Energy System Heat Network Fault Recovery Method and System Based on Multi-Source Network Decoupling

Abstract

This invention discloses a method and system for fault recovery of a heat network in an energy system based on multi-source network decoupling. The method includes: constructing a multi-source network based on a combined heat and power energy system; decoupling the multi-source network to generate multiple single-heat-source networks; obtaining an output coefficient table representing the output-heat load relationship of each heat source under different heat source parameters through simulation experiments on the single-heat-source networks; when a fault occurs, selecting the optimal shut-off valve for fault isolation based on the fault location; updating the topology of the isolated multi-source network and its network parameters; decoupling the updated multi-source network and updating the heat source parameters of each heat source; querying the output coefficient table based on the heat source parameters of each heat source to obtain the corresponding output coefficient; calculating the latest output value of each heat source based on the output coefficient and adjusting the output of these heat sources to that value. This method provides strong support for the safe operation of a combined heat and power energy system.

Description

Technical Field

[0001] This invention belongs to the field of energy system fault recovery, specifically relating to a method and system for energy system heating network fault recovery based on multi-source network decoupling. Background Technology

[0002] As the global energy crisis and environmental pollution situation continue to worsen, the energy sector is facing a profound transformation. Although the construction of new energy systems is accelerating, it still generates significant carbon emissions. Therefore, it is imperative to improve the overall efficiency of energy utilization to reduce pollutant and carbon dioxide emissions and promote a low-carbon, clean energy transition. Integrated energy systems, based on the fundamental principles of "multi-energy complementarity and tiered utilization," can fully leverage the complementary advantages of electricity, gas, cooling, and heating, offering more flexible resources, higher overall energy utilization efficiency, and lower carbon emissions. Against this backdrop, given that electricity and heat consumption dominate in industrial, commercial, residential, and office load scenarios, integrated heat and power (CHP) energy systems are one of the most widely deployed and applied typical forms of integrated energy.

[0003] Integrated heat and power (CHP) energy systems involve generators, pipelines, storage tanks, and other equipment with various potential faults and risks, which can have significant impacts on personnel, system, energy, and environmental safety. Furthermore, the generation and consumption of energy are dynamic in time and space, and unforeseen events such as weather changes and equipment failures often lead to imbalances between energy supply and demand in CHP systems. In addition, due to the high coupling between the power network and the heating network, faults occurring in the heating network can propagate to the power network, increasing the risk of cascading failures. Therefore, researching fault recovery methods for CHP systems is of great significance for improving the system's reliability and robustness.

[0004] Current research on faults in integrated heat-electric energy systems mainly focuses on the prevention phase. For complex integrated heat-electric energy systems, existing fault recovery methods typically target single fault types and are slow to respond to sudden and random faults. Therefore, the core issue in fault recovery for integrated heat-electric energy systems is how to address the diverse types of heat network faults, while maintaining versatility, in situations with strong coupling between thermal and electronic systems and complex topologies, while maximizing effectiveness.

[0005] Chinese patent application CN115130391A discloses a fault recovery method and system for a combined heat and power (CHP) energy system that takes thermal inertia into account. The method includes: determining first-stage constraints based on the start-up and shutdown status of the CHP units; establishing a first-stage model based on these constraints with the objective of minimizing the start-up and shutdown costs of the CHP units; determining the probability of line damage based on extreme weather information and establishing a fuzzy set of power line faults; determining the outlet temperature and heat supply of the heating pipelines; determining second-stage constraints based on the upper and lower limits of the output of each unit; establishing a second-stage model based on the second-stage constraints and the fuzzy set of power line faults with the objective of minimizing operating costs and load shedding penalties; and solving the two-stage model using a column-constraint generation algorithm to determine the start-up and shutdown status, output, and reinforcement scheme for each unit and power line.

[0006] Chinese patent application CN116070853A discloses an autonomous emergency dispatching method for heating system accidents, comprising: establishing a hydraulic operating condition model of the heating network, simulating accidents in various pipe sections and heat source accidents, analyzing changes in the hydraulic operating condition of the heating network, and establishing a heating network reconfiguration optimization model with the station flow guarantee rate, station pressure guarantee rate, user heating quality, and heating network stability under accident conditions as objective functions; solving the heating network reconfiguration optimization model to obtain the optimal heating network disconnection scheme or interconnection scheme; based on the reconfigured heating network topology, establishing a heat source dispatching optimization model with the objective functions of maximizing total heat supply, maximizing the quota heating coefficient, maximizing the flow guarantee coefficient of key users, minimizing the increase in normal heat source load, and minimizing pump energy consumption under accident conditions; solving the heat source dispatching optimization model to obtain the optimal strategy for heat source output; and establishing a heating station pump and valve control model to obtain the optimal heating station pump and valve control parameters.

[0007] The existing technologies described above suffer from significant real-time limitations when addressing heat network fault recovery in integrated heat-power energy systems. Current methods typically rely on complex online optimization models for solving these problems, such as using column and constraint generation algorithms to solve multi-stage models or constructing and solving heat network reconfiguration and heat source scheduling optimization models. These online optimization processes involve high-dimensional variables and nonlinear constraints (such as thermal inertia, hydraulic balance, and temperature propagation), resulting in lengthy computations that often require several minutes or even longer to generate a recovery strategy. However, heat network faults (such as sudden pressure drops due to pipe ruptures or sudden heat source shutdowns) require the system to respond within seconds to prevent the accident from escalating, a requirement that existing methods struggle to meet.

[0008] Existing technologies lack versatility and struggle to effectively cover diverse heating network fault scenarios. Many existing solutions require establishing corresponding optimization models or adjusting objective functions and constraints for different specific fault types (e.g., specific pipe segment accidents, heat source accidents). When the system faces unpredictable fault types or concurrent faults (e.g., heat source faults superimposed on pipe network leaks), existing methods often lack a unified processing framework, necessitating model or parameter reconfiguration. This not only increases operational complexity but also further delays fault recovery decision-making.

[0009] Existing technologies for fault recovery in integrated heat and power energy systems generally employ strongly coupled optimization methods. This means they require simultaneously and online solving complex equations relating the power and heat networks, such as jointly optimizing the electrical and thermal outputs of generating units and considering the impact of changes in the hydraulic conditions of the heating network on the overall system state. This strong coupling results in a massive optimization problem and highly nonlinear constraints (such as dynamic temperature variations in heating pipelines and pressure-flow relationships), significantly increasing computational complexity. In emergency recovery scenarios following a fault, this high complexity presents an irreconcilable contradiction with the requirement for rapid decision-making. Summary of the Invention

[0010] To address the issues of poor versatility and slow decision-making speed in existing recovery methods for integrated heat-electricity energy systems, this invention generates a heat output coefficient table offline. After a fault occurs, the system isolates the fault, updates the heat network information, and calculates the latest total heating load of heat sources at unbalanced nodes. By combining the heat output coefficient table with the data, the system quickly estimates the output of heat sources at unbalanced nodes and updates the original network, thus completing the redistribution of heat source output and achieving efficient recovery of various types of heat network faults.

[0011] To achieve the above-mentioned objectives, the present invention adopts the following technical solution.

[0012] This invention discloses a method for recovering from a heat network fault in an energy system based on multi-source network decoupling, comprising the following steps:

[0013] S1. Construct a multi-source network based on the integrated heat-electric energy system, decouple the multi-source network to generate a single heat source network with multiple non-equilibrium heat source nodes, and conduct simulation experiments on each single heat source network to obtain an output coefficient table representing the relationship between heat source output and heat load under different heat source parameters.

[0014] S2. When a fault occurs, select the optimal shut-off valve for fault isolation based on the location of the fault and isolate it; update the topology of the isolated multi-source network, perform hydraulic calculations for the heating network, and update the network parameters of the multi-source network; decouple the updated multi-source network and update the heat source parameters of each heat source.

[0015] S3. Based on the heat source parameters of each heat source, query the output coefficient table of the heat source output-heat load relationship, obtain the corresponding output coefficient, calculate the latest output value of each unbalanced heat source node, and adjust its output to that output value.

[0016] S4. Determine whether the fault recovery of the integrated heat-power energy system has reached the set design target based on the average heating temperature of the heat network nodes before and after the fault recovery. If it has not been reached, repeat steps S1 to S3.

[0017] More preferably,

[0018] The construction of a multi-source network based on the integrated heat-electricity energy system specifically includes:

[0019] Establish a graph structure for the integrated heat-electricity energy system. Each heat network node in the system serves as a node in the graph structure, including heat sources, intermediate nodes, and load nodes. Pipes connecting each heat network node serve as edges, and network parameters of the multi-source network serve as attributes of the edges. If the detected mass flow rate data of a pipe is the same as the initial recorded mass flow rate value, the network parameter corresponding to that pipe is a positive value; otherwise, it is a negative value.

[0020] More preferably,

[0021] The simulation experiments conducted on each single heat source network yielded a table of output coefficients representing the output-heat load relationship of each heat source under different heat source parameters. Specifically:

[0022] The heat source parameters include heat load and number of pipes. Several simulation experiments with varying heat load and number of pipes were conducted for each heat source to obtain the output coefficient of each heat source under different heat loads and number of pipes. The output coefficient table of the heat source output-heat load relationship under different heat source parameters was obtained by fitting.

[0023] More preferably,

[0024] The simulation experiment is specifically as follows:

[0025] First, keep all parameters except the heat source parameters unchanged. Then, take the set heating power as the total heat load value, distribute the total heat load value evenly to each load node, simulate until the system is in a stable state, and record the output value of the heat source at this time.

[0026] Subsequently, the distance from each pipe to the heat source is calculated. This distance represents the number of pipes through which hot water flows from the heat source to the pipe. The pipes are then isolated in descending order of distance, so that in the single heat source network formed after isolation, the proportion of the remaining pipes to the original number decreases sequentially according to a preset gradient value, provided that the number of remaining load nodes is not zero.

[0027] Given the number of remaining pipes mentioned above, a simulation of variable heat load power is performed. After the system stabilizes, the output value of the heat source is recorded. If the system becomes unstable, the experimental data for that set is discarded.

[0028] More preferably,

[0029] The set heating power ranges from 1% to 90% of the maximum heating power of the heat source.

[0030] The proportion of the remaining pipe quantity to the original quantity is set according to preset gradient values ​​of 80%, 60%, 40%, and 20%.

[0031] More preferably,

[0032] The system's stable state is specifically defined as follows: the fluctuation rate of the heating temperature at all load nodes does not exceed a set proportion within a set time period.

[0033] More preferably,

[0034] The process of selecting the optimal shut-off valve for fault isolation based on the location of the fault and isolating it specifically involves:

[0035] To determine the location of the fault, if there are valves on all sides of the pipeline where the fault occurs, select the nearest valve as the optimal valve to close. If there are no valves on either side of the pipeline where the fault occurs, start from the node on the valveless side of the pipeline where the fault occurs and perform a breadth-first traversal of the thermal system network in the integrated heat-electricity energy system. When a valve is encountered in any search direction, close the valve and stop the search in that direction. Continue traversing until the search in all directions stops.

[0036] More preferably,

[0037] The process of performing hydraulic calculations for the heating network and updating the network parameters of the multi-source network specifically involves:

[0038] Obtain the minimum spanning tree of the graph structure of the thermal-electric integrated energy system. Divide each pipe into branches and chains based on its resistance characteristics. If the chain branch mass flow rate correction is less than the set error convergence limit, keep the original network chain branch mass flow rate unchanged and output the current branch mass flow rate and chain mass flow rate. Otherwise, perform an iterative correction process: update the chain branch mass flow rate data to the original chain branch mass flow rate data plus the chain branch mass flow rate correction, and recalculate the branch mass flow rate based on the updated chain branch mass flow rate. Again, determine if the chain branch mass flow rate correction is less than the set error convergence limit. If not, repeat the iterative correction process until the chain branch mass flow rate correction is less than the set error convergence limit. The calculation of the branch mass flow rate is shown in the following formula:

[0039]

[0040] In the formula, For the mass flow rate of tree branches, The tree-tree correlation matrix, This is the chain-branch incidence matrix. The net injection or net extraction mass flow rate of a node. For the chain branch mass flow rate;

[0041] Chain branch mass flow correction The calculation method is as follows:

[0042]

[0043] In the formula, M It is the Jacobian matrix of the loop pressure drop equation with respect to the chain branch mass flow rate; This refers to the pressure drop of a single pipe.

[0044] More preferably,

[0045] The determination of whether the fault recovery of the integrated thermal-electric energy system has met the set design targets is as follows:

[0046] Calculate the relative rate of change of the average heating temperature of the heat network nodes after the fault is restored compared with that before the fault, and determine whether the relative rate of change is less than the set threshold. If it is less than the threshold, it means that the fault restoration of the integrated heat-electricity energy system has reached the set design target.

[0047] Another aspect of this invention discloses an energy system heat network fault recovery system based on the aforementioned method and multi-source network decoupling, comprising an output coefficient table construction module, a heat source parameter update module, a heat source output control module, and a fault recovery status judgment module, specifically including:

[0048] The output coefficient table construction module constructs a multi-source network based on the integrated heat-electric energy system, decouples the multi-source network, generates a single heat source network with multiple non-equilibrium heat source nodes, and conducts simulation experiments on each single heat source network to obtain an output coefficient table representing the relationship between heat source output and heat load under different heat source parameters.

[0049] The heat source parameter update module, when a fault occurs, selects the optimal shut-off valve for fault isolation based on the fault location and isolates it; updates the topology of the isolated multi-source network, performs hydraulic calculations for the heating network, and updates the network parameters of the multi-source network; decouples the updated multi-source network and updates the heat source parameters of each heat source.

[0050] The heat source output control module queries the output coefficient table of the heat source output-heat load relationship based on the heat source parameters of each heat source to obtain the corresponding output coefficient, calculates the latest output value of each unbalanced heat source node, and controls its output to that output value.

[0051] The fault recovery status judgment module determines whether the fault recovery of the integrated heat-power energy system has reached the set design target based on the average heating temperature of the heat network nodes before and after the fault recovery. If it has not reached the target, it returns to the output coefficient table construction module.

[0052] Compared with the prior art, the present invention has the following advantages:

[0053] This invention proposes a method and system for recovering heat network faults in energy systems based on multi-source network decoupling. In integrated heat-power energy systems, heat network faults are diverse and existing recovery methods are limited. This method achieves fault recovery by adjusting the output of heat sources at unbalanced nodes, making it a universal heat network fault recovery method that can better adapt to different heat source characteristics and operating conditions. Furthermore, the heat output coefficient table generated through the multi-source network decoupling method can significantly shorten decision-making time, greatly improving system reliability and operating efficiency. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of the energy system heat network fault recovery method based on multi-source network decoupling according to the present invention;

[0055] Figure 2 This is a network topology diagram according to an embodiment of the present invention;

[0056] Figure 3 This is a diagram showing the situation of the heating network valves in an embodiment of the present invention;

[0057] Figure 4 This is a network topology update diagram after a pipe burst in a heating network according to an embodiment of the present invention;

[0058] Figure 5 This is a single heat source network topology update diagram in an embodiment of the present invention;

[0059] Figure 6 This describes the average temperature variation of the nodes in the thermal system in this embodiment of the invention.

[0060] Figure 7 This shows the change in the average temperature change rate of a single heat source node in an embodiment of the present invention. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0062] Example 1:

[0063] like Figure 1 As shown, this invention discloses a method for energy system heat network fault recovery based on multi-source network decoupling, comprising the following steps:

[0064] S1. Construct a multi-source network based on the integrated heat-electric energy system, decouple the multi-source network to generate a single heat source network with multiple non-equilibrium heat source nodes, and obtain the output coefficient table representing the relationship between heat source output and heat load under different heat source parameters by conducting simulation experiments on each single heat source network.

[0065] Specifically, the construction of a multi-source network based on the integrated heat-electric energy system includes:

[0066] Establish a graph structure for the integrated heat-electricity energy system. Each heat network node in the system serves as a node in the graph structure, including heat sources, intermediate nodes, and load nodes. Pipes connecting each heat network node serve as edges, and network parameters of the multi-source network serve as attributes of the edges. If the detected mass flow rate data of a pipe is the same as the initial recorded mass flow rate value, the network parameter corresponding to that pipe is a positive value; otherwise, it is a negative value.

[0067] The simulation experiments conducted on each single heat source network yielded a table of output coefficients representing the output-heat load relationship of each heat source under different heat source parameters. Specifically:

[0068] The heat source parameters include heat load and number of pipes. Several simulation experiments with varying heat load and number of pipes were conducted for each heat source to obtain the output coefficient of each heat source under different heat loads and number of pipes. The output coefficient table of the heat source output-heat load relationship under different heat source parameters was obtained by fitting.

[0069] The simulation experiment is specifically as follows:

[0070] First, keep all parameters except the heat source parameters unchanged. Then, take the set heating power as the total heat load value, distribute the total heat load value evenly to each load node, simulate until the system is in a stable state, and record the output value of the heat source at this time.

[0071] Subsequently, the distance from each pipe to the heat source is calculated. This distance represents the number of pipes through which hot water flows from the heat source to the pipe. The pipes are then isolated in descending order of distance, so that in the single heat source network formed after isolation, the proportion of the remaining pipes to the original number decreases sequentially according to a preset gradient value, provided that the number of remaining load nodes is not zero.

[0072] Given the aforementioned remaining pipe quantities, a simulation of variable heat load power was performed. After the system stabilized, the output value of the heat source was recorded. If the system became unstable, the experimental data for that set was discarded.

[0073] The set heating power ranges from 1% to 90% of the maximum heating power of the heat source.

[0074] The proportion of the remaining pipe quantity to the original quantity is set according to preset gradient values ​​of 80%, 60%, 40%, and 20%.

[0075] The system's stable state is specifically defined as follows: the temperature fluctuation rate of all load nodes does not exceed 5% within 30 minutes;

[0076] The system instability specifically refers to the fact that the heating temperature of at least one load node fluctuates by more than 5% within 30 minutes.

[0077] S2. When a fault occurs, select the optimal shut-off valve for fault isolation based on the location of the fault and isolate it; update the topology of the isolated multi-source network, perform hydraulic calculations for the heating network, and update the network parameters of the multi-source network; decouple the updated multi-source network and update the heat source parameters of each heat source.

[0078] The process of selecting the optimal shut-off valve for fault isolation based on the location of the fault and isolating it specifically involves:

[0079] To determine the location of the fault, if there are valves on all sides of the pipeline where the fault occurs, select the nearest valve as the optimal valve to close. If there are no valves on either side of the pipeline where the fault occurs, start from the node on the valveless side of the pipeline where the fault occurs and perform a breadth-first traversal of the thermal system network in the integrated heat-electricity energy system. When a valve is encountered in any search direction, close the valve and stop the search in that direction. Continue traversing until the search in all directions stops.

[0080] The process of performing hydraulic calculations for the heating network and updating the network parameters of the multi-source network specifically involves:

[0081] Obtain the minimum spanning tree of the graph structure of the integrated thermal-electric energy system. Divide each pipe into branches and chains based on the pipe resistance characteristics. Initialize the chain mass flow rate and calculate the corresponding branch mass flow rate by inverting the full-rank matrix of the branch incidence matrix.

[0082]

[0083] In the formula, For the mass flow rate of tree branches, The tree-tree correlation matrix, This is the chain-branch incidence matrix. The net injection or net extraction mass flow rate of a node. For the chain branch mass flow rate;

[0084] Calculate the iteration matrix:

[0085]

[0086]

[0087] In the formula, the iteration matrix M It is the Jacobian matrix of the loop pressure drop equation with respect to the chain branch mass flow rate; This is the basic loop matrix, used to depict the relationship between each pipe and each loop; For flow resistance, Represents a diagonal matrix; For the mass flow rate of each pipeline; Pressure drop in a single pipe; The pressure provided to the circulating pump, The pressure consumed by the load.

[0088] Calculate the mass flow correction for the chain branch :

[0089]

[0090] If the chain branch mass flow correction is less than the set error convergence limit, the original chain branch mass flow remains unchanged, and the current tree mass flow and chain branch mass flow are output. Otherwise, an iterative correction process is executed, specifically: the chain branch mass flow data is updated to the original chain branch mass flow data plus the chain branch mass flow correction, and the tree mass flow is recalculated based on the updated chain branch mass flow. The chain branch mass flow correction is then checked again to see if it is less than the set error convergence limit. If it is not less, the iterative correction process is repeated until the chain branch mass flow correction is less than the set error convergence limit.

[0091] S3. Based on the heat source parameters of each heat source, query the output coefficient table of the heat source output-heat load relationship, obtain the corresponding output coefficient, calculate the latest output value of each unbalanced heat source node, and adjust its output to that output value.

[0092] S4. Determine whether the fault recovery of the integrated heat-power energy system has reached the set design target based on the average heating temperature of the heat network nodes before and after the fault recovery. If it has not been reached, repeat steps S1 to S3.

[0093] The determination of whether the fault recovery of the integrated heat and power energy system has achieved the design target is as follows:

[0094] Calculate the relative change rate of the average heating temperature of the heat network nodes after the fault is restored compared with that before the fault, and determine whether the relative change rate is less than 10%. If it is less than 10%, it means that the fault restoration of the integrated heat-electricity energy system has achieved the design target.

[0095] This invention also claims protection for an energy system heat network fault recovery system based on the aforementioned method and multi-source network decoupling, comprising an output coefficient table construction module, a heat source parameter update module, a heat source output control module, and a fault recovery status judgment module, specifically including:

[0096] The output coefficient table construction module constructs a multi-source network based on the integrated heat-electric energy system, decouples the multi-source network, generates a single heat source network with multiple non-equilibrium heat source nodes, and conducts simulation experiments on each single heat source network to obtain an output coefficient table representing the relationship between heat source output and heat load under different heat source parameters.

[0097] The heat source parameter update module, when a fault occurs, selects the optimal shut-off valve for fault isolation based on the fault location and isolates it; updates the topology of the isolated multi-source network, performs hydraulic calculations for the heating network, and updates the network parameters of the multi-source network; decouples the updated multi-source network and updates the heat source parameters of each heat source.

[0098] The heat source output control module queries the output coefficient table of the heat source output-heat load relationship based on the heat source parameters of each heat source to obtain the corresponding output coefficient, calculates the latest output value of each unbalanced heat source node, and controls its output to that output value.

[0099] The fault recovery status judgment module determines whether the fault recovery of the integrated heat-power energy system has reached the set design target based on the average heating temperature of the heat network nodes before and after the fault recovery. If it has not reached the target, it returns to the output coefficient table construction module.

[0100] Example 2:

[0101] Examples, as shown in the appendix Figure 2 As shown, in this embodiment, there are two energy networks: a heating network and a power grid, as well as energy coupling devices such as electric boilers. The parameters of these devices do not have a substantial impact on the method proposed in this invention, and therefore will not be described in detail here. In this embodiment, the standard outlet water temperature of the heat source at the heating network balance node is 70°C, the maximum load temperature difference is 40°C, the original network information contains 35 pipes, and the maximum total heat load is approximately 3MW.

[0102] In the offline state without any faults, the original multi-source heat network is decoupled into several equivalent single heat source networks according to the multi-source heat network decoupling method. Several simulation experiments with varying heat loads and varying number of pipes are carried out on the single heat source networks of unbalanced node heat sources. The output value and actual heat supply value are recorded for each unbalanced node heat source, and the heat supply-load ratio of each unbalanced node heat source is calculated. Within a certain error range, the output coefficient table describing the relationship between heat source output and heat load is as follows, and is kept by the heat network company.

[0103]

[0104] When a pipe bursts in pipeline No. 33 of the heating network, the fault recovery method shall be implemented as follows:

[0105] In the embodiment, the system heating network valves are configured as follows: Figure 3 As shown, according to the isolation principle, the two valves located to the left of the burst point of pipeline No. 33 and pipeline No. 30 are closed, and the updated heating network topology is as follows. Figure 4 As shown. Hydraulic calculations of the heating network show that the water flow in pipes 6 and 27 is reversed.

[0106] Therefore, the non-single heat source heating load points, related junction pipes and junction nodes of the system after fault isolation are as follows.

[0107]

[0108] Based on this, the three single heat source networks obtained through decoupling are as follows: Figure 5 As shown, the heat sources for subnetworks I and II are CHP2 and CHP1, respectively, and the heat source for subnetwork III is the balancing node heat source EB. The heating status of each heat source after isolation is updated according to the mass flow rate output ratio as follows.

[0109]

[0110] According to the updated single-heat-source network topology and heating information, the CHP2 (node ​​1) heating network has 24 pipes with a total supply load of 0.3395MW; the CHP1 (node ​​31) heating network has 26 pipes with a total supply load of 0.1180MW. Based on this, the output coefficient table shows that the output coefficient for CHP2 is 1.4096, and the calculated heat power should be updated to 0.47855MW; the output coefficient for CHP1 is 3.3501, and the calculated heat power should be updated to 0.39530MW.

[0111] After updating the original heating network system, observe the average temperature of the heating network nodes and the average rate of change of the node temperature, as follows: Figure 6 , 7 As shown, the fault simulation begins at 1800s, and the heat source output regulation begins at 7200s. The solid line represents the supply water temperature, and the dashed line represents the return water temperature.

[0112] As shown in the figure, the average temperature of the heating network nodes and the average rate of change of node temperature have both decreased significantly compared with before the application of the recovery strategy, proving that the recovery is good and there is no need to update the coefficient table.

[0113] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above examples; the examples and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for fault recovery of a heat network in an energy system based on multi-source network decoupling, characterized in that, The method includes the following steps: S1. Construct a multi-source network based on the integrated heat-electricity energy system. Decouple the multi-source network to generate a single-source network with multiple non-equilibrium heat source nodes. Conduct simulation experiments on each single-source network to obtain an output coefficient table representing the output-heat load relationship of each heat source under different heat source parameters. The heat source parameters include heat load and the number of pipes. The simulation experiment specifically involves: first, keeping all parameters except the heat source parameters unchanged, using multiple set heating powers as the total heat load values, evenly distributing the total heat load values ​​to each load node, simulating until the system reaches a stable state, and recording this result. The output value of the heat source is calculated. Then, the distance from each pipe to the heat source is calculated, which is the number of pipes through which hot water flows from the heat source to that pipe. The pipes are isolated in descending order of distance, so that the number of remaining pipes in the single heat source network after isolation decreases sequentially according to a preset gradient value, provided that the number of remaining load nodes is not zero. Under the condition that the number of remaining pipes decreases sequentially according to the preset gradient value, the variable heat load power is simulated. After the system stabilizes, the output value of the heat source is recorded. If the system becomes unstable, the experimental data of that set is discarded. S2. When a fault occurs, select the optimal shut-off valve for fault isolation based on the location of the fault and isolate it; update the topology of the isolated multi-source network, perform hydraulic calculations for the heating network, and update the network parameters of the multi-source network; decouple the updated multi-source network and update the heat source parameters of each heat source. S3. Based on the heat source parameters of each heat source, query the output coefficient table of the heat source output-heat load relationship, obtain the corresponding output coefficient, calculate the latest output value of each unbalanced heat source node, and adjust its output to that output value. S4. Determine whether the fault recovery of the integrated heat-power energy system has reached the set design target based on the average heating temperature of the heat network nodes before and after the fault recovery. If it has not been reached, repeat steps S1 to S3.

2. The energy system heating network fault recovery method based on multi-source network decoupling according to claim 1, characterized in that: The construction of a multi-source network based on the integrated heat-electricity energy system specifically includes: Establish a graph structure for the integrated heat-electricity energy system. Each heat network node in the system serves as a node in the graph structure, including heat sources, intermediate nodes, and load nodes. Pipes connecting each heat network node serve as edges, and network parameters of the multi-source network serve as attributes of the edges. If the detected mass flow rate data of a pipe is the same as the initial recorded mass flow rate value, the network parameter corresponding to that pipe is a positive value; otherwise, it is a negative value.

3. The energy system heat network fault recovery method based on multi-source network decoupling according to claim 1, characterized in that: The set heating power ranges from 1% to 90% of the maximum heating power of the heat source. The proportion of the remaining pipe quantity to the original quantity is set according to preset gradient values ​​of 80%, 60%, 40%, and 20%.

4. The energy system heating network fault recovery method based on multi-source network decoupling according to claim 3, characterized in that: The system's stable state is specifically defined as follows: the fluctuation rate of the heating temperature at all load nodes does not exceed a set proportion within a set time period.

5. A method for energy system heat network fault recovery based on multi-source network decoupling according to claim 1 or 4, characterized in that: The process of selecting the optimal shut-off valve for fault isolation based on the location of the fault and isolating it specifically involves: To determine the location of the fault, if there are valves on all sides of the pipeline where the fault occurs, select the nearest valve as the optimal valve to close. If there are no valves on either side of the pipeline where the fault occurs, start from the node on the valveless side of the pipeline where the fault occurs and perform a breadth-first traversal of the thermal system network in the integrated heat-electricity energy system. When a valve is encountered in any search direction, close the valve and stop the search in that direction. Continue traversing until the search in all directions stops.

6. The energy system heat network fault recovery method based on multi-source network decoupling according to claim 5, characterized in that: The process of performing hydraulic calculations for the heating network and updating the network parameters of the multi-source network specifically involves: Obtain the minimum spanning tree of the graph structure of the thermal-electric integrated energy system, and divide each pipe into branches and chains according to the resistance characteristics of the pipes; when the chain branch mass flow rate correction is less than the set error convergence limit, keep the original network chain branch mass flow rate unchanged, and output the branch mass flow rate and chain branch mass flow rate at this time. Otherwise, perform an iterative correction process, specifically: update the mass flow rate data of the chain branches to the original mass flow rate data of the chain branches plus the correction amount of the mass flow rate of the chain branches, and recalculate the mass flow rate of the branches based on the updated mass flow rate of the chain branches. Next, determine whether the chain branch mass flow rate correction is less than the set error convergence limit. If it is not less, repeat the iterative correction process until the chain branch mass flow rate correction is less than the set error convergence limit. The calculation of the branch mass flow rate is shown in the following formula: In the formula, For the mass flow rate of tree branches, The tree-tree correlation matrix, This is the chain-branch incidence matrix. The net injection or net extraction mass flow rate of a node. For the chain branch mass flow rate; Chain branch mass flow correction The calculation method is as follows: In the formula, M It is the Jacobian matrix of the loop pressure drop equation with respect to the chain branch mass flow rate; This refers to the pressure drop of a single pipe.

7. The energy system heat network fault recovery method based on multi-source network decoupling according to claim 6, characterized in that: The determination of whether the fault recovery of the integrated thermal-electric energy system has met the set design targets is as follows: Calculate the relative rate of change of the average heating temperature of the heat network nodes after the fault is restored compared with that before the fault, and determine whether the relative rate of change is less than the set threshold. If it is less than the threshold, it means that the fault restoration of the integrated heat-electricity energy system has reached the set design target.

8. A fault recovery system for a heat network based on multi-source network decoupling, according to the method of any one of claims 1-7, comprising an output coefficient table construction module, a heat source parameter update module, a heat source output control module, and a fault recovery status judgment module, characterized in that: The output coefficient table construction module constructs a multi-source network based on the integrated heat-electric energy system, decouples the multi-source network, generates a single heat source network with multiple non-equilibrium heat source nodes, and conducts simulation experiments on each single heat source network to obtain an output coefficient table representing the relationship between heat source output and heat load under different heat source parameters. The heat source parameter update module selects the optimal shut-off valve for fault isolation based on the location of the fault when a fault occurs, and isolates it accordingly. The topology of the isolated multi-source network is updated, hydraulic calculations of the heating network are performed, and the network parameters of the multi-source network are updated; the updated multi-source network is decoupled, and the heat source parameters of each heat source are updated. The heat source output control module queries the output coefficient table of the heat source output-heat load relationship based on the heat source parameters of each heat source to obtain the corresponding output coefficient, calculates the latest output value of each unbalanced heat source node, and controls its output to that output value. The fault recovery status judgment module determines whether the fault recovery of the integrated heat-power energy system has reached the set design target based on the average heating temperature of the heat network nodes before and after the fault recovery. If it has not reached the target, it returns to the output coefficient table construction module.

Images