shown.

[0097] The system operates with the goal of minimizing the comprehensive cost, including the coal-burning cost of thermal power units, the operation and maintenance cost of wind and solar renewable energy power generation units, the cost of abandoned wind and solar power, the cost of system participation in carbon trading, and the cost of system participation in green certificates. The minimum comprehensive cost objective function minf is as follows:

[0098] minf=min(f f +f w +f s +f qw +f qs +f CET +f GCT ) (1)

[0099] in:

[0100]

[0101] In the formula, f f is the coal burning cost of thermal power units during the dispatch period; w and f s are respectively the wind power operation cost and photovoltaic power generation operation cost during the dispatch period; w and ε s are the unit operating costs of wind power generation and photovoltaic power generation respectively; ν w and ν s are the unit wind abandonment penalty cost and the unit solar abandonment penalty cost respectively; f CET is the cost of participating in CET during the system scheduling period; α CET is the unit carbon emission rights trading price; R is the set of assessed main units; F i is the actual carbon emissions of unit i during the scheduling period; E i is the carbon quota of unit i during the scheduling period; P i (t) is the power generation of unit i in period t; β i is the carbon emission intensity of unit i; γ i is the carbon emission quota coefficient of unit i; T and Δt are the total duration of the scheduling cycle and the unit scheduling duration respectively; f GCT is the cost of the system participating in GCT; α GCT is the unit green certificate transaction cost; N ne and N ob They are the number of green certificates required for the system to meet the renewable energy consumption quota and the number of green certificates obtained by renewable energy power generators; RPS P is the system green certificate quota coefficient; load (t) is the load during period t; λ GCT P is the system green certificate quantity conversion coefficient; i (t) is the grid-connected power of the i-th renewable energy source in period t; n is the number of renewable energy sources;

[0102] The constraints are as follows:

[0103] Power balance constraints

[0104]

[0105] Output constraints of thermal power units

[0106]

[0107] Power constraints of renewable energy grid-connected electricity

[0108]

[0109] Tie line power constraint

[0110]

[0111] In the formula, and They are the output and climbing power upper and lower limits of thermal power unit i; and are the upper limits of grid-connected power of wind turbines and photovoltaic units respectively; P ex (t) is the transmission power of the tie line during period t, and They are the upper and lower limits of the transmission power of the tie line respectively.

[0112] The power system needs to ensure a dynamic balance between power supply and load. Therefore, the fundamental way to promote the system to absorb wind and solar power and reduce carbon emissions is on the load side. Under the background of priority grid connection of renewable energy on the power generation side, if the load side increases the load during the period of wind and solar abandonment, it can effectively promote the grid connection of wind and solar power in the corresponding period and give full play to the role of renewable energy absorption on the load side.

[0113] Step S102, based on the wind and solar renewable energy consumption on the load side, determine the load curve after the power user participates in the load-source cooperation; according to the load curve and the system minimum cost, determine the total green certificate income of the wind and solar renewable energy power generators and power users participating in the source-load cooperation.

[0114] The source-load cooperation method for consuming renewable energy is based on the existing power generation side model. The load side adjusts the load according to the wind and solar power generation information provided by the renewable energy power generator, increases the power load during the wind and solar power abandonment period, promotes the consumption of renewable energy, and the renewable energy power generator pays the user part of the green certificate income it obtains. Figure 3 As shown:

[0115] First, power users with load transfer capabilities sign an agreement with wind and solar power generators. The system performs pre-dispatch based on the load baseline, that is, the load curve when the load side does not consider source-load cooperation, with the lowest system cost, and announces the wind and solar power abandonment time period based on the pre-dispatch result. Then, the power user reports the load amount that can be transferred during the wind and solar power abandonment period. Next, the system obtains the load curve after the user participates in the source-load cooperation based on the load transfer situation reported by the user, and arranges the power generation plan based on the final load curve with the lowest system cost as the goal. Based on the power generation plan, the total green certificate revenue of wind and solar renewable energy power generators participating in the source-load cooperation and power users who meet the assessment requirements is determined. Finally, a load assessment is conducted on the power users who participate in the response, and users who meet the assessment requirements can obtain part of the green certificate revenue brought by the transferred load.

[0116] Under the background of CET and GCT, the wind and solar power consumption effect on the load side will be more obvious after load transfer, and more renewable energy generation can be connected to the grid during the dispatching period. The process of wind and solar renewable energy generation replacing traditional fossil energy generation will be accelerated, thereby reducing the carbon emissions and system costs generated by coal-fired thermal power units and increasing the green certificate income obtained by wind and solar power generators. Figure 4 shown.

[0117] Step S103, based on the pre-constructed green certificate revenue distribution model of Shapley value, the total revenue of green certificates is distributed to determine the green certificate revenue obtained by the power users participating in the source-load cooperation.

[0118] Profit distribution based on Shapley value can reflect the contribution of each participant to the overall goal, avoid egalitarianism in distribution, and is relatively reasonable and fair. According to the definition of Shapley value gain sharing theory, the benefits obtained by each sub-member are determined by the average marginal effect.

[0119] The green certificate income distribution model of Shapley value is as follows:

[0120] According to the definition of Shapley value gain sharing theory, the benefit obtained by each sub-member is determined by the average marginal effect.

[0121]

[0122] in

[0123]

[0124] Where: i is the benefit that member i should get when participating in the cooperation; s is the subset of the alliance of participating entities; S iis the set consisting of all subsets containing member i; |s| is the number of elements in set s; A(s) is the total benefit that all members of set s consisting of sub-alliances can obtain by participating in cooperation; A(s\{i}) is the benefit that the system obtains when member i in set s does not participate in cooperation; A(s)-A(s\{i}) is the marginal contribution of member i in joining the cooperative alliance set s. There are a total of (M-|s|)! (|s|-1)! ways for cooperation to occur; the probability of each occurrence is μ(|s|); M is the number of elements in the set of participating cooperative entities;

[0125] The green certificate income obtained by renewable energy power generators and power users after source-load cooperation is calculated as follows:

[0126]

[0127] In the formula, f r and f l are the green certificate income obtained by renewable energy power generators and electricity users respectively; α GCT is the unit green certificate transaction cost; N ob,0 and N ob,1 are the number of green certificates obtained by renewable energy power generators before and after participating in source-load cooperation; μr and μl are the additional green certificate income distribution coefficients of renewable energy power generators and loads obtained by formula (14).

[0128] The steps for distributing the income of the Yuanhe Cooperation Green Certificate are as follows:

[0129] (1): Obtain the baseline load curve: The baseline load curve refers to the original load curve without considering the source-load cooperation mechanism.

[0130] (2): Obtain original information: According to the system cost model, calculate the number of green certificates Nob,0 that renewable energy generators can obtain under the baseline load.

[0131] (3): Users adjust their electricity usage behavior: Electricity users adjust their electricity usage behavior based on the wind and solar power curtailment information released by wind and solar renewable energy power generators, transfer the load to the period when wind and solar power curtailment occurs, and promote the consumption of renewable energy.

[0132] (4): Obtain power generation information after user response: Calculate the number of green certificates Nob,1 that renewable energy power generators obtain after power users adjust their loads based on wind and solar power abandonment information.

[0133] (5): Baseline load assessment for power users: The baseline load of power users is assessed, and users who meet the assessment requirements can obtain green certificate benefits.

[0134] (6): Benefit calculation: Users who meet the baseline load assessment calculate their own green certificate benefits according to formula (8) and formula (14)-(15).

[0135] The allocation process is as follows Figure 5 shown.

[0136] Step S104, based on the green certificate income obtained by the power user and the electricity price cost of load transfer, with the goal of minimizing the total cost of load transfer for the power user, establish a low-carbon dispatch model for wind and solar power consumption on the load side; through the low-carbon dispatch model for wind and solar power consumption on the load side, complete the low-carbon dispatch of wind and solar power consumption on the load side.

[0137] Power users adjust their electricity consumption behavior based on wind and solar power abandonment information to promote the consumption of renewable energy. To facilitate model establishment, the renewable energy abandonment variables of power users are as follows:

[0138]

[0139] Where P q (t) is the amount of renewable energy abandoned in period t, and Z(t) is a 0-1 variable corresponding to whether renewable energy is abandoned or not. When Z(t) is 1, it means that there is renewable energy abandoned in period t. At this time, increasing the load is conducive to promoting the consumption of renewable energy; when Z(t) is 0, it means that there is no renewable energy abandoned in period t, and the load of this period is transferred to the wind and solar abandonment period;

[0140] The wind and solar power consumption low-carbon dispatch model on the load side is established with the minimum total cost of user load transfer. The objective function is as follows:

[0141]

[0142] Where P move (t) is the change in power load during period t, which is positive when the load increases and negative when the load decreases; h(t) is the electricity price during period t; λ GCT It is the conversion coefficient of the number of green certificates in the system. One green certificate corresponds to 1MWh of wind and solar power generation settlement electricity.

[0143] The constraints are as follows:

[0144] The amount of user load transferred during the period of wind and solar power abandonment should not be higher than the amount of wind and solar power abandoned during the same period:

[0145] P r (t)≤P q (t), Z(t)=1 (18)

[0146] The upper and lower limits of the user's actual transferable load

[0147] 0≤P move (t)≤δ max (t)P load (t) (19)

[0148] The total load of power users remains unchanged during the dispatch period

[0149]

[0150] Load cannot increase or decrease constraints at the same time

[0151] P r (t)P d (t)=0 (21)

[0152] Changing the user's electricity consumption behavior will reduce the user's electricity consumption satisfaction. In order to ensure that the user adjusts his or her electricity consumption behavior within an acceptable range, the user's electricity consumption satisfaction constraint should also be considered.

[0153] r min ≤r (22)

[0154] Where P r (t) is the load increase during period t, and P move (t) is related to the equation (23); δ max (t) is the upper limit coefficient of load transfer during period t; r min and the lower limit of user electricity satisfaction during the scheduling period, r is the actual user electricity satisfaction, calculated as shown in formula (24);

[0155]

[0156] Example 2

[0157] In order to verify the effectiveness of the low-carbon scheduling method proposed in this invention, the following scenarios are set for comparative analysis:

[0158] Scenario 1, the basic scenario, does not consider source-load cooperation and time-of-use electricity prices.

[0159] Scenario 2: Based on Scenario 1, source-load cooperation is considered.

[0160] Scenario 3: Consider the time-of-use electricity price mechanism.

[0161] Scenario 4: Source-load cooperation is considered based on the time-of-use electricity price mechanism of Scenario 3.

[0162] Four scenarios are simulated and the cost comparison is shown in Table 1.

[0163] Table 1 Comparison of system operation results in various scenarios

[0164]

[0165] As can be seen from Table 1, whether it is a partial power price scenario or a time-of-use power price scenario, after considering the source-load cooperation, the system's CET cost, GCT cost, comprehensive total cost, green power ratio, carbon emissions, wind and solar power curtailment, net load peak-valley difference, etc. are all improved. This shows that the source-load cooperation mechanism proposed in the present invention can increase the amount of renewable energy connected to the grid and reduce the system's comprehensive cost and carbon emissions on the basis of ensuring the net load peak-valley difference of the power system.

[0166] Scenario 2 applies the source-load cooperation mechanism proposed in the present invention on the basis of a portion of the electricity price in Scenario 1. Compared with Scenario 1, the total system cost on a single dispatch day is reduced by 4.45%, the wind and solar power curtailment is reduced by 358.08MWh, and CO2 emissions are reduced by 332.69 tons. This is because after the establishment of the source-load cooperation, users obtain wind and solar power curtailment information from renewable energy power generators every day. Under the incentive of green certificate income, users will transfer the load to the wind and solar power curtailment period. Because wind and solar power generation have lower cost advantages under the background of CET and GCT, after the load is transferred to the wind and solar power curtailment period, the system will give priority to grid-connected wind and solar power generation in the corresponding period, which is conducive to increasing the proportion of green electricity in the system and reducing costs. Because wind power dominates renewable energy power generation, wind power has anti-peak regulation characteristics. The transfer of load from other periods to the wind and solar power curtailment period can reduce the load peak, which is conducive to reducing the net load peak-to-valley difference. Consider the load information before and after the source-load cooperation. Figure 6 As shown, the amount of wind and solar power curtailment refers to the amount of wind and solar power curtailment in the original scenario.

[0167] Scenario 4 applies the source-load cooperation mechanism proposed in this invention on the basis of the time-of-use electricity price in Scenario 3. Compared with Scenario 3, the total system cost on a single dispatch day is reduced by 4.12%, the wind and solar power curtailment is reduced by 286.62MWh, and CO2 emissions are reduced by 262.74 tons. Scenario 4 applies the source-load cooperation mechanism proposed in this article after considering the time-of-use electricity price demand response, which can reflect the difference in wind and solar power output in the same electricity price range, and show this difference through green certificates to attract users' attention.

[0168] Although time-of-use electricity prices can promote the grid connection of wind and solar renewable energy, there is still room for further improvement in the role of time-of-use electricity prices in absorbing renewable energy on the load side. This is because the price range of time-of-use electricity prices remains unchanged in the short term, while the wind and solar output on different dispatch days is random, resulting in the high-generation period of wind power and the low-load period, as well as the low-generation period of wind power and the peak load period, only maintaining the same overall trend, not strictly corresponding to each period, and the wind and solar output in the same electricity price range is random. When users adjust their electricity consumption behavior with the goal of minimizing their own electricity costs, they will not consider the difference in wind and solar output in different periods of the same electricity price range. Therefore, time-of-use electricity price demand response is still insufficient in tapping the wind and solar absorption capacity on the load side.

[0169] Load information before and after source-load cooperation under the time-of-use electricity price mechanism is as follows: Figure 7As shown in the figure, after the source-load cooperation relationship is established, the accuracy of user load transfer tracking renewable energy output is improved through the wind and solar curtailment signals. In most periods, the user load in scenario 4 is consistent with the TOU scenario. This is because the price difference of unit electricity in different electricity price periods is higher than the green certificate income brought by unit electricity to promote wind and solar consumption. When users make decisions on their own electricity consumption behavior, the priority of the electricity price range is higher than the priority of the wind and solar curtailment period. Unlike TOU electricity prices, after considering the source-load cooperation, users will pay attention to the difference in wind and solar output in different periods of the same electricity price range, and give priority to transferring loads to the wind and solar curtailment period in the lower electricity price range. Taking the scenario in this article as an example, the electricity price of the 8th to 10th period is the same as that of the 14th to 16th period, but there is wind and solar curtailment in the 14th to 16th period. Under the same electricity price conditions, users will give priority to transferring loads to the 14th to 16th period to obtain additional green certificate income.

[0170] The above-mentioned calculation example verification is an illustrative demonstration of the proposed patent, and is not a limitation of the proposed dispatching method. The low-carbon dispatching method for wind and solar power consumption that considers the green certificate income on the load side and the source-load cooperation mechanism proposed in the present invention has a relatively wide applicability. For ordinary technicians in the field of power systems, other different forms of changes or modifications can be made on the basis of the above description, and the changes or modifications derived therefrom are still within the protection scope of the invention.

[0171] Example 3

[0172] Based on the same inventive concept, the present invention also provides a wind and solar power consumption low-carbon dispatching system 800 based on load-side green certificate income, including:

[0173] The renewable energy consumption determination module 810 is used to determine the consumption of wind and solar renewable energy on the load side according to the system dispatch cost model on the power generation side;

[0174] The green certificate total revenue determination module 820 is used to determine the load curve after the power user participates in the load-source cooperation based on the wind and solar renewable energy consumption on the load side; determine the green certificate total revenue of the wind and solar renewable energy power generators and power users participating in the source-load cooperation according to the load curve and the system minimum cost;

[0175] The green certificate revenue allocation module 830 is used to allocate the total green certificate revenue based on the pre-constructed Shapley value green certificate revenue allocation model to determine the green certificate revenue obtained by the power users participating in the source-load cooperation;

[0176] The low-carbon dispatch module 840 is used to establish a low-carbon dispatch model for wind and solar power consumption on the load side based on the green certificate income obtained by the power user and the electricity price cost of the transferred load, with the goal of minimizing the total cost of the power user's load transfer; and complete the low-carbon dispatch of wind and solar power consumption on the load side through the low-carbon dispatch model for wind and solar power consumption on the load side.

[0177] Furthermore, the green certificate total income determination module includes:

[0178] The load side does not consider the load curve of source-load cooperation and pre-dispatches at the lowest system cost, and announces the wind and solar curtailment periods based on the pre-dispatching results;

[0179] According to the load transfer amount reported by the power user during the wind and solar power abandonment period, the load curve after the power user participates in the load-source cooperation is obtained.

[0180] Furthermore, the green certificate total income determination module includes:

[0181] A power generation plan determination module, used to determine a power generation plan based on the load curve with the goal of minimizing system cost;

[0182] The green certificate total revenue determination submodule determines the total green certificate revenue of wind and solar renewable energy power generators participating in source-load cooperation and power users who meet the assessment requirements based on the power generation plan.

[0183] Furthermore, the green certificate income distribution module includes:

[0184] The green certificate income distribution model construction module is based on the green certificate income distribution model of Shapley value Shapley, specifically:

[0185] According to the definition of Shapley value gain sharing theory, the benefit obtained by each sub-member is determined by the average marginal effect.

[0186]

[0187] in

[0188]

[0189] Where: i is the benefit that member i should get when participating in the cooperation; s is the subset of the alliance of participating entities; S i is the set consisting of all subsets containing member i; |s| is the number of elements in set s; A(s) is the total benefit that all members of set s composed of sub-alliances can obtain by participating in the cooperation; A(s\{i}) is the benefit that the system obtains when member i in set s does not participate in the cooperation; A(s)-A(s\{i}) is the marginal contribution of member i in joining the cooperative alliance set s. The total benefit of cooperation is There are ways for each of them to appear; the probability of each occurrence is μ(|s|); M is the number of elements in the alliance set of participating cooperative entities;

[0190] The green certificate income obtained by renewable energy power generators and power users after source-load cooperation is calculated as follows:

[0191]

[0192] In the formula, f r and f l are the green certificate income obtained by renewable energy power generators and electricity users respectively; α GCT is the unit green certificate transaction cost; N ob,0 and N ob,1 are the number of green certificates obtained by renewable energy power generators before and after participating in source-load cooperation; μr and μl are the additional green certificate income distribution coefficients of renewable energy power generators and loads obtained by formula (14).

[0193] The present invention provides a low-carbon scheduling method and system for wind and solar power consumption based on green certificate income on the load side, which establishes a source-load connection based on GCT, unifies the wind and solar power consumption targets on both sides of the source and load through green certificates, guides power users to increase their electricity demand during wind and solar power abandonment periods, and reduces the amount of wind and solar power abandoned in the system.

[0194] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0195] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0196] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0197] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalents that do not depart from the spirit and scope of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A low-carbon dispatching method for wind and solar power consumption based on the green certificate income of the load side, characterized in that: include: Determine the consumption of wind and solar renewable energy on the load side based on the system dispatch cost model on the power generation side; Based on the wind and solar renewable energy consumption on the load side, determine the load curve after the power user participates in the load-source cooperation; based on the load curve and the minimum system cost, determine the total green certificate income of the wind and solar renewable energy power generators and power users participating in the source-load cooperation; Based on the pre-built Shapley value green certificate income distribution model, the total income of the green certificate is distributed to determine the green certificate income obtained by the power users participating in the source-load cooperation; According to the green certificate income obtained by the electricity user and the electricity price cost of load transfer, a low-carbon dispatch model for wind and solar power consumption on the load side is established with the goal of minimizing the total cost of load transfer for the electricity user; through the low-carbon dispatch model for wind and solar power consumption on the load side, the low-carbon dispatch of wind and solar power consumption on the load side is completed.

2. The method according to claim 1, characterized in that According to the system dispatch cost model on the power generation side, determine the consumption of wind and solar renewable energy on the load side, including: The system operates with the goal of minimizing the comprehensive cost, including the coal cost of thermal power units, the operation and maintenance cost of wind and solar renewable energy power generation units, the cost of abandoned wind and solar power, the cost of system participation in carbon trading, and the cost of system participation in green certificates. The minimum comprehensive cost objective function min f is as follows: min f=min(f f +f w +f s +f qw +f qs +f CET +f GCT ) (1) in: In the formula, f f is the coal burning cost of thermal power units during the dispatch period; w and f s are respectively the wind power operation cost and photovoltaic power generation operation cost during the dispatch period; w and ε s are the unit operating costs of wind power generation and photovoltaic power generation respectively; ν w and ν s are the unit wind abandonment penalty cost and the unit solar abandonment penalty cost respectively; f CET is the cost of participating in CET during the system scheduling period; α CET is the unit carbon emission rights trading price; R is the set of assessed main units; F i is the actual carbon emissions of unit i during the scheduling period; E i is the carbon quota of unit i during the scheduling period; P i (t) is the power generation of unit i in period t; β i is the carbon emission intensity of unit i; γ i is the carbon emission quota coefficient of unit i; T and Δt are the total duration of the scheduling cycle and the unit scheduling duration respectively; f GCT is the cost of the system participating in GCT; α GCT is the unit green certificate transaction cost; N ne and N ob They are the number of green certificates required for the system to meet the renewable energy consumption quota and the number of green certificates obtained by renewable energy power generators; RPS P is the system green certificate quota coefficient; load (t) is the load during period t; λ GCT P is the system green certificate quantity conversion coefficient; i (t) is the grid-connected power of the i-th renewable energy source in period t; n is the number of renewable energy sources; The constraints are as follows: Power balance constraints Output constraints of thermal power units Power constraints of renewable energy grid-connected electricity Tie line power constraint In the formula, and They are the output and climbing power upper and lower limits of thermal power unit i respectively; and are the upper limits of grid-connected power of wind turbines and photovoltaic units respectively; P ex (t) is the transmission power of the tie line during period t, and They are the upper and lower limits of the transmission power of the tie line respectively.

3. The method according to claim 1, characterized in that Based on the consumption of wind and solar renewable energy on the load side, the load curve after the power user participates in the load-source cooperation is determined, including: The load side does not consider the load curve of source-load cooperation and pre-dispatches at the lowest system cost, and announces the wind and solar curtailment periods based on the pre-dispatching results; According to the load transfer amount reported by the power user during the wind and solar power abandonment period, the load curve after the power user participates in the load-source cooperation is obtained.

4. The method according to claim 1, characterized in that: Based on the load curve and the lowest system cost, the total green certificate revenue of wind and solar renewable energy power generators and power users participating in the source-load cooperation is determined, including: According to the load curve, a power generation plan is determined with the goal of minimizing system cost; Based on the power generation plan, the total green certificate income of wind and solar renewable energy power generators participating in source-load cooperation and power users meeting the assessment requirements is determined.

5. The method according to claim 1, characterized in that Based on the pre-built Shapley value green certificate income distribution model, the total income of the green certificate is distributed to determine the green certificate income obtained by the power users participating in the source-load cooperation, including: The green certificate income distribution model of Shapley value is as follows: According to the definition of Shapley value gain sharing theory, the benefit obtained by each sub-member is determined by the average marginal effect. in Where: i is the benefit that member i should get when participating in the cooperation; s is the subset of the alliance of participating entities; S i is the set consisting of all subsets containing member i; |s| is the number of elements in set s; A(s) is the total benefit that all members of set s consisting of sub-alliances can obtain by participating in cooperation; A(s\{i}) is the benefit that the system obtains when member i in set s does not participate in cooperation; A(s)-A(s\{i}) is the marginal contribution of member i in joining the cooperative alliance set s. There are a total of (M-|s|)! (|s|-1)! ways for cooperation to occur; the probability of each occurrence is μ(|s|); M is the number of elements in the set of participating cooperative entities; The green certificate income obtained by renewable energy power generators and power users after source-load cooperation is calculated as follows: In the formula, f r and f l are the green certificate income obtained by renewable energy power generators and electricity users respectively; α GCT is the unit green certificate transaction cost; N ob,0 and N ob,1 are the number of green certificates obtained by renewable energy power generators before and after participating in source-load cooperation; μr and μl are the additional green certificate income distribution coefficients of renewable energy power generators and loads obtained by formula (14).

6. The method according to claim 1, characterized in that According to the green certificate income obtained by the power user and the electricity price cost of the transferred load, with the goal of minimizing the total cost of the power user's transferred load, a low-carbon dispatch model for wind and solar power consumption on the load side is established, including: The variables for renewable energy curtailment by electricity users are as follows: Where P q (t) is the amount of renewable energy abandoned in period t, and Z(t) is a 0-1 variable corresponding to whether renewable energy is abandoned or not. When Z(t) is 1, it means that there is renewable energy abandoned in period t. At this time, increasing the load is conducive to promoting the consumption of renewable energy; when Z(t) is 0, it means that there is no renewable energy abandoned in period t, and the load of this period is transferred to the wind and solar abandonment period; The wind and solar power consumption low-carbon dispatch model on the load side is established with the minimum total cost of user load transfer. The objective function is as follows: Where P move (t) is the change in power load during period t, which is positive when the load increases and negative when the load decreases; h(t) is the electricity price during period t; λ GCT It is the conversion coefficient of the number of green certificates in the system. One green certificate corresponds to 1MWh of wind and solar power generation settlement electricity. The constraints are as follows: The amount of user load transferred during the period of wind and solar power abandonment should not be higher than the amount of wind and solar power abandoned during the same period: P r (t)≤P q (t),Z(t)=1 (18) The upper and lower limits of the user's actual transferable load 0≤|P move (t)|≤δ max (t)P load (t) (19) The total load of power users remains unchanged during the dispatch period Load cannot increase or decrease constraints at the same time P r (t)P d (t)=0 (21) Changing the user's electricity consumption behavior will reduce the user's electricity consumption satisfaction. In order to ensure that the user adjusts his or her electricity consumption behavior within an acceptable range, the user's electricity consumption satisfaction constraint should also be considered. r min ≤r (22) Where P r (t) is the load increase during period t, and P move (t) is shown in equation (23); δ max (t) is the upper limit coefficient of load transfer during period t; r min and the lower limit of user electricity satisfaction during the scheduling period, r is the actual user electricity satisfaction, calculated as shown in formula (24); 7. A low-carbon dispatching system for wind and solar power consumption based on the green certificate income of the load side, characterized by: include: The renewable energy consumption determination module is used to determine the consumption of wind and solar renewable energy on the load side according to the system dispatch cost model on the power generation side; A green certificate total revenue determination module is used to determine the load curve after the power user participates in the load-source cooperation based on the wind and solar renewable energy consumption on the load side; and to determine the green certificate total revenue of the wind and solar renewable energy power generators and power users participating in the source-load cooperation based on the load curve and the system minimum cost; A green certificate revenue allocation module is used to allocate the total green certificate revenue based on a pre-built Shapley value green certificate revenue allocation model to determine the green certificate revenue obtained by the power users participating in the source-load cooperation; The low-carbon dispatch module is used to establish a low-carbon dispatch model for wind and solar power consumption on the load side according to the green certificate income obtained by the power user and the electricity price cost of the transferred load, with the goal of minimizing the total cost of the power user's load transfer; and complete the low-carbon dispatch of wind and solar power consumption on the load side through the low-carbon dispatch model for wind and solar power consumption on the load side.

8. The system according to claim 7, characterized in that The green certificate total income determination module includes: The load side does not consider the load curve of source-load cooperation and pre-dispatches at the lowest system cost, and announces the wind and solar curtailment periods based on the pre-dispatching results; According to the load transfer amount reported by the power user during the wind and solar power abandonment period, the load curve after the power user participates in the load-source cooperation is obtained.

9. The system according to claim 7, characterized in that The green certificate total income determination module includes: A power generation plan determination module, used to determine a power generation plan based on the load curve with the goal of minimizing system cost; The green certificate total revenue determination submodule determines the total green certificate revenue of wind and solar renewable energy power generators participating in source-load cooperation and power users who meet the assessment requirements based on the power generation plan.

10. The system according to claim 7, characterized in that Green certificate income distribution module, including: The green certificate income distribution model construction module is based on the green certificate income distribution model of Shapley value Shapley, specifically: According to the definition of Shapley value gain sharing theory, the benefit obtained by each sub-member is determined by the average marginal effect. in Where: i is the benefit that member i should get when participating in the cooperation; s is the subset of the alliance of participating entities; S i is the set consisting of all subsets containing member i; |s| is the number of elements in set s; A(s) is the total benefit that all members of set s consisting of sub-alliances can obtain by participating in cooperation; A(s\{i}) is the benefit that the system obtains when member i in set s does not participate in cooperation; A(s)-A(s\{i}) is the marginal contribution of member i in joining the cooperative alliance set s. There are a total of (M-|s|)! (|s|-1)! ways for cooperation to occur; the probability of each occurrence is μ(|s|); M is the number of elements in the set of participating cooperative entities; The green certificate income obtained by renewable energy power generators and power users after source-load cooperation is calculated as follows: In the formula, f r and f l are the green certificate income obtained by renewable energy power generators and electricity users respectively; α GCT is the unit green certificate transaction cost; N ob,0 and N ob,1 are the number of green certificates obtained by renewable energy power generators before and after participating in source-load cooperation; μr and μl are the additional green certificate income distribution coefficients of renewable energy power generators and loads obtained by formula (14).

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