CN109472050B - Thermal inertia-based hybrid time scale scheduling method for cogeneration system - Google Patents
Thermal inertia-based hybrid time scale scheduling method for cogeneration system Download PDFInfo
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Abstract
The invention provides a mixed time scale scheduling method of a cogeneration system based on thermal inertia, which comprises the steps of firstly establishing a regional heat supply network thermal inertia model and a building thermal inertia model, secondly establishing a mixed time scale scheduling model of the cogeneration system, including a day-ahead scheduling model, a day-in-rolling scheduling model, a real-time scheduling model and an automatic power generation control model, and finally respectively determining scheduling time scales of power supply and heating equipment under the day-ahead scheduling model, the day-in-rolling scheduling model and the real-time scheduling model based on equipment operation constraint and load characteristics. The mixed time scale scheduling method fully considers the difference of the transmission network and the load characteristic of the electric subsystem and the thermal subsystem, adds the thermal inertia of the heating system as a constraint condition into an optimal scheduling model, coordinates the mutual matching of the four models, furthest promotes the heat and power cogeneration system to consume renewable energy sources, and gradually reduces the influence of renewable energy sources and load uncertainty on the power balance of the system.
Description
Technical Field
The invention relates to an optimal scheduling method for a cogeneration system, and particularly belongs to the technical field of energy system operation optimization.
Background
Cogeneration (Combined Heat and Power Generation, CHP) has gained widespread attention in the world and industry as an efficient way of energy utilization. By the end of 2016, the world cogeneration unit total capacity has reached 755.2GW, where the asia-pacific and european areas occupy 46% and 39%, respectively. In the netherlands, finland and denmark, cogeneration units already occupy more than 60% of the total number of thermal power units; in China, 80% of industrial heat supply and 30% of civil heat supply are provided by cogeneration units.
On one hand, the cogeneration unit brings good benefits in terms of improving the energy utilization rate and reducing the environmental pollution; on the other hand, the strong coupling between the generation and heating of the units limits the operational flexibility of the system, which problem will be increasingly pronounced as more and more renewable energy sources with random output characteristics (such as wind power and photovoltaic) are connected to the grid. For example, in northeast China, the winter night thermal load demands are much greater than daytime, which is in contrast to the output electrical power characteristics of wind farms. Because the cogeneration unit usually operates in a mode of 'fixed-temperature electricity', the thermal power output of the unit has to be increased at night in order to meet a large amount of thermal load demands, and the electric power output of the unit also increases, so that the excessive electric power occupies a space for absorbing a large amount of wind power at night, and the wind power has to be abandoned in a large scale in order to ensure the safe and stable operation of the system. According to the statistical data of the national energy bureau, the total waste air volume of the nation reaches 419 hundred million kilowatt-hours in 2017, and the waste air proportions of Gansu, xinjiang and Jilin provinces reach 33%, 29% and 21% respectively. Therefore, how to coordinate the popularization of the cogeneration unit and promote the wind power consumption has become a key problem for preventing the sustainable development of the cogeneration system.
Although there have been proposed measures for improving wind power consumption by providing active energy storage devices such as energy storage stations, heat storage tanks, and using passive heat storage devices represented by thermal inertia of regional heat supply networks and heat storage characteristics of buildings. However, these measures require additional investment costs and have limited potential for wind power.
Disclosure of Invention
The invention aims to: the invention provides a mixed time scale scheduling method of a cogeneration system based on thermal inertia, which aims to reduce investment cost and promote the cogeneration system to consume renewable energy sources to the greatest extent.
The technical scheme is as follows: the invention provides a mixed time scale scheduling method of a cogeneration system based on thermal inertia, which comprises the following steps of firstly establishing a thermal inertia model of a heating system based on thermodynamic law, wherein the model comprises two aspects: firstly, a regional heating network thermal inertia model caused by transmission delay and heat storage capacity of the regional heating network; and secondly, a building thermal inertia model is caused by the heat storage property of the building enclosure structure. And secondly, a mixed time scale scheduling model of the cogeneration system is built, wherein the mixed time scale scheduling model comprises four models, namely a day-ahead scheduling model, a day-in-day rolling scheduling model, a real-time scheduling model and an automatic power generation control model, power supply and heat equipment in each model are scheduled according to different time scales, and the four models are matched with each other, so that the influence of renewable energy sources and load uncertainty on the power balance of the system is reduced step by step. And finally, considering the difference of the electric subsystem and the thermal subsystem in the aspect of operation characteristics, and respectively determining the scheduling time scales of each power supply and heating device under a day-ahead scheduling model, a day-in rolling scheduling model and a real-time scheduling model based on the equipment operation constraint and the load characteristics.
The beneficial effects are that: the mixed time scale scheduling method fully considers the difference of the transmission network and the load characteristic of the electric subsystem and the thermal subsystem, adds the thermal inertia of the heating system as a constraint condition into an optimal scheduling model, coordinates the mutual matching of the four models, can furthest promote the heat and power cogeneration system to consume renewable energy sources, and gradually reduces the influence of renewable energy sources and load uncertainty on the power balance of the system.
Drawings
FIG. 1 is a system block diagram of the present invention;
FIG. 2 is a flow chart of the present invention;
FIG. 3 is a graph of the electrical power scheduling results of the present invention;
fig. 4 is a thermal power scheduling result diagram of the present invention.
Detailed Description
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
As shown in fig. 1, the cogeneration system of this embodiment is composed of a large power grid, a cogeneration unit, an electric boiler, a distributed heat pump, an energy storage power station, a fan, a generator, and a gas boiler. In the system, a cogeneration unit bears heat supply base load, the electric power shortage is compensated by a generator, a power grid, a fan and energy storage equipment, and the heat power shortage is compensated by an electric boiler, a gas boiler and a distributed heat pump. The system is connected with a large power grid through a connecting line, electricity can be purchased from the power grid and sold to the power grid, the system simultaneously provides energy requirements for electricity and heat loads, and the dispatching center performs unified optimization through input prediction information, price information, room temperature constraint and system operation constraint and then issues an optimization operation instruction to each device for execution.
As shown in fig. 2, the hybrid time scale scheduling method of the cogeneration system based on thermal inertia in this embodiment specifically includes the following steps:
step 1: establishing a thermal inertia model of the heating system, wherein the model comprises two aspects: and (3) a step of: establishing a thermal inertia model of the regional heating network caused by the transmission delay and the heat storage capacity of the regional heating network, and secondly: building a building thermal inertia model caused by the heat storage characteristic of the building enclosure;
step 2: taking the thermal inertia model of the heating system as a constraint condition, and establishing a mixed time scale scheduling model of the cogeneration system;
step 3: determining the scheduling time scale of each power supply and heat supply device according to a building thermal inertia model and a combined time scale scheduling model of a cogeneration system, wherein each heat supply device comprises: the respective heating apparatuses include: cogeneration units, gas boilers, distributed heat pumps, and electric boilers.
The thermal inertia model of the regional heating network in the step 1 comprises the following steps: the method comprises the steps of carrying out transmission delay on a heating medium between two adjacent nodes in a regional heating network, a temperature model of the heating medium at any node, a heat storage characteristic model of the heating network and a temperature loss model;
the transmission delay of the heat medium in the regional heat supply network between two adjacent nodes is as follows:
wherein ,τij The transmission delay of the pipe section between the node i and the node j is; l (L) ij The length of the pipe section between the node i and the node j; v ij The flow rate of the hot coal in the pipe section between the node i and the node j;
the temperature model of the heating medium at any node is as follows:
wherein ,Ti For the temperature of the heating medium at the node i, q ki The heat medium flow in the pipe section connected with the node k to the node i; t (T) ki The temperature of the heating medium at the node i end in the pipe section connected from the node k to the node i is set; s is S i The method comprises the steps that the node sets are directly connected with the node i and the heat medium flows to the node i;
the heat storage characteristic model of the heat supply network is represented by the change range of the temperature of the heat medium, and specifically comprises the following formula:
wherein ,Tin,x and Tout,x The temperature of the heating medium flowing into and out of the pipeline x respectively; subscripts min and max are respectively the minimum value and the maximum value of the corresponding physical quantity; s is S p Is a set of all pipes;
the temperature loss model is as follows:
when the inlet temperature and the outlet temperature of the heating medium in one pipeline are required to meet the formula 4, the heat loss is regarded as energy loss generated when the heat storage network is used as energy storage equipment for charging and discharging heat;
wherein ,Tair,ex Is the outdoor ambient temperature; l (L) x Is the length of x pipe; r is the thermal resistance of the pipeline; c w Is the specific heat capacity of the heating medium;the mass flow of the heating medium in the pipeline x is shown, and e is the base number of natural logarithm;
building a building thermal inertia model;
because the building enclosure structure has larger thermal resistance, the room temperature changes slowly along with the external temperature under the condition of unchanged heat supply, and the building enclosure structure presentsAn "inertial" feature is presented. Meanwhile, for heating buildings such as civil heating buildings and the like which are mainly comfortable, a change interval (generally 18-26 ℃ in China) is usually reserved at room temperature, and the change interval provides a certain space for heat storage of the buildings. Building indoor temperature T air Satisfies the thermodynamic equation shown in (5)
Step 1.1, establishing a thermodynamic equation:
wherein ,Tair For building indoor temperature, Q in The heat dissipation power of the radiator; and />Heat transfer and heat consumption power, cold air permeation and heat consumption power, cold air intrusion and ventilation and heat consumption power of building envelope respectively, c air 、ρ air 、V air Specific heat capacity, density and volume of indoor air respectively; t (T) air,0 The room temperature is the initial time; t is a time variable;
the said and />The calculation method comprises the following steps:
wherein ,Kenv The heat transfer coefficient of the building envelope; f (F) env The heat dissipation area is just opposite to the building; gamma is a temperature difference correction coefficient; x is x h 、x o and xw The room height addition rate, the orientation correction rate and the wind power addition rate are respectively;constant pressure specific heat capacity for outdoor air; ρ air,ex Is the density of the outdoor air; l (L) infil Is the cold air quantity of permeation; n is the cold air invasion additional rate of the outer door;heat consumption caused by heat transfer to the outer door of the building; η is the ratio of the basic heat consumption power of the outer door to the total basic heat consumption power of the building; l (L) ven The ventilation amount required for the building;
step 1.2, establishing a countercurrent hot water-air heat exchanger model:
wherein ,KRad and FRad The heat transfer coefficient and the heat dissipation area of the radiator are respectively; beta is the comprehensive correction coefficient of the number of radiator assembly sheets, the connection form and the installation form; t (T) av The average temperature of the heating medium in the radiator; t (T) in and Tout The water inlet temperature and the water outlet temperature of the radiator are respectively; m is m w Is the flow of the heating medium;
step 1.3: the relationship between the heat dissipation power and the water supply temperature and the indoor temperature of the heat supply network can be obtained by the formula 7:
step 1.4: setting up coefficients alpha, alpha 1 、α 2 and α3 ，α、α 1 、α 2 and α3 The calculation formula is as follows:
by combining coefficients alpha, alpha 1 、α 2 and α3 Substituting into formula 5, the reduction can be obtained:
the discrete solution is obtained as follows:
where n is the number of scheduled time intervals, n=0, 1,2 …; Δt is the scheduled time interval;a water supply temperature for the b-th schedule period; />B=n for the outdoor temperature of the b-th scheduling period;
in order to ensure heating comfort, the room temperature fluctuates within a certain range:
wherein , and />The lower and upper limits of room temperature, respectively.
In step 2, the hybrid time scale scheduling model of the cogeneration system includes: a day-ahead scheduling model, a day-in rolling scheduling model, a real-time scheduling model and an automatic power generation control model.
Typical equipment commonly found in cogeneration systems is divided into three categories according to how long the equipment responds to scheduling instructions: the first is a slow response device, with response times between half an hour and several hours, typically executing scheduling instructions in a day-ahead or day-ahead rolling scheduling model; the second type is a fast response device, with response times between one minute and half an hour, typically acting in a daily rolling schedule model or a real-time schedule model; the third type is an ultrafast response device, with response times within one minute, typically acting in a real-time dispatch or automatic generation control (Automatic Generation Control, AGC) model. The classification of a typical device is shown in table 1.
TABLE 1 typical device class
The specific establishment steps of the day-ahead scheduling model are as follows:
step 2.1: the cogeneration system operates under the constraint of a regional heat supply network thermal inertia model, a building thermal inertia model, node flow balance, greenhouse average temperature and grid operation, the power supply equipment is updated once in one hour, and the heat supply equipment is updated once in 1-24 hours;
the thermal inertia model of the heat supply network is shown in formulas 1-4, the thermal inertia model of the building is shown in formulas 11-12, and the node flow balance is shown in formula 13:
wherein, the flow flowing into the node i is positive, and the flow flowing out is negative.
The average greenhouse temperature is shown in formula 14:
wherein ,for the average value of the temperature in the inner chamber of a day, t represents the time period,/->The indoor temperature is t time period; the temperature is generally 22 ℃ in winter;
step 2.2; an objective function is established, the following daily operation cost is minimized as a target, and the specific objective function is as follows:
wherein , and />Representing fuel cost, operation maintenance cost, tie line interaction cost and wind abandon penalty cost of the t-period system respectively, wherein ∈> and />The specific calculation method comprises the following steps:
wherein and />Respectively representing the consumption of delta fuel in t period and the price of the fuel; /> and />Respectively representing the consumption of the lambda-th fuel and the price of the lambda-th fuel in the t period; /> and />Respectively representing the electric power output by sigma-th power supply equipment in t period and the operation maintenance coefficient of the equipment; /> and />Respectively represent the t period of time gamma 1 The heat power output by the heat supply equipment and the operation maintenance coefficient of the equipment; p (P) t tie,p and />Respectively representing the electric power injected on the time period connecting line and the electricity price on the time period connecting line; p (P) t tie,s and />Respectively representing the electric power output on the time period connecting line and the electricity price on the time period connecting line; p (P) t wind,real and Pt wind,cons Respectively representing the actual output power of the wind power plant and the consumed wind power in the period t; p is p wind Representing a wind abandon punishment coefficient; s is S fuel 、S sele 、S elec and Sheat Respectively representing a set of fuels used by the system without the unit combination equipment, a set of fuels used by the unit combination equipment, a set of system power supply equipment and a set of system heat supply equipment.
Step 2.3; according to the result of the objective function, the system directly obtains the next day of unit combination, the start-stop state and the planned output value of the power supply/heating equipment and the transmission power of the system interconnecting line. And (5) taking a daily rolling scheduling model as a reference.
The specific day-ahead scheduling model table is shown in table 2:
TABLE 2 day-ahead scheduling model
The specific construction of the daily rolling scheduling model comprises the following steps:
step 3.1: the cogeneration system operates under the constraint of a regional heating network thermal inertia model, a building thermal inertia model, node flow balance, greenhouse average temperature and power grid operation, and power supply equipment in the daily rolling scheduling model is updated once in 15-30 minutes, and heat supply equipment is updated once in 15-6 hours;
step 3.2: the method aims at minimizing the running cost within 2-8 hours in the future, carrying out rolling correction on the power supply and heating equipment running time of the residual time, and establishes the objective function as follows:
in the intra-day rolling schedule model,at t 1 Time-period system fuel cost, operation maintenance cost, tie-line interaction cost and wind-abandoning punishment cost, the calculation method refers to formula 16, and the parameter t is calculated 1 Substituting the time interval delta t between the power supply equipment and the daily rolling scheduling model into a formula 16, wherein R is the scheduling time scale of the power supply equipment; />The number of times is corrected for scrolling; z is the predicted time of each round of rolling correction;
step 3.3: based on the result of the objective function, the system directly obtains the actual processing value of the slow/fast response device, the planned transmission power of the system link, and the reserved capacity of the slow/fast response device. For reference to the real-time scheduling model, the specific daily rolling scheduling model table is shown in table 3:
table 3 Rolling scheduling model within day
The specific steps of the real-time scheduling model are as follows:
step 4.1: the cogeneration system operates under the constraints of a regional heating network thermal inertia model, a building thermal inertia model, node flow balance, greenhouse average temperature and grid operation, the power supply equipment is updated once in 5-15 minutes, and the heating equipment is updated once in 5-30 minutes;
step 4.2: in order to minimize the deviation between the actual power of the tie line within 2-8 hours in the future and the power in the rolling schedule model in the day, an objective function is established as follows:
wherein ,R2 A schedule time scale for the power supply device; t is t 2 For scheduling time, Z 2 The predicted time optimized for each round of scrolling,representing t 2 Real-time interactive power on time-of-day link, +.>Representing t 2 The interaction power of the model stage is rolled and scheduled in the day on the time connecting line.
Step 4.3: according to the objective function, the system directly obtains the actual output value of the quick response equipment, the time transmission power of the system interconnection line and the reserved capacity of the ACG unit. Taking an automatic power generation control model as a reference, wherein a specific real-time scheduling model is shown in a table 4;
table 4 real-time scheduling model
The automatic power generation control model mainly comprises correction control and blocking management, wherein the correction control utilizes the capacity information of a second-level AGC unit reserved in the real-time scheduling model, and the AGC unit is scheduled in real time by combining with AGC software, so that the system frequency and the power transmission of a connecting wire reach the assessment index of an information physical system; the blocking management is used for processing the problem of line section power flow out-of-limit in real time, and the potential safety hazard is rapidly eliminated.
Determining the scheduling time scale of each power supply and heat supply device, wherein the large-scale cogeneration unit bears the heat supply base load, and if the selected scheduling time scale is too small, the unit is frequently operated, so that the operation and maintenance cost of the unit is greatly increased; if the selected scheduling time scale is too large, the unit acts once every quite long time, which may cause serious unbalance of the heat supply quantity and the heat demand quantity of the system, and the comfort level requirement of a heating user cannot be met. For a heating system with quantity adjustment or temperature change by stages, frequent change of the operation flow of a heat network easily causes large-scale fluctuation of the pressure of a primary pipe network, hidden danger of bursting of a pipeline exists, and a large-scale cogeneration unit under the operation mode is adopted by adopting a scheduling time scale as large as possible on the premise of meeting the comfort level requirement of a heating user. For a quality control heating system adopting quality control or changing flow in stages, hydraulic unbalance is not easy to occur, the influence of operation and maintenance cost under different scheduling time scales on the overall economy of the system can be considered, and the scheduling time scale is determined by maximizing the system operation economy and specifically comprises the following aspects:
1. the method comprises the following specific steps of determining the scheduling time scale of a large-scale cogeneration unit of a quantity-regulated heating system or a temperature-regulated heating system by stages, wherein the specific steps are as follows:
step 5.1: for the case where the outside ambient temperature falls, an initial value of room temperature is given and the outside ambient temperature is assumed to fall in the worst case, as shown in formula 19:
wherein ,is the minimum value of the water supply temperature; />Is the maximum value of the outdoor temperature; />Is the maximum rate of outdoor temperature drop;
step 5.2: sequentially increasing the time from 0 by Δt until a critical time point is foundThe following conditions are satisfied:
equation 11 solving function using building thermal inertia modelObtained->The maximum scheduling time scale of the large-scale cogeneration unit under the condition;
step 5.3 for the case where the ambient temperature rises, given the initial value of room temperature and assuming that the ambient temperature rises in the worst case, as shown in equation 20:
wherein Is the maximum value of the water supply temperature; />Is the minimum value of the outdoor temperature; />Is the maximum rate of rise of outdoor temperature;
sequentially increasing the time from 0 by Δt untilFinding a critical point in timeThe following conditions are satisfied:
solving the function using equation 11Obtained->The maximum scheduling time scale of the large-scale cogeneration unit is the maximum scheduling time scale under the condition;
using the maximum schedule time scale for both cases in a system containing y heat users, the maximum schedule time scale for a large cogeneration unit can be determined by equation 23:
2. the method for determining the scheduling time scale of the large-scale cogeneration unit of the quality control heating system for quantitatively controlling or changing the flow in stages specifically comprises the following steps:
step 6.1, determining that the scheduling time scale of the large-scale cogeneration unit meets the following formula according to the operation constraint and the load characteristic of the equipment:
Δt min ≤Δt≤Δt max (24)
wherein Δtmin A minimum schedule time scale determined by unit operation constraints;
step 6.2: in the day-ahead scheduling model, day operation cost is taken as an objective function, and scheduling time intervals are taken as follows:
Δt＝ε min Δt I ,(ε min +1)Δt I ,...,(ε max -1)Δt I (25)
wherein ΔtI For supplying the day-ahead dispatch stageScheduling time intervals for the electrical devices; coefficient epsilon min and εmax The minimum and maximum allowable scheduling time intervals of the cogeneration unit are respectively represented,
where ceil () is an upward rounding function;
obtaining daily operation cost of the system under each scheduling time scale, and finally determining the scheduling time scale of the cogeneration unit according to the minimum daily operation cost;
scheduling time scale of other devices:
for the power supply equipment, the scheduling time scale can be selected according to a conventional method on the premise of meeting the operation constraint of the equipment, for example, a day-ahead scheduling model takes 1 hour, a day-in rolling scheduling model takes 15 minutes, a real-time scheduling model takes 5 minutes and an AGC model takes 10 seconds.
For the heat supply equipment, considering that the process of responding to the dispatching instruction is longer, the heat load does not require strict real-time balance of heat power, and only needs balance of heat supply quantity and heat demand in a period of time, the dispatching time interval of the heat supply equipment can be set to be 2-3 times of the dispatching time interval of the power supply equipment under the corresponding dispatching model, for example, the dispatching time interval of the heat storage equipment can be taken to be 2 hours in the day-ahead dispatching model, the dispatching time interval of the gas boiler and the distributed heat pump can be taken to be 30 minutes in the day-ahead rolling dispatching model, and the dispatching time scales of the equipment are shown in table 5;
table 5 scheduling time scale for each device
As shown in fig. 3, the day-ahead scheduling result, the day-ahead rolling scheduling result and the real-time scheduling result of the system electric power are shown, and it can be seen that the errors between the three and the actual output are reduced accordingly, so that the scheduling method in the embodiment gradually reduces the influence of the uncertainty of the system on the power balance of the system.
As shown in fig. 4, a day-ahead schedule result, a day-ahead scroll schedule result, and a real-time schedule result of the system thermal power are shown. Similarly, the errors of the three and the actual output are reduced, and meanwhile, the thermal power output and the thermal load do not need to be matched in real time by considering the thermal inertia of the heating system, but fluctuate around the thermal load in a small range, so that more flexibility is provided for the optimized operation of the system and the consumption of renewable energy sources.
In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction. The various possible combinations of the invention are not described in detail in order to avoid unnecessary repetition.
Claims (2)
1. The mixed time scale scheduling method of the cogeneration system based on thermal inertia is characterized by comprising the following steps of;
step 1: establishing a thermal inertia model of the heating system, wherein the model comprises two aspects: and (3) a step of: establishing a thermal inertia model of the regional heating network caused by the transmission delay and the heat storage capacity of the regional heating network, and secondly: building a building thermal inertia model caused by the heat storage characteristic of the building enclosure;
step 2: taking the thermal inertia model of the heating system as a constraint condition, and establishing a mixed time scale scheduling model of the cogeneration system;
step 3: determining a schedule time scale for each heating apparatus according to a building thermal inertia model and a cogeneration system hybrid time scale schedule model, the = each heating apparatus comprising: cogeneration units, gas boilers, distributed heat pumps and electric boilers;
the thermal inertia model of the regional heating network in the step 1 comprises the following steps: the method comprises the steps of carrying out transmission delay on a heating medium between two adjacent nodes in a regional heating network, a temperature model of the heating medium at any node, a heat storage characteristic model of the heating network and a temperature loss model;
the transmission delay of the heat medium in the regional heat supply network between two adjacent nodes is as follows:
wherein ,τij The transmission delay of the pipe section between the node i and the node j is; l (L) ij The length of the pipe section between the node i and the node j; v ij The flow rate of the hot coal in the pipe section between the node i and the node j;
the temperature model of the heating medium at any node is as follows:
wherein ,Ti For the temperature of the heating medium at the node i, q ki The heat medium flow in the pipe section connected with the node k to the node i; t (T) ki The temperature of the heating medium at the node i in the pipe section connected from the node k to the node i; s is S i The method comprises the steps that the node sets are directly connected with the node i and the heat medium flows to the node i;
the heat storage characteristic model of the heat supply network is represented by the change range of the temperature of the heat medium, and specifically comprises the following formula:
wherein ,Tin,x and Tout,x The temperature of the heating medium flowing into and out of the pipeline x respectively; subscripts min and max are respectively the minimum value and the maximum value of the corresponding physical quantity; s is S p Is a set of all pipes;
the temperature loss model is shown in formula 4:
wherein ,Tair,ex Is the outdoor ambient temperature; l (L) x Is the length of x pipe; r is the thermal resistance of the pipeline; c w Is the specific heat capacity of the heating medium;the mass flow of the heating medium in the pipeline x is shown, and e is the base number of natural logarithm;
the building of the building thermal inertia model caused by the heat storage property of the building enclosure structure specifically comprises the following steps:
step 1.1: establishing a thermodynamic equation:
wherein ,Tair For building indoor temperature, Q in The heat dissipation power of the radiator; and />Heat transfer and heat consumption power, cold air permeation and heat consumption power, cold air intrusion and ventilation and heat consumption power of building envelope respectively, c air 、ρ air 、V air Specific heat capacity, density and volume of indoor air respectively; t (T) air,0 The room temperature is the initial time; t is a time variable;
the said and />The calculation method comprises the following steps:
wherein ,Kenv The heat transfer coefficient of the building envelope; f (F) env The heat dissipation area is just opposite to the building; gamma is a temperature difference correction coefficient; x is x h 、x o and xw The room height addition rate, the orientation correction rate and the wind power addition rate are respectively;constant pressure specific heat capacity for outdoor air; ρ air,ex Is the density of the outdoor air; l (L) infil Is the cold air quantity of permeation; n is the cold air invasion additional rate of the outer door; />Heat consumption caused by heat transfer to the outer door of the building; η is the ratio of the basic heat consumption power of the outer door to the total basic heat consumption power of the building; l (L) ven The ventilation amount required for the building;
step 1.2: establishing a countercurrent hot water-air heat exchanger model:
wherein ,KRad and FRad The heat transfer coefficient and the heat dissipation area of the radiator are respectively; beta is the comprehensive correction coefficient of the number of radiator assembly sheets, the connection form and the installation form; t (T) av The average temperature of the heating medium in the radiator; t (T) in and Tout The water inlet temperature and the water outlet temperature of the radiator are respectively; m is m w Is the flow of the heating medium;
step 1.3: the relationship between the heat dissipation power and the water supply temperature and the indoor temperature of the heat supply network is obtained by the formula 7:
step 1.4: setting up coefficients alpha, alpha 1 、α 2 and α3 ，α、α 1 、α 2 and α3 The calculation formula is as follows:
by combining coefficients alpha, alpha 1 、α 2 and α3 Substituting into the formula 5, and simplifying to obtain:
the discrete solution is obtained as follows:
where n is the number of scheduled time intervals, n=0, 1,2 …; Δt is the scheduled time interval;a water supply temperature for the b-th schedule period; />B=n for the outdoor temperature of the b-th scheduling period;
to ensure heating comfort, the room temperature fluctuates in a certain range:
wherein , and />Respectively at room temperatureA lower limit and an upper limit;
the mixed time scale scheduling model of the cogeneration system comprises a day-ahead scheduling model; the specific establishment steps of the day-ahead scheduling model are as follows:
step 2.1: the cogeneration system operates under the constraint of a regional heat supply network thermal inertia model, a building thermal inertia model, node flow balance, greenhouse average temperature and grid operation, the power supply equipment is updated once in one hour, and the heat supply equipment is updated once in 1-24 hours;
the thermal inertia model of the heat supply network is shown in formulas 1-4, the thermal inertia model of the building is shown in formulas 11-12, and the node flow balance is shown in formula 13:
wherein, the flow flowing into the node i is positive, and the flow flowing out is negative;
the average greenhouse temperature is shown in formula 14:
wherein ,for the average value of the temperature in the inner chamber of the day, t represents the time variable +.>The indoor temperature is t time period;
step 2.2; an objective function is established, the following daily operation cost is minimized as a target, and the specific objective function is as follows:
wherein , and />Representing fuel cost, operation maintenance cost, tie line interaction cost and wind abandon penalty cost of the t-period system respectively, wherein ∈> and />The specific calculation method comprises the following steps:
wherein and />Respectively representing the consumption of delta fuel in t period and the price of the fuel; /> and />Respectively representing the consumption of the lambda-th fuel and the price of the lambda-th fuel in the t period; /> and />Respectively represent the sigma-th seed supply of the t periodThe electric power output by the electric equipment and the operation maintenance coefficient of the equipment; /> and />Respectively represent the t period of time gamma 1 The heat power output by the heat supply equipment and the operation maintenance coefficient of the equipment; p (P) t tie,p and />Respectively representing the electric power injected on the time period connecting line and the electricity price on the time period connecting line; p (P) t tie,s and />Respectively representing the electric power output on the time period connecting line and the electricity price on the time period connecting line; p (P) t wind,real and Pt wind,cons Respectively representing the actual output power of the wind power plant and the consumed wind power in the period t; p is p wind Representing a wind abandon punishment coefficient; s is S fuel 、S sele 、S elec and Sheat Respectively representing a set of fuels used by the system without unit combination equipment, a set of fuels used by the unit combination equipment, a set of system power supply equipment and a set of system heat supply equipment;
step 2.3; according to the result of the objective function, the system directly obtains the next-day unit combination, the start-stop state and the planned output value of the power supply/heating equipment and the transmission power of a system interconnecting line;
the mixed time scale scheduling model of the cogeneration system further comprises a daily rolling scheduling model, and the daily rolling scheduling model is specifically built by the following steps:
step 3.1: the cogeneration system operates under the constraint of a regional heating network thermal inertia model, a building thermal inertia model, node flow balance, greenhouse average temperature and grid operation, the power supply equipment in the daily rolling scheduling model is updated once within 15-30 minutes, and the heat supply equipment is updated once within 15-6 hours;
step 3.2: the method aims at minimizing the running cost within 2-8 hours in the future, carrying out rolling correction on the power supply and heating equipment running time of the residual time, and establishes the objective function as follows:
in the intra-day rolling schedule model,at t 1 Time-period system fuel cost, operation maintenance cost, tie-line interaction cost and wind-abandoning punishment cost, the calculation method refers to formula 16, and the parameter t is calculated 1 Substituting the time interval delta t between the power supply equipment and the daily rolling scheduling model into a formula 16, wherein R is the scheduling time scale of the power supply equipment; />The number of times is corrected for scrolling; z is the predicted time of each round of rolling correction;
step 3.3: according to the result of the objective function, the system directly obtains the actual processing value of the slow/fast response equipment, the planned transmission power of the system interconnection line and the reserved capacity of the slow/fast response equipment;
the mixed time scale scheduling model of the cogeneration system further comprises a real-time scheduling model, and the real-time scheduling model is specifically built by the following steps:
step 4.1: the cogeneration system operates under the constraints of a regional heating network thermal inertia model, a building thermal inertia model, node flow balance, greenhouse average temperature and grid operation, the power supply equipment is updated once in 5-15 minutes, and the heating equipment is updated once in 5-30 minutes;
step 4.2: in order to minimize the deviation between the actual power of the tie line within 2-8 hours in the future and the power in the rolling schedule model in the day, an objective function is established as follows:
wherein ,R2 A schedule time scale for the power supply device; t is t 2 For scheduling time, Z 2 The predicted time optimized for each round of scrolling,representing t 2 Real-time interactive power on time-of-day link, +.>Representing t 2 The interactive power of the rolling scheduling model stage in the day on the moment connecting line;
step 4.3: according to the objective function, the system directly obtains the actual output value of the quick response equipment, the time transmission power of the system interconnection line and the reserved capacity of the ACG unit;
the determining of the scheduling time scale of each heating device specifically comprises the following aspects:
the method comprises the following specific steps of determining the scheduling time scale of a large-scale cogeneration unit of a quantity-regulated heating system or a temperature-regulated heating system by stages, wherein the specific steps are as follows:
step 5.1: for the case where the outside ambient temperature falls, an initial value of room temperature is given and the outside ambient temperature is assumed to fall in the worst case, as shown in formula 19:
wherein ,is the minimum value of the water supply temperature; />Is the maximum value of the outdoor temperature; />Is the maximum rate of outdoor temperature drop;
step 5.2: sequentially increasing the time from 0 by Δt until a critical time point is foundThe following conditions are satisfied:
equation 11 solving function using building thermal inertia modelObtained->The maximum scheduling time scale of the large-scale cogeneration unit under the condition;
step 5.3 for the case where the ambient temperature rises, given the initial value of room temperature and assuming that the ambient temperature rises in the worst case, as shown in equation 21:
wherein Is the maximum value of the water supply temperature; />Is the minimum value of the outdoor temperature; />Is the maximum rate of rise of outdoor temperature;
sequentially increasing the time from 0 by deltat until a certain critical time point is foundThe following conditions are satisfied:
solving the function using equation 11Obtained->The maximum scheduling time scale of the large-scale cogeneration unit is the maximum scheduling time scale under the condition;
the maximum scheduling time scale of the two conditions is utilized in a system containing y heat users, and the maximum scheduling time scale of the large-scale cogeneration unit is determined by the formula 23:
the method for determining the scheduling time scale of the large-scale cogeneration unit of the quality-adjusting heating system comprises the following steps of:
step 6.1, determining that the scheduling time scale of the large-scale cogeneration unit meets the following formula according to the operation constraint and the load characteristic of the equipment:
Δt min ≤Δt≤Δt max (24)
wherein Δtmin A minimum schedule time scale determined by unit operation constraints;
step 6.2: in the day-ahead scheduling model, day operation cost is taken as an objective function, and scheduling time intervals are taken as follows:
Δt＝ε min Δt I ,(ε min +1)Δt I ,...,(ε max -1)Δt I (25)
wherein ΔtI A scheduling time interval of power supply equipment in a day-ahead scheduling stage; coefficient epsilon min and εmax The minimum and maximum allowable scheduling time intervals of the cogeneration unit are respectively represented,
where ceil () is an upward rounding function;
obtaining daily operation cost of the system under each scheduling time scale, and finally determining the scheduling time scale of the cogeneration unit according to the minimum daily operation cost;
the scheduling time scale of other heat supply equipment is 2-3 times of the time scale of the power supply equipment under the corresponding mixed time scale scheduling model.
2. The thermal inertia-based cogeneration system hybrid time scale scheduling method of claim 1, wherein: the hybrid time scale scheduling model of the cogeneration system further comprises an automatic power generation control model; the automatic power generation control model comprises correction control and blocking management, wherein the correction control utilizes the capacity information of the second-level AGC unit reserved in the real-time scheduling model, and the AGC unit is scheduled in real time by combining with AGC software, so that the system frequency and the power transmission of the connecting wire reach the assessment index of the information physical system; the blocking management is used for processing the problem of line section power flow out-of-limit in real time, and the potential safety hazard is rapidly eliminated.
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