An electric-thermal combined regulation method for heat energy sub-quality utilization

Abstract

The application discloses a kind of electric-thermal combined regulation methods for heat energy sub-quality utilization, belong to the field of integrated energy system optimal scheduling.The method is first according to the demand of heat object to heat energy grade and divides heat load, establishes supply-demand matching relationship and distinguishes heat supply path;Again, the multi-grade heat energy output model of electric heat storage device and constraint are constructed;Then, the joint scheduling optimization model containing multiple constraints is built, and the output plan of each subject is solved with the minimum operation cost as the target;Finally, based on the scheduling result, each grade heat energy price is generated.The application realizes the fine modeling of electric heat storage device and electric-thermal collaborative regulation, avoids heat energy inefficient utilization, improves system operation efficiency, flexibility and economy, and provides support for the optimized application of heat storage resources in integrated energy system.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy system operation control and optimization scheduling technology, specifically involving an electric-thermal joint regulation method for the high-quality utilization of thermal energy. Background Technology

[0002] As integrated energy systems continue to evolve towards higher efficiency, the deep integration of power and heating systems is gradually becoming a key approach to improving energy utilization efficiency. Against this backdrop, the bidirectional conversion and coordinated regulation between electrical and thermal energy are of great significance for promoting the absorption of new energy sources and enhancing the system's flexible adjustment capabilities.

[0003] In practical heating systems, different heat users have significantly different requirements for heat energy quality. For example, steam turbine power generation typically requires a high-temperature steam heat source, industrial production processes have a rigid demand for medium- and high-temperature steam, while residential heating and domestic hot water mainly rely on medium- and low-temperature heat energy. If the differences in heat energy quality are ignored and regulation is only based on the total heat output, it is easy to lead to the inefficient use of high-quality heat energy, or the inability of low-quality heat energy to meet the heating needs of high-quality heat energy users, thereby significantly reducing the overall efficiency and flexibility of the system.

[0004] In existing combined electric and thermal systems, the coupling of electrical and thermal energy mainly relies on equipment such as electric boilers and electric thermal storage devices to convert electrical energy in the power system into thermal energy and supply heat to the load side. With the development of thermal storage materials and structural design, some electric thermal storage devices have already achieved the technology of thermal energy output by quality, enabling the generation and release of thermal energy of different qualities at the equipment level, providing the necessary technical foundation for quality-based heating.

[0005] However, from the perspective of system operation and scheduling, existing technologies generally treat thermal energy as a single equivalent energy source, lacking a unified modeling and coordinated control mechanism for thermal energy at different temperature levels in terms of generation conditions, output capacity, and applicable objects. Existing electric thermal storage or thermal energy storage technologies primarily use "total charge-release heat" as the core control variable at the scheduling level, failing to clearly distinguish the control paths for different qualities of thermal energy and their matching relationships with various types of heat loads at the system level. This makes it difficult to support the control requirements of the same thermal storage unit coordinating the output of different qualities of thermal energy to different heat users. Summary of the Invention

[0006] To address the aforementioned shortcomings, the present invention aims to propose an electric-thermal joint control method for the utilization of thermal energy of different qualities. Under the framework of coordinated operation of the power system and the heating system, this method can clearly distinguish the generation and demand characteristics of thermal energy of different qualities, characterize the ability and constraints of the electric thermal storage device to output multi-level thermal energy, and realize the joint control of electrical energy and thermal energy of different qualities.

[0007] The technical solution adopted in this invention is: an electro-thermal joint control method for the quality utilization of thermal energy, comprising the following steps:

[0008] Step S1. Obtain the heat load demand information of each heat user in the system, and classify the heat load into different grades according to the differences in the heat energy grade demand of the heat user; determine the available heat range of different heat supply entities for each heat user, establish the supply and demand matching relationship of each grade of heat energy, and distinguish the heat supply path as direct heat supply and heat supply via pipeline.

[0009] Step S2. For the electric thermal storage device, establish a capability model for outputting thermal energy of different qualities under different operating or energy states, and set output constraints for each quality of thermal energy to characterize the operating characteristics of the electric thermal storage device in providing multi-level thermal energy to different heat users.

[0010] Step S3. Introduce the electric thermal storage device into the electric thermal control system, construct a joint scheduling optimization model, including power balance constraints, supply and demand balance constraints of thermal energy of each grade, constraints of power generation entities, constraints of heat generation entities, and constraints of electric thermal storage devices. With the minimum system operating cost as the objective function, perform unified optimization and solution for the output of electrical energy and thermal energy of each grade to obtain the output plan of each power generation entity and heat supply entity in each time period.

[0011] Step S4. Based on the joint scheduling optimization results, generate the corresponding price of each grade of heat energy according to the marginal supply cost and additional cost of each grade of heat energy in the system operation, and determine the transaction price of heat energy among the various entities.

[0012] Furthermore, in step S1, the power generation units in the system are divided into steam turbines that can accept heat from thermal storage bodies and other generator sets that do not accept heat from thermal storage bodies. Based on the differences in heat quality requirements of different heat users, the system load is divided into steam turbine heat load, industrial heat load, and residential heat load. Considering the differences in the heat supply paths for different heat users, the steam turbine heat load and industrial heat load adopt a direct heating method, meaning that heat energy is supplied to the heat users by electric thermal storage devices or industrial-side gas-fired steam boilers through direct connection, and the heating process does not pass through the residential heating network. The residential heat load adopts a heating method that is transported through the heating network, meaning that heat energy is injected into the residential heating network by electric thermal storage devices or residential-side heat sources, and then supplied to the residential heat load after being transported through the network. Based on this, and based on the access information of the electric thermal storage devices, industrial-side heat sources, and residential-side heat sources in the system, a heat matching relationship is established between different heat supply entities and various heat users to determine the set of equipment that can directly or indirectly receive heat during the joint control process for various heat users.

[0013] Furthermore, in step S2, power and energy constraints of the thermal storage body are established. The thermal energy output level of the thermal storage body varies under different energy levels. When the energy of the thermal storage body is in the low range, it only supplies heat to the external residential heating network; when the energy of the thermal storage body is in the medium range, it supplies heat to the external residential heating network or to industrial loads; when the energy of the thermal storage body is in the high range, it supplies heat to the external residential heating network, to industrial loads, and to the steam turbine. The operating logic of the segmented heating of the thermal storage body is characterized by binary states, and it is transformed into mixed integer linear constraints through the Big-M method to realize the characterization of the heating capacity of the thermal storage body under different energy levels.

[0014] Furthermore, in step S2, during the operation of the thermal storage body, electrical power is input and then converted into effective heat charging power through electro-thermal conversion. During the heat release phase, the thermal storage body releases the stored thermal energy, and its total heat release power is used to supply heat to the steam turbine, industrial load, and residential heating network, respectively. The sum of each heat release branch constitutes the total heat release power of the thermal storage body. Moreover, the power and energy state of the thermal storage body are subject to physical constraints, the expression of which is as follows:

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[0021] In the formula: heat storage body The total heat load that can be supplied by the steam turbine; heat storage body The connected industrial heat load collection; heat storage body The connection point for the residential heating pipeline; , Regenerator During the period , energy, heat storage body During the period Effective heat charging power, heat storage body During the period The heat dissipation power, The length of a single scheduling period. heat storage body Energy retention coefficient, , Regenerator The heat dissipation efficiency, heat storage body The electrothermal conversion efficiency, heat storage body During the period Input electrical power, , Regenerator The upper and lower limits of input power, , Regenerator The upper and lower limits of heat release power, heat storage body During the period steam turbine The heat dissipation power, heat storage body During the period To industrial load The heat dissipation power, heat storage body During the period Connection point to residential heating pipeline The heat dissipation power, , Regenerator The upper and lower limits of thermal storage capacity.

[0022] In step S2, the operating logic of the segmented heating of the heat storage body is characterized using binary states, and then transformed into mixed integer linear constraints using the Big-M method, the expression of which is as follows:

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[0032] In the formula: , Regenerator Low-energy threshold and high-energy threshold; , , Regenerator During the period Indicator variables located in the low / medium / high energy range; It is 10000; , Regenerator steam turbine The upper and lower limits of the heat supply; , Regenerator To industrial load The upper and lower limits of the heat supply; , Regenerator Midpoint of residential heating pipeline The upper and lower limits of the heat supply.

[0033] Furthermore, in step S3, the constraints of the joint scheduling optimization model are specifically as follows:

[0034] Power balance constraints: The system power balance is characterized by linearized power flow equations, and the voltage of each node and the power flow of each branch are limited within a preset range;

[0035] Power generation constraints: The output of each generator set is limited to the preset upper and lower limits;

[0036] Heat supply and demand balance constraints for each grade: Differentiated heat power balance equations are established for heat loads used by steam turbines, industrial heat loads, and residential heat loads.

[0037] Constraints on heat production entities: The heat production capacity of industrial gas-fired steam boilers and residential water boilers is limited to the preset upper and lower limits;

[0038] Constraints of electric thermal storage devices include power constraints, energy constraints, and output constraints of thermal energy of various qualities of the thermal storage body.

[0039] Furthermore, in step S3, the linearized power flow equations are used to characterize the system's power balance as follows:

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[0048] In the formula: This represents the total number of nodes in the power system. , They are nodes exist Constantly inject active power and reactive power; , They are nodes exist The per-unit values ​​of the bus phase and voltage amplitude at any given time; , They are nodes exist The per-unit values ​​of the bus phase and voltage amplitude at any given time; , They are nodes and nodes The line between The active and passive currents of time This is the system's baseline capacity; , They are nodes and nodes The per-unit values ​​of the line resistance and reactance; , They are respectively Time Node The active power and reactive power generated by the steam turbine; , They are respectively Time Node The active and reactive power generated by other generators; , They are respectively Time Node The active and reactive load power; for Time Node Input electrical power of the heat storage body For formula Lagrange multipliers;

[0049] The expressions for the voltage at each node and the power flow limitation range of each branch are as follows:

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[0053] In the formula: , They are nodes and nodes The upper and lower limits of active power between; , They are nodes and nodes The upper and lower limits of reactive power between; , They are nodes Voltage upper and lower limits;

[0054] The expressions for the output limit range of each generator are as follows:

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[0057] In the formula: , Each node The upper and lower limits of the active power of the steam turbine; , Each node The upper and lower limits of the active power of other generators;

[0058] The total heat received by a directly connected heating load is equal to the sum of the heat supplied by all heat sources directly connected to it; the total heat received by a piped heating load is obtained by the net injected heat power of the system through power distribution at the network level.

[0059] The steam turbine's heat load is supplied by electric thermal storage devices and internal heat sources within the plant, and its constraint expression is as follows:

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[0063] In the formula: For steam turbine A collection of connected electric thermal storage devices; For steam turbine During the period The heat absorbed; For steam turbine During the period The heat power absorbed by coal combustion; , Steam turbine During the period The upper and lower limits of heat absorption from the electric thermal storage device; For steam turbine During the period Total electrical power generated; For steam turbine The energy conversion coefficient that converts heat energy into electrical energy;

[0064] The industrial heat load is supplied by electric thermal storage devices and industrial-side gas-fired steam boilers, as expressed below:

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[0067] In the formula: For industrial load A collection of directly connectable electric thermal storage devices; For industrial load A collection of industrial-side gas-fired steam boilers that can be directly connected; For industrial load During the period Required thermal power; industrial-side gas-fired steam boiler During the period The released heat power; industrial-side gas-fired steam boiler During the period The released heat power; , Industrial-side gas-fired steam boilers During the period The upper and lower limits of the released heat power. For formula Lagrange multipliers;

[0068] The residential heat load is provided by electric thermal storage devices and residential water boilers, as expressed below:

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[0080] In the formula: Points in the residential heating pipe network All connected residential water boilers; Points in the residential heating pipe network All connected electric thermal storage devices; Points in the residential heating pipe network All residential heating loads connected; For time period node Heat load at the location; For time period Residential heating load Required calories; For time period Residential water boilers Generates thermal power; It is the specific heat capacity of water; For nodes The heat exchange flow rate; It is a node The nearest upstream node; It is a node Heat release is near downstream nodes; , Time periods node , The water supply temperature; , Time periods node , The return water temperature; , These are the nodes for the water supply pipe and the return pipe. arrive Traffic; , These are the nodes for the water supply pipe and the return pipe. arrive Traffic; For time period node Accepting nodes The water supply temperature; For water supply period node To the node The water supply temperature; For the return water pipe period node Accepting node The return water temperature; For time period node To the node Return water temperature; , They are nodes Upper and lower limits of water supply temperature; , They are nodes Upper and lower limits of return water temperature; , , These are pipes Heat transfer coefficient per unit length, length, flow rate; The ambient temperature; For formula Lagrange multipliers.

[0081] Furthermore, in step S3, the expression for the objective function is:

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[0088] In the formula: Total number of scheduling attempts; A collection of steam turbines that can accept heat from thermal storage bodies; A collection of steam turbines heated by unacceptable heat storage media; It is a collection of heat storage bodies; This is a collection of industrial-side gas-fired steam boilers; For the collection of residential side-water boilers; This represents the total operating cost of the system throughout the entire scheduling cycle. , , , , They represent time periods respectively. Generators that do not accept heat from thermal storage bodies Acceptable heating steam turbine and the operating cost of the new type of heat storage body Industrial-side gas-fired steam boilers Cost of residential side water boilers ; For other generators Cost coefficient; For steam turbine The coal cost coefficient; , , Regenerator Provide unit heat cost coefficients for steam turbine heating, industrial heating, and residential heating; industrial-side gas-fired steam boiler The corresponding unit heat cost coefficient; Gas-fired hot water boiler for residential use The corresponding unit of thermal cost coefficient.

[0089] Furthermore, in step S4, the specific process of generating the heat price is as follows:

[0090] First, based on the joint scheduling results of step S3, the values ​​of integer variables in each time period are determined, so that the original mixed integer model degenerates into a continuous convex optimization subproblem;

[0091] Then, the Lagrangian function of this continuous subproblem is constructed, and the dual variables of the corresponding constraints are obtained based on the KKT optimality conditions, as shown in the following formula:

[0092]

[0093] In the formula: For Lagrange functions, Includes all continuous decision variables; These are all equality constraints in the model; For all inequality constraints in the model; The vector that combines all equality-constrained Lagrange multipliers; The vector that combines all inequality-constrained Lagrange multipliers;

[0094] Next, the dual variables are used to characterize the marginal cost level of various heat energy supply and demand balance constraints, and the marginal price of heat energy of different qualities is defined as follows:

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[0098] In the formula: for Nodes within the time period Electricity price, , They are respectively Industrial heat load during the period Hot price Nodes within the time period Heating price for residential use;

[0099] Finally, a virtual turbine heat load demand variable is introduced. By taking the partial derivative of the Lagrange function, its dual variable is obtained and used as the heat price of the steam turbine's heating supply, thus characterizing the price of the high-quality thermal energy from the steam turbine. The formula is as follows:

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[0102] In the formula: for Periodic steam turbine The rigid load demand, i.e. Always equal to zero. for Periodic steam turbine Accepting the heating price For formula Lagrange multipliers.

[0103] This invention also provides an electro-thermal combined control system for the quality utilization of thermal energy, comprising:

[0104] The system includes a data acquisition and supply-demand matching module, an electric thermal storage device modeling module, a joint scheduling and optimization module, and a heat price generation module. It implements the process of the electric-thermal joint control method for high-quality utilization of thermal energy, as described above, through a modular program.

[0105] The data acquisition and supply-demand matching module is used to acquire the heat load demand information of each heat user in the system, classify the heat load into different grades according to the differences in the heat energy grade demand of the heat user, determine the available heat range of different heat supply entities for each heat user, establish the supply-demand matching relationship of each grade of heat energy, and distinguish the heat supply path as direct heat supply and heat supply via pipeline.

[0106] The electric thermal storage device modeling module is used to establish a capability model of the electric thermal storage device to output different quality thermal energy under different operating or energy states, and to set output constraints for each quality of thermal energy in order to characterize the operating characteristics of the electric thermal storage device in providing multi-level thermal energy to different heat users.

[0107] The joint scheduling optimization module is used to introduce the electric thermal storage device into the electric thermal control system, and to construct a joint scheduling optimization model that includes power balance constraints, supply and demand balance constraints of thermal energy of each grade, constraints of power generation entities, constraints of heat generation entities, and constraints of electric thermal storage devices. With the minimum system operating cost as the objective function, the output of electrical energy and thermal energy of each grade is uniformly optimized and solved to obtain the output plan of each power generation entity and heat supply entity in each time period.

[0108] The heat price generation module is used to generate the price of each grade of heat energy based on the joint scheduling optimization results, according to the marginal supply cost and additional cost of each grade of heat energy in the system operation, and to determine the transaction price of heat energy between the various entities.

[0109] The beneficial effects and advantages of this invention are as follows: By constructing a novel thermal storage body operation model for an electric-thermal integrated system, this invention systematically characterizes the ability of the thermal storage body to output different qualities of thermal energy to steam turbines, industrial loads, and residential heating systems under different energy states. This achieves refined modeling and unified control of the thermal storage body's energy state, heating path, and heat release power. Furthermore, by embedding the thermal storage body model into the electric-thermal integrated control system, the control and operation decisions can simultaneously reflect the system's economic efficiency and operational feasibility requirements, effectively improving the flexibility and utilization efficiency of the thermal storage body in multi-energy collaborative operation. Simultaneously, this invention generates heat prices for different qualities of thermal energy based on the joint scheduling results. These heat prices reflect the impact of the system's marginal heating cost, thereby enhancing the guiding role of price signals on system operation. By performing refined modeling and unified control of the thermal storage body at the system level, this invention avoids disordered scheduling during the thermal storage body's heating process, improves the overall system operating efficiency, and enhances the economy, flexibility, and engineering applicability of the electric-thermal integrated system under complex operating conditions. This has significant practical significance and promotional value for the optimized control and large-scale application of thermal storage resources in integrated energy systems. Attached Figure Description

[0110] Figure 1 This is a flowchart of an electro-thermal joint control method for the high-quality utilization of thermal energy according to the present invention.

[0111] Figure 2 This is a system framework diagram of an electro-thermal joint control method for the high-quality utilization of thermal energy according to the present invention.

[0112] Figure 3 This is a topology diagram of an electro-thermal joint control method for the high-quality utilization of thermal energy according to the present invention.

[0113] Figure 4 This diagram shows the scheduling results of a thermal storage body using an electro-thermal joint control method for the high-quality utilization of thermal energy, as described in this invention.

[0114] Figure 5The graph shows the node average electricity price results of an electric-thermal joint control method for the quality utilization of thermal energy according to the present invention.

[0115] Figure 6 The graph shows the heat price result of an electro-thermal joint control method for the high-quality utilization of thermal energy according to the present invention. Detailed Implementation

[0116] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. However, the present invention is not limited to the specific embodiments.

[0117] Example 1

[0118] like Figure 1 As shown, a combined electric-thermal control method for the efficient utilization of thermal energy comprises the following steps:

[0119] Step S1. As Figure 2 As shown, the system acquires the heat load demand information of each heat-consuming object and classifies the heat load into different grades based on the differences in heat energy demand of each heat-consuming object; it establishes the supply and demand matching relationship of heat energy of each grade, determines the available heat range of each heat-consuming object for different heating entities, and distinguishes between direct heating and heating via pipeline. The specific implementation method is as follows:

[0120] First, generator sets are divided into two categories: one category consists of steam turbines that can accept heat from thermal storage media. (Hereinafter referred to as steam turbine), another type is other generators that do not accept heat from heat storage bodies. (Hereinafter referred to as other generators); the load is classified into turbine heat loads based on the heat-consuming objects and their different requirements for heat energy quality. Industrial heat load and residential heating load .

[0121] Heating methods are categorized based on differences in heating pathways: Steam turbine heat users and industrial heat users adopt direct heating, meaning that heat is supplied point-to-point to the corresponding heat load directly by electric thermal storage devices or industrial steam boilers, and the heating process does not enter the residential heating network; residential heat users adopt pipeline heating, meaning that heat is injected into the access node of the residential heating network by electric thermal storage devices or residential hot water boilers, and then supplied to the residential heat users through pipelines.

[0122] Then, obtain the configuration and access information of the electric thermal storage devices in the system, and determine the configuration of each electric thermal storage device. The total heat load that can be supplied by the steam turbine Industrial heat load and residential heating pipe connection points .

[0123] Next, the configuration and access information of industrial gas-fired steam boilers and residential water boilers in the system is obtained, and the configuration of each industrial gas-fired steam boiler is determined. Industrial heat load that can be supplied Identify each residential water boiler Residential heating pipe connection point .

[0124] Based on this, for any steam turbine heat application Determine the collection of electric thermal storage devices that can be used for heating. For any industrial heat-consuming object Determine the set of electric thermal storage devices that can be directly connected. Determine the industrial-side gas-fired steam boiler assembly that can be directly connected. For any residential heating user Determine its access node in the residential heating network. .

[0125] Record the points in the residential heating pipe network All connected residential water boilers are Record the points in the residential heating pipe network All connected electric thermal storage devices are Record the points in the residential heating pipe network The heating load of all connected residential units is .

[0126] Step S2. For the electric thermal storage device, establish a capability model for outputting different qualities of thermal energy under different operating or energy states, and set output constraints for each quality of thermal energy to characterize the operating characteristics of the electric thermal storage device in providing multi-level thermal energy to different heat users; the specific implementation method is as follows:

[0127] During operation, the thermal storage body receives electrical power, which is then converted into effective heat charge through electro-thermal conversion. In the heat release phase, the thermal storage body releases its stored thermal energy. The total heat release power can be used to supply heat to steam turbines, industrial loads, and residential heating networks. The sum of all heat release branches constitutes the total heat release power of the thermal storage body. Furthermore, the power and energy state of the thermal storage body are subject to physical constraints. The expression for the above process is as follows:

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[0134] In the formula: , Regenerator During the period , energy, heat storage body During the period Effective heat charging power, heat storage body During the period The heat dissipation power, The length of a single scheduling period. heat storage body Energy retention coefficient, , Regenerator The heat dissipation efficiency, heat storage body The electrothermal conversion efficiency, heat storage body During the period Input electrical power, , Regenerator The upper and lower limits of input power, , Regenerator The upper and lower limits of heat release power, heat storage body During the period steam turbine The heat dissipation power, heat storage body During the period To industrial load The heat dissipation power, heat storage body During the period Connection point to residential heating pipeline The heat dissipation power, , Regenerator The upper and lower limits of thermal storage capacity.

[0135] During heat release, the stored energy in a thermal storage medium is gradually released. The decrease in energy level directly leads to a drop in the storage medium's temperature, thus limiting the temperature it can provide. Since the heat exchange process requires the heat source temperature to be higher than the outlet temperature of the heated medium, when the energy level of the thermal storage medium is low, its temperature is insufficient to heat the heating medium to a higher temperature level. Therefore, it can only supply heat to external residential heating networks with lower supply water temperature requirements. When the energy level of the thermal storage medium is in the medium range, its temperature level increases accordingly, providing a larger heat exchange temperature difference, thus meeting the heating demand for medium temperature levels. At this time, the thermal storage medium can supply heat to both external residential heating networks and industrial heat loads. When the energy level of the thermal storage medium is in the high range, its internal temperature rises significantly, enabling it to provide a high-temperature heat source, thus meeting high-temperature heat demand. In this state, in addition to supplying heat to external residential heating networks and industrial loads, the thermal storage medium can also provide heat to steam turbines.

[0136] The segmented operation logic described above is characterized by introducing binary state variables and then transforming them into mixed-integer linear constraints using the Big-M method, thereby achieving orderly switching of the heat storage body's heating path under different energy levels. The expression is as follows:

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[0146] In the formula: , Regenerator Low energy threshold and high energy threshold , , Regenerator During the period Indicator variables in the low / medium / high energy range, To be a sufficiently large positive number, in this embodiment we take 10000. , Regenerator steam turbine The upper and lower limits of the heat supply, , Regenerator To industrial load The upper and lower limits of the heat supply, , Regenerator Midpoint of residential heating pipeline The upper and lower limits of the heat supply.

[0147] Step S3. Introduce the electric thermal storage device into the electric thermal control system, construct a joint scheduling optimization model that includes power balance constraints, supply and demand balance constraints for each grade of thermal energy, constraints for power generation entities, constraints for heat production entities, and constraints for the electric thermal storage device. Using the minimum system operating cost as the objective function, perform unified optimization to solve for the output of electrical energy and thermal energy at each grade, obtaining the output plan for each power generation entity and heat supply entity in each time period. The specific implementation method is as follows:

[0148] The power balance of the system is characterized by linearized power flow equations, as shown in the following expression:

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[0157] In the formula: This represents the total number of nodes in the power system. , They are nodes exist Constantly injecting active power and reactive power. , They are nodes exist The per-unit values ​​of the bus phase and voltage amplitude at any given time. , They are nodes exist The per-unit values ​​of the bus phase and voltage amplitude at any given time. , They are nodes and nodes The line between The active and passive currents of time As the system's baseline capacity, , They are nodes and nodes The per-unit values ​​of the line resistance and reactance. , They are respectively Time Node The active power and reactive power generated by the steam turbine. , They are respectively Time Node The active and reactive power generated by other generators, , They are respectively Time Node Active and reactive load power, for Time Node Input electrical power of the heat storage body For formula Lagrange multipliers.

[0158] To ensure the safe operation of the line, the voltage at each node and the power flow in each branch should be limited within a certain range, as expressed below:

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[0162] In the formula: , They are nodes and nodes The upper and lower limits of active power between them. , They are nodes and nodes The upper and lower limits of reactive power between, , They are nodes Voltage upper and lower limits.

[0163] To ensure the safe operation of the generating units, the output of each generator should be limited, as shown in the following expression:

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[0166] In the formula: , Each node The upper and lower limits of the active power of the steam turbine. , Each node The upper and lower limits of the active power of other generators.

[0167] Then, heat power balance equations are established for the steam turbine heat load and industrial heat load that are directly heated, as well as for the residential heat load that is heated through pipelines. The total heat received by the directly connected heat load is equal to the sum of the heat supplied by all heat sources directly connected to it; the total heat received by the pipeline heat load is obtained by the net injected heat power of the system through network-level power distribution.

[0168] The steam turbine heat load is supplied by the electric thermal storage device and the internal heat source of the power plant. It is the amount input to the steam turbine to generate electrical power. However, the electrical power generated by the steam turbine itself is a decision variable in the control system. Therefore, the steam turbine heat load is not a rigid demand, and its constraint expression is as follows:

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[0172] In the formula: For steam turbine During the period The heat absorbed, For steam turbine During the period The heat power absorbed by coal combustion , Steam turbine During the period The upper and lower limits of heat absorption from the electric thermal storage device. For steam turbine During the period Total electrical power generated For steam turbine The energy conversion coefficient that converts heat energy into electrical energy.

[0173] The industrial heat load is supplied by electric thermal storage devices and industrial-side gas-fired steam boilers, and it is a rigid demand, expressed as follows:

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[0176] In the formula: For industrial load During the period Required thermal power industrial-side gas-fired steam boiler During the period The released heat power, , Industrial-side gas-fired steam boilers During the period The upper and lower limits of the released heat power. For formula Lagrange multipliers.

[0177] The residential heat load is provided by electric thermal storage devices and residential water boilers, and it is a rigid demand, expressed as follows:

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[0189] In the formula: For time period Residential heating load Required calories For time period Residential water boilers Generates heat power, It is the specific heat capacity of water. For nodes heat exchange flow rate, It is a node The nearest upstream node, It is a node The heat release is near the downstream node. , Time periods node , water supply temperature, , Time periods node , The return water temperature , These are the nodes for the water supply pipe and the return pipe. arrive Traffic, , These are the nodes for the water supply pipe and the return pipe. arrive Traffic, For time period node Accepting nodes water supply temperature, For water supply period node To the node water supply temperature, For the return water pipe period node Accepting node The return water temperature For time period node To the node Return water temperature, , They are nodes Upper and lower limits of water supply temperature, , They are nodes Upper and lower limits of return water temperature , , These are pipes The heat transfer coefficient per unit length, length, and flow rate. The ambient temperature, For formula Lagrange multipliers.

[0190] The expression for the objective function of minimizing the total cost of the combined electrothermal system is as follows:

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[0195]

[0196]

[0197] In the formula: Total number of scheduling attempts The total operating cost of the system over the entire scheduling cycle. , , , , They represent time periods respectively. Generators that do not accept heat from thermal storage bodies Acceptable heating steam turbine and the operating cost of the new type of heat storage body Industrial-side gas-fired steam boilers Cost of residential side water boilers ; For other generators The cost coefficient, For steam turbine The coal cost coefficient, , , Regenerator Provide unit heat cost coefficients for steam turbine heating, industrial heating, and residential heating. industrial-side gas-fired steam boiler The corresponding unit heat cost coefficient, Gas-fired hot water boiler for residential use The corresponding unit of thermal cost coefficient.

[0198] Step S4. Based on the joint scheduling optimization results, generate the price of each grade of heat energy according to the marginal supply cost and additional cost of each grade of heat energy in system operation; the specific implementation method is as follows:

[0199] First, based on the joint scheduling results of step S3, the values ​​of integer variables in each time period are determined. Under the condition that the values ​​of integer variables are fixed, the original mixed integer model degenerates into a convex optimization subproblem containing only continuous decision variables.

[0200] Subsequently, a Lagrangian function is constructed for this continuous subproblem, and the dual variable formula (51) for the corresponding constraint is obtained based on its KKT optimality condition. The dual variable represents the marginal cost level of various heat energy supply and demand balance constraints under the current operating state and heating structure, and can be used to define the marginal price of heat energy of different qualities, as shown in formulas (52)-(54):

[0201]

[0202]

[0203]

[0204]

[0205] In the formula: For Lagrange functions, Includes all continuous decision variables. These are all equality constraints in the model. For all inequality constraints in the model, The vector that combines all equality-bound Lagrange multipliers. The vector that combines all inequality-constrained Lagrange multipliers. for Nodes within the time period Electricity price, , They are respectively Industrial heat load during the period Hot price Nodes within the time period The price of heating for residential use.

[0206] The heat demand on the turbine side is not an exogenously given rigid demand, but rather a scheduling variable determined by the turbine's output decision. Therefore, the heat power absorbed by the turbine cannot be directly regarded as an independent load and its heat price cannot be defined accordingly. To characterize the marginal value of the heat energy absorbed by the turbine, this invention introduces a virtual turbine heat load demand variable. This virtual demand is identically set to zero in the model, meaning it does not change the original scheduling feasible region or optimal solution; it is only used for price derivation. With fixed integer variable values ​​and the model degenerating into a continuous convex optimization problem, the partial derivative of the corresponding Lagrangian function with respect to this virtual demand variable is obtained. Its dual variable reflects the marginal cost required for the system to provide an additional unit of high-quality heat energy to the turbine under the current operating state. Based on this, the dual variable can be defined as the heat price of the turbine's heating supply, thus characterizing the price of high-quality heat energy from the turbine, as shown in the following formula:

[0207]

[0208]

[0209] In the formula: for Periodic steam turbine rigid load demand ( (constantly equal to zero) for Periodic steam turbine Accepting the heating price For formula Lagrange multipliers.

[0210] Example 2

[0211] The topology diagram of an electro-thermal joint control method for high-quality utilization of thermal energy in this embodiment of the invention is shown below. Figure 3As shown. At the power network nodes, steam turbines that can accept heat from thermal storage, other generators that cannot accept heat from thermal storage, electric thermal storage devices, and power loads are connected; at the heat network nodes, residential water boilers, electric thermal storage devices, and residential heat loads are connected; industrial steam boilers and electric thermal storage devices directly supply heat to industrial heat loads; electric thermal storage devices can supply heat to steam turbines that can accept heat from thermal storage.

[0212] The following is a diagram showing the scheduling results of a thermal storage body using an electro-thermal joint control method for high-quality thermal energy utilization in an embodiment of the present invention. Figure 4 As shown. During periods t2-t3, the new energy units output a large amount of power, and the thermal storage body 1 stores a large amount of heat, creating conditions for providing high-grade heat in t4. Subsequently, in t5-t7, medium-grade heat is used to prioritize supplying rigid industrial loads. When the energy approaches the lower energy limit (t8-t9), the heating capacity degrades, and it can only supply the residential heating network. In t10, the low-price electricity segment is used to quickly recharge to the medium energy zone to restore the medium-grade heating capacity, and in t10-t12, medium-grade heat is used to supply rigid industrial loads. The temporal behavior of thermal storage body 2 is generally consistent with that of thermal storage body 1, but it intervenes in the heating network earlier, and the lower energy limit appears later, but the terminal is more easily pulled to the lower limit by the heating network. This complements the operating strategy of thermal storage body 1, which prioritizes industrial use and maintains the medium energy zone at the terminal.

[0213] The node average electricity price result of an electric-thermal joint regulation method for high-quality utilization of thermal energy in this embodiment of the invention is shown in the figure below. Figure 5 As shown in the diagram, during periods t1 and t12, the renewable energy output is not fully utilized, and the marginal power source is renewable energy units, resulting in extremely low electricity prices. However, during t2, t3, t10, and t11, renewable energy is fully utilized, and conventional units still do not need to output power. This means that for every unit increase in electrical load, the thermal storage reduces its absorption of electrical energy and its release of heat to the thermal load, causing other suppliers of the thermal load to increase their output. Therefore, electricity prices are significantly affected by thermal cost parameters. During periods of high load and limited renewable energy (t4–t9), the system needs to activate conventional thermal power units to fill the gap, meaning the marginal units are conventional thermal power, and electricity prices rise. Although in t4, the thermal storage releases heat to the turbine and generates electricity, conventional units are still required, and the marginal power source is still determined by conventional thermal power; therefore, electricity prices remain high.

[0214] The heat price result diagram of an electro-thermal joint control method for the quality utilization of thermal energy in an embodiment of the present invention is shown in the figure below. Figure 6As shown, for every unit increase in the rigid load demand of the steam turbine, the value of the variable of heat supply from the thermal storage body to the steam turbine decreases. Since the steam turbine generates electricity after thermoelectric conversion, it produces less electricity, which is then generated by traditional thermal power units. Therefore, the heat price equals this marginal electricity price multiplied by the thermoelectric conversion efficiency. The industrial heat price is determined by industrial steam boilers from t3 to t9. From t1 to t2 and t10 to t12, industrial boilers do not operate, and the incremental heat on the industrial side is mainly supplied by the thermal storage body. However, due to resource competition between the industrial and residential sides, the industrial heat price simultaneously reflects the opportunity cost of "residential boilers compensating for the use of thermal storage resources." The residential heat price is determined by residential water boilers from t1 to t11; only at t12 does the marginal main supply on the residential side shift to residential heating via thermal storage.

[0215] The above analysis fully demonstrates that the proposed method can accurately characterize the marginal formation mechanism of electricity price and multi-grade heat price at the system level, clearly reveal the coupled influence of electricity-side constraints, heat-side supply structure and energy state of heat storage on price signals, and provide an interpretable and quantifiable theoretical basis for electricity-heat coordinated operation and price guidance.

Claims

1. A method for combined electric and thermal regulation for the efficient utilization of thermal energy, characterized in that, Includes the following steps: Step S1. Obtain the heat load demand information of each heat user in the system, and classify the heat load into different grades according to the differences in the heat energy grade demand of the heat user; determine the available heat range of different heat supply entities for each heat user, establish the supply and demand matching relationship of each grade of heat energy, and distinguish the heat supply path as direct heat supply and heat supply via pipeline. Step S2. For the electric thermal storage device, establish a capability model for outputting thermal energy of different qualities under different operating or energy states, and set output constraints for each quality of thermal energy to characterize the operating characteristics of the electric thermal storage device in providing multi-level thermal energy to different heat users. Step S3. Introduce the electric thermal storage device into the electric thermal control system, construct a joint scheduling optimization model, including power balance constraints, supply and demand balance constraints of thermal energy of each grade, constraints of power generation entities, constraints of heat generation entities, and constraints of electric thermal storage devices. With the minimum system operating cost as the objective function, perform unified optimization and solution for the output of electrical energy and thermal energy of each grade to obtain the output plan of each power generation entity and heat supply entity in each time period. Step S4. Based on the joint scheduling optimization results, generate the corresponding price of each grade of heat energy according to the marginal supply cost and additional cost of each grade of heat energy in the system operation, and determine the transaction price of heat energy among the various entities.

2. The electro-thermal joint control method for the quality utilization of thermal energy according to claim 1, characterized in that, In step S1, the power generation units in the system are divided into steam turbines that can accept heat from thermal storage bodies and other generator sets that do not accept heat from thermal storage bodies. Based on the differences in heat quality requirements of different heat users, the system load is divided into steam turbine heat load, industrial heat load, and residential heat load. Considering the differences in heat supply paths for different heat users, the steam turbine heat load and industrial heat load adopt a direct heating method, meaning that heat energy is supplied to the heat users by electric thermal storage devices or industrial-side gas-fired steam boilers through direct connection, and the heating process does not pass through the residential heating network. The residential heat load adopts a heating method that is transported through the heating network, meaning that heat energy is injected into the residential heating network by electric thermal storage devices or residential-side heat sources, and then supplied to the residential heat load after being transported through the network. Based on this, and based on the access information of the electric thermal storage devices, industrial-side heat sources, and residential-side heat sources in the system, a heat matching relationship is established between different heat supply entities and various heat users to determine the set of equipment that can directly or indirectly receive heat from various heat users during joint control.

3. The electro-thermal joint control method for high-quality utilization of thermal energy according to claim 2, characterized in that, In step S2, power and energy constraints of the thermal storage body are established. The thermal energy output of the thermal storage body varies at different energy levels. When the energy of the thermal storage body is in a low range, it only supplies heat to the external residential heating network; when the energy of the thermal storage body is in a medium range, it supplies heat to the external residential heating network or to industrial loads; when the energy of the thermal storage body is in a high range, it supplies heat to the external residential heating network, to industrial loads, and to the steam turbine. The segmented heating operation logic of the thermal storage body is characterized by binary states, and it is converted into mixed integer linear constraints by the Big-M method to characterize the heating capacity of the thermal storage body at different energy levels.

4. The electro-thermal joint control method for the quality utilization of thermal energy according to claim 3, characterized in that, In step S2, during operation, the thermal storage body receives electrical power, which is then converted into effective heat charge power through electro-thermal conversion. During the heat release phase, the thermal storage body releases the stored thermal energy. The total heat release power is used to supply heat to the steam turbine, industrial loads, and residential heating networks. The sum of each heat release branch constitutes the total heat release power of the thermal storage body. Furthermore, the power and energy state of the thermal storage body are subject to physical constraints, as expressed below: In the formula: heat storage body The total heat load that can be supplied by the steam turbine; heat storage body The connected industrial heat load collection; heat storage body The connection point for the residential heating pipeline; , Regenerator During the period , energy, heat storage body During the period Effective heat charging power, heat storage body During the period The heat dissipation power, The length of a single scheduling period. heat storage body Energy retention coefficient, , Regenerator The heat dissipation efficiency, heat storage body The electrothermal conversion efficiency, heat storage body During the period Input electrical power, , Regenerator The upper and lower limits of input power, , Regenerator The upper and lower limits of heat release power, heat storage body During the period steam turbine The heat dissipation power, heat storage body During the period To industrial load The heat dissipation power, heat storage body During the period Connection point to residential heating pipeline The heat dissipation power, , Regenerator The upper and lower limits of thermal storage capacity.

5. The electro-thermal joint control method for the quality utilization of thermal energy according to claim 4, characterized in that, In step S2, the operating logic of the segmented heating of the heat storage body is characterized using binary states, and then transformed into mixed integer linear constraints using the Big-M method, the expression of which is as follows: In the formula: , Regenerator Low energy threshold and high energy threshold; , , Regenerator During the period Indicator variables located in the low / medium / high energy range; It is 10000; , Regenerator steam turbine Upper and lower limits of heating capacity; , Regenerator To industrial load Upper and lower limits of heating capacity; , Regenerator Midpoint of residential heating network The upper and lower limits of the heat supply.

6. The electro-thermal joint control method for the quality utilization of thermal energy according to claim 5, characterized in that, In step S3, the constraints of the joint scheduling optimization model are specifically as follows: Power balance constraints: The system power balance is characterized by linearized power flow equations, and the voltage of each node and the power flow of each branch are limited within a preset range; Power generation constraints: The output of each generator set is limited to the preset upper and lower limits; Heat supply and demand balance constraints for each grade: Differentiated heat power balance equations are established for heat loads used by steam turbines, industrial heat loads, and residential heat loads. Constraints on heat production entities: The heat production capacity of industrial gas-fired steam boilers and residential water boilers is limited to the preset upper and lower limits; Constraints of electric thermal storage devices include power constraints, energy constraints, and output constraints of thermal energy of various qualities of the thermal storage body.

7. The electro-thermal joint control method for the quality utilization of thermal energy according to claim 6, characterized in that, In step S3, the linearized power flow equations are used to characterize the system's power balance as follows: In the formula: This represents the total number of nodes in the power system. , They are nodes exist Constantly inject active power and reactive power; , They are nodes exist The per-unit values ​​of the bus phase and voltage amplitude at any given time; , They are nodes exist The per-unit values ​​of the bus phase and voltage amplitude at any given time; , They are nodes and nodes The line between The active and passive currents of time This is the system's baseline capacity; , They are nodes and nodes The per-unit values ​​of the line resistance and reactance; , They are respectively Time Node The active power and reactive power generated by the steam turbine; , They are respectively Time Node The active and reactive power generated by other generators; , They are respectively Time Node The active and reactive load power; for Time Node Input electrical power of the heat storage body For formula Lagrange multipliers; The expressions for the voltage at each node and the power flow limitation range of each branch are as follows: In the formula: , They are nodes and nodes The upper and lower limits of active power between; , They are nodes and nodes The upper and lower limits of reactive power between; , They are nodes Voltage upper and lower limits; The expressions for the output limit range of each generator are as follows: In the formula: , Each node The upper and lower limits of the active power of the steam turbine; , Each node The upper and lower limits of the active power of other generators; The total heat received by a directly connected heating load is equal to the sum of the heat supplied by all heat sources directly connected to it; the total heat received by a piped heating load is obtained by the net injected heat power of the system through power distribution at the network level. The steam turbine's heat load is supplied by electric thermal storage devices and internal heat sources within the plant, and its constraint expression is as follows: In the formula: For steam turbine A collection of connected electric thermal storage devices; For steam turbine During the period The heat absorbed; For steam turbine During the period The heat power absorbed by coal combustion; , Steam turbine During the period The upper and lower limits of heat absorption from the electric thermal storage device; For steam turbine During the period Total electrical power generated; For steam turbine The energy conversion coefficient that converts heat energy into electrical energy; The industrial heat load is supplied by electric thermal storage devices and industrial-side gas-fired steam boilers, as expressed below: In the formula: For industrial load A collection of directly connectable electric thermal storage devices; For industrial load A collection of industrial-side gas-fired steam boilers that can be directly connected; For industrial load During the period Required thermal power; industrial-side gas-fired steam boiler During the period The released heat power; industrial-side gas-fired steam boiler During the period The released heat power; , Industrial-side gas-fired steam boilers During the period The upper and lower limits of the released heat power. For formula Lagrange multipliers; The residential heat load is provided by electric thermal storage devices and residential water boilers, as expressed below: In the formula: Points in the residential heating pipe network All connected residential water boilers; Points in the residential heating pipe network All connected electric thermal storage devices; Points in the residential heating pipe network All residential heating loads connected; For time period node Heat load at the location; For time period Residential heating load Required calories; For time period Residential water boilers Generates thermal power; It is the specific heat capacity of water; For nodes The heat exchange flow rate; It is a node The nearest upstream node; It is a node Heat release is near downstream nodes; , Time periods node , The water supply temperature; , Time periods node , The return water temperature; , These are the nodes for the water supply pipe and the return pipe. arrive Traffic; , These are the nodes for the water supply pipe and the return pipe. arrive Traffic; For time period node Accepting nodes The water supply temperature; Water supply period node To the node The water supply temperature; For the return water pipe period node Accepting node The return water temperature; For time period node To the node Return water temperature; , They are nodes Upper and lower limits of water supply temperature; , They are nodes Upper and lower limits of return water temperature; , , These are pipes Heat transfer coefficient per unit length, length, flow rate; The ambient temperature; For formula Lagrange multipliers.

8. The electro-thermal joint control method for high-quality utilization of thermal energy according to claim 7, characterized in that, In step S3, the expression for the objective function is: In the formula: Total number of scheduling attempts; A collection of steam turbines that can accept heat from a thermal storage medium; A collection of steam turbines heated by unacceptable heat storage media; It is a collection of heat storage bodies; This is a collection of industrial-side gas-fired steam boilers; For the collection of residential side-water boilers; This represents the total operating cost of the system throughout the entire scheduling cycle. , , , , They represent time periods respectively. Generators that do not accept heat from thermal storage bodies Acceptable heating steam turbine and the operating cost of the new type of heat storage body Industrial-side gas-fired steam boilers Cost of residential side water boilers ; For other generators Cost coefficient; For steam turbine The coal cost coefficient; , , Regenerator Provide unit heat cost coefficients for steam turbine heating, industrial heating, and residential heating; industrial-side gas-fired steam boiler The corresponding unit heat cost coefficient; Gas-fired hot water boiler for residential use The corresponding unit of thermal cost coefficient.

9. A method for combined electric and thermal regulation for the quality utilization of thermal energy according to claim 8, characterized in that, In step S4, the specific process of generating the heat price is as follows: First, based on the joint scheduling results of step S3, the values ​​of integer variables in each time period are determined, so that the original mixed integer model degenerates into a continuous convex optimization subproblem; Then, the Lagrangian function of this continuous subproblem is constructed, and the dual variables of the corresponding constraints are obtained based on the KKT optimality conditions, as shown in the following formula: In the formula: For Lagrange functions, Includes all continuous decision variables; These are all equality constraints in the model; For all inequality constraints in the model; The vector that combines all equality-constrained Lagrange multipliers; The vector that combines all inequality-constrained Lagrange multipliers; Next, the dual variables are used to characterize the marginal cost level of various heat energy supply and demand balance constraints, and the marginal price of heat energy of different qualities is defined as follows: In the formula: for Nodes within the time period Electricity price, , They are respectively Industrial heat load during the period Hot price Nodes within the time period Heating price for residential use; Finally, a virtual turbine heat load demand variable is introduced. By taking the partial derivative of the Lagrange function, its dual variable is obtained and used as the heat price of the steam turbine's heating supply, thus characterizing the price of the high-quality thermal energy from the steam turbine. The formula is as follows: In the formula: for Periodic steam turbine The rigid load demand, i.e. Always equal to zero. for Periodic steam turbine Accepting the heating price For formula Lagrange multipliers.

10. An electro-thermal combined control system for the quality utilization of thermal energy, characterized in that, include: The module includes data acquisition and supply-demand matching, electric thermal storage device modeling, joint scheduling and optimization, and heat price generation. The process of the method as described in any one of claims 1-9 is implemented through a modular program; The data acquisition and supply-demand matching module is used to acquire the heat load demand information of each heat user in the system, classify the heat load into different grades according to the differences in the heat energy grade demand of the heat user, determine the available heat range of different heat supply entities for each heat user, establish the supply-demand matching relationship of each grade of heat energy, and distinguish the heat supply path as direct heat supply and heat supply via pipeline. The electric thermal storage device modeling module is used to establish a capability model of the electric thermal storage device to output different quality thermal energy under different operating or energy states, and to set output constraints for each quality of thermal energy in order to characterize the operating characteristics of the electric thermal storage device in providing multi-level thermal energy to different heat users. The joint scheduling optimization module is used to introduce the electric thermal storage device into the electric thermal control system, and to construct a joint scheduling optimization model that includes power balance constraints, supply and demand balance constraints of thermal energy of each grade, constraints of power generation entities, constraints of heat generation entities, and constraints of electric thermal storage devices. With the minimum system operating cost as the objective function, the output of electrical energy and thermal energy of each grade is uniformly optimized and solved to obtain the output plan of each power generation entity and heat supply entity in each time period. The heat price generation module is used to generate the price of each grade of heat energy based on the joint scheduling optimization results, according to the marginal supply cost and additional cost of each grade of heat energy in the system operation, and to determine the transaction price of heat energy between the various entities.

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