Method and device for optimizing energy consumption of producer and consumer by considering energy storage life loss

Abstract

The invention discloses a method and a device for optimizing energy consumption of a consumer in consideration of energy storage life loss. The method comprises the following steps: acquiring electricity purchasing price and electricity selling price of the consumer from a power grid; according to the electricity purchasing price and the electricity selling price from the power grid by the consumer and the electricity purchasing power and the electricity selling power from the power grid by the consumer, obtaining the electricity utilization cost of the consumer; according to the electricity utilization cost, the comfort loss cost caused by the energy utilization change, the energy storage life loss cost and the photovoltaic system operation and maintenance cost, a producer and consumer total operation cost function is constructed; and according to the total energy consumption optimization constraint, the energy storage system constraint, the interruptible load constraint, the transferable load constraint and the power balance constraint, solving the total operation cost function of the producer and the consumer, and determining an energy consumption strategy of the producer and the consumer. By adding the energy storage life loss cost and solving the energy storage life loss cost when constructing the total operation cost function of the producer and the disagger, the solved energy consumption optimization strategy of the producer and the disagger is accurate and feasible while the full life cycle cost of the energy storage equipment is considered.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method and device for optimizing energy use of producers and consumers taking into account the life loss of energy storage. Background Art

[0002] With the continuous construction of new power systems and the gradual liberalization of the power sales market, the penetration rate of distributed energy on the demand side continues to increase, and traditional electricity users are gradually transformed into prosumers with the dual attributes of "source-load". Prosumers refer to users who are both electricity consumers and electricity producers. The role of such users in the energy market is becoming increasingly prominent.

[0003] Prosumers use energy storage systems to balance supply and demand and improve energy efficiency. However, the life loss of energy storage systems, especially the degradation caused by frequent charging and discharging, is a key factor affecting their economic benefits and reliability. Traditional prosumer energy optimization strategies often focus on common factors such as electricity costs and supply and demand balance. When building models and formulating plans, the life loss of energy storage systems is not taken into consideration. As the key link for prosumers to balance electricity supply and demand, frequent charging and discharging cycles will inevitably cause life loss of energy storage systems. It is precisely because of this neglect that the prosumer energy optimization strategy obtained through solution is not accurate enough and cannot achieve the expected results in practical applications. Summary of the invention

[0004] The embodiments of the present application provide a method and device for optimizing energy consumption of prosumers taking into account the life loss of energy storage. By adding the energy storage life loss cost and solving it when constructing the total operating cost function of the prosumer, it is possible to make the energy consumption optimization strategy of the prosumer obtained by solving it accurate and feasible while taking into account the full life cycle cost of the energy storage equipment.

[0005] In a first aspect, an embodiment of the present application provides a method for optimizing energy consumption by a prosumer taking into account energy storage life loss, the method comprising: The electricity price information calculated by the power grid according to the output of new energy is used to determine the purchase price of electricity from the power grid and the sales price of electricity from the power grid by the prosumer; the electricity cost of the prosumer is obtained according to the purchase price of electricity from the power grid, the sales price of electricity from the power grid, the purchase power of the prosumer from the power grid and the sales power of the prosumer to the power grid; the comfort loss cost caused by the energy consumption change of the prosumer is obtained according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer and the predicted electricity consumption power of the prosumer; the energy storage life of the prosumer is determined according to the comfort loss coefficient of the prosumer; the comfort loss cost caused by the energy consumption change of the prosumer is obtained according to the energy storage life of the prosumer. The loss cost coefficient, the charging power of the energy storage system and the discharging power of the energy storage system are used to obtain the energy storage life loss cost of the prosumer; the photovoltaic system operation and maintenance cost of the prosumer is obtained according to the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer; the total operation cost function of the prosumer is constructed according to the electricity cost, the comfort loss cost caused by the energy consumption change, the energy storage life loss cost and the photovoltaic system operation and maintenance cost; the total operation cost function of the prosumer is solved according to the total energy consumption optimization constraints, the energy storage system constraints, the interruptible load constraints, the transferable load constraints and the power balance constraints to determine the energy consumption strategy of the prosumer.

[0006] In a possible implementation, the electricity cost of the prosumer is obtained according to the electricity purchase price of the prosumer from the power grid, the electricity sale price of the prosumer to the power grid, the power purchased by the prosumer from the power grid, and the power sold by the prosumer to the power grid, including: Obtain a first product of the price at which the prosumer purchases electricity from the grid and the power at which the prosumer purchases electricity from the grid; obtain a second product of the price at which the prosumer sells electricity to the grid and the power at which the prosumer sells electricity to the grid; obtain a first difference between the first product and the second product, the first difference being the electricity cost of the prosumer.

[0007] In a possible implementation, obtaining the comfort loss cost caused by the energy consumption change of the prosumer according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer, and the predicted power consumption of the prosumer includes: Obtain a second difference between the optimized power consumption of the prosumer and the predicted power consumption of the prosumer; obtain a third product of the demand response comfort loss coefficient of the prosumer and the square of the second difference, wherein the third product is the comfort loss cost caused by the energy consumption change of the prosumer.

[0008] In a possible implementation, the energy storage life loss cost of the prosumer is obtained according to the energy storage life loss cost coefficient of the prosumer, the energy storage system charging power, and the energy storage system discharging power, including: Determine the energy storage life loss cost coefficient of the prosumer according to the energy storage efficiency, the rated power of the energy storage, the unit operation and maintenance cost of the target time period, the estimated operating life of the energy storage system, the discount rate, the number of cycles of the target time period, the energy storage cost of the energy storage, the power storage cost of the energy storage and the rated service life of the energy storage; obtain a first sum of the charging power of the energy storage system and the discharging power of the energy storage system; obtain a fourth product of the first sum and the energy storage life loss cost coefficient of the prosumer, the fourth product being the energy storage life loss cost coefficient of the prosumer.

[0009] In one possible implementation, the calculation formula of the energy storage life loss cost coefficient of the prosumer is as follows: ; in, is the energy storage efficiency; is the rated power of the energy storage; is the unit operation and maintenance cost for the target time period; is the estimated operating life of the energy storage system; is the discount rate; is the number of cycles of the target time period; an energy storage cost for said stored energy; is the power storage cost of the energy storage; is the rated service life of the energy storage.

[0010] In a possible implementation, the photovoltaic system operation and maintenance cost of the prosumer is obtained according to the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer, including: The fifth product of the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer is obtained, and the fifth product is the photovoltaic system operation and maintenance cost of the prosumer.

[0011] In one possible implementation, the total cost function of the prosumer is constructed based on the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost, and the photovoltaic system operation and maintenance cost, including: The total operating cost is obtained based on the sum of the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost and the photovoltaic system operation and maintenance cost; the total operating cost function of the prosumer is constructed by minimizing the total operating cost within the regulation cycle.

[0012] In a possible implementation, according to the total energy consumption optimization constraint, the energy storage system constraint, the interruptible load constraint, the transferable load constraint and the power balance constraint, the total operation cost function of the prosumer is solved, including: Under the premise of satisfying the total energy optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints and power balance constraints, the total operating cost function of the prosumer is used as the particle fitness of each optimization in the improved particle swarm algorithm based on reverse learning. If the number of iterations exceeds the preset number of iterations, or the error of any iteration is less than the preset error, the solution is terminated, and the particle position corresponding to the swarm optimal value of the improved particle swarm algorithm based on reverse learning is determined as the solution of the total operating cost function of the prosumer.

[0013] In a second aspect, an embodiment of the present application provides a prosumer energy optimization device taking into account energy storage life loss, the device comprising: An acquisition module, used to determine the electricity price that the prosumer purchases from the grid and the electricity price that the prosumer sells to the grid through the electricity price information calculated by the grid according to the output of new energy; and for obtaining the electricity cost of the prosumer according to the electricity price purchased by the prosumer from the power grid, the electricity price sold by the prosumer to the power grid, the power purchased by the prosumer from the power grid, and the power sold by the prosumer to the power grid; and for obtaining the comfort loss cost caused by the energy consumption change of the prosumer according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer and the predicted power consumption power of the prosumer; and for obtaining the energy storage life loss cost of the prosumer according to the energy storage life loss cost coefficient of the prosumer, the energy storage system charging power and the energy storage system discharging power; and for obtaining the photovoltaic system operation and maintenance cost of the prosumer according to the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer; A construction module is used to construct a total operating cost function for prosumers based on electricity costs, comfort loss costs caused by energy consumption changes, energy storage life loss costs, and photovoltaic system operation and maintenance costs; The solution module is used to solve the total operating cost function of the prosumer and determine the energy consumption strategy of the prosumer according to the total energy consumption optimization constraint, the energy storage system constraint, the interruptible load constraint, the transferable load constraint and the power balance constraint.

[0014] In a third aspect, an embodiment of the present application provides a computer, including: A memory, a processor, and an executable program code stored in the memory and executable on the processor, wherein the executable program code is configured to implement part or all of the steps described in any method in the first aspect.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which is stored a prosumer energy optimization program that takes into account the life loss of energy storage. When the prosumer energy optimization program that takes into account the life loss of energy storage is executed by a processor, some or all of the steps described in any method in the first aspect are implemented.

[0016] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in any method of the first aspect of the embodiment of the present application. The computer program product can be a software installation package.

[0017] By implementing the embodiments of the present application, the electricity price information calculated by the power grid according to the output of new energy is first used to determine the electricity price at which the prosumer purchases electricity from the power grid and the electricity price at which the prosumer sells electricity to the power grid; then, the electricity cost of the prosumer is obtained based on the electricity price at which the prosumer purchases electricity from the power grid, the electricity price at which the prosumer sells electricity to the power grid, the power purchased by the prosumer from the power grid, and the power sold by the prosumer to the power grid; then, the comfort loss cost caused by the energy consumption change of the prosumer is obtained based on the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer, and the predicted electricity consumption power of the prosumer; then, the comfort loss cost caused by the energy consumption change of the prosumer is obtained based on the prosumer demand response comfort loss coefficient, the optimized energy consumption power of the prosumer, and the predicted electricity consumption power of the prosumer. The energy storage life loss cost coefficient, energy storage system charging power and energy storage system discharging power of the prosumer are used to obtain the energy storage life loss cost of the prosumer; then, the photovoltaic system operation and maintenance cost of the prosumer is obtained according to the photovoltaic cost coefficient and photovoltaic predicted output of the prosumer; then, the total operation cost function of the prosumer is constructed according to the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost and the photovoltaic system operation and maintenance cost; finally, according to the total energy consumption optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints and power balance constraints, the total operation cost function of the prosumer is solved to determine the energy consumption strategy of the prosumer. By adding the energy storage life loss cost and solving it when constructing the total operation cost function of the prosumer, it is possible to make the energy consumption optimization strategy of the prosumer obtained by the solution accurate and feasible while considering the full life cycle cost of the energy storage equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0019] Figure 1 It is a schematic diagram of the architecture of a prosumer energy optimization system taking into account the energy storage life loss provided in an embodiment of the present application; Figure 2It is a flow chart of a method for optimizing energy consumption of prosumers taking into account energy storage life loss provided in an embodiment of the present application; Figure 3 is a flow chart of a method for obtaining the electricity cost of a prosumer provided in an embodiment of the present application; Figure 4 It is a flow chart of a method for obtaining the comfort loss cost caused by the energy consumption change of the prosumer provided in an embodiment of the present application; Figure 5 It is a flow chart of a method for obtaining the energy storage life loss cost of a prosumer provided in an embodiment of the present application; Figure 6 It is a flow chart of a method for constructing a total cost function of a producer and consumer provided in an embodiment of the present application; Figure 7 It is a structural schematic diagram of a prosumer energy optimization device taking into account energy storage life loss provided in an embodiment of the present application; Figure 8 It is a structural diagram of a computer provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. According to the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0021] The terms "first", "second", "third", etc. in the specification, claims and drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof 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 limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0022] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0023] With the continuous construction of new power systems and the gradual liberalization of the power sales market, the penetration rate of distributed energy on the demand side continues to increase, and traditional electricity users are gradually transformed into prosumers with the dual attributes of "source-load". Prosumers refer to users who are both electricity consumers and electricity producers. The role of such users in the energy market is becoming increasingly prominent.

[0024] Prosumers use energy storage systems to balance supply and demand and improve energy efficiency. However, the life loss of energy storage systems, especially the degradation caused by frequent charging and discharging, is a key factor affecting their economic benefits and reliability. Traditional prosumer energy optimization strategies often focus on common factors such as electricity costs and supply and demand balance. When building models and formulating plans, the life loss of energy storage systems is not taken into consideration. As the key link for prosumers to balance electricity supply and demand, frequent charging and discharging cycles will inevitably cause life loss of energy storage systems. It is precisely because of this neglect that the prosumer energy optimization strategy obtained through solution is not accurate enough and cannot achieve the expected results in practical applications.

[0025] In the embodiment of the present application, the power grid first obtains the electricity price information calculated according to the output of new energy, and determines the electricity price that the prosumer purchases from the power grid and the electricity price that the prosumer sells to the power grid; then, the electricity cost of the prosumer is obtained according to the electricity price that the prosumer purchases from the power grid, the electricity price that the prosumer sells to the power grid, the power purchased from the power grid by the prosumer, and the power sold to the power grid by the prosumer; then, the comfort loss cost caused by the energy consumption change of the prosumer is obtained according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer, and the predicted electricity consumption power of the prosumer; then, the comfort loss cost caused by the energy consumption change of the prosumer is obtained according to the storage power of the prosumer The energy life loss cost coefficient, the energy storage system charging power and the energy storage system discharging power are used to obtain the energy storage life loss cost of the prosumer; then, the photovoltaic system operation and maintenance cost of the prosumer is obtained according to the photovoltaic cost coefficient and photovoltaic predicted output of the prosumer; then, the total operation cost function of the prosumer is constructed according to the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost and the photovoltaic system operation and maintenance cost; finally, according to the total energy consumption optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints and power balance constraints, the total operation cost function of the prosumer is solved to determine the energy consumption strategy of the prosumer. By adding the energy storage life loss cost and solving it when constructing the total operation cost function of the prosumer, it is possible to make the energy consumption optimization strategy of the prosumer obtained by the solution accurate and feasible while considering the full life cycle cost of the energy storage equipment.

[0026] The energy optimization method and device for prosumers considering energy storage life loss provided in the embodiments of the present application can be applied to Figure 1 In the prosumer energy optimization system shown, see Figure 1 , Figure 1 1 is a schematic diagram of the architecture of a prosumer energy optimization system provided in an embodiment of the present application. The prosumer energy optimization system 100 includes a terminal 101 and a server 102. The terminal 101 can communicate with the server 102 through a network. The terminal 101 refers to a device used by a user, such as a smart phone, a computer, etc. In this solution, the terminal 101 provides an interface for the user to interact with the prosumer energy optimization system 100 that considers the energy storage life loss. Through the terminal 101, the user can interact with the prosumer energy optimization system 100 that considers the energy storage life loss, receive the prosumer energy optimization strategy obtained by solving and sent from the server 102, and display it on the user interface. The user can understand the prosumer energy optimization strategy executed in the current time period through the terminal 101, and can also set or change multiple parameters required to be used in determining the prosumer energy optimization strategy through the terminal 101, such as the prosumer photovoltaic cost coefficient and the prosumer demand response comfort loss coefficient.

[0027] Server 102 refers to a remote computer used to process a large number of computing tasks and store data. In this solution, server 102 is responsible for constructing the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost, and the photovoltaic system operation and maintenance cost based on the multiple data obtained. Server 102 will then construct the total operating cost function of the prosumer based on the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost, and the photovoltaic system operation and maintenance cost, and then solve the total operating cost function of the prosumer based on the total energy consumption optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints, and power balance constraints to determine the prosumer's energy consumption strategy.

[0028] Based on this, the present application provides a method and device for optimizing energy consumption of producers and consumers taking into account the loss of energy storage life. The present application is described in detail below in conjunction with the accompanying drawings.

[0029] See also Figure 2 , Figure 2 is a flow chart of a method for optimizing energy consumption by prosumers taking into account energy storage life loss provided in an embodiment of the present application, such as Figure 2 As shown, the method comprises the following steps: S201, determining the electricity price at which the prosumer purchases electricity from the grid and the electricity price at which the prosumer sells electricity to the grid through electricity price information calculated by the grid according to the output of new energy.

[0030] Among them, the power grid collects relevant data on renewable energy power generation in real time through various monitoring equipment and sensors installed on renewable energy power generation facilities such as wind power and photovoltaic power generation facilities. The relevant data include but are not limited to power generation, power generation, voltage, frequency, etc. For example, in a large wind farm, each wind turbine is equipped with a monitoring device to transmit its own operating data to the farm-level monitoring system, which is then summarized by the farm-level monitoring system and uploaded to the power grid dispatching center.

[0031] Among them, the power grid uses professional power market pricing models and algorithms to calculate the real-time electricity price of the power market based on the real-time monitoring of the output of new energy, power grid load forecasts, power system operation status and other related factors. This electricity price changes dynamically and takes into account various factors such as the supply and demand relationship of electricity in different periods, power generation costs, and power grid operation efficiency. After that, the power grid will inform the relevant producers and consumers of the real-time electricity price information of the power market through specific information release channels, such as the power market trading platform, official website, SMS notifications, etc. The producers and consumers will then determine the purchase price of electricity from the power grid and the sales price of electricity to the power grid based on the real-time electricity price information of the power market.

[0032] Specifically, prosumers can determine the price of electricity purchased from the grid and the price of electricity sold to the grid based on their own renewable energy power generation costs, expected revenues, market competition, and judgments on future electricity market price trends. For example, for the price of electricity purchased from the grid, if prosumers expect future electricity prices to rise and the current real-time electricity price is relatively low, they will choose to purchase more electricity at the current real-time electricity price. On the contrary, if prosumers believe that the current electricity price is too high and their own electricity demand is not urgent, they will choose to temporarily reduce the amount of electricity purchased.

[0033] For the electricity price sold to the grid, if the prosumer believes that its own power generation cost is low and expects the market price to be high, the electricity price will be set relatively high. On the contrary, if the prosumer hopes to sell the electricity as soon as possible, it will refer to the real-time market electricity price and set the electricity price below the market average.

[0034] S202, obtaining the electricity cost of the prosumer according to the electricity purchase price of the prosumer from the grid, the electricity sale price of the prosumer to the grid, the power purchased by the prosumer from the grid, and the power sold by the prosumer to the grid.

[0035] The power purchased by the prosumer from the grid refers to the power consumed per unit time when the prosumer obtains electricity from the grid, usually in kilowatts (kW) or megawatts (MW). When the prosumer's own electrical equipment is running, it needs to draw electricity from the grid to meet its electricity demand. The rate at which this electricity is drawn is the power purchased.

[0036] The power sold by prosumers to the grid refers to the power output per unit time when prosumers transmit excess power generated by their own renewable energy power generation equipment (such as solar panels, wind turbines, etc.) to the grid, also in kilowatts (kW) or megawatts (MW). When the renewable energy power generation of prosumers exceeds their own electricity demand, the remaining power can be sold to the grid, and the rate of power transmission to the grid is the power sold.

[0037] In one possible implementation, see Figure 3 , Figure 3 is a flow chart of a method for calculating the electricity cost of a producer and consumer provided in an embodiment of the present application, such as Figure 3 As shown, according to the electricity price purchased by the prosumer from the grid, the electricity price sold by the prosumer to the grid, the power purchased by the prosumer from the grid, and the power sold by the prosumer to the grid, the electricity cost of the prosumer is obtained, including: obtaining a first product of the electricity price purchased by the prosumer from the grid and the power purchased by the prosumer from the grid; obtaining a second product of the electricity price sold by the prosumer to the grid and the power sold by the prosumer to the grid; obtaining a first difference between the first product and the second product, the first difference being the electricity cost of the prosumer.

[0038] Among them, the electricity cost of the prosumer is equal to the difference between the electricity purchase fee and the electricity sales fee. At a certain moment, the electricity purchase fee is the product of the electricity purchase price and the purchased power of the prosumer from the power grid, and the electricity sales fee is the product of the electricity sales price and the electricity sales power of the prosumer to the power grid. At this time, the electricity cost of the prosumer is equal to the product of the electricity purchase price and the purchased power of the prosumer from the power grid minus the product of the electricity sales price and the electricity sales power of the prosumer to the power grid.

[0039] Specifically, the calculation formula for electricity cost at time t is as follows: ; in, is the electricity price that the prosumer purchases from the grid at time t, is the electricity price sold by the prosumer to the grid at time t, and They are respectively the power purchased by the prosumer from the grid and the power sold by the prosumer to the grid at time t.

[0040] It can be seen that in this example, the electricity cost of the prosumer is determined by the difference between the product of the power purchase price and the power purchased by the prosumer from the grid and the product of the power sale price and the power sold by the prosumer to the grid. This can accurately reflect the economic income and expenditure in its electricity transaction, thereby encouraging the prosumer to optimize energy allocation and flexibly adjust strategies according to electricity price fluctuations.

[0041] S203, obtaining the comfort loss cost caused by the energy consumption change of the prosumer according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer and the predicted electricity consumption power of the prosumer.

[0042] Among them, the comfort loss coefficient of the demand response of the prosumer refers to a quantitative indicator of the degree of comfort reduction caused by the prosumer changing its own electricity consumption behavior pattern when responding to demand. For example, in order to respond to the load adjustment requirements of the power grid, the prosumer may adjust the air-conditioning temperature, reduce the use of electrical appliances, etc., and these behaviors will have a certain impact on the comfort of their life or production. At this time, the comfort loss coefficient of the prosumer's demand response can be used to measure the impact of such behaviors on the comfort of life or production.

[0043] Specifically, the comfort loss coefficient of the demand response of the prosumer can be configured or changed by the user at the terminal of the prosumer energy optimization system. The comfort loss coefficient of the demand response of the prosumer can also be established by the user to establish a mathematical model, classify and quantify the various electricity consumption behaviors of the prosumer and the corresponding user comfort, and then combine the comfort feedback data of the prosumer under different electricity consumption behaviors to establish a relationship model between the change in electricity consumption behavior and the comfort loss, so as to obtain the demand response comfort loss coefficient.

[0044] The optimized energy consumption of prosumers refers to the most reasonable and economical power consumption obtained through optimization algorithms or strategies based on the prosumers' own energy production capacity, power equipment characteristics, power demand, and external environmental factors (such as electricity prices, grid load conditions, etc.). The optimized energy consumption of prosumers can minimize the power cost while meeting the basic power demand of prosumers.

[0045] Specifically, the optimized energy consumption of prosumers can be obtained by establishing an optimization model. First, the optimization goal is determined, such as minimizing electricity costs or maximizing energy efficiency. Then, considering constraints such as the energy production capacity of prosumers, the power range and operating time requirements of electrical equipment, the power supply capacity and safety restrictions of the power grid, etc., appropriate optimization algorithms are selected, such as linear programming, nonlinear programming, genetic algorithms, etc., to solve the model and obtain the optimized energy consumption of prosumers.

[0046] Among them, the predicted power consumption of the prosumer refers to the estimated value of the power consumption of the prosumer in a certain period of time in the future. Specifically, the predicted power consumption of the prosumer can be calculated by methods based on historical data and methods based on physical models. The methods based on historical data include time series analysis, neural networks, support vector machines, etc. By analyzing the past power consumption data of the prosumer, mining the laws and trends therein, establishing a prediction model, and then predicting future power consumption. The method based on the physical model is to establish a corresponding power consumption calculation model based on the physical characteristics of the prosumer's power equipment, such as type, quantity, usage law, and production activities, and combine future production plans, life arrangements and other information to predict power consumption.

[0047] In one possible implementation, see Figure 4 , Figure 4 is a flow chart of a method for obtaining the comfort loss cost caused by the energy consumption change of the prosumer provided in an embodiment of the present application, such as Figure 4 As shown, according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer and the predicted power consumption power of the prosumer, the comfort loss cost caused by the energy consumption change of the prosumer is obtained, including: Obtain a second difference between the optimized power consumption of the prosumer and the predicted power consumption of the prosumer; obtain a third product of the demand response comfort loss coefficient of the prosumer and the square of the second difference, wherein the third product is the comfort loss cost caused by the energy consumption change of the prosumer.

[0048] Among them, the difference between the optimized power consumption of the prosumer and the predicted power consumption reflects the degree of change in the actual power consumption behavior. The larger the difference, the greater the change in power consumption behavior, and the greater the impact on comfort. The difference is squared to highlight the impact of the change on the comfort loss, because the comfort loss is often not a simple linear relationship with the change in power consumption. Then the demand response comfort loss coefficient is multiplied by the square of the difference. Since the demand response comfort loss coefficient can be adjusted according to different prosumers or different power consumption scenarios, the comfort loss cost caused by the energy consumption change of the prosumer obtained by the final multiplication can comprehensively consider the comfort loss caused by the power consumption changes under different individual differences and power consumption scenarios.

[0049] Specifically, the calculation formula for the comfort loss cost caused by the energy consumption change of the prosumer at time t is as follows: ; in, is the comfort loss cost caused by the energy consumption change of the prosumer at time t, is the demand response comfort loss coefficient at time t, and They are the optimized power consumption and predicted power consumption of the prosumer at time t respectively.

[0050] Optionally, since the comfort loss is often not in a simple linear relationship with the change in electricity consumption, in different electricity consumption scenarios, in addition to directly multiplying the square of the difference by the demand response comfort loss coefficient to obtain the comfort loss cost caused by the energy consumption change of the prosumer, you can also use an exponential function (such as an exponential function with the natural constant e as the base) or a piecewise function (such as using a linear function when the difference is small; using a quadratic function or exponential function when the interpolation is large) on the difference, and then multiply the obtained value by the demand response comfort loss coefficient to obtain the comfort loss cost caused by the energy consumption change of the prosumer.

[0051] It can be seen that in this example, by multiplying the square of the difference between the optimized power consumption of the prosumer and the predicted power consumption by the demand response comfort loss coefficient, the comfort loss cost caused by the energy consumption change of the prosumer can be obtained, which can comprehensively consider the comfort loss caused by different individual differences and changes in power consumption under power consumption scenarios.

[0052] S204, obtaining the energy storage life loss cost of the prosumer according to the energy storage life loss cost coefficient of the prosumer, the energy storage system charging power and the energy storage system discharging power.

[0053] Among them, the energy storage life loss cost coefficient of the prosumer is used to measure the cost corresponding to the life loss of the energy storage equipment caused by the unit charge and discharge amount during the charging and discharging process of the energy storage system. Different types of energy storage technologies (such as lithium-ion batteries, lead-acid batteries, etc.) have different life loss characteristics. This coefficient can reflect the relationship between the value loss of the energy storage equipment caused by charging and discharging and the charge and discharge amount. Specifically, the energy storage life loss cost coefficient of the prosumer can be obtained directly from the relevant information provided by the energy storage equipment manufacturer, and then set or changed by the user at the terminal of the prosumer energy optimization system. Alternatively, the energy storage life loss cost coefficient of the prosumer can also be obtained by conducting long-term experimental tests on the energy storage equipment, collecting data on the number of charge and discharge cycles and the performance attenuation of the equipment, and then calculating the life loss cost corresponding to the unit charge and discharge amount based on the initial cost and expected life of the equipment, thereby obtaining the coefficient.

[0054] Among them, the energy storage system charging power refers to the electric power absorbed by the energy storage system per unit time during the charging process. The energy storage system charging power reflects the rate at which the energy storage system receives electric energy, usually in kilowatts (kW) or megawatts (MW). Specifically, the energy storage system charging power can be directly measured by the power measurement equipment installed in the energy storage system charging circuit.

[0055] Among them, the energy storage system discharge power refers to the electric power released to the external load per unit time during the discharge process of the energy storage system. The energy storage system discharge power reflects the ability of the energy storage system to provide electrical energy to the outside world, usually in kilowatts (kW) or megawatts (MW). Specifically, the energy storage system charging power can be directly measured by the power measurement equipment installed in the energy storage system discharge circuit.

[0056] The energy storage life loss cost of the prosumer refers to the cost incurred by the prosumer due to the loss of energy storage equipment life during the charging and discharging process of the energy storage system. Specifically, the charge and discharge amount of the energy storage system in a certain period of time can be calculated based on the charging power and the discharging power, and then multiplied by the energy storage life loss cost coefficient to obtain the energy storage life loss cost in the period of time.

[0057] In one possible implementation, see Figure 5 , Figure 5 is a flow chart of a method for obtaining the energy storage life loss cost of a prosumer provided in an embodiment of the present application, such as Figure 5 As shown, according to the energy storage life loss cost coefficient of the prosumer, the energy storage system charging power and the energy storage system discharging power, the energy storage life loss cost of the prosumer is obtained, including: Determine the energy storage life loss cost coefficient of the prosumer according to the energy storage efficiency, the rated power of the energy storage, the unit operation and maintenance cost of the target time period, the estimated operating life of the energy storage system, the discount rate, the number of cycles of the target time period, the energy storage cost of the energy storage, the power storage cost of the energy storage and the rated service life of the energy storage; obtain a first sum of the charging power of the energy storage system and the discharging power of the energy storage system; obtain a fourth product of the first sum and the energy storage life loss cost coefficient of the prosumer, the fourth product being the energy storage life loss cost coefficient of the prosumer.

[0058] Among them, energy storage efficiency refers to the energy conversion efficiency of the energy storage system during the charging and discharging process, usually expressed as a percentage. The rated power of energy storage refers to the power that the energy storage system can continuously and stably output or input, in units of watts (W), kilowatts (kW) or megawatts (MW). The unit operation and maintenance cost of the target time period refers to the maintenance and operation cost required for the energy storage system per unit time or per unit charge and discharge volume within a specific target time period. The maintenance and operation cost includes the cost of equipment maintenance, overhaul, replacement of parts and labor management. The estimated operating life of the energy storage system is the estimated time that the energy storage system can operate normally and maintain a certain performance based on factors such as energy storage technology, equipment quality and usage conditions. The discount rate refers to the ratio of converting future costs or benefits to current values, which can be set or changed by the user directly at the terminal of the prosumer energy optimization system. The number of cycles in the target time period refers to the number of complete cycles of charging and discharging that the energy storage system completes within the target time period. The energy storage cost of energy storage refers to the cost required to store a unit of energy (such as per kilowatt-hour), including the purchase cost of energy storage equipment, installation cost and other costs related to energy storage. The power storage cost of energy storage refers to the cost of the equipment required to achieve the rated power. The rated service life of energy storage refers to the expected service life that the energy storage system can achieve, which can be directly obtained from the technical data provided by the energy storage equipment manufacturer.

[0059] Among them, the energy storage efficiency, the rated power of the energy storage, the unit operation and maintenance cost of the target time period, the estimated operating life of the energy storage system, the number of cycles in the target time period, the energy storage cost of the energy storage, the power storage cost of the energy storage and the rated service life of the energy storage can all be directly obtained.

[0060] Among them, the charging and discharging amount of the energy storage system in a certain period of time is calculated through the charging power and discharging power of the energy storage system, and then multiplied by the energy storage life loss cost coefficient to obtain the energy storage life loss cost in this period of time.

[0061] Specifically, the calculation formula for energy storage life loss cost is as follows: ; in, is the energy storage life loss cost of the prosumer at time t, is the energy storage life loss cost coefficient at time t, and They are respectively the charging power and discharging power of the energy storage system at time t.

[0062] It can be seen that in this example, the charging and discharging amount of the energy storage system in a certain period of time is calculated by the charging power and discharging power of the energy storage system, and then multiplied by the energy storage life loss cost coefficient to obtain the energy storage life loss cost in the time period, which can accurately reflect the energy storage life loss cost under different circumstances.

[0063] In a possible implementation, when determining the energy storage life loss cost coefficient of the prosumer according to the energy storage efficiency, the rated power of the energy storage, the unit operation and maintenance cost of the target time period, the estimated operating life of the energy storage system, the discount rate, the number of cycles of the target time period, the energy storage cost of the energy storage, the power storage cost of the energy storage and the rated service life of the energy storage, the calculation formula of the energy storage life loss cost coefficient of the prosumer is as follows: ; in, is the energy storage efficiency; is the rated power of the energy storage; is the unit operation and maintenance cost for the target time period; is the estimated operating life of the energy storage system; is the discount rate; is the number of cycles of the target time period; an energy storage cost for said stored energy; is the power storage cost of the energy storage; is the rated service life of the energy storage.

[0064] It can be seen that in this example, by considering technical indicators such as energy storage efficiency and power, as well as economic factors such as operation and maintenance costs and estimated life, and then reflecting the time value of money through the discount rate, various factors affecting the energy storage life loss cost are taken into consideration, which is conducive to ensuring the accuracy of the calculated energy storage life loss cost coefficient, and facilitating the subsequent accurate assessment of the energy storage life loss cost for producers and consumers.

[0065] S205, obtaining the photovoltaic system operation and maintenance cost of the prosumer according to the photovoltaic cost coefficient and photovoltaic predicted output of the prosumer.

[0066] Among them, the photovoltaic cost coefficient of the prosumer is used to measure the cost input ratio corresponding to the unit power generation of the prosumer in the photovoltaic power generation process. Photovoltaic predicted output refers to the estimated value of the power generation of the photovoltaic system in a certain period of time in the future. Photovoltaic prediction processing can be based on physical model prediction, calculated according to the solar radiation model, the electrical characteristics model of photovoltaic cells, etc.; or based on data-driven methods, such as using machine learning algorithms such as neural networks and support vector machines to learn and analyze a large amount of historical data, and establish a prediction model to estimate photovoltaic predicted output.

[0067] The operation and maintenance cost of the photovoltaic system of the prosumer refers to the maintenance and operation costs that the prosumer needs to pay during the entire life cycle of the photovoltaic system in order to ensure the normal operation and power generation efficiency of the photovoltaic system. It includes regular inspection, cleaning, maintenance, parts replacement, personnel training and operation costs of the monitoring system.

[0068] In a possible implementation, the photovoltaic system operation and maintenance cost of the prosumer is obtained according to the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer, including: The fifth product of the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer is obtained, and the fifth product is the photovoltaic system operation and maintenance cost of the prosumer.

[0069] The calculation formula for the operation and maintenance cost of the photovoltaic system of the prosumer is as follows: ; in, is the photovoltaic system operation and maintenance cost of the prosumer at time t, is the photovoltaic cost coefficient of the prosumer at time t, Contribute to photovoltaic forecasting.

[0070] It can be seen that in this example, the photovoltaic cost coefficient reflects the comprehensive cost per unit of power generation, and the photovoltaic predicted output reflects the power generation. The photovoltaic system operation and maintenance cost of the prosumer is obtained by multiplying the photovoltaic cost coefficient of the prosumer and the photovoltaic predicted output, which is conducive to quickly and accurately obtaining the photovoltaic system operation and maintenance cost of the prosumer.

[0071] S206, constructing a total operating cost function for the prosumer based on the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost, and the photovoltaic system operation and maintenance cost.

[0072] In one possible implementation, see Figure 6 , Figure 6 is a flow chart of a method for constructing a total cost function of producers and consumers provided in an embodiment of the present application, such as Figure 6 As shown, according to the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost and the photovoltaic system operation and maintenance cost, the total operating cost function of the prosumer is constructed, including: The total operating cost is obtained based on the sum of the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost and the photovoltaic system operation and maintenance cost; the total operating cost function of the prosumer is constructed by minimizing the total operating cost within the regulation cycle.

[0073] Specifically, the formula for the total operating cost function of the prosumer is as follows: ; Where C is the total operating cost of the prosumer, To schedule time slots, and are the photovoltaic system operation and maintenance costs and energy storage life loss costs of the prosumer at time t, respectively; The cost of comfort loss caused by changes in energy consumption; It is the electricity interaction cost between prosumers and the grid.

[0074] It can be seen that in this example, by comprehensively considering the electricity cost, comfort loss cost, energy storage life loss cost and photovoltaic system operation and maintenance cost, we can avoid focusing on a single cost and ignoring other related costs. Then, the function is constructed with the minimum total operating cost as the goal, which is conducive to the subsequent solution of the function and accurately obtaining the energy optimization strategy for producers and consumers.

[0075] S207, solving the total operating cost function of the prosumer according to the total energy consumption optimization constraint, the energy storage system constraint, the interruptible load constraint, the transferable load constraint and the power balance constraint, and determining the energy consumption strategy of the prosumer.

[0076] The specific constraints are as follows: (1) Total energy consumption constraints: In order to meet the basic electricity demand of prosumers, the total energy consumption needs to be within the set range: ; ; in, and Optimize the minimum and maximum values ​​of total power for the load within the cycle; and The minimum and maximum values ​​of power are optimized for the load within the time slot.

[0077] (2) Energy storage system constraints Assuming that the energy storage system of each producer and consumer is mainly composed of batteries, the charging and discharging constraints that should be met are as follows: ; ; ; ; in, and are the maximum values ​​of charging and discharging power of the energy storage system respectively; is the state of charge of the energy storage system at time t; and are the maximum and minimum values ​​of the energy storage system capacity.

[0078] In addition, the energy storage system can only be charged or discharged at each moment: ; This section uses the big M method to linearize the above nonlinear constraints. It is a binary state variable and M is assumed to be an infinite constant, as shown in the following formula: .

[0079] (3) Interruptible load constraints Interruptible loads mainly refer to temperature control loads such as air conditioners and water heaters. Temperature control loads can be uniformly modeled as follows: ; ; ; in, is the temperature of the temperature control load r at time t; is the equivalent thermal resistance; is the equivalent thermal capacitance; is the equivalent heat ratio.

[0080] in, is the switch state of the temperature control load r at time t (on is 1, off is 0); is the outdoor temperature; Set the temperature for the load, is the preset fluctuation value; is the overall power consumption of the temperature control load; is the rated power of the temperature-controlled load r in the switching state; is the number of temperature control loads.

[0081] (4) Transferable load constraints Transferable loads can work at a time when the electricity price is relatively low within the set time to complete the task, and once work starts, it cannot be suspended. The power consumption model of this type of load can be expressed as: ; in, is the total power consumption of the transferable load at time t, is the power of the transferable load k at time t, is the startup state variable of the transferable load k at time t, is the number of transferable loads.

[0082] Among them, the constraints that the transferable load needs to meet are: ; ; in, and They are the earliest and latest start-up time of the transferable load k, and are the start and end working time of the transferable load k, respectively. The second formula indicates whether the transferable load k is in the starting state at time t in the working interval. If it is in the starting state, it is 1, and if it is not in the starting state, it is 0. Indicates from The minimum continuous working time of the transferable load k starting from time.

[0083] (5) Power balance constraints ; ; Since each producer and consumer can only participate in the transaction as a buyer or seller in the same period, the power purchased and sold should meet the following constraints (linearized using the Big M method): .

[0084] In a possible implementation, according to the total energy consumption optimization constraint, the energy storage system constraint, the interruptible load constraint, the transferable load constraint and the power balance constraint, the total operation cost function of the prosumer is solved, including: Under the premise of satisfying the total energy optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints and power balance constraints, the total operating cost function of the prosumer is used as the particle fitness of each optimization in the improved particle swarm algorithm based on reverse learning. If the number of iterations exceeds the preset number of iterations, or the error of any iteration is less than the preset error, the solution is terminated, and the particle position corresponding to the swarm optimal value of the improved particle swarm algorithm based on reverse learning is determined as the solution of the total operating cost function of the prosumer.

[0085] Among them, the preset number of iterations and the preset error can be set or changed by the user at the terminal of the prosumer energy optimization system.

[0086] Among them, the improved particle swarm algorithm based on reverse learning is used to solve the constructed total operating cost function C of the prosumer. The specific steps include: (1) Initialize the speed and position of the particle (initialize the power generation and consumption data of the producers and consumers, the initial purchase and sale electricity prices and other parameters).

[0087] (2) In the process of iterative optimization of the particle swarm, the energy optimization strategy of the prosumer is generated according to the particle position of each optimization.

[0088] (3) Calculate the particle fitness F (i.e., objective function C) under this optimization, update the speed and position of the particle swarm according to the speed and position update formula, and perform reverse learning on the particle swarm. Assuming that there is a feasible solution x in the search space, its reverse solution The calculation formula is: ; ; Optional, reverse solution The calculation formula can also be: ; ; Among them, rand() is a random number between 0 and 1. is the position of the j-th dimension of the ith particle at the m-th iteration; is the historical minimum value of the i-th particle in the j-th dimension during the m-th optimization; is the historical maximum value of the i-th particle in the j-th dimension during the m-th optimization.

[0089] (4) The adaptive weight w that changes with the particle fitness F is calculated according to the following formula.

[0090] ; in, is the current fitness value, is the average fitness value, is the minimum fitness value.

[0091] (5) Determine the number of iterations and the error range. Within the range of the number of iterations, multiple optimization searches are performed to obtain the optimal values ​​of individual particles and the optimal values ​​of the group. The particle position corresponding to the final group optimal value is the optimal solution for optimizing the energy consumption of the producer and consumer.

[0092] It can be seen that in this example, under the premise of multiple constraints (total energy optimization, energy storage system, interruptible load, transferable load and power balance), the total operating cost function of the prosumer is set as the particle fitness, and the improved particle swarm algorithm based on reverse learning can effectively search for the optimal solution. The preset number of iterations and the preset error are used as the end conditions, so that the algorithm can avoid invalid over-iteration and stop in time when the accuracy requirements are met. The particle position corresponding to the final optimal value of the group is used as the function solution, which can achieve the optimization of the total operating cost of the prosumer.

[0093] See also Figure 7 , Figure 7 is a schematic diagram of a structure of a prosumer energy optimization device taking into account the energy storage life loss provided in an embodiment of the present application, such as Figure 7As shown, the prosumer energy optimization device 700 considering the energy storage life loss includes: The acquisition module 701 is used to determine the electricity purchase price of the prosumer from the grid and the electricity sale price of the prosumer to the grid through the electricity price information calculated by the grid according to the output of new energy; and for obtaining the electricity cost of the prosumer according to the electricity price purchased by the prosumer from the power grid, the electricity price sold by the prosumer to the power grid, the power purchased by the prosumer from the power grid, and the power sold by the prosumer to the power grid; and for obtaining the comfort loss cost caused by the energy consumption change of the prosumer according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer and the predicted power consumption power of the prosumer; and for obtaining the energy storage life loss cost of the prosumer according to the energy storage life loss cost coefficient of the prosumer, the energy storage system charging power and the energy storage system discharging power; and for obtaining the photovoltaic system operation and maintenance cost of the prosumer according to the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer; A construction module 702 is used to construct a total operating cost function of the prosumer based on the electricity cost, the comfort loss cost caused by the energy consumption change, the energy storage life loss cost and the photovoltaic system operation and maintenance cost; The solution module 703 is used to solve the total operating cost function of the prosumer according to the total energy consumption optimization constraint, the energy storage system constraint, the interruptible load constraint, the transferable load constraint and the power balance constraint, and determine the energy consumption strategy of the prosumer.

[0094] In one possible implementation, in terms of obtaining the electricity cost of the prosumer based on the electricity purchase price of the prosumer from the grid, the electricity sale price of the prosumer to the grid, the electricity purchase power of the prosumer from the grid, and the electricity sale power of the prosumer to the grid, the acquisition module 701 is specifically used to: obtain a first product of the electricity purchase price of the prosumer from the grid and the electricity purchase power of the prosumer from the grid; obtain a second product of the electricity sale price of the prosumer to the grid and the electricity sale power of the prosumer to the grid; obtain a first difference between the first product and the second product, the first difference being the electricity cost of the prosumer.

[0095] In a possible implementation, in terms of obtaining the comfort loss cost caused by the change in energy consumption of the prosumer based on the comfort loss coefficient of the prosumer's demand response, the optimized energy power of the prosumer and the predicted power of the prosumer, the acquisition module 701 is specifically used to: obtain the second difference between the optimized power of the prosumer and the predicted power of the prosumer; obtain the third product of the comfort loss coefficient of the prosumer's demand response and the square of the second difference, the third product being the comfort loss cost caused by the change in energy consumption of the prosumer.

[0096] In one possible implementation, in terms of obtaining the energy storage life loss cost of the prosumer based on the energy storage life loss cost coefficient of the prosumer, the charging power of the energy storage system and the discharging power of the energy storage system, the acquisition module 701 is specifically used to: determine the energy storage life loss cost coefficient of the prosumer based on the energy storage efficiency, the rated power of the energy storage, the unit operation and maintenance cost of the target time period, the estimated operating life of the energy storage system, the discount rate, the number of cycles of the target time period, the energy storage cost of the energy storage, the power storage cost of the energy storage and the rated service life of the energy storage; obtain a first sum of the charging power of the energy storage system and the discharging power of the energy storage system; obtain a fourth product of the first sum and the energy storage life loss cost coefficient of the prosumer, the fourth product being the energy storage life loss cost coefficient of the prosumer.

[0097] In one possible implementation, the calculation formula of the energy storage life loss cost coefficient of the prosumer is as follows: ; in, is the energy storage efficiency; is the rated power of the energy storage; is the unit operation and maintenance cost for the target time period; is the estimated operating life of the energy storage system; is the discount rate; is the number of cycles of the target time period; an energy storage cost for said stored energy; is the power storage cost of the energy storage; is the rated service life of the energy storage.

[0098] In one possible implementation, in terms of obtaining the operation and maintenance cost of the photovoltaic system of the prosumer based on the photovoltaic cost coefficient and photovoltaic predicted output of the prosumer, the acquisition module 701 is specifically used to: obtain the fifth product of the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer, and the fifth product is the operation and maintenance cost of the photovoltaic system of the prosumer.

[0099] In one possible implementation, in terms of constructing a total cost function for prosumers based on electricity costs, comfort loss costs caused by changes in energy consumption, energy storage life loss costs, and photovoltaic system operation and maintenance costs, construction module 702 is specifically used to: obtain the total operating cost based on the sum of the electricity costs, comfort loss costs caused by changes in energy consumption, energy storage life loss costs, and photovoltaic system operation and maintenance costs; and construct the total operating cost function for prosumers by minimizing the total operating cost within the regulation cycle.

[0100] In one possible implementation, in terms of solving the total operating cost function of the prosumer according to the total energy consumption optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints and power balance constraints, the solution module 703 is specifically used to: on the premise of satisfying the total energy consumption optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints and power balance constraints, use the total operating cost function of the prosumer as the particle fitness of each optimization in the improved particle swarm algorithm based on reverse learning; if the number of iterations exceeds the preset number of iterations, or the error of any iteration is less than the preset error, the solution is terminated, and the particle position corresponding to the swarm optimal value of the improved particle swarm algorithm based on reverse learning is determined as the solution of the total operating cost function of the prosumer.

[0101] It is worth noting that the specific functional implementation of the prosumer energy optimization device 700 considering the energy storage life loss can be found in the above Figure 2 The description of the method for optimizing the energy consumption of prosumers considering the life loss of energy storage is shown, for example, the acquisition module 701 is used to implement the relevant contents of executing S201-S205, the construction module 702 is used to implement the relevant contents of executing S206, and the solution module 703 is used to implement the relevant contents of executing S207. The various units or modules in the device for optimizing the energy consumption of prosumers considering the life loss of energy storage 700 can be respectively or completely combined into one or several other units or modules to constitute, or one (some) of the units or modules can be further divided into multiple units or modules with smaller functions to constitute, which can achieve the same operation without affecting the realization of the technical effects of the embodiments of the present invention. The above-mentioned units or modules are divided according to logical functions. In practical applications, the functions of one unit (or module) are implemented by multiple units (or modules), or the functions of multiple units (or modules) are implemented by one unit (or module).

[0102] According to the description of the above method embodiment and related device embodiment, please refer to Figure 8 , Figure 8 It is a schematic diagram of the structure of a computer provided in an embodiment of the present application. Figure 8The computer 800 shown includes a processor 801 , a memory 802 , a communication interface 803 and a bus 804 . The processor 801 , the memory 802 , and the communication interface 803 are connected to each other through the bus 804 .

[0103] Optionally, the memory 802 is a ROM, a static storage device, a dynamic storage device or a RAM.

[0104] The memory 802 can store executable program codes. When the executable program codes stored in the memory 802 are executed by the processor 801, the processor 801 and the communication interface 803 are used to execute Figure 2 The illustrated embodiment shows various steps of a method for optimizing energy usage of a prosumer taking into account energy storage life loss.

[0105] Processor 801 uses a general-purpose CPU, a microprocessor, an application-specific integrated circuit ASIC, a GPU or one or more integrated circuits to execute relevant programs to execute the energy optimization method for prosumers taking into account the energy storage life loss of the method embodiment of the present application.

[0106] The processor 801 can also be an integrated circuit chip with signal processing capabilities. In the implementation process, the various steps of the energy optimization method for prosumers considering the energy storage life loss of the present application can be completed by the hardware integrated logic circuit or software instructions in the processor 801. Optionally, the processor 801 is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, discrete hardware component. The processor can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor is a microprocessor or the processor is any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor to execute, or a combination of hardware and software modules in the decoding processor to execute. The optional software module is located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register or other mature storage medium in the art. The storage medium is located in the memory 802, and the processor 801 reads the information in the memory 802, and combines its hardware to complete the functions required to be executed by the modules included in a prosumer energy optimization device 700 that takes into account the energy storage life loss in an embodiment of the present application, or executes the prosumer energy optimization method that takes into account the energy storage life loss in the method embodiment of the present application.

[0107] The communication interface 803 uses a transceiver or other related device such as, but not limited to, a transceiver.

[0108] The bus 804 may include a path for transmitting information between various components of the computer 800 (eg, the memory 802 , the processor 801 , and the communication interface 803 ).

[0109] It should be noted that although Figure 8 The computer 800 shown only shows a memory, a processor, and a communication interface, but in the specific implementation process, those skilled in the art should understand that the computer 800 also includes other devices necessary for normal operation. At the same time, according to specific needs, those skilled in the art should understand that the computer 800 may also include hardware devices for implementing other additional functions. In addition, those skilled in the art should understand that the computer 800 may also include only the devices necessary for implementing the embodiments of the present application, and does not necessarily include Figure 8 All devices shown in .

[0110] An embodiment of the present application provides a computer-readable storage medium, in which a computer program for electronic data exchange is stored. The computer program includes execution instructions, and the execution instructions are used to execute part or all of the steps of any one of the methods for optimizing energy consumption by prosumers taking into account the life loss of energy storage as recorded in the above-mentioned embodiments of the method for optimizing energy consumption by prosumers taking into account the life loss of energy storage. The above-mentioned computer includes an electronic terminal device.

[0111] An embodiment of the present application provides a computer program product, wherein the computer program product includes a computer program, and the computer program can be operated to enable a computer to perform part or all of the steps of any method for optimizing energy consumption of producers and consumers taking into account the life loss of energy storage as recorded in the above method embodiments. The computer program product can be a software installation package.

[0112] It should be noted that, for any of the aforementioned embodiments of the method for optimizing energy consumption by prosumers taking into account the loss of energy storage life, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited to the described order of actions, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by this application.

[0113] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principle and implementation method of a method and device for optimizing energy consumption of prosumers taking into account the life loss of energy storage in the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​a method and device for optimizing energy consumption of prosumers taking into account the life loss of energy storage in the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

[0114] The present application is described with reference to the flowcharts and / or block diagrams of the methods, hardware products, and computer program products of the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks 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.

[0115] 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 including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 The memory may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0116] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "one" does not exclude multiple situations. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0117] A person skilled in the art can understand that all or part of the steps in the various methods of any of the above-mentioned embodiments of the method for optimizing the energy consumption of producers and consumers taking into account the life loss of energy storage can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a disk or an optical disk, etc.

[0118] It can be understood that any product that is controlled or configured to execute the processing method of the flowchart described in an embodiment of the method for optimizing energy consumption of producers and consumers taking into account the life loss of energy storage, such as the device and computer program product of the above flowchart, falls within the scope of the related products described in this application.

[0119] Obviously, those skilled in the art can make various changes and modifications to the method and device for optimizing energy consumption of prosumers considering energy storage life loss provided by 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 optimizing energy consumption by prosumers considering energy storage life loss, characterized in that: The method comprises: Determine the electricity price at which the prosumer purchases electricity from the grid and the electricity price at which the prosumer sells electricity to the grid using the electricity price information calculated by the grid based on the output of new energy; Obtaining the electricity cost of the prosumer according to the electricity purchase price of the prosumer from the power grid, the electricity sale price of the prosumer to the power grid, the power purchased by the prosumer from the power grid, and the power sold by the prosumer to the power grid; Obtaining the comfort loss cost caused by the energy consumption change of the prosumer according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer and the predicted power consumption power of the prosumer; Obtaining the energy storage life loss cost of the prosumer according to the energy storage life loss cost coefficient of the prosumer, the energy storage system charging power, and the energy storage system discharging power; Obtaining the photovoltaic system operation and maintenance cost of the prosumer according to the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer; Constructing a total operating cost function for the prosumer based on the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost, and the photovoltaic system operation and maintenance cost; According to the total energy consumption optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints and power balance constraints, the total operating cost function of the prosumer is solved to determine the energy consumption strategy of the prosumer.

2. The method according to claim 1, characterized in that The obtaining of the electricity cost of the prosumer according to the electricity purchase price of the prosumer from the power grid, the electricity sale price of the prosumer to the power grid, the power purchased by the prosumer from the power grid, and the power sold by the prosumer to the power grid comprises: Obtaining a first product of the electricity price purchased by the prosumer from the power grid and the power purchased by the prosumer from the power grid; Obtaining a second product of the electricity price sold by the prosumer to the power grid and the power sold by the prosumer to the power grid; A first difference between the first product and the second product is obtained, where the first difference is the electricity cost of the prosumer.

3. The method according to claim 1, characterized in that The obtaining of the comfort loss cost caused by the energy consumption change of the prosumer according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer and the predicted power consumption of the prosumer includes: Obtaining a second difference between the optimized power consumption of the prosumer and the predicted power consumption of the prosumer; A third product of the demand response comfort loss coefficient of the prosumer and the square of the second difference is obtained, wherein the third product is the comfort loss cost caused by the energy consumption change of the prosumer.

4. The method according to claim 1, characterized in that The energy storage life loss cost of the prosumer is obtained according to the energy storage life loss cost coefficient of the prosumer, the energy storage system charging power and the energy storage system discharging power, including: Determine the energy storage life loss cost coefficient of the prosumer according to the energy storage efficiency, the rated power of the energy storage, the unit operation and maintenance cost of the target time period, the estimated operating life of the energy storage system, the discount rate, the number of cycles of the target time period, the energy storage cost of the energy storage, the power storage cost of the energy storage and the rated service life of the energy storage; Obtaining a first sum of the energy storage system charging power and the energy storage system discharging power; A fourth product of the first sum and the energy storage life loss cost coefficient of the prosumer is obtained, wherein the fourth product is the energy storage life loss cost coefficient of the prosumer.

5. The method according to claim 4, characterized in that The calculation formula of the energy storage life loss cost coefficient of the prosumer is as follows: ； in, is the energy storage efficiency; is the rated power of the energy storage; is the unit operation and maintenance cost for the target time period; is the estimated operating life of the energy storage system; is the discount rate; is the number of cycles of the target time period; an energy storage cost for said stored energy; is the power storage cost of the energy storage; is the rated service life of the energy storage.

6. The method according to claim 1, characterized in that The photovoltaic system operation and maintenance cost of the prosumer is obtained according to the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer, including: The fifth product of the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer is obtained, and the fifth product is the photovoltaic system operation and maintenance cost of the prosumer.

7. The method according to any one of claims 1 to 6, characterized in that: The total cost function of the prosumer is constructed based on the electricity cost, the comfort loss cost caused by energy consumption changes, the energy storage life loss cost and the photovoltaic system operation and maintenance cost, including: The total operating cost is obtained according to the sum of the electricity cost, the comfort loss cost caused by the energy consumption change, the energy storage life loss cost and the photovoltaic system operation and maintenance cost; The total operating cost function of producers and consumers is constructed by minimizing the total operating cost within the regulation cycle.

8. The method according to claim 1, characterized in that The method of solving the total operation cost function of the prosumer according to the total energy optimization constraint, the energy storage system constraint, the interruptible load constraint, the transferable load constraint and the power balance constraint comprises: Under the premise of satisfying the total energy optimization constraints, energy storage system constraints, interruptible load constraints, transferable load constraints and power balance constraints, the total operating cost function of the prosumer is used as the particle fitness of each optimization in the improved particle swarm algorithm based on reverse learning. If the number of iterations exceeds the preset number of iterations, or the error of any iteration is less than the preset error, the solution is terminated, and the particle position corresponding to the swarm optimal value of the improved particle swarm algorithm based on reverse learning is determined as the solution of the total operating cost function of the prosumer.

9. A prosumer energy optimization device taking into account energy storage life loss, characterized in that: The device comprises: An acquisition module, used to determine the electricity price that the prosumer purchases from the grid and the electricity price that the prosumer sells to the grid through the electricity price information calculated by the grid according to the output of new energy; and for obtaining the electricity cost of the prosumer according to the electricity price purchased by the prosumer from the power grid, the electricity price sold by the prosumer to the power grid, the power purchased by the prosumer from the power grid, and the power sold by the prosumer to the power grid; and for obtaining the comfort loss cost caused by the energy consumption change of the prosumer according to the demand response comfort loss coefficient of the prosumer, the optimized energy consumption power of the prosumer and the predicted power consumption power of the prosumer; and for obtaining the energy storage life loss cost of the prosumer according to the energy storage life loss cost coefficient of the prosumer, the energy storage system charging power and the energy storage system discharging power; and for obtaining the photovoltaic system operation and maintenance cost of the prosumer according to the photovoltaic cost coefficient and the photovoltaic predicted output of the prosumer; A construction module is used to construct a total operating cost function for prosumers based on electricity costs, comfort loss costs caused by energy consumption changes, energy storage life loss costs, and photovoltaic system operation and maintenance costs; The solution module is used to solve the total operating cost function of the prosumer and determine the energy consumption strategy of the prosumer according to the total energy consumption optimization constraint, the energy storage system constraint, the interruptible load constraint, the transferable load constraint and the power balance constraint.

10. A computer, characterized in that: include: A memory, a processor, and an executable program code stored in the memory and executable on the processor, wherein the processor executes the steps of the method for optimizing energy consumption of producers and consumers taking into account the loss of energy storage life as described in any one of claims 1 to 8 when executing the executable program code.

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