CN114322044B - Comprehensive energy system and operation control method thereof - Google Patents
Comprehensive energy system and operation control method thereof Download PDFInfo
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- CN114322044B CN114322044B CN202111586424.7A CN202111586424A CN114322044B CN 114322044 B CN114322044 B CN 114322044B CN 202111586424 A CN202111586424 A CN 202111586424A CN 114322044 B CN114322044 B CN 114322044B
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
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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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/30—Hydrogen technology
- Y02E60/36—Hydrogen production from non-carbon containing sources, e.g. by water electrolysis
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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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Abstract
The invention discloses a comprehensive energy system and an operation control method thereof, wherein the system comprises a control center, and a power supply subsystem, a heat supply subsystem and a cooling subsystem which are respectively connected with the control center; the heat supply subsystem comprises a medium-low temperature heat storage tank, a high-temperature heat storage tank and an electric heating boiler which are sequentially connected through pipelines; the high-temperature heat storage tank is used for exchanging heat with the medium-low temperature heat storage tank; the electric boiler is used for circularly exchanging heat with the high-temperature heat storage tank; the control center is used for determining the operation strategy of the system according to the real-time load received in each period and a preset operation control model, and periodically controlling the power supply subsystem, the heat supply subsystem and the cold supply subsystem according to the operation strategy. According to the system, the low-grade heat source recovered by the medium-low temperature heat storage tank is stored in the high-temperature heat storage tank, and the high-temperature heat storage tank is circularly heated by the electric heating boiler, so that the low-grade heat energy is heated up in a gradient manner, and the problem that the low-grade heat source cannot be efficiently utilized due to the fact that the temperature is too low is solved.
Description
Technical Field
The invention relates to the technical field of renewable energy sources, in particular to a comprehensive energy source system and an operation control method thereof.
Background
An energy station is a modern energy supply mode which realizes energy supply nearby a load center. At present, with the rapid development of hydrogen energy technology, hydrogen-containing comprehensive energy stations have made a series of technological breakthroughs.
In the existing hydrogen-containing comprehensive energy station, because the temperature of low-grade heat sources provided by equipment such as a hydrogen fuel cell, a solar heat collector and the like is low, when the hydrogen-containing comprehensive energy station is used as direct energy, the applicable occasions are narrow, and the heat energy supply requirement of a load center is often difficult to meet.
Therefore, how to realize the efficient utilization of low-grade heat sources is an important problem to be solved urgently in the current hydrogen-containing comprehensive energy station.
Disclosure of Invention
In view of the above technical problems, the present invention provides a comprehensive energy system, which can improve the energy utilization rate of the comprehensive energy system by converting low-grade heat energy into high-grade heat energy.
In a first aspect, the present invention provides an integrated energy system comprising: the system comprises a control center, and a power supply subsystem, a heat supply subsystem and a cooling subsystem which are respectively connected with the control center; wherein the content of the first and second substances,
the heat supply subsystem comprises a medium-low temperature heat storage tank, a high-temperature heat storage tank and an electric heating boiler which are sequentially connected through pipelines; wherein, the first and the second end of the pipe are connected with each other,
the high-temperature heat storage tank is used for exchanging heat with the medium-low temperature heat storage tank; the electric boiler is used for performing circulating heat exchange with the high-temperature heat storage tank;
the control center is used for determining an operation strategy of the system according to the real-time load received in each period and a preset operation control model, and periodically controlling the power supply subsystem, the heat supply subsystem and the cooling subsystem according to the operation strategy.
Optionally, the heating subsystem further comprises: ground source heat pumps and solar thermal collectors;
the ground source heat pump and the solar heat collector are respectively connected with the pipeline of the medium-low temperature heat storage tank and used for providing heat for the medium-low temperature heat storage tank.
Optionally, the power supply subsystem specifically includes: the photovoltaic plate, the electrolytic cell, the hydrogen storage tank and the hydrogen fuel cell are connected in sequence; wherein the content of the first and second substances,
a hydrogen stop valve which is in communication connection with the control center is arranged between the hydrogen storage tank and the hydrogen fuel cell;
the hydrogen fuel cell is connected with a medium-low temperature heat storage tank in the heat supply subsystem.
Optionally, the pipeline is provided with a control device in communication connection with the control center;
the control device comprises a water pump and a flow control valve.
In a second aspect, the present invention provides a method for controlling an operation of an integrated energy system, the method including:
determining an operation strategy of the comprehensive energy system according to the real-time load received in each period and a preset operation control model;
periodically controlling the integrated energy system based on the operation strategy; in each cycle:
judging whether the difference value of the real-time load and the predicted load in the current period exceeds a preset threshold value or not;
if yes, updating the predicted load according to the real-time load of the current period; at the same time, the user can select the desired position,
solving the operation control model based on the real-time load of the current period to obtain an operation strategy of the current period;
controlling the operation of the comprehensive energy system according to the operation strategy of the current period;
if not, controlling the operation of the comprehensive energy system according to the operation strategy of the previous period.
Optionally, the objective function of the operation control model is to minimize the operation cost of the integrated energy system;
and the constraint conditions of the operation control model comprise energy balance constraint and equipment physical constraint and are used for carrying out bilinear constraint on the temperature and the flow of the comprehensive energy system.
Optionally, the energy balance constraints include an electrical demand balance constraint, a thermal demand balance constraint, and a cold demand balance constraint;
the device physical constraints include hydrogen storage device constraints and heat storage device constraints.
Optionally, the solving the operation control model based on the real-time load of the current period specifically includes:
inputting the real-time load of the current period into the operation control model;
iteratively solving the operation control model based on the upper and lower bounds of the temperature and the flow to obtain an optimal solution; in each iteration solving process:
linearly relaxing the constraint conditions of the operation control model, and solving the linearly relaxed operation control model to obtain a relaxation solution of the current iteration wheel;
judging whether the relaxation solution of the current iteration wheel meets the constraint condition before relaxation;
if so, setting the relaxation solution of the current iteration wheel as the optimal solution and outputting the optimal solution;
if not, updating the upper and lower bounds of the temperature and the flow by utilizing the relaxation of the current iteration wheel;
and carrying out iteration solution of the next iteration round on the operation control model based on the updated upper and lower bounds of the temperature and the flow.
Optionally, the solving the operation control model after the linear relaxation specifically includes:
a group of artificial variables is newly added in the relaxed operation control model, and a linear programming problem is constructed;
judging whether the check numbers of the temperature, the flow and the product of the temperature and the flow before relaxation are the same or not;
and if so, setting the product of the temperature and the flow as a basic variable, and performing basic operation.
Optionally, the updating the predicted load according to the real-time load of the current period specifically includes:
inputting the real-time load of the current period into a pre-constructed clustering model to obtain a long-term load prediction result; the clustering category in the clustering model is determined by a minimum intra-class two-norm criterion and a maximum inter-class one-norm criterion; at the same time, the user can select the required time,
inputting the real-time load of the current period into a pre-constructed time sequence prediction model to obtain a short-term load prediction result;
and correcting the long-term load prediction result by using the short-term load prediction result to obtain the predicted load.
Compared with the prior art, the invention has the beneficial effects that:
the comprehensive energy system provided by the invention recovers the low-grade heat source through the medium-low temperature heat storage tank, stores the recovered low-grade heat in the high-temperature heat storage tank, and simultaneously circularly heats the high-temperature heat storage tank by using the electric heating boiler so as to realize the step temperature rise of the low-grade heat source, thereby effectively solving the problem that the low-grade heat source cannot be efficiently utilized due to too low temperature; the utilization rate of renewable energy sources is improved, and the carbon emission in the heat supply process can be obviously reduced.
Furthermore, the invention also provides an operation control method of the comprehensive energy system, which simultaneously considers the constraints of two variables of temperature and flow on the system optimization control, designs a solving method aiming at a model containing bilinear constraints of temperature and flow, realizes the efficient and stable acquisition of the results of temperature and flow, effectively improves the operation efficiency of the comprehensive energy system and reduces the fuel consumption. Compared with the constant temperature and variable volume or the constant volume and variable temperature constraint in the traditional control method, the operation control method provided by the invention can describe the physical process of system operation more truly and provide more operation optimization spaces.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a block diagram of an integrated energy system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an integrated energy system according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of an operation control method of an integrated energy system according to an embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the integrated energy system and the operation control method thereof provided by the present invention are further described in detail with reference to the accompanying drawings and the detailed description.
Please refer to fig. 1. In a first aspect, an embodiment of the present invention provides an integrated energy system, which specifically includes: the system comprises a control center 1, and a power supply subsystem 2, a heat supply subsystem 3 and a cold supply subsystem 4 which are respectively connected with the control center 1.
Specifically, the heat supply subsystem 3 is connected to the power supply subsystem 2 and the cold supply subsystem 4 respectively.
The heating subsystem 3 comprises a medium-low temperature heat storage tank 31, a high-temperature heat storage tank 32 and an electric boiler 33 which are connected in sequence through pipelines. The high-temperature heat storage tank 32 is used for exchanging heat with the medium-low temperature heat storage tank 31, and the electric boiler 33 is used for exchanging heat with the high-temperature heat storage tank 32 in a circulating manner; the pipeline is provided with a control device 34 which is in communication connection with the control center 1.
The control center 1 is configured to determine an operation strategy of the system according to the real-time load received in each period and a preset operation control model, and periodically control the power supply subsystem 2, the heat supply subsystem 3, and the cold supply subsystem 4 according to the operation strategy.
In the embodiment of the present invention, the heat storage temperature of the medium and low temperature heat storage tank is set to be between 40 ℃ and 65 ℃, and the heat storage temperature of the high temperature heat storage tank is set to be more than 70 ℃.
In this embodiment, the heating subsystem 3 further includes a ground source heat pump 36 and a solar heat collector 35, where the ground source heat pump 36 and the solar heat collector 35 are respectively connected to the medium-low temperature heat storage tank 31 through a pipeline and are configured to provide heat for the medium-low temperature heat storage tank 31.
In this embodiment, the power supply subsystem 2 specifically includes a photovoltaic panel 21, an electrolytic cell 22, a hydrogen storage tank 23, and a hydrogen fuel cell 24 connected in sequence; wherein a hydrogen stop valve which is connected with the control center 1 in a communication way is arranged between the hydrogen storage tank 23 and the hydrogen fuel cell 24; the hydrogen fuel cell 24 is connected to a medium-low temperature heat storage tank 31 in the heating subsystem 3.
It should be noted that the ground source heat pump 36, the solar heat collector 35 and the hydrogen fuel cell 24 can provide low-grade heat for the medium-low temperature heat storage tank 31.
In this embodiment, the control device 34 disposed on the pipeline includes a water pump and a flow control valve, both of which operate according to the control signal provided by the control center 1 to control the optimal operation of each subsystem in the energy system.
The specific structure of the above-described integrated energy system will be described below by way of an example.
Please refer to fig. 2. The comprehensive energy system that this embodiment provided specifically is a hydrogen-containing comprehensive energy station, the energy supply equipment at energy station specifically includes power supply unit, heating equipment and cooling equipment.
Specifically, the power supply device includes a photovoltaic panel 21, an electrolytic cell 22, a hydrogen storage tank 23, and a hydrogen fuel cell 24; the heat supply equipment comprises a solar heat collector 35, a ground source heat pump 36, a medium-low temperature heat storage tank 31, a high-temperature heat storage tank 32 and an electric boiler 33; the cooling device may specifically be an absorption chiller.
In this embodiment, the hydrogen-containing integrated energy station system further includes a control center 1, and a control device 34 disposed between each energy supply device and its connection pipeline; the control device 34 is in communication connection with the control center 1, and is configured to control operation of each device of the energy station in real time according to a signal transmitted by the control center 1.
Specifically, the control device 34 includes a device switch, a water pump, a flow control valve, and a hydrogen shut-off valve.
In particular, the photovoltaic panels 21 are used to supply electrical energy to the energy station, or to supply electrical energy to the electrolyzer 22. After the electrolyzer 22 completes the hydrogen production, the hydrogen is compressed and delivered to the hydrogen storage tank 23, and the hydrogen storage tank 23 is used for providing hydrogen for the hydrogen fuel cell 24.
Specifically, the hydrogen gas stored in the hydrogen storage tank 23 may also be purchased from the outside.
The hydrogen fuel cell 24 can provide electric energy for the energy station, and can be connected with the medium-low temperature heat storage tank 31 to provide a low-grade heat source for the medium-low temperature heat storage tank 31.
In one embodiment, the hydrogen fuel cell 24 may be coupled to the primary side of the first plate exchanger to exchange heat between the incoming and return water; the secondary side of the first plate exchanger is connected with a medium-low temperature heat storage tank 31 in the heat supply equipment, and the medium-low temperature heat storage tank 31 collects low-grade heat generated by the hydrogen fuel cell 24 through the first plate exchanger.
It should be noted that the control device 34 provided at the hydrogen fuel cell 24 is specifically a device switch and a hydrogen stop valve, and is used for controlling the heat energy supply and the hydrogen consumption of the hydrogen fuel cell 24; wherein the hydrogen shut-off valve is provided between the hydrogen storage tank 23 and the hydrogen fuel cell 24.
Specifically, the control device 34 provided at the heat exchange circuit of the hydrogen fuel cell 24 is specifically a water pump and a flow control valve for controlling the flow rate and the head of the circuit.
In this embodiment, the medium-low temperature heat storage tank 31 is respectively connected to the ground source heat pump 36 and the solar heat collector 35, and specifically, low-grade heat provided by the ground source heat pump 36 and the solar heat collector 35 is collected through the water inlet and return pipelines.
Specifically, the water exchange loops between the medium and low temperature heat storage tank 31, the ground source heat pump 36 and the solar heat collector 35 are both configured with a water pump and a flow control valve to control the flow and the lift of the water exchange loop; in addition, the ground source heat pump 36 and the solar heat collector 35 are also provided with equipment switches to accurately control the amount of heat exchange.
It should be noted that, in a specific embodiment, the medium and low temperature heat storage tank 31 also exchanges heat with the high temperature heat storage tank 32 through the second plate heat exchange, and supplements the water temperature in time; the high temperature heat storage tank 32 can be heated by exchanging water with the electric boiler 33.
Specifically, the high temperature heat storage tank 32 also provides high temperature hot water for the energy station through the third plate exchange; and provides high temperature hot water for the absorption chiller through the fourth plate exchange loop.
In this embodiment, the medium-low temperature heat storage tank 31 can directly supply medium-low temperature hot water to the energy station; the high temperature heat storage tank 32 can respectively provide high temperature hot water for the energy station and the absorption refrigerator through the third plate exchanger and the fourth plate exchanger, and the absorption refrigerator provides refrigeration requirement for the energy station through a cold water loop.
It should be noted that the electric boiler 33 and the absorption chiller are both controlled by a device switch, and each water changing loop is provided with a water pump and a flow control valve to control the flow rate and the lift.
The comprehensive energy system provided by the embodiment of the invention recovers the low-grade heat source through the medium-low temperature heat storage tank, stores the recovered low-grade heat in the high-temperature heat storage tank, and circularly heats the high-temperature heat storage tank by using the electric heating boiler so as to realize the step temperature rise of the low-grade heat source, effectively solves the problem that the low-grade heat source cannot be efficiently utilized due to too low temperature, and can obviously reduce the carbon emission in the heat supply process while improving the utilization rate of renewable energy.
In order to realize the operation control of the comprehensive energy system, the existing method mainly performs energy supply control of the system in a constant temperature and variable volume or constant volume and variable temperature mode in a control model. However, in practical engineering applications, both the temperature and the flow rate of the energy system can be adjusted, and it is difficult to ensure efficient and accurate operation of the system by the existing method.
On the improvement of the control method of the comprehensive energy system, if only the quantification (temperature or capacity) of the control model in the existing method is adjusted to be a variable, the improved model has bilinear constraint, the convex problem of the original method is also converted into a non-convex nonlinear programming problem, and the programming problem containing the bilinear constraint cannot be solved through the existing open source solver.
In order to solve the above technical problems, in a second aspect, an embodiment of the present invention correspondingly provides an operation control method of an integrated energy system, where the method includes the following steps.
S1: and determining an operation strategy of the comprehensive energy system according to the real-time load received in each period and a preset operation control model.
It should be noted that the integrated energy system is mainly used for providing energy according to the load demand of the user, and therefore, the supply of the system energy is mainly determined according to the load demand.
In this embodiment, the integrated energy system needs to dynamically obtain the latest real-time load data to determine that the supplied energy matches the current load demand.
The load requirements specifically include electrical loads, medium and low temperature thermal loads, high temperature thermal loads, and cold loads.
S2: and periodically controlling the comprehensive energy system based on the operation strategy.
In each period, whether the difference value of the real-time load and the predicted load in the current period exceeds a preset threshold value is judged.
If yes, updating the predicted load according to the real-time load of the current period; meanwhile, solving the operation control model based on the real-time load of the current period to obtain an operation strategy of the current period; and controlling the operation of the comprehensive energy system according to the operation strategy of the current period.
And if not, controlling the operation of the comprehensive energy system according to the operation strategy of the previous period.
It can be understood that the operation control method can be specifically applied to the control center 1 of the integrated energy system, so that the control center 1 generates a control signal according to the obtained operation strategy, and sends the control signal to the control device 34 corresponding to each pipeline in the system to control each device to operate optimally, thereby realizing efficient operation of the system.
It should be noted that, in the first period of starting operation of the integrated energy system, the real-time load of the first period is firstly input into a pre-constructed clustering model to obtain a long-term load prediction result; meanwhile, inputting the real-time load of the first period into a pre-constructed time sequence prediction model to obtain a short-term load prediction result; and finally, correcting the long-term load prediction result by using the short-term load prediction result to obtain an initial predicted load.
Further, the operation control model is solved based on the obtained initial predicted load, an operation strategy of the comprehensive energy system in the first period is obtained, and the operation of the comprehensive energy system is controlled based on the operation strategy of the first period.
Specifically, when entering the next cycle, the initial predicted load is used to compare the real-time load obtained in the next cycle, and whether the value of the initial predicted load needs to be updated is determined.
The updating process specifically comprises the following steps: inputting the real-time load of the current period into a pre-constructed clustering model to obtain a long-term load prediction result; meanwhile, inputting the real-time load of the current period into a pre-constructed time sequence prediction model to obtain a short-term load prediction result; and correcting the long-term load prediction result by using the short-term load prediction result to obtain a new predicted load after updating the initial predicted load.
Specifically, for the calculation of the predicted load, the embodiment may use the collected historical data to construct a prediction model, and then obtain a predicted load result by solving the model.
Wherein the historical data comprises load data and climate data.
In one embodiment, the climate data and the load data can be arranged into a structured data set, and the data is subjected to data preprocessing firstly to remove gross errors and irregular large load data; and then, the data is arranged into structured load data and climate data by taking hours as units, and specifically, the characteristic vector can be designed into the parallel arrangement of the load data and the climate data.
Further, according to a criterion of two norms in the minimum class and one norm between the maximum classes, clustering analysis is carried out on the historical data, and a clustering result with the clustering number of k is obtained.
And after the clustering class k is determined, clustering the historical data to obtain the average characteristic vector and the average load data in each class, and further obtain a long-term load prediction result.
It should be noted that the criterion of two norms within a minimum class and one norm between maximum classes is used to determine the number k of clustering classes, and specifically, k may be determined by minimizing the variance of samples within a class and maximizing the one norm of the difference vector of samples between classes, and the formula is expressed as:
wherein x is s,i Is the ith eigenvector in s class, ns is the number of samples in s class,
is the mean of the eigenvectors within the s class.
Furthermore, a time sequence prediction model can be built according to historical data so as to predict short-term load.
In this embodiment, the timing prediction model is specifically an LSTM network. After the LSTM network is constructed and trained by using historical data, the user load and the state of the energy storage equipment which run in real time can be input into the LSTM network model which is trained to carry out short-term load prediction when the system runs, and a short-term load prediction result is obtained.
Specifically, the energy storage device state refers to a current energy storage state of an energy storage device in the integrated energy system, where the energy storage device includes a medium-low temperature heat storage tank 31 and a high-temperature heat storage tank 32.
Further, the long term load prediction is modified using the short term load prediction results based on a sigma-nearest neighbor approach.
It can be understood that there is often a difference between the short-term load prediction data and the long-term load prediction data, and when the absolute value of the difference between the short-term load data and the long-term load data is greater than a certain ratio σ, the long-term load data is corrected by using the short-term load data using a proportional adaptive compensation method, and the corrected load data is used as the current predicted load.
The specific implementation of the above-described operation control method will be described below with reference to a specific embodiment.
And after the comprehensive energy system starts to operate, acquiring the specific load demand of a user and inputting the load demand into the system. Firstly, solving a pre-constructed operation control model according to an initial predicted load obtained by calculation to obtain a predicted operation strategy of the system; the strategy comprises the operation power of each device of the system, the water changing amount and the water temperature of each pipeline and the water level and the water temperature of each heat storage tank.
It should be noted that, when the system starts to operate, the operation control model needs to be initialized, and the initialization parameters include: the power rating of the hydrogen fuel cell 24, the capacity of the medium-low temperature heat storage tank 31, the upper and lower limits of the temperature and the water level, the capacity of the high-temperature heat storage tank 32, the upper and lower limits of the temperature and the water level, the installed capacity of the photovoltaic panel 21, the rated power of the electrolytic cell 22, the rated power of the electric heating boiler 33, the capacity of the hydrogen storage tank 23, the rated power and the energy conversion efficiency of the ground source heat pump 36, the rated power of the solar heat collector 35, the rated power and the energy conversion efficiency of the absorption refrigerator.
After the parameter initialization of the model is completed, the embodiment provides a controllable quantity relaxation iterative solution algorithm to solve the model, so as to obtain the operation strategy of the system.
Specifically, the system performs negative feedback control and operation according to the obtained operation strategy, where the negative feedback control refers to performing negative feedback control on the control device 34 through the flow control valve, the water pump, the device switch, the hydrogen stop valve, and the like according to the deviation between the operation strategy and the actual operation situation when the device power, the pipeline flow rate, the pipeline water temperature, and the like in the actual operation of the system are different from the corresponding power, flow rate, water temperature, and the like in the operation strategy, so that the deviation between the actual operation situation and the operation strategy is as small as possible.
When the system receives a new real-time load demand, if the current operation strategy is judged not to meet the current actual load of the user, the predicted load is updated by using the real-time load data, and the new operation strategy is regenerated based on the output result of the real-time load in the operation control model.
And if so, continuing to operate the system according to the current operation strategy until the system stops operating after reaching the operation time.
In the embodiment, the output result of the operation control model is used for ensuring that the operation cost and the fuel consumption are reduced as much as possible on the premise of meeting the load requirement of a user. Thus, the objective function of the model is set to:
wherein λ is h 、
λ sol Respectively representing a hydrogen purchase price, an electricity purchase price and an electricity sale price at the ith moment;
respectively representing the hydrogen buying quantity, the electricity buying quantity and the electricity selling quantity at the ith time of the day d. Wherein the trade unit of hydrogen is kg, and the unit of electric quantity is kWh.
It should be noted that hydrogen purchase cannot occur at every moment, so the present embodiment of the present invention is configured to purchase hydrogen once a day.
Specifically, the constraints of the operation control model are set as energy balance constraints and plant physical constraints.
The energy balance constraint refers to conservation of energy supplied by an energy system and energy consumed by the energy system, and specifically comprises an electric demand balance constraint, a medium-low temperature demand heat balance constraint, a high temperature demand heat balance constraint and a cold demand balance constraint.
The electrical demand balance constraint may be expressed as
Wherein the content of the first and second substances,
respectively representing the power purchase amount of the system, the power generation amount of the photovoltaic panel 21, the power generation amount of the hydrogen fuel cell 24, the power consumption of the electrolytic cell 22, the power consumption of the ground source heat pump 36 and the power load of the energy station at the ith moment of the day d.
The medium and low temperature demand heat balance constraint can be expressed as
Wherein the content of the first and second substances,
respectively represents the heat produced by the hydrogen fuel cell 24, the heat produced by the ground source heat pump 36, the heat produced by the solar heat collector 35, the heat output or absorbed by the medium-low temperature heat storage tank 31, the heat transferred into the medium-low temperature heat storage tank 31 from the high-temperature heat storage tank 32, and the medium-low temperature heat load of the energy station at the ith time of day.
The high temperature demand thermal balance constraint may be expressed as
Wherein k is eb Representing the energy conversion efficiency of the electric boiler 33,
respectively representing the consumed heat of the absorption chiller and the high-temperature thermal load of the energy station at the ith time of day d.
The cold demand balance constraint can be expressed as
Wherein, the first and the second end of the pipe are connected with each other,
respectively representing the refrigerating capacity of the absorption refrigerator and the refrigerating load of the energy station at the ith time of the day d.
The physical constraints of the equipment in the constraint conditions of the operation control model are specifically mathematical descriptions of the energy transfer and energy conversion processes of the equipment in the system, and mainly comprise constraints of a hydrogen storage tank and constraints of a heat storage tank.
In particular, the amount of the solvent to be used,
a daytime constraint representing a long time scale of the hydrogen storage tank 23,
representing the in-day constraints of the hydrogen storage tank 23 on a short time scale.
Wherein, the first and the second end of the pipe are connected with each other,
the hydrogen storage amount of the hydrogen storage tank 23, the hydrogen purchase amount, the hydrogen production amount of the electrolytic cell 22, and the hydrogen consumption amount of the hydrogen fuel cell 24 at the day-d and the i-th time are shown, respectively.
In the present embodiment, the constraint equation of the medium and low temperature thermal storage tank 31 is expressed as:
wherein c represents a specific heat capacity.
It is understood that the variable m in the above constraint equation of the medium-low temperature heat storage tank 31 specifically refers to the flow rate, and the variable τ refers to the temperature. In order to solve the difficulty that the conventional open source solver cannot solve the problem of bilinear constraint planning including temperature and flow, the execution process of the controllable quantity relaxation iteration solving algorithm provided by the embodiment of the invention is as follows.
Specifically, inputting the real-time load of the current period to an operation control model; and carrying out reformation transformation on the original operation control model, and then carrying out iterative solution on the operation control model based on the upper and lower bounds of bilinear constraints of temperature and flow so as to obtain an optimal solution.
In each iteration solving process: and linearly relaxing the constraint conditions of the operation control model, and solving the linearly relaxed operation control model to obtain a relaxation solution of the current iteration wheel.
Judging whether the relaxation solution of the current iteration wheel meets the constraint condition before relaxation; if yes, setting the relaxation solution as an optimal solution and outputting the optimal solution; and if not, updating the upper and lower bounds of the temperature and the flow by using the relaxation solution of the current iteration wheel.
And carrying out the iteration solution of the next iteration round on the operation control model based on the updated upper and lower limits of the temperature and the flow.
In the solving process, the original model is reformed, that is: the product of the temperature and the flow is defined as a reforming variable H, and after reforming, the bilinear constraint only exists in the constraint of the reforming variable H.
Further, the model is simplified according to upper and lower limit constraints of temperature and flow in the model, and bilinear constraints of the temperature and the flow are subjected to linear relaxation.
Specifically, m · τ in the original model is uniformly reduced to H, which is expressed as
The constraint of the original medium-low temperature heat storage tank 31 becomes:
according to the upper and lower bound constraints of two variables of flow and temperature in the original problem, H is relaxed into the following linear constraint:
m L ≤m≤m H
τ L ≤τ≤τ H
H≥m L τ+mτ L -m L τ L
H≥m H τ+mτ H -m H τ H
H≤m H τ+mτ L -m H τ L
H≤mτ H +m L τ-m L τ H
the relaxed linear model can be solved quickly.
Specifically, the method for rapidly solving the relaxed linear model comprises the following steps: adding a group of artificial variables to construct a new linear programming problem with a standard base; the artificial variables refer to mathematical variables that are not included in the original problem but are added for the convenience of solution.
And when solving a new linear programming problem, replacing the newly added artificial variables by using m, tau and H in the model as new basic variables, and solving the linear model by using an H-priority rule and a simplex method.
The H-priority rule is specifically: and when m, tau and H check numbers are the same, preferentially taking H as a new base variable to perform the base operation. The constraints of H are easier to find the optimal solution than the constraints of the remaining variables.
Since the obtained optimal solution is not necessarily in the original problem feasible domain, the feasibility of the solution needs to be verified. Specifically, the solution result is substituted back into the original bilinear constraint, and if the constraint is met, the solution is directly output as the optimal solution of the bilinear model; if not, performing controlled quantity adaptive boundary reduction according to the infeasible solution, updating the upper and lower bounds of the model controlled quantity, and judging the iteration termination condition.
Specifically, the lower bound of the relaxation model objective function is updated, namely: the objective function value of the new model should be greater than or equal to the current function. Further, the controllable amount boundary condition is updated in a self-adaptive mode, and the upper and lower boundaries of the temperature and flow parameters are updated.
If the boundary reduction proportion of the current variable is already large, setting a smaller updating proportion; if the boundary reduction proportion of the current variable is smaller, a larger updating proportion is used for carrying out boundary reduction. The specific reduction method is as follows:
m k,L ≤m k ≤m k,H
τ k,L ≤τ k ≤τ k,H
m k+1,H ＝min(m k,H ,m k+1 +e·max(m k,H -m k+1 ,m k+1 -m k,L ))
m k+1,L ＝max(m k,L ,m k+1 -e·max(m k,H -m k+1 ,m k+1 -m k,L ))
τ k+1,H ＝min(τ k,H ,τ k+1 +e·max(τ k,H -τ k+1 ,τ k+1 -τ k,L ))
τ k+1,L ＝max(τ k,L ,τ k+1 -e·max(τ k,H -τ k+1 ,τ k+1 -τ k,L ))
wherein e represents an adaptive reduction coefficient, m k,L ,m k,H ,m k The lower bound, the upper bound and the solution result of the flow at the k-th iteration are represented. Tau is k,L ,τ k,H ,τ k The lower and upper bounds of the temperature at the kth iteration are shown, along with the solution. The updated boundary is used for the next relaxation and solution of the model.
And if the updated boundary gap is small and the termination condition is met, searching the infeasible solution in the reverse direction along the last updated path until the infeasible solution is feasible. Wherein, the updating path refers to a straight line between the last solution and the last feasible solution, and the feasible solution is output after reversely searching from the last solution along the straight line.
It should be noted that the feasible solution result finally output by the model specifically includes: the operating power, hydrogen consumption, and heat generation of the hydrogen fuel cell 24 at each time; the power generated by the photovoltaic panel 21 at each moment; the operating power and hydrogen production capacity of the electrolyzer 22 at each moment; the heat collection power of the solar heat collector 35 at each moment; the capacity, hydrogen storage amount, and hydrogen use amount of the hydrogen storage tank 23 at each time; the working power of the electric boiler 33 at each moment; the water temperature and the water level of the medium and low temperature heat storage tank 31, the water change amount and the water change temperature between the medium and low temperature heat storage tank 31 and the hydrogen fuel cell 24, the water change amount and the water change temperature between the medium and low temperature heat storage tank 31 and the high temperature heat storage tank 32, the water change amount and the water change temperature between the medium and low temperature heat storage tank 31 and the ground source heat pump 36, the water change amount and the water change temperature between the medium and low temperature heat storage tank 31 and the solar heat collector 35, the water temperature and the water amount of the medium and low temperature heat storage tank 31 for supplying energy to the energy source station, and the water temperature and the water amount of the medium and low temperature heat storage tank 31 for supplementing water at each moment; the water temperature and the water level of the high temperature heat storage tank 32, the water change amount and the water change temperature between the high temperature heat storage tank 32 and the medium and low temperature heat storage tank 31, the water change amount and the water change temperature between the high temperature heat storage tank 32 and the electric boiler 33, the water change amount and the water change temperature between the high temperature heat storage tank 32 and the absorption refrigerator, and the hot water amount and the heated water temperature circularly heated by the high temperature heat storage tank 32 and the electric boiler 33 at each moment; the working power of the absorption type refrigerating machine is absorbed at each moment.
The operation control method of the comprehensive energy system provided by the embodiment considers the constraints of temperature and flow bivariates on system optimization control at the same time, and efficiently solves the constraints, so that the operation efficiency of the comprehensive energy system is effectively improved, and the fuel consumption is reduced; on the other hand, compared with the constant temperature and variable volume or the constant volume and variable temperature constraint in the traditional control method, the operation control method can describe the physical process of system operation more truly and provide more operation optimization spaces.
In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the operation control method according to any one of the above embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by a computer program, which may be stored in a computer-readable storage medium, and may include the processes of the embodiments of the methods when executed. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (7)
1. An integrated energy system, comprising: the system comprises a control center, and a power supply subsystem, a heat supply subsystem and a cold supply subsystem which are respectively connected with the control center;
the heat supply subsystem comprises a medium-low temperature heat storage tank, a high-temperature heat storage tank and an electric heating boiler which are sequentially connected through pipelines; wherein, the first and the second end of the pipe are connected with each other,
the high-temperature heat storage tank is used for exchanging heat with the medium-low temperature heat storage tank; the electric boiler is used for performing circulating heat exchange with the high-temperature heat storage tank;
the heating subsystem further comprises:
ground source heat pumps and solar collectors;
the ground source heat pump and the solar heat collector are respectively connected with the pipeline of the medium-low temperature heat storage tank and are used for providing heat for the medium-low temperature heat storage tank;
the power supply subsystem specifically comprises:
the photovoltaic plate, the electrolytic cell, the hydrogen storage tank and the hydrogen fuel cell are connected in sequence; wherein, the first and the second end of the pipe are connected with each other,
a hydrogen stop valve which is in communication connection with the control center is arranged between the hydrogen storage tank and the hydrogen fuel cell;
the hydrogen fuel cell is connected with a medium-low temperature heat storage tank in the heat supply subsystem;
the control center is used for determining an operation strategy of the system according to the real-time load received in each period and a preset operation control model, and periodically controlling the power supply subsystem, the heat supply subsystem and the cooling subsystem according to the operation strategy;
the method includes that the control center is used for determining an operation strategy of a system according to a real-time load received in each period and a preset operation control model, and periodically controlling the power supply subsystem, the heat supply subsystem and the cold supply subsystem according to the operation strategy, and specifically includes:
determining an operation strategy of the system according to the real-time load received in each period and a preset operation control model;
periodically controlling the power supply subsystem, the heat supply subsystem, and the cold supply subsystem based on the operating strategy; in each cycle:
judging whether the difference value of the real-time load and the predicted load in the current period exceeds a preset threshold value or not;
if yes, updating the predicted load according to the real-time load of the current period; at the same time, the user can select the desired position,
solving the operation control model based on the real-time load of the current period to obtain an operation strategy of the current period;
controlling the power supply subsystem, the heat supply subsystem and the cold supply subsystem to operate according to the operation strategy of the current period;
if not, controlling the operation of the power supply subsystem, the heat supply subsystem and the cold supply subsystem according to the operation strategy of the previous period;
wherein the solving of the operation control model based on the real-time load of the current period specifically includes:
inputting the real-time load of the current period into the operation control model;
iteratively solving the operation control model based on upper and lower bounds of temperature and flow to obtain an optimal solution; in each iteration solving process:
linearly relaxing the constraint conditions of the operation control model, and solving the linearly relaxed operation control model to obtain a relaxed solution of the current iteration wheel;
judging whether the relaxation solution of the current iteration wheel meets the constraint condition before relaxation;
if so, setting the relaxation solution of the current iteration wheel as the optimal solution and outputting the optimal solution;
if not, updating the upper and lower bounds of the temperature and the flow by utilizing the relaxation of the current iteration wheel;
and carrying out the iteration solution of the next iteration round on the operation control model based on the updated upper and lower limits of the temperature and the flow.
2. The integrated energy system of claim 1, wherein the pipeline is provided with a control device in communication with the control center;
the control device comprises a water pump and a flow control valve.
3. An operation control method of an integrated energy system applied to the integrated energy system according to any one of claims 1 to 2, characterized by comprising:
determining an operation strategy of the comprehensive energy system according to the real-time load received in each period and a preset operation control model;
periodically controlling the integrated energy system based on the operation strategy; in each cycle:
judging whether the difference value of the real-time load and the predicted load in the current period exceeds a preset threshold value or not;
if yes, updating the predicted load according to the real-time load of the current period; at the same time, the user can select the desired position,
solving the operation control model based on the real-time load of the current period to obtain an operation strategy of the current period;
controlling the operation of the comprehensive energy system according to the operation strategy of the current period;
if not, controlling the operation of the comprehensive energy system according to the operation strategy of the previous period;
wherein the solving of the operation control model based on the real-time load of the current period specifically includes:
inputting the real-time load of the current period into the operation control model;
iteratively solving the operation control model based on upper and lower bounds of temperature and flow to obtain an optimal solution; in each iteration solving process:
linearly relaxing the constraint conditions of the operation control model, and solving the linearly relaxed operation control model to obtain a relaxation solution of the current iteration wheel;
judging whether the relaxation solution of the current iteration wheel meets the constraint condition before relaxation;
if so, setting the relaxation solution of the current iteration wheel as the optimal solution and outputting the optimal solution;
if not, updating the upper and lower bounds of the temperature and the flow by utilizing the relaxation of the current iteration wheel;
and carrying out iteration solution of the next iteration round on the operation control model based on the updated upper and lower bounds of the temperature and the flow.
4. The operation control method according to claim 3,
the objective function of the operation control model is to minimize the operation cost of the comprehensive energy system;
and the constraint conditions of the operation control model comprise energy balance constraint and equipment physical constraint and are used for carrying out bilinear constraint on the temperature and the flow of the comprehensive energy system.
5. The operation control method according to claim 4,
the energy balance constraints include an electrical demand balance constraint, a thermal demand balance constraint, and a cold demand balance constraint;
the device physical constraints include hydrogen storage device constraints and heat storage device constraints.
6. The operation control method according to claim 3, wherein the solving of the operation control model after linear relaxation is specifically:
adding a group of artificial variables in the relaxed operation control model to construct a linear programming problem;
judging whether the temperature before relaxation, the flow and the check number of the product of the temperature and the flow are the same or not;
if so, setting the product of the temperature and the flow as a basic variable, and performing a basic operation.
7. The operation control method according to claim 3, wherein the updating the predicted load according to the real-time load of the current cycle includes:
inputting the real-time load of the current period into a pre-constructed clustering model to obtain a long-term load prediction result; the clustering category in the clustering model is determined by a minimum intra-class two-norm criterion and a maximum inter-class one-norm criterion; at the same time, the user can select the desired position,
inputting the real-time load of the current period into a pre-constructed time sequence prediction model to obtain a short-term load prediction result;
and correcting the long-term load prediction result by using the short-term load prediction result to obtain the predicted load.
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