CN112398169B - Heat storage CHP and thermal power deep regulating combined optimization peak regulating method considering user side response - Google Patents
Heat storage CHP and thermal power deep regulating combined optimization peak regulating method considering user side response Download PDFInfo
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- H—ELECTRICITY
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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Abstract
The invention relates to the technical field of automation of an electric power system, and aims to provide a heat storage CHP and thermal power deep-regulating combined optimization peak regulation method taking response of a user side into consideration.
Description
Technical Field
The invention relates to the technical field of power system automation, in particular to a heat storage CHP and thermal power deep regulating combined optimization peak regulating method considering user side response.
Background
Because clean energy such as wind power is strong in environmental protection, low-carbon economy is facilitated, energy structures are optimized, and the installed capacity of the wind power generator is greatly increased in recent years. Along with the higher permeability of wind power in a power system, the defects of the wind power are continuously displayed, and the random and severe fluctuation of wind power generation caused by the characteristics of actual wind speed such as instability, unpredictability and the like brings great challenges to power grid power generation planning and scheduling and the like. Because the wind power output has uncertainty, the phenomenon that the power supply amount in a system is larger than the load demand amount often occurs in a wind power large-power generation period, so that a large amount of abandoned wind is generated, namely the anti-peak shaving characteristic of wind power. Along with the continuous increase of power consumption, the peak-valley difference of the load side of the power grid is increasingly increased, and the uncertainty and the anti-peak regulation characteristic of the power generation of the clean energy source side are added, so that the existing regulation resources of the power system are difficult to meet the peak regulation requirement, the system scheduling burden is heavier, and the large-scale clean energy source is obviously insufficient.
In winter heating period, a cogeneration (combined heat and power, CHP) unit operates in a mode of 'heat and power setting', so that long-time high-strength output heat resources are usually required to meet heat load demands, and a wind turbine unit often needs to run in a wind-discarding mode to maintain grid stability due to uncertainty. The heat storage device is additionally arranged in the CHP system, so that the flexible heat storage and release capability of heat storage to heat energy can be utilized, the traditional working mode of 'electricity fixation by heat' is broken, and when the heat supply quantity of the system in the wind power high-generation time period is larger than the heat load demand, the heat storage can be utilized to store redundant heat energy, so that the generation of abandoned wind is reduced. At present, domestic and foreign researches focus on optimization of a combined operation mode of a wind power plant and a CHP power plant with a heat storage device, and a single heat storage device is used for coordinating wind power on-line income and punishment cost, so that the capacity requirement on the heat storage device is high. Under the background of high thermal power generation ratio of the current power system, if the flexible operation capacity of the thermal power generating unit can be fully and effectively excavated, the peak regulation capacity of the power system is greatly improved. The deep peak shaving of the thermal power generating unit is used as one of the most successful thermal power flexibility transformation technology practices, and is one of the most practical and effective methods for improving new energy consumption capacity at present.
In addition to flexible peak shaving resources at the source side, demand side response is also a big research hotspot to facilitate new energy consumption. The dynamic time-sharing electricity price is used for guiding electricity consumption behaviors of power users, excitation electricity price and the like of the users participating in peak shaving auxiliary service are properly formulated, so that load originally in a peak period of electricity consumption is transferred to a load valley period, the load electricity consumption in the valley period is obviously improved through demand response, a load curve is effectively changed, negative influence of wind power anti-peak shaving characteristics on the system for absorbing wind power is reduced, and the peak shaving pressure of a power grid is reduced on the basis of not damaging electricity interests of the users.
The proportion of clean energy such as wind power and the like which is connected into a power grid is continuously increased, the peak shaving pressure of a system is continuously increased, the phenomenon of wind abandoning exists in a large quantity, and the problems that the research of comprehensively considering heat storage, deep peak shaving of thermal power and demand response coordination scheduling to improve the wind power consumption is less and flexible peak shaving resource excavation on the source side and the load side is insufficient are solved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a heat storage CHP and thermal power deep dispatching combined optimization peak shaving method taking response of a user side into consideration, wherein the system comprises a CHP unit, a thermal power unit, a wind turbine unit, a heat storage device and the like, optimization variables are electric load, time-of-use electricity price and charging and discharging power of the heat storage device, the optimization target is that the total dispatching cost of the system is minimized, and the total dispatching cost comprises operation cost of the thermal power unit, operation cost of the CHP unit, operation and maintenance cost of wind power and punishment cost of wind abandoning. Aiming at the model solving problem, the invention converts the model into a mixed integer programming problem.
The aim of the invention is realized by the following technical scheme: the heat storage CHP and thermal power deep regulating combined optimization peak regulating method considering user side response comprises the following steps:
step 1: according to the heat storage device, a heat storage model is built, and when the heat storage capacity of the heat storage device at the time t is C hs,t The thermal storage model is that,
C hs,t ＝(1-σ)C hs,t-1 +P hs,t
wherein sigma is the self-heat release rate of the heat storage device, i.e. the heat energy loss rate of the heat storage device per unit time, P hs,t For charging and discharging heat power of the heat storage device at the time t, P hs,t <0 indicates that the heat storage device is releasing heat, P hs,t >0 indicates that the heat storage device is in a heat storage state, the heat storage amount of the heat storage device should satisfy the following constraint,
wherein,and->Respectively representing the minimum and maximum heat storage capacity allowed by the heat storage device,/->And->Respectively represent the minimum and maximum heat storage power allowed by the heat storage device, when +.>And->When the value is negative, the minimum heat release power and the maximum heat release power are represented, and the step 2 is executed;
step 2: establishing a thermal power deep regulating model according to a thermal power unit to obtain thermal power deep regulating cost, wherein the thermal power deep regulating cost is,
C g_deep ＝C g +aC l +bC o
wherein C is o For oil cost, a and b are Boolean variables, p o The oil charging price of the peak regulating electric quantity per unit depth of the thermal power unit is O g,i,t The integrated electric quantity is obtained when the actual power of the ith thermal power generating unit is deeply regulated in the t period and is lower than the steady combustion load value of deep regulation without oil throwing;for the ith unit, the load power is regulated and stabilized without adding oil, and the load power is increased>The oil feeding depth of the ith unit is used for regulating and stabilizing the combustion load power,for the minimum technical output of the ith thermal power unit,/->Maximum technical output of ith thermal power unit, C l Represents the economic cost of life loss required by the unit to participate in deep peak shaving, T represents a scheduling period, I g Representing the number of thermal power generating units, and executing the step 3;
step 3: a user response model is constructed, specifically as follows,
wherein S is dr,n User satisfaction, delta, for nth participation demand response n,t For the demand response decision variable, delta, of the load n at time t n,t When=1, the load responds, and the transfer power is Δp load,n,t A positive value indicates that the user increases the power, a negative value indicates that the user decreases the power,for the optimized time-sharing electricity price, +.>To optimize the electricity price before P load,n,t For the load power after demand response, +.>To optimize the pre-load power, the total amount of power used by the user in a scheduling period is kept constant, +.>For a minimum value of user response peak shaving satisfaction in one scheduling period, +.>And->Respectively represent the minimum and maximum load transfer power allowed by the nth user, t np Load adjustable time period allowed for nth user ρ Rmin And ρ Rmax Respectively the minimum and maximum limit values of time-of-use electricity price, deltaρ Rmin And Δρ Rmax Step 4 is executed for the minimum and maximum value of the response quantity allowed by the time-sharing electricity price respectively;
step 4: taking the electric load, the time-sharing electricity price and the charging and discharging power of the heat storage device as optimization variables, minimizing the total dispatching cost of the system as an optimization target, calculating the total dispatching cost, wherein the total dispatching cost is
min C s ＝C g_deep +C h +C w +C w_curt
P ceh,i,t ＝P ce,i,t +ξP ch,i,t
Wherein C is g_deep The method is thermal power unit operation cost, including conventional unit operation cost and thermal power unit depth peak regulation cost; c (C) h For the operation cost of the CHP unit, C w C is wind power operation and maintenance cost w_curt To pay for wind disposal, alpha i 、β i 、γ i Is the coal consumption coefficient, P of the CHP unit ce,i,t And P ch,i,t The electric power and the thermal power values of the ith CHP unit in the t period are respectively, P ceh,i,t For the power generated by the ith CHP unit at the moment t, xi represents the electric power value reduced when the CHP unit increases the unit thermal power, theta is the wind power operation and maintenance cost coefficient, and P w_r,t The actual output power of wind power at the moment t is mu, the cost coefficient of wind abandon punishment is P w_f,t And predicting power for the wind power at the moment t.
Preferably, in the step 2, the life loss cost C of the unit l Is that
Wherein, gamma g,i,t In the state of participating in deep regulation at t moment of ith thermal power generating unit, gamma g,i,t =1 represents the unit participating in deep peak regulation, γ g,i,t =0 means that the unit does not participate in deep tone; c (C) l Represents the economic cost of life loss required by the unit to participate in deep peak shaving, Y g For the price of the machine set, N g Indicating the number of cycles of cracking, for indicating the fatigue loss of the metal material, E g Represents the elastic modulus, sigma, of the metal material a Sum sigma ω Representing the stress and fatigue strength limit values of the material at the calculated points respectively,representing the coefficient of area reduction of the material.
Preferably, in the step 2, the linear constraint after the equivalent conversion is
Wherein, c 1 And c 2 Is a constant arbitrarily greater than 0, a and b are Boolean variables having a value of 0 or 1, S g,i,t Is a 0-1 variable.
Preferably, in the step 4, there are also electric power balance constraint, thermal power unit maximum and minimum output constraint and CHP unit maximum and minimum output constraint, which are specifically as follows,
the electric power balance constraint is that,
wherein P is ce,i,t For the electric power of the ith CHP set in the period t,
the thermal power balance constraint is that,
wherein P is ch,i,t For the thermal power of the ith CHP unit in the t period,for the demand of the thermal load at the moment t, the output of the thermal power conventional unit meets the following constraint,
the output of the thermal power conventional unit meets the following constraint,
the output of the thermal power depth peak shaver set meets the following constraint,
the output of the CHP set should be satisfied,
in the method, in the process of the invention,and->Minimum and maximum electric power of the ith CHP unit, respectively, < >>And->The minimum and maximum heat powers of the ith CHP unit are respectively.
Preferably, the method also comprises a rotation standby constraint, a start-stop constraint and a unit climbing constraint, and concretely comprises that the rotation standby constraint is that,
in the method, in the process of the invention,and R is down,t The upper and lower climbing limit values of the thermal power generating unit are respectively set;
when the running state of the thermal power generating unit at the time t is different from the running state at the adjacent time, the output of the unit is equal to the minimum output value so as to ensure the safe and stable running of the unit, the start-stop constraint is that,
the climbing constraint of the unit is that
And->The upper climbing limit value and the lower climbing limit value of the thermal power generating unit are respectively +.>And->The upper and lower climbing limit values of the CHP unit are respectively set.
The beneficial effects of the invention are as follows:
(1) The traditional 'electricity by heat fixation' is broken through by the heat storage device at the source side, the electric heating characteristic curve of the CHP unit is improved, and meanwhile, the electric power regulation capacity and the regulation flexibility are improved through deep peak regulation of the thermal power unit;
(2) The load side coordinates the electricity utilization behavior of a user through a demand response model based on peak regulation excitation electricity price and time-sharing electricity price, so that the peak-valley difference of the power grid is reduced;
(3) The source-load side combined optimization peak shaving method aims at minimizing the total dispatching cost of the system, comprehensively considers the heat storage constraint, the life loss cost of the thermal power generating unit, the user response satisfaction constraint and the like, optimizes the peak shaving effect of the system while maximally reducing the dispatching operation cost of the system, reduces the wind power waste air quantity, and further promotes the large-scale wind power friendly grid connection.
Drawings
FIG. 1 is a schematic diagram of a heat storage CHP and thermal power deep regulating combined optimization peak regulating method considering user side response.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to fig. 1 of the drawings, it being apparent that the embodiments described are only some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments that may be obtained by a person of ordinary skill in the art without making any inventive effort fall within the scope of the present invention.
In the description of the present invention, it should be understood that the terms "counterclockwise," "clockwise," "longitudinal," "transverse," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, are merely for convenience in describing the present invention, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention.
As shown in FIG. 1, the prior literature researches the wind farm and conventional thermal power unit combined peak regulation scheduling method on the basis of considering the demand response by considering the heat storage CHP and thermal power deep regulation combined optimization peak regulation method of the user side response, and proves that the method can effectively improve the running economy of the system and reduce the wind abandoning phenomenon, and comprises the following steps:
step 1: according to the heat storage device, a heat storage model is built, and when the heat storage capacity of the heat storage device at the time t is C hs,t The thermal storage model is that,
C hs,t ＝(1-σ)C hs,t-1 +P hs,t
wherein sigma is the self-heat release rate of the heat storage device, i.e. the heat energy loss rate of the heat storage device per unit time, P hs,t For charging and discharging heat power of the heat storage device at the time t, P hs,t <0 indicates that the heat storage device is releasing heat, P hs,t >0 indicates that the heat storage device is in a heat storage state, the heat storage amount of the heat storage device should satisfy the following constraint,
wherein,and->Respectively representing the minimum and maximum heat storage capacity allowed by the heat storage device,/->And->Respectively represent the minimum and maximum heat storage power allowed by the heat storage device, when +.>And->When the value is negative, the minimum heat release power and the maximum heat release power are represented, and the step 2 is executed;
step 2: the deep regulating model of the thermal power unit is established according to the thermal power unit to obtain the deep regulating cost of the thermal power unit, and the deep regulating cost of the thermal power unit can be divided into a non-oil-feeding deep regulating stage and an oil-feeding deep regulating stage according to different depths, wherein in the non-oil-feeding stage, the deep regulating cost comprises start-stop, coal consumption cost and life loss cost, and in the oil-feeding deep regulating stage, the cost consists of coal consumption, start-stop cost, life loss cost and oil feeding cost together, the deep regulating cost of the thermal power unit (comprising the peak regulating cost of a conventional unit) is as follows,
C g_deep ＝C g +aC l +bC o
wherein C is o For oil cost, a and b are Boolean variables, p o The oil charging price of the peak regulating electric quantity per unit depth of the thermal power unit is O g,i,t The integrated electric quantity is obtained when the actual power of the ith thermal power generating unit is deeply regulated in the t period and is lower than the steady combustion load value of deep regulation without oil throwing;for the ith unit, the load power is regulated and stabilized without adding oil, and the load power is increased>The oil feeding depth of the ith unit is used for regulating and stabilizing the combustion load power,for the minimum technical output of the ith thermal power unit,/->Maximum technical output of ith thermal power unit, C l Representing the economic cost of life loss required by the unit to participate in deep peak shaving, T represents a scheduling periodStage I g Representing the number of thermal power generating units, and executing the step 3;
step 3: constructing a user response model, the user-side response can be generally divided into three modes: the load can be transferred, the load can be interrupted and the load can be increased and regulated, and the peak regulation optimization and regulation for promoting the wind power absorption are mainly studied, so that the peak regulation of the load can be interrupted is not considered. The peak regulation excitation rewards can be obtained by increasing the load, but the electricity cost is increased, the benefit is low, and therefore, the user response model participating in the combined peak regulation is not considered, and only the transferable load is considered. Taking account of electricity consumption expenditure conditions before and after user response, introducing a user response satisfaction parameter S dr,n A user response model is constructed, specifically as follows,
the users as power consumers participate in peak shaving service to meet certain satisfaction constraint so as to ensure the power quality,
the capacity and time period of regulation of the transferable load should satisfy the following constraint,
the time-of-use electricity price before and after optimization should satisfy the following constraint:
ρ Rmin ≤ρ t R ≤ρ Rmax
wherein S is dr,n User satisfaction, delta, for nth participation demand response n,t For the demand response decision variable, delta, of the load n at time t n,t When=1, the load responds, and the transfer power is Δp load,n,t A positive value indicates that the user increases the power, a negative value indicates that the user decreases the power,for the optimized time-sharing electricity price, +.>To optimize the electricity price before P load,n,t For the load power after demand response, +.>To optimize the pre-load power, the total amount of power used by the user in a scheduling period is kept constant, +.> For a minimum value of user response peak shaving satisfaction in one scheduling period, +.>And->Respectively represent nth usersMinimum and maximum allowed load transfer power, t np Load adjustable time period allowed for nth user ρ Rmin And ρ Rmax Respectively the minimum and maximum limit values of time-of-use electricity price, deltaρ Rmin And Δρ Rmax Step 4 is executed for the minimum and maximum value of the response quantity allowed by the time-sharing electricity price respectively;
step 4: the method comprises the steps of taking electric load, time-sharing electricity price and heat charging and discharging power of a heat storage device as optimization variables, minimizing total system scheduling cost as an optimization target, calculating total scheduling cost, carrying out peak scheduling by considering user response, CHP (common heat generation) and thermal power depth peak scheduling multi-main body combined optimization of the heat storage device, wherein the optimization variables are the electric load, the time-sharing electricity price and the heat charging and discharging power of the heat storage device, the optimization target is the total system scheduling cost minimization, the total scheduling cost comprises thermal power unit operation cost, CHP unit operation cost, wind power operation maintenance cost and wind discarding punishment cost, and the total scheduling cost is
min C s ＝C g_deep +C h +C w +C w_curt
In order to maintain stable heat supply, the CHP unit is not allowed to stop normally, so the operation cost of the CHP unit is expressed as
P ceh,i,t ＝P ce,i,t +ξP ch,i,t
Wherein C is g_deep The method is thermal power unit operation cost, including conventional unit operation cost and thermal power unit depth peak regulation cost; c (C) h For the operation cost of the CHP unit, C w For the wind power operation and maintenance cost,C w_curt to pay for wind disposal, alpha i 、β i 、γ i Is the coal consumption coefficient, P of the CHP unit ce,i,t And P ch,i,t The electric power and the thermal power values of the ith CHP unit in the t period are respectively, P ceh,i,t For the power generated by the ith CHP unit at the moment t, xi represents the electric power value reduced when the CHP unit increases the unit thermal power, theta is the wind power operation and maintenance cost coefficient, and P w_r,t The actual output power of wind power at the moment t is mu, the cost coefficient of wind abandon punishment is P w_f,t And predicting power for the wind power at the moment t.
In the step 2, the peak shaving cost is affected by the peak shaving depth when the thermal power generating unit participates in the deep shaving, and the larger the peak shaving depth is, the larger the service life loss of the unit is, so that the service life loss cost of the unit is considered in addition to the coal consumption cost when the thermal power generating unit participates in the deep shaving scene, and the service life loss cost C of the unit is considered l Is that
Wherein, gamma g,i,t In the state of participating in deep regulation at t moment of ith thermal power generating unit, gamma g,i,t =1 represents the unit participating in deep peak regulation, γ g,i,t =0 means that the unit does not participate in deep tone; c (C) l Represents the economic cost of life loss required by the unit to participate in deep peak shaving, Y g For the price of the machine set, N g Indicating the number of cycles of cracking, for indicating the fatigue loss of the metal material, E g Represents the elastic modulus, sigma, of the metal material a Sum sigma ω Representing the stress and fatigue strength limit values of the material at the calculated points respectively,representing the coefficient of area reduction of the material.
It should be noted that, in the step 2, the linear constraint after the equivalent conversion is
Wherein, c 1 And c 2 Is a constant arbitrarily greater than 0, a and b are Boolean variables having a value of 0 or 1, S g,i,t Is a 0-1 variable.
It is worth to be noted that, in the step 4, there are also electric power balance constraint, thermal power unit maximum and minimum output constraint and CHP unit maximum and minimum output constraint, concretely as follows,
the electrical power balance constraints (without network loss),
wherein P is ce,i,t For the electric power of the ith CHP set in the period t,
the thermal power balance constraint ignores the heat energy loss of the heat storage device in the transmission process,
wherein P is ch,i,t For the thermal power of the ith CHP unit in the t period,for the demand of the thermal load at the moment t, the output of the thermal power conventional unit meets the following constraint,
the output of the thermal power conventional unit meets the following constraint,
the output of the thermal power depth peak shaver set meets the following constraint,
the output of the CHP set should be satisfied,
in the method, in the process of the invention,and->Minimum and maximum electric power of the ith CHP unit, respectively, < >>And->The minimum and maximum heat powers of the ith CHP unit are respectively.
It is worth to say, also includes rotation standby constraint, start-stop constraint and unit climbing constraint, specifically, the rotation reserve constraint is that,
in the method, in the process of the invention,and R is down,t The upper and lower climbing limit values of the thermal power generating unit are respectively set;
when the running state of the thermal power generating unit at the time t is different from the running state at the adjacent time, the output of the unit is equal to the minimum output value so as to ensure the safe and stable running of the unit, the start-stop constraint is that,
the climbing constraint of the unit is that
And->The upper climbing limit value and the lower climbing limit value of the thermal power generating unit are respectively +.>And->The upper and lower climbing limit values of the CHP unit are respectively set.
It is worth to say that, according to the above-mentioned optimization objective and constraint conditions, a CPLEX solver is adopted to solve, and a yanminip tool box is used to call the CPLEX in MATLAB, so that the model is converted into a mixed integer programming problem.
In summary, the working principle of the embodiment is that the model optimizes the electric load, the time-of-use electricity price and the charging and discharging power of the heat storage device, so that the total scheduling cost of the system (comprising the running cost of the thermal power unit, the running cost of the CHP unit, the wind power operation maintenance cost and the wind discarding punishment cost) is minimized, the peak regulation economy is ensured, meanwhile, the wind discarding quantity is reduced, the new energy consumption is promoted, the heat storage device is arranged in the thermodynamic system at the source side, the traditional 'fixed electricity with heat' is broken, the electric heating characteristic curve of the CHP unit is improved, the wind power is stored in a large heat generation period, the heat is released in a heat peak period of a user, the wind discarding problem caused by wind power uncertainty fluctuation is effectively relieved, and the wind power consumption space is enlarged; meanwhile, the source side thermal power generating unit participates in deep peak regulation to improve power regulation capacity and regulation flexibility, peak regulation cost modeling of different peak regulation depths is performed based on unit life loss cost, the load side coordinates the power consumption behavior of a user through a demand response model based on dynamic time-of-use power price, peak-valley difference of a power grid is reduced, the consumption expenditure conditions of power consumption before and after user response are considered, and a user response satisfaction parameter is introduced to realize economic regulation and control of peak regulation resources of the user side.
Claims (5)
1. The heat storage CHP and thermal power deep regulating combined optimization peak regulating method considering user side response is characterized by comprising the following steps of:
step 1: according to the heat storage device, a heat storage model is built, and when the heat storage capacity of the heat storage device at the time t is C hs,t The thermal storage model is that,
C hs,t ＝(1-σ)C hs,t-1 +P hs,t
wherein sigma is the self-heat release rate of the heat storage device, i.e. the heat energy loss rate of the heat storage device per unit time, P hs,t For charging and discharging heat power of the heat storage device at the time t, P hs,t <0 indicates that the heat storage device is releasing heat, P hs,t >0 indicates that the heat storage device is in a heat storage state, the heat storage amount of the heat storage device should satisfy the following constraint,
wherein,and->Respectively represent storageMinimum and maximum heat storage capacity allowed by the thermal device, < > for>And->Respectively represent the minimum and maximum heat storage power allowed by the heat storage device, when +.>And->When the value is negative, the minimum heat release power and the maximum heat release power are represented, and the step 2 is executed;
step 2: establishing a thermal power deep regulating model according to a thermal power unit to obtain thermal power deep regulating cost, wherein the thermal power deep regulating cost is,
C g_deep ＝C g +aC l +bC o
wherein C is o For oil cost, a and b are Boolean variables, p o The oil charging price of the peak regulating electric quantity per unit depth of the thermal power unit is O g,i,t The integrated electric quantity is obtained when the actual power of the ith thermal power generating unit is deeply regulated in the t period and is lower than the steady combustion load value of deep regulation without oil throwing;for the ith unit, the load power is regulated and stabilized without adding oil, and the load power is increased>Oil injection deep regulation stable combustion load power for ith unit,/->For the minimum technical output of the ith thermal power unit,/->Maximum technical output of ith thermal power unit, C l Represents the economic cost of life loss required by the unit to participate in deep peak shaving, T represents a scheduling period, I g Representing the number of thermal power generating units, P g，i，t Step 3 is executed for technical output of the ith thermal power generating unit at the moment t;
step 3: a user response model is constructed, specifically as follows,
wherein S is dr,n User satisfaction, delta, for nth participation demand response n,t For the demand response decision variable, delta, of the load n at time t n,t When=1, the load responds, and the transfer power is Δp load,n,t A positive value indicates that the user increases the power, a negative value indicates that the user decreases the power,for the optimized time-sharing electricity price, +.>To optimize the electricity price before P load,n,t For the load power after demand response, +.>To optimize the pre-load power, the total amount of power used by the user in a scheduling period is kept constant, +.> For a minimum value of user response peak shaving satisfaction in one scheduling period, +.>Andrespectively represent the minimum and maximum load transfer power allowed by the nth user, t np Load adjustable time period allowed for nth user ρ Rmin And ρ Rmax Respectively the minimum and maximum limit values of time-of-use electricity price, deltaρ Rmin And Δρ Rmax Step 4 is executed for the minimum and maximum value of the response quantity allowed by the time-sharing electricity price respectively;
step 4: taking the electric load, the time-sharing electricity price and the charging and discharging power of the heat storage device as optimization variables, minimizing the total dispatching cost of the system as an optimization target, calculating the total dispatching cost, wherein the total dispatching cost is
min C s ＝C g_deep +C h +C w +C w_curt
P ceh,i,t ＝P ce,i,t +ξP ch,i,t
Wherein C is g_deep The method is thermal power unit operation cost, including conventional unit operation cost and thermal power unit depth peak regulation cost; c (C) h For the operation cost of the CHP unit, C w C is wind power operation and maintenance cost w_curt To pay for wind disposal, alpha i 、β i 、γ i Is the coal consumption coefficient, P of the CHP unit ce,i,t And P ch,i,t The electric power and the thermal power values of the ith CHP unit in the t period are respectively, P ceh,i,t For the power generated by the ith CHP unit at the moment t, xi represents the electric power value reduced when the CHP unit increases the unit thermal power, theta is the wind power operation and maintenance cost coefficient, and P w_r,t The actual output power of wind power at the moment t is mu, the cost coefficient of wind abandon punishment is P w_f,t Wind power prediction power is carried out for the moment t; i h Is the number of CHP units.
2. The method for optimizing and peak shaving by combining heat storage CHP and thermal power deep shaving in consideration of user side response according to claim 1, wherein in said step 2, life loss cost C of the unit l Is that
Wherein, gamma g,i,t In the state of participating in deep regulation at t moment of ith thermal power generating unit, gamma g,i,t =1 represents the unit participating in deep peak regulation, γ g,i,t =0 means that the unit does not participate in deep tone; c (C) l Represents the economic cost of life loss required by the unit to participate in deep peak shaving, Y g，i Price of ith thermal power generating unit, N g Indicating the number of cycles of cracking, for indicating the fatigue loss of the metal material, E g Represents the elastic modulus, sigma, of the metal material a Sum sigma ω Representing the stress and fatigue strength limit values of the material at the calculated points respectively,representing the coefficient of area reduction of the material.
3. The method for optimizing and peak shaving by combining heat storage CHP and thermal power deep shaving with consideration of user side response according to claim 2, wherein in the step 2, the linear constraint after equivalent conversion is as follows
Wherein, c 1 And c 2 Is a constant arbitrarily greater than 0, a and b are Boolean variables having a value of 0 or 1, S g,i,t Is a 0-1 variable.
4. The method for optimizing and regulating peak by combining heat storage CHP and thermal power deep regulating with consideration of user side response according to claim 3, wherein in the step 4, electric power balance constraint, thermal power unit maximum and minimum output constraint and CHP unit maximum and minimum output constraint are further included, concretely comprising the following steps,
the electric power balance constraint is that,
wherein P is ce,i,t For the electric power of the ith CHP set in the period t,
the thermal power balance constraint is that,
wherein P is ch,i,t For the thermal power of the ith CHP unit in the t period,as the required amount of the heat load at the time t,
the output of the thermal power conventional unit meets the following constraint,
the output of the thermal power depth peak shaver set meets the following constraint,
the output of the CHP set should be satisfied,
in the method, in the process of the invention,and->Minimum and maximum electric power of the ith CHP unit, respectively, < >>And->The minimum and maximum heat powers of the ith CHP unit are respectively.
5. The heat storage CHP and thermal power deep tone combined optimization peak shaving method considering user side response according to claim 4 is characterized by further comprising rotation standby constraint, start-stop constraint and unit climbing constraint, and specifically comprising,
the rotation reserve constraint is that,
in the method, in the process of the invention,and->The upper and lower climbing limit values of the thermal power generating unit are respectively set; />The method comprises the steps of providing the minimum technical output of an ith thermal power unit in a t period; />The maximum technical output of the ith thermal power unit in the t period is obtained;
when the running state of the thermal power generating unit at the time t is different from the running state at the adjacent time, the output of the unit is equal to the minimum output value so as to ensure the safe and stable running of the unit, the start-stop constraint is that,
the climbing constraint of the unit is that
And->The upper climbing limit value and the lower climbing limit value of the thermal power generating unit are respectively +.>And->The upper and lower climbing limit values of the CHP unit are respectively; s is S g，i，t-1 A variable of 0-1 represents the start-stop state of the unit at the time t-1; s is S g，i，t+1 A variable of 0-1 represents the start-stop state of the unit at the time t+1; p (P) g，i，t+1 The technical output of the ith thermal power generating unit at the time t+1 is realized.
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