CN114417603A - Electric heating integrated energy system affine energy flow calculation method considering heat supply network transmission and distribution capacity - Google Patents
Electric heating integrated energy system affine energy flow calculation method considering heat supply network transmission and distribution capacity Download PDFInfo
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Abstract
The invention relates to an electric heating integrated energy system affine energy flow calculation method considering heat supply network transmission and distribution capacity, which comprises the following steps of S1, acquiring parameter data of an electric heating interconnection system; step S2, constructing an affine model of the coupling element; step S3, calculating heat supply network affine flow, heat supply network affine temperature, heat supply network affine energy flow and affine power flow based on a heat supply network affine model; step S4, calculating the affine quantities of the thermal power and the electric power of the coupling element according to different control modes of the coupling element; step S5, judging whether the power affine quantities of the coupling elements iterated twice before and after are completely matched, if the power affine quantities of the coupling elements are not matched, updating the boundary quantities of the power grid and the heat grid, taking the affine power of the coupling elements obtained in the iteration as the initial value of the affine power of the coupling elements in the next iteration, and recalculating the affine energy flow of the energy sub-network; and if the affine power of the coupling element is converged, ending the iteration. The invention can consider the transmission and distribution capacity of the heat supply network and effectively improve the operation reliability of the electric heating comprehensive energy system.
Description
Technical Field
The invention relates to the field of energy network control, in particular to an affine energy flow calculation method of an electric heating comprehensive energy system considering the transmission and distribution capacity of a heat supply network.
Background
The electricity-heat comprehensive energy system is coupled with various energy networks to realize complementation and mutual assistance of different energy sources and improve the utilization efficiency of the energy sources, however, the physical characteristics of the multi-energy flow are different, the interaction influence mechanism is complex, the influence by external factors is large, and the uncertain operation characteristics are strong. The electric-thermal comprehensive energy system has various energy conversion devices and complex uncertain behaviors. The load is influenced by factors such as human factors and weather, and the load presents strong uncertainty. In addition, the running efficiency of a coupling unit of the electric heating system is influenced by various factors such as working conditions, ambient temperature and the like, and the power conversion of the unit has strong uncertainty. The uncertainty of the electric-thermal comprehensive energy system puts higher requirements on operation control, so that the transfer process and the influence of uncertainty factors need to be deeply and quantitatively analyzed, uncertainty modeling is carried out on an electric heating system, uncertainty energy flow analysis is further realized, and the capability of the system for coping with uncertainty is improved.
Disclosure of Invention
In view of the above, the present invention provides an affine power flow calculation method for an electric heating integrated energy system considering transmission and distribution capabilities of a heat supply network, which considers the transmission and distribution capability limitations of the heat supply network, retains the transfer process of uncertainty factors, and realizes quantitative analysis of state quantities by the uncertainty factors.
In order to achieve the purpose, the invention adopts the following technical scheme:
an electric heating integrated energy system affine energy flow calculation method considering heat supply network transmission and distribution capacity comprises the following steps:
step S1, acquiring parameter data of the electric heating interconnection system;
step S2, taking the coupling element as a boundary node, splitting the electric heating interconnection network to obtain different energy sub-networks, constructing a heat network affine model based on Taylor expansion, and constructing a coupling element affine model;
step S3, calculating affine flow of a heat supply network through a forward process and an affine temperature of the heat supply network through a backward process based on a heat supply network affine model, calculating affine energy flow of the heat supply network considering transmission and distribution capacity, and simultaneously calculating affine power flow of the power grid;
step S4, calculating the affine quantities of the thermal power and the electric power of the coupling element according to different control modes of the coupling element;
step S5, judging whether the power affine quantities of the coupling elements iterated twice before and after are completely matched, if the power affine quantities of the coupling elements are not matched, updating the boundary quantities of the power grid and the heat grid, taking the affine power of the coupling elements obtained in the iteration as the initial value of the affine power of the coupling elements in the next iteration, and recalculating the affine energy flow of the energy sub-network; and if the affine power of the coupling element is converged, ending the iteration.
Further, the parameter data of the electric heating interconnection system comprise a network topology structure of multi-energy flow, uncertain affine quantity and initial power of a coupling element.
Further, the thermal network affine model specifically includes:
different noise cells are adopted to respectively represent the uncertainty of the heat load of different nodes of the heat supply network, the coefficient of the noise cell represents the uncertainty degree of the heat load, and the affine model of the node heat power is as shown in the formula:
in the formula:
represents affine thermal power, and ^ represents affine quantity; fi,0Represents a thermal power center value, subscript i represents the ith node, and 0 represents an affine center value; epsilonijRepresenting a noise element, and representing a j-th uncertainty factor influencing the node i; f. ofijRepresenting a noise element coefficient, and representing the magnitude of a j uncertainty factor influencing the thermal power of a node i; miRepresenting the number of uncertainty factors affecting thermal power at node i.
(1) Hydraulic affine model
Each node of the heat supply network should satisfy a flow balance equation, i.e., the sum of flows flowing into the node is equal to the sum of flows flowing out of the node plus the node load injection water flow, as follows:
in the formula:
representing the sum of pipe flows into the node;
representing the sum of the pipe flows of the outflow nodes;
representing the node load injection flow;
(2) thermodynamic affine model based on Taylor expansion
The thermal model mainly represents the temperature transfer relationship of each node in the heat supply network, and in the thermal network, the relationship between load thermal power consumption and flow and temperature is as follows:
in the formula: c represents the specific heat capacity of water;
representing the affine quantity of the heat supply temperature of the node; to represents the output temperature;
the relationship between the head end temperature and the tail end temperature of each pipeline is as follows:
in the formula:
represents the pipe end temperature;
represents the pipeline head end temperature; t isaRepresents the ambient temperature; λ represents the heat transfer coefficient of the pipe; l represents the length of the pipeline;
and (3) retaining the Taylor expansion to a second-order term, and converting the Taylor expansion into addition, subtraction, multiplication and division affine operation, wherein the formula is shown as the following equation:
if a plurality of pipeline flows flow into or out of a certain node of the heat supply network, the node is called a mixed node; the temperature of the hot water leaving the mixing node is equal to the mixed temperature of the hot water at the mixing node, and the node power conservation equation is:
in the formula: m isoutRepresenting pipe flow out of the node; m isinRepresenting pipe flow into the node;
represents the temperature of the hot water flowing into the node;
the temperature after mixing of the hot water is shown.
(3) Coupling element affine model
The coupling elements of the electric-heat interconnection system comprise a combined heat and power generation unit CHB and a heat pump, the gas turbine is a gas turbine, and the uncertainty of the thermoelectric power ratio is represented as follows:
in the formula:
thermal power for CHP;
electrical power generated for the CHP;
the extraction steam turbine is a steam type unit, and the uncertainty of the thermoelectric power ratio is expressed as follows:
in the formula: pconIs a constant;
the electric-thermal conversion efficiency of the heat pump changes along with the temperature difference between a heat source and a heat load, and an affine model of the heat pump is as follows:
in the formula:
the electric heat conversion efficiency of the heat pump;
thermal power generated for the heat pump;
the electrical power consumed by the heat pump.
Further, the step S3 is specifically:
in the forward-pushing process, firstly establishing an affine model of the load by using different noise elements, calculating the flow required by the load, and determining the flow of each pipeline according to the formula forward-pushing along the reverse direction of flow transmission;
in the back substitution process, the heat supply temperature of a heat source is fixed in a heat supply network, the affine flow obtained in the forward pushing process is substituted into a formula and an expression from the heat source nodes along the power transmission direction, and the heat supply temperature of each node of the heat supply network is calculated one by one. In the regenerative network, determining the regenerative temperature of each node of the heat supply network from the load node along the heat power transfer direction of the regenerative network;
the heat supply temperature of the heat source is fixed in the iteration process, and the flow constraint of the network is smaller than the upper flow limit mupWhen the heat supply flow of the main heat source A needs to exceed the upper limit mupWhen the uncertain load can be responded, the heat supply of the secondary heat source B is adjusted to meet the uncertain demand;
the pipeline affine flow connected with the heat source A and the heat source B is obtained in the iteration process as follows:
in the formula:
and
flow affine values respectively representing the conduits connected to heat source A, B; m isA,0And mB,0Represents the corresponding center value; k is the total number of noise elements in the iteration process; epsilonkIs the k noise element; mu.sA,kAnd muB,kRespectively, the flow noise figure of the pipe connected to heat source A, B;
when the upper limit of the flow interval in the iteration process is higher than the limit value of the pipeline flow, the flow of the heat source A is adjusted, namely the heat supply amount of the heat supply source A is adjusted, and the adjusted pipeline flow is as follows:
at this time, the upper limit of the uncertainty flow interval of the pipeline A is mupNot exceeding the limit;
the thermal power output part with the reduced heat source A is complemented by the heat source B to meet the load requirement of the network, so that the thermal power of the heat source B during iteration is correspondingly improved; at the moment, the pipeline flow of the heat source B is still ensured not to exceed the limit; when the flow rates of the pipeline A and the pipeline B both exceed the limit value, the uncertain load requirements cannot be met;
repeating the forward-backward substitution process of the affine energy flow until iteration converges, wherein the convergence condition is that the Euclidean distance between noise element coefficients of the iteration state quantities of the previous iteration and the next iteration is smaller than a threshold value;
further, the step S4 is specifically: if the unit works in a mode of 'fixing electricity with heat', firstly calculating the affine thermal power of the CHP unit according to the obtained affine power flow of the heat supply network, and then calculating the affine electric power of the CHP unit according to the relation of the coupling elements; if the unit works in the mode of 'in electric heating', firstly, the affine electric power of the CHP unit is calculated according to the obtained power grid affine energy flow, and then the affine heating power of the CHP unit is calculated according to the relation of the coupling elements.
Further, the step S5 is specifically:
the heat supply temperature of the heat source is fixed in the iteration process, and the flow constraint of the network is smaller than the upper flow limit mupWhen the heat supply flow of the main heat source A needs to exceed the upper limit mupWhen the uncertain load can be responded, the heat supply of the secondary heat source B is adjusted to meet the uncertain demand;
the pipeline affine flow connected with the heat source A and the heat source B is obtained in the iteration process as follows:
in the formula:
and
flow affine values respectively representing the conduits connected to heat source A, B; m isA,0And mB,0Represents the corresponding center value; k is the total number of noise elements in the iteration process; epsilonkIs the k noise element; mu.sA,kAnd muB,kRespectively, the flow noise figure of the pipe connected to heat source A, B;
when the upper limit of the flow interval in the iteration process is higher than the limit value of the pipeline flow, the flow of the heat source A is adjusted, namely the heat supply amount of the heat supply source A is adjusted, and the adjusted pipeline flow is as follows:
at this time, the upper limit of the uncertainty flow interval of the pipeline A is mupNot exceeding the limit;
the thermal power output part with the reduced heat source A is complemented by the heat source B to meet the load requirement of the network, so that the thermal power of the heat source B during iteration is correspondingly improved; at the moment, the pipeline flow of the heat source B is still ensured not to exceed the limit; and when the flow rates of the pipeline A and the pipeline B both exceed the limit value, the uncertain load requirements cannot be met.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention takes the transmission and distribution capacity limit of the heat supply network into account, reserves the transfer process of the uncertainty factor and realizes the quantitative analysis of the uncertainty factor on the state quantity;
2. the invention deeply and quantitatively analyzes the transmission process and the influence of uncertainty factors, and performs uncertainty modeling on an electric heating system so as to realize uncertainty performance flow analysis.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments.
Referring to fig. 1, the invention provides an affine energy flow calculation method for an electric heating integrated energy system considering transmission and distribution capacity of a heat supply network, which includes the following steps:
step S1, acquiring parameter data of the electric heating interconnection system;
step S2, taking the coupling element as a boundary node, splitting the electric heating interconnection network to obtain different energy sub-networks, and constructing a heat network affine model and a coupling element affine model based on Taylor expansion;
step S3, calculating affine flow of a heat supply network through a forward process and an affine temperature of the heat supply network through a backward process based on a heat supply network affine model, calculating affine energy flow of the heat supply network considering transmission and distribution capacity, and simultaneously calculating affine power flow of the power grid;
step S4, calculating the affine quantities of the thermal power and the electric power of the coupling element according to different control modes of the coupling element;
step S5, judging whether the power affine quantities of the coupling elements iterated twice before and after are completely matched, if the power affine quantities of the coupling elements are not matched, updating the boundary quantities of the power grid and the heat grid, taking the affine power of the coupling elements obtained in the iteration as the initial value of the affine power of the coupling elements in the next iteration, and recalculating the affine energy flow of the energy sub-network; and if the affine power of the coupling element is converged, ending the iteration.
In this embodiment, the thermal network affine model is specifically as follows:
different noise cells are adopted to respectively represent the uncertainty of the heat load of different nodes of the heat supply network, the coefficient of the noise cell represents the uncertainty degree of the heat load, and the affine model of the node heat power is as shown in the formula:
in the formula:
represents affine thermal power, and ^ represents affine quantity; fi,0Represents a thermal power center value, subscript i represents the ith node, and 0 represents an affine center value; epsilonijRepresenting a noise element, and representing a j-th uncertainty factor influencing the node i; f. ofijRepresenting a noise element coefficient, and representing the magnitude of a j uncertainty factor influencing the thermal power of a node i; miRepresenting the number of uncertainty factors affecting thermal power at node i.
(1) Hydraulic affine model
Each node of the heat supply network should satisfy a flow balance equation, i.e., the sum of flows flowing into the node is equal to the sum of flows flowing out of the node plus the node load injection water flow, as follows:
in the formula:
representing the sum of pipe flows into the node;
representing the sum of the pipe flows of the outflow nodes;
representing the node load injection flow;
(2) thermodynamic affine model based on Taylor expansion
The thermal model mainly represents the temperature transfer relationship of each node in the heat supply network, and in the thermal network, the relationship between load thermal power consumption and flow and temperature is as follows:
in the formula: c represents the specific heat capacity of water;
representing the affine quantity of the heat supply temperature of the node; t isoRepresents the output temperature;
the relationship between the head end temperature and the tail end temperature of each pipeline is as follows:
in the formula:
represents the pipe end temperature;
represents the pipeline head end temperature; t isaRepresents the ambient temperature; λ represents the heat transfer coefficient of the pipe; l represents the length of the pipeline;
and (3) retaining the Taylor expansion to a second-order term, and converting the Taylor expansion into addition, subtraction, multiplication and division affine operation, wherein the formula is shown as the following equation:
if a plurality of pipeline flows flow into or out of a certain node of the heat supply network, the node is called a mixed node; the temperature of the hot water leaving the mixing node is equal to the mixed temperature of the hot water at the mixing node, and the node power conservation equation is:
in the formula: m isoutRepresenting pipe flow out of the node; m isinRepresenting pipe flow into the node;
represents the temperature of the hot water flowing into the node;
the temperature after mixing of the hot water is shown.
(3) Coupling element affine model
The coupling elements of the electric-heat interconnection system comprise a combined heat and power generation unit CHB and a heat pump, the gas turbine is a gas turbine, and the uncertainty of the thermoelectric power ratio is represented as follows:
in the formula:
thermal power for CHP;
electrical power generated for the CHP;
the extraction steam turbine is a steam type unit, and the uncertainty of the thermoelectric power ratio is expressed as follows:
in the formula: pconIs a constant;
the electric-thermal conversion efficiency of the heat pump changes along with the temperature difference between a heat source and a heat load, and an affine model of the heat pump is as follows:
in the formula:
the electric heat conversion efficiency of the heat pump;
thermal power generated for the heat pump;
the electrical power consumed by the heat pump.
In this embodiment, a multi-source complementary affine energy flow forward-backward substitution method considering the transmission and distribution capacity of the heat supply network is adopted, and specifically:
(1) heat supply network affine energy flow forward-backward substitution method
First, the central value of the state quantity is calculated according to the deterministic energy flow and is used as an initial affine energy flow iteration value.
In the forward-pushing process, firstly, affine models of loads are built by using different noise elements, the flow rate required by the loads is calculated, and then the flow rate of each pipeline is determined according to the formula forward-pushing along the reverse direction of flow rate transmission.
In the back substitution process, the heat supply temperature of a heat source is fixed in a heat supply network, the affine flow obtained in the forward pushing process is substituted into a formula and an expression from the heat source nodes along the power transmission direction, and the heat supply temperature of each node of the heat supply network is calculated one by one. In the regenerative network, starting from a load node, the regenerative temperature of each node of the heat supply network is determined along the heat power transmission direction of the regenerative network.
And repeating the forward-backward substitution process of the affine energy flow until iteration converges, wherein the convergence condition is that the Euclidean distance between noise element coefficients of the iteration state quantities of the previous iteration and the next iteration is smaller than a threshold value.
(2) Multi-source complementary affine energy flow iteration considering heat supply network transmission and distribution capacity
Assuming that the heating temperature of the heat source is fixed in the iterative process, the flow constraint of the network should be less than the upper flow limit mup. When the heat supply flow of the main heat source A needs to exceed the upper limit mupWhen the uncertain load can be responded, the heat supply of the secondary heat source B is adjusted to meet the uncertain demand. The pipeline affine flow connected with the heat source A and the heat source B is obtained in an iteration process as follows:
in the formula:
and
flow affine values respectively representing the conduits connected to heat source A, B; m isA,0And mB,0Represents the corresponding center value; k is the total number of noise elements in the iteration process; epsilonkIs the k noise element; mu.sA,kAnd muB,kRespectively, represent the flow noise figure of the pipe connected to heat source A, B.
When the upper limit of the flow interval in the iteration process is higher than the limit value of the pipeline flow, the flow of the heat source A is adjusted, namely the heat supply amount of the heat supply source A is adjusted, and the adjusted pipeline flow is as follows:
at this time, the upper limit of the uncertainty flow interval of the pipeline A is mupThe limit is not exceeded.
The reduced thermal power output portion of heat source a will be complemented by heat source B to meet the load requirements of the network, thus correspondingly increasing the thermal power of heat source B during the iteration. At this point, it should still be ensured that the tube flow of heat source B does not go out of limit. And when the flow rates of the pipeline A and the pipeline B both exceed the limit value, the uncertain load requirements cannot be met.
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 foregoing is directed to preferred embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow. However, any simple modification, equivalent change and modification of the above embodiments according to the technical essence of the present invention are within the protection scope of the technical solution of the present invention.
Claims (6)
1. An electric heating integrated energy system affine energy flow calculation method considering heat supply network transmission and distribution capacity is characterized by comprising the following steps:
step S1, acquiring parameter data of the electric heating interconnection system;
step S2, taking the coupling element as a boundary node, splitting the electric heating interconnection network to obtain different energy sub-networks, constructing a heat network affine model based on Taylor expansion, and constructing a coupling element affine model;
step S3, calculating affine flow of a heat supply network through a forward process and an affine temperature of the heat supply network through a backward process based on a heat supply network affine model, calculating affine energy flow of the heat supply network considering transmission and distribution capacity, and simultaneously calculating affine power flow of the power grid;
step S4, calculating the affine quantities of the thermal power and the electric power of the coupling element according to different control modes of the coupling element;
step S5, judging whether the power affine quantities of the coupling elements iterated twice before and after are completely matched, if the power affine quantities of the coupling elements are not matched, updating the boundary quantities of the power grid and the heat grid, taking the affine power of the coupling elements obtained in the iteration as the initial value of the affine power of the coupling elements in the next iteration, and recalculating the affine energy flow of the energy sub-network; and if the affine power of the coupling element is converged, ending the iteration.
2. The method for calculating affine power flow of an electric heating integrated energy system considering transmission and distribution capacity of a heat supply network according to claim 1, wherein parameter data of the electric heating interconnection system comprise network topology of multi-power flow, uncertain affine quantity and coupling element affine power.
3. The method for calculating the affine power flow of the electric heating integrated energy system considering the transmission and distribution capacity of the heat supply network according to claim 1, wherein the affine model of the heat supply network is as follows:
different noise cells are adopted to respectively represent the uncertainty of the heat load of different nodes of the heat supply network, the coefficient of the noise cell represents the uncertainty degree of the heat load, and the affine model of the node heat power is as shown in the formula:
in the formula:
represents affine thermal power, and ^ represents affine quantity; fi,0Represents a thermal power center value, subscript i represents the ith node, and 0 represents an affine center value; epsilonijRepresenting a noise element, and representing a j-th uncertainty factor influencing the node i; f. ofijRepresenting a noise element coefficient, and representing the magnitude of a j uncertainty factor influencing the thermal power of a node i; miRepresenting the number of uncertainty factors affecting thermal power at node i.
(1) Hydraulic affine model
Each node of the heat supply network should satisfy a flow balance equation, i.e., the sum of flows flowing into the node is equal to the sum of flows flowing out of the node plus the node load injection water flow, as follows:
in the formula:
representing the sum of pipe flows into the node;
representing the sum of the pipe flows of the outflow nodes;
representing the node load injection flow;
(2) thermodynamic affine model based on Taylor expansion
The thermal model mainly represents the temperature transfer relationship of each node in the heat supply network, and in the thermal network, the relationship between load thermal power consumption and flow and temperature is as follows:
in the formula: c represents the specific heat capacity of water;
representing the affine quantity of the heat supply temperature of the node; t isoRepresents the output temperature;
the relationship between the head end temperature and the tail end temperature of each pipeline is as follows:
in the formula:
represents the pipe end temperature;
represents the pipeline head end temperature; t isaRepresents the ambient temperature; λ represents the heat transfer coefficient of the pipe; l represents the length of the pipeline;
and (3) retaining the Taylor expansion to a second-order term, and converting the Taylor expansion into addition, subtraction, multiplication and division affine operation, wherein the formula is shown as the following equation:
if a plurality of pipeline flows flow into or out of a certain node of the heat supply network, the node is called a mixed node; the temperature of the hot water leaving the mixing node is equal to the mixed temperature of the hot water at the mixing node, and the node power conservation equation is:
in the formula: m isoutRepresenting pipe flow out of the node; m isinRepresenting flowsThe pipe flow of the inlet node;
represents the temperature of the hot water flowing into the node;
the temperature after mixing of the hot water is shown.
(3) Coupling element affine model
The coupling elements of the electric-heat interconnection system comprise a combined heat and power generation unit CHB and a heat pump, the gas turbine is a gas turbine, and the uncertainty of the thermoelectric power ratio is represented as follows:
in the formula:
thermal power for CHP;
electrical power generated for the CHP;
the extraction steam turbine is a steam type unit, and the uncertainty of the thermoelectric power ratio is expressed as follows:
in the formula: pconIs a constant;
the electric-thermal conversion efficiency of the heat pump changes along with the temperature difference between a heat source and a heat load, and an affine model of the heat pump is as follows:
in the formula:
the electric heat conversion efficiency of the heat pump;
thermal power generated for the heat pump;
the electrical power consumed by the heat pump.
4. The method for calculating affine power flow of an electric heating integrated energy system considering transmission and distribution capacity of a heat supply network according to claim 3, wherein the step S3 is specifically as follows:
in the forward-pushing process, firstly establishing an affine model of the load by using different noise elements, calculating the flow required by the load, and determining the flow of each pipeline according to the formula forward-pushing along the reverse direction of flow transmission;
in the back substitution process, the heat supply temperature of a heat source is fixed in a heat supply network, the affine flow obtained in the forward pushing process is substituted into a formula and an expression from the heat source nodes along the power transmission direction, and the heat supply temperature of each node of the heat supply network is calculated one by one. In the regenerative network, determining the regenerative temperature of each node of the heat supply network from the load node along the heat power transfer direction of the regenerative network;
the heat supply temperature of the heat source is fixed in the iteration process, and the flow constraint of the network is smaller than the upper flow limit mupWhen the heat supply flow of the main heat source A needs to exceed the upper limit mupWhen the uncertain load can be responded, the heat supply of the secondary heat source B is adjusted to meet the uncertain demand;
the pipeline affine flow connected with the heat source A and the heat source B is obtained in the iteration process as follows:
in the formula:
and
flow affine values respectively representing the conduits connected to heat source A, B; m isA,0And mB,0Represents the corresponding center value; k is the total number of noise elements in the iteration process; epsilonkIs the k noise element; mu.sA,kAnd muB,kRespectively, the flow noise figure of the pipe connected to heat source A, B;
when the upper limit of the flow interval in the iteration process is higher than the limit value of the pipeline flow, the flow of the heat source A is adjusted, namely the heat supply amount of the heat supply source A is adjusted, and the adjusted pipeline flow is as follows:
at this time, the upper limit of the uncertainty flow interval of the pipeline A is mupNot exceeding the limit;
the thermal power output part with the reduced heat source A is complemented by the heat source B to meet the load requirement of the network, so that the thermal power of the heat source B during iteration is correspondingly improved; at the moment, the pipeline flow of the heat source B is still ensured not to exceed the limit; when the flow rates of the pipeline A and the pipeline B both exceed the limit value, the uncertain load requirements cannot be met;
and repeating the forward-backward substitution process of the affine energy flow until iteration converges, wherein the convergence condition is that the Euclidean distance between noise element coefficients of the iteration state quantities of the previous iteration and the next iteration is smaller than a threshold value.
5. The method for calculating affine power flow of an electric heating integrated energy system considering transmission and distribution capacity of a heat supply network according to claim 3, wherein the step S4 is specifically as follows: if the unit works in a mode of 'fixing electricity with heat', firstly calculating the affine thermal power of the CHP unit according to the obtained affine power flow of the heat supply network, and then calculating the affine electric power of the CHP unit according to the relation of the coupling elements; if the unit works in the mode of 'in electric heating', firstly, the affine electric power of the CHP unit is calculated according to the obtained power grid affine energy flow, and then the affine heating power of the CHP unit is calculated according to the relation of the coupling elements.
6. The method for calculating affine power flow of an electric heating integrated energy system considering transmission and distribution capacity of a heat supply network according to claim 1, wherein the step S5 is specifically as follows:
and judging whether the power affine quantities of the two iteration coupling elements are completely matched. If the affine power of the coupling element is not matched, updating the boundary quantities of the power grid and the heat supply network, taking the affine power of the coupling element obtained in the iteration as the initial value of the affine power of the coupling element in the next iteration, and recalculating the affine energy flow of the energy sub-network; and if the affine power of the coupling element is converged, ending the iteration.
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