CN112070397A - Multi-power-supply expansion optimization decision method and system for coordinated operation of non-fossil energy power generation - Google Patents

Multi-power-supply expansion optimization decision method and system for coordinated operation of non-fossil energy power generation Download PDF

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CN112070397A
CN112070397A CN202010932577.1A CN202010932577A CN112070397A CN 112070397 A CN112070397 A CN 112070397A CN 202010932577 A CN202010932577 A CN 202010932577A CN 112070397 A CN112070397 A CN 112070397A
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power generation
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郑宽
闫晓卿
徐志成
张富强
鲁刚
元博
焦冰琦
徐沈智
冯君淑
张晋芳
刘俊
李卓男
栗楠
金艳鸣
伍声宇
傅观君
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State Grid Hebei Electric Power Co Ltd
State Grid Energy Research Institute Co Ltd
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State Grid Energy Research Institute Co Ltd
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    • G06Q10/06375—Prediction of business process outcome or impact based on a proposed change
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q50/06—Electricity, gas or water supply
    • 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
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • 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
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    • 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
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    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses a multi-power-supply expansion optimization decision method and a system considering coordinated operation of non-fossil energy power generation, wherein the method comprises the following steps: determining an optimization objective function by taking the minimum total cost of power supply of the whole society in a prospect as an optimization objective; determining power system extension planning constraints, power system operation constraints, power generation resource constraints, and non-fossil energy power development policy constraints of the optimization objective function; and forming a multi-region multi-scene electric power planning model according to the optimization objective function and the constraint, and solving the multi-region multi-scene electric power planning model. The invention can finally solve the development scale, the layout and the construction time sequence of various power supplies including nuclear power, new energy and the like, and the trans-provincial electric power transmission scale.

Description

Multi-power-supply expansion optimization decision method and system for coordinated operation of non-fossil energy power generation
Technical Field
The invention relates to the technical field of computers, in particular to a multi-power-supply expansion optimization decision method and system considering coordinated operation of non-fossil energy power generation.
Background
Under the global large background of coping with climate change together, the realization of energy clean and low-carbon development is a strategic choice for energy transformation of countries in the world. The nuclear energy and the new energy are used as important components of non-fossil energy, and have a significant role in constructing a clean, low-carbon, safe and efficient energy system in China. With the large-scale intermittent new energy access to the power system, the safe and stable operation of the power grid faces a great challenge. The nuclear power output is stable, the rotational inertia is large, and necessary electric power, electric quantity and rotational inertia support can be provided for a power system accessed by high-proportion new energy. At present, from the aspect of technical economy, the new energy power generation technology is rapidly improved, and the economic competitiveness is continuously improved; and nuclear power is further improved along with the safety requirement, the technology is in the stage of transformation and upgrading from the second generation improvement to the third generation, the market competitiveness is reduced to some extent, and the orderly development of the nuclear power is influenced to a certain extent. Therefore, under the general constraint condition that the residual potential of hydropower is limited and clean energy needs to be developed rapidly in the future, nuclear power and new energy such as wind and light form a relatively obvious mutual substitution relation.
Disclosure of Invention
The invention aims to provide a multi-power-supply expansion optimization decision method and system considering coordinated operation of non-fossil energy power generation, and aims to solve the problems in the prior art.
The invention provides a multi-power supply expansion optimization decision method, which comprises the following steps:
determining an optimization objective function by taking the minimum total cost of power supply of the whole society in a prospect as an optimization objective;
determining power system extension planning constraints, power system operation constraints, power generation resource constraints, and non-fossil energy power development policy constraints of the optimization objective function;
and forming a multi-region multi-scene electric power planning model according to the optimization objective function and the constraint, and solving the multi-region multi-scene electric power planning model.
The invention provides a multi-power-supply expansion optimization decision system considering coordinated operation of non-fossil energy power generation, which comprises:
the optimization objective function module is used for determining an optimization objective function by taking the minimum total cost of the power supply of the whole society in a prospect as an optimization objective;
the constraint calculation module is used for determining power system extension planning constraints, power system operation constraints, power generation resource constraints and non-fossil energy power development policy constraints of the optimization objective function;
and the solving module is used for forming a multi-region multi-scene electric power planning model according to the optimization objective function and the constraint and solving the multi-region multi-scene electric power planning model.
By adopting the embodiment of the invention, according to the development potential, development conditions and energy utilization requirements of the power generation resources in the target area, the lowest total cost of power supply in the whole society in a planning period is taken as a target, the energy supply capacity, power and electricity balance, system operation, environmental space and the like are taken as constraint conditions, the nuclear power and new energy coordinated operation strategy is mainly considered to construct and optimize the problem, and the development scale, the layout and the construction time sequence of various power supplies including nuclear power, new energy and the like and the trans-provincial power transmission scale are finally solved and obtained.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic diagram of a multi-power-supply extended optimization decision method considering a planning and operation interaction mechanism according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a multi-power-supply extended optimization planning model considering coordinated development of various non-fossil energy sources such as nuclear power, new energy and the like according to an embodiment of the invention;
FIG. 3 is a flow chart of a multi-power-supply extended optimization decision method considering coordinated operation of non-fossil energy power generation according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a typical weekly nuclear power, new energy and other power source coordinated operation situation of a power grid reference scene of a certain region in 2035 in an embodiment of the invention;
fig. 5 is a schematic diagram of a multi-power-supply extended optimization decision system considering coordinated operation of non-fossil energy power generation according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a multi-power-supply expansion optimization decision-making system considering non-fossil energy power generation coordinated operation, and aims to break through the 'competitive substitution' relationship between nuclear power and new energy, analyze the feasibility of a nuclear power and new energy coordinated operation mode from the optimal perspective of a full power system, and optimally provide a multi-power-supply expansion optimization planning scheme with the optimal total system cost on the basis of meeting the requirements of safety and stability, energy conservation and emission reduction of the power system.
Aiming at the inherent thought problem of mutual crowding of development space of nuclear power and new energy in the industry, the embodiment of the invention establishes a research method from two aspects of planning and operation, and deeply analyzes the coordinated development problem of the nuclear power and the new energy, as shown in figure 1:
on the planning level, aiming at coordination problems in aspects of development scale, layout and the like of nuclear power and new energy, medium-and-long-term power system extension simulation research is carried out on the national scale, and sensitivity analysis is carried out on inland nuclear power starting time; and meanwhile, a typical area is selected, nuclear power development scale sensitivity analysis is performed under the situation that new energy resources with different proportions are accessed into the power system, and finally a strategy suggestion for promoting the coordinated development of nuclear power and new energy resources is provided.
In the operation aspect, multi-dimensional operation simulation analysis is carried out on a typical scene of a target area mainly aiming at the problem of influence of nuclear power and other power supplies participating in power grid peak regulation in different modes on the aspects of new energy consumption, system operation economy and the like, and finally a strategy proposal for promoting the coordinated operation of the nuclear power and the new energy is provided.
As shown in fig. 2, according to the development potential, development conditions and energy demand of the power generation resources in the target area, the embodiment of the present invention takes the lowest total cost of power supply in the whole society in the planning period as a target, takes the energy supply capacity, power and electricity balance, system operation, environmental space, and the like as constraint conditions, and mainly considers the nuclear power and new energy coordinated operation strategy to construct an optimization problem, and finally solves the development scale, layout and construction timing sequence, and trans-provincial power transmission scale, and the like of various power supplies including nuclear power, new energy, and the like.
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. 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 "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise. Furthermore, the terms "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Method embodiment
According to an embodiment of the present invention, a multi-power-supply expansion optimization decision method considering non-fossil energy power generation coordinated operation is provided, fig. 3 is a flowchart of the multi-power-supply expansion optimization decision method considering non-fossil energy power generation coordinated operation according to the embodiment of the present invention, as shown in fig. 3, the multi-power-supply expansion optimization decision method considering non-fossil energy power generation coordinated operation according to the embodiment of the present invention specifically includes:
step 301, determining an optimization objective function by taking the minimum total cost of the power supply of the whole society in the expectation as an optimization objective, namely determining the optimization objective function:
the method takes the minimum total cost of power supply in the whole society in expectation as an optimization target, and comprises investment, operation and maintenance, fuel, emission cost and equipment residual value of different horizontal years in each area, namely:
Figure BDA0002670737970000051
wherein, Z and T respectively represent a divided region set and a set of expected horizontal years, and subscripts Z and T respectively identify a corresponding region and a horizontal year; r iszRepresenting a discount rate; the superscripts I, OM, F, C and S respectively represent investment, operation and maintenance, fuel, emission cost and equipment residual value of the tth horizontal year of the area z; each subentry is calculated by the following equation:
Figure BDA0002670737970000061
Figure BDA0002670737970000062
Figure BDA0002670737970000063
Figure BDA0002670737970000064
Figure BDA0002670737970000065
wherein M iszSet of power types, M, representing region zz,mSet of units, L, representing class m power supplies in zone zS zA set of cross-regional channels representing a starting point in region z; XG, XNG and XRG respectively represent the total installation scale, the newly increased scale and the retired scale of the power supply m unit i of the region z in the horizontal year t; XL and XNL respectively represent the total capacity and the newly added capacity of a cross-region channel l of a starting point in a region z in a horizontal year t; EG represents the annual power generation amount of the power supply m unit i of the region z in the horizontal year t; EL represents the exchange electric quantity of a cross-region channel l of a starting point in a region z in a horizontal year t; cNG represents the unit capacity cost of the new power supply; cNL, the unit capacity and unit distance construction cost of the channel, DL, the power transmission distance of the cross-regional channel l of the starting point in the region z; cGF and cGV respectively represent the fixed operation and maintenance cost of unit capacity of the power supply and the variable operation and maintenance cost of the power supply; the cLF and the cLV respectively represent the fixed operation and maintenance cost and the variable operation and maintenance cost of the power grid in unit distance of unit capacity of the cross-region channel; cC represents the power discharge cost of the power supply m unit i of the area z in the horizontal year t; cS represents the unit capacity residual value coefficient of the power supply m unit i of the area z in the horizontal year t.
Step 302, determining power system extension planning constraints, power system operation constraints, power generation resource constraints, and non-fossil energy power development policy constraints of the optimization objective function, namely defining each constraint:
the constraints considered include power system extension planning constraints, power system operation constraints, power generation resource constraints, energy and power development policy constraints, and the like.
Power system extension planning constraint
The method mainly dynamically corrects the installed power supply capacity and the trans-regional channel power transmission capacity according to the increasing and retirement condition in a horizontal year within a prospect, namely:
Figure BDA0002670737970000071
Figure BDA0002670737970000072
Figure BDA0002670737970000073
in the formulae (1-8): y ism,iRepresenting the operating life of the power supply m unit i if t-ym,iIf the expected date does not fall into the prospect, the corresponding year before the prospect is traced.
Second, the integral operation constraint of the power system in consideration of the multi-power supply coordinated operation
The method mainly takes power balance constraint, system adequacy constraint, power output constraint, trans-regional power transmission constraint and the like in each scene of each region in each horizontal year.
Each typical scenario needs to ensure power supply and demand balance time by time, namely:
Figure BDA0002670737970000074
the left term of the above formula sequentially represents that when the area z is in the horizontal year t scene s time interval t, the accumulated output of other power sources except the energy storage, the accumulated net input power of the starting point in the cross-area channel of the area z, the accumulated net input power of the falling point in the cross-area channel of the area z and the accumulated net output of the energy storage are obtained, and the right term Pz,t,s,nRepresenting the instant power demand of the whole society; pG、PL1、PL2、PES1、PES2Respectively representing the current power output, the power flow from the starting point to the drop point of the cross-region channel, the power flow from the drop point to the starting point of the cross-region channel, and the power generation and energy storage power of the stored energy; mES zTo representA set of energy storage types for region z; szRepresenting a set of scenes for region z and N representing a set of time periods for scene s.
According to the power balance constraint, the annual accumulated power generation and exchange electric quantity of various power supplies and channels in each region can be measured, namely:
Figure BDA0002670737970000081
Figure BDA0002670737970000082
in the formula: y istRepresents the number of days of the gregorian calendar, ρ, corresponding to the horizontal yearz,t,sRepresenting the probability of the occurrence of the wind-solar load scenario s under consideration.
System adequacy constraints ensure that there is enough equipment to meet peak load demands, i.e.:
Figure BDA0002670737970000083
in the formula, gammaGAnd gammaLRepresenting the capacity confidence coefficient of each power supply and channel, beta representing the system standby coefficient, PPKIndicating the annual peak load for each area.
The power output constraint mainly ensures that the running output of various units is within a reasonable range, namely:
Figure BDA0002670737970000084
Figure BDA0002670737970000085
the formula (1-14) is used for restraining the output of power sources except for energy storage and new energy power generation, wherein muG1And muG2Respectively representing the upper and lower limit coefficients of the power output, MREA new energy generation set representing region z; equation 15 forConstraining the new energy to generate power, wherein muRERepresenting the predicted power coefficient of new energy generation time by time in the corresponding scene, related to the new energy resource level, PCURIndicating the energy rejection for the corresponding period.
The energy storage operation needs to consider the constraints of force and storage capacity at the same time, namely:
Figure BDA0002670737970000086
Figure BDA0002670737970000087
Figure BDA0002670737970000091
Figure BDA0002670737970000092
Figure BDA0002670737970000093
the time-interval-by-time energy storage power generation and storage power constraint is given by the formulas (1-16), wherein UESThe binary variable is taken, the value of 1 represents that the stored energy is in a power generation state, and otherwise, the stored energy is in a power storage state; mu.sESExpressing the upper limit coefficient of energy storage output, and the formula 17 is the constraint of energy storage capacity, alphaMAX、αMIN、αINIRespectively representing an energy storage maximum storage capacity coefficient, a minimum storage capacity coefficient and an initial storage capacity coefficient; | N | represents the number of elements of the set N; etaES1、ηES2Respectively representing the energy storage power generation efficiency and the energy storage efficiency, and respectively establishing upper and lower reservoir capacity constraints for pumped storage according to a formula 17; for the photo-thermal power generation with energy storage, joint modeling is performed according to the formula 15 and the formula 17;
the trans-regional power transmission constraint ensures that the channel switching power is within a reasonable range, namely:
Figure BDA0002670737970000094
Figure BDA0002670737970000095
in the formula of ULThe binary variable is taken as a binary variable, the value of 1 represents that the channel allows forward power flow, and the reverse power flow is allowed otherwise; mu.sLRepresenting the channel switching power ceiling factor.
Third, power generation resource constraint
The method mainly considers the endowments and balance constraints of various power generation energy resources.
For coal/gas for power generation, there are:
Figure BDA0002670737970000096
Figure BDA0002670737970000097
in the formula: sigmaGExpressing the unit power generation coal consumption; fP、FI、FE、FORespectively representing the local production quantity, the call-in quantity, the call-out quantity and other industry usage quantities (including stock newly-increased) of fuel m in the region z; fI1Represents the net inlet quantity of fuel m; mFERepresenting the set of fossil energy generation types for region z, equation 20 ensures that the total blend amount for the interval fuel is generally balanced.
The constraints of various power generation resources and the number of hours of unit utilization are considered as follows:
Figure BDA0002670737970000101
in the formula: htThe number of annual hours representing the horizontal year t; mu.sCRmax、μCRminRespectively representing the maximum and minimum capacity factors of the unit i in the region z horizontal year t power supply m.
Policy constraint for non-fossil energy power development
Mainly considering carbon emission (formula (1-22)), total energy consumption (formula (1-23)), proportion of non-fossil energy to primary energy consumption (formula (1-24)), proportion of non-fossil energy to power generation (formula (1-25)), energy curtailment (formula (1-26)), and the like. The specific form is as follows:
Figure BDA0002670737970000102
Figure BDA0002670737970000103
Figure BDA0002670737970000104
Figure BDA0002670737970000105
Figure BDA0002670737970000106
in the above equation: sigmaCO2Indicating the unit degree of electricity CO of each power supply2Coefficient of emission, FCO2CO indicating horizontal year t set2An upper limit of emissions; fE、FNERespectively representing the total energy consumption of the horizontal year t and the total energy consumption of other industries except the electric industry; fNFEThe lower limit of the non-fossil energy power generation bidding coal representing the horizontal year t is obtained by calculating according to the proportion of the non-fossil energy to primary energy consumption and the non-fossil energy non-power generation scale; etaNFE、ηCURRespectively represents the lower specific gravity limit and the upper energy abandon rate limit of the non-fossil energy power generation amount in the horizontal year t to the total power generation amount.
In addition, the capacity lower limit of the newly added unit year by year is also restricted, and the capacity lower limit is mainly used for considering the planned deterministic unit but not yet operating, not yet operating under construction, and the like.
And 303, forming a multi-region multi-scene electric power planning model according to the optimization objective function and the constraint, and solving the multi-region multi-scene electric power planning model.
After the optimization target and the constraint are established, a multi-region and multi-scene power planning model can be formed; the model is a mixed integer linear model, has large constraint and variable scale, and is suitable for calling CPLEX and other mature commercial mathematical programming software to solve.
Taking a certain regional power grid as an example, the technical scheme of the embodiment of the invention is utilized to analyze the size and distribution of the power supply in 2035 years. As shown in table 1.
TABLE 1 reference situation in the power installation of each province 2035 years in a regional power grid (unit: ten thousand kW)
TABLE 1
Figure BDA0002670737970000111
As shown in fig. 4, a typical week is selected as the week with the largest new energy generating capacity ratio (about 14%), and the phenomenon of wind and light abandonment is basically avoided through flexible power supply adjustment such as pumping and storage, and at the moment, the nuclear power does not participate in peak shaving. Aiming at the typical week, other conditions are unchanged, the new energy installation is improved by 1 time, the generated energy accounts for 25% of the whole, if nuclear power does not participate in peak shaving, wind and light are abandoned, the electricity abandon rate is about 5.6% when the electricity abandon amount is about 5.4 hundred million kilowatts. However, if the nuclear power operation mode is adjusted, 20% of installed capacity of the nuclear power operation mode is allowed to participate in peak shaving, the electricity waste can be reduced to 3.7% when about 1.8 hundred million kilowatts of electricity waste are reduced.
System embodiment
According to an embodiment of the present invention, a multi-power-supply expansion optimization decision system considering coordinated operation of non-fossil energy power generation is provided, fig. 5 is a schematic diagram of the multi-power-supply expansion optimization decision system considering coordinated operation of non-fossil energy power generation according to an embodiment of the present invention, as shown in fig. 5, the multi-power-supply expansion optimization decision system considering coordinated operation of non-fossil energy power generation according to an embodiment of the present invention specifically includes:
an optimization objective function module 50, configured to determine an optimization objective function with the minimum total cost of power supply for the whole society in a prospect as an optimization objective; the optimization objective function module 50 is specifically configured to:
determining an optimization objective function according to equations 1 to 6:
Figure BDA0002670737970000121
Figure BDA0002670737970000122
Figure BDA0002670737970000123
Figure BDA0002670737970000124
Figure BDA0002670737970000125
Figure BDA0002670737970000126
wherein Z and T respectively represent a divided region set and a prospect horizontal year set, and subscripts Z and T respectively identify a corresponding region and a horizontal year; r iszRepresenting a discount rate; the superscripts I, OM, F, C and S respectively represent investment, operation and maintenance, fuel, emission cost and equipment residual value of the tth horizontal year of the area z; mzSet of power types, M, representing region zz,mSet of units, L, representing class m power supplies in zone zS zA set of cross-regional channels representing a starting point in region z; XG, XNG, XRG indicating region z at horizontal year tThe total installation, newly increased and retired scales of the power supply m unit i; XL and XNL respectively represent the total capacity and the newly added capacity of a cross-region channel l of a starting point in a region z in a horizontal year t; EG represents the annual power generation amount of the power supply m unit i of the region z in the horizontal year t; EL represents the exchange electric quantity of a cross-region channel l of a starting point in a region z in a horizontal year t; cNG represents the unit capacity cost of the new power supply; cNL, the unit capacity and unit distance construction cost of the channel, DL, the power transmission distance of the cross-regional channel l of the starting point in the region z; cGF and cGV respectively represent the fixed operation and maintenance cost of unit capacity of the power supply and the variable operation and maintenance cost of the power supply; the cLF and the cLV respectively represent the fixed operation and maintenance cost and the variable operation and maintenance cost of the power grid in unit distance of unit capacity of the cross-region channel; cC represents the power discharge cost of the power supply m unit i of the area z in the horizontal year t; cS represents the unit capacity residual value coefficient of the power supply m unit i of the area z in the horizontal year t;
a constraint calculation module 52, configured to determine an electric power system extension planning constraint, an electric power system operation constraint, a power generation resource constraint, and a non-fossil energy power development policy constraint of the optimization objective function;
the constraint calculation module 52 is specifically configured to:
according to the formula 7-formula 9, based on the situation of increasing and retirement every horizontal year in the prospect, the installed power supply capacity and the trans-regional channel transmission capacity are dynamically corrected:
Figure BDA0002670737970000131
Figure BDA0002670737970000132
Figure BDA0002670737970000133
wherein, ym,iRepresenting the operating life of the power supply m unit i if t-ym,iIf the current year does not fall into the prospect, tracing back to the corresponding year before the prospect;
determining power balance constraints in each scene of each region for each horizontal year according to formula 10:
Figure BDA0002670737970000134
wherein, the left term in the formula 10 sequentially indicates that, when the area z is in the horizontal year at the t scene s time interval t, the accumulated output of other power sources except the energy storage, the accumulated net input power of the starting point in the cross-zone channel of the area z, the accumulated net input power of the falling point in the cross-zone channel of the area z, and the accumulated net output of the energy storage, and the right term Pz,t,s,nRepresenting the instant power demand of the whole society; pG、PL1、PL2、PES1、PES2Respectively representing the current power output, the power flow from the starting point to the drop point of the cross-region channel, the power flow from the drop point to the starting point of the cross-region channel, and the power generation and energy storage power of the stored energy; mES zA set of energy storage types representing a region z; szA scene set representing a region z, N representing a period set of a scene s;
according to formulas 11-12, based on power balance constraints, the annual accumulated power generation and exchange electric quantity of various power supplies and channels in each region is calculated:
Figure BDA0002670737970000141
Figure BDA0002670737970000142
wherein, ytRepresents the number of days of the gregorian calendar, ρ, corresponding to the horizontal yearz,t,sRepresenting the probability of occurrence of the wind-solar load scenario s under consideration;
calculating system adequacy constraints in each scene of each region for each horizontal year according to formula 13:
Figure BDA0002670737970000143
wherein, γGAnd gammaLRepresenting the capacity confidence coefficient of each power supply and channel, beta representing the system standby coefficient, PPKRepresenting annual peak loads in each region;
calculating the power output constraints of each region in each scene every horizontal year according to the formulas 14-15:
Figure BDA0002670737970000144
Figure BDA0002670737970000145
wherein equation 14 is used to constrain the power output beyond energy storage, new energy generation, where μG1And muG2Respectively representing the upper and lower limit coefficients of the power output, MREA new energy generation set representing region z; equation 15 is used to constrain the new energy generation output, where μRERepresenting the predicted power coefficient of new energy generation time by time in the corresponding scene, related to the new energy resource level, PCURIndicating a power dump for the corresponding time period;
and (3) calculating the output and storage capacity constraint of the energy storage operation at the same time according to the formulas 16-17:
Figure BDA0002670737970000151
Figure BDA0002670737970000152
Figure BDA0002670737970000153
Figure BDA0002670737970000154
Figure BDA0002670737970000155
wherein, the formula 16 is the time-interval-by-time energy storage power generation and storage power constraint, wherein UESThe binary variable is taken, the value of 1 represents that the stored energy is in a power generation state, and otherwise, the stored energy is in a power storage state; mu.sESExpressing the upper limit coefficient of energy storage output, and the formula 17 is the constraint of energy storage capacity, alphaMAX、αMIN、αINIRespectively representing an energy storage maximum storage capacity coefficient, a minimum storage capacity coefficient and an initial storage capacity coefficient; | N | represents the number of elements of the set N; etaES1、ηES2Respectively representing the energy storage power generation efficiency and the energy storage efficiency, and respectively establishing upper and lower reservoir capacity constraints for pumped storage according to a formula 17; for the photo-thermal power generation with energy storage, joint modeling is performed according to the formula 15 and the formula 17;
calculating the trans-regional power transmission constraint in each scene of each region in each horizontal year according to a formula 18:
Figure BDA0002670737970000156
Figure BDA0002670737970000157
wherein, ULThe binary variable is taken as a binary variable, the value of 1 represents that the channel allows forward power flow, and the reverse power flow is allowed otherwise; mu.sLRepresenting the channel switching power upper limit coefficient;
calculating the endowments and balance constraints of various power generation energy resources:
for the coal/gas for power generation, various power generation energy resource endowments and balance constraints are calculated according to formulas 19-20:
Figure BDA0002670737970000161
Figure BDA0002670737970000162
wherein σGExpressing the unit power generation coal consumption; fP、FI、FE、FORespectively representing the local production quantity, the call-in quantity, the call-out quantity and other industrial usage quantities of the fuel m in the area z; fI1Represents the net inlet quantity of fuel m; mFERepresenting the set of fossil energy power generation types for the region z, equation 20 ensures overall balance of the total blending amount of interval fuel;
calculating various power generation resource endowments and unit utilization hour number constraints according to a formula 21:
Figure BDA0002670737970000163
wherein HtThe number of annual hours representing the horizontal year t; mu.sCRmax、μCRminRespectively representing the maximum and minimum capacity factors of a unit i in a power supply m in the horizontal year t of the area z;
calculating an energy power development policy constraint for the optimization objective function according to equations 22-26:
Figure BDA0002670737970000164
Figure BDA0002670737970000165
Figure BDA0002670737970000166
Figure BDA0002670737970000167
Figure BDA0002670737970000168
wherein σCO2Indicating the unit degree of electricity CO of each power supply2Coefficient of emission, FCO2CO indicating horizontal year t set2An upper limit of emissions; fE、FNERespectively representing the total energy consumption of the horizontal year t and the total energy consumption of other industries except the electric industry; fNFEThe lower limit of the non-fossil energy power generation bidding coal representing the horizontal year t is obtained by calculating according to the proportion of the non-fossil energy to primary energy consumption and the non-fossil energy non-power generation scale; etaNFE、ηCURRespectively represents the lower specific gravity limit and the upper energy abandon rate limit of the non-fossil energy power generation amount in the horizontal year t to the total power generation amount.
The constraint calculation module 52 is further configured to:
and determining the annual newly added unit capacity lower limit constraint of the optimization objective function according to the planned deterministic unit which is not started and put into operation or put into production.
And the solving module 54 is configured to form a multi-region multi-scenario power planning model according to the optimization objective function and the constraint, and solve the multi-region multi-scenario power planning model.
The embodiment of the present invention is a system embodiment corresponding to the above method embodiment, and specific operations of each module may be understood with reference to the description of the method embodiment, which is not described herein again.
In summary, according to the development potential, the development conditions and the energy consumption requirements of the power generation resources in the target area, the lowest total power supply cost of the whole society in the planning period is taken as a target, the energy supply capacity, the power and electricity balance, the system operation, the environmental space and the like are taken as constraint conditions, the nuclear power and new energy coordinated operation strategy is mainly considered to construct an optimization problem, and the development scale, the layout and the construction time sequence of various power supplies including nuclear power, new energy and the like and the trans-provincial power transmission scale are finally solved.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A multi-power-supply expansion optimization decision method considering coordinated operation of non-fossil energy power generation is characterized by comprising the following steps:
determining an optimization objective function by taking the minimum total cost of power supply of the whole society in a prospect as an optimization objective;
determining power system extension planning constraints, power system operation constraints, power generation resource constraints, and non-fossil energy power development policy constraints of the optimization objective function;
and forming a multi-region multi-scene electric power planning model according to the optimization objective function and the constraint, and solving the multi-region multi-scene electric power planning model.
2. The method according to claim 1, wherein determining the optimization objective function with the minimum total cost of the power supply for the whole society in the expectation as the optimization objective specifically comprises:
determining an optimization objective function according to equations 1 to 6:
Figure FDA0002670737960000011
Figure FDA0002670737960000012
Figure FDA0002670737960000013
Figure FDA0002670737960000014
Figure FDA0002670737960000015
Figure FDA0002670737960000016
wherein Z and T respectively represent a divided region set and a prospect horizontal year set, and subscripts Z and T respectively identify a corresponding region and a horizontal year; r iszRepresenting a discount rate; the superscripts I, OM, F, C and S respectively represent investment, operation and maintenance, fuel, emission cost and equipment residual value of the tth horizontal year of the area z; mzSet of power types, M, representing region zz,mSet of units, L, representing class m power supplies in zone zS zA set of cross-regional channels representing a starting point in region z; XG, XNG and XRG respectively represent the total installation scale, the newly increased scale and the retired scale of the power supply m unit i of the region z in the horizontal year t; XL and XNL respectively represent the total capacity and the newly added capacity of a cross-region channel l of a starting point in a region z in a horizontal year t; EG represents the annual power generation amount of the power supply m unit i of the region z in the horizontal year t; EL denotes the horizontal year of the cross-zone channel l starting at zone zt, the amount of exchanged electricity; cNG represents the unit capacity cost of the new power supply; cNL, the unit capacity and unit distance construction cost of the channel, DL, the power transmission distance of the cross-regional channel l of the starting point in the region z; cGF and cGV respectively represent the fixed operation and maintenance cost of unit capacity of the power supply and the variable operation and maintenance cost of the power supply; the cLF and the cLV respectively represent the fixed operation and maintenance cost and the variable operation and maintenance cost of the power grid in unit distance of unit capacity of the cross-region channel; cC represents the power discharge cost of the power supply m unit i of the area z in the horizontal year t; cS represents the unit capacity residual value coefficient of the power supply m unit i of the area z in the horizontal year t.
3. The method of claim 2, wherein determining the power system extension planning constraints of the optimization objective function specifically comprises:
according to the formula 7-formula 9, based on the situation of increasing and retirement every horizontal year in the prospect, the installed power supply capacity and the trans-regional channel transmission capacity are dynamically corrected:
Figure FDA0002670737960000021
Figure FDA0002670737960000022
Figure FDA0002670737960000023
wherein, ym,iRepresenting the operating life of the power supply m unit i if t-ym,iIf the expected date does not fall into the prospect, the corresponding year before the prospect is traced.
4. The method of claim 2, wherein determining the power system operating constraints of the optimization objective function specifically comprises:
determining power balance constraints in each scene of each region for each horizontal year according to formula 10:
Figure FDA0002670737960000031
wherein, the left term in the formula 10 sequentially indicates that, when the area z is in the horizontal year at the t scene s time interval t, the accumulated output of other power sources except the energy storage, the accumulated net input power of the starting point in the cross-zone channel of the area z, the accumulated net input power of the falling point in the cross-zone channel of the area z, and the accumulated net output of the energy storage, and the right term Pz,t,s,nRepresenting the instant power demand of the whole society; pG、PL1、PL2、PES1、PES2Respectively representing the current power output, the power flow from the starting point to the drop point of the cross-region channel, the power flow from the drop point to the starting point of the cross-region channel, and the power generation and energy storage power of the stored energy; mES zA set of energy storage types representing a region z; szA scene set representing a region z, N representing a period set of a scene s;
according to formulas 11-12, based on power balance constraints, the annual accumulated power generation and exchange electric quantity of various power supplies and channels in each region is calculated:
Figure FDA0002670737960000032
Figure FDA0002670737960000033
wherein, ytRepresents the number of days of the gregorian calendar, ρ, corresponding to the horizontal yearz,t,sRepresenting the probability of occurrence of the wind-solar load scenario s under consideration;
calculating system adequacy constraints in each scene of each region for each horizontal year according to formula 13:
Figure FDA0002670737960000034
wherein, γGAnd gammaLIndicating capacity of each power supply and channelQuantity confidence coefficient, beta, represents the system backup coefficient, PPKRepresenting annual peak loads in each region;
calculating the power output constraints of each region in each scene every horizontal year according to the formulas 14-15:
Figure FDA0002670737960000041
Figure FDA0002670737960000042
wherein equation 14 is used to constrain the power output beyond energy storage, new energy generation, where μG1And muG2Respectively representing the upper and lower limit coefficients of the power output, MREA new energy generation set representing region z; equation 15 is used to constrain the new energy generation output, where μRERepresenting the predicted power coefficient of new energy generation time by time in the corresponding scene, related to the new energy resource level, PCURIndicating a power dump for the corresponding time period;
and (3) calculating the output and storage capacity constraint of the energy storage operation at the same time according to the formulas 16-17:
Figure FDA0002670737960000043
Figure FDA0002670737960000044
wherein, the formula 16 is the time-interval-by-time energy storage power generation and storage power constraint, wherein UESThe binary variable is taken, the value of 1 represents that the stored energy is in a power generation state, and otherwise, the stored energy is in a power storage state; mu.sESExpressing the upper limit coefficient of energy storage output, and the formula 17 is the constraint of energy storage capacity, alphaMAX、αMIN、αINIRespectively representing the maximum storage capacity coefficient, the minimum storage capacity coefficient and the initial storage capacity of the stored energyA quantitative coefficient; | N | represents the number of elements of the set N; etaES1、ηES2Respectively representing the energy storage power generation efficiency and the energy storage efficiency, and respectively establishing upper and lower reservoir capacity constraints for pumped storage according to a formula 17; for the photo-thermal power generation with energy storage, joint modeling is performed according to the formula 15 and the formula 17;
calculating the trans-regional power transmission constraint in each scene of each region in each horizontal year according to a formula 18:
Figure FDA0002670737960000051
wherein, ULThe binary variable is taken as a binary variable, the value of 1 represents that the channel allows forward power flow, and the reverse power flow is allowed otherwise; mu.sLRepresenting the channel switching power ceiling factor.
5. The method according to claim 2, wherein determining the power generation resource constraints of the optimization objective function specifically comprises:
calculating the endowments and balance constraints of various power generation energy resources:
for the coal/gas for power generation, various power generation energy resource endowments and balance constraints are calculated according to formulas 19-20:
Figure FDA0002670737960000052
Figure FDA0002670737960000053
wherein σGExpressing the unit power generation coal consumption; fP、FI、FE、FORespectively representing the local production quantity, the call-in quantity, the call-out quantity and other industrial usage quantities of the fuel m in the area z; fI1Represents the net inlet quantity of fuel m; mFERepresenting the set of fossil energy power generation types for the region z, equation 20 ensures overall balance of the total blending amount of interval fuel;
calculating various power generation resource endowments and unit utilization hour number constraints according to a formula 21:
Figure FDA0002670737960000054
wherein HtThe number of annual hours representing the horizontal year t; mu.sCRmax、μCRminRespectively representing the maximum and minimum capacity factors of the unit i in the region z horizontal year t power supply m.
6. The method according to claim 2, wherein determining energy power development policy constraints of the optimization objective function specifically comprises:
calculating an energy power development policy constraint for the optimization objective function according to equations 22-26:
Figure FDA0002670737960000061
Figure FDA0002670737960000062
Figure FDA0002670737960000063
Figure FDA0002670737960000064
Figure FDA0002670737960000065
wherein σCO2Indicating the unit degree of electricity CO of each power supply2Coefficient of emission, FCO2Indicates horizontal year t setCO of2An upper limit of emissions; fE、FNERespectively representing the total energy consumption of the horizontal year t and the total energy consumption of other industries except the electric industry; fNFEThe lower limit of the non-fossil energy power generation bidding coal representing the horizontal year t is obtained by calculating according to the proportion of the non-fossil energy to primary energy consumption and the non-fossil energy non-power generation scale; etaNFE、ηCURRespectively represents the lower specific gravity limit and the upper energy abandon rate limit of the non-fossil energy power generation amount in the horizontal year t to the total power generation amount.
7. The method of claim 1,
and determining the annual newly added unit capacity lower limit constraint of the optimization objective function according to the planned deterministic unit which is not started and put into operation or put into production.
8. A multi-power-supply-extended optimization decision system considering coordinated operation of non-fossil energy power generation, comprising:
the optimization objective function module is used for determining an optimization objective function by taking the minimum total cost of the power supply of the whole society in a prospect as an optimization objective;
the constraint calculation module is used for determining power system extension planning constraints, power system operation constraints, power generation resource constraints and non-fossil energy power development policy constraints of the optimization objective function;
and the solving module is used for forming a multi-region multi-scene electric power planning model according to the optimization objective function and the constraint and solving the multi-region multi-scene electric power planning model.
9. The system of claim 8,
the optimization objective function module is specifically configured to:
determining an optimization objective function according to equations 1 to 6:
Figure FDA0002670737960000071
Figure FDA0002670737960000072
Figure FDA0002670737960000073
Figure FDA0002670737960000074
Figure FDA0002670737960000075
Figure FDA0002670737960000076
wherein Z and T respectively represent a divided region set and a prospect horizontal year set, and subscripts Z and T respectively identify a corresponding region and a horizontal year; r iszRepresenting a discount rate; the superscripts I, OM, F, C and S respectively represent investment, operation and maintenance, fuel, emission cost and equipment residual value of the tth horizontal year of the area z; mzSet of power types, M, representing region zz,mSet of units, L, representing class m power supplies in zone zS zA set of cross-regional channels representing a starting point in region z; XG, XNG and XRG respectively represent the total installation scale, the newly increased scale and the retired scale of the power supply m unit i of the region z in the horizontal year t; XL and XNL respectively represent the total capacity and the newly added capacity of a cross-region channel l of a starting point in a region z in a horizontal year t; EG represents the annual power generation amount of the power supply m unit i of the region z in the horizontal year t; EL represents the exchange electric quantity of a cross-region channel l of a starting point in a region z in a horizontal year t; cNG represents the unit capacity cost of the new power supply; cNL, the unit capacity and unit distance construction cost of the channel, DL, the power transmission distance of the cross-regional channel l of the starting point in the region z; cGF and cGV represents the fixed operation and maintenance cost of unit capacity of the power supply and the variable operation and maintenance cost of the kilowatt-hour meter; the cLF and the cLV respectively represent the fixed operation and maintenance cost and the variable operation and maintenance cost of the power grid in unit distance of unit capacity of the cross-region channel; cC represents the power discharge cost of the power supply m unit i of the area z in the horizontal year t; cS represents the unit capacity residual value coefficient of the power supply m unit i of the area z in the horizontal year t;
the constraint calculation module is specifically configured to:
according to the formula 7-formula 9, based on the situation of increasing and retirement every horizontal year in the prospect, the installed power supply capacity and the trans-regional channel transmission capacity are dynamically corrected:
Figure FDA0002670737960000081
Figure FDA0002670737960000082
Figure FDA0002670737960000083
wherein, ym,iRepresenting the operating life of the power supply m unit i if t-ym,iIf the current year does not fall into the prospect, tracing back to the corresponding year before the prospect;
determining power balance constraints in each scene of each region for each horizontal year according to formula 10:
Figure FDA0002670737960000084
wherein, the left term in the formula 10 sequentially indicates that, when the area z is in the horizontal year at the t scene s time interval t, the accumulated output of other power sources except the energy storage, the accumulated net input power of the starting point in the cross-zone channel of the area z, the accumulated net input power of the falling point in the cross-zone channel of the area z, and the accumulated net output of the energy storage, and the right term Pz,t,s,nRepresenting the instant power demand of the whole society; pG、PL1、PL2、PES1、PES2Respectively representing the current power output, the power flow from the starting point to the drop point of the cross-region channel, the power flow from the drop point to the starting point of the cross-region channel, and the power generation and energy storage power of the stored energy; mES zA set of energy storage types representing a region z; szA scene set representing a region z, N representing a period set of a scene s;
according to formulas 11-12, based on power balance constraints, the annual accumulated power generation and exchange electric quantity of various power supplies and channels in each region is calculated:
Figure FDA0002670737960000091
Figure FDA0002670737960000092
wherein, ytRepresents the number of days of the gregorian calendar, ρ, corresponding to the horizontal yearz,t,sRepresenting the probability of occurrence of the wind-solar load scenario s under consideration;
calculating system adequacy constraints in each scene of each region for each horizontal year according to formula 13:
Figure FDA0002670737960000093
wherein, γGAnd gammaLRepresenting the capacity confidence coefficient of each power supply and channel, beta representing the system standby coefficient, PPKRepresenting annual peak loads in each region;
calculating the power output constraints of each region in each scene every horizontal year according to the formulas 14-15:
Figure FDA0002670737960000094
Figure FDA0002670737960000095
wherein equation 14 is used to constrain the power output beyond energy storage, new energy generation, where μG1And muG2Respectively representing the upper and lower limit coefficients of the power output, MREA new energy generation set representing region z; equation 15 is used to constrain the new energy generation output, where μRERepresenting the predicted power coefficient of new energy generation time by time in the corresponding scene, related to the new energy resource level, PCURIndicating a power dump for the corresponding time period;
and (3) calculating the output and storage capacity constraint of the energy storage operation at the same time according to the formulas 16-17:
Figure FDA0002670737960000101
Figure FDA0002670737960000102
wherein, the formula 16 is the time-interval-by-time energy storage power generation and storage power constraint, wherein UESThe binary variable is taken, the value of 1 represents that the stored energy is in a power generation state, and otherwise, the stored energy is in a power storage state; mu.sESExpressing the upper limit coefficient of energy storage output, and the formula 17 is the constraint of energy storage capacity, alphaMAX、αMIN、αINIRespectively representing an energy storage maximum storage capacity coefficient, a minimum storage capacity coefficient and an initial storage capacity coefficient; | N | represents the number of elements of the set N; etaES1、ηES2Respectively representing the energy storage power generation efficiency and the energy storage efficiency, and respectively establishing upper and lower reservoir capacity constraints for pumped storage according to a formula 17; for the photo-thermal power generation with energy storage, joint modeling is performed according to the formula 15 and the formula 17;
calculating the trans-regional power transmission constraint in each scene of each region in each horizontal year according to a formula 18:
Figure FDA0002670737960000103
wherein, ULThe binary variable is taken as a binary variable, the value of 1 represents that the channel allows forward power flow, and the reverse power flow is allowed otherwise; mu.sLRepresenting the channel switching power upper limit coefficient;
calculating the endowments and balance constraints of various power generation energy resources:
for the coal/gas for power generation, various power generation energy resource endowments and balance constraints are calculated according to formulas 19-20:
Figure FDA0002670737960000104
Figure FDA0002670737960000111
wherein σGExpressing the unit power generation coal consumption; fP、FI、FE、FORespectively representing the local production quantity, the call-in quantity, the call-out quantity and other industrial usage quantities of the fuel m in the area z; fI1Represents the net inlet quantity of fuel m; mFERepresenting the set of fossil energy power generation types for the region z, equation 20 ensures overall balance of the total blending amount of interval fuel;
calculating various power generation resource endowments and unit utilization hour number constraints according to a formula 21:
Figure FDA0002670737960000112
wherein HtThe number of annual hours representing the horizontal year t; mu.sCRmax、μCRminRespectively representing the maximum and minimum capacity factors of a unit i in a power supply m in the horizontal year t of the area z;
calculating an energy power development policy constraint for the optimization objective function according to equations 22-26:
Figure FDA0002670737960000113
Figure FDA0002670737960000114
Figure FDA0002670737960000115
Figure FDA0002670737960000116
Figure FDA0002670737960000117
wherein σCO2Indicating the unit degree of electricity CO of each power supply2Coefficient of emission, FCO2CO indicating horizontal year t set2An upper limit of emissions; fE、FNERespectively representing the total energy consumption of the horizontal year t and the total energy consumption of other industries except the electric industry; fNFEThe lower limit of the non-fossil energy power generation bidding coal representing the horizontal year t is obtained by calculating according to the proportion of the non-fossil energy to primary energy consumption and the non-fossil energy non-power generation scale; etaNFE、ηCURRespectively represents the lower specific gravity limit and the upper energy abandon rate limit of the non-fossil energy power generation amount in the horizontal year t to the total power generation amount.
10. The system of claim 8, wherein the constraint computation module is further configured to:
and determining the annual newly added unit capacity lower limit constraint of the optimization objective function according to the planned deterministic unit which is not started and put into operation or put into production.
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