CN114048976B - Variable frequency air conditioner load regulation and control method considering multiple response potential influence factors - Google Patents
Variable frequency air conditioner load regulation and control method considering multiple response potential influence factors Download PDFInfo
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Abstract
The invention relates to a variable frequency air conditioner load regulation and control method considering multiple response potential influence factors, which comprises the following steps: acquiring the demand response potential of the variable frequency air conditioner in the district of the distribution network according to the variable frequency air conditioner response potential evaluation model; according to the demand response potential of the variable-frequency air conditioner, acquiring the target power of the variable-frequency air conditioner through a day-ahead scheduling model; clustering the variable frequency air conditioners in the district of the distribution network to obtain a plurality of aggregation groups; and according to the target power of the variable frequency air conditioner, grouping temperature control is carried out on the variable frequency air conditioner clusters in the district of the distribution network by taking the aggregation group as a unit through a joint scheduling model. Compared with the prior art, the invention comprehensively guides the variable-frequency air conditioner to participate in the power system demand response resource to play the role of peak clipping and valley filling in the power system, and has low control difficulty, high efficiency and high accuracy.
Description
Technical Field
The invention relates to the technical field of smart grids, in particular to a variable-frequency air conditioner load regulation and control method considering multiple response potential influence factors.
Background
In recent years, with the continuous increase of economic development and living standard of people, the air conditioner load is increased, the peak load ratio of the air conditioner in an economically developed area exceeds 50 percent and rises year by year, so that the air conditioner becomes an important factor influencing the peak-valley difference of a system, meanwhile, the standby capacity requirement is obviously increased after large-scale intermittent energy power generation is accessed, and the characteristics of strong controllability, great scheduling potential and the like are considered in consideration of the air conditioner load, so that the air conditioner load can be polymerized by a load aggregator to participate in the power balance control of the system, and the air conditioner load plays a great role in peak clipping and valley filling, system maintenance stability, auxiliary service provision and the like. As the market share of the variable-frequency air conditioner gradually rises from 57.9% in 2014 to 77.3% in 2019, the demand of the variable-frequency air conditioner for fully exploiting the response potential is increasingly urgent when the variable-frequency air conditioner is researched and developed according to the regulation scheme participating in the response of the demand side, but the whole regulation research of the existing variable-frequency air conditioner is less, and the part of increasingly-increased response resources are difficult to be guided to play the peak clipping and valley filling roles in the power system.
At present, students at home and abroad have conducted intensive research on the excavation and utilization of the load response potential of large-scale air conditioners. The method comprises the steps that a learner establishes an air conditioner comprehensive control model for factors such as class periodic temperature change, user participation demand side response will, power grid side scheduling demand compliance and the like, the schedulable potential is mined, the learner comprehensively considers the user response will to establish a central air conditioner control strategy based on an elastic temperature adjustable margin, the best profit of an aggregator is realized, the learner groups air conditioner operation states according to a state queue model, and the temperature interval is used for setting start-stop conversion temperature to control the air conditioner operation state change. The research has achieved great achievements in the aspect of large-scale air conditioner load regulation, but has two more remarkable problems, namely, the fixed-frequency air conditioner is taken as an object, and the research achievements are difficult to directly apply in the high-duty ratio variable-frequency air conditioner access scene due to obvious difference between the running modes of the variable-frequency air conditioner and the fixed-frequency air conditioner.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide the variable-frequency air conditioner load regulation and control method considering the influence factors of multiple response potentials, which comprehensively guides the variable-frequency air conditioner to participate in the peak clipping and valley filling actions of power system demand response resources in the power system, and has the advantages of low control difficulty, high efficiency and high accuracy.
The aim of the invention can be achieved by the following technical scheme:
A variable frequency air conditioner load regulation and control method considering multiple response potential influence factors comprises the following steps:
acquiring the demand response potential of the variable frequency air conditioner in the district of the distribution network according to the variable frequency air conditioner response potential evaluation model;
according to the demand response potential of the variable-frequency air conditioner, acquiring the target power of the variable-frequency air conditioner through a day-ahead scheduling model;
Clustering the variable frequency air conditioners in the district of the distribution network to obtain a plurality of aggregation groups;
according to the target power of the variable frequency air conditioner, grouping temperature control is carried out on the variable frequency air conditioner clusters in the district of the distribution network by taking the aggregation group as a unit through a joint scheduling model;
The invention provides a variable frequency air conditioner load regulation and control method, which adopts a three-layer regulation and control framework comprising a potential evaluation layer, a day-ahead scheduling layer and a day-ahead control layer, analyzes and researches response potential, a scheduling model and a control strategy of a variable frequency air conditioner to comprehensively guide the variable frequency air conditioner to participate in power system demand response, acquires the variable frequency air conditioner demand response potential through the variable frequency air conditioner response potential evaluation model in the potential evaluation layer, acquires variable frequency air conditioner target power through the day-ahead scheduling layer and considers the variable frequency air conditioner aggregation response potential in day-ahead economic optimal scheduling of a distribution network, maximally utilizes the potential, exerts the economic value, has complicated process and large workload if different brands and models of variable frequency air conditioners are respectively modeled, and performs grouping temperature control on variable frequency air conditioner clusters in the distribution network region through a joint scheduling model in the day-ahead control layer, so that the air conditioner load follows the scheduling plan, greatly improves the working efficiency and reduces the control difficulty.
Further, the expression of the variable frequency air conditioner response potential evaluation model is as follows:
wherein A i is the thermal conductivity of room i, For the energy efficiency ratio of the variable frequency air conditioner of the room i, the theta a is the outdoor temperature,Is the temperature set value of the variable frequency air conditioner in room i, N 1 is the number of the end users of the variable frequency air conditioner, P BPagg is the aggregate power of the variable frequency air conditioner, ζ is the user controllability,An upper limit for the temperature adjustable margin;
and obtaining the current large-scale variable frequency air conditioner load aggregate power according to the outdoor temperature at the current moment and the variable frequency air conditioner temperature set value of the room by a calculation formula of the variable frequency air conditioner aggregate power.
Further, the calculation formula of the upper limit of the temperature adjustable margin is as follows:
wherein mu i,t is a user willingness degree influence factor of the ith variable frequency air conditioner terminal user at the moment t, AndThe upper limit and the lower limit of the initial adjustable margin of the indoor temperature of the ith variable frequency air conditioner user at the moment t are respectively set.
Further, the calculation formula of the user willingness degree influence factor is as follows:
Wherein, p base is the expected electricity price of the user, p real is the current electricity price, p max is the highest electricity price, mu i,t is the user willingness factor of the ith variable-frequency air conditioner terminal user at the moment t, E is the education level of the user, I is the household income of the user, A is the average age of the user, a 1、a2、a3、a4、ω1、ω2、ω3 and omega 4 are set values, and a 1≤a2≤a3≤1,0≤a4 is more than or equal to 0 and less than or equal to 1;
When the current electricity price is higher than the expected electricity price of the user, the electricity cost is higher than the psychological expected electricity cost of the user, the user hopefully receives the instruction of the dispatching center to participate in the demand response to obtain subsidies, the electricity cost is reduced, the requirement on the thermal comfort degree is reduced, the indoor temperature adjustable margin is increased, otherwise, the user is more careful about the thermal comfort degree, the possibility of receiving participation in the demand response is lower, the indoor temperature adjustable margin is relatively reduced, in addition, the receiving degree of the user on the demand response is related to household income, education degree and age of the user, so that a user receiving degree model is established, the willingness degree of the user to accept the demand response control is described, and the accuracy is high.
Further, the calculating process of the initial adjustable margin of the indoor temperature comprises the following steps:
Constructing a predicted average ballot number index PMV for describing the thermal comfort degree through Franker thermal comfort degree equation;
The relation expression of the PMV value I PMV and the indoor temperature theta is obtained, and specifically:
and determining an initial adjustable margin of the indoor temperature of the constant-frequency air conditioner according to the set threshold value of the I PMV.
Further, the expression of the day-ahead scheduling model is:
wherein N 2 is the number of schedulable units, T is the total time period number of scheduling periods, C Gj is the power generation cost of the unit j in the time period T, For the output of the unit j in the period t, F BPAC is the load scheduling cost of the variable frequency air conditioner, and F sh、Fcut and F tr are respectively translatable, reducible and transferable load scheduling cost;
among the multiple types of loads, the basic load has extremely strict requirements on electricity utilization time and power, is almost rigid, and mainly considers flexible loads such as translatable loads, reducible loads and transferable loads as scheduling resources.
Further, constraint conditions of the day-ahead scheduling model comprise active power balance constraint, conventional unit output constraint, conventional unit climbing constraint and variable-frequency air conditioner aggregate power constraint;
the active power balance constraint is as follows:
wherein, AndBase load, air-conditioning load, translatable load power, reducible load power and translatable load power at time t respectively;
The conventional unit output constraint is as follows:
Wherein, P Gjmin and P Gjmax are respectively the lower limit and the upper limit of the output of the unit j;
the climbing constraint of the conventional unit is as follows:
wherein, D Rj and U Rj are respectively the maximum descending speed and the maximum ascending speed of the unit j in unit time, and Deltat is the climbing time;
the frequency conversion air conditioner aggregate power constraint is as follows:
wherein, AndThe lower limit and the upper limit of the air conditioner load at the time t are respectively set.
Further, the process of clustering the variable frequency air conditioners in the distribution network district comprises the following steps:
taking steady-state parameters and temperature change parameters of the variable-frequency air conditioner as characteristic attributes, adopting a K-means clustering algorithm, and clustering a large number of variable-frequency air conditioners into different aggregation subgroups according to the principle that the steady-state parameters and the temperature change parameters of the variable-frequency air conditioner are similar;
wherein the steady-state parameters of the variable frequency air conditioner are as follows A is the heat conductivity coefficient of a room, eta 2 is the energy efficiency ratio of the variable frequency air conditioner, the temperature change parameter is RxC, R is the equivalent heat resistance of the room, and C is the equivalent heat capacity of the room.
Further, the expression of the joint scheduling model is:
wherein, Is the actual load of the variable-frequency air conditioner of the ith group,For the target power at time t, count i is the number of air conditioners in the ith aggregation group,Respectively the temperature set value, the initial temperature set value, the upper temperature limit and the indoor temperature of the room where the i-th group of variable-frequency air conditioners are positioned at the moment t,The outdoor temperature is set to be the time t,AndThe transition period power and the initial power of the i-th group variable frequency air conditioner are respectively.
Furthermore, the combined scheduling model is solved through a particle swarm algorithm, and the control effect is stable and accurate.
Compared with the prior art, the invention has the following beneficial effects:
(1) According to the invention, a three-layer regulation and control framework is adopted, the three-layer regulation and control framework comprises a potential evaluation layer, a day-ahead dispatching layer and a day-ahead control layer, response potential, a dispatching model and a control strategy of the variable-frequency air conditioner are analyzed and researched, so that the variable-frequency air conditioner is comprehensively guided to participate in the peak clipping and valley filling functions of power system demand response resources in the power system, the variable-frequency air conditioner demand response potential is obtained through the variable-frequency air conditioner response potential evaluation model in the potential evaluation layer, the variable-frequency air conditioner target power is obtained through the day-ahead dispatching layer, the variable-frequency air conditioner aggregation response potential is considered in day-ahead economic optimal dispatching of a distribution network, the economic value of the variable-frequency air conditioner is exerted to the maximum extent, if the variable-frequency air conditioner brands and models of different users in the distribution network jurisdiction are different, the process is complicated and the workload is large, and the variable-frequency air conditioner clusters in the distribution network jurisdiction are subjected to grouping temperature control through the joint dispatching model in the day-ahead control layer, so that the air conditioner load follows the dispatching plan is greatly improved, and the control difficulty is reduced;
(2) According to the invention, the load aggregate power of the current large-scale variable frequency air conditioner can be obtained according to the outdoor temperature at the current moment and the temperature set value of the variable frequency air conditioner in the room by a calculation formula of the aggregate power of the variable frequency air conditioner, so that the calculated amount of a dispatching center is greatly reduced;
(3) The user willingness influence factor considers the influence of the current electricity price on the user willingness, when the current electricity price is higher than the user expected electricity price, the electricity cost is higher than the user psychological expected electricity cost, the user hopefully accepts the scheduling center to instruct the participation demand response to acquire the subsidy, the electricity cost is reduced, the thermal comfort requirement is reduced, the indoor temperature adjustable margin is increased, otherwise, the user is more conscious of the thermal comfort level, the possibility of accepting the participation demand response is lower, the indoor temperature adjustable margin is relatively reduced, and the evaluation accuracy is improved;
(4) According to the invention, the particle swarm algorithm is used for solving the joint scheduling model, so that the control effect is stable and accurate.
Drawings
FIG. 1 is a three-layer regulation structure diagram of a variable frequency air conditioner;
FIG. 2 is a diagram of the operation state of the variable frequency air conditioner;
FIG. 3 is a response potential schematic;
FIG. 4 is a schematic illustration of user thermal comfort;
FIG. 5 is a graph of aggregate power versus time for a typical day variable frequency air conditioner in summer;
FIG. 6 is a graph of user willingness versus time;
FIG. 7 is a schematic diagram of an air conditioner temperature elastic adjustable section;
FIG. 8 is a schematic diagram of response potential of a variable frequency air conditioner in each period;
FIG. 9 is a schematic diagram of the load distribution before scheduling;
FIG. 10 is a schematic diagram of the load distribution after scenario 1 scheduling;
FIG. 11 is a schematic diagram of a variable frequency air conditioner load scheduling plan;
fig. 12 is a schematic diagram of a control result of the variable frequency air conditioner.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
A variable frequency air conditioner load regulation and control method considering multiple response potential influence factors comprises the following steps:
acquiring the demand response potential of the variable frequency air conditioner in the district of the distribution network according to the variable frequency air conditioner response potential evaluation model;
according to the demand response potential of the variable-frequency air conditioner, acquiring the target power of the variable-frequency air conditioner through a day-ahead scheduling model;
Clustering the variable frequency air conditioners in the district of the distribution network to obtain a plurality of aggregation groups;
according to the target power of the variable frequency air conditioner, grouping temperature control is carried out on the variable frequency air conditioner clusters in the district of the distribution network by taking the aggregation group as a unit through a joint scheduling model;
As shown in fig. 1, the invention provides a variable frequency air conditioner load regulation and control method, which adopts a three-layer regulation and control framework comprising a potential evaluation layer, a day-ahead dispatching layer and a day-ahead control layer, analyzes and researches on response potential, a dispatching model and a control strategy of a variable frequency air conditioner to comprehensively guide the variable frequency air conditioner to participate in power system demand response, acquires the variable frequency air conditioner demand response potential through the variable frequency air conditioner response potential evaluation model in the potential evaluation layer, acquires variable frequency air conditioner target power through the day-ahead dispatching layer, considers the variable frequency air conditioner aggregate response potential in the day-ahead economic optimal dispatching of a distribution network, maximally utilizes the potential, exerts the economic value, has the difference between brands and models of variable frequency air conditioners installed by different users in the distribution network jurisdiction, has complicated process and large workload if the variable frequency air conditioners are modeled respectively, and performs grouping temperature control on the variable frequency air conditioner clusters in the distribution network jurisdiction through a joint dispatching model in the day-ahead dispatching layer, so that the air conditioner load follows the dispatching plan, the working efficiency is greatly improved, and the control difficulty is reduced.
The variable frequency air conditioner basic model can be divided into a steady-state model and a dynamic model;
during steady state, the indoor temperature is kept unchanged and equal to the air conditioner temperature set value, and the steady state power P BP of the variable frequency air conditioner is as follows:
PBP＝(θa-θset)A/η2
Wherein, theta a is the outdoor temperature, theta set is the air conditioner temperature set value, A is the room heat conduction coefficient, eta 2 is the energy efficiency ratio of the variable frequency air conditioner;
when in dynamic state, namely the temperature set value of the variable frequency air conditioner changes, the indoor temperature is transited to a new set value and is kept in a new steady state again, and the dynamic power and the indoor temperature change conditions in the transition period are as follows:
Wherein P trans is the dynamic power of the transition period, k is the power change coefficient, k is proportional to the temperature change amount, when the set temperature rises, k is less than 0, otherwise k is more than 0, R is the room equivalent thermal resistance, the unit is ℃/kW, C is the room equivalent heat capacity, the unit is kW.h/DEGC, and k is taken as a constant to be 0.15 when the temperature set value up-regulating operation is carried out in view of model simplification;
The temperature set point is adjusted up from 26 ℃ to 27 ℃ at 20 minutes of operation, and as shown in fig. 2, the running state of the variable frequency air conditioner can be obtained by a steady-state model and a dynamic model of the variable frequency air conditioner.
Considering that after a general user starts the variable frequency air conditioner to set the temperature to be in line with the temperature range of the comfort level of the user, the temperature of the air conditioner is repeatedly adjusted less, and even if a small number of users adjust the temperature set value, the temperature range of the air conditioner is not too large, so that the variable frequency air conditioner can be approximately considered to be operated in a steady state operation state more, the polymerization power of the variable frequency air conditioner can be approximately calculated by using the steady state power of the single variable frequency air conditioner, and the polymerization power of the variable frequency air conditioner is as follows:
Wherein P BPagg is the aggregate power of the variable frequency air conditioner, A i is the heat conductivity coefficient of room i, For the energy efficiency ratio of the variable frequency air conditioner of the room i, the theta a is the outdoor temperature,For the temperature set value of the variable frequency air conditioner in the room i, N 1 is the number of variable frequency air conditioner terminal users (the number of the variable frequency air conditioner terminal users, the number of the rooms and the number of the variable frequency air conditioner terminal are equal), and in consideration of the condition that the workload is overlarge when the actual air conditioner parameters are collected, A i, the temperature set value of the variable frequency air conditioner is generated in batches according to a uniform distribution rule in a reasonable numerical range by a Monte Carlo method,And
Further from the perspective of simplified calculation, the calculated expected values of all parameters of the variable frequency air conditioner can be adopted to calculate the aggregate power of the variable frequency air conditioner, so that the aggregate power model of the variable frequency air conditioner is as follows:
and obtaining the current large-scale variable frequency air conditioner load aggregate power according to the outdoor temperature at the current moment and the variable frequency air conditioner temperature set value of the room by a calculation formula of the variable frequency air conditioner aggregate power.
After the aggregate power of the variable-frequency air conditioner is obtained, a variable-frequency air conditioner response potential evaluation model under the action of multiple response potential influence factors is established on the basis of the aggregate power, and the maximum demand response potential which can be achieved by the variable-frequency air conditioner cluster under the demand response event is analyzed. Firstly, considering the influence of user thermal comfort on response potential, taking a temperature interval which best meets the user thermal comfort requirement as an initial adjustable margin of the indoor temperature of a user of the variable-frequency air conditioner, introducing a user willingness degree model on the basis, analyzing the influence of multiple factors such as electricity price information, household income, education degree, age distribution and the like on the response willingness degree of the user participation requirement, and finally, calculating the response potential, considering the influence of the user controllability degree, namely the user duty ratio of the user actually provided with terminal control equipment, wherein the response potential analysis process is shown in figure 3.
User thermal comfort: by adopting an international Franker thermal comfort equation, a predicted average vote number (PREDICTED MEAN vot, PMV) index is constructed to approximately estimate the thermal comfort, the influence of indoor temperature on human comfort is quantified, the relation between a PMV value and human feel is shown as a figure 4, the smaller the PMV value is, the higher the user comfort is represented, and when other conditions are at a comfort level, the theta relation between the PMV value and the temperature is obtained as follows:
The initial adjustable margin of the indoor temperature of the constant-frequency air conditioner is determined according to the set threshold value of I PMV, the PMV value is minimum at 26 ℃, the comfort level is highest, the user is in the optimal comfort level state when the PMV value is between minus 0.5 and 0.5 according to the ISO7730 standard, the corresponding indoor temperature is 24.8-27.3 ℃, and the initial adjustable margin of the indoor temperature of the variable-frequency air conditioner user can be used.
User willingness degree: defining a user expected electricity price p base, if the current electricity price p real is higher than p base, showing that the electricity cost is higher than the user psychological expectation at this time, the user prefers to acquire subsidies through participation demand response, the electricity cost is reduced, the requirement on thermal comfort level can be properly reduced, the temperature adjustable margin is increased, otherwise, the user prefers to have a thermal comfort level, the participation demand response will is lower, the temperature adjustable margin is relatively reduced, the user willingness is seen to be mainly embodied in the sensitivity degree of the user to the electricity price, the sensitivity degree of the user to the electricity price is related to factors such as household income, education degree, age of the user and the like, and the influence of the factors is respectively influenced by the education level by the userHousehold income influence coefficientMean age influence coefficientTo express, the three determine the subjective response coefficient togetherReflecting the sensitivity degree of the user response willingness to the electricity price:
Defining a user willingness degree influence factor representing the user willingness degree:
The method comprises the steps of enabling mu i,t to be a user willingness influence factor of an ith variable-frequency air conditioner terminal user at t moment, enabling p base to be an expected electricity price of the user, enabling p real to be a current electricity price, enabling p max to be a highest electricity price, enabling mu i,t to be the user willingness influence factor of the ith variable-frequency air conditioner terminal user at t moment, enabling E to be an education level of the user, enabling I to be household income of the user, enabling A to be average age of the user family, enabling a 1、a2、a3、a4、ω1、ω2、ω3 and omega 4 to be set values, enabling 0 to be less than or equal to a 1≤a2≤a3≤1,0≤a4≤1,ω1、ω2、ω3 to be increased gradually from low to high, and enabling omega 4 to be a threshold value of influence of the user willingness by household income.
When mu i,t is positive, the user is positive response willingness; when mu i,t is negative, the user responds to the willingness negatively, and the numerical value reflects the strength of the willingness.
The user participation demand response will change along with the change of external conditions, namely the adjustable margin of the indoor temperature set value where the variable frequency air conditioner terminal is positioned dynamically changes on the basis of the initial adjustable margin of the indoor temperature which meets the user thermal comfort. In the cooling mode, regulation parameters are defined:
Wherein delta theta i,t is the temperature margin adjustment quantity of the ith variable frequency air conditioner terminal at the moment t caused by the wish of a user, AndThe upper limit and the lower limit of the initial adjustable margin of the indoor temperature of the ith variable frequency air conditioner user at the moment t are respectively,AndThe magnitude of Δθ i,t is proportional to the value of the user willingness-affecting factor μ i,t, respectively the upper and lower limits of the temperature-adjustable margin for consideration of the user willingness.
User controllability: the 2009 PG & E company SmartAC controls the air conditioning load under four distribution feeders, evaluates its potential to participate in auxiliary services, and results the display: the controllability of two feeder lines reaches 80%, the controllability of the other two feeder lines is close to 60%, although the actual implementation demand response projects of China are fewer, the proportion of users with terminal control equipment is relatively lower, the intelligent power grid construction and the rapid development of intelligent Internet of things technology in the last ten years provide technical support for the participation of the load side in demand response, the proportion of the variable-frequency air conditioner which is a new-generation product and is provided with intelligent control terminals is higher, and the current variable-frequency user controllability zeta can be reasonably assumed to be 60%.
Combining a variable frequency air conditioner aggregate power model, knowing that the basic parameters and the outdoor temperature are related, the variable frequency air conditioner aggregate operation power is only related to the variable frequency air conditioner temperature set value, the maximum load reduction capacity of the variable frequency air conditioner can be deduced and obtained by obtaining the user adjustable temperature upper limit, and when the air conditioner initial temperature set value is theta set,i in the period of t, the variable frequency air conditioner aggregate powerThe adjustable interval of (2) is as follows:
And The lower limit and the upper limit of the adjustable interval of the aggregation power of the variable frequency air conditioner are respectively, and at the moment, the aggregation response potential of the variable frequency air conditioner is the initial aggregation power of the variable frequency air conditionerLower limit of adjustable section of aggregation power of variable frequency air conditionerThe difference value between the two is expressed as the following expression of a response potential evaluation model of the variable frequency air conditioner:
after the aggregate power and response potential of the variable-frequency air conditioner are obtained, a large number of variable-frequency air conditioner loads exist in an actual power grid, and meanwhile, flexible loads with considerable scales exist and can be used by a dispatching center. For this, a day-ahead scheduling model which comprehensively considers the load aggregation response potential and the flexible load response characteristic of the variable-frequency air conditioner is established, and the potential of the cooperative participation of the multi-type load-side resources in the system regulation is fully excavated to exert the economic value.
Among the multiple types of loads, the basic load has extremely strict requirements on electricity utilization time and power, is almost rigid, and mainly considers flexible loads such as translatable loads, reducible loads and transferable loads as scheduling resources.
The translatable load allows the load power consumption period to be wholly translated to other time periods, the power consumption period before translation of a translatable load L sh is [ t 1,t2 ], the starting time after translation is represented as t sh, the acceptable period after translation is [ t sh-,tsh+ ], and the period after translation of the load can be represented as [ t sh,tsh+t2-t1 ]. Let 0-1 variable α t denote the translational state of L sh in the t period, α t =0 denote no response to the translation, α t =1 denote response to the translation, and the scheduling cost F sh of the translatable load is:
Wherein F is sh
c For the scheduling cost of load unit power translation, P t sh is the power translated for the t period.
The load can be reduced by a certain proportion according to the power supply adequacy of a certain period, the power of the load L cut in the period t is P t cut, the reduction state is represented by a 0-1 variable gamma t, gamma t =0 represents no response reduction, gamma t =1 represents response reduction, and the scheduling cost F cut for reducing the load is:
Wherein F c cut is the scheduling cost of unit power reduction, The power is predicted for the time period before day t,The power after the period t is cut down.
The response characteristic of the transferable load is more flexible than that of the translatable load, the power of each period can be reasonably adjusted under the condition of ensuring that the total power of the transferable load is unchanged, the operation period before transferring a certain transferable load L tr is [ t 3,t4 ], the acceptable period after transferring is [ t tr-,ttr+ ], the transferring state of the load in the t period is represented by a 0-1 variable beta τ, beta τ =0 represents non-response transfer, beta τ =1 represents response transfer, and the scheduling cost F tr of the transferable load is as follows:
Where F c tr is the scheduling cost of the unit power transfer, and P t tr is the load power transferred in the t period.
In the day-ahead scheduling model, the minimum sum of the unit operation cost in a period, the variable-frequency air conditioner load and the basic flexible load response compensation cost is taken as a target, and the expression of the day-ahead scheduling model is as follows:
Wherein T is the total time period number of the dispatching cycle, N 2 is the number of the dispatchable units, Generating cost for the unit j in a period t; For the output of the unit j in the period t, F BPAC is the load scheduling cost of the variable frequency air conditioner, F c BPAC is the load unit power scheduling cost of the variable frequency air conditioner, For the t period of time in response to the power of the front variable frequency air conditioner load,And responding the power of the post-frequency conversion air conditioner load for the t period.
The constraint conditions of the day-ahead scheduling model comprise active power balance constraint, conventional unit output constraint, conventional unit climbing constraint and variable-frequency air conditioner aggregate power constraint;
the active power balance constraint is:
wherein, AndBase load, air-conditioning load, translatable load power, reducible load power and translatable load power at time t respectively;
the output constraint of the conventional unit is as follows:
Wherein, P Gjmin and P Gjmax are respectively the lower limit and the upper limit of the output of the unit j;
the climbing constraint of the conventional unit is as follows:
wherein, D Rj and U Rj are respectively the maximum descending speed and the maximum ascending speed of the unit j in unit time, and Deltat is the climbing time;
the aggregate power constraint of the variable frequency air conditioner is as follows:
wherein, AndThe lower limit and the upper limit of the air conditioner load at the time t are respectively set.
In summary, a day-ahead scheduling model of mixed integer linear programming is constructed, a CPLEX solver is adopted to solve the day-ahead scheduling model, and a cooperative scheduling plan of 'source-load' is obtained, so that a load aggregation scheduling plan of the variable-frequency air conditioner is formed.
After the aggregate scheduling plan of the variable frequency air conditioner is obtained, the aggregate scheduling plan of the variable frequency air conditioner is used as a control target, a grouping control model of the variable frequency air conditioner is further designed, firstly, differences among brands and models of variable frequency air conditioners installed by different users in a distribution network district are considered, and if the variable frequency air conditioner is modeled respectively, the process is complicated and the workload is high. In this regard, the present invention clusters the variable frequency air conditioners in the jurisdiction with specific parameters, and performs grouping control, and the process of clustering the variable frequency air conditioners in the jurisdiction of the distribution network includes:
taking steady-state parameters and temperature change parameters of the variable-frequency air conditioner as characteristic attributes, adopting a K-means clustering algorithm, and clustering a large number of variable-frequency air conditioners into different aggregation subgroups according to the principle that the steady-state parameters and the temperature change parameters of the variable-frequency air conditioner are similar;
The steady-state power of the variable frequency air conditioner is closely related to the quotient of the heat conductivity coefficient A and the energy efficiency ratio eta 2 of the variable frequency air conditioner, so that the steady-state parameters of the variable frequency air conditioner are as follows The transition period of the variable frequency air conditioner has the same length as the equivalent thermal resistance R of the room room equivalent heat capacity CClosely related, the temperature change parameter is thus defined as rxc.
As can be seen from the operation state of the variable frequency air conditioner in fig. 1, when the temperature set value of the variable frequency air conditioner is raised, the variable frequency air conditioner operates under the new steady-state power after the small proportion of power is reduced in the transient state process, and the influence of the transient state power reduction on the distribution network is small, so that the variable frequency air conditioner can be directly controlled in groups by adopting a temperature control method, the aggregate power of the variable frequency air conditioner is controlled to follow a scheduling plan, that is, the deviation between the aggregate power of the variable frequency air conditioner and the target power of the variable frequency air conditioner is controlled to be minimum, and the expression of the joint scheduling model is as follows:
wherein, Is the actual load of the variable-frequency air conditioner of the ith group,For the target power at time t, count i is the number of air conditioners in the ith aggregation group,Respectively the temperature set value, the initial temperature set value, the upper temperature limit and the indoor temperature of the room where the i-th group of variable-frequency air conditioners are positioned at the moment t,The outdoor temperature is set to be the time t,AndThe transition period power and the initial power of the i-th group variable frequency air conditioner are respectively.
And the particle swarm algorithm is used for solving the joint scheduling model, so that the control effect is stable and accurate.
According to the embodiment, the simplified distribution network system is used as a simulation system for analysis, and the guiding significance of the three-layer regulation and control framework of the frequency conversion air conditioner on guiding the frequency conversion air conditioner to participate in demand response is verified. The power supply side of the distribution network system is provided with 6 generator sets, and the load side is provided with 10000 variable-frequency air conditioners and a certain amount of translatable, reducible and transferable loads besides the basic load. The parameter ranges of the variable frequency air conditioner are shown in table 1:
Table 1 variable frequency air conditioner load parameter ranges
The time-of-use electricity prices are shown in table 2:
Table 2 time-of-use electricity price meter
The parameters of each conventional unit in the distribution network system are shown in table 3:
TABLE 3 conventional unit parameters
The compensating electricity price of translatable, reducible and transferable loads is 0.25 yuan (kW.h) -1, 0.3 yuan (kW.h) -1 respectively.
Assuming that the variable frequency air conditioner users all set the air conditioner temperature in a temperature range of 25-27 ℃ which accords with the user thermal comfort, taking the outdoor temperature in the typical day in summer as the outdoor temperature input, and calculating the variable frequency air conditioner aggregation power by utilizing a variable frequency air conditioner aggregation model; in addition, the difference between 10000 fixed-frequency air conditioners and variable-frequency air conditioners under the condition that the outdoor temperature and the room thermal parameters are the same is analyzed by combining the fixed-frequency air conditioner aggregation model in the prior study, and the power curves of the 10000 fixed-frequency air conditioners and the variable-frequency air conditioners are drawn in fig. 5. As can be seen from fig. 5, under the same other conditions, although the operation principle of the monomer variable frequency air conditioner is different from that of the monomer fixed frequency air conditioner, the change trend of the polymerization power of the monomer variable frequency air conditioner after a large amount of polymerization is consistent, and the change trend is related to the outdoor temperature, because: when the outdoor temperature is low, the indoor temperature can be stabilized within the comfort level range set by a user by only needing less power no matter the outdoor temperature is fixed frequency or the variable frequency air conditioner; when the outdoor temperature is higher, the temperature difference between the outdoor temperature and the indoor temperature set value is larger, the room temperature is kept at the user set value for the variable frequency air conditioner, larger steady-state power is needed, and the starting period of the fixed frequency air conditioner is needed to keep a higher duty ratio in the operation period, so that the average operation power of the fixed frequency air conditioner is correspondingly increased. In addition, it is not difficult to find that under the condition that other conditions are the same, the aggregation power of the variable frequency air conditioner with the same quantity is smaller than that of the fixed frequency air conditioner, the aggregation power peak value of the variable frequency air conditioner is 7312KW at 14 PM, the aggregation power of the fixed frequency air conditioner reaches 8658KW at the moment, the aggregation power of the fixed frequency air conditioner and the aggregation power are different by 1346KW, the variable frequency air conditioner can save 15.54% of energy compared with the fixed frequency air conditioner, and the variable frequency air conditioner is an energy-saving advantage brought by a variable frequency technology, and is a great reason that the variable frequency air conditioner is used for replacing the fixed frequency air conditioner to become a main stream household air conditioner.
In order to evaluate the actual aggregate response potential of the variable-frequency air conditioner clusters in the power distribution network, the embodiment uses the average-period electricity price in the time-sharing electricity price as the expected electricity price p base of the user based on the actual data of education level, income, age and the like of the household users in the Shanghai region, and the response willingness degree of the user participation demands in each period is calculated by a potential evaluation model as shown in fig. 6.
In the period of 24:00-7:00, the electricity price is lower than the basic electricity price, and the user willingness degree is-0.1652, so that the user participation demand response willingness is negative at the moment; in the time periods of 7:00-10:00, 13:00-16:00 and 21:00-24:00, the electricity price is equal to the basic electricity price, and the willingness degree of the user is 0 at the moment, so that the user can respond to the participation requirement and maintain a neutral state at the moment; in the time periods of 10:00-15:00 and 18:00-21:00, the electricity price is higher than the basic electricity price, the willingness degree of the user is 0.2441, and the user is positive in demand response attitude. The calculation of the user elastic temperature adjustable interval in combination with the user willingness model is shown in fig. 7.
The initial temperature set values of the variable frequency air conditioner clusters are uniformly distributed within 25-27 ℃, the initial temperature set values are expected to be 26 ℃, the current user controllability is considered to be 60%, and the maximum load reduction capacity of the cluster air conditioner loads in each time period is calculated based on the variable frequency air conditioner response potential evaluation model provided by the embodiment, wherein the maximum load reduction capacity is shown in figure 8.
The user willingness passive period has a small temperature adjustable range, and the response potential is only 298.4KW; the user holds the neutral attitude period, the temperature adjustment needs to meet the basic thermal comfort requirement of the user, and the response potential is 438.8KW at the moment; the user will actively take time, the temperature adjustable interval is further expanded, the response potential reaches 644.5KW, and the response potential evaluation model can effectively evaluate the load elastic aggregation response potential of the variable-frequency air conditioner in different time periods.
In this embodiment, after the aggregate power and the aggregate response potential of the clustered variable frequency air conditioner in the distribution network are obtained, the load resource distribution condition of each period in the distribution network before scheduling can be obtained by combining the base load and the base flexible load, as shown in fig. 9.
In order to verify the positive effect of the load aggregation response potential of the variable-frequency air conditioner and the basic flexible load on the running cost economy of the distribution network, the embodiment sets the following 3 scenes for comparison:
scene 1: the variable-frequency air conditioner load and the basic flexible load participate in demand response;
Scene 2: only the basic flexible load participates in demand response, and the variable-frequency air conditioner load does not participate;
Scene 3: neither takes part in demand response;
the day-ahead scheduling model which takes the response potential and the basic flexible load response characteristic of the variable-frequency air conditioner into account through CPLEX solution can obtain the system running cost under three scenes as shown in Table 4.
Table 4 running cost table in different scenarios
As can be seen from table 4, only the basic flexible load is considered to participate in the reduction of the running cost of the demand response system by 0.489 ten thousand yuan; if the variable-frequency air conditioner load also participates in demand response, the running cost can be reduced by 0.359 ten thousand yuan, and the economic benefit of the load side schedulable resource is improved by 4.13% fully; in addition, the economic benefit brought by the variable frequency air conditioner load can be found to be almost equivalent to the basic flexible load, and the significance of developing the variable frequency air conditioner load modeling research and excavating the response potential is great.
Fig. 10 shows the distribution of the load after the load is scheduled in scenario 1. As can be seen from comparison of fig. 9, the transferable load is transferred from the high electricity rate period to 5 where the electricity rate is lower: 00-8:00, translatable load shifts from evening load peaks to valleys 6:00-10:00, the load can be reduced and the load of the variable frequency air conditioner is 7: the cutting of 00-24:00 is carried out to different degrees, and the peak clipping and valley filling effects are obvious. The scheduling plan for the variable frequency air conditioner load is obtained from the comparison, namely the scheduled reduction amount of the variable frequency air conditioner load in each period is shown in fig. 11, and the scheduling plan is taken as a real-time control target of the variable frequency air conditioner load to guide the control layer to carry out accurate control.
To verify the effectiveness of the joint scheduling model of this embodiment, a K-means clustering method is first used to determine the steady-state parametersAnd clustering 10000 variable-frequency air conditioner loads in the system by using the temperature change parameter RC, dividing the variable-frequency air conditioner loads into 30 air conditioner aggregation groups, and then controlling the variable-frequency air conditioner groups to run according to a scheduling plan by taking a period of 13:00-14:00 as an example, and controlling the variable-frequency air conditioners to complete a 644.5KW load reduction target. In addition, the conventional control method of the fixed-frequency air conditioner and the improved control method of the fixed-frequency air conditioner are used for controlling the fixed-frequency air conditioner under the same condition to finish the same load reduction amount, so that the control difference between the fixed-frequency air conditioner and the fixed-frequency air conditioner is compared, and the control result is shown in fig. 12.
As can be seen from fig. 12, when the control model of the present invention performs group temperature control on the variable frequency air conditioner, the variable frequency air conditioner can stably and accurately follow the preset target power, except for the small power drop in the power transition stage after temperature adjustment.
Comparing the control effect of the joint scheduling model with the control effect of the fixed-frequency air conditioner by the control strategy of the traditional control method of the fixed-frequency air conditioner, the method can find that a transition stage of power drop exists no matter the variable-frequency air conditioner or the fixed-frequency air conditioner after temperature adjustment is carried out on a cluster at the initial stage of control, the transition stage of the variable-frequency air conditioner is obviously shorter than the fixed-frequency air conditioner, the 8 th minute after the control is finished, the fixed-frequency air conditioner is stable after the 20 th minute after the control is finished, and under the condition that the temperature control is adopted, the response speed of the variable-frequency air conditioner is faster, and the target power can be reached faster; in addition, compared with the maximum difference 451.8KW of the target power, the maximum difference 451.8KW of the generated power of the variable frequency air conditioner in the transition stage is higher than 1382.8KW of the target power, the improved control method of the fixed frequency air conditioner is used for adjusting the temperature when the fixed frequency air conditioner component is introduced in the preparation time based on the traditional method so as to distribute the power drop to the preparation period, the maximum power drop of the variable frequency air conditioner is still 809.6KW which is 2 times as high as that of the variable frequency air conditioner although the remarkable improvement effect is achieved, the controlled stability of the variable frequency air conditioner is higher than that of the fixed frequency air conditioner, and the impact on a power grid is small when the large-scale temperature control is carried out; finally, the control precision of the stable control period is compared, the aggregation power of the fixed-frequency air conditioner fluctuates up and down along with the control target, and the variable-frequency air conditioner can stably and accurately follow the target power.
In conclusion, the response speed, the control stability and the control precision of the variable frequency air conditioner are superior to those of the fixed frequency air conditioner, and the variable frequency air conditioner has excellent controllability to respond to the flexible resource requirement of the distribution network.
The embodiment provides a variable frequency air conditioner load regulation and control method considering multiple response potential influence factors, which can guide the variable frequency air conditioner to participate in the demand response of a power system in the aspects of response potential, scheduling model, control strategy and the like of the variable frequency air conditioner.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the person skilled in the art according to the inventive concept shall be within the scope of protection defined by the claims.
Claims (1)
1. A variable frequency air conditioner load regulation and control method considering multiple response potential influence factors is characterized by comprising the following steps:
acquiring the demand response potential of the variable frequency air conditioner in the district of the distribution network according to the variable frequency air conditioner response potential evaluation model;
according to the demand response potential of the variable-frequency air conditioner, acquiring the target power of the variable-frequency air conditioner through a day-ahead scheduling model;
Clustering the variable frequency air conditioners in the district of the distribution network to obtain a plurality of aggregation groups;
According to the target power of the variable frequency air conditioner, the variable frequency air conditioner clusters in the district of the distribution network are subjected to grouping temperature control by taking the aggregation group as a unit through a joint scheduling model,
The expression of the variable-frequency air conditioner response potential evaluation model is as follows:
wherein A i is the thermal conductivity of room i, For the energy efficiency ratio of the variable frequency air conditioner of the room i, the theta a is the outdoor temperature,For the temperature set value of the variable frequency air conditioner in the room i, N 1 is the number of the end users of the variable frequency air conditioner, P BPagg is the aggregate power of the variable frequency air conditioner, x is the user controllability,For the upper limit of the temperature adjustable margin,
The calculation formula of the upper limit of the temperature adjustable margin is as follows:
wherein mu i,t is a user willingness degree influence factor of the ith variable frequency air conditioner terminal user at the moment t, AndThe upper limit and the lower limit of the initial adjustable margin of the indoor temperature of the ith variable frequency air conditioner user at the moment t are respectively,
The calculation formula of the user willingness degree influence factor is as follows:
Wherein, p base is the expected electricity price of the user, p real is the current electricity price, p max is the highest electricity price, E is the education level of the user, I is the household income of the user, A is the average age of the user, a 1、a2、a3、a4、ω1、ω2、ω3 and omega 4 are set values, a 1≤a2≤a3≤1,0≤a4 is more than or equal to 0 and less than or equal to 1,
The calculating process of the initial adjustable margin of the indoor temperature comprises the following steps:
Constructing a predicted average ballot number index PMV for describing the thermal comfort degree through Franker thermal comfort degree equation;
The relation expression of the PMV value I PMV and the indoor temperature theta is obtained, and specifically:
Determining the initial adjustable margin of the indoor temperature of the constant-frequency air conditioner according to the set threshold value of I PMV,
The expression of the day-ahead scheduling model is as follows:
wherein N 2 is the number of schedulable units, T is the total time period number of scheduling periods, C Gj is the power generation cost of the unit j in the time period T, For the output of the unit j in the period t, F BPAC is the load scheduling cost of the variable frequency air conditioner, F sh、Fcut and F tr are respectively translatable, reducible and transferable load scheduling cost,
The constraint conditions of the day-ahead scheduling model comprise active power balance constraint, conventional unit output constraint, conventional unit climbing constraint and variable-frequency air conditioner aggregate power constraint;
the active power balance constraint is as follows:
wherein, AndBase load, air-conditioning load, translatable load power, reducible load power and translatable load power at time t respectively;
The conventional unit output constraint is as follows:
Wherein, P Gjmin and P Gjmax are respectively the lower limit and the upper limit of the output of the unit j;
the climbing constraint of the conventional unit is as follows:
Wherein, D Rj and U Rj are respectively the maximum descending speed and the maximum ascending speed of the unit j in unit time, and Deltat is the climbing time;
the frequency conversion air conditioner aggregate power constraint is as follows:
The process for clustering the variable frequency air conditioners in the distribution network district comprises the following steps:
taking steady-state parameters and temperature change parameters of the variable-frequency air conditioner as characteristic attributes, adopting a K-means clustering algorithm, and clustering a large number of variable-frequency air conditioners into different aggregation subgroups according to the principle that the steady-state parameters and the temperature change parameters of the variable-frequency air conditioner are similar;
wherein the steady-state parameters of the variable frequency air conditioner are as follows A is the heat conductivity of a room, eta 2 is the energy efficiency ratio of the variable frequency air conditioner, the temperature change parameter is RxC, R is the equivalent heat resistance of the room, C is the equivalent heat capacity of the room,
The expression of the joint scheduling model is as follows:
wherein, Is the actual load of the variable-frequency air conditioner of the ith group,For the target power at time t, count i is the number of air conditioners in the ith aggregation group,Respectively the temperature set value, the initial temperature set value, the upper temperature limit and the indoor temperature of the room where the i-th group of variable-frequency air conditioners are positioned at the moment t,The outdoor temperature is set to be the time t,AndThe transition period power and the initial power of the i-th group variable frequency air conditioner are respectively, k is a power change coefficient, the power change coefficient is proportional to the temperature change quantity, when the set temperature rises, k is less than 0, otherwise k is more than 0,
And solving the joint scheduling model through a particle swarm algorithm.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN107143968A (en) * | 2017-04-14 | 2017-09-08 | 东南大学 | Peak regulation control method based on air-conditioning polymerization model |
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| CN107143968A (en) * | 2017-04-14 | 2017-09-08 | 东南大学 | Peak regulation control method based on air-conditioning polymerization model |
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