A comprehensive energy optimization scheduling method and system based on heat load modeling

Abstract

The present invention discloses a comprehensive energy optimization scheduling method and system based on heat load modeling, and belongs to the field of comprehensive energy optimization technology. The comprehensive energy optimization scheduling method based on heat load modeling of the present invention establishes an accurate heat load calculation model in a building, and considers the temperature tolerance within the user comfort temperature range, and sets the corresponding heat load change limit. It is used as a constraint and brought into the constraint equations of other parts of the system. The minimum daily operating cost is taken as the objective function, and the optimization result is calculated by the solver. After the optimization is completed, a temperature crossing check is performed. If the requirements are not met, a double-layer loop iteration is performed until the system economy is optimal within the temperature tolerance limit, and the scheduling plan and system operation status of each device in the system are determined. The heat load calculation model in the building of the present invention has a small error, can ensure high accuracy, and has low complexity, high calculation speed and good convergence.

Description

Technical Field

[0001] The invention relates to a comprehensive energy optimization scheduling method and system based on heat load modeling, and belongs to the technical field of comprehensive energy optimization. Background Art

[0002] At present, in the process of processing the heat load of the park's comprehensive energy optimization scheduling, since the control variable corresponding to the heat source is the thermal power, and the demand corresponding to the heat load is the allowable range of the temperature value (such as the building set temperature), there are mainly two processing solutions:

[0003] 1. Through simple thermal characteristic calculation of the building, the temperature value is first converted into thermal power, and then the allowable range of thermal power is given, and then the corresponding constraint equations are established. These constraint equations are added to the overall constraint conditions, and the solver is used to solve and calculate the optimization results.

[0004] 2. According to the functional relationship between thermal power, heat load and building temperature, directly establish the corresponding nonlinear constraint equation or use professional building modeling software to model the thermal characteristics of the building environment in detail to determine the range of heat load changes at each optimization time point.

[0005] The first treatment method mentioned above: Due to the accuracy problems of the traditional heat load modeling method, there is an error in the power range corresponding to the determined temperature range, and the final optimization result of the park's comprehensive energy system has a large error with the actual situation.

[0006] The second solution mentioned above: Since the relationship between building heat load and building temperature is very complex and nonlinear, if these nonlinear complex equations are directly put into the optimization problem, when the scale of the problem is large, it will greatly affect the calculation speed and convergence. The parametric software used in the field of building is complex to use, requires large computing power, and takes a long time to complete the calculation, which is not suitable for use in iterative comprehensive energy optimization. Summary of the invention

[0007] In view of the defects of the prior art, an object of the present invention is to provide a comprehensive energy optimization scheduling method based on heat load modeling, which constructs an accurate heat load calculation model in the building, takes into account the temperature tolerance within the user comfort temperature range, takes the minimum daily operating cost as the objective function, determines that the scheduling plan of each equipment in the system has a small error with the system operating status, has high accuracy, high calculation speed and good convergence.

[0008] The second purpose of the present invention is to provide a comprehensive energy optimization scheduling system based on heat load modeling that is particularly suitable for optimizing the scheduling of comprehensive energy in the park under a certain temperature tolerance by establishing a heat load calculation module in the building and various park energy supply modules, determining an optimization scheduling plan, and scheduling each device in the park's comprehensive energy system to achieve the goal of minimizing the daily operating cost with a small error and ensuring high accuracy.

[0009] To achieve one of the above purposes, a technical solution of the present invention is:

[0010] A comprehensive energy optimization scheduling method based on heat load modeling,

[0011] The following steps are involved:

[0012] The first step is to analyze the main influencing factors of the building and establish a heat load calculation model in the building according to the laws of thermodynamics;

[0013] The second step is to set the corresponding heat load change limit according to the building heat load calculation model in the first step and the temperature schedule given by the user, taking into account the temperature tolerance within the user's comfort temperature range;

[0014] In the third step, the temperature tolerance and heat load change limit in the second step are used as constraints and brought into the constraint equation. The minimum daily operating cost is taken as the objective function, and the optimization result is calculated by the solver.

[0015] The fourth step is to perform a temperature over-limit check on the optimization results in the third step after the optimization is completed. If the requirements are not met, a double-layer loop iteration is performed until the optimal system economy is achieved within the temperature tolerance limit. The scheduling plan for the energy supply of each device in the system and the system operation status are determined.

[0016] After continuous exploration and experimentation, the present invention first analyzes various major influencing factors of the building, and establishes an accurate calculation model for the heat load in the building according to the laws of thermodynamics. Then, according to this model, when the user gives a temperature schedule, the temperature tolerance within the user's comfort temperature range is considered, and the corresponding heat load change limit is set. This is used as a constraint and brought into the constraint equations of other parts of the system. The objective function is to minimize the daily operating cost, and the optimization result is calculated by the solver. After the optimization is completed, a temperature crossing check is performed. If the requirements are not met, a double-layer loop iteration is performed until the system economy is optimal within the temperature tolerance limit, and the scheduling plan and system operation status of each device in the system are determined.

[0017] Furthermore, compared with the existing heat load modeling methods for integrated energy systems in parks, which are inaccurate or computationally expensive, the present invention proposes a heat load modeling method that guarantees accuracy, is simple to calculate, and can be used in iterative optimization.

[0018] Furthermore, the heat load calculation model of the building of the present invention has a small error and can ensure high accuracy, and the heat load modeling method of the present invention has low complexity, high calculation speed and good convergence. This more accurate thermal modeling method is particularly suitable for optimizing the scheduling of the park's integrated energy system under temperature tolerance.

[0019] As the preferred technical measures:

[0020] In the first step, the building heat load calculation model is based on the detailed building factors and the average temperature schedule required by users in the building. , establish the heat load of the single building in the park The simplified differential formula at time t under different temperature schedule change curves is as follows:

[0021] (1)

[0022] In formula (1), is the equivalent projected area of ​​the wall, is the equivalent projected area of ​​the window, is the equivalent projected area of ​​the roof, is the equivalent floor heat transfer projected area, is the specific heat capacity of air, is the air density, is the altitude correction factor, is the correction coefficient for longitude and latitude changes, is the correction coefficient of the building's sunlight orientation, W is The solar constant, The number of heat dissipation devices in the building ， Cooling load for all equipment.

[0023] As the preferred technical measures:

[0024] The detailed building factors include: the impact of the building's internal space on the heat load, basic sunshine curve, building facade material and layout, weather factors, and heat dissipation of equipment inside the building;

[0025] Building area Impact, layer height Impact, number of floors The impact of the spatial division plan, which affects the overall heat load, heat storage characteristics and internal heat radiation conduction process of the building;

[0026] According to the heat radiation conduction effect in the building space, there will be obvious differences in the temperature at the bottom of the building, the temperature in the middle space and the temperature at the top of the building; and the effect of this heat distribution will vary according to different building spaces and structures. In order to simplify the analysis process, the temperature in the building is mainly divided into the bottom temperature , average body temperature and top temperature , corresponding to the heat transfer processes of the roof, wall and window, and floor respectively;

[0027] The specific location of the building is crucial to the determination of heat load, which is determined by the longitude, latitude and altitude of the building. These factors will significantly affect the basic sunshine curve of the building on the specified date and directly affect the input heat load of sunlight to the building;

[0028] The method for determining the basic sunshine curve is as follows:

[0029] By using the altitude correction factor 、 Correction coefficient of longitude and latitude change , Building sunlight orientation correction coefficient , Solar constant W (W / m 2 ), the basic solar radiation load per unit building exterior surface area is obtained as (W / m 2 );

[0030] Building facade material and layout are equivalent to wall heat transfer coefficient , roof heat transfer coefficient and geothermal heat transfer coefficient , window heat transfer coefficient ;

[0031] The facades of the building will use a variety of different materials and structures, and these effects are equivalent to the wall heat transfer coefficient , roof heat transfer coefficient and geothermal heat transfer coefficient ; At the same time, the layout and opening ratio of windows on the facade will also vary. These effects are equivalent to the window heat transfer coefficient ;

[0032] The weather factor is determined as follows:

[0033] By introducing historical meteorological data, various weather factors are equivalent to the comprehensive atmospheric passing rate. , to simulate various weather conditions that may occur in the simulation to help correct the heat load calculation;

[0034] Meteorological historical data include hourly or sub-hourly data for each key element;

[0035] The key factors include geothermal temperature, dry bulb temperature, dew point temperature, relative humidity, air pressure, direct normal radiation, diffuse reflection;

[0036] The method for determining the heat dissipation of equipment inside the building is as follows:

[0037] As the functions of buildings vary, the heat dissipated by the equipment inside the building during operation will exchange heat with the air and affect the temperature inside the building. The number of heat dissipation devices in the building is , the historical measured heat dissipation of each device is recorded as , then the heat dissipation load of all equipment is recorded as .

[0038] As the preferred technical measures:

[0039] In the second step, the iterative correction method of temperature tolerance is as follows:

[0040] In the actual integrated energy system of the park, under the temperature schedule determined in the building, the temperature can be deviated to a certain extent within the user comfort level. This insensitivity to the temperature change inside the building is named temperature tolerance in this paper. It can be used as a demand response method to shift the building heat load and optimize the energy supply curve of the park.

[0041] Step 1: Obtain user tolerance constraints. When different building models are used in the heat load calculation of different buildings in the park during the optimization scheduling process, the temperature tolerance range will correspond to different heat load ranges. In the scheduling process, it is necessary to ensure that the user comfort is within an acceptable range. The average set temperature value of each building is , the user's tolerance temperature deviation range is , then the corresponding The upper and lower limits of the heat load of each building at the moment are , At the same time, the tolerance change limit of heat load of all buildings in one day is , at time t, the node n where building N is located is subject to the temperature tolerance constraint as shown in formula (2):

[0042] (2)

[0043] Step 2: Perform iterative correction of temperature crossing the line, and verify whether the temperature in the building crosses the line after each iteration to ensure that the temperature change in the building in the optimized scheduling result meets the user's comfort requirements;

[0044] Because it is necessary to accurately consider the calculation of the building's electric and thermal load, which takes into account the complex thermal delay effects that may exist in the building, and the user's planned temperature curve within the temperature tolerance will change during the iteration process; so each time the traditional expression constraints are used for calculation during the iteration process, the input heat load may actually cause the temperature in the building to exceed the limit; therefore, after each iteration, it is necessary to verify whether the temperature in the building has exceeded the limit to ensure that the temperature changes in the building in the optimized scheduling results meet the user's comfort needs.

[0045] As the preferred technical measures:

[0046] In the fourth step, the energy supply capacity of each device is different and is subject to structural constraints. The energy supply capacity of each device is modeled to obtain constraint equations that can reflect the characteristics of each device and the network, which include electric energy conversion model, electric heat conversion model, electrical conversion model, electric cooling conversion model, gas heat conversion model, energy supply bus and heat pipe network model.

[0047] As the preferred technical measures:

[0048] The electric energy conversion model is used to model photovoltaic equipment, wind turbine equipment, and battery energy storage equipment. The corresponding constraints include electric energy balance constraints, upper and lower limit constraints of equipment status, and upper and lower limit constraints of energy storage. The specific calculation formula is as follows:

[0049] (3)

[0050] In formula (3), , They are Purchase and sell electricity from the power grid at all times. , They are The power generation of photovoltaic and wind turbines at all times; , are the battery discharging and charging power respectively; for The electric energy conversion model outputs electric power at the moment; , Equipment The upper and lower limits of power; For equipment exist The electrical power at the time; for The battery capacity at all times; , They are the upper and lower limits of battery power respectively; is the battery power self-loss rate; , are the battery discharge and charge efficiencies respectively;

[0051] The electrothermal conversion model is used to model devices with electrothermal conversion capabilities;

[0052] Equipment with electric heat conversion capabilities includes electric boilers and / or electric heat pumps and / or heat storage tanks. The corresponding constraints include energy balance constraints, electric heat equipment state constraints, and heat storage constraints. The specific calculation formula is as follows:

[0053] (4)

[0054] In formula (4), Inputting electrical power to the electrothermal conversion model; , They are The electrical and thermal power of the electric boiler at all times; , are the electrical and thermal power of the electric heat pump respectively; , are the efficiencies of electric boilers and electric heat pumps, respectively; , are the heat release and heat storage power of the heat storage tank respectively; is the output thermal power of the electrothermal conversion model; for The heat storage capacity of the heat storage tank at all times; , They are the upper and lower limits of the heat storage capacity of the heat storage tank respectively; is the heat energy self-loss rate of the heat storage tank; , They are heat release and heat storage efficiency of the heat storage tank respectively.

[0055] As the preferred technical measures:

[0056] The electrical conversion model is used to model the power-to-gas device and the gas storage tank. Its corresponding constraints include energy balance constraints, electrical conversion equipment constraints, and gas storage device constraints. The specific calculation formula is as follows:

[0057] (5)

[0058] In formula (5), for The electric power input to the gas-to-electricity conversion model at each moment; for Input electrical power to the electric-to-gas device at all times; for The volume of gas output by the electric-to-gas device at each moment; is the efficiency of the power-to-gas device; is the calorific value of natural gas; , respectively Degassing and gas storage volume of the gas tank at all times; for The gas volume output by the gas-to-electricity conversion model at the moment; where, for The gas storage capacity of the gas tank at all times; , They are the upper and lower limits of the gas storage capacity of the gas tank respectively; is the gas storage capacity self-loss rate of the gas storage tank; , They are gas tank deflation and gas storage efficiency;

[0059] The electric cooling conversion model is used to model the electric refrigerator and the cold storage tank. The corresponding constraints include the energy balance constraint of the electric cooling conversion model, the electric cooling equipment state constraint, and the cold storage device constraint. The specific calculation formula is as follows:

[0060] (6)

[0061] In formula (6), Inputting electrical power to the electric cooling conversion model; , They are the electrical power and cooling power of the electric refrigerator respectively; is the energy efficiency coefficient of the electric refrigerator; , They are the cooling and storage power of the cold storage tank respectively; Output cooling power for electric cooling conversion models for The cold storage capacity of the cold storage tank at all times; , They are the upper and lower limits of the cold storage capacity of the cold storage tank respectively; is the heat energy self-loss rate of the cold storage tank; , They are the cooling and storage efficiency of the cold storage tank respectively; , They are the state variables of the cold storage tank for cooling and storing cold respectively;

[0062] The gas-heat conversion model is used to model gas turbines, gas boilers and combined heat and power units. Its corresponding constraints include energy balance constraints, gas-heat conversion equipment constraints and energy storage device constraints. The specific calculation formula is as follows:

[0063] (7)

[0064] In formula (7), , They are Gas consumption of gas turbines and gas boilers at all times; , are the efficiencies of gas turbine and gas boiler respectively; , They are The gas turbine outputs electrical power and thermal power at each moment; for The gas boiler outputs thermal power at all times; is the heat loss rate of the gas turbine; is the input gas volume of the gas-heat conversion model; Output thermal power for the gas-heat conversion model;

[0065] The energy supply bus and heat pipe network model are used to model the functional bus, which includes the power bus and the heat network bus. The specific constraint formula is as follows:

[0066] (8)

[0067] In formula (8), for The electrical load power at the moment, for The thermal power injected into the heating network by the system at any moment, for The cold power injected into the heating network by the system at any moment.

[0068] As the preferred technical measures:

[0069] The objective function is the optimization objective function of the park integrated energy system operation, which includes the exchange fee with the power grid and the gas fee, and is optimized and dispatched with the goal of economic optimization, as shown in formula (9):

[0070] (9)

[0071] In the formula, , They are The electricity purchase and sales costs of the power grid at all times; For gas costs; , are the efficiencies of gas turbine and gas boiler respectively; for Gas turbine power generation at the moment; for The heating power of the gas boiler at all times.

[0072] To achieve one of the above purposes, another technical solution of the present invention is:

[0073] A comprehensive energy optimization and dispatching system for a park based on heat load modeling.

[0074] The above-mentioned comprehensive energy optimization scheduling method based on heat load modeling is applied, which includes a heat load calculation module in the building, an electric energy conversion module, an electric heat conversion module, an electrical conversion module, an electric cooling conversion module, an air heat conversion module, an energy supply bus and a heat pipe network module;

[0075] According to the optimized scheduling plan determined by the heat load calculation module in the building, each equipment in the park's integrated energy system is scheduled to achieve the goal of minimizing daily operating costs.

[0076] After continuous exploration and experimentation, the present invention establishes a heat load calculation module in a building and various park energy supply modules, determines an optimized scheduling plan, and schedules each device in the park's comprehensive energy system to achieve the goal of minimizing daily operating costs.

[0077] Furthermore, the test results show that the present invention has a small error and can ensure high accuracy, and is particularly suitable for optimizing the scheduling of the park's integrated energy system under a certain temperature tolerance. The scheme is detailed in the following, which is practical and easy to implement.

[0078] As the preferred technical measures:

[0079] The building heat load calculation module analyzes the main influencing factors of the building, considers the temperature tolerance within the user's comfort temperature range according to the laws of thermodynamics, takes the minimum daily operating cost as the objective function, and determines the scheduling plan and system operation status of each device in the system;

[0080] The power conversion module is used to model photovoltaic equipment, wind turbine equipment, and battery energy storage equipment. Its corresponding constraints include power balance constraints, upper and lower limit constraints of equipment status, and upper and lower limit constraints of energy storage;

[0081] The electrothermal conversion module is used to model the equipment with electrothermal conversion capability. Its corresponding constraints include energy balance constraints, electrothermal equipment state constraints, and thermal energy storage constraints.

[0082] The electrical conversion module is used to model the power-to-gas device and the gas storage tank. Its corresponding constraints include energy balance constraints, electrical conversion equipment constraints, and gas storage device constraints.

[0083] The electric cooling conversion module is used to model the electric refrigerator and the cold storage tank. Its corresponding constraints include the energy balance constraint of the electric cooling conversion model, the electric cooling equipment state constraint, and the cold storage device constraint.

[0084] The gas-heat conversion module is used to model gas turbines, gas boilers and combined heat and power units. Its corresponding constraints include energy balance constraints, gas-heat conversion equipment constraints and energy storage device constraints;

[0085] The energy bus and heat network modules are used to model the power bus and heat network bus.

[0086] Compared with the prior art, the present invention has the following beneficial effects:

[0087] After continuous exploration and experimentation, the present invention first analyzes various major influencing factors of the building, and establishes an accurate calculation model for the heat load in the building according to the laws of thermodynamics. Then, according to this model, when the user gives a temperature schedule, the temperature tolerance within the user's comfort temperature range is considered, and the corresponding heat load change limit is set. This is used as a constraint and brought into the constraint equations of other parts of the system. The objective function is to minimize the daily operating cost, and the optimization result is calculated by the solver. After the optimization is completed, a temperature crossing check is performed. If the requirements are not met, a double-layer loop iteration is performed until the system economy is optimal within the temperature tolerance limit, and the scheduling plan and system operation status of each device in the system are determined.

[0088] Furthermore, compared with the existing heat load modeling methods for integrated energy systems in parks, which are inaccurate or computationally expensive, the present invention proposes a heat load modeling method that guarantees accuracy, is simple to calculate, and can be used in iterative optimization.

[0089] Furthermore, the heat load calculation model of the building of the present invention has a small error and can ensure high accuracy, and the heat load modeling method of the present invention has low complexity, high calculation speed and good convergence. This more accurate thermal modeling method is particularly suitable for optimizing the scheduling of the park's integrated energy system under temperature tolerance.

[0090] Furthermore, the present invention establishes a heat load calculation module in the building and various park energy supply modules, determines an optimized scheduling plan, and schedules each device in the park's comprehensive energy system to achieve the goal of minimizing daily operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] Figure 1 is a flow chart of the iterative correction method of the present invention;

[0092] Figure 2 It is a structural diagram of the park comprehensive energy system of the present invention;

[0093] Figure 3 is a system structure diagram of a calculation example of the present invention;

[0094] Figure 4 is the daily load power curve of the system of the present invention;

[0095] Figure 5 is the daily heat load power curve of the system of the present invention;

[0096] Figure 6It is the electricity purchase and sale price curve of the system of the present invention;

[0097] Figure 7 It is an economical display of the optimization results of the system of the present invention. DETAILED DESCRIPTION

[0098] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0099] On the contrary, the present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. Those skilled in the art can fully understand the present invention without the description of these details.

[0100] like Figure 1 As shown in the figure, a comprehensive energy optimization scheduling method based on heat load first analyzes various major influencing factors of the building, and establishes an accurate calculation model of the heat load in the building according to the laws of thermodynamics. Then, based on this model, when the user gives a temperature schedule, the temperature tolerance within the user's comfort temperature range is considered, and the corresponding heat load change limit is set. It is used as a constraint and brought into the constraint equations of other parts of the system. The minimum daily operating cost is taken as the objective function, and the optimization result is calculated by the solver. After the optimization is completed, a temperature crossing check is performed. If the requirements are not met, a double-layer loop iteration is performed until the system economy is optimal within the temperature tolerance limit, and the scheduling plan and system operation status of each device in the system are determined.

[0101] The building heat load calculation model of the present invention takes into account detailed building factors, ensures accuracy, has fast calculation time, and is suitable for iterative optimization of integrated energy systems. The building heat load calculation model of the present invention is used to perform double-layer iterative optimization of the park integrated energy system under temperature tolerance, and the result can simultaneously ensure the user's comfort and the economy of the system.

[0102] The detailed building factors include: the impact of the building's interior space on the heat load, basic sunshine curve, building facade material and layout, weather factors, and heat dissipation of equipment inside the building.

[0103] A specific embodiment of the present invention taking into account the influence of the internal space of a building on the heat load is as follows:

[0104] Building interior space impact is broken down into floor area , Floor height , Number of floors and space division plan, etc. These factors will affect the overall heat load, heat storage characteristics and internal heat radiation conduction of the building. According to the heat radiation conduction effect in the building space, the temperature at the bottom of the building, the temperature in the middle space and the temperature at the top of the building will have obvious differences. And this heat distribution effect will vary according to different building spaces and compositions. In order to simplify the analysis process, the temperature inside the building is mainly divided into the bottom temperature , average body temperature and top temperature , corresponding to the heat transfer processes of the roof, walls and windows, and floor respectively.

[0105] The present invention considers a specific embodiment of the basic sunshine curve:

[0106] The specific location of the building is crucial to the determination of heat load, which is determined by the longitude and latitude of the building and the altitude. These factors will significantly affect the basic sunshine curve of the building on the specified date and directly affect the input heat load of sunlight to the building; by determining the altitude correction factor 、 Correction coefficient of longitude and latitude change , Building sunlight orientation correction coefficient , the solar constant is W (W / m 2 ), the basic solar radiation load per unit building exterior surface area is obtained as (W / m2)

[0107] The present invention considers a specific embodiment of the building facade material and layout:

[0108] The facades of the building will use a variety of different materials and structures, and these effects are equivalent to the wall heat transfer coefficient , roof heat transfer coefficient and geothermal heat transfer coefficient ; At the same time, the layout and opening ratio of windows on the facade will also vary. These effects are equivalent to the window heat transfer coefficient ;

[0109] A specific embodiment of the present invention taking weather factors into consideration:

[0110] Weather influencing factors have hourly or sub-hourly data, which are used for each key element required in the calculation process. The detailed weather table needs to include hourly or sub-hourly data for each key element (i.e. geothermal temperature, dry bulb temperature, dew point temperature, relative humidity, air pressure, direct normal radiation, diffuse reflection). Humidity, air pressure, direct normal radiation, diffuse horizontal radiation, total opaque sky cover, wind direction, wind speed) and some auxiliary data, such as rain or snow, are introduced into the historical meteorological data to make various weather factors equivalent to the comprehensive atmospheric pass rate. , to simulate various weather conditions that may occur in the simulation, to help correct the heat load calculation.

[0111] The present invention considers a specific embodiment of heat dissipation of equipment inside a building:

[0112] As the functions of buildings vary, the heat dissipated by the equipment inside the building during operation will exchange heat with the air and affect the temperature inside the building. The number of heat dissipation devices in the building is , the historical measured heat dissipation of each device is recorded as , then the heat dissipation load of all equipment is recorded as .

[0113] A specific embodiment of the accurate building heat load calculation of the present invention:

[0114] After considering the above detailed building factors, the average temperature schedule required by building users is recorded as , it is possible to establish the heat load of individual buildings in the park The simplified differential formula at time t under different temperature schedule change curves is as follows:

[0115] (1)

[0116] In formula (1), is the equivalent projected area of ​​the wall, is the equivalent projected area of ​​the window, is the equivalent projected area of ​​the roof, is the equivalent floor heat transfer projected area, is the specific heat capacity of air, is the air density.

[0117] A specific embodiment of the temperature tolerance iterative correction method of the present invention:

[0118] In the actual campus integrated energy system, under the temperature schedule determined in the building, the temperature can be deviated to a certain extent within the user comfort level. This insensitivity to changes in internal building temperature is named temperature tolerance in this article. It can be used as a demand response method to shift the building heat load and optimize the campus energy supply curve.

[0119] Step 1: Get user tolerance constraints

[0120] When different building models are used in the heat load calculation of different buildings in the park during the optimization and scheduling process, the temperature tolerance range will correspond to different heat load ranges. In the scheduling process, it is necessary to ensure that the user comfort is within an acceptable range. The average set temperature value of each building is , the user's tolerance temperature deviation range is , then the corresponding The upper and lower limits of the heat load of each building at the moment are , At the same time, the tolerance limit of heat load variation of all buildings in a day is , at time t, the node n where building N is located is subject to the temperature tolerance constraint as shown in formula (2):

[0121] (2)

[0122] Step 2: Perform iterative correction of temperature crossing the line

[0123] Because it is necessary to accurately consider the building's electric and heating load calculations, which may include complex thermal delay effects in the building, and the user's planned temperature curve within the temperature tolerance will change during the iteration process. Therefore, each time the traditional expression constraints are used for calculations during the iteration process, the input heat load may actually cause the temperature in the building to exceed the limit. Therefore, after each iteration, it is necessary to verify whether the temperature in the building has exceeded the limit to ensure that the temperature change in the building in the optimized scheduling result meets the user's comfort requirements. The algorithm flow chart is shown below. Figure 1 shown.

[0124] like Figure 2-Figure 6 As shown, a specific embodiment of the optimization scheduling method of the present invention is applied:

[0125] This method is applied to the integrated energy system of a park including three buildings. Figure 2 As shown in the example structure diagram Figure 3 shown.

[0126] In the present invention, the park comprehensive energy system in the application scenario is divided into various park energy supply modules, including electric energy conversion module, electric heat conversion module, electrical conversion module, electric cooling conversion module, gas heat conversion module, energy supply bus and heat pipe network module.

[0127] A specific embodiment of the electric energy conversion module of the present invention:

[0128] This module includes photovoltaic, wind turbine, battery energy storage and other equipment. The corresponding constraints include power balance constraints, upper and lower limits of equipment status constraints and upper and lower limits of energy storage constraints:

[0129] (3)

[0130] In formula (3), , They are Purchase and sell electricity from the power grid at all times. , They are The power generation of photovoltaic and wind turbines at all times; , are the battery discharging and charging power respectively; for The electric energy conversion module outputs electric power at that moment; , Equipment The upper and lower limits of power; For equipment exist The electrical power at the time; for The battery capacity at all times; , They are the upper and lower limits of battery power respectively; is the battery power self-loss rate; , They are the battery discharge and charge efficiency respectively.

[0131] A specific embodiment of the electrothermal conversion module of the present invention:

[0132] This module includes electric boilers, electric heat pumps and heat storage tanks, which are devices with electric heat conversion capabilities. The corresponding constraints include energy balance constraints, electric heat equipment state constraints, and thermal energy storage constraints:

[0133] (4)

[0134] In formula (4), inputting electric power to the electric-thermal conversion module; , They are The electrical and thermal power of the electric boiler at all times; , are the electrical and thermal power of the electric heat pump respectively; , are the efficiencies of electric boilers and electric heat pumps, respectively; , are the heat release and heat storage power of the heat storage tank respectively; is the output thermal power of the electrothermal conversion module; for The heat storage capacity of the heat storage tank at all times; , They are the upper and lower limits of the heat storage capacity of the heat storage tank respectively; is the heat energy self-loss rate of the heat storage tank; , They are heat release and heat storage efficiency of the heat storage tank respectively.

[0135] A specific embodiment of the electrical conversion module of the present invention:

[0136] This module includes equipment such as power-to-gas devices and gas storage tanks. The corresponding constraints include energy balance constraints, power conversion equipment constraints and gas storage device constraints:

[0137] (5)

[0138] In formula (5), for The gas-to-electric conversion module inputs electric power at each moment; for Input electrical power to the electric-to-gas device at all times; for The volume of gas output by the electric-to-gas device at each moment; is the efficiency of the power-to-gas device; is the calorific value of natural gas; , respectively Degassing and gas storage volume of the gas tank at all times; for The gas volume output by the gas-to-electricity conversion module at the moment; where, for The gas storage capacity of the gas tank at all times; , They are the upper and lower limits of the gas storage capacity of the gas tank respectively; is the gas storage capacity self-loss rate of the gas storage tank; , They are gas tank deflation and gas storage efficiency respectively.

[0139] A specific embodiment of the electric cooling conversion module of the present invention:

[0140] This module includes an electric refrigerator and a cold storage tank. The corresponding constraints include the energy balance constraint of the electric cooling conversion module, the state constraint of the electric cooling equipment, and the cold storage device constraint:

[0141] (6)

[0142] In formula (6), inputting electric power to the electric cooling conversion module; , They are the electrical power and cooling power of the electric refrigerator respectively; is the energy efficiency coefficient of the electric refrigerator; , They are the cooling and storage power of the cold storage tank respectively; Output cooling power for electric cooling conversion module for The cold storage capacity of the cold storage tank at all times; , They are the upper and lower limits of the cold storage capacity of the cold storage tank respectively; is the heat energy self-loss rate of the cold storage tank; , They are the cooling and storage efficiency of the cold storage tank respectively; , They are the state variables of the cold storage tank for cooling and storing cold respectively.

[0143] A specific embodiment of the gas-heat conversion module of the present invention:

[0144] This module includes gas turbines, gas boilers and combined heat and power units. The corresponding constraints include energy balance constraints, gas-heat conversion equipment constraints and energy storage device constraints:

[0145] (7)

[0146] In formula (7), , They are Gas consumption of gas turbines and gas boilers at all times; , are the efficiencies of gas turbine and gas boiler respectively; , They are The gas turbine outputs electrical power and thermal power at each moment; for The gas boiler outputs thermal power at all times; is the heat loss rate of the gas turbine; The input gas volume of the gas-heat conversion module; Output thermal power to the gas-heat conversion module.

[0147] A specific embodiment of the energy supply bus of the present invention:

[0148] The functional buses in this system include the power bus and the heat network bus. The specific constraints are as follows:

[0149] (8)

[0150] In formula (8), for The electrical load power at the moment, for The thermal power injected into the heating network by the system at any moment, for The cold power injected into the heating network by the system at any moment.

[0151] A specific embodiment of the objective function of the present invention:

[0152] The optimization objective function of the park's integrated energy system operation includes the exchange fee with the power grid and the gas fee. Taking the optimal economic performance as an example, the optimization scheduling is performed as shown in formula (9):

[0153] (9)

[0154] In the formula, , They are The electricity purchase and sales costs of the power grid at all times; For gas costs; , are the efficiencies of gas turbine and gas boiler respectively; for Gas turbine power generation at the moment; for The heating power of the gas boiler at all times.

[0155] According to the results of the previous day's optimized dispatch, the dispatch plan of each device in the park's integrated energy system and the planned power of the grid connection line are obtained. Figure 7 The total required thermal power in the optimization results of the present invention is compared with the optimized scheduling of the park without using this method. The temperature in each building in the results fluctuates within 10% of the set temperature.

[0156] Definitions of professional terms used in this invention:

[0157] Park integrated energy system: a small physical network system that includes energy supply, energy transmission, and energy consumption in various energy forms (electricity, gas, water, and heat). (Similar definitions: multi-energy flow system, multi-energy flow microgrid system, and multi-energy complementary system)

[0158] Day-ahead optimization: For the next 24 hours, an effective operation plan is obtained through optimization calculation, and each device is guided to operate according to this plan in the next 24 hours.

[0159] Temperature tolerance: After the user determines the set temperature inside the building, they are insensitive to temperature changes within a certain comfort range, so there is a certain tolerance limit for temperature changes and the heat load can be adjusted within the limit.

[0160] Building factors: When considering the precise heat load of a building, the present invention takes into account various main building-related factors that specifically affect the heat load in the building, including the interior space of the building, the material layout of the building's facade, the internal equipment of the building, the basic sunshine curve, weather factors, etc.

[0161] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program codes.

[0162] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A comprehensive energy optimization scheduling method based on heat load modeling, characterized in that: The following steps are involved: The first step is to analyze the main influencing factors of the building and establish a heat load calculation model in the building according to the laws of thermodynamics; The second step is to set the corresponding heat load change limit according to the building heat load calculation model in the first step and the temperature schedule given by the user, taking into account the temperature tolerance within the user's comfort temperature range; In the third step, the temperature tolerance and heat load change limit in the second step are used as constraints and brought into the constraint equation. The minimum daily operating cost is taken as the objective function, and the optimization result is calculated by the solver. Step 4: After the optimization is completed, the optimization result in step 3 is checked for temperature crossing. If the requirements are not met, a double-layer loop iteration is performed until the system economic efficiency is optimal within the temperature tolerance limit, and the scheduling plan for energy supply of each device in the system and the system operation status are determined; In the first step, the building heat load calculation model is based on the detailed building factors and the average temperature schedule required by users in the building. , establish the heat load of the single building in the park The simplified differential formula at time t under different temperature schedule change curves is as follows: （1） In formula (1), is the equivalent projected area of ​​the wall, is the equivalent projected area of ​​the window, is the equivalent projected area of ​​the roof, is the equivalent floor heat transfer projected area, is the specific heat capacity of air, is the air density, is the altitude correction factor, is the correction coefficient for longitude and latitude changes, is the correction coefficient of the building's sunlight orientation, W is The solar constant, The number of heat dissipation devices in the building ， Cooling load for all equipment; In the fourth step, the energy supply capacity of each device is different and is subject to structural constraints. The energy supply capacity of each device is modeled to obtain constraint equations that can reflect the characteristics of each device and network, including an electric energy conversion model, an electric heat conversion model, an electrical conversion model, an electric cooling conversion model, a gas heat conversion model, an energy supply bus and a heat pipe network model; The objective function is the optimization objective function of the park integrated energy system operation, which includes the exchange fee with the power grid and the gas fee, and is optimized and dispatched with the goal of economic optimization, as shown in formula (9): （9） In the formula, , They are The electricity purchase and sales costs of the power grid at all times; For gas costs; , are the efficiencies of gas turbine and gas boiler respectively; for Gas turbine power generation at the moment; for The heating power of the gas boiler at all times.

2. The comprehensive energy optimization scheduling method based on heat load modeling according to claim 1 is characterized in that: The detailed building factors include: the impact of the building's internal space on the heat load, basic sunshine curve, building facade material and layout, weather factors, and heat dissipation of equipment inside the building; Building area Impact, layer height Impact, number of floors Impact, spatial division plan, which affects the overall heat load, heat storage characteristics and internal heat radiation conduction process of the building; The building temperature is divided into the bottom temperature , average body temperature and top temperature , corresponding to the heat transfer processes of the roof, wall and window, and floor respectively; The method for determining the basic sunshine curve is as follows: By using the altitude correction factor 、 Correction coefficient of longitude and latitude change , Building sunlight orientation correction coefficient , Solar constant W , the heat radiation load of basic sunshine impact on unit building exterior surface area is obtained as ; Building facade material and layout are equivalent to wall heat transfer coefficient , roof heat transfer coefficient and geothermal heat transfer coefficient , window heat transfer coefficient ; The weather factor is determined as follows: By introducing historical meteorological data, various weather factors are equivalent to the comprehensive atmospheric passing rate. , to simulate various weather conditions that appear in the simulation to help correct the heat load calculation; Meteorological historical data include hourly or sub-hourly data for each key element; The key factors include geothermal temperature, dry bulb temperature, dew point temperature, relative humidity, air pressure, direct normal radiation, diffuse reflection; The method for determining the heat dissipation of equipment inside the building is as follows: As the functions of buildings vary, the heat dissipated by the equipment inside the building during operation will exchange heat with the air and affect the temperature inside the building. The number of heat dissipation devices in the building is , the historical measured heat dissipation of each device is recorded as , then the heat dissipation load of all equipment is recorded as .

3. The comprehensive energy optimization scheduling method based on heat load modeling according to claim 1 is characterized in that: In the second step, the iterative correction method of temperature tolerance is as follows: Step 1: Obtain user tolerance constraints. The average set temperature of each building is , the user's tolerance temperature deviation range is , then the corresponding The upper and lower limits of the heat load of each building at the moment are , At the same time, the tolerance change limit of heat load of all buildings in one day is , at time t, the node n where building N is located is subject to the temperature tolerance constraint as shown in formula (2): （2） Step 2: Perform iterative correction for temperature crossing the line. After each iteration, check whether the temperature inside the building crosses the line to ensure that the temperature change inside the building in the optimized scheduling result meets the user comfort requirements.

4. The comprehensive energy optimization scheduling method based on heat load modeling according to claim 3 is characterized in that: The electric energy conversion model is used to model photovoltaic equipment, wind turbine equipment, and battery energy storage equipment. The corresponding constraints include electric energy balance constraints, upper and lower limit constraints of equipment status, and upper and lower limit constraints of energy storage. The specific calculation formula is as follows: （3） In formula (3), , They are Purchase and sell electricity from the power grid at all times. , They are The power generation of photovoltaic and wind turbines at all times; , are the battery discharging and charging power respectively; for The electric energy conversion model outputs electric power at the moment; , Equipment The upper and lower limits of power; For equipment exist The electrical power at the time; for The battery capacity at all times; , They are the upper and lower limits of battery power respectively; is the battery power self-loss rate; , are the battery discharge and charge efficiencies respectively; The electrothermal conversion model is used to model devices with electrothermal conversion capabilities; Equipment with electric heat conversion capabilities includes electric boilers and / or electric heat pumps and / or heat storage tanks. The corresponding constraints include energy balance constraints, electric heat equipment state constraints, and heat storage constraints. The specific calculation formula is as follows: （4） In formula (4), Inputting electrical power to the electrothermal conversion model; , They are The electrical and thermal power of the electric boiler at all times; , are the electrical and thermal power of the electric heat pump respectively; , are the efficiencies of electric boilers and electric heat pumps, respectively; , are the heat release and heat storage power of the heat storage tank respectively; is the output thermal power of the electrothermal conversion model; for The heat storage capacity of the heat storage tank at all times; , They are the upper and lower limits of the heat storage capacity of the heat storage tank respectively; is the heat energy self-loss rate of the heat storage tank; , They are heat release and heat storage efficiency of the heat storage tank respectively.

5. The comprehensive energy optimization scheduling method based on heat load modeling according to claim 4 is characterized in that: The electrical conversion model is used to model the power-to-gas device and the gas storage tank. Its corresponding constraints include energy balance constraints, electrical conversion equipment constraints, and gas storage device constraints. The specific calculation formula is as follows: （5） In formula (5), for The electric power input to the gas-to-electricity conversion model at each moment; for Input electrical power to the electric-to-gas device at all times; for The volume of gas output by the electric-to-gas device at each moment; is the efficiency of the power-to-gas device; is the calorific value of natural gas; , respectively Degassing and gas storage volume of the gas tank at all times; for The gas volume output by the gas-to-electricity conversion model at the moment; where, for The gas storage capacity of the gas tank at all times; , They are the upper and lower limits of the gas storage capacity of the gas storage tank respectively; is the gas storage capacity self-loss rate of the gas storage tank; , They are gas tank deflation and gas storage efficiency; The electric cooling conversion model is used to model the electric refrigerator and the cold storage tank. The corresponding constraints include the energy balance constraint of the electric cooling conversion model, the electric cooling equipment state constraint, and the cold storage device constraint. The specific calculation formula is as follows: （6） In formula (6), Inputting electrical power to the electric cooling conversion model; , They are the electrical power and cooling power of the electric refrigerator respectively; is the energy efficiency coefficient of the electric refrigerator; , They are the cooling and storage power of the cold storage tank respectively; Output cooling power for electric cooling conversion models for The cold storage capacity of the cold storage tank at all times; , They are the upper and lower limits of the cold storage capacity of the cold storage tank respectively; is the heat energy self-loss rate of the cold storage tank; , They are the cooling and storage efficiency of the cold storage tank respectively; , They are the state variables of the cold storage tank for cooling and storing cold respectively; The gas-heat conversion model is used to model gas turbines, gas boilers and combined heat and power units. Its corresponding constraints include energy balance constraints, gas-heat conversion equipment constraints and energy storage device constraints. The specific calculation formula is as follows: （7） In formula (7), , They are Gas consumption of gas turbines and gas boilers at all times; , are the efficiencies of gas turbine and gas boiler respectively; , They are The gas turbine outputs electrical power and thermal power at each moment; for The gas boiler outputs thermal power at all times; is the heat loss rate of the gas turbine; is the input gas volume of the gas-heat conversion model; Output thermal power for the gas-heat conversion model; The energy supply bus and heat pipe network model are used to model the functional bus, which includes the power bus and the heat network bus. The specific constraint formula is as follows: （8） In formula (8), for The electrical load power at the moment, for The thermal power injected into the heating network by the system at any moment, for The cold power injected into the heating network by the system at any moment.

6. A comprehensive energy optimization and dispatching system for a park based on heat load modeling, characterized in that: An integrated energy optimization scheduling method based on heat load modeling as described in any one of claims 1 to 5 is applied, which includes a heat load calculation module in a building, an electric energy conversion module, an electric heat conversion module, an electrical conversion module, an electric cooling conversion module, an air heat conversion module, an energy supply bus and a heat pipe network module; According to the optimized scheduling plan determined by the heat load calculation module in the building, each equipment in the park's integrated energy system is scheduled to achieve the goal of minimizing daily operating costs.

7. A park comprehensive energy optimization and scheduling system based on heat load modeling as claimed in claim 6, characterized in that: The building heat load calculation module analyzes the main influencing factors of the building, considers the temperature tolerance within the user's comfort temperature range according to the laws of thermodynamics, takes the minimum daily operating cost as the objective function, and determines the scheduling plan and system operation status of each device in the system; The power conversion module is used to model photovoltaic equipment, wind turbine equipment, and battery energy storage equipment. Its corresponding constraints include power balance constraints, upper and lower limit constraints of equipment status, and upper and lower limit constraints of energy storage; The electrothermal conversion module is used to model the equipment with electrothermal conversion capability. Its corresponding constraints include energy balance constraints, electrothermal equipment state constraints, and thermal energy storage constraints. The electrical conversion module is used to model the power-to-gas device and the gas storage tank. Its corresponding constraints include energy balance constraints, electrical conversion equipment constraints, and gas storage device constraints. The electric cooling conversion module is used to model the electric refrigerator and the cold storage tank. Its corresponding constraints include the energy balance constraint of the electric cooling conversion model, the electric cooling equipment state constraint, and the cold storage device constraint. The gas-heat conversion module is used to model gas turbines, gas boilers and combined heat and power units. Its corresponding constraints include energy balance constraints, gas-heat conversion equipment constraints and energy storage device constraints; The energy bus and heat network modules are used to model the power bus and heat network bus.

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