CN113128775B - Comprehensive energy system scheduling method and device considering demand response and coupling degree - Google Patents
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Abstract
The invention belongs to the field of comprehensive energy scheduling, and provides a comprehensive energy system scheduling method and device considering demand response and coupling degree. The method comprises the steps of obtaining output and energy consumption information of the comprehensive energy system to obtain equipment operation cost; obtaining the waste air volume to obtain the waste air cost; constructing a comprehensive energy economy optimization scheduling model by taking the minimum total operation cost of the comprehensive energy system as an objective function based on the sum of the demand response cost, the equipment operation cost and the wind abandoning cost to form the total operation cost of the comprehensive energy system; and solving the comprehensive energy economic optimization scheduling model under the condition that the coupling degree comprises network constraint, energy station collection constraint and demand response constraint to obtain the use scheduling instruction of each energy in the comprehensive energy system so as to control the working state of each energy and improve the demand response capability and the reliability of system operation.
Description
Technical Field
The invention belongs to the field of comprehensive energy scheduling, and particularly relates to a comprehensive energy system scheduling method and device considering demand response and coupling degree.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Environmental pollution caused by the production and consumption processes of non-renewable fossil energy sources restricts the development of economy. With the gradual increase of energy demand and the continuous increase of environmental pressure in the industrial production process, the requirement of energy structure optimization cannot be met by simply optimizing the energy supply side and the transportation side. Energy suppliers and governments of various countries are actively seeking long-term solutions to energy shortages.
With the advancement of power market innovation, demand Response (DR) is widely recognized as an effective means of integrating consumer terminal response potential. The bidirectional interaction between the demand side and the power grid can effectively relieve the contradiction of power supply tension, balance the fluctuation brought to the power grid by the intermittence of the renewable energy sources, and effectively improve the safety and the stability of the power grid operation. Meanwhile, the reasonable utilization of the electric power can be guided by introducing the demand response, and more space is provided for wind power integration. However, the inventors found that the above-mentioned research is mainly focused on the conventional demand response of the power system, the diversity of the energy demand is not considered, the optimal configuration of the energy cannot be achieved, thereby reducing the energy demand response flexibility and the energy use satisfaction,
disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a method and a device for scheduling an integrated energy system in consideration of demand response and coupling degree, which can improve the coupling degree between integrated energy systems, improve demand response capability and system operation reliability, and bring greater flexibility to demand response.
In order to achieve the purpose, the invention adopts the following technical scheme:
a first aspect of the present invention provides a method for scheduling an integrated energy system considering demand response and coupling degree.
An integrated energy system scheduling method considering demand response and coupling degree, comprising:
acquiring output and energy consumption information of the comprehensive energy system to obtain the running cost of the equipment; obtaining the waste air volume to obtain the waste air cost;
constructing a comprehensive energy economy optimization scheduling model by taking the minimum total operation cost of the comprehensive energy system as a target function based on the sum of the demand response cost, the equipment operation cost and the wind curtailment cost to form the total operation cost of the comprehensive energy system;
and solving the comprehensive energy economy optimization scheduling model under the condition that the coupling degree comprises network constraint, energy station collection constraint and demand response constraint is considered, and obtaining a use scheduling instruction of each energy in the comprehensive energy system so as to control the working state of each energy and improve the demand response capability and the reliability of system operation.
Further, the output and energy consumption information includes output of a thermal power generating unit, natural gas input of an energy hub, electric output of a cogeneration unit, heat output of the cogeneration unit, output of a wind power generating unit, gas consumption of a gas boiler, power consumption of an electric boiler and gas consumption of the cogeneration unit.
Further, the internal constraints of the energy hub are: and the CHP unit, the gas boiler, the electric boiler and the P2G equipment coupling equipment meet the unit capacity and climbing rate constraints.
Further, the demand response constraints include power system constraints and natural gas system constraints.
Further, the coupling degree comprises a network constraint which is a thermodynamic system constraint.
Further, the wind abandoning cost is the product of the wind abandoning amount and the wind abandoning cost coefficient.
Further, the demand response cost includes an incentive demand response cost and an alternative demand response cost.
A second aspect of the present invention provides an integrated energy system dispatching device considering demand response and coupling degree.
An integrated energy system dispatching device considering demand response and coupling degree, comprising:
the information acquisition module is used for acquiring the output and energy consumption information of the comprehensive energy system to obtain the equipment operation cost; obtaining the waste air volume to obtain the waste air cost;
the scheduling model building module is used for forming the total operation cost of the comprehensive energy system based on the sum of the demand response cost, the equipment operation cost and the wind curtailment cost, and building a comprehensive energy economic optimization scheduling model by taking the minimum total operation cost of the comprehensive energy system as an objective function;
and the scheduling instruction output module is used for solving the comprehensive energy economic optimization scheduling model under the condition that the coupling degree is considered to include network constraint, energy station collection constraint and demand response constraint, and obtaining the use scheduling instruction of each energy in the comprehensive energy system so as to control the working state of each energy and improve the demand response capability and the reliability of system operation.
A third aspect of the invention provides a computer-readable storage medium.
A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps of the method for integrated energy system dispatch taking into account demand response and coupling as described above.
A fourth aspect of the invention provides a computer apparatus.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method for integrated energy system dispatch taking into account demand response and degree of coupling as described above when executing the program.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a demand response strategy in an industrial automation system, and on the basis, provides a method for describing the coupling degree of a comprehensive energy system, establishes a comprehensive energy system optimization model considering demand response and the coupling degree, and can achieve the purpose of peak clipping and valley filling by guiding a user to adjust energy use behaviors, so that the energy supply pressure of a load peak value is relieved, the system can absorb more wind energy along with the improvement of the coupling degree, and the economy and the energy structure are improved. The increase of the coupling degree can improve the demand response capability and the reliability of system operation, and bring greater flexibility to the demand response. Meanwhile, the complementarity of heterogeneous energy brought by the improved coupling degree can improve the user energy consumption satisfaction degree in the demand response process.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a flowchart of an integrated energy system scheduling method considering demand response and coupling degree according to an embodiment of the present invention;
FIG. 2 is a physical significance of the degree of coupling of an embodiment of the present invention;
FIG. 3 is a test system including three energy hubs according to an embodiment of the present invention;
FIG. 4 is a total system load before and after demand response for an embodiment of the present invention;
FIG. 5 (a) is a schematic diagram of a capacity before demand response architecture according to an embodiment of the present invention;
FIG. 5 (b) is a diagram of a capacity structure after demand response according to an embodiment of the present invention;
FIG. 6 is an economic indicator for different degrees of coupling for embodiments of the present invention;
FIG. 7 is a variance and peak-to-valley difference of the total load of the system according to an embodiment of the present invention;
FIG. 8 shows the air rejection for different coupling degrees according to an embodiment of the present invention;
FIG. 9 is a P2G output at different degrees of coupling for embodiments of the present invention;
FIG. 10 is a graph of performance satisfaction and cost satisfaction for an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Compared to conventional power systems, integrated Energy Systems (IES) can provide a variety of forms of energy supply. It is considered to be the main carrier form of future energy sources. By realizing the coordination planning and complementary mutual assistance among the various energy source subsystems such as cold, heat, electricity, gas and the like, the coupling relation among the energy source subsystems is strengthened, the consumption of renewable energy sources can be effectively promoted, and the overall response capability of a user is improved.
In addition to guiding the user to adjust his energy usage plan through incentives or pricing signals, the integrated energy system provides a new approach to demand response due to its multi-energy coupling. The existing literature establishes a manufacturer production scheduling model driven by electric power and natural gas based on time and events, so that the cost of the manufacturer can be saved, and the interaction between the manufacturer and an energy supplier is promoted. The existing literature considers the influence of the consumer behavior coupling effect on demand response, and establishes a refined comprehensive demand response model so as to reduce the dissatisfaction of consumers.
Multiple energy couplings may transform energy types, providing more flexible resources for demand response. Obviously, this interaction is closely related to the degree of coupling of the integrated energy system, which refers to the ability of the subsystems of the integrated energy system to transfer energy via the coupling means. On the basis, the coupling degree is used for representing the strength of energy flow connection among subsystems of the comprehensive energy system. Quantitative description of the degree of coupling helps to clearly analyze the interaction between multi-energy source coupling complementation and demand response.
The invention provides a demand response strategy adaptive to a comprehensive energy system in order to give full play to the maneuverability and flexibility of a demand side. The invention considers the coupling degree of the comprehensive energy system to quantitatively describe the correlation degree of the energy flow among the energy subsystems of the system. The invention aims at the optimal system economy and establishes a comprehensive energy system model considering the coupling degree including network constraint, energy station constraint and demand response constraint. The invention establishes a typical test system to verify the effect of demand response on mobilizing demand side flexibility. In addition, the interaction effect between the degree of coupling and the demand response is also analyzed herein.
DR reduces the energy supply pressure during peak hours and optimizes the load curve by guiding the user to change the electricity utilization behavior. The invention considers the demand response of the energy station node load in the comprehensive energy system.
The demand response strategy is as follows:
the energy station has energy conversion equipment such as an electric boiler, P2G equipment, a gas boiler, a CHP unit and the like, can select energy in different forms, optimizes the operation mode of the energy conversion equipment, and meets the requirement terminals with the same quality. Therefore, the energy conversion relation of the energy collection station can be utilized to realize the substitution of different energy sources, thereby achieving the purposes of complementary mutual assistance among the energy sources, peak load regulation and system flexibility improvement. The cogeneration unit and the gas boiler supply heat by burning natural gas, and the electric boiler supplies heat. Thus, a higher energy source may be selectively priced to meet the thermal load demand of the user over a period of time.
The power load and the natural gas load before and after the demand response are shown in formulas (1) to (2).
Wherein, the first and the second end of the pipe are connected with each other,
respectively a power load and a natural gas load before demand response; delta D C ,ΔQ C Respectively responding to the power load and the natural gas load for participating in the demand; d C And Q C Respectively, a demand-responded electrical load and a natural gas load.
User satisfaction:
for the energy demand of the same user, the conversion relation between electricity and gas in the demand response is the formulas (3) to (6).
ΔD C,j,t ＝-γΔQ C,m,t (3)
Wherein, W e ,W g Respectively the electric power and the natural gas heat value; eta e ,η g Electrical and natural gas efficiencies, respectively;
respectively participating in demand response electric power and natural gas load lower limits; />
Respectively participating in demand response load upper limits; the subscripts j, m represent the ability to participate in the demand responseA source category; t represents the time.
The demand response guides the user to change the way he uses energy, affecting the cost of use. According to the formula (7), the energy utilization condition of the user can be changed within a certain time by the participation of the user in demand response, so that the energy utilization satisfaction degree is influenced. As shown in the formula (8), the user participates in demand response by taking economy as guidance, and the expenditure satisfaction degree of the user is influenced.
Wherein r and p respectively represent the user satisfaction degree of energy mode and the satisfaction degree of expense expenditure; Δ q of t 、VC t Respectively representing the load transferred at the time t and the changed expense cost; q. q.s t And C t Respectively representing the total load and the total expenditure at time t.
As shown in fig. 2, the coupling degree of the IES refers to the degree of correlation or dependency between the electrical, gas and thermal subsystems, and is a physical quantity representing the energy transmission and conversion capability between the subsystems.
As the coupling deepens, the energy flow relationship between the systems becomes tighter. The coupling degree of the IES affects the effect of demand response, such as peak load shedding capability, wind power consumption capability, customer satisfaction, etc. Furthermore, as the degree of coupling increases, both the output of the coupling device and the demand response can have an impact on the economics of system operation.
The subsystems are interconnected by coupling means, so that the degree of coupling is closely related to the capacity of the subsystems. The coupling degree of energy m and energy n in the power supply unit i represents the ratio of the capacity of the coupling unit for transmitting the two types of energy to the total capacity of the unit, and is given by an equation (9).
Wherein the content of the first and second substances,
the coupling degree between energy m and energy n in the energy station i is shown; />
Is the operating state of the coupling element; />
Is the total capacity of the coupling elements between the energy m and the energy n in the energy collection station i; e IES Is the total capacity of the elements in the IES.
The energy m to energy n conversion device can only convert energy in one direction, but cannot convert energy in two directions. The capacity of the energy conversion device determines the ability of the energy conversion between the subsystems.
Wherein the content of the first and second substances,
representing the capacity of a single coupling element.
The degree of coupling between the two subsystems of the IES can be represented as (11).
Wherein, the first and the second end of the pipe are connected with each other,
representing the coupling degree between the energy m and the energy n in the integrated energy system; d IES Representing degree of coupling of an integrated energy system(ii) a P, Q, H represents electrical, natural gas, thermal energy, respectively.
By definition, the degree of coupling of the IES refers to the ability of each subsystem to improve energy efficiency, reduce peak load, and reduce system operating cost through energy conversion.
Example one
As shown in fig. 1, the present embodiment provides an integrated energy system scheduling method considering demand response and coupling degree, which includes:
step 1: acquiring output and energy consumption information of the comprehensive energy system to obtain the running cost of the equipment; and obtaining the abandoned air quantity to obtain the abandoned air cost.
Step 2: and constructing a comprehensive energy economy optimization scheduling model by taking the minimum total operation cost of the comprehensive energy system as a target function based on the sum of the demand response cost, the equipment operation cost and the wind curtailment cost.
The output and energy consumption information comprises output of a thermal power generating unit, natural gas input of an energy hub, electric output of a cogeneration unit, heat output of the cogeneration unit, output of a wind power unit, gas consumption of a gas boiler, power consumption of an electric boiler and gas consumption of the cogeneration unit.
The comprehensive energy economy optimization scheduling model considers the system scheduling problem of 24 hours a day, and takes the minimum total operation cost of the comprehensive energy system as an objective function:
F＝min(C opra +C qf +C R ) (13)
to ensure the overall efficiency, the total cost of the IES is composed of equipment operating cost, wind curtailment power cost, and demand response cost. The equipment operating cost can be described as (14).
Wherein a, b and c represent cost coefficients of the thermal power generating unit; d. e and f represent cost coefficients of the CHP unit;
respectively representing the output of a thermal power generating unit, a gas well compressor, a wind power generating unit, a CHP unit, P2G equipment, a gas boiler, an electric boiler and a coal-fired unit; pi g 、π w 、π P2G 、π gb 、π eb 、π h Respectively showing the cost coefficients of a gas well compressor, a wind turbine generator, P2G equipment, a gas boiler, an electric boiler and a coal-fired unit.
The wind abandonment is a phenomenon that a part of wind power generation is forced to be abandoned for some reason and a corresponding generator set is closed. The wind curtailment cost may be described as (15).
C qf ＝π qf W qf (15)
Wherein, C qf Representing the cost of wind abandonment; pi qf Representing a wind curtailment cost coefficient; w qf The air reject rate is shown.
The demand response cost is shown as (16).
Wherein, C R Representing a demand response cost; delta D C 、ΔQ C 、ΔH C Respectively representing the electric, gas and heat loads participating in demand response; pi Dc 、π Qc 、π Hc Representing the demand response cost coefficients of electrical, gas, and thermal loads, respectively.
And step 3: and solving the comprehensive energy economic optimization scheduling model under the condition that the coupling degree comprises network constraint, energy station collection constraint and demand response constraint to obtain the use scheduling instruction of each energy in the comprehensive energy system so as to control the working state of each energy and improve the demand response capability and the reliability of system operation.
Wherein the internal constraints of the energy hub are: the constraints on unit capacity and ramp rate that are met by the CHP unit, gas boiler, electric boiler, P2G plant coupling equipment can be described as (18) - (19).
0≤P n,t ≤P n,max (18)
Wherein, P n,t 、
Respectively representing the output and the climbing of equipment in the energy collection station; p is n,max 、/>
Respectively representing the upper limit of the output of the equipment in the energy station and the upper limit of the climbing slope.
Large amounts of stored electricity are technically difficult and therefore less costly and larger capacity natural gas storage is used herein. At the end of the scheduling period, the reservoir level should be restored to the initial state, as shown in fig. 20. The storage balance equation can be described as (21). The storage capacity limit may be described as (22) - (23).
Wherein, the first and the second end of the pipe are connected with each other,
representing the gas storage power; />
Represents the existing amount of natural gas; />
Respectively representing the upper and lower limits of the gas storage power; />
Indicating the capacity of the gas storage device.
The balance constraint of the power system can be described as (24), where the capacity of the power generation equipment should be equal to the sum of the power usage of the equipment and the customer.
Wherein the content of the first and second substances,
representing the power input of the power station; />
Representing the electrical load, e CHPe Representing the electrical efficiency of the CHP unit. />
As shown in (25), wind power generation is limited by wind power prediction. Total wind curtailment for IES on a typical day is shown (26).
The natural gas load balancing constraint can be expressed as (27), where the natural gas production is equal to the sum of the plant and customer consumption.
Wherein the content of the first and second substances,
natural gas input representing a power station; />
Representing the natural gas load, e P2G Indicating P2G device efficiency.
The thermal load balancing constraint may be described as (28).
Wherein the content of the first and second substances,
representing the output of the coal-fired unit; />
Represents the thermal load; e.g. of the type CHPh 、e eb 、e gb Respectively showing the heat efficiency of the CHP unit, the efficiency of the electric boiler and the efficiency of the gas boiler.
The coal-fired unit capacity constraint can be described as (29).
Wherein the content of the first and second substances,
and representing the upper limit of the output of the coal-fired unit.
The solution of the nonlinear model of the integrated energy system considering the demand response and the coupling degree is a complex problem. The GAMS is a software platform for building and solving large complex programming problems. The interior point method solver IPOPT is suitable for solving a large-scale nonlinear optimization problem and is widely applied to many fields. Therefore, GAMS/IPOPT is used herein to address this problem.
This example constructed a test system with 3 energy hubs, as shown in FIG. 3Shown in the figure. The right side of the figure is the IEEE 39 node network model and the left side is the Belgian 20 node natural gas system. The power grid and the natural gas network are connected together through three energy collecting stations. From the system perspective, the energy station has a plurality of input and output interfaces [16] The power transmission and transformation center is the key of IES energy coupling.
Based on the existing typical winter day data and corrected for it. The power unit is referred to as pu with 100MVA as reference value. The reference value for the cost unit is 4 $/(MVA), denoted mu.
The energy hub in the example comprises an electric load, a natural gas load and a heat load, wherein the load participating in the demand response accounts for 40%. The impact of demand response on system operation is mainly explored in terms of energy supply reliability and environmental protection.
FIG. 4 is a graph comparing the total system load before and after demand response. After the demand response is implemented, the total load curve tends to be flat, and the load variance in each period is reduced from 14.98 to 6.24. This indicates that the demand response achieves peak clipping and valley filling, and the load curve tends to be flat. Meanwhile, the demand response can improve the power supply quality and avoid the system from operating in the peak period with low efficiency. We set 80% capacity of capacity equipment to the energy supply congestion value. The results show a significant reduction in the congestion time of the energy supply.
One valuable advantage of demand response is that it can absorb wind by increasing nighttime loads. Therefore, through the demand response, the energy supply structure can be optimized, and the environmental pollution caused by fossil fuels is reduced. The introduction of the demand response improves the utilization rate of equipment and the safety of energy supply, and ensures the efficient operation of the IES.
In order to explore the influence of the degree of coupling on the system economy, the degree of coupling is increased linearly, wherein the degree of coupling is determined by equations (9) - (12). This is not considered because there is no demand response mentioned herein when the degree of coupling is 0.
Figure 6 shows the economic indicators of different degrees of coupling. On the one hand, as the degree of coupling increases, the operating cost of the system decreases. The complementary interaction among all subsystems reduces the air abandoning rate, and the output of the coal-fired unit and the output of the gas well compressor are reduced. Therefore, energy efficiency is improved. On the other hand, as the degree of coupling increases, the participation in demand response increases, so that the cost of system demand response increases.
The slope of the curve becomes smaller gradually and finally becomes 0, which shows that the influence of the improvement of the coupling degree on the system economy tends to be flat. When the coupling degree is 20%, the overall economic index of the system is considerable. In other words, the coupling degree of the system is improved, so that the economical efficiency of the system is not improved continuously, and the equipment investment cost is increased. And a proper coupling degree is sought, so that the economic efficiency is optimized.
The comprehensive energy system realizes complementary mutual assistance among heterogeneous energy sources through coupling of different energy sources, provides a new way for consumption of renewable energy sources, and provides greater flexibility for loads on demand sides.
The flexibility of demand response is mainly reflected in two aspects. In one aspect, the demand response may guide the user to adjust the energy usage plan to smooth the peaks and valleys of the load curve. On the other hand, the demand response can improve the wind power consumption capability of the system by increasing the energy consumption. The degree of coupling of the energy systems is related to the transfer of energy between the different energy systems, which affects the flexibility of the demand response. The influence of the coupling degree on the demand response effect is mainly analyzed from three aspects of system energy supply reliability, environmental protection and user satisfaction.
Fig. 7 reflects the variance and peak-to-valley difference of the total load of the system at different degrees of coupling. As the degree of coupling increases, the variance and the peak-to-valley difference of the load curve decrease. It can be seen that an increase in the degree of coupling will improve the peak and valley clipping effect of the demand response. This indicates that the integrated energy system provides more space for demand response through energy complementation. However, optimizing peak clipping and valley filling by increasing the degree of coupling is limited. When the coupling degree reaches 20%, it is not significant to flatten the load curve by increasing the IES coupling degree.
The air reject rate at different degrees of coupling is shown in fig. 8. The improvement of the coupling degree further stimulates the advantage of demand response, thereby improving the grain load and increasing the wind power consumption. Along with the increase of the coupling degree, the output of the wind turbine generator is reduced in the daytime, the output of the wind turbine generator is increased at night, and the time distribution rule of wind is met. However, the load capacity of the grid for wind power is limited in consideration of the uncertainty and volatility of wind power. Therefore, when the coupling degree reaches 30%, an inflection point exists, and the wind power utilization rate cannot be improved by continuously improving the coupling degree.
FIG. 9 shows the output of P2G units with different coupling degrees. This phenomenon has two causes. On one hand, with the increase of the coupling degree, the whole participation of demand response is increased, and the total load of the system tends to be smooth; during the day, energy usage is reduced and wind output is reduced. The energy consumption increases at night, so the wind power generation capacity increases. On the other hand, an increase in the degree of coupling results in an increase in the output of the P2G devices of the system. The P2G plant converts more electrical energy into natural gas, which also increases the consumption of wind power. Similarly, since the power grid has a limited carrying capacity, the improvement of the coupling degree has a limited effect on increasing the P2G output.
The coupling degree of the comprehensive energy system can influence the satisfaction degree of energy using modes and the satisfaction degree of expense expenditure of users, along with the increase of the coupling degree, more and more users select higher use price ratio and more sufficient energy types to meet the use requirements. This makes the energy supply safer and more reliable, and the possibility of load reduction smaller. Thereby improving user satisfaction with the energy usage mode. For cost satisfaction, as the degree of coupling increases, users can reduce energy costs by selectively replacing energy sources with higher cost energy sources. Therefore, the degree of satisfaction of expenditure is also improved.
However, as the degree of coupling increases to a certain degree, the increasing degree of coupling does not improve user satisfaction. Therefore, other ways to improve the user experience, such as improving the grid structure, and further improving the reliability of energy supply, are necessary.
The degree of coupling of the integrated energy systems actually reflects the complementary ability between the energy systems. The energy complementation and mutual assistance of different forms, different prices and different use peak values improves the demand response capability, increases the wind power consumption and provides greater flexibility for the operation of a comprehensive energy system. However, due to the presence of the inflection point, optimizing the various indicators by increasing the degree of coupling has limited effectiveness. Conversely, blindly increasing the degree of coupling also increases the equipment investment costs. Therefore, the method has important significance for system optimization by finding the acceptable coupling degree of the economic index, the energy supply reliability index and the wind power consumption index.
Wherein, the variable table is:
n: the number of energy hubs; a-f: a cost factor; pi g ,π w ,π h : capacity equipment cost coefficient; pi P2G : cost coefficient of P2G unit; pi gb : gas boiler cost factor; pi eb : electric boiler cost factor; Δ t: a unit scheduling period; v. of CHP : scheduling coefficients of the cogeneration units; v. of eb : an electric boiler scheduling coefficient; e.g. of the type P2G : P2G device efficiency; e.g. of a cylinder gb : gas boiler efficiency; e.g. of the type eb : electric boiler efficiency; e.g. of the type CHP : cogeneration unit efficiency;
a demand response preload; delta D C ,ΔQ C : participating in demand response load;
participating in a demand response load lower bound; />
Participating in a demand response load upper bound; w e ,W g : electrical power and natural gas heating values; eta e ,η g : electrical and natural gas efficiency; Δ q of t : energy converted during time t; q. q.s t : total energy in the t period; m is min : the user can meet the lower limit of the degree; m is max : the upper limit of the user satisfaction; delta C t : spending expense variable quantity in t time period; c t : total expense for time period t; p is a radical of formula min : a lower satisfaction limit of expenditure cost; p is a radical of formula max : an upper limit of satisfaction degree of expenditure cost; />
Coupling elementAn operating state; />
An upper limit of energy transfer between the two energy systems; />
A coupling element capacity; />
Coupling degree between energy m and energy n in the comprehensive energy system; d IES : the coupling degree of the comprehensive energy system; f: the total operating cost of the integrated energy system; c opra : equipment operating costs; c qf : wind abandon punishment cost; />
The output of the thermal power generating unit; />
Energy hub natural gas input; />
The cogeneration unit generates electricity; />
The heat output of the cogeneration unit; />
The wind turbine generator outputs power; />
The output of the coal-fired unit; />
Gas well compressor output; />
The power consumption of the P2G unit; />
Gas consumption of the gas boiler; />
The power consumption of the electric boiler; />
The gas consumption of the cogeneration unit; w qf : air volume is abandoned; />
The climbing rate of the cogeneration unit; />
The climbing rate of the electric boiler;
the gas boiler climbing rate; />
The climbing rate of the P2G equipment; />
The P2G equipment outputs power; />
The output of the electric boiler;
outputting power from the gas-fired boiler; />
Gas storage power; />
The existing amount of natural gas; />
Gas storage powerAn upper limit; />
Lower limit of gas storage power; />
Capacity of the gas storage device; />
An energy hub electrical input; />
An electrical load; />
An upper limit of electrical input of the energy hub; />
Wind power prediction power; />
Energy hub natural gas input; />
Gas load; an energy hub natural gas input upper limit; />
A thermal load; />
The upper limit of the output of the coal-fired unit.
Example two
The embodiment provides an integrated energy system dispatching device considering demand response and coupling degree, which comprises:
the information acquisition module is used for acquiring the output and energy consumption information of the comprehensive energy system to obtain the equipment operation cost; obtaining the waste air volume to obtain the waste air cost;
the scheduling model building module is used for forming the total operation cost of the comprehensive energy system based on the sum of the demand response cost, the equipment operation cost and the wind curtailment cost, and building a comprehensive energy economic optimization scheduling model by taking the minimum total operation cost of the comprehensive energy system as an objective function;
and the scheduling instruction output module is used for solving the comprehensive energy economic optimization scheduling model under the condition that the coupling degree is considered to include network constraint, energy station collection constraint and demand response constraint, and obtaining the use scheduling instruction of each energy in the comprehensive energy system so as to control the working state of each energy and improve the demand response capability and the reliability of system operation.
It should be noted that, in the present embodiment, each module in the apparatus corresponds to each step in the first embodiment one to one, and the specific implementation process is the same, and the description is not repeated here.
EXAMPLE III
The present embodiment provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the integrated energy system dispatching method considering demand response and coupling degree as described above.
Example four
The embodiment provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the method for scheduling the integrated energy system considering the demand response and the coupling degree.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by a computer program, which may be stored in a computer readable storage medium and executed by a computer to implement the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An integrated energy system scheduling method considering demand response and coupling degree, comprising:
acquiring output and energy consumption information of the comprehensive energy system to obtain the running cost of the equipment; obtaining the waste air volume to obtain the waste air cost;
constructing a comprehensive energy economy optimization scheduling model by taking the minimum total operation cost of the comprehensive energy system as an objective function based on the sum of the demand response cost, the equipment operation cost and the wind abandoning cost to form the total operation cost of the comprehensive energy system;
solving an economic optimization scheduling model of the comprehensive energy under the condition that the coupling degree including network constraint, energy station collection constraint and demand response constraint is considered, and obtaining a use scheduling instruction of each energy in the comprehensive energy system so as to control the working state of each energy and improve the demand response capability and the reliability of system operation;
by guiding a user to adjust the energy use behavior, the purpose of peak clipping and valley filling can be achieved through demand response, so that the energy supply pressure of a load peak value is relieved, the system can absorb more wind energy along with the improvement of the coupling degree, and the economy and the energy structure are improved; the increase of the coupling degree can improve the demand response capability and the reliability of system operation, and bring greater flexibility to demand response; meanwhile, the complementarity of heterogeneous energy brought by the improved coupling degree can improve the user energy consumption satisfaction degree in the demand response process.
2. The method of claim 1, wherein the capacity and energy consumption information comprises capacity of a thermal power generating unit, capacity hub natural gas input, cogeneration unit power capacity, cogeneration unit thermal capacity, wind power unit power capacity, gas boiler consumption, electric boiler consumption, and cogeneration unit consumption.
3. The method for integrated energy system dispatching taking into account demand response and degree of coupling of claim 1, wherein said energy hub internal constraints are: and the CHP unit, the gas boiler, the electric boiler and the P2G equipment coupling equipment meet the unit capacity and climbing rate constraints.
4. The method for integrated energy system dispatching taking into account demand response and degree of coupling of claim 1, wherein the demand response constraints comprise power system constraints and natural gas system constraints.
5. The method of claim 1, wherein the degree of coupling comprises a network constraint and a thermodynamic system constraint.
6. The integrated energy system dispatching method considering demand response and coupling degree of claim 1, wherein the wind curtailment cost is a product of the wind curtailment amount and a wind curtailment cost coefficient.
7. The method of claim 1, wherein the demand response cost includes an incentive demand response cost and an alternative demand response cost.
8. An integrated energy system dispatching device considering demand response and coupling degree, comprising:
the information acquisition module is used for acquiring the output and energy consumption information of the comprehensive energy system to obtain the equipment operation cost; obtaining the waste air volume to obtain the waste air cost;
the scheduling model building module is used for forming the total operation cost of the comprehensive energy system based on the sum of the demand response cost, the equipment operation cost and the wind curtailment cost, and building a comprehensive energy economic optimization scheduling model by taking the minimum total operation cost of the comprehensive energy system as an objective function;
and the scheduling instruction output module is used for solving the comprehensive energy economic optimization scheduling model under the condition that the coupling degree is considered to include network constraint, energy station collection constraint and demand response constraint, and obtaining the use scheduling instruction of each energy in the comprehensive energy system so as to control the working state of each energy and improve the demand response capability and the reliability of system operation.
9. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps of the method for integrated energy system dispatch taking into account demand response and degree of coupling as set forth in any one of claims 1 to 7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method of integrated energy system dispatch considering demand response and degree of coupling as claimed in any one of claims 1 to 7.
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