Electricity utilization optimization scheduling method and device and computer equipment

Abstract

The invention relates to the technical field of power utilization scheduling, in particular to a power utilization optimization scheduling method. According to the technical scheme, the method comprises the steps that the priority of heating, cooling and charging, the reference hot water use amount, the reference ice water use amount, the reference charging amount, the first power threshold value, the second power threshold value, the third power threshold value, the time period of heating, cooling and charging and the time period of stopping heating, cooling and charging are set; according to the method, household electricity consumption power, hot water consumption, icy water consumption and automobile charging quantity are detected, household electricity reference power, reference hot water consumption, reference icy water consumption and reference charging quantity are calculated, the household electricity consumption power at each time point is predicted by constructing a B spline curve model, and heating, cooling and charging time periods are selected; the power utilization distribution is planned according to the daily power utilization condition of residents, the accuracy of power prediction is improved, the optimization degree of power utilization scheduling is enhanced, and therefore reasonable utilization of power generation resources and saving of power utilization cost are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of electricity dispatching, and in particular to an electricity optimization dispatching method, device and computer equipment. Background Art

[0002] As household electricity demand continues to increase, electricity load is increasing day by day, so electricity scheduling methods are gradually gaining widespread attention. At present, due to grid restrictions and safety factors, solar energy is subject to output power restrictions when generating power at full power, resulting in a waste of power generation resources. Since the electricity consumption part is connected to the grid, there is no effective and intelligent planning for electricity consumption, so the electricity cost has not been effectively reduced.

[0003] In view of this, we propose an electricity optimization scheduling method, device and computer equipment to solve the existing problems. Summary of the invention

[0004] The purpose of the present invention is to provide a method, device and computer equipment for optimizing electricity scheduling to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: the power consumption optimization scheduling method includes default automatic scheduling, setting automatic scheduling, and manual power consumption scheduling, and the working steps of default automatic scheduling include:

[0006] S1: Detect household power consumption, take 24 hours as a unit time, calculate the household power consumption reference power on weekdays and weekends according to the household power consumption detection on previous weekdays and weekends, and set the first power threshold, the second power threshold, and the third power threshold;

[0007] S2: Detect the water consumption of household hot water and household ice water and the charging capacity of the smart charging pile, and calculate the reference hot water consumption, reference ice water consumption, and reference charging capacity on working days and rest days based on the detection of the hot water consumption, ice water consumption, and car charging capacity on previous working days and rest days;

[0008] S3: Select a time period during which the household electricity reference power per unit time is continuously lower than the first power threshold, and set this time period as the first time period, and continuously heat the household hot water or cool the household ice water or charge the smart charging pile during the first time period;

[0009] S4: Select a time period in which the household electricity reference power is continuously higher than the first power threshold and lower than the third power threshold within a unit time, and set it as a second time period. In the second time period, construct a B-spline curve model according to the household electricity reference power at the time point;

[0010] S5: intermittently heating household hot water or cooling household ice water or charging the smart charging pile in the second time period, and determining the time interval of heating or cooling or charging in the second time period according to the B-spline curve model constructed in S4;

[0011] S6: Select a time period in which the household electricity reference power per unit time is continuously higher than the third power threshold, and set it as the third time period. During the third time period, suspend heating household hot water or cooling household ice water or charging the smart charging pile.

[0012] Furthermore, the default order of heating, cooling and charging is: first heat, wait for the household hot water with a reference amount of hot water to be heated, then cool, wait for the household ice water with a reference amount of ice water to be cooled, and finally charge until the reference charge amount is charged.

[0013] Furthermore, if the hot water of the reference hot water quantity, the ice water of the reference ice water quantity, and the reference charging quantity have completed heating, cooling, and charging respectively and there is still power, all the hot water in the hot water storage tank is heated, and then all the ice water in the ice water tank is cooled, and finally the smart charging pile is charged.

[0014] Furthermore, in S4, the independent variable of the B-spline curve model is the time point, and the dependent variable is the household electricity reference power. The household electricity reference power corresponding to the time point is used as a node to obtain the control point, thereby constructing the B-spline curve model.

[0015] Furthermore, in S5, the household power consumption at each time point is predicted according to the B-spline curve model constructed in S4, and is divided into a time period above the second power threshold and a time period below the second power threshold.

[0016] Further, heating, cooling or charging is suspended in a time period higher than the second power threshold, and heating, cooling or charging is performed in a time period lower than the second power threshold.

[0017] Furthermore, setting the automatic scheduling includes adjusting the priority of heating, cooling and charging, reference hot water consumption, reference ice water consumption, reference charging amount, first power threshold, second power threshold and third power threshold.

[0018] Furthermore, manual electricity scheduling includes manually and autonomously setting a time period for heating, cooling and charging, and a time period for stopping heating, cooling and charging.

[0019] The power optimization scheduling device is used for the power optimization scheduling method, including a power generation module, a detection module, a calculation module, a smart charging pile charging module, an energy control module, a household power output module, and a setting module;

[0020] Among them, the detection module is used to detect household electricity power, hot water consumption, ice water consumption, and vehicle charging capacity;

[0021] The calculation module is used to calculate the reference power of household electricity, reference hot water consumption, reference ice water consumption, and reference charging amount, and to construct a B-spline curve model and predict the household electricity power at each time point, and select the time periods of heating, cooling, and charging;

[0022] The energy control module is used to heat household hot water and cool household ice water;

[0023] The setting module is used to set the priority of heating, cooling and charging, reference hot water consumption, reference ice water consumption, reference charging amount, first power threshold, second power threshold, third power threshold, time period for heating, cooling and charging, and time period for stopping heating, cooling and charging.

[0024] The power optimization scheduling computer equipment is used in the power optimization scheduling device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the power optimization scheduling device to complete the power optimization scheduling method.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The present invention detects household power consumption, hot water consumption, ice water consumption, and automobile charging amount, thereby calculating household power consumption reference power, reference hot water consumption, reference ice water consumption, and reference charging amount, and predicts household power consumption at each time point by constructing a B-spline curve model, thereby selecting time periods for heating, cooling, and charging, and planning electricity distribution according to residents' daily electricity consumption, thereby improving the accuracy of power prediction, and further enhancing the optimization of electricity scheduling, thereby ensuring the rational use of power generation resources and saving of electricity costs, and setting the priority of heating, cooling, and charging, reference hot water consumption, reference ice water consumption, reference charging amount, a first power threshold, a second power threshold, a third power threshold, a time period for heating, cooling, and charging, and a time period for stopping heating, cooling, and charging, so as to flexibly distribute electricity according to residents' electricity demand. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of unit distribution of the electricity optimization scheduling method of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0029] Embodiment 1

[0030] like Figure 1As shown, the power generation unit generates electricity from solar energy, wind energy, and low-power turbine hydropower. Taking the case where the smart charging pile takes precedence over the energy conversion device as an example, when solar energy is generating electricity, the load at home cannot consume the generated electricity. The smart charging pile works to consume the electricity generated by solar energy or wind energy, ensuring that the flow of electricity at the grid is zero and no electricity is consumed from the grid. If the electricity generated by the full power of solar energy is still not consumed when the smart charging pile is working, the energy conversion device and the smart charging pile consume electricity together to ensure that the flow of electricity at the grid is zero and no electricity is consumed from the grid.

[0031] The power consumption optimization scheduling methods include default automatic scheduling, setting automatic scheduling, and manual power scheduling. The working steps of default automatic scheduling include:

[0032] S1: Detect household power consumption, take 24 hours as a unit time, calculate the household power consumption reference power on weekdays and weekends according to the household power consumption detection on previous weekdays and weekends, and set the first power threshold, the second power threshold, and the third power threshold;

[0033] S2: Detect the water consumption of household hot water and household ice water and the charging capacity of the smart charging pile, and calculate the reference hot water consumption, reference ice water consumption, and reference charging capacity on working days and rest days based on the detection of the hot water consumption, ice water consumption, and car charging capacity on previous working days and rest days;

[0034] S3: Select a time period during which the household electricity reference power per unit time is continuously lower than the first power threshold, and set this time period as the first time period, and continuously heat the household hot water or cool the household ice water or charge the smart charging pile during the first time period;

[0035] S4: Select a time period in which the household electricity reference power is continuously higher than the first power threshold and lower than the third power threshold within a unit time, and set it as a second time period. In the second time period, a B-spline curve model is constructed according to the household electricity reference power at the time point; wherein the independent variable of the B-spline curve model is the time point, and the dependent variable is the household electricity reference power. The household electricity reference power corresponding to the time point is used as a node, and the control point is obtained to construct the B-spline curve model;

[0036] S5: intermittently heat household hot water or cool household ice water or charge the smart charging pile in the second time period, and determine the time interval for heating, cooling or charging in the second time period according to the B-spline curve model constructed in S4; wherein, the household power consumption at each time point is predicted according to the B-spline curve model constructed in S4, and is divided into a time period higher than a second power threshold and a time period lower than the second power threshold, and heating, cooling or charging is suspended in the time period higher than the second power threshold, and heating, cooling or charging is performed in the time period lower than the second power threshold

[0037] S6: Select a time period in which the household electricity reference power per unit time is continuously higher than the third power threshold, and set it as the third time period. During the third time period, suspend heating household hot water or cooling household ice water or charging the smart charging pile.

[0038] The default order of heating, cooling and charging is: first heat, wait until the household hot water with a reference amount of hot water is heated, then cool down, wait until the household ice water with a reference amount of ice water is cooled, and finally charge until the reference charge amount is charged. If the hot water with a reference amount of hot water, the ice water with a reference amount of ice water, and the reference charge amount are heated, cooled, and charged respectively and there is still power, heat all the hot water in the hot water storage tank, then cool down all the ice water in the ice water storage tank, and finally charge the smart charging pile.

[0039] Setting automatic scheduling includes adjusting the priority of heating, cooling and charging, reference hot water usage, reference ice water usage, reference charging amount, first power threshold, second power threshold and third power threshold.

[0040] Manual electricity scheduling includes manually and autonomously setting the time periods for heating, cooling and charging, and the time periods for stopping heating, cooling and charging.

[0041] The power optimization scheduling device is used for the power optimization scheduling method, including a power generation module, a detection module, a calculation module, a smart charging pile charging module, an energy control module, a household power output module, and a setting module;

[0042] Among them, the detection module is used to detect household electricity power, hot water consumption, ice water consumption, and vehicle charging capacity;

[0043] The calculation module is used to calculate the reference power of household electricity, reference hot water consumption, reference ice water consumption, and reference charging amount, and to construct a B-spline curve model and predict the household electricity power at each time point, and select the time periods of heating, cooling, and charging;

[0044] The energy control module is used to heat household hot water and cool household ice water;

[0045] The setting module is used to set the priority of heating, cooling and charging, reference hot water consumption, reference ice water consumption, reference charging amount, first power threshold, second power threshold, third power threshold, time period for heating, cooling and charging, and time period for stopping heating, cooling and charging.

[0046] The power optimization scheduling computer equipment is used in the power optimization scheduling device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the power optimization scheduling device to complete the power optimization scheduling method.

[0047] The working principle of the power consumption optimization scheduling method, device and computer equipment based on the first embodiment is:

[0048] Residents have different lifestyles on weekdays and weekends, and their electricity usage patterns are different accordingly. Therefore, the electricity scheduling parameters on weekdays and weekends are also different.

[0049] For the default automatic scheduling work steps, take the working day as an example, take 24 hours as the unit time, use the detection unit to detect the household power consumption, take one hour as the time interval, and the measured household power consumption is P HE , h=1,2,...,24. Assume that the detection unit has detected the household power for N working days, and the household power reference is P r,HE , P HE,Dd is the household power reference power at the hth time point on the dth day. Let the first power threshold be P1, the second power threshold be P2, and the third power threshold be P3.

[0050] The detection unit is used to detect the water consumption of household hot water and household ice water and the charging amount of the smart charging pile. The reference hot water consumption is WC r,H , WC H,Dd is the amount of hot water used on day d. The reference amount of ice water is WC r,I , WC I,Dd The amount of ice water used on day d. The reference charge is CC r , CC Dd is the charging amount on the dth day. Let the first power threshold be P1, the second power threshold be P2, and the third power threshold be P3.

[0051] The algorithm formula for the n-order m-segment B-spline curve is:

[0052]

[0053] Where: P i,n (t) is the value of the i-th segment after the n-th B-spline curve transformation, where i = 1, 2, 3, ..., m; t is the value before the B-spline curve transformation, and for each point of the curve segment, 0 ≤ t ≤ 1 is satisfied, t = 0 represents the beginning node of the i-th segment, and t = 1 represents the end node of the i-th segment; p i+k-1 is the control point of the i-th segment of the B-spline curve; F k,n(t) is a piecewise mixing function of an n-order B-spline curve, where 0≤t≤1, k=0,1,2,...,n.

[0054] Select (m+1) time nodes in the second time period, and set the time node set as T N , the corresponding household electricity reference power set is P N , F(T N )·p=P N , F(T N ) is T N The piecewise mixing function of p is the set of control points of the B-spline curve model, and p is obtained from this.

[0055] Assume that any time point in the second time period is T, then the predicted household power consumption at that time point is P = F(T)·p. P is compared with P2 to select the time period for heating, cooling, and charging.

[0056] After the unit time ends, the calculation module recalculates the household electricity reference power, reference hot water consumption, reference ice water consumption, and reference charging amount, reconstructs the B-spline curve model, re-predicts the household electricity power at each time point, and reselects the heating, cooling, and charging time periods.

[0057] The above-mentioned specific embodiments are only several preferred embodiments of the present invention. Based on the technical solutions of the present invention and the relevant inspirations of the above-mentioned embodiments, those skilled in the art can make various alternative improvements and combinations to the above-mentioned specific embodiments.

Claims

1. The power consumption optimization scheduling method includes default automatic scheduling, setting automatic scheduling, and manual power consumption scheduling, which is characterized by: The default automatic scheduling work steps include: S1: Detect household power consumption, take 24 hours as a unit time, calculate the household power consumption reference power on weekdays and weekends according to the household power consumption detection on previous weekdays and weekends, and set the first power threshold, the second power threshold, and the third power threshold; S2: Detect the water consumption of household hot water and household ice water and the charging capacity of the smart charging pile, and calculate the reference hot water consumption, reference ice water consumption, and reference charging capacity on working days and rest days based on the detection of the hot water consumption, ice water consumption, and car charging capacity on previous working days and rest days; S3: Select a time period during which the household electricity reference power per unit time is continuously lower than the first power threshold, and set this time period as the first time period, and continuously heat the household hot water or cool the household ice water or charge the smart charging pile during the first time period; S4: Select a time period in which the household electricity reference power is continuously higher than the first power threshold and lower than the third power threshold within a unit time, and set it as a second time period. In the second time period, construct a B-spline curve model according to the household electricity reference power at the time point; S5: intermittently heating household hot water or cooling household ice water or charging the smart charging pile in the second time period, and determining the time interval of heating or cooling or charging in the second time period according to the B-spline curve model constructed in S4; S6: Select a time period in which the household electricity reference power per unit time is continuously higher than the third power threshold, and set it as the third time period. During the third time period, suspend heating household hot water or cooling household ice water or charging the smart charging pile.

2. The method for optimizing power consumption according to claim 1, characterized in that: The default order for heating, cooling, and charging is: First, heat up until the reference amount of hot water is heated up, then cool down until the reference amount of ice water is cooled down, and finally charge until the reference amount of charging is completed.

3. The method for optimizing power consumption according to claim 2, characterized in that: If the hot water used as a reference hot water quantity, the ice water used as a reference ice water quantity, and the reference charging quantity have completed heating, cooling, and charging respectively and there is still power left, heat all the hot water in the hot water storage tank, cool down all the ice water in the ice water storage tank, and finally charge the smart charging pile.

4. The method for optimizing power consumption according to claim 1, characterized in that: In S4, the independent variable of the B-spline curve model is the time point, and the dependent variable is the household electricity reference power. The household electricity reference power corresponding to the time point is used as the node to obtain the control point, so as to construct the B-spline curve model.

5. The method for optimizing power consumption according to claim 1, characterized in that: In S5, the household power consumption at each time point is predicted according to the B-spline curve model constructed in S4, and is divided into a time period above the second power threshold and a time period below the second power threshold.

6. The method for optimizing power consumption according to claim 5, characterized in that: Heating, cooling or charging is suspended during a time period higher than the second power threshold, and heating, cooling or charging is performed during a time period lower than the second power threshold.

7. The method for optimizing power consumption according to claim 1, characterized in that: Setting automatic scheduling includes adjusting the priority of heating, cooling and charging, reference hot water usage, reference ice water usage, reference charging amount, first power threshold, second power threshold and third power threshold.

8. The method for optimizing power consumption according to claim 1, characterized in that: Manual electricity scheduling includes manually and autonomously setting the time periods for heating, cooling and charging, and the time periods for stopping heating, cooling and charging.

9. An electricity consumption optimization scheduling device, used in the electricity consumption optimization scheduling method according to any one of claims 1 to 8, characterized in that: It includes power generation module, detection module, calculation module, smart charging pile charging module, energy control module, household electricity output module and setting module; Among them, the detection module is used to detect household electricity power, hot water consumption, ice water consumption, and vehicle charging capacity; The calculation module is used to calculate the reference power of household electricity, reference hot water consumption, reference ice water consumption, reference charging amount, and construct a B-spline curve model to predict the household electricity power at each time point, and select the time periods of heating, cooling, and charging; The energy control module is used to heat household hot water and cool household ice water; The setting module is used to set the priority of heating, cooling and charging, reference hot water consumption, reference ice water consumption, reference charging amount, first power threshold, second power threshold, third power threshold, time period for heating, cooling and charging, and time period for stopping heating, cooling and charging.

10. A computer device for optimizing power consumption and scheduling, used in the device for optimizing power consumption and scheduling as claimed in claim 9, characterized in that: It includes a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the power optimization scheduling device to complete the power optimization scheduling method.

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