Park power supply system optimization operation method and device containing fused salt heat storage and electric energy storage

Abstract

The embodiment of the invention provides an optimized operation method and device for a park power supply system containing fused salt heat storage and electric energy storage. The method comprises the steps that the park power supply system comprising a fused salt heat storage system, a battery energy storage system and a heating ventilation air conditioning system is constructed; constructing a first system model of the heating ventilation air conditioning system, a second system model of the fused salt heat storage system and a third system model of the battery energy storage system; according to the first system model, the second system model and the third system model, constructing a target power cost function for calculating the power consumption cost of the park and a constraint condition corresponding to the target power cost function; and under the condition that the constraint condition is met, the target electric power cost function is calculated until a set park electric power consumption cost condition is met, and the fused salt heat storage system and the battery energy storage system are controlled to charge and discharge based on a charge and discharge plan obtained through calculation. The peak load is adjusted by combining thermal energy storage and electric energy storage, so that the consumption mode is effectively smoothed, and the power consumption in the peak period is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of park power systems, and in particular to a method and device for optimizing operation of a park power supply system containing molten salt heat storage and electric energy storage. Background Art

[0002] In the field of optimized operation of campus power supply systems, the research goal is to adjust peak loads through reasonable planning and operation optimization strategies to smooth consumption patterns and reduce power consumption during peak hours. Energy Storage Systems (ESS) have great potential for achieving peak load reduction by reducing power consumption during peak load demand, compensating for irregular power generation patterns of renewable energy, and improving power quality and reliability. In this case, peak load reduction is achieved by charging the energy storage system during off-peak hours and discharging it during peak hours.

[0003] Energy can be stored through different strategies, such as Battery Energy Storage Systems (BESS) and Thermal Energy Storage Systems (TESS), among which molten salt thermal storage technology is currently an advanced thermal energy storage system, which uses molten salt as a heat storage medium to store and release thermal energy through physical changes or chemical reactions. Among them, BESS is a practical candidate for peak load shaving due to its high efficiency, short charging / discharging time, and easy installation. However, the relatively short life cycle of BESS, high investment cost, and high maintenance cost hinder its large-scale use. On the other hand, TESS is also a practical technology that can be used for energy management and cost savings in the park. The use of TESS has benefits such as low environmental impact and greenhouse gas emissions, but it cannot meet the congestion load in the park, and due to its low thermal capacity, it needs to be used in large units.

[0004] In summary, due to the above advantages and disadvantages of TESS and BESS, using TESS and BESS side by side can supplement their mentioned limitations. In addition, the simultaneous application of TESS and BESS will lead to a reduction in the capacity of BESS, thus saving investment and maintenance costs. However, how to effectively use TESS and BESS to achieve the optimized operation of the park power supply system is an urgent problem to be solved. Summary of the invention

[0005] The embodiments of the present invention provide a method and device for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage, which realizes the rational use of molten salt heat storage and electric energy storage to reduce power consumption during peak hours.

[0006] In a first aspect, this embodiment provides a method for optimizing operation of a park power supply system containing molten salt heat storage and electric energy storage, the method comprising:

[0007] Construct a campus power supply system including a molten salt thermal storage system, a battery energy storage system, and a HVAC system;

[0008] Constructing a first system model of the HVAC system, a second system model of the molten salt heat storage system, and a third system model of the battery energy storage system;

[0009] According to the first system model, the second system model and the third system model, construct a target power cost function for calculating the power consumption cost of the park and constraints corresponding to the target power cost function;

[0010] The target power cost function is calculated under the constraint condition until the set park power consumption cost condition is reached, and the molten salt heat storage system and the battery energy storage system are controlled to charge and discharge based on the calculated charge and discharge plan.

[0011] In a second aspect, this embodiment provides a device for optimizing operation of a park power supply system containing molten salt heat storage and electric energy storage, the device comprising:

[0012] The campus system building module is used to build a campus power supply system including a molten salt thermal storage system, a battery energy storage system, and a HVAC system;

[0013] A subsystem construction module, used to construct a first system model of the HVAC system, a second system model of the molten salt heat storage system, and a third system model of the battery energy storage system;

[0014] A function construction module, used to construct a target power cost function for calculating the power consumption cost of the park and constraints corresponding to the target power cost function according to the first system model, the second system model and the third system model;

[0015] The operation optimization module is used to calculate the target power cost function under the constraint condition until the set park power consumption cost condition is reached, and the molten salt heat storage system and the battery energy storage system are controlled to charge and discharge respectively based on the calculated charge and discharge plan.

[0016] The embodiment of the present invention provides a method and device for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage, the method comprising: first constructing a park power supply system including a molten salt heat storage system, a battery energy storage system and a HVAC system; secondly constructing a first system model of the HVAC system, a second system model of the molten salt heat storage system and a third system model of the battery energy storage system; then constructing a target power cost function for calculating the power consumption cost of the park and constraints corresponding to the target power cost function according to the first system model, the second system model and the third system model; finally, calculating the target power cost function under the constraints until the set park power consumption cost condition is reached, and controlling the molten salt heat storage system and the battery energy storage system to charge and discharge based on the calculated charge and discharge plan. The above technical solution manages energy by combining molten salt heat storage technology with electric energy storage to achieve peak load reduction and reduce the capacity of the battery energy storage system. The optimal charging and discharging scheduling of the molten salt heat storage system and the battery energy storage system is transformed into an optimization problem. By modeling the park's power supply system and determining the objective function of the optimization problem, the operation optimization of the molten salt heat storage system and the battery energy storage system is determined by solving the objective function, solving the problem of how to use the molten salt heat storage system and the battery energy storage system to reduce electricity consumption during peak hours.

[0017] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 A schematic flow chart of a method for optimizing operation of a park power supply system containing molten salt heat storage and electric energy storage provided in Example 1 of the present invention;

[0020] Figure 2 This is an example diagram of the architecture of a campus power supply system provided in Embodiment 1 of the present invention;

[0021] Figure 3 A schematic flow chart of another method for optimizing operation of a park power supply system containing molten salt heat storage and electric energy storage provided in Embodiment 2 of the present invention;

[0022] Figure 4A schematic diagram of the structure of a park power supply system optimization operation device containing molten salt heat storage and electric energy storage provided in Example 3 of the present invention;

[0023] Figure 5 A schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "original", "target", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any other variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] In the field of optimized operation of campus power supply systems, the research goal is to adjust peak loads through reasonable planning and operation optimization strategies to smooth consumption patterns and reduce power consumption during peak hours. ESS has great potential for peak load reduction by reducing power consumption during peak load demand, compensating for irregular power generation patterns of renewable energy, and improving power quality and reliability. In this case, peak load reduction is achieved by charging the energy storage system during off-peak hours and discharging it during peak hours. Energy can be stored through different strategies, such as battery energy storage systems and molten salt thermal storage systems. Molten salt thermal storage technology is currently an advanced thermal energy storage system that uses molten salt as a thermal storage medium to store and release thermal energy through physical changes or chemical reactions.

[0027] Each storage technology has specific limitations and requirements. Among them, battery energy storage systems are practical candidates for peak load shaving due to their high efficiency, short charging / discharging time, and easy installation. Nevertheless, the relatively short life cycle of battery energy storage systems, high investment costs, and high maintenance costs hinder their large-scale use. The battery size should be accurately determined because the main part of the battery energy storage system cost is related to the installation, maintenance, and replacement costs, which are proportional to the battery capacity, life, and degradation rate of the battery. On the other hand, the molten salt thermal storage system is also a practical technology that can be used for energy management and cost savings in the park. The molten salt thermal storage system is designed to store heat or cold in a storage medium for later use at various temperatures, and the molten salt thermal storage system provides the heating and cooling needs of the park and reduces the peak hours by storing energy during off-peak hours and releasing energy during peak hours. Although the use of the molten salt thermal storage system has the benefits of low environmental impact and greenhouse gas emissions, it cannot meet the congestion load in the park and needs to be used in large units due to its low thermal capacity. Therefore, due to the above advantages and disadvantages of molten salt heat storage system and battery energy storage system, using molten salt heat storage system and battery energy storage system side by side can supplement their mentioned limitations. In addition, the simultaneous application of molten salt heat storage system and battery energy storage system will lead to a reduction in the capacity of the battery energy storage system, thereby saving investment and maintenance costs. Therefore, how to effectively use molten salt heat storage system and battery energy storage system to achieve the optimized operation of the park power supply system is an urgent problem to be solved.

[0028] In summary, how to combine molten salt heat storage technology with electric energy storage, and use reasonable planning and operation optimization strategies to adjust peak loads, more effectively smooth consumption patterns and reduce electricity consumption during peak hours is an urgent problem that needs to be solved.

[0029] Embodiment 1

[0030] Figure 1 A flow chart of a method for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage is provided in Example 1 of the present invention. The method can be applicable to the case of optimizing the park power supply system. The method can be executed by an optimized operation device for a park power supply system containing molten salt heat storage and electric energy storage. The optimized operation device for a park power supply system containing molten salt heat storage and electric energy storage can be implemented in the form of hardware and / or software and is generally integrated in an electronic device.

[0031] like Figure 1 As shown, the method for optimizing operation of a park power supply system containing molten salt heat storage and electric energy storage provided in the first embodiment may specifically include the following steps:

[0032] S101. Construct a campus power supply system including a molten salt heat storage system, a battery energy storage system and a HVAC system.

[0033] The power supply system of the park is modeled, which consists of a HVAC system, a molten salt heat storage system and a battery energy storage system. Model building is to convert the optimization operation problem of the park power supply system to be studied into a mathematical model, and clearly define the objective function and constraints. It should be noted that in addition to defining the HVAC system, the molten salt heat storage system, and the battery energy storage system, this embodiment also includes the power consumption model corresponding to the load power consumption of the park.

[0034] Among them, the HVAC system consists of a chiller, an electric boiler, a cooling tower and a water pump. The chiller consists of an evaporator, a compressor, a thermal expansion valve and a condenser, which is responsible for providing cooling loads for the buildings in the park. Two pumps are connected to supply the cold water provided by the evaporator to the building and return the water in the building to the condenser. The waste heat generated in the condenser can be regarded as the feed of the molten salt thermal storage system. The cooling tower is generally considered to discharge the waste heat generated by the condenser and reduce the water temperature. By integrating the molten salt thermal storage system into the building, the waste heat in the cooling tower can be used to fill the water tank demand in winter. In this case, the valve of the cooling tower is closed and the hot water generated in the condenser moves to the water level storage. Therefore, energy is saved and the power consumption associated with the cooling tower and the connected pump is eliminated.

[0035] The water tanks can transfer heat to the molten salt thermal storage system because of their high ability to store energy in the park system. The water tanks are connected to the chillers and are provided by the heat generated in the condenser of the chillers. In this embodiment, an energy management method including a molten salt thermal storage system and a battery energy storage system is constructed to reduce the capacity of the battery energy storage system. Including a molten salt thermal storage system and a battery energy storage system to reduce the capacity of the battery energy storage system and reach the peak load of the user.

[0036] For example, Figure 2 This is an example diagram of the architecture of a campus power supply system provided in Embodiment 1 of the present invention, such as Figure 2 As shown, the entire park includes the main power grid, battery energy storage system, molten salt heat storage system, air conditioning and HVAC system, park load electricity consumption, etc. The energy management functional unit that integrates the operation and scheduling of each system is recorded as the Energy Management Unit (EMU). The energy management unit is interactively connected with the main power grid, battery energy storage system, molten salt heat storage system, air conditioning and HVAC system, and park load electricity consumption. For example, the energy management unit has charging / discharging control over the battery energy storage system, the energy management unit obtains the initial state of charge (SOC) of the battery energy storage system, and the energy management unit controls the air conditioning and HVAC system by on / off, which will not be repeated here. In addition, the real-time electricity price affects the energy management unit's control over the charging and discharging of each system.

[0037] S102, constructing a first system model of a HVAC system, a second system model of a molten salt heat storage system, and a third system model of a battery energy storage system.

[0038] In this embodiment, based on the characteristic analysis of the HVAC system, the HVAC system is modeled, and the model obtained by modeling is recorded as the first system model. In this embodiment, the HVAC system consists of a chiller, an electric boiler, a cooling tower and a water pump. The chiller consists of an evaporator, a compressor, a thermal expansion valve and a condenser, and is responsible for providing cooling loads for the buildings in the park. The two pumps are connected to supply the cold water provided by the evaporator to the building and return the water in the building to the condenser. The waste heat generated in the condenser can be regarded as the feed of the molten salt heat storage system. Based on this, the heat generated by the chiller can be determined according to the outlet temperature, inlet temperature, water flow rate and specific heat capacity of the condenser, and the power consumption model of the chiller can be constructed based on the heat generated by the chiller and the power consumption used to generate the heat.

[0039] In addition, the electric boiler in the HVAC system is considered to be another major electricity consumer in the building, especially during peak hours. The heat provided by the electric boiler is determined based on the outlet temperature, inlet temperature, water flow rate, and specific heat capacity of the water. Based on the heat provided by the electric boiler and the power consumption used to generate the heat, the power consumption model of the electric boiler is constructed. The above model is the first system model of the HVAC system.

[0040] In this embodiment, the water tanks are mainly used to transfer heat to the molten salt heat storage system because they have a high ability to store energy in the park system. The water tanks are connected to the chillers and are provided by the heat generated in the chiller condenser. The heat stored in the molten salt heat storage system is determined according to the outlet temperature of the condenser, the inlet temperature, the water flow rate provided to the molten salt heat storage system, and the specific heat capacity of the water. The molten salt heat storage system operates in two modes, including a charging mode and a discharging mode. The molten salt heat storage system is charged by the heat generated in the condenser and discharged during peak hours to eliminate the power consumption of the electric boiler, the chiller and its pump. By extracting the relationship between the heat stored in the molten salt heat storage system and the electricity consumed to generate this heat, a charging / discharging model of the molten salt heat storage system can be obtained, which is recorded as the second system model.

[0041] In this embodiment, according to the charging / discharging power, self-discharging rate, time interval and charging / discharging efficiency of the battery energy storage system, a kinetic model of electric energy storage is constructed and recorded as the third system model.

[0042] S103: construct a target power cost function for calculating the power consumption cost of the park and constraint conditions corresponding to the target power cost function according to the first system model, the second system model and the third system model.

[0043] It is understandable that in buildings, peak loads are mainly caused by electrical equipment such as lights, computers, and thermal equipment. Since different types of energy storage systems are used in buildings, the peak load reduction mechanism should be designed considering different scenarios and campus coverage peaks in electricity consumption. The waste heat generated in the chiller condenser is charged during the day. In addition, the chiller operates in the condenser and consumes electricity to generate heat for charging until it reaches its maximum capacity during off-peak hours. In addition, the battery energy storage system is provided by the grid during off-peak hours. Charging in the energy storage system is done taking into account its maximum capacity and constraints.

[0044] In this embodiment, the molten salt thermal storage system and the battery energy storage system for peak load regulation of discharge are studied through different scenarios. One of the situations is that a large part of the peak load is caused by transferable loads, which can be understood as non-essential loads. Therefore, the molten salt thermal storage system is used to discharge to serve the transferable load. If the peak load exceeds the energy stored in the molten salt thermal storage system, the battery energy storage system corresponds to the fixed load in the building. In this scenario, the battery energy storage system is used to meet the fixed load requirements.

[0045] Another scenario is when the peak load is caused by fixed loads and movable loads. In this case, the molten salt thermal storage system and the battery energy storage system are used to meet the demand and cut the peak. In this case, the molten salt thermal storage system and the battery energy storage system provide electricity in the condenser and the main grid, respectively. Therefore, the total electricity consumption during the off-peak period is increased relative to the original electricity consumption. Then, during the peak period, the molten salt thermal storage system and the battery energy storage system discharge heat and electricity, respectively, to meet the load demand in the park. Therefore, through the optimization method, the optimal operation plans of the molten salt thermal storage system and the battery energy storage system are defined respectively to manage the transferable and fixed loads. The goal is to minimize the power consumption during the peak period while keeping the ESS charged during the off-peak period. In addition, the power consumption should not exceed the threshold. Considering all the above points, the target power cost function is expressed as:

[0046]

[0047] -1≤x i ≤1,

[0048] -1≤v+Zx T τ≤c,

[0049]

[0050] Where n is the number of time intervals in a day, x is the decision variable representing the charging / discharging schedule, and x iis the decision variable representing the charging / discharging schedule at time i, which is calculated by the first system model, the second system model and the third system model. i is the power consumption of the park at time i, P r and T represent the electricity price function and peak threshold, respectively. κ is the maximum charge and discharge power of the energy storage system. υ represents the initial energy storage capacity of the energy storage system (kWh). max represents the maximum capacity of the energy storage system (kWh), and τ represents the time interval, which is set to 15 minutes. The decision variable has a positive and negative range, (0≤x i ≤1) corresponds to charging, (-1≤x i ≤0) corresponds to the discharge mode. -1≤v+Zx T τ≤c, which represents the energy that can be stored in the energy storage system.

[0051] It is important to know that, given the first system model of the HVAC system, the second system model of the molten salt heat storage system, and the third system model of the battery energy storage system, the heat is considered a known quantity, and the amount of electricity can be calculated based on the heat and the constructed system model. The specific decision of x is based on the actual needs at a certain moment, such as cooling or heating, the amount of electrical load, and the amount of thermal load. i . Exemplary, x of the molten salt thermal storage system i The capacity of the battery energy storage system can be calculated based on the second system model of the molten salt heat storage system, and the capacity of the battery energy storage system can be calculated based on the third system model of the battery energy storage system. However, the capacity of the battery energy storage system is limited and is considered to be one of the constraints of the optimization problem.

[0052] S104. Calculate the target power cost function under the constraint conditions until the set park power consumption cost conditions are reached, and control the molten salt thermal storage system and the battery energy storage system to charge and discharge based on the calculated charging and discharging plan.

[0053] The setting of the power consumption cost condition of the park refers to the minimum power consumption cost of the park. The charging and discharging plan refers to the charging and discharging cycle of the molten salt thermal storage system and the battery energy storage system.

[0054] In this embodiment, a meta-heuristic optimization algorithm is used to derive the optimal charge and discharge cycle of the molten salt heat storage system and the battery energy storage system. In this embodiment, the particle swarm optimization (PSO) algorithm in the meta-heuristic method is used to solve the target power cost function. The purpose of using the meta-heuristic algorithm is to find a feasible solution within an acceptable time scale. PSO can solve the optimization problem of constraints by treating the constraints as penalties in the cost function. Taking the constraints as the penalty of the target power cost function, the penalty functions corresponding to the energy stored in the battery energy storage system in the charging mode and the discharging mode are constructed respectively.

[0055] Following the above description, based on the penalty function and the target power cost function, an updated target power cost function is constructed. The updated target power cost function is solved by the particle swarm algorithm until the target power cost function is minimized, and the calculated charging and discharging plan is obtained. Based on the charging and discharging plan, the molten salt thermal storage system and the battery energy storage system are controlled to charge and discharge respectively.

[0056] By combining the molten salt heat storage system with the battery energy storage system, peak load reduction can be achieved and the capacity of the battery energy storage system can be reduced; in addition, the optimal scheduling of charging and discharging of the molten salt heat storage system and the battery energy storage system is expressed as an optimization problem, and the optimization process is implemented through a meta-heuristic method to meet the demand load related to the standard during peak hours. In addition, the waste heat generated by the chiller can be stored and delivered to the park during peak hours. Therefore, during peak hours, the electricity consumption associated with the heating system is eliminated from the total electricity demand and the capacity required by the battery energy storage system is reduced. Based on the above description, the optimized operation of the park power supply system can be carried out more effectively.

[0057] The embodiment of the present invention provides a method for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage, which manages energy by combining molten salt heat storage technology with electric energy storage to achieve peak load reduction and reduce the capacity of the battery energy storage system. The optimal scheduling of charging and discharging of the molten salt heat storage system and the battery energy storage system is transformed into an optimization problem. By modeling the park power supply system and determining the objective function of the optimization problem, the operation optimization of the molten salt heat storage system and the battery energy storage system is determined by solving the objective function, thereby solving the problem of how to use the molten salt heat storage system and the battery energy storage system to reduce power consumption during peak hours.

[0058] As an optional embodiment of the embodiment of the present invention, based on the above embodiment, this optional embodiment can be optimized after constructing a campus power supply system including a molten salt heat storage system, a battery energy storage system and a HVAC system, and further includes: connecting the output end of the chiller of the HVAC system to the input end of the molten salt heat storage system, and connecting the output end of the molten salt heat storage system to the campus load equipment.

[0059] Among them, the HVAC system consists of a chiller, an electric boiler, a cooling tower and a water pump. The chiller consists of an evaporator, a compressor, a thermal expansion valve and a condenser, which is responsible for providing cooling loads for the buildings in the park. Two pumps are connected to supply the cold water provided by the evaporator to the building and return the water in the building to the condenser. The waste heat generated in the condenser can be regarded as the feed of the molten salt thermal storage system. The cooling tower is generally considered to discharge the waste heat generated by the condenser and reduce the water temperature. By integrating the molten salt thermal storage system into the building, the waste heat in the cooling tower can be used to fill the water tank demand in winter. In this case, the valve of the cooling tower is closed and the hot water generated in the condenser moves to the water level storage. Therefore, energy is saved and the power consumption associated with the cooling tower and the connected pump is eliminated.

[0060] The water tanks are mainly used to transfer heat to the molten salt thermal storage system because of their high ability to store energy in the park system. The water tanks are connected to the chillers and are supplied by the heat generated in the chiller condenser. The output of the HVAC system's chiller is connected to the input of the molten salt thermal storage system, and the output of the molten salt thermal storage system is connected to the park load equipment.

[0061] The above technical solution concretizes the connection relationship between the HVAC system and the molten salt heat storage system.

[0062] Embodiment 2

[0063] Figure 3 A flow chart of another method for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage provided in Embodiment 2 of the present invention. This embodiment is a further optimization of the above embodiment. In this embodiment, the optimization is further limited to "constructing a first system model of the HVAC system, a second system model of the molten salt heat storage system, and a third system model of the battery energy storage system", and the optimization is further limited to "calculating the target power cost function under the constraints until the set park power consumption cost conditions are reached, and controlling the charging and discharging of the molten salt heat storage system and the battery energy storage system respectively based on the calculated charging and discharging plan".

[0064] like Figure 3 As shown, this embodiment 2 provides a method for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage, which specifically includes the following steps:

[0065] S201. Construct a campus power supply system including a molten salt heat storage system, a battery energy storage system and a HVAC system.

[0066] S202. Determine the heat generated by the chiller according to the water outlet temperature, water inlet temperature, water flow rate and specific heat capacity of the condenser.

[0067] In this embodiment, the HVAC system consists of a chiller, an electric boiler, a cooling tower and a water pump. The chiller consists of an evaporator, a compressor, a thermal expansion valve and a condenser, and is responsible for providing cooling loads for the buildings in the park. Two pumps are connected to supply the cold water provided by the evaporator to the building and return the water in the building to the condenser. The waste heat generated in the condenser can be regarded as the feed of the molten salt heat storage system. The waste heat generated by the condenser is the heat generated by the chiller, and its calculation formula is expressed as:

[0068] Q CND =m CND C P (T CNDOW -T CNDIW ),

[0069] Among them, Q CND is the waste heat generated in the condenser, m CND is the water flow rate in the condenser, C p is the specific heat of water, T CNDOW and T CNDIW are the outlet water temperature and inlet water temperature of the condenser respectively.

[0070] S203: construct a power consumption model of the chiller based on the heat generated by the chiller and the power consumption used to generate the heat.

[0071] In this embodiment, the power consumption of the chiller corresponding to the heat generated can be obtained, and the power consumption model of the chiller can be obtained by interpolating the relationship between the heat generated by the chiller and the power consumption through a second-order function.

[0072] S204, determining the amount of heat provided by the electric boiler according to the water outlet temperature, water inlet temperature, water flow rate and specific heat capacity of the water of the electric boiler.

[0073] Among them, electric boilers in HVAC systems are considered to be another major electricity consumer in buildings, especially during peak hours. The electricity cost of running an electric boiler at 98% efficiency is very significant. The heat provided by the boiler is calculated based on the principles of thermodynamics as follows:

[0074] Q B =m BW C P (T BO -T BI ),

[0075] Among them, Q B The heat generated by the boiler m BW represents the water flow through the electric boiler, T BO and T BIThey are the water outlet temperature and water inlet temperature in the electric boiler respectively.

[0076] S205: construct a power consumption model of the electric boiler based on the heat provided by the electric boiler and the power consumption used to generate the heat.

[0077] Among them, the power consumption can be obtained through historical measurement data, which can also be understood as the power consumption used to generate the heat can be measured through historical data. After the heat provided by the electric boiler and the power consumption used to generate the heat are known, the relationship between the generated heat and the consumed power is extracted to define the power consumption corresponding to the required heat demand of the boiler, that is, to obtain the power consumption model of the electric boiler.

[0078] S206: Record the power consumption model of the chiller and the power consumption model of the electric boiler as the first system model.

[0079] In this embodiment, the power consumption model of the chiller and the power consumption model of the electric boiler obtained above are recorded as the first system model.

[0080] S207. Determine the amount of heat stored in the molten salt heat storage system according to the water outlet temperature and water inlet temperature of the condenser, the water flow rate provided to the molten salt heat storage system, and the specific heat capacity of water.

[0081] In this embodiment, the water tanks are mainly used to transfer heat to the molten salt thermal storage system because they have a high ability to store energy in the park system. The water tanks are connected to the chillers and are provided by the heat generated in the chiller condenser. Based on the heat generated by the chiller, the average inlet temperature of the water in the insulation tank after passing through the pump can be known. The average inlet temperature of the water in the insulation tank is 37°C. The heat stored in the molten salt thermal storage system is expressed by assuming a constant rate of mass water flow, and the calculation formula is expressed as:

[0082] Q TESS =m TESS C P ΔT TESS

[0083] Among them, Q TESS is the heat energy transferred to the molten salt thermal storage system, m TESS The mass flow rate of hot water supplied to the condenser, C p is the specific heat capacity of water, T TESS is the temperature difference in the condenser, which is the difference between the outlet temperature and the inlet temperature of the condenser.

[0084] S208. Based on the heat stored in the molten salt heat storage system and the amount of electricity that can be generated by the heat, a charging model of the molten salt heat storage system is constructed as a second system model.

[0085] It should be noted that the water tank operates in two modes, including charging mode and discharging mode. The water tank is charged by the heat generated in the condenser and discharged during peak hours to eliminate the power consumption of the electric boiler, chiller and its pump. By extracting the relationship between the heat stored in the molten salt heat storage system and the electricity consumed to generate this heat, the charging and discharging model of the molten salt heat storage system can be obtained, which is recorded as the second system model. Among them, the difference between the charging model and the discharging model is only whether the first sign is positive or negative.

[0086] S209: construct a kinetic model of electric energy storage according to the charging / discharging power, self-discharging rate, time interval, and charging / discharging efficiency of the battery energy storage system, which is recorded as a third system model.

[0087] Among them, the kinetic formula for storing energy in the battery can be expressed as:

[0088] E BESS (t) = (1-σ)E BESS (t-1)+κx(t)τη,

[0089] Among them, E BESS (t) is the energy stored at time t, κx(t) is the charge / discharge power, σ is the self-discharge rate of the battery, τ is the time interval, and η is the discharge / charge efficiency of the battery energy storage system. If κx(t)<0, the battery pack discharges to the load, and if κx(t)>0, the battery pack is charged by the grid. The capacity of the battery energy storage system is limited and is considered to be one of the constraints of the optimization problem.

[0090] It should be noted that, compared with other types of batteries, lithium-ion batteries have high energy density, high efficiency and long cycle life, and a group of lithium-ion batteries is considered to reduce peak values. In this embodiment, the battery energy storage system preferably uses lithium-ion batteries.

[0091] S210: Construct a target power cost function for calculating the power consumption cost of the park and constraint conditions corresponding to the target power cost function based on the first system model, the second system model and the third system model.

[0092] S211. Taking the constraint condition as the penalty of the target power cost function, a penalty function corresponding to the energy stored in the battery energy storage system in the charging mode and the discharging mode is constructed respectively.

[0093] In this embodiment, PSO in the metaheuristic method is used to solve the target power cost function. The purpose of using the metaheuristic algorithm is to find a feasible solution within an acceptable time scale. PSO can solve the optimization problem of constraints by treating the constraints as penalties in the cost function. Taking the constraints as penalties for the target power cost function, the penalty functions corresponding to the energy stored in the battery energy storage system in the charging mode and the discharging mode are constructed respectively. Specifically:

[0094] Charging mode (0≤x i ≤1), the penalty function is expressed as:

[0095] Discharge mode (-1≤x i ≤0), the penalty function is expressed as:

[0096] Where Penalty represents the penalty value, α1 and α2 are constants, c represents the maximum capacity of the energy storage system, and w = (υ + Zx T τ), which represents the energy stored in the energy storage system.

[0097] S212: construct an updated target power cost function based on the penalty function and the target power cost function.

[0098] In this embodiment, based on the penalty function and the target power cost function, an updated target power cost function is constructed. The updated target power cost function is expressed as:

[0099]

[0100] Among them, G(x) represents the electricity consumption cost of the park, p i represents the power load of the park at time i, T represents the peak function, kx i Indicates the charge / discharge power, P r (x i ) represents the price function, and Penalty represents the penalty function.

[0101] In this embodiment, the impact of peak and valley electricity prices is taken into account to prevent charging during peak electricity prices. The total power demand of the park at any time should not exceed the threshold specified by the main grid. The price function is expressed as:

[0102]

[0103] Among them, P r (x i ) represents the on-grid electricity price, β represents the real-time electricity price of the park, and p i represents the power load of the park at time i, kx irepresents the charge / discharge power, and T represents the peak function.

[0104] It is understandable that T is a threshold value, and the price of electricity will become more expensive if it exceeds this value. However, the consideration is to reduce the peak load as much as possible, so the energy storage utilization rate is relatively high. Therefore, the total amount of charging and discharging in each stage should be close to T, otherwise it will be very expensive. The electricity price function ensures that the total amount is close to T. If the electricity consumption in this stage does not exceed T, it is β. If it exceeds T, β will change according to the actual electricity consumption, making the price higher, thus ensuring that the optimization target is as small as possible from T. In this embodiment, a comprehensive economic analysis is performed based on the electricity price to prevent charging at peak electricity prices.

[0105] S213, using a particle swarm algorithm to solve the updated target power cost function until the target power cost function is minimized, and obtaining a calculated charging and discharging plan.

[0106] Among them, the charging and discharging plan includes the charging and discharging plan of the molten salt heat storage system and the charging and discharging plan of the battery energy storage system.

[0107] In this embodiment, PSO in the metaheuristic method is used to solve the target power cost function. The purpose of using the metaheuristic algorithm is to find a feasible solution within an acceptable time scale. PSO is used to simulate the social behavior of birds and fish. In this embodiment, the first step is to generate an initial population of randomly obtained candidate solutions, called a group, named particles. Each particle moves on the search space and has three main vectors: the current velocity vector, the best position vector of all particles, and its own best position vector. In each iteration of executing PSO, the velocity and position of particle j are updated as:

[0108]

[0109] in, i=1,2,...,M, and are the position and velocity vector of particle j when executing PSO iteration i, P best represents the optimal position of a single particle in the updated target power cost function, G best is the optimal position of all particles. One of the advantages of using PSO is that only a few parameters need to be adjusted and controlled, such as cognitive factor c1, social factor c2, inertia weight w, random value range x i , swarm size, and maximum number of iterations. Then, the positions are evaluated by the PSO cost function and the best position is determined. This process is repeated until the desired accuracy is achieved.

[0110] The optimization process based on PSO can be described as: initializing the parameters of the particle swarm optimization algorithm; generating a random initial population and the positions and velocities of randomly initialized particles; evaluating the cost function of the particles to define local and global solutions; updating the velocity of each particle; updating the optimal position and optimal cost; judging whether the optimization criteria are met, if so, defining it as the optimal solution and ending the optimization, if not, judging whether the maximum number of iterations has been reached; if the maximum number of iterations has been reached, defining it as the optimal solution and ending the optimization, if the maximum number of iterations has not been reached, calculating the penalty term, adding 1 to the number of iterations, and returning to re-executing the steps of evaluating the cost function of the particles to define local and global solutions.

[0111] The particle swarm algorithm is used to solve the updated target electricity cost function until the target electricity cost function is minimized, and the calculated charging and discharging plan is obtained. The charging and discharging plan includes charging and discharging of the molten salt heat storage system and charging and discharging of the battery energy storage system.

[0112] S214. Based on the charging and discharging plan, the molten salt heat storage system and the battery energy storage system are controlled to charge and discharge respectively.

[0113] The above technical scheme specifies the steps of constructing the models of each system in the park power supply system, and the steps of calculating the target power cost function under the constraint conditions until the set park power consumption cost conditions are reached, and controlling the charging and discharging of the molten salt heat storage system and the battery energy storage system based on the calculated charging and discharging plan. It is realized that the molten salt heat storage system and the battery energy storage system are used as two main energy storage systems to achieve peak load reduction. Through the analysis of the characteristics of different systems, the HVAC components, battery energy storage system, molten salt heat storage system, etc. are modeled. Different from the traditional optimization algorithm, the heuristic algorithm is used to improve the accuracy and speed of the calculation, so that the charging and discharging schemes of the molten salt heat storage system and the battery energy storage system can be effectively optimized, and the optimal charging and discharging scheme can be solved.

[0114] Embodiment 3

[0115] Figure 4 This is a schematic diagram of the structure of a park power supply system optimization operation device containing molten salt heat storage and electric energy storage provided in Example 3 of the present invention. The device can be applied to the situation of optimizing the park power supply system. The park power supply system optimization operation device containing molten salt heat storage and electric energy storage can be implemented in the form of hardware and / or software, and is generally integrated in electronic equipment. Figure 4 As shown, the system includes: a park system building module 31, a subsystem building module 32, a function building module 33 and an operation optimization module 34; wherein,

[0116] A park system construction module 31 is used to construct a park power supply system including a molten salt heat storage system, a battery energy storage system and a HVAC system;

[0117] A subsystem construction module 32, for constructing a first system model of a HVAC system, a second system model of a molten salt heat storage system, and a third system model of a battery energy storage system;

[0118] A function construction module 33, used to construct a target power cost function for calculating the power consumption cost of the park and constraints corresponding to the target power cost function according to the first system model, the second system model and the third system model;

[0119] The operation optimization module 34 is used to calculate the target power cost function under the constraint conditions until the set park power consumption cost conditions are reached, and control the molten salt thermal storage system and the battery energy storage system to charge and discharge based on the calculated charging and discharging plan.

[0120] The embodiment of the present invention provides an optimized operation device for a park power supply system containing molten salt heat storage and electric energy storage, which manages energy by combining molten salt heat storage technology with electric energy storage to achieve peak load reduction and reduce the capacity of the battery energy storage system. The optimal scheduling of charging and discharging of the molten salt heat storage system and the battery energy storage system is transformed into an optimization problem. By modeling the park power supply system and determining the objective function of the optimization problem, the operation optimization of the molten salt heat storage system and the battery energy storage system is determined by solving the objective function, thereby solving the problem of how to use the molten salt heat storage system and the battery energy storage system to reduce power consumption during peak hours.

[0121] Optionally, the device further includes a connection module, specifically configured to:

[0122] Connect the output end of the chiller of the HVAC system to the input end of the molten salt heat storage system, and connect the output end of the molten salt heat storage system to the park load equipment.

[0123] Optionally, the HVAC system includes a water chiller and an electric boiler, the water chiller including a condenser;

[0124] Further, the subsystem building module 32 includes a first building unit, which is used to:

[0125] Determine the heat generated by the chiller based on the condenser’s water outlet temperature, water inlet temperature, water flow rate, and specific heat capacity of water;

[0126] Based on the heat generated by the chiller and the power consumption used to generate the heat, a power consumption model of the chiller is constructed;

[0127] Determine the heat provided by the electric boiler based on the outlet temperature, inlet temperature, water flow rate and specific heat capacity of the water;

[0128] Based on the heat provided by the electric boiler and the power consumption used to generate the heat, a power consumption model of the electric boiler is constructed;

[0129] The power consumption model of the chiller and the power consumption model of the electric boiler are recorded as the first system model.

[0130] Optionally, the subsystem building module 32 includes a second building unit, which is used to:

[0131] Determine the amount of heat stored in the molten salt heat storage system based on the water outlet temperature and water inlet temperature of the condenser, the water flow rate provided to the molten salt heat storage system, and the specific heat capacity of water;

[0132] Based on the heat stored in the molten salt heat storage system and the amount of electricity that can be generated by the heat, a charging model of the molten salt heat storage system is constructed.

[0133] Optionally, the subsystem building module 32 includes a third building unit, specifically configured to:

[0134] According to the charging / discharging power, self-discharging rate, time interval and charging / discharging efficiency of the battery energy storage system, a kinetic model of electric energy storage is constructed and recorded as the third system model.

[0135] Optionally, the optimization module 34 is run, specifically for:

[0136] Taking the constraint condition as the penalty of the target power cost function, the penalty function corresponding to the energy stored in the battery energy storage system in the charging mode and the discharging mode is constructed respectively;

[0137] Based on the penalty function and the target power cost function, construct an updated target power cost function;

[0138] The particle swarm algorithm is used to solve the updated target power cost function until the target power cost function is minimized, and the calculated charging and discharging plan is obtained. The charging and discharging plan includes charging and discharging of the molten salt heat storage system and charging and discharging of the battery energy storage system.

[0139] Based on the charging and discharging plan, the molten salt thermal storage system and the battery energy storage system are controlled to charge and discharge respectively.

[0140] Optionally, the updated target electricity cost function is expressed as:

[0141]

[0142] Among them, G(x) represents the electricity consumption cost of the park, p i represents the power load of the park at time i, T represents the peak function, kx i Indicates the charge / discharge power, P r (x i ) represents the price function, and Penalty represents the penalty function.

[0143] Alternatively, the price function is expressed as:

[0144]

[0145] Among them, P r (x i ) represents the on-grid electricity price, β represents the real-time electricity price of the park, and p i represents the power load of the park at time i, kx i represents the charge / discharge power, and T represents the peak function.

[0146] In charging mode, the penalty function is expressed as:

[0147] In discharge mode, the penalty function is expressed as:

[0148] Where Penalty represents the penalty value, α1 and α2 are constants, c represents the maximum capacity of the energy storage system, and w = (υ + Zx T τ), which represents the energy stored in the energy storage system.

[0149] The device for optimizing operation of a park power supply system containing molten salt heat storage and electric energy storage provided in an embodiment of the present invention can execute the method for optimizing operation of a park power supply system containing molten salt heat storage and electric energy storage provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0150] Embodiment 4

[0151] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The components, their connections and relationships, and their functions shown herein are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0152] like Figure 5 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0153] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0154] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as the optimization operation method of the park power supply system containing molten salt heat storage and electric energy storage.

[0155] In some embodiments, the method for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the method for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to execute the method for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage by any other appropriate means (e.g., by means of firmware).

[0156] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0157] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0158] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0159] To provide interaction with a user, the systems and techniques described herein can be implemented on a vehicle having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the vehicle. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0160] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0161] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0162] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code for the operation of the present disclosure, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0163] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0164] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing the operation of a park power supply system containing molten salt heat storage and electric energy storage, characterized in that: include: Construct a campus power supply system including a molten salt thermal storage system, a battery energy storage system, and a HVAC system; Constructing a first system model of the HVAC system, a second system model of the molten salt heat storage system, and a third system model of the battery energy storage system; According to the first system model, the second system model and the third system model, construct a target power cost function for calculating the power consumption cost of the park and constraints corresponding to the target power cost function; The target power cost function is calculated under the constraint condition until the set park power consumption cost condition is reached, and the molten salt heat storage system and the battery energy storage system are controlled to charge and discharge based on the calculated charge and discharge plan.

2. The method according to claim 1, characterized in that After the construction of the campus power supply system including the molten salt heat storage system, the battery energy storage system and the HVAC system, it also includes: The output end of the chiller of the HVAC system is connected to the input end of the molten salt heat storage system, and the output end of the molten salt heat storage system is connected to the park load equipment.

3. The method according to claim 1, characterized in that The HVAC system includes a water chiller and an electric boiler, and the water chiller includes a condenser; The step of constructing a first system model of the HVAC system comprises: Determining the heat generated by the chiller according to the water outlet temperature, water inlet temperature, water flow rate and specific heat capacity of water of the condenser; Constructing a power consumption model of the chiller based on the heat generated by the chiller and the power consumption used to generate the heat; Determining the amount of heat provided by the electric boiler according to the water outlet temperature, water inlet temperature, water flow rate and specific heat capacity of water of the electric boiler; constructing a power consumption model of the electric boiler based on the heat provided by the electric boiler and the power consumption used to generate the heat; The power consumption model of the chiller and the power consumption model of the electric boiler are recorded as the first system model.

4. The method according to claim 3, characterized in that: The second system model of the molten salt heat storage system is constructed, comprising: Determining the amount of heat stored in the molten salt heat storage system according to the water outlet temperature, the water inlet temperature, the water flow rate provided to the molten salt heat storage system, and the specific heat capacity of water of the condenser; Based on the heat stored in the molten salt heat storage system and the amount of electricity that can be generated by the heat, a charging / discharging model of the molten salt heat storage system is constructed and recorded as a second system model.

5. The method according to claim 1, characterized in that The constructing of the third system model of the battery energy storage system comprises: According to the charging / discharging power, self-discharging rate, time interval and charging / discharging efficiency of the battery energy storage system, a kinetic model of the electric energy storage is constructed and recorded as the third system model.

6. The method according to claim 1, characterized in that The target power cost function is calculated under the constraint condition until the set park power consumption cost condition is reached, and the molten salt thermal storage system and the battery energy storage system are controlled to charge and discharge based on the calculated charge and discharge plan, including: Taking the constraint condition as a penalty for the target power cost function, respectively constructing penalty functions corresponding to the energy stored in the battery energy storage system in the charging mode and the discharging mode; constructing an updated target power cost function based on the penalty function and the target power cost function; Using a particle swarm algorithm to solve the updated target power cost function until the target power cost function is minimized, and obtaining a calculated charge and discharge plan, wherein the charge and discharge plan includes a charge and discharge plan for the molten salt heat storage system and a charge and discharge plan for the battery energy storage system; Based on the charging and discharging plan, the molten salt heat storage system and the battery energy storage system are controlled to charge and discharge respectively.

7. The method according to claim 6, characterized in that The updated target electricity cost function is expressed as: Among them, G(x) represents the electricity consumption cost of the park, p i represents the power load of the park at time i, T represents the peak function, kx i Indicates the charge / discharge power, P r (x i ) represents the price function, and Penalty represents the penalty function.

8. The method according to claim 7, characterized in that The price function is expressed as: Among them, P r (x i ) represents the on-grid electricity price, β represents the real-time electricity price of the park, and p i represents the power load of the park at time i, kx i represents the charge / discharge power, and T represents the peak function.

9. The method according to claim 7, characterized in that: In charging mode, the penalty function is expressed as: In the discharge mode, the penalty function is expressed as: Where Penalty represents the penalty value, α1 and α2 are constants, c represents the maximum capacity of the energy storage system, and w = (υ + Zx T τ), which represents the energy stored in the energy storage system.

10. A park power supply system optimization operation device containing molten salt heat storage and electric energy storage, characterized in that: include: The campus system building module is used to build a campus power supply system including a molten salt thermal storage system, a battery energy storage system, and a HVAC system; A subsystem construction module, used to construct a first system model of the HVAC system, a second system model of the molten salt heat storage system, and a third system model of the battery energy storage system; A function construction module, used to construct a target power cost function for calculating the power consumption cost of the park and constraints corresponding to the target power cost function according to the first system model, the second system model and the third system model; The operation optimization module is used to calculate the target power cost function under the constraint condition until the set park power consumption cost condition is reached, and the molten salt heat storage system and the battery energy storage system are controlled to charge and discharge respectively based on the calculated charge and discharge plan.

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