A load-side demand response method and system for a low-carbon urban integrated energy system

Abstract

This invention discloses a load-side demand response method and system for a low-carbon urban integrated energy system, comprising: establishing a load-side demand response model for the low-carbon urban integrated energy system; classifying the air conditioning function penetration rate on the load side of the low-carbon urban integrated energy system and determining the functional penetration rate classification result; establishing a model for air conditioning participation in peak shaving in the low-carbon urban integrated energy system; and performing demand response based on the load-side demand response model, the functional penetration rate classification result, and the air conditioning participation in peak shaving model to determine the total load change in the load-side demand response. This invention classifies load demand response into price-sensitive demand response and energy conversion demand response based on the energy consumption characteristics of the low-carbon urban integrated energy system load side; proposes the participation of air conditioning in grid peak shaving on the load side of the low-carbon urban integrated energy system and provides a quantitative calculation method for the air conditioning function penetration rate, which can provide a reference for the low-carbon operation optimization strategy of the low-carbon urban integrated energy system.

Description

Technical Field

[0001] This invention relates to the field of low-carbon dispatch and operation technology of power systems, and more specifically, to a load-side demand response method and system for a low-carbon urban integrated energy system. Background Technology

[0002] As climate issues become increasingly prominent, 178 parties worldwide signed the Paris Agreement, committing to a unified approach to global climate change action. Due to the diversified development of urban energy sources, the electricity demands and consumption patterns of system users are becoming more varied, leading to a greater number of carbon emission sources. Therefore, carbon emission control, environmental requirements, and energy supply pressures will pose significant challenges to the rational operation of urban integrated energy systems.

[0003] The development of urban integrated energy systems has been rapid, leading to significant changes in energy supply methods. Traditionally, urban energy supply relied primarily on coal, natural gas, and grid power, mainly powered by synchronous generators. However, with the decarbonization of the energy structure, clean energy sources, such as wind power and solar power, are participating in energy supply and are gradually adopting distributed grid-connected methods. Thermal storage devices, combined heat and power (CHP) equipment, and energy storage systems will also participate extensively in the charging and discharging processes of the system's energy.

[0004] Therefore, a load-side demand response method for low-carbon urban integrated energy systems that takes into account the participation of electrical energy flow in grid peak shaving is needed. Summary of the Invention

[0005] This invention proposes a load-side demand response method and system for a low-carbon urban integrated energy system to address the lack of low-carbon operation and scheduling in modern low-carbon urban integrated energy systems.

[0006] To address the aforementioned problems, according to one aspect of the present invention, a load-side demand response method for a low-carbon urban integrated energy system is provided, the method comprising:

[0007] Establish a load-side demand response model for a low-carbon urban integrated energy system;

[0008] The air conditioning function penetration rate of the load side of the integrated energy system in a low-carbon city is divided, and the result of the function penetration rate division is determined.

[0009] Establish a model for air conditioning participation in peak shaving within a low-carbon city's integrated energy system;

[0010] Based on the load-side demand response model, functional penetration rate division results, and air conditioning participation peak shaving model, the total load change in the load-side demand response is determined.

[0011] Preferably, the load-side demand response model of the low-carbon urban integrated energy system includes: a price-sensitive demand response sub-model and an energy conversion demand response sub-model, wherein the price-sensitive demand response sub-model includes: a load reduction model and an adjustable load model.

[0012] The load reduction model includes:

[0013]

[0014] The adjustable load model includes:

[0015]

[0016] The energy conversion-type demand response sub-model includes:

[0017]

[0018] in, Let t be the initial load reduction amount. The initial load reduction at time t; Ξ CL (t,k) is the demand flexibility matrix for load reduction prices, ψ k Let ζ be the electricity price at time k. Cus User satisfaction rating Let k be the initial electricity price at time k; Let Ξ be the initial adjustable load at time t. AL (t,k) is an adjustable load price demand flexibility matrix. The initial adjustable load at time t; These represent the replaceable electrical load and the corresponding heat load, respectively; ζ is the energy conversion coefficient; H ε H h These are the unit calorific value of electrical energy and thermal energy, respectively; η ε η h These are the energy utilization rates of electrical energy and thermal energy, respectively.

[0019] Preferably, the determination of the functional penetration rate of air conditioning on the load side of the low-carbon urban integrated energy system, and the determination of the functional penetration rate classification result, includes:

[0020] Collect the maximum power utilization of building cooling / heating in the integrated energy system of low-carbon cities.

[0021] Collect the latest rated power (P) of the air conditioning load connected to the grid in the integrated energy system of low-carbon cities. AC,Rated ;

[0022] use Calculate the peak-shaving utilization rate η of the integrated energy system in a low-carbon cityAC,PS :

[0023] use Calculate the demand response utilization rate η of the integrated energy system in a low-carbon city. AC,DR .

[0024] Preferably, the establishment of a low-carbon urban integrated energy system air conditioning participation peak-shaving model includes:

[0025] Establish an air conditioning thermodynamic model, including:

[0026]

[0027] Establish an indoor air temperature model, including:

[0028]

[0029] Among them, the polynomials f1, f2, f3, and f4 satisfy:

[0030]

[0031] The power model for air conditioning participating in grid peak shaving at time t is established as follows:

[0032]

[0033] Where, Θ H Indoor body temperature, T in (t) represents the indoor air temperature at time t, P W·V (t) is the water vapor pressure, S(t) is the wind speed at time t, σ air Relative air humidity; Δ 11 Δ 12 Δ 13 Δ 14 Δ 21 Δ 22 and Δ 23 All are constants; Q p It is the rated cooling capacity of the coolant pack, γ C·W It is the water vapor temperature coefficient. These are the operating states of RAC, with T1 and T0 representing the operating states respectively. and The initial room temperature at that time; σ a V represents the relative humidity of the air. B For the building volume, κ S S is the heat storage coefficient of the building's interior walls. w_in S represents the area of ​​the building's interior walls. top and S w T represents the thermal conductivity of the building's roof and walls, respectively. wc T wjThese are the outlet and inlet temperatures of the cooling water, respectively, T. out (t) represents the outdoor temperature at time t, κ e κ z κ x These are the equipment cooling load, lighting cooling load, and human visual cooling load coefficients, q e q z Heat dissipation per unit area q for equipment and lighting, respectively. x q n Q represents the heat dissipation from the human body, specifically the sensible heat and latent heat. L (t) represents the indoor cooling load at time t, Q r (t) represents the personnel cooling load at time t, S C For cooling area, and These represent the number of passengers and the passenger flow boundary, respectively, ε Clu m is the aggregation coefficient; w C w These are the mass and specific heat capacity of chilled water, respectively; Q RAC R is the cooling power of the air conditioner when it reaches steady state; a It is the equivalent thermal resistance of RAC; P RAC (t) represents the peak reduction potential at time t, N RAC Q represents the number of refrigeration and air conditioning systems in the IES. RAC,i Let Δ be the cooling power of the i-th refrigeration and air conditioning system. RAC1 Δ is the principal term coefficient for the electrical power of the refrigeration and air conditioning system. RAC2 and l RAC These are the main term coefficient and constant term for the cooling power of the refrigeration and air conditioning system, respectively.

[0034] Preferably, the determination of the total load change in load-side demand response based on the load-side demand response model, functional penetration rate division results, and air conditioning participation peak-shaving model includes:

[0035]

[0036] in, Let t be the total load change in the load-side demand response. The load change can be reduced after the load demand response is reduced at time t. The adjustable load demand response change at time t; These are the alternative electrical load and the corresponding thermal load, respectively; P RAC (t) represents the peak shaving potential of the air conditioning system at time t; B CL B AL BR1, BR2, B RACThese are, respectively, the load demand response logic control factor that can be reduced, the load demand response logic control factor that can be adjusted, the electrical load logic control factor that can be substituted, the thermal load logic control factor that can be substituted, and the RAC peak shaving logic control factor.

[0037] According to another aspect of the present invention, a load-side demand response system for a low-carbon urban integrated energy system is provided, the system comprising:

[0038] Demand response model building unit, used to build load-side demand response models for integrated energy systems in low-carbon cities;

[0039] The functional penetration rate division unit is used to divide the air conditioning functional penetration rate on the load side of the integrated energy system of a low-carbon city and determine the functional penetration rate division result.

[0040] The peak-shaving model establishment unit is used to establish a peak-shaving model for air conditioning participation in a low-carbon urban integrated energy system.

[0041] The total load change determination unit is used to determine the total load change of the load-side demand response based on the load-side demand response model, the functional penetration rate division results, and the air conditioning participation peak shaving model.

[0042] Preferably, the load-side demand response model of the low-carbon urban integrated energy system includes: a price-sensitive demand response sub-model and an energy conversion demand response sub-model, wherein the price-sensitive demand response sub-model includes: a load reduction model and an adjustable load model.

[0043] The load reduction model includes:

[0044]

[0045] The adjustable load model includes:

[0046]

[0047] The energy conversion-type demand response sub-model includes:

[0048]

[0049] in, Let t be the initial load reduction amount. The initial load reduction at time t; Ξ CL (t,k) is the demand flexibility matrix for load reduction prices, ψ k Let ζ be the electricity price at time k. Cus User satisfaction rating Let k be the initial electricity price at time k; Let Ξ be the initial adjustable load at time t. AL (t,k) is an adjustable load price demand flexibility matrix. The initial adjustable load at time t; These represent the replaceable electrical load and the corresponding heat load, respectively; ζ is the energy conversion coefficient; H ε H h These are the unit calorific value of electrical energy and thermal energy, respectively; η ε η h These are the energy utilization rates of electrical energy and thermal energy, respectively.

[0050] Preferably, the functional penetration rate division unit is used to divide the air conditioning functional penetration rate on the load side of the low-carbon urban integrated energy system, and to determine the functional penetration rate division result, including:

[0051] Collect the maximum power utilization of building cooling / heating in the integrated energy system of low-carbon cities.

[0052] Collect the latest rated power (P) of the air conditioning load connected to the grid in the integrated energy system of low-carbon cities. AC,Rated ;

[0053] use Calculate the peak-shaving utilization rate η of the integrated energy system in a low-carbon city AC,PS :

[0054] use Calculate the demand response utilization rate η of the integrated energy system in a low-carbon city. AC,DR .

[0055] Preferably, the peak-shaving model establishment unit establishes a peak-shaving model for air conditioning participation in a low-carbon urban integrated energy system, comprising:

[0056] Establish an air conditioning thermodynamic model, including:

[0057]

[0058] Establish an indoor air temperature model, including:

[0059]

[0060] Among them, the polynomials f1, f2, f3, and f4 satisfy:

[0061]

[0062] The power model for air conditioning participating in grid peak shaving at time t is established as follows:

[0063]

[0064] Where, Θ HIndoor body temperature, T in (t) represents the indoor air temperature at time t, P W·V (t) is the water vapor pressure, S(t) is the wind speed at time t, σ air Relative air humidity; Δ 11 Δ 12 Δ 13 Δ 14 Δ 21 Δ 22 and Δ 23 All are constants; Q p It is the rated cooling capacity of the coolant pack, γ C·W It is the water vapor temperature coefficient. These are the operating states of RAC, with T1 and T0 representing the operating states respectively. and The initial room temperature at that time; σ a V represents the relative humidity of the air. B For the building volume, κ S S is the heat storage coefficient of the building's interior walls. w_in S represents the area of ​​the building's interior walls. top and S w T represents the thermal conductivity of the building's roof and walls, respectively. wc T wj These are the outlet and inlet temperatures of the cooling water, respectively, T. out (t) represents the outdoor temperature at time t, κ e κ z κ x These are the equipment cooling load, lighting cooling load, and human visual cooling load coefficients, q e q z Heat dissipation per unit area q for equipment and lighting, respectively. x q n Q represents the heat dissipation from the human body, specifically the sensible heat and latent heat. L (t) represents the indoor cooling load at time t, Q r (t) represents the personnel cooling load at time t, S C For cooling area, and These represent the number of passengers and the passenger flow boundary, respectively, ε Clu m is the aggregation coefficient; w C w These are the mass and specific heat capacity of chilled water, respectively; Q RAC R is the cooling power of the air conditioner when it reaches steady state; a It is the equivalent thermal resistance of RAC; P RAC (t) represents the peak reduction potential at time t, N RAC Q represents the number of refrigeration and air conditioning systems in the IES. RAC,i is the cooling power of the i-th refrigeration and air conditioning system, Δ RAC1 Δ is the principal term coefficient for the electrical power of the refrigeration and air conditioning system. RAC2 and l RAC These are the main term coefficient and constant term for the cooling power of the refrigeration and air conditioning system, respectively.

[0065] Preferably, the total load change determination unit determines the total load change based on the load-side demand response model, the functional penetration rate division result, and the air conditioning participation peak shaving model, including:

[0066]

[0067] in, Let t be the total load change in the load-side demand response. The load change can be reduced after the load demand response is reduced at time t. The adjustable load demand response change at time t; These are the alternative electrical load and the corresponding thermal load, respectively; P RAC (t) represents the peak shaving potential of the air conditioning system at time t; B CL B AL BR1, BR2, B RAC These are, respectively, the load demand response logic control factor that can be reduced, the load demand response logic control factor that can be adjusted, the electrical load logic control factor that can be substituted, the thermal load logic control factor that can be substituted, and the RAC peak shaving logic control factor.

[0068] This invention provides a load-side demand response method and system for a low-carbon urban integrated energy system, comprising: establishing a load-side demand response model for the low-carbon urban integrated energy system; classifying the air conditioning function penetration rate on the load side of the low-carbon urban integrated energy system and determining the function penetration rate classification result; establishing a model for air conditioning participation in peak shaving in the low-carbon urban integrated energy system; and performing demand response based on the load-side demand response model, the function penetration rate classification result, and the air conditioning participation in peak shaving model to determine the total load change in the load-side demand response. This invention classifies load demand response into price-sensitive demand response and energy conversion-type demand response based on the energy consumption characteristics of the low-carbon urban integrated energy system load side; proposes a method for quantitatively calculating the air conditioning function penetration rate on the load side of the low-carbon urban integrated energy system, providing a reference for low-carbon operation optimization strategies for low-carbon urban integrated energy systems. Attached Figure Description

[0069] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0070] Figure 1A flowchart of a load-side demand response method 100 for a low-carbon urban integrated energy system according to an embodiment of the present invention;

[0071] Figure 2 This is a schematic diagram of the load-side demand response process of a low-carbon urban integrated energy system that takes into account the participation of electrical energy flow in grid peak shaving, according to an embodiment of the present invention.

[0072] Figure 3 A topology diagram of a low-carbon urban integrated energy system according to an embodiment of the present invention;

[0073] Figure 4 This is a schematic diagram of the active power output curve of the air conditioner after participating in peak shaving and valley filling according to an embodiment of the present invention.

[0074] Figure 5 This is a schematic diagram of the load-side demand response system 500 of a low-carbon urban integrated energy system according to an embodiment of the present invention. Detailed Implementation

[0075] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0076] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0077] Figure 1 This is a flowchart of a load-side demand response method 100 for a low-carbon urban integrated energy system according to an embodiment of the present invention. Figure 1As shown in the figure, the load-side demand response of the low-carbon urban integrated energy system provided by this invention participates in the peak-shaving model to determine the total load change in the load-side demand response. Based on the energy consumption characteristics of the load side of the low-carbon urban integrated energy system, this invention classifies load demand response into price-sensitive demand response and energy conversion demand response; it proposes that air conditioning on the load side of the low-carbon urban integrated energy system participate in grid peak shaving, and provides a quantitative calculation method for the penetration rate of air conditioning functions, which can provide a reference for the low-carbon operation optimization strategy of the low-carbon urban integrated energy system. The load-side demand response method 100 of the low-carbon urban integrated energy system provided by this invention starts from step 101, in which a load-side demand response model of the low-carbon urban integrated energy system is established.

[0078] Preferably, the load-side demand response model of the low-carbon urban integrated energy system includes: a price-sensitive demand response sub-model and an energy conversion demand response sub-model, wherein the price-sensitive demand response sub-model includes: a load reduction model and an adjustable load model.

[0079] The load reduction model includes:

[0080]

[0081] The adjustable load model includes:

[0082]

[0083] The energy conversion-type demand response sub-model includes:

[0084]

[0085] in, Let t be the initial load reduction amount. The initial load reduction at time t; Ξ CL (t,k) is the demand flexibility matrix for load reduction prices, ψ k Let ζ be the electricity price at time k. Cus User satisfaction rating Let k be the initial electricity price at time k; Let Ξ be the initial adjustable load at time t. AL (t,k) is an adjustable load price demand flexibility matrix. The initial adjustable load at time t; These represent the replaceable electrical load and the corresponding heat load, respectively; ζ is the energy conversion coefficient; H ε H h These are the unit calorific value of electrical energy and thermal energy, respectively; η ε η hThese are the energy utilization rates of electrical energy and thermal energy, respectively.

[0086] Combination Figure 2 As shown, in this invention, the first step is to input the demand response classification results, each demand response parameter, and the initial load state quantity.

[0087] Based on the characteristics of grid load response, the demand response of low-carbon city integrated energy systems is divided into price-sensitive demand response and energy conversion demand response. Demand response parameters include load reduction demand response parameters, adjustable load demand response parameters, and energy conversion load demand response parameters. Among these, load reduction demand response parameters and initial load state quantities include: initial load at time t. Electricity price change Δψ at time k after DR k Initial electricity price at time k The flexibility coefficient ε of load at time t to electricity price at time k t,k A flexible matrix of load reduction, price, and demand. CL (t,k), User satisfaction coefficient ζ Cus The adjustable load demand response parameters and initial load state quantities include: the adjustable load price-demand flexibility matrix Ξ. AL (t,k), Initial adjustable load at time t Among them, the energy conversion load demand response parameters and initial load state quantities include: energy conversion coefficient ζ; and the unit calorific value of electrical energy and thermal energy, respectively H. ε H h The energy utilization rates of electrical energy and thermal energy are respectively η ε and η h .

[0088] In this invention, a load-side demand response model for a low-carbon urban integrated energy system is established.

[0089] Based on the characteristics of grid load response, the demand response of integrated energy systems in low-carbon cities is divided into price-sensitive demand response and energy conversion-related demand response.

[0090] Loads participating in price-sensitive demand response are categorized into reduceable loads and adjustable loads. The reduceable load model uses a price-demand flexibility matrix to represent the demand response characteristics of reduceable loads.

[0091] The element ε in the t-th row and k-th column of the flexible matrix Ξ(t,k) t,k The flexibility coefficient of load at time t in relation to electricity price at time k:

[0092]

[0093] In the formula, Let be the load change at time t after DR. Let Δψ be the initial load at time t. k Let DR represent the change in electricity price at time k. Let k be the initial electricity price at time k.

[0094] The amount of load change that can be reduced after reducing load demand response is:

[0095]

[0096] In the formula, Let Ξ be the initial load reduction amount at time t. CL (t,k) is the demand flexibility matrix for load reduction prices, ψ k Let ζ be the electricity price at time k. Cus This represents the user satisfaction rating.

[0097] The adjustable load model uses a price-demand flexibility matrix to represent the adjustable load demand response characteristics. The adjustable load change at time t after the demand response is... for:

[0098]

[0099] In the formula, Ξ is the initial adjustable load at time t; AL (t,k) is an adjustable load price demand flexibility matrix.

[0100] The energy conversion load demand response model is as follows:

[0101]

[0102] In the formula, These represent the replaceable electrical load and the corresponding heat load, respectively; ζ is the energy conversion coefficient; H ε H h These are the unit calorific value of electrical energy and thermal energy, respectively; η ε η h These are the energy utilization rates of electrical energy and thermal energy, respectively.

[0103] In step 102, the air conditioning function penetration rate is divided on the load side of the low-carbon city integrated energy system, and the result of the function penetration rate division is determined.

[0104] Preferably, the determination of the functional penetration rate of air conditioning on the load side of the low-carbon urban integrated energy system, and the determination of the functional penetration rate classification result, includes:

[0105] Collect the maximum power utilization of building cooling / heating in the integrated energy system of low-carbon cities.

[0106] Collect the latest rated power (P) of the air conditioning load connected to the grid in the integrated energy system of low-carbon cities. AC,Rated ;

[0107] use Calculate the peak-shaving utilization rate η of the integrated energy system in a low-carbon city AC,PS :

[0108] use Calculate the demand response utilization rate η of the integrated energy system in a low-carbon city. AC,DR .

[0109] In this invention, the air conditioning function penetration rate of the load side of the integrated energy system in a low-carbon city is classified based on the day-ahead air conditioning load utilization rate. Specifically, the function penetration rate classification steps are as follows:

[0110] (1) Collect the maximum power of building cooling / heating utilization in the low-carbon city integrated energy system.

[0111] (2) Collect the latest value of the grid-connected rated power of the air conditioning load of the low-carbon city integrated energy system P AC,Rated ;

[0112] (3) Calculate the peak-shaving utilization rate η of the integrated energy system in a low-carbon city. AC,PS And satisfy:

[0113]

[0114] (4) Calculate the demand response utilization rate η of the integrated energy system in a low-carbon city. AC,DR And satisfy:

[0115]

[0116] In step 103, a model for the participation of air conditioning in peak shaving in a low-carbon city integrated energy system is established.

[0117] Preferably, the establishment of a low-carbon urban integrated energy system air conditioning participation peak-shaving model includes:

[0118] Establish an air conditioning thermodynamic model, including:

[0119]

[0120] Establish an indoor air temperature model, including:

[0121]

[0122] Among them, the polynomials f1, f2, f3, and f4 satisfy:

[0123]

[0124] The power model for air conditioning participating in grid peak shaving at time t is established as follows:

[0125]

[0126] Where, Θ H Indoor body temperature, T in (t) represents the indoor air temperature at time t, P W.V (t) is the water vapor pressure, S(t) is the wind speed at time t, σ air Relative air humidity; Δ 11 Δ 12 Δ 13 Δ 14 Δ 21 Δ 22 and Δ 23 All are constants; Q p It is the rated cooling capacity of the coolant pack, γ C.W It is the water vapor temperature coefficient. These are the operating states of RAC, with T1 and T0 representing the operating states respectively. and The initial room temperature at that time; σ a V represents the relative humidity of the air. B For the building volume, κ S S is the heat storage coefficient of the building's interior walls. w_in S represents the area of ​​the building's interior walls. top and S w T represents the thermal conductivity of the building's roof and walls, respectively. wc T wj These are the outlet and inlet temperatures of the cooling water, respectively, T. out (t) represents the outdoor temperature at time t, κ e κ z κ x These are the equipment cooling load, lighting cooling load, and human visual cooling load coefficients, q e q z Heat dissipation per unit area q for equipment and lighting, respectively. x q n Q represents the heat dissipation from the human body, specifically the sensible heat and latent heat. L (t) represents the indoor cooling load at time t, Q r (t) represents the personnel cooling load at time t, S C For cooling area, and These represent the number of passengers and the passenger flow boundary, respectively, ε Clu m is the aggregation coefficient; w C w These are the mass and specific heat capacity of chilled water, respectively; Q RAC R is the cooling power of the air conditioner when it reaches steady state;a It is the equivalent thermal resistance of RAC; P RAC (t) represents the peak reduction potential at time t, N RAC Q represents the number of refrigeration and air conditioning systems in the IES. RAC,i Let Δ be the cooling power of the i-th refrigeration and air conditioning system. RAC1 Δ is the principal term coefficient for the electrical power of the refrigeration and air conditioning system. RAC2 and l RAC These are the main term coefficient and constant term for the cooling power of the refrigeration and air conditioning system, respectively.

[0127] In this invention, a model for the participation of air conditioning in peak shaving within a low-carbon urban integrated energy system is established. Specifically, it includes:

[0128] Establish an air conditioning thermodynamic model:

[0129]

[0130] Where, Θ H Indoor body temperature, T in (t) represents the indoor air temperature at time t, P W.V (t) is the water vapor pressure, S(t) is the wind speed at time t, σ air This refers to relative humidity. Δ 11 Δ 12 Δ 13 Δ 14 Δ 21 Δ 22 and Δ 23 These are constants with values ​​of 1.07, 0.2, -0.65, -2.7, 6.105, 17.27, and 237.7, respectively.

[0131] The indoor air temperature model is established as follows:

[0132]

[0133] Among them, Q p It is the rated cooling capacity of the coolant pack, γ C.W It is the water vapor temperature coefficient. These are the operating states of RAC, with T1 and T0 representing the operating states respectively. and The initial room temperature at that time.

[0134] Among them, the polynomials f1, f2, f3, and f4 satisfy:

[0135]

[0136] Where, σ a V represents the relative humidity of the air. B For the building volume, κS S is the heat storage coefficient of the building's interior walls. w_in S represents the area of ​​the building's interior walls. top and S w T represents the thermal conductivity of the building's roof and walls, respectively. wc T wj These are the outlet and inlet temperatures of the cooling water, respectively, T. out (t) represents the outdoor temperature at time t, κ e κ z κ x These are the equipment cooling load, lighting cooling load, and human visual cooling load coefficients, q e q z These are the heat dissipation per unit area for equipment and lighting, respectively. q x q n Q represents the heat dissipation from the human body, specifically the sensible heat and latent heat. L (t) represents the indoor cooling load at time t, Q r (t) represents the personnel cooling load at time t, S C For cooling area, and These represent the number of passengers and the passenger flow boundary, respectively, ε Clu is the clustering coefficient. m w C w These are the mass and specific heat capacity of the chilled water, respectively.

[0137] The cooling power of the air conditioner when it reaches steady state is:

[0138]

[0139] Among them, R a It is the equivalent thermal resistance of RAC.

[0140] The power model for air conditioning participating in grid peak shaving at time t is established as follows:

[0141]

[0142] Among them, P RAC (t) represents the peak reduction potential at time t, N RAC Q represents the number of refrigeration and air conditioning systems in the IES. RAC,i Let Δ be the cooling power of the i-th refrigeration and air conditioning system. RAC1 Δ is the principal term coefficient for the electrical power of the refrigeration and air conditioning system. RAC2 and l RAC These are the main term coefficient and constant term for the cooling power of the refrigeration and air conditioning system, respectively.

[0143] In step 104, demand response is performed based on the load-side demand response model, functional penetration rate division results, and air conditioning participation peak shaving model to determine the total load change in load-side demand response.

[0144] Preferably, the determination of the total load change in load-side demand response based on the load-side demand response model, functional penetration rate division results, and air conditioning participation peak-shaving model includes:

[0145]

[0146] in, Let t be the total load change in the load-side demand response. The load change can be reduced after the load demand response is reduced at time t. The adjustable load demand response change at time t; These are the alternative electrical load and the corresponding thermal load, respectively; P RAC (t) represents the peak shaving potential of the air conditioning system at time t; B CL B AL BR1, BR2, B RAC These are, respectively, the load demand response logic control factor that can be reduced, the load demand response logic control factor that can be adjusted, the electrical load logic control factor that can be substituted, the thermal load logic control factor that can be substituted, and the RAC peak shaving logic control factor.

[0147] Combination Figure 2 As shown, based on the established model and the input response parameters and initial load state quantities, calculations are performed, and the total load change in the load-side demand response is output.

[0148] Wherein, the total load change in the load-side demand response at time t is:

[0149]

[0150] in, Let t be the total load change in the load-side demand response. The load change can be reduced after the load demand response is reduced at time t. The adjustable load demand response change at time t; These are the alternative electrical load and the corresponding thermal load, respectively; P RAC (t) represents the peak shaving potential of the air conditioning system at time t; B CL B AL BR1, BR2, B RACThese are, respectively, the load demand response logic control factor that can be reduced, the load demand response logic control factor that can be adjusted, the electrical load logic control factor that can be substituted, the thermal load logic control factor that can be substituted, and the RAC peak shaving logic control factor.

[0151] In this invention, a typical low-carbon urban integrated energy system is established based on the method of this invention, with the topology as follows: Figure 3 As shown in the diagram, the system utilizes an upstream power grid and a gas grid, respectively. Gas is purchased from the upstream gas grid to power the combined heat and power (CHP) unit and the gas boiler (GB), while surplus electricity can be sold back to the upstream power grid. Energy coupling devices include the CHP, heat pump (HP), and GB, enabling bidirectional flow of electrical and thermal energy. The CHP consists of a gas turbine (GT), a waste heat boiler (WHB), and a low-temperature waste heat power generation unit based on the organic Rankine cycle (ORC), operating in a decoupled heat and power mode suitable for various system operating conditions. Since the gas boiler requires electricity during startup and operation, the HP and gas boiler can absorb wind power and bear some of the heat load. Wind power is transmitted long-distance via DC transmission from the Shagohuang large-scale new energy base to the low-carbon urban integrated energy system coupled with the receiving-end power grid. Smart buildings on the load side are increasingly participating in the low-carbon optimized operation of integrated low-carbon energy systems, with electric vehicles and thermal storage air conditioning being the main examples. Introducing demand response can smooth load curve fluctuations, achieving interactive coupling of electricity and heat, peak shaving and valley filling, and reducing operating costs. The active power output curve of air conditioning after participating in peak shaving and valley filling is shown below. Figure 4 As shown.

[0152] The present invention proposes a load-side demand response model for a low-carbon urban integrated energy system that takes into account the participation of electrical energy flow in grid peak shaving; it also proposes a method for calculating the air conditioning function penetration rate applicable to low-carbon urban integrated energy systems; and it proposes an air conditioning load peak shaving model applicable to low-carbon urban integrated energy systems. This solves the technical problem of the lack of low-carbon operation scheduling in modern low-carbon urban integrated energy systems and can provide a reference for the optimization strategy of low-carbon operation of low-carbon urban integrated energy systems.

[0153] Figure 5 This is a schematic diagram of the load-side demand response system 500 of a low-carbon urban integrated energy system according to an embodiment of the present invention. Figure 5As shown, the load-side demand response system 500 of the low-carbon urban integrated energy system provided in this embodiment of the invention includes: a demand response model establishment unit 501, a functional penetration rate division unit 502, a peak shaving model establishment unit 503, and a total load change determination unit 504.

[0154] Preferably, the demand response model establishment unit 501 is used to establish a load-side demand response model for a low-carbon urban integrated energy system.

[0155] Preferably, the load-side demand response model of the low-carbon urban integrated energy system includes: a price-sensitive demand response sub-model and an energy conversion demand response sub-model, wherein the price-sensitive demand response sub-model includes: a load reduction model and an adjustable load model.

[0156] The load reduction model includes:

[0157]

[0158] The adjustable load model includes:

[0159]

[0160] The energy conversion-type demand response sub-model includes:

[0161]

[0162] in, Let t be the initial load reduction amount. The initial load reduction at time t; Ξ CL (t,k) is the demand flexibility matrix for load reduction prices, ψ k Let ζ be the electricity price at time k. Cus User satisfaction rating Let k be the initial electricity price at time k; Let Ξ be the initial adjustable load at time t. AL (t,k) is an adjustable load price demand flexibility matrix. The initial adjustable load at time t; These represent the replaceable electrical load and the corresponding heat load, respectively; ζ is the energy conversion coefficient; H ε H h These are the unit calorific value of electrical energy and thermal energy, respectively; η ε η h These are the energy utilization rates of electrical energy and thermal energy, respectively.

[0163] Preferably, the functional penetration rate division unit 502 is used to divide the air conditioning functional penetration rate on the load side of the low-carbon urban integrated energy system and determine the functional penetration rate division result.

[0164] Preferably, the functional penetration rate division unit 502 is used to divide the air conditioning functional penetration rate on the load side of the low-carbon urban integrated energy system and determine the functional penetration rate division result, including:

[0165] Collect the maximum power utilization of building cooling / heating in the integrated energy system of low-carbon cities.

[0166] Collect the latest rated power (P) of the air conditioning load connected to the grid in the integrated energy system of low-carbon cities. AC,Rated ;

[0167] use Calculate the peak-shaving utilization rate η of the integrated energy system in a low-carbon city AC,PS :

[0168] use Calculate the demand response utilization rate η of the integrated energy system in a low-carbon city. AC,DR .

[0169] Preferably, the peak-shaving model establishment unit 503 is used to establish a peak-shaving model for air conditioning in a low-carbon urban integrated energy system.

[0170] Preferably, the peak-shaving model establishment unit 503 establishes a low-carbon city integrated energy system air conditioning participation peak-shaving model, including:

[0171] Establish an air conditioning thermodynamic model, including:

[0172]

[0173] Establish an indoor air temperature model, including:

[0174]

[0175] Among them, the polynomials f1, f2, f3, and f4 satisfy:

[0176]

[0177] The power model for air conditioning participating in grid peak shaving at time t is established as follows:

[0178]

[0179] Where, Θ H Indoor body temperature, T in (t) represents the indoor air temperature at time t, P W.V (t) is the water vapor pressure, S(t) is the wind speed at time t, σair Relative air humidity; Δ 11 Δ 12 Δ 13 Δ 14 Δ 21 Δ 22 and Δ 23 All are constants; Q p It is the rated cooling capacity of the coolant pack, γ C.W It is the water vapor temperature coefficient. These are the operating states of RAC, with T1 and T0 representing the operating states respectively. and The initial room temperature at that time; σ a V represents the relative humidity of the air. B For the building volume, κ S S is the heat storage coefficient of the building's interior walls. w_in S represents the area of ​​the building's interior walls. top and S w T represents the thermal conductivity of the building's roof and walls, respectively. wc T wj These are the outlet and inlet temperatures of the cooling water, respectively, T. out (t) represents the outdoor temperature at time t, κ e κ z κ x These are the equipment cooling load, lighting cooling load, and human visual cooling load coefficients, q e q z Heat dissipation per unit area q for equipment and lighting, respectively. x q n Q represents the heat dissipation from the human body, specifically the sensible heat and latent heat. L (t) represents the indoor cooling load at time t, Q r (t) represents the personnel cooling load at time t, S C For cooling area, and These represent the number of passengers and the passenger flow boundary, respectively, ε Clu m is the aggregation coefficient; w C w These are the mass and specific heat capacity of chilled water, respectively; Q RAC R is the cooling power of the air conditioner when it reaches steady state; a It is the equivalent thermal resistance of RAC; P RAC (t) represents the peak reduction potential at time t, N RAC Q represents the number of refrigeration and air conditioning systems in the IES. RAC,i Let Δ be the cooling power of the i-th refrigeration and air conditioning system. RAC1 Δ is the principal term coefficient for the electrical power of the refrigeration and air conditioning system. RAC2 and l RACThese are the main term coefficient and constant term for the cooling power of the refrigeration and air conditioning system, respectively.

[0180] Preferably, the total load change determination unit 504 is used to determine the total load change of the load-side demand response based on the load-side demand response model, the functional penetration rate division result and the air conditioning participation peak shaving model.

[0181] Preferably, the total load change determination unit 504 determines the total load change based on the load-side demand response model, functional penetration rate division results, and air conditioning participation peak shaving model, including:

[0182]

[0183] in, Let t be the total load change in the load-side demand response. The load change can be reduced after the load demand response is reduced at time t. The adjustable load demand response change at time t; These are the alternative electrical load and the corresponding thermal load, respectively; P RAC (t) represents the peak shaving potential of the air conditioning system at time t; B CL B AL BR1, BR2, B RAC These are, respectively, the load demand response logic control factor that can be reduced, the load demand response logic control factor that can be adjusted, the electrical load logic control factor that can be substituted, the thermal load logic control factor that can be substituted, and the RAC peak shaving logic control factor.

[0184] The load-side demand response system 500 of the low-carbon urban integrated energy system of the present invention corresponds to the load-side demand response method 100 of the low-carbon urban integrated energy system of the present invention, and will not be described again here.

[0185] The present invention has been described with reference to a few embodiments. However, it will be apparent to those skilled in the art that other embodiments besides those disclosed above fall equivalently within the scope of the present invention.

[0186] Generally, all terms used in this invention are interpreted according to their ordinary meaning in the art, unless otherwise expressly defined herein. All references to “a / the / the [device, component, etc.]” ​​are openly interpreted as at least one instance of said device, component, etc., unless otherwise expressly stated. The steps of any method disclosed herein need not be performed in the exact order disclosed unless explicitly stated otherwise.

[0187] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0188] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0189] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0190] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0191] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention.

Claims

1. A load-side demand response method for a low-carbon urban integrated energy system, characterized in that, The method includes: Establish a load-side demand response model for a low-carbon urban integrated energy system; The air conditioning function penetration rate of the load side of the integrated energy system in a low-carbon city is divided, and the result of the function penetration rate division is determined. Establish a model for air conditioning participation in peak shaving within a low-carbon city's integrated energy system; Based on the load-side demand response model, functional penetration rate division results, and air conditioning participation peak shaving model, demand response is performed to determine the total load change in load-side demand response. The load-side demand response model of the low-carbon urban integrated energy system includes: a price-sensitive demand response sub-model and an energy conversion demand response sub-model. The price-sensitive demand response sub-model includes: a load reduction model and an adjustable load model. The load reduction model includes: The adjustable load model includes: The energy conversion-type demand response sub-model includes: in, Let t be the initial load reduction amount. Let t be the initial load reduction amount. To reduce load price demand flexibility matrix, ψ k Let ζ be the electricity price at time k. Cus User satisfaction rating Let k be the initial electricity price at time k; Let t be the initial adjustable load. To create an adjustable load-price-demand flexibility matrix, The initial adjustable load at time t; These represent the replaceable electrical load and the corresponding heat load, respectively; ζ is the energy conversion coefficient; H ε H h These are the unit calorific value of electrical energy and thermal energy, respectively; η ε η h These are the energy utilization rates of electrical energy and thermal energy, respectively. The determination of the functional penetration rate classification of air conditioning functions on the load side of the integrated energy system in low-carbon cities includes: Collect the maximum power utilization of building cooling / heating in the integrated energy system of low-carbon cities. Collect the latest rated power (P) of the air conditioning load connected to the grid in the integrated energy system of low-carbon cities. AC,Rated ; use Calculate the peak-shaving utilization rate η of the integrated energy system in a low-carbon city AC,PS : use Calculate the demand response utilization rate η of the integrated energy system in a low-carbon city. AC,DR ; The establishment of a low-carbon urban integrated energy system air conditioning participation peak-shaving model includes: Establish an air conditioning thermodynamic model, including: Establish an indoor air temperature model, including: Among them, the polynomials f1, f2, f3, and f4 satisfy: The power model for air conditioning participating in grid peak shaving at time t is established as follows: Where, Θ H Indoor body temperature, T in (t) represents the indoor air temperature at time t, P W . V (t) is the water vapor pressure, S(t) is the wind speed at time t, σ air Relative air humidity; Δ 11 Δ 12 Δ 13 Δ 14 Δ 21 Δ 22 and Δ 23 All are constants; Q p It is the rated cooling capacity of the coolant pack, γ C . W It is the water vapor temperature coefficient. These are the operating states of RAC, with T1 and T0 representing the operating states respectively. and The initial room temperature at that time; σ a V represents the relative humidity of the air. B For the building volume, κ S S is the heat storage coefficient of the building's interior walls. w_in S represents the area of ​​the building's interior walls. top and S w The thermal conductivity, T, represents the thermal conductivity of the building's roof and walls, respectively. wc T wj These are the outlet and inlet temperatures of the cooling water, respectively, T. out (t) represents the outdoor temperature at time t, κ e κ z κ x These are the equipment cooling load, lighting cooling load, and human visual cooling load coefficients, q e q z Heat dissipation per unit area q for equipment and lighting, respectively. x q n Q represents the heat dissipation from the human body, specifically the sensible heat and latent heat. L (t) represents the indoor cooling load at time t, Q r (t) represents the personnel cooling load at time t, S C For cooling area, and These represent the number of passengers and the passenger flow boundary, respectively, ε Clu m is the aggregation coefficient; w C w These are the mass and specific heat capacity of chilled water, respectively; Q RAC R is the cooling power of the air conditioner when it reaches steady state; a It is the equivalent thermal resistance of RAC; P RAC (t) represents the peak reduction potential at time t, N RAC Q represents the number of refrigeration and air conditioning systems in the IES. RAC,i Let Δ be the cooling power of the i-th refrigeration and air conditioning system. RAC1 Δ is the principal term coefficient for the electrical power of the refrigeration and air conditioning system. RAC2 and l RAC These are the main term coefficient and constant term for the cooling power of the refrigeration and air conditioning system, respectively.

2. The method according to claim 1, characterized in that, The demand response based on the load-side demand response model, functional penetration rate division results, and air conditioning participation peak shaving model, determining the total load change in load-side demand response, includes: in, Let t be the total load change in the load-side demand response. The load change can be reduced after the load demand response is reduced at time t. The adjustable load demand response change at time t; These are the alternative electrical load and the corresponding thermal load, respectively; P RAC (t) represents the peak shaving potential of the air conditioning system at time t; B CL B AL BR1, BR2, B RAC These are, respectively, the load demand response logic control factor that can be reduced, the load demand response logic control factor that can be adjusted, the electrical load logic control factor that can be substituted, the thermal load logic control factor that can be substituted, and the RAC peak shaving logic control factor.

3. A load-side demand response system for a low-carbon urban integrated energy system, characterized in that, The system includes: Demand response model building unit, used to build load-side demand response models for integrated energy systems in low-carbon cities; The functional penetration rate division unit is used to divide the air conditioning functional penetration rate on the load side of the integrated energy system of a low-carbon city and determine the functional penetration rate division result. The peak-shaving model establishment unit is used to establish a peak-shaving model for air conditioning participation in a low-carbon urban integrated energy system. The total load change determination unit is used to determine the total load change of the load-side demand response based on the load-side demand response model, the functional penetration rate division result and the air conditioning participation peak shaving model. The load-side demand response model of the low-carbon urban integrated energy system includes: a price-sensitive demand response sub-model and an energy conversion demand response sub-model. The price-sensitive demand response sub-model includes: a load reduction model and an adjustable load model. The load reduction model includes: The adjustable load model includes: The energy conversion-type demand response sub-model includes: in, Let t be the initial load reduction amount. Let t be the initial load reduction amount. To reduce load price demand flexibility matrix, ψ k Let ζ be the electricity price at time k. Cus User satisfaction rating Let k be the initial electricity price at time k; Let t be the initial adjustable load. To create an adjustable load-price-demand flexibility matrix, The initial adjustable load at time t; These represent the replaceable electrical load and the corresponding heat load, respectively; ζ is the energy conversion coefficient; H ε H h These are the unit calorific value of electrical energy and thermal energy, respectively; η ε η h These are the energy utilization rates of electrical energy and thermal energy, respectively. The functional penetration rate division unit is used to divide the air conditioning functional penetration rate on the load side of the integrated energy system in a low-carbon city, and to determine the functional penetration rate division result, including: Collect the maximum power utilization of building cooling / heating in the integrated energy system of low-carbon cities. Collect the latest rated power of air conditioning load connected to the grid in low-carbon urban integrated energy systems. use Calculate the peak-shaving utilization rate η of the integrated energy system in a low-carbon city AC,PS : use Calculate the demand response utilization rate η of the integrated energy system in a low-carbon city. AC,DR ; The peak-shaving model establishment unit establishes a peak-shaving model for air conditioning in a low-carbon urban integrated energy system, including: Establish an air conditioning thermodynamic model, including: Establish an indoor air temperature model, including: Among them, the polynomials f1, f2, f3, and f4 satisfy: The power model for air conditioning participating in grid peak shaving at time t is established as follows: Where, Θ H Indoor body temperature, T in (t) represents the indoor air temperature at time t, P W . V (t) is the water vapor pressure, S(t) is the wind speed at time t, σ air Relative air humidity; Δ 11 Δ 12 Δ 13 Δ 14 Δ 21 Δ 22 and Δ 23 All are constants; Q p It is the rated cooling capacity of the coolant pack, γ C . W It is the water vapor temperature coefficient. These are the operating states of RAC, with T1 and T0 representing the operating states respectively. and The initial room temperature at that time; σ a V represents the relative humidity of the air. B For the building volume, κ S S is the heat storage coefficient of the building's interior walls. w_in S represents the area of ​​the building's interior walls. top and S w The thermal conductivity, T, represents the thermal conductivity of the building's roof and walls, respectively. wc T wj These are the outlet and inlet temperatures of the cooling water, respectively, T. out (t) represents the outdoor temperature at time t, κ e κ z κ x These are the equipment cooling load, lighting cooling load, and human visual cooling load coefficients, q e q z Heat dissipation per unit area q for equipment and lighting, respectively. x q n Q represents the heat dissipation from the human body, specifically the sensible heat and latent heat. L (t) represents the indoor cooling load at time t, Q r (t) represents the personnel cooling load at time t, S C For cooling area, and These represent the number of passengers and the passenger flow boundary, respectively, ε Clu m is the aggregation coefficient; w C w These are the mass and specific heat capacity of chilled water, respectively; Q RAC R is the cooling power of the air conditioner when it reaches steady state; a It is the equivalent thermal resistance of RAC; P RAC (t) represents the peak reduction potential at time t, N RAC Q represents the number of refrigeration and air conditioning systems in the IES. RAC,i Let Δ be the cooling power of the i-th refrigeration and air conditioning system. RAC1 Δ is the principal term coefficient for the electrical power of the refrigeration and air conditioning system. RAC2 and l RAC These are the main term coefficient and constant term for the cooling power of the refrigeration and air conditioning system, respectively.

4. The system according to claim 3, characterized in that, The total load change determination unit determines the total load change based on the load-side demand response model, functional penetration rate division results, and air conditioning participation peak shaving model, including: in, Let t be the total load change in the load-side demand response. The load change can be reduced after the load demand response is reduced at time t. The adjustable load demand response change at time t; These are the alternative electrical load and the corresponding thermal load, respectively; P RAC (t) represents the peak shaving potential of the air conditioning system at time t; B CL B AL BR1, BR2, B RAC These are, respectively, the load demand response logic control factor that can be reduced, the load demand response logic control factor that can be adjusted, the electrical load logic control factor that can be substituted, the thermal load logic control factor that can be substituted, and the RAC peak shaving logic control factor.

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