Power grid energy scheduling method and device, electronic equipment, medium and program product
By constructing an objective function to minimize the operating cost of the power grid and solving the objective function under constraints, the problem of high operating costs and the inability to dispatch renewable energy after the introduction of carbon capture and storage technology is solved, and the power grid is reduced running costs and the effect of improving low-carbon performance.
Patent Information
- Application Number
- CN202411543835.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-31
- Publication Date
- 2025-01-21
AI Technical Summary
After the introduction of carbon capture and storage technology, the power grid operation requires a large amount of operating costs and cannot be dispatched with existing renewable energy sources, resulting in waste of resources and thus increasing the operating costs of the power grid.
Build a target function, the target is the operating cost of minimizing the grid, including the cost of coal -fired units, carbon capture costs, solvent loss costs, operating costs of gas turbines, capacity degradation costs of energy storage systems, power grid interaction costs, and renewable energy dispatching costs Essence Determine the constraints of the target function, including electric power balance constraints, thermal balance constraints, power grid power exchange constraints, coal -fired units operation constraints, gas turbine operation constraints, carbon capture facility solvent storage tanks, constraints of energy storage facilities, and renewable energy reserve constraints Essence Under these constraints, solve the target function, get the result of the minimum operating cost, and dispatch the power grid energy based on the results.
By optimizing the operating costs of the power grid, it can effectively reduce the operating costs of the power grid, avoid resource waste, and improve the low-carbon performance of the power grid.
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Figure CN119340990A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of power grid energy management, and in particular to a power grid energy scheduling method, device, electronic equipment, medium and program product. Background Art
[0002] Due to the introduction of the "dual carbon" target, the share of coal-fired power plants in the power generation process of the power grid needs to be reduced. To achieve this process, it is necessary not only to reduce carbon emissions in the power grid, but also to increase the proportion of renewable energy power generation capacity. However, due to the characteristics of large volatility of renewable energy output, connecting it to the power grid increases the uncertainty and risk of system operation, greatly increasing the difficulty of controlling power grid operation.
[0003] At present, by introducing carbon capture and storage technology into the power grid, the carbon dioxide emitted by coal-fired machines is classified and processed to transform the carbon emissions of coal-fired units, thereby avoiding the complete retirement of coal-fired units and ensuring the existence of flexibly dispatchable power resources in the power system.
[0004] However, after the introduction of carbon capture and storage technology, the operation of the power grid requires a lot of operating costs, and it cannot be dispatched with the existing renewable energy output, resulting in a lot of resource waste, which in turn increases the operating costs of the power grid. Summary of the invention
[0005] The present application provides a power grid energy scheduling method, device, electronic device, medium and program product to solve the problem in the prior art that after the introduction of carbon capture and storage technology, the operation of the power grid requires a large amount of operating costs and cannot be scheduled with the existing renewable energy output, resulting in a large amount of resource waste, thereby increasing the operating cost of the power grid.
[0006] In a first aspect, the present application provides a power grid energy dispatching method, the method comprising:
[0007] The objective function is constructed with the minimum operating cost of the power grid's coal-fired unit cost, carbon capture cost, solvent loss cost, gas turbine operating cost, energy storage system capacity degradation cost, grid interaction cost, and renewable energy dispatch cost as the target;
[0008] Determining the constraints of the objective function; wherein the constraints include electric power balance constraints, heat balance constraints, grid power exchange constraints, coal-fired unit operation constraints, gas turbine operation constraints, carbon capture facility solvent storage tank constraints, energy storage facility operation constraints, and renewable energy reserve constraints;
[0009] The objective function is solved under the constraint conditions to obtain a solution result of the objective function, and the grid energy is dispatched according to the solution result of the objective function.
[0010] In a second aspect, the present application provides a power grid energy dispatching device, the device comprising:
[0011] A building module for constructing an objective function with the minimum operating cost of the coal-fired unit cost of the power grid, the carbon capture cost, the solvent loss cost, the operating cost of the gas turbine, the capacity degradation cost of the energy storage system, the grid interaction cost, and the renewable energy dispatch cost as the target;
[0012] A determination module, used to determine the constraint conditions of the objective function; wherein the constraint conditions include electric power balance constraint, heat balance constraint, grid power exchange constraint, coal-fired unit operation constraint, gas turbine operation constraint, carbon capture facility solvent storage tank constraint, energy storage facility operation constraint and renewable energy reserve constraint;
[0013] The scheduling module is used to solve the objective function under the constraint conditions, obtain the solution result of the objective function, and schedule the power grid energy according to the solution result of the objective function.
[0014] 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 program, the power grid energy scheduling method as described in any embodiment of the present application is implemented.
[0015] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the power grid energy scheduling method as described in any embodiment of the present application.
[0016] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the power grid energy scheduling method as described in any embodiment of the present application.
[0017] The scheme of the present application takes the minimum operating cost of the coal-fired unit cost, carbon capture cost, solvent loss cost, gas turbine operating cost, capacity degradation cost of the energy storage system, grid interaction cost and renewable energy dispatching cost as the target, constructs the objective function; determines the constraint conditions of the objective function; wherein the constraint conditions include power balance constraint, heat balance constraint, grid power exchange constraint, coal-fired unit operation constraint, gas turbine operation constraint, carbon capture facility solvent storage tank constraint, energy storage facility operation constraint and renewable energy reserve constraint; solves the objective function under the constraint conditions to obtain the solution result of the objective function, and dispatches the grid energy according to the solution result of the objective function. That is, the scheme of the present application constructs the objective function with the minimum operating cost as the target, and solves the objective function under the constraint conditions, so as to obtain the operating cost required for the operation of various grids after the introduction of carbon capture and storage technology, and realizes dispatching with the existing renewable energy output, avoiding resource waste, thereby reducing the operation cost of the grid and improving the low-carbon performance of the grid. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.
[0019] Figure 1 It is a flow chart of the power grid energy dispatching method provided by this application;
[0020] Figure 2 is another flow chart of the power grid energy dispatching method provided by the present application;
[0021] Figure 3 It is a structural schematic diagram of a power grid energy dispatching device provided by the present application;
[0022] Figure 4 It is a structural schematic diagram of the electronic device provided by this application. DETAILED DESCRIPTION
[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.
[0024] Figure 1 The present invention provides a flowchart of a method for dispatching power grid energy, which can be performed by a power grid energy dispatching device, which can be implemented in software and / or hardware. In a specific embodiment, the device can be applied to an electronic device, which can be a computer capable of controlling the operation of a power grid. The following embodiments will be described by taking the application of the device in an electronic device as an example, referring to Figure 1 , the method may specifically include the following steps:
[0025] Step 101, construct an objective function with the minimum operating cost of the coal-fired unit cost of the power grid, the carbon capture cost, the solvent loss cost, the operating cost of the gas turbine, the capacity degradation cost of the energy storage system, the power grid interaction cost and the renewable energy dispatch cost as the target.
[0026] Specifically, by introducing the carbon dioxide capture system into the coal-fired unit and converting it into a carbon capture power plant, the emitted carbon dioxide can be classified and processed, thereby achieving the sustainable use of fossil fuels. The cost of the coal-fired unit of the power grid is the operating cost of the coal-fired unit, the carbon capture cost is the operating cost of the carbon dioxide capture system, the solvent loss cost is the loss cost of the solvent required in the carbon capture process, the operating cost of the gas turbine is the operating cost of the gas turbine, the capacity degradation cost of the energy storage system is the cost of the capacity change of the energy storage device, the grid interaction cost is the cost of the power storage system and the grid to interact with the grid, and the renewable energy dispatching cost is the dispatching cost of electricity generated by renewable energy such as wind power generation or photovoltaic power generation. Taking the minimum operating cost of the coal-fired unit cost of the power grid, the carbon capture cost, the solvent loss cost, the operating cost of the gas turbine, the capacity degradation cost of the energy storage system, the grid interaction cost and the renewable energy dispatching cost as the target, the objective function is constructed, that is, the minimum value of the above costs is taken as the target cost, and the grid cost is reduced to the target cost.
[0027] Optionally, the formula of the objective function is expressed as Formula 1.
[0028] F DA =min(C CPP +C CCPP +C SS +C MT +C ESS +C grid +C DR ) Formula 1
[0029] Among them, F DA is the objective function, C CPP is the cost of coal-fired units, C CCPP is the carbon capture cost, C SS is the solvent loss cost, C MT is the operating cost of the gas turbine, CESS is the capacity degradation cost of the energy storage system, C grid is the grid interaction cost, C DR Dispatch costs for renewable energy.
[0030] Specifically, the formula for the cost of a coal-fired unit is expressed as Formula 2.
[0031]
[0032] in, Indicates the start or stop status of the i-th coal-fired unit at time t. i Represents the operating cost coefficient of the i-th coal-fired unit, in RMB / MWh 2 . represents the power output of the i-th coal-fired unit at time t. i Represents the operating cost coefficient of the i-th coal-fired unit, in RMB / MWh. i Represents the operating cost coefficient of the i-th coal-fired unit, in RMB. Indicates the start or stop status of the i-th coal-fired unit at time t-1. represents the start-up and shutdown cost of the i-th coal-fired unit, in RMB. Therefore, the operation of the coal-fired unit within 24 hours is composed of the operating cost of each coal-fired unit within 24 hours.
[0033] The formula for carbon capture cost is expressed as Equation 3.
[0034]
[0035] Among them, μ C Indicates the carbon trading price, in ￥. C Indicates the total carbon dioxide production of coal-fired units, in tons. C Represents the carbon emission quota coefficient of coal-fired units. It represents the power output of the ith coal-fired unit at time t. Δt represents the time step of each hour in the 24-hour period. Represents the output power of the j-th coal-fired unit at time t.
[0036] The formula for solvent loss cost is expressed as Equation 4.
[0037]
[0038] Among them, L SS Indicates the cost coefficient of ethanolamine solvent, in ￥ / kg. θ SS Represents the cost coefficient of ethanolamine solvent during the operation of the carbon capture system, in kg / t. represents the carbon output of the i-th coal-fired unit at time t.
[0039] The operating cost of a gas turbine is expressed as Equation 5.
[0040]
[0041] Among them, C CH4 Indicates the price of natural gas per cubic meter, in ￥ / m 3 . It represents the output efficiency of the jth engine at time t. NG Indicates the lower calorific value of natural gas, in kWh / m 3 .
[0042] The capacity degradation cost of the energy storage system is expressed as Formula 6.
[0043]
[0044] in, Represents the investment cost of the energy storage system (ESS), in RMB. is the discharge power of the energy storage system at time t. is the charging power of the energy storage system at time t. Indicates the maximum number of operation cycles of the ESS. Indicates the rated capacity of ESS.
[0045] The grid interaction cost is expressed as Equation 7.
[0046]
[0047] Among them, P grid (t) is the exchange power between the energy storage facility and the grid at time t, price P (t) represents the unit electricity price at time t.
[0048] The dispatch cost of renewable energy is expressed as Equation 8.
[0049]
[0050] in, is the power load that can be reduced in the power grid at time t, is the transferable load of the power grid at time t, is the electrolytic aluminum load of the power grid at time t, ε P represents the excitation factor of the controllable power, is the heat load that can be reduced in the power grid at time t, is the transferable heat load of the power grid at time t, ε H Indicates the excitation factor of the controllable heat load. H (t) represents the unit heat price at time t.
[0051] Step 102, determining the constraints of the objective function.
[0052] Among them, the constraints include electric power balance constraints, heat balance constraints, grid power exchange constraints, coal-fired unit operation constraints, gas turbine operation constraints, carbon capture facility solvent storage tank constraints, energy storage facility operation constraints and renewable energy reserve constraints.
[0053] Specifically, the electric power balance constraints, heat balance constraints, power grid power exchange constraints, coal-fired unit operation constraints, gas turbine operation constraints, carbon capture facility solvent storage tank constraints, energy storage facility operation constraints and renewable energy reserve constraints of the objective function are determined according to the performance of the power grid.
[0054] Optionally, the formula for the electric power balance constraint is expressed as Formula 9.
[0055]
[0057] Among them, P i J (t) is the output power of the i-th coal-fired unit at time t, is the output power of the jth coal-fired unit at time t, P WPP (t) is the output power of the target wind farm at time t, P PV (t) is the output power of the target photovoltaic power plant at time t, is the discharge power of the energy storage system at time t, is the charging power of the energy storage system at time t, P grid (t) is the exchange power between the energy storage facility and the grid at time t, P load (t) is the power load of the power grid at time t, is the power load that can be reduced at time t, is the transferable load of the power grid at time t, is the electrolytic aluminum load of the power grid at time t. Therefore, the power balance constraint is that the power output at time t is equal to the power load.
[0058] Optionally, the formula for the thermal balance constraint is expressed as Formula 10.
[0059]
[0060] in, is the heat output of the j-th coal-fired unit at time t, is the heat load that can be reduced in the power grid at time t, is the transferable heat load of the power grid at time t, H load(t) is the heat load of the power grid at time t. Therefore, the heat balance constraint is that the heat output at time t is equal to the heat load.
[0061] Optionally, the formula for the grid power exchange constraint is expressed as Formula 11.
[0062]
[0063] in, P grid is the preset minimum power exchange value, P grid (t) is the exchange power between the energy storage facility and the grid at time t, It is the preset maximum value of power exchange.
[0064] Optionally, the coal-fired unit operation constraints include coal-fired unit output constraints, coal-fired unit ramp rate constraints, and coal-fired unit start and stop time constraints. The gas turbine operation constraints include gas turbine power constraints, gas turbine ramp rate constraints, exhaust heat constraints, and heating capacity constraints. The constraints of the solvent storage tank of the carbon capture facility include constraints on solvent volume changes and solvent volume constraints. The energy storage facility operation constraints include discharge power constraints, charging power constraints, charging and discharging constraints, capacity constraints, and energy storage duration capacity constraints.
[0065] Specifically, the output constraint of the coal-fired unit is expressed as Formula 12.
[0066]
[0067] in, is the preset minimum output power value of the i-th coal-fired unit, represents the power output of the i-th coal-fired unit at time t, is the preset maximum output power of the i-th coal-fired unit.
[0068] The ramp rate constraint of the coal-fired unit refers to the constraint on the load change rate of the coal-fired unit. The ramp rate constraint of the coal-fired unit is expressed as Formula 13.
[0069]
[0070] in, is the preset load increase rate of the i-th coal-fired unit, represents the power output of the i-th coal-fired unit at time t-1, is the preset load reduction rate of the i-th coal-fired unit, in MW / min. Therefore, the ramp rate constraint of the coal-fired unit is that the change value of the power output at time t to the power output at time t-1 should be within the preset change range.
[0071] The start and stop time constraint of coal-fired units is expressed as formula 14.
[0072]
[0073] in, represents the continuous operation time of the i-th coal-fired unit at time t-1, represents the downtime of the i-th coal-fired unit at time t-1. is the preset minimum startup time of the i-th coal-fired unit, is the preset shutdown time of the i-th coal-fired unit. Indicates the start or stop status of the i-th coal-fired unit at time t. Indicates the start or stop status of the i-th coal-fired unit at time t-1.
[0074] The gas turbine power constraint is expressed as Equation 15.
[0075]
[0076] in, is the preset lower limit of the output power of the jth gas turbine, represents the output power of the jth coal-fired unit at time t, is the preset upper limit of the output power of the jth gas turbine.
[0077] The gas turbine ramp rate constraint is expressed as Equation 16.
[0078]
[0079] in, represents the load increase rate of the jth gas turbine, represents the load reduction rate of the jth gas turbine. Represents the output power of the j-th coal-fired unit at time t-1.
[0080] The exhaust heat constraint is expressed as Equation 17.
[0081]
[0082] in, represents the exhaust heat available to the jth gas turbine at time t. Represents the output efficiency of the jth gas turbine at time t. represents the exhaust heat coefficient of the jth gas turbine.
[0083] The heating capacity constraint is expressed as Equation 18.
[0084]
[0085] in, It represents the heating capacity of the jth gas turbine at time t. represents the flue gas recovery rate of the jth heat exchanger, represents the heating coefficient of the jth heat exchanger.
[0086] The constraint on the solvent volume change is expressed as Equation 19.
[0087]
[0088] Among them, V i CFL V (t) represents the volume of rich solvent in the storage tank of the i-th carbon capture coal-fired unit at time t. i CPL (t) represents the volume of lean solvent in the storage tank of the i-th carbon capture coal-fired unit at time t. During the carbon capture process, carbon dioxide in the rich solvent is precipitated to obtain a lean solvent. V i CFL (t-1) represents the volume of rich solvent in the storage tank of the i-th carbon capture coal-fired unit at time t-1. V i CPL (t-1) represents the volume of lean solvent in the storage tank of the i-th carbon capture coal-fired unit at time t-1. V i CA (t) represents the capacity of the solvent storage tank of the i-th carbon capture coal-fired unit at time t.
[0089] The solvent volume constraint is expressed as Equation 20.
[0090]
[0091] Therefore, the solvent volume constraint is that the solvent volume is smaller than the capacity of the solvent storage tank of the carbon capture coal-fired unit, and the initial volume during the carbon capture process is equal to the solvent volume at the end of carbon capture.
[0092] The discharge power constraint is expressed as formula 21, and the charging power constraint is expressed as formula 22. That is, the charge and discharge amounts during the charging and discharging process are both less than and equal to the full charge state. The charging and discharging constraints are expressed as
[0093] Equation 23, the capacity constraint is expressed as Equation 24, and the energy storage duration capacity constraint is expressed as Equation 25.
[0094]
[0095] in, represents the discharge power of ESS at time t, represents the charging power of ESS at time t. and They represent the discharge and charge state variables of ESS respectively. ESS(t) represents the capacity of ESS at time t. E ESS and are the lower and upper capacity limits of ESS respectively.
[0096] Optionally, the renewable energy reserve constraint includes an upward rotation reserve constraint and a downward rotation reserve constraint, the upward rotation reserve constraint is expressed as Formula 26, and the downward rotation reserve constraint is expressed as Formula 27. The upward rotation reserve is a reserve storage process, and the downward rotation reserve is a reserve use process.
[0097]
[0098] in, and Represent the reserve capacity factors of wind power, photovoltaic power and load respectively, P i J represents the minimum net output power of the ith coal-fired unit, Represents the maximum net output power of the i-th coal-fired unit.
[0099] Step 103, solving the objective function under the constraint conditions, obtaining the solution of the objective function, and dispatching the grid energy according to the solution of the objective function.
[0100] Specifically, the objective function is solved under the constraint conditions, that is, according to the independent variables of the objective function such as the start and stop state of the coal-fired unit, the power output of the coal-fired unit, and the power output of the gas turbine, the optimal solution of the objective function, that is, the corresponding minimum cost value, is determined, and finally the solution result of the objective function is obtained, and the power grid energy is dispatched according to the solution result of the objective function. The process of determining the optimal solution can be completed by a variety of optimization algorithms, such as genetic algorithms, simulated annealing algorithms, and ant colony algorithms. Thus, a day-ahead scheduling plan is formulated 24 hours in advance, Δt is 1 hour, and the scheduling method of independent variables such as the start and stop state of the coal-fired unit, the power output of the coal-fired unit, and the power output of the gas turbine is determined according to the optimal solution of the objective function, and the power grid energy is dispatched according to the scheduling method, thereby maximizing the low-carbon performance of the system, reducing the overall operating cost of the integrated energy system, and achieving the low-carbon, economical and efficient system scheduling goals.
[0101] The scheme of the present application takes the minimum operating cost of the coal-fired unit cost, carbon capture cost, solvent loss cost, gas turbine operating cost, capacity degradation cost of the energy storage system, grid interaction cost and renewable energy dispatching cost as the target, constructs the objective function; determines the constraint conditions of the objective function; wherein the constraint conditions include power balance constraint, heat balance constraint, grid power exchange constraint, coal-fired unit operation constraint, gas turbine operation constraint, carbon capture facility solvent storage tank constraint, energy storage facility operation constraint and renewable energy reserve constraint; solves the objective function under the constraint conditions to obtain the solution result of the objective function, and dispatches the grid energy according to the solution result of the objective function. That is, the scheme of the present application constructs the objective function with the minimum operating cost as the target, and solves the objective function under the constraint conditions, so as to obtain the operating cost required for the operation of various grids after the introduction of carbon capture and storage technology, and realizes dispatching with the existing renewable energy output, avoiding resource waste, thereby reducing the operation cost of the grid and improving the low-carbon performance of the grid.
[0102] Figure 2 is another flow chart of the power grid energy dispatching method provided by the present application. Figure 1 Based on the illustrated embodiment and various optional implementation schemes, the steps of solving the objective function under the constraint conditions and obtaining the solution result of the objective function are described in detail. Figure 2 As shown, the method may include the following steps:
[0103] Step 201, construct an objective function with the minimum operating cost of the coal-fired unit cost of the power grid, the carbon capture cost, the solvent loss cost, the operating cost of the gas turbine, the capacity degradation cost of the energy storage system, the grid interaction cost and the renewable energy dispatch cost as the target.
[0104] Step 202, determining the constraints of the objective function.
[0105] Step 203, using a particle swarm optimization algorithm to solve the objective function under the constraint conditions, and obtaining a solution result of the objective function.
[0106] Specifically, according to the independent variables of the objective function, such as the start-stop state of the coal-fired unit, the power output of the coal-fired unit, the power output of the gas turbine, the volume of the rich solvent in the storage tank of the carbon capture coal-fired unit, the discharge power of the energy storage system, and the charging power of the energy storage system, the position x of each particle in the search space is randomly initialized. i and speed v i etc. Location x i The determination of is shown in formula 28.
[0107]
[0108] Speed i The determination of is shown in formula 29.
[0109] v i =[v1, v2, ..., v 16 ] Formula 29
[0110] For each particle, its objective function is calculated as the fitness value, as shown in formula 30.
[0111]
[0112] Among them, i represents the i-th coal-fired unit, and j represents the j-th gas turbine.
[0113] Multiple particles move according to their own positions and speeds, and the individual historical optimal position is set as the current particle's historical optimal position The best individual in the group is the current global optimal position The velocity of each particle is updated according to formula 31.
[0114]
[0115] Update the position of each particle according to formula 32
[0116]
[0117] in, is the velocity of the ith particle, is the position of the ith particle, the inertia weight ω is initialized to 0.9, the target weight is 0.4, and the change step size is determined according to the target iteration number. For example, if the target iteration number is 10, the change step size is 0.05. After 10 iterations, ω reaches the target weight of 0.4. c1 and c2 are acceleration coefficients, which are fixed at 2.0. and are two random numbers in the interval [0,1]. After each particle movement, the fitness function value of the particle is evaluated, and the global optimal position and historical optimal position of the particle are updated. If the iteration stop condition is met, such as the number of iterations reaches the target number of iterations, the optimal solution is less than the preset value, etc., then the optimal solution is output. If the iteration stop condition is not met, return to the step of calculating the objective function of each particle as the fitness value until the iteration stop condition is met.
[0118] Step 204: dispatching grid energy according to the solution of the objective function.
[0119] Specifically, after determining the solution of the objective function, the optimal values corresponding to independent variables such as the start and stop state of the coal-fired unit, the power output of the coal-fired unit, the power output of the gas turbine, the volume of the rich solvent in the storage tank of the carbon capture coal-fired unit, the discharge power of the energy storage system, and the charging power of the energy storage system are determined according to the optimal solution of the objective function, and the coal-fired unit, the gas turbine, the rich solvent in the storage tank of the carbon capture coal-fired unit, the lean solvent in the storage tank of the carbon capture coal-fired unit, and the energy storage system are adjusted according to the optimal values, so that the independent variable values corresponding to the above-mentioned devices reach the optimal values of the independent variables corresponding to the optimal solution of the objective function, thereby realizing the dispatch of power grid energy.
[0120] The solution of the present application adopts a particle swarm optimization algorithm to solve the objective function under constraints to obtain the solution of the objective function, thereby determining the scheduling method of independent variables such as the start and stop status of the coal-fired unit, the power output of the coal-fired unit, and the power output of the gas turbine, thereby maximizing the low-carbon performance of the system and reducing the overall operating cost of the integrated energy system.
[0121] Figure 3 Schematic diagram of a power grid energy dispatching device provided in this application, which is suitable for executing the power grid energy dispatching method provided in this application. Figure 3 As shown, the device may specifically include:
[0122] The construction module 301 is used to construct an objective function with the minimum operating cost of the coal-fired unit cost of the power grid, the carbon capture cost, the solvent loss cost, the operating cost of the gas turbine, the capacity degradation cost of the energy storage system, the power grid interaction cost and the renewable energy scheduling cost as the target.
[0123] Determination module 302 is used to determine the constraints of the objective function; wherein the constraints include electric power balance constraints, heat balance constraints, grid power exchange constraints, coal-fired unit operation constraints, gas turbine operation constraints, carbon capture facility solvent storage tank constraints, energy storage facility operation constraints and renewable energy reserve constraints.
[0124] The scheduling module 303 is used to solve the objective function under the constraint conditions, obtain the solution result of the objective function, and schedule the grid energy according to the solution result of the objective function.
[0125] In one embodiment, the formula of the objective function of the construction module 301 is expressed as: DA =min(C CPP +C CCPP +C SS +C MT +C ESS +C grid +C DR ), where F DAis the objective function, C CPP is the cost of coal-fired units, C CCPP is the carbon capture cost, C SS is the solvent loss cost, C MT is the operating cost of the gas turbine, C ESS is the capacity degradation cost of the energy storage system, C grid is the grid interaction cost, C DR Dispatch costs for renewable energy.
[0126] In one embodiment, the formula for determining the electric power balance constraint in the module 302 is expressed as: Among them, P i J (t) is the output power of the i-th coal-fired unit at time t, is the output power of the jth coal-fired unit at time t, P WPP (t) is the output power of the target wind farm at time t, P PV (t) is the output power of the target photovoltaic power plant at time t, is the discharge power of the energy storage system at time t, is the charging power of the energy storage system at time t, P grid (t) is the exchange power between the energy storage facility and the grid at time t, P load (t) is the power load of the power grid at time t, is the power load that can be reduced in the power grid at time t, is the transferable load of the power grid at time t, is the electrolytic aluminum load of the power grid at time t.
[0127] In one embodiment, the formula for determining the thermal balance constraint in the module 302 is expressed as: in, is the heat output of the j-th coal-fired unit at time t, is the heat load that can be reduced in the power grid at time t, is the transferable heat load of the power grid at time t, H load (t) is the heat load of the power grid at time t.
[0128] In one embodiment, the formula for determining the power exchange constraint of the power grid in the module 302 is expressed as: in, P grid is the preset minimum power exchange value, P grid (t) is the exchange power between the energy storage facility and the grid at time t, It is the preset maximum value of power exchange.
[0129] In one embodiment, the coal-fired unit operating constraints determined in module 302 include coal-fired unit output constraints, coal-fired unit ramp rate constraints, and coal-fired unit start and stop time constraints; the gas turbine operating constraints include gas turbine power constraints, gas turbine ramp rate constraints, exhaust heat constraints, and heating capacity constraints; the constraints of the carbon capture facility solvent storage tank include solvent volume change constraints and solvent volume constraints; the energy storage facility operating constraints include discharge power constraints, charging power constraints, charging and discharging constraints, capacity constraints, and energy storage duration capacity constraints.
[0130] In one embodiment, the scheduling module 303 solves the objective function under the constraints to obtain the solution result of the objective function, and is specifically used to: solve the objective function under the constraints by using a particle swarm optimization algorithm to obtain the solution result of the objective function.
[0131] The device of the present application takes the minimum operating cost of the coal-fired unit cost, carbon capture cost, solvent loss cost, gas turbine operating cost, capacity degradation cost of the energy storage system, grid interaction cost and renewable energy dispatching cost of the power grid as the target, constructs the objective function; determines the constraint conditions of the objective function; wherein the constraint conditions include power balance constraint, heat balance constraint, grid power exchange constraint, coal-fired unit operation constraint, gas turbine operation constraint, carbon capture facility solvent storage tank constraint, energy storage facility operation constraint and renewable energy reserve constraint; solves the objective function under the constraint conditions to obtain the solution result of the objective function, and dispatches the grid energy according to the solution result of the objective function. That is, the scheme of the present application constructs the objective function with the minimum operating cost as the target, and solves the objective function under the constraint conditions, so as to obtain the operating cost required for the operation of various power grids after the introduction of carbon capture and storage technology, and realizes dispatching with the existing renewable energy output, avoiding resource waste, thereby reducing the operating cost of the power grid and improving the low-carbon performance of the power grid.
[0132] The present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the power grid energy scheduling method provided in any of the above embodiments is implemented.
[0133] The present application also provides a computer-readable medium having a computer program stored thereon, and when the program is executed by a processor, the power grid energy scheduling method provided in any of the above embodiments is implemented.
[0134] Reference below Figure 4 , which shows a structural schematic diagram of an electronic device 400 suitable for implementing the present application. Figure 4 The electronic device shown is only an example and should not bring any limitation to the function and scope of use of the present application.
[0135] like Figure 4 As shown, the electronic device 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage part 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 are also stored. The CPU 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.
[0136] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.
[0137] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the above-mentioned functions defined in the system of the present application are executed.
[0138] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.
[0139] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.
[0140] The modules and / or units described in this application may be implemented in software or hardware. The modules and / or units described may also be provided in a processor, for example, may be described as: a processor including a construction module, a determination module, and a scheduling module. The names of these modules do not, in some cases, constitute limitations on the modules themselves.
[0141] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device performs the following operations:
[0142] Taking the minimum operating cost of the power grid's coal-fired unit cost, carbon capture cost, solvent loss cost, gas turbine operating cost, capacity degradation cost of the energy storage system, grid interaction cost and renewable energy scheduling cost as the target, construct an objective function; determine the constraints of the objective function; the constraints include electric power balance constraints, heat balance constraints, grid power exchange constraints, coal-fired unit operation constraints, gas turbine operation constraints, carbon capture facility solvent storage tank constraints, energy storage facility operation constraints and renewable energy reserve constraints; solve the objective function under the constraints to obtain the solution of the objective function, and dispatch the grid energy according to the solution of the objective function.
[0143] According to the technical solution of the present application, the objective function is constructed with the minimum operating cost of the coal-fired unit cost, carbon capture cost, solvent loss cost, gas turbine operating cost, capacity degradation cost of the energy storage system, grid interaction cost and renewable energy dispatching cost as the target; the constraint conditions of the objective function are determined; wherein the constraint conditions include power balance constraint, heat balance constraint, grid power exchange constraint, coal-fired unit operation constraint, gas turbine operation constraint, carbon capture facility solvent storage tank constraint, energy storage facility operation constraint and renewable energy reserve constraint; the objective function is solved under the constraint conditions to obtain the solution result of the objective function, and the grid energy is dispatched according to the solution result of the objective function. That is, the solution of the present application constructs the objective function with the minimum operating cost as the target, and solves the objective function under the constraint conditions, so as to obtain the operating cost required for the operation of various grids after the introduction of carbon capture and storage technology, and realizes dispatching with the existing renewable energy output, avoiding resource waste, thereby reducing the operating cost of the grid and improving the low-carbon performance of the grid.
[0144] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements a power grid energy scheduling method as provided in any embodiment of the present application.
[0145] In the process of implementation, the computer program product can be written in one or more programming languages or a combination thereof to perform the computer program code of the present application, and the programming language includes an object-oriented programming language, such as Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).
[0146] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved, and this document is not limited here.
[0147] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.
Claims
1. A power grid energy dispatching method, characterized in that: The method comprises: The objective function is constructed with the minimum operating cost of the power grid's coal-fired unit cost, carbon capture cost, solvent loss cost, gas turbine operating cost, energy storage system capacity degradation cost, grid interaction cost, and renewable energy dispatch cost as the target; Determining the constraints of the objective function; wherein the constraints include electric power balance constraints, heat balance constraints, grid power exchange constraints, coal-fired unit operation constraints, gas turbine operation constraints, carbon capture facility solvent storage tank constraints, energy storage facility operation constraints, and renewable energy reserve constraints; The objective function is solved under the constraint conditions to obtain a solution result of the objective function, and the grid energy is dispatched according to the solution result of the objective function.
2. The method according to claim 1, characterized in that The objective function is expressed as follows: F DA =min(C CPP +C CCPP +C SS +C MT +C ESS +C grid +C DR ); Among them, F DA is the objective function, C CPP is the cost of coal-fired units, C CCPP is the carbon capture cost, C SS is the solvent loss cost, C MT is the operating cost of the gas turbine, C ESS is the capacity degradation cost of the energy storage system, C grid is the grid interaction cost, C DR Dispatch costs for renewable energy.
3. The method according to claim 1, characterized in that The formula of the electric power balance constraint is expressed as: Among them, P i J (t) is the output power of the i-th coal-fired unit at time t, P j GT (t) is the output power of the jth coal-fired unit at time t, P WPP (t) is the output power of the target wind farm at time t, P PV (t) is the output power of the target photovoltaic power plant at time t, is the discharge power of the energy storage system at time t, is the charging power of the energy storage system at time t, P grid (t) is the exchange power between the energy storage facility and the grid at time t, P load (t) is the power load of the power grid at time t, is the power load that can be reduced at time t, is the transferable load of the power grid at time t, is the electrolytic aluminum load of the power grid at time t.
4. The method according to claim 3, characterized in that: The formula for the thermal balance constraint is expressed as: in, is the heat output of the j-th coal-fired unit at time t, is the heat load that can be reduced in the power grid at time t, is the transferable heat load of the power grid at time t, H load (t) is the heat load of the power grid at time t.
5. The method according to claim 4, characterized in that The formula of the power exchange constraint of the power grid is expressed as: in, P grid is the preset minimum power exchange value, P grid (t) is the exchange power between the energy storage facility and the grid at time t, It is the preset maximum value of power exchange.
6. The method according to claim 5, characterized in that The coal-fired unit operation constraints include coal-fired unit output constraints, coal-fired unit ramp rate constraints, and coal-fired unit start and stop time constraints; The gas turbine operation constraints include gas turbine power constraints, gas turbine ramp rate constraints, exhaust steam heat constraints, and heating capacity constraints; The constraints of the solvent storage tank of the carbon capture facility include constraints on solvent volume change and solvent volume constraints; The energy storage facility operation constraints include discharge power constraints, charging power constraints, charging and discharging constraints, capacity constraints, and energy storage duration capacity constraints.
7. The method according to claim 1, characterized in that The step of solving the objective function under the constraint conditions to obtain a solution result of the objective function includes: The objective function is solved under the constraint conditions using a particle swarm optimization algorithm to obtain a solution result of the objective function.
8. A power grid energy dispatching device, characterized in that: The device comprises: A building module for constructing an objective function with the minimum operating cost of the coal-fired unit cost of the power grid, the carbon capture cost, the solvent loss cost, the operating cost of the gas turbine, the capacity degradation cost of the energy storage system, the grid interaction cost, and the renewable energy dispatch cost as the target; A determination module, used to determine the constraint conditions of the objective function; wherein the constraint conditions include electric power balance constraint, heat balance constraint, grid power exchange constraint, coal-fired unit operation constraint, gas turbine operation constraint, carbon capture facility solvent storage tank constraint, energy storage facility operation constraint and renewable energy reserve constraint; The scheduling module is used to solve the objective function under the constraint conditions, obtain the solution result of the objective function, and schedule the power grid energy according to the solution result of the objective function.
9. 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 program, the power grid energy scheduling method as described in any one of claims 1 to 7 is implemented.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the power grid energy scheduling method as described in any one of claims 1 to 7 is implemented.
11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the power grid energy dispatching method according to any one of claims 1 to 7.