Optical storage direct flexible park adjustable load orderly energy utilization method and system

Abstract

The invention discloses an optical storage direct flexible park adjustable load orderly energy consumption method and system. The method comprises the following steps: constructing a first power grid architecture for a target park; establishing each equipment model in the target park, wherein each equipment model comprises a first type of model and a second type of model; establishing a first objective function and a first constraint condition based on the first power grid architecture and each equipment model; and solving the first objective function based on a first constraint condition to obtain an optimal scheme for orderly energy utilization of the adjustable load of the optical storage direct-flexible park. Through the implementation of the application, fine regulation and control of the adjustable load in the park can be realized, so that the energy utilization efficiency of the park is optimized while the power utilization demand of a user is met. And the park can be promoted to develop in a greener, more efficient and more intelligent direction, and a new solution is provided for realizing sustainable energy management.

Description

Technical Field

[0001] The present invention relates to the technical field of orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park, and in particular to a method and system for orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park. Background Art

[0002] The photovoltaic storage direct and flexible technology came into being under the background of global energy transformation. It aims to cope with many challenges faced by traditional power grids in accessing an increasing number of intermittent renewable energy sources, meeting the growing demand for electricity, ensuring grid stability and improving energy efficiency. The photovoltaic storage direct and flexible technology integrates advanced technologies such as photovoltaic power generation, energy storage system, DC power distribution and flexible power consumption to adapt to environmental protection requirements, technological development, policy incentives and changes in user needs, and promote the development of smart grids and clean energy. In the photovoltaic storage direct and flexible park, the main power generation equipment is rooftop distributed photovoltaics. Through the large-scale construction of photovoltaics, the power demand of user loads can be met; the excess photovoltaic power generation can be stored through distributed energy storage, and the power can be released and supplied to users when the photovoltaic power generation is low or no power generation; inside the buildings of the park, through the DC distribution system, the DC power generated by photovoltaics can be directly supplied to DC loads through voltage reduction, reducing the loss of AC-DC conversion; flexible power consumption is that the load users change their own power consumption by accepting the regulation of the dispatching center, reducing the power consumption of users during peak power consumption periods, encouraging more power consumption during low power consumption periods, and promoting peak shaving and valley filling.

[0003] The current operation method of the photovoltaic storage direct flexible park microgrid is as follows: the park produces electricity through distributed photovoltaic power generation, power grid purchase and other methods, and the electricity is directly supplied to the power load. Due to the access to new energy power generation, there will be surplus electricity when it is generated in large quantities. The excess electricity is stored in the park through power storage equipment (batteries, large capacitors, etc.). The park is usually optimized with the goal of minimizing the comprehensive operating cost (new energy power generation cost, equipment operating cost, electricity purchase cost, etc.) and the best peak shaving and valley filling effect. For photovoltaic storage direct flexible parks, the park usually only considers reducing operating costs and improving the effect of peak shaving and valley filling. The means of regulating adjustable loads are relatively rigid. The adjustable loads are only regulated by means of time-of-use electricity prices and price compensation, and user satisfaction is often ignored. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a method and system for orderly energy use of adjustable loads in a photovoltaic storage direct-flexible park, which can solve the problems mentioned in the background technology.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park, comprising:

[0009] Build the first power grid architecture for the target park;

[0010] Establishing each equipment model in the target park, wherein each equipment model includes a first type model and a second type model;

[0011] Establishing a first objective function and a first constraint condition based on the first power grid architecture and each device model;

[0012] The first objective function is solved based on the first constraint condition to obtain the optimal solution for orderly energy use of adjustable loads in the photovoltaic storage direct and flexible park.

[0013] As a preferred solution of the method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park described in the present invention, the first objective function includes:

[0014] The first objective function is an arbitrary function that aims to minimize the target park's operating cost, minimize the net load variance, and maximize the energy satisfaction of various adjustable loads.

[0015] As a preferred solution of the method for orderly energy use of adjustable loads in a photovoltaic storage and direct-flexible park described in the present invention, the first constraint condition includes:

[0016] The first constraint condition is to establish a target park equipment operation constraint based on the first power grid architecture and each equipment model;

[0017] The first constraint condition includes several different target park equipment operation constraints.

[0018] As a preferred solution of the method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park described in the present invention, wherein: the equipment models in the target park are established, and the equipment models include the first type of models and the second type of models include:

[0019] The first type of model is the equipment model whose load is classified as the adjustable part among the equipment models in the target park;

[0020] The second type of model is the equipment model whose load is classified as the non-adjustable part among the equipment models in the target park.

[0021] As a preferred scheme of the method for orderly energy use of adjustable loads in a photovoltaic storage and direct flexible park described in the present invention, the target park operating costs include the operating costs of distributed photovoltaic power generation, energy storage equipment, the cost of purchasing and selling electricity from the external grid, the cost of charging electric vehicles, and the operating costs of air-conditioning equipment.

[0022] As a preferred solution of the method for orderly energy use of adjustable loads in a photovoltaic storage direct-flexible park described in the present invention, the various adjustable load energy use satisfactions include electric vehicle charging efficiency satisfaction and air conditioning user thermal comfort satisfaction.

[0023] As a preferred solution of the method for orderly energy use of adjustable loads in a photovoltaic storage direct-flexible park described in the present invention, the minimum net load variance is obtained through the actual power load power and the total load power of the day-ahead scheduling plan.

[0024] In a second aspect, the present invention provides a load-adjustable orderly energy use system for a photovoltaic storage direct-flexible park, comprising:

[0025] An architecture building module, used to build a first power grid architecture for a target park;

[0026] A first model building module, used to build models of various devices in the target park, wherein the various device models include first-type models and second-type models;

[0027] A second model building module, used to establish a first objective function and a first constraint condition based on the first power grid architecture and each device model;

[0028] A solution module is used to solve the first objective function based on the first constraint condition to obtain the optimal solution for orderly energy use of adjustable loads in the photovoltaic storage direct and flexible park.

[0029] In a third aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0030] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method described above when executed by a processor.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention proposes a method and system for orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park, constructs a first power grid architecture for a target park; establishes models of each device in the target park, and each device model includes a first type of model and a second type of model; establishes a first objective function and a first constraint condition based on the first power grid architecture and each device model; solves the first objective function based on the first constraint condition to obtain the optimal solution for orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park. Through the implementation of this application, it is possible to achieve fine control of the adjustable loads in the park, thereby optimizing the energy efficiency of the park while meeting the electricity demand of users. This application not only takes into account the economic cost, but also takes into account user satisfaction and the stability of the power grid. By dynamically adjusting the load, it effectively alleviates the peak and valley load differences of the power grid and improves the efficiency of energy utilization. The implementation of this application helps to promote the development of the park in a more green, efficient and intelligent direction, and provides a new solution for achieving sustainable energy management. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing 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 labor. Among them:

[0033] Figure 1 A method flow chart of a method and system for orderly energy use of adjustable loads in a photovoltaic storage direct-flexible park provided by an embodiment of the present invention;

[0034] Figure 2 An internal structural diagram of a computer device of a method and system for orderly energy use of adjustable loads in a photovoltaic storage direct-flexible park provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0036] Example 1

[0037] Reference Figure 1-Figure 2 , which is the first embodiment of the present invention, provides a method and system for orderly energy use of adjustable loads in a photovoltaic storage direct-flexible park, including:

[0038] There are some problems in the existing related technologies, such as insufficient precision in load control within the park, low energy efficiency, and difficulty in balancing user satisfaction and grid stability.

[0039] This application provides a method that can effectively solve the above-mentioned problems. Next, we will combine multiple embodiments to explain in detail how to achieve the orderly energy use method of the adjustable load of the photovoltaic storage direct and flexible park;

[0040] Figure 1 A method flow chart of a method and system for orderly energy use of adjustable loads in a photovoltaic storage direct-flexible park is shown, including:

[0041] S101, building the first power grid architecture for the target park;

[0042] In an optional embodiment, different photovoltaic storage direct and flexible parks contain different main parts, which can generally include distributed photovoltaics, energy storage and power loads, DC distribution systems, intelligent control systems, two-way communication networks and other key parts. The AC power grid requires an inverter to convert the DC power generated by photovoltaics into AC power, while in the photovoltaic storage direct and flexible park, electricity is mainly transmitted and distributed in the form of DC, which reduces the loss in the energy conversion process. The intelligent control system is used to monitor and manage the operating status of the entire system, including power production and consumption. The intelligent control system can adjust the supply and demand balance of energy according to real-time data to achieve intelligent scheduling of equipment in the park. The communication network allows data to flow between components and supports remote monitoring, control and optimization operations. This is crucial for achieving automated management and fault detection. However, this application is intended to process the orderly energy use of adjustable loads in photovoltaic storage direct and flexible parks, so non-key parts such as DC distribution systems, intelligent control systems, and two-way communication networks are not considered. Relevant technical personnel can add or reduce the parts that need to be considered according to actual needs.

[0043] In the embodiment of the present application, the target park in the present application mainly comprises distributed photovoltaic, energy storage and power load. The distributed photovoltaic equipment in the target park is mainly used by users in the park; the energy storage is mainly used to absorb the excess photovoltaic and the excess electricity generated in the park, and the time-of-use electricity price can be used to purchase and store electricity at a lower price during the valley period, and release the electricity for load use or sell the electricity during the peak period to achieve energy arbitrage;

[0044] In the embodiment of the present application, electric vehicles and air-conditioning equipment in the target park are used as adjustable loads for detailed analysis.

[0045] It should be noted that building the first power grid architecture for the target park can provide a flexible and efficient energy management platform for the park. By optimizing the configuration and management of renewable energy and energy storage resources in the park, the dependence on traditional power grids can be effectively reduced, energy waste can be reduced, and energy efficiency can be improved. In addition, by dynamically adjusting the load through the intelligent control system, the orderly distribution of the load can be achieved, thereby improving the stability and economy of the power grid while ensuring the user's electricity demand. This orderly energy use method not only helps to improve the energy management level of the park, but also promotes the sustainable development of the park and provides strong support for the green transformation of the park. It can also provide a solid foundation for the establishment of the following first objective function.

[0046] S102, establishing each equipment model in the target park, each equipment model includes a first type model and a second type model;

[0047] In the embodiment of the present application, each device model in the target park is established, and each device model includes a first type of model and a second type of model including:

[0048] The first type of model is the equipment model whose load is classified as the adjustable part in each equipment model in the target park;

[0049] The second type of model is the equipment model whose load is classified as the non-adjustable part among the equipment models in the target park.

[0050] In an optional embodiment, the power load can be divided into adjustable load and non-adjustable load according to its flexibility. Some power loads cannot be interrupted for safety and technical reasons, such as life-sustaining equipment in hospitals, equipment in data centers, basic lighting, etc., and such loads are set as non-adjustable loads; some power loads, such as electric vehicles, air-conditioning equipment, and some power equipment of household users, can accept grid dispatching and can increase or decrease power consumption in a short time to assist in balancing the supply and demand of the grid. Such loads are adjustable loads.

[0051] In an optional embodiment, the power load can also be divided into adjustable load and non-adjustable load in other ways, for example, according to the usage characteristics of the power load, such as peak and valley electricity price responsiveness, user behavior patterns, etc. For adjustable loads, the intelligent control system can monitor the power grid load status in real time and dynamically adjust the load usage according to the real-time demand of the power grid to achieve the purpose of optimizing energy use and improving power grid stability. For non-adjustable loads, the system ensures that they can obtain stable power supply under any circumstances to ensure the normal operation of key facilities.

[0052] In an optional embodiment, the power load can also be divided into adjustable load and non-adjustable load in other ways, for example, according to the urgency and importance of the power load. For example, for some emergency service facilities, such as fire protection systems, emergency lighting, etc., they should be regarded as non-adjustable loads under any circumstances to ensure that they can be used immediately in an emergency. For some non-critical commercial or residential electricity, such as billboards, non-emergency lighting, etc., these can be classified as adjustable loads to reduce their power consumption when the power grid load is tight. Through this classification, the intelligent control system can manage the power resources in the park more accurately, ensure the stable operation of key facilities, and improve the overall energy efficiency.

[0053] In the embodiment of the present application, the power load can be divided into adjustable load and non-adjustable load according to its flexibility. Among them, the first type of model is a model established for electric vehicles, air-conditioning equipment, and some power-consuming equipment of household users. The second type of model is a model established for hospital life support equipment, data center equipment, basic lighting and other equipment.

[0054] In the embodiment of the present application, the distributed photovoltaic power generation power is related to the rated value of the device itself, the light intensity and the ambient temperature:

[0055]

[0056] Among them, P pv is the actual power of photovoltaic power generation, P pv,test is the maximum power generation of the photovoltaic device under standard test conditions, I out is the actual outdoor light intensity, I test k is the light intensity under standard test environment, generally 1kW / m2; p is the power temperature coefficient of photovoltaic power generation, generally taken as 0.004, T out is the actual outdoor temperature, T test It is the temperature under standard test environment, usually 25℃.

[0057] Furthermore, the charging and discharging power of energy storage equipment is affected by its own capacity and equipment efficiency, and in actual operation, the amount of energy stored at a certain moment is related to the previous moment:

[0058]

[0059] Among them, S ES,t+1 , S ES,t is the power of the energy storage device at time t+1 and time t, P cha,t , P dis,t is the charging and discharging power of the energy storage device at time t; η cha , η disCharging and discharging efficiency of energy storage devices.

[0060] Furthermore, the power load can be divided into adjustable load and non-adjustable load:

[0061] P Load,t =P un,t +(P ev,t +P ac,t )

[0062] Among them, P Load,t , P un,t , P ev,t , P ac,t It is the total power of power load, power of non-adjustable load, power of electric vehicle charging and power of air conditioner at time t.

[0063] Furthermore, electric vehicle charging is mainly divided into fast charging and slow charging modes:

[0064]

[0065] Where N is the number of electric vehicles connected to the charging station at time t, P ev,fast , P ev,slow Fast charging and slow charging power of electric vehicles, X ev,n is the fast charging mark of the nth electric vehicle, X ev,n When it is 1, the current time is fast charging mode, X ev,n When it is 0, the current moment is in slow charging mode.

[0066] Furthermore, the air conditioning load provides cooling capacity through electric refrigeration. The park can issue dispatching instructions to regulate the air conditioning load through air conditioning load aggregators and other channels to increase or reduce the power consumption of air conditioning. Generally, when the outdoor temperature is higher than the indoor temperature, the air conditioning starts to run. The power consumption of the air conditioning is mainly related to the outdoor and indoor temperatures:

[0067]

[0068] Among them, T out,t , T set,t is the outdoor temperature at time t and the indoor set temperature, λ is the air conditioning energy efficiency coefficient, and R is the equivalent thermal resistance of the building.

[0069] It should be noted that the establishment of each equipment model in the target park, including the first type of model and the second type of model, can provide accurate load information for the intelligent control system, thereby realizing real-time scheduling of adjustable loads and stable power supply for non-adjustable loads. Through the establishment of this model, the system can dynamically adjust the use of adjustable loads according to the real-time demand and load status of the power grid to optimize energy use and improve the stability of the power grid. At the same time, for non-adjustable loads, the system ensures that they can obtain a stable power supply under any circumstances to ensure the normal operation of key facilities. In addition, through the establishment of the model, the system can also predict and evaluate the impact of different loads on the power grid, provide data support for the energy management and planning of the park, and further improve the energy efficiency and economy of the park.

[0070] S103, establishing a first objective function and a first constraint condition based on the first power grid architecture and each device model;

[0071] In the embodiment of the present application, the first objective function includes:

[0072] The first objective function is an arbitrary function that aims to minimize the target park's operating cost, minimize the net load variance, and maximize the energy satisfaction of various adjustable loads.

[0073] In an optional embodiment, the first objective function can be established in a variety of ways, for example, linear programming, nonlinear programming, integer programming or mixed integer linear programming methods can be used. The construction of the objective function needs to comprehensively consider multiple factors such as the economy of the park, energy efficiency and user satisfaction. For example, the lowest operating cost can take into account the operation and maintenance costs of the equipment, the cost of energy purchase and possible penalty costs; the minimum net load variance focuses on reducing grid load fluctuations to reduce the impact on the grid and improve the stability of the grid; and the maximum adjustable load energy satisfaction requires consideration of user expectations and satisfaction with power supply to ensure that the load is reasonably scheduled while meeting user needs.

[0074] In an optional embodiment, the first objective function can also be established through other algorithms, such as genetic algorithms, simulated annealing algorithms, etc., to adapt to the specific needs and conditions of different parks. Through these algorithms, the optimal solution or approximate optimal solution that meets the requirements of the objective function can be found, thereby achieving precise control of the energy management of the park. In addition, the establishment of the first objective function also needs to consider the long-term development plan of the park to ensure the sustainability and adaptability of the energy management strategy. In practical applications, the parameters of the first objective function can be dynamically adjusted according to the real-time and historical data of the park to cope with changes in the energy market and the actual situation of the park's operations. In this way, the park can flexibly respond to various energy challenges and achieve optimization of energy management.

[0075] In the embodiment of the present application, linear programming is used to establish a multi-objective function to design the first objective function.

[0076] In the embodiment of the present application, the target park operating cost includes the operating cost of distributed photovoltaic power generation, the operating cost of energy storage equipment, the cost of purchasing and selling electricity from the external grid, the cost of charging electric vehicles, and the operating cost of air conditioning equipment. The various adjustable load energy satisfactions include the satisfaction with the charging benefits of electric vehicles and the thermal comfort satisfaction of air conditioning users. The minimum net load variance is obtained through the actual power load power and the total load power of the day-ahead scheduling plan.

[0077] In the embodiment of the present application, the first constraint condition includes:

[0078] The first constraint condition is to establish the target park equipment operation constraint based on the first power grid architecture and each equipment model;

[0079] The first constraint condition includes several different target park equipment operation constraints.

[0080] In an optional embodiment, depending on the first power grid architecture and the different equipment models, the constraints that need to be designed or the constraints that need to be considered for park operations are different. No limitation is made here, and relevant technical personnel can set different constraints according to actual conditions.

[0081] In the embodiment of the present application, the multi-objective function of orderly energy use of adjustable loads in the photovoltaic storage direct flexible park is constructed with the lowest target park operation cost, the smallest net load variance and the maximum satisfaction of various adjustable loads. The park operation cost f1 includes the operating cost of distributed photovoltaic power generation, the operating cost of energy storage equipment, the cost of electricity purchase and sale from the external grid, the cost of electric vehicle charging, and the operating cost of air conditioning equipment:

[0082]

[0083] Among them, r pv 、r ES 、r e,t 、r ev 、r ac is the unit price of distributed photovoltaic operation, the unit price of energy storage equipment charging and discharging, the time-of-use electricity price at time t, the unit price of electric vehicle charging, and the unit price of air conditioning operation. buy,t , P sell,t It is the power purchased and sold from the external power grid at time t.

[0084] Furthermore, the net load variance f2 describes the fluctuation degree of the park's optimized operation and is also an indicator of the adjustable load's participation in regulation. The smaller the net load variance, the more stable the park's operation.

[0085]

[0086] Among them, P Load,t is the actual load power at time t, is the total load after the adjustable load participates in regulation, P Load,plan,t is the total load power consumption of the day-ahead dispatch plan at time t, which is predicted from historical data.

[0087] Furthermore, the adjustable load energy satisfaction f3 includes the electric vehicle charging benefit satisfaction f ev Thermal comfort satisfaction of air-conditioning users ac The higher the satisfaction, the more it conforms to the interests of users.

[0088] f3=f ev +f ac

[0089]

[0090] L t =(MW)-3.05[5.733-0.007(MW)-P a ]-

[0091] 0.42(MW-58.15)-1.73×10 -2 M(5.867-P a )-

[0092] 1.4×10 -3 M(34-T in,t )-3.96×10 -8 f cl [(t cl +273) 4 -

[0093] (t r +273) 4 ]-f cl h c (t cl -T in,t )

[0094] Among them, a and b are the electric vehicle charging preference coefficients, M is the human energy metabolism rate, and L t is the heat load of the user's body at time t, W is the mechanical work done by the human body, P a is the partial pressure of water vapor around the human body, T in,t is the indoor temperature at time t, f cl is the clothing area coefficient, t cl is the average temperature of the outer surface of the garment, t r is the average radiation temperature of the environment, h c is the convective heat transfer coefficient.

[0095] In an optional embodiment, each objective function may be normalized.

[0096]

[0097] F=c1F1+c2F2+c3F3

[0098] c1+c2+c3=1

[0099] Among them, F n is the normalized value of the nth objective function, f n,min 、f n,max is the minimum and maximum value of the nth objective function, F is the normalized total objective function value, c1, c2, c3 are the weight coefficients set for each objective function.

[0100] In the embodiment of the present application, a first constraint condition for the operation of the park equipment is established. The first constraint condition in the present application is specifically as follows:

[0101] Distributed photovoltaic power generation power is not greater than the maximum power:

[0102] 0≤P pv,t ≤P pv,max

[0103] Among them, P pv,max It is the maximum value of photovoltaic power generation.

[0104] Furthermore, the amount of energy stored in an energy storage device is limited by its capacity, and the charge and discharge power is related to the amount of energy stored in the previous period:

[0105] 0≤S ES,t ≤S ES,max

[0106] 0≤P dis,t+1 ≤S ES,t

[0107] 0≤P cha,t+1 ≤S ES,max -S ES,t

[0108] Among them, S ES,max is the maximum storage capacity of the energy storage device, P dis,t+1 , P cha,t+1 are the discharge power and charging power at time t+1.

[0109] Furthermore, electric vehicle charging constraints:

[0110] 0≤P ev,t ≤H×P ev,fast

[0111] Among them, H is the number of charging piles in the park.

[0112] Furthermore, the operation of air conditioners is subject to the temperature range set indoors and the installed capacity of the air conditioners:

[0113] T in,min ≤T in,t ≤T in,max

[0114] 0≤P ac,t ≤P ac,max

[0115] Among them, T in,min , T in,max The minimum and maximum values ​​for the indoor temperature setting, P ac,max It is the maximum installed capacity of the air conditioner.

[0116] Furthermore, the power supply in the park should be greater than the power demand, and the balance constraints are as follows:

[0117] P pv,t +P dis,t +P buy,t ≥P ev,t +P ac,t +P un,t +P cha,t +P sell,t

[0118] Among them, P pv,t represents the photovoltaic power generation power at time t, P dis,t represents the discharge power of the energy storage device at time t, P buy,t Represents the power purchased from the external power grid at time t. ev,t P represents the charging power of the electric vehicle at time t. ac,t P represents the charging power of the air conditioner at time t. un,t Represents other unspecified power requirements. cha,t Represents the charging power of the energy storage device at time t. sell,t Represents the electric power sold to the external power grid at time t.

[0119] It should be noted that establishing the first objective function and the first constraint condition based on the first power grid architecture and each device model can achieve efficient utilization of energy and dynamic optimization of loads in the park. Through the optimization algorithm, the operating status of each device can be adjusted in real time to meet the power demand of the park while reducing dependence on the external power grid. In addition, by setting reasonable weight coefficients, the operating priorities of different devices can be balanced to ensure stable power supply of critical loads and improve the energy efficiency and economic benefits of the entire park. In practical applications, this method can effectively cope with the volatility of renewable energy and improve the flexibility and reliability of the park's energy system.

[0120] S104, solving the first objective function based on the first constraint condition to obtain the optimal solution for orderly energy use of adjustable loads in the photovoltaic, storage, direct and flexible park.

[0121] In an optional embodiment, the solution method and results are different depending on how the first constraint condition is used to solve the first objective function. The present application does not impose any restrictions here, because after the above-mentioned first constraint condition and the first target model are obtained, it is necessary to use the first constraint condition to solve the first objective function. No matter what solution method is used or what solver is used, it needs to be performed under the first constraint condition.

[0122] In an optional embodiment, the solution method or solver may include solving using a Gurobi solver, solving using a CPLEX solver, solving using a linear programming method, solving using a nonlinear programming method, solving using a heuristic algorithm, etc.

[0123] In the embodiment of the present application, in order to solve the nonlinear term contained in the first objective function, the Gurobi solver is selected for solving, and the specific steps can be as follows:

[0124] Step 1: Input the 24-hour predicted power load data of a solar-storage-direct-flexible park, including adjustable load and non-adjustable load; input the time-of-use electricity price, and input the capacity parameters, operation parameters, and cost parameters of each device;

[0125] Step 2: Taking the output of each device and the adjustable load power as the variables to be optimized, determine the boundary range of the output of each device according to the first constraint condition;

[0126] Step 3: Input the normalized first objective function and use the Gurobi solver to solve the optimal equipment output solution.

[0127] In summary, the present invention proposes a method for orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park, constructs a first power grid architecture for a target park; establishes models of each device in the target park, and each device model includes a first type of model and a second type of model; establishes a first objective function and a first constraint condition based on the first power grid architecture and each device model; solves the first objective function based on the first constraint condition to obtain an optimal solution for orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park. Through the implementation of this application, it is possible to achieve fine control of the adjustable loads in the park, thereby optimizing the energy efficiency of the park while meeting the electricity demand of users. This application not only takes into account the economic cost, but also takes into account user satisfaction and the stability of the power grid. By dynamically adjusting the load, it effectively alleviates the peak and valley load differences of the power grid and improves the efficiency of energy utilization. The implementation of this application helps to promote the development of the park in a more green, efficient and intelligent direction, and provides a new solution for achieving sustainable energy management.

[0128] This embodiment also provides a solar-storage direct-flexible park load-adjustable orderly energy use system, including:

[0129] An architecture building module, used to build a first power grid architecture for a target park;

[0130] The first model building module is used to build models of each device in the target park, and each device model includes a first type model and a second type model;

[0131] A second model building module, used to establish a first objective function and a first constraint condition based on the first power grid architecture and each device model;

[0132] The solution module is used to solve the first objective function based on the first constraint condition to obtain the optimal solution for orderly energy use of adjustable loads in the photovoltaic storage direct and flexible park.

[0133] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0134] This embodiment also provides a computer device, which may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 2As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse.

[0135] This embodiment further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0136] Build the first power grid architecture for the target park;

[0137] Establishing models of various devices in the target park, wherein each device model includes a first type model and a second type model;

[0138] Establishing a first objective function and a first constraint condition based on the first power grid architecture and each device model;

[0139] Based on the first constraint, the first objective function is solved to obtain the optimal solution for orderly energy use of adjustable loads in the photovoltaic storage direct and flexible park.

[0140] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0141] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0142] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0143] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0144] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0145] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0146] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park, characterized in that: include: Build the first power grid architecture for the target park; Establishing each equipment model in the target park, wherein each equipment model includes a first type model and a second type model; Establishing a first objective function and a first constraint condition based on the first power grid architecture and each device model; The first objective function is solved based on the first constraint condition to obtain the optimal solution for orderly energy use of adjustable loads in the photovoltaic storage direct and flexible park.

2. The method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park according to claim 1 is characterized in that: The first objective function includes: The first objective function is an arbitrary function that aims to minimize the target park's operating cost, minimize the net load variance, and maximize the energy satisfaction of various adjustable loads.

3. The method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park as claimed in claim 2 is characterized in that: The first constraint condition includes: The first constraint condition is to establish a target park equipment operation constraint based on the first power grid architecture and each equipment model; The first constraint condition includes several different target park equipment operation constraints.

4. The method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park as claimed in claim 3 is characterized in that: The device models in the target park are established, wherein the device models include first-type models and second-type models including: The first type of model is the equipment model whose load is classified as the adjustable part among the equipment models in the target park; The second type of model is the equipment model whose load is classified as the non-adjustable part among the equipment models in the target park.

5. The method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park as claimed in claim 4 is characterized in that: The target park operating costs include the operating costs of distributed photovoltaic power generation, the operating costs of energy storage equipment, the costs of purchasing and selling electricity from the external grid, the costs of charging electric vehicles, and the operating costs of air-conditioning equipment.

6. The method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park as claimed in claim 5 is characterized in that: The various adjustable load energy satisfaction levels include electric vehicle charging efficiency satisfaction and air-conditioning user thermal comfort satisfaction.

7. The method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park as claimed in claim 6 is characterized in that: The minimum net load variance is obtained by the actual power load power and the total load power of the day-ahead scheduling plan.

8. A photovoltaic storage direct and flexible park load adjustable orderly energy use system, characterized in that: include: An architecture building module, used to build a first power grid architecture for a target park; A first model building module, used to build models of various devices in the target park, wherein the various device models include first-type models and second-type models; A second model building module, used to establish a first objective function and a first constraint condition based on the first power grid architecture and each device model; A solution module is used to solve the first objective function based on the first constraint condition to obtain the optimal solution for orderly energy use of adjustable loads in the photovoltaic storage direct and flexible park.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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