CN114091762A - Energy system double-layer operation optimization method and system based on stepped carbon trading - Google Patents
Energy system double-layer operation optimization method and system based on stepped carbon trading Download PDFInfo
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Abstract
The invention provides a double-layer operation optimization method of an energy system based on step carbon trading, which comprises the following steps: acquiring energy data of the comprehensive energy system; establishing a comprehensive energy system optimization model by using energy data; obtaining an operation optimization strategy by utilizing a comprehensive energy system optimization model, a particle swarm algorithm and a linear programming method; the method comprises the steps of establishing an integrated energy system optimization model, dividing each main body of the integrated energy system into three layers, and establishing each main body optimization model which comprises an upper-layer energy supplier optimization model and a lower-layer user optimization model.
Description
Technical Field
The invention relates to the technical field of energy systems, in particular to a double-layer operation optimization method and system of an energy system based on step carbon trading.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the increasing problems of environmental pollution and energy shortage, an integrated energy system containing renewable energy will become an important direction for green energy transformation. The vigorous use of renewable energy can effectively reduce the environmental pollution problem, and the development of the combined cooling heating and power technology can effectively improve the utilization efficiency of clean energy, so that the comprehensive energy system integrating renewable energy and cooling heating and power energy is widely developed and researched by students all over the world.
How to reasonably, economically and reliably operate the comprehensive energy system is the key for guaranteeing the reliable energy utilization of users. At present, random optimization of uncertain renewable energy sources is mainly considered, comprehensive optimization of load demand response is considered, linear optimization with optimal economic cost is considered, the problem of carbon dioxide emission is considered in the optimization of the comprehensive energy system in order to accelerate the realization of a double-carbon target, and the operation optimization of the comprehensive energy system based on carbon trading has important significance along with the development of a carbon trading market. The existing energy system optimization method does not always consider the problem of carbon dioxide emission, does not perform optimization operation based on carbon trading, and is not ideal in optimization effect.
Disclosure of Invention
The invention provides an energy system double-layer operation optimization method and system based on stepped carbon trading to solve the problems.
According to some embodiments, the invention adopts the following technical scheme:
a double-layer operation optimization method of an energy system based on stepped carbon trading comprises the following steps:
acquiring energy data of the comprehensive energy system;
establishing a comprehensive energy system optimization model by using energy data;
obtaining an operation optimization strategy by utilizing a comprehensive energy system optimization model, a particle swarm algorithm and a linear programming method;
the method comprises the steps of establishing an integrated energy system optimization model, dividing each main body of the integrated energy system into three layers, and establishing an upper-layer main body optimization model and a lower-layer main body optimization model, wherein the upper-layer main body optimization model comprises an upper-layer energy supplier optimization model and a lower-layer user optimization model.
Further, the energy data comprises electric energy price, wind power and photovoltaic data and cold, heat, electricity and gas energy data required by a user.
Further, the establishing of the comprehensive energy system optimization model further comprises the step of setting a carbon trading mechanism in a middle carbon emission trading center.
Further, the carbon transaction mechanism comprises a ladder carbon transaction mechanism facing the energy supplier and a reward transaction mechanism facing the user.
Furthermore, each main body of the comprehensive energy system is divided into three layers, and specifically comprises an upper-layer energy supplier, a middle-layer carbon emission trading center and a lower-layer flexible user.
Further, the operation optimization strategy is obtained by utilizing the comprehensive energy system optimization model, the particle swarm optimization and the linear programming method, and the operation optimization strategy comprises the step of solving the upper-layer energy supplier optimization model by utilizing the particle swarm optimization to obtain the decision variables of the upper-layer energy supplier optimization model.
Further, the operation optimization strategy is obtained by utilizing the comprehensive energy system optimization model, the particle swarm optimization and the linear programming method, and the decision variables are obtained by utilizing the linear programming to solve the lower-layer user optimization model.
A double-layer operation optimization system of an energy system based on stepped carbon trading comprises:
a data acquisition module configured to acquire energy data of the integrated energy system;
an optimization module configured to build an integrated energy system optimization model using the energy data;
the computing module is configured to obtain decision variables by utilizing a comprehensive energy system optimization model, a particle swarm algorithm and a linear programming method;
the method for establishing the comprehensive energy system optimization model comprises the steps of dividing each main body of the comprehensive energy system into three layers, and establishing each main body optimization model which comprises an upper-layer energy supplier optimization model and a lower-layer user optimization model.
A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method for dual-tier operation optimization of an energy system based on ladder carbon trading.
A terminal device comprising a processor and a computer readable storage medium, the processor being configured to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the energy system double-layer operation optimization method based on the ladder carbon trading.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, a carbon transaction mechanism is considered on the energy supply side, so that the emission of carbon dioxide in the use of energy can be effectively reduced, and the system can run more cleanly and efficiently; a carbon transaction mechanism based on a reward mechanism is considered on the demand side, so that the energy cost, the energy consumption and the carbon dioxide emission of a user can be effectively reduced; the invention adopts a double-layer optimization mode, simultaneously considers the capacity mode of energy suppliers and the energy utilization requirement of users, and greatly improves the economical efficiency and the environmental protection property of system operation.
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The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
FIG. 1 is an architectural diagram of the present embodiment;
fig. 2 is a flow chart of the particle swarm algorithm of the present embodiment.
The specific implementation mode is as follows:
the invention is further described with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. 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 application 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 example embodiments according to the present application. 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.
Example 1.
As shown in fig. 1, a method for optimizing the double-layer operation of an energy system based on a stepped carbon trading includes:
acquiring energy data of the comprehensive energy system;
establishing a comprehensive energy system optimization model by using energy data;
obtaining an operation optimization strategy by utilizing a comprehensive energy system optimization model, a particle swarm algorithm and a linear programming method;
the method comprises the steps of establishing an integrated energy system optimization model, dividing each main body of the integrated energy system into three layers, and establishing each main body optimization model which comprises an upper-layer energy supplier optimization model and a lower-layer user optimization model.
The energy data comprises electric energy price, wind power and photovoltaic data and cold, heat, electricity and gas energy data required by a user.
The establishment of the comprehensive energy system optimization model further comprises the step of arranging a carbon trading mechanism in the middle carbon emission trading center.
The carbon transaction mechanism comprises a ladder carbon transaction mechanism facing the energy supplier and a reward transaction mechanism facing the user.
Each main body of the comprehensive energy system is divided into three layers, and specifically comprises an upper-layer energy supplier, a middle-layer carbon emission trading center and a lower-layer flexible user.
The operation optimization strategy is obtained by utilizing the comprehensive energy system optimization model, the particle swarm algorithm and the linear programming method, and the operation optimization strategy comprises the step of solving the upper-layer energy supplier optimization model by utilizing the particle swarm algorithm to obtain the decision variables of the upper-layer energy supplier optimization model.
The method comprises the steps of obtaining an operation optimization strategy by utilizing an integrated energy system optimization model, a particle swarm algorithm and a linear programming method, and solving a lower-layer user optimization model by utilizing the linear programming to obtain a decision variable of the lower-layer user optimization model.
In particular, the method comprises the following steps of,
a double-layer operation optimization method of an energy system based on stepped carbon trading comprises the following steps:
step 1, dividing each main body in the comprehensive energy system into three layers, establishing mathematical models of the main bodies of an upper layer and a lower layer, and making a foundation for further establishing a system optimization model. The system double-layer optimization block diagram is shown in figure 1.
And 2, setting a carbon transaction mechanism, and establishing an upper main body optimization model and a lower main body optimization model of the system.
And 3, solving decision variables of each main body of the upper layer and the lower layer by adopting a particle swarm algorithm and linear programming on the upper layer and the lower layer.
In the step 1, each main body of the comprehensive energy system is divided into three layers, namely an upper-layer energy supplier, namely a combined cooling heating and power system, and supplies cooling and heating energy to users through an energy conversion technology at the same time, and the output condition of each device of the system is formulated according to economy; the middle layer is a carbon emission trading center, and mainly establishes a step carbon trading mechanism for an upper-layer energy supplier and a reward carbon trading mechanism for a lower-layer user; the lower layer is flexible users, and user demand response strategies are formulated mainly according to energy prices.
And (3) the mathematical models of all the subjects in the step 1 are mainly mathematical models of upper-layer energy suppliers and lower-layer users. The internal mathematical model of the upper-layer energy supplier is mainly an equipment model of a gas turbine, a waste heat recovery device, a gas boiler, an absorption refrigerator and an electric refrigerator.
The gas turbine model can be expressed by the relationship between the generating efficiency and the output electric power as follows:
in the formula (I), the compound is shown in the specification,
in order to achieve the power generation efficiency of the gas turbine,
and PnElectric power output and rated power output for the gas turbine are provided.
The waste heat generated by the gas turbine can be recycled by recovery, and the mathematical model of the recovered waste heat is as follows:
in the formula eta1Is the gas turbine heat dissipation loss coefficient.
The absorption refrigerator converts the recovered waste heat of the gas turbine into cold energy and outputs cold power
The model is as follows:
in the formula etacThe refrigerating efficiency of the absorption type refrigerator is improved.
The waste heat recovery device converts the waste heat of the gas turbine to supply heat load and outputs heat power
Comprises the following steps:
in the formula etahIs the thermal efficiency of the waste heat recovery equipment.
The electric refrigerator consumes electric energy to provide insufficient cold energy, and the mathematical model of the electric refrigerator is as follows:
in the formula (I), the compound is shown in the specification,
the refrigerating capacity of the electric refrigerating machine at the moment t,
consuming electrical energy, COP, for electric refrigerationecIs the refrigeration coefficient of the electric refrigerator.
The mathematical model of the lower layer user is a demand response model of the user, and the electrical load comprises a fixed electrical load and a translatable electrical load, and can be expressed as:
in the formula (I), the compound is shown in the specification,
for a fixed load at time t,
representing a translatable load, a user can adjust the time and power of electricity consumption according to the energy price, and the following constraints are required to be met:
in the formula (I), the compound is shown in the specification,
upper limit of translatable load at time t, WselThe total amount of translatable load over the T time periods.
The thermal load also comprises two parts, namely a fixed thermal load and a reducible thermal load, as follows:
in the formula (I), the compound is shown in the specification,
for a fixed thermal load at time t,
representing that the thermal load can be cut, the following constraints need to be satisfied:
in the formula (I), the compound is shown in the specification,
the upper limit of the thermal load at time t can be reduced.
The carbon transaction mechanism in the step 2 comprises a ladder carbon transaction mechanism facing the energy supplier and a reward transaction mechanism facing the user. The step carbon trading mechanism adopts a gratuitous carbon emission quota mechanism, when the total carbon emission of the system exceeds the carbon emission quota, corresponding carbon emission quota needs to be purchased, and when the total carbon dioxide emission of the system is lower than the carbon emission quota, the redundant carbon emission quota can be sold to obtain the income, namely the model can be expressed as follows:
in the formula, CctcIs the carbon transaction cost; eaCarbon emission allowance for energy providers; c. CcAnd cfTrading prices for carbon emissions when the carbon emissions quota is less than and exceeded, respectively; Δ E is a single value interval in which the carbon emission quota is increased; δ is the carbon emission right trade price rate exceeding the carbon emission quota portion.
The actual carbon emission of the system mainly comes from a gas turbine, a gas boiler and a power grid in a combined cooling heating and power system, and can be expressed as follows:
in the formula, gammaiIs the carbon emission coefficient of the ith carbon dioxide emission source,
the output power of the ith carbon dioxide emission source at the moment t.
The rewarding carbon transaction mechanism at the user side is that when the carbon dioxide emission amount generated corresponding to the total energy power used by the user is less than the carbon dioxide quota, a certain welfare reward can be performed on the user, and the welfare reward can be expressed as:
Cctl＝α(Eal-E0l)
in the formula, EalCarbon emission quota for user, E0lIs the actual total carbon dioxide emission of the user, which can be expressed as:
in the formula, betaiA reward factor for the carbon emissions of the user,
the ith energy source power used by the user at time t.
The optimization model in step 2 is mainly an optimization objective of an upper-layer energy provider and an optimization objective of a user, and the optimization objective of the energy provider can be expressed as:
in the formula (I), the compound is shown in the specification,
the cost of consuming natural gas for energy suppliers,
the cost of purchasing electrical energy from the grid for an energy provider,
and the operation and maintenance cost of each device of the energy supplier.
The cost of fuel consumed by the gas turbine and the gas boiler when operating can be expressed in the form of a quadratic function, that is:
in the formula (I), the compound is shown in the specification,
and
the output electric power of the gas turbine and the output thermal power of the boiler at the moment t are respectively; a ise，be，ce(ah，bh，ch) Is a cost factor of the gas turbine (boiler).
The power grid purchase cost can be expressed as:
the system operation and maintenance cost can be expressed as:
in the formula, muiThe operating maintenance cost coefficient for the ith device of the energy supplier,
power is output for the energy source of the ith device.
The optimization goal of the user is to minimize the total cost of energy used by the user, which can be expressed as:
in the formula (I), the compound is shown in the specification,
the cost of purchasing electrical energy for the user,
the cost of purchasing thermal energy for the user,
the cost for the user to participate in the demand response can be expressed as:
in the formula (I), the compound is shown in the specification,
is the price of cold, heat, electricity and gas energy,
using the power of cold, heat, electricity and gas energy sources for the user at t momenteAnd muhThe discomfort factor for electrical load transfer and thermal load shedding, respectively.
The particle swarm algorithm in the step 3 is specifically shown in a flow chart in fig. 2, and the linear programming solution is realized by a CPLEX solver.
Example 2.
A double-layer operation optimization system of an energy system based on stepped carbon trading comprises:
a data acquisition module configured to acquire energy data of the integrated energy system;
an optimization module configured to build an integrated energy system optimization model using the energy data;
the computing module is configured to obtain decision variables by utilizing a comprehensive energy system optimization model, a particle swarm algorithm and a linear programming method;
the method comprises the steps of establishing an integrated energy system optimization model, dividing each main body of the integrated energy system into three layers, and establishing each main body optimization model which comprises an upper-layer energy supplier optimization model and a lower-layer user optimization model.
Example 3.
A computer-readable storage medium, wherein a plurality of instructions are stored, and the instructions are adapted to be loaded by a processor of a terminal device and execute a method for optimizing double-layer operation of an energy system based on a ladder carbon trading provided by the embodiment.
Example 4.
A terminal device comprising a processor and a computer readable storage medium, the processor being configured to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the energy system double-layer operation optimization method based on the ladder carbon trading provided by the embodiment.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application 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, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. 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.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. A double-layer operation optimization method of an energy system based on stepped carbon trading is characterized by comprising the following steps:
acquiring energy data of the comprehensive energy system;
establishing a comprehensive energy system optimization model by using energy data;
obtaining an operation optimization strategy by using a comprehensive energy system optimization model, a particle swarm algorithm and a linear programming method;
the method for establishing the comprehensive energy system optimization model comprises the steps of dividing each main body of the comprehensive energy system into three layers, and establishing each main body optimization model which comprises an upper-layer energy supplier optimization model and a lower-layer user optimization model.
2. The double-layer operation optimization method for the energy system based on the ladder carbon trading is characterized in that the energy data comprises electric energy prices, wind power and photovoltaic data and cold, heat, electricity and gas energy data required by a user.
3. The method as claimed in claim 2, wherein the step carbon trading-based energy system double-layer operation optimization method further comprises the step carbon emission trading center setting a carbon trading mechanism.
4. The method of claim 3, wherein the carbon trading mechanism comprises a ladder carbon trading mechanism facing the energy supplier and a reward trading mechanism facing the user.
5. The double-layer operation optimization method for the energy system based on the stepped carbon trading as claimed in claim 4, wherein each main body of the integrated energy system is divided into three layers, and specifically comprises an upper-layer energy supplier, a middle-layer carbon emission trading center and a lower-layer flexible user.
6. The double-layer operation optimization method for the energy system based on the stepped carbon trading as claimed in claim 5, wherein the obtaining of the operation optimization strategy by using the comprehensive energy system optimization model and the particle swarm algorithm and the linear programming method comprises solving the upper energy supplier optimization model by using the particle swarm algorithm to obtain the decision variables of the upper energy supplier optimization model.
7. The double-layer operation optimization method for the energy system based on the stepped carbon trading of claim 6, wherein the operation optimization strategy is obtained by using a comprehensive energy system optimization model, a particle swarm algorithm and a linear programming method, and further comprising the step of solving a lower-layer user optimization model by using linear programming to obtain decision variables of the lower-layer user optimization model.
8. A double-deck operation optimization system of energy system based on ladder carbon transaction, characterized by, includes:
a data acquisition module configured to acquire energy data of the integrated energy system;
an optimization module configured to build an integrated energy system optimization model using the energy data;
the computing module is configured to obtain decision variables by utilizing a comprehensive energy system optimization model, a particle swarm algorithm and a linear programming method;
the method comprises the steps of establishing an integrated energy system optimization model, dividing each main body of the integrated energy system into three layers, and establishing each main body optimization model which comprises an upper-layer energy supplier optimization model and a lower-layer user optimization model.
9. A computer-readable storage medium having stored thereon a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method for dual-tier operation optimization of an energy system based on ladder carbon trading as claimed in any one of claims 1 to 7.
10. A terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the energy system double-layer operation optimization method based on the ladder carbon trading in any one of claims 1-7.
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| CN114707776A (en) * | 2022-06-08 | 2022-07-05 | 山东暖谷新能源环保科技有限公司 | Carbon emission double control-based low-carbon energy consumption optimization system and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114707776A (en) * | 2022-06-08 | 2022-07-05 | 山东暖谷新能源环保科技有限公司 | Carbon emission double control-based low-carbon energy consumption optimization system and method |
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