An integrated energy system optimization method, device, equipment and medium

Abstract

Embodiments of the present application disclose a comprehensive energy system optimization method, device, equipment and medium, wherein the method comprises: determining at least one candidate position of a heat storage tank in a comprehensive energy system; the candidate position is located between two heat supply pipelines in a heat supply network of the comprehensive energy system; determining a target function of the comprehensive energy system in a preset time period; the target function comprises a total cost of operation of the comprehensive energy system; and determining an optimization scheme of the comprehensive energy system based on each candidate position, at least one constraint condition and the target function. Through the execution of the technical scheme provided by the embodiments of the present application, complementary utilization of the heat network and the heat storage equipment can be realized, thereby changing the matching curve of the heat and power load, relieving the heat and power coupling relationship of the combined heat and power unit, expanding the flexible adjustment space of the system, improving the consumption level of wind energy, and reducing carbon dioxide emissions.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system technology, and in particular to an integrated energy system optimization method, apparatus, equipment and medium. Background Technology

[0002] In recent years, centralized heating systems using thermal power plants as heat sources have developed rapidly, with many cities' central urban areas forming unified urban centralized heating systems. However, because heating networks utilize the time delay in heat transport to improve system flexibility, their heat storage capacity is passive and cannot achieve uncontrolled heat storage, limiting the extent to which system flexibility can be improved. Even with large-scale wind energy integration, excessive wind energy waste still occurs. Thermal energy storage equipment, by storing and releasing heat, can store excess energy during peak energy production and off-peak consumption periods, thereby achieving energy transfer over time, improving system flexibility and enabling large-scale wind energy utilization. However, its application involves relatively high investment and maintenance costs, resulting in poor economic efficiency.

[0003] The optimization scheme of the integrated energy system (IES) in related technologies does not make full use of the complex pipeline nodes of the heating network. It only treats the thermal storage tank as a supply-side device and does not fully consider the role of the thermal storage tank in the integrated energy system and the changes it causes. As a result, the wind power absorption is not optimal, and thus the economic efficiency is poor. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and medium for optimizing an integrated energy system, which can achieve complementary utilization of heating networks and thermal storage equipment, thereby changing the matching curve of heat and power loads, alleviating the thermoelectric coupling relationship of cogeneration units, expanding the system's flexibility adjustment space, improving the absorption level of wind energy, and reducing carbon dioxide emissions.

[0005] In a first aspect, embodiments of the present invention provide a method for optimizing a comprehensive energy system, the method comprising:

[0006] Identify at least one candidate location for a thermal storage tank in an integrated energy system; the candidate location is located between two heating pipes in the heating network of the integrated energy system.

[0007] Determine the objective function of the integrated energy system over a preset time period; the objective function includes the total operating cost of the integrated energy system.

[0008] The optimization scheme of the integrated energy system is determined based on each of the candidate positions, at least one constraint, and the objective function; the constraints include heating network constraints, thermal storage tank constraints, cogeneration unit constraints, wind turbine constraints, and the power balance constraints of the integrated energy system.

[0009] Secondly, embodiments of the present invention also provide a comprehensive energy system optimization device, the device comprising:

[0010] A thermal storage tank candidate location determination module is used to determine at least one candidate location of a thermal storage tank in an integrated energy system; the candidate location is located between two heating pipelines in the heating network of the integrated energy system;

[0011] The objective function determination module is used to determine the objective function of the integrated energy system over a preset time period; the objective function includes the total operating cost of the integrated energy system.

[0012] The optimization scheme determination module is used to determine the optimization scheme of the integrated energy system based on each of the candidate positions, at least one constraint condition, and the objective function; the constraint conditions include heating network constraints, thermal storage tank constraints, cogeneration unit constraints, wind turbine constraints, and the power balance constraints of the integrated energy system.

[0013] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the integrated energy system optimization method according to any embodiment of the present invention.

[0017] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the integrated energy system optimization method described in any embodiment of the present invention.

[0018] The technical solution provided by this invention identifies at least one candidate location for a thermal storage tank in an integrated energy system. The candidate location is situated between two heating pipes in the integrated energy system's heating network. An objective function for the integrated energy system is determined over a preset time period. This objective function includes the total operating cost of the integrated energy system. An optimization scheme for the integrated energy system is determined based on each candidate location, at least one constraint, and the objective function. The constraints include heating network constraints, thermal storage tank constraints, combined heat and power (CHP) unit constraints, wind turbine constraints, and the power balance constraints of the integrated energy system. By implementing the technical solution provided by this invention, complementary utilization of the heating network and thermal storage equipment can be achieved, thereby altering the matching curve of the heat and power load, alleviating the thermoelectric coupling relationship of the CHP unit, expanding the system's flexibility and adjustment space, improving the absorption of wind energy, and reducing carbon dioxide emissions.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a comprehensive energy system optimization method provided in an embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram of the integrated energy system structure provided in an embodiment of the present invention;

[0023] Figure 3 This is a topology diagram of the heating network structure provided in an embodiment of the present invention;

[0024] Figure 4 This is a schematic diagram of the structure of an integrated energy system optimization device provided in an embodiment of the present invention;

[0025] Figure 5 This is a schematic diagram of an electronic device structure provided in an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "objective," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Figure 1 This is a flowchart of a comprehensive energy system optimization method provided in an embodiment of the present invention. The method can be executed by a comprehensive energy system optimization device, which can be implemented in software and / or hardware and can be configured in an electronic device for comprehensive energy system optimization. The method is applied to scenarios involving the optimization of comprehensive energy systems. Figure 1 As shown, the technical solution provided by the embodiments of the present invention specifically includes:

[0029] S110: Determine at least one candidate location for a thermal storage tank in an integrated energy system.

[0030] The candidate location is situated between two heating pipes in the integrated energy system's heating network.

[0031] Among them, such as Figure 2 , Figure 3 As shown, the integrated energy system includes combined heat and power (CHP) units, heat exchangers, a heating network, a power grid, wind turbines, and CHP loads. The CHP units supply the heat load, while the power grid and wind turbines supply the electrical load. The heating network transports heat energy, and thermal storage tanks are connected to certain nodes in the water supply pipeline. Installing these thermal storage tanks at pipeline nodes within the heating network allows for active heat storage while fully utilizing the high time delay characteristic of heat transport, achieving a combined effect of active and passive heat storage. This, in turn, enables greater utilization of wind energy, reduces fuel consumption, and contributes to carbon emission reduction.

[0032] Since the number and location of heating pipes in the heating network are fixed, and the candidate locations of the heat storage tanks are located between two adjacent heating pipes, this scheme can determine the various candidate locations of heating pipes in the heating network.

[0033] S120: Determine the objective function of the integrated energy system within a preset time period.

[0034] The objective function includes the total cost of operating the integrated energy system.

[0035] The preset time period can be one day or two days, and can be set according to actual needs. The objective function of the integrated energy system within the preset time period can be determined based on the gas purchase cost, electricity purchase cost, unit operation and maintenance cost, renewable energy penalty cost, and carbon emission cost within the preset time period.

[0036] In this embodiment, optionally, determining the objective function of the integrated energy system over a preset time period includes: determining the gas purchase cost, electricity purchase cost, unit operation and maintenance cost, renewable energy penalty cost, and carbon emission cost of the integrated energy system over the preset time period; and determining the objective function of the integrated energy system over the preset time period based on the gas purchase cost, the electricity purchase cost, the unit operation and maintenance cost, the renewable energy penalty cost, and the carbon emission cost.

[0037] For example, this solution can determine the objective function of the integrated energy system over a preset time period based on the following formula:

[0038] C tc =C gpc +C epc +C omc +C rpc +C cec ,

[0039] Among them, C tc C represents the objective function of the integrated energy system over a preset time period. gpc C represents the gas purchase cost of the integrated energy system over a preset time period. epc C represents the electricity purchase cost of the integrated energy system over a preset time period. omc C represents the unit operation and maintenance cost of the integrated energy system over a preset time period. rpc C represents the renewable energy penalty cost of the integrated energy system over a preset time period. cec This indicates the carbon emission cost of an integrated energy system over a predetermined time period.

[0040] Therefore, by determining the objective function of the integrated energy system within a preset time period based on gas purchase cost, electricity purchase cost, unit operation and maintenance cost, renewable energy penalty cost, and carbon emission cost, a reliable data model for the economic optimization of the integrated energy system can be provided, which in turn can provide a calculation basis for determining the optimization scheme of the integrated energy system.

[0041] In this embodiment, optionally, the process for determining the gas purchase cost includes: determining the gas purchase cost based on the hourly power generation of the cogeneration unit, the hourly heating power of the cogeneration unit, the efficiency of the cogeneration unit, and the lower calorific value of natural gas within the preset time period; the process for determining the electricity purchase cost includes: determining the electricity purchase cost based on the hourly grid-purchased electricity volume, the hourly grid-purchased electricity price, the hourly grid-sold electricity volume, and the hourly grid-sold electricity price within the preset time period; the process for determining the unit operation and maintenance cost includes: determining the unit operation and maintenance cost based on the hourly power generation of the cogeneration unit, the cogeneration unit maintenance cost coefficient, the hourly actual power of the wind turbine generator, and the wind turbine generator maintenance cost coefficient within the preset time period; the process for determining the renewable energy penalty cost includes: determining the renewable energy penalty cost based on the hourly predicted power of the wind turbine generator, the hourly actual power of the wind turbine generator, and the renewable energy discard penalty cost coefficient within the preset time period; the process for determining the carbon emission cost includes: determining the carbon emission cost based on the hourly carbon emission of the cogeneration unit, the hourly carbon emission quota of the cogeneration unit, and the carbon emission price within the preset time period.

[0042] This scheme can determine the gas purchase cost for a preset time period based on the following formula:

[0043]

[0044] Among them, C gpc EP represents the daily gas purchase cost of an integrated energy system. CHP,t HP represents the power generation capacity of a combined heat and power (CHP) unit in hour t. CHP,t η represents the heating power of the combined heat and power unit in hour t. CHP LHV represents the efficiency of a combined heat and power (CHP) unit. gas Indicates the low calorific value of natural gas, c gas This indicates the price of natural gas.

[0045] This plan can determine the electricity purchase cost for a preset time period based on the following formula:

[0046]

[0047] Among them, C epc This indicates the daily electricity purchase cost of the integrated energy system. This represents the grid purchase price of electricity in hour t. This represents the electricity price sold by the grid in hour t. This represents the amount of electricity purchased from the power grid in hour t. This represents the electricity sold by the power grid in hour t.

[0048] This solution can determine the unit operation and maintenance costs for a preset time period based on the following formula:

[0049]

[0050] Among them, C omc ε represents the daily operating and maintenance cost of the integrated energy system. CHP This represents the maintenance cost coefficient for combined heat and power (CHP) units. ε represents the actual power output of the wind turbine in hour t. WT This represents the maintenance cost coefficient for wind turbine generator sets.

[0051] This scheme can determine the renewable energy penalty cost for a preset time period based on the following formula:

[0052]

[0053] Among them, C rpc This indicates the daily renewable energy penalty cost of the integrated energy system. This represents the predicted power output of the wind turbine in hour t. This represents the penalty cost coefficient for discarding renewable energy.

[0054] This scheme can determine the carbon emission cost for a preset time period based on the following formula:

[0055]

[0056] Among them, C cec This indicates the carbon emission cost of an integrated energy system within one day. This represents the carbon emissions of the combined heat and power unit in hour t. This represents the carbon emission allowance for the combined heat and power (CHP) unit in hour t. This indicates the price of carbon emissions.

[0057] Therefore, by determining the daily costs of gas purchase, electricity purchase, unit operation and maintenance, renewable energy penalties, and carbon emission costs, the total operating cost of an integrated energy system can be determined, which in turn provides a basis for calculation to determine the optimal solution for the integrated energy system.

[0058] S130: Determine the optimization scheme of the integrated energy system based on each of the candidate positions, at least one constraint condition, and the objective function.

[0059] The constraints include heating network constraints, thermal storage tank constraints, combined heat and power unit constraints, wind turbine constraints, and the power balance constraints of the integrated energy system.

[0060] In this embodiment, optionally, determining the heating power of the cogeneration unit based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network includes: determining the output power of the first pipe connected to the thermal storage tank and the input power of the second pipe based on the candidate location of the thermal storage tank; determining the input power and output power of each pipe in the heating network based on the input power, the output power, the constraints of the heating network, and the constraints of the thermal storage tank; and determining the heating power of the cogeneration unit based on the input power of the inlet pipe and the output power of the outlet pipe connected to the heat exchanger in the heating network.

[0061] Specifically, the first and second pipes can be pipes adjacent to the heat storage tank, respectively. Each heating pipe in the heating network has a corresponding number. Assuming the candidate location of the heat storage tank is at the node between heating pipe 3 and heating pipe 4, the heat storage tank maintains a certain thermal balance with the heat transfer fluid within the heating network during operation. This scheme can determine the heat storage and heat release of the heat storage tank in one day based on the candidate location and the following constraints:

[0062]

[0063] Where l3 represents heating pipe 3 and l4 represents heating pipe 4. This represents the amount of heat stored in the thermal storage tank in hour t. c represents the amount of heat released by the thermal storage tank in hour t. w L represents the heat capacity ratio of water. pipe,sw G represents the collection of water supply pipes in a heating network. l3,t This represents the mass flow rate of pipe l3 in hour t. This indicates the time it takes for heat to flow within pipe l3. G represents the time it takes for heat to flow within pipe l4. l4,t Let t represent the mass flow rate of pipe l4 in hour t, and sw represent the water supply pipe.

[0064] The heat storage capacity of the thermal storage tank is limited, which can be expressed by the following formula:

[0065]

[0066] HP hs,t This represents the actual heat capacity of the thermal storage tank in hour t. and These represent the minimum and maximum heat storage capacity of the thermal storage tank, respectively. and These represent the minimum and maximum thermal coefficients of the thermal storage tank, respectively.

[0067] Thermal storage tanks have certain limitations in heat storage and release during the heat storage and release process, which can be expressed based on the following formula:

[0068]

[0069]

[0070] in, and Let represent the heat stored and heat released by the thermal storage tank in hour t, respectively. and These represent the maximum heat storage capacity and maximum heat release capacity of the thermal storage tank, respectively. and These represent the maximum heat storage coefficient and the maximum heat release coefficient of the thermal storage tank, respectively.

[0071] After determining the heat storage capacity and heat release of the heat storage tank in hour t, this scheme can determine the input and output heat of all heating pipes in the heating network in hour t based on the following heating network constraints. The heating network has certain thermal and hydraulic limitations during operation, which can be described based on the following points:

[0072] a. According to the law of conservation of mass, the sum of the mass flow rates into a node is equal to the sum of the mass flow rates out of that node:

[0073]

[0074] Among them, G l,t This represents the mass flow rate of pipe l in hour t. and Let represent the sets of pipes flowing into node n and out of node n, respectively; l represents the pipe number.

[0075] The upper and lower limits for mass flow rate are as follows:

[0076]

[0077] in, and Let L represent the minimum and maximum mass flow rates of pipe l in hour t, respectively; pipe It represents the collection of all pipes in a heating network.

[0078] b. When circulating water flows through the heating network pipes, a pressure drop loss will occur at both ends of the pipes, which can be expressed as:

[0079]

[0080] Where, ΔPN l,t Le represents the pressure drop loss of pipeline l in hour t; l and R l ρ represents the length and radius of pipe l, respectively; w dc and g represent the density of water and the acceleration due to gravity, respectively; l This represents the coefficient of friction of pipe l.

[0081] c. In addition, when circulating water flows through the circulating water pump installed inside the pipe, the circulating water pump consumes electrical energy to increase the water pressure and overcome the pressure drop loss caused by the water flowing through the pipe. The specific formula is as follows:

[0082]

[0083] in, and These represent the electrical power consumed by the circulating water pump in pipe l in hour t and its efficiency, respectively; PH u,t The pressure rise of pump u in hour t represents the pressure increase of pump u in hour t; c1, c2, and c3 represent different coefficients of the pump; L wp This represents the collection of all water pumps.

[0084] d. According to heat transfer theory, the heat loss in a heating network can be expressed as:

[0085]

[0086] in, and T soil These represent the pipe l at t+Δτ. l The outlet temperature at time t, the inlet temperature of pipe l at hour t, and the soil temperature; ξ l Δτ represents the heat loss coefficient of pipe l. l The delay time of pipe l can be determined based on the following formula:

[0087]

[0088] Among them, G l This represents the mass flow rate of pipe l.

[0089] e. The hot water temperature limits at the inlet and outlet of the pipe are:

[0090]

[0091] in, and These represent the minimum water supply temperature and the maximum water supply temperature, respectively. and These represent the minimum return water temperature and the maximum return water temperature, respectively; L pipe,sw and L pipe,rw These represent the sets of supply water pipes and return water pipes in the heating network, respectively; rw represents the return water pipe.

[0092] f. The hot water mixing temperature at each node in the heating network can be determined based on the following formula:

[0093]

[0094] in, This indicates the hot water temperature at the mixing node.

[0095] After determining the input and output heat of all heating pipes in the heating network, this scheme can determine the input heat of the inlet pipes connected to the heat exchanger and the output heat of the outlet pipes. Then, based on the heat balance constraints of hot water flowing through the heat exchanger, the hourly heating power of the cogeneration unit, the heating power supplied to the building by the heating network, and the heat storage power of the heating network can be determined.

[0096]

[0097]

[0098]

[0099] in, This represents the inlet temperature of heating pipe l1 (the inlet pipe connected to the heat exchanger) in hour t. This represents the outlet temperature of heating pipe l1 (the inlet pipe connected to the heat exchanger) at hour t. This represents the outlet temperature of heating pipe l2 (the outlet water pipe connected to the heat exchanger) at hour t. This represents the inlet temperature (HP) of heating pipe l2 (the outlet pipe connected to the heat exchanger) in hour t. CHP,t η represents the heating power of the combined heat and power unit in hour t. CHP HP indicates the efficiency of a combined heat and power (CHP) unit. bd,t Indicates the building's required thermal power, in HP. DHN,t This represents the thermal storage capacity of the heating network in hour t. This represents the input heat power of the heating network in hour t. This represents the output heat power of the heating network in hour t. This represents the heat loss of the heating network in hour t.

[0100] Therefore, by determining the heating power of the cogeneration unit based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network, it is possible to comprehensively consider the impact of the thermal storage tank on the heating network, determine the heating power and power generation of the cogeneration unit, and provide a reliable data source for subsequent steps.

[0101] In one feasible implementation, optionally, the process of determining the power generation capacity of the cogeneration unit includes: determining the heating power of the cogeneration unit based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network; and determining the power generation capacity of the cogeneration unit based on the heating power of the cogeneration unit and the constraints of the cogeneration unit.

[0102] For example, after determining the hourly heating power of the cogeneration unit, this scheme can determine the power generation power of the cogeneration unit based on its heating power and constraints:

[0103] HP CHP,t =ζ CHP ·EP CHP,t

[0104] Where, ζ CHP This indicates the heat-to-power ratio of a combined heat and power (CHP) unit.

[0105] Furthermore, the power generation and heating capacity of a combined heat and power (CHP) unit are subject to certain limitations, which can be expressed as:

[0106]

[0107]

[0108]

[0109] in, and These represent the downward ramp rate and the upward ramp rate of the combined heat and power (CHP) unit, respectively. This indicates the minimum generating capacity of a combined heat and power (CHP) unit. This indicates the maximum generating capacity of the combined heat and power (CHP) unit. This indicates the minimum heating power of the combined heat and power unit. This indicates the maximum heating power of the combined heat and power unit.

[0110] Therefore, the heating power of the cogeneration unit is determined based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network; the power generation of the cogeneration unit is determined based on the heating power and constraints of the cogeneration unit. This allows for a comprehensive consideration of the impact of the thermal storage tank on the heating network, determining the heating power and power generation of the cogeneration unit, and providing a reliable data source for subsequent steps.

[0111] In another feasible implementation, optionally, the process of determining the actual power of the wind turbine includes: determining the actual power of the wind turbine based on the power generation capacity of the combined heat and power unit, the constraints of the wind turbine, and the power balance constraints of the integrated energy system.

[0112] For example, the constraints of a wind turbine include: the power generation of a wind turbine is highly dependent on wind speed, and the actual power of the wind turbine can be determined based on the following formula:

[0113]

[0114] Among them, EP WP,t N represents the actual power of the wind turbine at time t. WP This indicates the installed capacity of the wind turbine, v. t v iw v aw v ow These represent the actual wind speed, cut-in wind speed, rated wind speed, and cut-out wind speed of the wind turbine, respectively.

[0115] The power balance constraints of an integrated energy system include: the integrated energy system must maintain power balance at all times during operation, which can be expressed as:

[0116]

[0117] in, and EP represents the grid purchase volume and grid sales volume in the integrated energy system at hour t, respectively; load,t EP represents the user's electrical load in hour t; WP,t This represents the power consumption of the circulating water pump in hour t.

[0118] Therefore, the actual power of the wind turbine is determined based on the power generation capacity of the combined heat and power (CHP) unit, the constraints of the wind turbine, and the power balance constraints of the integrated energy system. This allows for the determination of the actual power of the wind turbine, providing a reliable data source for subsequent steps.

[0119] In another feasible implementation, optionally, determining the optimization scheme of the integrated energy system based on each of the candidate positions, at least one constraint, and the objective function includes: for each candidate position, inputting the candidate position into each of the constraints and the objective function to determine the candidate optimization result respectively; and taking the scheme associated with the minimum value among the candidate optimization results as the optimization scheme of the integrated energy system.

[0120] For each candidate location of the thermal storage tank, this scheme can determine the candidate optimization results of the integrated energy system based on the candidate location, various constraints, and the objective function. The minimum value among all candidate optimization results is determined as the optimal candidate optimization result. Then, based on the candidate optimization result, the optimization scheme of the integrated energy system is determined, such as the location of the thermal storage tank, the heat loss and delay time generated during the transportation of heat energy in the heating network, and the heat loss and delay time generated during the transportation of heat released from the thermal storage tank.

[0121] Therefore, by inputting each candidate position into the constraints and objective function, candidate optimization results are determined. The scheme associated with the minimum value among the candidate optimization results is taken as the optimal scheme for the integrated energy system. This allows for the optimization of the integrated energy system, achieving economic minimization.

[0122] The specific effects achievable by the integrated energy system optimization method based on combined thermal storage are as follows: During the day, heat load is low, electricity load is high, and wind power generation is also low. On the one hand, due to the passive thermal storage effect of the heating network, the current heating load is higher than the actual heat load, which promotes the increase of heat output of the cogeneration unit. On the other hand, since thermal storage tanks are installed at the nodes of the heating network, the cogeneration unit can further increase its heat output to store the excess heat in the thermal storage tanks for nighttime heating. Both factors together lead to an increase in the output power of the cogeneration unit, resulting in a heating load higher than the actual heat load, while the electricity load remains unchanged. This makes the equivalent heat-to-power ratio close to the optimal heat-to-power ratio of the cogeneration unit, improving the unit's operating efficiency. At night, heat load and wind power generation are higher, and... The lower electrical load is due to two main factors. First, the delay in heat transport within the heating network causes the current heating load to be lower than the actual heat load, resulting in reduced heat output and electricity output from the cogeneration unit, while increasing wind power consumption. Second, the presence of thermal storage tanks at nodes within the heating network, which store significant amounts of heat energy during the day, allows these tanks to release heat, further reducing the heat output of the cogeneration unit and consequently lowering electricity output. This increases wind power consumption and alleviates the thermoelectric coupling effect. Both factors combined lead to a decrease in the output power of the cogeneration unit, resulting in a lower heating load than the actual heat load, while the electricity load remains unchanged. This makes the equivalent heat-to-power ratio approach the optimal heat-to-power ratio of the cogeneration unit, improving its operating efficiency. Furthermore, since the thermal storage tank is installed at the node, the storage and release of heat in the thermal storage tank also have the dynamic characteristics of the heating network. There is also a certain time difference between its heat storage / release and the load of the unit at the heat source and the user side. This enables the thermal storage tank to adjust its output according to the relationship between thermal and electrical load and wind power generation, thereby further adjusting the heat load curve and promoting the absorption of wind power.

[0123] The technical solution provided by this invention identifies at least one candidate location for a thermal storage tank in an integrated energy system. The candidate location is situated between two heating pipes in the integrated energy system's heating network. An objective function for the integrated energy system is determined over a preset time period. This objective function includes the total operating cost of the integrated energy system. An optimization scheme for the integrated energy system is determined based on each candidate location, at least one constraint, and the objective function. The constraints include heating network constraints, thermal storage tank constraints, combined heat and power (CHP) unit constraints, wind turbine constraints, and the power balance constraints of the integrated energy system. By implementing the technical solution provided by this invention, complementary utilization of the heating network and thermal storage equipment can be achieved, thereby altering the matching curve of the heat and power load, alleviating the thermoelectric coupling relationship of the CHP unit, expanding the system's flexibility and adjustment space, improving the absorption of wind energy, and reducing carbon dioxide emissions.

[0124] Figure 4This is a schematic diagram of the integrated energy system optimization device provided in an embodiment of the present invention. The device can be configured in an electronic device used for integrated energy system optimization. Figure 4 As shown, the device includes:

[0125] The thermal storage tank candidate location determination module 210 is used to determine at least one candidate location of a thermal storage tank in the integrated energy system; the candidate location is located between two heating pipelines in the heating network of the integrated energy system;

[0126] The objective function determination module 220 is used to determine the objective function of the integrated energy system over a preset time period; the objective function includes the total operating cost of the integrated energy system.

[0127] The optimization scheme determination module 230 is used to determine the optimization scheme of the integrated energy system based on each of the candidate positions, at least one constraint condition, and the objective function; the constraint conditions include heating network constraints, thermal storage tank constraints, cogeneration unit constraints, wind turbine constraints, and the power balance constraints of the integrated energy system.

[0128] Optionally, the objective function determination module 220 includes a cost determination unit, used to determine the gas purchase cost, electricity purchase cost, unit operation and maintenance cost, renewable energy penalty cost, and carbon emission cost of the integrated energy system in a preset time period; and an objective function determination unit, used to determine the objective function of the integrated energy system in the preset time period based on the gas purchase cost, the electricity purchase cost, the unit operation and maintenance cost, the renewable energy penalty cost, and the carbon emission cost.

[0129] Optionally, the process for determining the gas purchase cost includes a gas purchase cost determination subunit, used to determine the gas purchase cost based on the hourly power generation of the cogeneration unit, the hourly heating power of the cogeneration unit, the efficiency of the cogeneration unit, and the lower calorific value of natural gas within the preset time period; the process for determining the electricity purchase cost includes a gas-electricity purchase cost determination subunit, used to determine the electricity purchase cost based on the hourly grid-purchased electricity volume, the hourly grid-purchased electricity price, the hourly grid-sold electricity volume, and the hourly grid-sold electricity price within the preset time period; the process for determining the unit operation and maintenance cost includes a unit operation and maintenance cost determination subunit, used to determine the gas purchase cost based on the hourly power generation of the cogeneration unit within the preset time period. The process for determining the operating and maintenance cost of the combined heat and power (CHP) unit includes a renewable energy penalty cost determination subunit, which is used to determine the renewable energy penalty cost based on the predicted power of the wind turbine per hour, the actual power of the wind turbine per hour, and the renewable energy discard penalty cost coefficient during the preset time period. The process for determining the carbon emission cost includes a carbon emission cost determination subunit, which is used to determine the carbon emission cost based on the carbon emission of the CHP unit per hour, the carbon emission quota of the CHP unit per hour, and the carbon emission price during the preset time period.

[0130] Optionally, the process of determining the power generation capacity of the cogeneration unit includes: determining the heating power of the cogeneration unit based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network; and determining the power generation capacity of the cogeneration unit based on the heating power of the cogeneration unit and the constraints of the cogeneration unit.

[0131] Optionally, the process of determining the actual power of the wind turbine includes: determining the actual power of the wind turbine based on the power generation capacity of the combined heat and power unit, the constraints of the wind turbine, and the power balance constraints of the integrated energy system.

[0132] Optionally, determining the heating power of the cogeneration unit based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network includes: determining the output power of the first pipe connected to the thermal storage tank and the input power of the second pipe based on the candidate location of the thermal storage tank; determining the input power and output power of each pipe in the heating network based on the input power, the output power, the constraints of the heating network, and the constraints of the thermal storage tank; and determining the heating power of the cogeneration unit based on the input power of the inlet pipe and the output power of the outlet pipe connected to the heat exchanger in the heating network.

[0133] Optionally, the optimization scheme determination module 230 includes a candidate optimization result determination unit, used to input the candidate position into each of the constraints and the objective function to determine the candidate optimization result for each candidate position; and an optimization scheme determination unit, used to take the scheme associated with the minimum value among the candidate optimization results as the optimization scheme of the integrated energy system.

[0134] The apparatus provided in the above embodiments can execute the integrated energy system optimization method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0135] Figure 5 A schematic diagram of an electronic device 30 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0136] like Figure 5 As shown, the electronic device 30 includes at least one processor 31 and a memory, such as a read-only memory (ROM) 32 or a random access memory (RAM) 33, communicatively connected to the at least one processor 31. The memory stores computer programs executable by the at least one processor. The processor 31 can perform various appropriate actions and processes based on the computer program stored in the ROM 32 or loaded from storage unit 38 into the RAM 33. The RAM 33 can also store various programs and data required for the operation of the electronic device 30. The processor 31, ROM 32, and RAM 33 are interconnected via a bus 34. An input / output (I / O) interface 35 is also connected to the bus 34.

[0137] Multiple components in electronic device 30 are connected to I / O interface 35, including: input unit 36, such as keyboard, mouse, etc.; output unit 37, such as various types of monitors, speakers, etc.; storage unit 38, such as disk, optical disk, etc.; and communication unit 39, such as network card, modem, wireless transceiver, etc. Communication unit 39 allows electronic device 30 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0138] Processor 31 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 31 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 31 performs the various methods and processes described above, such as intelligent voice outbound calling methods.

[0139] In some embodiments, the intelligent voice outbound calling method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 38. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 30 via ROM 32 and / or communication unit 39. When the computer program is loaded into RAM 33 and executed by processor 31, one or more steps of the intelligent voice outbound calling method described above may be performed. Alternatively, in other embodiments, processor 31 may be configured to perform the intelligent voice outbound calling method by any other suitable means (e.g., by means of firmware).

[0140] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0141] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0142] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0143] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0144] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0145] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0146] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0147] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for optimizing a comprehensive energy system, characterized in that, include: Identify at least one candidate location for a thermal storage tank in an integrated energy system; the candidate location is located between two heating pipes in the heating network of the integrated energy system. Determine the objective function of the integrated energy system over a preset time period; the objective function includes the total operating cost of the integrated energy system. The optimization scheme of the integrated energy system is determined based on each candidate position, at least one constraint, and the objective function; the constraints include heating network constraints, thermal storage tank constraints, cogeneration unit constraints, wind turbine constraints, and the power balance constraints of the integrated energy system. The objective function for determining the integrated energy system over a preset time period includes: The gas purchase cost, electricity purchase cost, unit operation and maintenance cost, renewable energy penalty cost, and carbon emission cost of the integrated energy system are determined respectively for a preset time period; The objective function of the integrated energy system is determined based on the gas purchase cost, the electricity purchase cost, the unit operation and maintenance cost, the renewable energy penalty cost, and the carbon emission cost over a preset time period. The process for determining the power generation capacity of a combined heat and power (CHP) unit includes: The heating power of the cogeneration unit is determined based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network. The power generation capacity of the cogeneration unit is determined based on the heating power of the cogeneration unit and the constraints of the cogeneration unit. The determination of the heating power of the combined heat and power unit based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network includes: The output power of the first pipe connected to the thermal storage tank and the input power of the second pipe are determined based on the candidate location of the thermal storage tank. Based on the input power and output power, the heating network constraints, and the thermal storage tank constraints, the input power and output power of each pipe in the heating network are determined. The heating power of the combined heat and power unit is determined based on the input power of the inlet pipe and the output power of the outlet pipe, which are respectively connected to the heat exchanger in the heating network.

2. The method according to claim 1, characterized in that, The process of determining the gas purchase cost includes: determining the gas purchase cost based on the hourly power generation of the cogeneration unit, the hourly heat generation of the cogeneration unit, the efficiency of the cogeneration unit, and the lower calorific value of natural gas within the preset time period; The process of determining the electricity purchase cost includes: determining the electricity purchase cost based on the grid purchase volume per hour, the grid purchase price per hour, the grid sales volume per hour, and the grid sales price per hour during the preset time period; The process of determining the unit operation and maintenance cost includes: determining the unit operation and maintenance cost based on the power generation of the cogeneration unit per hour, the cogeneration unit maintenance cost coefficient, the actual power of the wind turbine per hour, and the wind turbine maintenance cost coefficient during the preset time period; The process of determining the renewable energy penalty cost includes: determining the renewable energy penalty cost based on the predicted power of the wind turbine per hour during the preset time period, the actual power of the wind turbine per hour, and the renewable energy discard penalty cost coefficient; The process of determining carbon emission costs includes: determining the carbon emission cost based on the hourly carbon emission of the cogeneration unit during the preset time period, the hourly carbon emission quota of the cogeneration unit, and the carbon emission price.

3. The method according to claim 1, characterized in that, The process of determining the actual power of a wind turbine includes: The actual power of the wind turbine is determined based on the power generation capacity of the combined heat and power unit, the constraints of the wind turbine generator, and the power balance constraints of the integrated energy system.

4. The method according to claim 1, characterized in that, Determining the optimization scheme of the integrated energy system based on each candidate location, at least one constraint, and the objective function includes: For each candidate position, the candidate position is input into each of the constraints and the objective function to determine the candidate optimization result; The scheme associated with the minimum value among the candidate optimization results is taken as the optimization scheme of the integrated energy system.

5. A comprehensive energy system optimization device, characterized in that, include: A thermal storage tank candidate location determination module is used to determine at least one candidate location of a thermal storage tank in an integrated energy system; the candidate location is located between two heating pipelines in the heating network of the integrated energy system; The objective function determination module is used to determine the objective function of the integrated energy system over a preset time period; the objective function includes the total operating cost of the integrated energy system. The optimization scheme determination module is used to determine the optimization scheme of the integrated energy system based on each of the candidate positions, at least one constraint condition, and the objective function; the constraint conditions include heating network constraints, thermal storage tank constraints, cogeneration unit constraints, wind turbine constraints, and the power balance constraints of the integrated energy system. The objective function determination module includes a cost determination unit, used to determine the gas purchase cost, electricity purchase cost, unit operation and maintenance cost, renewable energy penalty cost, and carbon emission cost of the integrated energy system within a preset time period. The objective function determination unit is used to determine the objective function of the integrated energy system within a preset time period based on the gas purchase cost, the electricity purchase cost, the unit operation and maintenance cost, the renewable energy penalty cost, and the carbon emission cost. The process for determining the power generation capacity of a combined heat and power (CHP) unit includes: The heating power of the cogeneration unit is determined based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network. The power generation capacity of the cogeneration unit is determined based on the heating power of the cogeneration unit and the constraints of the cogeneration unit. The determination of the heating power of the combined heat and power unit based on the candidate location of the thermal storage tank, the constraints of the thermal storage tank, and the constraints of the heating network includes: The output power of the first pipe connected to the thermal storage tank and the input power of the second pipe are determined based on the candidate location of the thermal storage tank. Based on the input power and output power, the heating network constraints, and the thermal storage tank constraints, the input power and output power of each pipe in the heating network are determined. The heating power of the combined heat and power unit is determined based on the input power of the inlet pipe and the output power of the outlet pipe, which are respectively connected to the heat exchanger in the heating network.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the integrated energy system optimization method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the integrated energy system optimization method according to any one of claims 1-4.

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