CN114357687B - Hybrid time scale collaborative operation method of comprehensive energy system considering real-time simulation - Google Patents

Hybrid time scale collaborative operation method of comprehensive energy system considering real-time simulation Download PDF

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CN114357687B
CN114357687B CN202111006018.9A CN202111006018A CN114357687B CN 114357687 B CN114357687 B CN 114357687B CN 202111006018 A CN202111006018 A CN 202111006018A CN 114357687 B CN114357687 B CN 114357687B
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陈�胜
张晓�
储典韬
朱蕾
梁泽宇
杨林泽
卫志农
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Hohai University HHU
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Abstract

The invention discloses a hybrid time scale collaborative operation method of a comprehensive energy system considering real-time simulation, which considers the difference between the dynamic process and the scheduling period of an electric power system and a natural gas system under the condition of high-proportion new energy infiltration, namely the scheduling of the electric power system is divided into day-ahead operation and real-time operation, and the natural gas system only comprises day-ahead scheduling decisions. The invention takes the cooperation of the day-ahead scheduling of the power system and the natural gas system into account, simultaneously takes the influence of the natural gas system simulation quantitative analysis of the new energy fluctuation in real-time operation into account, and realizes the hybrid time scale cooperation of the comprehensive energy system under the limited information interaction. The method effectively protects the information privacy of the operation of the power system and the natural gas system, and is expected to provide a theoretical basis for the collaborative operation analysis of the comprehensive energy system with high-proportion new energy penetration.

Description

Hybrid time scale collaborative operation method of comprehensive energy system considering real-time simulation
Technical Field
The invention relates to the field of operation and simulation of an integrated energy system, in particular to a hybrid time scale cooperative operation method of the integrated energy system considering real-time simulation.
Background
In the low-carbon transformation path of an energy system, high-proportion new energy infiltration plays an extremely important strategic role. However, intermittent new energy grid connection brings great challenges to real-time balance of a power system, and the traditional coal-electric unit is difficult to provide sufficient flexible support. In contrast, a more flexible gas turbine set can provide support for new energy grid connection, and therefore is widely applied in recent years. It should be noted that the low-carbon transformation of the energy system is diversified, but the high-proportion new energy and the gas turbine set are more feasible to be connected in a grid. Under the background, the electric power system and the natural gas system show a gradual deep coupling trend, and effective cooperation between the electric power system and the natural gas system is very important for ensuring economic operation of the comprehensive energy system and consumption of new energy.
However, co-scheduling between the power system and the natural gas system needs to solve the problem of the mixing time scale. Specifically, the dynamic process of the power system is generally in the millisecond to second order, and the dynamic process of the natural gas system is in the minute to hour order in physical characteristics. The characteristic determines the difference of the two scheduling periods in the actual engineering; generally, the power system includes day-ahead scheduling (with a 24-hour period) and real-time scheduling (with a 15-minute/1-hour period); whereas natural gas systems typically only include day-ahead scheduling (with 24 hour periods), the net load fluctuations for the real-time operational phase are balanced by the pipeline-pack. Based on this, the gas-electricity integrated energy system needs to fully consider two aspects in the mixed time scale collaborative operation: firstly, gas-electricity cooperative operation on a time scale before the day; and secondly, on a real-time scale, the output of the gas turbine set is adjusted due to the fluctuation of new energy, and the influence on the real-time operation of the natural gas system is further analyzed (the real-time simulation of the natural gas system is needed).
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a hybrid time scale collaborative operation method of a comprehensive energy system considering real-time simulation.
The technical scheme is as follows: a hybrid time scale collaborative operation method of an integrated energy system considering real-time simulation comprises the following steps:
step 1, obtaining operation parameters of a comprehensive energy system, wherein the operation parameters comprise parameter information of a generator set, a circuit, an air source, a pipeline and a pressurizing station;
step 2, obtaining scene information of electric load, gas load and wind power output;
step 3, aiming at the operation parameters, the load information and the wind power output information of the comprehensive energy system, establishing a day-ahead and real-time two-stage scheduling model of the power system by taking the minimum expected cost of the day-ahead and real-time two-stage of the power system as an optimization target, and generating a day-ahead and real-time two-stage scheduling decision scheme;
step 4, establishing a day-ahead scheduling model of the natural gas system by taking the minimum day-ahead operation cost of the natural gas system as an optimization target, and interacting day-ahead operation information with the electric power system in the step 3;
step 5, establishing a real-time simulation model of the natural gas system based on the day-ahead decision information of the natural gas system in the step 4 and the real-time scheduling decision scheme of the power system in the step 3, and quantitatively analyzing the influence of the fluctuation of the wind power output on the real-time operation of the natural gas system in the real-time operation;
step 6, outputting a day-ahead and real-time operation result of the power system by the power grid dispatching center;
and 7, outputting a day-ahead scheduling result and a real-time simulation result of the natural gas system by the gas network scheduling center.
Further, in step 3, the constraints of the day-ahead and real-time operation of the power system include:
Figure BDA0003237233680000021
Figure BDA0003237233680000022
Figure BDA0003237233680000023
Figure BDA0003237233680000024
Figure BDA0003237233680000025
Figure BDA0003237233680000026
Figure BDA0003237233680000027
Figure BDA0003237233680000028
Figure BDA0003237233680000029
Figure BDA00032372336800000210
Figure BDA00032372336800000211
Figure BDA00032372336800000212
Figure BDA00032372336800000213
wherein i and j refer to power nodes, w refers to a wind turbine, t refers to a time section, v refers to a generator set, s refers to a scene, d refers to an electrical load,
Figure BDA0003237233680000031
refers to the set of electrical loads connected to node i,
Figure BDA0003237233680000032
refers to the set of generator sets connected with the node i,
Figure BDA0003237233680000033
refers to the wind turbine generator set connected with the node i, E (i) refers to the node set connected with the node i, and omega R And omega G The coal-fired unit and the gas unit are respectively integrated; delta. For the preparation of a coating it Refers to the voltage phase angle, delta, of node i at time t jt Refers to the voltage phase angle, delta, of node j at time t its Refers to the voltage phase angle, delta, of the node i at the moment t under the scene s jts Refers to the voltage phase angle of the node j at the time t under the scene s,
Figure BDA0003237233680000034
refers to the output of the unit v at the moment t,
Figure BDA0003237233680000035
refers to the output of the unit v at the moment t-1,
Figure BDA0003237233680000036
and
Figure BDA0003237233680000037
respectively representing the output increment and the output decrement of the unit v in a scene s at the moment t,
Figure BDA0003237233680000038
and
Figure BDA0003237233680000039
respectively the output increment and the output decrement of the unit v in a scene s at the moment t-1,
Figure BDA00032372336800000310
the load is cut; b ij Refers to the susceptance of the line i-j,
Figure BDA00032372336800000311
refers to the installed capacity of the generator set v,
Figure BDA00032372336800000312
refers to the transmission capacity of the lines i-j,
Figure BDA00032372336800000313
refers to the climbing upper limit value of the generator set v,
Figure BDA00032372336800000314
refers to the dispatching value of the wind turbine generator w at the moment t in the day-ahead stage,
Figure BDA00032372336800000315
refers to the schedulable capacity of the wind turbine generator w at time t,
Figure BDA00032372336800000316
the deviation value of the output value of the real-time operation scene s of the wind turbine generator and the day-ahead operation output is indicated,
Figure BDA00032372336800000317
the demand of the electric load d at the time t is indicated;
Figure BDA00032372336800000318
and with
Figure BDA00032372336800000319
Respectively refers to the maximum value of the upward climbing and the downward climbing of the unit v,
Figure BDA00032372336800000320
refers to the schedulable capacity of the wind generating set v under the scene s.
Further, in step 4, the day-ahead operation model of the natural gas system is as follows:
Figure BDA00032372336800000321
Figure BDA00032372336800000322
Figure BDA00032372336800000323
Figure BDA00032372336800000324
Figure BDA00032372336800000325
Figure BDA00032372336800000326
Figure BDA00032372336800000327
Figure BDA00032372336800000328
Figure BDA00032372336800000329
Figure BDA00032372336800000330
Figure BDA00032372336800000331
Figure BDA0003237233680000041
wherein w indicates an air source, e indicates an air load, k indicates a pressurizing station, and m and n indicate natural gas nodes; g (m) denotes a set of nodes connected to node m, C (m) denotes a set of pressurizing stations connected to node m,
Figure BDA0003237233680000042
for the set of loads connected to node m,
Figure BDA0003237233680000043
for the set of gensets connected to node m,
Figure BDA0003237233680000044
is a gas source set connected with the node m;
Figure BDA0003237233680000045
refers to the gas production cost of the gas source w,
Figure BDA0003237233680000046
the cost of the gas cutting load is indicated,
Figure BDA0003237233680000047
the demand, θ, of the air load e at time t k Means conversion efficiency of the pressurizing station K, K mn Is the storage constant, W, of the m-n of the pipeline mn Is the Weymouth constant for pipe m-n,
Figure BDA0003237233680000048
and with
Figure BDA0003237233680000049
Respectively, the lower limit and the upper limit of the pressurization ratio of the pressurization station k,
Figure BDA00032372336800000410
is the upper limit of the gas transmission capacity of the pressurizing station k,
Figure BDA00032372336800000411
is the upper limit value of the climbing amount of the air source w,
Figure BDA00032372336800000412
and
Figure BDA00032372336800000413
respectively the minimum and maximum values of the pressure at node m, L min The lower limit of the storage capacity of the gas transmission pipe network;
Figure BDA00032372336800000414
refers to the gas production rate of the gas source w at the moment t,
Figure BDA00032372336800000415
refers to the gas production of the gas source w at the time t-1,
Figure BDA00032372336800000416
refers to the air-cutting load at the time t,
Figure BDA00032372336800000417
refers to the flow rate of the pressurizing station k at the time t,
Figure BDA00032372336800000418
is the natural gas quantity, F, consumed by the gas unit v at the moment t mnt Means the flow value, F, of the m-n head end of the pipeline at the time t nmt Refers to the flow value at the m-n end of the pipeline at time t,
Figure BDA00032372336800000430
means the average flow value, L, of m-n in the pipeline at the time t mnt Refers to the pipe stock of the m-n at the time t, L m,n,t-1 Refers to the pipe stock L of the m-n pipeline at the time of t-1 mnt=24 Means the pipe stock of the pipe m-n at the time t =24, pi mt Refers to the pressure value of the node m at the time t, pi nt Refers to the pressure value of the node n at the time t,
Figure BDA00032372336800000419
refers to the pressure value at the inlet of the pressurizing station k at the moment t,
Figure BDA00032372336800000420
refers to the pressure value, u, at the outlet of the pressurizing station k at time t mt And the marginal gas price of the node m at the time t is indicated.
Further, in step 5, the real-time simulation model of the natural gas system is represented as:
Figure BDA00032372336800000421
Figure BDA00032372336800000422
Figure BDA00032372336800000423
Figure BDA00032372336800000424
Figure BDA00032372336800000425
Figure BDA00032372336800000426
Figure BDA00032372336800000427
wherein the content of the first and second substances,
Figure BDA00032372336800000428
refers to the flow value of the pressurizing station k at the moment t under the scene s,
Figure BDA00032372336800000429
refers to the natural gas quantity consumed by the gas unit v at the moment t under the scene s, F mnts Refers to the flow value F of the head end of the pipeline m-n at the time t under the scene s nmts Refers to the flow value of the m-n end of the pipeline at the time t under the scene s,
Figure BDA0003237233680000051
refers to the average flow value L of the m-n of the pipeline at the time t under the scene s mnts Refers to the pipe stock of the m-n pipeline at the time t under the scene s, L m,n,t-1,s Refers to the storage capacity of the m-n pipeline at the t-1 moment under the scene s, pi mts Refers to the pressure value, pi, of the node m at the moment t under the scene s nts Refers to the pressure value of the node n at the time t under the scene s,
Figure BDA0003237233680000052
refers to the pressure value at the inlet of the pressurizing station k at the moment t under the scene s,
Figure BDA0003237233680000053
refers to the pressure value rho of the outlet of the pressurizing station k at the moment t under the scene s kt Pressure ratio, η, of the pressure station at time t v And the power generation efficiency of the gas turbine set v is obtained.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is an integrated energy system algorithm diagram.
FIG. 3 is a schematic diagram of node pressure out-of-limit probability under real-time simulation of a natural gas system.
Detailed Description
The present invention is further illustrated by the following description in conjunction with the accompanying drawings and specific examples, it is to be understood that these examples are included solely for the purpose of illustration and not as a definition of the limits of the invention, and that various equivalent modifications of the invention will occur to those skilled in the art upon reading the present specification and fall within the scope of the appended claims.
The invention provides a hybrid time scale collaborative operation method of a comprehensive energy system considering real-time simulation, which considers a day-ahead-real-time two-stage operation decision of an electric power system and a day-ahead operation decision of a natural gas system, constructs a day-ahead collaborative scheduling model of the electric power system and the natural gas system, and provides a real-time simulation method of the natural gas system to quantitatively analyze the influence of new energy fluctuation on the real-time operation of the natural gas system and provide reference for the day-ahead collaborative decision of the comprehensive energy system. The invention aims to realize efficient and economic operation of the comprehensive energy system under high-proportion new energy penetration through a mixed time scale collaborative operation mechanism of the comprehensive energy system.
Power system operation model
Objective function of day-ahead-real-time two-stage decision
The objective function of the day-ahead and real-time two-stage random operation model of the power system is as follows:
Figure BDA0003237233680000054
in the formula: t denotes a time section, v denotes a generator set, s denotes a scene, d denotes an electrical load, and m denotes a natural gas node; omega G For gas turbine set, Ω R Is a coal-fired unit set;
Figure BDA0003237233680000055
the operation and maintenance of the gas turbine set are fixed by the cost eta v For the generating efficiency of the gas turbine set v,
Figure BDA0003237233680000061
the cost of generating electricity for the coal-fired unit,
Figure BDA0003237233680000062
for the cost of load shedding, σ s As a weight of the scene s,
Figure BDA0003237233680000063
for the proportionality coefficient of extra gas purchase of the gas turbine set in real-time operation (generally slightly larger than 1),
Figure BDA0003237233680000064
the proportionality coefficient (generally slightly less than 1) for selling the surplus natural gas by the gas turbine set in real-time operation; u. of m(v),t Refers to the gas price of the natural gas node m at the time t,
Figure BDA0003237233680000065
refers to the output of the unit v at the moment t,
Figure BDA0003237233680000066
and
Figure BDA0003237233680000067
respectively representing the output increment and the output decrement of the unit v in a scene s at the moment t,
Figure BDA0003237233680000068
the load was cut.
Equation (B-1) describes the expected cost of day-ahead-real-time operation of the power system, where the first term is the operating cost scheduled day-ahead, the second term is the expected value of the adjustment cost of the gas turbine unit under real-time operation, the third term is the expected value of the adjustment cost of the coal turbine unit under real-time operation, and the fourth term is the expected value of the down-cut load cost under real-time operation.
Day-ahead operation constraints for power systems
In day-ahead scheduling, the operating constraints that the power system needs to meet include:
Figure BDA0003237233680000069
Figure BDA00032372336800000610
Figure BDA00032372336800000611
Figure BDA00032372336800000612
Figure BDA00032372336800000613
in the formula: i and j refer to power nodes, w refers to wind turbines,
Figure BDA00032372336800000614
refers to the set of electrical loads connected to node i,
Figure BDA00032372336800000615
refers to the set of generator sets connected with the node i,
Figure BDA00032372336800000616
the node I is connected with a wind turbine generator set, and E (i) is connected with the node I; delta it Refers to the voltage phase angle, delta, of node i at time t jt Referring to the phase angle of the voltage at node j at time t,
Figure BDA00032372336800000617
refers to the scheduling value of the wind turbine generator w at the time t,
Figure BDA00032372336800000618
the output of the unit v at the time t-1 is indicated; b ij Refers to the susceptance of the lines i-j,
Figure BDA00032372336800000619
is the demand of the load d at time t,
Figure BDA00032372336800000620
refers to the schedulable capacity of the wind turbine generator w at time t,
Figure BDA00032372336800000621
refers to the installed capacity of the generator set v,
Figure BDA00032372336800000622
refers to the transmission capacity of the lines i-j,
Figure BDA00032372336800000623
refers to the climbing upper limit value of the generator set v.
Equation (B-2) describes the power balance of the power node day ahead; the formula (B-3) indicates the transmission capacity constraint of the transmission line; the formula (B-4) is the capacity constraint of the generator set; the formula (B-5) is the climbing constraint of the generator set; the formula (B-6) refers to the output constraint of the wind turbine generator.
Real-time operation constraints for power systems
The constraints to be met for the real-time operation of the power system include:
Figure BDA0003237233680000071
Figure BDA0003237233680000072
Figure BDA0003237233680000073
Figure BDA0003237233680000074
Figure BDA0003237233680000075
Figure BDA0003237233680000076
Figure BDA0003237233680000077
Figure BDA0003237233680000078
in the formula: delta. For the preparation of a coating it Refers to the voltage phase angle, delta, of the node i at the moment t under the scene s jt Refers to the voltage phase angle of the node j at the time t under the scene s,
Figure BDA0003237233680000079
and
Figure BDA00032372336800000710
respectively representing the output increment and the output decrement of the unit v in a scene s at the moment t-1,
Figure BDA00032372336800000711
the deviation value of the output value of the real-time operation scene s of the wind turbine generator w and the day-ahead operation output is indicated;
Figure BDA00032372336800000712
and
Figure BDA00032372336800000713
respectively refers to the maximum value of the upward climbing and the downward climbing of the unit v,
Figure BDA00032372336800000714
refers to the schedulable capacity of the wind turbine generator v in the scene s.
The formula (B-7) represents a power balance equation of a real-time operation scene s, and the fluctuation of the wind power output, the adjustment amount of the generator set and the load shedding amount are calculated; the formula (B-8) indicates the transmission capacity constraint of the transmission line; equation (B-9) represents the power generation capacity constraint accounting for real-time adjustments; the formula (B-10) refers to the climbing constraint of the adjacent sections of the running generator set in real time; the formulas (B-11) and (B-12) respectively refer to the upper limit value of the upper regulating variable and the lower regulating variable of the real-time operation of the generator set v; the formula (B-13) refers to the wind curtailment constraint of real-time operation; the equation (B-14) indicates the real-time shear load constraint.
Natural gas system operation model
Unlike the two-stage day-ahead decision-real-time adjustment scheduling model of the power system, the scheduling decision of the natural gas system generally only includes day-ahead decisions, and the net load change (caused by wind power output fluctuation) of real-time operation can be stabilized by the management of the pipeline. Therefore, the natural gas system operation model comprises a day-ahead decision-making model and a real-time simulation model, wherein the day-ahead decision-making model is used for making a day-ahead scheduling plan, and the real-time simulation model is used for simulating the influence of wind power output fluctuation on the natural gas system.
Day-ahead operation model of natural gas system
The day-ahead operation model of the natural gas system is as follows:
Figure BDA00032372336800000715
Figure BDA00032372336800000716
Figure BDA0003237233680000081
Figure BDA0003237233680000082
Figure BDA0003237233680000083
Figure BDA0003237233680000084
Figure BDA0003237233680000085
Figure BDA0003237233680000086
Figure BDA0003237233680000087
Figure BDA0003237233680000088
Figure BDA0003237233680000089
Figure BDA00032372336800000810
in the formula: w indicates an air source, e indicates an air load, k indicates a pressurizing station, and m and n indicate natural gas nodes; g (m) denotes a set of nodes connected to node m, C (m) denotes a set of pressurizing stations connected to node m,
Figure BDA00032372336800000811
for the set of loads connected to node m,
Figure BDA00032372336800000812
for the set of gensets connected to node m,
Figure BDA00032372336800000813
is a gas source set connected with the node m;
Figure BDA00032372336800000814
refers to the gas production cost of the gas source w,
Figure BDA00032372336800000815
the cost of the gas cutting load is indicated,
Figure BDA00032372336800000816
the demand, θ, of the air load e at time t k Means conversion efficiency of the pressurizing station K, K mn Is the storage constant, W, of the m-n of the pipeline mn Is the Weymouth constant for pipe m-n,
Figure BDA00032372336800000817
and
Figure BDA00032372336800000818
respectively, the lower limit and the upper limit of the pressurization ratio of the pressurization station k,
Figure BDA00032372336800000819
is the upper limit of the gas transmission capacity of the pressurizing station k,
Figure BDA00032372336800000820
is the upper limit value of the climbing amount of the air source w,
Figure BDA00032372336800000821
and
Figure BDA00032372336800000822
respectively the minimum and maximum values of the pressure at node m, L min The lower limit of the storage capacity of the gas transmission pipe network;
Figure BDA00032372336800000823
refers to the gas production rate of the gas source w at the moment t,
Figure BDA00032372336800000824
refers to the gas production of the gas source w at the time t-1,
Figure BDA00032372336800000825
refers to the air-cut load amount at the time t,
Figure BDA00032372336800000826
refers to the flow rate of the pressurizing station k at the time t,
Figure BDA00032372336800000827
is the natural gas quantity, F, consumed by the gas unit v at the moment t mnt Means the flow value, F, of the head end of the pipeline m-n at the time t nmt Refers to the flow value at the m-n end of the pipeline at the time t,
Figure BDA00032372336800000828
means the average flow value, L, of m-n in the pipeline at the time t mnt Refers to the pipe stock of the m-n at the time t, L m,n,t-1 Refers to the pipe stock L of the pipe m-n at the time t-1 mnt=24 Means the pipe stock of the pipe m-n at the time t =24, pi mt Refers to the pressure value, pi, of the node m at the moment t nt Refers to the pressure value of the node n at the time t,
Figure BDA00032372336800000829
refers to the pressure value at the inlet of the pressurizing station k at the moment t,
Figure BDA00032372336800000830
refers to the pressure value at the outlet of the pressurizing station k at the moment t.
The formula (B-15) is the day-ahead operation cost of the natural gas system, including gas production cost and gas cutting load cost; equation (B-16) for natural gas nodal flow balance, its dual variable u mt Representing the marginal gas price of the node; the formula (B-17) represents the average flow equation of the pipeline; the formula (B-18) represents that the difference of the flow rates of the head end and the tail end of the pipeline is the change value of the pipe stock of the pipeline on two adjacent sections; the formula (B-19) describes that the pipeline storage is in direct proportion to the average pressure of the pipeline; the formula (B-20) describes the nonlinear relation between the pipeline flow and the node pressure, and second-order cone relaxation is adopted to convert the non-convex constraint into the convex constraint; the expression (B-21) represents the compression ratio constraint of the compression station; the formula (B-22) represents the flow restriction of the pressurizing station; formula (B-23) represents the ramp constraint between adjacent sections of the gas source; formula (B-24) is a cut gas load constraint; equation (B-25) is the node pressure constraint; equation (B-26) represents the pipeline inventory constraint.
Real-time simulation model of natural gas system
For the real-time operation of a natural gas system, the day-ahead scheduling decision (including gas source output and compression ratio of a pressurizing station) needs to be kept unchanged, and the fluctuation of net load is stabilized by adopting the pipeline storage of a pipeline. The real-time simulation model of the natural gas system is represented as:
Figure BDA0003237233680000091
Figure BDA0003237233680000092
Figure BDA0003237233680000093
Figure BDA0003237233680000094
Figure BDA0003237233680000095
Figure BDA0003237233680000096
Figure BDA0003237233680000097
in the formula:
Figure BDA0003237233680000098
refers to the flow value of the pressurizing station k at the moment t under the scene s,
Figure BDA0003237233680000099
refers to the natural gas quantity consumed by the gas unit v at the moment t under the scene s, F mnts Refers to the flow value F of the m-n head end of the pipeline at the time t under the scene s nmts Means that the m-n end of the pipeline under scene s is at the time tThe flow rate value of (a) is,
Figure BDA00032372336800000910
refers to the average flow value L of the m-n pipeline at the time t under the scene s mnts Refers to the pipe stock of the m-n pipeline at the time t under the scene s, L m,n,t-1,s Refers to the storage capacity of the m-n pipeline at the t-1 moment under the scene s, pi mts Refers to the pressure value, pi, of the node m at the moment t under the scene s nts Refers to the pressure value of the node n at the moment t under the scene s,
Figure BDA00032372336800000911
refers to the pressure value at the inlet of the pressurizing station k at the moment t under the scene s,
Figure BDA00032372336800000912
refers to the pressure value rho of the outlet of the pressurizing station k at the moment t under the scene s kt Refers to the pressurization ratio of the pressurization station at time t (depending on the day-ahead scheduling decision).
Equation (B-27) describes a node flow balance equation running in real time, which is different from the day-ahead scheduling in the amount of natural gas consumed by the gas turbine set and the pipeline flow value; the formula (B-28) and the formula (B-29) respectively describe the average value of the pipeline flow and the pipeline storage balance equation under real-time operation; equation (B-30) describes a linear relationship of real-time operating pipeline inventory to pipeline mean pressure; formula (B-31) describes a form of the Weymouth equation running in real time; the expression (B-32) represents the pressure relationship between the pressure ratio outlet and the pressure relationship between the pressure ratio inlet at a fixed pressure ratio; the amount of natural gas consumed by the gas turbine group is calculated by the formula (B-33).
The electric power system operation models (B-1) - (B-14) and the natural gas system operation models (B-15) - (B-33) are combined, information interaction of day-ahead operation of the electric power system operation models and the natural gas system operation models comprises natural gas demand and day-ahead price of natural gas of the gas turbine set, and the natural gas system flexibility (pipe stock) supports stabilization of participation of the gas turbine set in new energy fluctuation in real-time operation, so that a day-ahead and real-time mixing time scale cooperation mechanism of the electric power system and the natural gas system is formed.
Example analysis
The comprehensive energy system case (composed of a 4-node power system and a 4-node natural gas system) shown in fig. 2 is adopted, wherein a gas turbine set of a power node 2 is connected with a natural gas node 3, a wind turbine set is located at the power node 1, and 100 typical scenes are adopted to describe the randomness of wind power output. Based on the calculation example, the out-of-limit of the natural gas system in real time operation is simulated by adopting the method of the invention (the result is shown in figure 3, the probability of the out-of-limit of 10% reaches 7%), which shows that the fluctuation of the wind turbine set is stabilized in real time by adopting the gas turbine set, the out-of-limit of the natural gas node pressure is easily caused, the natural gas system real-time simulation model adopted by the invention can better simulate the operation risk, and provides technical support for gas-electricity cooperation under the penetration of high-proportion new energy.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.

Claims (1)

1. A hybrid time scale collaborative operation method of an integrated energy system considering real-time simulation is characterized by comprising the following steps:
step 1, obtaining operation parameters of a comprehensive energy system, wherein the operation parameters comprise parameter information of a generator set, a circuit, an air source, a pipeline and a pressurizing station;
step 2, obtaining scene information of electric load, gas load and wind power output;
step 3, establishing a day-ahead and real-time two-stage scheduling model of the power system by taking the minimum expected cost of the day-ahead and real-time two-stage of the power system as an optimization target according to the operation parameters, the load information and the wind power output information of the comprehensive energy system, and generating a day-ahead and real-time two-stage scheduling decision scheme;
step 4, establishing a natural gas system day-ahead scheduling model by taking the minimum day-ahead operation cost of the natural gas system as an optimization target, and interacting day-ahead operation information with the electric power system in the step 3;
step 5, establishing a real-time simulation model of the natural gas system based on the day-ahead decision information of the natural gas system in the step 4 and the real-time scheduling decision scheme of the power system in the step 3, and quantitatively analyzing the influence of the fluctuation of the wind power output on the real-time operation of the natural gas system in the real-time operation;
step 6, outputting a day-ahead and real-time operation result of the power system by the power grid dispatching center;
step 7, outputting a day-ahead scheduling result and a real-time simulation result of the natural gas system by the gas network scheduling center;
in step 3, the day-ahead and real-time operation constraints of the power system include:
Figure FDA0003884490390000011
Figure FDA0003884490390000012
Figure FDA0003884490390000013
Figure FDA0003884490390000014
Figure FDA0003884490390000015
Figure FDA0003884490390000016
Figure FDA0003884490390000017
Figure FDA0003884490390000018
Figure FDA0003884490390000019
Figure FDA00038844903900000110
Figure FDA00038844903900000111
Figure FDA0003884490390000021
Figure FDA0003884490390000022
wherein i and j refer to power nodes, w refers to a wind turbine, t refers to a time section, v refers to a generator set, s refers to a scene, d refers to an electrical load,
Figure FDA0003884490390000023
refers to the set of electrical loads connected to node i,
Figure FDA0003884490390000024
refers to the set of generator sets connected to node i,
Figure FDA0003884490390000025
refers to the wind turbine generator set connected with the node i, E (i) refers to the node set connected with the node i, and omega R And omega G Respectively refers to a coal-fired unit and a gas unit set; delta it Indicates the electricity of node i at time tPhase angle of voltage delta jt Refers to the voltage phase angle, delta, of node j at time t its Refers to the voltage phase angle, delta, of the node i at the moment t under the scene s jts Refers to the voltage phase angle of node j at time t under scenario s,
Figure FDA0003884490390000026
refers to the output of the unit v at the moment t,
Figure FDA0003884490390000027
refers to the output of the unit v at the moment t-1,
Figure FDA0003884490390000028
and
Figure FDA0003884490390000029
respectively representing the output increment and the output decrement of the unit v in a scene s at the moment t,
Figure FDA00038844903900000210
and
Figure FDA00038844903900000211
respectively representing the output increment and the output decrement of the unit v in a scene s at the moment t-1,
Figure FDA00038844903900000212
the load is cut; b ij Refers to the susceptance of the lines i-j,
Figure FDA00038844903900000213
refers to the installed capacity of the generator set v,
Figure FDA00038844903900000214
refers to the transmission capacity of the lines i-j,
Figure FDA00038844903900000215
refers to the climbing upper limit value of the generator set v,
Figure FDA00038844903900000216
refers to the dispatching value of the wind turbine generator w at the moment t in the day-ahead stage,
Figure FDA00038844903900000217
refers to the schedulable capacity of the wind turbine generator w at time t,
Figure FDA00038844903900000218
the deviation value of the output value of the real-time operation scene s of the wind turbine generator and the day-ahead operation output is indicated,
Figure FDA00038844903900000219
the demand of the electric load d at the time t is indicated;
Figure FDA00038844903900000220
and with
Figure FDA00038844903900000221
Respectively refers to the maximum value of the upward climbing and the downward climbing of the unit v,
Figure FDA00038844903900000222
the schedulable capacity of the wind generating set v under the scene s is indicated;
in step 4, the day-ahead operation model of the natural gas system is as follows:
Figure FDA00038844903900000223
Figure FDA00038844903900000224
Figure FDA00038844903900000225
Figure FDA00038844903900000226
Figure FDA00038844903900000227
Figure FDA00038844903900000228
Figure FDA00038844903900000229
Figure FDA00038844903900000230
Figure FDA00038844903900000231
Figure FDA00038844903900000232
Figure FDA0003884490390000031
Figure FDA0003884490390000032
wherein w indicates an air source, e indicates an air load, k indicates a pressurizing station, and m and n indicate natural gas nodes; g (m) denotes a set of nodes connected to node m, C (m) denotes a set of pressurizing stations connected to node m,
Figure FDA0003884490390000033
for the set of loads connected to node m,
Figure FDA0003884490390000034
for the set of gensets connected to node m,
Figure FDA0003884490390000035
is a gas source set connected with the node m;
Figure FDA0003884490390000036
refers to the gas production cost of the gas source w,
Figure FDA0003884490390000037
the cost of the gas cutting load is indicated,
Figure FDA0003884490390000038
the demand, θ, of the air load e at time t k Means conversion efficiency of the pressurizing station K, K mn Is the storage constant, W, of the pipe m-n mn Is the Weymouth constant for pipe m-n,
Figure FDA0003884490390000039
and
Figure FDA00038844903900000310
respectively a lower limit and an upper limit of the pressurization ratio of the pressurization station k,
Figure FDA00038844903900000311
is the upper limit of the gas transmission capacity of the pressurizing station k,
Figure FDA00038844903900000312
is the upper limit value of the climbing amount of the air source w,
Figure FDA00038844903900000313
and
Figure FDA00038844903900000314
respectively the minimum and maximum of the pressure at node m, L min The lower limit of the gas transmission pipe storage;
Figure FDA00038844903900000315
refers to the gas production rate of the gas source w at the moment t,
Figure FDA00038844903900000316
refers to the gas production rate of the gas source w at the moment t-1,
Figure FDA00038844903900000317
refers to the air-cut load amount at the time t,
Figure FDA00038844903900000318
refers to the flow rate of the pressurizing station k at the time t,
Figure FDA00038844903900000319
refers to the natural gas quantity, F, consumed by the gas unit v at the moment t mnt Means the flow value, F, of the m-n head end of the pipeline at the time t nmt Refers to the flow value of the m-n end of the pipeline at the time t,
Figure FDA00038844903900000320
means the average flow value, L, of the m-n pipeline at the time t mnt Refers to the pipe stock of the pipe m-n at the time t, L m,n,t-1 Refers to the pipe stock L of the m-n pipeline at the time of t-1 mnt=24 Means the pipe stock of the pipe m-n at the time t =24, pi mt Refers to the pressure value of the node m at the time t, pi nt Refers to the pressure value of the node n at the time t,
Figure FDA00038844903900000321
refers to the pressure value at the inlet of the pressurizing station k at the moment t,
Figure FDA00038844903900000322
refers to the pressure value, u, of the outlet of the pressurizing station k at the time t mt Indicating the node marginal gas price of the node m at the moment t;
in step 5, the real-time simulation model of the natural gas system is represented as:
Figure FDA00038844903900000323
Figure FDA00038844903900000324
Figure FDA00038844903900000325
Figure FDA00038844903900000326
Figure FDA00038844903900000327
Figure FDA00038844903900000328
Figure FDA00038844903900000329
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003884490390000041
refers to the flow value of the pressurizing station k at the moment t under the scene s,
Figure FDA0003884490390000042
refers to the natural gas quantity consumed by the gas unit v at the moment t under the scene s, F mnts Refers to the flow value F of the head end of the pipeline m-n at the time t under the scene s nmts Refers to the flow value of the m-n end of the pipeline at the time t under the scene s,
Figure FDA0003884490390000043
refers to the average flow value L of the m-n of the pipeline at the time t under the scene s mnts Refers to the pipe stock of the m-n pipeline at the time t under the scene s, L m,n,t-1,s Refers to the pipe stock pi of the pipe m-n at the t-1 moment under the scene s mts Refers to the pressure value, pi, of the node m at the moment t under the scene s nts Refers to the pressure value of the node n at the time t under the scene s,
Figure FDA0003884490390000044
refers to the pressure value at the inlet of the pressurizing station k at the time t under the scene s,
Figure FDA0003884490390000045
refers to the pressure value, rho, of the outlet of the pressurizing station k at the time t under the scene s kt Pressure ratio of the pressure station at time t, eta v And the power generation efficiency of the gas turbine set v is obtained.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107732982A (en) * 2017-10-20 2018-02-23 河海大学 Consider the integrated energy system Multiple Time Scales dispatching method of Model Predictive Control
CN108596453A (en) * 2018-04-10 2018-09-28 山东大学 Consider integrated energy system Optimization Scheduling and the system a few days ago of network dynamics
WO2019134254A1 (en) * 2018-01-02 2019-07-11 上海交通大学 Real-time economic dispatch calculation method using distributed neural network
CN110544025A (en) * 2019-08-21 2019-12-06 河海大学 Optimal scheduling method for gas-electricity comprehensive energy system combining electricity to gas and gas storage tank

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110029142A1 (en) * 2010-07-02 2011-02-03 David Sun System tools that provides dispatchers in power grid control centers with a capability to make changes
US10585468B2 (en) * 2016-08-18 2020-03-10 Virtual Power Systems, Inc. Datacenter power management using dynamic redundancy
CN110135631B (en) * 2019-04-26 2022-02-22 燕山大学 Electric comprehensive energy system scheduling method based on information gap decision theory

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107732982A (en) * 2017-10-20 2018-02-23 河海大学 Consider the integrated energy system Multiple Time Scales dispatching method of Model Predictive Control
WO2019134254A1 (en) * 2018-01-02 2019-07-11 上海交通大学 Real-time economic dispatch calculation method using distributed neural network
CN108596453A (en) * 2018-04-10 2018-09-28 山东大学 Consider integrated energy system Optimization Scheduling and the system a few days ago of network dynamics
CN110544025A (en) * 2019-08-21 2019-12-06 河海大学 Optimal scheduling method for gas-electricity comprehensive energy system combining electricity to gas and gas storage tank

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
基于改进两阶段鲁棒优化的区域综合能源系统经济调度;单福州等;《电测与仪表》;20181212(第23期);110-115 *
基于机会约束的多能源枢纽电气互联综合能源系统日前经济调度;周晟锐等;《现代电力》;20200410(第02期);91-98 *
电―气互联综合能源系统多时间尺度动态优化调度;梅建春等;《电力系统自动化》;20180524(第13期);42-48 *
计及网络动态特性的电―气―热综合能源系统日前优化调度;董帅等;《电力系统自动化》;20180529(第13期);18-25 *

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