Power retail package making method and system considering user regulation capability

Abstract

The invention discloses a power retail package making method and system considering user regulation ability, and relates to the technical field of power markets. The method comprises the following steps: constructing an electric power retail package integral model considering user adjustment capability, wherein the electric power retail package integral model is used for giving electric power retail package integral corresponding to a user according to an actual adjustment condition of the user; according to the number of participation adjustment times, sustainable adjustment time and accumulated electric quantity of the adjustable users in the power retail package, an adjustable user power retail package economic model based on LSTM is constructed, and economic rewards are given to the users; an adjustable user power retail package power quantity model based on LSTM is constructed, and the user power quantity is rewarded; and constructing an electric power retail package model considering the user adjustment capability, and adjusting the original electric power retail package according to the economic reward and the electric quantity reward. According to the invention, by formulating the intelligent and personalized power retail package, the participation degree and satisfaction degree of the user are improved, and the flexibility of the power system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power market, and in particular to a method and system for formulating power retail packages taking into account user regulation capabilities. Background Art

[0002] With the growth of global energy demand and the application of renewable energy, the power system is facing increasing pressure. Traditional electricity retail packages are usually fixed pricing methods, which may have the following shortcomings:

[0003] 1) Existing packages do not fully consider users’ specific electricity consumption behaviors and adjustment capabilities, resulting in a deviation between the actual benefits of the packages and user needs;

[0004] 2) The existing electricity price mechanism may not be flexible enough to respond to changes in the electricity market and fluctuations in user demand in real time, thus affecting users’ enthusiasm for participating in the electricity retail market;

[0005] 3) The electricity retail packages on the market may be too homogeneous, lacking customized services for different user groups, and unable to effectively meet the diverse needs of users;

[0006] 4) Existing packages ignore the improvement of user participation and fail to effectively utilize users’ own adjustment capabilities to optimize electricity consumption patterns;

[0007] 5) Traditional forecasting models may not be advanced enough to accurately predict users’ electricity demand and changing trends in the electricity market.

[0008] Therefore, the method of formulating electricity retail packages that takes into account the user's adjustment ability has multiple meanings: through customized electricity retail packages, users can more intuitively feel the intimacy and practicality of the package design, thereby increasing users' enthusiasm for participating in the electricity retail market; users' electricity consumption behavior can be regulated through electricity price signals, and package design can encourage users to use electricity during periods of low electricity demand, which helps to balance electricity supply and demand and optimize the allocation of electricity resources; through flexible adjustment on the user side, the peak-to-valley difference of the power system can be reduced, the operating cost of the system can be reduced, and the economy and reliability of the power system can be improved. Summary of the invention

[0009] In view of the problems existing in the existing electricity retail packages, such as neglect of user adjustment ability, lack of flexibility in electricity price mechanism, lack of customization of packages, failure to improve user participation, inaccurate prediction model, etc., the present invention proposes a method and system for formulating electricity retail packages taking into account user adjustment ability. Through intelligent analysis methods and optimization mechanisms, a new way of customizing electricity retail packages is provided, which effectively improves the overall efficiency and flexibility of the power system, while optimizing the user experience and the economic benefits of electricity retailers.

[0010] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0011] On the one hand, the present invention proposes a method for formulating a power retail package taking into account user adjustment capabilities, the method comprising:

[0012] Construct an electricity retail package points model that takes into account the user's regulation ability, including an electricity retail package regulation times points model, an electricity retail package sustainable regulation time points model, and an electricity retail package accumulated electricity points model, which are used to give users corresponding electricity retail package points based on their actual regulation situations;

[0013] According to the number of times the adjustable user participates in the adjustment in the electricity retail package, the sustainable adjustment time and the accumulated electricity, an LSTM-based adjustable user electricity retail package economic model is constructed to give economic rewards to the user; the adjustable user electricity retail package economic model aims to minimize the sum of the adjustment number deviation, the sustainable adjustment time deviation, the accumulated electricity deviation and the economic reward cost, and takes the adjustment number constraint, the sustainable adjustment time constraint, the accumulated electricity constraint and the issuance of economic reward constraint as constraint conditions, and trains the economic reward factor given to the adjustable user based on the LSTM algorithm;

[0014] According to the number of times the adjustable user participates in the adjustment in the electricity retail package, the sustainable adjustment time and the accumulated electricity, an adjustable user electricity retail package electricity model based on LSTM is constructed to give the user electricity rewards; the adjustable user electricity retail package electricity model aims to minimize the sum of the adjustment number deviation, the sustainable adjustment time deviation, the accumulated electricity deviation and the electricity reward cost, and takes the adjustment number constraint, the sustainable adjustment time constraint, the accumulated electricity constraint and the power generation reward constraint as the constraint conditions, and trains the electricity reward factor given to the adjustable user based on the LSTM algorithm;

[0015] According to the economic model of the adjustable user electricity retail package and the electricity quantity model of the adjustable user electricity retail package, economic rewards and electricity quantity rewards are given to the user's actual adjustment ability, and an electricity retail package model that takes into account the user's adjustment ability is constructed. According to the economic rewards and electricity quantity rewards, the original electricity retail package is adjusted, including basic fee adjustment and package included electricity quantity adjustment.

[0016] As a preferred solution of the present invention, the electricity retail package adjustment times integral model is expressed as:

[0017]

[0018] In the formula, F cishuis the number of adjustments of the electricity retail package; N1, N2, and N3 are the number of adjustments thresholds; k1, k2, and k3 are the integral coefficients corresponding to the number of adjustments thresholds; a is the unit integral; n is the number of user adjustments;

[0019] The sustainable regulation time integral model of the electricity retail package is expressed as:

[0020]

[0021] In the formula, F shijian is the sustainable adjustment time integral of the electricity retail package; T1, T2, and T3 are sustainable adjustment time thresholds respectively; α1, α2, and α3 are the integral coefficients corresponding to the sustainable adjustment time respectively; t is the sustainable adjustment time of the user;

[0022] The electricity retail package cumulative electricity points model is expressed as:

[0023]

[0024] In the formula, F dianliang is the accumulated electricity points of the electricity retail package; Q1, Q2, and Q3 are the accumulated electricity thresholds; β1, β2, and β3 are the integral coefficients corresponding to the accumulated electricity; q is the accumulated electricity of the user;

[0025] Among them, the calculation formula of the cumulative power thresholds Q1, Q2, and Q3 is:

[0026]

[0027] Where △P(t) is the user's adjustment ability at time t.

[0028] As a preferred solution of the present invention, the electricity retail package points model also includes an additional points reward model, which is expressed as:

[0029] F jiangli =θ·a,n≥N3,t≥T3,q≥Q3;

[0030] In the formula, F jiangli is the extra bonus points; θ is the extra bonus points coefficient.

[0031] As a preferred solution of the present invention, the objective function of the economic model of the adjustable user electricity retail package is expressed as: minF piancp ;

[0032] in,

[0033] F piancp =|N G -n|+|T G -t|+|Q G-q|+P buc ;

[0034] P buc =φ1·F cishu +φ2·F shijian +φ3·F dianliang +φ4·F jiangli ;

[0035] In the formula, F piancp is the adjustment deviation of the economic model of the adjustable user electricity retail package; N G is the number of adjustments issued, n is the number of user adjustments; T G is the sustainable adjustment time issued, t is the sustainable adjustment time of the user; Q G is the cumulative power delivered, q is the cumulative power of the user; P buc is the economic reward for electricity retail package users; φ1, φ2, φ3, φ4 are the economic reward factors for users respectively; F cishu F is the number of electricity retail package adjustment points, shijian Sustainable adjustment of time credits for electricity retail packages, F dianliang Accumulate electricity points for electricity retail packages, F jiangli For extra bonus points;

[0036] The specific constraints are:

[0037] Adjustment times constraint: N min <n<N max ;

[0038] Sustainable adjustable time constraint: T min <t<T max ;

[0039] Cumulative power constraint: Q min <q<Q max ;

[0040] Issue economic incentive constraints: P buc <P XF ;

[0041] Where N min 、N max are the minimum and maximum adjustment times respectively; T min 、T max are the minimum and maximum sustainable adjustment time respectively; Q min , Q max are the minimum and maximum accumulated power respectively; P XF Provide financial incentives to users of electricity retail packages;

[0042] The economic incentive P for electricity retail package users buc, the economic rewards P issued to electricity retail package users XF , the number of adjustments issued N G , user adjustment times n, issued sustainable adjustment time T G , the user can continuously adjust the time t, the cumulative power Q G and the user's accumulated power q as input, the user's economic reward factor φ i , i=1,2,3,4 are outputs, and a LSTM-based model for adjusting user economic reward factors is constructed The economic reward factor given to adjust the user based on LSTM algorithm training is expressed as:

[0043]

[0044] In the formula, φ i Represents the economic reward factor of the i-th user.

[0045] As a preferred solution of the present invention, the objective function of the adjustable user electricity retail package electricity model is expressed as: minF piancq ;

[0046] in,

[0047] F piancq =|N G -n|+|T G -t|+|Q G -q|+Q buc ;

[0048] Q buc =ψ1·F cishu +ψ2·F shijian +ψ3·F dianliang +ψ4·F jiangli ;

[0049] In the formula, F piancq N is the adjustment deviation of the adjustable user electricity retail package electricity model; G is the number of adjustments issued, n is the number of user adjustments; T G is the sustainable adjustment time issued, t is the sustainable adjustment time of the user; Q G is the cumulative power delivered, q is the cumulative power of the user; Q buc is the electricity consumption reward for electricity retail package users; ψ1, ψ2, ψ3, and ψ4 are the user electricity consumption reward factors respectively; F cishu F is the number of electricity retail package adjustment points, shijian Sustainable adjustment of time credits for electricity retail packages, F dianliang Accumulate electricity points for electricity retail packages, F jiangli For extra bonus points;

[0050] The model constraints are as follows:

[0051] Adjustment times constraint: N min <n<N max ;

[0052] Sustainable adjustable time constraint: T min <t<T max ;

[0053] Cumulative power constraint: Q min <q<Q max ;

[0054] The power generation reward constraint is: Q buc XF ;

[0055] Where N min 、N max are the minimum and maximum adjustment times respectively; T min , T max are the minimum and maximum sustainable adjustment time respectively; Q min , Q max are the minimum and maximum accumulated power respectively; Q XF Provide electricity consumption rewards to users of electricity retail packages;

[0056] Reward Q with electricity consumption of electricity retail package users buc , the electricity retail package user electricity reward Q XF , the number of adjustments issued N G , user adjustment times n, issued sustainable adjustment time T G , the user can continuously adjust the time t, the cumulative power Q G and the user's accumulated power q as input, the user's power reward factor ψ j , j = 1, 2, 3, 4 are outputs, and a LSTM-based model for adjusting user power reward factors is constructed. Based on the LSTM algorithm training, the power reward factor given to adjust the user is expressed as:

[0057]

[0058] In the formula, ψ j Represents the power reward factor of the jth user.

[0059] As a preferred solution of the present invention, the electricity retail package model includes a basic fee adjustment model and a package included electricity adjustment model;

[0060] The basic cost adjustment model is expressed as:

[0061] P chenb ​=P taoc +P buc ;

[0062] The package includes a power adjustment model represented as follows:

[0063] Q chenb =Q taoc +Q buc ;

[0064] Where P chenb P is the adjusted basic fee for electricity retail packages; taoc is the original electricity retail package basic fee, P buc Economic rewards for electricity retail package users based on their regulatory capabilities; Q chenb The electricity consumption included in the adjusted electricity retail package; Q taoc The original retail electricity package includes electricity consumption, Q buc It is an electricity reward given to users of electricity retail packages based on their regulation capabilities.

[0065] On the other hand, the present invention proposes a system for formulating a power retail package considering user adjustment capability. Based on the method for formulating a power retail package considering user adjustment capability as described above, the system comprises:

[0066] The integral model building module is used to build an electricity retail package integral model that takes into account the user's adjustment ability, including an electricity retail package adjustment times integral model, an electricity retail package sustainable adjustment time integral model, and an electricity retail package accumulated electricity integral model;

[0067] The economic model building module is used to build an LSTM-based economic model of the adjustable user's electricity retail package according to the number of times the adjustable user participates in the electricity retail package, the sustainable adjustment time and the accumulated electricity, and give the user economic rewards;

[0068] The power model building module is used to build an LSTM-based power retail package power model for adjustable users according to the number of times the adjustable users participate in the power retail package, the sustainable adjustment time and the accumulated power, and give users power rewards;

[0069] A package model building module, used to give economic rewards and electricity rewards to the user's actual regulation ability according to the adjustable user electricity retail package economic model and the adjustable user electricity retail package electricity model, and to build an electricity retail package model that takes into account the user's regulation ability;

[0070] The package adjustment module is used to adjust the original electricity retail package according to the electricity retail package model, including basic fee adjustment and package included electricity adjustment.

[0071] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of a method for formulating a power retail package taking into account the user's adjustment capability are implemented as described above.

[0072] Compared with the prior art, the beneficial effects of the present invention are: by constructing a multi-dimensional integral model (number of adjustments, sustainable adjustment time, accumulated electricity), combined with an economic and electricity model based on the LSTM algorithm, the user's adjustment ability is comprehensively analyzed and optimized, and accurate user adjustment behavior prediction and reward distribution are achieved. Through the integral model and LSTM algorithm, the user's adjustment ability is accurately evaluated and predicted; the economic reward and electricity reward mechanism are optimized to ensure a reasonable balance between the reward cost and the adjustment effect; the flexibility of the power system is improved to support a wider range of renewable energy access and power dispatch; the cost and included electricity of the power retail package are dynamically adjusted to optimize the allocation of power resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0074] in:

[0075] Figure 1 is a flow chart of the method of the present invention;

[0076] Figure 2 It is a schematic diagram of the modular structure of the system of the present invention. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0078] like Figure 1 As shown in FIG. 1 , an embodiment of the present invention is provided, which provides a method for formulating a power retail package taking into account the user's adjustment capability, comprising the following steps:

[0079] S1: Construct an electricity retail package points model that takes into account the user's regulation ability, which is used to give users corresponding electricity retail package points according to their actual regulation situation, and enhance the enthusiasm of adjustable users to participate in electricity retail packages;

[0080] The electricity retail package points model includes the electricity retail package adjustment times points model, the electricity retail package sustainable adjustment time points model and the electricity retail package accumulated electricity points model.

[0081] In one embodiment, the electricity retail package adjustment times integral model is expressed as:

[0082]

[0083] In the formula, F cishu is the number of adjustments of the electricity retail package; N1, N2, and N3 are the number of adjustments thresholds; k1, k2, and k3 are the integral coefficients corresponding to the number of adjustments thresholds; a is the unit integral; n is the number of user adjustments;

[0084] The sustainable regulation time integral model of electricity retail packages is expressed as:

[0085]

[0086] In the formula, F shijian is the sustainable adjustment time integral of the electricity retail package; T1, T2, and T3 are sustainable adjustment time thresholds respectively; α1, α2, and α3 are the integral coefficients corresponding to the sustainable adjustment time respectively; t is the sustainable adjustment time of the user;

[0087] The cumulative electricity points model of the electricity retail package is expressed as:

[0088]

[0089] In the formula, F dianliang is the accumulated electricity points of the electricity retail package; Q1, Q2, and Q3 are the accumulated electricity thresholds; β1, β2, and β3 are the integral coefficients corresponding to the accumulated electricity; q is the accumulated electricity of the user;

[0090] Among them, the cumulative power thresholds Q1, Q2, and Q3 are mainly calculated based on the adjustment time. Different cumulative adjustment times will produce different power. The calculation formula is:

[0091]

[0092] Where △P(t) is the user's adjustment ability at time t.

[0093] Furthermore, the electricity retail package points model also includes an additional points reward model, that is, when the number of user adjustments, the user's sustainable adjustment time, and the user's cumulative electricity consumption all exceed N3, T3, and Q3, additional rewards are given to the adjustment users, expressed as:

[0094] F jiangli =θ·a,n≥N3,t≥T3,q≥Q3;

[0095] In the formula, F jiangli is the extra bonus points; θ is the extra bonus points coefficient.

[0096] S2: According to the number of times the adjustable users participate in the electricity retail package, the sustainable adjustment time and the accumulated electricity, an adjustable user electricity retail package economic model based on LSTM (Long Short-Term Memory) is constructed to give users certain economic rewards to encourage them to better participate in electricity retail package activities;

[0097] The economic model of the adjustable user electricity retail package aims to minimize the sum of the adjustment number deviation, sustainable adjustment time deviation, cumulative electricity deviation and economic reward cost, and takes the adjustment number constraint, sustainable adjustment time constraint, cumulative electricity constraint and economic reward constraint as constraints. The economic reward factor given to the adjustable user is trained based on the LSTM algorithm to ensure that the user is given appropriate economic rewards.

[0098] In a specific embodiment, the objective function of the economic model of the adjustable user electricity retail package is expressed as: minF piancp ;

[0099] in,

[0100] F piancp =|N G -n|+|T G -t|+|Q G -q|+P buc ;

[0101] P buc =φ1·F cishu +φ2·F shijian +φ3·F dianliang +φ4·F jiangli ;

[0102] In the formula, F piancp is the adjustment deviation of the economic model of the adjustable user electricity retail package; N G is the number of adjustments issued; T G The sustainable adjustment time for the release; Q G is the cumulative power delivered; P bucIt is the economic reward for the electricity retail package users; φ1, φ2, φ3, φ4 are the economic reward factors for users respectively; the economic reward is given mainly based on the actual number of adjustments, actual sustainable adjustment time, actual accumulated electricity, and performance of the users;

[0103] The specific constraints are:

[0104] Adjustment times constraint: N min <n<N max ;

[0105] Sustainable adjustable time constraint: T min <t<T max ;

[0106] Cumulative power constraint: Q min <q<Q max ;

[0107] Issue economic incentive constraints: P buc <P XF ;

[0108] Where N min 、N max are the minimum and maximum adjustment times respectively; T min 、T max are the minimum and maximum sustainable adjustment time respectively; Q min , Q max are the minimum and maximum accumulated power respectively; P XF Economic rewards for users of electricity retail packages issued; the economic rewards given cannot exceed the value of the economic rewards issued;

[0109] The economic incentive P for electricity retail package users buc , the economic rewards P issued to electricity retail package users XF , the number of adjustments issued N G , user adjustment times n, issued sustainable adjustment time T G , the user can continuously adjust the time t, the cumulative power Q G and the user's accumulated power q as input, the user's economic reward factor φ i , i=1,2,3,4 are outputs, and a LSTM-based model for adjusting user economic reward factors is constructed The economic reward factor given to adjust the user based on LSTM algorithm training is expressed as:

[0110]

[0111] In the formula, φ i Represents the economic reward factor of the i-th user.

[0112] S3: According to the number of times the adjustable user participates in the electricity retail package, the sustainable adjustment time and the accumulated electricity, an LSTM-based adjustable user electricity retail package electricity model is constructed to give the user electricity rewards;

[0113] The electricity retail package electricity model for adjustable users aims to minimize the sum of adjustment number deviation, sustainable adjustment time deviation, cumulative electricity deviation and electricity reward cost, and takes adjustment number constraint, sustainable adjustment time constraint, cumulative electricity constraint and power generation reward constraint as constraint conditions. The electricity reward factor given to the adjustable users is trained based on the LSTM algorithm to ensure that users are given appropriate electricity rewards.

[0114] Specifically, the objective function of the adjustable user electricity retail package electricity model is expressed as: minF piancq ;

[0115] in,

[0116] F piancq =|N G -n|+|T G -t|+|Q G -q|+Q buc ;

[0117] Q buc =ψ1·F cishu +ψ2·F shijian +ψ3·F dianliang +ψ4·F jiangli ;

[0118] In the formula, F piancq is the adjustment deviation of the electricity retail package model of the adjustable user; Q buc It is the electricity reward for the electricity retail package users; ψ1, ψ2, ψ3, ψ4 are the user electricity reward factors respectively; the electricity reward is given mainly based on the user's actual adjustment times, actual sustainable adjustment time, actual accumulated electricity, and performance;

[0119] The model constraints are as follows:

[0120] Adjustment times constraint: N min <n<N max ;

[0121] Sustainable adjustable time constraint: T min <t<T max ;

[0122] Cumulative power constraint: Q min <q<Q max ;

[0123] The power generation reward constraint is: Q buc <QXF ;

[0124] In the formula, Q XF The electricity reward for the electricity retail package users issued; the electricity reward given cannot exceed the electricity reward value issued

[0125] Reward Q with electricity consumption of electricity retail package users buc , the electricity retail package user electricity reward Q XF , the number of adjustments issued N G , user adjustment times n, issued sustainable adjustment time T G , the user can continuously adjust the time t, the cumulative power Q G and the user's accumulated power q as input, the user's power reward factor ψ j , j = 1, 2, 3, 4 are outputs, and a LSTM-based model for adjusting user power reward factors is constructed. Based on the LSTM algorithm training, the power reward factor given to adjust the user is expressed as:

[0126]

[0127] In the formula, ψ j Represents the power reward factor of the jth user.

[0128] S4: Based on the economic model of the adjustable user electricity retail package and the electricity quantity model of the adjustable user electricity retail package, a certain economic reward and electricity quantity reward are given to the user's actual adjustment ability, and an electricity retail package model that takes into account the user's adjustment ability is constructed. Based on the economic reward and electricity quantity reward, the original electricity retail package is adjusted, including basic fee adjustment and package included electricity quantity adjustment.

[0129] In a preferred embodiment, the electricity retail package model includes a basic fee adjustment model and a package included electricity adjustment model;

[0130] The basic cost adjustment model is expressed as:

[0131] P chenb =P taoc +P buc ;

[0132] The package includes the power adjustment model expressed as:

[0133] Q chenb =Q taoc +Q buc ;

[0134] Where P chenb P is the adjusted basic fee for electricity retail packages; taoc is the original electricity retail package basic fee, Pbuc Economic rewards for electricity retail package users based on their regulatory capabilities; Q chenb The electricity consumption included in the adjusted electricity retail package; Q taoc The original retail electricity package includes electricity consumption, Q buc It is an electricity reward given to users of electricity retail packages based on their regulation capabilities.

[0135] After the above steps, reasonable electricity retail packages can be formulated for adjustable users. According to the users' actual adjustment capabilities, certain economic and electricity rewards can be given to enhance users' enthusiasm for participating in electricity retail package activities.

[0136] like Figure 2 As shown, another embodiment of the present invention provides a system for formulating a power retail package considering the user's adjustment capability, based on the power retail package formulating method considering the user's adjustment capability as described above, including:

[0137] The integral model building module is used to build an electricity retail package integral model that takes into account the user's adjustment ability, including an electricity retail package adjustment times integral model, an electricity retail package sustainable adjustment time integral model, and an electricity retail package accumulated electricity integral model;

[0138] The economic model building module is used to build an LSTM-based economic model of the adjustable user's electricity retail package according to the number of times the adjustable user participates in the electricity retail package, the sustainable adjustment time and the accumulated electricity, and give the user economic rewards;

[0139] The power model building module is used to build an LSTM-based power retail package power model for adjustable users according to the number of times the adjustable users participate in the power retail package, the sustainable adjustment time and the accumulated power, and give users power rewards;

[0140] A package model building module is used to give economic rewards and electricity rewards to users' actual regulation capabilities based on the economic model of adjustable user electricity retail packages and the electricity model of adjustable user electricity retail packages, and to build an electricity retail package model that takes into account the user's regulation capabilities;

[0141] The package adjustment module is used to dynamically adjust the electricity retail package according to the electricity retail package model, including adjustment of basic fees and adjustment of the electricity included in the package.

[0142] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or other arbitrary combinations. When implemented using software, it can be implemented in whole or in part in the form of a computer program product, which includes one or more computer instructions. When loading and executing computer program instructions on a computer, the process or function according to the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0143] In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a disk or an optical disk, etc.

[0144] Therefore, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for formulating a power retail package that takes into account the user's adjustment capability as described above.

[0145] In summary, the present invention can comprehensively and accurately evaluate the user's regulation ability in the electricity retail package by introducing a multi-dimensional electricity retail package integral model (adjustment number integral model, sustainable adjustment time integral model, cumulative electricity integral model); the integral model of adjustment number, sustainable adjustment time and cumulative electricity can refine the regulation behavior of each user, thereby providing electricity retailers with quantitative user regulation data and accurately evaluating the user's regulation ability; through a comprehensive evaluation of user regulation behavior, electricity retailers can understand the regulation ability of each user in advance, optimize load scheduling, avoid over-reliance on the regulation behavior of a certain type of user, thereby improving the flexibility and stability of the entire power system.

[0146] LSTM can capture the long-term changes in user regulation behavior through time series prediction, thereby optimizing the issuance of economic rewards. Through the training of the LSTM model, power retailers can accurately predict the user's future regulation behavior based on the user's historical regulation data, and reasonably issue economic rewards based on the prediction results, avoiding excessive or insufficient reward expenditures, and improving the accuracy of economic rewards; using the regulation number deviation, sustainable regulation time deviation, and accumulated electricity deviation as constraints, optimize the economic incentive mechanism to ensure the sustainability and rationality of the reward mechanism. Power retailers can flexibly adjust economic rewards according to the regulation conditions of different users, thereby maximizing the regulation effect and balancing the reward cost and regulation benefits.

[0147] Through the LSTM-based power model, it is possible to predict the user's future power demand based on the user's regulation behavior, and issue corresponding power rewards based on their regulation capabilities and behaviors. It can ensure the rationality of rewards, avoid excessive rewards, and encourage users to actively participate in power regulation. Through accurate prediction and regulation of power, it can effectively reduce the fluctuation of power supply, especially during peak load periods. By encouraging users to participate in load regulation, it can reduce power waste, stabilize power supply, and improve the overall stability and efficiency of the power system.

[0148] Through the analysis results based on economic incentives and electricity incentives, power retailers can dynamically adjust users' electricity packages to make them more in line with users' actual needs and adjustment behaviors. For example, adjust the basic fee and the amount of electricity included in the package to ensure that users can receive corresponding compensation when participating in the adjustment, thereby increasing their motivation to participate. The adjustment of the package can effectively help power retailers balance their revenue and costs, improve the market competitiveness and profitability of power retailers through reasonable pricing and flexible electricity adjustment strategies, and at the same time ensure the interests of users.

[0149] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for formulating a power retail package taking into account user regulation capabilities, characterized in that: The method comprises: Construct an electricity retail package points model that takes into account the user's regulation ability, including an electricity retail package regulation times points model, an electricity retail package sustainable regulation time points model, and an electricity retail package accumulated electricity points model, which are used to give users corresponding electricity retail package points based on their actual regulation situations; According to the number of times the adjustable user participates in the adjustment in the electricity retail package, the sustainable adjustment time and the accumulated electricity, an LSTM-based adjustable user electricity retail package economic model is constructed to give economic rewards to the user; the adjustable user electricity retail package economic model aims to minimize the sum of the adjustment number deviation, the sustainable adjustment time deviation, the accumulated electricity deviation and the economic reward cost, and takes the adjustment number constraint, the sustainable adjustment time constraint, the accumulated electricity constraint and the issuance of economic reward constraint as constraint conditions, and trains the economic reward factor given to the adjustable user based on the LSTM algorithm; According to the number of times the adjustable user participates in the adjustment in the electricity retail package, the sustainable adjustment time and the accumulated electricity, an adjustable user electricity retail package electricity model based on LSTM is constructed to give the user electricity rewards; the adjustable user electricity retail package electricity model aims to minimize the sum of the adjustment number deviation, the sustainable adjustment time deviation, the accumulated electricity deviation and the electricity reward cost, and takes the adjustment number constraint, the sustainable adjustment time constraint, the accumulated electricity constraint and the power generation reward constraint as the constraint conditions, and trains the electricity reward factor given to the adjustable user based on the LSTM algorithm; According to the economic model of the adjustable user electricity retail package and the electricity quantity model of the adjustable user electricity retail package, economic rewards and electricity quantity rewards are given to the user's actual adjustment ability, and an electricity retail package model that takes into account the user's adjustment ability is constructed. According to the economic rewards and electricity quantity rewards, the original electricity retail package is adjusted, including basic fee adjustment and package included electricity quantity adjustment.

2. A method for formulating a power retail package considering user adjustment capability according to claim 1, characterized in that: The electricity retail package adjustment times integral model is expressed as: In the formula, F cishu is the number of adjustments of the electricity retail package; N1, N2, and N3 are the number of adjustments thresholds; k1, k2, and k3 are the integral coefficients corresponding to the number of adjustments thresholds; a is the unit integral; n is the number of user adjustments; The sustainable regulation time integral model of the electricity retail package is expressed as: In the formula, F shijian is the sustainable adjustment time integral of the electricity retail package; T1, T2, and T3 are sustainable adjustment time thresholds respectively; α1, α2, and α3 are the integral coefficients corresponding to the sustainable adjustment time respectively; t is the sustainable adjustment time of the user; The electricity retail package cumulative electricity points model is expressed as: In the formula, F dianliang is the accumulated electricity points of the electricity retail package; Q1, Q2, and Q3 are the accumulated electricity thresholds; β1, β2, and β3 are the integral coefficients corresponding to the accumulated electricity; q is the accumulated electricity of the user; Among them, the calculation formula of the cumulative power thresholds Q1, Q2, and Q3 is: Where △P(t) is the user's adjustment ability at time t.

3. A method for formulating a power retail package considering user adjustment capability according to claim 2, characterized in that: The electricity retail package points model also includes an additional points reward model, which is expressed as: F jiangli =θ·a,n≥N3,t≥T3,q≥Q3; In the formula, F jiangli is the extra bonus points; θ is the extra bonus points coefficient.

4. A method for formulating a power retail package considering user adjustment capability according to claim 1, characterized in that: The objective function of the economic model of the adjustable user electricity retail package is expressed as: minF piancp ; in, F piancp =|N G -n|+|T G -t|+|Q G -q|+P buc ; P buc =φ1·F cishu +φ2·F shijian +φ3·F dianliang +φ4·F jiangli ; In the formula, F piancp is the adjustment deviation of the economic model of the adjustable user electricity retail package; N G is the number of adjustments issued, n is the number of user adjustments; T G is the sustainable adjustment time issued, t is the sustainable adjustment time of the user; Q G is the cumulative power delivered, q is the cumulative power of the user; P buc is the economic reward for electricity retail package users; φ1, φ2, φ3, φ4 are the economic reward factors for users respectively; F cishu F is the number of electricity retail package adjustment points, shijian Sustainable adjustment of time credits for electricity retail packages, F dianliang Accumulate electricity points for electricity retail packages, F jiangli For extra bonus points; The specific constraints are: Adjustment times constraint: N min <n<N max ; Sustainable adjustable time constraint: T min <t<T max ; Cumulative power constraint: Q min <q<Q max ; Issue economic incentive constraints: P buc <P XF ; Where N min 、N max are the minimum and maximum adjustment times respectively; T min 、T max are the minimum and maximum sustainable adjustment time respectively; Q min , Q max are the minimum and maximum accumulated power respectively; P XF Provide financial incentives to users of electricity retail packages; The economic incentive P for electricity retail package users buc , the economic rewards P issued to electricity retail package users XF , the number of adjustments issued N G , user adjustment times n, issued sustainable adjustment time T G , the user can continuously adjust the time t, the cumulative power Q G and the user's accumulated power q as input, the user's economic reward factor φ i , i=1,2,3,4 are outputs, and a LSTM-based model for adjusting user economic reward factors is constructed The economic reward factor given to adjust the user based on LSTM algorithm training is expressed as: In the formula, φ i Represents the economic reward factor of the i-th user.

5. A method for formulating a power retail package considering user regulation capability according to claim 1, characterized in that: The objective function of the adjustable user electricity retail package electricity model is expressed as: minF piancq ; in, F piancq =|N G -n|+|T G -t|+|Q G -q|+Q buc ; Q buc =ψ1·F cishu +ψ2·F shijian +ψ3·F dianliang +ψ4·F jiangli ; In the formula, F piancq N is the adjustment deviation of the adjustable user electricity retail package electricity model; G is the number of adjustments issued, n is the number of user adjustments; T G is the sustainable adjustment time issued, t is the sustainable adjustment time of the user; Q G is the cumulative power delivered, q is the cumulative power of the user; Q buc is the electricity consumption reward for electricity retail package users; ψ1, ψ2, ψ3, and ψ4 are the user electricity consumption reward factors respectively; F cishu F is the number of electricity retail package adjustment points, shijian Sustainable adjustment of time credits for electricity retail packages, F dianliang Accumulate electricity points for electricity retail packages, F jiangli For extra bonus points; The model constraints are as follows: Adjustment times constraint: N min <n<N max ; Sustainable adjustable time constraint: T min <t<T max ; Cumulative power constraint: Q min <q<Q max ; The power generation reward constraint is: Q buc XF ;​ Where N min 、N max are the minimum and maximum adjustment times respectively; T min 、T max are the minimum and maximum sustainable adjustment time respectively; Q min , Q max are the minimum and maximum accumulated power respectively; Q XF Provide electricity consumption rewards to users of electricity retail packages; Reward Q with electricity consumption of electricity retail package users buc , the electricity retail package user electricity reward Q XF , the number of adjustments issued N G , user adjustment times n, issued sustainable adjustment time T G , the user can continuously adjust the time t, the cumulative power Q G and the user's accumulated power q as input, the user's power reward factor ψ j , j = 1, 2, 3, 4 are outputs, and a LSTM-based model for adjusting user power reward factors is constructed. Based on the LSTM algorithm training, the power reward factor given to adjust the user is expressed as: In the formula, ψ j Represents the power reward factor of the jth user.

6. A method for formulating a power retail package considering user regulation capability according to claim 1, characterized in that: The electricity retail package model includes a basic fee adjustment model and a package included electricity adjustment model; The basic cost adjustment model is expressed as: P chenb =P taoc +P buc ; The package includes a power adjustment model represented as follows: Q chenb =Q taoc +Q buc ; Where P chenb P is the adjusted basic fee for electricity retail packages; taoc is the original electricity retail package basic fee, P buc Economic rewards for electricity retail package users based on their regulatory capabilities; Q chenb The electricity consumption included in the adjusted electricity retail package; Q taoc The original retail electricity package includes electricity consumption, Q buc It is an electricity reward given to users of electricity retail packages based on their regulation capabilities.

7. A system for formulating a power retail package taking into account user regulation capabilities, based on a method for formulating a power retail package taking into account user regulation capabilities as claimed in any one of claims 1 to 6, characterized in that: The system comprises: The integral model building module is used to build an electricity retail package integral model that takes into account the user's adjustment ability, including an electricity retail package adjustment times integral model, an electricity retail package sustainable adjustment time integral model, and an electricity retail package accumulated electricity integral model; The economic model building module is used to build an LSTM-based economic model of the adjustable user's electricity retail package according to the number of times the adjustable user participates in the electricity retail package, the sustainable adjustment time and the accumulated electricity, and give the user economic rewards; The power model construction module is used to construct an LSTM-based adjustable user power retail package power model according to the number of times the adjustable user participates in the power retail package, the sustainable adjustment time and the accumulated power, and give the user power rewards; the package model construction module is used to give economic rewards and power rewards to the user's actual adjustment ability according to the adjustable user power retail package economic model and the adjustable user power retail package power model, and construct a power retail package model that takes into account the user's adjustment ability; The package adjustment module is used to adjust the original electricity retail package according to the electricity retail package model, including basic fee adjustment and package included electricity adjustment.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for formulating a power retail package taking into account user adjustment capabilities are implemented as described in any one of claims 1 to 6.

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