A method for constructing a user power consumption load response model and a computing device

Abstract

The application discloses a method for constructing a user electricity load response model, comprising the following steps: determining a user category based on the energy-saving and environment-protecting consciousness of the user; determining a load demand of the user based on the electricity power and use state of each device of each user; constructing a first target function based on the user category and the load reduction amount of the user, wherein the load reduction amount of the user is determined based on the load demand and the load reduction demand of the user; setting a second target function based on the load change state of each device and the inconvenience coefficient of each device response; and constructing the user electricity load response model by using the first target function and the second target function. The application also discloses a computing device for executing the above method.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy power, and more particularly, to a method for constructing a user electricity load response model. BACKGROUND

[0002] User demand response is an important part of power demand management. It refers to the power user adjusting his own electricity plan according to the electricity price information and incentive information formulated by the power supply department, adjusting the operation mode through the technical improvement of the electricity equipment or the control means to change the electricity load characteristic curve, minimizing the user electricity cost under the user satisfaction and user production process constraint condition.

[0003] In the implementation process of power demand response, the change of inherent electricity behavior often reduces the user comfort, resulting in user dissatisfaction with the demand response project, low enthusiasm for participating in the demand response, and poor implementation effect of the demand response.

[0004] Therefore, a residential user load response model considering user comfort is needed to improve the enthusiasm of users participating in demand response. SUMMARY

[0005] To this end, the present application provides a method for constructing a user electricity load response model and a computing device, in an attempt to solve or at least alleviate at least one of the problems existing above.

[0006] According to one aspect of the present application, a method for constructing a user electricity load response model is provided, which is executed in a computing device and includes: determining the category to which the user belongs based on the energy-saving and environmental protection awareness of the user; determining the load demand of the user based on the electricity power and use state of each device of each user; constructing a first objective function based on the category to which the user belongs and the load reduction amount of the user, wherein the load reduction amount of the user is determined based on the load demand and the load reduction demand of the user; setting a second objective function based on the load change state of each device and the inconvenience coefficient of each device response; and constructing the user electricity load response model by using the first objective function and the second objective function.

[0007] Optionally, the method according to the present application further includes the step of: scheduling the electricity demand of different devices of each category of user by solving the user electricity load response model to achieve the load reduction demand.

[0008] Optionally, in the method according to the present application, the step of determining the category to which the user belongs based on the energy-saving and environmental protection awareness of the user further includes: setting the user dissatisfaction degree for different categories of user.

[0009] Optionally, in the method according to the present application, the first objective function is adapted to allocate the load reduction demand to each type of user based on user dissatisfaction, so as to minimize the user dissatisfaction.

[0010] Optionally, in the method according to the present application, the first objective function is expressed as:

[0011] wherein α j is the user dissatisfaction of the jth user, ΔP j is the load reduction amount of the jth user.

[0012] Optionally, in the method according to the present application, based on the type of user and the load reduction amount of the user, the step of constructing the first objective function further comprises: setting at least one first constraint condition for the first objective function, so as to constrain the user load reduction amount and the user dissatisfaction.

[0013] Optionally, in the method according to the present application, the first constraint condition at least comprises:

[0014] ΔP = P Total -P Peak ,

[0015] ΔP j ≤ 0.5P j ,

[0016]

[0017] 0 ≤ α j ≤ 1,

[0018] wherein ΔP is the load reduction amount, P Total is the load demand of the user, P Peak is the load reduction demand, ΔP j is the load reduction amount of the jth user, and α j is the user dissatisfaction of the jth user.

[0019] Optionally, in the method according to the present application, the load change state of each device is determined by the usage state of each device after the demand response is implemented and the usage state of each device before the demand response is implemented.

[0020] Optionally, in the method according to the present application, the second objective function is adapted to minimize the inconvenience degree of the user response based on the inconvenience coefficient of each device response.

[0021] Optionally, in the method according to the present application, based on the load change state of each device and the inconvenience coefficient of each device response, the step of constructing the second objective function further comprises: setting at least one second constraint condition for the second objective function, so as to constrain the single user load reduction amount.

[0022] Optionally, in the method according to the present application, the second constraint condition at least comprises:

[0023]

[0024] 0≤β ij ≤1,

[0025]

[0026] wherein U ij is the load change state of the i-th device of the j-th user, P ij is the power consumption of the i-th device of the j-th user, β ij is the inconvenience coefficient of the i-th device of the j-th user.

[0027] According to still another aspect of the present application, there is provided a computing device comprising: one or more processors; and memory; one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing any of the methods as described above.

[0028] According to still another aspect of the present application, there is provided a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform any of the methods as described above.

[0029] In summary, according to the scheme of the present application, the users are classified according to their energy conservation and environmental protection awareness (i.e. the acceptance degree of the users to demand response), and initial values of user dissatisfaction degree to demand response are set for users of different categories. Then, considering the user dissatisfaction degree in the user response stage and the inconvenience degree in the device response stage, a first objective function and a second objective function are constructed, and a demand response model based on mixed integer linear programming algorithm is established, so as to realize the distribution of load reduction demand among users of different categories, and make the load reduction burden of a single user not too heavy. BRIEF DESCRIPTION OF DRAWINGS

[0030] To the accomplishment of the foregoing and related ends, certain illustrative aspects are described herein in connection with the following description and the annexed drawings. These aspects are indicative of various ways in which the principles disclosed herein can be practiced and all aspects and equivalents thereof are intended to be within the scope of the claimed subject matter. The above- and other advantages of the present disclosure, as defined solely by the claims, will become more fully apparent from the detailed description given herein below and the accompanying drawings, wherein like elements are referred to by like reference numerals. Such description is given for the sake of

[0031] Figure 1A schematic diagram showing the configuration of the computing device 100 according to an embodiment of the present application is shown;

[0032] Figure 2 A schematic diagram showing the flow of the method 200 of constructing a user load response model according to an embodiment of the present application is shown;

[0033] Figure 3 A graph showing the user load curve before and after demand response according to an embodiment of the present application is shown;

[0034] Figure 4 A schematic diagram showing the daily load curve and the change in user dissatisfaction before and after demand response for a type of user (a user with a very strong awareness of energy conservation) according to an embodiment of the present application is shown;

[0035] Figure 5 A schematic diagram showing the daily load curve and the change in user dissatisfaction before and after demand response for a type of user (a user with a strong awareness of energy conservation) according to an embodiment of the present application is shown;

[0036] Figure 6 A schematic diagram showing the daily load curve and the change in user dissatisfaction before and after demand response for a type of user (a user with an average awareness of energy conservation) according to an embodiment of the present application is shown; and

[0037] Figures 7A to 7C A comparative schematic diagram showing the load reduction amount for various types of users according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0038] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood, and the scope of the present disclosure can be accurately conveyed to those skilled in the art.

[0039] In order to measure the comfort of the user, according to the embodiments of the present disclosure, the concept of user dissatisfaction is introduced to evaluate the attitude of the user to the demand response constraint. By constructing a residential user (hereinafter referred to as "user") load response model taking into account the user dissatisfaction, and by solving and optimizing the model, the enthusiasm of the user to participate in demand response is improved.

[0040] In the method of constructing a user electricity load response model according to the present disclosure, the execution of demand response is divided into two stages. The first stage is the user response stage. After the power grid enterprise starts the demand response project, the load reduction amount is allocated to each user according to the acceptance degree of the participating user. The second stage is the equipment response stage. After receiving the load reduction signal, the user schedules different devices (usually household appliances). In one embodiment, the user's scheduling of different household appliances depends on the degree of inconvenience brought to the user by turning off the device.

[0041] The method of constructing a user electricity load response model according to the present disclosure is suitable for being executed in a computing device. Figure 1 is a block diagram of an example computing device 100.

[0042] In the basic configuration 102, the computing device 100 typically includes one or more processors 104 and a system memory 106. A memory bus 108 can be used for communicating between the processor 104 and the system memory 106.

[0043] Depending on the desired configuration, the processor 104 can be any type of processor, including but not limited to a microprocessor (μP), a microcontroller (μC), a digital signal processor (DSP), or any combination thereof. The processor 104 can include one or more levels of cache memory 110 and 112, which can be employed to reduce the memory access time. The example processor core 114 can include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP Core), or any combination thereof. An example memory controller 118 can be used with the processor 104 or, in some implementations, the memory controller 118 can be an internal part of the processor 104.

[0044] Depending on the desired configuration, the system memory 106 can be any type of memory that is accessible by the processor 104, including but not limited to volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.), or any combination thereof. The system memory 106 can include an operating system 120, one or more applications 122, and program data 124. In some embodiments, the application 122 can be arranged to operate with the operating system 120 on the program data 124. In some embodiments, the computing device 100 is configured to execute the method 200 of constructing a user electricity load response model, and the program data 124 contains instructions for executing the above method.

[0045] The computing device 100 also includes a storage device 132 that can include non-removable storage 136 and removable storage 138, which are connected via a storage interface bus 134.

[0046] The computing device 100 can also include an interface bus 140 that facilitates communication from various interface devices (e.g., output devices 142, peripheral interfaces 144, and communication devices 146) to the basic configuration 102 via the bus / interface controller 130. Example output devices 142 include a graphics processing unit 148 and an audio processing unit 150. They can be configured to facilitate communication over one or more A / V ports 152, such as to various external devices such as a display or speakers via one or more A / V ports 152. Example peripheral interfaces 144 can include a serial interface controller 154 or a parallel interface controller 156, which can be configured to facilitate communication over one or more I / O ports 158 with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, image input device) or other peripheral devices (e.g., printer, scanner, etc.). An example of the communication device 146 can include a network controller 160, which can be arranged to facilitate communications with one or more other computing devices 162 over a network communication link via one or more communication ports 164.

[0047] The network communication link can be one example of a communication media. Communication media can typically be embodied by computer readable instructions, data structures, program modules, and / or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and can include any information delivery media. A "modulated data signal" can be a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media can include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), microwave, infrared (IR) and other wireless media. The term computer readable media as used herein can include both storage media and communication media. In some embodiments, computer readable media stores one or more programs implementing methods of operating an electricity-heat game based power distribution system according to the present application.

[0048] The computing device 100 can be implemented as a portion of a small- sized portable (or mobile) electronic device such as a cellular telephone, a digital camera, a personal digital assistant (PDA), a personal media player device, a wireless web appliance, a personal headset, an application-specific device, or a hybrid device that can include any of the above functions. The computing device 100 can also be implemented as a personal computer including both desktop and notebook configurations.

[0049] Figure 2 A flowchart of a method 200 of constructing a user electricity load response model according to one embodiment of the present disclosure is shown. As shown, the method 200 starts at step S210. Figure 2

[0050] In step S210, based on the energy conservation and environmental protection awareness of the user, the category to which the user belongs is determined.

[0051] The applicant has found in long-term research that the energy conservation and environmental protection awareness of the user is an important factor affecting the demand response behavior of the user. Generally, the stronger the energy conservation and environmental protection awareness of the user, the higher the enthusiasm of participating in demand response, and the stronger the acceptance of load reduction. In one embodiment, according to the energy conservation and environmental protection awareness of the user, the residential user can be divided into four categories, including: user with extremely strong energy conservation awareness, user with relatively strong energy conservation awareness, user with general energy conservation awareness, and user unwilling to participate in demand response. The four types of users are introduced as follows.

[0052] (1) User with extremely strong energy conservation awareness. This type of user has very strong energy conservation and environmental protection awareness, can recognize the social benefits brought by demand response, has high acceptance of demand response, low dissatisfaction, can accept more load reduction, and has high enthusiasm.

[0053] (2) User with relatively strong energy conservation awareness. This type of user is motivated by the economic benefits brought by the demand response project and participates in the demand response. Due to the benefits of the demand response project, the consumer is motivated to join the project, but has only moderate tolerance for load reduction.

[0054] (3) User with general energy conservation awareness. This type of user is willing to participate in demand response, but is unwilling to accept more load reduction due to low motivation.

[0055] (4) User unwilling to participate in demand response: This type of user has a skeptical attitude towards demand response and is unwilling to reduce load.

[0056] According to the embodiments of the present disclosure, corresponding user dissatisfaction is set for different categories of users. Generally, the user dissatisfaction is set as a∈(0,1).

[0057] ​In one embodiment, the user dissatisfaction is proportional to the degree of inconvenience brought to the user by deactivating the user's device, i.e. the more inconvenient the deactivation of the device, the greater the impact on the user's comfort, and the higher the user's dissatisfaction with the demand response. In addition, the user dissatisfaction is proportional to the load reduction of the user. In general, the user's dissatisfaction with the demand response depends on both the length of the device operation response and the load reduction. In other words, as the length of the load reduction and the load reduction change, the user dissatisfaction also changes, and the user dissatisfaction set in step S210 can be regarded as an initial value of the user dissatisfaction.

[0058] According to one embodiment of the present disclosure, the dissatisfaction of various types of users is shown in Table 1. Of course, it is not limited thereto.

[0059] Table 1: Dissatisfaction of various types of users

[0060] User category Dissatisfaction Users with very strong energy saving awareness [0.2,0.5) Users with strong energy saving awareness [0.5,0.7) Users with average energy saving awareness [0.7,1) Users unwilling to participate in demand response 1

[0061] Subsequently, in step S220, the load demand of the user is determined based on the power consumption of each device of each user and the usage state of each device.

[0062] Corresponding to the user response stage described above, step S220 can be performed in two steps as follows.

[0063] First, the power consumption of each device of each user within a given time is determined.

[0064] Suppose there are n users in total, and the total load P Total (t) consumed by the users within a given time t is:

[0065]

[0066] In the formula, P j (t) is the load demand of the jth user within time t.

[0067] Suppose each user has m electrical devices, then the total power consumption P Total within a given time is:

[0068]

[0069] In the formula, P ij is the power consumed by the ith device of the jth user, i∈{1,2,3, …, m}, j∈{1,2,3, …, n}.

[0070] Subsequently, the load demand of the user is determined based on the power consumption of each device of each user and the usage state of each device.

[0071] According to load characteristics, user loads can be divided into adjustable loads and fixed loads. Adjustable loads refer to loads that can be interrupted by users during peak periods of the power grid or in emergency situations. Fixed loads refer to loads that cannot be interrupted by users during peak periods of electricity consumption. Therefore, the total power consumption (or load demand) of a user within a given time t can be represented as:

[0072]

[0073] wherein, Pfixedis the load demand of fixed non-adjustable equipment, Padjustableis the load demand of adjustable equipment.

[0074] Further, the user's electrical equipment state is as follows.

[0075]

[0076] And for each user, the equipment state of the user's electrical equipment is:

[0077] A j = {D1 D2 D3 … … D m} (5)

[0078] wherein, A j represents the use state of all electrical equipment of the jthuser. D i is the on-off state of the electrical equipment, D ∈ {0, 1}. When D i = 1, it indicates "on"; when D i = 0, it indicates "off". A ij represents the state of the ithdevice of the jthuser, which changes over time.

[0079] In summary, the load demand of a user can be represented as:

[0080]

[0081] Subsequently, in step S230, a first objective function is constructed based on the category to which the user belongs and the load reduction amount of the user.

[0082] Wherein, the load reduction amount of the user is determined based on the load demand and the load reduction demand of the user. Assuming that the demand response implementer requires the user to reduce the peak load to P peak , the load reduction amount of the user is as follows.

[0083] ΔP = P Total - P Peak (7)

[0084] wherein, ΔP is the load reduction amount, P Total is the load demand of the user, PPeak for load curtailment demand.

[0085] for each user, the load curtailment amount of each user is denoted as ΔP j Then,

[0086]

[0087] In the user response stage, the load curtailment demand is reasonably allocated to various types of users according to the user dissatisfaction degree. Based on this, a first objective function is set. That is, the first objective function is adapted to allocate the load curtailment demand to various types of users based on the user dissatisfaction degree, so as to minimize the user dissatisfaction degree.

[0088] In an embodiment, the first objective function is expressed as follows:

[0089]

[0090] In the formula, α j is the user dissatisfaction degree of the jth user for demand response, ΔP j is the load curtailment amount of the jth user.

[0091] In addition, according to the embodiments of the present disclosure, when constructing the first objective function, at least one first constraint condition is set for the first objective function to constrain the user load curtailment amount and the user dissatisfaction degree.

[0092] Since an individual user should not be burdened with an excessively heavy load curtailment amount, for each user, the maximum possible reduction of the user load curtailment amount is set to 50%, that is,

[0093] ΔP j ≤ 0.5P j (10)

[0094] In addition to the above formula (10), the first constraint condition for the first objective function can also include the above formula (7) and formula (8), and the related constraint for the user satisfaction degree:

[0095] 0 ≤ α j ≤ 1 (11)

[0096] In summary, the first constraint condition at least includes one of the following conditions:

[0097]

[0098] wherein ΔP is the load curtailment amount, P Total is the load demand of the user, P Peak is the load curtailment demand, ΔP j is the load curtailment amount of the jth user, α jUser dissatisfaction degree of the jth user.

[0099] In addition, in order to ensure that the load reduction demand is fairly distributed among the users responding, the following factors also need to be considered:

[0100] 1) The same user should not be given the instruction to reduce demand every time;

[0101] 2) The demand response project implementer should select users to participate in the demand response plan on a fair basis.

[0102] Assuming that the initial values of the user dissatisfaction degrees of the same type of users are the same, the user dissatisfaction degree is mainly affected by the load reduction duration and the load reduction amount. As the load reduction duration and the load reduction amount increase, the user dissatisfaction degree gradually increases. If a specific user is selected to reduce load in any time period t, the user's dissatisfaction degree will increase in the next time period, so that the user with the lowest dissatisfaction degree will not be required to reduce load again in the next time period.

[0103] In addition, limiting the maximum reduction of the load reduction amount of each user to 50% can also ensure that a specific user will not be required to reduce more load because of having a lower dissatisfaction degree.

[0104] Subsequently, the device response stage is entered, and each device of each user is scheduled according to the load reduction demand. In step S240, a second objective function is set based on the load change state of each device and the inconvenience coefficient of each device response.

[0105] According to an embodiment, step S240 can be performed in two steps as follows.

[0106] First, the load change state of each device after the demand response is implemented is determined. In an embodiment, the load change state of each device is determined by the use state of each device after the demand response is implemented and the use state of each device before the demand response is implemented.

[0107] The use state of each device after the demand response is implemented is as follows.

[0108]

[0109] Similarly, for each user, the use state of the electrical device is as follows:

[0110] B j = {D1 D2 D3 …… D m} (13)

[0111] In the formula, B j represents the use state of all electrical devices of the jth user after the demand response is implemented, and B ijrepresents the state of the i-th device of the j-th user after the demand response is implemented.

[0112] Therefore, the load change state U ij As shown in the following formula.

[0113]

[0114] wherein A ij is determined by the aforementioned formula (4).

[0115] Next, a second objective function is set in combination with the inconvenience coefficient of each device response.

[0116] The degree of inconvenience brought by the deactivation of different devices determines the on-off state of each type of device after the demand response is implemented. In order to improve the user response comfort, the optimization goal of the second stage of demand response, i.e. the second objective function, is to minimize the degree of inconvenience of user response based on the inconvenience coefficient of each device response.

[0117] In one embodiment, the second objective function is represented as follows:

[0118]

[0119] wherein β ij is the inconvenience coefficient of each device response.

[0120] In addition, the load reduction ΔP before and after the demand response is implemented is shown in the following formula.

[0121]

[0122] wherein, is the load demand of the adjustable device, U ij is the load change state before and after the demand response is implemented.

[0123] In addition, at least one second constraint condition is set for the second objective function to constrain the single user load reduction.

[0124] In one embodiment, the second constraint condition at least includes:

[0125]

[0126] 0≤β ij ≤1

[0127]

[0128] Under the second constraint condition, the single user load reduction amount will be less than or equal to the total load reduction amount required by the operator, and load rebound may occur. Therefore, in an embodiment, when solving, the load reduction demand is reduced by 20% in proportion to solve until the optimal solution is obtained.

[0129] Then in step S250, a user electricity load response model is constructed using the first objective function and the second objective function.

[0130] More specifically, based on the first objective function and its first constraint condition, the second objective function and its second constraint condition described above, a user electricity load response model is generated. For related content of the first objective function, the first constraint condition, the second objective function, and the second constraint condition, please refer to the above, which will not be repeated here.

[0131] Based on the user electricity load response model constructed according to the present disclosure, the method 200 further comprises the step of: scheduling the electricity demand of different devices of various types of users by solving the constructed user electricity load response model to achieve the load reduction demand.

[0132] In an embodiment, the user electricity load response model is solved by calling the CPLEX12.8 optimization software in the YALMIP toolbox under the MATLAB R2017b platform to obtain the load reduction demand for each user to guide the user to schedule the device.

[0133] Further, to illustrate the effect of the user electricity load response model according to the present disclosure, the daily load curve of 74 residential households in a certain place is selected below for example analysis.

[0134] First, the users are classified, and the initial dissatisfaction of various types of users is determined, and the proportion is counted, as shown in Table 1.

[0135] Table 1: Dissatisfaction of various types of users and user proportion

[0136] User category Dissatisfaction User proportion Users with very strong energy saving awareness [0.2,0.5) 30％ Users with strong energy saving awareness [0.5,0.7) 27％ Users with average energy saving awareness [0.7,1) 35％ Users unwilling to participate in response 1 8％

[0137] According to the investigation, the residential houses are mainly equipped with the following devices (household appliances), and the inconvenience coefficients of various types of devices are shown in Table 2. The inconvenience coefficient of the non-adjustable device is 1, and the inconvenience coefficient of the adjustable device is (0, 1].

[0138] Table 2: Inconvenience coefficient of household appliances

[0139]

[0140]

[0141] The load demand of the user is simulated every 15 minutes. The load demand of each user in each time period is updated according to the degree of participation of the user in the demand response. The demand response is performed in three peak periods, i.e., from 7:30 to 10:30 in the morning, from 12:30 to 02:30 in the afternoon, and from 7:00 to 10:30 in the evening.

[0142] The load demand of the user before and after the demand response is shown in Table 3, and the load curve is shown in Figure 3 For comparison, the response result without considering the dissatisfaction of the user is added in Table 3.

[0143] Table 3 Load change before and after the demand response

[0144]

[0145] It can be seen from Figure 3 that, after the implementation of the demand response, the load demand of the user in the peak period is reduced, and the load demand of the user in the non-peak period is increased. This shows that the load demand of the user will not be reduced because of the implementation of the demand response, but is transferred. It can be seen from Table 3 that, without considering the dissatisfaction of the user, the load reduction of the user is greater. However, the promotion of the demand response is largely dependent on the acceptance of the user, and the acceptance of the user is directly related to the load reduction. According to the scheme of the present disclosure, not only the load reduction in the peak period is considered, but also the comfort of the user is considered. In the non-peak period, the load demand of the user rebounds, which improves the acceptance of the user to the demand response.

[0146] The daily load curve and the change of the dissatisfaction of the user with strong energy-saving awareness before and after the demand response are shown in Figure 4 It can be seen from Figure 4 that, if the user participates in the demand response in a time period, the dissatisfaction of the user in the next time period will increase. When the user no longer participates in the demand response, the dissatisfaction of the user to the demand response will continuously decrease until the initial state.

[0147] The daily load curve and the change of the dissatisfaction of the user with strong energy-saving awareness before and after the demand response are shown in Figure 5 、 Figure 6 The load reduction of each type of user after the demand response is shown in Figures 7A-7C It can be seen from the above figures that, according to the user electricity load response model constructed by the present disclosure, the load reduction demand can be fairly and reasonably distributed among the users. By not repeatedly selecting the user with low dissatisfaction, the fairness of the demand response is established, and the acceptance of the user to the demand response is improved.

[0148] According to the scheme of the present disclosure, the influence of user dissatisfaction on the implementation effect of a demand response project is studied. Based on the method for constructing a user power load response model of the present disclosure, users are classified according to their energy-saving and environmental protection awareness (i.e., the acceptance of the users to the demand response); and initial values of user dissatisfaction to the demand response are set for users of different categories. Then, considering the user dissatisfaction in the user response stage and the inconvenience degree in the equipment response stage, a first objective function and a second objective function are constructed, and a demand response model based on a mixed integer linear programming algorithm is established, so as to realize the distribution of load reduction demand among users of different categories, and make the load reduction burden of a single user not too heavy.

[0149] The example results show that the load demand reduced by the user in the peak period can be satisfied in the off-peak period. Compared with the traditional demand response algorithm, the demand response model considering user dissatisfaction proposes a more reasonable demand response strategy, which is more conducive to the promotion and implementation of the demand response project.

[0150] It should be understood that, in order to simplify the present disclosure and to help understand one or more of the various inventive aspects, various features of the present application are sometimes grouped together in a single embodiment, figure or description of the embodiments. However, the method of the disclosure should not be interpreted as reflecting an intention that the claimed application requires more features than those explicitly recited in each claim. Rather, as reflected in the claims below, the inventive aspects are in less than all the features of the single embodiment disclosed earlier. Therefore, the claims following the specific embodiments are hereby expressly incorporated into the specific embodiments, wherein each claim itself is a separate embodiment of the present application.

[0151] Those skilled in the art will understand that the modules or units or components of the devices in the examples disclosed herein can be arranged in the devices as described in the examples, or alternatively can be located in one or more devices different from the devices in the examples. The modules in the foregoing examples can be combined into one module or can be further divided into multiple sub-modules.

[0152] Those skilled in the art will understand that the modules in the devices in the embodiments can be adaptably changed and disposed in one or more devices different from the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and furthermore can be divided into multiple sub-modules or sub-units or sub-components. Except that at least some of such features and / or processes or units are mutually exclusive, all the features disclosed in the specification (including the accompanying claims, abstract and drawings) and all the processes or units of any method or device so disclosed can be combined in any combination. Unless explicitly stated otherwise, each feature disclosed in the specification (including the accompanying claims, abstract and drawings) can be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0153] The present application also discloses:

[0154] A5. The method of A4, wherein the first objective function is expressed as:

[0155] wherein α j is the user dissatisfaction degree of the jth user, ΔP j is the load reduction amount of the jth user.

[0156] A7. The method of A6, wherein the first constraint condition comprises at least:

[0157] ΔP = P Total -P Peak ,

[0158] ΔP j ≤ 0.5P j ,

[0159]

[0160] 0 ≤ α j ≤ 1,

[0161] wherein Δ; is the load reduction amount, P Total is the load demand of the user, P Peak is the load reduction demand, ΔP j is the load reduction amount of the jth user, α j is the user dissatisfaction degree of the jth user.

[0162] A11. The method of A10, wherein the second constraint condition comprises at least:

[0163]

[0164] 0 ≤ β ij ≤ 1,

[0165]

[0166] wherein, U ij is the load change state of the i-th device of the j-th user, P ij is the power consumption of the i-th device of the j-th user, β ij is the inconvenience coefficient of the i-th device of the j-th user in response.

[0167] Furthermore, to the extent consistent with USPTO rules and practice, one or more embodiments shown and described as text can also be practiced as apparatus claims or claims for articles of manufacture. It should also be understood that a specific implementation of the invention can well not meet one or more of the criteria set forth in the above summary, but which by virtue of being comprised in a specific implementation of the invention nonetheless falls within the scope of the invention. Also, the term "comprising" is used in the inclusive sense of "including" and not the exclusive sense "consisting only of. Also, the use of "based on", "implemented by" or "implemented using", "wherein", "whereby" and / or the like are deemed to implicate the functions described in the specification.

[0168] Furthermore, some of the embodiments described herein are of apparatuses, methods, or processes combinations of which are described throughout this specification. Accordingly, each claim in dependent on any prior claim can perform the corresponding combination of elements in the dependent claim. The combination of which each claim is directed can be a method or a processing machine that implements a process (which can otherwise be referred to as a machine process). It should also be understood that, in this specification, relative terms of orientation and / or position, such as, top, bottom, left, right, and the like, are made only with reference to the orientation and / or position of the figures as part of a process to more particularly show elements of the application.

[0169] As used herein, the ordinal terms "first," "second," "third," etc. merely denote different instances of ordinary objects, without necessarily implying a given order, sequence, or chronology to the objects being described, unless specified otherwise.

[0170] While the application has been described in terms of several embodiments, those skilled in the art will recognize that the application can be practiced with modifications and alterations limited only by the spirit and scope of the claims. Additionally, although this description has focused on the use of the application in the context of a computer system, it should be understood that the application is not limited to use in this context, but is capable of implementation in conjunction with a variety of other apparatuses. The disclosures of patents, patent applications, and publications are incorporated herein by reference in their entireties. Although the application has been described and illustrated with a certain degree of particularity, it is understood that the present disclosure of the application has been made by way of example and that changes in details of the application can be made without departing from the spirit, the scope and the principles of the application.

Claims

1. A method for constructing a user electricity load response model, executed in a computing device, comprising: Based on users' awareness of energy conservation and environmental protection, determine the user's category; Determine the user's load demand based on the power consumption and usage status of each user's devices; Based on the user's category and the user's load reduction amount, a first objective function is constructed. The user's load reduction amount is determined based on the user's load demand and load reduction demand. The user's load demand includes adjustable load and fixed load. The adjustable load refers to the load that the user can interrupt during peak power grid periods or in an emergency. The fixed load refers to the load that the user cannot interrupt during peak power consumption periods. Based on the load change status of each device and the inconvenience coefficient of each device's response, a second objective function is set. The user's electricity load response model is constructed using the first objective function and the second objective function; The second objective function, based on the load change status of each device and the inconvenience coefficient of each device's response, includes: After the demand response is implemented, the load change status of each device is determined. The load change status of each device is determined by the usage status of each device after the demand response is implemented and the usage status of each device before the demand response is implemented. The degree of inconvenience caused by the shutdown of different devices determines the power on / off status of various devices after the demand response is implemented. Based on the inconvenience coefficient of each device's response, a second objective function is set. This second objective function is suitable for minimizing the inconvenience of user response in the next time period after the implementation of the demand response, based on the inconvenience coefficient of each device's response. The step of determining the user category based on the user's energy conservation and environmental protection awareness further includes: setting user dissatisfaction levels for different user categories; and the first objective function is adapted to allocate the load reduction demand to various user categories based on user dissatisfaction, so as to minimize user dissatisfaction.

2. The method of claim 1, further comprising the step of: By solving the user electricity load response model, the electricity demand of different devices of various users can be scheduled to achieve load reduction.

3. The method as described in claim 1, wherein, The first objective function is expressed as: Where, α j Let ΔP be the user dissatisfaction level corresponding to the j-th user. j Let n be the load reduction amount for the j-th user, and n represent the number of users.

4. The method according to any one of claims 1-3, wherein, The steps for constructing the first objective function based on the user's category and the user's load reduction amount also include: For the first objective function, at least one first constraint condition is set to constrain the user load reduction amount and user dissatisfaction.

5. The method of claim 4, wherein, The first constraint includes at least: ΔP=P Total -P Peak , ΔP j ≤0.5P j , 0≤α j ≤1， Where ΔP is the load reduction amount, P Total To meet the user's load requirements, P Peak To reduce load demand, ΔP j Let α be the load reduction amount for the j-th user. j Let j represent the user dissatisfaction of the j-th user, and n represent the number of users.

6. The method according to any one of claims 1-3, wherein, The step of setting the second objective function based on the load change status of each device and the inconvenience coefficient of each device's response further includes: For the second objective function, at least one second constraint is set to constrain the load reduction of a single user.

7. The method of claim 6, wherein, The second constraint includes at least: 0≤β ij ≤1， Among them, U ij For the load change status of the i-th device of the j-th user, P ij Let β be the power consumption of the i-th device of the j-th user. ij Let ΔP be the inconvenience factor for the i-th device response of the j-th user, n represent the number of users, m represent the number of devices, and ΔP be the load reduction amount. j This represents the load reduction amount for the j-th user.

8. A computing device, comprising: One or more processors; and Memory; One or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods according to claims 1-7.

9. A computer-readable storage medium storing one or more programs, said one or more programs including instructions that, when executed by a computing device, cause the computing device to perform any one of the methods according to claims 1-7.

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