Scheduling method and device for integrated energy system

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. To reduce carbon emissions, renewable energy has been extensively applied in the construction of new power systems in recent years. Among these, integrated energy systems primarily based on renewable energy are considered a promising development framework due to their multi-energy integration characteristics and efficient energy utilization rate, and are widely applicable to industrial parks and urban systems. In integrated energy systems, electricity and heat are the two main energy carriers on the demand side. Renewable energy and auxiliary cogeneration units on the power generation / heat side can provide clean and efficient electrical and thermal energy. Meanwhile, battery energy storage and thermal storage equipment can provide additional flexibility to the system to respond to uncertainties in renewable energy output and ensure real-time power balance between electrical and thermal energy.

[0003] Online scheduling methods for integrated energy systems are a widely focused research area. Existing studies can be divided into three main categories based on the uncertainty modeling methods.

[0004] The first type of research focuses on pre-planning and primarily employs two-stage optimization methods, such as random optimization, robust optimization, and distributional robust optimization. Random optimization models uncertainty through sampling scenarios and minimizes expected costs. Robust optimization optimizes the worst-case cost for a predetermined set of uncertainties. Distributional robust optimization assumes that the probability distribution of uncertainty is inaccurate, optimizing the cost under the most unfavorable probability distribution. This combines the advantages of random optimization and robust optimization. However, while two-stage optimization models assume that real-time scheduling is performed after all uncertain parameters have been observed, in reality, uncertainties are observed sequentially in time order, also known as "unpredictability."

[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 currently observed uncertainties and the Bellman optimality principle, and reinforcement learning is a typical example. However, the real-time cost function used to train dynamic programming requires a large amount of data, and the convergence guarantee and interpretability of the algorithm remain issues that need to be addressed.

[0006] The third type of research is online scheduling using explicit or implicit policies. Explicit policies enforce an affine relationship between real-time scheduling values ​​and uncertainty parameters, but they are not optimal. Implicit policies specify upper and lower bounds on real-time scheduling variables through constraints, which improves optimality compared to explicit policies, but there is no mature technical framework yet.

[0007] Furthermore, none of the above three types of research combines advance planning with real-time scheduling, nor do they take into account the errors that may appear in advance forecasts, which poses significant challenges to 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, which means that at every point in time, through short-term prediction of future uncertainties, a certainty optimization problem is solved within the current and future short-term time period to obtain the current pre-optimal decision. In real-time operation, the operating state of each component 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 many more elements, offering significant advantages in real-time scheduling of integrated energy systems, including the integration of multiple energy sources. Furthermore, the adoption of forecasting and real-time adjustments improves the economics and optimization of operation. However, this method requires high forecast accuracy, and in systems with a high proportion of renewable energy, forecast errors are often large, significantly impacting the MPC calculation results. Furthermore, renewable energy forecasts are typically short-term. This results in the short-term nature of rolling optimization, resulting in insufficient energy storage scheduling and difficulty handling deferrable loads in the system.

[0010] In light of the above, there is a need for a scheduling method for integrated energy systems 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 advance planning and real-time scheduling to fully utilize the system's flexibility, reduce the impact of prediction errors, and achieve stronger optimality. [Means for solving the problem]

[0013] According to one aspect of the present invention, at least one embodiment provides a scheduling method for an integrated energy system, including: constructing an element power model for an element of the integrated energy system; and constructing a system model of the integrated energy system based on the element power model and the power of a renewable energy node. Here, 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 thermal storage element, and a load. The load includes at least one of a fixed thermal load, a fixed electrical load, and a deferable electrical load. The system model and forecast data from the renewable energy node are used to optimize flexibility of the integrated energy system and obtain a flexibility optimization result. Based on the flexibility optimization result, a feasibility constraint for the integrated energy system is determined. Using the feasibility constraint for the integrated energy system as a constraint and the operating cost of the integrated energy system as an optimization target, real-time scheduling of the integrated energy system is realized using real-time data from the renewable energy node. The system model of the integrated energy system includes at least an element power model based on electrical power and an element power model based on thermal power.

[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 / discharge power for the energy storage element, constructing a thermal energy model based on thermal 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.

[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, wherein 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 heat load.

[0016] Optionally, optimizing the flexibility of the integrated energy system using the system model and renewable energy node forecast data and obtaining a system flexibility optimization result includes expressing power of renewable energy nodes as a function of electrical power of elements of the integrated energy system based on a real-time power balance model of electrical energy of the integrated energy system; quantitatively characterizing the flexibility of the integrated energy system in each time period as a difference between upper and lower power limits 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 constructing a first objective function for flexibility, the first objective function aiming to maximize flexibility and distribute it evenly among the multiple time periods; and performing optimization calculations based on the first objective function to obtain a system flexibility optimization result, wherein the constraints 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 that 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 element of the integrated energy system in that time period, respectively; relative constraints of renewable energy; and relative conditions of feasibility.

[0017] Optionally, the renewable energy relative constraints include an upper limit of flexibility of the integrated energy system in each time period being 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 flexibility of the integrated energy system in each time period being 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, wherein the first coefficient and the second coefficient are both predetermined positive numbers greater than 0 and less than 1.

[0018] Optionally, the relative conditions for 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 feasibility constraints for the integrated energy system based on the flexibility optimization results. do This 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 feasibility constraints for electric energy supply based on the upper and lower power limits of 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 power purchased from the electricity grid in the current time period, and the power generated by 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 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.

[0020] Optionally, realizing real-time scheduling of the integrated energy system using real-time data of renewable energy nodes with feasibility constraints of the integrated energy system as constraints and operating costs of the integrated energy system as optimization targets includes: constructing a second objective function for operating costs of the power generation / heat generation side of the integrated energy system based on the operating costs 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, thereby obtaining the scheduling policy for the power generation / heat generation side; and determining scheduling policies for the energy storage element, the heat storage element, and the load based on the scheduling policy for the power generation / heat generation side.

[0021] Optionally, the constraints of the second objective function include at least one of a feasibility constraint of the integrated energy system, the heat generation power of the heat generation element satisfying a heat generation model of the heat generation element, the power generation power of the power generation element satisfying a power generation model of the power generation element, the heat generation power of the heat generation and power generation elements satisfying 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 satisfying the power generation model of the heat generation and power generation elements, the power purchased from the electricity grid being greater than or equal to 0, and the actual usage power of the renewable energy node in the current time slot being 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 slot.

[0022] According to another aspect of the present invention, at least one embodiment provides a scheduling device for an integrated energy system, including: a first construction module constructs element power models for elements of the integrated energy system, and constructs a system model of the integrated energy system based on the element power models and the power of renewable energy nodes. Here, the elements include one or more of heat-generating elements, power-generating elements, heat-generating and power-generating elements, energy storage elements, thermal storage elements, and loads. The loads include at least one of fixed thermal loads, fixed electrical loads, and deferable electrical loads. 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 for the integrated energy system based on the flexibility optimization result. a scheduling module uses the feasibility constraint for the integrated energy system as a constraint, an operating cost of the integrated energy system as an optimization target, and uses real-time data from renewable energy nodes to realize real-time scheduling of the integrated energy system. The system model of the integrated energy system includes at least an element power model based on electrical power and an element power model based on thermal power.

[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 / discharge power for the energy storage element; constructing a thermal energy model based on thermal 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.

[0024] Optionally, the first construction module is further used to construct a real-time power balance model of electric energy of the integrated energy system based on the power of renewable energy nodes and the electric power of elements present in the integrated energy system, and to construct 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, wherein the electric power includes the power generation power of power generation elements, the power generation power of heat generation and power generation elements, the charging and discharging power of energy storage elements, the fixed electric power of fixed electric loads, and the delayable electric power of delayable electric loads, and the thermal power includes the heat generation power of heat generation elements, the heat generation power of heat generation and power generation elements, the heat storage and release power of heat storage elements, and the fixed thermal power of fixed thermal loads.

[0025] Optionally, the first optimization module is further configured to: express 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 characterize 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; construct a first objective function for 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 to maximize flexibility and distribute it evenly across the multiple time slots; and perform an optimization calculation based on the first objective function to obtain a system flexibility optimization result, wherein constraints of the first objective function include: upper and lower limits of output power of each element of the integrated energy system in each time slot satisfying the element power model corresponding to the element; upper and lower limits of flexibility of the integrated energy system in each time slot corresponding to the upper and lower limits of output of the element of the integrated energy system in the time slot, respectively; a relative constraint of renewable energy; and a relative constraint 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 a feasibility constraint for electric energy supply based on the upper and lower power limits of 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 generated by each element operating in real time in the current time period; and setting a feasibility constraint for thermal energy supply based on the upper and lower power limits of 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 for 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 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 power purchased from the power grid, and the true utilization power of the renewable energy node as power generation / heat generation side decision variables, and obtain the scheduling policy for the power generation / heat generation 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 / heat generation side.

[0028] According to another aspect of the present 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. [Effects 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 construct an integrated energy system model and a simplified element model, roughly optimize the system flexibility using renewable energy forecast data, provide feasibility constraints based on the system flexibility optimization results, and finally take into account the operating costs of the power generation and heat generation side and realize real-time scheduling using real-time data of renewable energy, thereby effectively combining pre-planning and real-time scheduling, fully utilizing the system flexibility, reducing the impact of forecast errors, and achieving relatively strong optimality.

[0030] Various other benefits and advantages 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 construed as limitations on the invention. Furthermore, like reference numerals refer to like parts throughout the drawings. [Brief explanation 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. [Figure 2] 2 is a flowchart of a scheduling method for an integrated energy system according to an embodiment of the present invention. [Figure 3] FIG. 10 is a diagram illustrating an example of a result of optimizing system flexibility in an embodiment of the present invention. [Figure 4] 10A and 10B are diagrams illustrating examples of upper and lower limits of charging power of an energy storage element in an embodiment of the present invention. [Figure 5] 10A and 10B are diagrams illustrating examples of upper and lower limits of charging power for heat storage in an embodiment of the present invention. [Figure 6] FIG. 10 is a diagram showing an example of upper and lower limits of the cogeneration unit output in an embodiment of the present invention. [Figure 7] FIG. 10 is a diagram showing an example of upper and lower limits of a boiler output in an embodiment of the present invention. [Figure 8]10A and 10B 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. 10 is a diagram illustrating 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. 10 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. 10 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. 10 is a diagram illustrating an example of upper and lower bounds 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 real-time utilization status of renewable energy in an embodiment of the present invention. [Figure 14] FIG. 10 is a diagram showing another example of a real-time scheduling result of the integrated energy system according to the embodiment of the present invention. [Figure 15] FIG. 1 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 the configuration of the scheduling device for the integrated energy system according to the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0032]

[0023] Exemplary embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While the accompanying drawings illustrate exemplary embodiments of the present invention, it should be understood that the present invention is not limited to the embodiments described herein, but can be embodied in various forms. 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] References to "one embodiment" or "an embodiment" throughout the specification should be understood to mean that a particular feature, structure, or characteristic associated with an embodiment is included in at least one embodiment of the present 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. Furthermore, these particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Terms such as "first," "second," and the like, used 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 such terms, when used interchangeably, may enable the embodiments of the present invention described herein to be practiced, for example, in an order other than that illustrated or described herein. Furthermore, the terms "comprise" and "have," and all variations thereof, are intended to be non-exclusively inclusive. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not limited to the explicitly recited steps or units, but may also include other steps or units not explicitly recited and that are inherent to the process, method, product, or apparatus. In the specification and claims, "and / or" means 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 can take within a certain time period. Similarly, a lower bound and a lower limit have the same meaning and both refer to the minimum value that a parameter can take within a certain 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 execution order 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 set forth in the claims. Changes can 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 can be omitted, substituted, or added as appropriate. For example, described methods can be performed in an order different from that described, and various steps can be added, omitted, or combined. Furthermore, features described with reference to some examples can be combined in other examples.

[0036] An application scenario of an embodiment of the present invention is a method for pre-planning and real-time scheduling of an integrated energy system, which maximizes system flexibility through pre-fuzzy prediction, sets feasibility constraints, and realizes real-time scheduling of the system by integratedly considering the operating costs of the power generation and heat generation sides. The content of an embodiment of the present invention is a method for pre-planning and real-time scheduling of an integrated energy system based on flexibility. This method specifically includes: building an integrated energy system model and a simplified element model; roughly optimizing the system flexibility using renewable energy forecast data; providing feasibility constraints based on the system flexibility optimization result; considering the operating costs of the power generation and heat generation sides, realizing real-time scheduling using real-time renewable energy data, and providing feasibility proof for the real-time scheduling.

[0037] FIG. 1 provides a schematic diagram of an integrated energy system to which an embodiment of the present invention can be applied, and mainly includes a cogeneration unit, a boiler, an energy storage element (e.g., a battery energy storage element), a thermal storage element, and a load. Here, the load is divided into an electric load and a thermal 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 referred to as 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) via 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 thermal storage element, and the thermal load are connected via a thermal path. The cogeneration unit, the boiler, and the thermal storage element provide thermal energy to the thermal load via the thermal path.

[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, constructing an element power model for an element of the integrated energy system, and constructing a system model of the integrated energy system based on the element power model 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 heat load, a fixed electrical load, and a delayable electrical load.

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

[0040] Here, the term "heat-generating element" refers to an element that independently generates thermal energy and provides the thermal energy to a load in the integrated energy system, such as a boiler. The term "power-generating element" refers to an element that independently generates electrical energy and provides the electrical energy to a load in the integrated energy system, such as a diesel engine. The term "heat-generating and power-generating element" refers to an element that simultaneously generates thermal energy and electrical energy and can provide the thermal energy and electrical energy to a load in the integrated energy system, such as a cogeneration unit. An embodiment of the present invention proposes an integrated energy system model and a simplified element model. This model comprehensively considers the models of various cogeneration units, boilers, energy storage elements, thermal storage elements, and loads in the integrated energy system, and also proposes a relaxation model for delayable electrical loads.

[0041] Specifically, in step 21, constructing element power models for the elements 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 generation element model. The power generation 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 generation element in the time period t, and H is the upper and lower limits (min, max) of the power generation power of the power generation element. (Formula 0) is a power generation model of the power generation 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 simultaneously generate electricity and thermal energy using a heat engine or power plant. In a typical power plant, the heat remaining from the power generation process is mainly released into the environment through a cooling tower or cooling water, but in a cogeneration plant, the heat is 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 power generation and heat generation power outputs of the heat generation and power generation elements (e.g., cogeneration units) in time period t, respectively. rHP is the electrical thermal coefficient ratio of the heat generation and power generation elements (e.g., cogeneration units). P are the upper and lower limits (min, max) of the power generation, respectively. T is the number of time periods. (Equation 1) is a power generation model of the first type of heat generation and power generation elements, and (Equation 2) is a heat generation model of the first type of heat generation and power generation elements.

[0049] The second type is a condensing unit (e.g., a steam turbine cogeneration unit) that mainly utilizes the residual heat after the steam turbine. The feasible operating region 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 amount and heat generation amount of the pole, 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 generation and heat generation constraints are linear and time independent. The embodiment of the present invention is applicable to two types of unit models. The following content takes the first type of cogeneration unit as an example.

[0054] (2) Heat-generating 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 generation power of the heat generation element in time period t. H is the upper and lower limits (min, max) of the heat generation power of the heat generation element. (Equation 5) is a heat generation model of the heat generation element.

[0057] (3) Energy storage element model. Energy storage devices such as batteries are currently one of the fastest-responding energy storage methods. 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 for real-time operation. Its model can be expressed as follows:

[0058]

number

[0059]

number

[0060]

number

[0061] In the above equations, PB(t) is the charge / discharge power of the energy storage element in time period t, and 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 represents the upper and lower capacity limits (min, max) of the energy storage element, respectively. σB is the self-discharge coefficient of the energy storage element. Δt is the length of time period t. (Equation 6) to (Equation 8) are the electrical energy models of the energy storage element.

[0062] (4) Heat storage element model. Thermal energy storage is a technology that allows for the capture and storage of thermal energy (i.e., heat) for future use. Because thermal energy is easier to store than electrical energy, thermal storage can help balance power supply and demand in energy systems, and its operating principle is similar to that of battery energy storage. Similarly, thermal storage has high charging and discharging efficiency and can be considered ideal. 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 heat storage capacity, respectively. σH is the self-loss coefficient of the heat storage element. (Equation 9) to (Equation 11) are the thermal energy models of the heat storage element.

[0067] (5) Load model. Electric loads in an integrated energy system can be broadly divided into two types: fixed loads and deferrable loads. Fixed loads, PL(t), typically have fixed, variable characteristics and are not affected by external conditions or user behavior changes. Their power can be modeled as a deterministic 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 loads that can be shifted without affecting the quality of service provided. The amount of electricity for such loads is usually fixed, but their power during each time period can be adjusted or shifted. Typical examples are electric water heaters and certain types of industrial machinery. Shifting these loads to periods of low overall power demand can balance the energy system's power supply and demand, improving reliability and reducing costs. This process is commonly referred to as demand-side response. Deferrable loads can be described as follows:

[0068]

number

[0069]

number

[0070] In the above equation, 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 amount of electricity 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, and is similar to the fixed electric load PL(t) described above, so a description thereof will be omitted here.

[0072] (6) Integrated energy system model. In actual 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 renewable energy nodes and the electric power of elements in the integrated energy system, where the electric power includes the power generated by power generating elements, the power generated by heat generating and power generating elements, the charging and discharging power of energy storage elements, the fixed electric power of fixed electric loads, and the delayable electric power of delayable electric loads.A real-time power balance model of thermal energy of the integrated energy system is constructed based on the thermal power of elements in the integrated energy system, where the thermal power includes the heat generating power of heat generating elements, the heat generating power of heat generating and power generating elements, the heat storage and discharging power of heat storage elements, and the fixed thermal power of fixed heat loads.

[0074] The following description will be mainly given taking as an example the integrated energy system shown in Fig. 1. 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 constructed based on 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 constructed based on the heat generation power of the co-generator unit, the heat generation power of the boiler, the heat storage and discharge power of the heat storage element, and the fixed thermal power of the fixed thermal load.

[0076]

number

[0077]

number

[0078] In the above equation, PR(t) is the renewable energy utilization power in time period t. Equation 14 is a real-time power balance model of the electric energy of the integrated energy system, and Equation 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, an embodiment of the present invention proposes a method for roughly optimizing system flexibility using renewable energy node forecast data. Based on a rough renewable energy output forecast curve in advance, this method fully utilizes the system's flexibility and constructs a quadratic convex optimization problem to calculate the system's ability to respond to uncertainties in renewable energy output power. While maximizing system flexibility, the system's flexibility is uniformly distributed across each time period. The "renewable energy relative constraint" in the optimization problem ensures that the ability to respond to uncertainties in renewable energy output power is distributed within the possible range of renewable energy output, and the "relative feasibility condition" in the optimization problem ensures the feasibility of the following 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 for 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 uncertainty in the output power of renewable energy. In embodiments of the present invention, it is desirable for the system's flexibility to be as large as possible, thereby being able to respond to a wider range of fluctuations in renewable energy output. However, since uncertainty exists in each time period, it is desirable for the system's flexibility to be evenly distributed across each time period. Therefore, in embodiments of the present invention, the system's flexibility in each time period is quantitatively characterized as the difference between the upper and lower limits of the renewable energy power that can be supported, i.e., the upper limit (up) of P0(t) minus the lower limit (low) of P0(t).

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

[0085]

number

[0086]

number

[0087] The flexibility of the system is composed of the flexibility of each internal element, i.e., 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, i.e., as follows:

[0088]

number

[0089]

number

[0090]

number

[0091]

number

[0092] A first objective function for the flexibility of the integrated energy system in multiple 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 maximize flexibility and distribute it evenly across the multiple time periods. An optimization calculation is performed based on the first objective function to obtain a system flexibility optimization result. Here, the constraints 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 satisfy the element power model corresponding to that 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 slot correspond to the upper and lower limits of the output of the elements of the integrated energy system in that time slot, respectively. Xup and Xlow in the following (Equation 23) satisfy (Equation 19) to (Equation 22). Relative constraint condition for renewable energy. Corresponds to (d) in the following (Equation 23). Relative condition for feasibility. Specifically, this includes the upper limit of the flexibility of the integrated energy system in each time slot being equal to or greater than the lower limit of the flexibility of the integrated energy system in that time slot, and the upper limit of the output of the elements of the integrated energy system in each time slot being equal to or greater than the lower limit of the output of the elements in that time slot, and corresponds to (c) and (e) in the following (Equation 23).

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

[0094]

number

[0095] In the above equation, ω is a very small positive number, a constant related to the system, which can be set empirically. This quadratic term acts as a variance, allowing the system's flexibility optimization results to be uniformly distributed. The arguments are the upper and lower limits of the system and each element's flexibility in each time period, namely, Xup and Xlow. In addition to satisfying the basic element constraints (Equations 1) to (Equation 13) and the power balance (Equations 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. This will be proven 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 slot is equal to or greater than the product of a first coefficient α and the power of the renewable energy node in that time slot, and equal to or less than the power of a second renewable energy node in that time slot; and a lower limit of the flexibility of the integrated energy system in each time slot 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 that time slot, where the first coefficient α and the second coefficient β are both predetermined positive numbers greater than 0 and less than 1. That is, as follows.

[0097]

number

[0098] In the above equation, α and β are predetermined coefficients, and PR(t) is the predicted value of renewable energy output. This equation indicates that the flexibility of the integrated energy system, i.e., its ability to respond to uncertainties in renewable energy output power, should be distributed within the possible range of renewable energy output. As shown in Figure 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 system flexibility. The area between the curve on which P0up is located and the line with the ordinate of 0 is the possible range of renewable energy output, with the upper limit being the predicted value of the total renewable energy output and the lower limit being 0. Figures 4 to 10 are diagrams showing examples of the calculation results 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 electrical load, Figure 9 shows the upper and lower limits of the feasibility constraints of the electrical energy supply node, and Figure 10 shows the upper and lower limits of the feasibility constraints of the thermal energy supply 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, feasibility constraints for the integrated energy system are determined based on the flexibility optimization results.

[0101] In step 23, the embodiment of the present invention determines feasibility constraints based on the system flexibility optimization results. The feasibility constraints constrain the upper and lower limits of the power of the electric energy and thermal energy supplying nodes and correspond to the limits of the system flexibility range. As long as the power of the electric energy and thermal energy supplying nodes is within the corresponding upper and lower limits, a real-time scheduling policy that makes the system feasible is always guaranteed. 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 electrical energy supply and 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 upper and lower power limits of the energy supplying nodes of the integrated energy system can be further calculated by xup and xlow. Here, the upper and lower power limits of the electric energy supplying node Pb(t) are as follows:

[0104]

number

[0105]

number

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

[0107]

number

[0108]

number

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

[0110] For example, the upper and lower limits of the electric and thermal energy supplying nodes obtained by the flexibility optimization described above correspond to the limits of the system's flexibility range. That is, as long as the power of the electric and thermal energy supplying nodes is within the corresponding upper and lower limits, the system's flexibility is allowed, and a real-time scheduling policy always exists to make the system feasible. This conclusion is proven as follows. Therefore, the feasibility constraints for 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 real-time operation in 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 results of the upper and lower limits of the feasibility constraint for an electric energy supply node, and Figure 12 shows an example of the calculation results of the upper and lower limits of the feasibility constraint for a thermal energy supply node.

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

[0115] In step 24, the embodiment of the present invention implements real-time scheduling using real-time data of renewable energy, taking into account the operation costs 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 for the power generation / heat generation side operating cost of the integrated energy system is constructed based on the operating costs of each element in the current time slot and the electricity purchasing cost of the power grid. For example, the second objective function for the power generation / heat generation side operating cost of the integrated energy system is constructed based on the operating costs of the cogeneration unit, the heat generation cost of the boiler, and the electricity purchasing cost of the power grid in the current time slot. Next, the power generation / heat generation side operating cost 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 heat generation cost Cboiler(t) is proportional to the fuel consumed, so the cost can be considered as a linear function of the heat generation 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 and are all 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 for the power generation and heat generation side, and a scheduling policy is optimized with the goal of minimizing the second objective function, thereby obtaining the scheduling policy for the power generation and heat generation side.For example, the power generation and heat generation of the cogeneration unit in the current time slot, the heat generation power of the boiler, the power purchased from the power grid, and the true power usage of the renewable energy node are set as decision variables for the power generation and heat generation side, and a scheduling policy is optimized with the goal of minimizing the second objective function, thereby obtaining the scheduling policy for 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 the heat generating model of the heat generating element. The power generated by the power generating element satisfies the power generation model of the power generating 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. 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 forecast of future renewable energy output, and only solve the optimization problem for 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 or equal to PR(t) and greater than or equal to 0. By solving (Equation 34), the real-time scheduling policy for the power generation and heat generation side, y(t), can be obtained. 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] Clearly, 0≦λ1(t)≦1, 0≦λ2(t)≦1. Below, we prove the feasibility of the scheduling policy. The decision variables on the power generation / 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 summarized 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 the "relative condition for feasibility" PB(t)(up)≧PB(t)(low) in (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 to construct an element power model for an element of the integrated energy system, and construct 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 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 electrical load, and a delayable electrical load. A first optimization module 1502 is used to utilize the system model and renewable energy node forecast data to optimize the flexibility of the integrated energy system and obtain a flexibility optimization result. A first determination module 1503 is used for determining feasibility constraints of the integrated energy system based on the flexibility optimization result. The scheduling module 1504 is used to realize 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 an optimization target.

[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 relatively strong 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 / discharge power for the energy storage element; constructing a thermal energy model based on thermal 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.

[0151] Optionally, the first construction module is further used to construct a real-time power balance model of electric energy of the integrated energy system based on the power of renewable energy nodes and the electric power of elements present in the integrated energy system, and to construct 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 the power generated by the power generating elements, the power generated by the heat generating and power generating elements, the charging and discharging power of the energy storage elements, the fixed electric power of the fixed electric loads, and the delayable electric power of the delayable electric loads, and the thermal power includes the heat generating power of the heat generating elements, the heat generating power of the heat generating and power generating elements, the heat storage and discharging power of the heat storage elements, and the fixed thermal power of the fixed thermal loads.

[0152] Optionally, the first optimization module is further configured to: express 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 characterize 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; construct a first objective function for 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 to maximize flexibility and distribute it evenly across the multiple time slots; and perform an optimization calculation based on the first objective function to obtain a system flexibility optimization result, wherein constraints of the first objective function include: upper and lower limits of output power of each element of the integrated energy system in each time slot satisfying the element power model corresponding to the element; upper and lower limits of flexibility of the integrated energy system in each time slot corresponding to the upper and lower limits of output of the element of the integrated energy system in the time slot, respectively; a relative constraint of renewable energy; and a relative constraint of feasibility.

[0153] Optionally, the renewable energy relative constraints include an upper limit of flexibility of the integrated energy system in each time period being 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 flexibility of the integrated energy system in each time period being 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, wherein the first coefficient and the second coefficient are both predetermined positive numbers greater than 0 and less than 1.

[0154] Optionally, the relative conditions for 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 a feasibility constraint for electric energy supply based on the upper and lower power limits of 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 generated by each element operating in real time in the current time period; and setting a feasibility constraint for thermal energy supply based on the upper and lower power limits of 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 for 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; 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 power purchased from the electricity grid, and the true utilization power of the renewable energy node as power generation / heat generation side decision variables, thereby obtaining the scheduling policy for the power generation / heat generation 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 / heat generation side.

[0157] Optionally, the constraints of the second objective function include at least one of a feasibility constraint of the integrated energy system, the heat generation power of the heat generation element satisfying a heat generation model of the heat generation element, the power generation power of the power generation element satisfying a power generation model of the power generation element, the heat generation power of the heat generation and power generation elements satisfying 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 satisfying the power generation model of the heat generation and power generation elements, the power purchased from the electricity grid being greater than or equal to 0, and the actual usage power of the renewable energy node in the current time slot being 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 slot.

[0158] It should be noted that each system provided in the above embodiments is a device 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 device embodiments to obtain the same technical effects. The device provided in the embodiments of the present invention can implement all the method steps implemented by the method embodiments and 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 is a schematic diagram of a scheduling device for another integrated energy system 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 memory 1603 and executable on processor 1601 .

[0161] The transceiver 1602 is used to transmit and receive data under the control of the processor 1601. The processor 1601 is used to read the computer program in the memory and perform the following operations: An element power model is constructed for an element of the integrated energy system, and a system model of the integrated energy system is constructed 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 heat load, a fixed electric load, and a delayable electric load. The system model and renewable energy node forecast data are utilized to optimize the flexibility of the integrated energy system, and a flexibility optimization result is obtained. Based on the flexibility optimization results, feasibility constraints for the integrated energy system are determined. 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 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 effects can be achieved, so to avoid redundancy, no further description will be given here.

[0163] In FIG. 16, the bus architecture may include any number of interconnecting buses and bridges, specifically connecting one or more processors, such as processor 1601, to various types of memory, such as memory 1603. The bus architecture may also connect various types of other circuits, such as peripheral equipment, regulators, and power management circuits. These are all well known in the art and will not be further described 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 that communicates 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 externally connected devices. Connected devices may 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 by the processor 1601 during its operations.

[0165] The apparatus in this embodiment is a device corresponding to the scheduling method for an integrated energy system, and the implementation forms in the above embodiments can all be applied to this device embodiment 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 all be communicatively connected via a bus interface, and the functions of the processor 1601 can also be realized by the transceiver 1602, and the functions of the transceiver 1602 can also be realized by the processor 1601. The above device provided in the embodiment of the present invention can implement all the method steps implemented in the above method embodiments and achieve the same technical effects, and therefore the same parts and beneficial effects of this embodiment as those of the method embodiments 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: An element power model is constructed for an element of the integrated energy system, and a system model of the integrated energy system is constructed 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 heat load, a fixed electric load, and a delayable electric load. The system model and renewable energy node forecast data are utilized to optimize the flexibility of the integrated energy system, and a flexibility optimization result is obtained. Based on the flexibility optimization results, feasibility constraints for the integrated energy system are determined. 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 utilizing real-time data of renewable energy nodes.

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

[0168] Those skilled in the art can understand that the units and algorithm steps of each example 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 in different ways for each specific application, but these realizations should not be considered beyond the scope of the present disclosure.

[0169] For convenience and brevity of description, the specific operation processes of the above-described systems, devices and units are not repeated here, and those skilled in the art are aware of the corresponding processes in the method embodiments.

[0170] It should be understood that the disclosed apparatus and method may be implemented in other ways in some embodiments provided by the present invention. The apparatus embodiments described above are merely exemplary. For example, the division of units described merely represents a division of logical functions, and other division methods may be used in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented. Furthermore, the couplings, direct couplings, and communication connections between the components shown or discussed may be indirect couplings or communication connections via interfaces, devices, or units, and may be electrical, mechanical, or other types of couplings.

[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. That is, 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 physically separate, or two or more may be integrated.

[0173] When the functions are realized in the form of software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on this understanding, the substantial or prior art contributions of the technical means of the present disclosure, or portions 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 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 methods described in each embodiment of the present disclosure. The storage medium includes various media capable of storing 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 substitutions that can be easily thought of by those skilled in the art 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 element power models for elements of the integrated energy system, the elements including one or more of loads including at least one of fixed thermal loads, fixed electrical loads, and delayable electrical loads, heat generating elements, power generating elements, heat generating and power generating elements, energy storage elements, and heat storage elements, and constructing a system model of the integrated energy system based on the element power models and the power of renewable energy nodes; Optimizing the flexibility of the integrated energy system using the system model and renewable energy node forecast data to obtain a flexibility optimization result; determining feasibility constraints for the integrated energy system based on the flexibility optimization results; and The feasibility constraint of the integrated energy system is a constraint, the operation cost of the integrated energy system is an optimization target, and realizing real-time scheduling of the integrated energy system by using real-time data of the renewable energy node; The system model of the integrated energy system includes at least an element power model based on electrical power and an element power model based on thermal power, A scheduling method for an integrated energy system, comprising:

2. 2. The method for scheduling an integrated energy system according to claim 1, constructing element power models for the elements of the integrated energy system, 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 for the heat generation and the power generation element and a heat generation model based on heat generation power; 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.

3. 2. The method for scheduling an integrated energy system according to claim 1, 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 the thermal power of the elements present in the integrated energy system; wherein the electric power includes power generated by the power generating element, power generated by the heat generating and 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, wherein the thermal power includes the heat generation power of the heat generation element, the heat generation power of the heat generation and power generation element, the heat storage and release power of the heat storage element, and the fixed thermal power of the fixed thermal load.

4. 4. The method for scheduling an integrated energy system according to claim 3, 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 electrical energy of the integrated energy system; Quantitatively characterizing the flexibility of the integrated energy system in each time period as the difference between upper and lower renewable energy power limits in that 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 aiming to maximize flexibility and distribute it evenly across 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, The relative constraints on renewable energy are: an upper limit of flexibility of the integrated energy system in each time slot is equal to or greater than a product of a first coefficient and a power of the renewable energy node in that time slot, and is equal to or less than a power of a second renewable energy node in that time slot; 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 that 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, The relative conditions for feasibility are: an upper limit of flexibility of the integrated energy system in each time period is equal to or greater than a lower limit of flexibility of the integrated energy system in the 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 for scheduling an integrated energy system according to claim 1, determining a feasibility constraint 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 electrical energy supply and thermal energy supply of the integrated energy system based on the upper and lower limits of the outputs of the elements of the integrated energy system in each time period; Setting a feasibility constraint on the supply of electric energy based on upper and lower power limits of the supply of electric energy of the integrated energy system, including the actual usage power of the renewable energy node operating in real time in the current time period, the power purchased from the electric grid in the current time period, and the power generated by each element operating in real time in the current time period; A scheduling method for an integrated energy system, comprising setting a feasibility constraint for thermal energy supply based on upper and lower power limits of 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 for scheduling an integrated energy system according to claim 1, 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, constructing a second target function of the power generation / heat generation side operating cost of the integrated energy system based on the operating cost of each element in the current time period and the electricity purchase cost of the electricity grid; The power generation and heat generation of each element in the current time period, the power purchased from the electricity grid, and the true power usage of the renewable energy node are used 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, The constraint of the second objective function is feasibility constraints for 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 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; The electricity purchased from the electricity grid is 0 or more; The scheduling method for an integrated energy system, characterized in that the actual usage 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.

10. A scheduling device for an integrated energy system, comprising: a first construction module for constructing element power models for elements of the integrated energy system, the elements including one or more of loads including at least one of fixed thermal loads, fixed electrical loads, and delayable electrical loads, heat generating elements, power generating elements, heat generating and power generating elements, energy storage elements, and thermal storage elements, and for constructing a system model of the integrated energy system based on the element power models and power of renewable energy nodes; 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 feasibility constraints for the integrated energy system based on the flexibility optimization results; a scheduling module for realizing real-time scheduling of the integrated energy system by using real-time data of the renewable energy nodes, with the feasibility constraint of the integrated energy system as a constraint and the operation cost of the integrated energy system as an optimization target; 1. A scheduling device for an integrated energy system, wherein the system model of the integrated energy system includes at least an element power model based on electric power and an element power model based on thermal power.

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: construction of a heat generation model based on heat generation power for the heat generation element; construction of a power generation model based on power generation power for the power generation element; construction of a power generation model based on power generation power for the heat generation and the power generation element and a heat generation model based on heat generation power; construction of an electric energy model based on charge / discharge power for the energy storage element; construction of a thermal energy model based on heat storage / release power for the heat storage element; construction of an electric load model based on fixed electric power for the fixed electric load; construction of a total electric quantity relaxation model based on delayable electric power for the delayable electric load; and construction of 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; It is used to construct a real-time power balance model of thermal energy of the integrated energy system based on the thermal power of the elements present in the integrated energy system; wherein the electric power includes power generated by the power generating element, power generated by the heat generating and 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 the heat generation power of the heat generation element, the heat generation power of the heat generation and power generation element, the heat storage and release power of the heat storage element, and the 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 electrical energy of the integrated energy system; Quantitatively characterizing the flexibility of the integrated energy system in each time period as the difference between upper and lower renewable energy power limits in that time period; constructing a first target function for flexibility of the integrated energy system over a plurality of time periods based on upper and lower limits of flexibility of the integrated energy system over each time period, the first target function aiming to maximize flexibility and distribute it evenly over 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 that 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 characterized by 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 electrical energy supply and thermal energy supply of the integrated energy system based on the upper and lower limits of the outputs of the elements of the integrated energy system in each time period; Setting a feasibility constraint on the supply of electric energy based on upper and lower power limits of the supply of electric energy of the integrated energy system, including the actual usage power of the renewable energy node operating in real time in the current time period, the power purchased from the electric grid in the current time period, and the power generated by 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 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: constructing a second target function of the power generation / heat generation side operating cost of the integrated energy system based on the operating cost of each element in the current time period and the electricity purchase cost of the electricity grid; The power generation and heat generation of each element in the current time period, the power purchased from the electricity grid, and the true power usage of the renewable energy node are used 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 the scheduling policy for the power generation and heat generation side.

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