Multi-energy distribution network scheduling method and device, electronic equipment and storage medium

Abstract

The invention discloses a multi-energy distribution network scheduling method and device, electronic equipment and a storage medium, and belongs to the technical field of computers. The method comprises the following steps: acquiring an electrical load, a gas load and a thermal load of a user side at a target moment of the multi-energy distribution network; obtaining a scheduling scheme of the multi-energy distribution network according to a scheduling model based on the electrical load, the gas load and the thermal load at the target moment; scheduling the multi-energy distribution network based on the scheduling scheme; wherein the scheduling model takes minimization of the operation cost of the multi-energy distribution network as a target, and takes the requirements of the multi-energy distribution network for responding to the electric load, the gas load and the thermal load of the user side and the requirement for meeting the steady-state transmission of the electric power, the natural gas and the thermal power as constraints. According to the scheduling method of the multi-energy distribution network disclosed by the invention, the operation cost of the multi-energy distribution network can be minimized on the premise of meeting multi-energy requirements and energy steady-state transmission.

Description

Technical Field

[0001] The present application belongs to the field of computer technology, and in particular, relates to a scheduling method, device, electronic device and storage medium for a multi-energy distribution network. Background Art

[0002] With the development of the energy sector, under the concept of energy Internet, the operation of multiple energy sources such as electricity, gas, and heat is realized through multi-energy distribution network scheduling to respond to energy supply demand.

[0003] However, in general, there are multiple mutual couplings in the dispatching process of multiple energy networks such as power grid, heat grid, gas grid, etc. in the multi-energy distribution network. At the same coupling point, gas turbines, gas boilers, ground source heat pumps, power-to-gas equipment and other energy conversion equipment are running at the same time, and multiple energy transmissions are crisscrossed. In such a complex situation, while meeting the multi-energy demand and energy steady-state transmission, the operating cost of the multi-energy distribution network is extremely high. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a scheduling method, device, electronic device and storage medium for a multi-energy distribution network to minimize the operating cost of the multi-energy distribution network while meeting multi-energy demands and energy steady-state transmission.

[0005] In a first aspect, the present application provides a scheduling method for a multi-energy distribution network, the method comprising:

[0006] Obtaining the electric load, gas load and thermal load on the user side of the multi-energy distribution network at a target time;

[0007] Based on the electric load, gas load and thermal load at the target time, according to the scheduling model, obtaining a scheduling plan for the multi-energy distribution network;

[0008] Scheduling the multi-energy distribution network based on the scheduling scheme;

[0009] Among them, the scheduling model aims to minimize the operating cost of the multi-energy distribution network, and is constrained by the multi-energy distribution network's response to the user's side electric load, gas load and thermal load requirements and the satisfaction of steady-state transmission of electricity, natural gas and heat.

[0010] According to the scheduling method of the multi-energy distribution network of the present application, according to the scheduling model aimed at minimizing the operating cost of the multi-energy distribution network, based on the electric load, gas load and thermal load at the target moment of the multi-energy distribution network, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained. At the same time, the scheduling model is constrained by the multi-energy distribution network's response to energy demand and satisfaction of steady-state transmission of energy, so that the scheduling scheme of the multi-energy distribution network obtained based on the electric load, gas load and thermal load at the target moment of the multi-energy distribution network satisfies multi-energy demand and steady-state transmission of energy while minimizing the operating cost of the multi-energy distribution network.

[0011] According to one embodiment of the present application, the operating cost of the multi-energy distribution network includes: the operating cost of the energy conversion equipment included in the multi-energy distribution network, the penalty cost for abandoning wind and solar power, and the interaction cost with the superior energy network; the penalty cost for abandoning wind and solar power is determined based on the abandoned wind and solar power of each node in the multi-energy distribution network at the target time.

[0012] According to one embodiment of the present application, the constraints of the scheduling model include: a first constraint for indicating that the multi-energy distribution network responds to electric load, a second constraint for indicating that the multi-energy distribution network responds to gas load, a third constraint for indicating that the multi-energy distribution network responds to thermal load, a fourth constraint for indicating the steady-state transmission of electric energy in the power network, a fifth constraint for indicating the steady-state transmission of natural gas in the natural gas network, and a sixth constraint for indicating the balance of supply and demand in the thermal network.

[0013] According to one embodiment of the present application, the first constraint condition includes: a condition for indicating that the restriction on electricity usage satisfaction is met, a condition for indicating that the restriction on transferable electric load in any time period is met, a condition for indicating that the total amount of electric load before and after demand response is met, and at least one of the conditions for indicating that the peak-valley electricity price restriction is met.

[0014] According to one embodiment of the present application, the second constraint condition includes: a condition for indicating that the restriction on gas usage satisfaction is met, a condition for indicating that the restriction on transferable gas load in any time period is met, a condition for indicating that the total amount of gas load before and after demand response is met, and at least one of the conditions for indicating that the peak and valley gas price restriction is met.

[0015] According to an embodiment of the present application, the third constraint condition includes: a condition for indicating that an indoor temperature limit of the target building is satisfied after the demand response.

[0016] In a second aspect, the present application provides a scheduling device for a multi-energy distribution network, the device comprising:

[0017] A first acquisition module is used to acquire the electric load, gas load and thermal load on the user side of the multi-energy distribution network at a target time;

[0018] A second acquisition module is used to acquire a scheduling plan of the multi-energy distribution network based on the electric load, gas load and thermal load at the target time according to a scheduling model;

[0019] A scheduling module, used for scheduling the multi-energy distribution network based on the scheduling scheme;

[0020] The scheduling model aims to minimize the operating cost of the multi-energy distribution network, and takes the multi-energy distribution network's response to energy demand and satisfaction of steady-state energy transmission as constraints.

[0021] According to the scheduling device of the multi-energy distribution network of the present application, according to the scheduling model aimed at minimizing the operating cost of the multi-energy distribution network, based on the electric load, gas load and thermal load at the target moment of the multi-energy distribution network, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained. At the same time, the scheduling model is based on the constraints of the multi-energy distribution network's response to energy demand and satisfaction of steady-state transmission of energy, so that the scheduling scheme of the multi-energy distribution network obtained based on the electric load, gas load and thermal load at the target moment of the multi-energy distribution network satisfies multi-energy demand and steady-state transmission of energy while minimizing the operating cost of the multi-energy distribution network.

[0022] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the scheduling method for a multi-energy distribution network as in the first aspect described above is implemented.

[0023] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the scheduling method for a multi-energy distribution network as described in the first aspect above.

[0024] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the scheduling method for a multi-energy distribution network as described in the first aspect above.

[0025] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0027] Figure 1It is a flowchart of a scheduling method for a multi-energy distribution network provided in an embodiment of the present application;

[0028] Figure 2 It is a structural schematic diagram of a scheduling device for a multi-energy distribution network provided in an embodiment of the present application;

[0029] Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0031] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0032] In the following, in combination with the accompanying drawings, the scheduling method for a multi-energy distribution network, the scheduling device for a multi-energy distribution network, the electronic device and the readable storage medium provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

[0033] Among them, the scheduling method of the multi-energy distribution network can be applied to the terminal, and can be specifically executed by the hardware or software in the terminal.

[0034] The terminal includes, but is not limited to, a portable communication device such as a mobile phone or tablet computer with a touch-sensitive surface (e.g., a touch screen display and / or a touch pad). It should also be understood that in some embodiments, the terminal may not be a portable communication device, but a desktop computer with a touch-sensitive surface (e.g., a touch screen display and / or a touch pad).

[0035] In the following various embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse and a joystick.

[0036] The scheduling method for a multi-energy distribution network provided in an embodiment of the present application may be executed by an electronic device or a functional module or functional entity in the electronic device that can implement the scheduling method for a multi-energy distribution network. The electronic devices mentioned in the embodiment of the present application include but are not limited to mobile phones, tablet computers, computers, cameras, and wearable devices. The scheduling method for a multi-energy distribution network provided in an embodiment of the present application is described below using an electronic device as an example of the execution subject.

[0037] like Figure 1 As shown, the scheduling method of the multi-energy distribution network includes: step 110, step 120 and step 130.

[0038] In actual implementation, the scheduling method provided in the embodiment of the present application can be applied to a multi-energy distribution network. The multi-energy distribution network may include multiple nodes. Each node may include multiple energy conversion devices. The scheduling scheme obtained according to the scheduling model can be used to schedule the energy conversion devices of each node in the multi-energy distribution network. The energy conversion device may include at least one of a gas turbine, a gas boiler, a ground source heat pump, and a power-to-gas device, for example, the conversion of gas to electric energy is realized by a gas turbine, and the generated electric energy is transmitted to the power network, the conversion of gas to thermal energy is realized by a gas boiler, and the thermal energy conversion is realized by a ground source heat pump using soil and groundwater, and the generated thermal energy is transmitted to the thermal network, the conversion of electric energy to gas is realized by a power-to-gas device, and the generated gas is stored or used for gas turbines to generate electricity, etc. Specifically, the scheduling scheme obtained according to the scheduling model can be used to schedule the power and interactive flow of energy conversion devices such as gas turbines, gas boilers, ground source heat pumps, and power-to-gas devices.

[0039] Step 110: Obtain the electric load, gas load and thermal load on the user side of the multi-energy distribution network at the target time.

[0040] In actual implementation, the electric load can be the electric demand load on the user side of the multi-energy distribution network at the target time, the gas load can be the gas demand load on the user side of the multi-energy distribution network at the target time, and the thermal load can be the thermal demand load on the user side of the multi-energy distribution network at the target time.

[0041] Step 120: Based on the electric load, gas load and thermal load at the target time, according to the scheduling model, a scheduling plan for the multi-energy distribution network is obtained.

[0042] In actual implementation, the scheduling model can be used to determine the scheduling scheme of the multi-energy distribution network based on the electric load, gas load and thermal load of the multi-energy distribution network at any time; the any time can be the target time in step 120, and the scheduling scheme of the multi-energy distribution network can be a scheduling scheme that can minimize the operating cost of the energy conversion equipment included in the multi-energy distribution network while meeting the energy demand of the multi-energy distribution network and meeting the steady-state transmission of energy.

[0043] In actual implementation, the scheduling scheme obtained according to the scheduling model can be used to schedule a complex multi-energy system centered on the power subsystem and coupled with at least one of the natural gas subsystem and the thermal subsystem. The scheduling model aims to minimize the operating cost of the multi-energy distribution network, and is constrained by the multi-energy distribution network's response to the user's side's electric load, gas load and thermal load requirements and the satisfaction of steady-state transmission of electricity, natural gas and heat. Among them, the operating cost of the multi-energy distribution network may include at least one of the operating cost of the energy conversion equipment included in the multi-energy distribution network, the penalty cost of wind and solar abandonment, and the interaction cost with the upper-level energy network. Among them, the interaction cost with the upper-level energy network may include at least one of the interaction cost with the upper-level power grid and the interaction cost with the upper-level gas grid. Specifically, the dispatch model can minimize the operating cost of the energy conversion equipment included in the multi-energy distribution network as a goal, the dispatch model can also minimize the penalty cost of wind and solar power abandonment as a goal, the dispatch model can also minimize the interaction cost with the upper energy network as a goal, and the dispatch model can also minimize the sum of the operating cost of the energy conversion equipment included in the multi-energy distribution network, the penalty cost of wind and solar power abandonment, and the interaction cost with the upper energy network as a goal. For a complex multi-energy system centered on the power subsystem and coupled with at least one of the natural gas subsystem and the thermal subsystem, the actual conditions of different coupling nodes in the complex multi-energy system are different, and the operating cost of the multi-energy distribution network is also different. For example, the first coupling node is a coupling node between the power subsystem and the natural gas subsystem, and a gas turbine and a power-to-gas device are operated at the first coupling node; the second coupling node is a coupling node between the power subsystem, the natural gas subsystem, and the thermal subsystem, and a gas turbine, a gas boiler, a ground source heat pump, and a power-to-gas device are operated at the second coupling node. The operating cost of the multi-energy distribution network at the first coupling point is different from the operating cost of the multi-energy distribution network at the second coupling point.

[0044] In actual execution, the scheduling model may also include constraints. After obtaining the electric load, gas load and thermal load of the multi-energy distribution network at the target time, the target power data may be obtained based on the constraints in the scheduling model. The constraints may include constraints on the demand for energy response of the multi-energy distribution network and the steady-state transmission of energy. The target power data may be power data that meets the requirements for the multi-energy distribution network to respond to energy and the steady-state transmission of energy. In addition, the target cost data of the multi-energy distribution network may be preset in the scheduling model. After obtaining the target power data, the operating cost of the multi-energy distribution network may be calculated based on the target cost data and the target power data.

[0045] In actual implementation, the constraints in the dispatch model may include at least one of a first constraint indicating that the multi-energy distribution network responds to electric loads, a second constraint indicating that the multi-energy distribution network responds to gas loads, a third constraint indicating that the multi-energy distribution network responds to thermal loads, a fourth constraint indicating steady-state transmission of electric energy in the power network, a fifth constraint indicating steady-state transmission of natural gas in the natural gas network, and a sixth constraint indicating the balance of supply and demand in the thermal network. Among them, the constraints in the dispatch model can realize the constraints on the dispatch model in terms of the multi-energy distribution network responding to energy demands and satisfying steady-state transmission of energy. Specifically, the constraints on the dispatch model in terms of the multi-energy distribution network responding to energy demands can be realized based on at least one of the first constraint, the second constraint, and the third constraint, and the constraints on the dispatch model in terms of steady-state transmission of energy can be realized based on at least one of the fourth constraint, the fifth constraint, and the sixth constraint.

[0046] In actual implementation, the target optimization algorithm can be used to optimize the scheduling model to achieve a more optimized multi-energy distribution network scheduling scheme obtained according to the scheduling model. The target optimization algorithm may include at least one of the common optimization algorithms in the field such as the beetle beard algorithm and the particle swarm algorithm, and this application does not specifically limit this.

[0047] Step 130: Schedule the multi-energy distribution network based on the scheduling plan.

[0048] In actual implementation, after obtaining the scheduling plan, the power output, natural gas output and heat output of each node in the multi-energy distribution network can be adjusted based on the scheduling plan.

[0049] According to the scheduling method of the multi-energy distribution network of the present application, according to the scheduling model aimed at minimizing the operating cost of the multi-energy distribution network, based on the electric load, gas load and thermal load at the target moment of the multi-energy distribution network, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained. At the same time, the scheduling model is constrained by the multi-energy distribution network's response to energy demand and satisfaction of steady-state transmission of energy, so that the scheduling scheme of the multi-energy distribution network obtained based on the electric load, gas load and thermal load at the target moment of the multi-energy distribution network satisfies multi-energy demand and steady-state transmission of energy while minimizing the operating cost of the multi-energy distribution network.

[0050] In some embodiments, the operating cost of the multi-energy distribution network includes: the operating cost of the energy conversion equipment included in the multi-energy distribution network, the penalty cost for wind and solar power abandonment, and the interaction cost with the superior energy network; the penalty cost for wind and solar power abandonment is determined based on the wind and solar power abandonment of each node in the multi-energy distribution network at the target time.

[0051] In actual implementation, for a complex multi-energy system centered on the power subsystem and coupled with at least one of the natural gas subsystem and thermal subsystem, in the process of obtaining the dispatching plan of the multi-energy distribution network according to the dispatching model, in order to improve the carrying capacity of the complex multi-energy system and ensure the economic efficiency of the multi-energy distribution network operation, the operating cost of the multi-energy distribution network can be calculated. The operating cost of the multi-energy distribution network can be expressed by the following formula:

[0052]

[0053] In formula (1), F is the operating cost of the multi-energy distribution network, is the operating cost of the energy conversion equipment, is the penalty cost for curtailing wind and solar power, C E is the interaction cost with the upper grid, C NG is the interaction cost with the parent gas network.

[0054] In formula (1), the operating cost of energy conversion equipment is It can be calculated as follows:

[0055]

[0056] Among them, T is the optimization scheduling period; represents the unit operating cost of the energy conversion equipment at node n, N GT Indicates the number of gas turbines, N GB Indicates the number of gas boilers, N HP Indicates the number of ground source heat pumps, N P2G Indicates the number of power-to-gas devices, Represents the power of the energy conversion device at node n at time t.

[0057] In formula (1), the penalty cost for abandoning wind and solar power is It can be calculated as follows:

[0058]

[0059] in, represents the unit penalty cost of distributed renewable energy at node n; is the abandoned wind and solar power of distributed renewable energy at node n at time t.

[0060] In formula (1), the interaction cost C with the upper grid is E It can be calculated as follows:

[0061]

[0062] in, represents the unit interaction cost with the upper grid, Represents the interaction power with the upper-level power grid at time t.

[0063] In formula (1), the interaction cost C with the upper-level gas network is NG It can be calculated as follows:

[0064]

[0065] in, represents the unit interaction cost with the parent gas network, Represents the interactive flow with the upper gas network, N Gw Indicates the number of gas source nodes in the natural gas subsystem.

[0066] According to the scheduling method of a multi-energy distribution network of the present application, the operating cost of the multi-energy distribution network is calculated based on the operating cost of the energy conversion equipment included in the multi-energy distribution network, the penalty cost of wind and solar power abandonment, and the interaction cost with the superior energy network, so as to obtain a scheduling plan for the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network based on a scheduling model with the goal of minimizing the operating cost of the multi-energy distribution network, so that the scheduling plan of the multi-energy distribution network can meet the multi-energy demand and steady-state energy transmission while minimizing the operating cost of the multi-energy distribution network.

[0067] In some embodiments, the constraints of the scheduling model include: a first constraint for indicating that the multi-energy distribution network responds to electric load, a second constraint for indicating that the multi-energy distribution network responds to gas load, a third constraint for indicating that the multi-energy distribution network responds to thermal load, a fourth constraint for indicating the steady-state transmission of electric energy in the power network, a fifth constraint for indicating the steady-state transmission of natural gas in the natural gas network, and a sixth constraint for indicating the balance of supply and demand in the thermal network.

[0068] In actual implementation, the scheduling model can be constrained in terms of the multi-energy distribution network responding to energy demand based on at least one of the first constraint, the second constraint, and the third constraint, and the scheduling model can be constrained in terms of steady-state transmission of energy based on at least one of the fourth constraint, the fifth constraint, and the sixth constraint. Multi-energy distribution network responding to energy demand is one of the measures for load-side resources such as electricity, heat, and gas to participate in the optimal scheduling of complex multi-energy systems. Taking the electricity-gas-heat multi-energy distribution network as an example, considering user satisfaction and comfort, taking the multi-energy distribution network responding to energy demand as one of the constraints of the scheduling model can effectively give play to the dispatchable potential of load-side resources.

[0069] According to the scheduling method of the multi-energy distribution network of the present application, based on the scheduling model constrained by multiple constraints, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained, so that the scheduling scheme of the multi-energy distribution network can meet the multi-energy demand and steady-state transmission of energy while minimizing the operating cost of the multi-energy distribution network.

[0070] In some embodiments, the first constraint condition may include at least one of a condition for indicating that the restriction on electricity consumption satisfaction is met, a condition for indicating that the restriction on transferable electric load in any time period is met, a condition for indicating that the total amount of electric load before and after demand response is met, and a condition for indicating that the peak-valley electricity price restriction is met.

[0071] In the actual implementation process, the demand response electric load may be a transferable load, and the first constraint condition for indicating the multi-energy distribution network response electric load may be constructed based on the following formula:

[0072]

[0073] In the formula, χ US To improve the user's satisfaction with electricity usage, Indicates the minimum limit of satisfaction with electricity consumption mode, represents the change in demand response load at power network node n at time t, N represents the maximum limit of the transferred load at the power network node n at time t, ON represents the total number of power network nodes, represents the power load after demand response at power network node n at time t, represents the electric load before demand response at power network node n at time t, represents the peak electricity price after demand response, represents the valley value of electricity price after demand response, k E,mib represents the quantitative relationship of valley electricity price, k E,max Represents the quantitative relationship of valley electricity prices.

[0074] In actual implementation, the first constraint condition may include a condition for indicating that the restriction on the satisfaction of the electricity consumption mode is met, a condition for indicating that the restriction on the transferable electric load in any time period is met, a condition for indicating that the total amount of electric load before and after the demand response is met, and a condition for indicating that the peak-valley electricity price restriction is met. The first constraint condition may be constructed based on the following formulas:

[0075]

[0076] Among them, formula (10) can be used to construct the conditions that meet the restrictions on electricity consumption satisfaction, formula (11) can be used to construct the conditions that meet the restrictions on the transferable electricity load in any period of time, formula (12) can be used to construct the conditions that meet the total amount of electricity load before and after demand response, and formula (13) can be used to construct the conditions that meet the peak and valley electricity price restrictions.

[0077] In actual implementation, time-of-use electricity prices are introduced for incentives. The relationship between electricity loads before and after the demand response for satisfactory electricity consumption can be expressed by the following formula:

[0078]

[0079] In the formula, represents the power load after demand response at power network node n at time t, represents the electric load before demand response at power network node n at time t, N represents the change in demand response load at power network node n at time t, PN represents the total number of power network nodes, χ US is the user's satisfaction with electricity usage, E is the electricity price elasticity coefficient, represents the electricity price before demand response at time t, Represents the change in electricity price in response to demand at time t.

[0080] According to the scheduling method of the multi-energy distribution network of the present application, based on the scheduling model constrained by the first constraint condition, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained, so that the scheduling scheme of the multi-energy distribution network can meet the multi-energy demand and steady-state transmission of energy while minimizing the operating cost of the multi-energy distribution network.

[0081] In some embodiments, the second constraint condition includes: a condition for indicating that the restriction on gas usage satisfaction is met, a condition for indicating that the restriction on transferable gas load in any time period is met, a condition for indicating that the total amount of gas load before and after demand response is met, and at least one of the conditions for indicating that the peak and valley gas price restriction is met.

[0082] In the actual implementation process, the demand response gas load may be a transferable load, and the second constraint condition for indicating the multi-energy distribution network response gas load may be constructed based on the following formula:

[0083]

[0084] In the formula, γ US Indicates the user's satisfaction with gas usage. Indicates the minimum limit of gas usage satisfaction. represents the gas load change at the natural gas network node n at time t, represents the maximum limit of the transferred electric load at the natural gas network node n at time t, N GN represents the total number of gas network nodes, represents the gas load after demand response at natural gas network node n at time t, represents the gas load before demand response at natural gas network node n at time t, represents the peak gas price after demand response, represents the valley value of gas price after demand response, k G,min The quantitative relationship that characterizes valley gas prices and the quantitative relationship that characterizes peak gas prices.

[0085] In actual implementation, the second constraint condition may include a condition for indicating that the gas usage mode satisfaction limit is met, a condition for indicating that the gas load limit that can be transferred in any period is met, a condition for indicating that the total gas load limit before and after the demand response is met, and a condition for indicating that the peak and valley gas price limit is met. The second constraint condition may be constructed based on the following formulas:

[0086]

[0087] Among them, formula (21) can be used to construct the conditions for satisfying the gas usage mode satisfaction limit, formula (22) can be used to construct the conditions for satisfying the gas load limit that can be transferred in any time period, formula (23) can be used to construct the conditions for satisfying the total gas load limit before and after demand response, and formula (24) can be used to construct the conditions for satisfying the peak and valley gas price limit.

[0088] In the actual implementation process, the gas load relationship before and after the gas demand response is satisfactory can be expressed by the following formula:

[0089]

[0090] In the formula, represents the gas load after demand response at natural gas network node n at time t, represents the gas load before demand response at natural gas network node n at time t, represents the gas load change at the natural gas network node n at time t, γ US Indicates the user's satisfaction with gas usage, N GN represents the total number of nodes in the natural gas network, λ G is the gas price elasticity coefficient, represents the gas price before demand response at time t, Represents the change in gas price in response to demand at time t.

[0091] According to the scheduling method of the multi-energy distribution network of the present application, based on the scheduling model constrained by the second constraint condition, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained, so that the scheduling scheme of the multi-energy distribution network can meet the multi-energy demand and steady-state energy transmission while minimizing the operating cost of the multi-energy distribution network.

[0092] In some embodiments, the third constraint condition includes: a condition for indicating that an indoor temperature limit of the target building after the demand response is met.

[0093] In the actual implementation process, the third constraint condition for indicating the multi-energy distribution network response to thermal load can be constructed based on the following formula:

[0094]

[0095] In the formula, Indicates the upper limit of the user's heating comfort temperature. Indicates the lower limit of the user's heating comfort temperature. represents the temperature inside the building at time t.

[0096] In the actual implementation process, the heat load can be the heating load. Since the human body's perception of the external temperature is somewhat fuzzy, the indoor temperature of the building changes within a certain range to ensure the heating comfort of the user. The relationship between the heat load and the indoor temperature after the user's heating comfort demand response can be expressed by the following formula:

[0097]

[0098] In the formula, N represents the heat load after demand response at the heat network node n at time t; HU represents the number of heating users, Represents the basic load data at the thermal network node n, represents the temperature inside the building at time t, represents the temperature inside the building at time t+1, represents the temperature outside the building at time t, R B represents the equivalent thermal resistance of the building, C represents the heat capacity of air, N TN Indicates the total number of thermal network nodes.

[0099] According to the scheduling method of the multi-energy distribution network of the present application, based on the scheduling model constrained by the third constraint condition, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained, so that the scheduling scheme of the multi-energy distribution network can meet the multi-energy demand and steady-state energy transmission while minimizing the operating cost of the multi-energy distribution network.

[0100] In some embodiments, electric energy is transmitted at the speed of light, and its generation, transmission, and use are simultaneous. The power flow equation is usually used to describe the distribution of electric energy in the network. The fourth constraint condition can be constructed based on the mathematical model of the radial distribution network of the Distflow branch power flow theory. The mathematical model of the radial distribution network of the Distflow branch power flow theory can be based on the following formula:

[0101]

[0102]

[0103] Where T(n) represents the set of first nodes of the branch with node n as the last node, P mn,t represents the active power flowing from node m to node n in the power network at time t, R mn represents the active impedance of the power network branch mn, Q mn,t represents the reactive power flowing from node m to node n in the power network at time t, U m,t represents the voltage amplitude of the power network node m at time t, P nk,t represents the active power flowing from node n to node k in the power network at time t, P n,t represents the net injected active power of power network node n at time t, X mn represents the reactive impedance of the power network branch mn, Q nk,t represents the reactive power flowing from node n to node k in the power network at time t, Q n,t represents the net reactive power injected by node n of the power network at time t, φ(n) represents the set of branch end nodes with node n as the first node, and U n,t Represents the voltage amplitude of power network node n at time t.

[0104] According to the scheduling method of the multi-energy distribution network of the present application, based on the scheduling model constrained by the fourth constraint condition, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained, so that the scheduling scheme of the multi-energy distribution network can meet the multi-energy demand and steady-state transmission of energy while minimizing the operating cost of the multi-energy distribution network.

[0105] In the actual implementation process, the fifth constraint condition for indicating the steady-state transmission of natural gas in the natural gas network can be constructed based on the following formula:

[0106]

[0107] In the formula, ρ(n) represents the set of first nodes of the pipeline with node n as the last node, represents the natural gas flow rate transmitted by the natural gas pipeline in at time t, They represent the set of pipeline end nodes with node n as the first node, represents the natural gas flow rate transmitted by the natural gas pipeline nk at time t, represents the net injection flow of natural gas network node n at time t, represents the gas load after demand response at natural gas network node n at time t, represents the natural gas flow rate of the gas turbine (GT) equipment connected to the natural gas network node n at time t, represents the natural gas flow rate of the gas boiler (GB) equipment connected to the natural gas network node n at time t, represents the natural gas flow rate of the power to gas (P2G) device connected to the natural gas network node n at time t, Indicates the interaction flow with the upper-level gas network.

[0108] In actual implementation, the transmission speed of natural gas is relatively slow, and the transmission direction of natural gas is from the end of the pipeline with high gas pressure to the end of the pipeline with low gas pressure. The inflow and outflow of natural gas at each node are equal. The relationship between the pipeline flow rate of the gas network and the gas pressure at the nodes at both ends of the pipeline can be described with the help of the Weymouth equation, as shown below:

[0109]

[0110] In the formula, represents the natural gas flow rate transmitted by the natural gas pipeline in at time t, is the Weymouth characteristic parameter of the pipeline, that is, a constant related to factors such as the radius, length, and gas density of the natural gas pipeline. sgn() is a sign function that can return the positive or negative value of the parameter. If the parameter is positive, it returns 1, and if the parameter is negative, it returns -1.

[0111] According to the scheduling method of the multi-energy distribution network of the present application, based on the scheduling model constrained by the fifth constraint condition, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained, so that the scheduling scheme of the multi-energy distribution network can meet the multi-energy demand and steady-state transmission of energy while minimizing the operating cost of the multi-energy distribution network.

[0112] In actual implementation, the sixth constraint condition for indicating the balance between supply and demand of the heat network can be constructed based on the following formula:

[0113]

[0114] In the formula, represents the heat load after demand response at the heating network node n at time t, represents the charging power of the heat storage device, Indicates the heat release power of the heat storage device, N HS represents the total number of heat storage devices, represents the heating power of the cooling machine at node n at time t, N GT represents the number of gas turbines, represents the heating power of the gas boiler at node n at time t, N GB Indicates the number of gas boilers, represents the heating power of the ground source heat pump at node n at time t, N HP Indicates the number of ground source heat pumps.

[0115] In actual implementation, the thermal network generally uses steam or hot water as the medium to achieve energy transmission. The thermal network model usually includes a thermal model and a hydraulic model. The matrix H of the thermal model L,DR The form can be described by the following formula:

[0116] H L,DR =C w m w (T SP -T RE )(38);

[0117]

[0118] ∑m GO T GO =∑m CO T CO (40);

[0119]

[0120] In the formula, H L,DR The matrix representing the thermal model, C w represents the specific heat capacity of water, m w represents the thermal network node injection flow matrix, T SP represents the water supply temperature matrix of the thermal network node, T RE Represents the return water temperature matrix of the thermal network node, T FI Indicates the temperature at the head end of the thermal network pipeline, T OUT represents the building outdoor temperature matrix, T ST represents the terminal temperature of the thermal network pipe, η H represents the heat transfer coefficient, m GO represents the pipeline flow matrix flowing into the thermal network node, m CO represents the pipeline flow matrix out of the thermal network node, T GO Represents the hot water temperature matrix flowing into the thermal network node, T CO represents the hot water temperature matrix flowing out of the thermal network node, is the upper and lower limits of the temperature of the water supply temperature matrix of the thermal network node, is the lower limit of the temperature of the water supply temperature matrix of the thermal network node, is the lower limit of the temperature of the return water temperature matrix of the heat network nodes, is the lower limit of the temperature of the return water temperature matrix of the heat network nodes.

[0121] The matrix of the hydraulic model can be described by the following formula:

[0122] B 1 ·m = m W (42);

[0123] B 2 ·h f = 0 (43).

[0124] In the formula, B 1 represents the network incidence matrix, that is, the heat network node - pipeline incidence matrix, m is the flow velocity of each pipeline, and m w represents the heat network node injection flow matrix, B 2 represents the loop incidence matrix, and h f represents the head loss.

[0125] In actual implementation, the sixth constraint condition can be constructed according to the thermal model and the hydraulic model.

[0126] According to the scheduling method of the multi - energy distribution network of the present application, based on the scheduling model with the sixth constraint condition, a scheduling scheme of the multi - energy distribution network that minimizes the operating cost of the multi - energy distribution network is obtained, so that the scheduling scheme of the multi - energy distribution network meets the multi - energy demand and energy steady - state transmission while minimizing the operating cost of the multi - energy distribution network.

[0127] In the embodiment of the present application, the execution subject of the scheduling method of the multi - energy distribution network can be a scheduling device of the multi - energy distribution network. In the embodiment of the present application, taking the scheduling device of the multi - energy distribution network executing the scheduling method of the multi - energy distribution network as an example, the scheduling device of the multi - energy distribution network provided by the embodiment of the present application is described.

[0128] As Figure 2 shown, the scheduling device of the multi - energy distribution network includes: a first acquisition module 210, a second acquisition module 220, and a scheduling module 230, where,

[0129] The first acquisition module 210 is configured to acquire the electrical load, gas load, and thermal load on the user side at the target moment of the multi - energy distribution network;

[0130] The second acquisition module 220 is configured to obtain a scheduling scheme of the multi - energy distribution network based on the electrical load, gas load, and thermal load at the target moment according to the scheduling model;

[0131] The scheduling module 230 is configured to schedule the multi - energy distribution network based on the scheduling scheme;

[0132] Among them, the scheduling model aims to minimize the operating cost of the multi-energy distribution network, and is constrained by the multi-energy distribution network's response to users' demands for electric load, gas load and thermal load and the satisfaction of steady-state transmission of electricity, natural gas and heat.

[0133] According to the scheduling device of the multi-energy distribution network of the present application, according to the scheduling model aimed at minimizing the operating cost of the multi-energy distribution network, based on the electric load, gas load and thermal load at the target moment of the multi-energy distribution network, a scheduling scheme of the multi-energy distribution network that minimizes the operating cost of the multi-energy distribution network is obtained. At the same time, the scheduling model is based on the constraints of the multi-energy distribution network's response to energy demand and satisfaction of steady-state transmission of energy, so that the scheduling scheme of the multi-energy distribution network obtained based on the electric load, gas load and thermal load at the target moment of the multi-energy distribution network satisfies multi-energy demand and steady-state transmission of energy while minimizing the operating cost of the multi-energy distribution network.

[0134] In some embodiments, the operating cost of a multi-energy distribution network includes: the operating cost of the energy conversion equipment included in the multi-energy distribution network, the penalty cost for abandoning wind and solar power, and the interaction cost with the superior energy network; the penalty cost for abandoning wind and solar power is determined based on the abandoned wind and solar power power of each node in the multi-energy distribution network at the target time.

[0135] In some embodiments, the constraints of the scheduling model include: a first constraint for indicating that the multi-energy distribution network responds to electric load, a second constraint for indicating that the multi-energy distribution network responds to gas load, a third constraint for indicating that the multi-energy distribution network responds to thermal load, a fourth constraint for indicating the steady-state transmission of electric energy in the power network, a fifth constraint for indicating the steady-state transmission of natural gas in the natural gas network, and a sixth constraint for indicating the balance of supply and demand in the thermal network.

[0136] In some embodiments, the first constraint condition includes: a condition for indicating that the restriction on electricity usage satisfaction is met, a condition for indicating that the restriction on transferable electric load in any time period is met, a condition for indicating that the total amount of electric load before and after demand response is met, and at least one of the conditions for indicating that the peak and valley electricity price restriction is met.

[0137] In some embodiments, the second constraint condition includes: a condition for indicating that the restriction on gas usage satisfaction is met, a condition for indicating that the restriction on transferable gas load in any time period is met, a condition for indicating that the total amount of gas load before and after demand response is met, and at least one of the conditions for indicating that the peak and valley gas price restriction is met.

[0138] In some embodiments, the third constraint condition includes: a condition for indicating that an indoor temperature limit of the target building after the demand response is met.

[0139] The dispatching device of the multi-energy distribution network in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or it can be other devices other than the terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0140] The scheduling device of the multi-energy distribution network in the embodiment of the present application may be a device having an operating system. The operating system may be a Microsoft (Windows) operating system, an Android (Android) operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0141] The multi-energy distribution network scheduling device 200 provided in the embodiment of the present application can achieve Figure 1 To avoid repetition, the various processes implemented by the method embodiment are not described here.

[0142] In some embodiments, Figure 3 As shown, an embodiment of the present application also provides an electronic device 300, including a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the program is executed by the processor 301, each process of the above-mentioned multi-energy distribution network scheduling method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0143] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0144] An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned multi-energy distribution network scheduling method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0145] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0146] An embodiment of the present application also provides a computer program product, including a computer program, which implements the above-mentioned scheduling method for the multi-energy distribution network when executed by a processor.

[0147] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0148] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned multi-energy distribution network scheduling method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0149] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0150] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0151] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0152] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0153] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0154] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A scheduling method for a multi-energy distribution network, characterized in that: include: Obtaining the electric load, gas load and thermal load on the user side of the multi-energy distribution network at a target time; Based on the electric load, gas load and thermal load at the target time, according to the scheduling model, obtaining a scheduling plan for the multi-energy distribution network; Scheduling the multi-energy distribution network based on the scheduling scheme; Among them, the scheduling model aims to minimize the operating cost of the multi-energy distribution network, and is constrained by the multi-energy distribution network's response to the user's side's electric load, gas load and thermal load requirements and the satisfaction of steady-state transmission of electricity, natural gas and heat.

2. The method for dispatching a multi-energy distribution network according to claim 1, characterized in that: The operating cost of the multi-energy distribution network includes: the operating cost of the energy conversion equipment included in the multi-energy distribution network, the penalty cost for abandoning wind and solar power, and the interaction cost with the superior energy network; the penalty cost for abandoning wind and solar power is determined based on the abandoned wind and solar power of each node in the multi-energy distribution network at the target time.

3. The method for dispatching a multi-energy distribution network according to claim 1, characterized in that: The constraints of the scheduling model include: a first constraint for indicating that the multi-energy distribution network responds to electric load, a second constraint for indicating that the multi-energy distribution network responds to gas load, a third constraint for indicating that the multi-energy distribution network responds to thermal load, a fourth constraint for indicating the steady-state transmission of electric energy in the power network, a fifth constraint for indicating the steady-state transmission of natural gas in the natural gas network, and a sixth constraint for indicating the balance of supply and demand in the thermal network.

4. The method for dispatching a multi-energy distribution network according to claim 3, characterized in that: The first constraint condition includes: At least one of the conditions for indicating that restrictions on electricity usage satisfaction are met, the conditions for indicating that restrictions on transferable electricity loads during any period of time are met, the conditions for indicating that restrictions on the total amount of electricity loads before and after demand response are met, and the conditions for indicating that restrictions on peak and valley electricity prices are met.

5. The method for dispatching a multi-energy distribution network according to claim 3, characterized in that: The second constraint condition includes: At least one of the conditions for indicating that the gas usage satisfaction restriction is met, the conditions for indicating that the gas load transferable restriction is met during any period of time, the conditions for indicating that the total gas load restriction before and after demand response is met, and the conditions for indicating that the peak and valley gas price restriction is met.

6. The method for dispatching a multi-energy distribution network according to claim 3, characterized in that: The third constraint condition includes: a condition for indicating that an indoor temperature limit of the target building after the demand response is met.

7. A dispatching device for a multi-energy distribution network, characterized in that: include: A first acquisition module is used to acquire the electric load, gas load and thermal load on the user side of the multi-energy distribution network at a target time; A second acquisition module is used to acquire a scheduling plan of the multi-energy distribution network based on the electric load, gas load and thermal load at the target time according to a scheduling model; A scheduling module, used for scheduling the multi-energy distribution network based on the scheduling scheme; The scheduling model aims to minimize the operating cost of the multi-energy distribution network, and takes the multi-energy distribution network's response to energy demand and satisfaction of steady-state energy transmission as constraints.

8. An electronic 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, the scheduling method for the multi-energy distribution network as described in any one of claims 1-6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the scheduling method for a multi-energy distribution network as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the scheduling method for a multi-energy distribution network as described in any one of claims 1 to 6 is implemented.

Images