User-Side Integrated Energy System Dispatch Method and System Based on Multi-Function Information Fusion

Abstract

A user-side integrated energy system scheduling method and system based on multi-source information fusion is proposed. A day-ahead operation model is constructed using the day-ahead operation objective function and the operation constraints of the integrated energy system. The day-ahead operation objective function, which minimizes both electricity and heat costs for users, is used as the monthly operation objective function. The upper and lower limits of load adjustment in user load adjustment constraints are corrected using downlink channel operation state variables, while the upper and lower limits of power output adjustment in equipment unit output constraints are also corrected. The joint operation constraints of the power grid and heating network are corrected based on the maintenance plan of the user-side integrated energy system. A monthly operation model is constructed using the monthly operation objective function, the corrected joint operation constraints of the power grid and heating network, the corrected equipment unit output constraints, energy storage equipment operation constraints, and the corrected user load adjustment constraints. The optimal solution of the monthly operation model is used as the user-side integrated energy system scheduling scheme to improve user participation.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy systems, specifically, it relates to a day-ahead and monthly scheduling method and system for a user-side integrated energy system based on multi-source information fusion. Background Technology

[0002] Traditional integrated energy systems primarily rely on physical equipment, neglecting the influence of communication networks and social factors. However, as social factors increasingly impact energy systems, integrated energy systems require the assistance of social sciences to analyze influencing factors such as energy trading, policy mechanisms, and user behavior. Therefore, it is necessary to integrate diverse information from physical systems, information networks, and social factors to serve the operation of integrated energy systems.

[0003] In existing technologies, most integrated energy system scheduling methods are based on optimization using a single energy form or limited energy data, lacking the integration of diverse information. One user-side integrated energy utilization optimization interval planning method and system, while considering the coupling relationships of multiple energy forms, fails to fully integrate diverse information such as user behavior and environmental factors, resulting in insufficient adaptability and flexibility of the scheduling scheme. Most existing methods fail to adequately consider real-time data changes during optimization scheduling, leading to insufficient real-time and dynamic nature of the scheduling scheme. One integrated energy system optimization scheduling method, however, fails to respond promptly to real-time data changes in practical applications, affecting system operating efficiency. Furthermore, existing technologies exhibit low user participation, failing to fully mobilize user enthusiasm and impacting the overall optimization effect of the system. While an integrated energy system optimization operation method considering user demand response introduces a demand response mechanism, user participation remains limited, failing to fully leverage the role of users in system optimization. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a user-side integrated energy system scheduling method and system based on multi-source information fusion. This addresses the problem of insufficient information fusion in existing technologies, effectively reducing system operating costs while simplifying interaction with the upper-level power grid. It also solves the problem of poor real-time performance in existing technologies, enabling high-precision load forecasting and control. Furthermore, it addresses the problem of low user participation in existing technologies, optimizing the scheduling scheme of the user-side integrated energy system, improving operational capabilities, and enhancing user participation through incentive mechanisms and user feedback. This fully leverages the role of users in system optimization, achieving overall system optimization.

[0005] The present invention adopts the following technical solution.

[0006] This invention proposes a user-side integrated energy system scheduling method based on multi-source information fusion, comprising:

[0007] The day-ahead operating objective function is to maximize the operator's revenue. The day-ahead operating model of the user-side integrated energy system is constructed based on the day-ahead operating objective function and the operating constraints of the integrated energy system. The operating constraints include: joint operation constraints of the power grid and heating network, power output constraints of equipment units, operation constraints of energy storage equipment, and user load adjustment constraints.

[0008] Based on the day-ahead operation model, and according to the user's historical load data, the day-ahead operation objective function that minimizes both the user's electricity cost and heating cost is used as the monthly operation objective function.

[0009] Set the operating status variables of the downlink channel for the operator to transmit information to users; use the operating status variables of the downlink channel to correct the upper and lower limits of the load adjustment amount in the user load adjustment amount constraint, and at the same time correct the upper and lower limits of the output adjustment amount in the equipment unit output constraint.

[0010] Based on the maintenance plan for the user-side integrated energy system, the constraints on the joint operation of the power grid and heating network are revised;

[0011] A monthly operation model of the user-side integrated energy system is constructed using the monthly operation objective function, the modified joint operation constraints of the power grid and heating network, the modified power output constraints of the equipment units, the operation constraints of the energy storage equipment, and the modified user load adjustment constraints. The optimal solution of the monthly operation model is used as the scheduling scheme of the user-side integrated energy system.

[0012] Preferably, the objective function is run to satisfy the following relationship:

[0013] f = max(-C) g -C adj -C cur -C wgd +C ur,e +C ur,h )

[0014] In the formula, f is the objective function for the current day's operation, and C... g For unit operating costs, C adj To adjust energy costs, C cur For the cost of abandoning new energy sources, C wgd For external electricity purchase costs, C ur,e C represents the revenue generated by users' electricity consumption for the operator. ur,h The revenue generated by users' use of heat for operators.

[0015] Preferably, the constraints for the joint operation of the power grid and the heating network satisfy the following relationship:

[0016]

[0017] In the formula, P j,tLet A be the output of the unit connected to node j at time t. G P is the set of units connected to a node. hj,t For the current flow of branch hj at time t, A F and A E Let j be the set of nodes corresponding to the route with node j as the starting and ending point, respectively. and Let D be the upper and lower bounds of the power flow of branch hj at time t, respectively. j,t Let θ be the power load demand of node j at time t. j,t Let be the voltage phase angle at node j at time t. These are the upper and lower limits of the voltage phase angle at node j, respectively.

[0018] Preferably, the output constraint of the equipment unit satisfies the following relationship:

[0019]

[0020] In the formula, P n,i,t Let n be the output of node i at time t. and P represents the lower and upper limits of the output of device n at node i at time t. n,i,d and P n,i,u Let P be the lower and upper limits of the ramp power for node i and device n, respectively. n,i,t -P n,i,t-1 This is the output adjustment amount for node i and device n.

[0021] Preferably, the operating constraints of the energy storage device satisfy the following relationship:

[0022]

[0023] In the formula, S i,t S represents the total energy stored at time t for energy storage i. i,in,t Let S be the storage power of energy storage i at time t. i,out,t Let S be the power released by energy storage i at time t. i,min and S i,max Let λ be the lower and upper limits of the total energy storage capacity of energy storage i, respectively. i,t Let S be the state variable of energy storage i at time t, where 0 represents charging and 1 represents discharging. i,in,max S is the upper limit of the storage power of energy storage i at time t. i,out,max Let i be the upper limit of the power released from the stored energy i at time t.

[0024] Preferably, the user load adjustment constraint satisfies the following relationship:

[0025]

[0026] In the formula, load adj,i,t Let load be the load adjustment amount of node i at time t. adj,i,t,min Let load be the lower limit of the load adjustment amount when the load of node i is adjusted downward at time t. adj,i,t,max Let be the upper limit of the load adjustment amount when node i adjusts its load upwards at time t. This indicates that the load adjustment remains balanced throughout the entire time period, where T is the total number of time periods.

[0027] Preferably, historical load data of users under different energy packages is obtained, and electricity and heating costs of users under different energy packages are determined based on the day-ahead operation model;

[0028] The monthly load plan for users is based on the energy package with the lowest electricity and heating costs.

[0029] The electricity cost of users is taken as the revenue that users bring to the operator from electricity consumption, and the heating cost of users is taken as the revenue that users bring to the operator from heating consumption. Thus, the day-ahead operating objective function that minimizes both the electricity cost and the heating cost of users is determined as the monthly operating objective function.

[0030] Preferably, the modified user load adjustment constraint and the modified equipment unit output constraint satisfy the following relationship:

[0031]

[0032] In the formula, T down,1i T is the operating state variable of the downlink channel through which the operator transmits information to user i. down,1i A value of 1 indicates that the downlink channel is operating normally, T down,1i A value of 0 indicates that the downlink channel is malfunctioning.

[0033] Preferably,

[0034] In the formula, T down,1i T is the operating state variable of the downlink channel through which the operator transmits information to user i. down,1i A value of 1 indicates that the downlink channel is operating normally, T down,1i A value of 0 indicates that the downlink channel is malfunctioning.

[0035] Preferably, the constraints for the joint operation of the power grid and the heating network satisfy the following relationship:

[0036]

[0037] In the formula, t1, t2, ..., t n S is the maintenance time for equipment i. i Let P be the set of maintenance times for equipment i, and let P be the output of equipment during maintenance time. i,t It is 0.

[0038] This invention also proposes a user-side integrated energy system scheduling system based on multi-source information fusion, comprising:

[0039] The day-ahead scheduling module is used to construct a day-ahead operation model of the user-side integrated energy system with the objective function of maximizing operator revenue and the operation constraints of the integrated energy system. The operation constraints include: joint operation constraints of the power grid and heating network, power output constraints of equipment units, operation constraints of energy storage equipment, and user load adjustment constraints.

[0040] The multi-source information fusion module is used to, based on the day-ahead operation model and according to the user's historical load data, use the day-ahead operation objective function that minimizes both the user's electricity and heating costs as the monthly operation objective function; set the operation status variables of the downlink channel for the operator to transmit information to the user; use the operation status variables of the downlink channel to correct the upper and lower limits of the load adjustment amount in the user load adjustment amount constraint, and at the same time correct the upper and lower limits of the output adjustment amount in the equipment unit output constraint; and correct the joint operation constraints of the power grid and heating network according to the maintenance plan of the user-side integrated energy system.

[0041] The monthly scheduling module is used to construct a monthly operation model of the user-side integrated energy system based on the monthly operation objective function, the modified joint operation constraints of the power grid and heating network, the modified equipment unit output constraints, the energy storage equipment operation constraints, and the modified user load adjustment constraints; the optimal solution of the monthly operation model is used as the scheduling scheme of the user-side integrated energy system.

[0042] The present invention is also a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the method.

[0043] The present invention is also a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0044] The beneficial effects of this invention, compared with the prior art, include at least the following: This invention addresses the phenomenon of changes in the state of multiple information sources during the scheduling of integrated energy systems on the user side. It establishes day-ahead and monthly scheduling models, based on energy consumption forecasting, considering user load response, communication network failures, and equipment maintenance plans. It analyzes the role of multiple information sources in integrated energy system scheduling, providing a new solution for the formulation of integrated energy system scheduling plans, achieving safe and stable energy supply for integrated energy systems, and ensuring the economic and environmental protection of system operation. Day-ahead scheduling of integrated energy systems improves operational efficiency by incorporating user load adjustment mechanisms, while monthly scheduling enhances operational capabilities by considering changes in the characteristics of multiple information sources. Attached Figure Description

[0045] Figure 1 This is a flowchart of the user-side integrated energy system scheduling method based on multi-source information fusion proposed in this invention;

[0046] Figure 2 This is a diagram of the integrated energy system network model used in the embodiments of the present invention;

[0047] Figure 3 This is a diagram of the integrated energy system interaction scheme of Scheme 1 designed in the embodiments of the present invention;

[0048] Figure 4 This is a diagram of the integrated energy system interaction scheme of Scheme 2 designed in this embodiment of the invention;

[0049] Figure 5 This is a diagram of an energy storage scheduling scheme considering the impact of communication networks in an embodiment of the present invention;

[0050] Figure 6 This is a diagram of a power dispatching scheme considering the impact of communication networks in an embodiment of the present invention;

[0051] Figure 7 This is a diagram of an interaction scheme considering the impact of communication networks in an embodiment of the present invention. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0053] This invention proposes a user-side integrated energy system scheduling method based on multi-source information fusion, such as... Figure 1 As shown, it includes:

[0054] Step 1: Take the maximization of operator revenue as the day-ahead operating objective function, and construct the day-ahead operating model of the user-side integrated energy system based on the day-ahead operating objective function and the operating constraints of the integrated energy system. The operating constraints include: joint operation constraints of the power grid and heating network, power output constraints of equipment units, operation constraints of energy storage equipment, and user load adjustment constraints.

[0055] Specifically, in the day-ahead operation model of the user-side integrated energy system, the objective function for day-ahead operation is to maximize the operator's revenue, satisfying the following relationship:

[0056] f = max(-C) g -C adj -C cur -Cwgd +C ur,e +C ur,h )

[0057] In the formula, f is the objective function for the current day's operation, and C... g For unit operating costs, C adj To adjust energy costs, C cur For the cost of abandoning new energy sources, C wgd For external electricity purchase costs, C ur,e C represents the revenue generated by users' electricity consumption for the operator. ur,h The revenue that users generate for operators from heating;

[0058] in,

[0059]

[0060] In the formula, p g,t V represents the purchase price of natural gas for the gas turbine unit at time t. g,t Let P be the amount of natural gas purchased at time t. i,t Let λ be the output power of thermal power unit i at time t. i p is the proportion of maintenance costs for thermal power unit i. adj,t Let δ be the compensation unit price at time t. adj,t Let P be the adjustment ratio at time t. adj,t p is the adjustable amount of user load at time t. cur,t δ is the abandonment penalty coefficient. t P represents the abandonment rate. re,t p is the available active power output at time t. wgd,t Let P be the electricity price level at time t. wgd,t For the amount of electricity purchased at time t, p ur,e,t Let P be the user's electricity package price at time t. ur,e,t Let p be the user's electricity consumption at time t. ur,h For users' heating package pricing, P ur,h,t Let I represent the heat consumption of users at time t, where T is the total number of time periods and I is the total number of thermal power units.

[0061] Meanwhile, the day-ahead operation model of the user-side integrated energy system meets the operational constraints of the integrated energy system, including: joint operation constraints of the power grid and heating network, power output constraints of equipment units, operation constraints of energy storage equipment, and user load adjustment constraints.

[0062] In this embodiment, the operational constraints of the integrated energy system consist of network, equipment, and user components. The network component includes power grid operation constraints and heating network operation constraints. Network operation is limited by the physical model and involves energy losses, while heating network operation is affected by the environment, exhibiting a coupling relationship between the heating network and temperature, as shown in the interaction model. The equipment component includes constraints such as equipment output ramp-up, reflecting the limitations of the physical model. The user component allows for load transfer, with the transfer ratio determined by the user interaction model in the social layer.

[0063] The constraints for the joint operation of the power grid and the heating network satisfy the following relationship:

[0064]

[0065] In the formula, P j,t Let A be the output of the unit connected to node j at time t. G P is the set of units connected to a node. hj,t For the current flow of branch hj at time t, A F and A E Let j be the set of nodes corresponding to the route with node j as the starting and ending point, respectively. and Let D be the upper and lower bounds of the power flow of branch hj at time t, respectively. j,t Let θ be the power load demand of node j at time t. j,t Let be the voltage phase angle at node j at time t. These are the upper and lower limits of the voltage phase angle at node j, respectively.

[0066] The power output constraints of the equipment unit satisfy the following relationship:

[0067]

[0068] In the formula, P n,i,t Let n be the output of node i at time t. and P represents the lower and upper limits of the output of device n at node i at time t. n,i,d and P n,i,u Let P be the lower and upper limits of the ramp power for node i and device n, respectively. n,i,t -P n,i,t-1 This is the output adjustment amount for node i and device n.

[0069] The operating constraints of energy storage devices satisfy the following relationship:

[0070]

[0071] In the formula, S i,t S represents the total energy stored at time t for energy storage i. i,in,t Let S be the storage power of energy storage i at time t.i,out,t Let S be the power released by energy storage i at time t. i,min and S i,max Let λ be the lower and upper limits of the total energy storage capacity of energy storage i, respectively. i,t Let S be the state variable of energy storage i at time t, where 0 represents charging and 1 represents discharging. i,in,max S is the upper limit of the storage power of energy storage i at time t. i,out,max Let i be the upper limit of the power released from the stored energy i at time t.

[0072] The user load adjustment constraint satisfies the following relationship:

[0073]

[0074] In the formula, load adj,i,t Let load be the load adjustment amount of node i at time t. adj,i,t,min Let load be the lower limit of the load adjustment amount when the load of node i is adjusted downward at time t. adj,i,t,max Let be the upper limit of the load adjustment amount when node i adjusts its load upwards at time t. This indicates that the load adjustment remains balanced throughout the entire time period, where T is the total number of time periods.

[0075] In constructing a multi-information fusion-based user-side integrated energy system model, this invention actually performs steady-state modeling of the physical layer, information layer, and social layer separately. The user-side integrated energy system operation model includes a day-ahead operation model and a monthly operation model. In the day-ahead operation model, the environment in which the integrated energy system operates remains unchanged, and the load of the integrated energy system can be obtained from the short-term forecast model; solving the day-ahead scheduling model yields the scheduling scheme. In the monthly scheduling model, due to the larger time span, the environment in which the integrated energy system operates changes. At the social level, the user load within the integrated energy system needs to be adjusted based on short-term forecasts and user response patterns. At the information level, communication networks between operators, users, and equipment may experience failures, requiring the development of scheduling schemes for equipment and user disconnection according to the interaction model. At the physical level, due to equipment maintenance plans, operators need to respond in advance.

[0076] In this embodiment, the physical layer model of the user-side integrated energy system focuses on the system's operating status and assesses and senses the state of electrical, thermal, and gas energy flows within the system; the information layer model of the user-side integrated energy system connects to the communication channel through an interface to achieve information interaction; and the social layer model of the user-side integrated energy system establishes an interaction model between users and equipment, analyzing users' energy consumption patterns and intentions from multiple dimensions.

[0077] Step 2: Based on the day-ahead operation model, and according to the user's historical load data, the day-ahead operation objective function with the minimum electricity and heating costs for the user is used as the monthly operation objective function; set the operation status variables of the downlink channel for the operator to transmit information to the user; use the operation status variables of the downlink channel to correct the upper and lower limits of the load adjustment amount in the user load adjustment amount constraint, and at the same time correct the upper and lower limits of the output adjustment amount in the equipment unit output constraint; and correct the joint operation constraints of the power grid and heating network according to the maintenance plan of the user-side integrated energy system.

[0078] Based on the existing day-ahead operating model, a monthly operating model for the integrated energy system is established. By introducing changes in multi-dimensional information states, the operating strategies of the integrated energy system during long-term operation are discussed. At the social level, monthly changes in user energy packages are considered, and data mining is used to recommend the lowest-cost energy option to users. At the information level, temporary communication network failures or congestion for users and equipment are considered, and the operating scenarios and remedial scheduling schemes for the integrated energy system are studied. At the physical level, equipment maintenance plans are considered, and the operating scheme of the integrated energy system after some equipment is disconnected from the system is analyzed. After considering changes in multi-dimensional information states, the monthly plan for the integrated energy system is calculated and formulated by solving the operating model to cope with possible changes during the month.

[0079] Specifically, step 2 includes:

[0080] Step 2.1: Based on the day-ahead operation model, and according to the user's historical load data, the day-ahead operation objective function that minimizes both the user's electricity cost and heating cost is used as the monthly operation objective function;

[0081] In this embodiment, based on historical load data of users under different energy packages and a day-ahead operating model, the user's electricity and heating costs are determined. Relying on smart metering technology experiments, the types of electricity packages for users are set as shown in Table 1. In the first year, the user's electricity price is the same at all times, and no electricity package is used. In the second year, users are randomly assigned packages, including four types: A, B, C, and D. Each package includes three electricity price types, corresponding to the early morning, evening, and other time periods, respectively. The "other types" refer to users who are not assigned a normal package. The energy price in the packages is proportionally converted according to the electricity price levels of different provinces in China. Finally, the energy packages need to be expanded and converted to an electricity price curve that is consistent with the load curve.

[0082] Table 1 Types of Electricity Packages

[0083]

[0084] A comprehensive energy system operation strategy considering user load response: Based on user load response patterns and historical load data analysis, user plan matching is analyzed to provide users with plan change recommendations. User load changes under various plan change schemes are substituted into the day-ahead operation model to calculate user energy costs, i.e., the operator's user energy revenue. The plan with the lowest user energy cost is selected as the user's monthly load plan; the user energy cost satisfies the following relationship:

[0085]

[0086] In the formula, C k Let p be the energy cost for a user under the k-th energy package. k,t and P k,t C represents the unit price and energy consumption under the k-th energy package, respectively. M The package plan represents the lowest energy cost for users, with Tc being the final recommended package plan.

[0087] Step 2.2: Set the operating status variables of the downlink channel for the operator to transmit information to the user; use the operating status variables of the downlink channel to correct the upper and lower limits of the load adjustment amount in the user load adjustment amount constraint, and at the same time correct the upper and lower limits of the output adjustment amount in the equipment unit output constraint.

[0088] Strategies for Integrated Energy Systems Considering Communication Network Failures: During long-term operation, integrated energy systems may experience communication network failures or congestion, making it difficult for some devices or users to communicate directly with the operator. In such cases, the integrated energy system needs to adjust its scheduling scheme based on the type of failure, and constraints need to be added to the load and equipment sections of the model.

[0089] Therefore, the revised user load adjustment constraint satisfies the following relationship:

[0090]

[0091] The revised equipment unit output constraints satisfy the following relationship:

[0092]

[0093] In the formula, T down,1i T is the operating state variable of the downlink channel through which the operator transmits information to user i. down,1i A value of 1 indicates that the downlink channel is operating normally, T down,1i A value of 0 indicates that the downlink channel is malfunctioning.

[0094] Step 2.3: Based on the maintenance plan for the user-side integrated energy system, modify the constraints on the joint operation of the power grid and heating network;

[0095] Integrated energy system adjustment strategy considering equipment maintenance plans: During long-term operation of the integrated energy system, some equipment may be under maintenance and cannot be put into operation according to the system's scheduling plan. Therefore, it is necessary to adjust the operation plan and add the following constraints to the model:

[0096]

[0097] In the formula, t1, t2, ..., t n S is the maintenance time for equipment i. i Let P be the set of maintenance times for equipment i, and let P be the output of equipment during maintenance time. i,t It is 0.

[0098] Step 3: Construct a monthly operation model for the user-side integrated energy system using the monthly operation objective function, the modified joint operation constraints of the power grid and heating network, the modified power output constraints of the equipment units, the operation constraints of the energy storage equipment, and the modified user load adjustment constraints; the optimal solution of the monthly operation model is used as the scheduling scheme for the user-side integrated energy system.

[0099] The integrated energy system operation model designed in this invention is divided into two types: a day-ahead scheduling model and a monthly scheduling model. In the day-ahead scheduling model, the environment in which the integrated energy system operates remains unchanged, and the load of the integrated energy system can be obtained from the short-term forecast model. After solving the operation model, the scheduling scheme can be obtained. In the monthly scheduling model, because the time span is large, the environment in which the integrated energy system operates will change. At the social level, the user load within the integrated energy system needs to be adjusted based on the short-term forecast and user response patterns. At the information level, communication networks between operators, users, and equipment may fail, requiring the development of a scheduling scheme after equipment and user disconnection according to the interaction model. At the physical level, due to the impact of equipment maintenance plans, operators need to respond in advance.

[0100] This invention also proposes a user-side integrated energy system scheduling system based on multi-source information fusion, comprising:

[0101] The day-ahead scheduling module is used to construct a day-ahead operation model of the user-side integrated energy system with the objective function of maximizing operator revenue and the operation constraints of the integrated energy system. The operation constraints include: joint operation constraints of the power grid and heating network, power output constraints of equipment units, operation constraints of energy storage equipment, and user load adjustment constraints.

[0102] The multi-source information fusion module is used to, based on the day-ahead operation model and according to the user's historical load data, use the day-ahead operation objective function that minimizes both the user's electricity and heating costs as the monthly operation objective function; set the operation status variables of the downlink channel for the operator to transmit information to the user; use the operation status variables of the downlink channel to correct the upper and lower limits of the load adjustment amount in the user load adjustment amount constraint, and at the same time correct the upper and lower limits of the output adjustment amount in the equipment unit output constraint; and correct the joint operation constraints of the power grid and heating network according to the maintenance plan of the user-side integrated energy system.

[0103] The monthly scheduling module is used to construct a monthly operation model of the user-side integrated energy system based on the monthly operation objective function, the modified joint operation constraints of the power grid and heating network, the modified equipment unit output constraints, the energy storage equipment operation constraints, and the modified user load adjustment constraints; the optimal solution of the monthly operation model is used as the scheduling scheme of the user-side integrated energy system.

[0104] In a user-side integrated energy system, photovoltaic and wind power equipment embody the physical layer and form the foundation of the system; interfaces and communication networks represent the information layer, enabling interaction between equipment, users, and operators; and users represent the social layer. In this multi-information integrated energy system, users determine their electricity and heat load curves based on weather and price factors. Photovoltaic and wind power determine their grid-connected electricity volume based on weather conditions and grid demand. Gas-fired power units determine their electricity and heat supply based on natural gas prices and grid demand. Electric thermal storage develops its operating plan based on relevant policies and network demand. Electric boilers determine their heat supply based on electricity prices and heat load demand. Ultimately, the above decision-making information is uniformly adjusted by the integrated energy system operator. Based on the overall system load demand and the status of the external energy network, a final dispatch plan is determined to provide energy services to users within the system, dispatch plans for equipment within the system, and a power purchase curve for the external grid, serving as a node for the system.

[0105] This invention uses the proposed method to conduct power system dispatch experiments, with a case study based on Lianmin Village in Shanghai. The electric and heat load levels are obtained from actual project data, and missing data is filled in using information from experiments on smart metering technology for electricity. Finally, a user-side integrated electric and heat energy system is adopted, consisting of a modified IEEE 33-node distribution network and a 6-node heating network, as shown below. Figure 2 As shown.

[0106] The integrated energy system in the example includes photovoltaic, gas turbine, waste heat boiler, gas boiler, photovoltaic, electric boiler, ground source heat pump, electric thermal energy storage and other equipment. The equipment parameters are shown in Table 1.

[0107] Table 1 Equipment Parameters of Integrated Energy System

[0108] Parameter name numerical values Parameter name numerical values gas turbine 1000kW electric boiler 400kW Power generation efficiency 0.4 Heat production efficiency 0.9 Waste heat boiler 1350kW Electric energy storage 250kWh Heat production efficiency 0.54 Discharge power 80kW Gas boiler 500kW Charging power 100kW Heat production efficiency 0.95 Thermal energy storage 200kWh Photovoltaics 100kW Heat dissipation power 100kW Ground source heat pump 50kW thermal storage capacity 100kW Thermoelectric ratio 3.5 Natural gas prices <![CDATA[3 yuan / m 3 >

[0109] Based on this, comprehensive energy system scheduling optimization is carried out. During the scheduling process, the following two schemes are designed depending on whether the predicted user load is considered to participate in the regulation.

[0110] Option 1: During the scheduling process, user load adjustment interactions are not considered, and the predicted load is the actual load level participating in the scheduling.

[0111] Option 2: During the scheduling process, user load adjustment interaction is considered. The load of each node includes some household appliances as transferable load. According to user electricity consumption statistics, the working time of these appliances is between 16:00 and 22:00, and they can be transferred to other time periods in proportion.

[0112] Figure 3 and Figure 4 This diagram illustrates two integrated energy system interaction schemes. During daily dispatch, the integrated energy system needs to purchase electricity from the upper-level power grid and gas from the gas company. Scheme 2 allows for load adjustment among users. As shown in the diagram, the gas purchase volume of this integrated energy system is relatively stable, while the electricity purchase volume under Scheme 1 fluctuates significantly, posing certain dispatching difficulties when interacting with the upper-level power grid. Under Scheme 2, the electricity purchase curve is concentrated in a few time periods, with relatively smaller peak fluctuations, reducing the difficulty of interaction. User load adjustment mainly involves shifting evening loads to the early morning and morning, utilizing electricity price differences and combined heat and power (CHP) to reduce energy costs. This not only increases the revenue of the integrated energy operator but also provides subsidies to users, effectively improving the operational efficiency of the integrated energy system.

[0113] Table 2 shows the operating costs of the integrated energy system. Scheme 1 represents the normal operating state where user load cannot be adjusted, while Scheme 2 represents the high-efficiency operating state where user load can be adjusted. Scheme 2 shows lower user energy costs and higher daily operating revenue for the operator, indicating that the integrated energy system achieves a win-win situation. It can be considered that introducing a user load adjustment mechanism is beneficial to both the integrated energy system operator and users. The operator can improve the system's operating efficiency by adjusting the load and the conversion relationship between gas, electricity, and heat, thereby increasing its own revenue while reducing users' energy costs.

[0114] Table 2 Operating Costs of Integrated Energy Systems

[0115]

[0116] Communication networks are a crucial link in the information factors of integrated energy systems, affecting the interaction between operators, equipment, and users. Therefore, simulating communication disruptions in user load adjustment and energy storage dispatch can help analyze the extent to which integrated energy systems are affected by communication networks.

[0117] In the monthly dispatch plan, the communication network may fail on a certain day. Therefore, based on the above scheme 2, it is assumed that the communication between the energy storage and the user at node 16 fails on that day, the downlink channel is blocked, and the dispatch signal from the integrated energy system operator cannot be received. At this time, the energy storage operates according to the peak-valley price difference, and the user load does not change.

[0118] like Figure 5 , Figure 6 and Figure 7 The diagram shows the monthly scheduling scheme in case of communication network failure, including energy storage scheduling, power scheduling, and interactive schemes.

[0119] Communication systems can impact the scheduling of integrated energy systems, but the system can maintain normal operation when the fault range is small, indicating its strong anti-interference capability. In specific scheduling schemes, the operator's energy purchase curve shows a significant increase, indicating that the system's dependence on external systems increases after internal communication is disrupted. During equipment operation, energy storage, being outside the control of the dispatch system, fully utilizes the peak-valley price difference to increase local revenue through charging and discharging, but this does not align with the overall revenue of the integrated energy system. This demonstrates that the communication network can avoid local optima and ensure global optima.

[0120] Table 3 shows the operating costs of the integrated energy system. Scenario 1 represents the system under normal operating conditions, while Scenario 2 represents a failure in the system's communication network. When communication is disrupted, users and equipment can only operate according to predetermined strategies, limiting the formulation of scheduling plans.

[0121] Table 3 Operating Costs under Different Information Factors

[0122]

[0123] As can be seen, the system can maintain stable operation even when individual nodes experience problems. This is because the present invention establishes an independent behavioral interaction model for each device and user. When devices and users cannot receive scheduling arrangements from the operator, they can arrange scheduling schemes according to their own needs. Although the final scheme may not reach the global optimum, it can reduce the impact of faults on the system and is conducive to the stability and security of the integrated energy system.

[0124] This invention considers the changing characteristics of multi-dimensional information in user-side integrated energy systems during operation, requiring operators to adjust operational strategies according to different scenarios. First, a day-ahead operational model of the integrated energy system is constructed, including the operator's revenue function and operational constraints. Then, considering user load response, communication network failures, and equipment maintenance plans, a monthly operational model of the integrated energy system is proposed, demonstrating the value of multi-dimensional information fusion modeling. Under this multi-dimensional information fusion framework, integrated energy system operators formulate scheduling plans based on load forecasting results, consider user load response patterns and interactions with users, modify user packages and scheduling schemes, and fully utilize the multi-dimensional data of the integrated energy system to achieve safe and stable energy supply, ensuring the economic and environmental protection of system operation. Finally, a numerical example verifies the effectiveness of the proposed day-ahead and monthly scheduling methods for user-side integrated energy systems based on multi-dimensional information fusion.

[0125] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0126] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0127] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0128] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A user-side integrated energy system scheduling method based on multi-source information fusion, characterized in that, include: The day-ahead operating objective function is to maximize the operator's revenue. The day-ahead operating model of the user-side integrated energy system is constructed based on the day-ahead operating objective function and the operating constraints of the integrated energy system. The operating constraints include: joint operation constraints of the power grid and heating network, power output constraints of equipment units, operation constraints of energy storage equipment, and user load adjustment constraints. Based on the day-ahead operation model, and according to the user's historical load data, the day-ahead operation objective function that minimizes both the user's electricity cost and heating cost is used as the monthly operation objective function. Set the operating status variables of the downlink channel for the operator to transmit information to users; use the operating status variables of the downlink channel to correct the upper and lower limits of the load adjustment amount in the user load adjustment amount constraint, and at the same time correct the upper and lower limits of the output adjustment amount in the equipment unit output constraint. The revised user load adjustment constraints and the revised equipment unit output constraints satisfy the following relationship: In the formula, load adj,i,t Let T be the load adjustment amount of node i at time t. down,1i T is the operating state variable of the downlink channel through which the operator transmits information to user i. down,1i A value of 1 indicates that the downlink channel is operating normally, T down,1i A value of 0 indicates that the downlink channel is malfunctioning; load adj,i,t,min load adj,i,t,max These are the lower and upper limits of the load adjustment amount when node i adjusts its load downwards at time t, respectively, and T is the total number of time periods; In the formula, P n,i,t Let n be the output of node i at time t. and P represents the lower and upper limits of the output of device n at node i at time t. n,i,d and P n,i,u Let P be the lower and upper limits of the ramp power for node i and device n, respectively. n,i,t -P n,i,t-1 The output adjustment amount for node i and device n; Based on the maintenance plan for the user-side integrated energy system, the constraints on the joint operation of the power grid and heating network are revised; The constraints for the joint operation of the power grid and the heating network satisfy the following relationship: In the formula, t1, t2, ..., t n S is the maintenance time for equipment i. i Let P be the set of maintenance times for equipment i, and let P be the output of equipment during maintenance time. i,t =0; P j,t Let A be the output of the unit connected to node j at time t. G P is the set of units connected to a node. hj,t For the current flow of branch hj at time t, A F and A E Let j be the set of nodes corresponding to the route with node j as the starting and ending point, respectively. and Let D be the upper and lower bounds of the power flow of branch hj at time t, respectively. j,t Let θ be the power load demand of node j at time t. j,t Let be the voltage phase angle at node j at time t. These are the upper and lower limits of the voltage phase angle at node j, respectively; A monthly operation model of the user-side integrated energy system is constructed using the monthly operation objective function, the modified joint operation constraints of the power grid and heating network, the modified power output constraints of the equipment units, the operation constraints of the energy storage equipment, and the modified user load adjustment constraints. The optimal solution of the monthly operation model is used as the scheduling scheme of the user-side integrated energy system.

2. The user-side integrated energy system scheduling method based on multi-source information fusion according to claim 1, characterized in that, The objective function was run recently and the following relationship was satisfied: f=max(-C g -C adj -C cur -C wgd +C ur,e +C ur,h ) In the formula, f is the objective function for the current day's operation, and C... g For unit operating costs, C adj To adjust energy costs, C cur For the cost of abandoning new energy sources, C wgd For external electricity purchase costs, C ur,e C represents the revenue generated by users' electricity consumption for the operator. ur,h The revenue generated by users' use of heat for operators.

3. The user-side integrated energy system scheduling method based on multi-source information fusion according to claim 1, characterized in that, The constraints for the joint operation of the power grid and the heating network satisfy the following relationship: In the formula, P j,t Let A be the output of the unit connected to node j at time t. G P is the set of units connected to a node. hj,t For the current flow of branch hj at time t, A F and A E Let j be the set of nodes corresponding to the route with node j as the starting and ending point, respectively. and Let D be the upper and lower bounds of the power flow of branch hj at time t, respectively. j,t Let θ be the power load demand of node j at time t. j,t Let be the voltage phase angle at node j at time t. These are the upper and lower limits of the voltage phase angle at node j, respectively.

4. The user-side integrated energy system scheduling method based on multi-source information fusion according to claim 1, characterized in that, The power output constraints of the equipment unit satisfy the following relationship: In the formula, P n,i,t Let n be the output of node i at time t. and P represents the lower and upper limits of the output of device n at node i at time t. n,i,d and P n,i,u Let P be the lower and upper limits of the ramp power for node i and device n, respectively. n,i,t -P n,i,t-1 This is the output adjustment amount for node i and device n.

5. The user-side integrated energy system scheduling method based on multi-source information fusion according to claim 1, characterized in that, The operating constraints of energy storage devices satisfy the following relationship: In the formula, S i,t S represents the total energy stored at time t for energy storage i. i,in,t Let S be the storage power of energy storage i at time t. i,out,t Let S be the power released by energy storage i at time t. i,min and S i,max Let λ be the lower and upper limits of the total energy storage capacity of energy storage i, respectively. i,t Let S be the state variable of energy storage i at time t, where 0 represents charging and 1 represents discharging. i,in,max S is the upper limit of the storage power of energy storage i at time t. i,out,max Let i be the upper limit of the power released from the stored energy i at time t.

6. The user-side integrated energy system scheduling method based on multi-source information fusion according to claim 1, characterized in that, The user load adjustment constraint satisfies the following relationship: In the formula, load adj,i,t Let load be the load adjustment amount of node i at time t. adj,i,t,min Let load be the lower limit of the load adjustment amount when the load of node i is adjusted downward at time t. adj,i,t,max Let be the upper limit of the load adjustment amount when node i adjusts its load upwards at time t. This indicates that the load adjustment remains balanced throughout the entire time period, where T is the total number of time periods.

7. The user-side integrated energy system scheduling method based on multi-source information fusion according to claim 2, characterized in that, Obtain historical load data of users under different energy consumption packages, and determine the electricity and heating costs of users under different energy consumption packages based on the day-ahead operation model; The monthly load plan for users is based on the energy package with the lowest electricity and heating costs. The electricity cost of users is taken as the revenue that users bring to the operator from electricity consumption, and the heating cost of users is taken as the revenue that users bring to the operator from heating consumption. Thus, the day-ahead operating objective function that minimizes both the electricity cost and the heating cost of users is determined as the monthly operating objective function.

8. A user-side integrated energy system scheduling system based on multi-source information fusion, used to implement the user-side integrated energy system scheduling method based on multi-source information fusion as described in any one of claims 1 to 7, characterized in that, include: The day-ahead scheduling module is used to construct a day-ahead operation model of the user-side integrated energy system with the objective function of maximizing operator revenue and the operation constraints of the integrated energy system. The operation constraints include: joint operation constraints of the power grid and heating network, power output constraints of equipment units, operation constraints of energy storage equipment, and user load adjustment constraints. The multi-source information fusion module is used to, based on the day-ahead operation model and according to the user's historical load data, use the day-ahead operation objective function that minimizes both the user's electricity and heating costs as the monthly operation objective function; set the operation status variables of the downlink channel for the operator to transmit information to the user; use the operation status variables of the downlink channel to correct the upper and lower limits of the load adjustment amount in the user load adjustment amount constraint, and at the same time correct the upper and lower limits of the output adjustment amount in the equipment unit output constraint; and correct the joint operation constraints of the power grid and heating network according to the maintenance plan of the user-side integrated energy system. The monthly scheduling module is used to construct a monthly operation model of the user-side integrated energy system based on the monthly operation objective function, the modified joint operation constraints of the power grid and heating network, the modified equipment unit output constraints, the energy storage equipment operation constraints, and the modified user load adjustment constraints; the optimal solution of the monthly operation model is used as the scheduling scheme of the user-side integrated energy system.

9. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-7.

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