CN112993973B - Heat storage device and configuration method and device of power storage device - Google Patents
Heat storage device and configuration method and device of power storage device Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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Abstract
The embodiment of the invention provides a heat storage device, a configuration method of the heat storage device and a configuration device of the heat storage device. The method comprises the following steps: acquiring unit parameters of each thermal power plant and thermal power plant in an electric power system, energy and load prediction results of the electric power system, and cost parameters of a heat storage device and a power storage device; and acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage and electricity storage device. According to the heat storage device, the configuration method and the configuration device of the heat storage device, the configuration capacity and the configuration power of the heat storage device and the power storage device can be obtained more accurately by comprehensively considering the heat storage device and the heat storage device, so that the functions of different types of heat storage devices and the power storage device can be played, and the resource waste is reduced.
Description
Technical Field
The present invention relates to the field of energy technologies, and in particular, to a heat storage device, and a method and an apparatus for configuring a heat storage device.
Background
The renewable energy sources such as wind power and photovoltaic are rapidly developed, and meanwhile, the problems of wind power and photovoltaic of the power grid are increasingly serious, so that the further development of the renewable energy sources is obviously restricted. The renewable energy source duty ratio of wind power, photovoltaic and the like is continuously improved, so that the flexibility requirement of the power grid is increased. However, the conventional units of the power grid mainly comprise coal-fired units with lower flexibility, and power supply duty ratio of hydroelectric units, gas units and the like with higher flexibility is small, so that contradiction of insufficient system flexibility supply is more remarkable. In particular, in a heating season, most of coal-fired units in an operation state are cogeneration units, and in order to ensure the heating requirement, the cogeneration units adopt an operation mode of 'electricity by heat determination', so that the flexibility of the units is more insufficient, and the wind power wind discarding and photovoltaic light discarding problems are more serious.
In order to more efficiently utilize wind or light (solar) resources, the capacity and power configuration of the energy storage and heat storage devices is critical. The excessive capacity and power can lead to resource waste; the capacity and the power are too small, which can lead to wind power and photovoltaic light discarding and also can lead to the waste of natural resources. The existing configuration method is difficult to obtain accurate capacity and power configuration of the energy storage device and the heat storage device, and larger resource waste can be caused.
Disclosure of Invention
The embodiment of the invention provides a heat storage device and a configuration method and device of the heat storage device, which are used for solving or at least partially solving the defect of larger resource waste in the prior art.
In a first aspect, an embodiment of the present invention provides a heat storage device and a configuration method of the heat storage device, including:
acquiring unit parameters of each thermal power plant and thermal power plant in an electric power system, energy and load prediction results of the electric power system, and cost parameters of a heat storage device and a power storage device;
and acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage and electricity storage device.
Preferably, the specific step of obtaining the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the unit parameters of each thermal power plant and the thermal power plant in the electric power system, the energy and load prediction result of the electric power system, and the cost parameters of the heat storage and electricity storage device comprises the following steps:
establishing a double-layer planning model according to unit parameters of each thermal power plant and thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage device and the electricity storage device;
and acquiring the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the double-layer planning model.
Preferably, the specific step of obtaining the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the double-layer planning model includes:
converting the inner layer model into additional conditions of the outer layer model in the double-layer planning model according to KKT conditions of the inner layer model in the double-layer planning model;
and acquiring the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the mixed integer linear programming method and the additional conditions of the outer layer model and the outer layer model.
Preferably, the objective function of the outer layer model is
F＝C s +C h +C qf +C y
Wherein C is s Representing an initial investment cost of the electricity storage device; c (C) h Representing an initial investment cost of the heat storage device; c (C) qf Representing the wind abandoning punishment cost; c (C) y Representing the operating costs of the power system.
Preferably, the objective function of the inner layer model is
C y ＝∑C c (i,t)+∑C e (i,t)
Wherein C is c (i, t) represents the cost corresponding to the coal consumed by the ith thermal power generating unit at the time t; c (C) e And (i, t) represents the cost corresponding to the coal consumed by the ith cogeneration unit at the time t.
Preferably, the constraints of the inner layer model include:
the method comprises the steps of power balance constraint conditions, heat supply constraint conditions, wind power output constraint conditions, unit heat output upper and lower limit constraint conditions, unit climbing rate constraint conditions, cogeneration unit output upper and lower limit constraint conditions, heat storage and release power constraint conditions, heat storage device capacity constraint conditions, electricity storage device capacity constraint conditions, periodic heat storage constraint conditions and periodic electricity storage capacity constraint conditions.
Preferably, the specific step of converting the inner layer model into the additional condition of the outer layer model in the double layer planning model according to the KKT condition of the inner layer model in the double layer planning model comprises the following steps:
constructing an inner layer optimized Lagrangian function according to the equality constraint and the inequality constraint in the constraint condition of the inner layer model;
and converting the inner layer model into additional conditions of the outer layer model in the double-layer planning model according to the Lagrange function of the inner layer optimization.
In a second aspect, an embodiment of the present invention provides a heat storage device and a configuration device of the heat storage device, including:
the parameter acquisition module is used for acquiring unit parameters of each thermal power plant and thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage device and the electricity storage device;
and the configuration acquisition module is used for acquiring the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the unit parameters of each thermal power plant and the thermal power plant in the electric power system, the energy and load prediction result of the electric power system and the cost parameters of the heat storage and electricity storage device.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the steps of the method for configuring a heat storage device and an electric storage device being implemented when the program is executed as provided in any one of the various possible implementations of the first aspect.
In a fourth aspect, embodiments of the present invention provide a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a heat storage device and a method of configuring a power storage device as provided by any of the various possible implementations of the first aspect.
According to the configuration method and the configuration device of the heat storage device and the power storage device, provided by the embodiment of the invention, the configuration capacity and the configuration power of the heat storage device and the power storage device are obtained according to the unit parameters of each thermal power plant and thermal power plant in the power system, the energy and load prediction result of the power system and the cost parameters of the heat storage and power storage device by comprehensively considering the power storage device and the power storage device, so that the configuration capacity and the configuration power of the heat storage device and the power storage device can be more accurate, the functions of different types of heat storage devices and power storage devices can be exerted, the safe and stable operation of the whole system is met, the consumption of renewable energy sources is improved, and the resource waste caused by wind abandoning and other reasons is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a configuration method of a heat storage device and an electric storage device according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a configuration device of a heat storage device and an electric storage device according to an embodiment of the present invention;
fig. 3 is a schematic entity structure of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to overcome the problems in the prior art, the embodiment of the invention provides a heat storage device, a configuration method and a device thereof.
Fig. 1 is a schematic flow chart of a configuration method of a heat storage device and an electricity storage device according to an embodiment of the present invention. As shown in fig. 1, the method includes: and step S101, acquiring unit parameters of each thermal power plant and thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage device and the electricity storage device.
The electric power system comprises a thermal power plant, a wind power plant, a heat storage device and an electric storage device. The unit of the thermal power plant is a thermal power unit, the unit of the thermal power plant is a cogeneration unit, and the unit of the wind power plant is a wind turbine.
The plant parameters of the thermal power plant may include electrical output of the thermal power plant, and the like.
The unit parameters of the thermal power plant can comprise the electric output, the heat output and the like of the cogeneration unit.
The energy prediction result of the power system may include a prediction value of total wind power output in the power system, and the like.
The load prediction result of the electric power system can comprise an electric load prediction result at each moment of the electric power system and a prediction result of total heat load required to be born by each heat supply partition thermal power plant at each moment.
The cost parameters of the heat storage device may include a cost coefficient of the capacity of the heat storage device, a cost coefficient of the power of the heat storage device, an annual rate of the heat storage device, a maintenance cost per power per day of heat storage, and a lifetime of the heat storage device.
The cost parameters of the electrical storage device may include a cost factor for the capacity of the electrical storage device, a cost factor for the power of the electrical storage device, an annual rate of the electrical storage device, a corresponding maintenance cost per power storage per day, and a lifetime of the electrical storage device.
And step S102, acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage and electricity storage device.
Specifically, the configuration capacity and the configuration power of the heat storage device, and the configuration capacity and the configuration power of the power storage device, which minimize the total cost of the power system, may be obtained as configuration results according to the optimization method and the unit parameters of each thermal power plant and the thermal power plant in the power system, the energy and load prediction results of the power system, and the cost parameters of the heat storage and power storage devices.
According to the embodiment of the invention, the configuration capacity and the configuration power of the heat storage device and the electricity storage device are obtained by comprehensively considering the electricity storage device and the heat storage device according to the unit parameters of each thermal power plant and the thermal power plant in the electric power system, the energy and load prediction result of the electric power system and the cost parameters of the heat storage and electricity storage devices, so that more accurate configuration capacity and configuration power of the heat storage device and the electricity storage device can be obtained, and the scale of a proper amount of the energy storage device and the electricity storage device is determined, thereby playing the roles of different types of heat storage devices and the electricity storage device, improving the consumption of renewable energy sources while meeting the safe and stable operation of the whole system, avoiding the shortage of flexible resources of the system caused by a purely 'heat-fixed electricity' mode, and reducing the waste of resources caused by wind abandoning and the like. In addition, the environmental pollution and the energy consumption can be reduced, and considerable economic benefit, environmental benefit and social benefit can be generated.
Based on the foregoing embodiments, the specific steps of obtaining the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the unit parameters of each thermal power plant and the thermal power plant in the electric power system, the energy and load prediction result of the electric power system, and the cost parameters of the heat storage and electricity storage device include: and establishing a double-layer planning model according to unit parameters of each thermal power plant and thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage device and the electricity storage device.
Specifically, a planning model can be established according to unit parameters of each thermal power plant and thermal power plant in the electric power system, energy and load prediction results of the electric power system, and cost parameters of the heat storage device and the electricity storage device.
The objective function of the planning model, which aims to minimize the overall cost of the power system, is called the objective function of the skin model.
The total cost of the power system may include the operating cost of the power system, the initial investment costs of the power storage and heat storage devices, and the wind curtailment penalty cost.
In the objective function of the planning model, another objective function is nested, so that the planning model is a double-layer planning model. The other objective function is an objective function of the inner layer model. The objective function of the inner model is to minimize the running cost of the power system.
The inner layer model may include a number of constraints for constraining the power output of the generator set, the capacity and reserves of the heat storage device and the electricity storage device, and the like.
And acquiring the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the double-layer planning model.
Specifically, according to the optimization method, the configuration capacity and the configuration power of the heat storage device, which minimizes the total cost of the electric power system, and the configuration capacity and the configuration power of the electric power storage device are obtained as the optimal solutions of the two-layer planning model.
The optimal solution of the double-layer planning model is a configuration result.
According to the embodiment of the invention, by establishing the double-layer planning model and solving, more accurate configuration capacity and configuration power of the heat storage device and the electricity storage device can be obtained, and resource waste can be reduced.
Based on the foregoing disclosure of each embodiment, the specific steps of obtaining the configuration capacity and the configuration power of the heat storage device and the electric storage device according to the dual-layer planning model include: and converting the inner layer model into additional conditions of the outer layer model in the double-layer planning model according to the KKT conditions of the inner layer model in the double-layer planning model.
Specifically, since the dual-layer planning model includes an inner layer and an outer layer, in order to obtain an optimal solution for the dual-layer planning model, the dual-layer planning model needs to be converted into a single-layer planning model.
The karuss-Kuhn-turnconditions, also known as KKT conditions, are a necessary and sufficient condition for a nonlinear programming (Nonlinear Programming) problem to be able to optimize the solution under certain regular conditions.
According to the KKT condition of the layer model, the inner layer model can be converted into the additional condition of the outer layer model, so that the outer layer model can be combined to obtain the single-layer planning model.
And acquiring the configuration capacity and the configuration power of the heat storage device and the electric storage device according to the mixed integer linear programming method and the additional conditions of the outer layer model and the outer layer model.
Specifically, a mixed integer linear programming method may be adopted, and the configuration capacity and the configuration power of the heat storage device, and the configuration capacity and the configuration power of the power storage device, which minimize the total cost of the power system, are obtained according to the single-layer planning model obtained by conversion.
According to the embodiment of the invention, the double-layer planning model is converted into the single-layer planning model, and the single-layer planning model is solved, so that more accurate configuration capacity and configuration power of the heat storage device and the electricity storage device can be obtained, and resource waste can be reduced.
Based on the contents of the above embodiments, the objective function of the outer layer model is
F＝C s +C h +C qf +C y
Wherein C is s Representing an initial investment cost of the electricity storage device; c (C) h Representing an initial investment cost of the heat storage device; c (C) qf Representing the wind abandoning punishment cost; c (C) y Representing the operating costs of the power system.
In particular, the total cost of the power system may include an initial investment cost of the electricity storage device, an initial investment cost of the heat storage device, a wind curtailment penalty cost, and an operation cost of the power system.
The calculation formula of the initial investment cost of the electricity storage device is
Wherein E is s Representing a configuration capacity of the power storage device; p (P) s Representing the configuration power of the power storage device; k (K) E A cost factor representing the capacity of the electrical storage device; k (K) P A cost factor representing the power of the electrical storage device; r is (r) 0 Representing annual rate of the electricity storage device; k (K) W Maintenance cost corresponding to each power storage day; y is Y s Indicating the life of the electrical storage device. Subscript E, P, W is uppercase.
Wherein E is h Representation storeThe capacity of the thermal device; p (P) h Representing the configuration power of the heat storage device; k (K) e A cost coefficient representing a capacity of the heat storage device; k (K) p A cost coefficient representing the power of the heat storage device; r is (r) 1 Represents the annual rate of the heat storage device; k (K) w The maintenance cost corresponding to each day of heat storage per power; y is Y h Indicating the life of the heat storage device. Subscripts e, p, w are all lowercase.
C qf ＝K qf *(P for -P w )
Wherein K is qf A penalty factor corresponding to each unit of air discarding quantity is represented; p (P) for A predicted value of the total wind power output in the power system is represented; p (P) w Representing the actual value of the total wind power output in the power system.
Based on the content of the embodiments, the objective function of the inner layer model is that
C y ＝ΣC c (i,t)+ΣC e (i,t)
Wherein C is c (i, t) represents the cost corresponding to the coal consumed by the ith thermal power generating unit at the time t; c (C) e And (i, t) represents the cost corresponding to the coal consumed by the ith cogeneration unit at the time t.
Specifically, the cost C corresponding to the coal consumed by the ith thermal power generating unit at the time t c The calculation formula of (i, t) is
Wherein, the liquid crystal display device comprises a liquid crystal display device,the electric output of the ith thermal power generating unit at the time t is shown; a, a i 、b i And c i The coefficient obtained in advance can be determined according to the parameters of the thermal power generating unit.
Cost C corresponding to coal consumed by ith cogeneration unit at t moment e The calculation formula of (i, t) is
Wherein, the liquid crystal display device comprises a liquid crystal display device,the electric output of the ith cogeneration unit at the t moment is shown; />The heat output of the ith cogeneration unit at the t moment is shown; a is that i 、B i 、C i 、D i 、E i And F i For the pre-obtained coefficients, it may be determined based on parameters of the cogeneration unit.
Based on the content of the above embodiments, constraints of the inner layer model include: the method comprises the steps of power balance constraint conditions, heat supply constraint conditions, wind power output constraint conditions, unit heat output upper and lower limit constraint conditions, unit climbing rate constraint conditions, cogeneration unit output upper and lower limit constraint conditions, heat storage and release power constraint conditions, heat storage device capacity constraint conditions, electricity storage device capacity constraint conditions, periodic heat storage constraint conditions and periodic electricity storage capacity constraint conditions.
Specifically, the power balance constraint is that
Wherein, the liquid crystal display device comprises a liquid crystal display device,the electric output of the ith cogeneration unit at the t moment is shown; />The actual value of the wind power output of the power system at the moment t is the actual value of the wind power output of the power system at the moment t; />The stored electricity quantity (simply referred to as "stored electricity quantity") of the electricity storage device at the time t is represented; />Representing the stored electricity quantity of the electricity storage device at the time t-1; />The interaction quantity of the power system and an external power grid at the moment t is represented; />And (5) representing the electric load prediction result of the electric power system at the time t.
The heat supply constraint condition is that
Wherein k=1, 2, …, M is the total number of heating zones;the prediction result of the total heat load which needs to be born by the k-th partition thermal power plant at the t moment is shown; />Representing the heat storage amount of the k-th partition heat storage device at the time t; />Representing the heat storage amount of the k-th partition heat storage device at the time t-1; />The heat output of the ith cogeneration unit at the t moment is shown; />And->The union of (2) represents the set of cogeneration units of the kth partition.
The constraint condition of wind power output is that
Wherein, the liquid crystal display device comprises a liquid crystal display device,and the predicted value of the wind power output at the time t is shown.
The constraint conditions of the upper limit and the lower limit of the heat output of the unit are as follows
Wherein P is h,max,i The upper limit of the heat output of the i-th cogeneration unit is shown.
The constraint condition of the climbing rate of the unit is-P ram,i ≤P i t -P i t-1 ≤P ram,i
Wherein P is ram,i And the upper limit of the climbing of the heat output of the ith cogeneration unit is indicated.
The constraint conditions of the upper and lower limits of the output of the cogeneration unit are that
Wherein P is ei,min,i 、P el,max,i Respectively representing a lower limit and an upper limit of the electric output under the pure coagulation working condition; c m,i 、c v,i The upper and lower limits of the cogeneration unit are determined by the thermoelectric characteristics.
The constraint condition of heat storage and release power is that
The constraint condition of the stored electric power is that
The capacity constraint condition of the heat storage device is that
The capacity constraint condition of the electricity storage device is that
The constraint condition of periodic heat storage is that
Where T represents the duration of one cycle.
The constraint condition of the periodic electricity storage quantity is that
Embodiments of the invention
Based on the foregoing embodiments, the specific steps of converting the inner layer model into the additional condition of the outer layer model in the dual layer planning model according to the KKT condition of the inner layer model in the dual layer planning model include: and constructing a Lagrangian function of the inner layer optimization according to the equality constraint and the inequality constraint in the constraint condition of the inner layer model.
It is understood that the constraint conditions of the inner layer model include equality constraint and inequality constraint, for example, the electric power balance constraint, the periodic heat storage constraint, the periodic electric power storage constraint and the like are equality constraint, and the heat supply constraint, the wind power output constraint and the like are inequality constraint.
The constraint condition of the inner layer model is divided into equality constraint and inequality constraint, and the inner layer model is expressed as MinC y
Wherein, the liquid crystal display device comprises a liquid crystal display device,representing an equality constraint; />Representing inequality constraints; m represents the number of equality constraints; n represents the number of inequality constraints.
Constructing an inner-layer optimized Lagrangian function according to the equality constraint and the inequality constraint in the constraint conditions of the inner-layer model:
wherein lambda is j Corresponding to the j-th equality constraint Lagrangian multiplier; mu (mu) k Corresponding to the k-th inequality constraint, the Lagrangian multiplier.
And converting the inner layer model into additional conditions of the outer layer model in the double-layer planning model according to the Lagrange function of the inner layer optimization.
Specifically, the additional condition for converting the inner layer model into the outer layer model in the double-layer planning model according to the Lagrange function of the inner layer optimization is that
μ k ≥0
According to the embodiment of the invention, the double-layer planning model is converted into the single-layer planning model, and the single-layer planning model is solved, so that more accurate configuration capacity and configuration power of the heat storage device and the electricity storage device can be obtained, and resource waste can be reduced.
Fig. 2 is a schematic structural diagram of a configuration device of a heat storage device and an electric storage device according to an embodiment of the present invention. Based on the content of the above embodiments, as shown in fig. 2, the apparatus includes a parameter obtaining module 201 and a configuration obtaining module 202, where:
the parameter obtaining module 201 is configured to obtain unit parameters of each thermal power plant and thermal power plant in the power system, energy and load prediction results of the power system, and cost parameters of the heat storage device and the electricity storage device;
the configuration obtaining module 202 is configured to obtain configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system, and cost parameters of the heat storage and electricity storage device.
Specifically, the parameter acquisition module 201 and the configuration acquisition module 202 are electrically connected.
The parameter acquisition module 201 acquires unit parameters of each thermal power plant and thermal power plant in the power system, energy and load prediction results of the power system, and cost parameters of the heat storage device and the electricity storage device.
The configuration obtaining module 202 may obtain, as the configuration result, a configuration capacity and a configuration power of the heat storage device, which minimizes the total cost of the electric power system, and a configuration capacity and a configuration power of the electric power storage device, according to the optimization method and unit parameters of each of the thermal power plant and the thermal power plant in the electric power system, the energy and load prediction result of the electric power system, and the cost parameters of the heat storage and electric power storage device.
The specific method and flow of implementing corresponding functions by each module included in the configuration device of the heat storage device and the power storage device are detailed in the embodiments of the configuration method of the heat storage device and the power storage device, and are not repeated herein.
The arrangement device of the heat storage device and the electricity storage device is used for the arrangement method of the heat storage device and the electricity storage device of the foregoing embodiments. Therefore, the description and definition in the configuration methods of the heat storage device and the electric storage device in the foregoing embodiments may be used for understanding the respective execution modules in the embodiments of the present invention.
According to the embodiment of the invention, the configuration capacity and the configuration power of the heat storage device and the electric storage device are obtained by comprehensively considering the electric storage device and the heat storage device according to the unit parameters of each thermal power plant and the thermal power plant in the electric power system, the energy and load prediction result of the electric power system and the cost parameters of the heat storage and electric storage device, so that the more accurate configuration capacity and configuration power of the heat storage device and the electric storage device can be obtained, the functions of different types of heat storage devices and electric storage devices can be played, the safe and stable operation of the whole system is met, the consumption of renewable energy sources is improved, and the resource waste caused by wind abandoning and the like is reduced. In addition, the environmental pollution and the energy consumption can be reduced, and considerable economic benefit, environmental benefit and social benefit can be generated.
Fig. 3 is a schematic entity structure of an electronic device according to an embodiment of the present invention. Based on the content of the above embodiment, as shown in fig. 3, the electronic device may include: a processor (processor) 301, a memory (memory) 302, and a bus 303; wherein the processor 301 and the memory 302 perform communication with each other through the bus 303; the processor 301 is configured to invoke computer program instructions stored in the memory 302 and executable on the processor 301 to perform the configuration method of the heat storage device and the electricity storage device provided by the above method embodiments, for example, including: acquiring unit parameters of each thermal power plant and thermal power plant in an electric power system, energy and load prediction results of the electric power system, and cost parameters of a heat storage device and a power storage device; and acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage and electricity storage device.
Another embodiment of the present invention discloses a computer program product, including a computer program stored on a non-transitory computer readable storage medium, the computer program including program instructions, which when executed by a computer, are capable of executing the configuration method of the heat storage device and the electricity storage device provided in the above method embodiments, for example, including: acquiring unit parameters of each thermal power plant and thermal power plant in an electric power system, energy and load prediction results of the electric power system, and cost parameters of a heat storage device and a power storage device; and acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage and electricity storage device.
Further, the logic instructions in memory 302 described above may be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand alone product. Based on such understanding, the technical solution of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art or a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, randomAccessMemory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Another embodiment of the present invention provides a non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the method for configuring a heat storage device and an electricity storage device provided in the foregoing method embodiments, including, for example: acquiring unit parameters of each thermal power plant and thermal power plant in an electric power system, energy and load prediction results of the electric power system, and cost parameters of a heat storage device and a power storage device; and acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage and electricity storage device.
The apparatus embodiments described above are merely illustrative, wherein elements illustrated as separate elements may or may not be physically separate, and elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. It is to be understood that the foregoing aspects, in essence, or portions thereof, may be embodied in the form of a software product that may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., including instructions for causing a computer device (which may be a personal computer, server, or network device, etc.) to perform the various embodiments, or methods of portions of the embodiments, described above.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (6)
1. A heat storage device and a method of configuring a heat storage device, comprising:
acquiring unit parameters of each thermal power plant and thermal power plant in an electric power system, energy and load prediction results of the electric power system, and cost parameters of a heat storage device and a power storage device;
acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage and electricity storage device;
the specific steps of obtaining the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the unit parameters of each thermal power plant and the thermal power plant in the electric power system, the energy and load prediction result of the electric power system and the cost parameters of the heat storage and electricity storage device comprise:
establishing a double-layer planning model according to unit parameters of each thermal power plant and thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage device and the electricity storage device;
acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to the double-layer planning model;
the specific steps of obtaining the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the double-layer planning model comprise:
converting the inner layer model into additional conditions of the outer layer model in the double-layer planning model according to KKT conditions of the inner layer model in the double-layer planning model;
acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to a mixed integer linear programming method and additional conditions of the outer layer model and the outer layer model;
the objective function of the outer layer model is
F＝C s +C h +C qf +C y
Wherein C is s Representing an initial investment cost of the electricity storage device; c (C) h Representing an initial investment cost of the heat storage device; c (C) qf Representing the wind abandoning punishment cost; c (C) y Representing the running cost of the power system;
the objective function of the inner layer model is
C y ＝∑C c (i,t)+∑C e (i,t)
Wherein C is c (i, t) represents the cost corresponding to the coal consumed by the ith thermal power generating unit at the time t; c (C) e And (i, t) represents the cost corresponding to the coal consumed by the ith cogeneration unit at the time t.
2. The heat storage device and the configuration method of the electricity storage device according to claim 1, wherein the constraint condition of the inner layer model includes:
the method comprises the steps of power balance constraint conditions, heat supply constraint conditions, wind power output constraint conditions, unit heat output upper and lower limit constraint conditions, unit climbing rate constraint conditions, cogeneration unit output upper and lower limit constraint conditions, heat storage and release power constraint conditions, heat storage device capacity constraint conditions, electricity storage device capacity constraint conditions, periodic heat storage constraint conditions and periodic electricity storage capacity constraint conditions.
3. The method for configuring a heat storage device and an electric storage device according to claim 2, wherein the specific step of converting the inner layer model into the additional condition of the outer layer model in the double layer planning model according to the KKT condition of the inner layer model in the double layer planning model comprises:
constructing an inner layer optimized Lagrangian function according to the equality constraint and the inequality constraint in the constraint condition of the inner layer model;
and converting the inner layer model into additional conditions of the outer layer model in the double-layer planning model according to the Lagrange function of the inner layer optimization.
4. A heat storage device and a configuration device of a power storage device, characterized by comprising:
the parameter acquisition module is used for acquiring unit parameters of each thermal power plant and thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage device and the electricity storage device;
the configuration acquisition module is used for acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to unit parameters of each thermal power plant and the thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage and electricity storage device, and comprises the following steps:
establishing a double-layer planning model according to unit parameters of each thermal power plant and thermal power plant in the electric power system, energy and load prediction results of the electric power system and cost parameters of the heat storage device and the electricity storage device;
acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to the double-layer planning model;
the obtaining the configuration capacity and the configuration power of the heat storage device and the electricity storage device according to the double-layer planning model comprises the following steps:
converting the inner layer model into additional conditions of the outer layer model in the double-layer planning model according to KKT conditions of the inner layer model in the double-layer planning model;
acquiring configuration capacity and configuration power of the heat storage device and the electricity storage device according to a mixed integer linear programming method and additional conditions of the outer layer model and the outer layer model;
the objective function of the outer layer model is
F＝C s +C h +C qf +C y
Wherein C is s Representing an initial investment cost of the electricity storage device; c (C) h Representing an initial investment cost of the heat storage device; c (C) qf Representing the wind abandoning punishment cost; c (C) y Representing the running cost of the power system;
the objective function of the inner layer model is
C y ＝∑C c (i,t)+∑C e (i,t)
Wherein C is c (i, t) represents the cost corresponding to the coal consumed by the ith thermal power generating unit at the time t; c (C) e And (i, t) represents the cost corresponding to the coal consumed by the ith cogeneration unit at the time t.
5. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method for configuring a heat storage device and an electric storage device according to any one of claims 1 to 2 when the program is executed.
6. A non-transitory computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, realizes the steps of the configuration method of the heat storage device and the electricity storage device according to any one of claims 1 to 2.
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