CN113256009A - Two-stage multi-standby configuration method, system and device based on gas-heat inertia - Google Patents
Two-stage multi-standby configuration method, system and device based on gas-heat inertia Download PDFInfo
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Abstract
The invention discloses a two-stage multi-standby configuration method, a two-stage multi-standby configuration system and a two-stage multi-standby configuration device based on gas-heat inertia, and belongs to the field of comprehensive energy systems. According to the gas-heat-inertia-based two-stage multi-standby configuration method, the complex coupling relation among the gas-heat inertia power support size, the continuous input time and the continuous correction time of the comprehensive energy system is considered, the gas-heat-inertia standby unified model of the comprehensive energy system is constructed by combining the actual situation of standby configuration of the comprehensive energy system, the gas-inertia standby, the heat-inertia standby, the power generation side standby and the demand side standby are comprehensively considered, the lowest total cost of the standby configuration of the system in the two-stage scheduling period is taken as the target function of the standby configuration of the comprehensive energy system, day-ahead constraint, day-ahead intra-day association constraint and day-ahead intra-day association constraint are brought into consideration, standby configuration optimization is carried out on the actual park-level comprehensive energy system, and the running economy of the system is improved on the premise that the reliability level of the system is guaranteed.
Description
Technical Field
The invention relates to the field of comprehensive energy systems, in particular to a two-stage multi-standby configuration method, a two-stage multi-standby configuration system and a two-stage multi-standby configuration device based on gas-heat inertia.
Background
In recent years, the world energy crisis and environmental pressure promote the development of a comprehensive energy system, and the multi-energy complementary characteristics of the comprehensive energy system can help to improve the energy utilization efficiency and promote the consumption of new energy. However, the complexity of system operation is increased by the multi-energy coupling of the comprehensive energy sources, so that the problem of optimizing the standby configuration of the comprehensive energy source system needs to be deeply researched to deal with various source load uncertainties of system operation.
However, current technology focuses on the study of large grid backup configurations, and there is little concern about the study of integrated energy backup configurations. Considering that the large power grid and the comprehensive energy system have the risk of unbalanced supply and demand in actual operation, the reliability of system operation needs to be reasonably ensured, and the economical efficiency of system scheduling operation cost needs to be considered, so that the standby configuration method of the large power grid needs to be extended to the standby configuration of the comprehensive energy system. Accordingly, a two-stage multi-standby configuration method, system and apparatus based on gas thermal inertia is presented.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a two-stage multi-standby configuration method, a system and a device based on gas-heat inertia.
The purpose of the invention can be realized by the following technical scheme:
a two-stage multi-standby configuration method based on gas-heat inertia comprises the following steps:
constructing a standby model based on standby configuration of the comprehensive energy system and gas-heat inertia factors; constructing an objective function with the lowest total cost as a target based on the standby configuration cost of the integrated energy system;
constructing a day-ahead constraint based on the operation constraint of the comprehensive energy system; forming an intra-day constraint based on the prediction error; constructing correlation constraints in the day and the day based on correlation constraints called by the actual daily load-output situation and the daily transaction reserve capacity;
and optimizing the standby configuration of the integrated energy system according to the standby model, the cost function, the day-ahead constraint, the day-in constraint and the association constraint.
Further, the gas-heat inertia factors comprise the size of a gas-heat inertia power support, continuous input time and continuous correction time;
the standby model is as follows:
wherein R iskFor k-time gas-thermal inertia standby output, RmaxUpper limit of gas-thermal inertia backup output, okThe continuous input time of gas-heat inertia standby for k time period, max _ ON is the longest continuous input time of gas-heat inertia standby, f1(Rk) The functional relation between the maximum continuous input time of the gas-thermal inertia standby and the standby output is shown,
is (k + o)k) The gas-heat inertia standby continuous correction time is started in a time interval, min _ OFF is the shortest gas-heat inertia standby continuous correction time, f2(Rk,ok) And the function relation of the gas-thermal inertia standby shortest continuous correction time, the standby output and the continuous input time is shown.
Further, f1(Rk)、f2(Rk,ok) The expression formula of (a) is:
wherein R ismin、Rmax1、Rmax2、Rmax3、Rmax4、Rmax、(Ro)min、(Ro)max1、(Ro)max2、(Ro)max3、(Ro)max4、(Ro)maxAll are constant values determined by the gas-heat inertia characteristics of the integrated energy system.
Further, the backup configuration of the integrated energy system comprises gas inertia backup, thermal inertia backup, power generation side backup and demand side backup;
the objective function is:
wherein, CGR(k) For the time period k, the gas inertia standby cost,
for the time period k, the gas inertia reserve price,
for k time period gas inertia reserve day-ahead traffic volume,
for the price of natural gas in the period k,
for k time period gas inertia reserve daily actual input capacity, CHR(k) For the time period k the thermal inertia back-up cost,
for the period k of time the thermal inertia reserve price,
for k-time thermal inertia reserve day-ahead capacity,
the actual call price for the hot standby for the period k,
spare actual input capacity for thermal inertia during period k, CSR(k) For the k-period power generation side standby cost,
for the standby price on the power generation side for the period k,
reserve day-ahead capacity for the generation side at the k-period,
for the time period k the price of electricity,
reserve actual input capacity for the generating side for k periods, CDR(k) For the k period the demand side spare cost,
for the demand side reserve price for the period k,
for the spare day-ahead capacity on the demand side for the period k,
the actual call price is reserved for the demand side for period k,
the demand side is reserved with actual input capacity for the k period.
Further, the day-ahead constraints comprise a power balance constraint, an external power grid input constraint, an external gas grid input constraint, a gas inertia standby constraint, a thermal inertia standby constraint, a power generation side standby constraint and a demand side standby constraint;
the power balance constraint is:
wherein the content of the first and second substances,
electric energy distribution coefficient eta of k time period comprehensive energy systemTIn order to be efficient for the transformer,
for the input power of the external grid during the period k,
for the predicted value of the photovoltaic output in the k time period,
for the electric energy generating efficiency of the cogeneration unit,
for the external gas network input power for the period k,
predicted value of electrical load, η, for a period of kEBIn order to achieve the efficiency of the electric boiler,
in order to improve the heat energy generating efficiency of the cogeneration unit,
a predicted value of the thermal load for the k time period;
the external grid input constraints are:
wherein the content of the first and second substances,
the lower limit of the input power of the external power grid,
the upper limit of the input power of the external power grid,
for the input power down-ramp rate of the external power grid, Δ k is the time of a period of time,
inputting power climbing rate for an external power grid;
the external gas network input constraints are:
wherein the content of the first and second substances,
the lower limit of the input power of the external power grid,
the upper limit of the input power of the external power grid,
the input power of the external power grid is used for the downward slope climbing rate,
inputting power climbing rate for an external power grid;
the gas inertia standby constraint is as follows:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that gas inertia is put into standby in the period k,
indicating that gas inertia is not put into reserve during the period k,
is the upper limit of the gas inertia standby output,
gas inertia standby continuous ON time for k period, max _ ONGThe longest continuous input time for gas inertia standby,
representing the functional relation between the longest continuous input time of gas inertia standby and standby output,
is composed of
Time period gas start inertia standby continuous correction time, min _ OFFGThe shortest continuous correction time is reserved for gas inertia,
representing the functional relation between the gas inertia standby shortest continuous correction time and the standby output and continuous input time;
the thermal inertia backup constraints are:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that the thermal inertia is put into standby during the period k,
indicating that thermal inertia is not put to standby during the k period,
is the upper limit of the thermal inertia standby output,
starting thermal inertia standby continuous ON time for period k, max _ ONHThe longest continuous input time for thermal inertia standby,
representing the functional relation between the maximum continuous input time of the thermal inertia standby and the standby output,
is composed of
Time period starting thermal inertia standby continuous correction time, min _ OFFHThe shortest continuous correction time is reserved for thermal inertia,
representing the functional relation between the thermal inertia standby shortest continuous correction time and the standby output and continuous input time;
the standby constraint of the power generation side is as follows:
wherein the content of the first and second substances,
the lower limit of the standby output of the power generation side,
is the upper limit of the standby output of the power generation side,
for the standby downward climbing rate of the power generation side,
reserve climbing rate for the power generation side;
the demand side standby constraints are:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that the thermal inertia is put into standby during the period k,
indicating that thermal inertia is not put to standby during the k period,
the lower limit of the backup output of the demand side,
for the upper limit of the reserve output on the demand side,
the longest continuous input time is reserved for the demand side in a period of time.
Further, the prediction error comprises a photovoltaic prediction error, an electrical load prediction error and a thermal load prediction error; the intra-day constraint is:
wherein the content of the first and second substances,
for the k-period system actual photovoltaic prediction error,
the error is predicted for the actual electrical load of the system over the k period,
the error is predicted for the actual thermal load of the system over the k period.
Further, the association constraint is:
in another aspect of the present invention, a two-stage multi-standby configuration system based on gas thermal inertia is provided, the system comprising:
the standby configuration module is used for calculating standby configuration of the comprehensive energy system;
the cost regulation and control module is used for analyzing and regulating and controlling the operation cost of the comprehensive energy system;
the day-ahead constraint module is used for calculating power balance constraint, external power grid input constraint, external air grid input constraint, air inertia standby constraint, thermal inertia standby constraint, power generation side standby constraint and demand side standby constraint;
the in-day constraint module is used for calculating a photovoltaic prediction error, an electrical load prediction error and a thermal load prediction error;
the daily constraint module is used for calculating the correlation constraint for calling the daily load-out actual condition and the daily transaction reserve capacity;
and the execution module is used for optimizing the standby configuration of the comprehensive energy system based on the standby configuration module, the cost regulation and control module, the day-ahead constraint module, the in-day constraint module and the in-day constraint module.
In a third aspect of the invention, a storage device is proposed, in which a plurality of programs are stored, which are to be loaded and executed by a processor to implement the two-stage multi-standby configuration method based on gas thermal inertia according to any one of claims 1 to 7.
In a fourth aspect of the present invention, a processing apparatus is provided, comprising a processor adapted to execute various programs, the programs being loaded and executed by the processor to implement the gas thermal inertia based two-stage multi-standby configuration method according to any of claims 1 to 7
The invention has the beneficial effects that:
the invention provides a two-stage multi-standby configuration method based on gas-heat inertia, which fully excavates the inertia characteristics of a gas-heat system, constructs a gas-heat inertia standby unified model of the comprehensive energy system based on the complex coupling relation among the gas-heat inertia power support size, the continuous input time and the continuous correction time of the comprehensive energy system, utilizes the abundant flexibility of the multi-energy coupling of the comprehensive energy system, on the basis of the traditional power generation side and demand side standby mode, gas-heat inertia standby is added, the lowest total cost of system standby configuration in a two-stage scheduling period is taken as an objective function of comprehensive energy system standby configuration, and meanwhile, day-ahead constraint, day-in-day constraint and day-before-day association constraint are included, the backup configuration of the actual park-level comprehensive energy system is optimized, and the running economy of the system is improved on the premise of ensuring the reliability level of the system.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a schematic diagram of an integrated energy system according to the present invention;
FIG. 2 shows the configuration result of the spare traffic capacity (day ahead) of the integrated energy system according to the present invention;
fig. 3 shows the result of the backup actual output (within the day) configuration of the integrated energy system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
A two-stage multi-standby configuration method of an integrated energy system considering gas-heat inertia standby comprises the following steps:
considering the complex coupling relation among the gas-heat inertia power support size, the continuous input time and the continuous correction time of the comprehensive energy system, and combining the practical situation of standby configuration of the comprehensive energy system, constructing a gas-heat inertia standby unified model of the comprehensive energy system;
wherein, the longest continuous input time is related to the input standby power, and the shortest continuous correction time is related to the input standby power and the continuous input time. Combining with the actual situation of standby configuration of the comprehensive energy system, taking 24 hours as a complete scheduling cycle and each time interval as 1 hour, constructing a gas-thermal inertia standby unified model as follows:
wherein R iskFor k-time gas-thermal inertia standby output, RmaxUpper limit of gas-thermal inertia backup output, okThe continuous input time of gas-heat inertia standby for k time period, max _ ON is the longest continuous input time of gas-heat inertia standby, f1(Rk) The functional relation between the maximum continuous input time of the gas-thermal inertia standby and the standby output is shown,
is (k + o)k) The gas-heat inertia standby continuous correction time is started in a time interval, min _ OFF is the shortest gas-heat inertia standby continuous correction time, f2(Rk,ok) And the function relation of the gas-thermal inertia standby shortest continuous correction time, the standby output and the continuous input time is shown. f. of1(Rk)、f2(Rk,ok) The description is as follows:
wherein R ismin、Rmax1、Rmax2、Rmax3、Rmax4、Rmax、(Ro)min、(Ro)max1、(Ro)max2、(Ro)max3、(Ro)max4、(Ro)maxAll are constant values determined by the gas-heat inertia characteristics of the integrated energy system.
And (3) considering the complex coupling relation among the size of the gas-heat inertia power support, the continuous input time and the continuous correction time of the comprehensive energy system, constructing a gas-heat inertia standby unified model of the comprehensive energy system, and fully excavating the abundant flexibility contained in the comprehensive energy system.
Comprehensively considering gas inertia standby, thermal inertia standby, power generation side standby and demand side standby, and taking the lowest total cost of system standby configuration in a two-stage scheduling period as a target function of the comprehensive energy system standby configuration; the objective function C (k) is:
wherein, CGR(k) For the time period k, the gas inertia standby cost,
for the time period k, the gas inertia reserve price,
for k time period gas inertia reserve day-ahead traffic volume,
for the price of natural gas in the period k,
for k time period gas inertia reserve daily actual input capacity, CHR(k) For the time period k the thermal inertia back-up cost,
for the period k of time the thermal inertia reserve price,
for k-time thermal inertia reserve day-ahead capacity,
the actual call price for the hot standby for the period k,
spare actual input capacity for thermal inertia during period k, CSR(k) For the k-period power generation side standby cost,
for the standby price on the power generation side for the period k,
reserve day-ahead capacity for the generation side at the k-period,
for the time period k the price of electricity,
reserve actual input capacity for the generating side for k periods, CDR(k) For the k period the demand side spare cost,
for the demand side reserve price for the period k,
for the spare day-ahead capacity on the demand side for the period k,
the actual call price is reserved for the demand side for period k,
the demand side is reserved with actual input capacity for the k period. In the standby mode of the traditional power generation side and the demand sideOn the basis, gas-heat inertia is added for standby, and the abundant flexibility of the multi-energy coupling of the comprehensive energy system is fully utilized.
In the day-ahead scheduling stage, respectively considering power balance constraint, external power grid input constraint, external gas grid input constraint, gas inertia standby constraint, thermal inertia standby constraint, power generation side standby constraint and demand side standby constraint to jointly form day-ahead constraint;
(1) the power balance constraint is:
wherein the content of the first and second substances,
electric energy distribution coefficient eta of k time period comprehensive energy systemTIn order to be efficient for the transformer,
for the input power of the external grid during the period k,
for the predicted value of the photovoltaic output in the k time period,
for the electric energy generating efficiency of the cogeneration unit,
for the external gas network input power for the period k,
predicted value of electrical load, η, for a period of kEBIn order to achieve the efficiency of the electric boiler,
in order to improve the heat energy generating efficiency of the cogeneration unit,
predicted value of heat load in k period.
(2) The external grid input constraints are:
wherein the content of the first and second substances,
the lower limit of the input power of the external power grid,
the upper limit of the input power of the external power grid,
for the input power down-ramp rate of the external power grid, Δ k is the time of a period of time,
and inputting power climbing rate for the external power grid.
(3) The external air network input constraints are:
wherein the content of the first and second substances,
the lower limit of the input power of the external power grid,
the upper limit of the input power of the external power grid,
the input power of the external power grid is used for the downward slope climbing rate,
and inputting power climbing rate for the external power grid.
(4) The gas inertia standby constraints are:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that gas inertia is put into standby in the period k,
indicating that gas inertia is not put into reserve during the period k,
is the upper limit of the gas inertia standby output,
gas inertia standby continuous ON time for k period, max _ ONGThe longest continuous input time for gas inertia standby,
representing the functional relation between the longest continuous input time of gas inertia standby and standby output,
is composed of
Time period gas start inertia standby continuous correction time, min _ OFFGThe shortest continuous correction time is reserved for gas inertia,
and the function relation of the gas inertia standby shortest continuous correction time, the standby output and the continuous input time is shown.
(5) The thermal inertia standby constraints are:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that the thermal inertia is put into standby during the period k,
indicating that thermal inertia is not put to standby during the k period,
is the upper limit of the thermal inertia standby output,
starting thermal inertia standby continuous ON time for period k, max _ ONHThe longest continuous input time for thermal inertia standby,
representing the functional relation between the maximum continuous input time of the thermal inertia standby and the standby output,
is composed of
Time period starting thermal inertia standby continuous correction time, min _ OFFHThe shortest continuous correction time is reserved for thermal inertia,
and the function relation of the thermal inertia standby shortest continuous correction time, the standby output and the continuous input time is shown.
(6) The standby constraint on the power generation side is as follows:
wherein the content of the first and second substances,
the lower limit of the standby output of the power generation side,
is the upper limit of the standby output of the power generation side,
for the standby downward climbing rate of the power generation side,
the standby climbing rate is used as the power generation side.
(7) Demand side standby constraint:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that the thermal inertia is put into standby during the period k,
indicating that thermal inertia is not put to standby during the k period,
the lower limit of the backup output of the demand side,
for the upper limit of the reserve output on the demand side,
the longest continuous input time is reserved for the demand side in a period of time.
In the scheduling stage in the day, the backup configuration in a multi-backup mode is considered to meet the reliability constraints of the actual photovoltaic prediction error, the electrical load prediction error and the thermal load prediction error of the system, and the day constraints are formed;
the intra-day constraint is:
wherein the content of the first and second substances,
for the k-period system actual photovoltaic prediction error,
the error is predicted for the actual electrical load of the system over the k period,
the error is predicted for the actual thermal load of the system over the k period.
In the day-ahead and day-inside association scheduling stage, the correlation constraint of calling the day-ahead transaction reserve capacity, namely the reserve capacity of the transaction in the day-ahead reserve market, is considered by the comprehensive energy operator according to the actual daily-inside load-output situation.
And (3) forming a day-ahead-day association constraint:
and comprehensively considering the two-stage multi-standby configuration objective function, the day-ahead constraint, the day-in constraint and the day-ahead and day-in association constraint of the comprehensive energy system, and performing standby configuration optimization on the actual park-level comprehensive energy system. The total cost of the system standby configuration in the two-stage scheduling period is the lowest as a target function of the comprehensive energy system standby configuration, day-ahead constraint, day-ahead intra-day association constraint and day-ahead intra-day association constraint are brought into consideration, standby configuration optimization is carried out on the actual park level comprehensive energy system, and the system operation economy is improved on the premise that the system reliability level is guaranteed.
Example (b): taking a park level comprehensive energy system as an example, the system structure diagram of the electric-thermal multi-energy coupling in the comprehensive energy system is shown in fig. 1. The gas inertia backup output upper limit is 1000kW, the output lower limit is 0kW, the thermal inertia backup output upper limit is 800kW, the output lower limit is 0kW, the power generation side backup output upper limit is 1000kW, the output lower limit is 0kW, the downward climbing rate is 500kW/h, the upward climbing rate is 500kW/h, the demand side backup output upper limit is 800kW, and the output lower limit is 0 kW; the transformer efficiency is 0.98, the electric energy generation efficiency of the cogeneration unit is 0.30, the heat energy generation efficiency of the cogeneration unit is 0.40, and the electric boiler efficiency is 0.98. And (4) randomly sampling the actual photovoltaic prediction error, the actual electrical load prediction error and the actual thermal load prediction error of the system for 1000 times, and requiring that the standby configuration result meets all the random sampling uncertainties. The two-stage multi-standby configuration method of the comprehensive energy system considering gas-heat inertia standby is utilized, and the standby transaction capacity (day ahead) configuration result and the standby actual output (day in) configuration result are respectively shown in fig. 2 and 3.
The result shows that the system can fully excavate the inertia characteristics of the gas-heat system, and perform two-stage coordinated optimization configuration of multiple standby modes on the premise of meeting different constraints of various standby modes, so that the flexibility contained in the standby configuration of the comprehensive energy system is fully excavated, the economical efficiency of the operation of the comprehensive energy system is improved, and the operation advantages of the comprehensive energy system are brought into play.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.
Claims (10)
1. A two-stage multi-standby configuration method based on gas-heat inertia is characterized by comprising the following steps:
constructing a standby model based on standby configuration of the comprehensive energy system and gas-heat inertia factors; constructing an objective function with the lowest total cost as a target based on the standby configuration cost of the integrated energy system;
constructing a day-ahead constraint based on the operation constraint of the comprehensive energy system; forming an intra-day constraint based on the prediction error; constructing correlation constraints in the day and the day based on correlation constraints called by the actual daily load-output situation and the daily transaction reserve capacity;
and optimizing the standby configuration of the integrated energy system according to the standby model, the cost function, the day-ahead constraint, the day-in constraint and the association constraint.
2. The two-stage multi-standby configuration method based on gas-thermal inertia according to claim 1, wherein the gas-thermal inertia factors include gas-thermal inertia power support size, continuous on-time, and continuous off-time;
the standby model is as follows:
wherein R iskFor k-time gas-thermal inertia standby output, RmaxUpper limit of gas-thermal inertia backup output, okThe continuous input time of gas-heat inertia standby for k time period, max _ ON is the longest continuous input time of gas-heat inertia standby, f1(Rk) The functional relation between the maximum continuous input time of the gas-thermal inertia standby and the standby output is shown,
is (k + o)k) The gas-heat inertia standby continuous correction time is started in a time interval, min _ OFF is the shortest gas-heat inertia standby continuous correction time, f2(Rk,ok) And the function relation of the gas-thermal inertia standby shortest continuous correction time, the standby output and the continuous input time is shown.
3. The two-stage multiple standby configuration method based on aerothermal inertia of claim 2, wherein f1(Rk)、f2(Rk,ok) The expression formula of (a) is:
wherein R ismin、Rmax1、Rmax2、Rmax3、Rmax4、Rmax、(Ro)min、(Ro)max1、(Ro)max2、(Ro)max3、(Ro)max4、(Ro)maxAll are constant values determined by the gas-heat inertia characteristics of the integrated energy system.
4. The gas-thermal-inertia-based two-stage multi-backup configuration method of claim 1, wherein the backup configuration of the integrated energy system comprises gas-inertia backup, thermal-inertia backup, power generation-side backup, and demand-side backup;
the objective function is:
wherein, CGR(k) For the time period k, the gas inertia standby cost,
for the time period k, the gas inertia reserve price,
for k time period gas inertia reserve day-ahead traffic volume,
for the price of natural gas in the period k,
for k time period gas inertia reserve daily actual input capacity, CHR(k) For the time period k the thermal inertia back-up cost,
for the period k of time the thermal inertia reserve price,
for k-time thermal inertia reserve day-ahead capacity,
the actual call price for the hot standby for the period k,
spare actual input capacity for thermal inertia during period k, CSR(k) For the k-period power generation side standby cost,
for the standby price on the power generation side for the period k,
reserve day-ahead capacity for the generation side at the k-period,
for the time period k the price of electricity,
reserve actual input capacity for the generating side for k periods, CDR(k) For the k period the demand side spare cost,
for the demand side reserve price for the period k,
for the spare day-ahead capacity on the demand side for the period k,
the actual call price is reserved for the demand side for period k,
the demand side is reserved with actual input capacity for the k period.
5. The gas-thermal-inertia-based two-stage multi-standby configuration method of claim 1, wherein the day-ahead constraints include a power balance constraint, an external grid input constraint, an external gas grid input constraint, a gas inertia standby constraint, a thermal inertia standby constraint, a generation-side standby constraint, and a demand-side standby constraint;
the power balance constraint is:
wherein the content of the first and second substances,
electric energy distribution coefficient eta of k time period comprehensive energy systemTIn order to be efficient for the transformer,
for the input power of the external grid during the period k,
for the predicted value of the photovoltaic output in the k time period,
for the electric energy generating efficiency of the cogeneration unit,
for the external gas network input power for the period k,
predicted value of electrical load, η, for a period of kEBIn order to achieve the efficiency of the electric boiler,
in order to improve the heat energy generating efficiency of the cogeneration unit,
a predicted value of the thermal load for the k time period;
the external grid input constraints are:
wherein the content of the first and second substances,
the lower limit of the input power of the external power grid,
the upper limit of the input power of the external power grid,
for the input power down-ramp rate of the external power grid, Δ k is the time of a period of time,
inputting power climbing rate for an external power grid;
the external gas network input constraints are:
wherein the content of the first and second substances,
the lower limit of the input power of the external power grid,
the upper limit of the input power of the external power grid,
the input power of the external power grid is used for the downward slope climbing rate,
inputting power climbing rate for an external power grid;
the gas inertia standby constraint is as follows:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that gas inertia is put into standby in the period k,
indicating that gas inertia is not put into reserve during the period k,
is the upper limit of the gas inertia standby output,
gas inertia standby continuous ON time for k period, max _ ONGThe longest continuous input time for gas inertia standby,
representing the functional relation between the longest continuous input time of gas inertia standby and standby output,
is composed of
Time period gas start inertia standby continuous correction time, min _ OFFGFor gas inertia to reserve the shortest continuousThe time of the correction is adjusted,
representing the functional relation between the gas inertia standby shortest continuous correction time and the standby output and continuous input time;
the thermal inertia backup constraints are:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that the thermal inertia is put into standby during the period k,
indicating that thermal inertia is not put to standby during the k period,
is the upper limit of the thermal inertia standby output,
starting thermal inertia standby continuous ON time for period k, max _ ONHThe longest continuous input time for thermal inertia standby,
representing the functional relation between the maximum continuous input time of the thermal inertia standby and the standby output,
is composed of
Time period starting thermal inertia standby continuous correction time, min _ OFFHFor thermal inertia standby shortest connectionThe time is continuously corrected for a period of time,
representing the functional relation between the thermal inertia standby shortest continuous correction time and the standby output and continuous input time;
the standby constraint of the power generation side is as follows:
wherein the content of the first and second substances,
the lower limit of the standby output of the power generation side,
is the upper limit of the standby output of the power generation side,
for the standby downward climbing rate of the power generation side,
reserve climbing rate for the power generation side;
the demand side standby constraints are:
wherein the content of the first and second substances,
is a variable from 0 to 1, and is,
indicating that the thermal inertia is put into standby during the period k,
indicating that thermal inertia is not put to standby during the k period,
the lower limit of the backup output of the demand side,
for the upper limit of the reserve output on the demand side,
the longest continuous input time is reserved for the demand side in a period of time.
6. The gas-thermal-inertia-based two-stage multi-standby configuration method of claim 1, wherein the prediction error comprises a photovoltaic prediction error, an electrical load prediction error, and a thermal load prediction error; the intra-day constraint is:
wherein the content of the first and second substances,
for the k-period system actual photovoltaic prediction error,
the error is predicted for the actual electrical load of the system over the k period,
the error is predicted for the actual thermal load of the system over the k period.
7. The two-stage multi-standby configuration method based on gas thermal inertia of claim 1, wherein the association constraint is:
8. a two-stage multi-standby configuration system based on gas thermal inertia, the system comprising:
the standby configuration module is used for calculating standby configuration of the comprehensive energy system;
the cost regulation and control module is used for analyzing and regulating and controlling the operation cost of the comprehensive energy system;
the day-ahead constraint module is used for calculating power balance constraint, external power grid input constraint, external air grid input constraint, air inertia standby constraint, thermal inertia standby constraint, power generation side standby constraint and demand side standby constraint;
the in-day constraint module is used for calculating a photovoltaic prediction error, an electrical load prediction error and a thermal load prediction error;
the daily constraint module is used for calculating the correlation constraint for calling the daily load-out actual condition and the daily transaction reserve capacity;
and the execution module is used for optimizing the standby configuration of the comprehensive energy system based on the standby configuration module, the cost regulation and control module, the day-ahead constraint module, the in-day constraint module and the in-day constraint module.
9. A storage device having stored therein a plurality of programs for loading and execution by a processor to implement the gas thermal inertia based two-stage multiple standby configuration method of any one of claims 1-7.
10. A processing apparatus comprising a processor adapted to execute programs, wherein the programs are loaded and executed by the processor to implement the gas thermal inertia based two-stage multi-standby configuration method of any of claims 1-7.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170038786A1 (en) * | 2015-08-04 | 2017-02-09 | Nec Laboratories America, Inc. | Management of Grid-Scale Energy Storage Systems |
| CN110197312A (en) * | 2019-06-28 | 2019-09-03 | 东南大学 | A kind of user class integrated energy system Optimization Scheduling based on Multiple Time Scales |
| CN110247392A (en) * | 2019-06-14 | 2019-09-17 | 浙江大学 | More standby resources robust Optimal methods of meter and wind-powered electricity generation marginal capacity and Demand Side Response |
| CN110503271A (en) * | 2019-08-30 | 2019-11-26 | 南京工业大学 | Multi-type energy storage configuration method of comprehensive energy system |
| CN111291942A (en) * | 2020-03-05 | 2020-06-16 | 燕山大学 | Two-stage scheduling method and system of comprehensive energy system considering demand response |
| CN111950171A (en) * | 2020-07-03 | 2020-11-17 | 南京东博智慧能源研究院有限公司 | Backup configuration method for gas-thermal inertia backup participation park comprehensive energy system |
| CN112418488A (en) * | 2020-11-04 | 2021-02-26 | 南方电网科学研究院有限责任公司 | Comprehensive energy system scheduling method and device based on two-stage energy optimization |
| CN112700066A (en) * | 2021-01-14 | 2021-04-23 | 国网山东省电力公司青岛供电公司 | Optimal time scale coordination method for scheduling of electric-thermal integrated energy system |
-
2021
- 2021-05-31 CN CN202110600740.9A patent/CN113256009B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170038786A1 (en) * | 2015-08-04 | 2017-02-09 | Nec Laboratories America, Inc. | Management of Grid-Scale Energy Storage Systems |
| CN110247392A (en) * | 2019-06-14 | 2019-09-17 | 浙江大学 | More standby resources robust Optimal methods of meter and wind-powered electricity generation marginal capacity and Demand Side Response |
| CN110197312A (en) * | 2019-06-28 | 2019-09-03 | 东南大学 | A kind of user class integrated energy system Optimization Scheduling based on Multiple Time Scales |
| CN110503271A (en) * | 2019-08-30 | 2019-11-26 | 南京工业大学 | Multi-type energy storage configuration method of comprehensive energy system |
| CN111291942A (en) * | 2020-03-05 | 2020-06-16 | 燕山大学 | Two-stage scheduling method and system of comprehensive energy system considering demand response |
| CN111950171A (en) * | 2020-07-03 | 2020-11-17 | 南京东博智慧能源研究院有限公司 | Backup configuration method for gas-thermal inertia backup participation park comprehensive energy system |
| CN112418488A (en) * | 2020-11-04 | 2021-02-26 | 南方电网科学研究院有限责任公司 | Comprehensive energy system scheduling method and device based on two-stage energy optimization |
| CN112700066A (en) * | 2021-01-14 | 2021-04-23 | 国网山东省电力公司青岛供电公司 | Optimal time scale coordination method for scheduling of electric-thermal integrated energy system |
Non-Patent Citations (2)
| Title |
|---|
| 刘向向;卢婕;严勤;周琪;李昊翔;严强;: "考虑热惯性的居民楼宇综合能源系统日前运行优化", 可再生能源, no. 03, pages 129 - 135 * |
| 孙维佳等: "考虑气热惯性的综合能源系统备用配置方案", 电力系统自动化, pages 1 - 12 * |
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