Hydropower transaction strategy determination method and device, electronic equipment and storage medium

Abstract

The invention discloses a hydropower transaction strategy determination method and device, electronic equipment and a storage medium. The method comprises the following steps: determining at least one piece of historical power information corresponding to a target area and a historical water and electricity price group corresponding to each piece of historical power information; determining predicted power information of the target area on the prediction day; according to the at least one piece of historical electric power information, the historical electricity price group corresponding to each piece of historical electric power information and the predicted electric power information, determining a predicted electricity price group of the target area on the prediction day; and generating a hydropower transaction strategy based on the predicted hydropower electricity price group. By adopting the technical scheme of the invention, accurate prediction of the predicted hydropower electricity price group of the prediction day of the target area is realized, and finally the hydropower transaction strategy is generated based on the predicted hydropower electricity price group, so that loss reduction or income increase can be realized during hydropower selling, and the market performance of a hydropower generating unit is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of hydropower trading, and in particular, to a method, device, electronic device and storage medium for determining a hydropower trading strategy. Background Art

[0002] Hydropower trading is very important in the power dispatching during the power spot duration. Since the hydropower generation capacity is affected by natural conditions, the hydropower generation price fluctuates greatly. How to make an optimal trading strategy among various power market transactions (such as medium - long - term, day - ahead, real - time market) has become a key issue for improving power benefits.

[0003] The existing technologies usually only rely on historical generation data or simple water resource forecasts, and do not fully consider the volatility of market prices. Therefore, the existing power market dispatching methods are difficult to provide flexible and efficient spot trading strategies for hydropower units. Summary of the Invention

[0004] The present invention provides a method, device, electronic device and storage medium for determining a hydropower trading strategy to solve the situation where the electricity price prediction is inaccurate and the trading strategy is difficult to determine during the hydropower trading process.

[0005] According to one aspect of the present invention, a method for determining a hydropower trading strategy is provided. The method includes:

[0006] Determine at least one historical power information corresponding to a target area and a historical hydropower electricity price group corresponding to each historical power information; the power information is information within the target area that affects the electricity price of electricity and the degree of influence is greater than a preset degree; the historical power information is the power information of the target area on a historical day; the historical days corresponding to each historical power information are different; the hydropower electricity price group includes medium - long - term price, day - ahead price and spot price; the power information at least includes the power market bidding space, the power market clearing price and the power load of the target area;

[0007] Determine the predicted power information of the target area on the prediction day;

[0008] According to at least one historical power information, the historical hydropower electricity price group corresponding to each historical power information and the predicted power information, determine the predicted hydropower electricity price group of the target area on the prediction day;

[0009] Generate a hydropower trading strategy based on the predicted hydropower electricity price group.

[0010] According to another aspect of the present invention, a device for determining a hydropower trading strategy is provided. The device includes:

[0011] A historical data determination module, configured to determine at least one piece of historical power information corresponding to a target area and historical hydropower price groups corresponding to each piece of historical power information; the power information is information within the target area that affects the power price and the degree of influence is greater than a preset degree; the historical power information is the power information of the target area on a historical day; the historical days corresponding to each piece of historical power information are different; the hydropower price group includes medium - long - term price, day - ahead price, and spot price; the power information at least includes the power market bidding space, the power market clearing price, and the power load of the target area.

[0012] A prediction information determination module, configured to determine the predicted power information of the target area on a predicted day.

[0013] A power price prediction module, configured to determine the predicted hydropower price group of the target area on the predicted day according to at least one piece of historical power information, the historical hydropower price groups corresponding to each piece of historical power information, and the predicted power information.

[0014] A trading strategy generation module, configured to generate a hydropower trading strategy based on the predicted hydropower price group.

[0015] According to another aspect of the present invention, there is provided an electronic device, which includes:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, it enables the at least one processor to execute the hydropower trading strategy determination method of any embodiment of the present invention.

[0019] According to another aspect of the present invention, there is provided a computer - readable storage medium, which stores computer instructions for enabling a processor to implement the hydropower trading strategy determination method of any embodiment of the present invention when executed.

[0020] The technical solution of the embodiment of the present invention realizes the accurate prediction of the predicted hydropower price group of the target area on the predicted day by determining at least one piece of historical power information corresponding to the target area and historical hydropower price groups corresponding to each piece of historical power information; determining the predicted power information of the target area on the predicted day; and determining the predicted hydropower price group of the target area on the predicted day according to at least one piece of historical power information, the historical hydropower price groups corresponding to each piece of historical power information, and the predicted power information. And finally, based on the predicted hydropower price group, a hydropower trading strategy is generated, so that when selling hydropower, losses can be reduced or profits can be increased, thereby optimizing the market performance of hydropower units.

[0021] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. Brief Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0023] Figure 1 is a flowchart of a method for determining a hydropower trading strategy according to Embodiment 1 of the present invention;

[0024] Figure 2 is a flowchart of another method for determining a hydropower trading strategy according to Embodiment 2 of the present invention;

[0025] Figure 3 is a schematic structural diagram of a device for determining a hydropower trading strategy according to Embodiment 3 of the present invention;

[0026] Figure 4 is a schematic structural diagram of an electronic device for implementing the method for determining a hydropower trading strategy of the embodiments of the present invention. Detailed Embodiments

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0029] Embodiment 1

[0030] Figure 1 FIG. 6 is a flowchart of a method for determining a hydropower trading strategy provided by Embodiment 1 of the present invention. This embodiment is applicable to situations where price prediction and trading strategy formulation are required in hydropower trading. The method can be executed by a hydropower trading strategy determination device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device with data processing capabilities. As Figure 1 shown, the method includes:

[0031] S110. Determine at least one historical power information corresponding to the target area and a historical hydropower price group corresponding to each historical power information.

[0032] The power information is information within the target area that affects the electricity price and the degree of influence is greater than a preset degree; the historical power information is the power information of the target area on a historical day; the historical days corresponding to each historical power information are different; the hydropower price group includes medium - long - term price, day - ahead price, and spot price.

[0033] Since the power generation capacity of hydropower units is affected by natural conditions (such as water resource flow rate, etc.), how to make an optimal trading strategy among multiple electricity market transactions (such as medium - long - term, day - ahead, real - time markets) has become a key issue in improving electricity efficiency.

[0034] When predicting hydropower prices in the prior art, simply relying on historical data for prediction often leads to large deviations, making it difficult to adapt to the dynamic changes in the short - term market, and mostly predicting the price situation of a single market, failing to comprehensively predict medium - long - term, day - ahead, and real - time prices.

[0035] When predicting the predicted hydropower price group on the prediction day in this application, it is necessary to first obtain at least one historical power information corresponding to the target area and a historical hydropower price group corresponding to each historical power information.

[0036] For the selection of power information, information within the target area that affects the electricity price and the degree of influence is greater than a preset degree will be selected, including but not limited to the electricity market bidding space, electricity market clearing price, and target area electricity load.

[0037] Among them, the electricity market bidding space can be the price range in which buyers and sellers reach a transaction through bidding and asking prices during the electricity market transaction process. The lower limit of this range is usually the lowest price acceptable to the seller, and the upper limit is the highest price willing to be paid by the buyer.

[0038] The clearing price of the electricity market can be the bid price of the power generation enterprise that meets the last unit of electricity demand.

[0039] The power load of the target area can refer to the total electric power consumed by all users in the target area.

[0040] This enables, when predicting the electricity price on the prediction day, to avoid simply relying on the historical hydropower electricity price group for prediction and ignoring the changes in the data that affect the hydropower price, thereby ensuring the accuracy of the predicted hydropower electricity price group corresponding to the prediction day as much as possible.

[0041] Among them, the prediction day is the date when the target area needs to predict the electricity price.

[0042] S120. Determine the predicted power information of the target area on the prediction day.

[0043] Since the predicted power information of the target area on the prediction day will be announced before the actual value of the predicted hydropower electricity price group on the prediction day is announced, by using the predicted power information of the target area on the prediction day and the historical power information of the target area in previous periods, it is possible to predict the predicted hydropower electricity price group on the prediction day before the predicted hydropower electricity price group on the prediction day is announced. Therefore, it is necessary to determine the predicted power information of the target area on the prediction day on the prediction day.

[0044] S130. Determine the predicted hydropower electricity price group of the target area on the prediction day according to at least one historical power information, the historical hydropower electricity price groups corresponding to each historical power information, and the predicted power information.

[0045] After obtaining at least one historical power information and the predicted power information on the prediction day, at this time, the predicted power information and each historical power information can be compared to determine the historical day that is most similar to the prediction day in terms of power information, and based on the historical hydropower electricity price group corresponding to this historical day, determine the predicted hydropower electricity price group of the target area on the prediction day.

[0046] Exemplarily, when the prediction day is Day A, the historical days include Day B and Day C. At this time, the similarity between the predicted power information corresponding to Day A and the historical power information corresponding to Day B and Day C is 90% and 80% respectively. At this time, it can be determined that the predicted power information of Day A is closer to the historical power information of Day B. At this time, the predicted hydropower electricity price group of Day A can be determined through the historical hydropower electricity price group of Day B.

[0047] In an alternative solution, determining the predicted hydropower electricity price group of the target area on the prediction day according to at least one historical power information, the historical hydropower electricity price groups corresponding to each historical power information, and the predicted power information may include steps A1 - A3:

[0048] Step A1: Based on the similarity algorithm, determine the similarity between each historical power information and the predicted power information, and obtain the information similarity corresponding to each historical power information.

[0049] Step A2: Determine the historical hydropower price group corresponding to the historical power information with the maximum information similarity as the reference hydropower price group of the target area on the prediction day.

[0050] Step A3: Based on the reference hydropower price group and the information similarity of the historical power information corresponding to the reference hydropower price group, determine the predicted hydropower price group of the target area on the prediction day.

[0051] When determining the similarity between each historical power information and the predicted power information, to ensure the accuracy of the determination result, a similarity algorithm can be used to judge the similarity between each historical power information and the predicted power information, so as to obtain the information similarity corresponding to each historical power information.

[0052] After obtaining the information similarity corresponding to each historical power information, the historical hydropower price group corresponding to the historical power information with the maximum information similarity can be determined as the reference hydropower price group of the target area on the prediction day, and based on the reference hydropower price group, the predicted hydropower price group of the target area on the prediction day can be determined.

[0053] Optionally, the similarity algorithm is a cosine similarity algorithm or an Euclidean distance similarity algorithm.

[0054] S140: Generate a hydropower trading strategy based on the predicted hydropower price group.

[0055] After obtaining the predicted hydropower price group, that is, the medium - long - term price, day - ahead price, and spot price corresponding to the target area on the prediction day, corresponding hydropower trading strategies can be formulated according to the differences in the medium - long - term price, day - ahead price, and spot price, so as to reduce losses or increase profits when selling hydropower, and then optimize the market performance of hydropower generating units.

[0056] According to the technical solution of the embodiment of the present invention, by determining at least one historical power information corresponding to the target area and the historical hydropower price group corresponding to each historical power information; determining the predicted power information of the target area on the prediction day; and determining the predicted hydropower price group of the target area on the prediction day according to at least one historical power information, the historical hydropower price group corresponding to each historical power information, and the predicted power information, an accurate prediction of the predicted hydropower price group of the target area on the prediction day is realized, and finally, based on the predicted hydropower price group, a hydropower trading strategy is generated, so as to reduce losses or increase profits when selling hydropower, and then optimize the market performance of hydropower generating units.

[0057] Embodiment Two

[0058] Figure 2 The present invention provides a flowchart of another method for determining a hydropower trading strategy. Based on the above embodiments, the present embodiment further optimizes the process of generating a hydropower trading strategy based on a predicted hydropower price group in the foregoing embodiments. The present embodiment can be combined with various alternative solutions in one or more of the above embodiments. As Figure 2 shown, the method for determining a hydropower trading strategy in this embodiment may include the following steps:

[0059] S210. Determine at least one piece of historical power information corresponding to the target area and the historical hydropower price group corresponding to each piece of historical power information.

[0060] The power information is information that affects the power price in the target area and the influence degree is greater than a preset degree; the historical power information is the power information in the target area on a historical day; the historical days corresponding to each piece of historical power information are different; the hydropower price group includes medium - long - term price, day - ahead price, and spot price; the power information at least includes the power market bidding space, the power market clearing price, and the power load in the target area.

[0061] S220. Determine the predicted power information of the target area on the predicted day.

[0062] S230. Determine the predicted hydropower price group of the target area on the predicted day according to at least one piece of historical power information, the historical hydropower price group corresponding to each piece of historical power information, and the predicted power information.

[0063] S240. Determine the medium - long - term demand power generation amount of the target area on the predicted day and the power generation capacity of the hydropower unit.

[0064] S250. If the predicted medium - long - term price is greater than the predicted day - ahead price, the predicted day - ahead price is greater than the predicted spot price, and the power generation capacity of the hydropower unit is greater than the medium - long - term demand power generation amount, then execute the first strategy.

[0065] The first strategy is to control the hydropower unit to generate electricity according to the medium - long - term demand power generation amount.

[0066] The medium - long - term demand power generation amount may be the power generation amount to be sold at the medium - long - term price determined in advance.

[0067] In the case where the predicted medium - long - term price is greater than the predicted day - ahead price and the predicted day - ahead price is greater than the predicted spot price, it can be determined that the predicted medium - long - term price is the highest on the predicted day. At this time, if the power generation capacity of the hydropower unit is greater than the medium - long - term demand power generation amount, it indicates that the hydropower unit can meet the medium - long - term demand power generation amount. At this time, the hydropower unit will be directly controlled to generate electricity according to the long - term demand power generation amount.

[0068] In an alternative solution, based on the predicted hydropower price group, a hydropower trading strategy is generated, which may include steps B1 - B2:

[0069] Step B1: Determine the medium - and long - term demand power generation in the target area on the prediction day and the power generation capacity of the hydropower units.

[0070] Step B2: If the predicted medium - and long - term price is greater than the price before the prediction day, the price before the prediction day is greater than the predicted spot price, and the power generation capacity of the hydropower units is less than the medium - and long - term demand power generation, then execute the second strategy; the second strategy is to control the hydropower units to generate electricity at full capacity and purchase electricity corresponding to the predicted spot price according to the power generation demand difference; the power generation demand difference is obtained by subtracting the power generation capacity of the hydropower units from the medium - and long - term demand power generation.

[0071] When the predicted medium - and long - term price is greater than the price before the prediction day and the price before the prediction day is greater than the predicted spot price, if the power generation capacity of the hydropower units is less than the medium - and long - term demand power generation, it indicates that only generating electricity through hydropower units cannot meet the medium - and long - term demand power generation. At this time, the electricity can be purchased at the predicted spot price with the lowest price to make up for the difference in long - term demand power generation.

[0072] In an alternative solution, based on the predicted hydropower price group, a hydropower trading strategy is generated, which may include steps C1 - C2:

[0073] Step C1: Determine the medium - and long - term demand power generation in the target area on the prediction day and the power generation capacity of the hydropower units.

[0074] Step C2: If the predicted medium - and long - term price is less than the price before the prediction day, the price before the prediction day is less than the predicted spot price, and the power generation capacity of the hydropower units is greater than the medium - and long - term demand power generation, then execute the third strategy; the third strategy is to control the hydropower units to generate electricity at full capacity and sell the excess power generation according to the predicted spot price; the excess power generation is obtained by subtracting the medium - and long - term demand power generation from the power generation produced by the hydropower units generating electricity at full capacity.

[0075] When the predicted medium - and long - term price is less than the price before the prediction day and the price before the prediction day is less than the predicted spot price, since the predicted medium - and long - term price is relatively low, when generating electricity through hydropower units to meet the medium - and long - term demand power generation, the final benefit will be relatively low. At this time, if the power generation capacity of the hydropower units is greater than the medium - and long - term demand power generation, the hydropower units can be controlled to generate electricity at full capacity to obtain excess power generation, and the excess power generation can be sold according to the predicted spot price to increase the overall income.

[0076] In an alternative solution, based on the predicted hydropower price group, a hydropower trading strategy is generated, which may include steps D1 - D2:

[0077] Step D1: Determine the medium- and long-term demand power generation of the target area on the prediction date and the power generation capacity of the hydropower units.

[0078] Step D2: If the predicted medium- and long-term price is less than the price before the prediction date, the price before the prediction date is greater than the predicted spot price, and the power generation capacity of the hydropower units is greater than the medium- and long-term demand power generation, then implement the fourth strategy; the fourth strategy is to control the hydropower units to generate electricity at full capacity and sell the excess power generation according to the price before the prediction date; the excess power generation is obtained by subtracting the medium- and long-term demand power generation from the power generation produced by the hydropower units generating electricity at full capacity.

[0079] In the case where the predicted medium- and long-term price is less than the price before the prediction date and the price before the prediction date is greater than the predicted spot price, since the predicted medium- and long-term price is low, when generating electricity through hydropower units to meet the medium- and long-term demand power generation at this time, it will lead to a low final benefit. At this time, if the power generation capacity of the hydropower units is greater than the medium- and long-term demand power generation, the hydropower units can be controlled to generate electricity at full capacity, so as to obtain excess power generation, and the excess power generation is sold according to the price before the prediction date, thereby increasing the overall income.

[0080] According to the technical solution of the embodiment of the present invention, by determining the medium- and long-term demand power generation of the target area on the prediction date and the power generation capacity of the hydropower units; if the predicted medium- and long-term price is greater than the price before the prediction date, the price before the prediction date is greater than the predicted spot price, and the power generation capacity of the hydropower units is greater than the medium- and long-term demand power generation, then implement the first strategy, thereby clarifying the specific process of generating a hydropower trading strategy based on the predicted hydropower price group and providing guidance for actual implementation.

[0081] Embodiment III

[0082] Figure 3 This embodiment of the present invention provides a structural block diagram of a hydropower trading strategy determination device. This embodiment is applicable to the situation where price prediction and trading strategy formulation are required in hydropower trading. The hydropower trading strategy determination device can be implemented in the form of hardware and / or software, and the hydropower trading strategy determination device can be configured in an electronic device with data processing capabilities. As Figure 3 shown, the hydropower trading strategy determination device of this embodiment may include: a historical data determination module 310, a prediction information determination module 320, a power price prediction module 330, and a trading strategy generation module 340.

[0083] Among them:

[0084] A historical data determination module 310, configured to determine at least one piece of historical power information corresponding to a target area and historical hydropower price groups corresponding to each piece of historical power information; the power information is information within the target area that affects the electricity price and the degree of influence is greater than a preset degree; the historical power information is the power information of the target area on a historical day; the historical days corresponding to each piece of historical power information are different; the hydropower price group includes medium- and long-term prices, day-ahead prices, and spot prices; the power information at least includes the power market bidding space, the power market clearing price, and the power load of the target area.

[0085] A prediction information determination module 320, configured to determine the predicted power information of the target area on a prediction day.

[0086] A power price prediction module 330, configured to determine the predicted hydropower price group of the target area on the prediction day according to at least one piece of historical power information, the historical hydropower price groups corresponding to each piece of historical power information, and the predicted power information.

[0087] A trading strategy generation module 340, configured to generate a hydropower trading strategy based on the predicted hydropower price group.

[0088] Based on the above embodiments, optionally, the power price prediction module 330 includes:

[0089] Based on a similarity algorithm, determine the similarity between each piece of historical power information and the predicted power information to obtain the information similarity corresponding to each piece of historical power information.

[0090] Determine the historical hydropower price group corresponding to the historical power information with the largest information similarity as the reference hydropower price group of the target area on the prediction day.

[0091] Based on the reference hydropower price group and the information similarity of the historical power information corresponding to the reference hydropower price group, determine the predicted hydropower price group of the target area on the prediction day.

[0092] Based on the above embodiments, optionally, the similarity algorithm is a cosine similarity algorithm or an Euclidean distance similarity algorithm.

[0093] Based on the above embodiments, optionally, the trading strategy generation module 340 includes:

[0094] Determine the medium- and long-term demand power generation volume of the target area on the prediction day and the power generation capacity of the hydropower units of the hydropower units.

[0095] If the predicted medium- and long-term price is greater than the predicted day-ahead price, the predicted day-ahead price is greater than the predicted spot price, and the power generation capacity of the hydropower units is greater than the medium- and long-term demand power generation volume, then execute the first strategy; the first strategy is to control the hydropower units to generate power according to the medium- and long-term demand power generation volume.

[0096] Based on the above embodiments, optionally, the trading strategy generation module 340 includes:

[0097] Determine the medium- and long-term demand power generation of the target area on the prediction date and the power generation capacity of the hydropower units;

[0098] If the predicted medium- and long-term price is greater than the price before the prediction date, the price before the prediction date is greater than the predicted spot price, and the power generation capacity of the hydropower units is less than the medium- and long-term demand power generation, then execute the second strategy; the second strategy is to control the hydropower units to generate electricity at full capacity, and purchase the power generation corresponding to the predicted spot price according to the power generation demand difference; the power generation demand difference is obtained by subtracting the power generation capacity of the hydropower units from the medium- and long-term demand power generation.

[0099] Based on the above embodiments, optionally, the trading strategy generation module 340 includes:

[0100] Determine the medium- and long-term demand power generation of the target area on the prediction date and the power generation capacity of the hydropower units;

[0101] If the predicted medium- and long-term price is less than the price before the prediction date, the price before the prediction date is less than the predicted spot price, and the power generation capacity of the hydropower units is greater than the medium- and long-term demand power generation, then execute the third strategy; the third strategy is to control the hydropower units to generate electricity at full capacity, and sell the excess power generation according to the predicted spot price; the excess power generation is obtained by subtracting the medium- and long-term demand power generation from the power generation produced by the hydropower units generating electricity at full capacity.

[0102] Based on the above embodiments, optionally, the trading strategy generation module 340 includes:

[0103] Determine the medium- and long-term demand power generation of the target area on the prediction date and the power generation capacity of the hydropower units;

[0104] If the predicted medium- and long-term price is less than the price before the prediction date, the price before the prediction date is greater than the predicted spot price, and the power generation capacity of the hydropower units is greater than the medium- and long-term demand power generation, then execute the fourth strategy; the fourth strategy is to control the hydropower units to generate electricity at full capacity, and sell the excess power generation according to the price before the prediction date; the excess power generation is obtained by subtracting the medium- and long-term demand power generation from the power generation produced by the hydropower units generating electricity at full capacity.

[0105] The hydropower trading strategy determination device provided by the embodiments of the present invention can execute the hydropower trading strategy determination method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0106] Embodiment 4

[0107] Figure 4The schematic structural diagram of the electronic device 10 that can be used to implement the embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described herein and / or claimed.

[0108] As Figure 4 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0109] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0110] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the hydropower trading strategy determination method.

[0111] In some embodiments, the method for determining a hydropower trading strategy may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for determining a hydropower trading strategy described above may be executed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for determining a hydropower trading strategy by any other suitable means (e.g., by means of firmware).

[0112] Various embodiments of the systems and techniques described above in this document may be implemented in digital electronic circuitry, integrated circuit systems, field-programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0113] The computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs may be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine, or entirely on the remote machine or server.

[0114] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0115] In order to provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0116] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0117] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0118] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0119] The above specific embodiments do not constitute a limitation to the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining a hydropower trading strategy, characterized in that, Including: Determine at least one historical power information corresponding to the target area and the historical hydropower price groups corresponding to each historical power information; The power information is information within the target area that affects the power price and the degree of influence is greater than a preset degree; the historical power information is the power information of the target area on a historical day; the historical days corresponding to each historical power information are different; the hydropower price group includes medium- and long-term prices, day-ahead prices, and spot prices; the power information includes at least the power market bidding space, the power market clearing price, and the power load of the target area; Determine the predicted power information of the target area on the predicted day; According to at least one historical power information, the historical hydropower price groups corresponding to each historical power information, and the predicted power information, determine the predicted hydropower price group of the target area on the predicted day; the predicted hydropower price group includes the predicted medium- and long-term price, the predicted day-ahead price, and the predicted spot price; Generate a hydropower trading strategy based on the predicted hydropower price group.

2. The method according to claim 1, wherein According to at least one historical power information, the historical hydropower price groups corresponding to each historical power information, and the predicted power information, determining the predicted hydropower price group of the target area on the predicted day includes: Based on a similarity algorithm, determine the similarity between each historical power information and the predicted power information to obtain the information similarity corresponding to each historical power information; Determine the historical hydropower price group corresponding to the historical power information with the largest information similarity as the reference hydropower price group of the target area on the predicted day; Based on the reference hydropower price group and the information similarity of the historical power information corresponding to the reference hydropower price group, determine the predicted hydropower price group of the target area on the predicted day.

3. The method according to claim 2, wherein The similarity algorithm is a cosine similarity algorithm or an Euclidean distance similarity algorithm.

4. The method according to claim 1, characterized in that, Generating a hydropower trading strategy based on the predicted hydropower price group includes: Determine the medium- and long-term demand power generation volume of the target area on the predicted day and the power generation capacity of the hydropower units of the hydropower units; If the predicted medium- and long-term price is greater than the predicted day-ahead price, the predicted day-ahead price is greater than the predicted spot price, and the power generation capacity of the hydropower units is greater than the medium- and long-term demand power generation volume, then execute the first strategy; the first strategy is to control the hydropower units to generate power according to the medium- and long-term demand power generation volume.

5. The method according to claim 1, wherein Generating a hydropower trading strategy based on the predicted hydropower price group includes: Determine the medium- and long-term demand power generation volume of the target area on the predicted day and the power generation capacity of the hydropower units of the hydropower units; If the predicted medium- and long-term price is greater than the predicted day-ahead price; the predicted day-ahead price is greater than the predicted spot price, and the power generation capacity of the hydropower units is less than the medium- and long-term demand power generation volume, then execute the second strategy; the second strategy is to control the hydropower units to generate power at full capacity and purchase power generation corresponding to the predicted spot price according to the power generation demand difference; the power generation demand difference is obtained by subtracting the power generation capacity of the hydropower units from the medium- and long-term demand power generation volume.

6. The method according to claim 1, wherein Generating a hydropower trading strategy based on the predicted hydropower price group includes: Determine the medium- and long-term demand power generation volume of the target area on the predicted day and the power generation capacity of the hydropower units of the hydropower units; If the predicted medium- and long-term price is less than the price before the prediction date; the price before the prediction date is less than the predicted spot price, and the power generation capacity of the hydropower unit is greater than the medium- and long-term demand power generation, then the third strategy is executed; the third strategy is to control the hydropower unit to generate electricity at full capacity, and sell the excess power generation according to the predicted spot price; the excess power generation is obtained by subtracting the medium- and long-term demand power generation from the power generation produced by the full-capacity operation of the hydropower unit.

7. The method according to claim 1, characterized in that Based on the predicted hydropower price group, generate a hydropower trading strategy, including: Determine the medium- and long-term demand power generation in the target area on the prediction date and the power generation capacity of the hydropower unit. If the predicted medium- and long-term price is less than the price before the prediction date; the price before the prediction date is greater than the predicted spot price, and the power generation capacity of the hydropower unit is greater than the medium- and long-term demand power generation, then the fourth strategy is executed; the fourth strategy is to control the hydropower unit to generate electricity at full capacity, and sell the excess power generation according to the price before the prediction date; the excess power generation is obtained by subtracting the medium- and long-term demand power generation from the power generation produced by the full-capacity operation of the hydropower unit.

8. A device for determining a hydropower trading strategy, characterized in that, Including: A historical data determination module for determining at least one historical power information corresponding to the target area and the historical hydropower price group corresponding to each historical power information. The power information is information that affects the power price in the target area and the degree of influence is greater than the preset degree; the historical power information is the power information in the target area on the historical date; the historical dates corresponding to each historical power information are different; the hydropower price group includes the medium- and long-term price, the price before the day, and the spot price; the power information includes at least the power market bidding space, the power market clearing price, and the power load in the target area. A prediction information determination module for determining the predicted power information in the target area on the prediction date. A power price prediction module for determining the predicted hydropower price group in the target area on the prediction date according to at least one historical power information, the historical hydropower price group corresponding to each historical power information, and the predicted power information. A trading strategy generation module for generating a hydropower trading strategy based on the predicted hydropower price group.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the hydropower trading strategy determination method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a processor to execute the hydropower trading strategy determination method according to any one of claims 1-7 when executed.

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