An Optimal Configuration Method for Integrated Energy System Based on Multi-Station Integration

Abstract

The present invention relates to an optimization configuration method for an integrated energy system based on multi-station integration, comprising the following steps: constructing an integrated energy system integrating a substation, a data center station, an energy storage station and a new energy station, and establishing an energy complementary conversion model for each energy conversion device; establishing a two-layer collaborative planning model; determining the constraint conditions for the capacity configuration of the energy conversion device and the constraint conditions for the operation strategy of the energy conversion device; formulating an evaluation index for the integrated energy system architecture; solving the two-layer collaborative planning model to obtain the configuration and operation strategy of the final integrated energy system. Compared with the prior art, the present invention establishes a two-layer collaborative planning model, with the upper-layer model aiming at minimizing the annual planning total cost and the lower-layer model aiming at minimizing the daily operation cost, and collaboratively solving the capacity configuration and operation strategy of the energy conversion device in the integrated energy system, which can overcome the cost increase and resource waste caused by unreasonable configuration of the energy conversion device.

Description

Technical Field

[0001] The present invention relates to the technical field of optimal configuration of integrated energy systems, and particularly to an optimal configuration method for an integrated energy system based on multi-station integration. Background Art

[0002] With the rapid development of 3C technologies such as communication, computing, and sensing, as well as the upgrading requirements of the intelligent and energy-saving energy industry, building an energy Internet with the power grid as the backbone grid and highly integrated information and energy has become an important construction direction in the energy field of our country. At the beginning of 2019, State Grid Corporation of China proposed multi-station integration business as one of the special pilot tasks for the construction of the ubiquitous power Internet of Things. Multi-station integration is the basic guarantee for the construction of the ubiquitous power Internet of Things, and it is also an important support for creating emerging business markets and achieving green and low-carbon development.

[0003] As one of the important applications for the implementation of the power Internet of Things, "multi-station integration" converges resources such as substations, edge data center stations, charging stations, and energy storage stations, optimizes the allocation of urban resources, improves the efficiency of data perception and analysis operations, locally absorbs loads, reduces fluctuations in the power grid, and improves the safe and stable operation of the system. The core idea of multi-station integration is based on the hub role of substations in energy collection, transmission, and conversion and utilization. Through the reasonable integration of key facility resources such as substations, energy storage stations, and data centers, the "three-way integration" of energy flow, data flow, and service flow is achieved.

[0004] Currently, the research on "multi-station integration" mostly focuses on the charge and discharge strategies of energy storage power stations and the operation of data center stations. However, the research on the optimal configuration of the integrated energy system of multi-station integration is relatively lacking. In the previous research on the optimal configuration of integrated energy systems, the consideration of the reliability of load power supply and the consumption of renewable energy is also lacking. In practical applications, the unreasonable configuration of equipment will lead to waste of resources and an increase in operating costs. Summary of the Invention

[0005] The purpose of the present invention is to overcome the above-mentioned defects existing in the prior art and provide an optimal configuration method for an integrated energy system based on multi-station integration, mainly for the reasonable configuration of the selection and capacity of relevant energy conversion equipment in the integrated energy system of multi-station integration composed of substations, data center stations, energy storage stations, and new energy stations. While ensuring the economic operation of the integrated energy system, the power supply reliability of the integrated energy system is improved, the load is fully utilized to consume renewable energy, the system's wind and light abandonment is reduced, and thus the environmental benefits are taken into account and the system's carbon emissions are reduced.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An optimal configuration method for an integrated energy system based on multi-station integration, comprising the following steps:

[0008] Construct a comprehensive energy system, which integrates a substation, a data center station, an energy storage station, and a new energy station, obtain the energy conversion equipment to be configured in the comprehensive energy system, and establish an energy complementary conversion model for each energy conversion equipment;

[0009] Establish a two-layer collaborative planning model, which is used to solve the capacity configuration and operation strategy of the energy conversion equipment;

[0010] Determine the constraint conditions for the capacity configuration of the energy conversion equipment and the constraint conditions for the operation strategy of the energy conversion equipment;

[0011] Formulate evaluation indicators for the comprehensive energy system architecture;

[0012] Solve the two-layer collaborative planning model based on the energy complementary conversion model, constraint conditions, and evaluation indicators to obtain the capacity configuration and operation strategy of each energy conversion equipment, and obtain the configuration and operation strategy of the final comprehensive energy system.

[0013] Furthermore, the energy conversion equipment includes a heat pump, an electric chiller, an absorption chiller, a heat storage device, an energy storage device, and new energy station power generation equipment. The new energy station power generation equipment includes photovoltaic and wind turbines, and their energy complementary conversion models are respectively:

[0014] The energy complementary conversion model of the heat pump is:

[0015]

[0016] Among them, represents the output heat power of the heat pump at time, represents the electric power consumed by the heat pump at time t, ξ hp represents the heating performance coefficient of the heat pump, which is a fixed parameter; input The output heat power of the heat pump is obtained through this energy complementary conversion model

[0017] The energy complementary conversion model of the electric chiller is:

[0018]

[0019] Among them, represents the output cooling power of the electric chiller at time t, represents the electric power consumed by the electric chiller at time t, ψ ec represents the refrigeration coefficient of the electric chiller, which is a fixed parameter; input The output cooling power of the electric chiller is obtained through this energy complementary conversion model

[0020] The energy complementary conversion model of an absorption chiller is as follows:

[0021]

[0022] Among them, represents the output cooling power of the absorption chiller at time t, represents the heat power consumed by the absorption chiller at time t, ψ ac represents the coefficient of performance of the absorption chiller, which is a fixed parameter; input The output cooling power of the absorption chiller is obtained through this energy complementary conversion model

[0023] The energy complementary conversion model of the heat storage device is as follows:

[0024]

[0025] Among them, respectively represent the heat storage power and heat release power of the heat storage device at time t, respectively represent the heat storage efficiency and heat release efficiency of the heat storage device, which are fixed parameters, Q h,t+1 、Q h,t respectively represent the reserved heat energy of the heat storage device at time t + 1 and the reserved heat energy of the heat storage device at time t, ε represents the self-loss coefficient of the heat storage device, which is a fixed parameter, Δt represents the scheduling time interval; input and The reserved heat energy Q of the heat storage device is obtained through this energy complementary conversion model h,t+1 and Q h,t ;

[0026] The energy complementary conversion model of the energy storage device is as follows:

[0027]

[0028] Among them, SOC(t) represents the state of charge of the energy storage device at time t, δ represents the self-discharge coefficient of the energy storage device, which is a fixed parameter; P CES 、P DES respectively represent the charging power and discharging power of the energy storage device, η CES 、η DES respectively represent the charging efficiency and discharging efficiency of the energy storage device, which are fixed parameters, E soc.st represents the rated capacity of the energy storage device, which is a fixed parameter, Δt represents the scheduling time interval; input P CES and P DES , and the state of charge SOC(t) of the energy storage device is obtained through this energy complementary conversion model;

[0029] The energy complementary conversion model of photovoltaic is as follows:

[0030]

[0031] Among them, P pv represents the magnitude of the photovoltaic power generation, and P st.max represents the maximum test power of the photovoltaic under standard test conditions, which is a fixed parameter. E s represents the light intensity, and E s.st represents the light intensity under standard test conditions, which is a fixed parameter. k represents the power temperature coefficient, which is a fixed parameter. T o represents the actual temperature of the battery panel, and T st represents the temperature of the battery panel under standard test conditions, which is a fixed parameter; input E s and T o , and the power generation power P of the photovoltaic is obtained through this energy complementary conversion model pv ;

[0032] The energy complementary conversion model of the wind turbine is:

[0033]

[0034] Among them, P wt represents the output power of the wind turbine, and P r represents the rated power of the wind turbine, which is a fixed parameter. v represents the actual wind speed of the wind turbine generator set, and v ci , v co , v r respectively represent the cut-in wind speed, cut-out wind speed and rated wind speed of the wind turbine, which are fixed parameters; input v, and the output power P of the wind turbine is obtained through this energy complementary conversion model wt .

[0035] Furthermore, the upper layer model of the double-layer collaborative planning model aims to minimize the annual planning total cost f of the integrated energy system. The objective function of the upper layer model is:

[0036] min(f) = min(f1 + f2)

[0037] Among them, f represents the annual planning total cost of the integrated energy system, and f1 and f2 respectively represent the investment cost and operation and maintenance cost.

[0038] Furthermore, use i = 1, 2, 3, 4, 5, 6, 7 to represent the energy conversion equipment as wind turbine, photovoltaic, heat pump, electric chiller, absorption chiller, energy storage device, heat storage device respectively. Then the investment cost f1 is:

[0039]

[0040] Among them, iDenote the set of all energy conversion devices of type i, C fij Denote the initial investment cost of energy conversion device j of type i, which is a fixed quantity, C rij Denote the depreciation cost of energy conversion device j of type i, which is a fixed quantity, R ij Denote the capital recovery factor of energy conversion device j of type i, a ij Denote the quantity of energy conversion device j of type i, σ ij Denote the operating status of energy conversion device j of type i, which is a 0-1 variable and takes values of 0 or 1;

[0041] The capital recovery factor R ij The expression is:

[0042]

[0043] Among them, r represents the discount rate, n ij Denote the service life of energy conversion device j of type i;

[0044] Input i, w i , a ij , σ ij , r, n ij , and the investment cost f1 can be obtained;

[0045] Use k = 1, 2, 3, 4 to represent the four seasons of a year respectively, then the operation and maintenance cost f2 is:

[0046]

[0047] Among them, C kij Denote the operation and maintenance cost of energy conversion device j of type i in season k, Num kij Denote the operation and maintenance days of energy conversion device j of type i in season k; Input C kij and Num kij and the operation and maintenance cost f2 can be obtained.

[0048] Furthermore, the lower-layer model of the double-layer collaborative planning model aims to minimize the daily operation cost f day of the integrated energy system. The new energy station in the integrated energy system follows the principle of self-use of spontaneous power generation and feeding the surplus power into the grid. The objective function of the lower-layer model is:

[0049] min(f day ) = min(f3 + f4 + f5)

[0050] Among them, f day Denote the daily operation cost of the integrated energy system, and f3, f4, f5 represent the power purchase cost, the penalty cost for wind and light abandonment, and the load interruption cost respectively.

[0051] Furthermore, the electricity purchase cost f3 is as follows:

[0052] f3 = C buy.t P buy.t - C sell.t P sell.t

[0053] Wherein, C buy.t represents the electricity purchase price of the integrated energy system, which is a fixed parameter, and P buy.t represents the electricity purchase quantity of the integrated energy system, and C sell.t represents the on-grid electricity price of the integrated energy system, which is a fixed parameter, and P sell.t represents the on-grid electricity quantity of the integrated energy system; Inputting P buy.t and P sell.t can obtain the electricity purchase cost f3;

[0054] The penalty cost f4 for curtailment of wind and solar power is as follows:

[0055] f4 = C pv P des1 + C w P des2

[0056] Wherein, C pv and C w respectively represent the penalty cost for curtailment of solar power and the penalty cost for curtailment of wind power, which are fixed parameters, and P des1 and P des2 respectively represent the curtailment of solar power and the curtailment of wind power; Inputting P des1 and P des2 can obtain the penalty cost f4 for curtailment of wind and solar power;

[0057] The load interruption cost f5 is as follows:

[0058] f5 = C loss P loss

[0059] Wherein, C loss represents the unit penalty price suffered by the integrated energy system when the load is interrupted, which is a fixed parameter, and P loss represents the magnitude of the load quantity lost by the integrated energy system when the load is interrupted; Inputting P loss can obtain the load interruption cost f5.

[0060] Furthermore, let i = 1, 2, 3, 4 represent the heat pump, thermal energy storage device, electric chiller, and absorption chiller for the energy conversion equipment respectively. Then, the constraint conditions for the capacity configuration of the energy conversion equipment are:

[0061]

[0062] Among them, X ij represents the capacity of the energy conversion device j of type i, which is a fixed quantity, η ij represents the heat storage efficiency or heat release efficiency of the energy conversion device j of type i, a ij represents the number of the energy conversion device j of type i, σ ij represents the operating state of the energy conversion device j of type i, which is a 0-1 variable and takes values of 0 or 1, and respectively represent the maximum heat load and the maximum cooling load of the integrated energy system, both of which are fixed quantities.

[0063] Furthermore, the constraint conditions of the operation strategy of the energy conversion device include the power balance constraint condition, the heat balance constraint condition, the cold balance constraint condition, the transmission line power constraint condition, the new energy station operation constraint condition, the energy storage device operation constraint condition, the heat pump operation constraint condition, the electric refrigeration machine operation constraint condition, the absorption refrigeration machine constraint condition, and the heat storage device operation constraint condition;

[0064] The power balance constraint condition is:

[0065]

[0066] P net.t = P buy.t - P sell.t

[0067] Among them, P net.t represents the interactive power between the integrated energy system and the superior power grid at time t, which is related to the power purchase quantity P buy.t and the power grid connection quantity P sell.t of the integrated energy system. When the value of P net.t is greater than zero, it means that the integrated energy system needs to purchase electricity. When the value of P net.t is less than zero, it means that the excess electricity of the integrated energy system is fed into the power grid. P DES.t represents the discharge power of the energy storage device at time t, P pv.t represents the power generation power of the photovoltaic at time t, P wt.t represents the power generation power of the wind turbine at time t, P CES.t represents the charging power of the energy storage device at time t, P SL.t is an adjustable variable in the constraint condition, representing the electric power consumed by the integrated energy system at time t, that is, the electricity consumption of the entire integrated energy system except for the controllable energy conversion devices, represents the electric power consumed by the electric refrigeration machine at time t, represents the electric power consumed by the heat pump at time t;

[0068] The heat balance constraint condition is:

[0069]

[0070] Among them, represents the output heat power of the heat pump at time t, Q h,t represents the reserved heat energy of the heat storage device at time t, H t represents the magnitude of the heat load power of the integrated energy system and is an adjustable variable in the constraint conditions;

[0071] The cold balance constraint condition is:

[0072]

[0073] Among them, represents the output cooling power of the electric chiller at time t, represents the output cooling power of the absorption chiller at time t, C L,t represents the magnitude of the cold load power of the integrated energy system at time t and is an adjustable variable in the constraint conditions;

[0074] The transmission line power constraint condition is:

[0075] P net.t <P max

[0076] Among them, P net.t represents the interaction power between the integrated energy system and the superior power grid at time t, P max represents the maximum power that the integrated energy system is allowed to purchase electricity from the power grid at time t and is a fixed value;

[0077] The operation constraint condition of the new energy station is:

[0078]

[0079] Among them, P pvmax and P wmax respectively represent the maximum power generation of the photovoltaic and wind turbines, which are fixed values, P pv.t represents the power generation of the photovoltaic at time t, P wt.t represents the power generation of the wind turbine at time t;

[0080] The operation constraint condition of the energy storage device is:

[0081]

[0082] Among them, x DES represents the discharge state of the energy storage device, with a value of 0 or 1, x CES represents the charge state of the energy storage device, which is a 0-1 variable with a value of 0 or 1, P DEs.t represents the discharge power of the energy storage device at time t, P CES.trepresents the charging power of the energy storage device at time t, E soc.t represents the stored electricity of the energy storage device at time t, respectively represent the minimum discharge power, maximum discharge power, minimum charging power and maximum charging power of the energy storage device, and respectively represent the maximum stored electricity and minimum stored electricity of the energy storage device, E soc.末 and E soc.初 respectively represent the stored electricity at the initial moment and the stored electricity at the end moment of each day of the energy storage device; the constraint condition E soc.末 = E soc.初 means that the stored electricity values of the energy storage device at the end moment and the initial moment should be equal.

[0083] The operating constraint conditions of the heat pump are:

[0084]

[0085] Among them, represents the output heat power of the heat pump at time t, represents the maximum output heat power of the heat pump;

[0086] The operating constraint conditions of the electric refrigerating machine are:

[0087]

[0088] Among them, represents the output cooling power of the electric refrigerating machine at time t, represents the maximum output cooling power of the electric refrigerating machine;

[0089] The constraint conditions of the absorption refrigerating machine are:

[0090]

[0091] Among them, represents the output cooling power of the absorption refrigerating machine at time t, represents the maximum output cooling power of the absorption refrigerating machine;

[0092] The operating constraint conditions of the heat storage device are:

[0093]

[0094] y dis represents the heat release state of the heat storage device, which is a 0-1 variable with a value of 0 or 1, y ch represents the heat storage state of the heat storage device, which is a 0-1 variable with a value of 0 or 1, respectively represent the heat storage power and heat release power of the heat storage device at time t, Q h,tRepresents the reserved thermal energy of the thermal energy storage device at time t, Represents the minimum heat release power, maximum heat release power, minimum heat storage power and maximum heat storage power of the thermal energy storage device, and Represents the minimum reserved thermal energy and maximum reserved thermal energy of the thermal energy storage device, Q h.末 and Q h.初 Respectively represent the stored thermal energy at the initial moment and the stored thermal energy at the end moment of each day of the thermal energy storage device; the constraint condition Q h.末 = Q h.初 Indicates that the reserved thermal energy values of the thermal energy storage device at the end moment and the initial moment should be equal.

[0095] Furthermore, the evaluation indexes include the renewable energy utilization rate, load accommodation rate, system load shedding rate and carbon emission;

[0096] The calculation formula of the renewable energy utilization rate is:

[0097] Renewable energy utilization rate = (total power generation of new energy stations - light curtailment - wind curtailment) / total power generation of new energy stations;

[0098] The calculation formula of the load accommodation rate is:

[0099] Load accommodation rate = power generation of new energy stations accommodated by the integrated energy system / total power generation of new energy stations;

[0100] The calculation formula of the system load shedding rate is:

[0101] System load shedding rate = total system load shedding / total station load of the integrated energy system;

[0102] The calculation formula of the carbon emission is:

[0103] Carbon emission = carbon emission coefficient * (total power purchase of the integrated energy system - total power sold by new energy stations).

[0104] Furthermore, the decision variables of the upper layer model are the number and capacity of energy conversion devices, which contain 0-1 variables and belong to a mixed integer nonlinear programming model. The differential evolution algorithm is used to solve the upper layer model to obtain the number and capacity of energy conversion devices; the lower layer model optimizes the operation strategy of the integrated energy system, that is, the operation output scheme of each energy conversion device, which belongs to linear programming. The CPLEX linear solver is used to solve the lower layer model to obtain the operation output scheme of each energy conversion device.

[0105] Compared with the prior art, the present invention has the following beneficial effects:

[0106] (1) Establish a two - layer collaborative planning model. The upper - layer model aims to minimize the annual planning total cost, and the lower - layer model aims to minimize the daily operation cost. By jointly solving the capacity configuration and operation strategy of energy conversion equipment in the integrated energy system, it can overcome the cost increase and resource waste caused by unreasonable configuration of energy conversion equipment.

[0107] (2) Fully consider the randomness and volatility of renewable energy power generation in the new energy station. When establishing the integrated energy system, the electric energy generated by the new energy station is consumed locally, thereby reducing the impact of the new energy station on the safe and stable operation of the integrated energy system.

[0108] (3) When establishing a multi - station integrated energy system, due to the more complex structure of the integrated energy system, the electricity - using safety of the integrated energy system is fully considered, which is conducive to the safe and reliable energy supply of the integrated energy system. The optimization configuration method proposed in this application has high practical application value and provides a new idea for the optimization configuration of the integrated energy system. Brief Description of the Drawings

[0109] Figure 1 is the flowchart of the present invention;

[0110] Figure 2 is the structural schematic diagram of the integrated energy system;

[0111] Figure 3 is the variable relationship between the variables of the two - layer collaborative planning model;

[0112] Figure 4 is the solution schematic diagram of the two - layer collaborative planning model. Detailed Embodiment

[0113] The present invention will be described in detail below with reference to the drawings and specific embodiments. This embodiment is implemented on the premise of the technical solution of the present invention, and gives the detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0114] Embodiment 1:

[0115] An optimization configuration method for an integrated energy system based on multi - station integration, as Figure 1 shown, includes the following steps:

[0116] S1. Construct an integrated energy system, as Figure 2 shown. The integrated energy system integrates a substation, a data center station, an energy storage station, and a new energy station. In order to meet the electricity, heat, and cooling load demands in the integrated energy system, a certain number of energy conversion equipment, such as heat pumps, chillers, etc., need to be configured. In this step, the energy conversion equipment to be configured in the integrated energy system is obtained, and an energy complementary conversion model for each energy conversion equipment is established.

[0117] S2. Establish a two - layer collaborative planning model, which is used to solve the capacity configuration and operation strategy of energy conversion equipment. The upper - layer model aims to minimize the annual planning total cost of the integrated energy system, and the lower - layer model aims to minimize the daily operation cost of the integrated energy system.

[0118] S4. Determine the constraint conditions for the capacity configuration of energy conversion equipment and the constraint conditions for the operation strategy of energy conversion equipment.

[0119] S7. Formulate the evaluation index for the integrated energy system architecture.

[0120] S5. Solve the two - layer collaborative planning model based on the energy complementary conversion model, constraint conditions, and evaluation index to obtain the capacity configuration and operation strategy of each energy conversion equipment, and obtain the configuration and operation strategy of the final integrated energy system.

[0121] This application unifies the capacity configuration and operation strategy of energy conversion equipment in the integrated energy system with multi - station integration, conducts joint optimization, so as to obtain a reasonable equipment configuration plan and operation strategy. At the same time, the set constraint conditions also ensure the economic, safe, and reliable operation of each equipment in the integrated energy system.

[0122] See Figure 2 , the energy conversion equipment includes heat pumps, electric chillers, absorption chillers, heat storage devices, energy storage devices, and new - energy - station power generation equipment. The new - energy - station power generation equipment includes photovoltaic and wind turbines. The energy storage device in the energy storage station and the wind turbines and photovoltaics in the new - energy station provide part of the electrical energy demand for the energy conversion equipment in the integrated energy system. The heat pump and heat storage device are used to meet the heat load demand, and the electric chiller and absorption chiller meet the cooling load demand. The energy complementary conversion models of various types of energy conversion equipment are as follows:

[0123] (1) The essence of a heat pump is a mechanical device that uses the reverse Carnot cycle driven by energy to make a low - temperature object approach a higher temperature through compression and other methods. According to its thermodynamic input - output characteristics, the energy complementary conversion model of the heat pump is:

[0124]

[0125] Among them, represents the output heat power of the heat pump at time represents the electric power consumed by the heat pump at time t, and ξ hp represents the heating performance coefficient of the heat pump, which is a fixed parameter. Therefore, after obtaining or setting the electric power consumed by the heat pump, input through this energy complementary conversion model, the output heat power

[0126] (2) The electric refrigerating machine can also be called a compression refrigerating machine, which realizes the refrigeration effect by driving the compressor with electricity. The energy complementary conversion model of the electric refrigerating machine is as follows:

[0127]

[0128] Among them, represents the output cooling power of the electric refrigerating machine at time t, represents the electric power consumed by the electric refrigerating machine at time t, and ψ ec represents the refrigeration coefficient of the electric refrigerating machine, which is a fixed parameter; therefore, after obtaining or setting the electric power consumed by the electric refrigerating machine, input through this energy complementary conversion model, the output cooling power of the electric refrigerating machine can be obtained

[0129] (3) The working principle of the absorption refrigerating machine is to absorb the thermal energy of the combined heat and power unit and the gas boiler, and vaporize the liquid refrigerant under high pressure and high temperature after a certain throttling pressure reduction to absorb a large amount of heat in the environment, so that the temperature drops sharply to achieve the refrigeration purpose of the refrigerating machine. The energy complementary conversion model of the absorption refrigerating machine is as follows:

[0130]

[0131] Among them, represents the output cooling power of the absorption refrigerating machine at time t, represents the heat power consumed by the absorption refrigerating machine at time t, and ψ ac represents the refrigeration coefficient of the absorption refrigerating machine, which is a fixed parameter; therefore, after obtaining or setting the heat power consumed by the absorption refrigerating machine, input through this energy complementary conversion model, the output cooling power of the absorption refrigerating machine can be obtained

[0132] (4) The heat storage device, that is, the heat energy storage equipment, has a similar role in the energy hub as the electric energy storage equipment, performs peak shaving and valley filling on the daily heat load, and transfers the heat load across time periods. According to the output characteristics of the heat energy storage equipment, the energy complementary conversion model of the heat storage device is as follows:

[0133]

[0134] Among them, respectively represent the heat storage power and heat release power of the heat storage device at time t, respectively represent the heat storage efficiency and heat release efficiency of the heat storage device, which are fixed parameters, Q h,t+1 、Q h,trespectively represent the reserved thermal energy of the heat storage device at time t + 1 and the reserved thermal energy of the heat storage device at time t. ε represents the self-loss coefficient of the heat storage device, which is a fixed parameter. Δt represents the scheduling time interval. Therefore, after obtaining or setting the heat storage power and heat release power of the heat storage device, input and through this energy complementary conversion model, the reserved thermal energy Q h,t+1 and Q h,t ;

[0135] (5) Energy storage devices such as storage batteries, etc., whose energy complementary conversion model is:

[0136]

[0137] Among them, SOC(t) represents the state of charge of the energy storage device at time t, and δ represents the self-discharge coefficient of the energy storage device, which is a fixed parameter; P CES 、P DES respectively represent the charging power and discharging power of the energy storage device, unit: kW, η CES 、η DES respectively represent the charging efficiency and discharging efficiency of the energy storage device, which are fixed parameters, E soc.st represents the rated capacity of the energy storage device, which is a fixed parameter, unit: kWh, Δt represents the scheduling time interval; Therefore, after obtaining or setting the charging power and discharging power of the energy storage device, input P CES and P DES , through this energy complementary conversion model, the state of charge SOC(t) of the energy storage device can be obtained;

[0138] (6) The energy complementary conversion model of photovoltaic is:

[0139]

[0140] Among them, P pv represents the magnitude of the photovoltaic power generation, unit: kW, P st.max represents the maximum test power of the photovoltaic under standard experimental conditions, which is a fixed parameter, E s represents the light intensity, E s.st represents the light intensity under standard experimental conditions, which is a fixed parameter, k represents the power temperature coefficient, which is a fixed parameter, T o represents the actual temperature of the battery panel, T st represents the temperature of the battery panel under standard experimental conditions, which is a fixed parameter; Therefore, after obtaining or setting the light intensity and the actual temperature of the battery panel, input E s and T o , through this energy complementary conversion model, the photovoltaic power generation P pv ;

[0141] (7) The energy complementary conversion model of the wind turbine is as follows:

[0142]

[0143] Among them, P wt represents the output power of the wind turbine, unit: kW, P r represents the rated power of the wind turbine, which is a fixed parameter, unit: kW, v represents the actual wind speed of the wind turbine unit, unit: m / s, v ci , v co , v r respectively represent the cut-in wind speed, cut-out wind speed and rated wind speed of the wind turbine, which are fixed parameters; therefore, after obtaining or setting the wind speed and inputting v, the output power P of the wind turbine can be obtained through this energy complementary conversion model wt .

[0144] (I) Upper-layer model

[0145] The upper-layer model of the double-layer collaborative planning model aims to minimize the annual planning total cost f of the integrated energy system. The objective function of the upper-layer model is:

[0146] min(f) = min(f1 + f2)

[0147] Among them, f represents the annual planning total cost of the integrated energy system, and f1 and f2 respectively represent the investment cost and operation and maintenance cost.

[0148] Let i = 1, 2, 3, 4, 5, 6, 7 represent the energy conversion equipment as wind turbine, photovoltaic, heat pump, electric chiller, absorption chiller, energy storage device, heat storage device respectively. Then the investment cost f1 is:

[0149]

[0150] Among them, w i represents the set of all energy conversion equipment of type i, C fij represents the initial investment cost of the energy conversion equipment j of type i, which is a fixed quantity, C rij represents the depreciation cost of the energy conversion equipment j of type i, which is a fixed quantity, calculated here as 5% of the investment, R ij represents the capital recovery factor of the energy conversion equipment j of type i, a ij represents the quantity of the energy conversion equipment j of type i, σ ij represents the operating status of the energy conversion equipment j of type i, which is a 0-1 variable, taking values of 0 or 1, 1 for operation and 0 for suspension;

[0151] The expression of the capital recovery factor R ij is as follows:

[0152]

[0153] Among them, r represents the discount rate, and n ij represents the service life of the energy conversion device j of type i;

[0154] Input i, w i , a ij , σ ij , r, n ij , and the investment cost f1 can be obtained;

[0155] The operation seasonal characteristics of the equipment in the integrated energy system are relatively obvious. The heat load is low and the cold load is high in summer, while the cold load is relatively low and the heat load is high in winter. Therefore, the operation and maintenance of the equipment also have obvious seasonal characteristics. Using k = 1, 2, 3, 4 to represent the four seasons of a year respectively, the operation and maintenance cost f2 is:

[0156]

[0157] Among them, C kij represents the operation and maintenance cost of the energy conversion device j of type i in season k, and Num kij represents the number of operation and maintenance days of the energy conversion device j of type i in season k; Input C kij and Num kij and the operation and maintenance cost f2 can be obtained.

[0158] (2) Lower - layer model

[0159] The lower - layer model of the two - layer collaborative planning model aims to minimize the daily operation cost f day of the integrated energy system, mainly considering the power purchase cost, the penalty cost for wind and light abandonment, and the load interruption cost. The objective function of the lower - layer model is:

[0160] min(f day ) = min(f3 + f4 + f5)

[0161] Among them, f day represents the daily operation cost of the integrated energy system, and f3, f4, f5 represent the power purchase cost, the penalty cost for wind and light abandonment, and the load interruption cost respectively.

[0162] In the integrated energy system, the new energy station follows the principle of self - consumption of the generated electricity and selling the surplus electricity to the grid. The power purchase cost f3 is:

[0163] f3 = C buy.t P buy.t -C sell.t P sell.t

[0164] Among them, Cbuy.t Denotes the electricity purchase price of the integrated energy system, which is a fixed parameter, P buy.t Denotes the electricity purchase quantity of the integrated energy system, C sell.t Denotes the on-grid electricity price of the integrated energy system, which is a fixed parameter, P sell.t Denotes the on-grid electricity quantity of the integrated energy system; Input P buy.t and P sell.t The electricity purchase cost f3 can be obtained;

[0165] The penalty cost f4 for curtailment of wind and solar power is:

[0166] f4 = C pv P des1 + C w P des2

[0167] Among them, C pv and C w Denote the penalty cost for curtailment of solar power and the penalty cost for curtailment of wind power respectively, which are fixed parameters, P des1 and P des2 Denote the curtailment quantity of solar power and the curtailment quantity of wind power respectively; Input P des1 and P des2 The penalty cost f4 for curtailment of wind and solar power can be obtained;

[0168] The load interruption cost f5 is:

[0169] f5 = C loss P loss

[0170] Among them, C loss Denotes the unit penalty price when the integrated energy system interrupts the load, which is a fixed parameter, P loss Denotes the magnitude of the load quantity lost when the integrated energy system interrupts the load; Input P loss The load interruption cost f5 can be obtained.

[0171] The lower-layer model aims to minimize the daily operating cost f day of the integrated energy system. In the lower-layer model, the renewable energy consumption of the new energy station and the improvement of the power supply reliability of the system are mainly considered. The penalty cost for curtailment of wind and solar power and the penalty cost for load shedding are introduced to ensure the stable operation of the system while improving the economy.

[0172] The variable relationship between the variables of the two-layer collaborative planning model is as Figure 3 shown. The upper-layer model aims to minimize the annual planning total cost and studies issues such as the type, quantity, and capacity of energy conversion equipment in the integrated energy system. The lower-layer model aims to minimize the daily operating cost of the integrated energy system and formulates the output scheme of each energy conversion equipment.

[0173] (A) Constraints on capacity configuration

[0174] Let \(i = 1, 2, 3, 4\) represent the heat pump, heat storage device, electric chiller, and absorption chiller for the energy conversion equipment respectively. Then the constraint conditions for the capacity configuration of the energy conversion equipment are as follows:

[0175]

[0176] Among them, \(X\) ij represents the capacity of the energy conversion equipment \(j\) of type \(i\), which is a fixed quantity. \(\eta\) ij represents the heat storage efficiency or heat release efficiency of the energy conversion equipment \(j\) of type \(i\). \(a\) ij represents the number of the energy conversion equipment \(j\) of type \(i\). \(\sigma\) ij represents the operating status of the energy conversion equipment \(j\) of type \(i\), which is a 0 - 1 variable with values of 0 or 1. and respectively represent the maximum heat load and maximum cold load of the integrated energy system, both of which are fixed quantities.

[0177] (B) Constraint conditions of the operation strategy

[0178] The constraint conditions of the operation strategy of the energy conversion equipment include power balance constraint conditions, heat balance constraint conditions, cold balance constraint conditions, transmission line power constraint conditions, new energy station operation constraint conditions, energy storage device operation constraint conditions, heat pump operation constraint conditions, electric chiller operation constraint conditions, absorption chiller constraint conditions, and heat storage device operation constraint conditions;

[0179] (1) The power balance constraint condition is:

[0180]

[0181] \(P\) net.t \(= P\) buy.t - P sell.t

[0182] Among them, \(P\) net.t represents the interactive power between the integrated energy system and the superior power grid at time \(t\), with the unit of kW, which is related to the power purchase quantity \(P\) buy.t and the power grid connection quantity \(P\) sell.t of the integrated energy system. When the value of \(P\) net.t is greater than zero, it means that the integrated energy system needs to purchase electricity. When the value of \(P\) net.t is less than zero, it means that the excess electricity of the integrated energy system is fed into the grid. \(P\) DEs.t represents the discharge power of the energy storage device at time \(t\), with the unit of kW. \(P\) pv.t represents the power generation of the photovoltaic at time \(t\), with the unit of kW. \(P\) wt.t represents the power generation of the wind turbine at time \(t\), with the unit of kW. \(P\) CES.tRepresents the charging power of the energy storage device at time t, in kW, P SL.t Is an adjustable variable in the constraint conditions, in kW, representing the electrical power consumed by the integrated energy system at time t, and representing the electricity consumption of the entire integrated energy system except for the controllable energy conversion equipment Represents the electrical power consumed by the electric chiller at time t, in kW Represents the electrical power consumed by the heat pump at time t, in kW

[0183] (2) The heat balance constraint condition is:

[0184]

[0185] Among them, Represents the output heat power of the heat pump at time t, in kW, Q h,t Represents the reserved heat energy of the heat storage device at time t, in kW, H t Represents the magnitude of the heat load power of the integrated energy system, in kW, and is an adjustable variable in the constraint conditions

[0186] (3) The cold balance constraint condition is:

[0187]

[0188] Among them, Represents the output cold power of the electric chiller at time t, in kW Represents the output cold power of the absorption chiller at time t, in kW, C L,t Represents the magnitude of the cold load power of the integrated energy system at time t, in kW, and is an adjustable variable in the constraint conditions

[0189] (4) The transmission line power constraint condition is:

[0190] P net.t <P max

[0191] Among them, P net.t Represents the interaction power between the integrated energy system and the superior power grid at time t, in kW, P max Represents the maximum power magnitude that the integrated energy system is allowed to purchase electricity from the power grid at time t, in kW, and is a fixed value

[0192] (5) The operation constraint condition of the new energy station is:

[0193]

[0194] Among them, P pvmax And P wmax Respectively represent the maximum power generation of the photovoltaic and wind turbines, in kW, and are fixed values, Ppv. Represents the power generation power of the photovoltaic at time t, with the unit of kW, P wt.t Represents the power generation power of the wind turbine at time t; with the unit of kW

[0195] (6) The operation constraints of the energy storage station need to consider the operation constraints of multiple time periods, mainly including: constraints such as charge-discharge status and the magnitude of charge-discharge quantity

[0196] Charge-discharge state constraint:

[0197] x DES +x CES ≤1

[0198] Charge-discharge power constraint:

[0199]

[0200]

[0201] Capacity constraint:

[0202]

[0203] E soc.末 =E soc.初

[0204] Among them, x DES Represents the discharge state of the energy storage device, x CES Represents the charge state of the energy storage device. Both are 0-1 variables, taking values of 0 or 1 (where 1 represents the working state and 0 represents the non-working state), P DES.t Represents the discharge power of the energy storage device at time t, P CES.t Represents the charge power of the energy storage device at time t, E soc.t Represents the stored electricity of the energy storage device at time t Respectively represent the minimum discharge power, maximum discharge power, minimum charge power and maximum charge power of the energy storage device And Respectively represent the maximum stored electricity and minimum stored electricity of the energy storage device, E soc.末 And E soc.初 Respectively represent the stored electricity at the initial moment and the stored electricity at the end moment of each day of the energy storage device; the constraint condition E soc.末 =E soc.初 Indicates that the stored electricity values at the end moment and the initial moment of the energy storage device should be kept equal. The electricity in the energy storage device such as a battery is variable. Taking one day as the scheduling period, the start time of scheduling at 00:00 is the initial battery power, and the end time at 00:00 at night is the power at the end of the day. These two values need to be kept consistent

[0205] (7) The operation constraint conditions of the heat pump are:

[0206]

[0207] Among them, represents the output heat power of the heat pump at time t, with the unit of kW, represents the maximum output heat power of the heat pump, with the unit of kW;

[0208] (8) The operating constraint conditions of the electric refrigerating machine are:

[0209]

[0210] Among them, represents the output cooling power of the electric refrigerating machine at time t, with the unit of kW, represents the maximum output cooling power of the electric refrigerating machine, with the unit of kW;

[0211] (9) The constraint conditions of the absorption refrigerating machine are:

[0212]

[0213] Among them, represents the output cooling power of the absorption refrigerating machine at time t, with the unit of kW, represents the maximum output cooling power of the absorption refrigerating machine, with the unit of kW;

[0214] (10) The operating constraint conditions of the heat storage device include charge-discharge state constraint, charge-discharge power magnitude constraint, and capacity constraint. Among them, the charge-discharge state constraint:

[0215] y dis +y ch ≤1

[0216] The charge-discharge power magnitude constraint:

[0217]

[0218]

[0219] The capacity constraint:

[0220]

[0221] Q h.末 =Q h.初

[0222] y dis represents the heat release state of the heat storage device, and y ch represents the heat storage state of the heat storage device. Both are 0-1 variables, and the values are 0 or 1 (where 1 represents the working state and 0 represents the non-working state), respectively represent the heat storage power and heat release power of the heat storage device at time t, and Q h,t represents the reserved thermal energy of the heat storage device at time t, represent the minimum heat release power, maximum heat release power, minimum heat storage power and maximum heat storage power of the heat storage device, and represent the minimum reserved thermal energy and maximum reserved thermal energy of the heat storage device, Q h.末 and Q h.初 respectively represent the stored thermal energy at the initial moment and the stored thermal energy at the end moment of each day of the heat storage device; the constraint condition Q h.末 =Q h.初 means that the reserved thermal energy values of the heat storage device at the end moment and the initial moment should be equal.

[0223] The evaluation indexes include the renewable energy utilization rate, load absorption rate, system load shedding rate and carbon emission;

[0224] Score1, renewable energy utilization rate

[0225] Renewable energy utilization rate = (total power generation of new energy stations - discarded light - discarded wind) / total power generation of new energy stations;

[0226] Score2, load absorption rate

[0227] Load absorption rate = power generation of new energy stations absorbed by the integrated energy system / total power generation of new energy stations;

[0228] Score3, system load shedding rate

[0229] System load shedding rate = total system load shedding amount / total station load amount of the integrated energy system;

[0230] Score4, carbon emission

[0231] Carbon emission = carbon emission coefficient * (total power purchase amount of the integrated energy system - total power sale amount of new energy stations). In this embodiment, the carbon emission coefficient is taken as 0.889.

[0232] As Figure 4 shown, the decision variables of the upper layer model are the number and capacity of energy conversion devices, which contain 0-1 variables and belong to a mixed integer nonlinear programming model. The differential evolution algorithm is used to solve the upper layer model to obtain the number and capacity of energy conversion devices; the lower layer model optimizes the operation strategy of the integrated energy system, that is, the operation output scheme of each energy conversion device, which belongs to linear programming. The CPLEX linear solver is used to solve the lower layer model to obtain the operation output scheme of each energy conversion device.

[0233] Specifically, variables are first set, including device model capacity, system load, price parameters, etc., the time-of-use electricity price is determined, and multiple solutions that meet the constraints are initialized to generate an initial population. Based on the generated initial solutions, they are substituted into the energy complementary conversion models of various energy conversion devices, and the two-layer collaborative planning model is solved to obtain a solution. The evaluation index of the solution is calculated. If the requirements are not met, mutation, crossover, and greedy selection operations are performed on the population to obtain the next generation population. If the solution meets the requirements, it is output to obtain the final configuration plan and operation strategy of the integrated energy system.

[0234] The present application provides an optimization configuration method for an integrated energy system based on multi-station integration. The method establishes a new two-layer optimization configuration model, enabling the integrated energy system to have the best operation mode under optimal configuration, maximizing the consumption of new energy power generation while ensuring the economy of the integrated energy system, improving power supply reliability, and ensuring the power quality and power supply capacity of the integrated energy system, especially the data center station.

[0235] The preferred specific embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art can make many modifications and variations according to the concept of the present invention without creative labor. Therefore, all technical solutions that can be obtained by those skilled in the art in the technical field based on the concept of the present invention through logical analysis, reasoning, or limited experiments on the basis of the prior art should be within the protection scope determined by the claims.

Claims

1. An optimal configuration method for an integrated energy system based on multi-station integration, characterized in that, It includes the following steps: Construct a comprehensive energy system that integrates a substation, a data center station, an energy storage station, and a new energy station, obtain the energy conversion equipment to be configured in the comprehensive energy system, and establish an energy complementary conversion model for each energy conversion equipment; Establish a two-layer collaborative planning model, which is used to solve the capacity configuration and operation strategy of the energy conversion equipment; Determine the constraint conditions for the capacity configuration of the energy conversion equipment and the constraint conditions for the operation strategy of the energy conversion equipment; Formulate evaluation indicators for the comprehensive energy system architecture; Solve the two-layer collaborative planning model based on the energy complementary conversion model, constraint conditions, and evaluation indicators to obtain the capacity configuration and operation strategy of each energy conversion equipment, and obtain the configuration and operation strategy of the final comprehensive energy system; The energy conversion equipment includes a heat pump, an electric chiller, an absorption chiller, a heat storage device, an energy storage device, and new energy station power generation equipment. The new energy station power generation equipment includes photovoltaic and wind turbines, and their energy complementary conversion models are respectively: The energy complementary conversion model of the heat pump is: Among them, represents the output heat power of the heat pump at time t, represents the electric power consumed by the heat pump at time t, ξ hp represents the coefficient of performance of the heat pump for heating; The energy complementary conversion model of the electric chiller is: Among them, represents the output cooling power of the electric refrigerator at time t, represents the electric power consumed by the electric refrigerator at time t, ψ ec represents the coefficient of performance of the electric refrigerator; The energy complementary conversion model of the absorption chiller is: Among them, represents the output cooling power of the absorption chiller at time t, represents the heat power consumed by the absorption chiller at time t, and ψ ac represents the coefficient of performance of the absorption chiller; The energy complementary conversion model of the heat storage device is: Among them, respectively represent the heat storage power and heat release power of the heat storage device at time t, respectively represent the heat storage efficiency and heat release efficiency of the heat storage device, Q h,t+1 、Q h,t respectively represent the reserved heat energy of the heat storage device at time t + 1 and the reserved heat energy of the heat storage device at time t, ε represents the self-loss coefficient of the heat storage device, and Δt represents the scheduling time period interval; The energy complementary conversion model of the energy storage device is: Among them, SOC(t) represents the state of charge of the energy storage device at time t, and δ represents the self-discharge coefficient of the energy storage device; P CES and P DES represent the charging power and discharging power of the energy storage device respectively, η CES and η DES represent the charging efficiency and discharging efficiency of the energy storage device respectively, E soc.st represents the rated capacity of the energy storage device, and Δt represents the scheduling time period interval; The energy complementary conversion model of the photovoltaic is: Among them, P pv represents the magnitude of the photovoltaic power generation, and P st.max represents the maximum test power of the photovoltaic under standard test conditions. E s represents the light intensity, and E s.st represents the light intensity under standard test conditions. k represents the power temperature coefficient, and T o represents the actual temperature of the solar panel, and T st represents the temperature of the solar panel under standard test conditions; The energy complementary conversion model of the wind turbine is: Among them, P wt represents the output power of the wind turbine, and P r represents the rated power of the wind turbine. v represents the actual wind speed of the wind power generation set, and v ci , v co , v r represent the cut-in wind speed, cut-out wind speed and rated wind speed of the wind turbine, respectively.

2. The optimization configuration method of an integrated energy system based on multi-station integration according to claim 1, wherein The upper layer model of the two-layer collaborative planning model aims to minimize the annual planning total cost f of the comprehensive energy system. The objective function of the upper layer model is: min(f) = min(f1 + f2) Where f represents the annual planning total cost of the comprehensive energy system, and f1 and f2 represent the investment cost and operation and maintenance cost respectively.

3. The optimization configuration method of an integrated energy system based on multi-station integration according to claim 2, wherein Use i = 1, 2, 3, 4, 5, 6, 7 to represent the energy conversion equipment as wind turbine, photovoltaic, heat pump, electric chiller, absorption chiller, energy storage device, and heat storage device respectively. Then the investment cost f1 is: Among them, w i represents the set of all energy conversion devices of type i, where i fij represents the initial investment cost of energy conversion device j of type i, C rij represents the depreciation cost of energy conversion device j of type i, R ij represents the capital recovery factor of energy conversion device j of type i, a ij represents the number of energy conversion devices j of type i, σ ij represents the operating status of energy conversion device j of type i, taking values of 0 or 1; Capital recovery factor R ij The expression is as follows: where r represents the discount rate, and n ij represents the service life of the energy conversion device j of type i; Use k = 1, 2, 3, 4 to represent the four seasons of a year. Then the operation and maintenance cost f2 is: Among them, C kij represents the operation and maintenance cost of the energy conversion device j of type i in season k, and Num kij represents the number of days of operation and maintenance of the energy conversion device j of type i in season k.

4. A method for optimizing the configuration of an integrated energy system based on multi-station integration according to claim 1, wherein, The lower-layer model of the double-layer collaborative planning model aims to minimize the daily operating cost f of the integrated energy system day The objective function of the lower-layer model is as follows: min(f day ) = min(f3 + f4 + f5) Among them, f day represents the daily operating cost of the integrated energy system, and f3, f4, and f5 respectively represent the electricity purchase cost, the penalty cost for wind and photovoltaic curtailment, and the load interruption cost.

5. The optimization configuration method of an integrated energy system based on multi-station integration according to claim 4, characterized in that The electricity purchase cost f3 is: f3 = C buy.t P buy.t -C sell.t P sell.t Among them, C buy.t represents the electricity purchase price of the integrated energy system, and P buy.t represents the electricity purchase quantity of the integrated energy system. C sell.t represents the on-grid electricity price of the integrated energy system, and P sell.t represents the on-grid electricity quantity of the integrated energy system; The penalty cost f4 for wind and light abandonment is: f4 = C pv P des1 + C w P des2 Among them, C pv and C w represent the curtailment-of-solar-penalty cost and the curtailment-of-wind-penalty cost respectively, and P des1 and P des2 represent the curtailment-of-solar amount and the curtailment-of-wind amount respectively; The load interruption cost f5 is: f5 = C loss P loss Among them, C loss represents the unit penalty price suffered by the integrated energy system during interrupted load, and P loss represents the magnitude of the load loss of the integrated energy system during interrupted load.

6. The optimization configuration method of an integrated energy system based on multi-station integration according to claim 1, wherein Use i = 1, 2, 3, 4 to represent the energy conversion equipment as heat pump, heat storage device, electric chiller, and absorption chiller respectively. Then the constraint conditions for the capacity configuration of the energy conversion equipment are: Among them, X ij represents the capacity of the energy conversion device j of type i, η ij represents the heat storage efficiency or heat release efficiency of the energy conversion device j of type i, a ij represents the number of energy conversion devices j of type i, σ ij represents the operating status of the energy conversion device j of type i, with a value of 0 or 1, and respectively represent the maximum heat load and the maximum cooling load of the integrated energy system.

7. A method for optimizing the configuration of an integrated energy system based on multi-station integration according to claim 1, characterized in that, The constraint conditions for the operation strategy of the energy conversion equipment include power balance constraint conditions, heat balance constraint conditions, cold balance constraint conditions, transmission line power constraint conditions, new energy station operation constraint conditions, energy storage device operation constraint conditions, heat pump operation constraint conditions, electric chiller operation constraint conditions, absorption chiller constraint conditions, and heat storage device operation constraint conditions; The power balance constraint condition is: P net.t = P buy.t - P sell.t Among them, P net.t represents the interactive power between the integrated energy system and the superior power grid at time t, P buy.t represents the electricity purchase quantity of the integrated energy system, P sell.t the electricity generation quantity fed into the grid by the integrated energy system, P DES.t represents the discharge power of the energy storage device at time t, P pv.t represents the power generation power of the photovoltaic at time t, P wt.t represents the power generation power of the wind turbine at time t, P CES.t represents the charging power of the energy storage device at time t, P SL.t represents the electric power consumed by the integrated energy system at time t, represents the electric power consumed by the electric chiller at time t, represents the electric power consumed by the heat pump at time t; The heat balance constraint condition is: Among them, H t represents the magnitude of the thermal load power of the integrated energy system; The cold balance constraint condition is: Among them, C L,t represents the magnitude of the cooling load power of the integrated energy system at time t; The transmission line power constraint condition is: P net.t <P max Among them, P max represents the maximum power that the integrated energy system is allowed to purchase from the power grid at time t; The new energy station operation constraint condition is: Among them, P pvmax and P wmax respectively represent the maximum power generation of the photovoltaic and wind turbine generators; The energy storage device operation constraint condition is: Among them, x DES represents the discharge state of the energy storage device, with a value of 0 or 1, x CES represents the charge state of the energy storage device, with a value of 0 or 1, E soc.t represents the stored electricity of the energy storage device at time t, respectively represent the minimum discharge power, maximum discharge power, minimum charge power and maximum charge power of the energy storage device, and respectively represent the maximum stored electricity and minimum stored electricity of the energy storage device, E soc.末 and E soc.初 respectively represent the stored electricity of the energy storage device at the initial moment and the end moment of each day; The heat pump operation constraint condition is: Among them, represents the maximum output heat power of the heat pump; The electric chiller operation constraint condition is: Among them, represents the maximum output cooling power of the electric refrigerating machine; The absorption chiller constraint condition is: Among them, represents the maximum output cooling power of the absorption chiller; The heat storage device operation constraint condition is: y dis Indicates the heat release state of the heat storage device, with values of 0 or 1, y ch Indicates the heat storage state of the heat storage device, with values of 0 or 1, Indicates the minimum heat release power, maximum heat release power, minimum heat storage power, and maximum heat storage power of the heat storage device, and Indicates the minimum reserve heat energy and maximum reserve heat energy of the heat storage device, Q h.末 and Q h.初 respectively indicate the stored heat energy at the initial moment and the stored heat energy at the end moment of each day of the heat storage device.

8. A method for optimizing the configuration of an integrated energy system based on multi-station integration according to claim 1, characterized in that The evaluation indicators include the renewable energy utilization rate, the load accommodation rate, the system load shedding rate, and the carbon emission; The calculation formula for the utilization rate of renewable energy is as follows: Utilization rate of renewable energy = (total power generation of new energy station - light curtailment - wind curtailment) / total power generation of new energy station; The calculation formula for the load accommodation rate is as follows: Load accommodation rate = power generation of new energy station accommodated by integrated energy system / total power generation of new energy station; The calculation formula for the system load shedding rate is as follows: System load shedding rate = total system load shedding amount / total station load amount of integrated energy system; The calculation formula for the carbon emissions is as follows: Carbon emissions = carbon emission factor * (total power purchase amount of integrated energy system - total power sales amount of new energy station).

9. A method for optimizing the configuration of an integrated energy system based on multi-station integration according to claim 1, characterized in that, The differential evolution algorithm is used to solve the upper-layer model to obtain the quantity and capacity of energy conversion equipment, and the CPLEX linear solver is used to solve the lower-layer model to obtain the operation output schemes of each energy conversion equipment.

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