Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for measuring and calculating response cost and analyzing economy of multi-type adjusting resources.
The invention aims to realize the method for measuring and calculating the response cost and analyzing the economy of the multi-type adjustment resource, which comprises the following steps:
S1, measuring and calculating response cost of multi-type adjustment resources;
S2, establishing a multi-type adjustment resource economy optimization configuration model considering the total life cycle cost;
and S3, performing economic analysis of adjusting resource response under different scenes.
Further, the step S1 of performing multi-type adjustment resource response cost measurement includes:
The electric automobile participation demand response economical calculation process is as follows:
Ft,sc＝Rdr×(1-α)-Cdr(1)
Wherein Ft,sc is net cash flow of the t th year of participation demand response, Rdr is annual demand response income, Rdr is annual demand response organization income, alpha is divided into 30%, Cdr is annual demand response operation and maintenance cost, initial annual investment is 2%, P is unified price, element/kW, Q is single invited response quantity of a user, kW, n is number of times of release of demand side response years, k1 is response quantity coefficient, 1;k2 is single response speed coefficient, private pile is 0.8, power exchange station is 2;k3 is response activity duration, private pile is 3, private pile is 2, power exchange station is 1;k4 is response participation coefficient, and 1 is obtained;
the residential users cannot neglect the requirements of the residential users on the comfort level of life when participating in the demand response of the air conditioner load, so that the temperature change range in the running process of the air conditioner is limited to a certain extent, as shown in the following formula:
Td-d+δ/2≤Tset≤Td+d-δ/2(3)
Wherein, the allowable temperature deviation of the user is set as d, delta represents the accuracy of air conditioner temperature control, and Td is the expected temperature meeting the comfort level of the resident user;
In the process that resident users participate in demand response, the air conditioner temperature is required to be adjusted, so that the indoor temperature is deviated from the expected temperature, the comfort of the users is reduced, and the comfort loss cost is brought, and the calculation method comprises the following steps:
where k is the response cost factor.
Further, the step S2 of establishing a multi-type adjustment resource economy optimization configuration model considering the full life cycle cost includes:
(1) Electric automobile load model
1.1, Monomer electric automobile charge-discharge model
The charge-discharge power range of the monomer electric automobile should satisfy the following constraint:
wherein t is a time period number, 1 time period is obtained every 1h, and 24 time periods are obtained all day; Charging and discharging power of the electric automobile r in the period t are respectively carried out; The maximum charge and discharge power of the electric automobile r are respectively; the time for the electric automobile r to access and leave the charging pile is respectively;
In addition, the charge and discharge power of the electric automobile also meets the following mutual exclusion constraint:
the above-mentioned means that the electric automobile r can not be charged and discharged at the same time in a certain period;
The net charge constraint of the electric vehicle is:
Wherein: Respectively starting and ending moments of the controllable period of the electric automobile r, wherein delta t is a time interval; The battery power of the electric automobile in the controllable period starting and ending period is respectively;
1.2 model linearization
The charging and discharging power of the electric automobile group is represented by a decision variable Prt, Prt <0 represents that the electric automobile group discharges to the power grid, Prt >0 represents that the electric automobile group charges from the power grid, and a binary parameter Urt is introduced:
-Pr,maxUrt≤Prt≤Pr,maxUrt(9)
Wherein Prt is the power of the electric automobile r in the t period, Pr,max is the maximum power of the electric automobile r, Urt is a binary state variable of the electric automobile r, Urt =1 indicates that the electric automobile is connected with a charging pile, and Urt =0 indicates that the electric automobile is not connected with the charging pile;
the battery power constraint of each period of the electric automobile is as follows:
Ert＝Ert-1+PrtUrtΔt(11)
Ert is the battery electric quantity value of the electric automobile r in the t period; an initial electric quantity value when the electric automobile is connected with a charging pile; The maximum and minimum values of the r battery electric quantity of the electric automobile are respectively;
Each electric automobile needs to satisfy the charge quantity demand that electric automobile user set for when leaving the electric pile that fills, then has:
Wherein: a charge amount demand value set for a user of the electric vehicle;
1.3 Battery degradation model accounting for full lifecycle
The service life of an electrochemical cell is determined by the lesser of its cycle life Tcycle and floating life Tfloat, calculated as follows:
Wherein: The maximum charge-discharge cycle number in the service life of the battery under a certain specific charge-discharge depth d; For the average number of cycles of the battery per day at a depth D of charge and discharge, D for the average number of days of operation of the battery per year after taking into account the necessary operating maintenance time, for different types of electrochemical cells,Can be expressed as a function of depth d of charge and discharge, as shown in the following equation:
Wherein, the mathematical expression of f (d) can be obtained by fitting technology according to detailed experimental data provided by battery manufacturers;
In a charge-discharge cycle, if the battery is discharged from the initial charge Estart to the end charge Eend, then charged back to the initial charge Estart by Eend, or charged back to the end charge Eend by the initial charge Estart, and then discharged back to the initial charge Estart by Eend, the ratio of the difference between the start and end charges of the battery and the battery capacity in the cycle is the charge-discharge depth of the battery, as shown in the following formula:
wherein Ecap is the battery capacity;
Assuming that the depth of charge-discharge cycle of the battery during the period t-1 is dt-1, the depth of cycle dt of the battery during the period t can be calculated from the discharge power Pt of the battery during the period t-1 to t:
Where ηdis is the discharge efficiency of the battery, Pt is a non-negative value due to the omission of the charging process, the incremental aging of the battery by this cycling process can be expressed as θ (dt), and the marginal aging amount can be calculated by deriving and substituting Pt from θ (dt) as shown in the following formula:
The battery discharging depth (0-100%) is divided into L sections averagely, the discharging power corresponding to each section is Pldis, the replacement cost R ($) of the battery is distributed to the charging and discharging circulation depth of each section in proportion, and a piecewise linear approximate function is obtained, so that a battery circulation aging cost function C is constructed, and the function consists of L sections, wherein the following formula is shown:
wherein:
assigning a discharge power to each cycle depth segmentTo track the energy level of each segment independently and identify the current cycle depth, the battery cycle degradation cost can be expressed as the sum of the segment costs:
(2) Air conditioner load model
Thermodynamic and electrical models of buildings and air conditioners are described by a simplified model of the thermal dynamics of the communication system, as shown in the following formula:
In the formula,The temperature of the wall body is represented,Indicating the indoor air temperature; Representing internally acquired heat; Ca represents a wall temperature coefficient, Cm represents an indoor air temperature coefficient, and the relationship is shown as follows, wherein fAC,fs and fi are fractional coefficients;
For the electrical model of the ac system, the output power of the air conditioning loadRefrigerating capacityAnd compressor on/off stateThe relationship between them can be expressed asIs the coefficient of performance of the alternating current system;
The full life cycle cost CL of the air conditioner load comprises equipment loss cost Closs, equipment maintenance cost Cre and equipment scrapping recovery cost Cdis in the operation stage, namely CL＝Closs+Cre+Cdis;
(3) Electrolytic aluminum load model
The thermoelectric process is represented by a set of differential equations, as follows:
wherein:
In the above formula, τ is time, a is a coefficient, Ta is chamber air temperature, Ts is solid layer temperature, Te is liquid layer temperature, Hs is thermal conductance between chamber air and solid layer, He is thermal conductance between solid layer and liquid layer, Cs is thermal mass of solid layer, Ce is thermal mass of liquid layer, ke is current coefficient, Ie is current intensity for generating heat;
The full life cycle cost of the electrolytic aluminum load CL includes the raw material processing cost Cpro, the equipment use cost Cuse, the recovery cost Cre and the equipment loss cost Closs, namely CL＝Cpro+Cuse+Cre+Closs.
Further, the step S3 of performing the economic analysis of the resource response adjustment under different scenarios includes:
(1) Electric network time sequence production simulation model considering electric automobile
1) Objective function
For a regional power grid consisting of k subsystems, its time-series operation simulation can be modeled as a mixed integer linear programming model whose objective function is the cost of power generation by the generatorStarting-up costCost of downtimeThe demand response cost CDR (t), the electric vehicle battery cycle aging cost CL (t) and the electricity limiting penalty of the renewable energy source are formed together, and the form of the electricity limiting penalty is as follows;
Wherein Gk is the total number of generators of the subsystem k, H is the total operation time, H=8760, thetaS and thetaW respectively correspond to punishments of the light-discarding electric quantity and the wind-discarding electric quantity of each megawatt for the operation simulation of the annual hour level, pS,k (t) and pW,k (t) are photovoltaic and wind electric power received by the subsystem k at the moment t respectively,AndThe maximum power of photovoltaic and wind power at the moment t is obtained by converting meteorological data;
2) Power balance constraint
For any subsystem k, there is a power balancing constraint:
wherein pG,i (T) is the power output of the generator i at the time T, pW,k (T) is the wind power output at the time T in the system k, pS,k (T) is the photovoltaic output at the time T in the system k, TI,k (T) and TO,k (T) are the power flowing into and out of the subsystem k through the connecting line at the time T respectively, pL,k (T) is the load power at the time T in the system k, and pEV (T) is the total power of the electric vehicle load at the time T;
3) Standby constraint
For any subsystem k, the safe reserve capacity of the subsystem must be ensured, and the reserve constraint is:
Wherein ui (t) is the start-stop state of the generator i, the generator is 1 when running, and 0 when stopping; EpsilonW,k and epsilonS,k are respectively the maximum prediction error of the wind power output and the maximum prediction error of the photovoltaic output of the subsystem k, etaL,k is the maximum standby demand coefficient of the subsystem k, and 5% is taken;
4) Power supply output range constraint
Wherein pG,i is the minimum technical output when generator i is running;
5) Climbing constraint of generator
The output power of the unit i at the time t needs to meet the climbing constraint of the unit:
Wherein rU,i and rD,i are respectively the maximum uphill speed rate and the maximum downhill speed rate of the generator i, N is a larger constant, and the output constraints when the generator is started and stopped are respectively as follows:
Wherein sU,i represents the start-up state of generator i, sD,i represents the shutdown state of generator i, and N is a relatively large constant.
6) Minimum start-stop time constraint
Wherein ui (T) is the working state of the generator i at time T, and TU,i and TD,i respectively represent the time for which the generator i still needs to keep running and keeping the shutdown state at time T, and the time can be calculated by the following formula:
TU,i(t)＝min{MU,i,T-t+1}(40)
TD,i(t)＝min{MD,i,T-t+1}(41)
Wherein MU,i and MD,i are respectively the minimum start-up time and the minimum stop time of the generator i, namely the generator must keep running MU,i after each start-up, the generator must be restarted after at least passing through MD,i after each stop, and in the process of rolling solution, the last state of the previous rolling period can be input as the initial state of the current rolling period, so that the set of Ui0 hours and Di0 hours is supposed to be started for the last state of the previous rolling period, and the initial start-stop constraint of the current rolling period is as follows:
(2) Power grid time sequence production simulation model considering massive heterogeneous air conditioner loads
The full life cycle costs of the air conditioning load CL include the run-stage equipment loss costs Closs, equipment repair costs Cre, and equipment reject recovery costs Cdis. Namely CL＝Closs+Cre+Cdis. Thus, its full life cycle cost should also be embodied in the objective function.
For a regional power grid consisting of k subsystems, its time-series operation simulation can be modeled as a mixed integer linear programming model whose objective function is the cost of power generation by the generatorStarting-up costCost of downtimeThe demand response cost CDR (t), the full life cycle cost CL (t) and the electricity limiting penalty of the renewable energy source are combined together, and the form of the demand response cost CDR (t) and the full life cycle cost CL (t) are as follows;
Wherein Gk is the total number of generators of the subsystem k, H is the total operation time, H=8760, thetaS and thetaW respectively correspond to punishments of the light-discarding electric quantity and the wind-discarding electric quantity of each megawatt for the operation simulation of the annual hour level, pS,k (t) and pW,k (t) are photovoltaic and wind electric power received by the subsystem k at the moment t respectively,AndThe maximum power of photovoltaic and wind power at the moment t is obtained by converting meteorological data;
for any subsystem k, there is a power balancing constraint:
Wherein pG,i (T) is the power output of the generator i at the time T, pW,k (T) is the wind power output at the time T in the system k, pS,k (T) is the photovoltaic output at the time T in the system k, TI,k (T) and TO,k (T) are the power flowing into and out of the subsystem k through the connecting line at the time T respectively, pL,k (T) is the load power at the time T in the system k, and pAC (T) is the total power of mass air conditioner loads at the time T;
the standby constraint, the power supply output range constraint, the generator climbing constraint and the minimum start-up and stop time constraint are the same as those in a power grid time sequence production simulation model considering the electric automobile;
For an air conditioning load, the power of which is related to the outside temperature and the set temperature Tset,i, the indoor temperature Ta,i (T) is required to be kept floating within a certain range from the set temperature, and the floating difference is Δtset,i, namely the following formula:
at the same time, the air conditioning load should also operate within a set minimum and maximum power range, as follows,
The air conditioner is used as an adjustable load, the up-regulating power PACu,i (t) and the down-regulating power PACd,i (t) cannot be performed simultaneously, and the up-regulating power constraint is that:
Wherein uac,i (t) is a 0-1 variable, bigM is PACmax,i-PACmin,i;
(3) Power grid time sequence production simulation model considering flexible industrial electrolytic aluminum load
The full life cycle cost CL of the electrolytic aluminum load comprises raw material processing cost Cpro, equipment use cost Cuse, recovery cost Cre and equipment loss cost Closs, namely CL＝Cpro+Cuse+Cre+Closs, so the full life cycle cost is also reflected in an objective function;
for a regional power grid consisting of k subsystems, its time-series operation simulation can be modeled as a mixed integer linear programming model whose objective function is the cost of power generation by the generatorStarting-up costCost of downtimeThe demand response cost CDR (t), the full life cycle cost CL (t) and the electricity limiting penalty of the renewable energy source are combined together, and the form of the demand response cost CDR (t) and the full life cycle cost CL (t) are as follows;
Wherein Gk is the total number of generators of subsystem k, H is the total operation time, for the operation simulation of the annual hour level, H=8760, θS and θW respectively correspond to penalties of the light and wind power abandoned quantity per megawatt, pS,k (t) and pW,k (t) are respectively the photovoltaic and wind power admitted by subsystem k at time t,AndThe maximum power of photovoltaic and wind power at the moment t is obtained by converting meteorological data;
for any subsystem k, there is a power balancing constraint:
Wherein pG,i (T) is the power output of the generator i at the time T, pW,k (T) is the wind power output at the time T in the system k, pS,k (T) is the photovoltaic output at the time T in the system k, TI,k (T) and TO,k (T) are the power flowing into and out of the subsystem k through the connecting line at the time T respectively,pL,k (T) is the load power at the time T in the system k, and pEA (T) is the total power of the flexible electrolytic aluminum load at the time T;
the standby constraint, the power supply output range constraint, the generator climbing constraint and the minimum start-up and stop time constraint are the same as those in a power grid time sequence production simulation model considering the electric automobile;
The production of electrolytic aluminum is mainly carried out in an aluminum electrolysis cell, and direct current is generated into metallic aluminum through electrochemical reaction by molten cryolite melt containing aluminum oxide and other elements beneficial to electrolysis, so that in the working mode, the direct current is in the range of minimum allowable current and maximum allowable current of the electrolysis cell, as shown in the following formula,
Meanwhile, electrolytic aluminum is taken as an industrial production product, and has certain constraint on the yield, and the following formula is adopted:
Wherein IEA_base,i is the reference current when the electrolytic aluminum works, and T is the total working period;
As an adjustable load, the flexible electrolytic aluminum can not be simultaneously regulated by the up-regulating current IEAu,i (t) and the down-regulating current IEAd,i (t), and is similar to the charge and discharge power of an energy storage device, the up-regulating current constraint is as follows:
Wherein uEA,i (t) is a 0-1 variable and bigM is IEA max,i-IEA min,i.
The multi-type adjusting resource response cost measuring and calculating and economy analyzing method has the advantages that the multi-type adjusting resource response cost measuring and calculating and economy analyzing method comprises the steps of S1, conducting multi-type adjusting resource response cost measuring and calculating, S2, establishing a multi-type adjusting resource economy optimizing configuration model for measuring and calculating full life cycle cost, S3, conducting economy analysis of adjusting resource response under different scenes, conducting multi-scene economy analysis on the multi-type adjusting resource response cost measuring and calculating and economy analyzing method, aiming at typical callable electric loads, including electric automobile loads, air conditioner loads and electrolytic aluminum loads, analyzing response characteristics of the multi-type adjusting resources, providing a response cost measuring and calculating method, analyzing cost influence factors of the typical callable electric loads under the full life cycle, designing an adjusting resource response model for measuring and calculating full life cycle cost, providing economy optimizing configuration model, and conducting multi-scene economy analysis on the multi-type adjusting resources under the multi-scene according to typical scenes, the power load participation and the energy conservation scenes, and solving the problems of measuring and calculating the required and potential benefits of the power loads under the multi-scene.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The following description of the technical solutions in the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention relates to a method for measuring and calculating response cost and analyzing economy of multi-type regulation resources, which comprises the following steps:
S1, measuring and calculating response cost of multi-type adjustment resources;
S2, establishing a multi-type adjustment resource economy optimization configuration model considering the total life cycle cost;
and S3, performing economic analysis of adjusting resource response under different scenes.
Further, the step S1 of performing multi-type adjustment resource response cost measurement includes:
The electric automobile participation demand response economical calculation process is as follows:
Ft,sc＝Rdr×(1-α)-Cdr(1)
Wherein Ft,sc is net cash flow of the t th year of participation demand response, Rdr is annual demand response income, Rdr is annual demand response organization income, alpha is divided into 30%, Cdr is annual demand response operation and maintenance cost, initial annual investment is 2%, P is unified price, element/kW, Q is single invited response quantity of a user, kW, n is number of times of release of demand side response years, k1 is response quantity coefficient, 1;k2 is single response speed coefficient, private pile is 0.8, power exchange station is 2;k3 is response activity duration, private pile is 3, private pile is 2, power exchange station is 1;k4 is response participation coefficient, and 1 is obtained;
Because the real-time response capacity of the private pile, the special pile and the replacement station is from weak to strong, the response speed of the private pile and the special pile is set according to the notification before the day, and the response speed of the replacement station is set according to the notification 0.5h in advance. Considering that the electric automobile has higher response precision, the average response proportion of the electric automobile is assumed to be 80% -120%. In addition, considering that the vehicle has the longest connection time in the private pile, and then the private pile, the continuous response time of the power exchange station is shortest due to the constraint of the power exchange operation intensity, and the k3 value of the 3-class charging facilities is 3,2 and 1 respectively. And the electric automobile does not participate in demand response bidding during the trial, and the annual response coefficient of the 3-class charging facilities is uniformly taken as 1.
The residential users cannot neglect the requirements of the residential users on the comfort level of life when participating in the demand response of the air conditioner load, so that the temperature change range in the running process of the air conditioner is limited to a certain extent, as shown in the following formula:
Td-d+δ/2≤Tset≤Td+d-δ/2(3)
Wherein, the allowable temperature deviation of the user is set as d, delta represents the accuracy of air conditioner temperature control, and Td is the expected temperature meeting the comfort level of the resident user;
In the process that resident users participate in demand response, the air conditioner temperature is required to be adjusted, so that the indoor temperature is deviated from the expected temperature, the comfort of the users is reduced, and the comfort loss cost is brought, and the calculation method comprises the following steps:
where k is the response cost factor.
Further, the step S2 of establishing a multi-type adjustment resource economy optimization configuration model considering the full life cycle cost includes:
(1) Electric automobile load model
1.1, Monomer electric automobile charge-discharge model
The charge-discharge power range of the monomer electric automobile should satisfy the following constraint:
wherein t is a time period number, 1 time period is obtained every 1h, and 24 time periods are obtained all day; Charging and discharging power of the electric automobile r in the period t are respectively carried out; The maximum charge and discharge power of the electric automobile r are respectively; the time for the electric automobile r to access and leave the charging pile is respectively;
In addition, the charge and discharge power of the electric automobile also meets the following mutual exclusion constraint:
the above-mentioned means that the electric automobile r can not be charged and discharged at the same time in a certain period;
The net charge constraint of the electric vehicle is:
Wherein: Respectively starting and ending moments of the controllable period of the electric automobile r, wherein delta t is a time interval; The battery power of the electric automobile in the controllable period starting and ending period is respectively;
1.2 model linearization
The charging and discharging power of the electric automobile group is represented by a decision variable Prt, Prt <0 represents that the electric automobile group discharges to the power grid, Prt >0 represents that the electric automobile group charges from the power grid, and a binary parameter Urt is introduced:
-Pr,maxUrt≤Prt≤Pr,maxUrt(9)
Wherein Prt is the power of the electric automobile r in the t period, Pr,max is the maximum power of the electric automobile r, Urt is a binary state variable of the electric automobile r, Urt =1 indicates that the electric automobile is connected with a charging pile, and Urt =0 indicates that the electric automobile is not connected with the charging pile;
the battery power constraint of each period of the electric automobile is as follows:
Ert＝Ert-1+PrtUrtΔt(11)
Ert is the battery electric quantity value of the electric automobile r in the t period; an initial electric quantity value when the electric automobile is connected with a charging pile; The maximum and minimum values of the r battery electric quantity of the electric automobile are respectively;
Each electric automobile needs to satisfy the charge quantity demand that electric automobile user set for when leaving the electric pile that fills, then has:
Wherein: a charge amount demand value set for a user of the electric vehicle;
1.3 Battery degradation model accounting for full lifecycle
The service life of an electrochemical cell is determined by the lesser of its cycle life Tcycle and floating life Tfloat, calculated as follows:
Wherein: The maximum charge-discharge cycle number in the service life of the battery under a certain specific charge-discharge depth d; For the average number of cycles of the battery per day at a depth D of charge and discharge, D for the average number of days of operation of the battery per year after taking into account the necessary operating maintenance time, for different types of electrochemical cells,Can be expressed as a function of depth d of charge and discharge, as shown in the following equation:
Wherein, the mathematical expression of f (d) can be obtained by fitting technology according to detailed experimental data provided by battery manufacturers;
In a charge-discharge cycle, if the battery is discharged from the initial charge Estart to the end charge Eend, then charged back to the initial charge Estart by Eend, or charged back to the end charge Eend by the initial charge Estart, and then discharged back to the initial charge Estart by Eend, the ratio of the difference between the start and end charges of the battery and the battery capacity in the cycle is the charge-discharge depth of the battery, as shown in the following formula:
wherein Ecap is the battery capacity;
Assuming that the depth of charge-discharge cycle of the battery during the period t-1 is dt-1, the depth of cycle dt of the battery during the period t can be calculated from the discharge power Pt of the battery during the period t-1 to t:
Where ηdis is the discharge efficiency of the battery, Pt is a non-negative value due to the omission of the charging process, the incremental aging of the battery by this cycling process can be expressed as θ (dt), and the marginal aging amount can be calculated by deriving and substituting Pt from θ (dt) as shown in the following formula:
The battery discharging depth (0-100%) is divided into L sections averagely, the discharging power corresponding to each section is Pldis, the replacement cost R ($) of the battery is distributed to the charging and discharging circulation depth of each section in proportion, and a piecewise linear approximate function is obtained, so that a battery circulation aging cost function C is constructed, and the function consists of L sections, wherein the following formula is shown:
wherein:
the number of segments divided by the average of the battery cycle discharge depth is different, and the corresponding battery life curve fitting effect is also different, as shown in fig. 1. It can be seen that the larger the average number of segments of the battery charge-discharge cycle depth is, the better the fitting effect of the piecewise linear function is compared with the life loss curve of the primary battery, and when the number of segments is 4 segments, the approximate fitting precision is over 85 percent.
Assigning a discharge power to each cycle depth segmentTo track the energy level of each segment independently and identify the current cycle depth, the battery cycle degradation cost can be expressed as the sum of the segment costs:
(2) Air conditioner load model
Thermodynamic and electrical models of buildings and air conditioners are described by a simplified model of the thermal dynamics of the communication system, as shown in the following formula:
In the formula,The temperature of the wall body is represented,Indicating the indoor air temperature; Representing internally acquired heat; Ca represents a wall temperature coefficient, Cm represents an indoor air temperature coefficient, and the relationship is shown as follows, wherein fAC,fs and fi are fractional coefficients;
For the electrical model of the ac system, the output power of the air conditioning loadRefrigerating capacityAnd compressor on/off stateThe relationship between them can be expressed asIs the coefficient of performance of the alternating current system;
The full life cycle cost CL of the air conditioner load comprises equipment loss cost Closs, equipment maintenance cost Cre and equipment scrapping recovery cost Cdis in the operation stage, namely CL＝Closs+Cre+Cdis;
(3) Electrolytic aluminum load model
The equivalent integrated thermal parameter model of flexible industrial electrolytic aluminum is shown in fig. 2, and the thermoelectric process is represented by a set of differential equations, as follows:
wherein:
In the above formula, τ is time, a is a coefficient, Ta is chamber air temperature, Ts is solid layer temperature, Te is liquid layer temperature, Hs is thermal conductance between chamber air and solid layer, He is thermal conductance between solid layer and liquid layer, Cs is thermal mass of solid layer, Ce is thermal mass of liquid layer, ke is current coefficient, Ie is current intensity for generating heat;
The full life cycle cost of the electrolytic aluminum load CL includes the raw material processing cost Cpro, the equipment use cost Cuse, the recovery cost Cre and the equipment loss cost Closs, namely CL＝Cpro+Cuse+Cre+Closs.
Further, the step S3 of performing the economic analysis of the resource response adjustment under different scenarios includes:
(1) Electric network time sequence production simulation model considering electric automobile
1) Objective function
For a regional power grid consisting of k subsystems, its time-series operation simulation can be modeled as a mixed integer linear programming model whose objective function is the cost of power generation by the generatorStarting-up costCost of downtimeThe demand response cost CDR (t), the electric vehicle battery cycle aging cost CL (t) and the electricity limiting penalty of the renewable energy source are formed together, and the form of the electricity limiting penalty is as follows;
Wherein Gk is the total number of generators of the subsystem k, H is the total operation time, H=8760, thetaS and thetaW respectively correspond to punishments of the light-discarding electric quantity and the wind-discarding electric quantity of each megawatt for the operation simulation of the annual hour level, pS,k (t) and pW,k (t) are photovoltaic and wind electric power received by the subsystem k at the moment t respectively,AndThe maximum power of photovoltaic and wind power at the moment t is obtained by converting meteorological data;
2) Power balance constraint
For any subsystem k, there is a power balancing constraint:
wherein pG,i (T) is the power output of the generator i at the time T, pW,k (T) is the wind power output at the time T in the system k, pS,k (T) is the photovoltaic output at the time T in the system k, TI,k (T) and TO,k (T) are the power flowing into and out of the subsystem k through the connecting line at the time T respectively, pL,k (T) is the load power at the time T in the system k, and pEV (T) is the total power of the electric vehicle load at the time T;
3) Standby constraint
For any subsystem k, the safe reserve capacity of the subsystem must be ensured, and the reserve constraint is:
Wherein ui (t) is the start-stop state of the generator i, the generator is 1 when running, and 0 when stopping; EpsilonW,k and epsilonS,k are respectively the maximum prediction error of the wind power output and the maximum prediction error of the photovoltaic output of the subsystem k, etaL,k is the maximum standby demand coefficient of the subsystem k, and 5% is taken;
4) Power supply output range constraint
Wherein pG,i is the minimum technical output when generator i is running;
5) Climbing constraint of generator
The output power of the unit i at the time t needs to meet the climbing constraint of the unit:
Wherein rU,i and rD,i are respectively the maximum uphill speed rate and the maximum downhill speed rate of the generator i, N is a larger constant, and the output constraints when the generator is started and stopped are respectively as follows:
Wherein sU,i represents the start-up state of generator i, sD,i represents the shutdown state of generator i, and N is a relatively large constant.
6) Minimum start-stop time constraint
Wherein ui (T) is the working state of the generator i at time T, and TU,i and TD,i respectively represent the time for which the generator i still needs to keep running and keeping the shutdown state at time T, and the time can be calculated by the following formula:
TU,i(t)＝min{MU,i,T-t+1}(40)
TD,i(t)＝min{MD,i,T-t+1}(41)
Wherein MU,i and MD,i are respectively the minimum start-up time and the minimum stop time of the generator i, namely the generator must keep running MU,i after each start-up, the generator must be restarted after at least passing through MD,i after each stop, and in the process of rolling solution, the last state of the previous rolling period can be input as the initial state of the current rolling period, so that the set of Ui0 hours and Di0 hours is supposed to be started for the last state of the previous rolling period, and the initial start-stop constraint of the current rolling period is as follows:
taking a certain province as an example, the number of electric vehicles in the whole province is about 85 ten thousand, the charging power of each vehicle is about 6kW, and at least 4 hours are needed for each charging. If the electric automobile is in charge of the charging period from 18:00 to 6:00, and if the electric automobile is in charge of the charging period from 6:00 to 18:00, the electric automobile is in charge of the charging period from 6:00 to 6:00, and the electric automobile load of 850000 x 6k x 4/12 is about 1700 megawatts is used for replacing the original fixed load of the electric automobile in the corresponding period. At this time, the power system contains adjustable load, and then the time sequence production simulation technology is used for carrying out supply protection and extreme scene analysis. After the electric automobile is added, the load shedding conditions of the original middle and late 6 months, middle and late 7 months and middle and upper october are improved somewhat, and the whole situation is shown in figure 3.
Since the cut load contrast represented in the graph is not obvious, it is converted into a cut load ratio. It is known that after the electric automobile load is added, the load shedding rate is reduced from the original 1.6446% to 1.1634%, and the load shedding condition is improved to a certain extent. Typical days 6-20 to 22 are selected, and the charging action condition of the electric automobile is analyzed, as shown in fig. 4. For a 'power-saving' scene, the electric automobile starts to charge from 2:00 at night to about 6:00 a.m. and is not charged at a load late peak stage, and the electric automobile is charged at an early morning period with a relatively low load level, so that a certain load transfer effect is achieved, the pressure of a load peak is relieved, and the load shedding condition is reduced.
After the wind power installation capacity is increased by three times, the photovoltaic capacity is increased by four times, the wind discarding and light discarding situation of a certain power saving system in the whole summer after the new energy capacity is increased is simulated by time series production, and most wind discarding and light discarding occur in afternoon time in one day, and the photovoltaic is greatly emitted and cannot be consumed at this time, the light discarding quantity reaches a peak value at 13:00 and 15:00, and the wind discarding quantity reaches a peak value at 14:00. In order to improve the consumption of new energy and reduce the occurrence of the condition of wind and light discarding, an electric automobile is added with the adjustable load, the time sequence production simulation is carried out again, the 'conservation' extreme scene is analyzed, and the whole condition results are shown in figures 5 and 6. The graph shows that the wind and light discarding condition in the whole summer is obviously improved after the electric automobile is added, and the wind discarding rate and the light discarding rate are reduced by orders of magnitude after the electric automobile is added. For the 'conservation' scene, the electric automobile starts to charge from about 10:00 am and ends to charge about 14:00 am. At the moment, due to the charging action of the electric automobile, new energy sources greatly emitted in afternoon can be further absorbed, and the wind and light abandoning is reduced.
(2) Power grid time sequence production simulation model considering massive heterogeneous air conditioner loads
The full life cycle costs of the air conditioning load CL include the run-stage equipment loss costs Closs, equipment repair costs Cre, and equipment reject recovery costs Cdis. Namely CL＝Closs+Cre+Cdis. Thus, its full life cycle cost should also be embodied in the objective function.
For a regional power grid consisting of k subsystems, its time-series operation simulation can be modeled as a mixed integer linear programming model whose objective function is the cost of power generation by the generatorStarting-up costCost of downtimeThe demand response cost CDR (t), the full life cycle cost CL (t) and the electricity limiting penalty of the renewable energy source are combined together, and the form of the demand response cost CDR (t) and the full life cycle cost CL (t) are as follows;
Wherein Gk is the total number of generators of the subsystem k, H is the total operation time, H=8760, thetaS and thetaW respectively correspond to punishments of the light-discarding electric quantity and the wind-discarding electric quantity of each megawatt for the operation simulation of the annual hour level, pS,k (t) and pW,k (t) are photovoltaic and wind electric power received by the subsystem k at the moment t respectively,AndThe maximum power of photovoltaic and wind power at the moment t is obtained by converting meteorological data;
for any subsystem k, there is a power balancing constraint:
Wherein pG,i (T) is the power output of the generator i at the time T, pW,k (T) is the wind power output at the time T in the system k, pS,k (T) is the photovoltaic output at the time T in the system k, TI,k (T) and TO,k (T) are the power flowing into and out of the subsystem k through the connecting line at the time T respectively, pL,k (T) is the load power at the time T in the system k, and pAC (T) is the total power of mass air conditioner loads at the time T;
the standby constraint, the power supply output range constraint, the generator climbing constraint and the minimum start-up and stop time constraint are the same as those in a power grid time sequence production simulation model considering the electric automobile;
For an air conditioning load, the power of which is related to the outside temperature and the set temperature Tset,i, the indoor temperature Ta,i (T) is required to be kept floating within a certain range from the set temperature, and the floating difference is Δtset,i, namely the following formula:
at the same time, the air conditioning load should also operate within a set minimum and maximum power range, as follows,
The air conditioner is used as an adjustable load, the up-regulating power PACu,i (t) and the down-regulating power PACd,i (t) cannot be performed simultaneously, and the up-regulating power constraint is that:
Wherein uac,i (t) is a 0-1 variable, bigM is PACmax,i-PACmin,i;
Taking a certain province as an example, the cooling load of residents in the whole province in summer is about 27000 megawatts. Thus, the original fixed load was replaced with an air conditioning load of 27000 megawatts. At this time, the power system contains adjustable load, and then the time sequence production simulation technology is used for carrying out supply protection and extreme scene analysis. After the air conditioning load is added, the original load shedding conditions of the middle and late 6 months, the middle and late 7 months and the middle and late october are obviously improved, the load shedding occurs only when the load of the 8 months and the 7 days reaches the peak value, the whole situation is shown in fig. 7, the typical days 6 months and 20 days to 6 months and 22 days are selected, the action situation of the air conditioning load is analyzed, as shown in fig. 8 and 9, the air conditioning load is adjusted upwards from about 12:00 midday, the actual power is larger than the reference power, the indoor temperature is reduced, and the peak value of the actual power is about 28000 megawatts in response to high-temperature weather. Then, the actual power is smaller than the reference power after the beginning of the down regulation from about 15:00 pm, and when the fixed load reaches the peak at about 18:00 and 24:00, the down regulation of the air conditioner load is most obvious, and the pressure of the load is relieved, so that the load shedding condition is reduced.
(3) Power grid time sequence production simulation model considering flexible industrial electrolytic aluminum load
The full life cycle cost CL of the electrolytic aluminum load comprises raw material processing cost Cpro, equipment use cost Cuse, recovery cost Cre and equipment loss cost Closs, namely CL＝Cpro+Cuse+Cre+Closs, so the full life cycle cost is also reflected in an objective function;
for a regional power grid consisting of k subsystems, its time-series operation simulation can be modeled as a mixed integer linear programming model whose objective function is the cost of power generation by the generatorStarting-up costCost of downtimeThe demand response cost CDR (t), the full life cycle cost CL (t) and the electricity limiting penalty of the renewable energy source are combined together, and the form of the demand response cost CDR (t) and the full life cycle cost CL (t) are as follows;
Wherein Gk is the total number of generators of subsystem k, H is the total operation time, for the operation simulation of the annual hour level, H=8760, θS and θW respectively correspond to penalties of the light and wind power abandoned quantity per megawatt, pS,k (t) and pW,k (t) are respectively the photovoltaic and wind power admitted by subsystem k at time t,AndThe maximum power of photovoltaic and wind power at the moment t is obtained by converting meteorological data;
for any subsystem k, there is a power balancing constraint:
Wherein pG,i (T) is the power output of the generator i at the time T, pW,k (T) is the wind power output at the time T in the system k, pS,k (T) is the photovoltaic output at the time T in the system k, TI,k (T) and TO,k (T) are the power flowing into and out of the subsystem k through the connecting line at the time T respectively, pL,k (T) is the load power at the time T in the system k, and pEA (T) is the total power of the flexible electrolytic aluminum load at the time T;
the standby constraint, the power supply output range constraint, the generator climbing constraint and the minimum start-up and stop time constraint are the same as those in a power grid time sequence production simulation model considering the electric automobile;
The production of electrolytic aluminum is mainly carried out in an aluminum electrolysis cell, and direct current is generated into metallic aluminum through electrochemical reaction by molten cryolite melt containing aluminum oxide and other elements beneficial to electrolysis, so that in the working mode, the direct current is in the range of minimum allowable current and maximum allowable current of the electrolysis cell, as shown in the following formula,
Meanwhile, electrolytic aluminum is taken as an industrial production product, and has certain constraint on the yield, and the following formula is adopted:
Wherein IEA_base,i is the reference current when the electrolytic aluminum works, and T is the total working period;
As an adjustable load, the flexible electrolytic aluminum can not be simultaneously regulated by the up-regulating current IEAu,i (t) and the down-regulating current IEAd,i (t), and is similar to the charge and discharge power of an energy storage device, the up-regulating current constraint is as follows:
Wherein uEA,i (t) is a 0-1 variable and bigM is IEAmax,i-IEAmin,i.
Taking a certain province as an example, in eleven industries, the industrial electric load accounts for about 71.09%, wherein the nonferrous metal smelting and calendaring industry has a large adjustable potential, and the typical working condition load is about 4800 megawatts. Thus, the original fixed load was replaced with a 4800 megawatt flexible industrial electrolytic aluminum load. At this time, the power system contains adjustable load, and then the time sequence production simulation technology is used for carrying out supply protection and extreme scene analysis. After the electrolytic aluminum load is added, the load cutting conditions of the first 6 months, the second 7 months and the first and last trimester are not obviously improved, and the whole situation is shown in figure 10. Since the cut load contrast represented in the graph is not obvious, it is converted into a cut load ratio. It is known that after the flexible industrial electrolytic aluminum load is added, the load shedding rate is reduced from the original 6.3543% to 1.5198%, and the load shedding condition is improved to a certain extent. The action condition of the electrolytic aluminum load is analyzed by selecting typical days 6-20 to 22, as shown in fig. 11, and the condition of the electrolytic aluminum load is focused on the condition of the down regulation of the electrolytic aluminum load in the 'power-saving' scene, as can be seen from the figure, the down regulation of the electrolytic aluminum load is carried out from 18:00 in the evening to cope with the late peak of the load, the down regulation is most obvious at about 22:00, the actual power is reduced to 3000 megawatts, and the pressure of the load is relieved, so that the condition of the load shedding is reduced.
After the wind power installation capacity is increased by three times, the photovoltaic capacity is increased by four times, the wind discarding and light discarding situation of a certain power saving system in the whole summer after the new energy capacity is increased is simulated by time series production, and most wind discarding and light discarding occur in afternoon time in one day, and the photovoltaic is greatly emitted and cannot be consumed at this time, the light discarding quantity reaches a peak value at 13:00 and 15:00, and the wind discarding quantity reaches a peak value at 14:00. In order to improve the absorption of new energy and reduce the occurrence of the condition of waste wind and waste light, the adjustable load of flexible industrial electrolytic aluminum load is added, the time sequence production simulation is carried out again, the 'conservation' extreme scene is analyzed, the result of the whole condition is shown in figure 12, the waste wind and waste light phenomenon is not obviously improved when being observed by the figure, the waste wind and waste light phenomenon is converted into the total waste wind and waste light rate, and the total waste wind and waste light rate is reduced to a certain extent after the electrolytic aluminum load is added.
The multi-type adjusting resource response cost measuring and calculating and economic analysis method comprises the steps of S1, carrying out multi-type adjusting resource response cost measuring and calculating, S2, establishing a multi-type adjusting resource economic optimization configuration model for measuring full life cycle cost, S3, carrying out economic analysis for adjusting resource response under different scenes, researching multi-type adjusting resource response cost measuring and calculating and economic analysis, analyzing response characteristics of the multi-type adjusting resource aiming at typical callable electric loads including electric automobile loads, air conditioner loads and electrolytic aluminum loads, providing a response cost measuring and calculating method, analyzing cost influence factors of the typical callable electric loads under the full life cycle, designing an adjusting resource response model for measuring full life cycle cost, providing an economic optimization configuration model, carrying out multi-scene economic analysis for typical scenes, conservation scenes and conservation scenes of wind and solar loads, and solving the problems of ' electric load participation ' double conservation ' and ' cost and potential benefit ' in the multi-type adjusting resource under the multi-scene.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims.