CN115630748A - Optimization planning method, medium and system for multi-stage retired power supply of coal electric unit - Google Patents

Optimization planning method, medium and system for multi-stage retired power supply of coal electric unit Download PDF

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CN115630748A
CN115630748A CN202211391903.8A CN202211391903A CN115630748A CN 115630748 A CN115630748 A CN 115630748A CN 202211391903 A CN202211391903 A CN 202211391903A CN 115630748 A CN115630748 A CN 115630748A
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王潇笛
邓靖微
曹敏琦
杜新伟
袁川
李博
韩宇奇
张帅
张永杰
晁化伟
甄玉萌
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State Grid Sichuan Economic Research Institute
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Abstract

The invention discloses a method, a medium and a system for optimizing and planning a multi-stage retired power supply of a coal-electric machine set, relates to the technical field of power system planning, and solves the problems that related targets and constraint consideration on carbon emission are insufficient in the current power grid planning and the coal-electric retired path planning is unreasonable, and the technical scheme is as follows: collecting power grid information related to decommissioning of the coal-electric unit to generate a basic database; the method comprises the following steps of making a coal electric unit multistage retired power supply optimization model according to a basic database, wherein the coal electric unit multistage retired power supply optimization model comprises the following steps: a cost objective function and constraints for the cost objective function, the constraints comprising: planning constraints and operating constraints; and solving the coal electric unit multistage retired power supply optimization model to obtain the retired power supply optimization planning method of the coal electric unit in each stage. And establishing a constraint condition on the premise of considering carbon emission constraint, and solving a model by taking the lowest total cost as an optimization target to obtain the reasonable retirement scale and energy storage layout of the coal-electric unit.

Description

Optimization planning method, medium and system for multi-stage retired power supply of coal electric unit
Technical Field
The invention relates to the technical field of power system planning, in particular to a method, medium and system for optimizing and planning a multi-stage retired power supply of a coal-electric machine set.
Background
In the low-carbon transformation process, a large number of thermal power generating units are shut down in the power system, and a large number of new energy power supplies are required to be built to meet the requirement of newly increased electric power. With the gradual shutdown of thermal power generating units and the continuous grid connection of fluctuating power supplies such as high-proportion wind power and photovoltaic power, the problems of low inertia operation risk, balanced adjustment of supply and demand, weak frequency support and disturbance resistance of a power grid and the like become increasingly prominent, and how to realize reasonable decommissioning of the coal power generating units on the basis of safe and reliable replacement of clean energy is a key problem faced by the current power system transformation.
However, in the current power grid planning, the related targets and constraints on carbon emission are not considered enough, the related research is mostly biased to the analysis of the total energy supply and demand, the quantitative simulation analysis on the system power and electric quantity balance relation, the system inertia safety and the frequency safety is lacked, the influence of different coal-electricity decommissioning paths on the system is difficult to truly measure, and therefore a reasonable coal-electricity decommissioning path is difficult to obtain.
Disclosure of Invention
The application aims to provide a coal-electric unit multi-stage retired power supply optimization planning method, medium and system, which achieve 8230 @.
The technical purpose of the application is realized by the following technical scheme: comprises that
Collecting power grid information related to decommissioning of the coal-electric unit to generate a basic database;
and formulating a coal electric unit multi-stage retired power supply optimization model according to the basic database, wherein the coal electric unit multi-stage retired power supply optimization model comprises the following steps: a cost objective function and constraints for the cost objective function, the constraints comprising: planning constraints and operating constraints;
and solving the coal electric unit multistage retired power supply optimization model to obtain the retired power supply optimization planning method of the coal electric unit at each stage.
By adopting the technical scheme, on the premise of considering carbon emission constraint, in order to quantitatively analyze the influence of coal power decommissioning on system equivalent inertia, power supply and demand balance and frequency safety, relevant constraints are respectively established from the planning and operation level, the lowest total cost is taken as an optimization target, the reasonable decommissioning scale and decommissioning path of the coal power unit and the reasonable power structure, energy storage scale and layout can be obtained after the model is solved, and theoretical guidance is provided for the optimization planning of the power system under the carbon neutralization target.
Further, the basic database includes: the system planning general data, the unit basic parameter data and the production decision limiting condition data of each stage;
the system planning profile data comprising: the method comprises the following steps of establishing unit information, coal-electric unit information to be retired, unit information to be put into operation, the number y of system planning stages and the maximum predicted load of the y stage in a system planning period;
the unit basic parameter data comprises: unit type, installed capacity, climbing rate, carbon emission factor and service life;
the production decision limiting condition data of each stage comprises the following data of the y stage: the maximum carbon emission, the maximum allowable decommissioning capacity of the coal-electric unit and the maximum allowable building capacity of each type of unit to be built.
Further, a multistage retired power supply optimization model of the coal-electric unit is formulated according to the basic database, and the multistage retired power supply optimization model comprises the following steps:
establishing a decision variable of a coal-electric machine set multistage decommissioning power supply optimization model, and calculating decommissioning processing cost, coal-electric machine set maintenance cost, gas-electric machine set investment cost, gas-electric machine set maintenance cost, wind-solar machine set investment cost, pumped storage investment cost and system operation cost of the coal-electric machine set at the y stage according to the decision variable and data in the basic database;
and constructing a cost objective function according to the decommissioning treatment cost of the coal-electricity unit, the maintenance cost of the coal-electricity unit, the investment cost of the gas-electricity unit, the maintenance cost of the gas-electricity unit, the investment cost of the wind-solar unit, the investment cost of the pumped storage and the operation cost of the system in the y stage.
Further, the cost objective function is:
Figure BDA0003932222090000021
wherein the content of the first and second substances,
Figure BDA0003932222090000022
respectively representing the decommissioning treatment cost of the coal-electricity unit, the maintenance cost of the coal-electricity unit, the investment cost of the gas-electricity unit, the maintenance cost of the gas-electricity unit, the investment cost of the wind-light unit, the investment cost of the pumped storage and the operation cost of the system in the Y stage, wherein Y represents all stages to be planned, and delta represents delta y And representing the current value coefficient corresponding to the cost in the y stage.
Further, the planning constraints include: the method comprises the following steps of power source installed capacity electric power balance constraint, carbon emission constraint, coal electric unit decommissioning constraint and newly increased power source commissioning constraint.
Further, the operating constraints include: the method comprises the following steps of power balance constraint, system equivalent inertia constraint, peak regulation operation constraint, frequency modulation operation constraint, wind and light unit uncertainty output constraint, conventional unit output constraint, hydroelectric generating set operation constraint and pumped storage unit operation constraint.
Further, solving the coal electric unit multistage retired power supply optimization model comprises the following steps:
carrying out piecewise linearization on the generating cost of the unit in the objective function;
and (4) solving the multistage retired power supply optimization model of the coal electric unit after the piecewise linearization by calling the CPLEX through a GAMS (business intelligence system) programming solving program to obtain the retired power supply optimization planning method of the coal electric unit at each stage.
Further, the optimization planning method for the retired power supply of the coal electric unit at each stage comprises the following steps: the decommissioning scale of the coal electric machine set at each stage, the power supply structure at each stage and the energy storage layout at each stage.
A second aspect of the present application provides a computer-readable storage medium, where a computer program is stored, where the computer program, when executed by a processor, implements a method for optimizing and planning a multi-stage retired power supply of a coal-electric power generation unit as described in any one of the above.
The third aspect of the present application provides a multistage retired power supply optimization planning system for a coal electric machine set, where the multistage retired power supply optimization planning system for a coal electric machine set includes a processor and a machine-readable storage medium, where machine-executable instructions are stored in the machine-readable storage medium, and the machine-executable instructions are loaded and executed by the processor to implement any one of the above-mentioned multistage retired power supply optimization planning methods for a coal electric machine set.
Compared with the prior art, the method has the following beneficial effects: on the premise of considering carbon emission constraint, the invention establishes relevant constraint from the planning and operation level respectively for quantitatively analyzing the influence of coal power decommissioning on the equivalent inertia, power supply and demand balance and frequency safety of the system, takes the lowest total cost as an optimization target, can obtain the reasonable decommissioning scale and the quitting path of the coal power unit and the reasonable power structure, energy storage scale and layout after solving the model, and provides theoretical guidance for the optimization planning of the power system under the carbon neutralization target.
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The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
fig. 1 is a schematic diagram of a multi-stage retired power supply optimization planning method for a coal electric machine set according to an embodiment of the present invention.
Detailed Description
Hereinafter, the terms "includes" or "may include" used in various embodiments of the present application indicate the presence of the claimed function, operation, or element, and do not limit the addition of one or more functions, operations, or elements. Furthermore, as used in various embodiments of the present application, the terms "comprising," "having," and their derivatives, are intended to be only representative of particular features, integers, steps, operations, elements, components, or combinations of the foregoing, and should not be construed as first excluding the existence of, or adding to one or more other features, integers, steps, operations, elements, components, or combinations of the foregoing.
In various embodiments of the present application, the expression "or" at least one of B or/and C "includes any or all combinations of the words listed simultaneously. For example, the expression "B or C" or "at least one of B or/and C" may include B, may include C, or may include both B and C.
Expressions (such as "first", "second", and the like) used in various embodiments of the present application may modify various constituent elements in the various embodiments, but may not limit the respective constituent elements. For example, the above description does not limit the order and/or importance of the elements described. The foregoing description is for the purpose of distinguishing one element from another. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of various embodiments of the present application.
It should be noted that: if it is described that one constituent element is "connected" to or with another constituent element, the first constituent element may be directly connected to the second constituent element, and a third constituent element may be "connected" between the first constituent element and the second constituent element. In contrast, when one constituent element is "directly connected" to or with another constituent element, it is understood that there is no third constituent element between the first constituent element and the second constituent element.
The terminology used in the various embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the various embodiments of the present application. As used herein, the singular forms are intended to include the plural forms as well, unless the context clearly indicates otherwise. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application belong. The terms (such as those defined in commonly used dictionaries) should be interpreted as having a meaning that is consistent with their contextual meaning in the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in various embodiments.
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to examples and drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present application and are not used as limitations of the present application.
Example 1
The embodiment provides a coal electric unit multi-stage retired power supply optimization planning method, which considers carbon emission related targets and constraints in power grid planning, establishes a coal electric unit multi-stage retired power supply optimization model, and performs quantitative simulation analysis on a system power and electricity balance relation, system inertia safety and frequency safety, so that the influence of different coal electric retired paths on a system can be truly measured, and further the retired power supply optimization planning method of each stage of the coal electric unit is obtained.
Referring to fig. 1, fig. 1 is a schematic diagram of a multi-stage retired power supply optimization planning method for a coal-electric machine set, including
S1, collecting power grid information related to decommissioning of a coal-electric machine set, and generating a basic database;
s2, a coal electric unit multistage decommissioning power optimization model is formulated according to the basic database, and the coal electric unit multistage decommissioning power optimization model comprises the following steps: a cost objective function and constraints for the cost objective function, the constraints comprising: planning constraints and operating constraints;
and S3, solving the coal electric unit multistage retired power supply optimization model to obtain a retired power supply optimization planning method of each stage of the coal electric unit.
Specifically, in step S1, the problems that the power grid will face after the coal-electric machine set is decommissioned are analyzed from multiple aspects, including aspects such as supply and demand balance adjustment, system inertia level, frequency safety, and new energy development and utilization, and the power grid information related to decommissioning of the coal-electric machine set is collected, including: generating a basic database by using system planning general data, unit basic parameter data and production decision limiting condition data including carbon emission limitation, and providing reference for establishing a coal-electric unit multistage retired power supply optimization model;
the system planning profile data comprising: the method comprises the following steps of establishing unit information, to-be-decommissioned coal-electric unit information, to-be-commissioned unit information, the number y of system planning stages and the maximum predicted load of the y stage in a system planning period; the unit basic parameter data comprises: unit type, installed capacity, climbing rate, carbon emission factor and service life; the production decision limiting condition data of each stage comprises the following data of the y stage: the maximum carbon emission, the maximum allowable decommissioning capacity of the coal-electric unit and the maximum allowable building capacity of each type of unit to be built.
In step S2, a multistage retired power optimization model of the coal electric machine set is formulated according to the basic database, and the method includes:
s21, establishing decision variables of the coal-electric machine set multistage retired power supply optimization model, wherein the decision variables comprise: retired state variable alpha of coal electric unit in y stage i，y The state variable beta of the gas-electric machine set in the y stage i，y And the construction state variable B of the pumped storage unit in the y stage i，y Integral variable W built by wind-solar unit in the y stage i，y ,V i，y Calculating the decommissioning processing cost of the coal-electric machine set, the maintenance cost of the coal-electric machine set, the investment cost of the gas-electric machine set, the maintenance cost of the gas-electric machine set, the investment cost of the wind-solar machine set, the investment cost of pumped storage and the system operation cost in the y stage according to the decision variables and the data in the basic database;
s22, constructing a cost objective function according to the decommissioning treatment cost of the coal-electricity unit, the maintenance cost of the coal-electricity unit, the investment cost of the gas-electricity unit, the maintenance cost of the gas-electricity unit, the investment cost of the wind-light unit, the investment cost of the pumped storage and the system operation cost in the y stage.
The cost objective function is:
Figure BDA0003932222090000051
wherein the content of the first and second substances,
Figure BDA0003932222090000052
respectively representing the decommissioning treatment cost of the coal-electricity unit, the maintenance cost of the coal-electricity unit, the investment cost of the gas-electricity unit, the maintenance cost of the gas-electricity unit, the investment cost of the wind-light unit, the investment cost of the pumped storage and the system operation cost of the system in the Y stage, wherein Y represents all stages to be planned, delta y And representing the current value coefficient corresponding to the cost in the y stage.
Specifically, the decommissioning treatment cost of the coal electric unit is as follows:
Figure BDA0003932222090000053
wherein c is d Decommissioning costs corresponding to unit capacity of the coal-electric machine set, c s For the recovery yield corresponding to the unit capacity of the coal-electric machine set,
Figure BDA0003932222090000054
the installed capacity of the coal-electric machine set i.
The maintenance cost of the coal-electricity unit is as follows:
Figure BDA0003932222090000055
wherein
Figure BDA0003932222090000056
Is the maintenance cost corresponding to the unit capacity of the coal-electric machine set, epsilon is the annual growth rate of the maintenance cost,
Figure BDA0003932222090000057
the service life of the coal-electric machine set i is prolonged.
The investment cost of the gas-electric machine set is as follows:
Figure BDA0003932222090000061
wherein c is g The investment cost corresponding to the unit capacity of the gas-electric machine set,
Figure BDA0003932222090000062
the installed capacity of the gas-electric machine set i.
The maintenance cost of the gas-electric machine set is as follows:
Figure BDA0003932222090000063
wherein
Figure BDA0003932222090000064
For the maintenance cost corresponding to the unit capacity of the gas-electric machine set,
Figure BDA0003932222090000065
the service life of the gas-electric machine set i is prolonged.
The investment cost of the wind and light set is as follows:
Figure BDA0003932222090000066
wherein c is w The investment cost corresponding to the unit capacity of the wind turbine generator,
Figure BDA0003932222090000067
installed capacity of individual units of fan unit i, c pv The investment cost corresponding to the unit capacity of the photovoltaic power station,
Figure BDA0003932222090000068
the installed capacity of a single unit of the photovoltaic power station at the position i.
The pumped storage investment cost is as follows:
Figure BDA0003932222090000069
wherein
Figure BDA00039322220900000610
The investment cost corresponding to the storage capacity of the pumped storage unit,
Figure BDA00039322220900000611
is the maximum storage capacity of water pumping and energy storage at the position i,
Figure BDA00039322220900000612
the investment cost corresponding to the unit power of pumped storage,
Figure BDA00039322220900000613
and (5) pumping water at the position i to store the installed capacity of energy.
The system running cost includes the electricity generation cost and the start-up cost of coal-electricity unit and gas-electricity unit, the carbon emission punishment cost of coal-electricity unit, the CCUS treatment cost of gas-electricity unit, abandon water punishment cost, abandon wind and abandon light punishment cost, specifically does:
Figure BDA00039322220900000614
wherein a is i 、b i 、c i Characteristic coefficients of a power generation cost function of the unit i; u shape i，t Is the state of the unit i in the time period t, U i，t =1 said unit is in operation, U i，t =0 indicates that the unit is in a shutdown state; s i The starting cost of the unit i is calculated;
Figure BDA00039322220900000615
the carbon emission factor of the unit i; t is t y，i The annual utilization hours of the unit i in the y stage;
Figure BDA0003932222090000074
the water-electricity conversion coefficient of the hydroelectric generating set i; a. The i，t The method comprises the following steps of (1) providing the water discharge amount of a hydroelectric generating set i in a time period t;
Figure BDA0003932222090000075
and (4) electric power abandoning of the wind-light unit i in the time period t.
In step S2, according to requirements such as a carbon emission limit of a power grid, a power balance, a number limit of units to be put into operation, and the like, constraint conditions of a system planning level are constructed, and the planning constraint conditions include: the method comprises the following steps of power supply installed capacity electric power balance constraint, carbon emission constraint, coal electric unit retirement constraint and newly increased power supply commissioning constraint.
Specifically, the power source installed capacity power balance constraint:
Figure BDA0003932222090000071
wherein
Figure BDA0003932222090000076
The installed capacity of the hydroelectric generating set i; RM is a standby coefficient of the system load;
Figure BDA0003932222090000077
the maximum delivery power of the dc delivery line hl.
Carbon emission constraint:
Figure BDA0003932222090000072
wherein
Figure BDA0003932222090000078
The maximum carbon emissions of the system during the y stage.
Constraint of decommissioning of the coal-electric unit:
Figure BDA0003932222090000073
wherein
Figure BDA0003932222090000079
The maximum ratio of the capacity of each retired coal-electric unit to the total capacity is obtained; m is a sufficiently large constant; s y，min The minimum installed capacity of a single coal-electric unit in service at the y stage; t is t y，min The minimum annual utilization hours of the coal-electric machine set in the y stage;
Figure BDA00039322220900000710
is a service life mark of the coal-electric machine set,
Figure BDA00039322220900000711
and the time indicates that the coal electric unit i reaches the service life at the y stage.
Newly adding power supply commissioning constraint:
Figure BDA0003932222090000081
wherein
Figure BDA0003932222090000082
The maximum investment cost of the wind-solar unit at the y stage is obtained;
Figure BDA0003932222090000083
the maximum investment cost of the gas-electric machine set in the y stage is obtained;
Figure BDA0003932222090000084
the maximum investment cost of the pumped storage unit in the y stage is achieved.
In step S2, according to the conditions such as the minimum equivalent inertia requirement of the system, the peak-load and frequency-modulation requirements, and the like, considering four typical operation modes of rich, lean, rich and lean, and constructing constraint conditions of the system operation level, where the operation constraint conditions include: the method comprises the following steps of power balance constraint, system equivalent inertia constraint, peak regulation operation constraint, frequency modulation operation constraint, wind and light unit uncertainty output constraint, conventional unit output constraint, hydroelectric generating set operation constraint and pumped storage unit operation constraint.
Specifically, the power balance constraint:
Figure BDA0003932222090000085
wherein
Figure BDA0003932222090000087
Actual output of the coal electric unit i in a time period t;
Figure BDA0003932222090000088
the actual output of the hydroelectric generating set i in the time period t;
Figure BDA0003932222090000089
is a gas-electric machine set iActual force at time t;
Figure BDA00039322220900000810
actual output of the wind and light unit i in a time period t;
Figure BDA00039322220900000811
generating power for the pumped storage unit i in a time period t;
Figure BDA00039322220900000812
pumping power of the pumped storage unit i in a time period t; r is d，t A system load value for a time period t; p is hl，t The actual delivery power of the dc delivery line hl during the time period t.
System equivalent inertia constraint:
Figure BDA0003932222090000086
wherein
Figure BDA00039322220900000813
The minimum equivalent inertia of the system;
Figure BDA00039322220900000814
the inertia time constant of the coal electric unit i is obtained;
Figure BDA00039322220900000815
is the inertia time constant of the gas-electric machine set i;
Figure BDA0003932222090000091
and (4) the inertia time constant of the hydroelectric generating set i.
Peak shaving operation constraint:
Figure BDA0003932222090000092
wherein RU i The maximum upward climbing power of the conventional unit i; RD i Is the most common unit iLarge down-hill climbing power;
Figure BDA0003932222090000093
the minimum outgoing power for the direct current outgoing line hl; t is hl The minimum stabilization time after the adjustment of the outgoing power of the direct current outgoing line hl; a is a hl，t A state variable adjusted upward for the dc delivery line hl delivery power for a time period t; b hl，t A state variable adjusted downward for the power delivered by the dc delivery line hl for a time period t; delta P gmax The maximum installed capacity of a single unit in all units.
And (4) frequency modulation operation constraint:
Figure BDA0003932222090000094
wherein k is i Adjusting the power coefficient for the unit of the conventional unit i; Δ f max Maximum frequency deviation allowed for grid operation; k l The power coefficient is adjusted for units of system load.
Wind-solar unit uncertainty output constraint:
Figure BDA0003932222090000101
wherein
Figure BDA0003932222090000102
Actual output upper and lower limits of the wind and light unit i in the time period t;
Figure BDA0003932222090000103
the output predicted value of the wind and light set i in the time period t is obtained;
Figure BDA0003932222090000104
outputting an upper limit of a predicted value prediction error for the wind and light unit i in a t time period;
Figure BDA0003932222090000105
to constrain an event, θ is the confidence level, pr { ·Denotes the probability that an event holds, which is converted into a deterministic constraint, Δ P, by applying the Chebyshev inequality rμ The method is characterized in that the method is an average value of the prediction errors of the wind and light unit output prediction value, and sigma is a variance of the prediction errors of the wind and light unit output prediction value.
And (3) output constraint of a conventional unit:
Figure BDA0003932222090000106
wherein
Figure BDA0003932222090000107
The maximum output and the minimum output of the coal electric machine set and the gas electric machine set are respectively.
And (3) operation constraint of the hydroelectric generating set:
Figure BDA0003932222090000108
wherein
Figure BDA0003932222090000109
The minimum output of the hydroelectric generating set i; q. q.s i，t Generating flow of the hydroelectric generating set i in a time period t; c i，t The storage capacity of the hydropower unit I at the t time period;
Figure BDA00039322220900001010
the flow rate of the No. i hydroelectric generating set in storage at the time period t; q. q.s i，max 、q i，min The upper limit and the lower limit of the generating flow of the No. i hydroelectric generating set are respectively set; c i，max 、C i，min The upper limit and the lower limit of the storage capacity of the No. i hydroelectric generating set are respectively.
And (3) operation constraint of the pumped storage unit:
Figure BDA0003932222090000111
wherein
Figure BDA0003932222090000112
The pumping efficiency and the generating efficiency of the No. i pumping energy storage unit are respectively;
Figure BDA0003932222090000113
the pumping power and the generating power of the No. i pumping energy storage unit in the time period t are respectively; s i，t The water storage capacity of an upper reservoir of the pumping energy storage unit I at a time interval t; s. the i，max 、S i，min The maximum water storage capacity and the minimum water storage capacity of the I-type pumped storage unit are respectively;
Figure BDA0003932222090000114
the maximum and minimum power generation and pumping power of the I-type pumped storage unit are respectively; generating flow of the hydroelectric generating set i in a time period t; c i，t The storage capacity of the hydropower unit I at the t time period;
Figure BDA0003932222090000115
the binary integer variables are respectively the i-th pumped storage unit in the power generation state and the pumping state in the t period; s i，sta 、S i，fin The initial water storage capacity and the final water storage capacity of the No. i pumped storage unit are respectively.
In step S3, solving the coal-electric machine set multistage retired power optimization model includes:
the generating cost of the unit in the objective function is linearized in a segmented manner, and a multi-stage retired power supply optimization model of the coal-electric unit is converted into a mixed integer linear optimization model;
and (4) solving the multistage retired power supply optimization model of the coal electric unit after the piecewise linearization by calling the CPLEX through a GAMS (business intelligence system) programming solving program to obtain the retired power supply optimization planning method of the coal electric unit at each stage.
The optimization planning method for the retired power supply of the coal electric unit at each stage comprises the following steps: the decommissioning scale of the coal electric unit at each stage, the power supply structure at each stage and the energy storage layout at each stage.
According to the coal-electricity unit multi-stage decommissioning power supply optimization planning method provided by the embodiment, on the premise of considering carbon emission constraints, for quantitatively analyzing the influence of coal-electricity decommissioning on system equivalent inertia, power supply and demand balance and frequency safety, relevant constraints are respectively established from planning and operation levels, the lowest total cost is taken as an optimization target, a reasonable decommissioning scale and a quitting path of the coal-electricity unit and a reasonable power supply structure, energy storage scale and layout can be obtained after a model is solved, and theoretical guidance is provided for optimization planning of a power system in carbon and under the target.
In a second aspect of the present embodiment, a computer-readable storage medium is provided, where the computer-readable storage medium stores a computer program, where the computer program is executed by a processor to implement the method for planning power optimization for multi-stage retired power supply of a coal-electric machine group as described above.
In a third aspect of the present embodiment, a multistage retired power supply optimization planning system of a coal electric power unit is provided, where the multistage retired power supply optimization planning system of a coal electric power unit includes a processor and a machine-readable storage medium, where machine-executable instructions are stored in the machine-readable storage medium, and the machine-executable instructions are loaded and executed by the processor to implement the above-mentioned multistage retired power supply optimization planning method of a coal electric power unit.
Example 2
The embodiment is actually applied on the basis of the multi-stage retired power supply optimization planning method for the coal electric machine set provided in embodiment 1, and the multi-stage retired power supply optimization planning method for the coal electric machine set is applied to an improved RTS79 system to obtain a 2-stage multi-stage retired power supply planning for the coal electric machine set.
The basic information of the improved RTS79 system is: at present, 22 hydroelectric generating sets are shared, and the total installed capacity is 2405MW; 10 coal electric machine sets with total installed capacity of 1000MW; 10 gas-electric machine sets to be put into operation, wherein the total installed capacity is 1600MW; at a wind power plant 3 to be built, the installed capacity of each wind power plant is 30MW, and the maximum building number is 10; at the position 3 of the photovoltaic power station to be put into operation, the capacity of a single machine assembling machine of each photovoltaic power station is 30MW, and the maximum putting quantity is 10; 3 pumped storage units are to be put into operation, and the total installed capacity is 540MW; the current maximum load of the system is 2800MW, the load prediction result in the planning period is 2939MW of the system maximum load in the 1 st stage, and 3086MW of the system maximum load in the 2 nd stage.
According to the method, a target function and constraint conditions are established to obtain a coal-electric machine set multi-stage retired power supply optimization planning model, the established model is programmed by GAMS, CPLEX is called to solve to obtain a power supply planning scheme as follows:
TABLE 1 decommissioning arrangement of coal-electric machine group at each stage
Figure BDA0003932222090000121
TABLE 2 gas-electric machine set arrangement at each stage
Figure BDA0003932222090000131
TABLE 3 arrangement of wind-solar unit in each stage
Figure BDA0003932222090000132
TABLE 4 arrangement of pumped storage unit in each stage
Figure BDA0003932222090000133
On the whole, in the process that the system exits from the coal-electricity under the carbon emission constraint, in order to meet the requirements of the equivalent inertia level, peak regulation, frequency modulation and the like of the system, the gas-electric unit with the carbon capture technology becomes a priority to replace the coal-electric unit, and meanwhile, in order to meet the increased load requirement, the synchronous construction of the wind-light unit and the pumped storage unit is accompanied.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. A coal-electric machine set multi-stage retired power supply optimization planning method is characterized by comprising the following steps: comprises that
Collecting power grid information related to decommissioning of the coal-electric unit to generate a basic database;
and formulating a coal electric unit multi-stage retired power supply optimization model according to the basic database, wherein the coal electric unit multi-stage retired power supply optimization model comprises the following steps: a cost objective function and constraints for the cost objective function, the constraints comprising: planning constraints and operating constraints;
and solving the coal electric unit multistage retired power supply optimization model to obtain the retired power supply optimization planning method of the coal electric unit at each stage.
2. The coal-electric machine set multi-stage retired power supply optimization planning method according to claim 1, which is characterized by comprising the following steps of: the base database, comprising: the system planning general data, the unit basic parameter data and the production decision limiting condition data of each stage;
the system planning profile data comprising: the method comprises the following steps of establishing unit information, coal-electric unit information to be retired, unit information to be put into operation, the number y of system planning stages and the maximum predicted load of the y stage in a system planning period;
the unit basic parameter data comprises: unit type, installed capacity, climbing rate, carbon emission factor and service life;
the production decision limiting condition data of each stage comprises the following data of the y stage: the maximum carbon emission, the maximum allowable decommissioning capacity of the coal-electric unit and the maximum allowable building capacity of each type of unit to be built.
3. The method for optimizing and planning the multi-stage retired power supply of the coal-electric machine set according to claim 1, wherein the method comprises the following steps: and formulating a coal-electric machine set multi-stage retired power supply optimization model according to the basic database, which comprises the following steps:
establishing decision variables of a coal-electric machine set multistage retired power supply optimization model, and calculating retired processing cost of the coal-electric machine set, coal-electric machine set maintenance cost, gas-electric machine set investment cost, gas-electric machine set maintenance cost, wind-solar machine set investment cost, pumped storage investment cost and system operation cost in the y stage according to the decision variables and data in the basic database;
and constructing a cost objective function according to the decommissioning treatment cost of the coal-electric machine set, the maintenance cost of the coal-electric machine set, the investment cost of the gas-electric machine set, the maintenance cost of the gas-electric machine set, the investment cost of the wind-solar machine set, the investment cost of the pumped storage and the operation cost of the system in the y stage.
4. The coal-electric machine set multi-stage retired power supply optimization planning method according to claim 3, which is characterized by comprising the following steps of: the cost objective function is:
Figure FDA0003932222080000011
wherein the content of the first and second substances,
Figure FDA0003932222080000012
respectively representing the decommissioning treatment cost of the coal-electricity unit, the maintenance cost of the coal-electricity unit, the investment cost of the gas-electricity unit, the maintenance cost of the gas-electricity unit, the investment cost of the wind-light unit, the investment cost of the pumped storage and the system operation cost of the system in the Y stage, wherein Y represents all stages to be planned, delta y And representing the current value coefficient corresponding to the cost in the y stage.
5. The method for optimizing and planning the multi-stage retired power supply of the coal-electric machine set according to claim 1, wherein the method comprises the following steps: the planning constraints include: the method comprises the following steps of power supply installed capacity electric power balance constraint, carbon emission constraint, coal electric unit retirement constraint and newly increased power supply commissioning constraint.
6. The coal-electric machine set multi-stage retired power supply optimization planning method according to claim 1, which is characterized by comprising the following steps of: the operating constraints include: the method comprises the following steps of power balance constraint, system equivalent inertia constraint, peak regulation operation constraint, frequency modulation operation constraint, wind and light unit uncertainty output constraint, conventional unit output constraint, hydroelectric generating set operation constraint and pumped storage unit operation constraint.
7. The method for optimizing and planning the multi-stage retired power supply of the coal-electric machine set according to claim 4, wherein the method comprises the following steps: solving the coal-electric machine set multistage retired power supply optimization model, comprising the following steps of:
carrying out piecewise linearization on the generating cost of the unit in the objective function;
and (4) solving the multistage retired power supply optimization model of the coal electric unit after the piecewise linearization by calling the CPLEX through a GAMS (business intelligence system) programming solving program to obtain the retired power supply optimization planning method of the coal electric unit at each stage.
8. The coal-electric machine set multi-stage retired power supply optimization planning method according to claim 7, characterized by comprising the following steps: the optimization planning method for the retired power supply of the coal electric machine unit at each stage comprises the following steps: the decommissioning scale of the coal electric unit at each stage, the power supply structure at each stage and the energy storage layout at each stage.
9. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, implements a method for optimizing planning of a multi-stage retired power supply of a coal-electric power plant according to any of claims 1 to 8.
10. A coal electric machine set multi-stage retired power supply optimization planning system is characterized by comprising a processor and a machine-readable storage medium, wherein machine-executable instructions are stored in the machine-readable storage medium and loaded and executed by the processor to achieve the coal electric machine set multi-stage retired power supply optimization planning method according to any one of claims 1-8.
CN202211391903.8A 2022-11-08 2022-11-08 Optimization planning method, medium and system for multi-stage retired power supply of coal electric unit Pending CN115630748A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117937580A (en) * 2023-12-13 2024-04-26 国家电网有限公司华东分部 Power supply planning method, device, equipment and medium for arrival-time thermal power generating unit

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