Unit commitment method and system for integrated energy system considering network dynamic characteristics

Abstract

The application provides a unit commitment method and system of a comprehensive energy system considering network dynamic characteristics, and comprises the following steps: comprehensively considering energy production equipment and energy storage equipment in an electric-gas-heat comprehensive energy system, and meanwhile, considering a network transmission dynamic characteristic equation, taking system comprehensive cost minimization as an objective function, and constructing an electric-gas-heat comprehensive energy system unit commitment model considering network dynamic characteristics; determining constraint conditions of the electric-gas-heat comprehensive energy system unit commitment model considering network dynamic characteristics; and adopting a piecewise linearization method to linearize the model, so as to obtain a unit commitment scheme. The application reduces frequent start-stop of a traditional thermal power unit, optimizes a running period of the thermal power unit, improves a wind power accommodation space, and enhances economy and running flexibility of the system.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy system technology, and particularly relates to a method and system for combining integrated energy system units that takes into account the dynamic characteristics of the network. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Integrated energy systems encompass multiple resources such as electricity, gas, and heat, serving as a crucial platform for the future development of the energy internet. The advancements in technologies like combined heat and power (CHP) units, gas turbines, and electric boilers have deepened the coupling between different energy types in production, transmission, and distribution. By leveraging the spatiotemporal coupling mechanisms of different energy modules and through multi-source collaborative optimization, dynamic energy transmission, and the configuration of various energy storage types, integrated energy systems can effectively enhance the economic efficiency and flexibility of system operation.

[0004] Because energy systems such as electricity, heat, and natural gas have different energy supply and demand forms, their energy transmission dynamic characteristics vary significantly. Under these circumstances, many scholars have conducted in-depth research on the optimal scheduling problem of regional integrated energy systems that consider network energy transmission, achieving a series of results. Current energy transmission models are mainly divided into two modeling methods: steady-state and dynamic. In electro-gas coupled systems, the gas network steady-state model typically does not consider the influence of pipeline pressure, temperature, and other parameters on power flow; in electro-thermal coupled systems, the heat network steady-state model typically does not consider the time delay characteristics and temperature loss during heat propagation.

[0005] The above steady-state model improves computational efficiency. However, network transmission methods that consider the dynamic characteristics of the network have the following advantages:

[0006] 1) The dynamic characteristics of energy sources such as natural gas and hot water in the transmission of energy in the corresponding network, such as time delay and inertia, are equivalent to providing a certain energy storage capacity for the energy transmission network. Ignoring the dynamic characteristics will indirectly reduce the operational flexibility of the integrated energy system.

[0007] 2) With the development of the energy internet, the interconnection of "electricity-gas-heat" is enhanced. Considering the dynamic characteristics of gas networks and heat networks and the coupling optimization mechanism, it is of great significance to improve the transmission flexibility of the integrated energy network.

[0008] Meanwhile, with the increasing coupling of multiple energy sources, analyzing the power system unit combination problem within the framework of the regional energy internet has significant practical implications. The traditional power system unit combination problem addresses the uncertainty of power sources and loads within a region by planning the combination and output of various units to achieve optimal economic costs. However, due to the limited available flexibility resources in traditional power systems, when regional power sources and loads fluctuate significantly, thermal power units need to be frequently started and stopped to meet energy demand, resulting in substantial increased economic costs. In contrast, integrated energy systems offer numerous flexible resources, such as combined heat and power units, gas-fired boilers, and other energy conversion equipment. The dynamic transmission characteristics of natural gas and hot water further endow the system with energy storage capacity, enhancing the operational flexibility of integrated energy systems. Considering the dynamic characteristics of the network is crucial for the rational allocation of thermal power unit operating times and reducing economic losses caused by frequent start-ups and shutdowns. Summary of the Invention

[0009] To overcome the shortcomings of the prior art, this invention provides a method for combining units in an integrated energy system that considers the dynamic characteristics of the network. The proposed method effectively reduces the economic costs of thermal power units due to frequent start-ups and shutdowns, while increasing the capacity for wind power absorption and enhancing the operational flexibility of the system.

[0010] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0011] Firstly, a method for combining units in an integrated energy system that considers the dynamic characteristics of the network is disclosed, including:

[0012] Taking into account the energy production and storage equipment in the integrated energy system of electricity, gas, and heat, and considering the dynamic characteristic equations of network transmission, a unit combination model of the integrated energy system of electricity, gas, and heat, taking into account the network dynamic characteristics, is constructed with the goal of minimizing the overall system cost.

[0013] Determine the constraints of the integrated energy system unit combination model that takes into account the dynamic characteristics of the network;

[0014] The model is linearized using a piecewise linearization method to obtain the unit combination scheme.

[0015] As a further technical solution, when constructing a combined unit model of an integrated energy system that takes into account the dynamic characteristics of the network, the node method is used for modeling.

[0016] As a further technical solution, the energy production equipment and energy storage equipment include: conventional thermal power units, wind power generation systems, gas-fired CHP, GT and EB;

[0017] Using the latter three types of equipment as energy coupling units, gas-fired CHP and EB are responsible for supplying heat energy, and GT assists the thermal power unit in power peak regulation.

[0018] Meanwhile, electric and thermal energy storage devices are installed to absorb fluctuating resources and limit the thermal output of CHP units during periods of severe wind curtailment.

[0019] As a further technical solution, the overall system cost includes the start-up and shutdown cost of conventional units, the operating cost of conventional units, the gas source output cost, and the cost of wind curtailment.

[0020] As a further technical solution, the constraints of the integrated energy system unit combination model for electricity, gas, and heat include: grid constraints, natural gas grid constraints, heat grid constraints, and energy conversion equipment constraints.

[0021] As a further technical solution, the grid constraints include grid power balance constraints, unit output constraints, unit ramping constraints, minimum start-up and shutdown time and start-up and shutdown state constraints for conventional units, and relevant constraints for energy storage devices.

[0022] As a further technical solution, the natural gas network constraints include the gas source supplying gas flow to the gas load and coupling equipment through the natural gas network, the upper and lower limits of the gas source supply flow, the bidirectionality of the gas network flow, the equation describing the relationship between the gas network pipeline flow and pressure, the upper and lower limit constraints of the gas network node pressure, and the gas network flow balance constraints.

[0023] As a further technical solution, the heat network constraint conditions include using a working fluid flow model to describe the heat network flow, heat network balance constraint representation, and heat storage tank related constraint representation.

[0024] As a further technical solution, the constraints of the energy conversion equipment include the energy coupling constraints of the CHP unit and the representation of the energy coupling constraints of the CHP unit.

[0025] Secondly, a comprehensive energy system unit combination system considering the dynamic characteristics of the network is disclosed, including:

[0026] The model building module is configured to: comprehensively consider the energy production equipment and energy storage equipment in the integrated energy system of electricity, gas and heat, while taking into account the dynamic characteristic equation of network transmission, and construct a unit combination model of the integrated energy system of electricity, gas and heat that takes into account the dynamic characteristics of the network, with the goal of minimizing the overall system cost.

[0027] The constraint determination module is configured to: determine the constraints of the integrated energy system unit combination model that takes into account the dynamic characteristics of the network;

[0028] The solution module is configured to linearize the model using a piecewise linearization method to obtain the unit combination scheme.

[0029] The above one or more technical solutions have the following beneficial effects:

[0030] This invention proposes a modeling method for natural gas networks and thermal networks that considers the dynamic characteristics of the network. In this method, "pipe storage" is used to characterize the natural gas storage capacity in the pipeline, and transmission delay and temperature loss are used to describe the delay in the transmission of hot water in the network.

[0031] Compared to traditional power system unit combination models, this invention proposes a comprehensive energy system unit combination modeling method that considers multi-energy synergy and network dynamic characteristics. It comprehensively considers energy production and storage equipment, multi-energy coupling equipment, and network dynamic characteristics, utilizing these flexible resources to achieve dynamic conversion of electricity, gas, and heat energy. During peak heat load periods, the thermal network utilizes energy stored during transmission delays, working in conjunction with electric boilers, thermal storage tanks, and other equipment to achieve dynamic energy conversion from natural gas and electricity to heat energy. This decouples the "heat-driven power generation" mode of cogeneration units while increasing wind power absorption capacity. Similarly, during peak electricity consumption periods, "pipeline storage" in natural gas pipelines, in conjunction with gas turbines, thermal power units, and other equipment, achieves dynamic energy conversion from natural gas to electricity. Excess heat energy generated by cogeneration units is stored in the thermal network due to its dynamic characteristics. The multi-energy supply of electricity load reduces the start-up and shutdown frequency of thermal power units, improving system economy. Simultaneously, through the above synergistic methods, the operational flexibility of the regional integrated energy system is enhanced. Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0032] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention.

[0033] Figure 1 This is a schematic diagram of the topology of the integrated electric-gas-heat energy testing system for the verification of this invention.

[0034] Figure 2 This is a schematic diagram showing the unit combination results before and after considering network dynamic characteristics in the verification of an example of the present invention.

[0035] Figure 3 This is a schematic diagram of the system power balance in the verification of the present invention.

[0036] Figure 4 This is a schematic diagram of the system thermal power balance in the verification of the present invention.

[0037] Figure 5 A schematic diagram of the output of the cogeneration unit before and after considering the network dynamic characteristics in this invention example;

[0038] Figure 6 This is a schematic diagram comparing the output of wind turbine units in an example of the present invention;

[0039] Figure 7 The diagram shows the gas source output before and after considering the network dynamic characteristics in this invention example. Detailed Implementation

[0040] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0041] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0042] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0043] Example 1

[0044] This embodiment discloses a method for combining units in an integrated energy system that considers the dynamic characteristics of the network, including:

[0045] Taking into account the energy production and storage equipment in the integrated energy system of electricity, gas, and heat, and considering the dynamic characteristic equations of network transmission, a unit combination model of the integrated energy system of electricity, gas, and heat, taking into account the network dynamic characteristics, is constructed with the goal of minimizing the overall system cost.

[0046] Determine the constraints of the integrated energy system unit combination model that takes into account the dynamic characteristics of the network;

[0047] The model is linearized using a piecewise linearization method to obtain the unit combination scheme.

[0048] This embodiment, based on traditional power system unit combination methods, considers multi-energy coupling and the dynamic characteristics of natural gas and heating networks, proposing a comprehensive energy system unit combination method that takes into account network dynamics. First, it describes the gas-pipeline storage caused by the slow transmission speed and compressibility of natural gas. Simultaneously, it presents the dynamic characteristic equations of the heating network caused by temperature loss and transmission delay during hot water transmission. Based on this, considering various energy production equipment and electric and thermal energy storage devices, and using the comprehensive cost of the integrated electric-gas-heat energy system as the objective function, including the power generation cost of conventional thermal power units, gas source output cost, and wind curtailment cost, a unit combination model for the integrated electric-gas-heat energy system considering network dynamics is constructed. Then, considering that the operating cost function of traditional thermal power units and the flow-pressure relationship equation of gas pipelines both involve square terms, a piecewise linearization method is used to transform the original model into a MILP problem. Finally, the effectiveness of the proposed method is verified using an integrated electric-gas-heat energy testing system as an example.

[0049] First, regarding the analysis of network dynamic characteristics:

[0050] Regarding the dynamic characteristics of the air network

[0051] Because natural gas travels slowly and is compressible in pipeline networks, the flow rate of natural gas injected at the beginning of the pipeline differs from the flow rate flowing out at the end. This difference in flow rate is called "pipeline inventory." Pipeline inventory is directly proportional to the average pressure at both ends of the gas pipeline network, expressed as:

[0052] M gh,t =λ gh P gh,t (11)

[0053]

[0054] In the formula, M gh,t Let gh be the pipe's storage at time t; λ gh These are pipe parameters, related to pipe length, diameter, etc.; P gh,t Let P be the average pressure of pipe gh at time t. gh,t =(P g,t +P h,t ) / 2; These represent the air flow rates in the inflow and outflow pipes, respectively.

[0055] Regarding the dynamic characteristics of the heating network

[0056] The dynamic characteristics of a heating network are manifested in the time delay and temperature loss during hot water transfer. The time delay of hot water within the heating network causes the temperature at the pipe inlet to be slowly transferred to the outlet; this transfer time is called the transfer delay τ. Simultaneously, because the pipe temperature is higher than the ambient temperature during heat transfer, this results in temperature loss. The modeling method for this implementation is as follows:

[0057] 1) Transmission delay

[0058] Neglecting temperature loss, the pipe outlet temperature can be determined by the pipe inlet temperature and the transmission delay τ. kl,t This indicates that at time t, the outlet temperature of pipe kl should be equal to t-τ. kl,t The temperature of a moment.

[0059]

[0060] In the formula, To determine the outlet temperature of pipe kl at time t without considering temperature loss, For pipe kl at t-τ kl,t Inlet temperature at any given time; R kl L kl These represent the radius and length of pipe kl, respectively; m kl,t Let ρ be the flow rate of the working fluid in pipe kl at time t; ρ is the density of water.

[0061] 2) Temperature loss

[0062] Hot water experiences temperature loss during heat transfer within the heating network. The actual outlet temperature of the heating network pipe kl is calculated using the Sukhov formula and expressed as:

[0063]

[0064]

[0065] In the formula, To account for the actual outlet temperature of pipe kl at time t under temperature loss conditions; T t env H represents the ambient temperature at time t. kl,t Let C be the temperature loss coefficient of pipe kl at time t. P Let λ be the specific heat capacity of water. kl Let kl be the thermal conductivity coefficient of the pipe.

[0066] Then regarding the IES optimized scheduling model:

[0067] The research object of this disclosed technical solution is the electric-gas-heat (IES), which includes conventional thermal power units, wind power generation systems, gas-fired CHP, GT, and EB. The latter three types of equipment are used as energy coupling units. Gas-fired CHP and EB are responsible for supplying heat energy, while GT assists thermal power units in peak power regulation. Simultaneously, electric and thermal energy storage devices are installed to absorb fluctuating resources and limit the thermal output of CHP units during periods of severe wind curtailment.

[0068] 2.1 Objective Function

[0069] The technical solution disclosed herein aims to minimize the overall cost of IES.

[0070] min(F 11 +F 12 +F2+F3) (16)

[0071] In the formula, F 11 For conventional unit start-up and shutdown costs; F 12 F1 is the operating cost of conventional units; F2 is the cost of gas source output; F3 is the cost of wind curtailment.

[0072] 1) Power generation cost of conventional units

[0073] The cost of generating electricity from a conventional unit consists of start-up and shutdown costs and operating costs, expressed as follows:

[0074] F1 = F 11 +F 12 (17)

[0075]

[0076]

[0077] In the formula, This is a power-on variable; 1 indicates power-on, otherwise 0. This is a stop variable; 1 indicates a stop, otherwise 0. on,i S off,i These represent the start-up and shutdown costs of the unit, respectively; P i,t The active power output of conventional unit i at time t; a i b i c i U is the power generation cost coefficient for unit i; i,t N represents the start / stop flag of unit i at time t, where 1 indicates start-up and 0 indicates shutdown; T is the time period, which is set to 24 hours in this study focusing on day-ahead scheduling; N G This refers to the number of conventional generating units.

[0078] 2) Gas source output cost

[0079]

[0080] In the formula, Let be the gas output of gas source s at time t; The cost of gas source s; N GT This represents the number of gas sources.

[0081] 3) Cost of wind curtailment

[0082]

[0083] In the formula, P t wf P t w Let C represent the predicted and actual power output of the wind power system at time t, respectively. w This represents the wind curtailment penalty coefficient.

[0084] 2.2 Power Grid Constraints

[0085] 1) The power balance constraint of the power grid is expressed as:

[0086]

[0087] Pl mn,t =B mn (θ m,t -θ n,t ) (twenty three)

[0088] In the formula, Let be the electrical power of CHP unit i at time t; P represents the electrical power of unit i at time t. t EB P represents the electrical power consumed by EB at time t. t d P t ch P represents the discharge and charging power of the energy storage device at time t, respectively; t Load Let P be the load at time t; mn,t B represents the power flow of line mn at time t; mn Let θ be the admittance of the line mn; m,t Let be the phase angle of node m at time t.

[0089] 2) The unit output constraint is expressed as:

[0090] u i,t P i,min ≤P i,t ≤u i,t P i,max (twenty four)

[0091]

[0092] In the formula, P i,min P i,max These represent the upper and lower limits of the operating power of conventional generating units (i). This represents the upper limit of the operating power of the GT unit i.

[0093] 3) The unit ramp-up constraint is expressed as:

[0094]

[0095] In the formula, These represent the upward and downward ramp rates of conventional unit i, respectively.

[0096] 4) Minimum start-up and shutdown times and start-up / shutdown state constraints for conventional units. The start-up / shutdown state constraints for conventional units are expressed as follows:

[0097]

[0098] 5) The relevant constraints of the energy storage device are expressed as follows:

[0099]

[0100]

[0101]

[0102] In the formula, P t d,max P t ch,max These represent the discharge and charging power of the energy storage device and their corresponding upper limits, respectively. Indicates energy storage discharge and charging indicators; This represents the amount of electricity stored in the energy storage system at time t. Indicates the minimum and maximum amount of electricity that energy storage is allowed to store; Represents the initial and final amounts of energy stored, respectively; η d η ch These represent the energy storage discharge and charging efficiency, respectively.

[0103] 2.3 Gas Network Constraints

[0104] 1) The gas source supplies gas flow to the gas load and coupling equipment through the natural gas network. The upper and lower limits of the gas source supply flow rate are expressed as follows:

[0105]

[0106] In the formula, These represent the upper and lower limits of the airflow supplied by the gas source s, respectively.

[0107] 2) Taking into account the bidirectional nature of gas network flow, the equation describing the relationship between gas network pipeline flow and pressure is:

[0108]

[0109] In the formula, q gh,t Let gh be the average flow rate of pipe at time t. C represents the inflow and outflow of gh at time t, respectively; gh These are the pipe parameters.

[0110] 3) The upper and lower limits of the gas network node pressure are expressed as follows:

[0111]

[0112] In the formula, These represent the upper and lower limits of the pressure at the gas network nodes, respectively.

[0113] 4) The air flow balance constraint is expressed as:

[0114]

[0115] In the formula, Let t be the gas load at time t; The gas consumption of CHP unit i at time t; Let be the gas consumption of GT unit i at time t.

[0116] 5) Constraints in gas pipeline network

[0117] M gh,t =λ gh P gh,t (35)

[0118]

[0119] 2.4 Constraints of the Heating Network

[0120] 1) This paper uses a working fluid flow model to describe the power flow of the heating network, and the relevant constraints are expressed as follows:

[0121]

[0122] In the formula, These represent the outlet temperatures of the water supply and return pipes, respectively. These represent the inlet temperatures of the water supply and return pipes, respectively. These represent the temperatures at node b in the water supply and return pipelines, respectively.

[0123] 2) The heating network balance constraint is expressed as:

[0124]

[0125] In the formula, Let i be the thermal power of CHP unit i at time t; This represents the thermal power of EB at time t. These represent the heat release and heat charge power of the thermal storage tank at time t, respectively. Let t be the heat load at time t.

[0126] 3) The constraints related to the thermal storage tank are expressed as follows:

[0127]

[0128]

[0129]

[0130] In the formula, These represent the heat release and charging power of the thermal storage tank, as well as their respective upper limits. Indicates the heat release and charging status of the thermal storage tank; This represents the amount of electricity stored in the energy storage system at time t. This indicates the minimum and maximum amount of heat that the thermal storage tank is allowed to store; These represent the stored heat at the initial and final moments of the thermal storage tank, respectively; γ d γ ch These represent the heat release and heat charging efficiency of the thermal storage tank, respectively.

[0131] 4) Dynamic characteristics constraints of the heating network

[0132] The dynamic characteristic constraints of the heating network include two parts: transmission delay and temperature loss, expressed as follows:

[0133]

[0134]

[0135]

[0136] 2.5 Coupling Device Constraints

[0137] 1) The energy coupling constraint of the CHP unit is expressed as:

[0138]

[0139] In the formula, λ chp The thermoelectric conversion ratio of the CHP unit is taken as 1.8 in this paper; H GV It has a high calorific value, similar to natural gas.

[0140] 2) The energy coupling constraint of the EB unit is expressed as:

[0141]

[0142] In the formula, λ chp The heating efficiency of EB is taken as 0.95 in this paper.

[0143] 3. Linearized expression of nonlinear objective function and constraints

[0144] 3.1 Linearization of Operating Costs of Traditional Thermal Power Units

[0145] Equation (19) in the above model involves square terms, and Equation (47) gives the linearized representation of the generator set operating cost:

[0146]

[0147] In the formula, m is the number of segments; k i,s The slope of the coal consumption function of thermal power unit i in the s-th segment after segmentation; C 0,i This indicates that thermal power unit i is started up and operating at minimum output P. i,min Runtime costs; The output of thermal power unit i during time period t and segment s.

[0148] Accordingly, the constraints for the operation of thermal power units become:

[0149]

[0150] 3.2 Linearization of the equation relating flow rate and pressure in gas pipeline networks

[0151] Equation (32) in the above model involves square terms, and equations (49)-(53) give its linearization process:

[0152] Assuming the airflow in the pipe flows from node g to node h, introduce variables... make The original equation relating flow rate and pressure in the gas pipeline becomes:

[0153]

[0154] The squared term on the left side of the above formula is approximated by piecewise linearization. When the airflow moves from node g to node h, there is an upper limit value q for the gas flow rate in the pipe. gh If the maximum value is q, then the gas flow rate in the pipeline is [0, q]. gh,max Divide the interval into n equal segments, and let... For the gas flow rate in the pipeline within each segment, the following constraints apply:

[0155]

[0156]

[0157] In the formula, This is used to indicate whether the pipeline gas flow rate falls within the 0-1 range of this segment; To set [0, q gh,max After dividing the pipe into n equal segments, the value of the airflow rate in the l-th segment is... At the same time, let:

[0158]

[0159] The equation relating flow rate and pressure in the gas pipeline network can then be linearized as follows:

[0160]

[0161] In the formula, The slope of the l-th segment after segmental linearization of the gas flow rate in the natural gas pipeline.

[0162] Case Analysis

[0163] The feasibility and effectiveness of the proposed method were verified through simulation analysis on a single integrated electric-gas-thermal energy testing system. All simulation analyses were performed on a mobile workstation configured with an Intel Core i7-10700 processor (2.90GHz) and 16GB of RAM, using the CPLEX 12.6 solver in Matlab 2016a optimization software to solve the optimization problems. Unless otherwise specified, the parameters in the simulation analyses were set as follows: the maximum charging and discharging power of the electric energy storage device was 200MW, the maximum capacity was set to 700MW, the initial capacity was set to 300MW, and the charging and discharging efficiencies were both set to 0.95. The maximum charging and discharging power of the thermal storage tank was 300MW, the maximum capacity was set to 800MW, the initial capacity was set to 560MW, and the charging and discharging efficiencies were both set to 0.90. The initial pipeline storage of the natural gas network was set to 2 × 10⁻⁶ m³ / h. 6 m 3 The cost coefficient for wind curtailment is set at $50 / (MW·h).

[0164] Introduction to the Electric-Gas-Heat Integrated Energy Testing System

[0165] The topology of the integrated electric-gas-heat energy testing system is shown below. Figure 1 It consists of a modified IEEE 39-node power grid system, a 6-node natural gas network system, and an 8-node heating network system.

[0166] The relevant parameters of the natural gas system are shown in Table 1, and the relevant parameters of the heating system are shown in Table 2.

[0167] Table 1 Natural Gas System Pipeline Parameters

[0168]

[0169] Table 2 Heating System Piping Parameters

[0170]

[0171] The relevant parameters of traditional thermal power units are shown in Table 3, and the relevant parameters of combined heat and power units, gas turbines and electric boilers are shown in Table 4.

[0172] Table 3 Parameter Table for Thermal Power Units

[0173]

[0174] Table 4 Energy Coupling Equipment Parameter Table

[0175]

[0176]

[0177] 4.2 Unit Combination Analysis Considering Network Dynamic Characteristics

[0178] To analyze the impact of network dynamics on unit combination, the unit start-up and shutdown decision results before and after considering network dynamics were statistically analyzed, such as... Figure 2 As shown.

[0179] Depend on Figure 2 As a result, regardless of whether dynamic characteristics are considered, G1 and G6 remain operational due to their lower marginal costs; G3 remains shut down because its marginal cost is too high compared to the other units. Without considering dynamic characteristics, G2 operates from 10:00 to 18:00, G4 from 8:00 to 20:00, and G5 from 11:00 to 14:00. At other times, G2, G4, and G5 are shut down. This is because the midday period is peak electricity consumption, and G2, G4, and G5 operate to meet demand. However, when network dynamic characteristics are taken into account, the dynamic conversion efficiency of electricity, gas, and heat increases, and the coupling is deepened. During the midday period, the energy stored in the natural gas pipeline network can be released through gas turbines, converting natural gas into electricity to support grid power demand, causing G5 to be out of operation from 1:00 to 24:00. The delay effect of the heating network transmission mitigated and delayed the impact of load fluctuations on the IES (Enhanced Energy Systems), and the commissioning of the thermal storage tanks alleviated the heating pressure during peak nighttime heating periods, shifting the operating hours of G2 to 3:00-5:00. Meanwhile, G4 units, with lower marginal costs compared to G2 and G5, maintained the same start-stop status as before considering network dynamics.

[0180] By comparing the start-up and shutdown results under the two operating conditions, it can be concluded that, considering the dynamic characteristics of the network, the number of start-ups and shutdowns of conventional units is reduced, the unit operating time is optimized, and the cost increase caused by frequent start-ups and shutdowns of some conventional units is reduced. The energy conversion of electricity, gas, and heat energy at different times improves the operational flexibility of the system.

[0181] System operation optimization result analysis

[0182] Simulations were performed to obtain the power balance and thermal balance relationships considering the network dynamics, and the results are as follows: Figure 3 , Figure 4 As shown.

[0183] Depend on Figure 3 During periods of low load, the energy storage device absorbs excess wind power, reducing wind curtailment. During peak load periods, taking into account the dynamic characteristics of the network, excess energy in the heating and gas networks is converted into electrical energy. This is manifested in the combined heat and power units and gas turbines working in conjunction with conventional thermal power units, while the energy storage device releases electrical energy to meet load demand.

[0184] Depend on Figure 4 Nighttime is peak heating season. During this period, the heating network, thermal storage tanks, and electric boilers work in conjunction with the combined heat and power (CHP) units to meet the heat load demand. During off-peak hours, the electric boilers stop operating, and the thermal storage tanks absorb excess heat, improving the system's operational flexibility.

[0185] The overall system cost and various sub-costs were calculated before and after taking into account the dynamic characteristics of the network. The results are shown in Table 5.

[0186] Table 2 Cost Comparison Results (Ignoring / Considering Dynamic Characteristics)

[0187]

[0188] As shown in Table 5, considering the dynamic characteristics of the network, the total cost is reduced by approximately 7.34%, with decreases in both unit start-up and shutdown costs and operating costs. This reduces expenses caused by frequent unit start-ups and shutdowns, and deepens the coupling between electricity, gas, and heat energy. Simultaneously, wind curtailment costs decrease by approximately 19.3%, indicating that the proposed method is beneficial for wind power consumption.

[0189] Dynamic optimization effect analysis of integrated electricity-gas-heat energy system

[0190] (1) Analysis of the effect of dynamic characteristic optimization of heating network

[0191] The thermal output curves of the cogeneration unit before and after considering the dynamic characteristics of the heating network were obtained through simulation, and the results are as follows: Figure 5 As shown.

[0192] like Figure 5Model A and Model B represent the CHP heat output with and without considering the dynamic characteristics of the heating network, respectively. Comparing the two curves, when the dynamic characteristics of the heating network are not considered, the CHP heat output tracks the changes in heat load in real time to meet the heat power balance; when the dynamic characteristics of the heating network are considered, the heating network pipeline stores a portion of energy, which can work in conjunction with the CHP unit to cope with peak heat load periods, thus achieving a "heat-driven power generation" mode to a certain extent.

[0193] The changes in wind power output before and after considering the dynamic characteristics of the heating network were analyzed and compared with the predicted wind power values. The results are as follows: Figure 6 As shown.

[0194] Comprehensive analysis Figure 5 , Figure 6 Model A experiences severe wind curtailment between 1:00 and 8:00 and between 20:00 and 24:00. After accounting for pipeline transmission delays, the amount of wind curtailment is significantly reduced. This is because the energy stored in the heating network and the heat release from the thermal storage tanks during peak heating periods reduce the heat output of the CHP units during periods of high wind curtailment, thus saving CHP power generation costs while providing greater capacity for wind power integration.

[0195] (2) Analysis of the effect of optimization of dynamic characteristics of air network

[0196] The gas source output curves before and after considering the dynamic characteristics of the gas network were obtained through simulation, and the results are as follows. Figure 7 As shown.

[0197] like Figure 7 Model C and Model D represent the gas source output before and after considering the dynamic characteristics of the gas network, respectively. Comparing the two curves, since the gas network acts like an energy storage device, it stores energy from 1:00 to 8:00 and releases natural gas from 11:00 to 14:00, allowing the gas turbine to operate and work in conjunction with traditional thermal power units to balance the electrical load.

[0198] Example 2

[0199] The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the above-described method.

[0200] Example 3

[0201] The purpose of this embodiment is to provide a computer-readable storage medium.

[0202] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the above method.

[0203] Example 4

[0204] The purpose of this embodiment is to provide an integrated energy system unit combination system that takes into account the dynamic characteristics of the network, including:

[0205] The model building module is configured to: comprehensively consider the energy production equipment and energy storage equipment in the integrated energy system of electricity, gas and heat, while taking into account the dynamic characteristic equation of network transmission, and construct a unit combination model of the integrated energy system of electricity, gas and heat that takes into account the dynamic characteristics of the network, with the goal of minimizing the overall system cost.

[0206] The constraint determination module is configured to: determine the constraints of the integrated energy system unit combination model that takes into account the dynamic characteristics of the network;

[0207] The solution module is configured to linearize the model using a piecewise linearization method to obtain the unit combination scheme.

[0208] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For detailed implementation methods, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0209] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0210] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for combining generating units in an integrated energy system considering the dynamic characteristics of the network, characterized by: include: Taking into account the energy production and storage equipment in the integrated energy system of electricity, gas, and heat, and considering the dynamic characteristics of network transmission, a unit combination model of the integrated energy system of electricity, gas, and heat, taking into account the network dynamic characteristics, is constructed with the goal of minimizing the overall system cost. This model is expressed as: In the formula, This refers to the start-up and shutdown costs of conventional generating units; This refers to the operating cost of conventional generating units; Cost of power output for gas source; Cost of wind curtailment; In the formula, This is a power-on variable; 1 indicates power-on, otherwise 0. This is a shutdown variable; 1 indicates shutdown, otherwise 0. , These are the start-up and shutdown costs of the generating unit, respectively. The time period is set to 24 hours. This refers to the number of conventional generating units; Determine the constraints of the integrated energy system unit combination model that takes into account the dynamic characteristics of the network; The model is linearized using a piecewise linearization method to obtain the unit combination scheme. The linearized representation of the unit operating cost is as follows: （47） In the formula, m is the number of segments; The slope of the coal consumption function of thermal power unit i in the s-th segment after segmentation; This indicates that thermal power unit i is started up and operating at minimum output. Runtime costs; The output of thermal power unit i during time period t and segment s; The energy production and energy storage equipment includes: conventional thermal power units, wind power generation systems, gas-fired CHP, GT and EB; the latter three types of equipment are used as energy coupling units, gas-fired CHP and EB are responsible for supplying heat energy, and GT assists thermal power units in power peak shaving; at the same time, electric and thermal energy storage devices are set up to absorb fluctuating resources and limit the thermal output of CHP units during periods of severe wind curtailment. The constraints of the integrated energy system unit combination model for electricity, gas, and heat include: grid constraints, natural gas grid constraints, heat grid constraints, and energy conversion equipment constraints. The grid constraints include grid power balance constraints, unit output constraints, unit ramping constraints, minimum start-up and shutdown time and start-up and shutdown state constraints for conventional units, and relevant constraints for electric energy storage devices. Electric and thermal energy storage devices are set up to absorb fluctuating resources and limit the thermal output of CHP units during periods of severe wind curtailment. The relevant constraints of energy storage devices are expressed as follows: （28） （29） （30） In the formula, , These represent the discharge and charging power of the energy storage device and their corresponding upper limits, respectively. , Indicates energy storage discharge and charging indicators; express The amount of electricity stored in the energy storage system at all times; , Indicates the minimum and maximum amount of electricity that energy storage is allowed to store; , These represent the energy levels at the initial and final moments of energy storage, respectively. , These represent the energy storage discharge and charging efficiency, respectively. The constraints related to the thermal storage tank are expressed as follows: （39） （40） （41） In the formula, , These represent the heat release and charging power of the thermal storage tank, as well as their respective upper limits. , Indicates the heat release and charging status of the thermal storage tank; express The amount of electricity stored in the energy storage system at all times; , This indicates the minimum and maximum amount of heat that the thermal storage tank is allowed to store; , These represent the stored heat at the initial and final moments of the thermal storage tank, respectively. , These represent the heat release and heat charging efficiency of the thermal storage tank, respectively.

2. The integrated energy system unit combination method considering network dynamic characteristics as described in claim 1, characterized in that, When constructing a combined unit model of an integrated energy system that incorporates electricity, gas, and heat, taking into account the dynamic characteristics of the network, the node method is used for modeling.

3. The integrated energy system unit combination method considering network dynamic characteristics as described in claim 1, characterized in that, The natural gas network constraints include the gas source supplying gas flow to the gas load and coupling equipment through the natural gas network, the upper and lower limits of the gas source supply flow, the bidirectionality of the gas network flow, the equation describing the relationship between the gas network pipeline flow and pressure, the upper and lower limit constraints of the gas network node pressure, and the gas network flow balance constraints. The heating network constraints include the use of a working fluid flow model to describe the heating network flow, the representation of heating network balance constraints, and the representation of constraints related to the thermal storage tank. The constraints on the energy conversion equipment include the energy coupling constraints of the CHP unit and the representation of the energy coupling constraints of the CHP unit.

4. A combined energy system unit combination system considering network dynamic characteristics, employing the combined energy system unit combination method considering network dynamic characteristics as described in any one of claims 1-3, characterized in that, include: The model building module is configured to: comprehensively consider the energy production equipment and energy storage equipment in the integrated energy system of electricity, gas and heat, while taking into account the dynamic characteristic equation of network transmission, and construct a unit combination model of the integrated energy system of electricity, gas and heat that takes into account the dynamic characteristics of the network, with the goal of minimizing the overall system cost. The constraint determination module is configured to: determine the constraints of the integrated energy system unit combination model that takes into account the dynamic characteristics of the network; The solution module is configured to linearize the model using a piecewise linearization method to obtain the unit combination scheme.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method described in any one of claims 1-3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it performs the steps of the method described in any of claims 1-3 above.

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