CN114301094B - Model predictive control optimization operation method of PV/T (photovoltaic/thermal) coupled energy system - Google Patents
Model predictive control optimization operation method of PV/T (photovoltaic/thermal) coupled energy system Download PDFInfo
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention relates to a Model Predictive Control (MPC) optimization operation method of a PV/T coupled energy system, which comprises the following steps: s1, establishing a multi-objective function according to a PV/T coupled energy system, and taking the economy and the heat supply of the system as the multi-objective function optimally; s2, setting constraint conditions and boundary conditions based on the multi-objective function; s3, giving weight to the multi-objective function through fuzzy optimization, and establishing a system internal control algorithm so as to construct a mixed integer nonlinear model of predictive control; s4, obtaining a model prediction control result through a branch delimitation calculation method; s5, predicting a control result according to the model to obtainThe highest efficiency is used as an optimization objective function, and the optimal heating strategy of the system is calculated; according to the invention, the flexible energy utilization control strategy design of the PV/T coupled energy system enables the system to be more attached to the user load under the condition of meeting the user demand, thereby effectively solving the problems of unreasonable system energy distribution during operation,Low efficiency, etc.
Description
Technical Field
The invention belongs to the field of control of photovoltaic photo-thermal PV/T solar energy coupled energy systems, and particularly relates to a Model Predictive Control (MPC) optimization operation method of a PV/T coupled energy system.
Background
In the past few years, climate change has become a global problem to be solved, the building industry is one of the main energy consumption, the total building energy consumption rises year by year, the total energy consumption accounts for 30% of the total energy consumption, and in connection with this, the energy consumption of the system operation has attracted attention from vast scholars, and the building system is a promising method for reducing the energy consumption and reducing the emission of greenhouse gases. Photovoltaic photothermal PV/T solar energy coupled energy systems will dominate in future energy development as clean energy systems for converting solar energy into electrical and thermal energy. Therefore, how to reduce the energy consumption of the system operation is important.
The photovoltaic photo-thermal PV/T solar energy coupling energy system is a clean energy system which uses solar energy as main energy drive to supply power and heat for users and enables the capacity to be utilized in a grading way. The equipment such as the coupling heat storage water tank, the heat pump and the like can further improve the stability of the system, but because the system heat supply and the requirement of a user side cannot be matched in real time, heating can be generated untimely, and the self-consumption rate of the energy source of the external system is low, so that the system is the two main reasons of energy source waste at present, and therefore, the efficient and optimal operation method of the photovoltaic photo-thermal PV/T coupling energy source system is necessary to be developed.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides the photovoltaic photo-thermal PV/T coupled energy system operation method aiming at overcoming the defects in the prior art, and aims at improving the accuracy of heat supply, enhancing the self-consumption rate of the productivity of the system, avoiding the waste of the productivity, improving the energy reliability, saving the cost and reducing the whole carbon emission of the system on the basis of meeting the load of a user side.
The technical scheme adopted for solving the technical problems is as follows:
1. a Model Predictive Control (MPC) optimization operation method of a PV/T coupled energy system comprises a water cooling PV/T assembly, a heat pump and a heat storage water tank, wherein the coupled energy system realizes optimal control by the following steps:
s1, establishing a multi-objective function according to a photovoltaic photo-thermal PV/T (photovoltaic/thermal) coupled energy system, wherein the multi-objective function is based on the fact that the total cost of the system is minimum throughout the day and the heat required by supply is minimum; wherein: the multi-objective function is:
where E is the total cost of system operation, E grid(k) For the power consumption of the power grid, when the power consumption is positive, representing the power transmission from the power grid to the user; when negative, it indicates that the electric energy is sent from the system to the power grid, cost grid(k) The real-time electricity price of the power grid is represented by delta, the electricity utilization rate is represented by delta, Q is the total heat of a user side provided by the system, and Qdemand is represented by delta (k) The time-by-time heat of the user side provided by the system;
s2, setting constraint conditions and boundary conditions based on multiple objective functions;
s3, according to multiple objective functions and constraint conditions, based on the difference of the positions of the photovoltaic photo-thermal PV/T coupled energy systems, giving weights to the different objective functions through fuzzy optimization, establishing an internal control algorithm of an efficient operation model of the photovoltaic photo-thermal PV/T coupled energy systems, and further establishing a predictive control mixed integer nonlinear model based on the multiple objective functions, the constraint, the boundary conditions and the internal control algorithm;
s4, calculating a mixed integer nonlinear model of predictive control through a branch delimitation calculation method to generate a predictive control result; s5, according to the prediction control result, toThe highest efficiency is used as an optimization objective function, and different optimal heating strategies of the system are obtained in advance, wherein:
the saidThe highest efficiency as an optimization objective function is:
wherein P is PV 、P grid The photoelectric output power of the water cooling PV/T component and the power grid output power are respectively KW and eta pl 、η gl Electric efficiency of water cooling PV/T assembly and electric network respectively, E rad For cooling the solar radiation received by the PV/T assemblyThe unit is KW, l i For the working fluid to flow through the parts>Loss in KW.
Further, the objective function constraint condition and the boundary condition in the step S2 are set as follows:
wherein T is WT(k＝0) For the temperature of the thermal storage tank at time k of 0,for the initial temperature of the heat storage water tank T WT(k) For the temperature of the heat-storage water tank at time k, T WT(k-1) The temperature of the heat storage water tank at the time k-1, namely the temperature of the previous step length at the time k; u is the heat transfer coefficient of the heat storage water tank and the external environment; a is the heat radiation area of the heat storage water tank; t (T) amb(k-1) The ambient temperature near the heat storage water tank; />For cooling the heat supplied to the user side by the PV/T assembly>Heat supplied to the user side for the heat pump, +.>Heat supplied to the user side for the thermal storage tank; epsilon-charging the efficiency of the heat-releasing and heat-storing water tank; v is the volume of the water tank; c (C) p Constant pressure specific heat; delta is the time step; />Heat is generated when the heat pump is a heat pump k; COP of (k) The coefficient of performance of the heat pump is k; p (P) PV/T(k) To cool the electrical power of the PV/T assembly at k, P grid(k) The power transmission quantity of the power grid to the user at the time of k is represented by the power grid to the user when the power grid is positive, the power transmission of the system to the power grid when the power grid is negative, and P HP(k) When k is the power consumption of the heat pump; />For k, the heat quantity of the heat pump to be delivered to the heat storage water tank>For cooling the PV/T module heat at k, < >>Cooling the heat transported to the heat storage water tank by the PV/T component when the temperature is k;
wherein T is WT(k) The upper and lower limit values are set according to a photovoltaic photo-thermal PV/T coupled energy system, and the system sets the useful temperature of the water tank to be 28-60 ℃; t (T) PV/T(k) For cooling the temperature of the PV/T assembly at k, according to the photovoltaic photo-thermal PV/T coupled energy system setting, the system sets the useful temperature of the water-cooled PV/T assembly to 15-48 ℃; maxdemand is the maximum heat required at the user side, maxHP is the maximum heat supplied by the heat pump, minP PV/T(k) For cooling the minimum output electric power of the PV/T assembly at k time, maxP PV/T(k) Cooling the maximum output electric power of the PV/T assembly for k times; maxP HP(k) The maximum required electric power of the heat pump is k; ON/OFF is part ON or OFF.
Further, in the step S3, a Model Predictive Control (MPC) internal control algorithm process of the PV/T coupled energy system is constructed:
constructing a water temperature requirement of a user side, namely Tdemand and heat balance a of a heat storage water tank, a heat pump and a water cooling PV/T component in k, if the balance a is judged to be more than 0, a 'yes' path is taken, whether the temperature of the water cooling PV/T component in k is more than 38 ℃ is judged, if the temperature of the water cooling PV/T component in k is further judged to be more than 48 ℃, the heat storage water tank is heated by the water cooling PV/T component, otherwise, the water cooling PV/T component directly heats, if the temperature of the water cooling PV/T component in k is judged to be less than 38 ℃, and whether the electricity quantity Epv/T generated by the water cooling PV/T component in k can meet the electricity quantity required by heating is judged, if the temperature of the heat storage water tank is further judged to be more than 38 ℃, if the temperature of the water cooling PV/T component in k is more than 38 ℃, and if the temperature of the water cooling PV/T component in k is further judged, otherwise, the heat pump is started by solar energy electricity quantity to heat;
if the balance a is less than 0, namely, a 'no' path is taken, a heat balance b of the heat demand of the user side and the heat storage water tank and the water cooling PV/T component in k is constructed, whether the balance b is greater than 0 is judged, if yes, the heat pump is used for heating by utilizing the electric quantity of the power grid, if no, further judgment is made, if yes, whether the temperature of the heat storage water tank is greater than 38 ℃ is further judged by constructing the heat balance c of the heat demand of the user side and the water cooling PV/T component in k, otherwise, the water cooling PV/T component is used for directly heating. Further, in the step S4, the mixed integer nonlinear model of the predictive control is calculated by a branch delimitation method to generate an optimized result flow:
after solar radiation illuminance, power grid price, heat demand, water tank temperature, heat pump efficiency, PV/T temperature and load parameters are input, the calculated amount is simplified through an internal control algorithm, and the water tank and water cooling PV/T temperature is detected;
calculating actual electric power of the heat pump according to the thermal load, and calculating the power consumption of the power grid according to the electric power and thermal power balance relation;
initializing a photovoltaic photo-thermal (PV)/T coupled energy system; comprising the following steps: the total cost, the relaxation function of the required heat and the optimal value range are set to be 15 minutes as the initial time and 1140 minutes as the total step length, wherein:
selecting a node from the relaxation function of the total cost and the required heat, updating the value range of the node into a new range of the node, updating the optimal solution of the total cost and the required heat relaxation function and the lower limit of the optimal value, judging the magnitudes of the upper limit value and the lower limit value of the solution, if the feasible solution is a domain, making the lower limit of the solution equal to the upper limit output result, otherwise, introducing the relaxation problem of each solution node;
if the solution is feasible, updating the optimal solution node until a feasible solution is calculated, namely, the state of a control logic gate of each component of the system, and knowing the running state of each component of the system, namely, the control strategy of the system; if the solution is not feasible, the solution is divided into sub-problems for optimizing, namely the total cost of the system and the target problem of the required heat are divided into sub-problems, the relaxation calculation is carried out respectively, the solution is gradually advanced to a final date defined by a user from the beginning of a simulation period, the optimal solution and the optimal value are obtained, and in each step, the combination between the multi-objective function and the limiting condition is explored for calculation, so that the electricity charge and the required heat of the whole process are reduced to the minimum.
Further, the saidThe highest efficiency is as inside the optimized objective function for +.>The optimization objectives for the loss are:
min l i ＝H i,in -T 0 S i,in -(H i,out -T 0 S i,out )
wherein H is i,in 、H i,out The enthalpy of each component is input and output respectively, and the unit is KW and S i,in 、S i,out The entropy is input and output for each component, the unit is KW/K, T 0 The unit is K, which is the ambient temperature near the component; and has the following limitations:
wherein H is imin For the lower limit of the enthalpy of each component, H imax For the upper limit of the enthalpy of each component, S imin For the lower limit of the entropy of each component, S imax For the upper limit of the entropy of each component, T 0min T is the upper limit of the ambient temperature near the component 0max Is the lower limit of the ambient temperature near the accessory;
determining upper and lower limits of enthalpy and entropy of each component according to the predicted running conditions of the photovoltaic photo-thermal PV/T coupled energy system; and determining the upper limit and the lower limit of the ambient temperature according to the meteorological conditions input by the system predictive operation.
Advantageous effects
The invention has the advantages and positive effects that:
(1) According to the invention, through the design of the flexible control strategy of the photovoltaic photo-thermal PV/T coupled energy system, the energy supply of the system is more attached to the user load under the condition of meeting the user load, so that the unreasonable distribution of heat and electric quantity in the operation process of the photovoltaic photo-thermal PV/T coupled energy system is effectively solved, and the utilization rate of the system energy level is lowLow efficiency, etc. The method provides the possibility of selecting the optimal energy utilization or the optimal economy according to the self conditions for users.
(2) The invention gives users the weights to different objective functions based on fuzzy optimization, and the fuzzy optimization increases the reasonable application degree to different construction systems, thereby more embodying the advantages of local conditions.
(3) According to the invention, by establishing the internal control algorithm of the efficient operation model of the photovoltaic photo-thermal PV/T coupled energy system, the internal control algorithm can accelerate the convergence speed of the model, reduce the calculation time, improve the precision of final energy and required heat cost under the condition of not increasing the calculation capability requirement, and respectively correspond to surplus or deficiency of energy by adjusting the data difference between the set prediction period and the set real data to be positive and negative, so that the mismatch loss of the system is reduced and the precision of the final energy and the required heat cost is improved under the condition of not increasing the calculation capability requirement; the method is suitable for the problem of mixed integer nonlinearity of the photovoltaic photo-thermal PV/T coupled energy system optimization operation model.
(4) The branch delimitation calculation method has the advantages that the mixed integer nonlinear model of the predictive control is calculated by the branch delimitation calculation method to generate a predictive control result, the search space of a solution is reduced, the system can find an optimal path to solve the obstacle without entering an unexplored space, the result in progress can not be improved, the speed of finding an optimal value is increased by using a boundary for an objective function, and the like, and the method is more suitable for solving the efficient operation model of the photovoltaic photo-thermal PV/T coupled energy system.
(5) The water cooling PV/T component of the traditional PV/T system is respectively connected with the heat storage water tank and the heating tail end at the load side, is directly used for heating the building envelope, fully utilizes the defect of insufficient water temperature, achieves the indoor required temperature at a lower temperature, and further improves the energy consumption rate of the system.
Drawings
FIG. 1 is a Model Predictive Control (MPC) optimized operational energy flow diagram for a photovoltaic photo-thermal PV/T coupled energy system;
FIG. 2 is a flow chart of an internal control algorithm;
FIG. 3 is a flow chart of branch-and-bound algorithm computation;
FIG. 4 is a flow chart of mixed integer nonlinear model calculations for Model Predictive Control (MPC) optimization operations for a designed photovoltaic photo-thermal PV/T coupled energy system using a branch and bound algorithm;
fig. 5 is a schematic diagram of an exemplary photovoltaic photothermal PV/T coupled energy system design.
Detailed Description
The invention will now be further described by way of specific examples, which are illustrative only and not intended to limit the scope of the invention, of a schematic diagram of an exemplary photovoltaic photo-thermal PV/T coupled energy system design as shown in FIG. 4. The coupling energy system comprises a water cooling PV/T assembly, a heat pump and a heat storage water tank, wherein the water cooling PV/T assembly generates electric energy and heat energy, and the electric energy is used for meeting the electric load of a user and the electric consumption in the system or is transmitted to a power grid; when the heat energy generated by the water cooling PV/T component does not meet the heat load of the user side, the heat pump utilizes the electric quantity generated by the water cooling PV/T component or the electric quantity of the power grid to generate heat, the heat energy is stored in the heat storage water tank, and the water cooling PV/T component directly heats through the heat storage water tank or the heat pump when the heat energy generated by the water cooling PV/T component in winter and night does not meet the use condition. The PV/T coupled energy system is applied to a photovoltaic photo-thermal PV/T coupled energy system.
A Model Predictive Control (MPC) optimization operation method of a photovoltaic photo-thermal PV/T coupled energy system comprises the following steps:
s1, establishing a multi-objective function according to a photovoltaic photo-thermal PV/T (photovoltaic/thermal) coupled energy system, and taking the minimum total cost of the system and the minimum heat required for supplying as the objective function, wherein the multi-objective function can be obtained as follows:
where E is the total cost of system operation, E grid(k) For the power consumption of the power grid, when the power consumption is positive, representing the power transmission from the power grid to the user; when negative, it indicates that the electric energy is sent from the system to the power grid, cost grid(k) The real-time electricity price of the power grid is represented by delta, the electricity utilization rate is represented by delta, Q is the total heat of a user side provided by the system, and Qdemand is represented by delta (k) The user side provided to the system is heated time by time.
S2, setting constraint conditions and boundary conditions based on multiple objective functions
Wherein T is WT(k＝0) For the temperature of the thermal storage tank at time k of 0,for the initial temperature of the heat storage water tank T WT(k) For the temperature of the heat-storage water tank at time k, T WT(k-1) The temperature of the heat storage water tank at the time k-1, namely the temperature of the previous step length at the time k; u is the heat transfer coefficient of the heat storage water tank and the external environment; a is the heat radiation area of the heat storage water tank; t (T) amb(k-1) The ambient temperature near the heat storage water tank; />For water coolingThe PV/T assembly supplies heat to the user side, < >>Heat supplied to the user side for the heat pump, +.>Heat supplied to the user side for the thermal storage tank; epsilon-charging the efficiency of the heat-releasing and heat-storing water tank; v is the volume of the water tank; c (C) p Constant pressure specific heat; delta is the time step; />Heat is generated when the heat pump is a heat pump k; COP of (k) The coefficient of performance of the heat pump is k; p (P) PV/T(k) To cool the electrical power of the PV/T assembly at k, P grid(k) The power transmission quantity of the power grid to the user at the time of k is represented by the power grid to the user when the power grid is positive, the power transmission of the system to the power grid when the power grid is negative, and P HP(k) When k is the power consumption of the heat pump; />For k, the heat quantity of the heat pump to be delivered to the heat storage water tank>For cooling the PV/T module heat at k, < >>And (3) cooling the heat which is transmitted to the heat storage water tank by the PV/T assembly at the time of k.
Wherein T is WT(k) The upper and lower limit values are set according to a photovoltaic photo-thermal PV/T coupled energy system, and the useful temperature of the water tank is set to be 28-60 ℃ because of the designed system; t (T) PV/T(k) For cooling the temperature of the PV/T assembly at k, according to the photovoltaic photo-thermal PV/T coupled energy system settings, it is useful to cool the PV/T assembly because of the design system settingsThe temperature is 15 to 48 ℃; maxdemand is the maximum heat required at the user side, maxHP is the maximum heat supplied by the heat pump, minP PV/T(k) For cooling the minimum output electric power of the PV/T assembly at k time, maxP PV/T(k) Cooling the maximum output electric power of the PV/T assembly for k times; maxP HP(k) The maximum required electric power of the heat pump is k; ON/OFF is part ON or OFF.
Wherein: taking the design of the photovoltaic photo-thermal PV/T coupled energy system as an example, the temperature difference tracking cycle is allowed to start when the temperature of the heat collector of the water-cooled PV/T component reaches the upper limit temperature of 48 ℃. At the moment, the temperature T1 of the heat collector of the water cooling PV/T assembly and the temperature T2 of the backwater meet the conditions that T1-T2 is higher than 8 ℃, and meanwhile, when the water outlet temperature T3 of the water tank is lower than the upper limit temperature of 60 ℃, the heat collecting circulating pump is started to perform temperature difference circulation. When the water outlet temperature T3 of the water tank is lower than the lower limit temperature of 38 ℃, the heat collection circulating pump is closed, and the solar energy continuously heats the circulating water. And if the water outlet temperature of the water tank is lower than the set heating lower limit temperature of 38 ℃, starting the heat pump water supply tank to heat until the water outlet temperature T3 of the water tank reaches the set heating upper limit temperature of 48 ℃.
S3, according to different places where the photovoltaic photo-thermal PV/T coupled energy system is located and different objective functions, giving weights to users through fuzzy optimization, building an internal control algorithm of a high-efficiency operation model of the photovoltaic photo-thermal PV/T coupled energy system, building heat balance a of Tdemand and a heat storage water tank, a heat pump and a water cooling PV/T component in k time, if the balance a is judged to be greater than 0, a 'yes' way is taken, judging whether the temperature of the water cooling PV/T component in k time is greater than 38 ℃, if the temperature of the water cooling PV/T component in k time is further judged to be greater than 48 ℃, heating the heat storage water tank by the water cooling PV/T component if the temperature of the water cooling PV/T component in k time is further more than 48 ℃, if the temperature of the water cooling PV/T component in k time is judged to be less than 38 ℃, and if the power generation capacity Epv/T in k time of the water cooling PV/T component in k time can meet the power required for heating, further judging whether the temperature of the heat storage water tank is greater than 38 ℃, if the temperature of the heat storage water tank is greater than 38 ℃, otherwise, heating by utilizing solar energy is started; if the balance a is less than 0, namely, a 'no' path is taken, a heat balance b of the heat demand of the user side and the heat storage water tank and the water cooling PV/T component in k is constructed, whether the balance b is greater than 0 is judged, if yes, the heat pump is used for heating by utilizing the electric quantity of the power grid, if no, further judgment is made, if yes, whether the temperature of the heat storage water tank is greater than 38 ℃ is further judged by constructing the heat balance c of the heat demand of the user side and the water cooling PV/T component in k, otherwise, the water cooling PV/T component is used for directly heating. The internal control algorithm can accelerate the convergence speed of the model, reduce the calculation time, improve the precision of the final energy and the required heat cost under the condition of not increasing the calculation capability requirement, and respectively correspond to surplus or deficiency of energy by adjusting the data difference between the set prediction period and the set real data to be positive and negative, reduce the mismatch loss of the system under the condition of not increasing the calculation capability requirement, improve the precision of the final energy and the required heat cost, and further construct a mixed integer nonlinear model of predictive control based on the multi-objective function, the constraint, the boundary condition and the internal control algorithm; the internal control algorithm process is shown in figure 2. Based on an internal control algorithm, a mixed integer nonlinear model of predictive control is calculated through a branch delimitation calculation method to generate a model predictive control result, compared with other algorithms, the algorithm has the advantages that the search space of a solution is reduced, a system can find an optimal path to solve obstacles without entering an unexplored space, the result in progress can not be improved, the speed of finding an optimal value is accelerated by using a boundary for an objective function, and the like, and the method is more suitable for solving a high-efficiency operation model of a photovoltaic photo-thermal PV/T coupled energy system. The specific branch and bound algorithm process is shown in fig. 3, and the mixed integer nonlinear model calculation flow for the Model Predictive Control (MPC) optimization operation of the designed photovoltaic photo-thermal PV/T coupled energy system is realized by using the branch and bound algorithm as shown in fig. 4.
FIG. 3 is a flow chart of branch-and-bound algorithm calculation, and FIG. 4 is a flow chart of mixed integer nonlinear model calculation for Model Predictive Control (MPC) optimization operation of a designed photovoltaic photo-thermal PV/T coupled energy system using a branch-and-bound algorithm, progressing from a simulation cycle to a user-defined final date. After inputting solar radiation illuminance, power grid price, heat demand, water tank temperature, heat pump efficiency, PV/T temperature and load parameters, accurately calculating the result through an internal control algorithm, and detecting water tank and water cooling PV/T temperature; calculating the actual electric power of the heat pump according to the heat load, calculating the electric power consumption of a power grid according to the electric power and heat power balance relation, initializing the total cost of a solution initialization system, the relaxation function of the required heat and the optimal value range, selecting a node from the total cost and the relaxation function of the required heat, updating the value range to be a new range of the node, updating the optimal solution of the total cost and the relaxation function of the required heat and the lower limit of the optimal value, judging the magnitudes of the upper limit and the lower limit of the solution, if the feasible solution is a domain, enabling the lower limit of the solution to be equal to the upper limit output result, otherwise, introducing the relaxation problem of each solution node, and if the solution is feasible, updating the optimal solution node until the state of a control logic gate of each part of the system is calculated, and the running state of each part of the system, namely the control strategy of the system is known. If the solution is not a feasible solution, the solution is divided into sub-problems, namely the total cost of the system and the required heat target problem are divided into sub-problems, the relaxation calculation is respectively carried out, the initial time is set to be 15 minutes, and the optimal solution and the optimal value, namely the control strategy of the system, are obtained after the simulation period starts until the calculation reaches 131400 minutes (whole year). At each step, the calculation explores the combination between the objective function and the limiting conditions, thereby minimizing the electricity charge and the required heat of the whole process.
(4) According to the prediction result, outputting the total cost of the system and the state of the control logic gate of each component of the system when the required heat is optimal, knowing the running state of each component of the system, and calculating the system by optimal cost and optimal heat supplyAnd calculating and optimizing an objective function to obtain an operation control strategy of the photovoltaic photo-thermal PV/T coupled energy system.
Wherein, the constraint condition mainly comprises: the heat storage system comprises a heat storage water tank, an ambient temperature, a water cooling PV/T component photo-thermal part, a heat pump, a system energy supply and user load energy balance constraint, a user required heat and system heat supply balance, a heat pump component heat supply balance, a water cooling PV/T component photo-thermal part heat generation capacity upper and lower constraint condition, a water cooling PV/T component photovoltaic part electric generation capacity upper and lower constraint condition, a heat pump heating capacity upper and lower limit constraint, a pump rated power constraint condition, a heat storage water tank heat storage capacity upper and lower limit constraint, and a heat pump, a heat storage water tank and a water cooling PV/T component photo-thermal part upper and lower limit constraint of heat supply to users.
The reason for connecting the water-cooled PV/T assembly of the conventional PV/T system to the hot water tank and the load side heating end respectively is as follows: the low-temperature water can be directly used for heating the enclosure structure, the defect of insufficient water temperature generated by water cooling of the PV/T component is fully utilized, the indoor required temperature is achieved by the low temperature, and the energy consumption rate of the system is further improved.
The highest efficiency optimization objective function is:
wherein P is PV 、P grid The photoelectric output power of the water cooling PV/T component and the power grid output power are respectively KW and eta pl 、η gl Electric efficiency of water cooling PV/T assembly and electric network respectively, E rad For cooling the solar radiation received by the PV/T assemblyThe unit is KW, l i For the working fluid to flow through the parts>Loss in KW.
For the purpose ofThe optimization objectives for the loss are:
min l i ＝H i,in -T 0 S i,in -(H i,out -T 0 S i,out )
wherein H is i,in 、H i,out The enthalpy of each component is input and output respectively, and the unit is KW and S i,in 、S i,out The entropy is input and output for each component, the unit is KW/K, T 0 Is the ambient temperature near the component, in K. And has the following limitations:
wherein H is imin For the lower limit of the enthalpy of each component, H imax For the upper limit of the enthalpy of each component, S imin For the lower limit of the entropy of each component, S imax For the upper limit of the entropy of each component, T 0min T is the upper limit of the ambient temperature near the component 0max Is the lower limit of the ambient temperature near the accessory.
Determining upper and lower limits of enthalpy and entropy of each component according to actual system prediction running conditions; and determining the upper limit and the lower limit of the ambient temperature according to the meteorological conditions input by the system predictive operation.
The invention is not limited to the embodiments described above. The above description of specific embodiments is intended to describe and illustrate the technical aspects of the present invention, and is intended to be illustrative only and not limiting. Numerous specific modifications can be made by those skilled in the art without departing from the spirit of the invention and scope of the claims, which are within the scope of the invention.
Claims (2)
1. A model predictive control optimizing operation method of a PV/T coupled energy system is characterized in that: the coupling energy system comprises a water cooling PV/T component, a heat pump and a heat storage water tank, wherein the water cooling PV/T component generates electric energy and heat energy, and the electric energy is used for meeting the electric load of a user and the electric consumption in the system or is transmitted to a power grid; when the heat energy generated by the water cooling PV/T component does not meet the heat load of the user side, the heat pump utilizes the electric quantity generated by the water cooling PV/T component or the electric quantity of the power grid to generate heat, the heat energy is stored in the heat storage water tank, and the water cooling PV/T component directly heats through the heat storage water tank or the heat pump when the heat energy generated by the water cooling PV/T component in winter and night does not meet the use condition; the model predictive control operation method of the PV/T coupled energy system comprises the following steps:
s1, establishing a multi-objective function according to a PV/T (photovoltaic/thermal) coupled energy system, wherein the multi-objective function is based on the fact that the total daily cost of the system is minimum and the heat required by supply is minimum; wherein: the multi-objective function is:
where E is the total cost of system operation, E grid(k) For the power consumption of the power grid, when the power consumption is positive, representing the power transmission from the power grid to the user; when negative, it indicates that the electric energy is sent from the system to the power grid, cost grid(k) The real-time electricity price of the power grid is represented by delta, the electricity utilization rate is represented by delta, Q is the total heat of a user side provided by the system, and Qdemand is represented by delta (k) The time-by-time heat of the user side provided by the system;
s2, setting constraint conditions and boundary conditions based on multiple objective functions;
s3, according to multiple objective functions and constraint conditions, based on the difference of the positions of the PV/T coupled energy systems, a user gives weight to the different objective functions through fuzzy optimization, an internal control algorithm of a high-efficiency running model of the PV/T coupled energy system is built, and a mixed integer nonlinear model of predictive control is built based on the multiple objective functions, constraint, boundary conditions and the internal control algorithm;
s4, calculating a mixed integer nonlinear model of predictive control through a branch delimitation calculation method to generate a predictive control result;
s5, according to the prediction control result, toThe highest efficiency is used as an optimization objective function to obtain the optimal failure of the system in advanceA co-heating strategy, wherein:
the saidThe highest efficiency as an optimization objective function is:
wherein P is PV 、P grid The photoelectric output power of the water cooling PV/T component and the power grid output power are respectively KW and eta pl 、η gl Electric efficiency of water cooling PV/T assembly and electric network respectively, E rad For cooling solar radiation exergy received by the PV/T assembly in KW/l i For working-medium flowing through each partLoss in KW; wherein:
and in the step S2, the constraint condition and the boundary condition of the objective function are set as follows:
wherein T is WT(k＝0) T is the temperature of the heat storage water tank when the time k is 0 WT0 For the initial temperature of the heat storage water tank T WT(k) For the temperature of the heat-storage water tank at time k, T WT(k-1) The temperature of the heat storage water tank at the time k-1, namely the temperature of the previous step length at the time k; u is the heat transfer coefficient of the heat storage water tank and the external environment; a is the heat radiation area of the heat storage water tank; t (T) amb(k-1) The ambient temperature near the heat storage water tank;for cooling the heat supplied to the user side by the PV/T assembly>Heat supplied to the user side for the heat pump, +.>Heat supplied to the user side for the thermal storage tank; epsilon-charging the efficiency of the heat-releasing and heat-storing water tank; v is the volume of the water tank; c (C) p Constant pressure specific heat; delta is the time step; />Heat is generated when the heat pump is a heat pump k; COP of (k) The coefficient of performance of the heat pump is k; p (P) PV/T(k) To cool the electrical power of the PV/T assembly at k, P grid(k) The power transmission quantity of the power grid to the user at the time of k is represented by the power grid to the user when the power grid is positive, the power transmission of the system to the power grid when the power grid is negative, and P HP(k) When k is the power consumption of the heat pump; />For k, the heat quantity of the heat pump to be delivered to the heat storage water tank>For cooling the PV/T module heat at k, < >>Cooling the heat transported to the heat storage water tank by the PV/T component when the temperature is k;
wherein T is WT(k) The upper limit value and the lower limit value are set according to a photovoltaic photo-thermal PV/T coupled energy system; t (T) PV/T(k) The temperature of the PV/T assembly at the time of k is cooled by water, and the temperature is set according to a photovoltaic photo-thermal PV/T coupling energy system; maxdemand is the maximum heat required at the user side, maxHP is the maximum heat supplied by the heat pump, minP PV/T(k) For cooling the minimum output electric power of the PV/T assembly at k time, maxP PV/T(k) Cooling the maximum output electric power of the PV/T assembly for k times; maxP HP(k) The maximum required electric power of the heat pump is k; ON/OFF is part ON or OFF;
in the step S3, an internal control algorithm process of a high-efficiency operation model of the PV/T coupled energy system is established:
constructing a water temperature requirement of a user side, namely Tdemand and heat balance a of a heat storage water tank, a heat pump and a water cooling PV/T component in k, if the balance a is judged to be more than 0, a 'yes' path is taken, whether the temperature of the water cooling PV/T component in k is more than 38 ℃ is judged, if the temperature of the water cooling PV/T component in k is further judged to be more than 48 ℃, the heat storage water tank is heated by the water cooling PV/T component, otherwise, the water cooling PV/T component directly heats, if the temperature of the water cooling PV/T component in k is judged to be less than 38 ℃, and whether the electricity quantity Epv/T generated by the water cooling PV/T component in k can meet the electricity quantity required by heating is judged, if the temperature of the heat storage water tank is further judged to be more than 38 ℃, if the temperature of the water cooling PV/T component in k is more than 38 ℃, and if the temperature of the water cooling PV/T component in k is further judged, otherwise, the heat pump is started by solar energy electricity quantity to heat;
if the balance a is less than 0, namely, a 'no' path is taken, a heat balance b between the heat demand of the user side and the heat of the heat storage water tank and the water cooling PV/T component in k is constructed, whether the balance b is greater than 0 is judged, if yes, the heat pump is used for heating by utilizing the electric quantity of the power grid, if no, further judgment is made, if yes, whether the temperature of the heat storage water tank is greater than 38 ℃ is further judged by constructing the heat balance c between the heat demand of the user side and the heat of the water cooling PV/T component in k, otherwise, the water cooling PV/T component is used for directly heating; wherein:
in the step S4, the mixed integer nonlinear model of the predictive control is calculated by a branch delimitation method to generate an optimized result flow:
after solar radiation illuminance, power grid price, heat demand, water tank temperature, heat pump efficiency, PV/T temperature and load parameters are input, the calculated amount is simplified through an internal control algorithm, and the water tank and water cooling PV/T temperature is detected;
calculating actual electric power of the heat pump according to the thermal load, and calculating the power consumption of the power grid according to the electric power and thermal power balance relation;
initializing a photovoltaic photo-thermal (PV)/T coupled energy system; comprising the following steps: the total cost, the relaxation function of the required heat and the optimal value range are set to be 15 minutes as the initial time and 1140 minutes as the total step length, wherein:
selecting a node from the relaxation function of the total cost and the required heat, updating the value range of the node into a new range of the node, updating the optimal solution of the total cost and the required heat relaxation function and the lower limit of the optimal value, judging the magnitudes of the upper limit value and the lower limit value of the solution, if the feasible solution is a domain, making the lower limit of the solution equal to the upper limit output result, otherwise, introducing the relaxation problem of each solution node;
if the solution is feasible, updating the optimal solution node until a feasible solution is calculated, namely, the state of a control logic gate of each component of the system, and knowing the running state of each component of the system, namely, the control strategy of the system; if the solution is not feasible, the solution is divided into sub-problems for optimizing, namely the total cost of the system and the target problem of the required heat are divided into sub-problems, the relaxation calculation is carried out respectively, the solution is gradually advanced to a final date defined by a user from the beginning of a simulation period, the optimal solution and the optimal value are obtained, and in each step, the combination between the multi-objective function and the limiting condition is explored for calculation, so that the electricity charge and the required heat of the whole process are reduced to the minimum.
2. The model predictive control optimization method for a PV/T coupled energy system of claim 1, wherein: the saidThe highest efficiency is as inside the optimized objective function for +.>The optimization objectives for the loss are:
minl i ＝H i,in -T 0 S i,in -(H i,out -T 0 S i,out )
wherein H is i,in 、H i,out The enthalpy of each component is input and output respectively, and the unit is KW and S i,in 、S i,out The entropy is input and output for each component, the unit is KW/K, T 0 The unit is K, which is the ambient temperature near the component; and has the following limitations:
wherein H is imin For the lower limit of the enthalpy of each component, H imax For the upper limit of the enthalpy of each component, S imin For the lower limit of the entropy of each component, S imax For the upper limit of the entropy of each component, T 0min T is the upper limit of the ambient temperature near the component 0max Is the lower limit of the ambient temperature near the accessory;
determining upper and lower limits of enthalpy and entropy of each component according to the predicted running conditions of the photovoltaic photo-thermal PV/T coupled energy system; and determining the upper limit and the lower limit of the ambient temperature according to the meteorological conditions input by the system predictive operation.
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