Heat storage type water source heat pump heating control system and method based on peak-valley electricity price

Abstract

The present application relates to the technical field of energy storage, in particular to a heat storage type water source heat pump heating control system and method based on peak-valley electricity price, comprising the following steps: S1: obtaining heat demand characteristic information in a greenhouse, wherein the heat demand characteristic information comprises environmental information and planting plant information; predicting target demand heat in the greenhouse based on the heat demand characteristic information; S2: obtaining electricity price data in a cycle, the cycle comprising minimum electricity price data, maximum electricity price data and flat section electricity price data; obtaining a time period corresponding to the minimum electricity price data as a valley electricity period, and storing heat in a heat reservoir through a heat pump in the valley electricity period; obtaining a time period corresponding to the maximum electricity price data, and automatically storing heat in the heat reservoir in a flat electricity or valley electricity period, which can fully utilize low-price electricity and avoid excessive consumption of heat when the electricity price is too high, thereby improving energy utilization.

Description

Technical Field

[0001] This invention relates to the field of energy storage technology, specifically to a thermal storage-type water source heat pump heating control system and method based on peak-valley electricity pricing. Background Technology

[0002] Power supply bureaus across the country will offer a 50% discount on electricity prices to industrial, commercial, and residential users from 11 PM to 7 AM the following morning to encourage nighttime electricity consumption and improve the economic efficiency of power supply departments in various regions. The biggest beneficiaries of this peak-valley pricing are electric heating systems, whose operating costs will be significantly reduced, leading to a completely new landscape in the heating market. Electric heating is reliable, convenient, economical, and environmentally friendly, providing high-quality temperatures and comfort for greenhouses.

[0003] Currently, when growing plants out of season in greenhouses, the greenhouses need to be heated. If peak and off-peak electricity prices are not considered, users may heat the greenhouses when electricity prices are high, resulting in economic waste and low energy utilization.

[0004] Therefore, we propose a thermal storage-type water source heat pump heating control system and method based on peak-valley electricity pricing to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a thermal storage-type water source heat pump heating control system and method based on peak-valley electricity pricing, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a thermal storage-type water source heat pump heating control system and method based on peak-valley electricity pricing, the method comprising the following steps:

[0007] S1: Obtain heat demand characteristic information in the greenhouse, including environmental information and plant information; predict the target heat demand in the greenhouse based on the heat demand characteristic information;

[0008] S2: Obtain electricity price data within a cycle, which includes the lowest electricity price data, the highest electricity price data, and the flat electricity price data. Obtain the time period corresponding to the lowest electricity price data as the off-peak electricity period, and store heat in the heat storage through a heat pump during the off-peak electricity period. Obtain the time period corresponding to the highest electricity price data as the peak electricity period, and release heat to the heat storage during the peak electricity period. Calculate the remaining heat in the heat storage.

[0009] S3: Obtain the remaining heat in the heat storage facility and determine whether the remaining heat in the heat storage facility meets the target heat demand. If it is determined that the remaining heat in the heat storage facility meets the target heat demand, continue to execute the step of storing heat in the heat storage facility through a heat pump during the period with the lowest electricity price. If it is determined that the remaining heat in the heat storage facility does not meet the target heat demand, select the target electricity price period based on the flat electricity price to store heat in the heat storage facility.

[0010] Preferably, the step of predicting the target heat demand in the greenhouse based on heat demand characteristic information includes:

[0011] Obtain environmental information and plant information. The environmental information includes the current outdoor temperature, historical outdoor temperature, current indoor temperature, and historical indoor temperature. The plant information includes the types of plants, planting density, and growth stage of the plants.

[0012] Using the historical outdoor and indoor temperatures corresponding to the same type of plant as a training set, the existing heat prediction model is trained based on the training set, and multiple prediction models are obtained based on multiple different types of plant.

[0013] Based on multiple prediction models, extract the prediction model corresponding to the current plant species, input the current outdoor temperature and current indoor temperature corresponding to the current plant species into the prediction model, and obtain the first existing heat value;

[0014] A second existing heat value is calculated based on the plant information, and a comprehensive existing heat value is calculated based on the first existing heat value and the second existing heat value.

[0015] Establish a correspondence between plant information and actual heat demand values, and obtain multiple actual heat demand values ​​based on plant species, planting density and growth stage;

[0016] Obtain the actual calorie demand value corresponding to the plant information, and subtract the comprehensive existing calorie value from the actual calorie demand value to obtain the current target calorie demand value;

[0017] Obtain the duration between the current time and the start time of the next lowest electricity price, denoted as the heat consumption duration. The start time of the next lowest electricity price includes the start time of the next off-peak electricity price or the start time of the lowest electricity price in the next flat-rate electricity price. Multiply the current target heat demand by the heat consumption duration to obtain the target heat demand.

[0018] Preferably, the step of calculating the second existing heat based on plant information includes:

[0019] Obtain the types of plants to be planted and the corresponding growth stages of those plants, and determine the corresponding respiration rate based on the plant growth stages.

[0020] The total mass of plants per unit area is calculated based on plant density. The total mass of plants per unit area is multiplied by the respiration rate of each plant to obtain the total respiration rate of plants per unit area.

[0021] The second existing heat is calculated based on the correlation function Q2=D×M×R×206×t×S, where R is the respiration rate, M is the average mass of each plant, D is the plant density per unit area, and S is the area of ​​the same plant species.

[0022] Preferably, the step of selecting a target electricity price time period based on the flat-section electricity price for thermal energy storage in the thermal reservoir includes:

[0023] The remaining heat, consumed heat, and consumption rate of the thermal storage are obtained. The consumption time of the remaining heat is calculated based on the consumed heat, consumption rate, and remaining heat in the thermal storage. Based on the consumption time and the current time point, the first farthest time point corresponding to when the remaining heat in the thermal storage is completely consumed is determined. The time period between the current time point and the first farthest time point is recorded as the target thermal storage period. Within the target thermal storage period, multiple time points are divided according to electricity price data, and each time point corresponds to an electricity value.

[0024] The electricity values ​​corresponding to multiple time points are sorted in chronological order to form the original pointer queue. The original pointer queue is updated based on the remaining amount of the heat storage to obtain the latest pointer queue. Based on the latest pointer queue, the pointer head is set to the electricity value with the lowest electricity price to obtain the lowest electricity price.

[0025] a. Determine the time point corresponding to the lowest electricity price based on the latest pointer queue to obtain the target time point;

[0026] b. Determine the target heat storage capacity based on the remaining heat and heat consumption of the heat storage facility; obtain the duration corresponding to the lowest electricity price at the target time point as the standby heat storage period, and record the heat storage capacity during the standby heat storage period as the actual heat storage capacity.

[0027] c. Determine the relationship between the actual heat storage capacity and the target heat storage capacity; based on the determination results, carry out heat storage in the heat storage facility. The determination results include the actual heat storage capacity being less than the target heat storage capacity, the actual heat storage capacity being equal to the target heat storage capacity, and the actual heat storage capacity being greater than the target heat storage capacity.

[0028] Preferably, the step of determining the relationship between the actual heat storage capacity and the target heat storage capacity, and then performing heat storage in the thermal reservoir based on the determination result, includes:

[0029] If it is determined that the actual heat storage is less than the target heat storage, the pointer head is pointed to an electricity price other than the minimum electricity price based on the latest pointer queue to obtain the second lowest electricity price; the second lowest electricity price replaces the minimum electricity price, and steps a to c are executed until the actual heat storage is equal to the target heat storage or the actual heat storage is greater than the target heat storage.

[0030] If it is determined that the actual heat storage heat is equal to the target heat storage heat, then heat storage energy will be carried out in the heat storage facility when the current time point reaches the target time point.

[0031] If it is determined that the actual heat storage capacity is greater than the target heat storage capacity, the target heat storage duration is calculated based on the heat storage rate and the target heat storage capacity. The time points corresponding to multiple lowest electricity prices are sorted in ascending order of electricity value. Based on the time sorting, the time point corresponding to the highest electricity value among the multiple lowest electricity prices is taken as the final target time point. The heat storage duration corresponding to each electricity value when the actual heat storage capacity is equal to or less than the target heat storage capacity is obtained as the first heat storage duration. Based on the target heat storage duration, the heat storage duration of the last target time point is determined to obtain the second heat storage duration. Based on the second heat storage duration, the working duration of heat storage at the last target time point is determined. Based on the first heat storage duration and the second heat storage duration, the heat pump is started sequentially according to the time sorting of the corresponding target time points to store heat energy in the heat storage facility.

[0032] Preferably, the step of updating the original pointer queue based on the remaining amount in the hot storage to obtain the latest pointer queue includes:

[0033] Obtain the original pointer queue, determine the target time point in the target heat storage period based on the original pointer queue, calculate the remaining heat of the heat storage after heat storage at the target time point, and use it as the remaining heat of the second heat storage.

[0034] Based on the consumption time and the current time point, determine the farthest time point corresponding to when the remaining heat in the second heat storage is completely consumed, and use it as the second farthest time point;

[0035] The time period between the current time point and the second farthest time point is defined as the second target heat storage period.

[0036] Obtain the electricity value at each time point corresponding to the second target heat storage period, sort the electricity values ​​within the second target heat storage period in chronological order, and obtain the latest pointer queue.

[0037] A thermal storage-type water source heat pump heating control system based on peak-valley electricity pricing, applied to any of the above-described thermal storage-type water source heat pump heating control methods, includes:

[0038] The information acquisition module is used to acquire heat demand characteristic information in the greenhouse, including environmental information and plant information; and to predict the target heat demand in the greenhouse based on the heat demand characteristic information.

[0039] The information analysis module acquires electricity price data within a cycle, which includes the lowest electricity price, the highest electricity price, and the flat-period electricity price. It acquires the time period corresponding to the lowest electricity price as the off-peak electricity period, during which heat pumps store heat in the heat storage. It also acquires the time period corresponding to the highest electricity price as the peak electricity period, during which heat is released from the heat storage, and calculates the remaining heat in the heat storage.

[0040] The judgment control module is used to obtain the remaining heat of the hot storage and determine whether the remaining heat of the hot storage meets the target heat demand. If it is determined that the remaining heat of the hot storage meets the target heat demand, the step of storing heat in the hot storage through the heat pump during the period with the lowest electricity price continues. If it is determined that the remaining heat of the hot storage does not meet the target heat demand, the target electricity price period is selected based on the flat electricity price to store heat in the hot storage.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] 1. Based on the different information of the planted plants, predict the heat demand in the greenhouse, and determine whether the heat storage needs to be replenished by combining the remaining heat in the heat storage. Sort the time points of various electricity prices and replenish the corresponding heat storage in the order of time. It can store heat at the lowest electricity price when the remaining heat in the heat storage is sufficient. It automatically stores heat in the heat storage during the period when the electricity price is relatively flat or during off-peak hours. It can make full use of low-priced electricity and avoid excessive heat consumption when the electricity price is too high, thereby improving energy utilization efficiency.

[0043] 2. During off-peak hours, electricity is converted into heat energy for storage, which can then be used during peak hours. If lower electricity prices are anticipated during off-peak periods, the system can choose not to activate the heat pump during these times, instead directly utilizing the heat stored in the thermal storage. The timing and method of heat storage are dynamically adjusted based on electricity price trends to ensure that the heat stored can meet the energy needs of the next phase before the next electricity price increase. Water is heated via the heat pump during periods of low electricity prices, and then the stored heat energy is used during periods of high electricity prices, thereby reducing electricity costs. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0046] Figure 2 This is a system structure block diagram of the present invention.

[0047] The attached diagram lists the components represented by each number as follows:

[0048] 1. Information acquisition module; 2. Information analysis module; 3. Judgment and control module. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Example 1

[0051] Please see Figures 1 to 2 This invention provides a technical solution for a thermal storage-type water source heat pump heating control system and method based on peak-valley electricity pricing: The thermal storage-type water source heat pump heating control method based on peak-valley electricity pricing includes the following steps:

[0052] S1: Obtain heat demand characteristic information in the greenhouse, including environmental information and plant information; predict the target heat demand in the greenhouse based on the heat demand characteristic information;

[0053] The steps for predicting the target heat demand in a greenhouse based on heat demand characteristics include:

[0054] Obtain environmental information and plant information. The environmental information includes the current outdoor temperature, historical outdoor temperature, current indoor temperature, and historical indoor temperature. The plant information includes the types of plants, planting density, and growth stage of the plants.

[0055] Using the historical outdoor and indoor temperatures corresponding to the same type of plant as a training set, the existing heat prediction model is trained based on the training set, and multiple prediction models are obtained based on multiple different types of plant.

[0056] Based on multiple prediction models, extract the prediction model corresponding to the current plant species, input the current outdoor temperature and current indoor temperature corresponding to the current plant species into the prediction model, and obtain the first existing heat value;

[0057] A second existing heat value is calculated based on the plant information, and a comprehensive existing heat value is calculated based on the first existing heat value and the second existing heat value.

[0058] Establish a correspondence between plant information and actual heat demand values, and obtain multiple actual heat demand values ​​based on plant species, planting density and growth stage;

[0059] Specifically, the actual caloric requirements corresponding to historical plant species, planting density, various growth stages, and information on each plant are obtained and stored in a database as a training set. A model corresponding to the actual caloric requirements is trained using this training set. The current plant species, planting density, and growth stage are collected and input into the corresponding model to obtain a corresponding actual caloric requirement. For example, if the plant species is spinach and the planting density is P, the actual caloric requirement is Qy if the growth stage is seedling stage, and Qf if the growth stage is germination stage. Assuming the current plant species is spinach, the planting density is P, and the growth stage is seedling stage, then the corresponding actual caloric requirement is Qy. The actual caloric requirements of the plant will vary under different planting densities and growth stages. The relationship between growth stage and actual caloric requirement is established. For the same plant species and planting density, different growth stages correspond to different actual caloric requirements. For example, suppose a certain vegetable crop (e.g., spinach) is grown in a greenhouse and it is planned to be grown in the greenhouse year-round. To estimate the actual caloric requirements of spinach under different conditions, follow these steps: Understand the growth habits and ecological needs of spinach; for example, spinach prefers a warm (but not too hot) climate and requires ample sunlight and water. Determine an appropriate planting density to ensure spinach receives sufficient sunlight and space. Planting density can be determined by observing the distance between adjacent plants or referring to other planting recommendations. The caloric requirements of spinach may also change at different growth stages. For example, during the vegetative growth stage, spinach requires a large amount of heat to support its rapid growth, while during the fruiting stage, it may require less heat. Therefore, the current growth stage of the spinach needs to be considered when determining the actual caloric requirements. Spinach may be sensitive to temperature changes. In winter, spinach may need to be kept in a relatively warm greenhouse environment, while in the high temperatures of summer, spinach may need to avoid excessively hot temperatures. A range of actual caloric requirements for spinach under different conditions will be derived. For example, assuming we grow spinach in a greenhouse, we can derive the following range of heat values: during the high temperatures of spring and autumn, spinach may require approximately 10°C to 15°C of heat; during the high temperatures of summer, spinach may require approximately 12°C to 18°C ​​of heat; and during the low temperatures of winter, spinach may require approximately 10°C to 15°C of heat.

[0060] Obtain the actual calorie demand value corresponding to the plant information, and subtract the comprehensive existing calorie value from the actual calorie demand value to obtain the current target calorie demand value;

[0061] Obtain the duration between the current time and the start time of the next lowest electricity price, which is denoted as the heat consumption duration. The start time of the next lowest electricity price includes the start time of the next off-peak electricity price or the start time of the lowest electricity price in the next flat-rate electricity price. Multiply the current target heat demand by the heat consumption duration to obtain the target heat demand.

[0062] It should be noted that the prediction model corresponding to the current plant species is extracted based on multiple prediction models. The current outdoor temperature and the current indoor temperature corresponding to the current plant species are input into the prediction model to obtain the first existing heat value. Among them, only the temperature difference between the indoor and outdoor areas of the greenhouse is different, while other conditions are the same, including the volume of the greenhouse and the heat transfer medium, such as air. The prediction model for the first existing heat value is Q1 = CM × ΔT, where Q represents the heat inside the greenhouse, ΔT represents the temperature difference between the indoor and outdoor temperatures, and at this time, the indoor temperature is less than the outdoor temperature, C represents the specific heat capacity of air, and M represents the mass of the greenhouse, which is equal to the air density multiplied by the volume of the greenhouse.

[0063] The total available heat refers to the sum of heat generated by the environment and heat generated by planting plants;

[0064] The target heat demand Q is calculated based on the correlation function Q=(Qs-(Q1+Q2))×t, where Qs is the actual heat demand value corresponding to the plant information, t is the time between the current time point and the start time of the next minimum electricity price, Q1 is the first existing heat, and Q2 is the second existing heat.

[0065] Specifically, predictions are made based on environmental and plant information. Environmental information includes current weather temperature and current season information to predict the heat required in the next period. Plant information includes plant species, plant density, and plant growth stage. The heat requirement is different for each plant species, plant density, and plant growth stage. For example, under the same environment, some plant species require less heat, while others require more. The higher the planting density, the less heat is required. The heat requirement is also different for different plant growth stages. Historical data is used to predict the changing trends of environmental heat production and plant heat production. The comprehensive heat is obtained by combining the environmental heat production and the plant's own heat. Then, the actual heat requirement of the plant is subtracted from the comprehensive existing heat and multiplied by the duration from the current time period to the next off-peak electricity period to obtain the target heat requirement in the greenhouse.

[0066] The steps for calculating the second existing heat capacity based on plant information include:

[0067] Obtain the types of plants to be planted and the corresponding growth stages of those plants, and determine the corresponding respiration rate based on the plant growth stages.

[0068] The total mass of plants per unit area is calculated based on plant density. The total mass of plants per unit area is multiplied by the respiration rate of each plant to obtain the total respiration rate of plants per unit area.

[0069] The second existing heat is calculated based on the correlation function Q2=D×M×R×206×t×S, where R is the respiration rate, M is the average mass of each plant, D is the plant density per unit area, and S is the area of ​​the same plant species.

[0070] Specifically, based on the plant species and growth stage, relevant literature or databases are consulted to obtain the plant's respiration rate. The respiration rate is usually expressed as the amount of CO2 released or O2 consumed per unit time (e.g., per hour) per unit mass (e.g., per gram of dry weight) of plant tissue. The respiration rate may vary with environmental conditions (e.g., temperature, light, moisture, etc.). In this embodiment, an average respiration rate is assumed. The total respiration rate of plants per unit area is calculated: assuming the average mass (dry weight) and respiration rate of each plant are known. Based on the plant density (i.e., the number of plants per unit area), the total mass of plants per unit area is calculated. The total mass of plants per unit area is multiplied by the respiration rate of each plant to obtain the total respiration rate of plants per unit area. The heat generated by the plants is estimated: assuming all energy released by respiration is converted into heat. The energy released by respiration (i.e., the heat generated) can be estimated using the respiration rate and the efficiency of energy conversion during respiration. Typically, the energy released by consuming 1 mole of O2 (approximately 32 grams) is about 206 kJ (this is the energy released by the complete oxidation of glucose during aerobic respiration); assuming the respiration rate is R mol O2 / g dry weight·h, the average mass of each plant is M g dry weight, and the plant density is D plants / m² 2 The heat generated by plants per unit area per unit time is Q (kJ / m²). 2 / h) can be expressed as: Q=D×M×R×206;

[0071] S2: Obtain electricity price data within a cycle, which includes the lowest electricity price data, the highest electricity price data, and the flat electricity price data. Obtain the time period corresponding to the lowest electricity price data as the off-peak electricity period, and store heat in the heat storage through a heat pump during the off-peak electricity period. Obtain the time period corresponding to the highest electricity price data as the peak electricity period, and release heat to the heat storage during the peak electricity period. Calculate the remaining heat in the heat storage.

[0072] It should be noted that a thermal storage facility refers to a place used to store thermal energy during off-peak electricity hours;

[0073] S3: Obtain the remaining heat in the hot storage and determine whether the remaining heat in the hot storage meets the target heat demand. If it is determined that the remaining heat in the hot storage meets the target heat demand, continue to execute the step of storing heat in the hot storage through a heat pump during the period with the lowest electricity price. If it is determined that the remaining heat in the hot storage does not meet the target heat demand, select the target electricity price period based on the flat electricity price to store heat in the hot storage.

[0074] The steps for thermal energy storage in a thermal facility based on selecting a target electricity price time period according to the flat-rate electricity price include:

[0075] The remaining heat, consumed heat, and consumption rate of the thermal storage are obtained. The consumption time of the remaining heat is calculated based on the consumed heat, consumption rate, and remaining heat in the thermal storage. Based on the consumption time and the current time point, the first farthest time point corresponding to when the remaining heat in the thermal storage is completely consumed is determined. The time period between the current time point and the first farthest time point is recorded as the target thermal storage period. Within the target thermal storage period, multiple time points are divided according to electricity price data, and each time point corresponds to an electricity value.

[0076] The electricity values ​​corresponding to multiple time points are sorted in chronological order to form the original pointer queue. The original pointer queue is updated based on the remaining amount of the heat storage to obtain the latest pointer queue. Based on the latest pointer queue, the pointer head is set to the electricity value with the lowest electricity price to obtain the lowest electricity price.

[0077] It should be noted that a pointer queue refers to a clock-shaped arrangement of electricity values ​​at various points in time within a cycle (such as a day), with the pointers pointing sequentially to the lowest electricity price within the selectable range in ascending order of electricity value. This allows the target time point to be determined based on the time point corresponding to the lowest electricity price.

[0078] a. Determine the time point corresponding to the lowest electricity price based on the latest pointer queue to obtain the target time point;

[0079] b. Determine the target heat storage capacity based on the remaining heat and heat consumption of the heat storage facility; obtain the duration corresponding to the lowest electricity price at the target time point as the standby heat storage period, and record the heat storage capacity during the standby heat storage period as the actual heat storage capacity.

[0080] c. Determine the relationship between the actual heat storage capacity and the target heat storage capacity; based on the determination results, carry out heat storage in the heat storage facility. The determination results include the actual heat storage capacity being less than the target heat storage capacity, the actual heat storage capacity being equal to the target heat storage capacity, and the actual heat storage capacity being greater than the target heat storage capacity.

[0081] Determine the relationship between the actual and target thermal energy storage capacity; based on the determination result, the steps for thermal energy storage in the thermal reservoir include:

[0082] If it is determined that the actual heat storage is less than the target heat storage, the pointer head is pointed to an electricity price other than the minimum electricity price based on the latest pointer queue to obtain the second lowest electricity price; the second lowest electricity price replaces the minimum electricity price, and steps a to c are executed until the actual heat storage is equal to the target heat storage or the actual heat storage is greater than the target heat storage.

[0083] When this minimum electricity price replaces the target electricity price, the corresponding target time point will change. The change in the target time point will cause the pointer queue to be updated. After the pointer queue is updated, the remaining heat of the thermal storage and the standby heat storage period will change. Different standby heat storage periods will bring different actual heat storage heat. According to the update of the pointer queue, the heat storage heat at the minimum electricity price will affect the remaining heat of the thermal storage, causing both the remaining heat of the thermal storage and the actual heat storage heat to change. As a result, the judgment results of the two may be different. The first time the actual heat storage heat is less than the target heat storage heat is judged by the minimum electricity price. The second time the relationship between the actual heat storage heat and the target heat storage heat is judged by the next minimum electricity price, and so on.

[0084] If it is determined that the actual heat storage heat is equal to the target heat storage heat, then heat storage energy will be carried out in the heat storage facility when the current time point reaches the target time point.

[0085] If it is determined that the actual heat storage capacity is greater than the target heat storage capacity, the target heat storage duration is calculated based on the heat storage rate and the target heat storage capacity. The time points corresponding to multiple lowest electricity prices are sorted in ascending order of electricity value. Based on this time sorting, the time point corresponding to the highest electricity value among the multiple lowest electricity prices is taken as the final target time point. The heat storage duration corresponding to each electricity value when the actual heat storage capacity is equal to or less than the target heat storage capacity is obtained as the first heat storage duration. Based on the target heat storage duration, the heat storage duration for the last target time point is determined, resulting in the second heat storage duration. Based on the second heat storage duration, the working duration for heat storage at the final target time point is determined. Based on the first and second heat storage durations, the heat pumps are started sequentially according to the time sorting of the corresponding target time points to perform heat storage in the thermal reservoir.

[0086] It should be noted that water has a high specific heat capacity, enabling it to effectively store and release large amounts of heat energy. Using water as a heat storage medium allows for heating via heat pumps during periods of low electricity prices (typically at night or off-peak hours), and then releasing that heat for heating during periods of higher electricity prices. Users can utilize the low-price periods to heat water via heat pumps and then use the stored heat energy during periods of higher electricity prices, thereby reducing electricity costs.

[0087] Specifically, the lowest electricity price in a pointer queue is selected first. The time point corresponding to the lowest electricity price is chosen, and it is calculated whether the remaining heat is sufficient to cover the lowest electricity price. If so, heat storage begins at the time point corresponding to the lowest electricity price. If not, the duration of the lowest electricity price is obtained, and it is determined whether the heat stored within the first duration is sufficient to cover the start of off-peak electricity. If so, heat storage begins at the time point corresponding to the lowest electricity price. If not, a second lowest electricity price is obtained, the time point corresponding to the second lowest electricity price is determined, the duration of the second lowest electricity price is determined, and the heat stored for the second duration is predicted. The sum of the heat stored within the first duration and the heat stored within the second duration is compared to the target heat storage heat (calculated by subtracting the remaining heat from the consumed heat during the time period). If the sum of the heat stored within the specified time is less than the target heat storage amount, the duration of the third lowest electricity price will continue to be obtained until the sum of the heat stored within the specified time meets the target heat storage amount. If the sum of the heat stored within the specified time is equal to the target heat storage amount, the time points corresponding to each lowest electricity price will be obtained and sorted, and heat storage will be carried out in the order of the time points. If the sum of the heat stored within the specified time is greater than the target heat storage amount, the target heat storage amount will be subtracted from the sum of the heat stored to obtain the excess heat storage amount. The duration required for the excess heat storage amount will be determined, and the excess heat storage duration will be obtained. The highest electricity price among the three electricity prices will be selected, and the excess heat storage duration will be deducted from the heat storage duration corresponding to the highest electricity price (that is, the heat storage duration corresponding to the highest electricity price will be reduced so that the heat stored is exactly corresponding to the target heat storage amount, avoiding the situation where the electricity price is high due to heat storage during the parity period).

[0088] Assuming the period from 7:00 to 11:00 is the flat-price period, the latest pointer queue for electricity prices during this period is 7:00, 8:00, 9:00, and 10:00, with prices of 1 yuan, 0.6 yuan, 1.2 yuan, and 0.8 yuan respectively. Each price lasts for one hour. When the remaining heat in the storage facility is insufficient, first determine the furthest possible time point from which the remaining heat can be used. Sort the electricity prices from the current time point to the furthest possible time point within the flat-price period in ascending order. Select the lowest electricity price and the time point corresponding to the lowest price from the period leading to the furthest possible time point. Assuming the target heat demand at the current time point is Q1 (i.e., the heat required to reach this time), the remaining heat is Q2, Q1 is greater than Q2, and Q1-Q2 is the target heat storage capacity Q3. Assuming the heat obtained by storing heat for one hour at an electricity price of 0.6 yuan is Q4, determine the relationship between Q4 and Q3. If Q4 is greater than Q3, then we can directly wait for the time corresponding to the 0.6 yuan price to start storing heat. If Q4 is less than Q3, then... 3. Then, heat storage is performed again at an electricity price of 1 yuan. Assuming the heat obtained after one hour of heat storage at a price of 1 yuan is Q5, the relationship between the sum of Q5 and Q4 (Q7) and Q3 is determined. If Q7 is greater than Q3, Q4 is subtracted from Q3 to calculate the remaining heat storage capacity. The required heat storage time for the remaining heat storage capacity is calculated based on the heat transfer rate per unit time. The heat obtained by storing heat at a price of 1 yuan and the corresponding heat storage time is Q8. The heat obtained by adding Q8 and Q4 is the target heat storage capacity. If Q7 is less than Q3, the lowest remaining electricity price is selected for heat storage, such as the time point of 0.8 yuan. The time points of each electricity price are sorted by time, and the corresponding heat storage capacity is added in sequence according to the time. This allows heat storage to be performed at the lowest electricity price while ensuring that the remaining heat in the heat storage is sufficient. It automatically stores heat in the heat storage during periods of relatively flat or off-peak electricity prices, which can make full use of low-priced electricity and avoid excessive heat consumption when the electricity price is too high, thereby improving energy utilization efficiency.

[0089] The steps for updating the original pointer queue based on the remaining amount of thermal storage to obtain the latest pointer queue include: obtaining the original pointer queue; determining the target time point in the target thermal storage period based on the original pointer queue; calculating the remaining heat of the thermal storage after thermal storage at the target time point, as the second remaining heat of the thermal storage; determining the farthest time point corresponding to the complete consumption of the remaining heat of the second thermal storage based on the consumption time and the current time point, as the second farthest time point; recording the period between the current time point and the second farthest time point as the second target thermal storage period; obtaining the electricity value at each time point corresponding to the second target thermal storage period; sorting the electricity values ​​within the second target thermal storage period in chronological order to obtain the latest pointer queue.

[0090] It should be noted that the steps for calculating the remaining heat of the thermal storage after thermal energy storage at the target time point include: obtaining the original remaining heat of the thermal storage, the duration of the electricity value corresponding to the target time point, and the thermal storage rate at the target time point; obtaining the increased heat of thermal storage based on the thermal storage rate and duration; subtracting the heat consumed during the duration from the remaining heat of the thermal storage with the increased heat of thermal storage; the result is the remaining heat of the second thermal storage.

[0091] Specifically, the remaining heat is sufficient within the target heat storage period. The furthest point in time represents the time when heat storage is necessary. When the selected time point is closer to the front end, the remaining heat will continue to increase, and the corresponding furthest point in time will change accordingly. The change in the furthest point in time will cause the range of selectable electricity value to be different, so that the pointer queue can also change accordingly. At this time, the selected pointer queue is used according to the latest version to select the second lowest electricity value, so that the selected electricity value is always at the lowest price.

[0092] Assume the pointer sequence for electricity prices during the flat-rate period is 7:00, 8:00, 9:00, 10:00, and 11:00, with prices of 0.6 yuan, 1 yuan, 1.2 yuan, 0.8 yuan, and 0.9 yuan respectively, and each price lasting for one hour. An older version of the pointer sequence that satisfies the remaining heat in the thermal storage is 7:00 and 8:00, with prices of 0.6 yuan and 1 yuan respectively, and each price lasting for one hour. When the remaining heat in the thermal storage is insufficient, assuming the furthest possible time point for the remaining heat is 8:00, the lowest electricity price can be selected from any target time point before 7:00 and 8:00, i.e., 0.6 yuan. After storing heat at 0.6 yuan for a period of time, the remaining heat in the thermal storage will then be Q... Q1 becomes Q2, and Q2 > Q1, indicating that the remaining heat in the thermal storage has increased. When the remaining heat in the thermal storage becomes Q2, assuming that the remaining heat can be used until 10 o'clock, but still does not meet the target heat storage capacity, the electricity value corresponding to all target time points before 10 o'clock can be selected. The range of the pointer queue also changes from the current time point to 8 o'clock to the current time point to 10 o'clock. During this time period, there is an electricity value of 0.8 yuan, and 1 yuan is greater than 0.8 yuan. When selecting the next lowest electricity price, the electricity value of 0.8 yuan corresponding to 10 o'clock can be used, without having to consider the electricity value of 7 o'clock corresponding to the old version of the pointer queue. This can improve the selectivity of electricity value, thereby selecting the most suitable electricity price. This is an update of the pointer queue based on the target time point.

[0093] A thermal storage-type water source heat pump heating control system based on peak-valley electricity pricing, applied to any of the above-described thermal storage-type water source heat pump heating control methods, includes:

[0094] Information acquisition module 1 is used to acquire heat demand characteristic information in the greenhouse, including environmental information and plant information; and to predict the target heat demand in the greenhouse based on the heat demand characteristic information.

[0095] Information analysis module 2 acquires electricity price data within a cycle, which includes the lowest electricity price data, the highest electricity price data, and the flat-period electricity price data. It acquires the time period corresponding to the lowest electricity price data as the off-peak electricity period, during which the heat pump stores heat in the heat storage. It acquires the time period corresponding to the highest electricity price data as the peak electricity period, during which the heat storage releases heat and calculates the remaining heat in the heat storage.

[0096] The judgment control module 3 is used to obtain the remaining heat of the hot storage and determine whether the remaining heat of the hot storage meets the target heat demand. If it is determined that the remaining heat of the hot storage meets the target heat demand, the step of storing heat in the hot storage through the heat pump during the period with the lowest electricity price continues. If it is determined that the remaining heat of the hot storage does not meet the target heat demand, the target electricity price period is selected based on the flat electricity price to store heat in the hot storage.

[0097] This invention calculates the overall heat load demand of a greenhouse based on the types and quantities of plants grown there, as well as the heat requirements of each plant at different growth stages. It trains a predictive model using collected historical data and real-time monitoring information. Based on input environmental parameters and heat load demand, it predicts the heat required for the next period. The greenhouse environment is monitored according to the season and the heat requirements of the plants to determine the predicted heat demand. The relationship between the available heat in the heat storage and the required heat is assessed to determine whether heat storage is necessary. If heat storage is needed, the cheapest electricity price period before the heat storage runs out is identified for heat storage. If heat storage is not needed, monitoring continues until the lowest electricity price period. The remaining heat is then assessed again to determine if it is sufficient for the next period with the lowest electricity price. If sufficient, monitoring continues; otherwise, heat storage is performed during the lowest electricity price period until the remaining heat is sufficient for the next period with the lowest electricity price.

[0098] The system can monitor the greenhouse environment based on the season and the heat requirements of the plants, and predict the heat needed for the next period based on historical data and real-time monitoring information. Then, the system will determine whether more heat reserves need to be added to the heat storage facility based on the predicted heat demand and the heat storage status.

[0099] If cheaper electricity prices are expected during peak periods, the system can activate heat pumps and other equipment to convert electricity into heat energy for storage, which can then be used during off-peak periods. Conversely, if cheaper electricity prices are expected during off-peak periods, the system can choose not to activate heat pumps during off-peak periods and instead utilize the heat stored in the heat storage directly.

[0100] Furthermore, the system can dynamically adjust the timing and method of heat storage based on electricity price trends. For example, when electricity prices drop to a certain level, the system can increase heat storage capacity to ensure that the heat in the storage facility can meet the energy needs of the next stage before the next price increase. This not only makes full use of low-priced electricity but also avoids excessive heat consumption when electricity prices are too high, thus improving energy efficiency.

[0101] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0102] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for controlling heating using a thermal storage-type water source heat pump based on peak-valley electricity pricing, characterized in that, Includes the following steps: S1: Obtain heat demand characteristic information in the greenhouse, including environmental information and plant information; predict the target heat demand in the greenhouse based on the heat demand characteristic information; S2: Obtain electricity price data within a cycle, which includes the lowest electricity price data, the highest electricity price data, and the average electricity price data. Obtain the time period corresponding to the lowest electricity price data as the off-peak electricity period, and store heat in the heat storage through a heat pump during the off-peak electricity period. Obtain the time period corresponding to the highest electricity price data as the peak electricity period, release heat to the heat storage during the peak electricity period, and calculate the remaining heat of the heat storage; S3: Obtain the remaining heat in the heat storage facility and determine whether the remaining heat in the heat storage facility meets the target heat demand. If it is determined that the remaining heat in the heat storage facility meets the target heat demand, continue to execute the step of storing heat in the heat storage facility through a heat pump during the period with the lowest electricity price. If it is determined that the remaining heat in the heat storage facility does not meet the target heat demand, select the target electricity price period based on the flat electricity price to store heat in the heat storage facility.

2. The method for controlling a thermal storage-type water source heat pump heating system based on peak-valley electricity pricing according to claim 1, characterized in that: The steps for predicting the target heat demand in the greenhouse based on heat demand characteristic information include: Obtain environmental information and plant information. The environmental information includes the current outdoor temperature, historical outdoor temperature, current indoor temperature, and historical indoor temperature. The plant information includes the types of plants, planting density, and growth stage of the plants. Using the historical outdoor and indoor temperatures corresponding to the same type of plant as a training set, the existing heat prediction model is trained based on the training set, and multiple prediction models are obtained based on multiple different types of plant. Based on multiple prediction models, extract the prediction model corresponding to the current plant species, input the current outdoor temperature and current indoor temperature corresponding to the current plant species into the prediction model, and obtain the first existing heat value; A second existing heat value is calculated based on the plant information, and a comprehensive existing heat value is calculated based on the first existing heat value and the second existing heat value. Establish a correspondence between plant information and actual heat demand values, and obtain multiple actual heat demand values ​​based on plant species, planting density and growth stage; Obtain the actual calorie demand value corresponding to the plant information, and subtract the comprehensive existing calorie value from the actual calorie demand value to obtain the current target calorie demand value; Obtain the duration between the current time and the start time of the next lowest electricity price, denoted as the heat consumption duration. The start time of the next lowest electricity price includes the start time of the next off-peak electricity price or the start time of the lowest electricity price in the next flat-rate electricity price. Multiply the current target heat demand by the heat consumption duration to obtain the target heat demand.

3. The method for controlling a thermal storage-type water source heat pump heating system based on peak-valley electricity pricing according to claim 2, characterized in that: The step of calculating the second existing heat based on plant information includes: Obtain the types of plants to be planted and the corresponding growth stages of those plants, and determine the corresponding respiration rate based on the plant growth stages. The total mass of plants per unit area is calculated based on plant density. The total mass of plants per unit area is multiplied by the respiration rate of each plant to obtain the total respiration rate of plants per unit area. The second existing heat is calculated based on the correlation function Q2 = D × M × R × 206 × t × S, where R is the respiration rate, M is the average mass of each plant, D is the plant density per unit area, S is the area of ​​the same plant species, and t is the time between the current time and the start time of the next minimum electricity price.

4. The method for controlling a thermal storage-type water source heat pump heating system based on peak-valley electricity pricing according to claim 1, characterized in that: The steps for selecting a target electricity price time period based on the flat-section electricity price for thermal energy storage in the thermal reservoir include: The remaining heat, consumed heat, and consumption rate of the thermal storage are obtained. The consumption time of the remaining heat is calculated based on the consumed heat, consumption rate, and remaining heat in the thermal storage. Based on the consumption time and the current time point, the first farthest time point corresponding to when the remaining heat in the thermal storage is completely consumed is determined. The time period between the current time point and the first farthest time point is recorded as the target thermal storage period. Within the target thermal storage period, multiple time points are divided according to electricity price data, and each time point corresponds to an electricity value. The electricity values ​​corresponding to multiple time points are sorted in chronological order to form the original pointer queue. The original pointer queue is updated based on the remaining amount of the heat storage to obtain the latest pointer queue. Based on the latest pointer queue, the pointer head is set to the electricity value with the lowest electricity price to obtain the lowest electricity price. a. Determine the time point corresponding to the lowest electricity price based on the latest pointer queue to obtain the target time point; b. Determine the target heat storage capacity based on the remaining heat and heat consumption of the heat storage facility; obtain the duration corresponding to the lowest electricity price at the target time point as the standby heat storage period, and record the heat storage capacity during the standby heat storage period as the actual heat storage capacity. c. Determine the relationship between the actual heat storage capacity and the target heat storage capacity; based on the determination results, carry out heat storage in the heat storage facility. The determination results include the actual heat storage capacity being less than the target heat storage capacity, the actual heat storage capacity being equal to the target heat storage capacity, and the actual heat storage capacity being greater than the target heat storage capacity.

5. The method for controlling a thermal storage-type water source heat pump heating system based on peak-valley electricity pricing according to claim 4, characterized in that: The relationship between the actual heat storage capacity and the target heat storage capacity is determined. The steps for thermal energy storage in a thermal reservoir based on the assessment results include: If it is determined that the actual heat storage is less than the target heat storage, the pointer head is pointed to an electricity price other than the minimum electricity price based on the latest pointer queue to obtain the second lowest electricity price; the second lowest electricity price replaces the minimum electricity price, and steps a to c are executed until the actual heat storage is equal to the target heat storage or the actual heat storage is greater than the target heat storage. If it is determined that the actual heat storage heat is equal to the target heat storage heat, then heat storage energy will be carried out in the heat storage facility when the current time point reaches the target time point. If it is determined that the actual heat storage capacity is greater than the target heat storage capacity, the target heat storage duration is calculated based on the heat storage rate and the target heat storage capacity. The time points corresponding to multiple lowest electricity prices are sorted in ascending order of electricity value. Based on the time sorting, the time point corresponding to the highest electricity value among the multiple lowest electricity prices is taken as the final target time point. The heat storage duration corresponding to each electricity value when the actual heat storage capacity is equal to or less than the target heat storage capacity is obtained as the first heat storage duration. Based on the target heat storage duration, the heat storage duration of the last target time point is determined to obtain the second heat storage duration. Based on the second heat storage duration, the working duration of heat storage at the last target time point is determined. Based on the first heat storage duration and the second heat storage duration, the heat pump is started sequentially according to the time sorting of the corresponding target time points to store heat energy in the heat storage facility.

6. The method for controlling a thermal storage-type water source heat pump heating system based on peak-valley electricity pricing according to claim 4, characterized in that: The step of updating the original pointer queue based on the remaining amount in the hot storage to obtain the latest pointer queue includes: Obtain the original pointer queue, determine the target time point in the target heat storage period based on the original pointer queue, calculate the remaining heat of the heat storage after heat storage at the target time point, and use it as the remaining heat of the second heat storage. Based on the consumption time and the current time point, determine the farthest time point corresponding to when the remaining heat in the second heat storage is completely consumed, and use it as the second farthest time point; The time period between the current time point and the second farthest time point is defined as the second target heat storage period. Obtain the electricity value at each time point corresponding to the second target heat storage period, sort the electricity values ​​within the second target heat storage period in chronological order, and obtain the latest pointer queue.

7. A thermal storage-type water source heat pump heating control system based on peak-valley electricity pricing, applied to the thermal storage-type water source heat pump heating control method as described in any one of claims 1-6, characterized in that, include: The information acquisition module is used to acquire heat demand characteristic information in the greenhouse, including environmental information and plant information; and to predict the target heat demand in the greenhouse based on the heat demand characteristic information. The information analysis module acquires electricity price data within a cycle, which includes the lowest electricity price, the highest electricity price, and the flat-period electricity price. It acquires the time period corresponding to the lowest electricity price as the off-peak electricity period, during which heat pumps store heat in the heat storage. It also acquires the time period corresponding to the highest electricity price as the peak electricity period, during which heat is released from the heat storage, and calculates the remaining heat in the heat storage. The judgment control module is used to obtain the remaining heat of the hot storage and determine whether the remaining heat of the hot storage meets the target heat demand. If it is determined that the remaining heat of the hot storage meets the target heat demand, the step of storing heat in the hot storage through the heat pump during the period with the lowest electricity price continues. If it is determined that the remaining heat of the hot storage does not meet the target heat demand, the target electricity price period is selected based on the flat electricity price to store heat in the hot storage.

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