Dish-washing machine load carbon emission reduction method based on family going-out dining behavior

Abstract

The invention discloses a dishwasher load carbon emission reduction method based on family outgoing dining behaviors, and relates to the field of electric power system regulation and control, and the method comprises the steps: collecting dishwasher operation behavior data based on a dishwasher load data collection technology, and constructing a dishwasher working state prediction model; the method comprises the steps of predicting family outgoing dining behaviors, constructing a dish-washing machine load prediction model, constructing a dish-washing machine load carbon emission calculation model according to dish-washing machine loads and carbon emission factors per kilowatt-hour, and calculating dish-washing machine load carbon emission according to the dish-washing machine loads and the dish-washing machine load carbon emission by taking low-carbon economy as a target and taking minimum power consumption cost and minimum carbon emission as a target function. A dish-washing machine load carbon emission reduction model is constructed based on power operation constraint, continuous operation time constraint and operation range constraint, so that dish-washing machine load prediction accuracy can be improved, quantitative calculation of dish-washing machine carbon emission is realized, power consumption cost and carbon emission are comprehensively considered, the lowest power consumption cost and the lowest carbon emission of the dish-washing machine are ensured, and the dish-washing machine load prediction method is suitable for industrial production. And the goal of low-carbon economy is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system regulation and control, and in particular to a method for reducing carbon emissions from dishwasher loads based on family dining out behavior. Background Art

[0002] Modern dishwashers are often more energy efficient than manual washing, especially when using the energy-saving mode. By including dishwasher loads as a carbon reduction resource, energy efficiency can be improved in homes and businesses, reducing overall energy consumption. At the same time, carbon emissions will be further reduced if the electricity supply for dishwashers comes from renewable energy.

[0003] In the prior art, traditional methods often lack consideration of dining out behavior. Existing dishwasher load models usually assume that families eat at home every day and use dishwashers to wash dishes, while ignoring dining out behavior. This may cause the existing model to overestimate the actual frequency of dishwasher use, which in turn affects the accurate assessment of electricity demand and carbon emissions. In addition, the prior art lacks a specific dishwasher load carbon emission calculation model, and has not established a relationship model between dishwasher load and carbon emissions, which may affect the assessment of carbon emission reduction contributions and make it difficult to provide corresponding data support for policy making. At the same time, current technology lacks a carbon emission reduction model that comprehensively considers electricity costs and carbon emissions. Existing models may only focus on carbon emissions, or only focus on electricity costs, and fail to comprehensively consider the two, resulting in the inability to balance economy and environmental protection in actual applications.

[0004] Therefore, how to take into account family dining out behavior, build a dishwasher load prediction model, improve the accuracy of dishwasher load prediction, and build a dishwasher carbon emission model to achieve quantitative calculation of dishwasher carbon emissions, while comprehensively considering electricity costs and carbon emissions, scheduling the start time of the dishwasher load, and building a dishwasher load carbon emission reduction model to minimize the dishwasher's electricity cost and carbon emissions and achieve the goal of a low-carbon economy has become an urgent problem that needs to be solved today. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a dishwasher load carbon emission reduction method based on family dining out behavior. The method can take family dining out behavior into consideration, construct a dishwasher load prediction model, improve the accuracy of dishwasher load prediction, and construct a dishwasher carbon emission model to realize the quantitative calculation of dishwasher carbon emissions. At the same time, the electricity cost and carbon emissions are comprehensively considered, the start time of the dishwasher load is scheduled, and a dishwasher load carbon emission reduction model is constructed to minimize the electricity cost and carbon emissions of the dishwasher, thereby achieving the goal of a low-carbon economy.

[0006] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0007] The present invention is a method for reducing carbon emissions from dishwasher load based on family dining out behavior, comprising the following operations:

[0008] Based on dishwasher load data collection technology, collect dishwasher operation behavior data;

[0009] Based on the back propagation neural network, a dishwasher working state prediction model is constructed according to the dishwasher operation behavior data to predict the family dining out behavior, and then a dishwasher load prediction model is constructed according to the family dining out behavior to predict the dishwasher load;

[0010] According to the dishwasher load and the carbon emission factor of electricity, a dishwasher load carbon emission calculation model is constructed to calculate the dishwasher load carbon emission;

[0011] According to the dishwasher load and dishwasher load carbon emissions, with low-carbon economy as the goal, and minimizing electricity costs and carbon emissions as the objective functions, a dishwasher load carbon emission reduction model is constructed based on the constraints of power operation constraints, continuous operation time constraints and operation range constraints.

[0012] A further improvement of the present invention is that the dishwasher operation behavior data is as shown in formula (1):

[0013]

[0014] Where X is the collected dishwasher load operation data; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing; P a ,P b ,P c are the morning, mid-day and evening workloads of the dishwasher respectively; τ a ,τ b ,τ c are the working duration of the dishwasher in the morning, afternoon and evening respectively; δ a ,δ b ,δ c are the family's dining out status in the morning, afternoon and evening; q is the electricity price information; c is the carbon emission factor information per kilowatt-hour; η is the holiday information.

[0015] A further improvement of the present invention is that: based on the back propagation neural network, according to the dishwasher operation behavior data, combined with the family's historical dining out status in the morning, noon and evening and holiday information, a dishwasher working status prediction model based on the back propagation neural network is constructed to predict the family's dining out behavior, specifically including:

[0016] Collecting training data, training a back propagation neural network, and testing the back propagation neural network, training the back propagation neural network in an offline manner, training the back propagation neural network offline according to the historical dining out status of the family in the morning, noon, and evening and historical holiday information, and correlating the historical dining out status of the family in the morning, noon, and evening and historical holiday information to construct the family dining out behavior prediction model based on the back propagation neural network;

[0017] The input layer of the back propagation neural network includes four inputs, which are: a (t) is the family's dining out status in the morning at time t, where 1 means dining out and 0 means dining at home; δ b (t) is the family's lunch out status at time t, where 1 means dining out and 0 means dining at home; δ c (t) is the family dining out status at time t, where 1 is dining out and 0 is dining at home; η is holiday information; the output layer of the back propagation neural network includes 3 outputs, which are: δ a (t+Δt) is the predicted family dining out status at time t+Δt in the morning, where 1 means dining out and 0 means dining at home; δ b (t+Δt) is the predicted family lunch out status at time t+Δt, where 1 means dining out and 0 means dining at home; δ c (t+Δt) is the predicted state of the family dining out at night at time t+Δt, where 1 represents dining out and 0 represents dining at home. The hidden layer of the back propagation neural network uses a hyperbolic tangent function. After training, the output of the family dining out behavior prediction model based on the back propagation neural network is as shown in formula (2):

[0018]

[0019] In the formula, f a () is the prediction model of family morning dining out behavior based on back propagation neural network after training; f b () is the prediction model of family lunch eating out behavior based on back propagation neural network after training; f c () is the prediction model of family dining out behavior at night based on back propagation neural network after training; δ a (t) is the family's dining out status in the morning at time t, where 1 means dining out and 0 means dining at home; δ b (t) is the family's lunch out status at time t, where 1 means dining out and 0 means dining at home; δ c (t) is the family dining out status at time t, where 1 means dining out and 0 means dining at home; δa (t+Δt) is the predicted family dining out status at time t+Δt in the morning, where 1 means dining out and 0 means dining at home; δ b (t+Δt) is the predicted family lunch out status at time t+Δt, where 1 means dining out and 0 means dining at home; δ c (t+Δt) is the predicted family dining out status at time t+Δt, where 1 means dining out and 0 means dining at home; η is holiday information;

[0020] According to the predicted family dining out behavior, a dishwasher load prediction model based on family dining out behavior is constructed to predict the dishwasher load, as shown in formulas (3) to (10):

[0021] k=[δ a ,δ b ,δ c ](3)

[0022] In the formula, k = [δ a ,δ b ,δ c ] is the family's dining out behavior matrix for the morning, afternoon and evening, where k is 1 for dining out and 0 for dining at home;

[0023] When k = [0, 0, 0], it means that the family eats breakfast, lunch and dinner at home. The dishwasher load prediction model is shown in formula (4):

[0024]

[0025] Where P(t) is the load of the dishwasher; P a (t), P b (t), P c (t) are the morning, midday and evening workloads of the dishwasher respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing;

[0026] When k = [1, 0, 0], it means that the family eats out in the morning and eats at home in the afternoon and evening. There is no dishwasher load in the morning. The dishwasher load prediction model is shown in formula (5):

[0027]

[0028] Where P(t) is the load of the dishwasher; P b (t), P c(t) are the middle and evening workloads of the dishwasher, respectively; T3 is the end time of lunch; T4 is the end time of dishwashing at noon; T5 is the end time of dinner; T6 is the end time of dishwashing at night;

[0029] When k = [0, 1, 0], it means that the family eats out at noon and eats at home in the morning and evening. There is no dishwasher load at noon, and the dishwasher load operation range in the morning changes from (T1, T2) to (T1, T4). The dishwasher load prediction model is shown in formula (6):

[0030]

[0031] Where P(t) is the load of the dishwasher; P a (t), P b (t), P c (t) are the morning, midday and evening workloads of the dishwasher respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing;

[0032] When k = [0, 0, 1], it means that the family eats out at night and eats breakfast and lunch at home. There is no dishwasher load at night, and the operating range of the dishwasher load at noon changes from (T3, T4) to (T3, T6). The dishwasher load prediction model is shown in formula (7):

[0033]

[0034] Where P(t) is the load of the dishwasher; P a (t), P b (t) are the morning and mid-day workloads of the dishwasher, respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T6 is the end time of evening dishwashing;

[0035] When k = [1, 1, 0], it means that people eat out in the morning and at noon, and eat at home in the evening. There is no dishwasher load in the morning and at noon. The dishwasher load prediction model is shown in formula (8):

[0036] P(t)=P c (t),T5≤t≤T6(8)

[0037] Where P(t) is the load of the dishwasher; P c (t) is the evening workload of the dishwasher; T5 is the end time of dinner; T6 is the end time of dishwashing in the evening;

[0038] When k = [1, 0, 1], it means that the family eats out in the morning and evening and eats at home at noon. There is no dishwasher load in the morning and evening, and the operating range of the dishwasher load at noon changes from (T3, T4) to (T3, T6). The dishwasher load prediction model is shown in formula (9):

[0039] P(t)=P b (t),T3≤t≤T6(9)

[0040] Where P(t) is the load of the dishwasher; P b (t) is the workload of the dishwasher at noon; T3 is the end time of lunch; T6 is the end time of dishwashing in the evening;

[0041] When k = [0, 1, 1], it means that the family eats out at noon and in the evening, and eats at home in the morning. There is no dishwasher load at noon and in the evening. The dishwasher load operation time range in the morning changes from (T1, T2) to (T1, T6). The dishwasher load prediction model is shown in formula (10):

[0042] P(t)=P a (t),T1≤t≤T6(10)

[0043] Where P(t) is the load of the dishwasher; P a (t) is the morning workload of the dishwasher; T1 is the end time of breakfast; T6 is the end time of dishwashing in the evening.

[0044] A further improvement of the present invention is that: according to the dishwasher load, combined with the carbon emission factor per kilowatt-hour, a dishwasher load carbon emission calculation model is constructed to calculate the dishwasher load carbon emission, which specifically includes:

[0045] It is selected that the family eats breakfast, lunch and dinner at home, and the dishwasher load carbon emission calculation model is constructed, as shown in formula (11):

[0046]

[0047] In the formula, C p is the carbon emission of dishwasher load; T1', T2', and T3' are the start-up time of dishwasher load in the morning, middle, and evening, respectively; τ a ,τ b ,τ c P is the working duration of the dishwasher in the morning, afternoon and evening respectively; a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher respectively; λ c (t) is the carbon emission factor of the dishwasher load at time t.

[0048] A further improvement of the present invention is that: according to the dishwasher load and the dishwasher load carbon emission, with low-carbon economy as the goal, with minimum electricity cost and minimum carbon emission as the objective function, based on the constraints of power operation constraint, continuous operation time constraint and operation range constraint, by adjusting the morning, noon and evening dishwasher load start time T1', T2', T3', the dishwasher load carbon emission reduction model is constructed. The dishwasher load carbon emission reduction model is shown in formulas (12) to (15):

[0049] The objective function is shown in formula (12):

[0050]

[0051] Where F is the dishwasher load target; T1', T2', and T3' are the morning, midday, and evening dishwasher load start times, respectively; τ a ,τ b ,τ c P is the working duration of the dishwasher in the morning, afternoon and evening respectively; a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher respectively; λ c (t) is the carbon emission factor of dishwasher load at time t; q (t) is the electricity price at time t; Pmin is the minimum value operation;

[0052] The power operation constraint indicates that the load of the dishwasher in the morning, afternoon and evening shall not exceed the maximum and minimum operating power limits. The power operation constraint is shown in formula (13):

[0053]

[0054] Where P min , P max are the minimum and maximum loads of the dishwasher; P a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher, respectively;

[0055] The continuous operation time constraint indicates that the dishwasher must not exceed the minimum and maximum continuous operation time limits in the morning, afternoon and evening. The continuous operation time constraint is shown in formula (14):

[0056]

[0057] In the formula, τ min , τ max are the minimum and maximum continuous running time of the dishwasher respectively; τa ,τ b ,τ c They are the working duration of the dishwasher in the morning, afternoon and evening respectively;

[0058] The operating range constraint indicates that the start time of the dishwasher in the morning, afternoon and evening shall not be earlier than the end time of the meal, and a margin is left to ensure that the operation is completed before the end time of dishwashing. The operating range constraint is shown in formula (15):

[0059]

[0060] Where, T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing; T1', T2', T3' are the morning, noon and evening dishwasher load start times respectively; τ a ,τ b ,τ c They are the working duration of the dishwasher in the morning, afternoon and evening respectively.

[0061] The beneficial effects of the present invention are as follows: the present invention proposes a dishwasher load carbon emission reduction method based on family dining out behavior, based on the dishwasher load data collection technology, the dishwasher operation behavior data is collected; based on the back propagation neural network, according to the dishwasher operation behavior data, a dishwasher working state prediction model is constructed to predict the family dining out behavior, and then according to the family dining out behavior, a dishwasher load prediction model is constructed to predict the dishwasher load; according to the dishwasher load, combined with the kilowatt-hour carbon emission factor, a dishwasher load carbon emission calculation model is constructed to calculate the dishwasher load carbon emission; according to the dishwasher load and the dishwasher load carbon emission, with the goal of low-carbon economy, with the minimum electricity cost and the minimum carbon emission as the objective function, based on the constraints of power operation constraints, continuous operation time constraints and operation range constraints, a dishwasher load carbon emission reduction model is constructed, so that the family dining out behavior can be considered, a dishwasher load prediction model can be constructed, the accuracy of dishwasher load prediction can be improved, and a dishwasher carbon emission model can be constructed to realize the quantitative calculation of dishwasher carbon emissions, and at the same time, the electricity cost and carbon emissions are comprehensively considered, the start time of the dishwasher load is scheduled, and the dishwasher load carbon emission reduction model is constructed, so that the dishwasher has the lowest electricity cost and the lowest carbon emission, and the goal of low-carbon economy is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A flow chart of a method for reducing carbon emissions from dishwasher load based on family dining out behavior provided by an embodiment of the present invention;

[0063] Figure 2 A schematic diagram of a family dining out behavior prediction model based on a BP neural network provided in an embodiment of the present invention;

[0064] Figure 3 A schematic diagram of the load of a dishwasher when eating at home in the morning, afternoon and evening provided by an embodiment of the present invention;

[0065] Figure 4 A schematic diagram of a dishwasher load when dining out in the morning provided by an embodiment of the present invention;

[0066] Figure 5 A schematic diagram of a dishwasher load when dining out at noon provided by an embodiment of the present invention;

[0067] Figure 6 A schematic diagram of a dishwasher load for a night out provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0069] See also Figure 1 , a method for reducing carbon emissions from dishwasher load based on family dining out behavior of the present invention comprises the following operations:

[0070] S1, based on dishwasher load data collection technology, collects dishwasher operation behavior data;

[0071] S2, based on the back propagation neural network, according to the dishwasher operation behavior data, construct a dishwasher working state prediction model to predict the family dining out behavior, and then according to the family dining out behavior, construct a dishwasher load prediction model to predict the dishwasher load;

[0072] S3, constructing a dishwasher load carbon emission calculation model according to the dishwasher load and the carbon emission factor of electricity, and calculating the dishwasher load carbon emission;

[0073] S4, based on the dishwasher load and the dishwasher load carbon emissions, with low-carbon economy as the goal, and minimizing electricity costs and minimizing carbon emissions as the objective functions, a dishwasher load carbon emission reduction model is constructed based on the constraints of power operation constraints, continuous operation time constraints, and operation range constraints.

[0074] In S1, the dishwasher operation behavior data is shown in formula (1):

[0075]

[0076] Where X is the collected dishwasher load operation data; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing; P a ,P b ,P c are the morning, mid-day and evening workloads of the dishwasher respectively; τ a ,τ b ,τ c are the working duration of the dishwasher in the morning, afternoon and evening respectively; δ a ,δ b ,δ c are the family's dining out status in the morning, afternoon and evening; q is the electricity price information; c is the carbon emission factor information per kilowatt-hour; η is the holiday information.

[0077] In S2, the back propagation neural network is used to construct a dishwasher working state prediction model based on a back propagation neural network according to the dishwasher operation behavior data, combined with the family's historical dining out status in the morning, noon and evening and holiday information, to predict the family's dining out behavior, specifically including:

[0078] Collecting training data, training a back propagation neural network, and testing the back propagation neural network, training the back propagation neural network in an offline manner, training the back propagation neural network offline according to the historical dining out status of the family in the morning, noon, and evening and historical holiday information, and correlating the historical dining out status of the family in the morning, noon, and evening and historical holiday information to construct the family dining out behavior prediction model based on the back propagation neural network;

[0079] Among them, see Figure 2 , w ij represents the connection weight from the input layer to the output layer; b j represents the threshold value; w jk represents the connection weight from the hidden layer to the output layer; the input layer of the back propagation neural network includes 4 inputs, which are: δ a (t) is the family's dining out status in the morning at time t, where 1 means dining out and 0 means dining at home; δ b (t) is the family's lunch out status at time t, where 1 means dining out and 0 means dining at home; δ c (t) is the family dining out status at time t, where 1 is dining out and 0 is dining at home; η is holiday information; the output layer of the back propagation neural network includes 3 outputs, which are: δ a(t+Δt) is the predicted family dining out status at time t+Δt in the morning, where 1 means dining out and 0 means dining at home; δ b (t+Δt) is the predicted family lunch out status at time t+Δt, where 1 means dining out and 0 means dining at home; δ c (t+Δt) is the predicted state of the family dining out at night at time t+Δt, where 1 represents dining out and 0 represents dining at home. The hidden layer of the back propagation neural network uses a hyperbolic tangent function. After training, the output of the family dining out behavior prediction model based on the back propagation neural network is as shown in formula (2):

[0080]

[0081] In the formula, f a () is the prediction model of family morning dining out behavior based on back propagation neural network after training; f b () is the prediction model of family lunch eating out behavior based on back propagation neural network after training; f c () is the prediction model of family dining out behavior at night based on back propagation neural network after training; δ a (t) is the family's dining out status in the morning at time t, where 1 means dining out and 0 means dining at home; δ b (t) is the family's lunch out status at time t, where 1 means dining out and 0 means dining at home; δ c (t) is the family dining out status at time t, where 1 means dining out and 0 means dining at home; δ a (t+Δt) is the predicted family dining out status at time t+Δt in the morning, where 1 means dining out and 0 means dining at home; δ b (t+Δt) is the predicted family lunch out status at time t+Δt, where 1 means dining out and 0 means dining at home; δ c (t+Δt) is the predicted family dining out status at time t+Δt, where 1 means dining out and 0 means dining at home; η is holiday information;

[0082] According to the predicted family dining out behavior, a dishwasher load prediction model based on family dining out behavior is constructed to predict the dishwasher load, as shown in formulas (3) to (10):

[0083] k=[δ a ,δ b ,δ c ](3)

[0084] In the formula, k = [δ a ,δ b ,δc ] is the family's dining out behavior matrix for the morning, afternoon and evening, where k is 1 for dining out and 0 for dining at home;

[0085] When k = [0, 0, 0], it means that the family eats breakfast, lunch and dinner at home. The dishwasher load prediction model is shown in formula (4):

[0086]

[0087] Where P(t) is the load of the dishwasher; P a (t), P b (t), P c (t) are the morning, midday and evening workloads of the dishwasher respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing;

[0088] See also Figure 3 , the family eats at home in the morning, afternoon and evening, and the dishwasher works between the end of the meal and the cut-off time, generating different loads;

[0089] When k = [1, 0, 0], it means that the family eats out in the morning and eats at home in the afternoon and evening. There is no dishwasher load in the morning. The dishwasher load prediction model is shown in formula (5):

[0090]

[0091] Where P(t) is the load of the dishwasher; P b (t), P c (t) are the middle and evening workloads of the dishwasher, respectively; T3 is the end time of lunch; T4 is the end time of dishwashing at noon; T5 is the end time of dinner; T6 is the end time of dishwashing at night;

[0092] See also Figure 4 , when the family eats out in the morning and eats at home for lunch and dinner, there is no dishwasher load in the morning;

[0093] When k = [0, 1, 0], it means that the family eats out at noon and eats at home in the morning and evening. There is no dishwasher load at noon, and the dishwasher load operation range in the morning changes from (T1, T2) to (T1, T4). The dishwasher load prediction model is shown in formula (6):

[0094]

[0095] Where P(t) is the load of the dishwasher; P a (t), P b (t), Pc (t) are the morning, midday and evening workloads of the dishwasher respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing;

[0096] See also Figure 5 , the family eats out at noon, and eats at home in the morning and evening, so there is no dishwasher load at noon, and the dishwasher load operation range in the morning changes from (T1, T2) to (T1, T4);

[0097] When k = [0, 0, 1], it means that the family eats out at night and eats breakfast and lunch at home. There is no dishwasher load at night, and the operating range of the dishwasher load at noon changes from (T3, T4) to (T3, T6). The dishwasher load prediction model is shown in formula (7):

[0098]

[0099] Where P(t) is the load of the dishwasher; P a (t), P b (t) are the morning and mid-day workloads of the dishwasher, respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T6 is the end time of evening dishwashing;

[0100] See also Figure 6 , the family eats out at night, and eats breakfast and lunch at home, so there is no dishwasher load at night, and the dishwasher load operation range at noon changes from (T3, T4) to (T3, T6);

[0101] When k = [1, 1, 0], it means that people eat out in the morning and at noon, and eat at home in the evening. There is no dishwasher load in the morning and at noon. The dishwasher load prediction model is shown in formula (8):

[0102] P(t)=P c (t),T5≤t≤T6 (8)

[0103] Where P(t) is the load of the dishwasher; P c (t) is the evening workload of the dishwasher; T5 is the end time of dinner; T6 is the end time of dishwashing in the evening;

[0104] When k = [1, 0, 1], it means that the family eats out in the morning and evening and eats at home at noon. There is no dishwasher load in the morning and evening, and the operating range of the dishwasher load at noon changes from (T3, T4) to (T3, T6). The dishwasher load prediction model is shown in formula (9):

[0105] P(t)=P b (t),T3≤t≤T6 (9)

[0106] Where P(t) is the load of the dishwasher; P b (t) is the workload of the dishwasher at noon; T3 is the end time of lunch; T6 is the end time of dishwashing in the evening;

[0107] When k = [0, 1, 1], it means that the family eats out at noon and in the evening, and eats at home in the morning. There is no dishwasher load at noon and in the evening. The dishwasher load operation time range in the morning changes from (T1, T2) to (T1, T6). The dishwasher load prediction model is shown in formula (10):

[0108] P(t)=P a (t),T1≤t≤T6 (10)

[0109] Where P(t) is the load of the dishwasher; P a (t) is the morning workload of the dishwasher; T1 is the end time of breakfast; T6 is the end time of dishwashing in the evening.

[0110] In S3, the dishwasher load carbon emission calculation model is constructed according to the dishwasher load and the carbon emission factor of electricity, and the dishwasher load carbon emission is calculated, which specifically includes:

[0111] It is selected that the family eats breakfast, lunch and dinner at home, and the dishwasher load carbon emission calculation model is constructed, as shown in formula (11):

[0112]

[0113] In the formula, C p is the carbon emission of dishwasher load; T1', T2', and T3' are the start-up time of dishwasher load in the morning, middle, and evening, respectively; τ a ,τ b ,τ c P is the working duration of the dishwasher in the morning, afternoon and evening respectively; a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher respectively; λ c (t) is the carbon emission factor of the dishwasher load at time t.

[0114] In S4, according to the dishwasher load and the dishwasher load carbon emission, with low-carbon economy as the goal, and with minimum electricity cost and minimum carbon emission as the objective function, based on the constraints of power operation constraint, continuous operation time constraint and operation range constraint, by adjusting the morning, noon and evening dishwasher load start time T1', T2', T3', the dishwasher load carbon emission reduction model is constructed. The dishwasher load carbon emission reduction model is shown in formulas (12) to (15):

[0115] The objective function is shown in formula (12):

[0116]

[0117] Where F is the dishwasher load target; T1', T2', and T3' are the morning, midday, and evening dishwasher load start times, respectively; τ a ,τ b ,τ c P is the working duration of the dishwasher in the morning, afternoon and evening respectively; a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher respectively; λ c (t) is the carbon emission factor of dishwasher load at time t; q (t) is the electricity price at time t; min is the minimum value operation;

[0118] The power operation constraint indicates that the load of the dishwasher in the morning, afternoon and evening shall not exceed the maximum and minimum operating power limits. The power operation constraint is shown in formula (13):

[0119]

[0120] Where P min , P max are the minimum and maximum loads of the dishwasher; P a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher, respectively;

[0121] The continuous operation time constraint indicates that the dishwasher must not exceed the minimum and maximum continuous operation time limits in the morning, afternoon and evening. The continuous operation time constraint is shown in formula (14):

[0122]

[0123] In the formula, τ min , τ max are the minimum and maximum continuous running time of the dishwasher respectively; τ a ,τ b ,τc They are the working duration of the dishwasher in the morning, afternoon and evening respectively;

[0124] The operating range constraint indicates that the start time of the dishwasher in the morning, afternoon and evening shall not be earlier than the end time of the meal, and a margin is left to ensure that the operation is completed before the end time of dishwashing. The operating range constraint is shown in formula (15):

[0125]

[0126] Where, T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing; T1', T2', T3' are the morning, noon and evening dishwasher load start times respectively; τ a ,τ b ,τ c They are the working duration of the dishwasher in the morning, afternoon and evening respectively.

[0127] Through the introduction of the above embodiments, the present invention collects dishwasher operation behavior data based on dishwasher load data collection technology, dishwasher load prediction model, dishwasher load carbon emission calculation model and dishwasher load carbon emission reduction model through dishwasher load data collection technology; based on the back propagation neural network, a dishwasher working state prediction model is constructed according to the dishwasher operation behavior data to predict the family dining out behavior, and then a dishwasher load prediction model is constructed according to the family dining out behavior to predict the dishwasher load; according to the dishwasher load, combined with the kilowatt-hour carbon emission factor, a dishwasher load carbon emission calculation model is constructed to calculate the dishwasher load carbon emission; according to the dishwasher load and the dishwasher load carbon emission, with the goal of low-carbon economy, the minimum electricity cost and the minimum carbon emission as the objective function, based on the constraints of power operation constraints, continuous operation time constraints and operation range constraints, a dishwasher load carbon emission reduction model is constructed, so that the family dining out behavior can be considered, a dishwasher load prediction model can be constructed, the accuracy of dishwasher load prediction can be improved, and a dishwasher carbon emission model can be constructed to realize the quantitative calculation of dishwasher carbon emissions. At the same time, the electricity cost and carbon emissions are comprehensively considered, the start time of the dishwasher load is scheduled, and the dishwasher load carbon emission reduction model is constructed, so that the dishwasher has the lowest electricity cost and the lowest carbon emission.

[0128] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have the same meaning as in the context of the prior art, and will not be interpreted with an idealized or overly formal meaning unless defined similarly here.

[0129] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for reducing carbon emissions from dishwasher load based on family dining out behavior, characterized in that: The following operations are included: Based on dishwasher load data collection technology, collect dishwasher operation behavior data; Based on the back propagation neural network, a dishwasher working state prediction model is constructed according to the dishwasher operation behavior data to predict the family dining out behavior, and then a dishwasher load prediction model is constructed according to the family dining out behavior to predict the dishwasher load; According to the dishwasher load and the carbon emission factor of electricity, a dishwasher load carbon emission calculation model is constructed to calculate the dishwasher load carbon emission; According to the dishwasher load and dishwasher load carbon emissions, with low-carbon economy as the goal, and minimizing electricity costs and carbon emissions as the objective functions, a dishwasher load carbon emission reduction model is constructed based on the constraints of power operation constraints, continuous operation time constraints and operation range constraints.

2. A method for reducing carbon emissions from dishwasher load based on family dining out behavior according to claim 1, characterized in that: The dishwasher operation behavior data is shown in formula (1): Where X is the collected dishwasher load operation data; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing; P a ,P b ,P c are the morning, mid-day and evening workloads of the dishwasher respectively; τ a ,τ b ,τ c They are the working duration of the dishwasher in the morning, afternoon and evening respectively; δ a ,δ b ,δ c are the family's dining out status in the morning, afternoon and evening; q is the electricity price information; c is the carbon emission factor information per kilowatt-hour; η is the holiday information.

3. The method for reducing carbon emissions from dishwasher load based on family dining out behavior according to claim 1, characterized in that: The back propagation neural network is based on the dishwasher operation behavior data, combined with the family's historical dining out status in the morning, noon and evening and holiday information, to build a dishwasher working status prediction model based on the back propagation neural network to predict the family's dining out behavior, specifically including: Collecting training data, training a back propagation neural network, and testing the back propagation neural network, training the back propagation neural network in an offline manner, training the back propagation neural network offline according to the historical dining out status of the family in the morning, noon, and evening and historical holiday information, and associating the historical dining out status of the family in the morning, noon, and evening and historical holiday information to construct the family dining out behavior prediction model based on the back propagation neural network; The input layer of the back propagation neural network includes four inputs, which are: a (t) is the family's dining out status in the morning at time t, where 1 means dining out and 0 means dining at home; δ b (t) is the family's lunch out status at time t, where 1 means dining out and 0 means dining at home; δ c (t) is the family dining out status at time t, where 1 is dining out and 0 is dining at home; η is holiday information; the output layer of the back propagation neural network includes 3 outputs, which are: δ a (t+Δt) is the predicted family dining out status at time t+Δt in the morning, where 1 means dining out and 0 means dining at home; δ b (t+Δt) is the predicted family lunch out status at time t+Δt, where 1 means dining out and 0 means dining at home; δ c (t+Δt) is the predicted state of the family dining out at night at time t+Δt, where 1 represents dining out and 0 represents dining at home. The hidden layer of the back propagation neural network uses a hyperbolic tangent function. After training, the output of the family dining out behavior prediction model based on the back propagation neural network is as shown in formula (2): In the formula, f a () is the prediction model of family morning dining out behavior based on back propagation neural network after training; f b () is the prediction model of family lunch eating out behavior based on back propagation neural network after training; f c () is the prediction model of family dining out behavior at night based on back propagation neural network after training; δ a (t) is the family's dining out status in the morning at time t, where 1 means dining out and 0 means dining at home; δ b (t) is the family's lunch out status at time t, where 1 means dining out and 0 means dining at home; δ c (t) is the family dining out status at time t, where 1 means dining out and 0 means dining at home; δ a (t+Δt) is the predicted family dining out status at time t+Δt in the morning, where 1 means dining out and 0 means dining at home; δ b (t+Δt) is the predicted family lunch out status at time t+Δt, where 1 means dining out and 0 means dining at home; δ c (t+Δt) is the predicted family dining out status at time t+Δt, where 1 means dining out and 0 means dining at home; η is holiday information; According to the predicted family dining out behavior, a dishwasher load prediction model based on family dining out behavior is constructed to predict the dishwasher load, as shown in formulas (3) to (10): k=[δ a ,d b ,d c ] (3) In the formula, k = [δ a ,δ b ,δ c ] is the family's dining out behavior matrix for the morning, afternoon and evening, where k is 1 for dining out and 0 for dining at home; When k = [0, 0, 0], it means that the family eats breakfast, lunch and dinner at home. The dishwasher load prediction model is shown in formula (4): Where P(t) is the load of the dishwasher; P a (t), P b (t), P c (t) are the morning, midday and evening workloads of the dishwasher respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing; When k = [1, 0, 0], it means that the family eats out in the morning and eats at home in the afternoon and evening. There is no dishwasher load in the morning. The dishwasher load prediction model is shown in formula (5): Where P(t) is the load of the dishwasher; P b (t), P c (t) are the middle and evening workloads of the dishwasher, respectively; T3 is the end time of lunch; T4 is the end time of dishwashing at noon; T5 is the end time of dinner; T6 is the end time of dishwashing at night; When k = [0, 1, 0], it means that the family eats out at noon and eats at home in the morning and evening. There is no dishwasher load at noon, and the dishwasher load operation range in the morning changes from (T1, T2) to (T1, T4). The dishwasher load prediction model is shown in formula (6): Where P(t) is the load of the dishwasher; P a (t), P b (t), P c (t) are the morning, midday and evening workloads of the dishwasher respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing; When k = [0, 0, 1], it means that the family eats out at night and eats breakfast and lunch at home. There is no dishwasher load at night, and the operating range of the dishwasher load at noon changes from (T3, T4) to (T3, T6). The dishwasher load prediction model is shown in formula (7): Where P(t) is the load of the dishwasher; P a (t), P b (t) are the morning and mid-day workloads of the dishwasher, respectively; T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T6 is the end time of evening dishwashing; When k = [1, 1, 0], it means that people eat out in the morning and at noon, and eat at home in the evening. There is no dishwasher load in the morning and at noon. The dishwasher load prediction model is shown in formula (8): P(t)=P c (t),T5≤t≤T6 (8) Where P(t) is the load of the dishwasher; P c (t) is the evening workload of the dishwasher; T5 is the end time of dinner; T6 is the end time of dishwashing in the evening; When k = [1, 0, 1], it means that the family eats out in the morning and evening and eats at home at noon. There is no dishwasher load in the morning and evening, and the operating range of the dishwasher load at noon changes from (T3, T4) to (T3, T6). The dishwasher load prediction model is shown in formula (9): P(t)=P b (t),T3≤t≤T6 (9) Where P(t) is the load of the dishwasher; P b (t) is the workload of the dishwasher at noon; T3 is the end time of lunch; T6 is the end time of dishwashing in the evening; When k = [0, 1, 1], it means that the family eats out at noon and in the evening, and eats at home in the morning. There is no dishwasher load at noon and in the evening. The dishwasher load operation time range in the morning changes from (T1, T2) to (T1, T6). The dishwasher load prediction model is shown in formula (10): P(t)=P a (t),T1≤t≤T6 (10) Where P(t) is the load of the dishwasher; P a (t) is the morning workload of the dishwasher; T1 is the end time of breakfast; T6 is the end time of dishwashing in the evening.

4. The method for reducing carbon emissions from dishwasher load based on family dining out behavior according to claim 1, characterized in that: According to the dishwasher load and the carbon emission factor of electricity, a dishwasher load carbon emission calculation model is constructed to calculate the dishwasher load carbon emission, which specifically includes: It is selected that the family eats breakfast, lunch and dinner at home, and the dishwasher load carbon emission calculation model is constructed, as shown in formula (11): In the formula, C p is the carbon emission of dishwasher load; T1', T2', and T3' are the start-up time of dishwasher load in the morning, middle, and evening, respectively; τ a ,τ b ,τ c P is the working duration of the dishwasher in the morning, afternoon and evening respectively; a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher respectively; λ c (t) is the carbon emission factor of the dishwasher load at time t.

5. The method for reducing carbon emissions from dishwasher load based on family dining out behavior according to claim 1, characterized in that: According to the dishwasher load and the dishwasher load carbon emission, with low-carbon economy as the goal, and with minimum electricity cost and minimum carbon emission as the objective function, based on the constraints of power operation constraint, continuous operation time constraint and operation range constraint, by adjusting the morning, noon and evening dishwasher load start time T1', T2', T3', the dishwasher load carbon emission reduction model is constructed. The dishwasher load carbon emission reduction model is shown in formulas (12) to (15): The objective function is shown in formula (12): Where F is the dishwasher load target; T1', T2', and T3' are the morning, midday, and evening dishwasher load start times, respectively; τ a ,τ b ,τ c They are the working duration of the dishwasher in the morning, afternoon and evening respectively; P a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher respectively; λ c (t) is the carbon emission factor of dishwasher load at time t; q (t) is the electricity price at time t; min is the minimum value operation; The power operation constraint indicates that the load of the dishwasher in the morning, afternoon and evening shall not exceed the maximum and minimum operating power limits. The power operation constraint is shown in formula (13): Where P min , P max are the minimum and maximum loads of the dishwasher; P a (t), P b (t), P c (t) are the morning, mid-day and evening workloads of the dishwasher, respectively; The continuous operation time constraint indicates that the dishwasher must not exceed the minimum and maximum continuous operation time limits in the morning, afternoon and evening. The continuous operation time constraint is shown in formula (14): In the formula, τ min , τ max are the minimum and maximum continuous running time of the dishwasher respectively; τ a ,τ b ,τ c They are the working duration of the dishwasher in the morning, afternoon and evening respectively; The operating range constraint indicates that the start time of the dishwasher in the morning, afternoon and evening shall not be earlier than the end time of the meal, and a margin is left to ensure that the operation is completed before the end time of dishwashing. The operating range constraint is shown in formula (15): Where, T1 is the end time of breakfast; T2 is the end time of morning dishwashing; T3 is the end time of lunch; T4 is the end time of noon dishwashing; T5 is the end time of dinner; T6 is the end time of evening dishwashing; T1', T2', T3' are the morning, noon and evening dishwasher load start times respectively; τ a ,τ b ,τ c They are the working duration of the dishwasher in the morning, afternoon and evening respectively.

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