Efficient operation optimization method for integrated energy system

Abstract

The present invention discloses an efficient operation optimization method for an integrated energy system, including determining the optimization input data of the integrated energy system; introducing an integrated load aggregate into the integrated energy system to integrate the resources of electricity, cold and heat loads; establishing and solving an efficient operation optimization model for the integrated energy system considering the integrated load aggregate, and performing efficient operation of the integrated energy system according to the result. The efficient operation optimization method for the integrated energy system provided by the present invention reduces the carbon emissions of the system by introducing carbon emissions, improves the energy efficiency of the integrated energy system from the perspective of energy quality by introducing losses, and takes into account various indicators of the system by using a weighted fuzzy method, and fully taps the load-side resources by introducing an integrated load aggregate; therefore, the present invention comprehensively considers various types of energy, and has high reliability and good practicality.

Description

Technical Field

[0001] The invention belongs to the field of electrical automation, and in particular relates to a method for optimizing the efficient operation of a comprehensive energy system. Background Art

[0002] With the development of economy and technology and the improvement of people's living standards, integrated energy systems have gradually been applied to people's production and life, bringing endless convenience to people's production and life. At present, with the increasing prominence of environmental problems, integrated energy systems have gradually become the focus of researchers with their characteristics of optimizing energy structure, realizing multi-energy coupling, and green energy use. The efficient operation of integrated energy systems has become the top priority of research.

[0003] At present, although there have been many studies on the efficient operation of integrated energy systems, the current research results take fewer factors into consideration and have poor reliability. Moreover, current research generally only conducts operation research based on economic efficiency, which is also to some extent divorced from environmental protection and other requirements. Finally, current research generally only focuses on the electrical energy aspect of integrated energy systems, which is relatively narrow and less practical. Summary of the invention

[0004] The purpose of the present invention is to provide a method for optimizing the efficient operation of a comprehensive energy system which comprehensively considers various types of energy and has high reliability and good practicality.

[0005] The efficient operation optimization method of the integrated energy system provided by the present invention comprises the following steps:

[0006] S1. Determine the optimal input data of the integrated energy system; obtain different types of load data to determine the operating parameters of the integrated energy system;

[0007] S2. Introduce integrated load aggregates into the integrated energy system to integrate electricity, cooling and heating loads;

[0008] S3. Establish an efficient operation optimization model for the integrated energy system considering the integrated load aggregate;

[0009] S4. Solve the model established in step S3, and operate the integrated energy system efficiently based on the results.

[0010] The comprehensive energy system is composed of wind power, photovoltaics, gas turbines, gas boilers, electric boilers, energy storage equipment, electric refrigerators, absorption refrigerators and heat exchangers.

[0011] The step S2 introduces the integrated load aggregate into the integrated energy system to integrate the electricity, cooling and heating loads, and specifically includes the following steps:

[0012] Introduce integrated load aggregates into the integrated energy system; integrated load aggregates are used to provide auxiliary services to external energy networks and obtain corresponding payment funds, and are also used to provide guidance for the integrated energy system and perform corresponding load optimization;

[0013] The compensation funds C paid by the integrated load aggregate for the integrated energy system are calculated using the following formula: LA :

[0014]

[0015] Where T is the total number of dispatch periods; is a 0-1 variable used to indicate whether the electric load in period t participates in the reduction, and Indicates that the electric load participates in the reduction during period t, Indicates that the electric load does not participate in the reduction during the t period; b0 is the set fixed compensation fund for electric energy; b1 is the set unit compensation price for electric energy; P t cur is the power reduction of the electric load during period t; Δt is the time of a single scheduling period; is a 0-1 variable used to indicate whether the heat load in period t is involved in the reduction, and Indicates that the heat load in period t participates in the reduction, Indicates that the heat load in period t is not reduced; b2 is the set fixed compensation fund for heat energy; b3 is the set unit compensation price for heat energy; The power reduction for the heat load during period t; is a 0-1 variable used to indicate whether the cooling load in period t is involved in the reduction, and Indicates that the cooling load in period t participates in the reduction, Indicates that the cooling load in period t is not reduced; b4 is the set cooling energy fixed compensation fund; b5 is the set cooling energy unit compensation price; The cooling load is reduced for period t;

[0016] The following formula is used as the constraint condition:

[0017] Electric load reduction power upper and lower limit constraints: Where P cur,min The lower limit of power reduction for electric load; P cur,max Reducing power caps for electrical loads;

[0018] Thermal load reduction power upper and lower limit constraints: Where Q cur,min Cut the power limit for thermal load; Q cur,max Reduce power cap for heat loads;

[0019] Cooling load reduction power upper and lower limit constraints: Where Q c,cur,min The lower limit of power reduction for cooling load; Q c,cur,max Reduce power cap for cooling load;

[0020] Upper limit constraint on daily reduction of electric load: Where P daycur,max The upper limit of the daily reduction of electricity load;

[0021] Upper limit constraint on daily heat load reduction: Where Q daycur,max The upper limit of the daily reduction of heat load;

[0022] Upper limit constraint on daily cooling load reduction: Where Q c,daycur,max The upper limit of cooling load reduction per day;

[0023] Restrictions on the duration of load reduction: in is a 0 / 1 variable indicating whether the load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the load reduction has ended in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T1 is the electric control variable, which is used to control the duration of electric load reduction;

[0024] Heat load reduction duration constraints: in is a 0 / 1 variable indicating whether the heat load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the heat load reduction has ended in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T2 is the heat control variable, which is used to control the duration of heat load reduction;

[0025] Cooling load reduction duration constraints: in is a 0 / 1 variable indicating whether the cooling load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the cooling load has been reduced in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T3 is the cold control variable, which is used to control the duration of the cold load reduction;

[0026] The upper limit constraint of compensation funds for comprehensive load aggregation: C LA ≤C LA,max , where C LA,max The upper limit of compensation funds.

[0027] The step S3 of establishing the efficient operation optimization model of the integrated energy system considering the integrated load aggregate specifically includes the following steps:

[0028] Purchase energy, carbon emissions and The loss is taken as a multi-objective, and an efficient operation optimization model of the integrated energy system considering the integrated load aggregation is established;

[0029] The first optimization goal is to minimize the purchase energy:

[0030]

[0031] Where C1 is the purchased energy; P t grid V is the electric power output from the power grid to the integrated energy system during period t; t grid is the gas power output from the gas grid to the integrated energy system during period t; H L is the lower calorific value of natural gas; Δt is the time of a single scheduling period; T is the total number of scheduling periods;

[0032] Minimizing carbon emissions is the second optimization goal:

[0033]

[0034] Where C2 is carbon emissions; α grid is the carbon emission coefficient of the power grid; α tur is the carbon emission coefficient of the gas turbine; P t tur is the electrical power output of the gas turbine during period t; is the thermal power output of the gas turbine during period t; α gboi is the carbon emission coefficient of the gas boiler; is the thermal power output of the gas boiler during period t;

[0035] Integrated Energy Systems Minimizing the loss is the third optimization goal:

[0036]

[0037] Where C3 is the comprehensive energy system Loss; δ P is the power quality factor; δ V is the gas quality factor; H L is the lower calorific value of natural gas; P tload is the electric load during period t; P t cur is the power reduction of the electric load during period t; H is the thermal quality factor; is the heat load during period t; is the heat load reduction power during period t; C is the cold energy quality factor; is the cooling load during period t; The cooling load is reduced for period t;

[0038] The following formula is used as the constraint condition:

[0039] Electric power balance constraints:

[0040] P t gird +P t tur +P t wind +P t pv =P t load -P t cur +P t eboi +P t eref +P t bat

[0041] Where P t wind is the actual wind power output during period t; P t pv is the actual photovoltaic output during period t; P t eboi P is the electric power of the electric boiler during period t; t eref P is the electrical power of the electric refrigeration machine during period t; t bat is the electric power of the energy storage device during period t;

[0042] Thermal power balance constraints: in is the thermal power output of the electric boiler during period t; is the thermal power output of the heat exchanger to the heat load during period t;

[0043] Cold power balance constraints: in is the cooling power output of the electric refrigerator during period t; is the cooling power output of the absorption chiller during period t;

[0044] Gas power balance constraint: V t grid =V t tur +V t gboi , where V t tur is the input power of the gas turbine during period t; V t gboi is the input power of natural gas for gas boiler;

[0045] Wind power and photovoltaic constraints: P t wind ≤P t wind,max and P t pv ≤P t pv,max , where P t wind,max is the predicted wind power output during period t, P t pv,max The photovoltaic power output is predicted for period t;

[0046] Gas turbine power constraint: P tur,min ≤P t tur ≤P tur,max , where P tur,min is the lower limit of gas turbine output power, P t tur is the output power of the gas turbine during period t, and P t tur =η tur V t tur H L , η tur is the gas turbine electrical efficiency, and η tur Satisfy the formula β tur is the gas turbine heat loss coefficient; P tur,max Provides an upper limit on the electrical power output of the gas turbine;

[0047] Gas turbine climbing and sliding constraints: and where r up is the gas turbine ramp rate, r down is the gas turbine landslide rate;

[0048] Energy storage device constraints:

[0049] P t bat =P t c -Pt d

[0050]

[0051]

[0052]

[0053]

[0054]

[0055] Where P t bat is the charge / discharge power during time period t, charging is positive and discharging is negative; P t c is the charging power of the energy storage device during period t; P t d is the discharge power of the energy storage device during period t; E is the energy storage capacity of the energy storage device during period t; SOC,ini is the initial energy of the energy storage device; η c Charging efficiency of energy storage devices; is the charging power of the energy storage device during the τ period; is the discharge power of the energy storage device during the τ period; η d Discharge efficiency of energy storage device; is a 0-1 variable used to indicate whether the energy storage device is charged during period t, and Indicates charging. Indicates not charging; P c,min is the lower limit of energy storage rate of the energy storage device, P c,max An upper limit on the rate at which energy is stored in the energy storage device; is a 0-1 variable used to indicate whether the energy storage device is discharged during period t, and Indicates charging. Indicates not charging; P d,min is the lower limit of energy release rate of the energy storage device, P d,max is the upper limit of energy release rate; E SOC,min is the lower limit of energy storage; E is the energy storage value of the energy storage device during period t; SOC,max is the upper limit of energy storage;

[0056] Electric boiler constraints: Where Q eboi,min It is the lower limit of the thermal power output of the electric boiler; is the thermal power output of the electric boiler during period t and η eboi is the efficiency of electric boiler;

[0057] Gas boiler constraints: Where Q gboi,min It is the lower limit of thermal power output of gas boiler; is the thermal power output of the gas boiler during period t and η gboi is the gas boiler efficiency; Q gboi,max The upper limit of thermal power output of gas boiler;

[0058] Heat exchanger constraints:

[0059]

[0060]

[0061]

[0062] In the formula is the heat output power of the heat exchanger during period t; The heat input power of the heat exchanger during period t; is the thermal power output of the heat exchanger to the heat load during period t; Q is the heat power output from the heat exchanger to the absorption refrigerator during period t; exc,min Enter the lower limit of thermal power for the heat exchanger; Q exc,max Enter the upper thermal power limit for the heat exchanger;

[0063] Electric Refrigerator Constraints: Where Q c,eref,min It is the lower limit of cooling power output of the electric refrigerator; is the cooling power output of the electric refrigerator during period t, and η eref is the efficiency of the electric refrigerator; Q c,eref,max The upper limit of cooling power output of the electric refrigerator;

[0064] Absorption Chiller Constraints: Where Q c,sref,min It is the lower limit of cooling power output of absorption chiller; is the cooling power output of the absorption chiller during period t, and η sref is the efficiency of the absorption chiller; Q c,sref,max The upper limit of cooling power output for absorption chillers;

[0065] Purchase power constraint: 0≤P t gird ≤P gird,max , where P gird,max The upper limit of the power that can be purchased.

[0066] Step S4 of solving the model established in step S3 specifically includes the following steps:

[0067] A. Use the following formula to convert the three objective functions into membership functions through fuzzy processing:

[0068]

[0069]

[0070]

[0071] Where μ1 is the membership function value of the first optimization objective function; C1 is the purchased energy; θ1 is the purchased energy margin coefficient; is the purchased energy of the first optimization objective function when it is optimized alone; μ2 is the membership function value of the second optimization objective function; C2 is the carbon emission; θ2 is the carbon emission margin coefficient; is the carbon emission of the second optimization objective function when it is optimized separately; μ3 is the membership function value of the third optimization objective function; C3 is the comprehensive energy system loss; θ3 is Loss margin factor; The third optimization objective function is Loss;

[0072] Then, the comprehensive satisfaction μ is weighted by the weight coefficient, which is μ=W1μ1+W2μ2+W3μ3, where W1, W2 and W3 are weight coefficients; then, the maximum value of the comprehensive satisfaction maxμ is taken as the final single optimization target;

[0073] Finally, the optimization model for maximizing the comprehensive satisfaction is solved.

[0074] The efficient operation optimization method of the integrated energy system provided by the present invention reduces the carbon emissions of the system by introducing carbon emissions. The energy efficiency of the integrated energy system is improved from the perspective of energy quality by calculating the loss, and the weighted fuzzy method is used to take into account various system indicators. The load-side resources are fully tapped by introducing a comprehensive load aggregate. Therefore, the present invention comprehensively considers various types of energy, and has high reliability and good practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0076] Figure 2 It is a schematic diagram of the structure of the comprehensive energy system of the present invention. DETAILED DESCRIPTION

[0077] like Figure 1The method flow chart of the present invention is shown as follows: The efficient operation optimization method of the integrated energy system provided by the present invention comprises the following steps:

[0078] S1. Determine the optimal input data of the integrated energy system; obtain different types of load data to determine the operating parameters of the integrated energy system; the integrated energy system consists of wind power, photovoltaics, gas turbines, gas boilers, electric boilers, energy storage equipment, electric refrigerators, absorption refrigerators and heat exchangers; its structure is as follows Figure 2 As shown; the system purchases electricity from the power grid and natural gas from the gas grid, and introduces wind power and photovoltaic power generation for new energy; the gas turbine consumes natural gas to generate electricity, and together with the power purchased from the power grid and the new energy generation, it meets the user's electricity load demand and supplies power to the system's electrical equipment; the heat exchanger is used to recover the waste heat of the high-temperature flue gas of the gas turbine, and part of the recovered heat is used to meet the user's heat load demand, and the other part is used for cooling by the absorption refrigeration mechanism. The gas boiler consumes natural gas to generate heat, and the electric boiler consumes electricity to generate heat, both of which are used to meet the user's heat load demand; the electric refrigerator and the absorption refrigerator simultaneously meet the user's cooling load demand; in addition, the system also introduces energy storage devices to adjust the peak-valley difference;

[0079] S2. Introduce integrated load aggregates into the integrated energy system to integrate electricity, cooling and heating loads; specifically, the following steps are included:

[0080] Introduce integrated load aggregates into the integrated energy system; integrated load aggregates are used to provide auxiliary services to external energy networks and obtain corresponding payment funds, and are also used to provide guidance for the integrated energy system and perform corresponding load optimization;

[0081] The compensation funds C paid by the integrated load aggregate for the integrated energy system are calculated using the following formula: LA :

[0082]

[0083] Where T is the total number of dispatch periods; is a 0-1 variable used to indicate whether the electric load in period t participates in the reduction, and Indicates that the electric load participates in the reduction during period t, Indicates that the electric load does not participate in the reduction during the t period; b0 is the set fixed compensation fund for electric energy; b1 is the set unit compensation price for electric energy; P t cur is the power reduction of the electric load during period t; Δt is the time of a single scheduling period; is a 0-1 variable used to indicate whether the heat load in period t is involved in the reduction, and Indicates that the heat load in period t participates in the reduction, Indicates that the heat load in period t is not reduced; b2 is the set fixed compensation fund for heat energy; b3 is the set unit compensation price for heat energy; The power reduction for the heat load during period t; is a 0-1 variable used to indicate whether the cooling load in period t is involved in the reduction, and Indicates that the cooling load in period t participates in the reduction, Indicates that the cooling load in period t is not reduced; b4 is the set cooling energy fixed compensation fund; b5 is the set cooling energy unit compensation price; The cooling load is reduced for period t;

[0084] The following formula is used as the constraint condition:

[0085] Electric load reduction power upper and lower limit constraints: Where P cur,min The lower limit of power reduction for electric load; P cur,max Reducing power caps for electrical loads;

[0086] Thermal load reduction power upper and lower limit constraints: Where Q cur,min Cut the power limit for thermal load; Q cur,max Reduce power cap for heat loads;

[0087] Cooling load reduction power upper and lower limit constraints: Where Q c,cur,min The lower limit of power reduction for cooling load; Q c,cur,max Reduce power cap for cooling load;

[0088] Upper limit constraint on daily reduction of electric load: Where P daycur,max The upper limit of the daily reduction of electricity load;

[0089] Upper limit constraint on daily heat load reduction: Where Q daycur,max The upper limit of the daily reduction of heat load;

[0090] Upper limit constraint on daily cooling load reduction: Where Q c,daycur,max The upper limit of cooling load reduction per day;

[0091] Restrictions on the duration of load reduction: in is a 0 / 1 variable indicating whether the load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the load reduction has ended in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T1 is the electric control variable, which is used to control the duration of electric load reduction;

[0092] Heat load reduction duration constraints: in is a 0 / 1 variable indicating whether the heat load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the heat load reduction has ended in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T2 is the heat control variable, which is used to control the duration of heat load reduction;

[0093] Cooling load reduction duration constraints: in is a 0 / 1 variable indicating whether the cooling load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the cooling load has been reduced in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T3 is the cold control variable, which is used to control the duration of the cold load reduction;

[0094] The upper limit constraint of compensation funds for comprehensive load aggregation: C LA ≤C LA,max , where C LA,max The upper limit of the compensation fund;

[0095] S3. Establish an efficient operation optimization model for the integrated energy system considering the integrated load aggregate; specifically, it includes the following steps:

[0096] Purchase energy, carbon emissions and The loss is taken as a multi-objective, and an efficient operation optimization model of the integrated energy system considering the integrated load aggregation is established;

[0097] The first optimization goal is to minimize the purchase energy:

[0098]

[0099] Where C1 is the purchased energy; P t grid V is the electric power output from the power grid to the integrated energy system during period t; t grid is the gas power output from the gas grid to the integrated energy system during period t; H L is the lower calorific value of natural gas; Δt is the time of a single scheduling period; T is the total number of scheduling periods;

[0100] Minimizing carbon emissions is the second optimization goal:

[0101]

[0102] Where C2 is carbon emissions; α grid is the carbon emission coefficient of the power grid; α tur is the carbon emission coefficient of the gas turbine; P t tur is the electrical power output of the gas turbine during period t; is the thermal power output of the gas turbine during period t; α gboi is the carbon emission coefficient of the gas boiler; is the thermal power output of the gas boiler during period t;

[0103] Integrated Energy Systems Minimizing the loss is the third optimization goal:

[0104]

[0105] Where C3 is the comprehensive energy system Loss; δ P is the power quality factor; δ V is the gas quality factor; H L is the lower calorific value of natural gas; P t load is the electric load in period t; P t cur is the power reduction of the electric load during period t; H is the thermal quality factor; is the heat load during period t; is the heat load reduction power during period t; C is the cold energy quality factor; is the cooling load during period t; The cooling load is reduced for period t;

[0106] The following formula is used as the constraint condition:

[0107] Electric power balance constraints:

[0108] P t gird +P t tur +P t wind +P t pv =P t load -P t cur +P t eboi +Pt eref +P t bat

[0109] Where P t wind is the actual wind power output during period t; P t pv is the actual photovoltaic output during period t; P t eboi P is the electric power of the electric boiler during period t; t eref P is the electrical power of the electric refrigeration machine during period t; t bat is the electric power of the energy storage device during period t;

[0110] Thermal power balance constraints: in is the thermal power output of the electric boiler during period t; is the thermal power output of the heat exchanger to the heat load during period t;

[0111] Cold power balance constraints: in is the cooling power output of the electric refrigerator during period t; is the cooling power output of the absorption chiller during period t;

[0112] Gas power balance constraint: V t grid =V t tur +V t gboi , where V t tur is the input power of the gas turbine during period t; V t gboi is the input power of natural gas for gas boiler;

[0113] Wind power and photovoltaic constraints: P t wind ≤P t wind,max and P t pv ≤P t pv,max , where P t wind,max is the predicted wind power output during period t, P t pv,max The photovoltaic power output is predicted for period t;

[0114] Gas turbine power constraint: P tur,min ≤P t tur ≤P tur,max, where P tur,min is the lower limit of gas turbine output power, P t tur is the output power of the gas turbine during period t, and P t tur =η tur V t tur H L , η tur is the gas turbine electrical efficiency, and η tur Satisfy the formula β tur is the gas turbine heat loss coefficient; P tur,max Provides an upper limit on the electrical power output of the gas turbine;

[0115] Gas turbine climbing and sliding constraints: and where r up is the gas turbine ramp rate, r down is the gas turbine landslide rate;

[0116] Energy storage device constraints:

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123] Where P t bat is the charge / discharge power during time period t, charging is positive and discharging is negative; P t c is the charging power of the energy storage device during period t; P t d is the discharge power of the energy storage device during period t; E is the energy storage capacity of the energy storage device during period t; SOC,ini is the initial energy of the energy storage device; η c Charging efficiency of energy storage devices; The charging power of the energy storage device during the τ period; is the discharge power of the energy storage device during the τ period; η d Discharge efficiency of energy storage device; is a 0-1 variable used to indicate whether the energy storage device is charged during period t, and Indicates charging. Indicates not charging; P c,min is the lower limit of the energy storage rate for the energy storage device, P c,max An upper limit on the rate at which energy is stored in the energy storage device; is a 0-1 variable used to indicate whether the energy storage device is discharged during period t, and Indicates charging. Indicates not charging; P d,min is the lower limit of energy release rate of the energy storage device, P d,max is the upper limit of energy release rate; E SOC,min is the lower limit of energy storage; E is the energy storage value of the energy storage device during period t; SOC,max is the upper limit of energy storage;

[0124] Electric boiler constraints: Where Q eboi,min It is the lower limit of the thermal power output of the electric boiler; is the thermal power output of the electric boiler during period t and η eboi is the efficiency of electric boiler;

[0125] Gas boiler constraints: Where Q gboi,min It is the lower limit of thermal power output of gas boiler; is the thermal power output of the gas boiler during period t and η gboi is the gas boiler efficiency; Q gboi,max The upper limit of thermal power output of gas boiler;

[0126] Heat exchanger constraints:

[0127]

[0128]

[0129]

[0130] In the formula is the heat output power of the heat exchanger during period t; The heat input power of the heat exchanger during period t; is the thermal power output of the heat exchanger to the heat load during period t; Q is the heat power output from the heat exchanger to the absorption refrigerator during period t; exc,min Enter the lower limit of thermal power for the heat exchanger; Q exc,max Enter the upper limit of the heat power of the heat exchanger. The first formula represents the energy conversion relationship between the input and output of the heat exchanger itself, and the second formula is used to represent the purpose of the heat exchanger output power, that is, the relationship with the energy of other equipment.

[0131] Electric Refrigerator Constraints: Where Q c,eref,min It is the lower limit of cooling power output of the electric refrigerator; is the cooling power output of the electric refrigerator during period t, and η eref is the efficiency of the electric refrigerator; Q c,eref,max The upper limit of cooling power output of the electric refrigerator;

[0132] Absorption Chiller Constraints: Where Q c,sref,min It is the lower limit of cooling power output of absorption chiller; is the cooling power output of the absorption chiller during period t, and η sref is the efficiency of the absorption chiller; Q c,sref,max The upper limit of cooling power output for absorption chillers;

[0133] Purchase power constraint: 0≤P t gird ≤P gird,max , where P gird,max The upper limit of the power purchased;

[0134] S4. Solve the model established in step S3, and perform efficient operation of the integrated energy system based on the result; specifically, the steps include:

[0135] A. Use the following formula to convert the three objective functions into membership functions through fuzzy processing:

[0136]

[0137]

[0138]

[0139] Where μ1 is the membership function value of the first optimization objective function; C1 is the purchased energy; θ1 is the purchased energy margin coefficient; is the purchased energy of the first optimization objective function when it is optimized alone; μ2 is the membership function value of the second optimization objective function; C2 is the carbon emission; θ2 is the carbon emission margin coefficient; is the carbon emission of the second optimization objective function when it is optimized separately; μ3 is the membership function value of the third optimization objective function; C3 is the comprehensive energy system loss; θ3 is Loss margin factor; The third optimization objective function is Loss;

[0140] Then, the comprehensive satisfaction μ is weighted by the weight coefficient, which is μ=W1μ1+W2μ2+W3μ3, where W1, W2 and W3 are weight coefficients; then, the maximum value of the comprehensive satisfaction maxμ is taken as the final single optimization target;

[0141] Finally, the optimization model for maximizing the comprehensive satisfaction is solved.

Claims

1. A method for optimizing the efficient operation of an integrated energy system, comprising the following steps: S1. Determine the optimal input data of the integrated energy system; obtain different types of load data to determine the operating parameters of the integrated energy system; S2. Introduce integrated load aggregates into the integrated energy system to integrate electricity, cooling and heating loads; specifically, the following steps are included: Introduce integrated load aggregates into the integrated energy system; integrated load aggregates are used to provide auxiliary services to external energy networks and obtain corresponding payment funds, and are also used to provide guidance for the integrated energy system and perform corresponding load optimization; The compensation funds C paid by the integrated load aggregate for the integrated energy system are calculated using the following formula: LA : Where T is the total number of dispatch periods; is a 0-1 variable used to indicate whether the electric load in period t participates in the reduction, and Indicates that the electric load participates in the reduction during period t, Indicates that the electric load in period t does not participate in the reduction; b0 is the set fixed compensation fund for electric energy; b1 is the set unit compensation price for electric energy; is the power reduction of the electric load during period t; Δt is the time of a single scheduling period; is a 0-1 variable used to indicate whether the heat load in period t is involved in the reduction, and Indicates that the heat load in period t participates in the reduction, Indicates that the heat load in period t is not reduced; b2 is the set fixed compensation fund for heat energy; b3 is the set unit compensation price for heat energy; The power reduction for the heat load during period t; is a 0-1 variable used to indicate whether the cooling load in period t is involved in the reduction, and Indicates that the cooling load in period t participates in the reduction, Indicates that the cooling load in period t is not reduced; b4 is the set cooling energy fixed compensation fund; b5 is the set cooling energy unit compensation price; The cooling load is reduced for period t; The following formula is used as the constraint condition: Electric load reduction power upper and lower limit constraints: Where P cur,min The lower limit of power reduction for electric load; P cur,max Reducing power caps for electrical loads; Thermal load reduction power upper and lower limit constraints: Where Q cur,min Cut the power limit for thermal load; Q cur,max Reduce power caps for heat loads; Cooling load reduction power upper and lower limit constraints: Where Q c,cur,min The lower limit of power reduction for cooling load; Q c,cur,max Reduce power cap for cooling load; Upper limit constraint on daily reduction of electric load: Where P daycur,max The upper limit of the daily reduction of electricity load; Upper limit constraint on daily heat load reduction: Where Q daycur,max The upper limit of the daily reduction of heat load; Upper limit constraint on daily cooling load reduction: Where Q c,daycur,max The upper limit of cooling load reduction per day; Restrictions on the duration of load reduction: in is a 0 / 1 variable indicating whether the load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the load reduction has ended in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T1 is the electric control variable, which is used to control the duration of electric load reduction; Heat load reduction duration constraints: in is a 0 / 1 variable indicating whether the heat load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the heat load reduction has ended in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T2 is the heat control variable, which is used to control the duration of heat load reduction; Cooling load reduction duration constraints: in is a 0 / 1 variable indicating whether the cooling load starts to be reduced during period t, and Indicates the start of reduction. It means that the reduction has not started; is a 0 / 1 variable indicating whether the cooling load has been reduced in period t, and Indicates the end of the reduction, Indicates that the reduction has not ended; T3 is the cold control variable, which is used to control the duration of the cooling load reduction; The upper limit constraint of compensation funds for comprehensive load aggregation: C LA ≤C LA,max , where C LA,max The upper limit of the compensation fund; S3. Establish an efficient operation optimization model for the integrated energy system considering the integrated load aggregate; specifically, it includes the following steps: Purchase energy, carbon emissions and The loss is taken as a multi-objective, and an efficient operation optimization model of the integrated energy system considering the integrated load aggregation is established; The first optimization goal is to minimize the purchase energy: Where C1 is the purchased energy; P t grid V is the electric power output from the power grid to the integrated energy system during period t; t grid is the gas power output from the gas grid to the integrated energy system during period t; H L is the lower calorific value of natural gas; Δt is the time of a single scheduling period; T is the total number of scheduling periods; Minimizing carbon emissions is the second optimization goal: Where C2 is carbon emissions; α grid is the carbon emission coefficient of the power grid; α tur is the carbon emission coefficient of the gas turbine; P t tur is the electrical power output of the gas turbine during period t; is the thermal power output of the gas turbine during period t; α gboi is the carbon emission coefficient of the gas boiler; is the thermal power output of the gas boiler during period t; Integrated Energy Systems Minimizing the loss is the third optimization goal: Where C3 is the comprehensive energy system Loss; δ P is the power quality factor; δ V is the gas quality factor; H L is the lower calorific value of natural gas; P t load is the electric load during period t; P t cur is the power reduction of the electric load during period t; H is the thermal quality factor; is the heat load during period t; is the heat load reduction power during period t; C is the cold energy quality factor; is the cooling load during period t; The cooling load is reduced for period t; The following formula is used as the constraint condition: Electric power balance constraints: P t gird +P t tur +P t wind +P t pv =P t load -P t cur +P t eboi +P t eref +P t bat Where P t wind is the actual wind power output during period t; P t pv is the actual photovoltaic output during period t; P t eboi P is the electric power of the electric boiler during period t; t eref P is the electrical power of the electric refrigeration machine during period t; t bat is the electric power of the energy storage device during period t; Thermal power balance constraints: in is the thermal power output of the electric boiler during period t; is the thermal power output of the heat exchanger to the heat load during period t; Cold power balance constraints: in is the cooling power output of the electric refrigerator during period t; is the cooling power output of the absorption chiller during period t; Gas power balance constraint: V t grid =V t tur +V t gboi , where V t tur is the input power of the gas turbine during period t; V t gboi is the input power of natural gas for gas boiler; Wind power and photovoltaic constraints: P t wind ≤P t wind,max and P t pv ≤P t pv,max , where P t wind,max is the predicted wind power output during period t, P t pv,max The photovoltaic power output is predicted for period t; Gas turbine power constraint: P tur,min ≤P t tur ≤P tur,max , where P tur,min is the lower limit of gas turbine output power, P t tur is the output power of the gas turbine during period t, and P t tur =η tur V t tur H L , η tur is the gas turbine electrical efficiency, and η tur Satisfy the formula β tur is the gas turbine heat loss coefficient; P tur,max Provides an upper limit on the electrical power output of the gas turbine; Gas turbine climbing and sliding constraints: and where r up is the gas turbine ramp rate, r down is the gas turbine landslide rate; Energy storage device constraints: P t bat =P t c -P t d Where P t bat is the charge / discharge power during time period t, charging is positive and discharging is negative; P t c is the charging power of the energy storage device during period t; P t d is the discharge power of the energy storage device during period t; E is the energy storage capacity of the energy storage device during period t; SOC,ini is the initial energy of the energy storage device; η c Charging efficiency of energy storage devices; is the charging power of the energy storage device during the τ period; P τ d is the discharge power of the energy storage device during the τ period; η d is the discharge efficiency of the energy storage device; is a 0-1 variable used to indicate whether the energy storage device is charged during period t, and Indicates charging. Indicates not charging; P c,min is the lower limit of energy storage rate of the energy storage device, P c,max An upper limit on the rate at which energy is stored in the energy storage device; is a 0-1 variable used to indicate whether the energy storage device is discharged during period t, and Indicates charging. Indicates not charging; P d,min is the lower limit of energy release rate of the energy storage device, P d,max is the upper limit of energy release rate; E SOC,min is the lower limit of energy storage; E is the energy storage value of the energy storage device during period t; SOC,max is the upper limit of energy storage; Electric boiler constraints: Where Q eboi,min It is the lower limit of the thermal power output of the electric boiler; is the thermal power output of the electric boiler during period t and η eboi is the efficiency of electric boiler; Gas boiler constraints: Where Q gboi,min It is the lower limit of thermal power output of gas boiler; is the thermal power output of the gas boiler during period t and η gboi is the gas boiler efficiency; Q gboi,max The upper limit of thermal power output of gas boiler; Heat exchanger constraints: In the formula is the heat output power of the heat exchanger during period t; The heat input power of the heat exchanger during time period t; is the thermal power output of the heat exchanger to the heat load during period t; Q is the heat power output from the heat exchanger to the absorption refrigerator during period t; exc,min Input thermal power lower limit for heat exchanger; Q exc,max Enter the upper thermal power limit for the heat exchanger; Electric Refrigerator Constraints: Where Q c,eref,min It is the lower limit of cooling power output of the electric refrigerator; is the cooling power output of the electric refrigerator during period t, and η eref is the efficiency of the electric refrigerator; Q c,eref,max The upper limit of cooling power output of the electric refrigerator; Absorption Chiller Constraints: Where Q c,sref,min It is the lower limit of cooling power output of absorption chiller; is the cooling power output of the absorption chiller during period t, and η sref is the efficiency of the absorption chiller; Q c,sref,max The upper limit of cooling power output for absorption chillers; Purchase power constraint: 0≤P t gird ≤P gird,max , where P gird,max The upper limit of the power purchased; S4. Solve the model established in step S3, and operate the integrated energy system efficiently based on the results.

2. The efficient operation optimization method of the integrated energy system according to claim 1 is characterized in that The comprehensive energy system is composed of wind power, photovoltaics, gas turbines, gas boilers, electric boilers, energy storage equipment, electric refrigerators, absorption refrigerators and heat exchangers.

3. The efficient operation optimization method of the integrated energy system according to claim 1 is characterized in that Step S4 of solving the model established in step S3 specifically includes the following steps: A. Use the following formula to convert the three objective functions into membership functions through fuzzy processing: Where μ1 is the membership function value of the first optimization objective function; C1 is the purchased energy; θ1 is the purchased energy margin coefficient; is the purchased energy of the first optimization objective function when it is optimized alone; μ2 is the membership function value of the second optimization objective function; C2 is the carbon emission; θ2 is the carbon emission margin coefficient; is the carbon emission of the second optimization objective function when it is optimized separately; μ3 is the membership function value of the third optimization objective function; C3 is the comprehensive energy system loss; θ3 is Loss margin factor; The third optimization objective function is Loss; Then, the comprehensive satisfaction μ is weighted by the weight coefficient, which is μ=W1μ1+W2μ2+W3μ3, where W1, W2 and W3 are weight coefficients; then, the maximum value of the comprehensive satisfaction maxμ is taken as the final single optimization target; Finally, the optimization model for maximizing the comprehensive satisfaction is solved.

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