CN113285482A - Method and system for determining proportion of renewable energy sources to be connected into power grid - Google Patents

Method and system for determining proportion of renewable energy sources to be connected into power grid Download PDF

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CN113285482A
CN113285482A CN202110643236.7A CN202110643236A CN113285482A CN 113285482 A CN113285482 A CN 113285482A CN 202110643236 A CN202110643236 A CN 202110643236A CN 113285482 A CN113285482 A CN 113285482A
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flexibility
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reservation
carbon
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CN113285482B (en
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王蓓蓓
顾伟扬
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Southeast University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00—Adapting or protecting infrastructure or their operation
    • Y02A30/60—Planning or developing urban green infrastructure
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

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Abstract

The invention discloses a method for determining the proportion of renewable energy sources accessed to a power grid, which comprises the following steps: s1, considering the interaction among the new energy access proportion, the unit output, the flexibility reservation and the carbon emission cost, and establishing a model with the minimum total cost; s2, connecting the flexibility reservation model and the new energy to the ratio mu, and connecting the new energy and the load removal amount curlt、loadshedtCouple and deduce the curve about mu, curet、loadshedtFlexibility of reservation demand function; and S3, proposing a flexibility reservation variable from 0 to 1, constructing a carbon permutation cost function influenced by the flexibility reservation, and converting the carbon permutation cost function into a linear function related to the flexibility reservation. The invention researches the carbon emission influence caused by the fact that a large amount of power grids are accessed according to the carbon reduction and emission reduction requirements at present, and establishes the flexible new energy accessThe method comprises the steps of reserving a demand and carbon emission model, building a safe and stable power grid, calculating optimal new energy access and unit operation efficiency, and solving the balance problem between new energy consumption and energy conservation and emission reduction.

Description

Method and system for determining proportion of renewable energy sources to be connected into power grid
Technical Field
The invention relates to the technical field of electric power, in particular to a method and a system for determining the proportion of renewable energy sources connected to a power grid.
Background
With the proposal of 'carbon peak reaching and carbon neutralization', renewable energy is more concerned and researched to replace the traditional fossil energy to be connected into a power grid for power generation. However, renewable energy is limited by natural factors such as weather and the like, uncertainty is full of, the problem of safety and stability of the power grid can be caused when the renewable energy is accessed into the power grid in a large scale, and in order to match with the uncertainty of the output of the new energy, the fluctuation of the output of the new energy can be compensated by utilizing the characteristic that a unit can artificially determine the output.
The carbon emission coefficient of the unit is generally stable and unchanged in a normal output state, but when the unit is left for rotary standby, the efficiency of the unit is reduced, and the carbon emission coefficient may be increased due to the reserved flexibility. In this context, it is necessary to study the relationship between the proportion of new energy access and the flexibility reserve and carbon emission cost in certain power systems. The carbon emission can be effectively reduced after the renewable energy is added into the power grid, but meanwhile, in order to deal with the uncertainty of the new energy, a set needs to be reserved with certain flexibility, so that the carbon emission coefficient of the set is increased to a certain extent, and the carbon emission can be increased. Therefore, a method for determining a suitable renewable energy access ratio is needed to reduce carbon emissions and wind abandonment while ensuring stable operation of a power grid.
Disclosure of Invention
To address the above-mentioned deficiencies of the background art, it is an object of the present invention to provide.
The purpose of the invention can be realized by the following technical scheme:
a method for determining the proportion of renewable energy sources accessed to a power grid comprises the following steps:
s1, considering the interaction among the new energy access proportion, the unit output, the flexibility reservation and the carbon emission cost, and establishing a model with the minimum total cost;
s2, connecting the flexibility reservation model and the new energy to the ratio mu, and connecting the new energy and the load removal amount curlt、loadshedtCouple and deduce the curve about mu, curet、loadshedtFlexibility of reservation demand function;
and S3, proposing a flexibility reservation variable from 0 to 1, constructing a carbon permutation cost function influenced by the flexibility reservation, and converting the carbon permutation cost function into a linear function related to the flexibility reservation.
Preferably, step S1 includes:
s101, association of unit output and flexibility reservation
The unit output cost function:
Figure BDA0003108819260000021
wherein, C (P)g,t) For the unit operating costs, ag、bg、cgTo cost factor, Pg,tThe output of the unit g at the moment t;
flexibility reservation cost function:
Figure BDA0003108819260000022
Figure BDA0003108819260000023
wherein the content of the first and second substances,
Figure BDA0003108819260000024
reserve cost for flexibility, vg,t、wg,tProviding a 0-1 state quantity with upward and downward flexibility for the unit g at the time t,
Figure BDA0003108819260000025
the cost is reserved for the flexibility of the upper part and the lower part,
Figure BDA0003108819260000026
Figure BDA0003108819260000027
reserving the upward and downward flexibility for the unit g at the moment t;
coupling the output of the unit and the reserved flexibility:
Figure BDA0003108819260000028
Figure BDA0003108819260000029
wherein u isg,t、
Figure BDA00031088192600000210
Respectively representing a variable of 0-1 of the output state of the unit and the maximum and minimum values of the output of the unit;
s102, associating the output of the unit with the new energy access proportion
Figure BDA0003108819260000031
Wherein, curet、loadshedtFor the new energy and the load removal amount,
Figure BDA0003108819260000032
Ploadmaxis the net load, maximum load at time t, mu,
Figure BDA0003108819260000033
The new energy access proportion, the new energy prediction value and the new energy prediction per unit value are obtained;
s103, associating new energy access with flexibility reservation requirement
Figure BDA0003108819260000034
Figure BDA0003108819260000035
Wherein, FRUt、FRDtReserving requirements for the flexibility at the moment t, wherein sigma is the uncertainty of new energy, wind, and,
Figure BDA0003108819260000036
Is newEnergy sources are maximum and minimum;
s104, flexibility reservation, unit output and carbon emission association
Figure BDA0003108819260000037
Wherein, C (CE)g,t)、
Figure BDA0003108819260000038
M is the carbon emission cost and cost coefficientg、ngIn order to provide the increased carbon rank coefficient ratio when the up/down flexibility is reserved, xi is the carbon rank coefficient, and tau is the time interval.
Preferably, step S2 is specifically:
the flexibility reservation requirement is associated with the uncertainty of the new energy, the new energy and the load shedding amount:
Figure BDA0003108819260000039
Figure BDA00031088192600000310
wherein the amount of uncertainty
Figure BDA00031088192600000311
wind＝μ·loadmaxThen the correlation function F can be obtained1And F2：
Figure BDA00031088192600000312
Figure BDA0003108819260000041
Wherein the content of the first and second substances,
Figure BDA0003108819260000042
and (4) obtaining a per unit value of the new energy cutting amount.
Preferably, step S3 is specifically:
carbon sequestration cost function under influence of flexibility reservation
Figure BDA0003108819260000043
Wherein v isg,t、wg,tMust satisfy under the condition of unit start-up can get 1, specifically as follows:
0≤vg,t≤ug,t、0≤wg,t≤ug,t
the carbon rank cost function is a mixed integer nonlinear model, which is not beneficial to solving the optimal value, so the model needs to be linearized. It has been found from carbon emission cost constitution to mainly include two aspects: the carbon row that causes is arranged with the flexibility reservation to unit output carbon, specifically as follows:
Figure BDA0003108819260000044
wherein m xig＝mg·ξ，nξg＝ξ·ng。
Preferably, the model linearization method is as follows:
if the objective function contains a variable 0-1, it is very difficult to solve the optimal solution, and in order to simplify the difficulty of model solution, a certain linearization process needs to be performed on the mixed integer programming model, wherein the variable 0-1 mainly comprises ug,t、vg,t、wg,tAnd reserving state quantity for the startup and flexibility of the unit, and relaxing the nonlinear model according to the relationship among the three components to obtain the following linearized model:
Figure BDA0003108819260000045
Figure BDA0003108819260000046
Figure BDA0003108819260000047
Figure BDA0003108819260000048
Figure BDA0003108819260000049
a system for determining the proportion of renewable energy sources accessed to a power grid collects information such as a unit and new energy sources of the power grid; predicting the output of the new energy, and establishing an uncertain model of the new energy; the system establishes a comprehensive model considering carbon emission, flexibility reservation and new energy access proportion, obtains the optimal new energy access proportion by solving and comparing models with different access proportions, and plans and predicts the construction scale of new energy.
The invention has the beneficial effects that:
according to the invention, the carbon emission influence caused by the fact that a large amount of power grids are connected aiming at the carbon reduction and emission reduction requirements at present is researched, a model containing new energy access, flexibility reservation requirements and carbon emission is established, a safe and stable power grid is established, the optimal new energy access and unit operation efficiency are calculated, and the balance problem between new energy consumption and energy conservation and emission reduction is solved.
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The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a schematic flow chart of an embodiment of the present invention;
FIG. 2 shows the direct interaction relationship among the unit, new energy, carbon emission and flexibility reservation;
FIG. 3 is a load power curve and a predicted per unit value curve of new energy (wind power);
FIG. 4 is a wind power permeability and wind curtailment relationship under a flexibility reservation condition;
FIG. 5 illustrates the selection of units under different access ratios, considering carbon sequestration and flexibility reservation;
FIG. 6 is a graph of different permeability values taking into account the carbon rejection cost effect factor.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "opening," "upper," "lower," "thickness," "top," "middle," "length," "inner," "peripheral," and the like are used in an orientation or positional relationship that is merely for convenience in describing and simplifying the description, and do not indicate or imply that the referenced component or element must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be considered as limiting the present invention.
The embodiment provides flexibility reservation and carbon emission change under the condition of changing the access proportion of new energy (wind power) in a system with five machines and 500MW of maximum load.
The method mainly comprises the steps as shown in figure 1, unit information is shown in table 1, and load and wind power prediction per unit values are shown in figure 3; the relationship among the unit output, the new energy, the carbon emission and the flexibility reservation is shown in fig. 2, on one hand, the new energy is accessed to reduce the ratio of the unit output, on the other hand, the generated uncertainty causes the requirement of the power grid on the flexibility reservation, the flexibility reservation can cause the increase of the carbon emission, and in order to reduce the cost of the carbon emission, a balance needs to be made between the ratio of the new energy access and the level of the unit output.
Table 1: unit information
Figure BDA0003108819260000061
(1) Establishing a T-hour prediction model comprising a new energy prediction model and a load prediction model, and calculating the prediction uncertainty of the new energy:
σ＝windpre/5+wind/50
(2) calculating the flexibility reservation requirement of the new energy access condition:
Figure BDA0003108819260000071
Figure BDA0003108819260000072
(3) calculating the relation between the flexibility reservation requirement and the new energy and load removal:
Figure BDA0003108819260000073
Figure BDA0003108819260000074
wherein:
Figure BDA0003108819260000075
(4) establishing a permeability-related objective function considering carbon emission, flexibility reservation and minimization of unit operation cost, wherein the function period is Th (in the example, 24h is selected), and the time interval is Th (in the example, 1h is selected), and the specific steps are as follows:
Figure BDA0003108819260000076
the composition of each component is specified:
the unit operates:
Figure BDA00031088192600000710
the unit starts:
Figure BDA0003108819260000077
cost for cutting new energy: c (curl)t)＝pricecurt·curtt
Abandon the load cost: c (loadshed)t)＝priceloadshed·loadshedt
Upper flexibility reserve cost:
Figure BDA0003108819260000078
the following flexibility reserve costs:
Figure BDA0003108819260000079
carbon emission cost:
Figure BDA0003108819260000081
(5) establishing constraint conditions according to physical characteristics of the unit and the new energy:
balance constraint:
Figure BDA0003108819260000082
unit output restraint:
Figure BDA0003108819260000083
and (3) reserving constraint on upward and downward flexibility of the unit:
Figure BDA0003108819260000084
Figure BDA0003108819260000085
the unit provides 0-1 variable constraint whether the unit is flexible or not: v is not less than 0g,t≤ug,t、0≤wg,t≤ug,t
System flexibility requirementsAnd (3) constraint:
Figure BDA0003108819260000086
(6) the above model needs a certain conversion due to the existence of 0-1 variable, and is equivalent to a linear optimization model:
upper flexibility reservation linearization:
Figure BDA0003108819260000087
flexibility reservation linearization:
Figure BDA0003108819260000088
(7) the carbon emission cost function shows that the carbon emission cost is related to the output of the unit and the flexibility reservation, the nonlinear function can be converted into the following linear function, and the increased carbon emission caused by the flexibility reservation is
Figure BDA0003108819260000089
Wherein m xig＝mg·ξ，nξg＝ξ·ng：
Figure BDA00031088192600000810
In order to conveniently evaluate the quality of new energy under different access proportions, an average carbon rejection coefficient (ppCE) is provided as an index, wherein the CE isg,tCarbon emission:
ppCE＝∑CEg,t/∑Pg,t
(8) the relevant models were built and solved in MATLAB + yalcip + cplex.
Fig. 4 shows the wind curtailment conditions between the carbon emission model and the carbon emission model under different permeabilities, when the permeability is low, the wind curtailment is larger than that of the carbon emission model, the new energy is less accessed, the flexibility reservation requirement is less, but the cost of carbon emission reduction caused by the output of the new energy replacement unit is far greater than the cost increase caused by the flexibility reservation; with the increase of the permeability, the abandoned wind is larger in a model considering the carbon emission, the flexibility requirement caused by the increase of the new energy is increased, the carbon emission cost is increased sharply, and the new energy access proportion is restrained to a certain extent, namely the abandoned wind is increased; when the permeability is continuously increased to a certain degree, the total output of the unit reaches a limit threshold value, the carbon emission also reaches an extreme value, the cost reduction of the carbon emission generated by the output of the unit is reduced far more than the cost increase caused by the reservation of new energy on the flexibility, and therefore the wind abandonment is reduced on the contrary under the condition of considering the carbon emission.
Fig. 5 shows the unit startup combination under different permeabilities, and it can be seen from comparison with fig. 4 that a conventional unit is omitted compared with the permeabilities of 0.34 and 0.42, and the carbon emission coefficient of the conventional unit is much larger than that of the gas unit, so that in the model considering carbon emission, the new energy consumption level is higher and lower, and when the new energy is excessively high, the new energy consumption level is rather improved due to the limit of the unit output and flexibility reservation in the system and the influence on the carbon emission cost.
FIG. 6 shows the carbon rejection coefficients at different permeabilities in a model that accounts for and does not account for carbon rejection costs, which can be seen to be lower than the coefficients that do not account for carbon rejection costs; under the condition of not counting carbon emission, the influence on the cost is mainly on an organic unit, flexibility reservation and consumption level, so that the average coefficient is basically unchanged; however, when the carbon emission cost is considered, the permeability is too high, the unit cost, the carbon emission cost and the flexibility reservation mutually reach the optimal limit, and when the permeability is low, the permeability has larger elasticity of new energy substituting unit output, and the flexibility reservation cost at the moment is not heavy, so the average carbon emission coefficient is lower.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.

Claims (6)

1. A method for determining the proportion of renewable energy sources accessed to a power grid is characterized by comprising the following steps:
s1, considering the interaction among the new energy access proportion, the unit output, the flexibility reservation and the carbon emission cost, and establishing a model with the minimum total cost;
s2, connecting the flexibility reservation model and the new energy to the ratio mu, and connecting the new energy and the load removal amount curlt、loadshedtCouple and deduce the curve about mu, curet、loadshedtFlexibility of reservation demand function;
and S3, proposing a flexibility reservation variable from 0 to 1, constructing a carbon permutation cost function influenced by the flexibility reservation, and converting the carbon permutation cost function into a linear function related to the flexibility reservation.
2. The method for determining the proportion of the renewable energy source accessed to the power grid according to claim 1, wherein the step S1 comprises:
s101, association of unit output and flexibility reservation
The unit output cost function:
Figure FDA0003108819250000011
wherein, C (P)g,t) For the unit operating costs, ag、bg、cgTo cost factor, Pg,tThe output of the unit g at the moment t;
flexibility reservation cost function:
Figure FDA0003108819250000012
Figure FDA0003108819250000013
wherein the content of the first and second substances,
Figure FDA0003108819250000014
reserve cost for flexibility, vg,t、wg,tProviding a 0-1 state quantity with upward and downward flexibility for the unit g at the time t,
Figure FDA0003108819250000015
the cost is reserved for the flexibility of the upper part and the lower part,
Figure FDA0003108819250000016
Figure FDA0003108819250000017
reserving the upward and downward flexibility for the unit g at the moment t;
coupling the output of the unit and the reserved flexibility:
Figure FDA0003108819250000018
Figure FDA0003108819250000019
wherein u isg,t、
Figure FDA0003108819250000021
Respectively a machine set output state 0-1 variable and a machineThe maximum and minimum group output values;
s102, associating the output of the unit with the new energy access proportion
Figure FDA0003108819250000022
Wherein, curet、loadshedtFor new energy and load shedding, Pt NL、Pt load、PloadmaxIs the net load, maximum load at time t, mu,
Figure FDA0003108819250000023
The new energy access proportion, the new energy prediction value and the new energy prediction per unit value are obtained;
s103, associating new energy access with flexibility reservation requirement
Figure FDA0003108819250000024
Figure FDA0003108819250000025
Wherein, FRUt、FRDtReserving requirements for the flexibility at the moment t, wherein sigma is the uncertainty of new energy, wind, and,
Figure FDA0003108819250000026
The maximum and minimum output of new energy is obtained;
s104, flexibility reservation, unit output and carbon emission association
Figure FDA0003108819250000027
Wherein, C (CE)g,t)、
Figure FDA0003108819250000028
M is the carbon emission cost and cost coefficientg、ngIn order to provide the increased carbon rank coefficient ratio when the up/down flexibility is reserved, xi is the carbon rank coefficient, and tau is the time interval.
3. The method for determining the proportion of the renewable energy source to be connected to the power grid according to claim 1, wherein the step S2 specifically comprises:
the flexibility reservation requirement is associated with the uncertainty of the new energy, the new energy and the load shedding amount:
Figure FDA0003108819250000029
Figure FDA00031088192500000210
wherein the amount of uncertainty
Figure FDA0003108819250000031
wind＝μ·loadmaxThen the correlation function F can be obtained1And F2：
Figure FDA0003108819250000032
Figure FDA0003108819250000033
Wherein the content of the first and second substances,
Figure FDA0003108819250000034
and (4) obtaining a per unit value of the new energy cutting amount.
4. The method for determining the proportion of the renewable energy source to be connected to the power grid according to claim 1, wherein the step S3 specifically comprises:
carbon sequestration cost function under influence of flexibility reservation
Figure FDA0003108819250000035
Wherein v isg,t、wg,tMust satisfy under the condition of unit start-up can get 1, specifically as follows:
0≤vg,t≤ug,t、0≤wg,t≤ug,t
the carbon rank cost function is a mixed integer nonlinear model, which is not beneficial to solving the optimal value, so the model needs to be linearized. It has been found from carbon emission cost constitution to mainly include two aspects: the carbon row that causes is arranged with the flexibility reservation to unit output carbon, specifically as follows:
Figure FDA0003108819250000036
wherein m xig＝mg·ξ，nξg＝ξ·ng。
5. The method for determining the proportion of renewable energy sources accessed to the power grid according to claim 1, wherein the linearization method of the model is specifically as follows:
if the objective function contains a variable 0-1, it is very difficult to solve the optimal solution, and in order to simplify the difficulty of model solution, a certain linearization process needs to be performed on the mixed integer programming model, wherein the variable 0-1 mainly comprises ug,t、vg,t、wg,tAnd reserving state quantity for the startup and flexibility of the unit, and relaxing the nonlinear model according to the relationship among the three components to obtain the following linearized model:
Figure FDA0003108819250000037
Figure FDA0003108819250000038
Figure FDA0003108819250000041
Figure FDA0003108819250000042
Figure FDA0003108819250000043
6. a system for determining a proportion of renewable energy resources connected to a power grid, comprising: the system collects information of a set, new energy and the like of a power grid; predicting the output of the new energy, and establishing an uncertain model of the new energy;
the system obtains the optimal new energy access proportion by solving and comparing models with different access proportions according to the models in claims 1-5, and plans and predicts the construction scale of new energy.
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