CN-116976923-B - User multidimensional finite physical energy consumption behavior model depiction and parameter identification method

CN116976923BCN 116976923 BCN116976923 BCN 116976923BCN-116976923-B

Abstract

The invention discloses a user multidimensional finite physical energy consumption behavior model description and parameter identification method, which comprises the steps of establishing a multi-dimensional energy consumption demand framework of an electric power user containing multi-dimensional demands, dividing an energy application terminal device corresponding to the multi-dimensional demands into a time sensitive type, a temperature sensitive type and an electric quantity sensitive type, respectively establishing physical characteristic models of the energy application terminal device, establishing a multi-dimensional front Jing Hanshu of the finite physical energy consumption of the user facing the multi-dimensional demands, determining setting methods of satisfaction reference points of various demands and declarative preferences of the user on the various electric demands, constructing a log likelihood function of personal preference coefficients in a risk coefficient, a loss aversion coefficient and a weight function of a cost function of the foreground function, identifying parameters of the foreground function, obtaining parameter distribution which accords with actual selection preferences of the user, and defining the finite physical energy consumption behavior model of the user. The invention can effectively describe the limited physical energy utilization decision-making behavior of the user in actual production and life.

Inventors

GAN LEI
YU KUN
CHEN XINGYING
CHEN YUJIANG
HU YANGYI
SHEN JUN
WANG BO
HUA HAOCHEN
MEI FEI

Assignees

河海大学

Dates

Publication Date: 20260508
Application Date: 20230227

Claims (8)

1. A method for describing and identifying parameters of a user multidimensional finite physical energy consumption behavior model is characterized by comprising the following steps: (1) Establishing a power user multi-energy consumption demand framework based on psychological account theory; (2) Dividing the energy application terminal equipment corresponding to the multiple demands into three types of time sensitivity type, temperature sensitivity type and electric quantity sensitivity type, and respectively establishing physical characteristic models of the energy application terminal equipment; (3) Constructing a multi-dimensional front Jing Hanshu of the user limited rational energy for multiple demands based on the accumulated prospect theory; (4) Based on historical load data and social investigation data, a setting method of various demand satisfaction reference points and declarative preference of users for various electricity demands are determined; (5) Constructing a user limited rational energy utilization decision probability model based on the mixed Logit model, and establishing a log likelihood function of a risk coefficient, a loss aversion coefficient and a personal preference coefficient in a cost function of a foreground function; (6) Identifying parameters of the foreground function by adopting a maximum simulation likelihood estimation method to obtain parameter distribution which accords with actual selection preference of a user, and determining a limited physical energy consumption behavior model of the user; the step (2) comprises the following steps: (2.1) modeling physical characteristics of a time-sensitive device; For time-sensitive devices The electric cooker mainly comprises an electric cooker, a dish washer, a washing machine, a dust collector and a water heater, wherein the electricity consumption model is represented by the following formula: in the formula, Is a device The electricity consumption of one day; For the device in the period Is a power of (2); A start-stop state of the equipment in the period; And Respectively devices An upper limit and a lower limit of the movable time range; construction of resident user-to-device using time offset ratio of device The comfort level of use of (a) is as follows: in the formula, Is a comfort value; And The use time is the use time after the equipment is initialized and transferred respectively; (2.2) modeling physical characteristics of the temperature sensitive device; The temperature sensitive equipment comprises an air conditioner and a refrigerator, and a load power model is built by using a thermodynamic equivalent model: in the formula, And Respectively is The indoor temperature and the outdoor temperature at the moment, ; Is the equivalent heat capacity of the temperature sensitive device, ; For the equivalent thermal resistance, ; For the cooling/heating power of the device, Refrigerating/heating power and electric power for equipment The method can meet the certain proportion relation, , Is an energy efficiency ratio; the method is characterized in that the method is used for indicating the switching state of equipment, wherein the value is 0 during shutdown and 1 during startup; representing a simulation step size; And Upper and lower bounds representing the indoor temperature; (2.3) modeling physical characteristics of the power sensitive device; The electric quantity sensitive equipment mainly comprises an electric automobile, a mobile phone and a computer, wherein a load power model is represented by the following formula: in the formula, The state of charge of the power sensitive device at the moment t; the charging power of the equipment at the time t; e is the rated capacity of the battery of the equipment; Maximum charging power for the device; 、 the maximum state of charge and the minimum state of charge of the device, respectively.
2. The method for describing and identifying parameters of a user multidimensional finite physical energy consumption behavior model according to claim 1, wherein the step (1) is specifically as follows: (1.1) establishing a basic layer part of a multi-energy-consumption demand framework of an electric power user, wherein the basic layer framework comprises food demands, temperature demands, sanitary demands, lighting demands, travel demands and entertainment/work demands, and the demands belong to different physical accounts and are mutually independent; (1.2) establishing an upper layer part of a multi-energy consumption requirement framework of the power consumer, wherein the upper layer framework comprises social requirements and electricity consumption cost requirements, and the social requirements comprise public psychology and environmental protection awareness.
3. The method for describing and identifying parameters of a user multidimensional finite physical energy consumption behavior model according to claim 1, wherein the step (3) is specifically: (3.1) calculating a foreground theoretical cost function according to the following formula: in the formula, And A cost function representing the positive correlation and the negative correlation respectively; Attribute index values for satisfying the multi-dimensional demand electricity satisfaction of users; is the corresponding reference point; And Risk preference coefficients and risk avoidance coefficients, respectively; the sensitivity coefficient of the decision maker to loss and gain; is an index weight; (3.2) calculating a weight function based on the accumulated foreground theory; Assume that a certain attribute of a certain requirement of a user has a result The corresponding probability is Wherein Representing the loss of the product, Representative obtained, the weight function is as follows: in the formula, Is an initial weight function; As a cumulative weight function; risk attitude coefficients for decision makers to treat returns and losses; (3.3) any power usage scheme for multi-dimensional power usage requirements, the prospect functions are as follows: in the formula, For electricity use scheme Is a comprehensive prospect value of (1); is a parameter vector for each attribute; Is an index weight vector; And Respectively is the scheme Vector of each index value and corresponding probability; Is a reference point vector; Determining terms in a foreground function; is an error term.
4. The method for describing and identifying parameters of a user multidimensional finite physical energy consumption behavior model according to claim 1, wherein the step (4) is specifically: Calculating the cost and comfort index value and the corresponding probability of each power consumption mode of the user by combining the historical load data of various power consumption devices of the user and respectively using vectors And Meanwhile, decision reference points facing to various production and living demands are reasonably set according to the initial electricity utilization mode of a user, wherein the decision reference points comprise cost and electricity utilization comfort level, and vectors are used And (3) representing.
5. The method for describing and identifying parameters of a consumer behavior model of multi-dimensional finite physical energy of a user according to claim 1, wherein the consumer finite physical energy decision probability model constructed based on the hybrid logic model in the step (5) is as follows: in the formula, For users Selection scheme Probability of (2); the method comprises the steps of collecting all parameters to be estimated; Probability density function as a parameter; Unknown characteristic parameters of the parameter probability density function; The number of the schemes is; Is the scheme For the user A determined portion of the foreground values.
6. The method for describing and identifying parameters of a user multidimensional finite physical energy consumption behavior model according to claim 1, wherein the step (6) is specifically: (6.1) for a container comprising A data set of individual users whose log likelihood functions are: in the formula, Is the number of users; The number of decision scenes; The number of the schemes is; Representing a decision result matrix of the user; Representing a user In a scene Decision making is performed below, and If the user selects a scheme Then expression A value of 1, otherwise 0; (6.2) calculating simulation probability, at given point From probability density functions by Latin hypercube sampling A random vector is extracted and recorded as As preference parameters of the user 1, calculating a simulation probability value of the user 1 selecting an arbitrary scheme, and repeating the above operations Secondary times; (6.3) solving for optimum using genetic algorithm And (3) the value is a maximum value of the simulated maximum likelihood operator, and a multidimensional pre-Jing Hanshu parameter used for etching the consumption behavior of the limited physical energy source is defined.
7. A computer storage medium having stored thereon a computer program which, when executed by a processor, implements a method of user multidimensional finite energy consumption model characterization and parameter identification as claimed in any of claims 1 to 6.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements a method of user multidimensional finite energy consumption model characterization and parameter identification as claimed in any one of claims 1 to 6 when the computer program is executed.

Description

User multidimensional finite physical energy consumption behavior model depiction and parameter identification method Technical Field The invention relates to a modeling method for describing energy consumption using behaviors at a demand side, in particular to a method for describing a user multidimensional limited physical energy consumption behavior model and identifying parameters. Background Along with the rapid growth of the demand side resources and the development of measurement and control technologies, the demand side resources become important flexibility adjusting resources of the novel energy resource hospital system in the future. However, energy users have limited cognitive ability, mental power, decision computing power, and subjective preferences in addition to user decisions, resulting in situations where there is limited rationality in their energy use behavior. At present, most of the research based on the assumption of traditional classical economics "aims at describing the energy consumption behavior with the lowest energy cost or highest utility, but in general, such simple idealized description of the energy consumption behavior cannot correctly describe and explain the influence of multiple, time-varying and interrelated factors on the user behavior, resulting in modeling results which are inconsistent with reality, load regulation capability or flexibility and evaluation of optimism. Therefore, it is necessary to introduce a behavioral economics theory with limited rationality 'natural people' as a basic assumption, reasonably describe the consumption behavior of limited physical energy of users from the multi-energy demand of actual users, and provide basic theoretical basis and technical method support for the research on market mechanisms such as energy retail, end-to-end transaction, demand response and the like, and the aspects such as flexible resource assessment and regulation operation on the demand side of the power system. Disclosure of Invention The invention aims to provide the method for describing the user multidimensional finite physical energy consumption behavior model and the parameter identification, so that the user finite physical energy consumption behavior model and the parameter identification can be truly and reasonably described. The technical scheme is that the method for describing the user multidimensional finite physical energy consumption behavior model and identifying the parameters comprises the following steps: (1) And establishing a power user multi-energy consumption demand framework based on psychological account theory. (2) And dividing the energy utilization terminal equipment corresponding to the multiple demands into three types of time sensitivity, temperature sensitivity and electric quantity sensitivity, and respectively establishing physical characteristic models of the energy utilization terminal equipment. (3) And constructing a multi-dimensional front Jing Hanshu of the user limited rational energy for the multiple demands based on the accumulated prospect theory. (4) Based on the historical load data and the social investigation data, a setting method of various demand satisfaction reference points and the declarative preference of users for various electricity demands are determined. (5) Based on the mixed Logit model, constructing a user finite rational energy use decision probability model, and establishing a log likelihood function of a risk coefficient, a loss aversion coefficient and a personal preference coefficient in a cost function of a foreground function. (6) And identifying parameters of the foreground function by adopting a maximum simulation likelihood estimation method to obtain parameter distribution which accords with actual selection preference of a user, and determining a limited physical energy consumption behavior model of the user. The step (1) specifically comprises the following steps: (1.1) establish the basic unit of the multiple energy consumption demand framework of electric power user, basic unit includes food demand (corresponding to the use demand of equipment such as electromagnetism stove, refrigerator, rice cooker, etc.), temperature demand (corresponding to the use demand of equipment such as air conditioner, electric fan heater, etc.), health demand (corresponding to the power demand of equipment such as washing machine, dust catcher, hairdryer, etc.), illumination demand (corresponding to the power demand of lamp), trip demand (corresponding to the charge demand of electric automobile, storage battery car), amusement/work demand (corresponding to the power demand of equipment such as computer, cell-phone, TV, treadmill, etc.), each demand belongs to different physical accounts, mutually independent. (1.2) Establishing an upper layer part of a multi-energy consumption requirement framework of the electric power user, wherein the upper layer framework comprises social requirements and electricity c