Demand side load configuration method and system for multi-energy complementary integrated energy system

Abstract

The disclosure provides a demand side load configuration method and system for a multi-energy complementary integrated energy system, comprising: obtaining the internal characteristics of energy conversion, heat transfer and loss of each unit of the integrated energy system based on thermodynamic theory; based on the internal characteristics, the dynamic response time of the equipment in the integrated energy system, and the multi-stage change of the physical process of the critical point of the phase change of the working medium state of the equipment, the full working condition modeling of each equipment of the integrated energy system is realized through mechanism analysis and parameter identification method; wherein the integrated energy system comprises a combined heat and power system of a gas turbine, a photovoltaic power generation system, a refrigeration and heating equipment and an electric energy storage system, and the gas of the combined heat and power system of the gas turbine uses biomass gas; using the modeling results of the equipment of the integrated energy system, based on the demand side cold and heat and electricity dispatchable load demand, the demand side management configuration of multiple types of loads is realized.

Description

Technical Field

[0001] This disclosure belongs to the field of integrated energy system configuration technology, and particularly relates to a method and system for demand-side load configuration in a multi-energy complementary integrated energy system. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] The inventors discovered that most existing integrated energy systems are studied from the perspectives of system modeling, planning and design, and optimal scheduling. These studies are all based on ideal operating conditions and energy consumption scenarios for system optimization. However, due to the influence of the environment and equipment, the optimal configuration model under ideal operating conditions has significant errors, which seriously affects the accuracy and rationality of system planning. Secondly, existing integrated energy systems lack analysis of renewable energy sources such as biomass gas in demand-side optimization. Given the increasingly widespread use of biomass gas at present, existing integrated energy system demand-side optimization methods cannot meet current needs. Summary of the Invention

[0004] To address the aforementioned problems, this disclosure provides a demand-side load configuration method and system for a multi-energy complementary integrated energy system. The scheme is based on thermodynamic theory to analyze the energy conversion, heat transfer, and energy transfer processes of each unit in the integrated energy system. By analyzing the inherent characteristics such as losses, a full-condition model of multi-energy complementary integrated energy equipment, including internal combustion generator models, photovoltaic power generation system models, and refrigeration and heating equipment and electric energy storage systems, was established through mechanism analysis and parameter identification methods. This lays the foundation for subsequent integrated modeling of the entire energy system under all operating conditions. At the same time, the introduction of biomass gas into the integrated energy system effectively meets the current optimization configuration requirements of multi-energy complementary integrated energy systems and improves the accuracy of demand-side management configuration for various types of loads.

[0005] According to a first aspect of the present disclosure, a method for demand-side load configuration in a multi-energy complementary integrated energy system is provided, comprising:

[0006] Based on thermodynamic theory, the energy conversion and heat transfer of each unit in the integrated energy system are obtained. The inherent characteristics of loss;

[0007] Based on the inherent characteristics, the dynamic response time of the equipment in the integrated energy system, and the physical process of the multi-stage change of the phase transition critical point of the working fluid state, the full-condition modeling of each piece of equipment in the integrated energy system is realized through mechanism analysis and parameter identification methods; wherein, the integrated energy system includes a gas turbine combined heat and power system, a photovoltaic power generation system, a refrigeration and heating equipment, and an electric energy storage system, and the gas turbine combined heat and power system uses biomass gas.

[0008] Utilize the device modeling results of the integrated energy system, based on the demand side cold and heat and electricity dispatchable load demand, realize the demand side management configuration of multiple types of loads.

[0009] Further, the gas turbine tri-generation system includes system input, gas internal combustion engine, generator set and system output, which drives the generator to generate electricity by burning natural gas as power through the gas internal combustion engine, and uses the recovered waste heat for winter heating or summer cooling.

[0010] Further, the full working condition mathematical model of the gas turbine tri-generation system is represented as follows:

[0011]

[0012] Among them, is the total efficiency of the system, is the power generation E c is the cooling capacity corresponding E h is the heating capacity corresponding E Qg is the input

[0013] Further, the photovoltaic power generation system modeling adopts photovoltaic module and photovoltaic inverter modeling respectively, specifically, the full working condition mathematical model of the photovoltaic power generation system is represented as follows:

[0014] E pv.e (t)=E pv (t)*η pv

[0015] Among them, E pv.e (t) is the actual output electric power of the photovoltaic inverter, E PV is the output power of the solar photovoltaic array, η pv is the working efficiency of the photovoltaic inverter when the direct current power is E pv .

[0016] Further, the refrigeration and heating equipment includes electric compression heat pump and refrigeration unit or absorption heat pump and refrigeration unit, and the full working condition model of the refrigeration and heating equipment is specifically represented as follows:

[0017]

[0018]

[0019] Among them, E c is the cooling capacity corresponding E hFor the heat pump unit heating corresponding For the heat pump unit power

[0020] Further, the electric energy storage system includes an energy storage battery and an energy storage converter, and a full working condition mathematical model of the electric energy storage system is specifically represented as:

[0021] E bat.e (t) = V d I d η bat

[0022] Wherein, E bat.e (t) is an actual output electric power of the energy storage converter, η bat is an efficiency of the energy storage converter, V d is a direct current side voltage of the energy storage battery; and I d is a direct current side current of the energy storage battery.

[0023] Further, the biomass gas is prepared by using crop straw, forest waste, edible fungus residue, poultry manure and sewage sludge containing biomass as raw materials, and is a combustible gas generated by pyrolysis or gasification decomposition of biomass at high temperature.

[0024] According to a second aspect of the embodiment of the present disclosure, a demand side load configuration system for a multi-energy complementary comprehensive energy system is provided, comprising:

[0025] A data acquisition unit is configured to acquire inherent characteristics of energy conversion, heat transfer and losses of each unit of the comprehensive energy system based on thermodynamic theory;

[0026] A comprehensive energy system model construction unit is configured to realize full working condition modeling of each device of the comprehensive energy system by mechanism analysis and parameter identification method based on the inherent characteristics, dynamic response time of the device of the comprehensive energy system and multi-stage change of physical process of phase change critical point of the device working medium state; wherein, the comprehensive energy system includes a gas turbine trigeneration system, a photovoltaic power generation system, a refrigeration and heating device and an electric energy storage system, and biomass gas is used as fuel gas of the gas turbine trigeneration system;

[0027] A load management unit is configured to realize demand side management configuration of multiple types of loads based on demand side cold, heat and electricity adjustable load demand by using modeling results of the devices of the comprehensive energy system.

[0028] According to a third aspect of the embodiment of the present disclosure, a computer readable storage medium having a program stored thereon is provided, and the program is executed by a processor to realize a demand side load configuration method for a multi-energy complementary comprehensive energy system as described above.

[0029] According to a fourth aspect of the embodiments of the present disclosure, an electronic device is provided, comprising a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor implements a method for demand-side load configuration of a multi-energy complementary integrated energy system when executing the program.

[0030] Compared with the prior art, the present disclosure has the following beneficial effects:

[0031] The present disclosure provides a method and system for demand-side load configuration of a multi-energy complementary integrated energy system. The scheme is based on thermodynamic theory to analyze the internal characteristics of energy conversion, heat transfer, and losses of each unit of the integrated energy system. Mechanism analysis and parameter identification methods are used to establish full-condition models of multi-energy complementary integrated energy equipment, including internal combustion generator models, photovoltaic power generation system models, and refrigeration and heating equipment, and electric energy storage systems, which lays a foundation for subsequent integrated modeling of the integrated energy system under full conditions. At the same time, the use of biomass gas is introduced into the integrated energy system, effectively meeting the optimization configuration needs of the current multi-energy complementary integrated energy system, and improving the accuracy of demand-side management configuration of various types of loads.

[0032] The advantages of the additional aspects of the present disclosure will be partially given in the following description, partially will become apparent from the following description, or will be understood through the practice of the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0033] The accompanying drawings, which form a part of the present disclosure, are used to provide further understanding of the present disclosure, and the illustrative embodiments of the present disclosure and their description are used to explain the present disclosure, and do not constitute improper limitations on the present disclosure.

[0034] Figure 1 A biomass gas production process flowchart described in the embodiments of the present disclosure;

[0035] Figure 2 A daily gas production rate under different fermentation temperatures described in the embodiments of the present disclosure;

[0036] Figure 3 A typical light intensity variation curve in summer, winter, and transition seasons described in the embodiments of the present disclosure;

[0037] Figure 4 A schematic diagram of a typical structure of a natural gas combined cooling, heating, and power system described in the embodiments of the present disclosure;

[0038] Figure 5 Variable-condition characteristics of a photovoltaic power station described in the embodiments of the present disclosure;

[0039] Figure 6 A schematic diagram of an electrically driven compression heat pump and refrigeration unit described in the embodiments of the present disclosure;

[0040] Figure 7 Schematic diagram of the absorption heat pump and refrigerator unit described in the embodiments of the present disclosure;

[0041] Figure 8 Schematic diagram of the improved Thevenin model described in the embodiments of the present disclosure;

[0042] Figure 9(a) is a typical daily curve of the electrical load of residential land described in the embodiments of the present disclosure;

[0043] Figure 9(b) is a typical daily curve of the electrical load of public management and public service facilities land described in the embodiments of the present disclosure;

[0044] Figure 9(c) is a typical daily curve of the electrical load of commercial service industry facilities land described in the embodiments of the present disclosure;

[0045] Figure 9(d) is a typical daily curve of the electrical load of industrial land described in the embodiments of the present disclosure;

[0046] Figure 10(a) is a typical daily curve of the cooling load of office building described in the embodiments of the present disclosure;

[0047] Figure 10(b) is a typical daily curve of the cooling load of hotel described in the embodiments of the present disclosure;

[0048] Figure 10(c) is a typical daily curve of the cooling load of public facilities described in the embodiments of the present disclosure;

[0049] Figure 10(d) is a typical daily curve of the cooling load of restaurant described in the embodiments of the present disclosure;

[0050] Figure 11(a) is a typical daily curve of the heating load of residence described in the embodiments of the present disclosure;

[0051] Figure 11(b) is a typical daily curve of the heating load of commercial building described in the embodiments of the present disclosure;

[0052] Figure 11(c) is a typical daily curve of the heating load of hotel building described in the embodiments of the present disclosure;

[0053] Figure 11(d) is a typical daily curve of the heating load of hospital building described in the embodiments of the present disclosure. DETAILED DESCRIPTION

[0054] The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

[0055] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used in the solutions described in the embodiments have the same meaning as commonly understood by those skilled in the art to which the present disclosure belongs.

[0056] It is to be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments consistent with the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, steps, operations, devices, components and / or combinations thereof, but do not preclude the presence or addition of one or more other features, steps, operations, devices, components and / or combinations thereof.

[0057] The embodiments in the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0058] Embodiment one:

[0059] The purpose of the present embodiment is to provide a demand side load configuration method for a multi-energy complementary integrated energy system.

[0060] A demand side load configuration method for a multi-energy complementary integrated energy system, comprising:

[0061] Based on the thermodynamic theory, the intrinsic characteristics of energy conversion, heat transfer and loss of each unit of the integrated energy system are obtained;

[0062] Based on the intrinsic characteristics, the dynamic response time of the equipment in the integrated energy system, and the multi-stage change of the physical process of the phase change critical point of the equipment working medium state, the full working condition modeling of each device of the integrated energy system is realized by mechanism analysis and parameter identification method; wherein, the integrated energy system includes a combined heat and power system of gas engine, a photovoltaic power generation system, a refrigeration and heating equipment, and an electric energy storage system, and the gas of the combined heat and power system of gas engine uses biomass gas;

[0063] Using the modeling results of the equipment of the integrated energy system, based on the demand side cold and heat and power adjustable load demand, the demand side management configuration of multiple types of loads is realized.

[0064] Further, the combined heat and power system of gas engine includes system input, gas internal combustion engine, generator set and system output, which drives the generator to generate electricity by burning natural gas as power through the gas internal combustion engine, and recovers waste heat for winter heating or summer cooling.

[0065] Further, the full working condition mathematical model of the combined heat and power system of gas engine is expressed as follows:

[0066]

[0067] wherein, is the total efficiency of the system, is the power generation E c is the cooling capacity corresponding to E h is the heat supply corresponding to E Qg is the input

[0068] Further, the photovoltaic power generation system modeling adopts photovoltaic module and photovoltaic inverter modeling respectively, specifically, the full working condition mathematical model of the photovoltaic power generation system is expressed as follows:

[0069] E pv.e (t) = E pv (t) * η pv

[0070] Wherein, E pv.e (t) is the actual output electric power of the photovoltaic inverter, E PV is the output power of the solar photovoltaic array, η pv is the working efficiency of the photovoltaic inverter when the direct current power is E pv .

[0071] Further, the refrigeration and heating equipment includes an electric compression heat pump and refrigeration unit or an absorption heat pump and refrigeration unit, and the full working condition model of the refrigeration and heating equipment is specifically expressed as follows:

[0072]

[0073]

[0074] Wherein, E c is the heat supply corresponding to E h is the heat supply corresponding to is the power consumption of the heat pump unit

[0075] Further, the electric energy storage system includes an energy storage battery and an energy storage converter, and the full working condition mathematical model of the electric energy storage system is specifically expressed as follows:

[0076] E bat.e (t) = V d I d * η bat

[0077] Wherein, E bat.e (t) is the actual output electric power of the energy storage converter, η bat is the efficiency of the energy storage converter, V d is the direct current voltage of the energy storage battery; I d is the direct current of the energy storage battery.

[0078] Further, the biomass gas is prepared from crop stalks, forest waste, edible fungus residue, poultry manure, and sewage sludge containing biomass, and a combustible gas is generated by pyrolysis or gasification of the biomass at high temperature.

[0079] Specifically, in order to facilitate understanding, the scheme described in the embodiment is described in detail below in combination with the drawings:

[0080] The scheme described in the embodiment first analyzes the characteristics of renewable energy in the comprehensive energy system, including biomass gas characteristic analysis and photovoltaic power generation characteristic analysis, to lay a foundation for subsequent modeling and optimization work. Secondly, based on the thermodynamic theory, the internal characteristics of energy conversion, heat transfer and loss of each unit of the comprehensive energy system are analyzed, the dynamic response time of the equipment is analyzed, the physical process of multi-stage change of the critical point of the state phase change of the equipment working medium is studied, the modeling of the main equipment of the system is completed through mechanism analysis and parameter identification method, including the combined heat and power system of the gas turbine, the photovoltaic power generation system, the refrigeration and heating equipment, and the electric energy storage system. Finally, a model of the dispatchable load in the multi-energy system is constructed. The following is described in detail:

[0081] (1) Renewable energy characteristic analysis

[0082] (1) Biomass gas characteristic analysis

[0083] Biomass gas is a combustible gas generated by pyrolysis or gasification of biomass at high temperature, using crop stalks, forest waste, edible fungus residue, poultry manure, sewage sludge and other substances containing biomass as raw materials. Biomass gas is a complex mixture of gases. Generally, the methane (CH4) content in biomass gas is about 50% to 60%, the CO2 content is about 25% to 30%, and there are also small amounts of H2S, H2, CO and other gases. Because biomass gas contains a certain amount of sulfide, if it is burned directly without treatment, it will cause sulfur dioxide (SO2) emissions and damage the ecological environment. Therefore, the mature biomass gas engineering project currently has a desulfurization device. The common biomass gas preparation process is as shown in Figure 1

[0084] As shown in Figure 1 ​​As shown, the basic process flow for biomass gas production is as follows: Animal manure, domestic waste, and crop straw, after pretreatment, enter a mixing tank. An internal circulating pump thoroughly mixes the raw materials until homogeneous. The mixture then flows into an equalization tank, where the total solids (TS) concentration is adjusted to 6-8%. The mixture is then pumped into an anaerobic reactor for constant mesophilic fermentation, ensuring a high biogas production rate. The fermented biomass gas can be directly supplied to users after dehydration and desulfurization processes, or stored in a gas storage tank for backup. The effluent from anaerobic fermentation can also be separated into biogas residue and biogas slurry, which can be used as organic fertilizer in agricultural production, thus achieving waste recycling and improving energy efficiency.

[0085] Daily biomass gas production is a key factor affecting its application, and efficient gas production is an important prerequisite for the stable operation of renewable energy CCHP systems. However, many conditions influence biomass gas production, among which controlling the fermentation temperature is crucial for maintaining efficient and stable gas production. For example... Figure 2 The figure shows the biogas production rate at different fermentation temperatures.

[0086] from Figure 2 As can be seen, fermentation temperature has a significant impact on biomass gas production, and the increase in daily gas production efficiency is not positively correlated with the increase in fermentation temperature. There are two peak gas production values ​​during the temperature rise process: the first is around 35℃, i.e., mesophilic fermentation; the other is around 50℃, i.e., hyperthermic fermentation. In rural areas, assuming sufficient biomass energy and considering cost, the most economical fermentation temperature is 35℃. Furthermore, with a TS concentration maintained at 8%, the gas production rate per 100m³ tank can reach 1.2. 3 The daily gas production of the biomass gasification unit can be maintained at 120m³. 3 On the other hand, the methane content in biomass gas is also related to the fermentation temperature. Under the same production conditions, the methane content of the produced biomass gas will still fluctuate to some extent. In practical engineering, by installing an advanced air-fuel ratio control system on the internal combustion generator set to adjust the ratio of biomass gas to air in the intake system in real time, the impact of methane content fluctuations on the stable operation of the unit can be reduced. At the same time, equipping the unit with a gas storage tank of a certain capacity to store the remaining biomass gas is also an effective means of stabilizing the methane content of the biomass gas.

[0087] (2) Photovoltaic power generation characteristic analysis

[0088] Photovoltaic power generation technology uses the photovoltaic effect of the semiconductor interface to directly convert light energy into electricity. Solar cells are the key components of this technology. Encapsulation protects the series-connected solar cells to form a large-area photovoltaic module, which, together with power controllers and other components, forms a photovoltaic power generation device. Photovoltaic power generation has the advantages of small geographical limitations, safety and stability, high reliability, low pollution, no noise, no energy consumption, and easy transmission. Under standard conditions (solar irradiance 1000 W / m 2 , ambient temperature ), the photovoltaic mathematical model is as follows:

[0089]

[0090] wherein E pv is the photovoltaic output power;

[0091] P STC is the maximum test power under the standard conditions;

[0092] G AC is the light intensity;

[0093] G STC is the light intensity under standard conditions;

[0094] k is the power temperature coefficient;

[0095] T C represents the actual temperature of the panel;

[0096] T STC represents the temperature under standard conditions, generally 25℃.

[0097] As shown in equation (1), light intensity is a key factor for photovoltaic power generation output power, but the inherent randomness and volatility of light intensity have a greater impact on photovoltaic power generation. Figure 3 is the light intensity curve of a typical day in summer, winter, and transition season in a certain city. Under the same geographical conditions, the light intensity of different seasons and time periods changes significantly and has strong random volatility. Therefore, reasonable configuration of power generation equipment capacity and suppression of photovoltaic power generation volatility are important for the optimization design of multi-energy complementary integrated energy systems.

[0098] (II) Full working condition modeling of main equipment of integrated energy system

[0099] (1) Full working condition model research of gas turbine combined heat and power system

[0100] The combined cycle power (CCHP) system is a crucial coupling link on the "source" side of an integrated energy system. It refers to an integrated energy system that uses natural gas to drive a generator to produce electricity and recovers waste heat for winter heating and summer cooling. It mainly consists of several parts: system input, gas internal combustion engine, generator set, waste heat recovery unit, and system output. A typical structure is shown in the figure below.

[0101] The actual operating performance of a natural gas combined cooling, heating, and power (CCHP) system is affected by various factors. Actual operating conditions often deviate from design conditions, and equipment operating states frequently deviate from the sample's highest efficiency state. The working process involves not only energy transfer but also changes in the working fluid. To more accurately reflect the CCHP system model, this project is based on the second law of thermodynamics... Analysis, combined with a quality assessment of energy, is used to model and analyze the energy.

[0102] For gas turbine CCHP systems Balance can be expressed by the following formula:

[0103]

[0104] Among them, E Qg --enter kW (including fuel chemistry) physics and air physics );

[0105] —Power generation kW;

[0106] E c —Cooling capacity corresponding to kW;

[0107] E h —Heat supply corresponding kW;

[0108] E com —The combustion process of a micro gas turbine Loss, kW;

[0109] E v Cooling and ventilation Loss, kW;

[0110] E ex —Smoke extraction kW;

[0111] E evv —Error and other Loss, kW.

[0112] Overall system Efficiency is:

[0113]

[0114] 1) Input unit

[0115] System fuel Related to ambient temperature, fuel combustion temperature and total energy of fuel, the calculation formula is as follows:

[0116]

[0117] In the formula, Q G Total energy of fuel into the engine, kW (determined by the physical parameters of fuel, low calorific value, flow rate);

[0118] T0Ambient temperature, K;

[0119] T r Fuel combustion temperature, K.

[0120] 2) Power unit

[0121] In the integrated energy system, the gas power generation equipment is the core power equipment of the system, and the matching degree of its model and the actual system will directly determine the reference value of the simulation system for the actual system operation. When the equipment operates under different working conditions, the thermal efficiency of the gas engine and the electric efficiency of the generator are related to the part-load ratio (PLR) change, and the operating characteristics have obvious nonlinear representation. In order to further simulate the actual operating conditions of the gas power generation equipment, the variable working condition energy conversion characteristics thereof are studied in this project.

[0122] On the basis of analyzing the model mechanism of the internal combustion generator set, the internal combustion generator set model is obtained through data fitting based on the operating data of the set, and the model is as follows.

[0123] η e = α1PLR 3 α2PLR 2 | α3PLR α4 (5)

[0124] η g = β1PLR 5 - β26PLR 5 + β3PLR 3 - β4PLR 2 + β5PLR- β6 (6)

[0125] Wherein, α, β are fitting coefficients, PLR is the generator load ratio, η e is the power generation efficiency of the generator, and η g is the efficiency. Wherein PLR can be expressed as:

[0126]

[0127] wherein E pgu，nom is the rated power of the generator, E pgu (t) is the actual power of the generator.

[0128] The system output power of the generator under certain conditions is:

[0129]

[0130] When the unit works at a small PLR, the power generation efficiency of the generator and the internal combustion engine efficiency are both low, resulting in low overall power generation efficiency of the unit, causing a lot of energy waste. Therefore, the minimum load rate λ (0 < λ < 1) of the unit is often added to the unit model as a unit start constraint, and λ is taken as the unit start threshold. When the PLR of the unit < λ, i.e., E pgu (t) < λE pgu,nom , the unit does not reach the start threshold and will not start. Therefore, the operating constraint condition of the generator unit is:

[0131]

[0132] 3) Waste heat utilization unit

[0133] The gas trigeneration unit generates electricity at the same time, and will generate flue gas that can be utilized, i.e., the available waste heat. The directly determines the available cold or heat value, which is related to the flue gas temperature and flow. The scheme described in the embodiment utilizes the parameter identification method to determine the relationship between the flue gas temperature and the power generation value according to the relevant project data and actual operation experience, which can be expressed as:

[0134] The flue gas temperature can be fitted by a cubic polynomial as:

[0135]

[0136] The flue gas flow can be fitted by a quadratic polynomial as:

[0137]

[0138] wherein: and are the fitting coefficients.

[0139] The flue gas flow and temperature are brought into equation (12) to obtain the available waste heat and the power generation Nonlinear coupling relationship of the above equation is:

[0140]

[0141] In the formula is a polynomial fitting coefficient.

[0142] The flue gas generated by the gas turbine can be output to the heat pump for refrigeration and heating, or output to the heat exchange device for heating. The specific amount is related to the actual cold and heat demand.

[0143] The triple supply system supplies cold through the absorption heat pump. The corresponding is:

[0144]

[0145] In the formula, E c The corresponding kW;

[0146] T e The average water temperature at the inlet and outlet of the evaporator, K;

[0147] T c The average water temperature at the inlet and outlet of the condenser, K;

[0148] COP c The refrigeration performance coefficient of the heat pump;

[0149] The available waste heat for the heat pump, kW;

[0150] When the waste heat discharged by the gas turbine is all used for the heat pump unit, When the waste heat discharged by the gas turbine is partially used for the heat pump unit, according to the heat pump capacity configuration, take the coefficient ε,

[0151] The triple supply system supplies heat through the absorption heat pump and supplies hot water through the heat exchange device. The corresponding is divided into two parts: the heat supply corresponding to the heat pump unit and the hot water supply corresponding to the heat exchange device The proportion of the two is related to the actual demand of the user.

[0152]

[0153] Among them,

[0154] F h The corresponding kW;

[0155] T α — waste heat recovery temperature, K;

[0156] COP h — heat pump heating performance coefficient;

[0157] — available waste heat Heat pump part, kW;

[0158] — available waste heat Heat exchange part, kW;

[0159] In actual operation, external load demand, cold and heat source temperature, and ambient temperature have a great influence on the overall performance of the system. Through variable condition analysis, when the ambient temperature is 24-38℃, the system is cold and power supply or heat and power and cold supply, and the main equipment includes gas turbine, generator, heat exchanger, and heat pump unit. When the ambient temperature is -10-24℃, the system switches to heat and power supply.

[0160] The above heat, electricity, cold, and gas related values are respectively substituted into

[0161]

[0162] The system efficiency of different combined supply modes can be obtained:

[0163] Cold and power supply:

[0164] Heat and power supply:

[0165] Heat, power, and cold supply:

[0166] (2) Full working condition model research of photovoltaic power generation system

[0167] The photovoltaic power generation system mainly consists of a solar module and an inverter. The solar module converts solar energy into electrical energy, and the inverter controls the direct current voltage on the solar module side and converts it into a voltage level suitable for grid connection. According to the energy conversion process, this project separately models the photovoltaic module and the photovoltaic inverter.

[0168] 1) Photovoltaic module

[0169] ​Photovoltaic module is an important device of photovoltaic power generation system, its principle is to convert light energy into electricity by using the photoelectric effect of semiconductor materials. A large number of photovoltaic cells can be connected in series and parallel to form a photovoltaic array to generate voltage and output power that meet the needs of users. With the actual solar radiation and environmental temperature of the installation site of the photovoltaic module as input, the full working condition power output model of the module can be obtained, as shown in equation (19):

[0170] E PV (t)=N PV [G P (t) / G STC (t)][1+α(T PV,P (t)-T PV,ST )] (19)

[0171] Wherein: E PV is the output power of the solar photovoltaic array;

[0172] N PV is the maximum output power of the photovoltaic array under standard conditions, i.e. the installed capacity;

[0173] G P is the solar radiation intensity at time t;

[0174] G STC is the solar radiation intensity under standard conditions, and the scheme described in the present embodiment takes 1000 W / m 2 ;

[0175] α is the temperature coefficient of the PV cell;

[0176] T PV,P is the temperature of the battery pack at time t;

[0177] T PV,ST is the temperature of the battery pack under standard test conditions, and the scheme described in the present embodiment takes 25℃.

[0178] 2) Photovoltaic inverter

[0179] The photovoltaic inverter is a controller device, usually adopts maximum power point tracking control, controls the DC side voltage of the module, does not directly participate in energy conversion, but there is energy loss in its working process, the amount of actual energy transmission can be represented by working efficiency, the working efficiency of the inverter is directly related to the DC side power, the present project adopts the method of parameter identification to establish an empirical model of the efficiency of the inverter, as shown in equation (20):

[0180]

[0181] In the formula: η pv is the photovoltaic inverter efficiency when the DC power is E pvThe efficiency of the work at the time;

[0182] The polynomial fitting coefficients can be obtained from the manufacturer's test data;

[0183] In summary, the full working condition mathematical model of the photovoltaic power generation system can be expressed as:

[0184] E pv.e (t) = E pv (t) * η pv (21)

[0185] In the formula: E pv.e (t) is the actual output electric power of the photovoltaic inverter;

[0186] According to the above research, the scheme described in this embodiment takes a certain 5MW photovoltaic power station as an example, and obtains its working condition characteristics as shown in Figure 5 .

[0187] (3) Full working condition model research of refrigeration / heat equipment

[0188] 1) Electric compression heat pump and refrigeration unit

[0189] The electric compression heat pump and refrigeration unit is a device that generates a large amount of heat or cold by consuming a small amount of high-grade electric energy, mainly composed of electric compressor, condenser, expansion valve and evaporator and other components.

[0190] When the unit operates at a certain part load, the total heat exchange capacity decreases, the relative heat exchange area of the heat exchanger increases, and the heat exchange efficiency will be improved, so the efficiency of the unit will also be improved accordingly. At the same time, due to the reduction of condensing temperature, the increase of evaporation temperature and the reduction of refrigerant flow, the COP of the unit will be further improved at part load. When the part load rate of the unit further decreases, the refrigerant flow continues to decrease, and the compressor suction volume is too low, which leads to a significant reduction in compressor efficiency, and the COP of the unit will be greatly reduced. Therefore, when modeling the equipment, the operating conditions and part load factors of the unit are considered, and the COP of the unit obtained is consistent with the actual situation.

[0191] The maximum refrigerating capacity or heating capacity Q max of the unit under different working conditions is related to the evaporator side water flow M e , the condenser side water flow M c , the evaporator side outlet water temperature T eo , and the condenser side return water temperature T ci .

[0192] Q max = Q o R o (22)

[0193] Wherein: Q0 is the refrigerating or heating capacity of the unit under rated working condition, kW;

[0194] R0 is the correction coefficient of the unit under actual working condition.

[0195] The water temperature T S out of the unit at the using side is:

[0196] Q = CM S Δt (23)

[0197] Wherein: Q is the refrigerating or heating capacity of the unit under actual working condition, kW;

[0198] M S is the water flow at the using side of the unit, m 3 / h;

[0199] C is the specific heat capacity of the fluid, kJ / (kg·℃);

[0200] △t is the temperature difference of the supply and return water at the using side, ℃.

[0201] The part load ratio of the unit is:

[0202]

[0203] Under actual working condition, the input power required by the unit is not only related to M e , M c , T eo , T ci , but also related to the part load ratio of the unit:

[0204] P = P O P r1 P r2 (25)

[0205] Wherein: P is the input power of the unit under actual working condition, kW;

[0206] P0 is the rated input power of the unit, kW;

[0207] P r1 is the input power correction coefficient of the unit under different working conditions;

[0208] P r2 is the input power correction coefficient of the unit under part load;

[0209] Under actual working condition, the performance coefficient of the unit is:

[0210]

[0211] Referring to the DOE-2 model, R0, P r1 , P r2As shown below:

[0212]

[0213]

[0214] P r2 = a3 + a4PLE + a5PLE 2 (28)

[0215] wherein: r me is the ratio of actual water flow rate to rated water flow rate on the evaporator side;

[0216] r mc is the ratio of actual water flow rate to rated water flow rate on the condenser side;

[0217] r Teo is the ratio of actual outlet water temperature to rated outlet water temperature on the evaporator side;

[0218] r Tci is the ratio of actual return water temperature to rated return water temperature on the condenser side.

[0219] The heat efficiency of the unit is:

[0220]

[0221] wherein: T e is the average water temperature at the inlet and outlet of the evaporator, ℃;

[0222] T c is the average water temperature at the inlet and outlet of the condenser, ℃.

[0223] The cold efficiency of the unit is:

[0224]

[0225] wherein: T e is the average water temperature at the inlet and outlet of the evaporator, ℃;

[0226] T c is the average water temperature at the inlet and outlet of the condenser, ℃.

[0227] Based on the above, the full working condition model of the electric compression heat pump and refrigeration unit based on efficiency can be expressed as:

[0228]

[0229]

[0230] wherein: E c is the cooling corresponding to the heat pump unit kW;

[0231] E h For the heat pump unit heating corresponding kW;

[0232] For the heat pump unit power kW;

[0233] 2) Absorption heat pump and refrigeration unit

[0234] Absorption heat pump and refrigeration unit is a high-grade heat energy as the driving heat source, heat or cold generating equipment, mainly has the absorber, generator, condenser, expansion valve and evaporator components.

[0235] Similar electric compression unit, in the equipment modeling, considering the operation condition and part load factors of the unit, the unit COP and waste heat utilization performance in line with the actual situation.

[0236] The maximum refrigeration capacity or heat capacity Q of the unit under different operating conditions max , the actual refrigeration capacity or heat capacity Q of the unit, and the part load rate PLR of the unit are the same as the electric compression unit. Under the actual operating condition, the required heat consumption of the unit is not only related to M e , M c , T eo , T ci , PLE, but also related to the flow and temperature of the high-grade driving heat source.

[0237] Φ = Φ0Φ r1 Φ r2 Φ r3 (33)

[0238] Where: Φ is the actual heat consumption of the unit, kW;

[0239] Φ0 is the rated heat consumption of the unit, kW;

[0240] Φ r1 is the heat consumption correction coefficient of the unit under different operating conditions;

[0241] Φ r2 is the heat consumption correction coefficient of the unit under part load;

[0242] Φ r3 is the driving heat source parameter correction coefficient of the unit.

[0243] Under the actual operating condition, the performance coefficient of the unit is:

[0244]

[0245] Referring to the DOE-2 model, R0, Φr1 Φ r2 Φ r3 As shown below:

[0246]

[0247]

[0248] Q r2 =a3+a4PLE+a5PLE 2 (37)

[0249] Q r3 =a6+b5r my +b6r my 2 +c5r Tyi +c6r Tyi 2 (38)

[0250] Where: r me This is the ratio of the actual water flow rate on the evaporator side to the rated water flow rate.

[0251] r mc This is the ratio of the actual water flow rate on the condenser side to the rated water flow rate.

[0252] r Teo This is the ratio of the actual outlet water temperature on the evaporator side to the rated outlet water temperature.

[0253] r Tci This is the ratio of the actual return water temperature on the condenser side to the rated return water temperature.

[0254] Similar to electric compression heat pumps and refrigeration units, the unit operates in both cooling and heating modes. The efficiency can be obtained using equations (29) and (30) respectively, based on The full-condition model of efficiency can be obtained using equation (31).

[0255] (4) Study on full-condition model of energy storage equipment

[0256] In integrated energy systems, electrical energy storage provides short-term power supply and energy buffering, improves power quality, coordinates and optimizes system operation, and enhances economic efficiency, making it a major component. Currently, there are many types of energy storage technologies with varying working principles, but their structural topologies are generally similar. This embodiment uses electrochemical battery energy storage, which is widely used in current integrated energy systems, as an example to establish an electrical energy storage system equipment model.

[0257] The electrochemical energy storage is generally composed of energy storage battery, power conversion system (PCS) and energy storage monitoring management system. The energy storage battery realizes the conversion between electrical energy and chemical energy through electrochemical reaction; the PCS completes the charge and discharge control, power regulation, filtering and other control functions, and is the core component of the energy storage and power grid energy two-way transmission; the energy storage monitoring management system detects the charge and discharge of the energy storage device in real time, monitors the voltage, current, temperature and other state indicators, and adjusts the control according to the operation condition. According to the energy conversion process, the energy conversion (energy storage battery) and transmission link (converter) of the electrochemical energy storage are modeled respectively, and the energy storage monitoring management unit does not participate in the energy conversion, which is not involved here.

[0258] 1) Energy storage battery

[0259] When the lithium ion battery is running, complex electrochemical reactions occur inside the battery, and the internal parameters of the battery change with the SOC. In order to better reflect the full working condition characteristics of the energy storage battery, the improved Thevenin equivalent current model is used in this project. The improved Thevenin equivalent circuit model is shown in Figure 8

[0260] The continuous equation of the model can be listed according to Kirchhoff's circuit theorem as formulas (5.39) and (5.40):

[0261] V d (t)=V oc (t)-R0I d (t)-R P I p (t) (39)

[0262]

[0263] Where: V OC is the open circuit voltage of the energy storage battery;

[0264] R0 is the internal resistance of the battery;

[0265] R P is the polarization resistance of the battery;

[0266] C P is the polarization capacitance of the battery;

[0267] V d is the DC side voltage of the energy storage battery;

[0268] I d is the DC side current of the energy storage battery, negative when charging and positive when discharging;

[0269] Considering the operating conditions of chemical batteries, the chemical battery system is usually described as a typical nonlinear time-varying system, which is specifically reflected in the equivalent circuit model parameters V OC ​R0, R P and C P with nonlinear relationship of SOC. The improved parameters of the Thevenin battery model including R0, R P and C P can be identified by HPPC experiment. OC The open circuit voltage method combined with the least square method can be used to identify the parameters.

[0270] By using the constant current charge and discharge intermittent method with small ΔSOC, the reliable V OC -SOC curve can be obtained, and then the function relationship between V OC and SOC can be obtained by using the fitting tool:

[0271]

[0272] wherein: is the fitting coefficient;

[0273] S SOC is the SOC value of the battery;

[0274] In the actual experiment, the fitting curves of R0, R P and C P in the battery model are quite different from the actual measured data points, so the cubic Hermite polynomial interpolation is used, which has the advantages of function continuity and smooth curve.

[0275] 2) Energy storage converter (PCS)

[0276] The loss of the converter comes from the loss of the switching devices, isolation transformer, filter inductance, capacitance and other components. In this project, the efficiency of the converter is established as a function of the power on the DC side, which is fitted by a quintic polynomial, and can be expressed as:

[0277]

[0278] In summary, the full working condition mathematical model of the electrochemical energy storage system can be expressed as:

[0279] E bat.e (t) = V d I d * η bat (43)

[0280] wherein: E bat.e (t) is the actual output electric power of the energy storage converter;

[0281] The equations (39) and (40) are brought into equation (43) to obtain the output power equation of the electrochemical energy storage system.

[0282] (Three) schedulable load full working condition model research

[0283] Schedulable load can be directly realized in a combined cooling heating and power system without additional equipment, demand side management of multiple types of load, for solving the problem of energy supply and demand imbalance caused by load changes in the actual operation of multi-energy flow system has an important role. Therefore, the accurate schedulable modeling of electric, heat and cold load plays a key role in ensuring the efficient operation of the system.

[0284] (1) schedulable electric load full working condition model research

[0285] With the popularity of various household appliances, it can greatly facilitate people's life, dishwashers, washing machines and other household appliances can save people's time, liberate people's hands, televisions, game consoles and other household entertainment appliances can increase people's happiness index. However, with the increase of electrical equipment, the proportion of residential electricity load in the total social power load is getting larger and larger, and this part of the load is closely related to people's living habits. Due to the similar living habits and customs of people in the same area, this part of the load has the characteristics of concurrency, which increases the peak-valley difference of the power grid and threatens the safety of the power grid. In addition, the connection of renewable energy (photovoltaic, wind power) will also lead to increasing pressure on power grid peak shaving.

[0286] DR as an important control measure in the power grid system, plays an important role in maintaining system stability, reducing the peak-valley difference of the power grid, promoting the consumption of new energy such as photovoltaic and wind power, and promoting the development of distributed power generation. More and more people use smart meters and smart home appliances, which creates conditions for DR for residential electricity load. Residential load has become an increasingly important power demand side resource. Therefore, it is necessary to study how to realize the regulation of household smart appliances in DR and better schedule the power demand side resource.

[0287] According to the characteristics of the load equipment itself and people's living needs, household appliances can be divided into rigid load and schedulable load, where rigid load refers to power load that must be met in real time and has a great impact on life. This type of load does not participate in DR, so the scheme described in this embodiment is not studied. Schedulable load mainly includes interruptible load and non-interruptible load (shiftable load). Interruptible load, such as electric vehicles, has a fixed total charging capacity, but it can be charged and powered off at any time within a given charging time interval. It only needs to ensure that the total charging time meets the demand, so this type of device should be suspended during peak electricity consumption time. Non-interruptible load (shiftable load), as the name implies, once started, this type of load cannot be stopped until the required power consumption is met and the device is powered off. For example, dishwashers, washing machines.

[0288] In the DR scheme, the load shifting in the limited time (working interval) is introduced to represent the load change due to the willingness of the residential customers. The scheme described in this embodiment mainly analyzes the devices (adjustable electrical load) sensitive to the electricity price and incentive signal, and models them.

[0289] Assume that I is the set of schedulable smart appliances (loads) in the scheduling period T, IC is the set of interruptible appliances (loads) in I, the smart appliances (loads) in the working interval can be turned on or off at any time according to personal habits and scheduling strategies; I U is the set of non-interruptible smart appliances in I, once such devices are running, they cannot be turned off in the working time. The running period T is 24 hours (one day), and the control period is 1 hour, so for each device i ∈ I, its energy consumption and on / off state in the interval are e i (t) and y i (t) ∈ {0, 1}, t ∈ T, where t is a time in the period T (t = 1, 2, …, 24), 0 represents that the device is off, and 1 represents that the device is running. For simplicity, we assume that the energy consumption of each device is fixed r i in a single interval, where i ∈ I.

[0290] 1) Interruptible load

[0291] Given [A i ,B i ] ∈ T is the working interval of device i (the length of the working interval of the device must be greater than the length of the fixed working interval before the device participates in scheduling), where i ∈ I c , then the device i can run at any time in [A i ,B i ], and its total power consumption is fixed, and its specific working time is obtained by the collaborative optimization strategy. The energy consumption e i (t) of the device in the t period satisfies the following constraints:

[0292]

[0293] In the formula: E i is the total power consumption of device i in the scheduling period T.

[0294] The actual device running needs to satisfy the running time constraint, and the time constraints of different devices are different, so the on / off state of each device i needs to satisfy the following constraints:

[0295]

[0296]

[0297] In the formula: τ i,min and τ i,max are the upper and lower limits of the running time of the device i, respectively.

[0298] τ i is the actual runtime length of the device i.

[0299] 2) Non-interruptible load

[0300] For non-interruptible load, it still needs to meet the energy consumption constraint and the runtime constraint, as shown in the following formula:

[0301]

[0302]

[0303]

[0304] But for non-interruptible load, the device must run once it is turned on until it meets its required runtime, so an auxiliary binary variable μ i (t) is introduced to describe its start running state, when μ i (t) = 1 appears, the device starts running from this time until it meets the runtime, and the device is turned off, μ i (t) satisfies the following formula:

[0305]

[0306]

[0307]

[0308] In the above formula, it can be guaranteed that the non-interruptible device starts in the part interval [A i ,B i - τ i,min + 1] of its working interval and starts only once, that is, there is and only one time point of μ i (t) = 1, which ensures that it has enough continuous time points to work in the working interval until it meets the specified runtime of the device.

[0309] (2) Research on full working condition model of schedulable cooling and heating load

[0310] The cooling and heating load accounts for the largest proportion in building load. Increasing the demand side management of cooling and heating load can realize load adjustment on the energy consumption side and better coordinate the energy balance between the energy supply side and the energy consumption side. The scheme described in this embodiment takes residential buildings as an example to conduct modeling research on cooling and heating load. As can be known from the differential equation of indoor and outdoor temperature:

[0311]

[0312]

[0313] Wherein: T in Indoor temperature of the house;

[0314] T out The outdoor temperature of the house;

[0315] Q losses Energy loss in the building;

[0316] R eq Equivalent thermal resistance of the building;

[0317] M air For indoor air quality;

[0318] c is the specific heat capacity of air;

[0319] Q represents the energy required to maintain the indoor temperature, i.e., the user's heat load.

[0320] Combining equations (53) and (54), the dispatchable heat load Q can be obtained as follows:

[0321]

[0322] Where T is the control period, which is 1 hour in the scheme described in this embodiment.

[0323] φ is a constant and can be calculated using the following formula:

[0324]

[0325] Similarly, the dispatchable cooling load is expressed by the following formula:

[0326]

[0327] In equations (55) and (57), the scheduling of heating and cooling loads can be achieved by controlling the indoor temperature Tin.

[0328] (3) Energy supply / consumption demand and operating characteristics of the integrated energy system under all operating conditions

[0329] To obtain energy consumption curves for typical users, this project referenced the "Application Manual of Gas-fired Distributed Energy Technology (Cooling, Heating and Power)" and the "National Civil Building Engineering Design Technical Measures," and provided typical daily load curves for various user types, including: electricity load curves, heating load curves, and cooling load curves. All load data have been normalized.

[0330] As shown in Figures 9 to 11, due to differences in production and living needs, the electricity, heat, and cooling load characteristics of various users differ significantly. Therefore, the energy consumption characteristics of each user must be comprehensively considered in the load forecasting model.

[0331] Example 2:

[0332] The purpose of the embodiment is to provide a demand side load configuration system for a multi-energy complementary comprehensive energy system.

[0333] A demand side load configuration system for a multi-energy complementary comprehensive energy system comprises:

[0334] A data acquisition unit is configured to acquire inherent characteristics of energy conversion, heat transfer and loss of each unit of the comprehensive energy system based on thermodynamic theory;

[0335] A comprehensive energy system model construction unit is configured to realize full working condition modeling of each device of the comprehensive energy system by mechanism analysis and parameter identification method based on the inherent characteristics, dynamic response time of the device of the comprehensive energy system and multi-stage change of physical process of phase transition critical point of the working medium state of the device; wherein the comprehensive energy system comprises a combined heat and power system of a gas turbine, a photovoltaic power generation system, a refrigeration and heating device and an electric energy storage system, and biomass gas is used as the gas of the combined heat and power system of the gas turbine.

[0336] A load management unit is configured to realize demand side management configuration of various types of loads based on demand side cold, heat and electricity dispatchable load demand by using modeling results of the device of the comprehensive energy system.

[0337] Further, the system of the embodiment corresponds to the method of the first embodiment, and the technical details have been described in detail in the first embodiment, so the details are not described here.

[0338] The demand side load configuration system for a multi-energy complementary comprehensive energy system provided by the above embodiment can be realized, and has a broad application prospect.

[0339] The above only describes the preferred embodiments of the present disclosure and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.​

Claims

1. A method for demand-side load configuration in a multi-energy complementary integrated energy system, characterized in that, include: Based on thermodynamic theory, the intrinsic characteristics of energy conversion, heat transfer and energy loss of each unit in a comprehensive energy system are obtained; Based on the inherent characteristics, the dynamic response time of the equipment in the integrated energy system, and the physical process of the multi-stage change of the phase transition critical point of the working fluid state, the full-condition modeling of each piece of equipment in the integrated energy system is realized through mechanism analysis and parameter identification methods; wherein, the integrated energy system includes a gas turbine combined heat and power system, a photovoltaic power generation system, a refrigeration and heating equipment, and an electric energy storage system, and the gas turbine combined heat and power system uses biomass gas. The full-condition mathematical model of the gas turbine combined heat and power system is as follows: in, For the overall system efficiency, For generating electricity, The corresponding unit for cooling capacity is 1000 kilometres. For the corresponding heating supply, For inputting 㶲; The power generation is represented as follows: in, The generator's power generation efficiency. ; For the efficiency of internal combustion engines, ; , The fitting coefficients are denoted as PLR; PLR is the generator load rate. Inputting 㶲 represents the following: in, Substitute the fuel into the total energy of the gas turbine, kW; The ambient temperature, in K; Fuel combustion temperature, K; Using the equipment modeling results of the integrated energy system, demand-side management configuration of various types of loads can be realized based on the demand-side dispatchable load demand for cooling, heating, and electricity.

2. The demand-side load configuration method for a multi-energy complementary integrated energy system as described in claim 1, characterized in that, The gas turbine combined cycle power system includes system input, gas internal combustion engine, generator set and system output. It uses the gas internal combustion engine to burn natural gas as power to drive the generator to generate electricity, and recovers waste heat for winter heating or summer cooling.

3. The demand-side load configuration method for a multi-energy complementary integrated energy system as described in claim 1, characterized in that, The photovoltaic power generation system is modeled using separate modeling methods for photovoltaic modules and photovoltaic inverters. Specifically, the full-condition mathematical model of the photovoltaic power generation system is represented as follows: in, This refers to the actual output power of the photovoltaic inverter. E PV For the output power of the solar photovoltaic array, For photovoltaic inverters with DC power of Work efficiency at that time.

4. The demand-side load configuration method for a multi-energy complementary integrated energy system as described in claim 1, characterized in that, The refrigeration and heating equipment includes an electric compression heat pump and a refrigeration unit or an absorption heat pump and a refrigeration unit. The full-condition model of the refrigeration and heating equipment is specifically represented as follows: in, The corresponding cooling supply for heat pump units; The corresponding heat pump unit for heating; Electricity for heat pump units.

5. A demand-side load configuration method for a multi-energy complementary integrated energy system as described in claim 1, characterized in that, The energy storage system includes an energy storage battery and an energy storage converter. The specific mathematical model of the energy storage system under all operating conditions is as follows: in, This represents the actual output power of the energy storage converter. For energy storage converter efficiency, This refers to the DC side voltage of the energy storage battery. This refers to the DC-side current of the energy storage battery.

6. The demand-side load configuration method for a multi-energy complementary integrated energy system as described in claim 1, characterized in that, The biomass gas is a combustible gas produced by the pyrolysis or gasification of biomass containing substances such as crop straw, forest waste, edible fungus residue, poultry and livestock manure, and sewage sludge at high temperatures.

7. A demand-side load configuration system for a multi-energy complementary integrated energy system, characterized in that, The method for demand-side load configuration in a multi-energy complementary integrated energy system as described in any one of claims 1-6 includes: The data acquisition unit is used to acquire the intrinsic characteristics of energy conversion, heat transfer, and energy loss of each unit in the integrated energy system based on thermodynamic theory. The integrated energy system model building unit is used to model all operating conditions of each device in the integrated energy system based on the inherent characteristics, the dynamic response time of the equipment in the integrated energy system, and the physical process of the multi-stage change of the phase transition critical point of the working fluid state of the equipment, through mechanism analysis and parameter identification methods; wherein, the integrated energy system includes a gas turbine combined cycle power system, a photovoltaic power generation system, a refrigeration and heating equipment, and an electric energy storage system, and the gas turbine combined cycle power system uses biomass gas; The load management unit is used to utilize the equipment modeling results of the integrated energy system to realize demand-side management configuration of various types of loads based on the demand-side dispatchable load demand for cooling, heating, and electricity.

8. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements a demand-side load configuration method for a multi-energy complementary integrated energy system as described in any one of claims 1-6.

9. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements a demand-side load configuration method for a multi-energy complementary integrated energy system as described in any one of claims 1-6.

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