Method for constructing time-of-use electricity price model considering energy suppliers and energy consumers

Abstract

The present invention discloses a method for constructing a time-of-use electricity price model considering energy suppliers and energy consumers, including: obtaining basic parameters; establishing an optimized time-of-use electricity price model considering energy suppliers and energy consumers through the Stackelberg game theory, the model including a first model and a second model, the first model including a first objective function and a first constraint condition, and the second model including a second objective function and a second constraint condition; substituting the basic parameters into the first model, solving the first model with the goal of maximizing the profit of the energy supplier, and outputting a time-of-use electricity price plan; substituting the basic parameters into the second model, solving the second model with the goal of minimizing the electricity purchase cost of the energy consumer, and outputting an energy demand plan. It can be seen that the present invention fully considers the interaction between energy suppliers and energy consumers, and realizes the maximization of the profit of energy suppliers and the minimization of the cost of energy consumers.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and in particular, to a method, apparatus, and computing device for constructing a time-of-use electricity price model considering energy suppliers and energy consumers. Background Art

[0002] An energy supplier can provide energy for energy consumers. An energy consumer can be understood as a user who purchases energy from an energy supplier.

[0003] In recent years, time-of-use electricity pricing is one of the most well-known electricity-saving schemes. By encouraging users to shift their electricity demand from peak hours to off-peak hours, it can reduce the pressure on energy suppliers and the electricity purchase costs of users, and has great potential for peak shaving. Compared with uniform electricity pricing, time-of-use electricity pricing is a form of electricity price provided by energy suppliers to reduce peak electricity demand. Under time-of-use electricity pricing, the electricity prices for different time periods are set differently. The electricity price during peak hours is higher, and the electricity price during normal hours is lower. Therefore, it can encourage energy consumers to change their consumption patterns and shift their electricity demand from peak hours to normal hours. Although some energy suppliers have provided time-of-use electricity pricing, considering consumer behavior, it is not easy to determine the optimal time-of-use electricity price scheme to maximize the profit of energy suppliers and minimize the costs of energy consumers. Summary of the Invention

[0004] Therefore, the present invention provides a method for constructing a time-of-use electricity price model considering energy suppliers and energy consumers, aiming to solve or at least alleviate the problems mentioned above.

[0005] According to one aspect of the present invention, there is provided a method for constructing a time-of-use electricity price model considering energy suppliers and energy consumers, which is suitable for execution in a computing device. The method includes: obtaining basic parameters; establishing an optimization model for time-of-use electricity price considering energy suppliers and energy consumers through the Stackelberg game theory. The model includes a first model and a second model. The first model includes a first objective function and a first constraint condition, and the second model includes a second objective function and a second constraint condition; substituting the basic parameters into the first model and solving the first model with the goal of maximizing the profit of the energy supplier to output a time-of-use electricity price plan; substituting the basic parameters into the second model and solving the second model with the goal of minimizing the electricity purchase cost of the energy consumer to output an energy demand plan; where the first objective function is: Max PR 1 =R 1 -C 1 , where PR 1 represents the total profit of the energy supplier, R 1 represents the total income of the energy supplier, and C 1 represents the total operating cost of the energy supplier; where the second objective function is: Wherein, C i represents the total cost of the energy consumer under the time-of-use electricity price, represents the energy cost of the energy consumer, represents the cost of the energy demand during the peak period in the time-of-use electricity price of the energy consumer, represents the penalty cost of the energy consumer, and the penalty cost represents the cost caused by the deviation between the original start time and the new start time of the energy consumer.

[0006] Optionally, the first objective function includes:

[0007] Max PR 1 = R 1 - C 1

[0008]

[0009] C 1 = C 1 (1) + C 1 (2)

[0010]

[0011]

[0012] Wherein, represents the electricity cost of the i-th energy consumer, i represents the i-th energy consumer, and C 1 (1) represents the production cost of the energy supplier, and C 1 (2) represents the production capacity cost of the energy supplier, and c 1 represents the marginal operating cost of the energy supplier during the morning period, and c 2 represents the marginal operating cost of the energy supplier at noon, and c 3 represents the marginal operating cost of the energy supplier during the evening period. The marginal operating cost represents the increase in cost resulting from an increase in the electricity consumption of the energy consumer, and t represents the slot. represents the power demand of the energy supplier during the electricity peak period, b represents the capacity cost of the energy supplier during the electricity peak period, and μ represents the slot duration. One day is divided into a first preset number of time periods, and each time period corresponds to one of the slots.

[0013] Optionally, the second objective function includes:

[0014]

[0015]

[0016]

[0017]

[0018] Wherein, p 1 represents the electricity price during normal electricity consumption periods, represents the energy consumption of slot t, p 2 represents the electricity price during peak electricity consumption periods, p 3 represents the electricity price during super-peak electricity consumption periods, p 4 represents the super-peak period energy demand cost in the time-of-use electricity price of the energy consumer, h i1 represents the penalty price for the first move of energy consumer i,

[0019] represents the new start time of the first move of energy consumer i, represents the original start time of the first move of energy consumer i, h i2 represents the penalty price for the second move of energy consumer i, represents the new start time of the second move of energy consumer i, represents the original start time of the second move of energy consumer i, represents the penalty cost for the first move of energy consumer i, represents the penalty cost for the second move of energy consumer i. The penalty cost for the first move of energy consumer i is the cost caused by the deviation between the original start time and the new start time of the first move of energy consumer i. The penalty cost for the second move of energy consumer i represents the cost caused by the deviation between the original start time and the new start time of the second move of energy consumer i.

[0020] Optionally, the first constraint condition includes the consumption pattern constraint of the energy consumer, and the second constraint condition includes one or more of the start time interval constraint of the two-shift work allowed by the energy consumer, the two-shift working time constraint of the energy consumer, the slot energy consumption constraint, and the slot working time constraint.

[0021] Optionally, the consumption pattern constraint of the energy consumer includes:

[0022]

[0023] Wherein, i represents the i-th energy consumer, represents the energy consumption of the energy consumer, r i represents the variable that determines whether the energy consumer joins the time-of-use electricity price plan, represents the energy demand of the energy supplier.

[0024] Optionally, the start time interval constraint of the two-shift work allowed by the consumer includes:

[0025]

[0026]

[0027] In the formula, represents the earliest start time allowed for the first shift change of energy consumer i, represents the allowed shift change time for energy consumer i for the first time, represents the latest start time allowed for the first shift change of energy consumer i, represents the earliest start time allowed for the second shift change of energy consumer i, represents the allowed shift change time for energy consumer i for the second time, the latest start time allowed for the second shift change of energy consumer i.

[0028] Optionally, the two-shift working time constraint of the consumer includes:

[0029]

[0030] In the formula, v represents a shift of the energy consumer.

[0031] Optionally, the slot energy consumption constraint includes:

[0032]

[0033] In the formula, x i represents a processing machine, and the processing machine represents a machine that consumes a fixed power per hour, y it represents an auxiliary task, and the auxiliary task represents the increased power demand of the energy consumer, represents the working time of the processing machine.

[0034] Optionally, the slot working time constraint includes:

[0035]

[0036] In the formula, g represents a function of the working time of slot t and the new start time of movement of energy consumer i.

[0037] Optionally, the first model is solved by the enumeration method.

[0038] Optionally, the basic parameters include the basic parameters of the first model and the basic parameters of the second model. The basic parameters of the first model include: the electricity cost of energy consumers, the production cost of energy suppliers, the production capacity cost of energy suppliers, the marginal operating cost of energy suppliers during the morning period, the marginal operating cost of energy suppliers at noon, the marginal operating cost of energy suppliers in the evening, slots, the power demand of energy suppliers during peak electricity consumption periods, the capacity cost of energy suppliers during peak electricity consumption periods, the duration of slots, etc.; the basic parameters of the second model include the electricity price during normal electricity consumption periods, the energy consumption of slots, the electricity price during peak electricity consumption periods, the electricity price during peak electricity consumption spikes, the peak period energy demand cost in the time-of-use electricity price of energy consumers, the penalty price for the first move of energy consumers, the new start time of the first move of energy consumers, the original start time of the first move of energy consumers, the penalty price for the second move of energy consumers, the new start time of the second move of energy consumers, the original start time of the second move of energy consumers, etc.

[0039] According to one aspect of the present invention, there is provided a device for constructing a time-of-use electricity price model considering energy suppliers and energy consumers, which is adapted to be executed in a computing device. The device includes: a parameter acquisition module adapted to acquire basic parameters; a model construction module adapted to establish a first model and a second model of time-of-use electricity price considering energy suppliers and energy consumers through the Stackelberg game theory. The first model includes a first objective function and a first constraint condition, and the second model includes a second objective function and a second constraint condition; a model solving unit adapted to substitute the basic parameters into the first model, solve the first model with the goal of maximizing the profit of energy suppliers, and output a time-of-use electricity price plan. It is also adapted to substitute the basic parameters into the second model, solve the second model with the goal of minimizing the electricity purchase cost of consumers, and output an energy demand plan; wherein, the first objective function is: Max PR 1 =R 1 -C 1 , where PR 1 represents the total profit of energy suppliers, R 1 represents the total income of energy suppliers, and C 1 represents the total operating cost of energy suppliers; wherein, the second objective function is: where C i represents the total cost of energy consumers under the time-of-use electricity price, represents the energy cost of energy consumers, represents the peak period energy demand cost in the time-of-use electricity price of energy consumers, represents the penalty cost of energy consumers, and the penalty cost represents the cost caused by the deviation between the original start time and the new start time of energy consumers.

[0040] According to one aspect of the present invention, there is provided a computing device, comprising: at least one processor; and a memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, and the program instructions include instructions for performing the method as described above.

[0041] According to one aspect of the present invention, there is provided a readable storage medium storing program instructions, which when read and executed by a computing device, cause the computing device to execute the method as described above.

[0042] According to the technical solution of the present invention, a method for constructing a time-of-use electricity price model considering energy suppliers and energy consumers is proposed. The model includes a first model and a second model. In the first model, with the goal of maximizing the profit of the energy supplier, the electricity consumption plan of the energy consumer is introduced into the time-of-use electricity price model to determine the time-of-use electricity price plan, and the output time-of-use electricity price plan is sent to the energy consumer. In the second model, with the goal of minimizing the electricity purchase cost of the energy consumer, the electricity consumption cost is determined considering the time-of-use electricity price plan sent by the first model, and the electricity consumption plan is output. Thus, the present invention fully considers the interaction between the energy supplier and the energy consumer, that is, when formulating the time-of-use electricity price plan at the energy supplier side, the electricity consumption plan of the energy consumer is fully considered, and when the energy consumer formulates the electricity consumption plan, the time-of-use electricity price plan is fully considered, so as to maximize the profit of the energy supplier and minimize the cost of the energy consumer. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram showing the time-of-use electricity price period according to an embodiment of the present invention;

[0044] Figure 2 A structural block diagram showing a computing device 200 according to an embodiment of the present invention;

[0045] Figure 3 A flowchart showing a method 300 for constructing a time-of-use electricity price model considering energy suppliers and energy consumers according to an embodiment of the present invention;

[0046] Figure 4 A structural diagram showing a device 400 for constructing a time-of-use electricity price model considering energy suppliers and energy consumers according to an embodiment of the present invention;

[0047] Figure 5 A schematic diagram showing all single-shift energy consumers according to an embodiment of the present invention;

[0048] Figure 6 A schematic diagram showing all two-shift energy consumers according to an embodiment of the present invention;

[0049] Figure 7A schematic diagram showing the ratio of the penalty cost to the total cost corresponding to all single-shift energy consumers according to an embodiment of the present invention;

[0050] Figure 8 A schematic diagram showing the ratio of the penalty cost to the total cost corresponding to all two-shift energy consumers according to an embodiment of the present invention. Detailed implementation manners

[0051] The energy supplier can provide energy for energy consumers. The present invention does not limit the specific form of the energy supplier. For example, the energy supplier can be understood as an energy provider. An energy consumer can be understood as a user who purchases energy from the energy supplier. The present invention also does not limit the energy consumer. For example, the energy consumer can be understood as an energy consumer. It should be noted that the energy consumer can be understood as an industrial factory, and the industrial factory includes multiple processing machines.

[0052] In some embodiments, each energy consumer divides a day into a first preset number of time periods. Each time period here corresponds to a slot. The first preset number can be set according to the actual application scenario, and the present invention does not limit this. For example, the first preset number can be 24. That is to say, 24 hours of a day are divided into 24 time periods, and each time period corresponds to one hour. That is, a day is divided into 24 slots, which are t = 0 (the first slot), t = 1 (the second slot),..., t = 23 (the 24th slot).

[0053] Generally, an energy consumer may include multiple shifts in a day. The number of shifts included by different types of energy consumers in a day is different, and the time intervals of the shifts may also be different. The present invention does not limit this. For example, if one shift of an energy consumer is 8 hours, then a day is divided into three shifts, namely the morning shift from 8:00 to 16:00, the middle shift from 16:00 to 24:00, and the night shift from 0:00 to 8:00. If a day is divided into two shifts, then the shifts are the morning shift from 13:00 to 24:00 and the night shift from 0:00 to 12:00. When an energy consumer faces the choice of an electricity peak-valley time-of-use electricity price plan, it can rearrange its production plan to adapt to the new price structure. Of course, different energy consumers work different hours per day, such as 8 hours, 16 hours, 24 hours, etc.

[0054] The present invention provides a method for constructing a time-of-use electricity price model considering energy suppliers and energy consumers. This model analyzes the interaction relationship between energy suppliers and energy consumers. The energy supplier provides an initial time-of-use electricity price plan for its energy consumers. If the energy consumers accept the time-of-use electricity price plan provided by the energy supplier, then the energy consumers need to plan a new operation and management strategy, which is equivalent to a new electricity consumption plan, to adapt to the time-of-use electricity price strategy and their own production practice, so as to minimize the electricity consumption cost. The energy consumers feedback the planned electricity consumption plan to the energy supplier, and the energy supplier formulates a time-of-use electricity price strategy based on the electricity consumption plan of the energy consumers, so as to maximize the profit of the energy supplier.

[0055] In some embodiments, the time-of-use electricity price strategy includes the electricity price during normal electricity consumption periods, the electricity price during peak electricity consumption periods, the electricity price during super-peak electricity consumption periods, and a fixed electricity price. As for the time periods corresponding to each electricity price and the specific magnitudes of each electricity price, they can be set according to actual situations, and the present invention does not limit this.

[0056] For example, as shown in the time-of-use electricity price periods Figure 1 , if the energy consumers choose the fixed electricity price, then as can be seen from Figure 1 , the electricity price throughout the day is p 0 . If the energy consumers choose the time-of-use electricity price, then from 0:00 to 8:00 and from 20:00 to 24:00 are normal electricity consumption periods, and the electricity price during normal electricity consumption periods is p 1 , from 8:00 to 12:00 and from 16:00 to 20:00 are peak electricity consumption periods, and the electricity price during peak electricity consumption periods is p 2 , and from 12:00 to 16:00 is the super-peak electricity consumption period, and the electricity price during the super-peak electricity consumption period is p 3 .

[0057] The above-mentioned super-peak electricity consumption period can be understood as the period with the largest electricity consumption in a day, the normal electricity consumption period can be understood as the period with the least electricity consumption in a day, and the peak electricity consumption period can be understood as the period with electricity consumption between the super-peak period and the normal period. As can also be seen from Figure 1 , the electricity price is the highest during the super-peak period, followed by the peak electricity consumption period, then the fixed electricity price, and the lowest electricity price is during the normal electricity consumption period. As for the specific magnitudes of each electricity price, they can be set according to the actual application scenario, and the present invention does not limit this, as long as p 1 < p 0 < p 2 < p 3 is satisfied. However, it should be noted that in the initial stage of modeling, p 1 , p 0 , p 2 , p 3The initial value can also be set according to the actual application scenario, and the present invention does not limit this.

[0058] The method for constructing a time-of-use electricity price model considering energy suppliers and energy consumers provided by the present invention is suitable for execution in a computing device. Figure 2 The structural block diagram of a computing device 200 according to an embodiment of the present invention is shown. It should be noted that Figure 2 The shown computing device 200 is only an example. In practice, the computing device for implementing the screenshot processing method of the present invention can be a device of any model, and its hardware configuration can be the same as Figure 2 the shown computing device 200, or can be different from Figure 2 the shown computing device 200. In practice, the computing device for implementing the screenshot processing method of the present invention can add or delete hardware components of Figure 2 the shown computing device 200, and the present invention does not limit the specific hardware configuration of the computing device.

[0059] As Figure 2 shown, in the basic configuration 202, the computing device 200 typically includes a system memory 206 and one or more processors 204. A memory bus 208 can be used for communication between the processor 204 and the system memory 206.

[0060] Depending on the desired configuration, the processor 204 can be any type of processing, including but not limited to: microprocessor (μP), microcontroller (μC), digital signal processor (DSP), or any combination thereof. The processor 204 can include one or more levels of cache such as a level 1 cache 210 and a level 2 cache 212, a processor core 214, and registers 216. An example of a processor core 214 can include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP core), or any combination thereof. An example of a memory controller 218 can be used with the processor 204, or in some implementations, the memory controller 218 can be an internal part of the processor 204.

[0061] Depending on the desired configuration, the system memory 206 can be any type of memory, including but not limited to: volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.), or any combination thereof. The system memory 206 can include an operating system 220, one or more applications 222, and program data 224. In some embodiments, the application 222 can be arranged to operate on the operating system using the program data 224. The application 222 is used to execute the instructions of the method 300.

[0062] The computing device 200 further includes a storage device 232, which includes a removable storage 236 and a non-removable storage 238. Both the removable storage 236 and the non-removable storage 238 are connected to a storage interface bus 234. In the present invention, the relevant data of each event occurring during the program execution and the time information indicating the occurrence of each event can be stored in the storage device 232, and the operating system 220 is adapted to manage the storage device 232. Among them, the storage device 232 can be a disk.

[0063] The computing device 200 may further include an interface bus 240 that facilitates communication from various interface devices (e.g., an output device 242, a peripheral interface 244, and a communication device 246) to the basic configuration 202 via the bus / interface controller 230. Example output devices 242 include an image processing unit 248 and an audio processing unit 250. They can be configured to facilitate communication with various external devices such as a display or a speaker via one or more A / V ports 252. Example peripheral interfaces 244 may include a serial interface controller 254 and a parallel interface controller 256, which can be configured to facilitate communication with external devices such as input devices (e.g., a keyboard, a mouse, a pen, a voice input device, a touch input device) or other peripherals (e.g., a printer, a scanner, etc.) via one or more I / O ports 258. Example communication devices 246 may include a network controller 260, which can be arranged to facilitate communication with one or more other computing devices 262 via one or more communication ports 264 through a network communication link.

[0064] The network communication link can be an example of a communication medium. A communication medium can generally embody computer-readable instructions, data structures, program modules in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium. A "modulated data signal" can be a signal in which one or more of its data concentrations or its changes can encode information in the signal. As a non-limiting example, the communication medium can include wired media such as a wired network or a dedicated line network, and various wireless media such as sound, radio frequency (RF), microwave, infrared (IR), or other wireless media. The term computer-readable medium used herein can include both storage media and communication media.

[0065] The computing device 200 can be implemented as a server, such as a file server, a database server, an application server, and a WEB server, etc., or can be implemented as a part of a small-sized portable (or mobile) electronic device, which can be a cellular phone, a personal digital assistant (PDA), a personal media player device, a wireless network browsing device, a personal head-mounted device, an application-specific device, or a hybrid device that can include any of the above functions. The computing device 200 can also be implemented as a personal computer including desktop computer and notebook computer configurations.

[0066] The present invention takes into account energy suppliers and energy consumers as examples to conduct research.

[0067] Figure 3 A flowchart of a time-of-use electricity price model construction method 300 considering energy suppliers and energy consumers according to an embodiment of the present invention is shown. This method is suitable for being executed in Figure 2 the computing device 200 shown. As Figure 3 shown, the method 300 includes steps S310 to S330

[0068] In step S310, basic parameters are obtained. The basic data is the input data of the model. The basic parameters include the basic parameters of the first model and the basic parameters of the second model. The basic parameters of the first model include: the electricity cost of energy consumer i, the production cost of the energy supplier, the production capacity cost of the energy supplier, the marginal operating cost of the energy supplier during the morning period, the marginal operating cost of the energy supplier at noon, the marginal operating cost of the energy supplier in the evening, slots, the power demand of the energy supplier during the electricity peak period, the capacity cost of the energy supplier during the electricity peak period, and the duration of the slot.

[0069] The basic parameters of the second model include: the electricity price during normal electricity consumption periods, the energy consumption during slot t, the electricity price during the electricity peak period, the electricity price during the electricity spike period, the energy demand cost during the peak period in the time-of-use electricity price of the energy consumer, the penalty price for the first move of energy consumer i, the new start time of the first move of energy consumer i, the original start time of the first move of energy consumer i, the penalty price for the second move of energy consumer i, the new start time of the second move of energy consumer i, and the original start time of the second move of energy consumer i.

[0070] Subsequently, in step S320, an optimized time-of-use electricity price model considering energy suppliers and energy consumers is established through the Stackelberg game theory. The model includes an objective function and constraint conditions. An optimized time-of-use electricity price model considering energy suppliers and energy consumers is established according to the Stackelberg game theory, so as to analyze the interaction relationship between energy suppliers and energy consumers through game theory, and adjust the time-of-use electricity price accordingly based on the electricity consumption strategies of energy consumers, so as to achieve a balance between maximizing the profits of energy suppliers and minimizing the costs of energy consumers.

[0071] In some embodiments, the established optimized time-of-use electricity price model considering energy suppliers and energy consumers includes a first model and a second model. The first model is applied to energy suppliers, that is, the first model is applied to energy suppliers who supply energy, and the first model aims to maximize the profits of energy suppliers. The first model corresponds to a first objective function and a first set of constraint conditions. The second model is applied to energy consumers, that is, the second model corresponds to energy consumers who consume energy, and the second model aims to minimize the electricity purchase costs of energy consumers. The second model corresponds to a second objective function and a second set of constraint conditions. The first objective function and the second objective function are collectively referred to as the objective function, and the first set of constraint conditions and the second set of constraint conditions are collectively referred to as the constraint conditions.

[0072] The first objective function includes:

[0073] Max PR 1 =R 1 -C 1

[0074] In the formula, PR 1 represents the total profit of the energy supplier, R 1 represents the total income of the energy supplier, and C 1 represents the total operating cost of the energy supplier. Among them, the total operating cost includes the production cost of the energy supplier and the capacity cost of the energy supplier. The production cost of the energy supplier is the cost of generating energy by the energy supplier, and the capacity cost of the energy supplier is the capacity cost of the energy supplier.

[0075] The first objective function specifically includes:

[0076] Max PR 1 =R 1 -C 1

[0077]

[0078] C 1 =C 1 (1)+C 1 (2)

[0079]

[0080]

[0081] In the formula, represents, i represents, C 1 (1) represents the production cost of the energy supplier. The production cost can be understood as the cost of all the energy generated by the energy supplier throughout the day, C 1 (2) represents the production capacity cost of the energy supplier. The production capacity cost can be understood as the product of the capacity cost of the energy supplier during the peak period and the peak period electricity demand, c 1 represents the marginal operating cost of the energy supplier during the morning period, c 2 represents the marginal operating cost of the energy supplier during the noon period, representing c 3 The marginal operating cost of the energy supplier during the evening period. The marginal operating cost represents the increase in cost resulting from immediately increasing the electricity consumption of the energy consumer. t represents the time slot. Regarding the description of the time slot, it is as above and will not be elaborated here. t∈mid, t∈on, t∈off respectively represent the morning shift, night shift, and middle shift of the energy consumer. The specific time periods of t∈mid, t∈on, t∈off can be set according to the actual application scenario, and the present invention does not limit this. For example, t∈mid, t∈on, t∈off respectively correspond to 8:00 - 15:00, 0:00 - 7:00, 16:00 - 23:00. represents the electricity demand of the energy supplier during the electricity peak period. b represents the capacity cost of the energy supplier during the electricity peak period. μ represents the duration of the time slot. The description of the time slot is as above and will not be elaborated here. t∈mid, t∈on, t∈off respectively represent the morning shift, night shift, and middle shift of the energy consumer. The specific time periods of t∈mid, t∈on, t∈off can be set according to the actual application scenario, and the present invention does not limit this. For example, t∈mid, t∈on, t∈off respectively correspond to 8:00 - 15:00, 0:00 - 7:00, 16:00 - 23:00.

[0082] The first constraint condition corresponding to the first objective function includes the consumption pattern constraint of the energy consumer. Among them, the consumption pattern of the energy consumer can be understood as that the energy consumer transfers the electricity demand from the peak period to the ordinary electricity consumption period or the electricity peak period.

[0083] The consumption pattern constraint of the energy consumer is:

[0084]

[0085] In the formula, i represents the i-th energy consumer, represents the energy consumption of the energy consumer, r i represents the variable that determines whether the energy consumer joins the time-of-use electricity price plan. When the variable is the first preset value, it can be considered that the energy consumer joins the time-of-use electricity price plan. When the variable is the second preset value, it means that the energy consumer does not join the time-of-use electricity price plan. The first preset value and the second preset value can be set according to the actual application scenario, and the present invention does not set this. For example, the first preset value is 1 and the second preset value is 0. Then, r i being 1 means that the energy consumer i joins the time-of-use electricity price plan, ri When it is 0, it means that energy consumer i does not participate in the time-of-use electricity price plan. Represents the energy demand of the energy supplier.

[0086] The second objective function corresponding to the second model is:

[0087]

[0088] In the formula, C i Represents the total cost of the energy consumer under the time-of-use electricity price, Represents the energy cost of the energy consumer, Represents the energy demand cost during the peak period in the time-of-use electricity price of the energy consumer, Represents the penalty cost of the energy consumer. The penalty cost represents the cost caused by the deviation between the original start time and the new start time of the energy consumer.

[0089] The second objective function specifically includes:

[0090]

[0091]

[0092]

[0093]

[0094] In the formula, p 1 Represents the electricity price during the normal electricity consumption period, Represents the energy consumption at slot t, p 2 Represents the electricity price during the peak electricity consumption period, p 3 Represents the electricity price during the super-peak electricity consumption period, p 1 、p 2 、p 3 The unit of p 4 Represents the energy demand cost during the peak period in the time-of-use electricity price of the energy consumer, with the unit of yuan / kW, h i1 Represents the penalty price for the first move of energy consumer i, Represents the new start time of the first move of energy consumer i, Represents the original start time of the first move of energy consumer i, h i2 Represents the penalty price for the second move of energy consumer i, Represents the new start time of the second move of energy consumer i, Represents the original start time of the second move of energy consumer i, Represents the penalty cost for the first move of energy consumer i, Denote the penalty cost for the second move of energy consumer \(i\), the penalty cost for the first move of energy consumer \(i\), the cost caused by the deviation between the original start time and the new start time of the first move of energy consumer \(i\), and the penalty cost for the second move of energy consumer \(i\) represents the cost caused by the deviation between the original start time and the new start time of the second move of energy consumer \(i\).

[0095] The second constraint condition corresponding to the second objective function includes one or more of the following: the start time interval constraint of the two-shift operation allowed for the energy consumer, the two-shift working time constraint of the energy consumer, the slot energy consumption constraint, and the slot working time constraint.

[0096] 1) The start time interval constraint of the two-shift operation allowed for the energy consumer includes:

[0097]

[0098]

[0099] In the formula, represents the earliest start time allowed for the first shift change of energy consumer \(i\), represents the allowed time for the first shift change of energy consumer \(i\), represents the latest start time allowed for the first shift change of energy consumer \(i\), represents the earliest start time allowed for the second shift change of energy consumer \(i\), represents the allowed time for the second shift change of energy consumer \(i\), represents the latest start time allowed for the second shift change of energy consumer \(i\).

[0100] 2) The two-shift working time constraint of the energy consumer includes:

[0101]

[0102] In the formula, \(v\) represents a shift of the energy consumer.

[0103] 3) The slot energy consumption constraint includes:

[0104]

[0105] In the formula, \(x\) i represents the processing machine, the machine that consumes a fixed power per hour, and \(y\) it represents the auxiliary task, and the auxiliary task represents the increased power demand of the energy consumer. represents the working time of the processing machine.

[0106] 4) The slot working time constraint includes:

[0107]

[0108] Wherein, g represents a function of the working time of slot t and the new start time of the movement of energy consumer i.

[0109] Subsequently, in step S330, the basic parameters are substituted into the model, and the model is solved with the goal of maximizing the profit of the energy supplier and minimizing the electricity purchase cost of the energy consumer. The first model outputs a time-of-use electricity price plan. The second model outputs an energy demand plan, which can also be understood as the second model outputting an electricity consumption plan.

[0110] It should be understood that there are multiple methods for solving the model. The present invention is not limited to a specific implementation manner, and all methods capable of solving the above model are within the protection scope of the present invention.

[0111] To effectively solve the constructed two-layer model, in an embodiment of the present invention, the present invention first determines the optimal start time of the two shifts in the second model, that is, determines the electricity consumption plan, and sends it to the first model. According to the initial or previous determined electricity price plans and the electricity consumption plan currently fed back by the second model, the time-of-use electricity price plan is determined by using the enumeration method. Of course, the present invention does not limit the specific solution method, so all methods capable of solving the model constructed by the present invention are within the protection scope of the present invention.

[0112] For example, The feasible solution space of For the variable The objective function of the first model is continuous and convex. The function is non-differentiable at integer points. However, it is differentiable at points within the time interval, for example, the time interval between 6 o'clock and 7 o'clock. Here, the feasible solution space is divided into several intervals Then, the one-dimensional search method can be used to easily obtain the optimal points in each interval. Finally, the time point with the minimum cost is selected as the optimal start time, that is, the electricity consumption plan is determined. After that, set p 1 、p 2 、p 3 、p 4 The initial values, for example, set the initial solution p1 = ε, p2 = 2ε, p3 = 3ε, p4 = 4ε. After that, set p 1 、p 2 、p 3 、p 4 The constraints between, for example, ε ≤ p 1 ≤ p 0 、p 1 +ε ≤ p 3 ≤ p 3,max 、p 1 +ε ≤ p 2 ≤ p 3 、p 3+ε ≤ p 4 ≤ p 4,max 。And based on the set p 1 、p 2 、p 3 、p 4 's initial value and constraints, calculate the profit of the power supply company, continuously iterate, and output the p corresponding to the maximum profit 1 、p 2 、p 3 、p 4 's solution, as well as the calculated maximum profit of the power supply company.

[0113] Figure 4 FIG. shows a structural block diagram of a time-of-use electricity price model construction device 400 considering an energy supplier and an energy consumer according to an embodiment of the present invention. The device 400 can reside in a computing device 200, such as Figure 4 shown, the device 400 includes: a parameter acquisition unit 410, a model construction unit 420, and a model solution unit 430.

[0114] A parameter acquisition module, adapted to acquire basic parameters.

[0115] A model construction module, adapted to establish a first model and a second model of time-of-use electricity price considering an energy supplier and an energy consumer through the Stackelberg game theory. The first model includes a first objective function and a first constraint condition, and the second model includes a second objective function and a second constraint condition.

[0116] A model solution unit, adapted to substitute the basic parameters into the first model, solve the first model with the goal of maximizing the profit of the energy supplier, output the time-of-use electricity price solution, and is also adapted to substitute the basic parameters into the second model, solve the second model with the goal of minimizing the electricity purchase cost of the consumer, and output the electricity demand in each slot. One day is divided into a first preset number of time periods, and each time period corresponds to a slot.

[0117] Among them, the first objective function is: Max PR 1 = R 1 - C 1 , where PR 1 represents the total profit of the energy supplier, R 1 represents the total income of the energy supplier, and C 1 represents the total operating cost of the energy supplier.

[0118] Among them, the second objective function is: In the formula, C i represents the total cost of the energy consumer under the time-of-use electricity price, represents the energy cost of the energy consumer, Represents the cost of peak - period energy demand in the time - of - use electricity price for energy consumers. Represents the penalty cost of energy consumers.

[0119] It should be noted that the working principle of the time - of - use electricity price model construction device 400 considering energy suppliers and energy consumers is similar to the above - mentioned time - of - use electricity price model construction method 300 for energy suppliers and energy consumers. For the relevant parts, reference can be made to the description of the above - mentioned method 300, and details will not be repeated here.

[0120] The following will use a specific case to verify the numerical example simulation of the time - of - use electricity price optimization model considering energy suppliers and energy consumers constructed by the present invention.

[0121] In the present invention, numerical results obtained by calculating the costs and profits of energy consumers and energy suppliers under fixed electricity price and time - of - use electricity price are analyzed. The quadratic - change penalty cost is considered. where θ i ≥0 is the penalty factor of energy consumer i. It reflects the following intuitive conclusions: (i) No penalty occurs when there is no shift change. (ii) The more the time changes, the higher the penalty cost of energy consumers. (iii) The difficulty of movement increases with the increase of time change, that is, it is easy for energy consumers to move a little time, but it is difficult to move too much time. The fixed power demand x i is 100 kw. The additional power demand is y it = ρ i z it where z it is set to {10, 10, 10, 10, 8, 8, 8, 8, 8, 10, 12, 15, 20, 25, 25, 20, 17, 13, 8, 8, 10, 10, 10, 10}, and ρ i is the auxiliary coefficient of energy consumer i, representing the proportion of additional power demand in the total demand. 100 energy consumers are considered for each type of energy, with a total of 300 energy consumers. θ i and ρ i are two important factors for each energy consumer. They are generated by and where, represents the penalty factor of the second - order change of energy consumer i, σ 1 represents the deviation of the working time of energy consumers, represents the proportion of energy consumers of one type of energy in the total energy consumers, and σ 2 represents the proportion of the energy consumption of energy consumers in the total energy consumption. In the present invention, a normal distribution is adopted, and p 0 = 0.2.

[0122] 1. Time - of - use electricity price

[0123] In this section, we will discuss the impact of time-of-use electricity prices on traditional fixed electricity prices and then ignore the peak demand cost. Accordingly, the time-of-use electricity price p 4 is set to 0. First, set and σ 2 = 0.3. Analyze the impact of the penalty factor by setting it to different values. The numerical results are shown in Tables 1 to 3. Tables 1 to 4 are for different. P I is the revenue of the energy supplier brought by the time-of-use electricity price and can be calculated as the time-of-use electricity price profit - fixed electricity price profit. P M refers to the cost savings of the energy supplier brought by the time-of-use electricity price. P R is the revenue reduction of the energy supplier brought by the time-of-use electricity price. The electricity prices in different periods are also shown in Tables 1 to 4.

[0124] Table 1 Analysis of the energy supplier when

[0125]

[0126] Table 2 Analysis of the energy supplier when

[0127]

[0128] Table 3 Analysis of the energy supplier when

[0129]

[0130] Table 4 Analysis of the energy supplier when

[0131]

[0132] Secondly, and σ 1 = 0.3. Analyze its impact by setting ρ i to different values. The numerical results are shown in Table 5. Compared with Table 1, we find that the larger the value of ρ i , the greater the profit improvement. A larger ρ i means that the electricity demand during the peak period of users is much higher than that during normal periods. In this case, when the working hours of energy consumers change, more electricity demand can be eliminated during the peak period. It can also be seen from Table 5 that the impact of the deviation is small, which is the same as the results of Tables 1 to 4 above.

[0133] Table 5 Analysis of the energy supplier when

[0134]

[0135] Finally, the behavior of energy consumers is analyzed. For the same time-of-use electricity price offered by energy suppliers, different energy consumers correspond to different behaviors. It is interesting to discuss which energy consumers prefer to join the time-of-use electricity price plan and which energy consumers are more willing to stay with the traditional fixed electricity price. We set θ i ←N(6,1.8) and ρ i ←N(8,1.8). We already know that energy consumers with three shifts (i.e., including three shifts in a day) will not join the time-of-use electricity price plan. Figure 5 Shows all single-shift energy consumers. All two-shift (i.e., including two shifts in a day) energy consumers are as Figure 6 shown. Figure 5 and Figure 6 The square boxes in the figure are energy consumers who decide to stay in the fixed electricity price plan and do not participate in the time-of-use electricity price plan, and the diamonds refer to energy consumers who decide to join the time-of-use electricity price plan. This shows that energy consumers are naturally separated. When only one time-of-use electricity price is offered to all energy consumers and energy consumers have the option to stay with the fixed electricity price, energy consumers with a high ρ i value and a low θ i value will choose to join the time-of-use electricity price plan. For energy consumers who join the time-of-use electricity price plan, we need to know the ratio of the penalty cost to the total cost, as Figure 7 and Figure 8 shown, and the size of the bubbles in the figure shows the value of the ratio. For single-shift energy consumers, the largest ratio is 10.7%, as Figure 7 shown.

[0136] 2. Comparison of Four Time-of-Use Electricity Price Structures

[0137] This section analyzes four time-of-use electricity price structures, divides a day into three time periods, and includes the peak demand cost, denoted as T1. T2 is generated when the peak demand is ignored. Correspondingly, when a day is divided into two time periods, we provide two other structures. Let p 1 =p 2 to obtain T3 from T1. Let p 1 =p 2 to obtain T4 from T2. The comparison is shown in Table 6. We find that the impact of different structures on the profit growth of energy suppliers is almost the same, and the T3 structure is slightly better than the T2 structure. The structure with peak demand cost is slightly better than the structure without peak demand cost. An interesting finding is about the cost improvement. When the peak demand cost is included, the profit of energy suppliers is less, and at the same time, the cost is also less, revealing the compatibility of economic benefits and environmental protection.

[0138] Table 6 θ i←N(3,0.6) and ρ i ←Energy supplier analysis when N(4,0.3)

[0139]

[0140] As can be seen from the above, the present invention optimizes the time-of-use electricity price problem by using game theory. The interests of energy suppliers and the behaviors of energy consumers are described as a leader-follower game and solved by a two-layer algorithm. The analysis shows that this research can create a win-win situation for the power grid and energy consumers, that is, energy suppliers increase their profits while energy consumers reduce their costs. For energy suppliers, it is impossible and unnecessary to persuade all energy consumers to join the time-of-use electricity price. Even if only a small number of energy consumers join, the profit will increase significantly with the new electricity price. For energy consumers, it is important to quantify the impact of the time-of-use electricity price. When the penalty coefficient θ i is small and the auxiliary coefficient ρ i is large, energy suppliers can obtain greater benefits.

[0141] A8 The method as described in A5, wherein the consumer's two-shift working time constraint includes:

[0142]

[0143] In the formula, v represents a shift of the energy consumer.

[0144] A9 The method as described in A5, wherein the slot energy consumption constraint includes:

[0145]

[0146] In the formula, x i represents a processing machine, and the processing machine represents a machine that consumes a fixed power per hour, and y it represents an auxiliary task, and the auxiliary task represents the increased power demand of the energy consumer. represents the working time of the processing machine.

[0147] A10 The method as described in A5, wherein the slot working time constraint includes:

[0148]

[0149] In the formula, g represents a function of the working time of slot t and the new start time of movement of energy consumer i.

[0150] A11 The method as described in any one of A1 to A10, wherein the first model is solved by the enumeration method.

[0151] The method according to any one of A1 to A11, wherein the basic parameters include the basic parameters of the first model and the basic parameters of the second model, and the basic parameters of the first model include: the electricity cost of the energy consumer, the production cost of the energy supplier, the production capacity cost of the energy supplier, the marginal operating cost of the energy supplier during the morning period, the marginal operating cost of the energy supplier at noon, the marginal operating cost of the energy supplier in the evening, the slot, the power demand of the energy supplier during the peak electricity consumption period, the capacity cost of the energy supplier during the peak electricity consumption period, and one or more of the slot duration.

[0152] The basic parameters of the second model include one or more of the electricity price during the normal electricity consumption period, the energy consumption of the slot, the electricity price during the peak electricity consumption period, the electricity price during the peak electricity consumption spike period, the peak period energy demand cost in the time-of-use electricity price of the energy consumer, the penalty price for the first move of the energy consumer, the new start time of the first move of the energy consumer, the original start time of the first move of the energy consumer, the penalty price for the second move of the energy consumer, the new start time of the second move of the energy consumer, and the original start time of the second move of the energy consumer.

[0153] The various technologies described herein can be implemented in combination with hardware or software, or a combination thereof. Thus, the method and device of the present invention, or certain aspects or parts of the method and device of the present invention, can take the form of program code (i.e., instructions) embedded in a tangible medium, such as a removable hard disk, a USB flash drive, a floppy disk, a CD-ROM, or any other machine-readable storage medium. When the program is loaded into a machine such as a computer and executed by the machine, the machine becomes a device for practicing the present invention.

[0154] In the case where the program code is executed on a programmable computer, the computing device generally includes a processor, a processor-readable storage medium (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. Among them, the memory is configured to store the program code; the processor is configured to execute the method for constructing the time-of-use electricity price model considering the energy supplier and the energy consumer of the present invention according to the instructions in the program code stored in the memory.

[0155] By way of example and not limitation, the readable medium includes a readable storage medium and a communication medium. The readable storage medium stores information such as computer-readable instructions, data structures, program modules, or other data. The communication medium generally embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and includes any information transmission medium. A combination of any of the above is also included within the scope of the readable medium.

[0156] In the specification provided herein, the algorithms and displays are not inherently related to any particular computer, virtual system, or other device. A variety of general-purpose systems may also be used in conjunction with the examples of the present invention. The structure required to construct such systems will be apparent from the above description. Additionally, the present invention is not directed to any particular programming language. It should be understood that the teachings of the present invention described herein can be implemented in a variety of programming languages, and the description of a particular language above is for the purpose of disclosing the best mode of the present invention.

[0157] In the specification provided herein, numerous specific details are set forth. However, it can be understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0158] Similarly, it should be understood that, in order to streamline the present disclosure and assist in understanding one or more of the various inventive aspects, in the foregoing description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, the disclosed method should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim.

[0159] Those skilled in the art should understand that the modules or units or components of the devices in the examples disclosed herein may be arranged in the devices as described in that embodiment, or alternatively may be located in one or more devices different from those of the example. The modules in the foregoing examples may be combined into one module or further divided into multiple sub-modules.

[0160] Those skilled in the art can understand that the modules in the devices of the embodiments can be adaptively changed and disposed in one or more devices different from those of the embodiment. The modules or units or components in the embodiments can be combined into one module or unit or component, and further can be divided into multiple sub-modules or sub-units or sub-components. Except that at least some of such features and / or processes or units are mutually exclusive, any combination can be adopted to combine all the features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all the processes or units of any method or device so disclosed. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) can be replaced by an alternative feature that provides the same, equivalent, or similar purpose.

[0161] In addition, those skilled in the art will understand that although some of the embodiments described herein include certain features included in other embodiments rather than other features, the combination of features of different embodiments is meant to be within the scope of the present invention and forms different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0162] In addition, some of the embodiments are described herein as methods or combinations of method elements that can be implemented by a processor of a computer system or by other devices performing the functions. Thus, a processor having the necessary instructions for implementing the method or method element forms an apparatus for implementing the method or method element. In addition, the elements described herein of the apparatus embodiments are examples of the apparatus for performing the functions performed by the elements for the purpose of implementing the present invention.

[0163] As used herein, unless otherwise specified, the use of ordinal numbers "first", "second", "third", etc. to describe ordinary objects merely indicates different instances of similar objects and is not intended to imply that the objects so described must have a given order in terms of time, space, ranking, or in any other manner.

[0164] Although the present invention has been described in terms of a limited number of embodiments, those skilled in the art within the present technical field will appreciate that other embodiments can be conceived within the scope of the present invention as thus described. In addition, it should be noted that the language used in this specification has been principally selected for readability and teaching purposes and not for the purpose of explaining or limiting the subject matter of the present invention. Thus, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The disclosure of the present invention is illustrative, not restrictive, of the scope of the present invention, which is defined by the appended claims.

Claims

1. A method for constructing a time-of-use electricity price model considering energy suppliers and energy consumers, suitable for execution in a computing device, the method comprises: Obtaining basic parameters; Establishing a time-of-use electricity price optimization model considering energy suppliers and energy consumers through the Stackelberg game theory, the model including a first model and a second model, the first model including a first objective function and a first constraint condition, and the second model including a second objective function and a second constraint condition; Substituting the basic parameters into the first model, solving the first model with the goal of maximizing the profit of the energy supplier, and outputting a time-of-use electricity price plan; Substituting the basic parameters into the second model, solving the second model with the goal of minimizing the electricity purchase cost of the energy consumer, and outputting an energy demand plan; Among them, the first objective function is: Max PR 1 = R 1 - C 1 , where C 1 = C 1 (1) + C 1 (2), In the formula, PR 1 represents the total profit of the energy supplier, R 1 represents the total income of the energy supplier, C 1 represents the total operating cost of the energy supplier, represents the electricity cost of the i-th energy consumer, i represents the i-th energy consumer, C 1 (1) represents the production cost of the energy supplier, C 1 (2) represents the production capacity cost of the energy supplier, c 1 represents the marginal operating cost of the energy supplier during the morning period, c 2 represents the marginal operating cost of the energy supplier at noon, c 3 represents the marginal operating cost of the energy supplier during the evening period. The marginal operating cost represents the increase in cost resulting from an increase in the electricity consumption of the energy consumer. t represents the slot, b represents the capacity cost of the energy supplier during the peak electricity consumption period, μ represents the duration of the slot, the day is divided into the first preset number of time periods, each time period corresponds to one of the said slots, off, mid, and on respectively represent the morning shift, the middle shift, and the night shift; Among them, the second objective function is as follows: In the formula, C i represents the total cost of the energy consumer under the time-of-use electricity price, represents the energy cost of the energy consumer, represents the cost of the peak-hour energy demand in the time-of-use electricity price of the energy consumer, represents the penalty cost of the energy consumer, and the penalty cost represents the cost caused by the deviation between the original start time and the new start time of the energy consumer; The first constraint condition includes the consumption pattern constraint of the energy consumer, and the second constraint condition includes one or more of the start time interval constraint of the two-shift operation allowed by the energy consumer, the two-shift working time constraint of the energy consumer, the slot energy consumption constraint, and the slot working time constraint; Among them, the consumption pattern constraints of energy consumers include: In the formula, i represents an energy consumer, represents the energy consumption of the energy consumer, r i represents the variable that determines whether the energy consumer joins the time-of-use electricity price plan, represents the energy demand of the energy supplier.

2. The method according to claim 1, wherein, In the second objective function: where p 1 represents the electricity price during normal electricity consumption periods, represents the energy consumption of slot t, p 2 represents the electricity price during peak electricity consumption periods, p 3 represents the electricity price during ultra-peak electricity consumption periods, p 4 represents the ultra-peak period energy demand cost in the time-of-use electricity price of the energy consumer, h i1 represents the penalty price for the first move of energy consumer i, represents the new start time of the first move of energy consumer i, represents the original start time of the first move of energy consumer i, h i2 represents the penalty price for the second move of energy consumer i, represents the new start time of the second move of energy consumer i, represents the original start time of the second move of energy consumer i, represents the penalty cost for the first move of energy consumer i, represents the penalty cost for the second move of energy consumer i. The penalty cost for the first move of energy consumer i represents the cost caused by the deviation between the original start time and the new start time of the first move of energy consumer i. The penalty cost for the second move of energy consumer i represents the cost caused by the deviation between the original start time and the new start time of the second move of energy consumer i.

3. The method according to claim 1, wherein, The start time interval constraint of the two-shift operation allowed by the consumer includes: Wherein, represents the earliest start time allowed for the first shift change of energy consumer i, represents the time allowed for the first shift change of energy consumer i, represents the latest start time allowed for the first shift change of energy consumer i, represents the earliest start time allowed for the second shift change of energy consumer i, represents the time allowed for the second shift change of energy consumer i, represents the latest start time allowed for the second shift change of energy consumer i.

4. The method according to claim 3, wherein, The two-shift working time constraint of the consumer includes: In the formula, v represents a shift of the energy consumer.

5. The method according to claim 2, wherein, The slot energy consumption constraint includes: where x i represents a processing machine, which is a machine that consumes a fixed power per hour, and y it represents an auxiliary task, which represents the increased power demand of the energy consumer, represents the working hours of the processing machine.

6. The method according to claim 5, wherein, The slot working time constraint includes: In the formula, g represents a function of the working time of slot t and the new start time of movement of energy consumer i.

7. The method according to claim 1, wherein, Solving the first model by the enumeration method.

8. The method according to claim 1, wherein, The basic parameters include the basic parameters of the first model and the basic parameters of the second model. The basic parameters of the first model include: the electricity cost of the energy consumer, the production cost of the energy supplier, the production capacity cost of the energy supplier, the marginal operating cost of the energy supplier during the morning period, the marginal operating cost of the energy supplier during the noon period, the marginal operating cost of the energy supplier during the evening period, the slot, the power demand of the energy supplier during the electricity peak period, the capacity cost of the energy supplier during the electricity peak period, the slot duration, etc.; The basic parameters of the second model include the electricity price during the normal electricity consumption period, the energy consumption of the slot, the electricity price during the electricity peak period, the electricity price during the electricity spike period, the peak period energy demand cost in the time-of-use electricity price of the energy consumer, the penalty price for the first movement of the energy consumer, the new start time of the first movement of the energy consumer, the original start time of the first movement of the energy consumer, the penalty price for the second movement of the energy consumer, the new start time of the second movement of the energy consumer, the original start time of the second movement of the energy consumer, etc.

9. A device for constructing a time-of-use electricity price model considering energy suppliers and energy consumers, suitable for execution in a computing device, the device comprises: A parameter acquisition module, adapted to acquire basic parameters; A model construction module, adapted to establish a first model and a second model of time-of-use electricity price considering energy suppliers and energy consumers through the Stackelberg game theory. The first model includes a first objective function and a first constraint condition, and the second model includes a second objective function and a second constraint condition; A model solving unit, adapted to substitute the basic parameters into the first model, solve the first model with the goal of maximizing the profit of the energy supplier, and output a time-of-use electricity price plan. It is also adapted to substitute the basic parameters into the second model, solve the second model with the goal of minimizing the electricity purchase cost of consumers, and output the electricity demand at each slot. One day is divided into a first preset number of time periods, and each time period corresponds to one of the slots; Among them, the first objective function is: Max PR 1 = R 1 - C 1 , where C 1 = C 1 (1) + C 1 (2), In the formula, PR 1 represents the total profit of the energy supplier, R 1 represents the total income of the energy supplier, C 1 represents the total operating cost of the energy supplier, represents the electricity cost of the i-th energy consumer, i represents the i-th energy consumer, C 1 (1) represents the production cost of the energy supplier, C 1 (2) represents the production capacity cost of the energy supplier, c 1 represents the marginal operating cost of the energy supplier during the morning period, c 2 represents the marginal operating cost of the energy supplier at noon, c 3 represents the marginal operating cost of the energy supplier during the evening period. The marginal operating cost represents the increase in cost resulting from immediately increasing the electricity consumption of the energy consumer. t represents the slot, b represents the capacity cost of the energy supplier during the peak electricity consumption period, μ represents the duration of the slot, the day is divided into the first preset number of time periods, and each time period corresponds to one of the slots. off, mid, and on respectively represent the morning shift, the middle shift, and the night shift; Among them, the second objective function is as follows: In the formula, C i represents the total cost of the energy consumer under the time-of-use electricity price, represents the energy cost of the energy consumer, represents the cost of the peak-period energy demand in the time-of-use electricity price of the energy consumer, represents the penalty cost of the energy consumer, and the penalty cost represents the cost caused by the deviation between the original start time and the new start time of the energy consumer; The first constraint condition includes the consumption mode constraint of energy consumers, and the second constraint condition includes one or more of the start time interval constraint of the two-shift operation allowed by energy consumers, the two-shift working time constraint of energy consumers, the slot energy consumption constraint, and the slot working time constraint; Among them, the consumption pattern constraints of energy consumers include: In the formula, i represents an energy consumer, represents the energy consumption of the energy consumer, and r i represents a variable that determines whether the energy consumer joins the time-of-use electricity price plan, represents the energy demand of the energy supplier.

10. A computing device, comprising: at least one processor; and a memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, and the program instructions include instructions for executing the method according to any one of claims 1-8.

11. A readable storage medium storing program instructions, which when read and executed by a computing device, cause the computing device to execute the method according to any one of claims 1-8.

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