CN113762781B - Optimized scheduling method and device for electricity-gas integrated energy system considering electricity to gas - Google Patents

Optimized scheduling method and device for electricity-gas integrated energy system considering electricity to gas Download PDF

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CN113762781B
CN113762781B CN202111059153.XA CN202111059153A CN113762781B CN 113762781 B CN113762781 B CN 113762781B CN 202111059153 A CN202111059153 A CN 202111059153A CN 113762781 B CN113762781 B CN 113762781B
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陈虹
余涛
刘海涛
吕志鹏
孙添一
陆怀谷
史伟
张伟
周珊
宋振浩
杨晓霞
薛琳
刘梦
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State Grid Corp of China SGCC
State Grid Jiangsu Electric Power Co Ltd
Changzhou Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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State Grid Jiangsu Electric Power Co Ltd
Changzhou Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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Abstract

The invention provides an optimized dispatching method and device for an electricity-gas comprehensive energy system considering electricity to gas, wherein the method comprises the following steps: s1, establishing an electric-to-gas equipment model of the system, wherein the electric-to-gas equipment model meets a plurality of electric-to-gas constraints; s2, establishing a power system model meeting a plurality of power constraints and a natural gas system model meeting a plurality of natural gas constraints of the system; s3, establishing a minimum operation cost optimization problem model of the system according to the electric power-to-gas equipment model, the electric power system model and the natural gas system model; and S4, based on the minimized operation cost optimization problem model, taking the minimized operation cost as an optimization target, and performing optimized scheduling on the electric-to-gas equipment, the thermal power generating unit and the natural gas network in each production period by using second-order cone programming. Therefore, renewable energy sources can be fully consumed in time, the multi-energy flow intercoupling and mutual assistance coordination capacity can be effectively improved, and the system can run economically and stably.

Description

Optimized scheduling method and device for electricity-gas comprehensive energy system considering electricity to gas
Technical Field
The invention relates to the technical field of comprehensive new energy, in particular to an optimized scheduling method and an optimized scheduling device for an electricity-gas comprehensive energy system considering electricity to gas.
Background
In the face of the pressure of climate and environmental resources, the development of renewable energy becomes a necessary trend, and the phenomena of wind and light abandonment caused by the trend are still severe. In the past, for a long time, because of fewer coupling links among various energy systems, a relatively independent management mode of different energy systems is implemented. However, in new situations, the past management mode of operation can result in overall poor energy efficiency; moreover, when natural disasters such as extreme weather exist, necessary coordination and coordination are lacked among various energy supply systems, so that unilateral energy faults have the risk of causing complex chain reaction.
Therefore, it is important to grasp the inertia characteristics and delay characteristics of different energy forms and to mine and utilize complementary alternatives between different energy sources. The problems that a traditional multi-energy flow control framework is highly centralized, poor in real-time performance and poor in control precision and speed, small in inertia, weak in damping electric energy, large in inertia, strong in damping heat energy, fast in gas networking, efficient in cooperation and the like are solved, and the method is the key for breaking through the development bottleneck of a comprehensive energy system, improving the operation capacity of the comprehensive energy system and expanding the service capacity of the comprehensive energy system.
Disclosure of Invention
In the field of electric gas conversion technology, some scholars are dedicated to the application and research of Hydrogen Compressed Natural Gas (HCNG) in an integrated energy system and have achieved certain results. However, due to the characteristics of low density and high activity of hydrogen, some researchers have also proposed the existing difficulties of hydrogen injection into natural gas pipelines in terms of two-way coupling systems: since the hydrogen gas has a large difference in transmission rate and transmission loss from the conventional natural gas in the natural gas pipeline, and the energy density per unit volume of the hydrogen gas is about 1/3 of the natural gas, if the hydrogen gas is injected into the natural gas pipeline at the same flow rate, the average energy of the pipeline mixed gas fuel is reduced, that is, the energy storage capacity of the whole system is reduced, and short-term supply shortage of the natural gas fuel may be caused. Thus, each country places strict restrictions on hydrogen mixing in the natural gas network (typically up to 6% hydrogen content).
The invention provides an optimized dispatching method of an electricity-gas integrated energy system considering electricity to gas in order to overcome the defects of the related technology, so that renewable energy can be sufficiently consumed in time, the multi-energy flow interactive coupling and mutual assistance coordination capacity can be effectively improved, and the electricity-gas coupled integrated energy system can run economically and stably.
The technical scheme adopted by the invention is as follows:
an embodiment of the first aspect of the present invention provides an optimized scheduling method for an electricity-gas integrated energy system considering electricity to gas, where the system includes: the method comprises the following steps of:
s1, establishing an electric-to-gas equipment model of the system meeting a plurality of electric-to-gas constraints, wherein the plurality of electric-to-gas constraints comprise: reaction efficiency constraint, conversion power consumption constraint, combustion limit constraint, explosion limit constraint and heat value constraint;
s2, establishing a power system model meeting a plurality of power constraints and a natural gas system model meeting a plurality of natural gas constraints of the system;
s3, establishing a minimized operation cost optimization problem model of the system according to the electric power conversion equipment model, the electric power system model and the natural gas system model;
and S4, based on the minimized operation cost optimization problem model, taking minimized operation cost as an optimization target, converting the minimized operation cost optimization problem by using a second-order cone programming, and performing optimized scheduling on the electric-to-gas conversion equipment, the thermal power generating unit and the natural gas network in each production period.
In addition, the optimal scheduling method for the electricity-gas integrated energy system considering electricity to gas, which is provided by the above embodiment of the present invention, may further have the following additional technical features:
according to one embodiment of the invention, the electric conversion gas equipment adopts a polymer electrolyte membrane pool to carry out water electrolysis for hydrogen production, and the electric conversion gas equipment adopts DavyTMCarrying out methanation by the technology, wherein the reaction efficiency is restricted as follows;
Figure GDA0003675606570000021
wherein eta iselecReaction efficiency, eta, of processes for the production of hydrogen by electrolysis of watermethFor the efficiency of the methanation process, etaelec，tReaction efficiency eta at time slot t for the electrolysis of water to produce hydrogenmeth，tFor the reaction efficiency of the methanation process in the case of the time slot t, where each
Figure GDA0003675606570000031
Within a time slot, said ηelec，tAnd said ηmeth，tRemain unchanged, wherein the time is aggregated
Figure GDA0003675606570000032
According to one embodiment of the invention, the conversion power consumption constraint is:
Figure GDA0003675606570000033
Figure GDA0003675606570000034
wherein, the first and the second end of the pipe are connected with each other,
Figure GDA0003675606570000035
represents the consumption of the electric energy used by the electric gas conversion equipment for producing hydrogen,
Figure GDA0003675606570000036
is composed of
Figure GDA0003675606570000037
Flow rate of hydrogen, alpha, produced by time-slotted electric gas-converting plantselec，tTo the parameter of the power consumption corresponding to the hydrogen flow, αmeth，tFor the power consumption parameter corresponding to the methane flow rate,
Figure GDA0003675606570000038
represents the electric energy consumed by the electric gas conversion equipment for preparing methane,
Figure GDA0003675606570000039
is composed of
Figure GDA00036756065700000310
The time slot electricity changes the methane flow that the gas facility produced.
According to one embodiment of the invention, the flammability limit and the explosion limit constraints are respectively:
Figure GDA00036756065700000311
wherein the content of the first and second substances,
Figure GDA00036756065700000312
respectively an upper combustion limit and a lower combustion limit of methane,
Figure GDA00036756065700000313
respectively representing the upper explosion limit and the lower explosion limit of methane,
Figure GDA00036756065700000314
respectively as the upper limit and the lower limit of the combustion of the hydrogen,
Figure GDA00036756065700000315
respectively as the upper and lower explosion limits of hydrogen,
Figure GDA00036756065700000316
is composed of
Figure GDA00036756065700000317
The percentage of hydrogen content in the production pipeline of the time slot electric gas conversion equipment,
Figure GDA00036756065700000318
is composed of
Figure GDA00036756065700000319
Percentage of methane content in the production pipeline of the time slot electric gas conversion equipment.
According to one embodiment of the invention, the thermal value constraint is:
Figure GDA00036756065700000320
Figure GDA00036756065700000321
wherein, the first and the second end of the pipe are connected with each other,
Figure GDA00036756065700000322
is the heating value of the hydrogen gas,
Figure GDA00036756065700000323
is the heating value of methane.
According to one embodiment of the present invention, the minimization of operating cost optimization problem model is:
Figure GDA00036756065700000324
the coal consumption function of each thermal power generating unit can be expressed by the following quadratic equation:
Figure GDA0003675606570000041
wherein N represents the number of thermal power generating units,
Figure GDA0003675606570000042
represents the coal consumption cost of the thermal power generating unit i,
Figure GDA0003675606570000043
represents the starting cost of the thermal power generating unit i,
Figure GDA0003675606570000044
represents the shutdown cost of the thermal power generating unit i,
Figure GDA0003675606570000045
representing the cost of the natural gas network, Pi，tTo represent
Figure GDA0003675606570000046
Output of thermal power generating unit i in time slot CPV，tRepresents a light abandonment penalty cost, said CPV，tAnd is positively correlated with the electric quantity of the abandoned light.
According to one embodiment of the invention, the minimization of operating cost optimization problem is transformed by using second order cone programming, comprising:
with the second order cone programming, the Weymouth natural gas flow constraint equation is equivalently replaced by:
Figure GDA0003675606570000047
by using bilinear relaxation, the bilinear term to the right of the above equation can be replaced with the following equation:
Figure GDA0003675606570000048
Figure GDA0003675606570000049
Figure GDA00036756065700000410
Figure GDA00036756065700000411
Figure GDA00036756065700000412
wherein λ ismnRepresenting an auxiliary variable flowing through the pipe m-n, the pressure pi of the node mmThe superscript u and the superscript l are respectively an upper limit and a lower limit;
relaxed in a conical format, where the standard SOC formula is expressed as:
Figure GDA00036756065700000413
Figure GDA00036756065700000414
wherein, FmnDenotes the natural gas flow through the pipeline m-n, CmnWhich means that the Weymouth constant,
Figure GDA00036756065700000415
indicating the flow of natural gas out of node m,
Figure GDA00036756065700000416
representing the natural gas flow, pi, into the node mm、πnRespectively representing the pressure of the nodes m and n.
According to one embodiment of the invention, the optimized scheduling of the electric gas conversion equipment in each production period comprises the following steps:
to pair
Figure GDA0003675606570000051
Time slot is used for optimizing and scheduling hydrogen flow produced by the electric gas conversion equipment and the time slot is used for optimizing and scheduling hydrogen flow produced by the electric gas conversion equipment
Figure GDA0003675606570000052
Carrying out optimized scheduling on the methane flow produced by the electric gas conversion equipment in time slot;
the thermal power generating unit in each production period is optimally scheduled, and the method comprises the following steps:
for is to
Figure GDA0003675606570000053
Output of time slot thermal power generating unit i and
Figure GDA0003675606570000054
carrying out optimized scheduling on the starting and stopping conditions of the time slot thermal power generating unit i;
performing optimized scheduling on the natural gas network for each production period, including:
and optimally scheduling the natural gas flow numerical value from the node m to the node n, the natural gas pipeline flow direction from the node m to the node n and the pressure of the node m in the natural gas network in each production period in the natural gas network.
According to one embodiment of the invention, the plurality of power constraints comprises: the method comprises the following steps of (1) power balance constraint, hot standby constraint, unit output constraint, unit climbing constraint, unit start-stop constraint, start-stop cost constraint and line tide safety constraint; the plurality of natural gas constraints comprises: natural gas power balance constraints, Weymouth natural gas flow constraints, gas source storage capacity constraints, pipeline pressure constraints, and node flow constraints.
The embodiment of the second aspect of the invention provides an optimized dispatching device for an electricity-gas integrated energy system considering electricity to gas, wherein the system comprises: electricity changes gas equipment, thermal power generating unit and natural gas network, the device includes:
a first building module to build an electric-to-gas plant model of the system that satisfies a plurality of electric-to-gas constraints, wherein the plurality of electric-to-gas constraints comprise: reaction efficiency constraint, conversion power consumption constraint, combustion limit constraint, explosion limit constraint and heat value constraint;
a second building module for building a power system model of the system that satisfies a plurality of power constraints and a natural gas system model that satisfies a plurality of natural gas constraints;
the third establishing module is used for establishing a minimized operation cost optimization problem model of the system according to the electric power-to-gas equipment model, the electric power system model and the natural gas system model;
and the determining module is used for converting the minimum operation cost optimization problem by using second-order cone planning based on the minimum operation cost optimization problem model and taking the minimum operation cost as an optimization target so as to optimally schedule the electric-to-gas equipment, the thermal power generating unit and the natural gas network in each production period.
According to the technical scheme, firstly, aiming at an electric-gas integrated energy system, an electric-gas conversion equipment model meeting a plurality of electric-gas conversion constraints, an electric power system model meeting a plurality of electric power constraints and a natural gas system model meeting a plurality of natural gas constraints are established, then, a minimized operation cost optimization problem model is established, finally, the minimized operation cost is taken as an optimization target, and the minimized operation cost optimization problem is converted by using second-order cone planning so as to perform optimized scheduling on the electric-gas conversion equipment, the thermal power generating unit and the natural gas network in each production period. Therefore, according to the optimal scheduling method of the electricity-gas integrated energy system considering electricity to gas, which is disclosed by the embodiment of the invention, the optimal scheduling is carried out on the electricity-gas integrated energy system according to the reaction efficiency, the conversion power consumption, the flammable limit, the explosion limit and the combustion heat value of the electricity to gas equipment by taking the minimized operation cost as a target, so that timely and sufficient consumption of renewable energy sources, effective improvement of multi-energy flow cross-coupling and mutual-economic coordination capacity and stable operation of the system can be realized.
Drawings
Fig. 1 is a flowchart of an optimal scheduling method for an electricity-gas integrated energy system considering electricity to gas according to an embodiment of the present invention.
Fig. 2 is a schematic configuration diagram of an electric power conversion apparatus according to an embodiment of the present invention.
FIG. 3 is an analysis diagram of an example of an optimization scheduling algorithm of the second-order cone-based electric-gas integrated energy system according to an embodiment of the present invention.
FIG. 4 is a graph of the set output force for an exemplary hot standby state of 0.05 of the present invention.
FIG. 5 is a node phase angle radar plot for an exemplary hot standby state of 0.05 of the present invention.
Fig. 6 is a graph of the group output force ladder for an exemplary hot standby state of 0.2 of the present invention.
FIG. 7 is a node phase angle radar plot for an exemplary hot standby state of 0.2 of the present invention.
Fig. 8 is a typical solar photovoltaic output line graph of one example of the present invention.
Fig. 9 is a line graph of the annual average photovoltaic output and power generation for one example of the present invention.
FIG. 10 is a graph comparing total operating costs of a powered or unpowered electrical transfer device according to an example of the invention.
Fig. 11(a) is a schematic diagram of an operation cost corresponding to a change in a discard penalty parameter according to an example of the present invention.
Fig. 11(b) is a line graph of the impact of the curtailment penalty parameter change on the total operating cost according to an example of the present invention.
Fig. 12 is a block diagram illustrating an optimized dispatching device of an electric-gas integrated energy system with consideration of electricity to gas according to an embodiment 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.
Fig. 1 is a flowchart of an optimal scheduling method for an electricity-gas integrated energy system considering electricity to gas according to an embodiment of the present invention.
The electricity-gas comprehensive energy system considering electricity to gas in the embodiment of the invention comprises electricity to gas equipment, a thermal power generating unit and a natural gas network. The electric power to hydrogen (P2H) and the electric power to methane (P2M) are realized by the electric power to hydrogen equipment, and fig. 2 is a schematic structural diagram of the electric power to gas equipment, wherein the electric power to hydrogen relates to one step of the water electrolysis hydrogen production technology, and the electric power to methane relates to two steps of water electrolysis hydrogen production and methanation. Wherein the water electrolysis hydrogen production technology adopts a Polymer Electrolyte Membrane (PEM), and the methanation technology adopts Davy of Johnson Matthey companyTMProvided is a technique.
As shown in fig. 1, the optimal scheduling method of the electricity-gas integrated energy system considering electricity to gas includes the following steps:
s1, establishing an electric-to-gas conversion equipment model of the system, wherein the electric-to-gas conversion equipment model satisfies a plurality of electric-to-gas conversion constraints, and the plurality of electric-to-gas conversion constraints comprise: reaction efficiency constraints, conversion power consumption constraints, combustion limit constraints, explosion limit constraints, and heat value constraints.
Specifically, for the electricity-gas integrated energy system considering electricity to gas, an electricity to gas equipment model of the electricity-gas integrated energy system is established firstly, the model meets the constraint of reaction efficiency, the constraint of conversion power consumption, the constraint of combustion limit, the constraint of explosion limit and the constraint of heat value, so that the electricity to gas equipment model meeting certain constraint conditions of the electricity-gas integrated energy system is obtained, and the model has determined reaction efficiency, conversion power consumption, combustion limit, explosion limit and heat value.
Because the electric conversion gas equipment relates to a water electrolysis hydrogen production technology and a methanation technology, a plurality of electric conversion gas constraints are embodied in two aspects, namely a hydrogen production aspect and a methane production aspect, for example, a plurality of reaction efficiencies comprise a reaction efficiency of water electrolysis hydrogen production and a reaction efficiency of electric conversion gas equipment methane production.
It should be noted that the electric-to-gas device model according to the embodiment of the present invention may be applied to an electric-to-gas device of any electric-to-gas integrated energy system in the related art.
And S2, establishing a power system model meeting a plurality of power constraints and a natural gas system model meeting a plurality of natural gas constraints of the system.
Wherein the plurality of power constraints may include: the method comprises the following steps of (1) power balance constraint, hot standby constraint, unit output constraint, unit climbing constraint, unit start-stop constraint, start-stop cost constraint and line tide safety constraint; the plurality of natural gas constraints may include: natural gas power balance constraints, Weymouth natural gas flow constraints, gas source storage capacity constraints, pipeline pressure constraints, and node flow constraints.
It should be noted that the power system model is applicable to the power system topology of all the electric-gas integrated energy systems in the related art. The natural gas system model is applicable to the power system topology of all the electric-gas integrated energy systems in the related art.
And S3, establishing a minimum operation cost optimization problem model of the system according to the electric power-to-gas equipment model, the electric power system model and the natural gas system model.
And S4, based on the minimized operation cost optimization problem model, taking the minimized operation cost as an optimization target, and converting the minimized operation cost optimization problem by using second-order cone programming so as to optimally schedule the electric-to-gas equipment, the thermal power generating unit and the natural gas network in each production period. Specifically, after an electric-to-gas equipment model, an electric power system model and a natural gas system model which meet certain constraint conditions are established, a minimum operation cost optimization problem model of the electric-to-gas integrated energy system considering the electric-to-gas is established according to the three models, the minimum operation cost is taken as an optimization target, problem transformation is carried out by using second-order cone planning, and system variables, such as the conversion ratio of the electric-to-gas equipment (namely the ratio of the electric-to-gas equipment to convert hydrogen and methane), the starting and stopping conditions of a thermal power generating unit and the natural gas pipeline flow direction of a natural gas network, which meet the optimization target in each time period, namely each time period of production and operation of the electric-to-gas integrated energy system are formulated, so that the optimized scheduling of the electric-to-gas integrated energy system is realized.
According to the embodiment of the invention, on the basis of fully considering the difference of reaction efficiency, flammability limit, explosion limit, transmission safety, combustion heat value and the like in the process of producing hydrogen by electrolyzing water and methanation, the conversion proportion of the electric-to-gas equipment is re-planned and designed, specifically, the yield proportion of converted hydrogen and methane at each time interval is adopted, then, an electric-to-gas comprehensive energy system optimization scheduling model is established by combining an electric power system and a natural gas system according to the conversion proportion of the electric-to-gas equipment, and problem conversion is carried out by utilizing second-order cone planning, so that a scheduling scheme which meets the optimization target of the conversion proportion of the electric-to-gas equipment, the starting and stopping conditions of a thermal power generating unit and the flow direction of a natural gas pipeline is formulated.
According to the optimal scheduling method of the electricity-gas integrated energy system considering electricity to gas, which is disclosed by the embodiment of the invention, the electricity-gas integrated energy system is optimally scheduled according to the reaction efficiency, the converted power consumption, the flammable limit, the explosion limit and the combustion heat value of the electricity to gas equipment by taking the minimized operation cost as a target, so that the timely and sufficient consumption of renewable energy sources, the effective improvement of the multi-energy flow cross-coupling and mutual-assistance coordination capacity and the economic and stable operation of the system can be realized.
In one embodiment of the invention, the reaction efficiency constraint is;
Figure GDA0003675606570000091
wherein etaelecReaction efficiency, eta, of processes for the production of hydrogen by electrolysis of watermethFor the efficiency of the methanation process, etaelec，tReaction efficiency eta at time slot t for the electrolysis of water to produce hydrogenmeth，tFor the reaction efficiency of the methanation process in the time slot t, the time is integrated
Figure GDA0003675606570000092
And make the following assumptions: 1) each timeA
Figure GDA0003675606570000093
Within a time slot, etaelec，tAnd ηmeth，tKeeping unchanged, namely, a fixed value, wherein 2) the chemical reaction process is a complete reaction, and a reversible process does not exist.
In one embodiment, the conversion power consumption constraint is:
Figure GDA0003675606570000094
Figure GDA0003675606570000095
wherein the content of the first and second substances,
Figure GDA0003675606570000096
represents the consumption of the electric energy used by the electric gas conversion equipment for producing hydrogen,
Figure GDA0003675606570000097
is composed of
Figure GDA0003675606570000098
Hydrogen flow rate, alpha, produced by time-slotted electric gas-converting plantselec，tTo the parameter of the power consumption corresponding to the hydrogen flow, αmeth，tTo be a power consumption parameter corresponding to the methane flow rate,
Figure GDA0003675606570000101
represents the electric energy consumed by the electric gas conversion equipment for preparing methane,
Figure GDA0003675606570000102
is composed of
Figure GDA0003675606570000103
The time slot electricity changes the methane flow that the gas facility produced.
Since the electricity to methane needs to go through two processes, the electricity consumption of electricity to methane is also reducedThe device consists of two parts: alpha is alphaelec，tTo correspond to the parameter of the electrical power consumption of the electrolysis process, alphameth，tIs a parameter corresponding to the power consumption of the methanation process. For simplicity, only the chemical reaction of carbon dioxide with hydrogen is considered here, i.e. carbon dioxide with 4 times the amount of hydrogen at high temperature and pressure and under the action of a catalyst produces methane.
For the combustion limit and the explosion limit of an electric gas-converting device, the determination is made on the basis of the following considerations: hydrogen cannot be injected into existing natural gas pipelines on a large scale, otherwise hydrogen embrittlement and pipeline permeation can be caused, and methane can be directly injected into natural gas pipelines and storage devices, thereby realizing large-scale storage and long-distance transportation of energy.
A mixture of combustible gases (e.g., hydrogen, methane, carbon monoxide, etc.) and oxygen will only combust if the fuel concentration is within well-defined upper and lower experimentally determined limits (i.e., flammability limits). The minimum concentration (percentage) of gas in air under flammable conditions is defined as the Lower Flammability Limit (LFL) and the maximum Upper Flammability Limit (UFL). Similarly, the explosion limit is an upper limit and a lower limit of the fuel concentration at the time of explosion, and is expressed as a Lower Explosion Limit (LEL) and an Upper Explosion Limit (UEL), respectively.
In one embodiment, the flammability and explosion limit constraints are:
Figure GDA0003675606570000104
Figure GDA0003675606570000105
wherein, the first and the second end of the pipe are connected with each other,
Figure GDA0003675606570000106
respectively an upper limit and a lower limit of the combustion of the methane,
Figure GDA0003675606570000107
respectively representing the upper explosion limit and the lower explosion limit of methane,
Figure GDA0003675606570000108
respectively as the upper limit and the lower limit of the combustion of the hydrogen,
Figure GDA0003675606570000109
respectively as the upper and lower explosion limits of hydrogen,
Figure GDA00036756065700001010
is composed of
Figure GDA00036756065700001011
Percentage of hydrogen content in the production pipeline of the time slot electric gas conversion equipment,
Figure GDA00036756065700001012
is composed of
Figure GDA00036756065700001013
Percentage of methane content in the production pipeline of the time slot electric gas conversion equipment.
For the heating value constraint of an electric gas-converting plant, the amount of Lower Heating Value (LHV) is known to be determined by subtracting the heat of vaporization of water from the higher heating value. Any H that this would form2O is considered to be steam and therefore the energy required for water vapour is not released as heat. The energy density of hydrogen is only 25% of methane. When both release the same amount of energy, the volume of hydrogen is larger and storage and transport is more difficult. In one embodiment, the heat value constraint of the electric gas conversion device is:
Figure GDA0003675606570000111
wherein, the first and the second end of the pipe are connected with each other,
Figure GDA0003675606570000112
is the heating value of the hydrogen gas,
Figure GDA0003675606570000113
is the heating value of methane.
In the embodiment of the present invention, the power balance constraint of the power system model is:
Figure GDA0003675606570000114
wherein, Pi，tRepresenting the output of the thermal power generating unit i under the condition of the time slot t; pd，tRepresenting the demand of the user for electric quantity in the time slot t; the set of the thermoelectric generator sets in the power system is represented as
Figure GDA0003675606570000115
The set of electrical loads is represented as
Figure GDA0003675606570000116
The hot standby constraints of the power system model are:
Figure GDA0003675606570000117
Figure GDA0003675606570000118
wherein u isi，tShowing the starting and stopping states of the unit i in the time period t, as shown in the formula, when ui，tWhen the value is 0, the unit i is in a shutdown state in a time period t, and when u isi，tWhen the time is 1, the unit i is in an enabling state in a time period t; since the output range of the unit is limited, P is used herei，maxRepresenting the maximum output value of the unit i; rho is a hot standby coefficient, and can be adjusted according to the actual production condition, so that the output of the unit can meet the power consumption requirements of all users.
The unit output constraint of the power system model is as follows: u. ui，tPi，min≤Pi≤ui，tPi，maxWherein P isi，minRepresenting the minimum capacity limit for the unit i. Taking into account the 0-1 variable ui，tComparing the unit output constraint with the unit outputSimply described as Pi，min≤Pi≤Pi，maxMore suitable for practical situation when ui，tWhen the time slot is 0, the output limit constraint of the unit i is not required to be considered at the time slot, the calculated amount and the complexity are reduced to a certain extent, and the system scheduling operation efficiency is effectively improved.
The unit climbing constraint of the power system model is as follows: -Rd≤Pi，t-Pi，t-1≤RuWherein R isd、RuRespectively representing the down/up ramp rates of the unit. In the actual production process, the up-and-down climbing process of the unit needs to be fully considered.
The unit start-stop constraint of the power system model is as follows:
Figure GDA0003675606570000121
Figure GDA0003675606570000122
wherein, TS is the minimum shutdown time, and TO is the minimum startup time. In addition to the unit ramp constraints described above, assume that at time slot t-1, the start-stop state of unit i is u i，t-10, and the on-off state u of the next time slot ti，tThis means that the unit i changes from off to on, which in real-life situations takes some time, and vice versa. The machine set is started and stopped frequently in a short time, certain damage is caused to a stator and a rotor of the machine set by voltage difference, phase angle difference and frequency difference generated in the grid connection moment, and the inner surface and the outer surface of the rotor are subjected to the action of repeated alternating stress, so that the problems of mechanical stress damage such as coil binding looseness, iron core looseness, end heating and the like and insulation reduction and the like are serious.
The start-stop cost constraint of the power system model is as follows:
Figure GDA0003675606570000123
Figure GDA0003675606570000124
wherein the content of the first and second substances,
Figure GDA0003675606570000125
represents the starting cost of the unit i, and the same principle is adopted
Figure GDA0003675606570000126
Representing the shutdown cost of the unit i; hiAnd JiRespectively representing the single start-up/shut-down costs of the unit i.
The line power flow safety constraint of the power system model is as follows:
Pl，min≤Pl，t≤Pl，max
when the unit starts the minimum output Pi，minGreater than the ramp rate R, the unit ramp constraint will cause all shutdown units to be unable to be started again, and therefore can be rewritten as:
Pi，t-Pi，t-1≤ui，t-1(Ru-Si，u)+Si，u
wherein, to simplify the calculation, the start-up maximum ramp-up rate and the stop-up maximum ramp-down rate may both be taken as:
Figure GDA0003675606570000127
calculating a transfer distribution factor matrix G of the power flow, and rewriting the security constraint of the line power flow into:
Figure GDA0003675606570000131
wherein G isl-iDescribing the impact of the injected power of node i on line l, the simplified model variable is pi，t，sAnd ui，t。
Further, in the embodiments of the present inventionIn the natural gas system model, a natural gas network node set
Figure GDA0003675606570000132
The nodes are divided into two categories according to the connection relation of the nodes
Figure GDA0003675606570000133
Wherein
Figure GDA0003675606570000134
For a set of nodal connections corresponding to a compressor,
Figure GDA0003675606570000135
is a collection of nodal connections corresponding to the natural gas pipeline.
The natural gas power balance constraint of the natural gas system model is as follows:
Figure GDA0003675606570000136
wherein, for node m, fmnIndicating natural gas flow out of the node, fnmIndicating the natural gas flow rate of the injection node, and smRepresenting the natural gas flow rate injected directly into the node by the source.
The Weymouth natural gas flow constraint for the natural gas system model is:
Figure GDA0003675606570000137
Figure GDA0003675606570000138
Figure GDA0003675606570000139
Figure GDA00036756065700001310
using the Weymouth Natural gas flow constraint model, the relationship between natural gas flow and pipeline pressure is described herein.
Wherein sign (f)mn) The method comprises the steps that a binary variable for starting and stopping a unit is similar to the binary variable, the value is { -1,1}, the flow direction is positive and is 1, and the flow direction is negative and is 1; p is a radical ofm，pnRepresenting the pressure value of the node m, n; and L ismnThe length of the natural gas pipeline is expressed in km; dmnRepresents the inside diameter of the pipe in mm; t is a unit ofgRepresents natural gas temperature, set here at constant 281.15K; epsilon represents the absolute roughness of the natural gas pipeline and is set as a constant of 0.05 mm; δ represents the relative density of natural gas relative to air, set at 0.6106; z is a natural gas compression constant, and is set to 0.8.
The gas source storage capacity constraint of the natural gas system model is as follows:
Figure GDA00036756065700001311
wherein s is m，
Figure GDA0003675606570000141
Respectively representing a maximum value and a minimum value of the stored amount of the air supply. Since the capacity of each natural gas storage station is fixed, the natural gas flow output by each gas source should satisfy certain maximum constraints.
The pipeline pressure constraints for the natural gas system model are:
Figure GDA0003675606570000142
similar to the source storage constraint, this equation is the maximum value constraint for the pipeline pressure. The existing natural gas pipeline is mostly made of steel through casting, according to the national standard, the transmission pressure of natural gas in the pipeline is required to meet the operation standard of the pipeline, and the pipeline is damaged when the pressure is too high or too low.
The node flow constraint of the natural gas system model is as follows:
Figure GDA0003675606570000143
to eliminate the non-linearity caused by the pressure variable, the following variable substitutions are made:
Figure GDA0003675606570000144
thus, the line pressure constraint can be rewritten as:
Figure GDA0003675606570000145
in one embodiment of the invention, the minimization of operating cost optimization problem model is:
Figure GDA0003675606570000146
the coal consumption function of each thermal power generating unit can be expressed by the following quadratic equation:
Figure GDA0003675606570000147
wherein N represents the number of thermal power generating units,
Figure GDA0003675606570000148
represents the coal consumption cost of the thermal power generating unit i,
Figure GDA0003675606570000149
represents the starting cost of the thermal power generating unit i,
Figure GDA00036756065700001410
represents the shutdown cost of the thermal power generating unit i,
Figure GDA00036756065700001411
representing the cost of the natural gas network, Pi，tTo represent
Figure GDA00036756065700001412
Output of thermal power generating unit i in time slot CPV，tRepresents a light abandonment penalty cost, CPV，tAnd is positively correlated with the electric quantity of the abandoned light.
Default light abandon penalty cost C for simplifying the situationPV，tAnd the electric quantity of the abandoned light is in positive linear correlation.
It should be noted that the embodiment of the present invention optimizes the variables in table 1.
TABLE 1 optimization variables and their meanings
Figure GDA00036756065700001413
Figure GDA0003675606570000151
That is, in an embodiment of the present invention, in the step S4, performing optimized scheduling on the electrical gas conversion equipment for each production period may include: to pair
Figure GDA0003675606570000152
Optimized scheduling of hydrogen flow produced by time slot electric gas conversion equipment and pair
Figure GDA0003675606570000153
Optimizing and scheduling the methane flow produced by the time slot electric gas conversion equipment; the thermal power generating units in each production period are optimally scheduled, and the method comprises the following steps: to pair
Figure GDA0003675606570000154
Output of time slot thermal power generating unit i and
Figure GDA0003675606570000155
optimized scheduling for starting and stopping conditions of time slot thermal power generating unit i(ii) a The optimized scheduling of the natural gas network in each production period can comprise the following steps: and optimally scheduling the natural gas flow numerical value from the node m to the node n, the natural gas pipeline flow direction from the node m to the node n and the pressure of the node m in the natural gas network in each production period in the natural gas network.
In one embodiment of the present invention, in the step S4: with the minimized running cost as an optimization target, determining the conversion proportion of the electricity-gas conversion equipment, the starting and stopping conditions of the thermal power generating unit and the flow direction of the natural gas pipeline corresponding to each time period of the electricity-gas integrated energy system taking electricity into account by utilizing the second-order cone programming, and comprising the following steps:
with the second order cone programming, the Weymouth natural gas flow constraint equation is equivalently replaced by:
Figure GDA0003675606570000156
wherein, FmnDenotes the natural gas flow through the pipeline m-n, CmnWhich means that the Weymouth constant,
Figure GDA0003675606570000157
indicating the flow of natural gas out of node m,
Figure GDA0003675606570000158
representing the natural gas flow, pi, into the node mm、πnRespectively representing the pressure of the nodes m and n;
by using bilinear relaxation, the bilinear term to the right of the above equation can be replaced with the following equation:
Figure GDA0003675606570000161
Figure GDA0003675606570000162
Figure GDA0003675606570000163
Figure GDA0003675606570000164
Figure GDA0003675606570000165
wherein λ ismnRepresenting the auxiliary variable flowing through the pipe m-n, the pressure pi of the node mmThe superscript u and the superscript l are respectively an upper limit and a lower limit; relaxed in a conical format, where the standard SOC formula is expressed as:
Figure GDA0003675606570000166
Figure GDA0003675606570000167
specifically, the non-convexity of the steady-state gas flow model stems from the Weymouth Natural gas flow constraint, where the absolute value sign (f)mn) Non-smooth and non-differentiable, to solve this problem, embodiments of the present invention introduce a pair of binary variables
Figure GDA0003675606570000168
And
Figure GDA0003675606570000169
representing the forward and backward airflow directions of the ducts m-n, respectively. Thus, the Weymouth natural gas flow constraint equation for the natural gas system model is equivalently replaced with:
Figure GDA00036756065700001610
by using bilinear relaxation, the bilinear term on the right of the above equation can be enteredLine replacement (due to)
Figure GDA00036756065700001611
And
Figure GDA00036756065700001612
is a binary variable and therefore the relaxation is tight) and the relaxation is performed according to the cone format.
That is, the hydrogen and methane production ratio is controlled for the electric gas conversion equipment, the characteristics of the two gas fuels are fully exerted, and the electricity of the renewable energy is converted into the hydrogen and the methane through the electric gas conversion equipment and is coupled with a natural gas network for mutual assistance. Therefore, renewable energy sources are fully consumed in time, the multi-energy flow cross-coupling mutual-assistance coordination capacity is effectively improved, and the electricity-gas coupling comprehensive energy system is economically and stably operated.
Based on the above description, compared with the prior art, the embodiments of the present invention have the following technical effects: the embodiment of the invention mainly aims at optimizing and adjusting an electric-to-gas technology, replans and designs the internal structure of the electric-to-gas equipment in consideration of the difference of the physicochemical characteristics of two common gas fuels, namely hydrogen and methane, and is used as a photovoltaic power generation unit to be combined with an electric-to-gas comprehensive energy system for optimizing and scheduling, so that the optimal scheduling of a plurality of 0-1 binary decision variables can be realized, a non-convex problem is converted and solved through second-order cone programming, and the electric-to-gas conversion equipment has certain universality.
The implementation mode of the invention is divided into the implementation of establishing a model and an algorithm. The structure of the electric gas conversion equipment is shown in fig. 2, the electric-gas comprehensive energy system using the electric gas conversion equipment is shown in fig. 3, the number symbols in fig. 3 represent the node numbers of the power system, and the English letters correspond to Belgian place names.
To illustrate and verify the electrical-gas integrated energy system of the embodiment of the present invention in detail, the embodiment of the present invention performs the following simulations:
the data adopted by the power system data in the example analysis is IEEE30 nodes, and the rest of the data are shown in Table 2, and the data are subjected to per unit processing. The IEEE30 bus test case represents a portion of the united states power system (located in the midwest of the united states). The original IEEE30 node scenario considers the processing of 6 thermal power generating units, where the 6 th unit connected to node 8 is changed to a photovoltaic output device.
TABLE 2 IEEE30 node data
Figure GDA0003675606570000171
Figure GDA0003675606570000181
The natural gas network data adopts Belgian 24-node network data, and the detailed data comprises the following data: table 3 maximum daily demand for each province of the belgium natural gas network, daily gas production by natural gas producers of the belgium natural gas network, storage reservoir capacity of the belgium natural gas network, and node description of the belgium natural gas network. According to international, common natural gas sales regulations, natural gas is priced by heating value, with the common Unit being the Million British Thermal Unit (MBTU), where BTU is the british Thermal Unit; however, the natural gas transaction in China is based on volume as a reference standard, and the common unit is cubic meter (m 3). Given that 1MBTU ≈ 28.3m3, it can be obtained by performing unit conversion: 1$/MBTU ≈ 0.035$/m 3.
Table 3 belgium natural gas network node description
Figure GDA0003675606570000182
Figure GDA0003675606570000191
The photovoltaic unit is set to output the maximum electric energy of 15000kWh every day. The photovoltaic output fluctuation data of each period is based on photovoltaic project data of university of queensland of australia, which is supported by local government funds, and a 1.2MW solar photovoltaic system is originally installed in four buildings. In the calculation example, the output data of 27 days 02 and 2020 and 27 days 02 and 2020 in 2019 are intercepted and processed, and because the seasons of the southern hemisphere and the northern hemisphere are different, in order to enable the result to accord with national habits of a plurality of northern hemispheres including China, the data of 2 months 12 and 2020 in 2019 is regarded as summer data, and the data of 6 months to 8 months in 2019 is regarded as winter data. Because the project is a small-range pilot project, the project is different from IEEE30 node electric power data based on a power grid in the middle and western part of the United states and 24 node natural gas data based on Belgian countries in the same order of magnitude, the output of the unit is expanded by 30 times, namely, the unit is regarded as 30 identical units to run simultaneously. The discard penalty parameter is set to 0.08 $/kWh.
Fig. 4 shows that when the hot standby state is 0.05, the output cumulative ladder diagram of the unit is as shown on the left side of fig. 4, which basically conforms to the peak-valley distribution characteristics of power consumption in the real situation, i.e. the peak of incoming power consumption around noon in the daytime and the overall power consumption at night are reduced. In order to represent the output conditions of all the units, a trapezoidal graph on the right side of the graph 4 is drawn, all curves are basically stable, the conditions of starting and stopping for a plurality of times in a short time do not exist, and the system has a good effect on the overall stability of the system.
Further, in order to visually demonstrate the stability of the electric-gas integrated energy system network, a node phase angle radar chart when the hot standby state is 0.05 is drawn in fig. 5. Because the nodes are numerous and the tidal current phase angles of part of adjacent nodes are very close, only five nodes of nodes 1, 5, 10, 20 and 30 are selected as typical node representatives in the graph, the phase angles are respectively kept at 0.607379215, 0.290545415045306, 0.156158045261011, 0.088633319272121 and 0.0761448832330874 and are stabilized near 5 bits after a decimal point, and the stability requirement of the whole electricity-gas comprehensive energy system is met.
Similarly, when the hot standby of the unit is 0.2, fig. 6, 7 may be obtained. The output accumulation ladder diagram of the unit is shown on the left side of fig. 6, and basically accords with the distribution characteristics of power consumption peaks and valleys in the actual situation, namely, the power consumption peaks come before and after noon in the daytime and the power consumption is wholly reduced at night. FIG. 6 is a right ladder diagram showing the output conditions of the units, and the curves are substantially stable; the nodal phase angle radar plot of fig. 7 also demonstrates the stability of the electro-pneumatic energy system described herein at a thermal standby of 0.2. However, a certain problem can be found by comparing the situation with the hot standby 0.05, for example, the right side of fig. 6 shows that the output situation of the unit 4 is started or stopped in a short time near the 19 o' clock, which is caused by the high hot standby, and the capability of the system to cope with an emergency situation can be greatly improved on the premise that certain unit operation life and system stability are lost.
The photovoltaic output data of 27 days 02 and 2020 and 27 days 02 and 2020 in 2019 are selected, the operation result in the electricity-gas integrated energy system is shown in fig. 8 and 9, and the photovoltaic output at the same moment basically accords with summer > whole year > winter longitudinally, wherein 12 months-2 months next year are selected in winter, and 6 months-8 months are selected in summer. According to the weather data measured by the photovoltaic project, the photovoltaic output is naturally less due to the influence of natural factors such as low temperature, low illumination intensity and short daytime in winter. In contrast, the typical day of summer has significantly better operating conditions than the winter, with annual treatment conditions between the two, consistent with conventional wisdom recognition.
On the basis of ensuring that the photovoltaic output is well operated, in order to display the characteristics of energy saving, cleanness, quick absorption and the like of the electric-to-gas equipment, the photovoltaic unit of the No. 8 node in the IEEE network is only subjected to output calculation and is not subjected to electric-to-electric coupling system simulation, and the result shown in the figure 10 is obtained. Because the power system and the natural gas system operate independently and the photovoltaic unit is directly connected to the grid, the electricity-gas system which lacks the coupling mutual-aid relationship cannot timely absorb photovoltaic electric energy which is unstable and has stronger intermittence. Particularly, the cost is punished by abandoning light, so that the cost is higher than the running cost of the electricity-gas comprehensive energy system with the electricity-gas conversion equipment under the condition of no electricity-gas conversion equipment. If the ecological benefit of the electric gas conversion equipment caused by the consumption of the carbon dioxide gas is taken into consideration, the advantages of the electric gas conversion equipment are more prominent.
The operating cost is obtained by properly adjusting the light abandonment penalty parameters and respectively setting the light abandonment penalty parameters to be four numerical values of 0.01, 0.05, 0.08 and 0.12, as shown in fig. 11(a), and a line graph of the influence curve of the light abandonment penalty parameter change on the total operating cost of fig. 11(b) is drawn according to the operating result of the electricity-gas integrated energy system. When the light rejection penalty parameter is too small, the operation cost is larger, which is second to the operation cost in the case of the no-power transfer device shown in fig. 10, and it is described that even though the penalty parameter is small, the operation cost of the whole system is high due to the larger light rejection amount. With the increase of the light abandonment penalty parameter, the operation cost of the system is obviously reduced, and the consideration of the light abandonment penalty cost in the optimization target can ensure that the system can fully consume the photovoltaic electric quantity. However, the light abandoning penalty parameter is continuously increased, and the system operation cost is increased on the contrary because a certain penalty cost is generated after a small amount of unrendered photovoltaic is multiplied by a larger penalty coefficient.
Further, as shown by the dashed line in fig. 11(b), it can be estimated that the discard light penalty parameter and the operation cost have a non-linear relationship, but there should be a minimum value as labeled in the figure. When the light abandonment punishment parameter takes the value, the total operation cost of the system is minimum, and specific values are to be further researched. When the light abandoning penalty parameter is smaller than the optimal value, the curve is decreased quickly, the difference between the values of the light abandoning penalty parameter is not large, but the large light abandoning amount is multiplied by the value of the light abandoning penalty parameter to cause large penalty cost. Correspondingly, when the discard light penalty parameter is larger than the optimum value, the cost curve rises slowly because the discard light amount is kept at a small amount even if the discard light penalty parameter becomes significantly large.
In summary, the optimal scheduling method for the electricity-gas integrated energy system considering electricity to gas in the embodiment of the present invention takes minimization of the operation cost of the electricity-gas integrated energy system as an optimization target, calculates and optimizes variables such as the conversion ratio of the electricity-gas conversion device, the start-stop condition of the thermal power generating unit, and the flow direction of the natural gas pipeline in each time period, and further realizes timely and sufficient consumption of renewable energy, effective improvement of the multi-energy flow cross-coupling and cross-coordination capability, and economic and stable operation of the electricity-gas coupled integrated energy system.
Fig. 12 is a block diagram illustrating an optimized dispatching device of an electric-gas integrated energy system with electric power to gas conversion taken into account according to an embodiment of the present invention.
As shown in fig. 12, the optimal scheduling apparatus 100 for an electricity-gas integrated energy system considering electricity to gas includes: a first setup module 10, a second setup module 20, a third setup module 30 and a determination module 40.
A first establishing module 10, configured to establish an electrical to gas equipment model of the system that satisfies a plurality of electrical to gas constraints, where the plurality of electrical to gas constraints include: reaction efficiency constraint, conversion power consumption constraint, combustion limit constraint, explosion limit constraint and heat value constraint; a second building module 20 for building a power system model of the system that satisfies a plurality of power constraints and a natural gas system model that satisfies a plurality of natural gas constraints; a third establishing module 30, configured to establish a minimum operation cost optimization problem model of the system according to the electric power to gas equipment model, the electric power system model, and the natural gas system model; and the determining module 40 is configured to convert the minimum operation cost optimization problem by using a second-order cone programming based on the minimum operation cost optimization problem model and taking the minimum operation cost as an optimization target, so as to perform optimal scheduling on the electric-to-gas conversion equipment, the thermal power generating unit and the natural gas network in each production period.
It should be noted that, for other specific embodiments of the optimal scheduling apparatus for an electricity-gas integrated energy system considering electricity to gas, reference may be made to the specific embodiment of the optimal scheduling method for an electricity-gas integrated energy system considering electricity to gas, and details are not described here to avoid redundancy.
The optimal scheduling device of the electricity-gas comprehensive energy system considering electricity to gas in the embodiment of the invention can realize timely and sufficient consumption of renewable energy, effective improvement of multi-energy flow interactive coupling and mutual assistance coordination capacity and stable operation of system economy.
In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The meaning of "plurality" is two or more unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., 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. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present invention, but not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (9)

1. An optimized dispatching method for an electricity-gas integrated energy system considering electricity to gas, which is characterized in that the system comprises the following steps: the method comprises the following steps of:
s1, establishing an electric-to-gas equipment model of the system meeting a plurality of electric-to-gas constraints, wherein the plurality of electric-to-gas constraints comprise: reaction efficiency constraint, conversion power consumption constraint, combustion limit constraint, explosion limit constraint and heat value constraint;
s2, establishing a power system model meeting a plurality of power constraints and a natural gas system model meeting a plurality of natural gas constraints of the system;
s3, establishing a minimized operation cost optimization problem model of the system according to the electric power conversion equipment model, the electric power system model and the natural gas system model;
s4, based on the minimized operation cost optimization problem model, with minimized operation cost as an optimization target, converting the minimized operation cost optimization problem by using second-order cone programming to optimally schedule the electric-to-gas conversion equipment, the thermal power generating unit and the natural gas network in each production period;
the electric gas conversion equipment adopts a polymer electrolyte membrane pool to electrolyze water to prepare hydrogen, and the electric gas conversion equipment adopts DavyTMCarrying out methanation by the technology, wherein the reaction efficiency is restricted as follows;
Figure FDA0003684603680000011
wherein eta iselecReaction efficiency, eta, of processes for the production of hydrogen by electrolysis of watermethFor the efficiency of the methanation process, etaelec，tReaction efficiency eta at time slot t for the electrolysis of water to produce hydrogenmeth，tFor the reaction efficiency of the methanation process in the time slot t, wherein each
Figure FDA0003684603680000012
Within a time slot, said ηelec，tAnd said ηmeth，tRemain unchanged, wherein the time is aggregated
Figure FDA0003684603680000013
2. The method for optimized scheduling of an electricity-gas integrated energy system taking into account electricity to gas of claim 1, wherein the conversion power consumption constraint is:
Figure FDA0003684603680000014
Figure FDA0003684603680000015
wherein the content of the first and second substances,
Figure FDA0003684603680000016
represents the consumption of the electric energy used by the electric gas conversion equipment for producing hydrogen,
Figure FDA0003684603680000017
is composed of
Figure FDA0003684603680000018
Flow rate of hydrogen, alpha, produced by time-slotted electric gas-converting plantselec，tTo the parameter of the power consumption corresponding to the hydrogen flow, αmeth，tTo be a power consumption parameter corresponding to the methane flow rate,
Figure FDA0003684603680000021
represents the electric energy consumed by the electric gas conversion equipment for preparing methane,
Figure FDA0003684603680000022
is composed of
Figure FDA0003684603680000023
The time slot electricity changes the methane flow that the gas facility produced.
3. The method for optimizing scheduling of an electric-gas integrated energy system taking into account electric-gas conversion according to claim 2, wherein the combustion limit and the explosion limit are respectively:
Figure FDA0003684603680000024
wherein the content of the first and second substances,
Figure FDA0003684603680000025
respectively an upper limit and a lower limit of the combustion of the methane,
Figure FDA0003684603680000026
respectively representing the upper explosion limit and the lower explosion limit of methane,
Figure FDA0003684603680000027
respectively an upper limit and a lower limit of combustion of hydrogen,
Figure FDA0003684603680000028
respectively as the upper and lower explosion limits of hydrogen,
Figure FDA0003684603680000029
is composed of
Figure FDA00036846036800000210
Percentage of hydrogen content in the production pipeline of the time slot electric gas conversion equipment,
Figure FDA00036846036800000211
is composed of
Figure FDA00036846036800000212
Percentage of methane content in the production pipeline of the time slot electric gas conversion equipment.
4. The optimal scheduling method of the electricity-gas integrated energy system considering electricity to gas as claimed in claim 3, wherein the heat value constraint is:
Figure FDA00036846036800000213
MJ/kg, wherein,
Figure FDA00036846036800000214
is the heating value of the hydrogen gas,
Figure FDA00036846036800000215
is the heating value of methane.
5. The optimal scheduling method for the electricity-gas integrated energy system considering electricity to gas according to claim 4, wherein the optimal scheduling problem model of the minimum operation cost is as follows:
Figure FDA00036846036800000216
the coal consumption function of each thermal power generating unit can be expressed by the following quadratic equation:
Figure FDA00036846036800000217
wherein N represents the number of thermal power generating units,
Figure FDA00036846036800000218
represents the coal consumption cost of the thermal power generating unit i,
Figure FDA00036846036800000219
represents the starting cost of the thermal power generating unit i,
Figure FDA00036846036800000220
represents the shutdown cost of the thermal power generating unit i,
Figure FDA00036846036800000221
representing the cost of the natural gas network, Pi，tTo represent
Figure FDA00036846036800000222
Output of thermal power generating unit i in time slot CPV，tRepresents a light abandonment penalty cost, said CPV，tAnd is positively correlated with the electric quantity of the abandoned light.
6. The optimal scheduling method of an electricity-gas integrated energy system considering electricity to gas according to claim 5, wherein the transformation of the minimization of operation cost optimization problem using second order cone programming comprises:
with the second order cone programming, the Weymouth natural gas flow constraint equation is equivalently replaced by:
Figure FDA0003684603680000031
by using bilinear relaxation, the bilinear term to the right of the above equation can be replaced with the following equation:
Figure FDA0003684603680000032
Figure FDA0003684603680000033
Figure FDA0003684603680000034
Figure FDA0003684603680000035
Figure FDA0003684603680000036
wherein λ ismnRepresenting an auxiliary variable flowing through the pipe m-n, the pressure pi of the node mmThe upper mark u and the upper mark l are respectively an upper limit and a lower limit;
relaxed in a conical format, where the standard SOC formula is expressed as:
Figure FDA0003684603680000037
Figure FDA0003684603680000038
wherein, FmnDenotes the natural gas flow through the pipeline m-n, CmnWhich means that the Weymouth constant,
Figure FDA0003684603680000039
indicating the flow of natural gas out of node m,
Figure FDA00036846036800000310
representing the natural gas flow, pi, into the node mm、πnRespectively representing the pressure of the nodes m and n.
7. The method for optimally scheduling the electricity-gas integrated energy system considering the electricity to gas according to claim 6, wherein the optimally scheduling the electricity to gas equipment in each production period comprises:
to pair
Figure FDA00036846036800000311
Time slot is used for optimizing and scheduling hydrogen flow produced by the electric gas conversion equipment and the time slot is used for optimizing and scheduling hydrogen flow produced by the electric gas conversion equipment
Figure FDA00036846036800000312
Carrying out optimized scheduling on the methane flow produced by the electric gas conversion equipment in time slot;
the thermal power generating unit in each production period is optimally scheduled, and the method comprises the following steps:
to pair
Figure FDA00036846036800000313
Output of time slot thermal power generating unit i and
Figure FDA00036846036800000314
carrying out optimized scheduling on the start-stop condition of the time slot thermal power generating unit i;
performing optimized scheduling on the natural gas network at each production period, comprising:
and optimally scheduling the natural gas flow numerical value from the node m to the node n, the natural gas pipeline flow direction from the node m to the node n and the pressure of the node m in the natural gas network in each production period in the natural gas network.
8. The method for optimized scheduling of an electric-to-gas integrated energy system taking into account electric to gas of claim 1, wherein the plurality of power constraints comprise: the method comprises the following steps of (1) power balance constraint, hot standby constraint, unit output constraint, unit climbing constraint, unit start-stop constraint, start-stop cost constraint and line tide safety constraint;
the plurality of natural gas constraints comprises: natural gas power balance constraints, Weymouth natural gas flow constraints, gas source storage capacity constraints, pipeline pressure constraints, and node flow constraints.
9. An optimized dispatch device for an electric-gas integrated energy system taking into account electric to gas considerations for carrying out the method of claim 1, the system comprising: electricity changes gas equipment, thermal power generating unit and natural gas network, the device includes:
a first building module to build an electric-to-gas plant model of the system that satisfies a plurality of electric-to-gas constraints, wherein the plurality of electric-to-gas constraints comprise: reaction efficiency constraint, conversion power consumption constraint, combustion limit constraint, explosion limit constraint and heat value constraint;
a second building module for building a power system model of the system that satisfies a plurality of power constraints and a natural gas system model that satisfies a plurality of natural gas constraints;
the third establishing module is used for establishing a minimized operation cost optimization problem model of the system according to the electric power-to-gas equipment model, the electric power system model and the natural gas system model;
and the determining module is used for converting the minimum operation cost optimization problem by using second-order cone planning based on the minimum operation cost optimization problem model and taking the minimum operation cost as an optimization target so as to optimally schedule the electric-to-gas equipment, the thermal power generating unit and the natural gas network in each production period.
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