CN116845989A - Self-energy cluster double-layer distributed cooperative control method based on asynchronous dynamic event triggering - Google Patents
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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Abstract
A self-energy cluster double-layer distributed cooperative control method based on asynchronous dynamic event triggering, the method comprising: constructing a self-energy cluster control model based on multiple intelligent agents, wherein the model is used for describing a self-energy cluster distributed control framework; designing a heterogeneous energy network output control strategy based on a multi-agent consistent control method; according to the multi-source heterogeneous characteristics of the self-energy cluster, a dynamic event triggering communication protocol is designed; an internal device control strategy based on the "carbon-energy" mix price is established. The invention solves the problems of low carbon and safe operation of the comprehensive energy system of the self-energy cluster based on the double-layer distributed cooperative control method triggered by the asynchronous dynamic event, and the proposed control method can simultaneously have the characteristics of asynchronous communication, dynamic regulation, distributed implementation and the like, thereby ensuring the safe operation of the system and simultaneously effectively improving the economical efficiency and low carbon environmental protection of the system operation.
Description
Technical Field
The invention belongs to the technical field of cooperative control of energy systems, and particularly relates to a self-energy cluster double-layer distributed cooperative control method based on asynchronous dynamic event triggering.
Background
Environmental problems caused by exhaustion of fossil energy are increasingly attracting worldwide attention, so that a series of new technologies such as new energy technologies are also driven to be researched and popularized, and the safe, efficient and clean development of a comprehensive energy system is imperative. And how to realize the efficient coordination of internal multi-source heterogeneous energy, and complete the full fusion of links such as transverse development, conversion, storage, transportation, utilization and the like in a comprehensive energy system, thereby effectively meeting the energy demands of terminals and improving the energy utilization efficiency. The self-energy cluster with important characteristics such as full duplex, distributed, intelligent and the like is an important means for promoting the consumption of renewable energy sources, improving the energy utilization efficiency, promoting the carbon neutralization and realizing the carbon peak goal. At present, domestic and foreign scholars study on the safety, the high efficiency and the cleanness of a comprehensive energy system mainly from the modeling and the optimized operation of an energy junction and a self-energy source. However, for the low-carbon safe operation of the integrated energy system, little discussion and research has been done from the viewpoint of cooperative control of the energy units. With rapid development of information technology and expansion of engineering scale of practical energy systems, the problem of cooperative control of complex networks is attracting great attention. And as the development of the comprehensive energy system tends to be complicated and flexible, how to realize intelligent coordinated control of the comprehensive energy system through distributed cooperative control has important significance for improving the safety and reliability of the system operation.
Currently, the method for cooperatively controlling a complex system is mostly limited to a single electric energy network, and the mutual coupling of multiple energy networks is not considered sufficiently. Meanwhile, the influence of parameters such as line impedance and the like can lead to failure in parameter recovery after the system is distributed according to the capacity proportion.
Disclosure of Invention
Aiming at the bottleneck problem, the self-energy cluster double-layer distributed cooperative control method based on asynchronous dynamic event triggering provides a new solution, and can realize accurate regulation and control of the comprehensive energy system by dynamic regulation of asynchronous communication on the basis of a self-energy model in consideration of the multi-energy coupling characteristic of the system, so that safe, efficient and clean operation of the comprehensive energy system is realized.
Aiming at the defects of the prior art, the invention provides a self-energy cluster double-layer distributed cooperative control method based on asynchronous dynamic event triggering, which comprises the following steps:
step 1: constructing a self-energy cluster control model based on multiple intelligent agents, wherein the model is used for describing a self-energy cluster distributed control framework;
step 2: constructing a heterogeneous energy network output control strategy based on a multi-agent consistent control method;
step 2-1: based on a classical power network structure, designing an electric energy output strategy of the self-energy source;
step 2-1-1: based on a classical power network structure, a primary control strategy for electric energy output of self-energy is designed, and is expressed as follows:
wherein e represents electric energy, L e And L eN The actual power and rated power, k, of the electric energy output from the energy source i respectively q Regulating parameters of electric energy output, f N And f is the actual frequency and the rated frequency of the power grid detection respectively, τ i Is the time constant of the low pass filter.
Step 2-1-2: the electric energy output secondary control strategy designed from the energy source based on the dynamic consistent frequency control is expressed as follows:
in the method, in the process of the invention,the proportional gains of the proposed controllers, respectively. i, j represent different nodes, respectively. u represents the control adjustment amount. a, a ij The connection relationship between the self-energy agents is reflected for the elements in the adjacency matrix. />Representing a tracking frequency mismatch term to a neighboring node. g fi Is the virtual leader frequency gain.
Step 2-2: according to the characteristics of the central heating subnetwork, designing a heat energy output control strategy of the self-energy source;
step 2-2-1: according to the characteristics of the central heating subnetwork, a heat output primary control strategy is designed and expressed as follows:
wherein h represents heat energy, L h And L hN Representing the actual power and the rated power of the output heat energy from the energy source, respectively. k (k) p Is a regulating parameter for controlling heat energy. p and p N Representing the actual outlet pressure and rated outlet pressure of the system respectively.
Step 2-2-2: design of a heat output self-adaptive secondary control method based on multi-agent consistency method and utilization of heat output powerTo construct a first order linear multi-agent dynamic system and to design a corresponding consistent control protocol. Let->The expression is as follows:
u Hi ＝-R H q Hi
wherein R is H Coupling gain for thermal power, q Hi Representing the local neighbor thermal power allocation error. Further, the thermal power distribution error needs to satisfy the following:
wherein a is ij The connection relationship between the self-energy agents is reflected for the elements in the adjacency matrix. The consistent protocol of the proposed control method is set as:
in the method, in the process of the invention,and p i The pressure and the outlet pressure are estimated from the energy source i, respectively. R is R p Is the coupling gain.
Step 3: according to the multi-source heterogeneous characteristics of the self-energy cluster, a dynamic event triggering communication protocol is designed;
step 3-1: design a distributed power agreement protocol based on an asynchronous event trigger mechanism, letting dh=h/k p The expression is as follows:
in the subscriptRefer to heat output powerThe last event controlled triggers the moment to the current moment t, -, the>And is similarly the latest event trigger time to current time t of the electric output power control. R is R e For coupling gain of electric power, in a protocol design considering an event trigger mechanism, each event detector of the self energy source needs to determine update time of control action by using sampling information.
Step 3-2: the distributed power event trigger condition is designed as follows:
in sigma i And ρ i Is a positive scalar.And->The power distribution deviation between the current moment and the latest event triggering moment is respectively thermal power and electric power.
Step 3-3: designing a distributed frequency and pressure consistency protocol based on an asynchronous event triggering mechanism, wherein the distributed frequency consistency protocol is expressed as follows:
in the method, in the process of the invention,for frequency control from the most recent event trigger time to the current time t.
The distributed pressure agreement protocol is expressed as follows:
in the method, in the process of the invention,controlling the pressure from the latest event triggering time to the current time t;
step 3-4: designing a distributed frequency and pressure consistency protocol event trigger condition, wherein the frequency consistency protocol trigger condition is expressed as follows:
in the method, in the process of the invention,the conditional gain is triggered for the frequency of the self-energy i. The pressure agreement protocol trigger conditions are expressed as follows:
step 4: establishing an internal equipment control strategy based on a carbon-energy mixed price;
step 4-1: considering that electric and thermal loads are involved in energy sources, the "carbon-energy" mixed price is designed as follows:
in Pr, pr buy Is a "carbon-energy" mixed price that is considered from the consumer side to represent the price of purchasing energy from the energy source network, thereby facilitating the purchase of low carbon energy from the energy source. The variable m represents the form of energy contained in the self-energy source.Price is traded for normal energy markets. Gamma is carbon emission tax. />Is the carbon emission intensity of the energy source.
Step 4-2: the carbon emission intensity of the designed electric energy is expressed as:
wherein P is H P R For the electric output power of the power generation equipment and the renewable energy power generation equipment, P E Injecting power into the line c H Is the carbon emission intensity of the power generation equipment, which is a parameter determined by the power generation state, c E Is the line carbon emission intensity.
Step 4-3: the objective function design of the self-energy inner layer optimization control strategy considering low-carbon operation is as follows:
in Pr, pr sell Representing the price of selling energy from an energy network, P buy 、P sell Respectively representing the energy purchased from the energy source to the energy network and the energy sold. b represents different energy forms such as electricity, heat and the like.
Drawings
FIG. 1 is a schematic view of a self-energy structure according to an embodiment of the present invention;
FIG. 2 is a diagram of a self-powered cluster operation architecture according to an embodiment of the present invention;
fig. 3 is a flowchart of a self-energy cluster dual-layer distributed cooperative control method according to an embodiment of the present invention.
Detailed Description
The following describes specific embodiments of the present invention in detail with reference to the drawings.
The self-energy system based on the self-energy cluster double-layer distributed cooperative control method triggered by the asynchronous dynamic event in the embodiment comprises an energy exchange area and an energy port, wherein the energy exchange area comprises an energy transmission network, a load unit, a power generation unit, an energy storage unit and an energy conversion unit, and the energy port is connected with the corresponding energy network, as shown in fig. 1. The running structure diagram of the self-energy cluster is shown in fig. 2, and a plurality of self-energy sources acquire or sell energy sources from an energy network and are regulated through internal equipment of the self-energy sources to meet the load demand
The energy supply intelligent agent is a static intelligent agent corresponding to the energy supply side of the comprehensive energy system, monitors the energy supply condition of the energy supply side in real time, and responds to the control signal of the self-energy intelligent agent to calculate the power flow distribution between the self-energy and the power supply side. And adjusting the functional device according to the coordination control signals of the self-energy intelligent agent or the comprehensive management intelligent agent so as to ensure the energy supply of the respective energy sources.
The self-energy intelligent agent is a static intelligent agent corresponding to self-energy and is used for realizing distributed coordination control among the self-energy. The control targets of the respective energy sources are realized through adjustment, and the safe and stable operation of the comprehensive energy system is supported.
The comprehensive management agent is a virtual dynamic agent for maintaining a catalog of agents in the comprehensive energy system.
The advisory services agent is a virtual dynamic agent that maintains a catalog of agents and services that they can provide to other agents.
The self-energy cluster double-layer distributed cooperative control method based on asynchronous dynamic event triggering is carried out by adopting the self-energy system, the overall flow is shown in figure 3, and the method specifically comprises the following steps:
step 1: constructing a self-energy cluster control model based on multiple intelligent agents, and ensuring the full connection of the internal communication of the self-energy clusters by using a communication test, wherein the model is used for describing a self-energy cluster distributed control framework;
step 2: constructing a heterogeneous energy network output control strategy based on a multi-agent consistent control method;
step 2-1: based on a classical power network structure, designing an electric energy output strategy of the self-energy source;
step 2-1-1: based on a classical power network structure, a primary control strategy for electric energy output of self-energy is designed, and is expressed as follows:
L e ＝L eN +k q (f N -f)
in the method, in the process of the invention,representation pair L ei Solving first order derivative, L e And L eN The actual power and rated power, k, of the electric energy output from the energy source i respectively q For regulating parameters of electric energy output, f N And f is the actual frequency and the rated frequency of the power grid detection respectively. With a low pass filter, the primary control strategy can be further described as follows:
wherein τ i Is the time constant of the low pass filter.
The electric energy regulation parameters of the respective energy sources are designed according to the rated output power of the self-energy source electricity, and are expressed as follows:
wherein e represents electric energy, k iq For regulating parameters of electric energy output from energy source i, L eiN And d is a constant, which is the rated power of the electric energy output from the energy source i. In order to ensure the proportional distribution of the load, the ratio of the rated power output of the power of each energy source in the network to the power control adjustment parameter is a constant d.
Step 2-1-2: the electric energy output secondary control strategy designed from the energy source based on the dynamic consistent frequency control is expressed as follows:
in the method, in the process of the invention,is an input for power output control. Further, the expression is as follows:
wherein u is d In the form of an electrical power controller,representation pair u d First order derivative is obtained. />α i β i The proportional gains of the proposed controllers, respectively. i, j represent different nodes, respectively. u represents the control adjustment amount. a, a ij The connection relationship between the self-energy agents is reflected for the elements in the adjacency matrix. />Representing a tracking frequency mismatch term to a neighboring node. g fi Is the virtual leader frequency gain. f (f) ref The frequency, which is the virtual leader frequency, should be the reference value for the recovery frequency.
Step 2-2: according to the characteristics of the central heating subnetwork, designing a heat energy output control strategy of the self-energy source;
step 2-2-1: according to the characteristics of the central heating subnetwork, a heat output primary control strategy is designed and expressed as follows:
wherein h represents heat energy, L h And L hN Respectively represent the actual output heat energy of the self-energy sourceThe actual power and the rated power. k (k) p Is a regulating parameter for controlling heat energy. p and p N Representing the actual outlet pressure and rated outlet pressure of the system respectively.
To achieve a volumetric distribution of the heat load, the heat energy from the energy source is adjusted by a parameter k p The adjustment is carried out according to the following relation:
step 2-2-2: design of a heat output self-adaptive secondary control method based on multi-agent consistency method and utilization of heat output powerTo construct a first order linear multi-agent dynamic system and to design a corresponding consistent control protocol. Let->The system dynamics model can be expressed as:
in the method, in the process of the invention,for parameter H i U Hi The thermal power mismatch item is set according to the information of each neighbor self energy source and the self information, and can be expressed as follows:
u Hi ＝-R H q Hi
wherein R is H Coupling gain for thermal power, q Hi Representing the local neighbor thermal power allocation error. Further, the thermal power distribution error needs to satisfy the following:
wherein a is ij The connection relationship between the self-energy agents is reflected for the elements in the adjacency matrix.
In addition, the thermal power mismatch term is fed back to a Proportional Integral (PI) controller D i (s) and thereby generating a correction term δH i The heat output primary control strategy is adjusted as follows:
δH i ＝D i (s)u Hi
because the pipe impedances of the respective energy sources are different, the outlet pressures of the respective energy sources cannot be controlled to be the same value, and the outlet pressures of the respective energy sources are controlled to be within an acceptable rated pressure range. The consistency protocol of the proposed pressure control method is set as follows:
in the method, in the process of the invention,and p i The pressure and the outlet pressure are estimated from the energy source i, respectively. R is R p Is the coupling gain.
Pressure difference u pi Can be estimated from the estimated pressureReference pressure p to central heating network ref And (3) determining:
and feeding back the correction term to the PI controller to obtain a correction term:
δp i ＝G i (s)u pi
step 3: according to the multi-source heterogeneous characteristics of the self-energy cluster, a dynamic event triggering communication protocol is designed;
each self-energy source needs to interact its own information with the neighboring nodes to form a control strategy, but the updating of its control actions is not necessarily periodic.
Step 3-1: design a distributed power agreement protocol based on an asynchronous event trigger mechanism, letting dh=h/k p The expression is as follows:
in the subscriptIndicating the latest event trigger time to the current time t,/for thermal output power control>And is similarly the latest event trigger time to current time t of the electric output power control. R is R e For coupling gain of electric power, in a protocol design considering an event trigger mechanism, each event detector of the self energy source needs to determine update time of control action by using sampling information.
Step 3-2: the distributed power event trigger condition is designed as follows:
in sigma i And ρ i Is a positive scalar.
Step 3-3: designing a distributed frequency and pressure consistency protocol based on an asynchronous event triggering mechanism, wherein the distributed frequency consistency protocol is expressed as follows:
in the method, in the process of the invention,for frequency control from the most recent event trigger time to the current time t.
The distributed pressure agreement protocol is expressed as follows:
in the method, in the process of the invention,controlling the pressure from the latest event triggering time to the current time t;
step 3-4: designing a distributed frequency and pressure consistency protocol event trigger condition, wherein the frequency consistency protocol trigger condition is expressed as follows:
in the method, in the process of the invention,the conditional gain is triggered for the frequency of the self-energy i. The pressure agreement protocol trigger conditions are expressed as follows:
step 4: establishing an internal equipment control strategy based on a carbon-energy mixed price;
step 4-1: considering that electric and thermal loads are involved in energy sources, the "carbon-energy" mixed price is designed as follows:
in Pr, pr buy Is a "carbon-energy" mixed price that is considered from the consumer side to represent the price of purchasing energy from the energy source network, thereby facilitating the purchase of low carbon energy from the energy source. The variable m represents the form of energy contained in the self-energy source.Price is traded for normal energy markets. Gamma is carbon emission tax. />Is the carbon emission intensity of the energy source.
Step 4-2: the carbon emission intensity of the designed electric energy is expressed as:
wherein P is H ，P R For the electric output power of the power generation equipment and the renewable energy power generation equipment, P E Injecting power into the line c H Is the carbon emission intensity of the power generation equipment, which is a parameter determined by the power generation state, c E Is the line carbon emission intensity.
Step 4-3: the objective function design of the self-energy inner layer optimization control strategy considering low-carbon operation is as follows:
wherein Ω represents the total gain of the objective function, pr sell Representing the price of selling energy from an energy network, P buy 、P sell Respectively representing the energy purchased from the energy source to the energy network and the energy sold. b represents different energy forms such as electricity, heat and the like.
Step 4-4: and designing inner-layer optimization control operation constraint of the self-energy source. Wherein the equality constraint includes a relationship between port output and plant output, for a self-energy source comprising a cogeneration unit, a solid state transformer, an electric boiler, a gas boiler, etc., expressed as follows:
wherein e, g and h respectively represent three energy sources of electricity, gas and heat, and SST, CHP, boil, fur respectively represent a solid-state transformer, a cogeneration unit, an electric heating boiler and a gas boiler. The relationship between plant output and self-energy input is expressed as follows:
where η represents the conversion efficiency of the corresponding energy source of the corresponding device. Epsilon represents the distribution coefficient of the corresponding energy source. In addition, the operating characteristics and operating constraints are different according to the type of the device, and the output limit of the maximum capacity and the minimum capacity of the device needs to be met.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (7)
1. The double-layer distributed cooperative control method of the self-energy cluster based on the asynchronous dynamic event triggering is characterized by comprising the following steps of:
step 1: constructing a self-energy cluster control model based on multiple intelligent agents, wherein the model is used for describing a self-energy cluster distributed control framework;
step 2: constructing a heterogeneous energy network output control strategy based on a multi-agent consistent control method;
step 3: according to the multi-source heterogeneous characteristics of the self-energy cluster, a dynamic event triggering protocol is designed;
step 4: and establishing a self-energy internal equipment control strategy based on the carbon-energy mixed price.
2. The method according to claim 1, wherein the multiple agents in step 1 specifically include an energy supply agent, an integrated management agent, and a consultation service agent, the energy supply agent is a static agent corresponding to an energy supply side of the integrated energy system, the energy supply condition of the energy supply side is monitored in real time, a power flow distribution between the energy supply side and the self energy source is calculated in response to a control signal of the energy supply agent, and the function device is adjusted according to a coordination control signal of the self energy agent or the integrated management agent to ensure energy supply of respective energy sources, the self energy source agent is a static agent corresponding to the self energy sources, for realizing distributed coordination control between the self energy sources, the integrated management agent is a virtual dynamic agent for maintaining a directory of the various agents in the integrated energy system, and the consultation service agent is a virtual agent for providing the dynamic agent and other maintenance service agent to the user.
3. The method for controlling the self-energy cluster double-layer distributed cooperation based on the asynchronous dynamic event triggering according to claim 1, wherein the step 2 is characterized by constructing a heterogeneous energy network output control strategy based on a multi-agent consistent control method, and specifically comprises the following steps:
step 2-1: based on a classical power network structure, designing an electric energy output strategy of the self-energy source;
step 2-2: according to the characteristics of the central heating subnetwork, a heat energy output control strategy of the self-energy source is designed.
4. The method for controlling self-energy cluster double-layer distributed cooperation based on asynchronous dynamic event triggering according to claim 2, wherein the step 2-1 specifically comprises the following steps:
step 2-1-1: based on a classical power network structure, a primary control strategy for electric energy output of self-energy is designed, and is expressed as follows:
in the method, in the process of the invention,representation pair L ei Solving a first order derivative, wherein e represents electric energy, L e And L eN The actual power and rated power, k, of the electric energy output from the energy source i respectively q Regulating parameters of electric energy output, f N And f is the actual frequency and the rated frequency of the power grid detection respectively, τ i A time constant that is a low pass filter;
step 2-1-2: the electric energy output secondary control strategy designed from the energy source based on the dynamic consistent frequency control is expressed as follows:
wherein u is ei In the form of an electrical power controller,representation pair u ei First order derivative->α i β i Proportional gains of the proposed controllers, i, j representing different nodes, u representing the control adjustment quantity, a ij For the elements in the adjacency matrix, reflecting the connection relationship between the self-energy agents, ++>Represents a tracking frequency mismatch term, g, to a neighboring node fi For virtual leader frequency gain, f ref Frequency of virtual leaderThe value of which should be the reference value for the recovery frequency.
5. The method for controlling self-energy cluster double-layer distributed cooperation based on asynchronous dynamic event triggering according to claim 2, wherein the step 2-2 specifically comprises the following steps:
step 2-2-1: according to the characteristics of the central heating subnetwork, a heat output primary control strategy is designed and expressed as follows:
wherein h represents heat energy, L h And L hN Respectively representing the actual power and the rated power, k, of the output heat energy from the energy source p For regulating parameters of thermal energy control, p and p N Representing the actual water outlet pressure and rated water outlet pressure of the system respectively;
step 2-2-2: design of a heat output self-adaptive secondary control method based on multi-agent consistency method and utilization of heat output powerTo construct a first-order linear multi-agent dynamic system and design a corresponding consistent control protocol to enable +.>The expression is as follows:
u Hi ＝-R H q Hi
wherein u is Hi Is a thermal power controller, R H Coupling gain for thermal power, q Hi Representing the local neighbor thermal power allocation error, further, the thermal power allocation error needs to satisfy the following:
wherein a is ij For the elements in the adjacency matrix, reflecting the connection relation between the self-energy intelligent agents, the consistent control protocol of the proposed secondary control method is set as follows:
in the method, in the process of the invention,and p i Estimated pressure and outlet pressure from energy source i, R p Is the coupling gain.
6. The method for controlling the self-energy cluster double-layer distributed cooperative control based on the asynchronous dynamic event triggering according to claim 1, wherein the step 3 specifically comprises the following steps:
step 3-1: design a distributed power agreement protocol based on an asynchronous event trigger mechanism, letting dh=h/k p The expression is as follows:
in the subscriptIndicating the latest event trigger time to the current time t,/for thermal output power control>The latest event triggering time to the current time t, R which is controlled by electric output power e For coupling gain of electric power, in the protocol design considering the event trigger mechanism, each self-energy event detector needs to determine the update time of the control action by using sampling information;
step 3-2: the distributed power event trigger condition is designed as follows:
in sigma i And ρ i Is a positive scalar;
step 3-3: designing a distributed frequency consistency protocol and a pressure consistency protocol based on an asynchronous event triggering mechanism, wherein the distributed frequency consistency protocol is expressed as follows:
in the method, in the process of the invention,controlling the frequency from the latest event triggering time to the current time t;
the distributed pressure agreement protocol is expressed as follows:
in the method, in the process of the invention,controlling the pressure from the latest event triggering time to the current time t;
step 3-4: designing event trigger conditions of a distributed frequency consistency protocol and a pressure consistency protocol, wherein the event trigger conditions of the frequency consistency protocol are expressed as follows:
in the method, in the process of the invention,is self-energyi frequency trigger condition gain, pressure consistent protocol trigger condition is expressed as follows:
7. the method for controlling the self-energy cluster double-layer distributed cooperative control based on the asynchronous dynamic event triggering according to claim 1, wherein the step 4 establishes a self-energy internal equipment control strategy based on a 'carbon-energy' mixed price, and specifically comprises the following steps:
step 4-1: considering that electric and thermal loads are involved in energy sources, the "carbon-energy" mixed price is designed as follows:
in Pr, pr buy Is a "carbon-energy" mixed price, which represents a price of purchasing energy from an energy network from energy sources, from the consumer side, thereby facilitating purchasing low-carbon energy from energy sources, the variable m represents the form of energy contained in the energy sources,trade price for normal energy market, gamma is carbon emission tax, < ->Carbon emission intensity as an energy source;
step 4-2: the carbon emission intensity of the designed electric energy is expressed as:
wherein P is H ，P R Electric output power for power generation equipment and renewable energy power generation equipment，P E Injecting power into the line c H Is the carbon emission intensity of the power generation equipment, which is a parameter determined by the power generation state, c E The carbon emission intensity of the circuit;
step 4-3: the objective function design of the self-energy inner layer optimization control strategy considering low-carbon operation is as follows:
Min of：
wherein Ω represents the total gain of the objective function, pr sell Representing the price of selling energy from an energy network, P buy 、P sell The energy purchased from the energy source to the energy source network and the energy sold are respectively represented, and b represents different energy forms such as electricity, heat and the like.
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