Campus winter heating system planning method considering electric heating energy storage

Abstract

The invention discloses a campus winter heating system planning method considering electric heating energy storage, which comprises the following steps: counting information of hourly electric load and thermal load of buildings in a campus area, processing data into a (24,:) data array, and processing the data by using a k-means clustering algorithm; modeling each model of the equipment by using software; setting basic operation parameters of each piece of equipment; setting each constraint condition of the system, wherein the constraint conditions are divided into equality constraints and inequality constraints; setting an objective function of the system, wherein the objective function considers economic factors; based on the equipment modeling, the constraint condition and the objective function, matlab software is adopted to solve by using a gurobi solver, and output results are capacity configuration of each piece of equipment and related economic cost; according to the invention, the problems of independent equipment operation and single planned equipment existing in the current winter heating system of the campus area building are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy system planning, and particularly to a planning method for a campus winter heating system considering electro-thermal energy storage. Background Art

[0004] The existing campus heating methods mostly adopt the traditional municipal heat network heating method, which has the problems of high charging and high energy consumption. Although schools at all levels across the country are gradually promoting the construction of campus clean heating energy stations, there are still problems such as independent operation and single planning equipment. At the same time, as the energy source of the clean heating system, air energy, geothermal energy, etc. are the main energy sources, but the utilization of solar energy is still relatively less, and the utilization of the energy storage system is also relatively less. Summary of the Invention

[0005] The purpose of the present invention is to overcome the above deficiencies and provide a planning method for a campus winter heating system considering electro-thermal energy storage, so as to solve the problems of independent operation of equipment and single planning equipment in the current campus area building winter heating system.

[0006] To solve the above technical problems, the technical solution adopted by the present invention is: a planning method for a campus winter heating system considering electro-thermal energy storage, which includes the following steps:

[0007] Step 1: Statistically analyze the hourly electrical load and heat load information of campus area buildings, process the data into a data array of (24, :), and use the k-means clustering algorithm to process the data;

[0008] Step 2: Use software to model each model of the equipment. As the heating main body, the heat pump includes an air source heat pump, a ground source heat pump, and a water source heat pump. At the same time, photovoltaic and electric / thermal energy storage are introduced;

[0009] Step 3: Set the basic operating parameters of each equipment. Since this system considers the application scenario in winter, when setting the operating parameters of the equipment, it is necessary to consider the operating parameters in the most unfavorable environment to meet the heating requirements of regional buildings in winter. The COP value of the heat pump is set according to the most unfavorable environment of the current ultra-low temperature air source heat pumps of each heat pump manufacturer, so that the equipment can be used normally in an environment of -20°C;

[0010] Step 4: Set each constraint condition of the system. The constraint conditions are divided into equality constraints and inequality constraints;

[0011] Step 5: Set the objective function of the system. The objective function considers economic factors, so that technicians can set technical solutions and understand costs in a short time when using;

[0012] Step 6: Based on the above equipment modeling, constraint conditions, and objective function, use the Gurobi solver in Matlab software to solve the problem. The output results are the capacity configurations of each device and the related economic costs.

[0013] Preferably, the specific process of Step 1 is as follows: Replace all negative values in the matrix with 0 to exclude unreasonable values, and use the reshape function to arrange the data in the form of (24, :) for easy data processing; then select the k-means clustering algorithm to process the data and solve the values of relevant typical days, so as to be able to quickly calculate and solve using the solver in the subsequent steps. The specific number of clustering points is set and confirmed according to the image after clustering. In this way, the electricity load, heat load, and solar radiation intensity are processed separately.

[0014] Preferably, in the process of using software to model each device in Step 2, the heating equipment includes three types of heat pumps: air source heat pump, ground source heat pump, and water source heat pump. The power supply of the equipment is considered to use a photovoltaic system for power supply, and when there is a shortage, the municipal power grid is used for power supply. At the same time, electrical energy storage and thermal energy storage are considered; the electrical energy storage system considers using lead-acid batteries, and the thermal energy storage system uses a water tank as the thermal energy storage device and water as the thermal energy storage medium; the following variables are set according to the three parts of energy input, energy conversion, and energy storage. The energy input section includes the power of the photovoltaic system and the purchased electricity from the municipal power grid. The energy conversion section includes the electrical power and thermal power of the air source heat pump, ground source heat pump, and water source heat pump. The energy storage section includes the charging power and discharging power of the battery, and the heat storage power and heat release power of the hot water storage tank.

[0015] Preferably, in Step 4, the constraint conditions include the capacity constraint and output constraint of the device. For the energy storage system, it is necessary to constrain the state of charge and heat storage state of the system, and at the same time, it is also necessary to constrain the energy balance of the system.

[0016] Preferably, in Step 4, for the energy input section, the equality constraint is the power generation of the photovoltaic system, and its formula is as follows:

[0017]

[0018] In the formula, E k is the power generation of photovoltaic power, kWh; H t is the total solar radiation on the horizontal plane at time t, kWh / ㎡; E s is the irradiance under standard conditions, constant = 1 kWh / ㎡; P AZ is the installed capacity of the module, kWp; K is the comprehensive efficiency coefficient.

[0019] More preferably, the energy conversion section of the system is an air source heat pump, a ground source heat pump, or a water source heat pump, which converts electrical energy into heat energy. The heat output is calculated according to the following formula:

[0020]

[0021] In the formula, Q ASHP,t is the heat output of the air source heat pump at time t; P ASHP,t is the power consumption of the air source heat pump at time t; COP ASHP,t is the performance coefficient of the air source heat pump at time t; Q GSHP,t is the heat output of the ground source heat pump at time t; P GSHP,t is the power consumption of the ground source heat pump at time t; COP GSHP,t is the performance coefficient of the ground source heat pump at time t; Q WSHP,t is the heat output of the water source heat pump at time t; P WSHP,t is the power consumption of the water source heat pump at time t; COP WSHP,t is the performance coefficient of the water source heat pump at time t;

[0022] The energy storage section of the system is a storage battery and a hot water storage tank, which are used to adjust the electrical load and heat load of the regional building, playing the role of peak shaving and valley filling. The energy formula of the energy storage system is calculated according to the following formula:

[0023]

[0024]

[0025] In the formula, the subscript ES represents the storage battery, and TES represents the heat storage tank; E ES,t is the capacity of the storage battery at time t, kWh; is the rated total capacity of the storage battery, kWh; SOC t is the state of charge of the storage battery at time t; is the charging power of the storage battery at time t-1, kW; is the charging efficiency of the storage battery at time t-1; is the discharging power of the storage battery at time t-1, kW; is the discharging efficiency of the storage battery at time t-1; σ ES is the dissipation rate of the storage battery; H TES,t is the capacity of the heat storage tank at time t, kWh; is the rated total capacity of the heat storage tank, kWh(3600J); HSOC t is the heat storage state of the heat storage tank at time t; is the heat storage power of the heat storage tank at time t-1, kW; is the heat storage efficiency of the heat storage tank at time t-1; is the heat release power of the heat storage tank at time t-1, kW; is the heat release efficiency of the heat storage tank at time t-1.

[0026] More preferably, for the setting of the inequality constraints of the system, it is the capacity constraints of each device of the system and the description of the state of charge and heat storage state of the energy storage section. The inequality constraints of the relevant devices are calculated according to the following formula:

[0027]

[0028] In the formula, P ASHP , P GSHP , P WSHP are the power consumptions of the air source heat pump, ground source heat pump, and water source heat pump units; is the upper power limit of the air source heat pump, ground source heat pump, and water source heat pump; P PV is the actual power generation of the photovoltaic power generation system; is the upper power generation limit of the photovoltaic power generation system; η pv is the photoelectric conversion efficiency of the photovoltaic power generation system.

[0029] More preferably, for the inequality constraints of the system energy storage section, its constraint conditions are set according to the following formula:

[0030]

[0031]

[0032] In the formula, SOC min is the lower limit of the energy storage state of the battery; SOC max is the upper limit of the energy storage state of the battery; Q ES is the installed capacity of the battery, kWh; Q ES,t is the installed capacity of the battery at time t, kWh; is the charging power of the battery at time t, kW; P ch,max is the maximum charging power of the battery, kW; is the charging power of the battery at time t, kW; P dis,max is the maximum discharging power of the battery, kW; is the charging start / stop state of the battery; is the discharging start / stop state of the battery; is the start / stop state when the battery neither stores nor discharges energy; HSOC min is the lower limit of the energy storage state of the heat storage tank; HSOC max is the upper limit of the energy storage state of the heat storage tank; Q TES is the installed capacity of the heat storage tank, kWh; Q TES,t is the installed capacity of the heat storage tank at time t, kWh; is the charging power of the heat storage tank at time t, in kW; is the maximum charging power of the heat storage tank, in kW; is the charging power of the heat storage tank at time t, in kW; is the maximum discharging power of the heat storage tank, in kW; is the charging start / stop state of the heat storage tank; is the discharging start / stop state of the heat storage tank; is the start / stop state when the heat storage tank neither stores nor discharges energy; τ is the scheduling period.

[0033] More preferably, the energy balance constraint of the system is the electrical balance constraint and the thermal balance constraint, and their constraint conditions are as follows:

[0034]

[0035] In the formula, Q ASHP (t), Q GSHP (t), Q WSHP (t) are the heat production of the air source heat pump, the ground source heat pump, and the water source heat pump at time t; Q TES (t) is the charging and discharging heat of the heat storage tank at time t; HL(t) is the heat load of the regional building at time t; P PV (t) is the power generation of the photovoltaic power generation system at time t; P UG (t) is the power purchased from the power grid at time t; P ES (t) is the charge and discharge of the battery at time t; P ASHP (t), P GSHP (t), P WSHP (t) are the power consumption of the air source heat pump, the ground source heat pump, and the water source heat pump at time t; PL(t) is the electrical load of the regional building at time t.

[0036] Preferably, in step 5, the objective function of the system is set, and the objective function of the model is to be economically optimal, including the optimal energy consumption cost, investment cost, and maintenance cost of the system, and the equivalent annual cost. The formula is as follows:

[0037] C EAC = C INV + C OM + C Ener

[0038]

[0039] In the formula, C EAC is the equivalent annual cost; C INV is the system investment cost; C OM is the system maintenance cost; C Ener is the system operation cost; Cap i is the capacity of equipment i; ICi is the installation cost related to the capacity of device i; CRF i is the capital recovery factor of device i; r is the interest rate, %; y ω is the life cycle of device ω, in years; MFC i is the fixed maintenance cost of device i; is the unit price of purchasing electricity from the public power grid at time t, yuan / kWh; is the power of purchasing electricity from the public power grid at time t, kW; θ Cap,t is the operating cost of the device, yuan / kW; P Cap,t is the output of each device.

[0040] Advantages of the present invention:

[0041] 1. The present invention takes the combination of electricity purchase cost, investment cost and system maintenance cost as the optimal economic cost as the objective function, and has feasibility;

[0042] 2. The present invention considers photovoltaic as the power supply system on the basis of the original winter heating system, and at the same time considers the capacity configuration of electricity storage and heat storage;

[0043] 3. The method provided by the present invention can conveniently configure the heating system equipment capacity of the building energy system in the campus area, which is convenient for technicians to formulate technical solutions in a short time, and solves the problems of independent operation of equipment and single planned equipment existing in the current winter heating system of buildings in the campus area. Description of the drawings

[0044] Figure 1 is a schematic flow chart of a method for planning a campus winter heating system considering electro-thermal energy storage;

[0045] Figure 2 is a schematic diagram of the energy system architecture. Specific implementation manners

[0046] The present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0047] Embodiment 1: As Figure 1 shown, a method for planning a campus winter heating system considering electro-thermal energy storage, which includes the following steps:

[0048] Step 1: Statistically analyze the hourly electricity load and heat load information of the buildings in the campus area, process the data into a data array of (24, :), and use the k-means clustering algorithm to process the data. It is recommended to set the clustering points to 2, so as to obtain two typical days in the winter heating season.

[0049] In Step 1, it is necessary to statistically analyze and organize the hourly electric and heat load data of regional buildings, and at the same time, statistically analyze the solar radiation data in winter in the target area. Specifically, first, all negative values in the matrix need to be replaced with 0 to exclude unreasonable values, and the reshape function is used to arrange the data in the form of (24, :) for convenient data processing. Then, the k-means clustering algorithm is selected to process the data and solve the values of relevant typical days so that the solver can be used to quickly calculate and solve in the subsequent steps. It is recommended to set the number of clustering points to 2, and the specific number of clustering points needs to be set and confirmed according to the image after clustering. In this way, the electric load, heat load, and solar radiation intensity are processed separately.

[0050] Step 2: As Figure 2 shown, software is used to model each model of the equipment. As the main heating body, heat pumps include air-source heat pumps, ground-source heat pumps, and water-source heat pumps. At the same time, the introduction of photovoltaic and electric / heat energy storage is considered.

[0051] In Step 2, it is necessary to perform mathematical modeling on each device planned to be used. This invention is used to provide heat for regional buildings during the winter heating season. The main heating devices considered include three of the most widely used heat pump types: air-source heat pumps, ground-source heat pumps, and water-source heat pumps. The power supply of the devices is considered to use a photovoltaic system for power supply, and when there is a shortage, the municipal power grid is used for power supply. At the same time, electric energy storage and heat energy storage are considered. Among them, a relatively mature lead-acid battery is considered for the electric energy storage system, and a water tank is used as the heat storage device for the heat energy storage system, and water is used as the heat storage medium. Specifically, the following variables are set according to the three parts of energy input, energy conversion, and energy storage. The energy input section includes the power of the photovoltaic system and the purchased electricity obtained from the municipal power grid. The energy conversion section includes the electric power and heat power of air-source heat pumps, ground-source heat pumps, and water-source heat pumps. The energy storage section includes the charging power and discharging power of the battery, and the heat storage power and heat release power of the hot water storage tank.

[0052] Step 3: Set the basic operating parameters of each device. Since this system considers the application scenario in winter, when setting the operating parameters of the devices, it is necessary to consider the operating parameters in the most unfavorable environment to meet the heating requirements of regional buildings in winter. The COP value of the heat pump is set according to the most unfavorable environment of the current ultra-low temperature air-source heat pumps of each heat pump manufacturer, so that the device can be used normally in an environment of -20°C.

[0053] In Step 3, it is necessary to set various basic parameters of the equipment. Since the application scenario of this system is set in winter, the most unfavorable environmental factors of the system need to be considered in the setting of each parameter of the equipment to meet the heating requirements of regional buildings. Among them, the power generation efficiency of the photovoltaic is considered to be set at 15%-17%. The COP value of the heat pump system can be set by referring to the heat pump parameters of current mainstream heat pump manufacturers. Among them, for the air source heat pump, it is necessary to refer to the COP value under the most unfavorable environment of the ultra-low temperature air source heat pump for setting so that the system can meet the normal use of the equipment in an environment of -20°C.

[0054] Step 4: Set various constraint conditions of the system. The constraint conditions are divided into equality constraints and inequality constraints. Specifically, it includes the capacity constraint and output constraint of the equipment. For the energy storage system, it is necessary to constrain the state of charge and heat storage state of the system. At the same time, it is also necessary to constrain the energy balance of the system.

[0055] In Step 4, it is necessary to set various constraint conditions of the system. The set conditions are divided into equality constraints and inequality constraints. For the energy input section, the equality constraint is the power generation of the photovoltaic system, and its formula is as follows:

[0056]

[0057] In the formula, E k is the power generation of photovoltaic, kWh; H t is the total solar radiation on the horizontal plane at time t, kWh / ㎡; E s is the irradiance under standard conditions, constant = 1 kWh / ㎡; P AZ is the installed capacity of the components, kWp; K is the comprehensive efficiency coefficient.

[0058] The energy conversion section of the system is the air source heat pump, ground source heat pump, and water source heat pump, which convert electrical energy into heat energy. Its heat output can be calculated according to the following formula:

[0059]

[0060] In the formula, Q ASHP,t is the heat output of the air source heat pump at time t; P ASHP,t is the power consumption of the air source heat pump at time t; COP ASHP,t is the performance coefficient of the air source heat pump at time t; Q GSHP,t is the heat output of the ground source heat pump at time t; P GSHP,t is the power consumption of the ground source heat pump at time t; COP GSHP,t is the performance coefficient of the ground source heat pump at time t; Q WSHP,t is the heat output of the water source heat pump at time t; P WSHP,t is the power consumption of the water source heat pump at time t; COP WSHP,tCOP at time t is the coefficient of performance of the water source heat pump.

[0061] The energy storage section of the system consists of a battery and a hot water storage tank, which are used to regulate the electrical and thermal loads of the regional building, playing the role of peak shaving and valley filling. The energy formula of the energy storage system can be calculated according to the following formula:

[0062]

[0063] In the formula, the subscript ES represents the battery, and TES represents the heat storage tank; E ES,t is the battery capacity at time t, in kWh; is the rated total battery capacity, in kWh; SOC t is the state of charge of the battery at time t; is the battery charging power at time t-1, in kW; is the battery charging efficiency at time t-1; is the battery discharging power at time t-1, in kW; is the battery discharging efficiency at time t-1; σ ES is the dissipation rate of the battery, taken as 0.0001 here. H TES,t is the heat storage tank capacity at time t, in kWh; is the rated total heat storage tank capacity, in kWh (3600J); HSOC t is the heat storage state of the heat storage tank at time t; is the heat storage power of the heat storage tank at time t-1, in kW; is the heat storage efficiency of the heat storage tank at time t-1; is the heat release power of the heat storage tank at time t-1, in kW; is the heat release efficiency of the heat storage tank at time t-1.

[0064] For the setting of the inequality constraint conditions of the system, it is mainly the capacity constraints of each device in the system and the description of the state of charge and heat storage state of the energy storage section. The inequality constraints of the relevant devices can be calculated according to the following formula:

[0065]

[0066] In the formula, P ASHP , P GSHP , P WSHP are the power consumptions of the air source heat pump, ground source heat pump, and water source heat pump units; is the power upper limit of the air source heat pump, ground source heat pump, and water source heat pump; P PV is the actual power generation of the photovoltaic power generation system; is the power generation upper limit of the photovoltaic power generation system; η pv is the photoelectric conversion efficiency of the photovoltaic power generation system.

[0067] Inequality constraints for the system energy storage section, and the constraint conditions are set according to the following formula:

[0068]

[0069] In the formula, SOC min is the lower limit of the energy storage state of the battery, and here it is taken as 0.2; SOC max is the upper limit of the energy storage state of the battery, and here it is taken as 0.8; Q ES is the installed capacity of the battery, kWh; Q ES,t is the installed capacity of the battery at time t, kWh; is the charging power of the battery at time t, kW; P ch,max is the maximum charging power of the battery, kW; is the charging power of the battery at time t, kW; P dis,max is the maximum discharging power of the battery, kW; is the charging start / stop state of the battery; is the discharging start / stop state of the battery; is the start / stop state when the battery neither stores nor discharges energy. HSOC min is the lower limit of the energy storage state of the heat storage tank, and here it is taken as 0.2; HSOC max is the upper limit of the energy storage state of the heat storage tank, and here it is taken as 0.8; Q TES is the installed capacity of the heat storage tank, kWh; Q TES,t is the installed capacity of the heat storage tank at time t, kWh; is the charging power of the heat storage tank at time t, kW; is the maximum charging power of the heat storage tank, kW; is the charging power of the heat storage tank at time t, kW; is the maximum discharging power of the heat storage tank, kW; is the charging start / stop state of the heat storage tank; is the discharging start / stop state of the heat storage tank; is the start / stop state when the heat storage tank neither stores nor discharges energy; τ is the scheduling period, taken as 24 h.

[0070] In addition, the energy balance constraints of the system are electrical balance constraints and thermal balance constraints, and their constraint conditions are as follows:

[0071]

[0072] In the formula, Q ASHP (t), Q GSHP (t), Q WSHP (t) are the heat production amounts of the air source heat pump, ground source heat pump, and water source heat pump at time t; Q TES(t) is the heat charging and discharging amount of the heat storage tank at time t; HL(t) is the heat load of the regional building at time t; P PV (t) is the power generation amount of the photovoltaic power generation system at time t; P UG (t) is the power purchase amount from the power grid at time t; P ES (t) is the charge and discharge amount of the battery at time t; P ASHP (t), P GSHP (t), P WSHP (t) is the power consumption of the air source heat pump, ground source heat pump, and water source heat pump at time t; PL(t) is the electrical load of the regional building at time t.

[0073] Step Five: Set the objective function of the system. The objective function of this system mainly considers economic factors to facilitate technicians to set technical solutions and understand costs in a short time when using it.

[0074] In Step Five, it is necessary to set the objective function of the system. The objective function of this model is to achieve the optimal economy, including the optimal energy consumption cost, investment cost, and maintenance cost of the system, and the equivalent annual cost. The formula is as follows:

[0075] C EAC = C INV + C OM + C Ener

[0076]

[0077]

[0078] In the formula, C EAC is the equivalent annual cost; C INV is the system investment cost; C OM is the system maintenance cost; C Ener is the system operation cost; cap i is the capacity of equipment i; IC i is the installation cost related to the capacity of equipment i; CRF i is the capital recovery factor of equipment i; r is the interest rate, %; y ω is the life cycle of equipment ω, in years; MFC i is the fixed maintenance cost of equipment i; is the unit price of purchasing electricity from the public power grid at time t, yuan / kWh; is the power of purchasing electricity from the public power grid at time t, kW; θ Cap,t is the equipment operation cost, yuan / kW; P Cap,t is the output of each equipment.

[0079] Step 6: Based on the above device modeling, constraint conditions, and objective function, use the Gurobi solver in Matlab software for solution. The output results are the capacity configurations of each device and the related economic costs. This step requires using Matlab software to build the model, introducing the Yalmip toolbox, and using the Gurobi solver for solution.

[0080] The above embodiments are only the preferred technical solutions of the present invention and should not be regarded as limitations on the present invention. The protection scope of the present invention should be the technical solutions recorded in the claims, including the equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A campus winter heating system planning method considering electric thermal energy storage, characterized by: It includes the following steps: Step 1: Collect the hourly electricity load and heat load information of the campus area buildings, process the data into a (24,:) data array, and use the k-means clustering algorithm to process the data; Step 2: Use software to model each model of the equipment. As the main heating source, the heat pump includes air source heat pump, ground source heat pump and water source heat pump, and introduces photovoltaic and electric / thermal energy storage; Step 3: Set the basic operating parameters of each device. Since this system considers the application scenario in winter, the operating parameters of the equipment need to be set in the most unfavorable environment to meet the heating needs of regional buildings in winter. The COP value of the heat pump is set according to the most unfavorable environment of the ultra-low temperature air source heat pump of each heat pump manufacturer, which can meet the normal use of the equipment in an environment of -20℃; Step 4: Set various constraints of the system. Constraints are divided into equality constraints and inequality constraints. Step 5: Set the objective function of the system. The objective function takes economic factors into consideration so that technicians can set up technical solutions and understand costs in a short time when using the system. Step 6: Based on the above equipment modeling, constraints and objective functions, the gurobi solver is used in MATLAB software to solve the problem. The output results are the capacity configuration of each equipment and the related economic cost.

2. A campus winter heating system planning method considering electric thermal energy storage according to claim 1, characterized in that: The specific process of step 1 is as follows: replace all negative values ​​in the matrix with 0 to exclude unreasonable values, and use the reshape function to arrange the data into the form of (24,:) for easy data processing; The k-means clustering algorithm is then used to process the data and solve the values ​​of the relevant typical days so that the solver can be used to quickly calculate and solve in the future. The specific number of clustering points is set and confirmed based on the clustered image. In this way, the electricity, heat load and solar radiation intensity are processed separately.

3. According to claim 1, a campus winter heating system planning method considering electric thermal energy storage is characterized by: In the process of using software to model each model of the equipment in step 2, the heating equipment includes three types of heat pumps: air source heat pump, ground source heat pump and water source heat pump. The power supply of the equipment considers the use of photovoltaic system for power supply. When it is insufficient, the municipal power grid is used for power supply, and electric energy storage and thermal energy storage are considered at the same time; the power storage system considers the use of lead-acid batteries, and the heat storage system uses water tanks as heat storage equipment and uses water as heat storage medium; the following variables are set according to the three parts of energy input, energy conversion and energy storage. The energy input section includes the power of the photovoltaic system and the amount of electricity purchased from the municipal power grid. The energy conversion section includes the electric power and thermal power of the air source heat pump, the ground source heat pump and the water source heat pump. The energy storage section includes the charging power and discharging power of the battery, and the heat storage power and heat release power of the hot water storage tank.

4. A campus winter heating system planning method considering electric thermal energy storage according to claim 1, characterized in that: In step 4, the constraints include capacity constraints and output constraints of the equipment. For the energy storage system, the system's state of charge and heat storage state need to be constrained, and the system's energy balance also needs to be constrained.

5. A campus winter heating system planning method considering electric thermal energy storage according to claim 1 or 4, characterized in that: In step 4, for the energy input section, the equation constraint is the power generation of the photovoltaic system, and the formula is as follows: In the formula, E k is the photovoltaic power generation, kWh; H t is the total solar radiation on the horizontal surface at time t, kWh / ㎡; E s is the irradiance under standard conditions, constant = 1kWh / ㎡; P AZ is the installed capacity of the components, kWp; K is the comprehensive efficiency coefficient.

6. According to the method for planning a campus winter heating system taking into account electric thermal energy storage as described in claim 5, it is characterized by: The energy conversion modules of the system are air source heat pump, ground source heat pump and water source heat pump, which convert electrical energy into thermal energy. The heat output is calculated according to the following formula: In the formula, Q ASHP,t P is the heating capacity of the air source heat pump at time t; ASHP,t is the power consumption of the air source heat pump at time t; COP ASHP,t is the performance coefficient of the air source heat pump at time t; Q GSHP,t is the heating capacity of the ground source heat pump at time t; P GSHP,t is the power consumption of the ground source heat pump at time t; COP GSHP,t is the performance coefficient of the ground source heat pump at time t; Q WSHP,t P is the heating capacity of the water source heat pump at time t; WSHP,t is the power consumption of the water source heat pump at time t; COP WSHP,t is the coefficient of performance of the water source heat pump at time t; The energy storage modules of the system are batteries and hot water storage tanks, which are used to adjust the electrical load and thermal load of regional buildings, and play a role in peak load reduction and valley load filling. The energy formula of the energy storage system is calculated according to the following formula: In the formula, the subscript ES represents the battery, TES represents the heat storage tank; ES,t is the battery capacity at time t, kWh; is the total rated capacity of the battery, kWh; SOC t is the battery charge state at time t; is the battery charging power at time t-1, kW; is the battery charging efficiency at time t-1; is the battery discharge power at time t-1, kW; is the battery discharge efficiency at time t-1; σ ES is the dissipation rate of the battery; H TES,t is the capacity of the heat storage tank at time t, kWh; is the total rated capacity of the heat storage tank, kWh (3600J); HSOC t is the heat storage state of the heat storage tank at time t; is the heat storage power of the heat storage tank at time t-1, kW; is the heat storage efficiency of the heat storage tank at time t-1; is the heat release power of the heat storage tank at time t-1, kW; is the heat release efficiency of the heat storage tank at time t-1.

7. A campus winter heating system planning method considering electric thermal energy storage according to claim 6, characterized in that: The setting of the inequality constraints of the system is the capacity constraints of each device in the system and the description of the charge state and heat storage state of the energy storage plate. The inequality constraints of the relevant equipment are calculated according to the following formula: Where P ASHP , P GSHP , P WSHP The power consumption of air source heat pump, ground source heat pump and water source heat pump; P is the upper limit of the power of air source heat pump, ground source heat pump and water source heat pump; PV is the actual power generation of the photovoltaic power generation system; is the upper limit of the power generation of the photovoltaic power generation system; η pv is the photoelectric conversion efficiency of the photovoltaic power generation system.

8. A campus winter heating system planning method considering electric thermal energy storage according to claim 7, characterized in that: The inequality constraints of the system energy storage sector are set according to the following formula: In the formula, SOC min SOC is the lower limit of the battery's energy storage state; max is the upper limit of the battery’s energy storage state; Q ES is the installed capacity of the battery, kWh; Q ES,t is the installed capacity of the battery at time t, kWh; is the charging power of the battery at time t, kW; P ch,max is the maximum charging power of the battery, kW; is the charging power of the battery at time t, kW; P dis,max is the maximum discharge power of the battery, kW; It is the charging start and stop status of the battery; It is the start and stop state of battery discharge; It is the start-stop state in which the battery neither stores nor releases energy; HSOC min The lower limit of the energy storage state of the heat storage tank; HSOC max is the upper limit of the energy storage state of the heat storage tank; Q TES is the installed capacity of the heat storage tank, kWh; Q TES,t is the installed capacity of the heat storage tank at time t, kWh; is the charging power of the heat storage tank at time t, kW; is the maximum charging power of the heat storage tank, kW; is the charging power of the heat storage tank at time t, kW; is the maximum energy release power of the heat storage tank, kW; The charging start and stop status of the heat storage tank; It is the energy release start and stop status of the heat storage tank; is the start-stop state of the heat storage tank neither storing nor releasing energy; τ is the scheduling period.

9. A campus winter heating system planning method considering electric thermal energy storage according to claim 8, characterized in that: The energy balance constraints of the system are electrical balance constraints and thermal balance constraints, and their constraints are as follows: In the formula, Q ASHP (t), Q GSHP (t), Q WSHP (t) is the heat output of the air source heat pump, ground source heat pump and water source heat pump at time t; Q TES (t) is the heat of the heat storage tank at time t; HL(t) is the heat load of the regional building at time t; P PC (t) is the power generation of the photovoltaic power generation system at time t; P UG (t) is the amount of electricity purchased from the power grid at time t; P ES (t) is the charge and discharge capacity of the battery at time t; P ASHP (t), P GSHP (t), P WSHP (t) is the power consumption of air source heat pump, ground source heat pump and water source heat pump at time t; PL(t) is the power load of regional buildings at time t.

10. A campus winter heating system planning method considering electric thermal energy storage according to claim 1, characterized in that: In step 5, the objective function of the system is set. The objective function of the model is economic optimization, which includes the optimal energy consumption cost, investment cost and maintenance cost of the system, as well as the equivalent annual cost. The formula is as follows: C EAC =C INV +C OM +C Ener In the formula, C EAC is the equivalent annual cost; C INV is the system investment cost; C OM is the system maintenance cost; C Ener Cap is the system operating cost; i is the capacity of device i; IC i is the capacity-related installation cost of equipment i; CRF i is the capital recovery coefficient of equipment i; r is the interest rate, %; y ω is the life cycle of the equipment, years; MFC i is the fixed maintenance cost of equipment i; The unit price of electricity purchased from the public grid at time t, RMB / kWh; is the power purchased from the public grid at time t, kW; θ Cap,t is the equipment operating cost, yuan / kW; P Cap,t Contribute to each device.

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