Integrated energy system scheduling method and integrated energy system scheduling device

Abstract

To provide an integrated energy system scheduling method and device.SOLUTION: A method implements comparably strong optimality by sufficiently achieving flexibility of a system and reducing influence of a prediction error by constructing an integrated energy system model and element simplification model and roughly optimizing the flexibility of the system using renewable energy prediction data, providing a constraint condition on the basis of a flexibility optimization result of the system, and, finally, effectively combining an advance plan with real-time scheduling by implementing the real-time scheduling by considering operation costs on the power generation heating side and using real-time data on renewable energy.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to the technical field of power planning, and in particular to a scheduling method for an integrated energy system and a scheduling device for an integrated energy system. [Background technology]

[0002] The excessive use of fossil fuels has led to climate change and serious environmental problems. In order to reduce carbon emissions, renewable energy has been applied in large quantities in the construction of new power systems in recent years. Among them, the integrated energy system mainly based on renewable energy is considered to be a very promising development framework due to its multi-energy coupling characteristics and efficient energy utilization rate, and can be widely applied in industrial parks and urban systems. In the integrated energy system, electricity and heat are the two main energy carriers on the demand side. Renewable energy and auxiliary cogeneration units on the power generation and heat side can provide clean and efficient electric energy and thermal energy. Meanwhile, battery energy storage and thermal storage equipment can provide additional flexibility to the system to respond to the uncertainty of renewable energy output and ensure the real-time power balance of electric energy and thermal energy.

[0003] Online scheduling methods for integrated energy systems are a research area that has attracted widespread attention. Existing studies can be mainly divided into three types based on the uncertainty modeling methods.

[0004] The first type of research is from the perspective of pre-planning, and mainly adopts two-stage optimization methods, such as random optimization, robust optimization and distributional robust optimization. Random optimization is to model uncertainty through sampling scenarios and minimize the expected cost. Robust optimization is to optimize the worst-case cost in a predetermined uncertain set. Distributional robust optimization assumes that the probability distribution of uncertainty is inaccurate, that is, optimizes the cost in the most unfavorable probability distribution, and integrates the advantages of random optimization and robust optimization methods. However, the two-stage optimization model assumes that real-time scheduling is performed after all uncertain parameters are observed, but in reality, the uncertainty is observed sequentially in time order, which is also called "non-anticipatory".

[0005] The second type of research uses dynamic programming frameworks to solve the problem of unpredictability. Dynamic programming methods can be used to formulate real-time decisions based on the currently observed uncertainties and Bellman optimality principles, and reinforcement learning is a typical representative. However, the real-time cost function to train dynamic programming requires a large amount of data, and the convergence guarantee and interpretability of the algorithm are also issues that need to be studied.

[0006] The third type of research is online scheduling with explicit or implicit policies. Explicit policies enforce an affine relationship between real-time scheduling values ​​and uncertainty parameters, but the optimality is poor. Implicit policies specify upper and lower bounds on real-time scheduling variables through the form of constraints, which improves the optimality compared to explicit policies, but there is no mature technical framework yet.

[0007] Moreover, none of the above three types of research combines advance planning with real-time scheduling, nor do they take into account possible errors in advance prediction, which poses great difficulties in the practical application of integrated energy systems.

[0008] Model predictive control (MPC) is a widely used method for online scheduling of integrated energy systems. This method adopts a rolling optimization framework, that is, at every time point, through short-term prediction of future uncertainties, a certainty optimization problem is solved within the present and future short-term time period to obtain the current pre-optimal decision. In real-time operation, the operation state of each element is adjusted based on the true renewable energy output.

[0009] The rolling optimization problem solved by the MPC method can take into account the cooperative relationships between more elements, and has great advantages in the real-time scheduling of integrated energy systems including the combination of multi-energy. In addition, since it adopts prediction and real-time adjustment, its operation is economical and optimal. However, this method has high requirements for the accuracy of prediction, and in systems with a high proportion of renewable energy, the prediction error is always large, which greatly affects the calculation results of MPC. In addition, the prediction of renewable energy is usually short-term. This leads to the short-sightedness of the rolling optimization, insufficient scheduling of energy storage, and difficulty in handling deferrable loads in the system.

[0010] In light of the above, a scheduling method for integrated energy systems is needed that can effectively combine advance planning and real-time scheduling, fully utilize the flexibility of the system, reduce the impact of prediction errors, and achieve stronger optimality. [Prior art documents] [Patent documents]

[0011] [Patent Document 1] Chinese Patent No. 104616208 Summary of the Invention [Problem to be solved by the invention]

[0012] At least one embodiment of the present invention provides a method and apparatus for scheduling an integrated energy system that effectively combines pre-planning and real-time scheduling to fully utilize the system flexibility, reduce the impact of prediction errors, and achieve stronger optimality. [Means for solving the problem]

[0013] According to an aspect of the present invention, in at least one embodiment, there is provided a scheduling method for an integrated energy system, including: building an element power model for an element of the integrated energy system; building a system model of the integrated energy system based on the element power model and the power of a renewable energy node; where the element includes one or more of a heat generating element, a power generating element, a heat generating and power generating element, an energy storage element, a heat storage element, and a load; and the load includes at least one of a fixed thermal load, a fixed electrical load, and a deferable electrical load. Optimizing flexibility of the integrated energy system using the system model and renewable energy node forecast data to obtain a flexibility optimization result; determining a feasibility constraint of the integrated energy system based on the flexibility optimization result; setting the feasibility constraint of the integrated energy system as a constraint, setting the operation cost of the integrated energy system as an optimization target, and using real-time data of a renewable energy node to realize real-time scheduling of the integrated energy system.

[0014] Optionally, constructing element power models for elements of the integrated energy system includes one or more of: constructing a heat generation model based on heat generation power for the heat generation element; constructing a power generation model based on power generation power for the power generation element; constructing a power generation model based on power generation power and a heat generation model based on heat generation power for the heat generation and power generation elements; constructing an electric energy model based on charge and discharge power for the energy storage element; constructing a thermal energy model based on thermal storage and release power for the heat storage element; constructing an electric load model based on fixed electric power for the fixed electric load; constructing a total electrical quantity relaxation model based on deferable electric power for the deferable electric load; and constructing a thermal load model based on fixed thermal power for the fixed thermal load.

[0015] Optionally, constructing a system model of the integrated energy system based on the element power model and the power of a renewable energy node includes constructing a real-time power balance model of electric energy of the integrated energy system based on the power of a renewable energy node and the electric power of elements present in the integrated energy system, and constructing a real-time power balance model of thermal energy of the integrated energy system based on the thermal power of elements present in the integrated energy system, where the electric power includes power generation power of a power generation element, power generation power of a heat generation and power generation element, charging and discharging power of an energy storage element, fixed electric power of a fixed electric load, and delayable electric power of a delayable electric load, and the thermal power includes heat generation power of a heat generation element, heat generation power of a heat generation and power generation element, thermal storage and release power of a thermal storage element, and fixed thermal power of a fixed thermal load.

[0016] Optionally, optimizing the flexibility of the integrated energy system utilizing the system model and renewable energy node forecast data to obtain a system flexibility optimization result includes expressing a power of a renewable energy node as a function of an electric power of an element of the integrated energy system based on a real-time power balance model of electric energy of the integrated energy system; quantitatively characterizing the flexibility of the integrated energy system in each time period as a difference between an upper and lower power limit of renewable energy power in the time period; and characterizing the flexibility of the integrated energy system in a plurality of time periods based on the upper and lower flexibility limits of the integrated energy system in each time period. and performing an optimization calculation based on the first objective function to obtain a system flexibility optimization result, wherein the constraint conditions of the first objective function include that the upper and lower limits of the output power of each element of the integrated energy system in each time period satisfy the element power model corresponding to the element, that the upper and lower limits of the flexibility of the integrated energy system in each time period correspond to the upper and lower limits of the output of the element of the integrated energy system in the time period, respectively, a relative constraint condition of renewable energy, and a relative condition of feasibility.

[0017] Optionally, the relative constraints for the renewable energy include an upper limit of the flexibility of the integrated energy system in each time period that is greater than or equal to the product of a first coefficient and the power of the renewable energy node in that time period and less than or equal to the power of a second renewable energy node in that time period, and a lower limit of the flexibility of the integrated energy system in each time period that is greater than or equal to 0 and less than or equal to the product of a second coefficient and the power of the renewable energy node in that time period, both of which are predetermined positive numbers greater than 0 and less than 1.

[0018] Optionally, the relative conditions of feasibility include an upper limit of flexibility of the integrated energy system in each time period being greater than or equal to a lower limit of flexibility of the integrated energy system in that time period, and an upper limit of output of an element of the integrated energy system in each time period being greater than or equal to a lower limit of output of that element in that time period.

[0019] Optionally, determining a feasibility constraint of the integrated energy system based on the flexibility optimization result includes obtaining upper and lower limits of output of elements of the integrated energy system in each time period based on the flexibility optimization result; determining upper and lower power limits of electric energy supply and upper and lower power limits of thermal energy supply of the integrated energy system based on the upper and lower limits of output of elements of the integrated energy system in each time period; setting a feasibility constraint of electric energy supply based on the upper and lower power limits of electric energy supply of the integrated energy system including actual usage power of renewable energy nodes operating in real time in the current time period, electricity purchased from the power grid in the current time period, and power generation power of each element operating in real time in the current time period; and setting a feasibility constraint of thermal energy supply based on the upper and lower power limits of thermal energy supply of the integrated energy system including heat generation power of each element operating in real time in the current time period.

[0020] Optionally, realizing real-time scheduling of the integrated energy system by using real-time data of a renewable energy node with a feasibility constraint of the integrated energy system as a constraint, and an operating cost of the integrated energy system as an optimization target includes: constructing a second objective function of the operating cost of the power generation / heat generation side of the integrated energy system based on the operating cost of each element in the current time period and the electricity purchasing cost of the electricity grid; optimizing a scheduling policy with the objective of minimizing the second objective function, and obtaining a scheduling policy of the power generation / heat generation side; and determining scheduling policies of the energy storage element, the heat storage element, and the load based on the scheduling policy of the power generation / heat generation side.

[0021] Optionally, the constraints of the second objective function include at least one of the following: a feasibility constraint of the integrated energy system; the heat generation power of the heat generation element satisfies a heat generation model of the heat generation element; the power generation power of the power generation element satisfies a power generation model of the power generation element; the heat generation power of the heat generation and power generation elements satisfies the heat generation model of the heat generation and power generation elements and the power generation power of the heat generation and power generation elements satisfies the power generation model of the heat generation and power generation elements; the power purchased from the electricity grid is greater than or equal to 0; and the actual utilization power of the renewable energy node in the current time period is greater than or equal to 0 and less than or equal to the output power of the renewable energy node observed in the current time period.

[0022] According to another aspect of the present invention, in at least one embodiment, a scheduling device for an integrated energy system is provided, the scheduling device including: a first construction module constructs an element power model for an element of the integrated energy system, and constructs a system model of the integrated energy system based on the element power model and the power of a renewable energy node; wherein the element includes one or more of a heat generating element, a power generating element, a heat generating and power generating element, an energy storage element, a heat storage element, and a load; and the load includes at least one of a fixed heat load, a fixed electric load, and a deferable electric load. A first optimization module optimizes the flexibility of the integrated energy system using the system model and renewable energy node forecast data to obtain a flexibility optimization result. A first determination module determines a feasibility constraint of the integrated energy system based on the flexibility optimization result. A scheduling module uses the feasibility constraint of the integrated energy system as a constraint, an operation cost of the integrated energy system as an optimization target, and uses real-time data of a renewable energy node to realize real-time scheduling of the integrated energy system.

[0023] Optionally, constructing element power models for elements of the integrated energy system by the first construction module includes one or more of: constructing a heat generation model based on heat generation power for the heat generation element; constructing a power generation model based on power generation power for the power generation element; constructing a power generation model based on power generation power and a heat generation model based on heat generation power for the heat generation and power generation elements; constructing an electric energy model based on charge and discharge power for the energy storage element; constructing a thermal energy model based on thermal storage and release power for the heat storage element; constructing an electric load model based on fixed electric power for the fixed electric load; constructing a total electrical quantity relaxation model based on deferable electric power for the deferable electric load; and constructing a thermal load model based on fixed thermal power for the fixed thermal load.

[0024] Optionally, the first construction module is further used for constructing a real-time power balance model of electric energy of the integrated energy system based on the power of a renewable energy node and the electric power of an element present in the integrated energy system, and constructing a real-time power balance model of thermal energy of the integrated energy system based on the thermal power of an element present in the integrated energy system, where the electric power includes the power generation power of a power generation element, the power generation power of a heat generation and power generation element, the charging and discharging power of an energy storage element, the fixed electric power of a fixed electric load, and the delayable electric power of a delayable electric load, and the thermal power includes the heat generation power of a heat generation element, the heat generation power of a heat generation and power generation element, the heat storage and release power of a heat storage element, and the fixed thermal power of a fixed thermal load.

[0025] Optionally, the first optimization module is further used for: expressing the power of a renewable energy node as a function of the electric power of an element of the integrated energy system based on a real-time power balance model of electric energy of the integrated energy system; quantitatively characterizing the flexibility of the integrated energy system in each time slot as a difference between upper and lower power limits of renewable energy power in the time slot; constructing a first objective function of the flexibility of the integrated energy system in multiple time slots based on the upper and lower flexibility limits of the integrated energy system in each time slot, the first objective function aiming at the flexibility being as large as possible and evenly distributed in the multiple time slots; and performing an optimization calculation based on the first objective function to obtain a system flexibility optimization result, where the constraint conditions of the first objective function include: the upper and lower limits of the output power of each element of the integrated energy system in each time slot both satisfy the element power model corresponding to the element; the upper and lower limits of the flexibility of the integrated energy system in each time slot correspond to the upper and lower limits of the output of the element of the integrated energy system in the time slot, respectively; a relative constraint condition of renewable energy; and a relative condition of feasibility.

[0026] Optionally, the first determination module is further used for: obtaining upper and lower limits of output of elements of the integrated energy system in each time period based on the flexibility optimization result; determining upper and lower power limits of electric energy supply and upper and lower power limits of thermal energy supply of the integrated energy system based on the upper and lower output limits of elements of the integrated energy system in each time period; setting feasibility constraints for electric energy supply based on the upper and lower power limits of the electric energy supply of the integrated energy system, including the actual usage power of renewable energy nodes operating in real time in the current time period, the electricity purchased from the power grid in the current time period, and the power generation power of each element operating in real time in the current time period; and setting feasibility constraints for thermal energy supply based on the upper and lower power limits of the thermal energy supply of the integrated energy system, including the heat generation power of each element operating in real time in the current time period.

[0027] Optionally, the scheduling module is further used to construct a second objective function of the power generation / heating side operating cost of the integrated energy system based on the operating cost of each element in the current time period and the electricity purchasing cost of the power grid; optimize a scheduling policy with the goal of minimizing the second objective function, using the power generation and heat generation power of each element in the current time period, the electricity purchased from the power grid, and the true utilization power of the renewable energy node as power generation / heating side decision variables, and obtain a scheduling policy for the power generation / heating side; and determine scheduling policies for the energy storage element, the heat storage element, and the load based on the scheduling policy for the power generation / heating side.

[0028] According to another aspect of the invention, in at least one embodiment, there is provided a computer readable storage medium having stored thereon a program which, when executed by a processor, causes the steps of the above method to be implemented. Effect of the Invention

[0029] Compared with the prior art, the integrated energy system scheduling method and apparatus provided in the embodiments of the present invention constructs an integrated energy system model and an element simplified model, roughly optimizes the system flexibility using renewable energy forecast data, provides feasibility constraints based on the system flexibility optimization result, and finally takes into account the operating costs of the power generation and heat generation side and realizes real-time scheduling using real-time data of renewable energy, thereby effectively combining pre-planning and real-time scheduling, fully utilizing the flexibility of the system, reducing the impact of forecast errors, and achieving relatively strong optimality.

[0030] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of the preferred embodiments. The drawings are used only to illustrate the preferred embodiments and are not to be considered as limitations on the present invention. Also, like parts are designated by like reference numerals throughout the drawings. [Brief description of the drawings]

[0031] [Figure 1] 1 is a schematic diagram of an integrated energy system to which embodiments of the present invention can be applied. [Diagram 2] 2 is a flowchart of a scheduling method for an integrated energy system according to an embodiment of the present invention. [Diagram 3] FIG. 13 is a diagram showing an example of a result of optimization of system flexibility in an embodiment of the present invention. [Figure 4] FIG. 11 is a diagram showing an example of upper and lower limits of charging power of an energy storage element in an embodiment of the present invention. [Diagram 5] FIG. 11 is a diagram showing an example of upper and lower limits of charging power for heat storage in an embodiment of the present invention. [Figure 6] FIG. 4 is a diagram showing an example of upper and lower limits of the output of a cogeneration unit in an embodiment of the present invention. [Figure 7] FIG. 11 is a diagram showing an example of upper and lower limits of a boiler output in an embodiment of the present invention. [Figure 8]11A and 11B are diagrams illustrating examples of upper and lower limits of output of a delayable load in an embodiment of the present invention. [Figure 9] FIG. 13 is a diagram showing an example of upper and lower bounds of feasibility constraints of an electric energy supplying node in an embodiment of the present invention. [Figure 10] FIG. 13 is a diagram illustrating an example of upper and lower bounds of feasibility constraints on a thermal energy supplying node in an embodiment of the present invention. [Figure 11] FIG. 13 is a diagram illustrating an example of upper and lower bounds of feasibility constraints for an electric energy supplying node in an embodiment of the present invention. [Figure 12] FIG. 13 is a diagram showing an example of upper and lower limits of feasibility constraints for a thermal energy supplying node in an embodiment of the present invention. [Figure 13] FIG. 1 is a diagram showing an example of a real-time utilization status of renewable energy in an embodiment of the present invention. [Figure 14] FIG. 11 is a diagram showing another example of a real-time scheduling result of the integrated energy system in an embodiment of the present invention. [Figure 15] FIG. 2 is a diagram illustrating an example of a scheduling device for an integrated energy system according to an embodiment of the present invention. [Figure 16] FIG. 2 is another schematic diagram of a scheduling device for an integrated energy system according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0032] Hereinafter, exemplary embodiments of the present invention will be described in more detail with reference to the accompanying drawings. Although the accompanying drawings show exemplary embodiments of the present invention, it should be understood that the present invention can be realized in various forms without being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more complete understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0033] It should be understood that the references throughout the specification to "one embodiment" or "an embodiment" mean that a particular feature, structure, or characteristic associated with the embodiment is included in at least one embodiment of the invention. Thus, the appearances of "in one embodiment" or "in one embodiment" in various places throughout the specification do not necessarily refer to the same embodiment. Moreover, these particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. The terms "first," "second," and the like in the present specification and claims are intended to distinguish between similar objects and are not used to describe a particular order or priority. It should be understood that the data used in this manner may be interchanged where appropriate such that the embodiments of the invention described herein may be practiced, for example, in an order other than that shown or described herein. Moreover, the terms "comprise" and "have" and all variations thereof are intended to be non-exclusive. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units expressly recited, but may include other steps or units not expressly recited or that are inherent to the process, method, product, or apparatus. In the specification and claims, "and / or" refers to at least one of the connected objects. In this specification, an upper bound and an upper limit have the same meaning and both refer to the maximum value that a parameter may take within a time period. Similarly, a lower bound and a lower limit have the same meaning and both refer to the minimum value that a parameter may take within a time period.

[0034] In various embodiments of the present invention, the magnitude of the numbers of the following processes does not mean the order of execution. The order of execution of each process should be determined based on its function and inherent logic, and does not limit the implementation process of the embodiments of the present invention.

[0035] The following description provides examples rather than limitations on the scope, applicability, or configuration of the claimed invention. Changes may be made in the function and arrangement of the elements discussed without departing from the spirit and scope of the present disclosure. In various examples, various provisions or components may be omitted, substituted, or added as appropriate. For example, the methods described may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to some examples may be combined in other examples.

[0036] The application scenario of the embodiment of the present invention is a method for pre-planning and real-time scheduling of an integrated energy system, which maximizes the flexibility of the system through pre-fuzzy prediction, provides feasibility constraints, and realizes real-time scheduling of the system by comprehensively considering the operation costs of the power generation and heat generation side. The content of the embodiment of the present invention is a method for pre-planning and real-time scheduling of an integrated energy system based on flexibility. The method specifically includes: building an integrated energy system model and an element simplified model; using renewable energy prediction data to roughly optimize the flexibility of the system; providing feasibility constraint conditions based on the optimization result of the system flexibility; considering the operation costs of the power generation and heat generation side, using renewable energy real-time data to realize real-time scheduling, and providing feasibility proof for real-time scheduling.

[0037] FIG. 1 provides a schematic diagram of an integrated energy system to which the embodiment of the present invention can be applied, which mainly includes a cogeneration unit, a boiler, an energy storage element (e.g., a battery energy storage element), a heat storage element, and a load. Here, the load is divided into an electric load and a heat load. The electric load is further divided into a fixed load (fixed electric load) and a delayable load (deferrable electric load). In the embodiment of the present invention, the above components are called elements of the integrated energy system. In FIG. 1, the electric load, the battery energy storage, the power grid, the renewable energy, and the cogeneration unit are connected by power lines. The power grid, the renewable energy, and the cogeneration unit provide electric energy to the electric load and the energy storage element (e.g., a battery energy storage element) through the power lines, and the energy storage element (e.g., a battery energy storage element) can also provide electric energy to the electric load. The cogeneration unit, the boiler, the heat storage element, and the heat load are connected by thermal paths. The cogeneration unit, the boiler, and the heat storage element provide heat energy to the heat load through thermal paths.

[0038] Referring to Fig. 2, the scheduling method for an integrated energy system provided in an embodiment of the present invention includes: in step 21, construct an element power model for an element of the integrated energy system, and construct a system model of the integrated energy system according to the element power model and the power of a renewable energy node, where the element includes one or more of a heat generating element, a power generating element, a heat generating and power generating element, an energy storage element, a heat storage element, and a load, and the load includes at least one of a fixed heat load, a fixed electric load, and a delayable electric load.

[0039] The elements include cogeneration units, boilers, energy storage elements, thermal storage elements, and loads, the loads including fixed thermal loads, fixed electrical loads, and delayable electrical loads.

[0040] Here, the heat generating element is an element that generates heat energy by itself and provides heat energy to a load in the integrated energy system, such as a boiler. The power generating element is an element that generates electric energy by itself and provides electric energy to a load in the integrated energy system, such as a diesel engine. The heat generating and power generating element is an element that can simultaneously generate heat energy and electric energy and provide heat energy and electric energy to a load in the integrated energy system, such as a cogeneration unit. The embodiment of the present invention proposes an integrated energy system model and an element simplified model. This model takes into consideration the models of various cogeneration units, boilers, energy storage elements, heat storage elements and loads in the integrated energy system in an integrated manner, and also proposes a relaxation model for delayable electric loads.

[0041] Specifically, in step 21, constructing an element power model for an element of the integrated energy system specifically includes one or more of the following: constructing a heat generation model based on heat generation power for the heat generation element; constructing a power generation model based on power generation power for the power generation element; constructing a power generation model based on power generation power and a heat generation model based on heat generation power for the heat generation and power generation elements; constructing an electric energy model based on charge and discharge power for the energy storage element; constructing a thermal energy model based on thermal storage and release power for the heat storage element; constructing an electric load model based on fixed electric power for the fixed electric load; constructing a total electric quantity relaxation model based on deferable electric power for the delayable electric load; constructing a thermal load model based on fixed thermal power for the fixed thermal load.

[0042] Each will be explained below.

[0043] (0) Power generating element model. The power generating element generates electrical energy by burning fuel, etc. The model can be expressed as follows:

[0044]

number

[0045] In the above formula, hgen is the power generation power of the power generating element in the time period t, and H is the upper and lower limits (min, max) of the power generation power of the power generating element. (Formula 0) is a power generation model of the power generating element.

[0046] (1) Heat generation and power generation element model (e.g., cogeneration unit model). Heat and power generation elements (e.g., cogeneration) are facilities that use a heat engine or power plant to simultaneously generate electricity and thermal energy. In a typical power plant, the heat remaining from the power generation process is mainly released to the environment through a cooling tower or cooling water, but in a cogeneration plant, the heat can be recovered and used for residential, commercial, and industrial purposes. Heat and power generation elements (e.g., cogeneration) are generally divided into three types: gas turbine cogeneration units, internal combustion engine cogeneration units, and steam turbine cogeneration units. They can be broadly divided into two types based on their operating characteristics. The first type is a cogeneration unit consisting of a gas turbine engine and an internal combustion engine (e.g., gas turbine cogeneration unit and internal combustion engine cogeneration unit), and the power generation and heat generation of this type of unit can be expressed as a linear function.

[0047]

number

[0048] In the above (Equation 1) and (Equation 2), PcHp(t) and hcHp(t) are the generated power and generated power output of the heat generating and power generating elements (e.g., cogeneration units) in time period t, respectively. rHP is the electrical thermal coefficient ratio of the heat generating and power generating elements (e.g., cogeneration units). P are the upper and lower limits (min, max) of the generated power, respectively. T is the number of time periods. (Equation 1) is a power generation model of the first type of heat generating and power generating elements, and (Equation 2) is a heat generation model of the first type of heat generating and power generating elements.

[0049] The second type is a condensing unit (e.g. a steam turbine cogeneration unit) that mainly uses the residual heat after the steam turbine. The feasible operating domain is a polyhedron with several extreme points. The electrical power and heat output can be expressed as a convex combination of the extreme points.

[0050]

number

[0051]

number

[0052] In the above (Equation 3) and (Equation 4), P and H are the power generation and heat generation of the poles, respectively. The parameter Sk(t) has a sigma value of 1 and satisfies the condition 0≦Sk(t)≦1. k represents the number of poles. (Equation 3) is a power generation model of the second type of heat generation and power generation element, and (Equation 4) is a heat generation model of the second type of heat generation and power generation element.

[0053] For any heat generating and power generating element, the power generating and heat generating constraints are linear and time independent. The embodiment of the present invention is applicable to two types of unit models. The following takes the first type of cogeneration unit as an example.

[0054] (2) Heating element model (e.g. boiler model). A heat generating element (e.g. a boiler) generates heat by burning fuel or consuming electricity. Its model can be expressed as follows:

[0055]

number

[0056] In the above (Equation 5), hboil(t) is the heat generating power of the heat generating element in time period t. H is the upper and lower limits (min, max) of the heat generating power of the heat generating element. (Equation 5) is a heat generating model of the heat generating element.

[0057] (3) Energy storage element model. Energy storage Energy storage elements such as batteries are currently one of the most responsive energy storages. Battery stored energy can typically output several hours of electrical energy at full rated power. Battery energy storage can be used for short-term peak power and auxiliary services, such as providing operational storage and frequency control. Due to the high charging and discharging efficiency of battery energy storage, it can be considered ideal during real-time operation. Its model can be expressed as follows:

[0058]

number

[0059]

number

[0060]

number

[0061] In the above formulas, PB(t) is the charge / discharge power of the energy storage element in time period t, which can be positive or negative, corresponding to charging and discharging, respectively. EB(t) is the electrical energy of the energy storage element in time period t. PB(max) is the rated power of the energy storage element. EB represent the upper and lower capacity limits (min, max), respectively, of the energy storage element. σB is the self-discharge coefficient of the energy storage element. Δt is the length of time period t. (Equations 6) to (Equation 8) are electrical energy models of the energy storage element.

[0062] (4) Heat storage element model. Thermal storage is a technology that allows for the capture and storage of thermal energy (i.e. heat) for future use. Thermal energy is easier to store than electrical energy, so thermal storage can help balance power supply and demand in energy systems, and its operating principle is similar to that of battery stored energy. Similarly, thermal storage can be ideal, with high charging and discharging efficiency. The thermal storage model can be expressed as follows:

[0063]

number

[0064]

number

[0065]

number

[0066] In the above equations, hH(t) is the storage and release power of the heat storage element in time period t, which can be positive or negative, corresponding to thermal energy storage and thermal energy release, respectively. EH(t) is the thermal energy of the heat storage element in time period t. PH(max) is the rated power of the heat storage element. EH and are the upper and lower limits (min, max) of the thermal storage capacity, respectively. σH is the self-loss coefficient of the heat storage element. (Equations 9) to (Equation 11) are the thermal energy models of the heat storage element.

[0067] (5) Load model. Electricity loads in an integrated energy system can be broadly divided into two types: fixed loads and deferrable loads. Fixed loads, PL(t), are usually not affected by external conditions or user behavior changes and have fixed change characteristics, and their power can be modeled as a certainty load based on historical data. For example, motor loads, lighting loads, and industrial pump loads are typical fixed loads in a power system. Deferrable loads are electric loads that can be shifted without affecting the quality of service provided. The amount of electricity of such loads is usually fixed, but the power of each time period can be adjusted or shifted. Typical examples are electric water heaters and certain types of industrial machines. Shifting these loads to periods of low overall electricity demand can balance the electricity supply and demand of the energy system, increasing reliability and reducing costs. This process is also commonly called demand-side response. Deferrable loads are described as follows:

[0068]

number

[0069]

number

[0070] In the above formula, PD(t) is the power of the delayable load in time period t. The (min, max) of PD(t) are the upper and lower limits (min, max) of the power of the delayable load in the corresponding time period. PD is the total electric energy of the delayable load. rD is a relaxation coefficient, indicating that the upper limit of the total electric energy may be exceeded. This provides a relatively relaxed constraint here, since it is extremely difficult to strictly guarantee a constant electric energy in actual operation. (Equation 12) and (Equation 13) are the total electric energy relaxation models of the delayable electric load.

[0071] The fixed electrical load in the integrated energy system is denoted as PL(t). The heat load HL(t) in the integrated energy system is generally considered to be a fixed heat load, similar to the fixed electrical load PL(t) described above, and will not be described here.

[0072] (6) Integrated energy system model. In practical operation, an integrated energy system needs to guarantee a real-time power balance between electrical energy and thermal energy.

[0073] In an embodiment of the present invention, a real-time power balance model of electric energy of the integrated energy system is constructed based on the power of a renewable energy node and the electric power of elements present in the integrated energy system, where the electric power includes the power generation power of a power generation element, the power generation power of a heat generation and power generation element, the charging and discharging power of an energy storage element, the fixed electric power of a fixed electric load, and the delayable electric power of a delayable electric load. A real-time power balance model of thermal energy of the integrated energy system is constructed based on the thermal power of elements present in the integrated energy system, where the thermal power includes the heat generation power of a heat generation element, the heat generation power of a heat generation and power generation element, the heat storage and release power of a heat storage element, and the fixed thermal power of a fixed heat load.

[0074] In the following, the integrated energy system shown in Fig. 1 is mainly taken as an example for explanation. The integrated energy system shown in Fig. 1 does not include the power generation element described above, but does include a heat generation and power generation element, i.e., a cogeneration unit.

[0075] In an embodiment of the present invention, a real-time power balance model of electric energy of the integrated energy system is established according to the power of the renewable energy node, the power generated by the co-generator unit, the charging and discharging power of the energy storage element, the fixed electric power of the fixed electric load, and the delayable electric power of the delayable electric load, and a real-time power balance model of thermal energy of the integrated energy system is established according to the heat generation power of the co-generator unit, the heat generation power of the boiler, the heat storage and release power of the heat storage element, and the fixed thermal power of the fixed thermal load.

[0076]

number

[0077]

number

[0078] In the above formula, PR(t) is the renewable energy power in time period t. Formula 14 is a real-time power balance model of the electric energy of the integrated energy system, and Formula 15 is a real-time power balance model of the thermal energy of the integrated energy system.

[0079] In step 22, the system model and renewable energy node forecast data are used to optimize the flexibility of the integrated energy system, and a flexibility optimization result is obtained.

[0080] Here, in step 22, the embodiment of the present invention proposes a method for roughly optimizing the flexibility of the system using renewable energy node forecast data. For the rough renewable energy output forecast curve in advance, the method fully exploits the flexibility of the system and constructs a quadratic convex optimization problem to calculate the system's response capability to the uncertainty of the renewable energy output power. While maximizing the flexibility of the system, the flexibility of the system is uniformly distributed in each time period. The "relative constraint of renewable energy" in the optimization problem ensures that the response capability to the uncertainty of the renewable energy output power is distributed within the possible range of the renewable energy output, and the "relative condition of feasibility" in the optimization problem ensures the feasibility of the next real-time scheduling.

[0081] Specifically, based on a real-time power balance model of the electrical energy of the integrated energy system, the power of the renewable energy node is expressed as a function of the electrical power of the elements of the integrated energy system, where the integrated energy system is considered as a whole, and its uncertainty mainly comes from the renewable energy node. Based on the power balance, a power expression of the renewable energy node is obtained.

[0082]

number

[0083] The flexibility of the integrated energy system in each time period is quantitatively characterized as the difference between the upper and lower limits of renewable energy power in that time period. System flexibility is the ability to respond to uncertainties in the output power of renewable energy. In an embodiment of the present invention, it is desirable for the system flexibility to be as large as possible, so that it can respond to a wider range of fluctuations in renewable energy output. Meanwhile, since uncertainties exist in each time period, it is desirable for the system flexibility to be evenly distributed in each time period. Therefore, in an embodiment of the present invention, the flexibility of the system in each time period is quantitatively characterized as the difference between the upper and lower limits of the renewable energy power that can be handled, that is, the upper limit (up) of P0(t) minus the lower limit (low) of P0(t).

[0084] Similarly, during each time period, there are upper and lower limits on the output power of the elements in the system, which can be expressed as follows:

[0085]

number

[0086]

number

[0087] The flexibility of the system is composed of the flexibility of each element inside it, that is, the "upper limit" of the output of each element corresponds to the upper limit of the system flexibility, and the "lower limit" of the output of each element corresponds to the lower limit of the system flexibility, that is, as follows:

[0088]

number

[0089]

number

[0090]

number

[0091]

number

[0092] A first objective function of the flexibility of the integrated energy system in a plurality of time periods is constructed based on upper and lower limits of the flexibility of the integrated energy system in each time period. The first objective function aims to make the flexibility as large as possible and evenly distributed in the plurality of time periods. An optimization calculation is performed based on the first objective function to obtain a system flexibility optimization result. Here, constraint conditions of the first objective function include: The upper and lower limits of the output power of each element of the integrated energy system in each time period satisfy the element power model corresponding to the element. Xup and Xlow in (Equation 23) satisfy (Equation 1) to (Equation 13). The upper and lower limits of the flexibility of the integrated energy system in each time period correspond to the upper and lower limits of the output of the element of the integrated energy system in the time period. Xup and Xlow in the following (Equation 23) satisfy (Equation 19) to (Equation 22). Relative constraint condition of renewable energy. Corresponds to (d) in the following (Equation 23). Relative condition of feasibility. Specifically, includes that the upper limit of the flexibility of the integrated energy system in each time period is equal to or greater than the lower limit of the flexibility of the integrated energy system in the time period, and the upper limit of the output of the element of the integrated energy system in each time period is equal to or greater than the lower limit of the output of the element in the time period, and corresponds to (c) and (e) in the following (Equation 23).

[0093] In the embodiment of the present invention, it is desirable for the flexibility to be as large as possible and to be evenly distributed over each time period. Therefore, the optimization calculation of the system flexibility is shown as follows:

[0094]

number

[0095] In the above formula, ω is a very small positive number, a constant related to the system, and can be specifically set based on experience. This quadratic term can uniformly distribute the system flexibility optimization results as a variance. The arguments at this time are the upper and lower limits of the flexibility of the system and each element in each time period, that is, Xup and Xlow. In addition to satisfying the basic constraints of the elements (Equation 1) to (Equation 13) and the power balance (Equation 19) to (Equation 22), the optimization calculation must also satisfy the "relative constraints of renewable energy" and several "relative conditions of feasibility" to ensure feasibility during real-time scheduling, which will be proved later. Here, only the "relative constraints of renewable energy" will be explained.

[0096] In an embodiment of the present invention, the relative constraint conditions of the renewable energy include: an upper limit of the flexibility of the integrated energy system in each time period is equal to or greater than the product of a first coefficient α and the power of the renewable energy node in the time period, and equal to or less than the power of a second renewable energy node in the time period; and a lower limit of the flexibility of the integrated energy system in each time period is equal to or greater than 0, and equal to or less than the product of a second coefficient β and the power of the renewable energy node in the time period, where the first coefficient α and the second coefficient β are both positive numbers greater than 0 and less than 1. That is, as follows:

[0097]

number

[0098] In the above formula, α and β are predetermined coefficients, and PR(t) is the predicted value of the renewable energy output. This formula shows that the flexibility of the integrated energy system, that is, the ability to respond to the uncertainty of the renewable energy output power, should be distributed within the possible range of the renewable energy output. As shown in FIG. 3, the optimization result of the system flexibility is that the area between the curve on which P0LOW is located and the curve on which P0up is located is the range of the system flexibility. The area between the curve on which P0up is located and the straight line with the ordinate of 0 is the possible range of the renewable energy output, the upper limit of which is the predicted value of the sum of the renewable energy output, and the lower limit is 0. FIGS. 4 to 10 are diagrams showing an example of the calculation result of the upper and lower limits of the output of each element. Among them, Figure 4 shows the upper and lower limits of the charging power of an energy storage element (e.g., battery energy storage), Figure 5 shows the upper and lower limits of the charging power of a thermal storage element, Figure 6 shows the upper and lower limits of the cogeneration unit output, Figure 7 shows the upper and lower limits of the boiler output, Figure 8 shows the upper and lower limits of the output of a delayable electric load, Figure 9 shows the upper and lower limits of the feasibility constraint of an electric energy supplying node, and Figure 10 shows the upper and lower limits of the feasibility constraint of a thermal energy supplying node.

[0099] Through the above steps, the upper and lower limits of the flexibility of the integrated energy system in each time period, and the upper and lower limits of the output of the elements of the integrated energy system in that time period can be calculated.

[0100] In step 23, a feasibility constraint for the integrated energy system is determined based on the flexibility optimization result.

[0101] Here, in step 23, the embodiment of the present invention determines a feasibility constraint based on the system flexibility optimization result. The feasibility constraint constrains the upper and lower limits of the power of the electric energy and thermal energy supplying nodes, and corresponds to the limit of the flexibility range of the system. As long as the power of the electric energy and thermal energy supplying nodes is within the corresponding upper and lower limit range, it ensures that there is always a real-time scheduling policy that makes the system feasible. The electric energy supplying nodes include power grids, renewable energy nodes, cogeneration units, etc., and the thermal energy supplying nodes include cogeneration units, boilers, etc.

[0102] Specifically, in an embodiment of the present invention, the upper and lower power limits of the elements of the integrated energy system in each time period are obtained based on the flexibility optimization result, and then the upper and lower power limits of the electric energy supply and the upper and lower power limits of the thermal energy supply of the integrated energy system are determined based on the upper and lower power limits of the elements of the integrated energy system in each time period.

[0103] For example, by optimizing the flexibility of the system as described above, xup and xlow can be obtained, and the power upper and lower limits of the energy supplying node of the integrated energy system can be further calculated by xup and xlow. Here, the power upper and lower limits of the electric energy supplying node Pb(t) are as follows:

[0104]

number

[0105]

number

[0106] The power limits of the thermal energy supplying node are as follows:

[0107]

number

[0108]

number

[0109] Then, a feasibility constraint condition for electric energy supply is set based on upper and lower power limits of electric energy supply of the integrated energy system. Here, the electric energy supply of the integrated energy system includes an actual usage power of a renewable energy node operating in real time in a current time period, an electricity purchase power from an electric grid in a current time period, and a power generated by each element operating in real time in a current time period. Then, a feasibility constraint condition for electric energy supply is set based on upper and lower power limits of electric energy supply of the integrated energy system. Here, the thermal energy supply of the integrated energy system includes a heat generation power of a boiler operating in real time in a current time period, and a heat generation power of each element operating in real time in a current time period.

[0110] For example, the upper and lower limits of the electric energy and thermal energy supplying nodes obtained by the above flexibility optimization correspond to the limits of the system flexibility range. That is, as long as the power of the electric energy and thermal energy supplying nodes is within the corresponding upper and lower limit range, the system flexibility is allowed, and there is always a real-time scheduling policy to make the system feasible. This conclusion is proved as follows. Therefore, the feasibility constraints during real-time operation can be obtained.

[0111]

number

[0112]

number

[0113] The above (Equation 29) is the feasibility constraint for electric energy supply, and the above (Equation 30) is the feasibility constraint for thermal energy supply. In the above equations, Pr(t) is the true utilization power of renewable energy during real-time operation in time period t. Pgrid(t) is the power purchased from the power grid during time period t. PCHP(t) is the power generated by the cogeneration unit during real-time operation in time period t. hboil(t) is the heat generation power of the boiler during real-time operation in time period t. hCHP(t) is the heat generation power of the cogeneration unit during real-time operation in time period t. Figure 11 shows an example of the calculation result of the upper and lower limits of the feasibility constraint condition for an electric energy supply node, and Figure 12 shows an example of the calculation result of the upper and lower limits of the feasibility constraint condition for a thermal energy supply node.

[0114] In step 24, the feasibility constraint of the integrated energy system is taken as a constraint, the operation cost of the integrated energy system is taken as an optimization target, and real-time scheduling of the integrated energy system is realized by utilizing real-time data of renewable energy nodes.

[0115] Here, in step 24, the embodiment of the present invention realizes real-time scheduling using real-time data of renewable energy, taking into account the operation cost of the power generation and heat generation side. This real-time scheduling has good optimality, and its feasibility can be fully proven. The power generation and heat generation side includes nodes such as the power generation element, the heat and power generation element (e.g., cogeneration unit), heat generation element (e.g., boiler), and power grid.

[0116] Specifically, in an embodiment of the present invention, a second objective function of the operation cost of the power generation and heat generation side of the integrated energy system is constructed based on the operation cost of each element in the current time period and the electricity purchase cost of the power grid. For example, the second objective function of the operation cost of the power generation and heat generation side of the integrated energy system is constructed based on the operation cost of the cogeneration unit, the heat generation cost of the boiler, and the electricity purchase cost of the power grid in the current time period. Next, the above-mentioned operation cost of the power generation and heat generation side will be described.

[0117] The operating cost of a cogeneration unit CCHP(t) can be expressed as a quadratic function of the generated power.

[0118]

number

[0119] The boiler's heating cost Cboiler(t) is proportional to the fuel consumed, so the cost can be considered as a linear function of the heating power.

[0120]

number

[0121] The cost of purchasing electricity from the power grid, CGrid(t), is a linear function of the amount of electricity purchased.

[0122]

number

[0123] In the above formula, a, b, and c are the cost coefficients of the cogeneration unit, all of which are positive numbers. θ is the heat generation cost coefficient of the boiler. γ is the unit electricity price.

[0124] Then, the power generation and heat generation of each element in the current time slot, the power purchased from the power grid, and the true power usage of the renewable energy node are set as decision variables on the power generation and heat generation side, and a scheduling policy is optimized with the goal of minimizing the second objective function to obtain the scheduling policy on the power generation and heat generation side.For example, the power generation and heat generation of a cogeneration unit in the current time slot, the heat generation power of a boiler, the power purchased from the power grid, and the true power usage of the renewable energy node are set as decision variables on the power generation and heat generation side, and a scheduling policy is optimized with the goal of minimizing the second objective function to obtain the scheduling policy on the power generation and heat generation side.

[0125] Then, a scheduling policy for the energy storage element, the heat storage element, and the load is determined based on the scheduling policy for the power generation / heat generation side, where the constraint condition for the second objective function includes at least one of the following: Feasibility constraints for said integrated energy system. The heat generating power of the heat generating element satisfies a heat generating model of the heat generating element. The power generation power of the power generating element satisfies a power generation model of the power generating element. The heat generation power of the heat generation and power generation elements satisfies a heat generation model of the heat generation and power generation elements, and the power generation power of the heat generation and power generation elements satisfies a power generation model of the heat generation and power generation elements. Purchase electricity from the grid at least 0 power. The actual utilization power of the renewable energy node in the current time slot is greater than or equal to 0 and less than or equal to the observed output power of the renewable energy node in the current time slot.

[0126] For example, in real-time scheduling, we assume that there is no accurate prediction of future renewable energy output, and we simply solve the optimization problem of the power generation / heat generation side in the current time slot t. The decision variables for the power generation / heat generation side in this case are y(t)={PCHP(t),HCHP(t),HBoil(t),Pgrid(t),Pr(t)}.

[0127] This real-time scheduling optimization problem can be expressed as follows:

[0128]

number

[0129] In the above equation, PR(t) is the true output of renewable energy observed in time period t, and the actual utilization of renewable energy Pr(t) must be less than PR(t) and greater than or equal to 0. By solving (Equation 34), we can obtain the real-time scheduling policy y(t) on the power generation and heat generation side. Meanwhile, the energy storage and load side scheduling policy z(t)={PB(t),hH(t),PD(t)} can be given by the following method.

[0130]

number

[0131]

number

[0132]

number

[0133]

number

[0134]

number

[0135] Obviously, 0≦λ1(t)≦1, 0≦λ2(t)≦1. Below, we prove the feasibility of the scheduling policy. The decision variables on the power generation and heat generation side, y(t)={PCHP(t),HCHP(t),HBoil(t),Pgrid(t),Pr(t)}, naturally satisfy the system constraints and are therefore always feasible. Next, we only need to prove that z(t)={PB(t),hH(t),PD(t)} is always feasible. Taking battery energy storage as an example, (Equation 8) can be expressed in the following form:

[0136]

number

[0137] The upper and lower energy storage constraints (Equation 7) can be rearranged as follows:

[0138]

number

[0139] Since P(t)(up) and P(t)(low) naturally satisfy the constraints (equation 7), we have:

[0140]

number

[0141]

number

[0142] Furthermore, based on PB(t)(up)≧PB(t)(low) in the “relative condition for feasibility” of (equation 23) and (equation 37), the following equation is obtained.

[0143]

number

[0144] This proves Equation 41. Thermal storage has exactly the same form as battery energy storage, so we will omit the proof here.

[0145] For deferrable loads, the following equation can be obtained from the “relative condition for feasibility” in (equation 23), PD(t)(up) ≥ PD(t)(low), and (equation 39).

[0146]

number

[0147] (Equation 13) is clearly proven. This completely proves the feasibility of real-time scheduling of the system. The real-time scheduling results of the system are shown in Figures 13 and 14.

[0148] Referring to FIG. 15 , the configuration of the scheduling device of the integrated energy system provided in the embodiment of the present invention includes: The first construction module 1501 is used for constructing an element power model for an element of the integrated energy system, and constructing a system model of the integrated energy system according to the element power model and the power of a renewable energy node, where the element includes one or more of a heat generating element, a power generating element, a heat generating and power generating element, an energy storage element, a heat storage element, and a load, and the load includes at least one of a fixed heat load, a fixed electric load, and a delayable electric load. A first optimization module 1502 is used to utilize the system model and renewable energy node forecast data to optimize flexibility of the integrated energy system and obtain a flexibility optimization result. A first determination module 1503 is used for determining a feasibility constraint of the integrated energy system based on the flexibility optimization result. The scheduling module 1504 is used for realizing real-time scheduling of the integrated energy system using real-time data of renewable energy nodes, with the feasibility constraints of the integrated energy system as constraints and the operating cost of the integrated energy system as optimization targets.

[0149] According to the above modules, the embodiment of the present invention effectively combines pre-planning and real-time scheduling, fully utilizes the flexibility of the system, reduces the impact of prediction errors, and achieves stronger optimality.

[0150] Optionally, constructing element power models for elements of the integrated energy system by the first construction module includes one or more of: constructing a heat generation model based on heat generation power for the heat generation element; constructing a power generation model based on power generation power for the power generation element; constructing a power generation model based on power generation power and a heat generation model based on heat generation power for the heat generation and power generation elements; constructing an electric energy model based on charge and discharge power for the energy storage element; constructing a thermal energy model based on thermal storage and release power for the heat storage element; constructing an electric load model based on fixed electric power for the fixed electric load; constructing a total electrical quantity relaxation model based on deferable electric power for the deferable electric load; and constructing a thermal load model based on fixed thermal power for the fixed thermal load.

[0151] Optionally, the first construction module is further used for constructing a real-time power balance model of electric energy of the integrated energy system based on the power of a renewable energy node and the electric power of an element present in the integrated energy system, and constructing a real-time power balance model of thermal energy of the integrated energy system based on the thermal power of an element present in the integrated energy system, where the electric power includes the power generation power of a power generation element, the power generation power of a heat generation and power generation element, the charging and discharging power of an energy storage element, the fixed electric power of a fixed electric load, and the delayable electric power of a delayable electric load, and the thermal power includes the heat generation power of a heat generation element, the heat generation power of a heat generation and power generation element, the thermal storage and release power of a thermal storage element, and the fixed thermal power of a fixed thermal load.

[0152] Optionally, the first optimization module is further used for: expressing the power of a renewable energy node as a function of the electric power of an element of the integrated energy system based on a real-time power balance model of electric energy of the integrated energy system; quantitatively characterizing the flexibility of the integrated energy system in each time slot as a difference between upper and lower power limits of renewable energy power in the time slot; constructing a first objective function of the flexibility of the integrated energy system in multiple time slots based on the upper and lower flexibility limits of the integrated energy system in each time slot, the first objective function aiming at the flexibility being as large as possible and evenly distributed in the multiple time slots; and performing an optimization calculation based on the first objective function to obtain a system flexibility optimization result, where the constraint conditions of the first objective function include: the upper and lower limits of the output power of each element of the integrated energy system in each time slot both satisfy the element power model corresponding to the element; the upper and lower limits of the flexibility of the integrated energy system in each time slot correspond to the upper and lower limits of the output of the element of the integrated energy system in the time slot, respectively; a relative constraint condition of renewable energy; and a relative condition of feasibility.

[0153] Optionally, the relative constraints for the renewable energy include an upper limit of the flexibility of the integrated energy system in each time period that is greater than or equal to the product of a first coefficient and the power of the renewable energy node in that time period and less than or equal to the power of a second renewable energy node in that time period, and a lower limit of the flexibility of the integrated energy system in each time period that is greater than or equal to 0 and less than or equal to the product of a second coefficient and the power of the renewable energy node in that time period, both of which are predetermined positive numbers greater than 0 and less than 1.

[0154] Optionally, the relative conditions of feasibility include an upper limit of flexibility of the integrated energy system in each time period being greater than or equal to a lower limit of flexibility of the integrated energy system in that time period, and an upper limit of output of an element of the integrated energy system in each time period being greater than or equal to a lower limit of output of that element in that time period.

[0155] Optionally, the first determination module is further used for: obtaining upper and lower limits of output of elements of the integrated energy system in each time period based on the flexibility optimization result; determining upper and lower power limits of electric energy supply and upper and lower power limits of thermal energy supply of the integrated energy system based on the upper and lower output limits of elements of the integrated energy system in each time period; setting feasibility constraints for electric energy supply based on the upper and lower power limits of the electric energy supply of the integrated energy system, including the actual usage power of renewable energy nodes operating in real time in the current time period, the electricity purchased from the power grid in the current time period, and the power generation power of each element operating in real time in the current time period; and setting feasibility constraints for thermal energy supply based on the upper and lower power limits of the thermal energy supply of the integrated energy system, including the heat generation power of each element operating in real time in the current time period.

[0156] Optionally, the scheduling module is further used to construct a second objective function of the power generation / heating side operating cost of the integrated energy system based on the operating cost of each element in the current time period and the electricity purchasing cost of the power grid; optimize a scheduling policy with the goal of minimizing the second objective function, using the power generation and heat generation power of each element in the current time period, the electricity purchased from the power grid, and the true utilization power of the renewable energy node as power generation / heating side decision variables, and obtain a scheduling policy for the power generation / heating side; and determine scheduling policies for the energy storage element, the heat storage element, and the load based on the scheduling policy for the power generation / heating side.

[0157] Optionally, the constraints of the second objective function include at least one of the following: a feasibility constraint of the integrated energy system; the heat generation power of the heat generation element satisfies a heat generation model of the heat generation element; the power generation power of the power generation element satisfies a power generation model of the power generation element; the heat generation power of the heat generation and power generation elements satisfies the heat generation model of the heat generation and power generation elements and the power generation power of the heat generation and power generation elements satisfies the power generation model of the heat generation and power generation elements; the power purchased from the electricity grid is greater than or equal to 0; and the actual utilization power of the renewable energy node in the current time period is greater than or equal to 0 and less than or equal to the output power of the renewable energy node observed in the current time period.

[0158] It should be noted that each system provided in the above embodiments is an apparatus corresponding to the scheduling method for the integrated energy system, and the implementation forms in each of the above embodiments can be applied to the embodiments of the apparatus to obtain the same technical effects. The above apparatus provided in the embodiments of the present invention can realize all the method steps realized by the above method embodiments and can achieve the same technical effects, and the same parts and beneficial effects as those of the method embodiments in this embodiment will not be specifically described here.

[0159] 16, there is shown a schematic diagram of another integrated energy system scheduling device provided by an embodiment of the present invention. The device includes a processor 1601, a transceiver 1602, a memory 1603, a user interface 1604, and a bus interface.

[0160] In an embodiment of the present invention, the apparatus further includes a program stored in the memory 1603 and executable on the processor 1601 .

[0161] The transceiver 1602 is used to transmit and receive data under the control of the processor. The processor 1601 is used to read the computer program in the memory and perform the following operations: Element power models are constructed for elements of the integrated energy system, and a system model of the integrated energy system is constructed based on the element power models and the power of a renewable energy node, where the elements include one or more of a heat generating element, a power generating element, a heat generating and power generating element, an energy storage element, a heat storage element, and a load, and the load includes at least one of a fixed thermal load, a fixed electrical load, and a delayable electrical load. Utilizing the system model and renewable energy node forecast data, the flexibility of the integrated energy system is optimized to obtain a flexibility optimization result. A feasibility constraint for the integrated energy system is determined based on the flexibility optimization results. The feasibility constraint of the integrated energy system is taken as a constraint, the operation cost of the integrated energy system is taken as an optimization target, and real-time scheduling of the integrated energy system is realized by utilizing real-time data of renewable energy nodes.

[0162] It should be noted that in the embodiment of the present invention, when the computer program is executed by the processor 1601, each process of the embodiment of the scheduling method for the integrated energy system described above can be realized, and the same technical effect can be achieved, so to avoid duplication, it will not be described further here.

[0163] In FIG. 16, the bus architecture includes any number of interconnected buses and bridges, specifically connecting one or more processors, such as processor 1601, and various types of memory, such as memory 1603. The bus architecture may also connect various types of other circuits, such as peripheral equipment, regulators, power management circuits, etc., all of which are known in the art and will not be described further herein. The bus interface provides an interface. The transceiver 1602 may be multiple components, i.e., includes a transmitter and a receiver, and is provided as a unit to communicate with various types of other devices over a transmission medium. Depending on the user terminal, the user interface 1604 may be an interface for internal or external connected devices. The connected devices include, but are not limited to, a keypad, a display, a speaker, a microphone, a joystick, etc.

[0164] The processor 1601 manages the bus architecture and normal processing. The memory 1603 can store data used during operation by the processor 1601.

[0165] In addition, the device in this embodiment is a device corresponding to the scheduling method of the integrated energy system, and the implementation forms in each of the above embodiments can be applied to the embodiment of this device and can achieve the same technical effects. In this device, the transceiver 1602 and the memory 1603, and the transceiver 1602 and the processor 1601 can be communicatively connected via a bus interface, and the function of the processor 1601 can also be realized by the transceiver 1602, and the function of the transceiver 1602 can also be realized by the processor 1601. In addition, the above device provided in the embodiment of the present invention can realize all the method steps realized in the above-mentioned method embodiment and can achieve the same technical effects, and the same parts and beneficial effects as those in the method embodiment in this embodiment will not be specifically described here.

[0166] In some embodiments of the present invention, a computer readable storage medium is also provided having stored thereon a program that, when executed by a processor, performs the following steps: Element power models are constructed for elements of the integrated energy system, and a system model of the integrated energy system is constructed based on the element power models and the power of a renewable energy node, where the elements include one or more of a heat generating element, a power generating element, a heat generating and power generating element, an energy storage element, a heat storage element, and a load, and the load includes at least one of a fixed thermal load, a fixed electrical load, and a delayable electrical load. Utilizing the system model and renewable energy node forecast data, the flexibility of the integrated energy system is optimized to obtain a flexibility optimization result. A feasibility constraint for the integrated energy system is determined based on the flexibility optimization results. The feasibility constraint of the integrated energy system is taken as a constraint, the operation cost of the integrated energy system is taken as an optimization target, and real-time scheduling of the integrated energy system is realized by utilizing real-time data of renewable energy nodes.

[0167] This program, when executed by a processor, can realize all the implementation forms of the scheduling method for the integrated energy system described above and achieve the same technical effect, so in order to avoid duplication, it will not be described further here.

[0168] Those skilled in the art can understand that each example unit and algorithm step described in the embodiments disclosed herein can be realized by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software is determined by the specific application and design constraints of the technical means. Those skilled in the art can realize the described functions by different methods for each specific application, but these realizations should not be considered as going beyond the scope of the present disclosure.

[0169] For convenience and brevity, the specific operation processes of the above-described systems, devices and units are not described here repeatedly, and those are obvious to those skilled in the art, and should be referred to the corresponding processes in the method embodiments.

[0170] In some embodiments provided by the present invention, it is to be understood that the disclosed apparatus and method may be implemented in other ways. The above-described apparatus embodiments are merely exemplary. For example, the division of the described units is merely a division of logical functions, and there are other division ways in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not implemented. In addition, the coupling, direct coupling, or communication connection between each component shown or discussed may be an indirect coupling or communication connection via an interface, device, or unit, and may be electrical, mechanical, or other form.

[0171] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units, i.e., they may be located in one place or in multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the embodiments of the present disclosure.

[0172] Furthermore, each functional unit in each embodiment of the present disclosure may be integrated into a single processing unit, may be provided physically separately, or two or more may be integrated together.

[0173] The functions may be stored in a computer-readable storage medium when they are realized in the form of a software functional unit and sold or used as an independent product. Based on this understanding, the substantial or prior art contributions of the technical means of the present disclosure, or a part of the technical means, may appear in the form of a software product. The computer software product is stored in a storage medium and includes some instructions that cause a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to each embodiment of the present disclosure. The storage medium includes various media that can store program code, such as a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0174] The above description is a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or replacements that a person skilled in the art can easily think of within the technical scope disclosed by the present invention are included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims. [Explanation of symbols]

[0175] 1501...first construction module; 1502...first optimization module; 1503...first determination module; 1504...scheduling module; 1601: processor; 1602: transceiver; 1603: memory; 1604...User interface

Claims

1. 1. A method for scheduling an integrated energy system, comprising: Constructing an element power model for an element of the integrated energy system, the element power model including one or more of a load including at least one of a fixed thermal load, a fixed electrical load, and a delayable electrical load, a heat generating element, a power generating element, the heat generating element and the power generating element, an energy storage element, and a heat storage element, and constructing a system model of the integrated energy system based on the element power model and the power of a renewable energy node; Optimizing flexibility of the integrated energy system using the system model and renewable energy node forecast data to obtain a flexibility optimization result; determining a feasibility constraint for the integrated energy system based on the flexibility optimization results; and a feasibility constraint condition of the integrated energy system as a constraint condition, an operation cost of the integrated energy system as an optimization target, and realizing real-time scheduling of the integrated energy system by utilizing real-time data of the renewable energy node.

2. 2. The method of claim 1, further comprising the steps of: Constructing the element power models for the elements of the integrated energy system includes: A scheduling method for an integrated energy system, comprising one or more of: constructing a heat generation model based on heat generation power for the heat generation element; constructing a power generation model based on power generation power for the power generation element; constructing a power generation model based on power generation power and a heat generation model based on heat generation power for the heat generation element and the power generation element; constructing an electric energy model based on charge / discharge power for the energy storage element; constructing a thermal energy model based on heat storage / release power for the heat storage element; constructing an electric load model based on fixed electric power for the fixed electric load; constructing a total electric quantity relaxation model based on deferable electric power for the deferable electric load; and constructing a thermal load model based on fixed thermal power for the fixed thermal load.

3. 2. The method of claim 1, further comprising the steps of: Constructing the system model of the integrated energy system based on the element power model and the power of the renewable energy node, Building a real-time power balance model of the electrical energy of the integrated energy system based on the power of the renewable energy node and the electrical power of the elements present in the integrated energy system; building a real-time power balance model of thermal energy of the integrated energy system based on thermal powers of the elements present in the integrated energy system; Here, the electric power includes power generated by the power generating element, power generated by the heat generating element and the power generating element, charge / discharge power of the energy storage element, fixed electric power of the fixed electric load, and delayable electric power of the delayable electric load, A scheduling method for an integrated energy system, characterized in that the thermal power includes heat generation power of the heat generation element, heat generation power of the heat generation element and the power generation element, heat storage and release power of the heat storage element, and fixed thermal power of the fixed thermal load.

4. 4. The method for scheduling an integrated energy system according to claim 3, further comprising: Utilizing the system model and renewable energy node forecast data to optimize flexibility of the integrated energy system and obtain the flexibility optimization result of the system, expressing the power of the renewable energy node as a function of the electrical power of the elements of the integrated energy system based on a real-time power balance model of the electrical energy of the integrated energy system; Quantitatively characterizing the flexibility of the integrated energy system in each time period as a difference between an upper and lower renewable energy power limit in the corresponding time period; constructing a first target function of flexibility of the integrated energy system in a plurality of time periods based on upper and lower limits of flexibility of the integrated energy system in each of the time periods, the first target function having a goal of making flexibility as large as possible and uniformly distributed among the plurality of time periods; performing an optimization calculation based on the first objective function to obtain the flexibility optimization result of the system; Here, the constraint condition of the first objective function is The upper and lower limits of the output power of each element of the integrated energy system in each time period satisfy the element power model corresponding to the element; the upper and lower limits of the flexibility of the integrated energy system in each time period correspond to the upper and lower limits of the output of the elements of the integrated energy system in the corresponding time period; Relative constraints on renewable energy; and A method for scheduling an integrated energy system including a relative feasibility condition.

5. 5. The method for scheduling an integrated energy system according to claim 4, further comprising: The relative constraints on renewable energy are: an upper limit of the flexibility of the integrated energy system in each time period is equal to or greater than a product of a first coefficient and a power of the renewable energy node in that time period, and is equal to or less than a power of a second renewable energy node in that time period; A lower limit of the flexibility of the integrated energy system in each time period is greater than or equal to 0 and less than or equal to a product of a second coefficient and the power of the renewable energy node in the time period; A scheduling method for an integrated energy system, wherein the first coefficient and the second coefficient are both predetermined positive numbers greater than 0 and less than 1.

6. 5. The method for scheduling an integrated energy system according to claim 4, further comprising: The relative conditions for feasibility are: an upper limit of the flexibility of the integrated energy system in each time period is equal to or greater than a lower limit of the flexibility of the integrated energy system in the corresponding time period; A scheduling method for an integrated energy system, comprising: an upper limit of output of the element of the integrated energy system in each time period being equal to or greater than a lower limit of output of the element in that time period.

7. 2. The method of claim 1, further comprising the steps of: Determining feasibility constraints for the integrated energy system based on the flexibility optimization results, Obtaining upper and lower limits of the output of the elements of the integrated energy system in each time period based on the flexibility optimization result; determining upper and lower power limits for an electric energy supply and upper and lower power limits for a thermal energy supply of the integrated energy system based on the upper and lower limits of the output of the elements of the integrated energy system in each time period; Setting a feasibility constraint condition for electric energy supply based on upper and lower power limits of electric energy supply of the integrated energy system, including an actual usage power of the renewable energy node operating in real time in the current time period, an electric power purchased from the electric grid in the current time period, and a power generation power of each element operating in real time in the current time period; A scheduling method for an integrated energy system, comprising setting feasibility constraints for thermal energy supply based on upper and lower power limits for thermal energy supply of the integrated energy system, including the heat generation power of each element operating in real time during the current time period.

8. 2. The method of claim 1, further comprising the steps of: The feasibility constraint of the integrated energy system is a constraint, the operation cost of the integrated energy system is an optimization target, and real-time scheduling of the integrated energy system is realized by using real-time data of the renewable energy node. Building a second target function of the operating cost of the power generation and heat generation side of the integrated energy system according to the operating cost of each element in the current time period and the electricity purchase cost of the power grid; The power generation and heat generation of each element in the current time period, the power purchased from the power grid, and the true utilization power of the renewable energy node are set as decision variables on the power generation and heat generation side, and a scheduling policy is optimized with the goal of minimizing the second objective function to obtain a scheduling policy on the power generation and heat generation side; A scheduling method for an integrated energy system, comprising determining scheduling policies for the energy storage element, the heat storage element, and the load based on a scheduling policy for the power generation / heat generation side.

9. 9. The method for scheduling an integrated energy system according to claim 8, further comprising: The constraint condition of the second objective function is feasibility constraints for said integrated energy system; The heat generation power of the heat generation element satisfies a heat generation model of the heat generation element; the power generation power of the power generation element satisfies a power generation model of the power generation element; a heat generation power of the heat generating element and the power generating element satisfies a heat generation model of the heat generating element and the power generating element, and a power generation power of the heat generating element and the power generating element satisfies a power generation model of the heat generating element and the power generating element; The power purchased from the electricity grid is equal to or greater than 0; The scheduling method for an integrated energy system, comprising at least one of: an actual utilization power of the renewable energy node in the current time period being greater than or equal to 0 and less than or equal to an output power of the renewable energy node observed in the current time period.

10. A scheduling device for an integrated energy system, comprising: A first construction module for constructing an element power model for an element of the integrated energy system, the element power model including one or more of a load including at least one of a fixed thermal load, a fixed electric load, and a delayable electric load, a heat generating element, a power generating element, the heat generating element and the power generating element, an energy storage element, and a heat storage element, and constructing a system model of the integrated energy system based on the element power model and the power of a renewable energy node; a first optimization module for optimizing flexibility of the integrated energy system using the system model and renewable energy node forecast data to obtain a flexibility optimization result; a first determination module for determining a feasibility constraint of the integrated energy system based on the flexibility optimization result; and a scheduling module for setting a feasibility constraint condition of the integrated energy system as a constraint condition, setting an operation cost of the integrated energy system as an optimization target, and real-time scheduling of the integrated energy system by utilizing real-time data of the renewable energy node.

11. The scheduling device for an integrated energy system according to claim 10, constructing, by the first construction module, the element power models for the elements of the integrated energy system, A scheduling device for an integrated energy system comprising one or more of: constructing a heat generation model based on heat generation power for the heat generation element; constructing a power generation model based on power generation power for the power generation element; constructing a power generation model based on power generation power and a heat generation model based on heat generation power for the heat generation element and the power generation element; constructing an electric energy model based on charge / discharge power for the energy storage element; constructing a thermal energy model based on heat storage / release power for the heat storage element; constructing an electric load model based on fixed electric power for the fixed electric load; constructing a total electric quantity relaxation model based on delayable electric power for the delayable electric load; and constructing a thermal load model based on fixed thermal power for the fixed thermal load.

12. The scheduling device for an integrated energy system according to claim 10, The first construction module further comprises: Building a real-time power balance model of the electrical energy of the integrated energy system based on the power of the renewable energy node and the electrical power of the elements present in the integrated energy system; Based on the thermal power of the elements present in the integrated energy system, a real-time power balance model of the thermal energy of the integrated energy system is constructed; Here, the electric power includes power generated by the power generating element, power generated by the heat generating element and the power generating element, charge / discharge power of the energy storage element, fixed electric power of the fixed electric load, and delayable electric power of the delayable electric load, A scheduling device for an integrated energy system, characterized in that the thermal power includes heat generation power of the heat generation element, heat generation power of the heat generation element and the power generation element, heat storage and release power of the heat storage element, and fixed thermal power of the fixed thermal load.

13. The scheduling device for an integrated energy system according to claim 12, The first optimization module further comprises: expressing the power of the renewable energy node as a function of the electrical power of the elements of the integrated energy system based on a real-time power balance model of the electrical energy of the integrated energy system; Quantitatively characterizing the flexibility of the integrated energy system in each time period as a difference between an upper and lower renewable energy power limit in the corresponding time period; constructing a first target function of flexibility of the integrated energy system in a plurality of time periods based on upper and lower limits of flexibility of the integrated energy system in each time period, the first target function having a goal of making flexibility as large as possible and uniformly distributed among the plurality of time periods; Performing an optimization calculation based on the first objective function to obtain the flexibility optimization result of the system; Here, the constraint condition of the first objective function is The upper and lower limits of the output power of each element of the integrated energy system in each time period satisfy the element power model corresponding to the element; the upper and lower limits of the flexibility of the integrated energy system in each time period correspond to the upper and lower limits of the output of the elements of the integrated energy system in the corresponding time period; Relative constraints on renewable energy; and A scheduling device for an integrated energy system having a relative condition of feasibility.

14. The scheduling device for an integrated energy system according to claim 10, The first determination module further comprises: Obtaining upper and lower limits of the output of the elements of the integrated energy system in each time period based on the flexibility optimization result; determining upper and lower power limits for an electric energy supply and upper and lower power limits for a thermal energy supply of the integrated energy system based on the upper and lower limits of the output of the elements of the integrated energy system in each time period; Setting a feasibility constraint condition for electric energy supply based on upper and lower power limits of electric energy supply of the integrated energy system, including an actual usage power of the renewable energy node operating in real time in the current time period, an electric power purchased from the electric grid in the current time period, and a power generation power of each element operating in real time in the current time period; A scheduling device for an integrated energy system, characterized in that it is used to set feasibility constraints for thermal energy supply based on upper and lower power limits of the thermal energy supply of the integrated energy system, including the heat generation power of each element operating in real time during the current time period.

15. The scheduling device for an integrated energy system according to claim 10, The scheduling module further comprises: Building a second target function of the operating cost of the power generation and heat generation side of the integrated energy system according to the operating cost of each element in the current time period and the electricity purchase cost of the power grid; The power generation and heat generation of each element in the current time period, the power purchased from the power grid, and the true utilization power of the renewable energy node are set as decision variables on the power generation and heat generation side, and a scheduling policy is optimized with the goal of minimizing the second objective function to obtain a scheduling policy on the power generation and heat generation side; A scheduling device for an integrated energy system, characterized in that it is used to determine scheduling policies for the energy storage element, the heat storage element, and the load based on a scheduling policy for the power generation and heat generation side.

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