A distributed electric-thermal integrated energy system modeling method considering electric-thermal synergistic operation characteristics

Abstract

The application discloses a kind of distributed electric heating comprehensive energy system modeling methods considering electric heating collaborative operation characteristics.The method steps are as follows: first, determine the energy input, energy output and internal energy flow path of distributed electric heating comprehensive energy system;Then, based on the concept of energy hub, the distributed electric heating comprehensive energy system is decoupled into energy conversion unit, energy storage unit and energy transmission unit;Then, energy conversion unit mathematical model, energy storage unit mathematical model and energy transmission unit mathematical model are respectively constructed;Finally, the above three mathematical models are solved to obtain the distributed electric heating comprehensive energy system operation characteristic model.The present application can accurately describe the collaborative conversion and dynamic evolution characteristics of electric and thermal energy flow by establishing a detailed mathematical model, providing a high-precision model basis for capacity planning and optimal operation of distributed electric heating system.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy system planning technology, specifically relating to a modeling method for a distributed integrated energy system that considers the characteristics of electrothermal synergistic operation. Background Technology

[0002] Distributed integrated energy systems have attracted much attention due to their ability to achieve cascaded energy utilization and efficient absorption of renewable energy. Especially in northern heating regions or industrial parks, electricity and heat are the two primary end-use energy sources, tightly coupled through key equipment such as combined heat and power (CHP) units and electric heat pumps. To achieve the scientific planning and optimized operation of such systems, establishing a mathematical model that accurately reflects the internal physical processes and operational characteristics is a prerequisite.

[0003] However, existing integrated energy system modeling methods face numerous challenges when dealing with distributed electrothermal systems. On the one hand, traditional energy hub models mostly use constant conversion efficiency to describe equipment characteristics, neglecting the efficiency degradation of equipment such as gas turbines at partial load rates, as well as the actual operating characteristics of renewable energy sources such as photovoltaics and wind power affected by the nonlinearity of ambient temperature and wind speed. This leads to significant deviations between simulation results and actual operating conditions. On the other hand, existing models often attempt to encompass all energy forms, including cooling, heating, electricity, and gas, resulting in overly complex structures. For scenarios focusing solely on electrothermal synergy, this not only increases the computational burden but also fails to highlight the key characteristics of electrothermal coupling.

[0004] Therefore, there is an urgent need for a refined modeling method for the characteristics of distributed electric heating systems. This method should be able to standardize and decouple the conversion, storage and transmission links of the system based on the energy hub architecture, and focus on the variable operating conditions and environmental sensitivity of key equipment, so as to provide high-precision model support for system capacity configuration, operation scheduling and benefit evaluation. Summary of the Invention

[0005] The purpose of this invention is to provide a modeling method for a distributed electric-thermal integrated energy system that considers the characteristics of electric and thermal synergistic operation. By abstracting the complex physical system into three standard modules of conversion, storage, and transmission, a refined mathematical model is established, which can accurately describe the synergistic conversion and dynamic evolution characteristics of electric and thermal energy flows. This provides a high-precision model foundation for the capacity planning and optimized operation of distributed electric-thermal systems, facilitating subsequent system planning and optimized scheduling.

[0006] This invention is achieved through the following technical solution: A modeling method for a distributed integrated energy system considering the characteristics of electrothermal synergy includes the following steps: Step S1: Determine the energy input, energy output, and internal energy flow path of the distributed electric heating integrated energy system; Step S2: Based on the concept of energy hub, the distributed electrothermal integrated energy system is decoupled into three functional modules: energy conversion unit, energy storage unit, and energy transmission unit. Step S3: Construct a mathematical model of the energy conversion unit and establish a nonlinear or linear coupling conversion relationship between input energy and output energy; Step S4: Construct a mathematical model of the energy storage unit, and establish the dynamic equation of the energy storage state over time and the constraints on charging and discharging power. Step S5: Construct a mathematical model of the energy transmission unit and establish power balance equations for the electrical power bus and thermal power bus based on the law of conservation of energy. Step S6: Combine the mathematical models of the above three functional modules to obtain the operating characteristic model of the distributed electric and thermal integrated energy system.

[0007] In the above technical solution, further, in step S1: Energy inputs include natural gas supplied by pipeline networks, electricity supplied by the upstream power grid, and solar and wind energy resources in the environment; Energy output includes electrical load and thermal load to meet user needs; The energy flow paths within the system include the conversion path from natural gas to electricity / heat, the conversion path from electricity to heat, and the storage path for electricity / heat.

[0008] Furthermore, in step S2: The energy conversion unit includes a gas turbine, an electric heat pump, a photovoltaic system, and a wind turbine, and is responsible for converting the input energy into the intermediate or final energy form required by the system. The energy storage unit includes electrical energy storage and thermal storage devices, which are responsible for the translation of energy over time and smoothing out supply and demand fluctuations. The energy transmission unit includes an electric bus and a thermal bus, which are responsible for the distribution and balance of energy in the spatial dimension.

[0009] In step S3, the energy conversion unit includes a gas-fired combined heat and power unit, an electric heat pump unit, a photovoltaic generator unit, and a wind turbine generator unit. The mathematical model of the energy conversion unit is constructed, specifically including: (1) Gas-fired cogeneration unit Gas-fired combined heat and power (CHP) units are modeled as back-pressure units. Their mathematical model describes the relationship between fuel input power and unit operating conditions, output electrical power, and thermal power. Specifically: The following constraints must be satisfied simultaneously: In the formula, Fuel input power (kW); Indicates time; This is a Boolean variable, where 0 indicates that the unit is in a stopped state and 1 indicates that the unit is in a running state. and These are the electrical power (kW) and thermal power (kW) output by the unit, respectively. Energy loss coefficient (%) and These are the maximum and minimum values ​​(kW) of the unit's output electrical power, respectively. and The electrical efficiency (%) is the power output of the unit when it reaches its maximum and minimum values, respectively. and These are the fuel input loss power (kW) and the percentage of loss power relative to the fuel input power (%), respectively. and All are unit efficiency coefficients.

[0010] (2) Electric heat pump unit Electric heat pump units are used to convert low-grade heat energy into high-grade heat energy. Their mathematical model is as follows: In the formula, The heating capacity (kW) of the electric heat pump unit; The electrical power (kW) input to the electric heat pump unit; The energy efficiency coefficient of the electric heat pump unit; and These are the lower limit (kW) and upper limit (kW) of the heating capacity of the electric heat pump unit, respectively.

[0011] (3) Photovoltaic generator set The output power of a photovoltaic (PV) generator set is determined by the rated power of the unit, and is also affected by solar radiation intensity and temperature. The mathematical model of a PV generator set is as follows: In the formula, and These are the real-time power generation (kW) and rated power (kW) of the photovoltaic unit, respectively. The performance coefficient of the photovoltaic unit; and These are the hourly average values ​​of solar radiation intensity (W / m²). 2 ) and solar radiation intensity under standard conditions (usually taken as 1000 W / m²) 2 ); The power temperature coefficient of the photovoltaic unit (usually taken as -0.35 % / °C); and These are the operating temperature (°C) of the photovoltaic panel and the reference temperature under standard operating conditions (usually 25 °C).

[0012] (4) Wind turbine generator set The wind turbine generator model is described using a piecewise third-order polynomial, as follows: In the formula, and These are the real-time power generation (kW) and rated power (kW) of the wind turbine, respectively. , , These are the rated wind speed (m / s), cut-in wind speed (m / s), and cut-out wind speed (m / s) of the wind turbine unit, respectively. The wind speed is the hourly average (m / s).

[0013] In step S4, the mathematical model of the energy storage unit is described using discrete-time energy state equations, specifically including: (1) Electric energy storage unit The state of charge (SOC) of an energy storage unit determines its ability to absorb or supply electrical energy. At any given moment, the SOC of the energy storage unit is determined by the SOC of the previous moment and the amount of charge / discharge. Moreover, the SOC value needs to be limited to a certain range. The specific mathematical model of the energy storage unit is shown below: In the formula, and They are time points and State of charge (%) of the energy storage unit under the following conditions; Self-discharge coefficient (%) The unit time step (h); The rated energy storage capacity (kWh) of the energy storage unit. and The charging efficiency (%) and discharging efficiency (%) of the energy storage unit are respectively. and These represent the lower (%) and upper (%) of the state of charge of the energy storage unit, respectively. Power capacity conversion factor (kW / kWh) of electric energy storage units. and These are the charging power (kW) and discharging power (kW) of the energy storage unit, respectively. This refers to the rated power (kW) of the energy storage unit.

[0014] (2) Thermal storage unit The mathematical model of the storage unit can be described as follows: In the formula, and These are the thermal storage power (kW) and heat release power (kW) of the thermal storage unit, respectively. The rated power (kW) of the thermal storage unit; and They are time points and The energy storage status (%) of the thermal storage unit; The self-discharge coefficient (%) of the thermal storage unit; The unit time step (h); The rated energy storage capacity of the thermal energy storage unit (kWh); and The values ​​are the thermal storage efficiency (%) and the heat release efficiency (%) of the thermal storage unit, respectively. and These represent the lower limit (%) and upper limit (%) of the energy storage status of the thermal energy storage unit, respectively. This is the power capacity conversion factor (kW / kWh) for the thermal storage unit.

[0015] Furthermore, in step S5, the mathematical model of the energy transmission unit adopts a lossless bus model, which follows the following power balance constraints: In the formula, and These are the power values ​​(kW) of the energy flow into and out of the power bus, respectively. and These are the power values ​​(kW) of the energy flow into and out of the heat bus, respectively.

[0016] Step S6 specifically includes: (1) Combine the model equations of the energy conversion unit, energy storage unit and energy transmission unit to construct a discrete-time difference equation system; (2) Integrate the operating constraints of all units, including the upper and lower limits of output of each unit, the ramp rate constraint, the state of charge constraint of the energy storage device, and the power constraint of interaction with the external power grid.

[0017] The above set of equations and constraints serve as the mathematical basis for system simulation or optimization. They are input into the solver for calculation to obtain the system's operating state or optimal scheduling strategy under specific boundary conditions.

[0018] The beneficial effects of this invention are as follows: Compared with existing technologies, this invention significantly improves the theoretical accuracy and simulation reliability of distributed electrothermal integrated energy system modeling. Existing technologies often use constant conversion efficiency to describe equipment characteristics, neglecting performance degradation and environmental interference under complex operating conditions, leading to model distortion under partial load or extreme weather conditions. This invention, by constructing a refined mathematical model, introduces variable operating condition characteristics into the energy conversion unit, establishes a nonlinear coupling relationship based on the back-pressure unit characteristics for gas-fired cogeneration units, and finely characterizes the dynamic output characteristics of photovoltaic and wind turbine units as temperature, radiation, and wind speed change. This approach can more realistically reflect the actual energy consumption level and operating boundaries of the system under different load rates.

[0019] This invention enhances the coordinated response capability of electrothermal energy flow in the spatiotemporal dimensions by simultaneously establishing a set of discrete-time difference equations. The dynamic equations of the energy storage unit established in the model accurately define the evolution of the charged / heated state over time and the charging / discharging power constraints, realizing the translation and peak shaving of energy in the time dimension. This allows the model to deeply explore the peak-shaving potential of thermal inertia in distributed systems and quantitatively analyze the system flexibility under electrothermal coordinated operation, thus providing high-precision theoretical support for improving the renewable energy absorption rate and formulating optimal scheduling strategies. Attached Figure Description

[0020] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0021] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. This description is intended to explain the invention and not limit it. This invention discloses a modeling method for a distributed integrated electric and thermal energy system that considers the characteristics of electric and thermal synergistic operation, such as... Figure 1 This includes the following steps: Step S1: Determine the energy input, energy output, and internal energy flow path of the distributed electric heating integrated energy system; Step S2: Based on the concept of energy hub, the distributed electrothermal integrated energy system is decoupled into three functional modules: energy conversion unit, energy storage unit, and energy transmission unit. Step S3: Construct a mathematical model of the energy conversion unit and establish a nonlinear or linear coupling conversion relationship between input energy and output energy; Step S4: Construct a mathematical model of the energy storage unit, and establish the dynamic equation of the energy storage state over time and the constraints on charging and discharging power. Step S5: Construct a mathematical model of the energy transmission unit and establish power balance equations for the electrical power bus and thermal power bus based on the law of conservation of energy. Step S6: Combine the mathematical models of the above three functional modules to obtain the operating characteristic model of the distributed electric and thermal integrated energy system.

[0022] In step S1: Energy inputs include natural gas supplied by pipeline networks, electricity supplied by the upstream power grid, and solar and wind energy resources in the environment; Energy output includes electrical load and thermal load to meet user needs; The energy flow paths within the system include the conversion path from natural gas to electricity / heat, the conversion path from electricity to heat, and the storage path for electricity / heat.

[0023] In step S2: The energy conversion unit includes a gas turbine, an electric heat pump, a photovoltaic system, and a wind turbine, and is responsible for converting the input energy into the intermediate or final energy form required by the system. The energy storage unit includes electrical energy storage and thermal storage devices, which are responsible for the translation of energy over time and smoothing out supply and demand fluctuations. The energy transmission unit includes an electric bus and a thermal bus, which are responsible for the distribution and balance of energy in the spatial dimension.

[0024] In step S3, the energy conversion unit includes a gas-fired combined heat and power unit, an electric heat pump unit, a photovoltaic generator unit, and a wind turbine generator unit. The mathematical model of the energy conversion unit is constructed, specifically including: (1) Gas-fired cogeneration unit Gas-fired combined heat and power (CHP) units are modeled as back-pressure units. Their mathematical model describes the relationship between fuel input power and unit operating conditions, output electrical power, and thermal power. Specifically: The following constraints must be satisfied simultaneously: In the formula, Fuel input power (kW); Indicates time; This is a Boolean variable, where 0 indicates that the unit is in a stopped state and 1 indicates that the unit is in a running state. and These are the electrical power (kW) and thermal power (kW) output by the unit, respectively. Energy loss coefficient (%) and These are the maximum and minimum values ​​(kW) of the unit's output electrical power, respectively. and The electrical efficiency (%) is the power output of the unit when it reaches its maximum and minimum values, respectively. and These are the fuel input loss power (kW) and the percentage of loss power relative to the fuel input power (%), respectively. and All are unit efficiency coefficients.

[0025] (2) Electric heat pump unit Electric heat pump units are used to convert low-grade heat energy into high-grade heat energy. Their mathematical model is as follows: In the formula, The heating capacity (kW) of the electric heat pump unit; The electrical power (kW) input to the electric heat pump unit; The energy efficiency coefficient of the electric heat pump unit; and These are the lower limit (kW) and upper limit (kW) of the heating capacity of the electric heat pump unit, respectively.

[0026] (3) Photovoltaic generator set The output power of a photovoltaic (PV) generator set is determined by the rated power of the unit, and is also affected by solar radiation intensity and temperature. The mathematical model of a PV generator set is as follows: In the formula, and These are the real-time power generation (kW) and rated power (kW) of the photovoltaic unit, respectively. The performance coefficient of the photovoltaic unit; and These are the hourly average values ​​of solar radiation intensity (W / m²). 2 ) and solar radiation intensity under standard conditions (usually taken as 1000 W / m²) 2 ); The power temperature coefficient of the photovoltaic unit (usually taken as -0.35 % / °C); and These are the operating temperature (°C) of the photovoltaic panel and the reference temperature under standard operating conditions (usually 25 °C).

[0027] (4) Wind turbine generator set The wind turbine generator model is described using a piecewise third-order polynomial, as follows: In the formula, and These are the real-time power generation (kW) and rated power (kW) of the wind turbine, respectively. , , These are the rated wind speed (m / s), cut-in wind speed (m / s), and cut-out wind speed (m / s) of the wind turbine unit, respectively. The wind speed is the hourly average (m / s).

[0028] In step S4, the mathematical model of the energy storage unit is described using discrete-time energy state equations, specifically including: (1) Electric energy storage unit The state of charge (SOC) of an energy storage unit determines its ability to absorb or supply electrical energy. At any given moment, the SOC of the energy storage unit is determined by the SOC of the previous moment and the amount of charge / discharge. Moreover, the SOC value needs to be limited to a certain range. The specific mathematical model of the energy storage unit is shown below: In the formula, and They are time points and State of charge (%) of the energy storage unit under the following conditions; Self-discharge coefficient (%) The unit time step (h); The rated energy storage capacity (kWh) of the energy storage unit. and The charging efficiency (%) and discharging efficiency (%) of the energy storage unit are respectively. and These represent the lower (%) and upper (%) of the state of charge of the energy storage unit, respectively. Power capacity conversion factor (kW / kWh) of electric energy storage units. and These are the charging power (kW) and discharging power (kW) of the energy storage unit, respectively. This refers to the rated power (kW) of the energy storage unit.

[0029] (2) Thermal storage unit The mathematical model of the storage unit can be described as follows: In the formula, and These are the thermal storage power (kW) and heat release power (kW) of the thermal storage unit, respectively. The rated power (kW) of the thermal storage unit; and They are time points and The energy storage status (%) of the thermal storage unit; The self-discharge coefficient (%) of the thermal storage unit; The unit time step (h); The rated energy storage capacity of the thermal energy storage unit (kWh); and The values ​​are the thermal storage efficiency (%) and the heat release efficiency (%) of the thermal storage unit, respectively. and These represent the lower limit (%) and upper limit (%) of the energy storage status of the thermal energy storage unit, respectively. This is the power capacity conversion factor (kW / kWh) for the thermal storage unit.

[0030] In step S5, the mathematical model of the energy transmission unit adopts a lossless bus model, which follows the following power balance constraints: In the formula, and These are the power values ​​(kW) of the energy flow into and out of the power bus, respectively. and These are the power values ​​(kW) of the energy flow into and out of the heat bus, respectively.

[0031] Step S6 specifically includes: (1) Combine the model equations of the energy conversion unit, energy storage unit and energy transmission unit to construct a discrete-time difference equation system; (2) Integrate the operating constraints of all units, including the upper and lower limits of output of each unit, the ramp rate constraint, the state of charge constraint of the energy storage device, and the power constraint of interaction with the external power grid.

Claims

1. A modeling method for a distributed integrated energy system considering the characteristics of electrothermal synergy, characterized in that, Includes the following steps: Step S1: Determine the energy input, energy output, and internal energy flow path of the distributed electric heating integrated energy system; Step S2: Based on the concept of energy hub, the distributed electrothermal integrated energy system is decoupled into three functional modules: energy conversion unit, energy storage unit, and energy transmission unit. Step S3: Construct a mathematical model of the energy conversion unit and establish a nonlinear or linear coupling conversion relationship between input energy and output energy; Step S4: Construct a mathematical model of the energy storage unit, and establish the dynamic equation of the energy storage state over time and the constraints on charging and discharging power. Step S5: Construct a mathematical model of the energy transmission unit and establish power balance equations for the electrical power bus and thermal power bus based on the law of conservation of energy. Step S6: Combine the mathematical models of the above three functional modules to obtain the operating characteristic model of the distributed electric and thermal integrated energy system.

2. The modeling method for a distributed integrated electric and thermal energy system considering the characteristics of electric and thermal synergistic operation according to claim 1, characterized in that, In step S1: Energy inputs include natural gas supplied by pipeline networks, electricity supplied by the upstream power grid, and solar and wind energy resources in the environment; Energy output includes electrical load and thermal load to meet user needs; The internal energy flow paths include the conversion path from natural gas to electricity / heat, the conversion path from electricity to heat, and the storage path for electricity / heat.

3. The modeling method for a distributed integrated electric and thermal energy system considering the characteristics of electric and thermal synergistic operation according to claim 1, characterized in that, In step S2, the energy conversion unit includes a gas-fired cogeneration unit, an electric heat pump unit, a photovoltaic generator unit, and a wind turbine generator unit, which are used to convert the input energy form into the intermediate or terminal energy form required by the system. The energy storage unit includes electrical energy storage and thermal storage devices, which are used to realize the translation of energy in the time dimension and smooth out supply and demand fluctuations. The energy transmission unit includes an electrical bus and a thermal bus, which are used to realize the distribution and balance of energy in the spatial dimension.

4. The modeling method for a distributed integrated electric and thermal energy system considering the characteristics of electric and thermal synergistic operation according to claim 3, characterized in that, In step S3, the mathematical model of the energy conversion unit specifically includes: (1) Gas-fired cogeneration unit Gas-fired cogeneration units are modeled as back-pressure units, and their mathematical model is described as follows: ； The following constraints must be satisfied simultaneously: ； ； ； ； ； ； In the formula, Fuel input power, in kW; Indicates time; This is a Boolean variable, where 0 indicates that the unit is in a stopped state and 1 indicates that the unit is in a running state. and These are the electrical power and thermal power output of the unit, respectively (in kW). Energy loss coefficient, in percentages (%) and These are the maximum and minimum values ​​of the unit's output electrical power, respectively, in kW; and These represent the electrical efficiency when the unit's output power reaches its maximum and minimum values, respectively, in percentage (%). This refers to the power loss from fuel input, expressed in kW. The percentage of power loss relative to fuel input power, expressed as % . and All are unit efficiency coefficients; (2) Electric heat pump unit The mathematical model of the electric heat pump unit is as follows: ； ； In the formula, The heating capacity of the electric heat pump unit is expressed in kW. The electrical power input to the electric heat pump unit, measured in kW; The energy efficiency coefficient of the electric heat pump unit; and These are the lower and upper limits of the heating capacity of the electric heat pump unit, respectively, in kW; (3) Photovoltaic generator set The mathematical model for a photovoltaic power generation unit is as follows: ； In the formula, and These are the real-time power generation and rated power of the photovoltaic unit, respectively, in kW; The performance coefficient of the photovoltaic unit; This is the hourly average of solar radiation intensity, expressed in W / m². 2 ; Solar radiation intensity under standard conditions, expressed in W / m². 2 ; The power temperature coefficient of the photovoltaic unit, expressed in % / °C; and These are the operating temperature of the photovoltaic panel and the reference temperature under standard operating conditions, respectively, in °C. (4) Wind turbine generator set The model of the wind turbine generator is as follows: ； In the formula, and These are the real-time generating power and rated power of the wind turbine, respectively, in kW; , , These are the rated wind speed, cut-in wind speed, and cut-out wind speed of the wind turbine, respectively, in m / s; This represents the hourly average wind speed, in m / s.

5. A modeling method for a distributed integrated electric and thermal energy system considering the characteristics of electric and thermal synergistic operation, as described in claim 1, is characterized in that... In step S4, The mathematical model of an energy storage unit specifically includes: (1) The model of the electric energy storage unit is ； ； ； ； In the formula, and They are time points and The state of charge (SOC) of the energy storage units is expressed in % (%). The self-discharge coefficient is expressed in % (%). The unit time step is expressed in hours (h). This refers to the rated energy storage capacity of the electric energy storage unit, expressed in kWh. and These are the charging efficiency and discharging efficiency of the energy storage unit, respectively, in % . and These represent the lower and upper limits of the state of charge (SOC) of the energy storage unit, respectively, in percentages (%). This is the power capacity conversion factor for the electric energy storage unit, expressed in kW / kWh. and These are the charging power and discharging power of the energy storage unit, respectively, in kW; This refers to the rated power of the energy storage unit, expressed in kW. (2) The mathematical model of the thermal storage unit is: ； ； ； ； In the formula, and These are the thermal storage power and heat release power of the thermal storage unit, respectively, in kW; This refers to the rated power of the thermal storage unit, in kW. and They are time points and The energy storage status of the thermal energy storage unit, expressed in % %. The self-discharge coefficient of the thermal energy storage unit is expressed in % (%). The unit time step is expressed in hours (h). This refers to the rated energy storage capacity of the thermal energy storage unit, expressed in kWh. and These are the thermal storage efficiency and heat release efficiency of the thermal storage unit, respectively, in percentage (%). and These represent the lower and upper limits of the energy storage state of the thermal storage unit, respectively, in percentages (%). This is the power capacity conversion factor for the thermal storage unit, expressed in kW / kWh.

6. A modeling method for a distributed integrated electric and thermal energy system considering the characteristics of electric and thermal synergistic operation, as described in claim 1, is characterized in that... In step S5, the mathematical model of the energy transmission unit adopts a lossless bus model, which follows the following power balance constraints: ； ； In the formula, and These are the power values ​​of the energy flow into and out of the power bus, respectively, in kW; and These are the power values ​​of the energy flow into and out of the heat bus, respectively, in kW.

7. A modeling method for a distributed integrated electric and thermal energy system considering the characteristics of electric and thermal synergistic operation, as described in claim 1, is characterized in that... Step S6 specifically includes: (1) Combine the model equations of the energy conversion unit, energy storage unit and energy transmission unit to construct a discrete-time difference equation system; (2) Integrate the operating constraints of all units, including the upper and lower limits of output of each unit, the ramp rate constraint, the energy state constraint of the energy storage device, and the power constraint of interaction with the external power grid.

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