An electric heat integrated energy system preventive dispatching method, a terminal and a storage medium

Abstract

This application provides a preventative dispatch method, terminal, and storage medium for an integrated electric and thermal energy system, belonging to the field of power system dispatching technology. It constructs an uncertainty set based on the potential failure of transmission lines under extreme weather conditions and employs a two-stage robust optimization framework. First, a first-stage constraint set is established based on known extreme weather forecasts. Then, a second-stage constraint set is established based on the actual occurrence of extreme weather. The objective function is to minimize the sum of the electrical load gap and the thermal load gap under extreme weather conditions. By establishing the uncertainty set and introducing extreme events into the constraints, a complete two-stage robust preventative dispatch model is formed, which is then solved to obtain the preventative dispatch results. Therefore, backup and energy storage are arranged in advance before extreme weather, and network topology is adjusted to reduce the load gap caused by sudden outages. Robust optimization ensures that the system meets both heating and power supply needs under all possible outage scenarios, improving the overall reliability and resilience of the system.

Description

Technical Field

[0001] This invention relates to the technical field of power system dispatching, and in particular to a preventive dispatching method, terminal, and storage medium for an integrated electric and thermal energy system. Background Technology

[0002] Extreme weather poses a serious threat to exposed power transmission networks (PTNs). Current efforts to address this challenge largely focus on post-disaster emergency recovery or reinforcement of individual power systems, neglecting the deep coupling between power systems and other energy systems. Particularly in urban integrated energy systems centered on combined heat and power (CHP), power outages directly lead to the shutdown of CHP units, subsequently causing a collapse in heat supply, creating a cascading "electricity-heat" failure that significantly amplifies the consequences of disasters.

[0003] With the large-scale application of CHP units, the coupling between the power system and the district heating network is becoming increasingly close. This coupling can improve energy efficiency under normal operating conditions, but it is likely to become a risk transmission channel under extreme weather impacts, leading to more serious cascading power outages. However, if actively guided, it can also be transformed into a key fulcrum for improving system resilience.

[0004] Unlike PTNs, which are susceptible to damage from external forces, District Heating Networks (DHNs) are typically composed of multiple layers of insulated pipes, possessing inherent resistance to interference. More importantly, the hot water within a DHN exhibits significant thermal inertia, allowing it to proactively store substantial amounts of heat before extreme weather events occur through scheduling strategies. Even if CHP units shut down, DHNs can still guarantee heating quality for a certain period, preventing forced reductions in heat load. Furthermore, DHNs are reconfigurable, allowing for dynamic adjustments to the network connections by controlling connection valves and sectional valves. This divides the system into multiple independently operating micro-heating networks, enabling CHP units in unaffected areas to provide heat supplementation to more areas.

[0005] However, most existing research on integrated electric and heat systems (IEHS) still treats DHN regulation as a passive response or ex-post remedy, failing to incorporate its dynamic heat transfer process into a preventative scheduling framework. While some schemes attempt to introduce new energy carriers (such as hydrogen) to enhance flexibility, their reliance on technologies such as hydrogen electrolysis production and storage facilities, which are not yet commercially viable on a large scale, makes them difficult to implement in existing urban energy systems dominated by CHP and DHN.

[0006] Therefore, a preventative scheduling method is needed that is based on existing infrastructure and deeply integrates DHN dynamic energy storage and active reconfiguration capabilities. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to provide a preventive scheduling method, terminal and storage medium for an integrated electric and thermal energy system, which can enhance the ability of the integrated electric and thermal energy system to cope with the risk of power transmission interruption without adding complex energy conversion links.

[0008] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A preventive dispatching method for an integrated electric and thermal energy system includes: An uncertainty set is established based on the uncertainty of power transmission line outages in integrated electric and thermal energy systems under extreme weather conditions; Based on the uncertainty set, an objective function is established to minimize the sum of the electricity load gap and the heat load gap caused by extreme weather. Constraints are established, including a first-stage constraint set of known extreme weather forecasts and a second-stage constraint set of extreme weather occurrences. A two-stage robust preventive scheduling model is established based on the objective function and the constraints. Solve the two-stage robust preventive scheduling model and output the preventive scheduling results.

[0009] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows: A preventive dispatch terminal for an integrated electric and thermal energy system includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the various steps in the aforementioned preventive dispatch method for an integrated electric and thermal energy system.

[0010] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows: A storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned preventive scheduling method for an integrated electrothermal energy system.

[0011] The beneficial effects of this invention are as follows: An uncertainty set is constructed with the potential failure of transmission lines due to extreme weather as the core, and a two-stage robust optimization framework is adopted based on this. First, a first-stage constraint set is set based on known extreme weather forecasts; a second-stage constraint set is set based on the actual occurrence of extreme weather, with the objective function being the minimization of the sum of the electrical load gap and the thermal load gap under extreme weather conditions. By establishing the uncertainty set, extreme events are introduced into second-order constraints, forming a complete two-stage robust preventative scheduling model, which is then solved to obtain the preventative scheduling results. In this way, backup and energy storage are arranged in advance before extreme weather, reducing the load gap caused by sudden outages; robust optimization ensures that the system can still meet both heating and power supply needs under all possible outage scenarios; unnecessary frequent unit switching can be reduced, lowering operating costs and equipment wear; and the overall reliability and resilience of the system are improved. Attached Figure Description

[0012] Figure 1 This is a flowchart of a preventive scheduling method for an integrated electrothermal energy system according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a preventive dispatch terminal for an integrated electric and thermal energy system according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the operating area of ​​the extraction condensing cogeneration unit according to an embodiment of the present invention; Label Explanation: 1. A preventive dispatch terminal for an integrated electric and thermal energy system; 2. A memory; 3. A processor. Detailed Implementation

[0013] Glossary

[0014] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0015] In existing technologies, extreme weather often leads to the instantaneous shutdown of high-capacity transmission lines, resulting in a dual load gap in electricity and heat. Traditional resilience enhancement methods mostly employ deterministic models based on average load or historical extreme values, or only conduct emergency dispatching after a weather event occurs, lacking systematic optimization for "pre-event reservation and in-event compensation." Meanwhile, integrated power and heat energy systems are gradually becoming more widespread: power plants are coupled with various energy carriers such as cogeneration, heating networks, thermal energy storage, and heat pumps through the power network to achieve flexible load balancing and energy complementarity. Due to their internal coupling and multi-energy dual dispatching characteristics, the impact of extreme weather on integrated power and heat energy systems is more complex, and single-dimensional dispatching is insufficient to meet both reliability and economic requirements.

[0016] To address the aforementioned issues, this invention provides a preventative scheduling method for an integrated electric and thermal energy system. This method first constructs an uncertainty set of line outages based on extreme weather forecasts. Then, it uses a two-stage robust optimization approach to pre-arrange preventative decisions regarding generating units, combined heat and power (CHP), and energy storage. Finally, it automatically compensates for load gaps in actual outage scenarios. In this way, the electric and thermal system can maintain power and heat supply while minimizing gaps and operating costs under extreme weather conditions.

[0017] The following details a preventative scheduling method for an integrated electrothermal energy system according to the present invention. Please refer to [link / reference]. Figure 1 This includes the following steps: S1. Establish an uncertainty set based on the uncertainty of transmission line faults in an integrated electric and thermal energy system under extreme weather conditions.

[0018] Specifically, considering the uncertainty of transmission line faults under extreme weather conditions, the uncertainty range is defined by the maximum number of outages, and an uncertainty set is established:

[0019] In the formula, Represents an uncertain set; To indicate the line l A binary variable indicating whether a fault exists, when Time indicates line l Outage due to malfunction Time indicates line l Normal operation; l Indicates the first l One line, This represents a set of routes.

[0020] S2. Based on the uncertainty set, establish an objective function that minimizes the sum of the power load gap and the heat load gap caused by extreme weather, and establish constraints, including a first-stage constraint set of known extreme weather forecasts and a second-stage constraint set of extreme weather occurrences. Based on the objective function and the constraints, establish a two-stage robust preventive scheduling model.

[0021] Specifically, a two-stage robust preventative scheduling model is established. This model consists of an objective function and constraints, transforming the DHN from a passive transmission channel into an actively schedulable thermal storage and energy routing system. Details are as follows: S21. Establish an objective function that minimizes the sum of the electricity load deficit and the heat load deficit caused by extreme weather:

[0022] In the formula, Represents the set of busbars. Represents the set of thermal nodes. expresst Time bus b Electricity load demand and supply express t Time bus b The actual electrical load supplied express t Momentary thermal nodes n The heat load of supply and demand, express t Momentary thermal nodes n At the actual heat load supplied, Indicates the time step.

[0023] S22. Establish the first-stage constraint set for known extreme weather forecasts.

[0024] Specifically, the daytime unit operation plan, the deployment location of emergency repair personnel, and DHN reconfiguration constraints are determined based on extreme weather forecasts.

[0025] S221. Establish operating state constraints for thermal power units:

[0026] In the formula, To indicate a thermal power unit i exist t A binary variable indicating whether something is running at a given time. Time indicates thermal power unit i exist t Running at all times Time indicates thermal power unit i exist t Service is suspended at all times; To indicate a thermal power unit i exist t A binary variable indicating whether or not the program starts at a given time. Time indicates thermal power unit i exist t Start at any time, when The time indicates that the heat unit is in t Never start; To indicate a thermal power unit i exist t A binary variable indicating whether the machine is stopped at a certain time. 1 indicates a thermal power unit i exist t Always shut down Time indicates thermal power unit i exist t Never stop operating; express t +1 to t+MU iAny time point within a time period is an index to that time point within the time period. If the unit is in t Powering on at +1 time, then In the subsequent MU i It must remain operational within a given time period; therefore, for each moment within that interval... All have ; express t +1 to t+MD i Any time point within a time period is an index to that time point within the time period. If the unit is in t If the machine stops at time +1, then In the subsequent MD i The machine must remain in a stopped state for a given period of time; therefore, for each moment within that interval... All have ; Indicates a heat pump unit i The minimum continuous running time; Indicates a heat pump unit i The minimum continuous downtime; This refers to a collection of thermal power units.

[0027] The operating status reflects the continuous working state of the thermal power unit, while the start-stop status is an event variable that only takes a value of 1 at the instant the thermal power unit transitions from shutdown to operation, indicating a start-up operation has occurred. At other times (including continuous operation, continuous shutdown, or shutdown actions), the value is 0. The operating status describes whether the thermal power unit is currently on, while the start-stop status describes whether the thermal power unit has just been turned on. The start-stop status is only 1 when the operating status changes from 0 to 1.

[0028] As can be seen from the above description, the start-up, shutdown and continuous operation of thermal power units must follow the constraints of physical characteristics to avoid equipment damage caused by frequent start-ups and shutdowns.

[0029] S222. Establish pre-deployment constraints for emergency repair personnel: Pre-deployed nodes on the maintenance path s The number of emergency repair personnel cannot exceed the maximum capacity of the node, and each emergency repair personnel can only be pre-deployed on one node. s Place.

[0030]

[0031] In the formula, To express gratitude to the repair personnel c Are nodes pre-deployed on the maintenance path? s A binary variable, when The time indicated that the repair personnelc Nodes pre-deployed on the maintenance path s , The time indicated that the repair personnel c No nodes are pre-deployed on the maintenance path s ; Nodes on the maintenance path s Maximum number of emergency repair personnel that can be accommodated. A set of pre-deployed nodes for emergency repair personnel. Assemble the repair crew.

[0032] As described above, optimizing the deployment locations of emergency repair personnel in advance ensures that they can quickly reach the faulty line after extreme weather occurs.

[0033] S223. Establish reconfiguration constraints for the thermal network (DHN): As long as the pipeline p When in a connected state, water will flow from the node. j Flow to Node k , or from the node k Flow to Node j Each heating node, except for the heating station, has only one upstream heat source. Heating station nodes cannot have upstream inputs, thus ensuring that the entire heating network presents a radial topology.

[0034]

[0035]

[0036] In the formula, To indicate pipes p A binary variable indicating whether something is enabled or disabled. Time indicates pipeline p Turn on, Time indicates pipeline p closure; , For a binary variable representing the direction of water flow, when Time indicates water flow from the thermal node j Flow to thermal nodes k ,when Time indicates water flow from the thermal node k Flow to thermal nodes j ,when Time indicates water flow from the thermal node k Flow to thermal nodes j ,when Time indicates water flow from the thermal node j Flow to thermal nodes k ,when Time indicates water flow from the thermal node nFlow to thermal nodes j ,when Time indicates water flow from the thermal node j Flow to thermal nodes n ; Indicates a collection of heating pipes. Indicates with pipes p A set of connected thermal nodes. Represents the set of thermal nodes. Indicates thermal nodes n A set of connected thermal nodes. This represents the set of heat nodes connected to the heating station. Represents a set With sets The difference set.

[0037] As described above, by reconstructing constraints, the radial topological characteristics of the DHN can be clearly defined, the reconstruction potential of the DHN can be fully utilized, and the heating topology can be optimized in advance.

[0038] S23. Determine the constraints for the second stage.

[0039] Specifically, the second-stage model aims to address the worst-case operating scenarios after extreme weather actually occurs. Its core lies in coordinating the scheduling of emergency repair resources and the dynamic response of the thermal system to achieve rapid recovery of critical loads and system stability.

[0040] S231. Establish path planning constraints for emergency repair personnel: (1) Departure and initial deployment constraints: For any repair personnel c and nodes on the maintenance path s Only when the repair crew c Pre-deployed on nodes s Only when you are at a certain node can you travel to any other node; otherwise, you cannot. s If pre-deployed, it cannot travel from that node to any other node.

[0041]

[0042] In the formula, To express gratitude to the repair personnel c From the nodes on the maintenance path s Go to node h A binary variable, when The time indicated that the repair personnel c From node s Go to node h ,when The time indicated that the repair personnel c No repair node sGo to node h ; To express gratitude to the repair personnel c From node m Go to node s A binary variable; To express gratitude to the repair personnel c Are nodes pre-deployed on the maintenance path? s A binary variable, when The time indicated that the repair personnel c Nodes pre-deployed on the maintenance path s ,when The time indicated that the repair personnel c No nodes are pre-deployed on the maintenance path s ; This represents the set of nodes on the maintenance path (including faulty lines and nodes pre-deployed by emergency repair personnel).

[0043] (2) Fault repair constraints: If the repair personnel c For the line l Repairs will be carried out, and the line will definitely be checked after the repairs are completed. l Heading to the next location.

[0044]

[0045] In the formula, To indicate whether it is handled by emergency repair personnel c For the faulty line l The binary variable to be repaired, when The time indicated that the repair personnel c For the line l Repair is to be carried out when The time indicated that the repair personnel c No line l Repair; To express gratitude to the repair personnel c From the line l Go to node h A binary variable, when The time indicated that the repair personnel c From the line l Go to node h ,when The time indicated that the repair personnel c No from the line l Go to node h .

[0046] (3) Node traffic flow balance constraints:

[0047] In the formula, To express gratitude to the repair personnel c From node m Go to node h binary variables, To express gratitude to the repair personnel c From node o Go to node m A binary variable.

[0048] (4) Return to maintenance node constraints:

[0049] In the formula, To express gratitude to the repair personnel c From node o Head to the repair node s binary variables, To express gratitude to the repair personnel c From the maintenance node s Go to node h binary variables, To express gratitude to the repair personnel c Are nodes pre-deployed on the maintenance path? s A binary variable.

[0050] in, o , h A node in an emergency repair mission can be a fault point on a power transmission line or a node pre-deployed by repair personnel.

[0051] (5) Time logic constraints:

[0052]

[0053] In the formula, To express gratitude to the repair personnel c An integer variable representing the time elapsed since leaving maintenance node s. To express gratitude to the repair personnel c From node o Go to node h binary variables, To express gratitude to the repair personnel c Leave node h Integer variables of time, Indicates the repair personnel c Repair Node h Time required This indicates that the repair crew started from the node. o To the node h Time required; M represents a sufficiently large positive constant; Indicates the repair personnel c Leave node o Integer variables of time, To indicate whether it is handled by emergency repair personnel c For nodes o The binary variable to be repaired.

[0054] (6) Repair order and completion time constraints: Each faulty node o will not be repaired repeatedly, and will only be repaired by one group of personnel.

[0055]

[0056] In the formula, To represent nodes o exist t A binary variable indicating whether the repair is complete at any given time. Time represents node o exist t Repairs will be completed in a timely manner. Time represents node o exist t The repair was not completed at any time. Indicates the repair personnel c Leave node o An integer variable representing time.

[0057] As described above, the standardizes the entire process logic of emergency repair personnel, from "starting from the repair node, to repairing the fault, and then returning to the repair node." This constraint ensures that repair personnel only start from the pre-deployed repair node, that each faulty line is repaired by only one person, and that the repair and travel times are reasonably coordinated, maximizing fault repair efficiency and shortening power and heating outage duration.

[0058] S232. Establish dynamic operating constraints for DHN: (1) Dynamic heat transfer constraints:

[0059] In the formula, To indicate pipes p A binary variable indicating whether something is enabled or disabled. Time indicates pipeline p Turn on, Time indicates pipeline p closure; To indicate water supply pipes / return pipes p exist t The continuous variable of heat power flowing out at any given time. To indicate water supply pipes / return pipes p exist t The continuous variable of heat power flowing in at any given time; To indicate water supply pipes / return pipes p exist The continuous variable of heat power flowing in at any given time; Indicates pipeline p The heat loss coefficient, Indicates pipeline p Length, This indicates the specific heat capacity of the medium inside the pipe. This represents the mass flow rate constant. To indicate t The continuous variable of heat output of the heat station connected to heat node n at any given time. To indicate pipes p exist t The continuous variable of heat power flowing out at any given time. To indicate t The actual supply heat load at thermal node n is a continuous variable. To indicate pipes p exist t A continuous variable that constantly receives heat power. To indicate water supply pipes p exist t A continuous variable of heat power flowing out at all times. To indicate the return water pipe p exist t A continuous variable of heat power flowing out at all times. To indicate water supply pipes p exist t A continuous variable that constantly receives heat power. To indicate the return water pipe p exist t A continuous variable that constantly receives heat power; Indicates a collection of heating pipes. Represents the set of thermal nodes. Indicates originating from a thermal node n A collection of pipes, Indicates termination at a thermal node. n The set of pipes; M represents a sufficiently large positive constant. Indicates water supply pipe / return pipe p The lower limit of outflowing heat power. Indicates water supply pipe / return pipe p The upper limit of outflowing heat power. Indicates water supply pipe / return pipe p The lower limit of the incoming heat power. Indicates water supply pipe / return pipe p The upper limit of the incoming heat power.

[0060] (2) Constraints of heating stations:

[0061] In the formula, To indicate a heating station a exist t A continuous variable in thermal output at any given moment. To indicate a combined heat and power unit d exist t The continuous variable of thermal output at any given moment; To indicate a back-pressure cogeneration unit e exist t The continuous variable of electrical output at any given time. To indicate a back-pressure cogeneration unit e exist t The continuous variable of thermal output at any given time. Indicates a back-pressure cogeneration unit e Thermoelectric ratio (the ratio of thermal output to electrical output). To indicate a back-pressure cogeneration unit e exist t A binary variable indicating whether something is running at a given time. Time indicates back-pressure cogeneration unit e exist t Running at all times Time indicates back-pressure cogeneration unit e exist t The service is constantly suspended. Indicates a back-pressure cogeneration unit e The lower limit of electrical output, Indicates a back-pressure cogeneration unit e Upper limit of heat output Indicates a collection of heating stations. This indicates a collection of back-pressure combined heat and power units. This refers to a collection of extraction-condensing cogeneration units.

[0062] Please refer to Figure 3 For extraction condensing units, their operating range is described by extreme points:

[0063] In the formula, To indicate extraction condensing unit x exist t The electrical output is a continuous variable at any given time. Indicates extraction condensing unit x The slope of the feasible area boundary, To indicate extraction condensing unit x exist t The continuous variable of thermal output at any given time. All indicate extraction condensing units x The extreme values ​​of heat supply corresponding to the vertices of the feasible region. All indicate extraction condensing units x Extreme values ​​of electric output corresponding to vertices of the feasible region. Indicates extraction condensing unit x Maximum electrical output.

[0064] (3) Heat load constraint:

[0065] In the formula, express t Momentary thermal nodes n Actual heat load supplied express t Momentary thermal nodes n Heat load of supply and demand This represents the set of thermal nodes.

[0066] As can be seen from the above description, the above constraints can take into account the dynamic heat transfer characteristics and heat loss of DHN, thereby accurately depicting the heat transfer process in the pipeline.

[0067] S233. Establish transmission network (PTN) operation constraints.

[0068]

[0069] In the formula, To indicate the line l A binary variable indicating whether a fault exists, when Time indicates line l Outage due to malfunction, when Time indicates line l Normal operation; To indicate the line l exist t A binary variable indicating whether something is running at a given time. Time indicates line l exist t Normal operation at all times, when Time indicates line l exist t Service is suspended at all times; To indicate transmission lines l exist A binary variable indicating whether the repair is complete at any given time. Time indicates line l exist Repairs will be completed in a timely manner. Time indicates line l Not in Repairs are completed in a timely manner. This represents a set of routes.

[0070] (1) Power balance constraint:

[0071] In the formula, To indicate a thermal power unit i At any moment t The electrical output is a continuous variable. To indicate wind turbine w exist t The electrical output is a continuous variable at any given time. To indicate the line l exist t A continuous variable of power flow at any given time. To indicate t Time bus b The actual electrical load is a continuous variable. Indicates the connection with the busbar b A collection of interconnected thermal power units Indicates the connection with the busbar b A collection of interconnected wind turbine units. Indicates the connection with the busbar b A set of connected lines, This represents the set of busbars.

[0072] (2) Line transmission capacity constraints:

[0073] In the formula, To indicate the line l exist t A binary variable indicating whether something is running at a given time. Time indicates line l exist t Normal operation at all times, when Time indicates line l exist t The service is constantly suspended. Indicates the line l The upper limit of transmission capacity, To indicate the line l exist t A continuous variable of power flow at any given time. This represents a set of routes.

[0074] (3) Power output constraints of thermal power units: t The first time period system i The active power of the thermal power unit is between the set safe operating upper and lower limits:

[0075] In the formula, To indicate a thermal power unit i exist t A binary variable indicating whether something is running at a given time. Time indicates thermal power unit i exist t Running at all times Time indicates thermal power unit i exist t The service is constantly suspended. To indicate a thermal power unit i exist t The electrical output is a continuous variable at any given time. Indicates a heat pump unit i The lower limit of electrical output, Indicates a heat pump unit i The upper limit of electrical output; This refers to a collection of thermal power units.

[0076] (4) Power output constraints of wind turbine units: t The first time period system w The active power of the typhoon generator is between the set safe operating upper and lower limits:

[0077] In the formula, To indicate wind turbine w exist t The electrical output is a continuous variable at any given time. Indicates wind turbine w The upper limit of electrical output; This represents a collection of wind turbine units.

[0078] (5) Load reduction constraints:

[0079] In the formula, express t Time bus b Electricity load demand and supply To indicate t Time bus b The actual electrical load supplied is a continuous variable.

[0080] (6) Thermal power units include combined heat and power (CHP) units and non-CHP units. Thermal power unit ramp-up constraints:

[0081] In the formula, To indicate non-cogeneration units g exist t A binary variable indicating whether something is running at a given time. The time indicates non-cogeneration units g exist t Running at all times The time indicates non-cogeneration units g exist t The service is constantly suspended. Indicates non-cogeneration units g Rated shutdown ramp power, Indicates non-cogeneration units g Rated descent ramp power, To indicate non-cogeneration units g exist t The electrical output is a continuous variable at any given time. Indicates non-cogeneration units g Rated starting and ramping power, Indicates non-cogeneration units g Rated climbing power; This refers to a collection of non-cogeneration units.

[0082] As described above, these constraints ensure the safe operation of transmission lines and the power balance of the power system. Line power flow constraints prevent overload, node power balance constraints ensure supply and demand matching, and generator ramping constraints limit sudden changes in output. Together, these three constraints constitute the safety boundary for power system post-fault recovery, ensuring stable power supply during fault repair and preventing secondary faults.

[0083] S24. Generate the final model:

[0084] In the formula, Represents the binary variable vector of the first stage. Represents an uncertain binary variable. Represents an uncertain set; This represents the vector of continuous variables in the second stage. and Vectors representing the binary and integer variables of the second stage, respectively; Indicating the objective function with The corresponding parameter vector, For constant terms; This refers to the constraints of the first phase; Indicating the objective function with The corresponding parameter vector, Indicating the objective function with The corresponding parameter vector, Indicating the objective function with The corresponding parameter vector, This refers to the second-stage constraints other than PTN operational constraints. Refers to PTN operation constraints; The set of real numbers, The set of positive integers.

[0085] S3. Solve the two-stage robust preventive scheduling model and output the preventive scheduling results.

[0086] S31. Establish an outer loop master problem with the objective of minimizing the upper limit of system loss under the worst-case scenario, and use the first-stage constraint set as the constraint conditions of the outer loop master problem:

[0087] In the formula, This represents the maximum system loss in the worst-case scenario. Represents the binary variable vector of the first stage. Indicates the first A continuous variable vector in a scenario and They represent the first Vectors of binary and integer variables in each scenario The parameters passed from the outer loop subproblem to the outer loop master problem in the ro-th iteration of the outer loop are... Indicating the objective function with The corresponding parameter vector, Indicating the objective function with The corresponding parameter vector, Indicating the objective function with The corresponding parameter vector, Indicating the objective function with The corresponding parameter vector, Indicating the objective function with The corresponding parameter vector, For constant terms, The set of real numbers, It is a set of positive integers.

[0088] S32. The outer loop subproblem can be decomposed into an inner loop master problem and inner loop subproblems. An inner loop master problem is established with the objective of maximizing the system loss in the current scenario. The second-stage constraint set is used as the constraint condition for the inner loop master problem:

[0089] In the formula, This represents the system loss in the current scenario. Represents an uncertain set, This represents the continuous variable vector generated by the main problem of the inner loop during the ri-th iteration. The parameters for the inner loop are given by the main problem of the outer loop in the ro-th iteration of the outer loop. , The parameters returned to the main problem of the inner loop in the ri-th iteration of the inner loop are the subproblem parameters for the main problem of the inner loop. For uncertain binary variables, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For constant terms, The set of real numbers.

[0090] S33. Establish an inner loop subproblem with the objective of minimizing the system loss in the current scenario:

[0091] In the formula, This represents the vector of continuous variables in the second stage. and Vectors representing the binary and integer variables in the second stage, respectively. For the parameters passed from the main problem of the inner loop to the subproblems of the inner loop in the ri-th iteration of the inner loop, For constant terms, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, The set of real numbers, It is a set of positive integers.

[0092] S34. Set new constraints for the outer loop:

[0093] In the formula, This represents the continuous variable vector generated by the main problem of the outer loop in the (ro+1)th iteration of the outer loop. and Let represent the vectors of binary and integer variables generated by the main problem of the outer loop in the (ro+1)th iteration of the outer loop, respectively. Represents the binary variable vector of the first stage. The parameters returned from the outer loop subproblem to the outer loop main problem. For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, The set of real numbers, It is the set of positive integers; S35. Set new constraints for the inner loop:

[0094] In the formula, This represents the system loss in the current scenario. This represents the continuous variable vector generated by the main problem of the inner loop in the ri-th iteration of the inner loop. To provide parameters for the inner loop to the outer loop, and The parameters returned to the main problem in the inner loop are the parameters of the inner loop subproblem. For uncertain binary variables, As dual variables, For constant terms, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, For the objective function and The corresponding parameter vector, It is the set of real numbers. It is the set of all non-negative real numbers.

[0095] S36 iteratively solves the outer loop master problem, the inner loop master problem, and the inner loop subproblem, and outputs the preventive scheduling result.

[0096] S361. Initialize the upper and lower bounds of the outer loop, solve the outer loop master problem described in step S31, obtain the optimal solution for the first stage, and update the lower bound of the outer loop.

[0097] Specifically, initialize the number of outer loop iterations. Number of inner loop iterations and initialize the upper bound of the outer loop. Lower bound of outer circulation The initial decision variables of the first stage are used as the initial values ​​for the current iteration. Based on the initial values ​​for the current iteration, the outer loop master problem described in step S31 is solved to obtain the optimal solution for the current first stage decision, and the lower bound of the outer loop is updated. .

[0098] S362. Initialize the upper and lower bounds of the inner loop, input the optimal solution of the first stage into the inner loop, solve the inner loop master problem described in step S32, obtain the worst-case shutdown scenario, and update the upper bound of the inner loop.

[0099] Specifically, enter the inner loop and set the upper bound of the inner loop. Inner loop lower bound Using the first-stage decision scheme obtained in step S361 as input, initialize the second-stage decision variables of the inner loop. Solve the inner loop master problem described in step S32 to obtain the optimal solution of the current inner loop, and update the upper bound of the inner loop. And determine the worst-case shutdown scenario. .

[0100] S363. Solve the inner loop subproblem described in step S33 based on the worst-case shutdown scenario, and update the lower bound of the inner loop.

[0101] Specifically, based on the worst-case scenario obtained in step S362, the inner loop subproblem described in step S33 is solved, and the lower bound of the inner loop is updated. Let the number of iterations in the inner loop be... Then, add the new variables and constraints described in step S35 to the inner loop model, and return to step S362 to continue the iteration.

[0102] S364. Calculate the first difference between the upper bound of the inner loop and the lower bound of the inner loop. If the first difference is less than or equal to a preset convergence value, update the upper bound of the outer loop and fix the current worst-case scenario. If the first difference is greater than the preset convergence value, re-execute the steps of solving the inner loop master problem.

[0103] Specifically, for Make a judgment: if the conditions are met If the inner loop converges, the upper bound of the outer loop will be updated. And fix the worst-case scenario. If the conditions are not met, the steps for solving the inner loop master problem are repeated.

[0104] S365. Calculate the second difference between the upper bound of the outer loop and the lower bound of the outer loop. If the second difference is less than or equal to the preset convergence value, output the preventive scheduling result according to the fixed worst-case scenario. If the second difference is greater than the preset convergence value, re-execute the steps of solving the outer loop master problem.

[0105] Specifically, for Make a judgment: if the conditions are met If the outer loop converges, the preventative scheduling result is output; otherwise, the outer loop iteration count is reduced. Then, add the new variables and constraints described in step S34 to the outer loop model, and return to re-execute the steps of solving the outer loop master problem.

[0106] In summary, this method considers the deep coupling between the power system and the district heating system. Compared to isolated and incomplete analyses of the resilience of the power and heating systems under extreme weather conditions, this method integrates the energy storage characteristics, reconfiguration potential, and pre-deployment of emergency repair personnel within the district heating network (DHN). It proposes a preventative dispatching approach, fully leveraging the complementary advantages of CHP units and the energy storage value of the DHN to improve energy efficiency. This method is applicable to actual dispatching plan development, can be directly adapted to existing energy management systems, has high feasibility, helps reduce operating costs, and simultaneously enhances the resilience of the integrated power and heating energy system under extreme weather conditions.

[0107] Please refer to Figure 2 The present invention also provides a preventive scheduling terminal 1 for an integrated electric and thermal energy system, including a memory 2, a processor 3, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the various steps of the above-described preventive scheduling method for an integrated electric and thermal energy system.

[0108] The present invention also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the various steps of the above-described preventive scheduling method for an integrated electrothermal energy system.

[0109] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A preventive dispatching method for an integrated electric and thermal energy system, characterized in that, include: An uncertainty set is established based on the uncertainty of transmission line faults in an integrated electrothermal energy system under extreme weather conditions; Based on the uncertainty set, an objective function is established to minimize the sum of the electricity load gap and the heat load gap caused by extreme weather. Constraints are established, including a first-stage constraint set of known extreme weather forecasts and a second-stage constraint set of extreme weather occurrences. A two-stage robust preventive scheduling model is established based on the objective function and the constraints. Solve the two-stage robust preventive scheduling model and output the preventive scheduling results.

2. The preventive dispatching method for an integrated electrothermal energy system according to claim 1, characterized in that, Establish an objective function that minimizes the sum of the electricity load deficit and the heat load deficit caused by extreme weather, including: In the formula, Represents the set of busbars. Represents the set of thermal nodes. express t Time bus b Electricity load demand and supply express t Time bus b The actual electrical load supplied express t Momentary thermal nodes n Heat load of supply and demand express t Momentary thermal nodes n Actual heat load supplied Indicates the time step.

3. The preventive dispatching method for an integrated electrothermal energy system according to claim 1, characterized in that, An uncertainty set is established based on the uncertainty of transmission line faults in an integrated electric and thermal energy system under extreme weather conditions, including: In the formula, Represents an uncertain set; To indicate the line l A binary variable indicating whether a fault exists, when Time indicates line l Outage due to malfunction Time indicates line l Normal operation; l Indicates the first l One line, Indicates the maximum number of lines that are out of service. This represents a set of routes.

4. The preventive dispatching method for an integrated electrothermal energy system according to claim 1, characterized in that, Establish the first-stage constraint set for known extreme weather forecasts, including: Establish operating state constraints for thermal power units: In the formula, To indicate a thermal power unit i exist t A binary variable indicating whether something is running at a given time. Time indicates thermal power unit i exist t Running at all times Time indicates thermal power unit i exist t Service is suspended at all times; To indicate a thermal power unit i exist t A binary variable indicating whether or not the event is started at a given time. Time indicates thermal power unit i exist t Start at any time, when Time indicates thermal power unit i exist t Never start; To indicate a thermal power unit i exist t A binary variable indicating whether the machine is stopped at a certain time. Time indicates thermal power unit i exist t Always shut down Time indicates thermal power unit i exist t Never stop operating; for t +1 to t + MU i Any time within the time period; for t +1 to t + MD i Any time within the time period; Indicates a heat pump unit i The minimum continuous running time; Indicates a heat pump unit i The minimum continuous downtime; This represents a collection of thermal power units; Establish pre-deployment constraints for emergency repair personnel: In the formula, To express gratitude to the repair personnel c Are nodes pre-deployed on the maintenance path? s A binary variable, when The time indicated that the repair personnel c Nodes pre-deployed on the maintenance path s , The time indicated that the repair personnel c No nodes are pre-deployed on the maintenance path s ; Represents nodes on the maintenance path s Maximum number of emergency repair personnel that can be accommodated. This represents the set of nodes pre-deployed by emergency repair personnel. This indicates that the repair crew has assembled. Establish reconfiguration constraints for the thermal network: In the formula, To indicate pipes p Whether a binary variable is connected or not, when Time indicates pipeline p Connect, Time indicates pipeline p Turn off; , For a binary variable representing the direction of water flow, when Time indicates water flow from the thermal node j Flow to thermal nodes k ,when Time indicates water flow from the thermal node k Flow to thermal nodes j ,when Time indicates water flow from the thermal node k Flow to thermal nodes j ,when Time indicates water flow from the thermal node j Flow to thermal nodes k ,when Time indicates water flow from the thermal node n Flow to thermal nodes j ,when Time indicates water flow from the thermal node j Flow to thermal nodes n ; Indicates a collection of heating pipes. Indicates with pipes p A set of connected thermal nodes. Represents the set of thermal nodes. Indicates thermal nodes n A set of connected thermal nodes. This represents the set of thermal nodes connected to the heating station. The first stage constraint set is obtained by combining the constraints of the operating status of the thermal power unit, the pre-deployment constraints of the emergency repair personnel, and the reconstruction constraints of the thermal network.

5. The preventive dispatching method for an integrated electrothermal energy system according to claim 1, characterized in that, Establish a second-stage constraint set for extreme weather events, including: Establish path planning constraints for emergency repair personnel, including constraints on the departure and initial deployment of emergency repair personnel, constraints on the fault repair of emergency repair personnel, constraints on the traffic flow balance of nodes, constraints on the return of emergency repair personnel to the repair node, time logic constraints, and constraints on the repair order and completion time of emergency repair personnel. Establish dynamic operating constraints for the thermal network, which include dynamic heat transfer constraints, thermal station constraints, and heat load constraints. Establish operational constraints for the power transmission network, including power balance constraints, line transmission capacity constraints, power output constraints for thermal power units, power output constraints for wind power units, load shedding constraints, and ramping constraints for thermal power units. The second-stage constraint set is obtained by combining the path planning constraints of the emergency repair personnel, the dynamic operation constraints of the thermal network, and the operation constraints of the power transmission network.

6. The preventive dispatching method for an integrated electrothermal energy system according to claim 1, characterized in that, The nested C&CG algorithm is used to solve the two-stage robust preventive scheduling model, and the preventive scheduling results are output, including: Establish an outer loop master problem with the objective of minimizing the upper limit of system loss under the worst scenario, and use the first stage constraint set as the constraint condition of the outer loop master problem; Establish an inner loop master problem with the goal of maximizing the system loss in the current scenario, and use the second-stage constraint set as the constraint condition of the inner loop master problem; Establish an inner loop subproblem with the objective of minimizing the system loss in the current scenario; The outer loop master problem, the inner loop master problem, and the inner loop subproblems are solved iteratively to output the preventive scheduling result.

7. The preventive dispatching method for an integrated electrothermal energy system according to claim 6, characterized in that, The outer loop master problem, the inner loop master problem, and the inner loop subproblems are iteratively solved to output preventative scheduling results, including: Initialize the upper and lower bounds of the outer loop, solve the outer loop master problem, obtain the optimal solution for the first stage, and update the lower bound of the outer loop. Initialize the upper and lower bounds of the inner loop, input the optimal solution of the first stage into the inner loop, solve the main problem of the inner loop, obtain the worst-case failure scenario, and update the upper bound of the inner loop. Solve the inner loop subproblem based on the worst-case failure scenario and update the lower bound of the inner loop; Calculate the first difference between the upper bound of the inner loop and the lower bound of the inner loop. If the first difference is less than or equal to a preset convergence value, update the upper bound of the outer loop and fix the current worst-case scenario. If the first difference is greater than the preset convergence value, re-execute the steps of solving the inner loop master problem. Calculate the second difference between the upper bound and the lower bound of the outer loop. If the second difference is less than or equal to a preset convergence value, output a preventive scheduling result based on the fixed worst-case scenario. If the second difference is greater than the preset convergence value, re-execute the steps of solving the outer loop master problem.

8. The preventive dispatching method for an integrated electrothermal energy system according to claim 7, characterized in that, Solving the inner loop subproblem based on the worst-case failure scenario and updating the lower bound of the inner loop also includes: Add new constraints to the inner loop. These new constraints are used to bind the original variables and dual variables in the second phase.

9. A preventative dispatch terminal for an integrated electric and thermal energy system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements each step of the preventive scheduling method for an integrated electrothermal energy system according to any one of claims 1 to 8.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements each step of the preventive scheduling method for an integrated electrothermal energy system as described in any one of claims 1 to 8.

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