Multi-building integrated energy system low-carbon scheduling method considering thermal virtual energy storage and light environment design

Abstract

The invention discloses a multi-building integrated energy system low-carbon scheduling method considering thermal virtual energy storage and light environment design. The method comprises the steps of 1, building a building lighting energy consumption control model combining natural lighting and artificial lighting; 2, establishing a multi-building integrated energy system low-carbon scheduling model considering light environment design based on electric energy sharing; and 3, calling a Cplex solver to solve the low-carbon scheduling model and outputting a scheduling result and a carbon emission result according to known equipment parameters, load data of a typical day and an energy demand of a demand side. According to the invention, under the condition of considering the heat storage characteristic of the building and the control of illumination, the resource configuration of the multi-building integrated energy system and the output of equipment are reasonably optimized, so that the low-carbon property of the system can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy systems, and in particular to a low-carbon scheduling method for a multi-building integrated energy system taking into account thermal virtual energy storage and light environment design. Background Art

[0002] With the rapid growth of population and economic development, the demand for energy in buildings has risen sharply. As an innovative energy management method, the building integrated energy system utilizes the coordinated optimization of multiple energy forms, takes buildings as carriers, integrates multiple energy forms such as electricity, heat, cold energy, gas energy, etc., and combines advanced energy management and control technologies to achieve diversified energy supply and efficient utilization. The current design of the building integrated energy system should not only focus on the optimization of energy supply and consumption, but also consider the comprehensive regulation of the physical environment in the building. In particular, the adjustable control of building heat storage and indoor light environment has become one of the important strategies to reduce carbon emissions. Therefore, the development of a building integrated energy system scheduling method that takes into account both heat storage and light environment design has become a key trend in building energy conservation and low-carbon transformation.

[0003] At present, the research on integrated energy systems in buildings mainly focuses on the optimization and management of various forms of energy, such as the efficient use of electricity, natural gas, etc., and the improvement of traditional heating and cooling technologies, but ignores the heat storage characteristics of the building itself and the potential of natural light and adjustable artificial lighting. In existing research, there is little attention paid to combining the heat storage function of building materials with light environment design, resulting in low energy efficiency and difficulty in coping with fluctuations in energy demand. In addition, existing integrated energy systems in buildings generally lack flexible adjustment capabilities and fail to dynamically adjust energy use according to environmental changes, resulting in high carbon emissions. Therefore, how to improve the performance of integrated energy systems in buildings through multi-energy complementarity and precise control of adjustable resources remains an important problem in current research. Summary of the invention

[0004] The present invention aims to address the deficiencies of the above-mentioned prior art and proposes a low-carbon scheduling method for a multi-building integrated energy system taking into account thermal virtual energy storage and light environment design, in order to combine the building's own heat storage with the light environment design, maximize the potential of the building's adjustable resources, and control the equipment, indoor temperature and indoor light environment while meeting the energy needs of multiple users, thereby improving the performance and energy utilization efficiency of the building's integrated energy system and maintaining the low carbon nature of the system.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] The low-carbon scheduling method of a multi-building integrated energy system considering thermal virtual energy storage and light environment design of the present invention is characterized in that it includes the following steps:

[0007] Step 1: Based on the average indoor illumination, use formula (1) to build a building lighting energy consumption control model that combines natural lighting and artificial lighting;

[0008] (1)

[0009] In formula (1), t is any time; is the wall set of building i; is the wall in any direction of building i; is the lighting power required by building i at time t; is the comprehensive illumination value of the room i in building at time t; The area of ​​building i that needs to be illuminated; It represents the total solar radiation intensity received by the wall m in any direction per unit area of ​​building i at time t; is the light-transmitting enclosure area of ​​the wall m in any direction of building i at time t; Indicates the light visual efficiency; is the solar heat gain coefficient; represents the lighting effect of building i; represents the space utilization coefficient of building i; represents the lighting maintenance factor of building i;

[0010] Step 2: According to the needs of users in multiple buildings for energy, indoor thermal environment and light environment, a mathematical model of different energy type equipment in the multi-building integrated energy system is established, where the energy types include: electricity, heat, cold, and gas; the equipment includes: photovoltaic equipment PV, gas turbine GT, waste heat boiler WHB, gas boiler GB, electric refrigerator ER, absorption refrigerator AR, electric energy storage ESS, and thermal energy storage HES;

[0011] Step 3: Taking the minimum total carbon emissions as the goal, establish the objective function of the multi-building integrated energy system scheduling model;

[0012] Step 4: Establish the constraints of the multi-building integrated energy system scheduling model, including: equipment operation constraints, building thermal virtual energy storage constraints, lighting control constraints, energy conservation constraints, and power sharing constraints;

[0013] Step 5: Call the Cplex solver to solve the multi-building integrated energy system scheduling model to obtain the optimal carbon emissions and the optimal equipment operation plan.

[0014] The low-carbon scheduling method for a multi-building integrated energy system considering thermal virtual energy storage and light environment design described in the present invention is also characterized in that: in step 3, the objective function is established using formula (2):

[0015] (2)

[0016] In formula (2): , , They are the actual carbon emissions of electricity purchased by the multi-building integrated energy system, the actual carbon emissions of the gas turbine GT and the gas boiler GB, and:

[0017] (3)

[0018] In formula (3), T represents the total time; N represents the building set; , , They represent three carbon emission parameters of electricity purchase respectively; , and Represents three carbon emission parameters of gas turbine GT and gas boiler GB.

[0019] Furthermore, the constraints in step 4 include:

[0020] Step 4.1 Equipment operation constraints:

[0021] Step 4.1.1, use formula (4) to establish the equipment constraints of photovoltaic equipment PV of building i:

[0022] (4)

[0023] In formula (4), represents the output power value of the photovoltaic PV of building i at time t; Indicates the output power of photovoltaic cells under standard conditions; , They represent the irradiance of photovoltaic PV of building i at time t and the irradiance of photovoltaic PV under standard conditions respectively; It represents the power temperature coefficient; , , , They represent the operating temperature, outdoor temperature, temperature under standard conditions, and rated temperature of the photovoltaic panels of building i respectively; represents the actual output of photovoltaic PV of building i at time t;

[0024] Step 4.1.2: Use equation (5) to establish the equipment constraints of the gas turbine GT, waste heat boiler WHB and gas boiler GB of building i:

[0025] (5)

[0026] In formula (5), represents the electrical power output of the gas turbine GT of building i at time t; represents the power generation efficiency of the gas turbine GT; Indicates the calorific value of natural gas; represents the natural gas consumption of the gas turbine GT of building i at time t; represents the waste heat output by the gas turbine GT of building i at time t; Table GT heat loss coefficient; represents the thermal power output of the waste heat boiler WHB of building i using the waste heat of the gas turbine GT at time t; Indicates the heat recovery efficiency of waste heat boiler WHB; represents the output thermal power of the gas boiler GB of building i at time t; Indicates the thermal efficiency of the gas boiler GB; represents the natural gas consumption of the gas boiler GB of building i at time t; is a 0-1 variable, indicating the operation status of the gas turbine GT of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output electric power of the gas turbine GT of building i; represents the lower limit of the output electric power of the gas turbine GT of building i; represents the upper limit of the ramp rate of the gas turbine GT of building i; represents the lower ramp limit of the gas turbine GT of building i; is a 0-1 variable, indicating the operation status of the gas boiler GB of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output thermal power of the gas boiler GB of building i; represents the lower limit of the output thermal power of the gas boiler GB of building i; represents the upper limit of the ramp rate of the gas boiler GB in building i; represents the lower limit of the ramp of the gas boiler GB in building i;

[0027] Step 4.1.3: Use equation (6) to establish the equipment constraints of the electric refrigerator ER of building i:

[0028] (6)

[0029] In formula (6), represents the cooling power output of the electric refrigerator ER of building i at time t; represents the energy efficiency ratio of the electric refrigerator ER; represents the electrical power consumed by the electric refrigeration machine ER of building i at time t; is the cooling power output by the absorption chiller AR of building i at time t; represents the heat power absorbed by the absorption chiller AR of building i at time t; It represents the energy efficiency ratio of the absorption chiller AR; is a 0-1 variable, indicating the operational status of the electric refrigeration machine ER of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the cooling power output of the electric refrigeration machine ER in building i; represents the lower limit of the cooling power output of the electric refrigeration machine ER in building i; is a 0-1 variable, indicating the operation status of the absorption chiller AR of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output cooling power of the absorption chiller AR in building i; represents the lower limit of the cooling power output of the absorption chiller AR in building i;

[0030] Step 4.1.4: Use equation (7) to establish the equipment constraints of the energy storage equipment of building i:

[0031] (7)

[0032] In formula (7), , They represent the energy stored in the electric energy storage ESS and thermal energy storage HSS of building i at time t respectively; , They represent the charging and discharging power of the electric energy storage ESS of building i at time t respectively; , They represent the charging and discharging power of the thermal energy storage HSS of building i at time t respectively; , Indicates the charging and discharging efficiency of the electric energy storage ESS; , It represents the charging and discharging efficiency of the thermal energy storage HSS; Indicates the scheduling time interval; , represents the upper and lower limits of the capacity of the electric energy storage ESS of building i; , represents the upper and lower limits of the capacity of the thermal storage HSS of building i; , are 0-1 variables, representing the charging status of the electric energy storage ESS and thermal energy storage HSS of building i at time t, 0 represents no charging and 1 represents charging; , are 0-1 variables, representing the release status of the electric energy storage ESS and thermal energy storage HSS of building i at time t, 0 represents no energy release, and 1 represents energy release; , They represent the upper and lower limits of the charging power of the electric energy storage ESS of building i respectively; , They represent the upper and lower limits of the discharge power of the electric energy storage ESS of building i respectively; , They represent the upper and lower limits of the charging power of the thermal energy storage HSS of building i respectively; , They represent the upper and lower limits of the heat release power of the thermal energy storage HSS of building i respectively; Indicates the end time of scheduling; Indicates the scheduling start time;

[0033] Step 4.2: Use equation (8) to establish the thermal virtual energy storage constraint of building i:

[0034] (8)

[0035] In formula (8): Indicates the air density; represents the specific heat capacity of air; represents the indoor air capacity of building i; represents the indoor temperature of building i at time t; represents the heat transferred between the exterior wall of building i and the outdoors at time t; represents the heat transferred between the exterior window of building i and the outdoors at time t; represents the indoor self-heating of building i at time t; represents the heat transferred by the solar radiation exterior wall of building i at time t; represents the heat transferred by the solar radiation exterior window of building i at time t; represents the cooling power of the temperature control of building i at time t; represents the heating power of the temperature control of building i at time t, and:

[0036] (9)

[0037] In formula (9), represents the heat transfer coefficient of wall m in any direction of building i; represents the heat transfer area of ​​the wall m in any direction of building i; represents the heat transfer coefficient of the exterior window on the wall m in any direction of building i; represents the heat transfer area of ​​the exterior windows on the wall m in any direction of building i; Indicates the amount of heat dissipated by the human body; represents the number of people inside building i at time t; represents the clustering coefficient; Indicates the power consumption coefficient of the ballast; Indicates the heat insulation coefficient of the lampshade; represents the lighting power of building i at time t; Indicates the utilization factor; Indicates the installation factor; represents the load factor; represents the average power consumption of electronic equipment in building i at time t; represents the solar radiation absorption coefficient of the wall m in any direction of building i; represents the thermal resistance of the wall m of building i in any direction to solar radiation; represents the irradiance of wall m in any direction of building i at time t; represents the window transmittance of wall m in any direction of building i; represents the shading coefficient of wall m in any direction of building i; is the light-transmitting enclosure area of ​​the wall m in any direction of building i at time t; represents the virtual energy storage power of building i at time t; represents the temperature setting value of building i at time t; and:

[0038] (10)

[0039] In formula (10), , They represent the upper and lower limits of the temperature required to maintain user comfort in building i; , They represent the upper and lower limits of temperature change to maintain the comfort level of users in building i, respectively; represents the indoor temperature of building i at time t-1;

[0040] Step 4.3: Use equation (11) to establish lighting control constraints:

[0041] (11)

[0042] In formula (11): and are the maximum and minimum values ​​of indoor comfortable illumination for building i respectively;

[0043] Step 4.4: Use formula (12) to establish the purchase and sale energy constraints:

[0044] (12)

[0045] In formula (12): , They represent the maximum value of the purchased and sold electric power of building i respectively; , They represent the minimum value of the purchased and sold electric power of building i respectively; It represents the 0-1 variable of electricity purchase of building i at time t, where 0 represents no electricity purchase and 1 represents electricity purchase; It represents the 0-1 variable of electricity sales of building i at time t, where 0 represents no electricity sales and 1 represents electricity sales;

[0046] Step 4.5: Use equation (13) to establish energy conservation constraints:

[0047] (13)

[0048] In formula (13), represents the conventional electrical load of building i at time t; represents the conventional heat load of building i at time t; represents the normal cooling load of building i at time t; represents the shared electric power between building i and building j at time t;

[0049] Step 4.6: Use equation (14) to establish the power sharing constraint:

[0050] (14)

[0051] In formula (14): Indicates the maximum power shared between building i and building j.

[0052] An electronic device of the present invention includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the low-carbon scheduling method for a multi-building integrated energy system, and the processor is configured to execute the program stored in the memory.

[0053] The present invention provides a computer-readable storage medium, and the computer-readable storage medium stores a computer program, wherein the computer program executes the steps of the multi-building integrated energy system low-carbon scheduling method when executed by a processor.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] 1. The present invention proposes an equipment structure of a multi-building integrated energy system, including: photovoltaic equipment PV, gas turbine GT, waste heat boiler WHB, gas boiler GB, electric refrigerator ER, absorption refrigerator AR, electric energy storage ESS, thermal energy storage HES. Considering the thermal storage characteristics of buildings and the adjustable potential of artificial lighting, a low-carbon scheduling method for a multi-building integrated energy system considering thermal virtual energy storage and light environment design is proposed. Carbon emissions are reduced through coordinated optimization control of building equipment, building enclosure thermal storage and artificial lighting. On the basis of meeting reliable operation, a reasonable distribution of energy in the building integrated energy system is achieved.

[0056] 2. The low-carbon dispatching method for the multi-building integrated energy system of the present invention integrates multiple buildings and connects them in the form of power sharing, making full use of the characteristic of electric energy being easy to transmit and expanding the coverage of the energy system. Through power sharing, the range of energy available to the integrated energy system of each building is expanded, achieving energy complementarity in time and space, which not only ensures the load energy supply of each building, but also realizes the low-carbon operation of the entire system through the mutual assistance of multiple types of energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a structural diagram of the building integrated energy system of the present invention;

[0058] Figure 2 This is the operating framework diagram of the multi-building integrated energy system of the present invention;

[0059] Figure 3 It is the optimal operation scheme of the electrical equipment of the present invention;

[0060] Figure 4 It is the optimal operation scheme of the thermal equipment of the present invention;

[0061] Figure 5 It is the optimal operation scheme of the cooling equipment of the present invention;

[0062] Figure 6 It is the indoor temperature result of the present invention;

[0063] Figure 7 This is the building light environment composition scheme of the present invention. DETAILED DESCRIPTION

[0064] In this embodiment, a low-carbon scheduling method for a multi-building integrated energy system considering thermal virtual energy storage and light environment design is provided, and the steps are:

[0065] Step 1) According to the point illumination calculation principle, the total illumination value of a certain point on the indoor horizontal ground is the composite value of the illumination of natural light and artificial lighting acting on the point. Referring to this calculation idea, according to the indoor average illumination, use formula (1) to build a building lighting energy consumption control model combining natural lighting and artificial lighting;

[0066] (1)

[0067] In formula (1), t is any time; is the wall set of building i; is the wall in any direction of building i; is the lighting power required by building i at time t; is the comprehensive illumination value of the room i in building at time t; The area of ​​building i that needs to be illuminated; It represents the total solar radiation intensity received by the wall m in any direction per unit area of ​​building i at time t; is the light-transmitting enclosure area of ​​the wall m in any direction of building i at time t; Indicates the light visual efficiency; is the solar heat gain coefficient; represents the lighting effect of building i; represents the space utilization coefficient of building i; represents the lighting maintenance factor of building i.

[0068] Step 2) According to the energy, indoor thermal environment and light environment requirements of users in multiple buildings, a mathematical model of different energy type equipment in the multi-building integrated energy system is established, where the energy types include: electricity, heat, cold, and gas; the equipment is as follows: Figure 1 As shown, the equipment includes: photovoltaic equipment PV, gas turbine GT, waste heat boiler WHB, gas boiler GB, electric refrigerator ER, absorption refrigerator AR, electric energy storage ESS, thermal energy storage HES; establish a power sharing operation architecture for multi-building integrated energy systems, such as Figure 2 shown.

[0069] Step 3) Taking the minimum total carbon emissions as the goal, the objective function of the multi-building integrated energy system scheduling model is established using formula (2);

[0070] (2)

[0071] In formula (2): , , They are the actual carbon emissions of electricity purchased by the multi-building integrated energy system, the actual carbon emissions of the gas turbine GT and the gas boiler GB, and:

[0072] (3)

[0073] In formula (3), T represents the total time; N represents the building set; , , They represent three carbon emission parameters of electricity purchase respectively; , and Represents three carbon emission parameters of gas turbine GT and gas boiler GB.

[0074] Step 4) Establish the constraints of the multi-building integrated energy system scheduling model, including: equipment operation constraints, building thermal virtual energy storage constraints, lighting control constraints, energy conservation constraints, and power sharing constraints;

[0075] Step 4.1) Equipment operation constraints:

[0076] Step 4.1.1) Use equation (4) to establish the equipment constraints of the photovoltaic equipment PV of building i:

[0077] (4)

[0078] In formula (4), represents the output power value of the photovoltaic PV of building i at time t; Indicates the output power of photovoltaic cells under standard conditions; , They represent the photovoltaic irradiance of building i at time t and the photovoltaic irradiance under standard conditions respectively; It represents the power temperature coefficient; , , , They represent the operating temperature, outdoor temperature, temperature under standard conditions, and rated temperature of the photovoltaic panels in building i respectively; Represents the actual photovoltaic output of building i at time t.

[0079] Step 4.1.2) Use equation (5) to establish the equipment constraints of the gas turbine GT, waste heat boiler WHB and gas boiler GB of building i:

[0080] (5)

[0081] In formula (5), represents the electrical power output of the gas turbine GT of building i at time t; represents the power generation efficiency of the gas turbine GT; Indicates the calorific value of natural gas; represents the natural gas consumption of the gas turbine GT of building i at time t; represents the waste heat output by the gas turbine GT of building i at time t; Table GT heat loss coefficient; represents the thermal power output of the waste heat boiler WHB of building i using the waste heat of the gas turbine GT at time t; Indicates the heat recovery efficiency of waste heat boiler WHB; represents the output thermal power of the gas boiler GB of building i at time t; Indicates the thermal efficiency of the gas boiler GB; represents the natural gas consumption of the gas boiler GB of building i at time t; is a 0-1 variable, indicating the operation status of the gas turbine GT of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output electric power of the gas turbine GT of building i; represents the lower limit of the output electric power of the gas turbine GT of building i; represents the upper limit of the ramp rate of the gas turbine GT of building i; represents the lower ramp limit of the gas turbine GT of building i; is a 0-1 variable, indicating the operation status of the gas boiler GB of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output thermal power of the gas boiler GB of building i; represents the lower limit of the output thermal power of the gas boiler GB of building i; represents the upper limit of the ramp rate of the gas boiler GB in building i; It represents the lower limit of the ramp rate of the gas boiler GB in building i.

[0082] Step 4.1.3) Use equation (6) to establish the equipment constraints of the electric refrigerator ER of building i:

[0083] (6)

[0084] In formula (6), represents the cooling power output of the electric refrigerator ER of building i at time t; represents the energy efficiency ratio of the electric refrigerator ER; represents the electrical power consumed by the electric refrigeration machine ER of building i at time t; is the cooling power output by the absorption chiller AR of building i at time t; represents the heat power absorbed by the absorption chiller AR of building i at time t; It represents the energy efficiency ratio of the absorption chiller AR; is a 0-1 variable, indicating the operational status of the electric refrigeration machine ER of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the cooling power output of the electric refrigeration machine ER in building i; represents the lower limit of the cooling power output of the electric refrigeration machine ER in building i; is a 0-1 variable, indicating the operation status of the absorption chiller AR of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output cooling power of the absorption chiller AR in building i; It represents the lower limit of the cooling power output of the absorption chiller AR in building i.

[0085] Step 4.1.4) Use equation (7) to establish the equipment constraints of the energy storage equipment of building i:

[0086] (7)

[0087] In formula (7), , They represent the energy stored in the electric energy storage ESS and thermal energy storage HSS of building i at time t respectively; , They represent the charging and discharging power of the electric energy storage ESS of building i at time t respectively; , They represent the charging and discharging power of the thermal energy storage HSS of building i at time t respectively; , Indicates the charging and discharging efficiency of the electric energy storage ESS; , It represents the charging and discharging efficiency of the thermal energy storage HSS; Indicates the scheduling time interval; , represents the upper and lower limits of the capacity of the electric energy storage ESS of building i; , represents the upper and lower limits of the capacity of the thermal storage HSS of building i; , are 0-1 variables, representing the charging status of the electric energy storage ESS and thermal energy storage HSS of building i at time t, 0 represents no charging and 1 represents charging; , are 0-1 variables, representing the release status of the electric energy storage ESS and thermal energy storage HSS of building i at time t, 0 represents no energy release, and 1 represents energy release; , They represent the upper and lower limits of the charging power of the electric energy storage ESS of building i respectively; , They represent the upper and lower limits of the discharge power of the electric energy storage ESS of building i respectively; , They represent the upper and lower limits of the HSS charging power of the thermal energy storage of building i, respectively; , They represent the upper and lower limits of the heat storage HSS heat release power of building i respectively; Indicates the end time of scheduling; Indicates the scheduling start time.

[0088] Step 4.2) Use equation (8) to establish the thermal virtual energy storage constraint of building i:

[0089] (8)

[0090] In formula (8): Indicates the air density; represents the specific heat capacity of air; represents the indoor air capacity of building i; represents the indoor temperature of building i at time t; represents the heat transferred between the exterior wall of building i and the outdoors at time t; represents the heat transferred between the exterior window of building i and the outdoors at time t; represents the indoor self-heating of building i at time t; represents the heat transferred by the solar radiation exterior wall of building i at time t; represents the heat transferred by the solar radiation exterior window of building i at time t; represents the cooling power of the temperature control of building i at time t; represents the heating power of the temperature control of building i at time t, and:

[0091] (9)

[0092] In formula (9), represents the heat transfer coefficient of wall m in any direction of building i; represents the heat transfer area of ​​the wall m in any direction of building i; represents the heat transfer coefficient of the exterior window on the wall m in any direction of building i; represents the heat transfer area of ​​the exterior windows on the wall m in any direction of building i; Indicates the amount of heat dissipated by the human body; represents the number of people inside building i at time t; represents the clustering coefficient; Indicates the power consumption coefficient of the ballast; Indicates the heat insulation coefficient of the lampshade; represents the lighting power of building i at time t; Indicates the utilization factor; Indicates the installation factor; represents the load factor; represents the average power consumption of electronic equipment in building i at time t; represents the solar radiation absorption coefficient of the wall m in any direction of building i; represents the thermal resistance of the wall m of building i in any direction to solar radiation; represents the irradiance of wall m in any direction of building i at time t; represents the window transmittance of wall m in any direction of building i; represents the shading coefficient of wall m in any direction of building i; is the light-transmitting enclosure area of ​​the wall m in any direction of building i at time t; represents the virtual energy storage power of building i at time t; represents the temperature setting value of building i at time t; and:

[0093] (10)

[0094] In formula (10), , They represent the upper and lower limits of the temperature required to maintain the comfort level of users in building i. , They represent the upper limit of temperature change to maintain the comfort level of users in building i. Lower limit; represents the indoor temperature of building i at time t-1.

[0095] Step 4.3) Use equation (11) to establish lighting control constraints:

[0096] (11)

[0097] In formula (11): and are the maximum and minimum values ​​of indoor comfortable illumination for building i respectively;

[0098] Step 4.4) Use equation (12) to establish the purchase and sale energy constraints:

[0099] (12)

[0100] In formula (12): , They represent the maximum value of the purchased and sold electric power of building i respectively; , They represent the minimum value of the purchased and sold electric power of building i respectively; It represents the 0-1 variable of electricity purchase of building i at time t, where 0 represents no electricity purchase and 1 represents electricity purchase; A 0-1 variable representing the electricity sales of building i at time t, where 0 represents no electricity sales and 1 represents electricity sales.

[0101] Step 4.5) Use equation (13) to establish energy conservation constraints:

[0102] (13)

[0103] In formula (13), represents the conventional electrical load of building i at time t; represents the conventional heat load of building i at time t; represents the normal cooling load of building i at time t; Represents the shared electric power between building i and building j at time t.

[0104] Step 4.6) Use equation (14) to establish the power sharing constraint:

[0105] (14)

[0106] In formula (14): Indicates the maximum power shared between building i and building j.

[0107] Step 5: Call the Cplex solver to solve the multi-building integrated energy system scheduling model to obtain the optimal carbon emissions and the optimal equipment operation plan.

[0108] In this embodiment, an electronic device includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the above method, and the processor is configured to execute the program stored in the memory.

[0109] In this embodiment, a computer-readable storage medium stores a computer program on the computer-readable storage medium, and the computer program executes the steps of the above method when executed by a processor.

[0110] In this example, three buildings are set up, and the following four scenarios can be used for analysis.

[0111] Scenario 1: Thermal virtual energy storage is not considered, the building temperature is set to 24°C, lighting control is not considered, and indoor illumination is provided only by artificial lighting;

[0112] Scenario 2: Without considering thermal virtual energy storage, the building temperature is set to 24°C, and considering lighting control, the indoor illumination is provided by natural lighting and artificial lighting;

[0113] Scenario 3: Considering thermal virtual energy storage, the building temperature is set between 22 and 26°C, lighting control is not considered, and indoor illumination is provided only by artificial lighting;

[0114] Scenario 4: Considering thermal virtual energy storage, the building temperature is set between 22 and 26°C, and considering lighting control, the indoor illumination is provided by natural lighting and artificial lighting; as shown in Table 1:

[0115] Table 1 Carbon emissions from building integrated energy system scheduling under different scenarios

[0116]

[0117] From Table 1, we can see that: 1) By comparing the costs of scenario 1 and scenario 2, when the building does not consider thermal virtual energy storage, the dispatch carbon emissions of considering lighting control are lower than those of not considering lighting control, with a reduction of 8.9%; by comparing the costs of scenario 3 and scenario 4, when the building considers thermal virtual energy storage, the dispatch carbon emissions of considering lighting control are lower than those of not considering lighting control, with a reduction of 9.3%. 2) By comparing the costs of scenario 1 and scenario 3, when the building does not consider lighting control, the dispatch carbon emissions of considering thermal virtual energy storage are lower than those of not considering thermal virtual energy storage, with a reduction of 4.4%; by comparing the costs of scenario 2 and scenario 4, when the building considers lighting control, the dispatch carbon emissions of considering thermal virtual energy storage are lower than those of not considering thermal virtual energy storage, with a reduction of 4.8%. 3) By comparing the costs of scenario 1 and scenario 4, when the building considers both thermal virtual energy storage and lighting control, the dispatch carbon emissions are greatly reduced, with a reduction of 13.3%.

[0118] Figure 3 It is the optimal operation scheme of the electrical equipment of the present invention; Figure 4 The optimal operation scheme of the thermal equipment of the present invention; Figure 5 The optimal operation scheme of the cooling equipment of the present invention; Figure 6 is the indoor temperature result of the present invention; Figure 7 This is the building indoor light environment composition scheme of the present invention. Figure 3 , Figure 4 , Figure 5 It can be seen that electricity is provided by photovoltaic equipment, gas turbine power generation, electricity purchase, electric energy storage and electricity shared by other buildings, thermal energy is provided by waste heat boilers, gas boilers, thermal energy storage and thermal energy shared by other buildings, and building cooling is provided by absorption refrigeration and electric refrigeration. Among them, electricity is provided by gas turbines, electricity purchase, electric energy storage and shared electricity from 1:00 to 5:00 and 19:00 to 24:00. The reason is that there is heat load in the building during this period. Using gas boilers alone for heating will reduce the energy efficiency of the system. Therefore, gas turbines are required to provide heating first, and the excess electricity is supplied to the electric load. The power shortage can be met by purchasing electricity, discharging electric energy storage and receiving electricity shared by other buildings; electricity is provided by photovoltaic equipment, gas turbines, electricity purchase, electric energy storage and electricity shared by other buildings from 6:00 to 18:00. The reason is similar to 1:00 to 5:00. The difference is that photovoltaic equipment power generation belongs to clean energy production. In the present invention, photovoltaics can be used first to reduce the carbon emissions of the system. At the same time, low-carbon emission gas turbines and low-carbon electricity shared by other buildings are used to supplement the power shortage, and finally the power demand is met by purchasing electricity. Figure 6It can be seen that during the period of 2:00~8:00, since the temperature is set between 22℃~26℃, the outdoor temperature is basically within this range, and the absorption refrigeration and electric refrigeration do not operate; during the period of 9:00~23:00, in order to reduce energy consumption and carbon emissions, the absorption refrigeration and electric refrigeration jointly supply the indoor cooling load, and the indoor temperature is maintained at 26℃. Figure 7 During the period of 6:00~11:00, due to sufficient sunlight on the east side, the indoor lighting can be met by daylighting on the east side of the building. During the period of 11:00~20:00, the sunlight on the east side weakens and the sunlight on the west side increases. The indoor lighting can be met by daylighting on the west side of the building. Daylighting on other sides and artificial lighting are used as auxiliary. Through the mutual coordination of daylighting and lighting, while meeting the indoor illumination requirements, the indoor lighting power is minimized to the maximum extent, thereby reducing the carbon emissions caused by electricity production, achieving the effect of energy saving and carbon reduction.

Claims

1. A low-carbon scheduling method for a multi-building integrated energy system considering thermal virtual energy storage and light environment design, characterized in that: The following steps are involved: Step 1: Based on the average indoor illumination, use formula (1) to build a building lighting energy consumption control model that combines natural lighting and artificial lighting; (1) In formula (1), t is any time; is the wall set of building i; is the wall in any direction of building i; is the lighting power required by building i at time t; is the comprehensive illumination value of the room i in building at time t; The area of ​​building i that needs to be illuminated; It represents the total solar radiation intensity received by the wall m in any direction per unit area of ​​building i at time t; is the light-transmitting enclosure area of ​​the wall m in any direction of building i at time t; Indicates the light visual efficiency; is the solar heat gain coefficient; represents the lighting effect of building i; represents the space utilization coefficient of building i; represents the lighting maintenance factor of building i; Step 2: According to the needs of users in multiple buildings for energy, indoor thermal environment and light environment, a mathematical model of different energy type equipment in the multi-building integrated energy system is established, where the energy types include: electricity, heat, cold, and gas; the equipment includes: photovoltaic equipment PV, gas turbine GT, waste heat boiler WHB, gas boiler GB, electric refrigerator ER, absorption refrigerator AR, electric energy storage ESS, and thermal energy storage HES; Step 3: Taking the minimum total carbon emissions as the goal, establish the objective function of the multi-building integrated energy system scheduling model; Step 4: Establish the constraints of the multi-building integrated energy system scheduling model, including: equipment operation constraints, building thermal virtual energy storage constraints, lighting control constraints, energy conservation constraints, and power sharing constraints; Step 5: Call the Cplex solver to solve the multi-building integrated energy system scheduling model to obtain the optimal carbon emissions and the optimal equipment operation plan.

2. According to claim 1, a low-carbon scheduling method for a multi-building integrated energy system considering thermal virtual energy storage and light environment design is characterized by: In step 3, the objective function is established using formula (2): (2) In formula (2): , , They are the actual carbon emissions of electricity purchased by the multi-building integrated energy system, the actual carbon emissions of the gas turbine GT and the gas boiler GB, and: (3) In formula (3), T represents the total time; N represents the building set; , , They represent three carbon emission parameters of electricity purchase respectively; , and Represents three carbon emission parameters of gas turbine GT and gas boiler GB.

3. According to claim 2, a low-carbon scheduling method for a multi-building integrated energy system considering thermal virtual energy storage and light environment design is characterized in that: The constraints in step 4 include: Step 4.1 Equipment operation constraints: Step 4.1.1, use formula (4) to establish the equipment constraints of photovoltaic equipment PV of building i: (4) In formula (4), represents the output power value of the photovoltaic PV of building i at time t; Indicates the output power of photovoltaic cells under standard conditions; , They represent the irradiance of photovoltaic PV of building i at time t and the irradiance of photovoltaic PV under standard conditions respectively; It represents the power temperature coefficient; , , , They represent the operating temperature, outdoor temperature, temperature under standard conditions, and rated temperature of the photovoltaic panels of building i respectively; represents the actual output of photovoltaic PV of building i at time t; Step 4.1.2: Use equation (5) to establish the equipment constraints of the gas turbine GT, waste heat boiler WHB and gas boiler GB of building i: (5) In formula (5), represents the electrical power output of the gas turbine GT of building i at time t; represents the power generation efficiency of the gas turbine GT; Indicates the calorific value of natural gas; represents the natural gas consumption of the gas turbine GT of building i at time t; represents the waste heat output by the gas turbine GT of building i at time t; Table GT heat loss coefficient; represents the thermal power output of the waste heat boiler WHB of building i using the waste heat of the gas turbine GT at time t; Indicates the heat recovery efficiency of waste heat boiler WHB; represents the output thermal power of the gas boiler GB of building i at time t; Indicates the thermal efficiency of the gas boiler GB; represents the natural gas consumption of the gas boiler GB of building i at time t; is a 0-1 variable, indicating the operation status of the gas turbine GT of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output electric power of the gas turbine GT of building i; represents the lower limit of the output electric power of the gas turbine GT of building i; represents the upper limit of the ramp rate of the gas turbine GT of building i; represents the lower ramp limit of the gas turbine GT of building i; is a 0-1 variable, indicating the operation status of the gas boiler GB of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output thermal power of the gas boiler GB of building i; represents the lower limit of the output thermal power of the gas boiler GB of building i; represents the upper limit of the ramp rate of the gas boiler GB in building i; represents the lower limit of the ramp of the gas boiler GB in building i; Step 4.1.3: Use equation (6) to establish the equipment constraints of the electric refrigerator ER of building i: (6) In formula (6), represents the cooling power output of the electric refrigerator ER of building i at time t; It represents the energy efficiency ratio of the electric refrigerator ER; represents the electrical power consumed by the electric refrigeration machine ER of building i at time t; is the cooling power output by the absorption chiller AR of building i at time t; represents the heat power absorbed by the absorption chiller AR of building i at time t; It represents the energy efficiency ratio of the absorption chiller AR; is a 0-1 variable, indicating the operational status of the electric refrigeration machine ER of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the cooling power output of the electric refrigeration machine ER in building i; represents the lower limit of the cooling power output of the electric refrigeration machine ER in building i; is a 0-1 variable, indicating the operation status of the absorption chiller AR of building i at time t, 0 represents not in operation, and 1 represents in operation; represents the upper limit of the output cooling power of the absorption chiller AR in building i; represents the lower limit of the cooling power output of the absorption chiller AR in building i; Step 4.1.4: Use equation (7) to establish the equipment constraints of the energy storage equipment of building i: (7) In formula (7), , They represent the energy stored in the electric energy storage ESS and thermal energy storage HSS of building i at time t respectively; , They represent the charging and discharging power of the electric energy storage ESS of building i at time t respectively; , They represent the charging and discharging power of the thermal energy storage HSS of building i at time t respectively; , Indicates the charging and discharging efficiency of the electric energy storage ESS; , It represents the charging and discharging efficiency of the thermal energy storage HSS; Indicates the scheduling time interval; , represents the upper and lower limits of the capacity of the electric energy storage ESS of building i; , represents the upper and lower limits of the capacity of the thermal storage HSS of building i; , are 0-1 variables, representing the charging status of the electric energy storage ESS and thermal energy storage HSS of building i at time t, 0 represents no charging and 1 represents charging; , are 0-1 variables, representing the release status of the electric energy storage ESS and thermal energy storage HSS of building i at time t, 0 represents no energy release, and 1 represents energy release; , They represent the upper and lower limits of the charging power of the electric energy storage ESS of building i respectively; , They represent the upper and lower limits of the discharge power of the electric energy storage ESS of building i respectively; , They represent the upper and lower limits of the charging power of the thermal energy storage HSS of building i respectively; , They represent the upper and lower limits of the heat release power of the thermal energy storage HSS of building i respectively; Indicates the end time of scheduling; Indicates the scheduling start time; Step 4.2: Use equation (8) to establish the thermal virtual energy storage constraint of building i: (8) In formula (8): Indicates the air density; represents the specific heat capacity of air; represents the indoor air capacity of building i; represents the indoor temperature of building i at time t; represents the heat transferred between the exterior wall of building i and the outdoors at time t; represents the heat transferred between the exterior window of building i and the outdoors at time t; represents the indoor self-heating of building i at time t; represents the heat transferred by the solar radiation exterior wall of building i at time t; represents the heat transferred by the solar radiation exterior window of building i at time t; represents the cooling power of the temperature control of building i at time t; represents the heating power of the temperature control of building i at time t, and: (9) In formula (9), represents the heat transfer coefficient of wall m in any direction of building i; represents the heat transfer area of ​​the wall m in any direction of building i; represents the heat transfer coefficient of the exterior window on the wall m in any direction of building i; represents the heat transfer area of ​​the exterior windows on the wall m in any direction of building i; Indicates the amount of heat dissipated by the human body; represents the number of people inside building i at time t; represents the clustering coefficient; Indicates the power consumption coefficient of the ballast; Indicates the heat insulation coefficient of the lampshade; represents the lighting power of building i at time t; Indicates the utilization factor; Indicates the installation factor; represents the load factor; represents the average power consumption of electronic equipment in building i at time t; represents the solar radiation absorption coefficient of the wall m in any direction of building i; represents the thermal resistance of the wall m of building i in any direction to solar radiation; represents the irradiance of wall m in any direction of building i at time t; represents the window transmittance of wall m in any direction of building i; represents the shading coefficient of wall m in any direction of building i; is the light-transmitting enclosure area of ​​the wall m in any direction of building i at time t; represents the virtual energy storage power of building i at time t; represents the temperature setting value of building i at time t; and: (10) In formula (10), , They represent the upper and lower limits of the temperature required to maintain user comfort in building i; , They represent the upper and lower limits of temperature change to maintain the comfort level of users in building i, respectively; represents the indoor temperature of building i at time t-1; Step 4.3: Use equation (11) to establish lighting control constraints: (11) In formula (11): and are the maximum and minimum values ​​of indoor comfortable illumination for building i respectively; Step 4.4: Use formula (12) to establish the purchase and sale energy constraints: (12) In formula (12): , They represent the maximum value of the purchased and sold electric power of building i respectively; , They represent the minimum value of the purchased and sold electric power of building i respectively; It represents the 0-1 variable of electricity purchase of building i at time t, where 0 represents no electricity purchase and 1 represents electricity purchase; It represents the 0-1 variable of electricity sales of building i at time t, where 0 represents no electricity sales and 1 represents electricity sales; Step 4.5: Use equation (13) to establish energy conservation constraints: (13) In formula (13), represents the conventional electrical load of building i at time t; represents the conventional heat load of building i at time t; represents the normal cooling load of building i at time t; represents the shared electric power between building i and building j at time t; Step 4.6: Use equation (14) to establish the power sharing constraint: (14) In formula (14): Indicates the maximum power shared between building i and building j.

4. An electronic device, comprising a memory and a processor, characterized in that: The memory is used to store a program that supports the processor to execute the low-carbon scheduling method for a multi-building integrated energy system as described in any one of claims 1-3, and the processor is configured to execute the program stored in the memory.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the low-carbon scheduling method for a multi-building integrated energy system described in any one of claims 1 to 3 are executed.

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