Scheduling method and device based on electric energy harmony index of grid-connected main body device and medium

Abstract

The invention relates to a scheduling method, device and medium based on an electric energy harmony index of a grid-connected main body device, and the method comprises the following steps: respectively establishing mathematical models of the grid-connected main body device and obtaining operation data, the grid-connected main body device comprising a thermal power generating unit, a wind turbine generator, a photovoltaic system and an energy storage system; constructing an electric energy harmony index based on the mathematical model and the operation data, wherein the electric energy harmony index is a normalized weighted average of at least two indexes of a network access safety coordination capability index, a network access safety coordination performance index, an environmental protection index, a low-carbon index and an energy-saving index; constructing a multi-objective optimization model, wherein an objective function of the multi-objective optimization model comprises maximization of the total electric energy harmony index of the system and minimization of the total operation cost; and solving the multi-objective optimization model to obtain an optimal scheduling scheme of the grid-connected main body equipment. Compared with the prior art, equipment connected into the power grid can meet the green requirements of low carbon and environmental protection, and meanwhile, the requirements of harmony and safety of the power grid are met.

Description

Technical Field

[0001] The present invention relates to the technical field of grid-connected dispatching, and in particular to a dispatching method, device and medium based on the power harmony index of grid-connected main equipment. Background Art

[0002] With the global emphasis on environmental protection and sustainable development, renewable energy power generation technologies such as wind power and photovoltaic power have developed rapidly. These renewable energies have the advantages of being clean and renewable, can effectively reduce greenhouse gas emissions, and meet the requirements of low-carbon environmental protection. For wind power and photovoltaic power generation, due to the intermittency and uncertainty of their output affected by natural conditions (wind speed, light intensity), prediction technologies are mainly used to estimate their output in advance. During the real-time dispatching process, the grid dispatching center will adjust the output of conventional generating units according to the actual output of wind power and photovoltaic power generation and the load change situation. At the same time, it is necessary to reasonably arrange the reserve capacity to cope with the fluctuations in the output of wind power and photovoltaic power generation. For example, when the wind power output suddenly drops, the standby thermal power units or other flexible regulating power sources can be quickly started to ensure the power balance of the grid. In the problem of optimal dispatching of distribution networks containing renewable energy, it is necessary to consider the characteristics of renewable energy, and the calculation process is complex, time-consuming and has poor adaptability. Based on this, the prior art has given various solutions, such as using multi-objective optimization algorithms, fuzzy logic control, neural network control, etc. Among these methods, the multi-objective optimization algorithm has significant advantages. Especially when dealing with complex dispatching problems, it can comprehensively consider multiple objectives and constraints, so as to achieve a better dispatching scheme. For example, CN114567006A discloses a multi-objective optimal operation method and system for a distribution network to solve the problem that the prior art does not comprehensively consider the adjustment rate constraint of power adjustment resources, resulting in the optimization result being unable to be implemented in the adjustable resource power adjustment in actual projects, and can meet the maximum adjustment rate constraint, thereby making the optimization result more reasonable, meeting the actual constraints in the industrial community, and having the advantages of making the simulation calculation of the optimal dispatching of the distribution network more accurate and meeting the actual constraint requirements of the equipment participating in the optimization in the project. This method can set different optimization objective function expressions, different decision variables and constraint conditions according to different optimization scenarios when dealing with the problem of adjustable resources participating in the optimal operation of the distribution network, and flexibly adopt numerical optimization algorithms and intelligent algorithms. The scheme is simple, practical and truly feasible. However, this method only considers the operating cost and energy efficiency for optimization, and does not consider from the perspectives of environmental protection and grid operation safety. Summary of the Invention

[0003] The objective of the present invention is to overcome the defects of the above-mentioned existing technologies and provide a scheduling method, device and medium based on the power energy harmony index of grid-connected main equipment, ensuring that the equipment connected to the grid not only meets the green requirements of low-carbon environmental protection, but also can meet the requirements of grid harmony and safety.

[0004] The objective of the present invention can be achieved through the following technical solutions: According to the first aspect of the present invention, a scheduling method based on the power energy harmony index of grid-connected main equipment is provided. The method includes the following steps: Respectively establish a mathematical model of grid-connected main equipment and obtain operation data. The grid-connected main equipment includes thermal power units, wind power units, photovoltaic systems and energy storage systems; Construct a power energy harmony index based on the mathematical model and operation data. The power energy harmony index is the normalized weighted average of at least two of the grid connection safety coordination ability index, grid connection safety coordination performance index, green environmental protection index, low-carbon index and energy-saving index; Construct a multi-objective optimization model. The objective function of the multi-objective optimization model includes maximizing the total power energy harmony index of the system and minimizing the total operation cost; Solve the multi-objective optimization model to obtain the optimal scheduling plan of the grid-connected main equipment.

[0005] As a preferred technical solution, the grid connection safety coordination ability index is determined based on the primary frequency regulation ability, AGC ability, AVC ability, leading phase ability, lagging phase ability, black start ability, deep peak shaving ability, fast load shedding ability and unit steady-state performance of the grid-connected main body. Among them, When the primary frequency regulation performance index of the grid-connected generating unit meets the preset requirements, the corresponding primary frequency regulation ability index is 1; when it does not meet the requirements, the primary frequency regulation ability index is 0; When the AGC performance index of the grid-connected generating unit meets the preset requirements, the corresponding AGC ability index is 1; when it does not meet the requirements, the AGC ability index is 0; The calculation method of the AVC ability index is: , where is the AVC ability index, is the AVC performance qualification factor, is the monthly operation rate of AVC. When AVC can be adjusted to the target range according to the instruction requirements within the preset time, takes the value of 1, otherwise it is 0; The calculation method of the leading phase ability index is: , Among them, is the leading phase ability index, is the actual leading phase depth of the unit under the condition of 100% rated power, is the rated power of the unit; The calculation method of the lagging phase capacity index is: , where, is the lagging phase capacity index, is the actual lagging phase degree of the unit under the condition of 100% rated power, is the rated active power of the unit; The black start capacity is determined according to whether the unit has the black start capacity. If it has the black start capacity, the black start capacity index is 1, otherwise it is 0; When the minimum power generation of the generator set is less than or equal to 30% the deep peak shaving capacity index is 1, and when it is greater than 30% and less than or equal to 40% the deep peak shaving capacity index is 0.5, and when it is greater than 40% and less than or equal to 50% the deep peak shaving capacity index is 0.2, and when it is greater than or equal to 50% the deep peak shaving capacity index is 0; The fast load shedding capacity is determined according to whether the unit has the fast load shedding capacity. If it has the fast load shedding capacity, the fast load shedding capacity index is 1, otherwise it is 0; The calculation method of the steady-state performance index of the unit is: , where, and are the stable operation time of the unit and the total operation time of the unit respectively.

[0006] As an optimal technical solution, the grid connection safety coordination performance index is determined based on the primary frequency regulation performance, AGC performance, AVC performance, low-frequency regulation response performance, unit non-stop performance, and unit technical management performance. Among them, The primary frequency regulation performance index The calculation method is: , where, and are the qualified operation times of primary frequency regulation and the assessment times of primary frequency regulation actions respectively; The AGC performance index The calculation method is: , where, and are the qualified time of AGC performance and the total operation time of AGC operation respectively; The AVC performance index The calculation method is as follows: , wherein, and are the qualified time of AVC response and the total operation time of AVC respectively; The calculation method of the low-frequency regulation response performance index is: calculated according to the number of low-frequency regulation responses that the unit should participate in, and the number of low-frequency regulation responses participated by the unit each time , and are the actual action value and the theoretical action value respectively. When is greater than 1, it is assigned a value of 1, , is the number of low-frequency regulation responses that the unit should participate in during the evaluation period, is the low-frequency regulation response performance index; The calculation method of the unit out-of-service performance index is: , wherein, and are the number of unit trips and the maximum number of unit trips of all units in the whole network respectively; The unit technical management performance index is the score of the technical supervision quality evaluation of each unit.

[0007] As a preferred technical solution, the green environmental protection index is based on NO X emission index , SO2 emission index , soot emission index and solid waste emission index to determine. The calculation method of each index is: , , , , wherein, is the thermal power unit number, is the total number of thermal power units in the urban area, is the th unit's power generation proportion in the total power generation of all thermal power units in the whole network, , , , are the actual NO th unit's x , SO2, soot, and solid waste performance emission rates respectively.

[0008] As a preferred technical solution, the low-carbon index is based on the carbon emission index and carbon emission reduction index of the power plant and carbon emission reduction index and is determined, where the calculation method of each index is as follows: , , where is the serial number of the thermal power unit, is the total number of thermal power units in the urban area, is the proportion of the power generation of the th unit in the total power generation of all thermal power units in the power grid, is the actual CO2 performance emission rate of the th unit, is the carbon emission reduction of the th unit during power generation, is the total carbon emission reduction of the region during power generation.

[0009] As a preferred technical solution, the energy-saving index is based on the fossil energy consumption index , auxiliary power consumption index and water consumption index and is determined, where the calculation method of each index is as follows: , , , where is the serial number of the thermal power unit, is the total number of thermal power units in the urban area, is the proportion of the power generation of the th unit in the total power generation of all thermal power units in the power grid, is the power supply coal consumption of the th unit at 80% load rate, is the auxiliary power consumption corresponding to the th unit, is the power supply water consumption of the th unit.

[0010] As a preferred technical solution, the objective function of the multi-objective optimization model is expressed as: , , where T is the total number of time periods in the scheduling cycle, N is the total number of main grid-connected equipment, is the electrical energy harmony index of the equipment i in the t time period For the output of the device i during t the time period, and and and are respectively the operating costs of the thermal power unit, wind power unit, photovoltaic system and energy storage system at time t.

[0011] As a preferred technical solution, the constraint conditions of the multi-objective optimization model include power balance constraint, thermal power unit ramp constraint, energy storage SOC constraint and grid security constraint.

[0012] According to the second aspect of the present invention, there is provided an electronic device, including a memory and a processor, wherein a computer program is stored on the memory, and when the processor executes the program, the method described above is implemented.

[0013] According to the third aspect of the present invention, there is provided a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the method described above is implemented.

[0014] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention designs an electric energy harmony index for the dispatching scenario that faces both grid-connected traditional thermal power units and new energy grid-connected main equipment such as wind power and photovoltaic power, and takes the electric energy harmony index as one of the core optimization objectives, while taking into account the operating cost of the system. Through mathematical modeling and optimization algorithms, an optimal dispatching scheme is found under the condition of meeting the safe operation of the power grid. Specifically, through optimized dispatching, the present invention can reduce the dependence on traditional thermal power units, thereby reducing carbon emissions, realizing clean utilization of energy and low-carbon operation, and avoiding impacts on the power grid caused by the intermittency and uncertainty of new energy, improving safety. In addition, considering the system operating cost in the objective function can reasonably allocate the output of different power sources and reduce the overall operating cost of the system.

[0015] (2) The electric energy harmony index of the present invention can be constructed by selecting multiple different sub-indicators according to the needs of actual application scenarios, deeply considering the tendency of different scenarios for the dispatching scheme, realizing precise and effective dispatching under different scenarios, and having wide applicability.

[0016] (3) The present invention can adapt to different power grid structures and operating conditions, and has high flexibility and adaptability. Whether in a power grid with a high proportion of new energy or in a power grid dominated by traditional thermal power units, it can effectively achieve optimized dispatching. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0019] Unless otherwise defined, the technical terms or scientific terms involved in this application should have the ordinary meanings understood by those with ordinary skills in the technical field to which this application belongs. The words such as "a", "an", "one kind", "the" and the like involved in this application do not indicate a quantity limitation, and can represent a singular or plural number. The terms "including", "comprising", "having" and any variations thereof involved in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product or device including a series of steps or modules (units) is not limited to the listed steps or units, but may further include unlisted steps or units, or may further include other steps or units inherent to these processes, methods, products or devices. The words such as "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" may represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the front and rear associated objects. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific order for the objects.

[0020] Embodiment 1 This embodiment provides a scheduling method based on the power harmony index of grid-connected main equipment, as Figure 1 shown, the method includes the following steps: S1. Respectively establish a mathematical model of the grid-connected main equipment and obtain operation data. The grid-connected main equipment includes thermal power units, wind turbine units, photovoltaic systems, and energy storage systems.

[0021] The mathematical models of thermal power units, wind turbine units, photovoltaic systems, and energy storage systems can refer to the construction methods in the prior art. This embodiment only provides a possible implementation manner and does not limit the specific construction of the mathematical models of each device.

[0022] In one embodiment, the relationship between the fuel consumption and the output power of a thermal power unit is usually represented by a quadratic function: , Among them, is the output power (MW) of the thermal power unit, F is the fuel consumption, a , b , c are the unit characteristic parameters of the unit.

[0023] In this embodiment, the operating parameters of the thermal power unit obtained include but are not limited to: the output of the thermal power unit, the unit cost of coal, the unit climbing cost, the cumulative operating time, the start-stop cost of the thermal power unit, the number of start-stop units of the thermal power unit, the emission of polluting gases, the load power time curve of the thermal power unit, and the combustion power time curve of the thermal power unit.

[0024] In one embodiment, the output power model of the wind turbine can be: , Among them, is the air density, is the swept area of the wind turbine rotor, is the power coefficient, related to the tip speed ratio and the pitch angle , is the wind speed.

[0025] In this embodiment, the operating parameters of the wind turbine include but are not limited to: the real-time wind speed, the unit cost of wind abandonment, the power generation power of the wind turbine, and the actual grid-connected output of the wind turbine.

[0026] In one embodiment, the output power model of the photovoltaic system can be: , Among them, is the light intensity (W / m²), is the area of the photovoltaic panel, is the conversion efficiency, is the battery temperature, is the reference temperature, is the temperature coefficient.

[0027] In this embodiment, the operating parameters of the photovoltaic system include but are not limited to: the light intensity, the unit cost of light abandonment, the power generation power of the photovoltaic power station, and the actual grid-connected output of the photovoltaic power station.

[0028] In one embodiment, the mathematical model of the energy storage system mainly includes the SOC dynamic model: , Among them, is the SOC at time t, is the charge and discharge current at time t, is the time step, is the nominal capacity of the battery, is the charge and discharge efficiency of the battery.

[0029] In this embodiment, the operating parameters of the energy storage system include but are not limited to the current SOC, charge and discharge power, number of cycles, state of health, and temperature.

[0030] S2. Construct an electric energy harmony index based on the mathematical model and operating data.

[0031] In this embodiment, the electric energy harmony index is the normalized weighted average of at least two of the grid connection safety coordination ability index, grid connection safety coordination performance index, green environmental protection index, low-carbon index, and energy-saving index. Among them, the grid connection safety coordination ability index is used to evaluate the dynamic adjustment ability of the power system, including the grid connection adjustment ability, stability, fault recovery speed, etc. of the power grid. The grid connection safety coordination performance index is used to reflect the response performance of the power system in actual operation, such as response speed, response effect, etc. The green environmental protection index is used to measure the impact of the power system on the environment during the energy utilization process, such as pollutant emissions. The low-carbon index is used to evaluate the carbon emissions and carbon emission reduction during the operation of the power system to promote the development of the low-carbon economy. The energy-saving index is used to reflect the efficiency of the power system during the energy conversion and transmission process and reduce energy waste.

[0032] The flexibility of this embodiment lies in that different index combinations can be selected according to different actual usage scenarios. For example: in a power grid dominated by new energy, the green environmental protection index and the low-carbon index can be preferentially selected to promote the utilization of renewable energy and reduce carbon emissions; in an industrial area power grid, the energy-saving index and the grid connection safety coordination ability index can be preferentially selected to improve energy utilization efficiency and the stability of the power grid; in a residential area power grid, the grid connection safety coordination performance index and the energy-saving index can be comprehensively considered to ensure power supply safety and reduce the electricity cost of residents.

[0033] S3. Construct a multi-objective optimization model.

[0034] In this embodiment, the objective function of the multi-objective optimization model includes maximizing the total electric energy harmony index of the system and minimizing the total operating cost, expressed as: , , where, T is the total number of time periods in the scheduling cycle, N is the total number of main grid connection equipment, is the equipment i at t the electric energy harmony index in the time period, is the equipment i at t the output in the time period, , , , are the operating costs of the thermal power unit, wind power unit, photovoltaic system, and energy storage system at time t, respectively.

[0035] The constraint conditions of the multi-objective optimization model include: 1) Power balance constraint , where is the output of thermal power unit i at time period t, is the output of the wind power unit at time period t, is the output of the photovoltaic at time period t, is the discharge power of the energy storage system at time period t, is the charging power of the energy storage system at time period t, is the flexible load demand at time period t.

[0036] 2) Thermal power unit ramp rate constraint , where is the output of thermal power unit i at time period t, is the maximum ramp rate of thermal power unit i.

[0037] 3) Energy storage SOC constraint , where is the state of charge of the energy storage system at time period t, , are the minimum and maximum allowed states of charge of the energy storage, respectively.

[0038] 4) Power grid security constraint 41) Node voltage constraint , where is the voltage magnitude of node n at time period t, 1 is the reference voltage.

[0039] 42) Power flow constraint , where is the transmission power of line l at time period t, is the maximum allowed transmission capacity of line l.

[0040] S4. Solve the multi-objective optimization model to obtain the optimal scheduling scheme of the grid-connected main equipment.

[0041] The solution methods of the multi-objective optimization model include, but are not limited to: traditional mathematical programming methods (weight coefficient method, ε-constraint method), evolutionary algorithms (non-dominated sorting genetic algorithm, decomposition-based multi-objective evolutionary algorithm), decomposition-based methods (goal programming, hierarchical optimization), intelligent optimization algorithms (multi-objective particle swarm optimization, multi-objective differential evolution), etc. This embodiment does not limit the specific solution method adopted, and the difference in the solution method adopted does not affect the realization of the invention purpose of the present invention.

[0042] In one embodiment, taking the non-dominated sorting genetic algorithm (NSGA-II) as an example to illustrate its solution steps.

[0043] Step 1) Initialize the population: Generate an initial population P0 with a population size of N. Each individual represents a possible solution, usually represented by a vector.

[0044] Step 2) Non-dominated sorting: Perform non-dominated sorting on the individuals in the population, and divide the population into multiple non-dominated layers (Front). Each individual is assigned a crowding distance to measure the distribution density of the individual in the objective space.

[0045] Step 3) Selection operation: Use tournament selection to select individuals from the current population for reproduction. When selecting, individuals with a lower non-dominated layer are given priority. If the non-dominated layers are the same, individuals with a larger crowding distance are selected.

[0046] Step 4) Crossover and mutation: Perform crossover and mutation operations on the selected individuals to generate a new offspring population Q t 。

[0047] Step 5) Merge populations: Merge the parent population P t and the offspring population Q t into a temporary population R t with a size of 2N.

[0048] Step 6) Environmental selection: Perform non-dominated sorting and crowding calculation on the merged population R t and select the first N individuals as the new parent population P t+1 。

[0049] Step 7) Check whether the termination condition is met (such as reaching the maximum number of iterations or convergence condition). If it is met, terminate the algorithm and output the final non-dominated solution set (Pareto Front). Otherwise, return to Step 2).

[0050] Embodiment 2 Based on Embodiment 1, this embodiment elaborates in detail on the composition of the power harmony index.

[0051] (1) Grid-connection security coordination ability index

[0052] The grid-connection security coordination ability index is determined based on the primary frequency regulation ability, AGC (Automatic Generation Control) ability, AVC (Automatic Voltage Control) ability, leading power factor ability, lagging power factor ability, black start ability, deep peak shaving ability, fast load shedding ability, and unit steady-state performance of the grid-connected entity. , specifically: (11) Primary frequency regulation ability index

[0053] When the primary frequency regulation performance index of the grid-connected generator set meets the requirements of Clause 5.4.2.3.1-k of GB / T 31464, the corresponding primary frequency regulation ability index is 1; when it does not meet the requirements, the primary frequency regulation ability index is 0.

[0054] (12) AGC ability index

[0055] When the AGC performance index of the grid-connected generator set meets the requirements of Clause 5.4.2.3.1-l of GB / T 31464, the corresponding AGC ability index is 1; when it does not meet the requirements, the AGC ability index is 0.

[0056] (13) AVC ability index

[0057] The calculation method of the AVC ability index is: , where is the AVC ability index, is the AVC performance qualification factor, is the monthly operation rate of AVC. When AVC can be adjusted to the target range according to the command requirements within the preset time, takes the value of 1; otherwise, it is 0.

[0058] (14) Leading power factor ability index

[0059] The calculation method of the leading power factor ability index is: , where is the leading power factor ability index, It is the actual leading phase depth of the unit under the condition of 100% rated power. It is the rated power of the unit.

[0060] (15)Lagging phase ability index

[0061] The calculation method of the lagging phase ability index is: , Wherein, It is the lagging phase ability index. It is the actual lagging phase degree of the unit under the condition of 100% rated power. It is the rated active power of the unit.

[0062] (16)Black start ability index

[0063] The black start ability is determined according to whether the unit has the black start ability. If it has the black start ability, the black start ability index is 1, otherwise is 0.

[0064] (17)Deep peak shaving ability index

[0065] When the minimum power generation of the generator set is less than or equal to 30% , the deep peak shaving ability index is 1, greater than 30% and less than or equal to 40% , the deep peak shaving ability index is 0.5, greater than 40% and less than or equal to 50% , the deep peak shaving ability index is 0.2, greater than or equal to 50% , the deep peak shaving ability index is 0.

[0066] (18)Fast load shedding ability index

[0067] The fast load shedding ability is determined according to whether the unit has the fast load shedding ability. If it has the fast load shedding ability, the fast load shedding ability index is 1, if not is 0.

[0068] (19)Unit steady-state performance index

[0069] The calculation method of the unit steady-state performance index is: , Among them, and are the stable operation time and the total operation time of the unit respectively.

[0070] (2)Grid connection safety coordination performance index

[0071] The grid connection safety coordination performance index is determined based on the primary frequency regulation performance, AGC performance, AVC performance, low-frequency regulation response performance, unit non-stop performance, and unit technical management performance. , specifically: (21)Primary frequency regulation performance index

[0072] , Among them, and are the qualified action times and the action assessment times of primary frequency regulation respectively.

[0073] (22)AGC performance index

[0074] , Among them, and are the qualified time of AGC performance and the total operation time of AGC operation respectively.

[0075] (23)AVC performance index

[0076] , Among them, and are the qualified time of AVC response and the total operation time of AVC operation respectively. The judgment condition for qualified AVC response is that the AVC operation rate should reach more than 98%, and the adjustment speed should meet the requirement of adjusting to the target range within 2 minutes according to the instruction.

[0077] (24)Low-frequency regulation response performance index

[0078] Calculated according to the number of low-frequency regulation response times that the unit should participate in, and the number of low-frequency regulation response times that the unit participates in each regulation , and are the actual action value and the theoretical action value respectively. When is greater than 1, it is assigned a value of 1. , is the number of low-frequency regulation response times that the unit should participate in during the evaluation period. is the low-frequency regulation response performance index; (25)Unit forced outage performance indicator

[0079] The calculation method of the unit forced outage performance indicator is as follows: , Among them, and are the number of unit trips and the maximum number of unit trips of each unit in the whole network respectively; (26)Unit technical management performance indicator

[0080] The unit technical management performance indicator is the score of the technical supervision quality evaluation of each unit.

[0081] (3)Green environmental protection index

[0082] The green environmental protection index is determined based on the NO X emission index , SO2 emission index , soot emission index and solid waste emission index . The calculation method of each index is as follows: , , , , , Among them, is the serial number of the thermal power unit, is the total number of thermal power units in the urban area, is the proportion of the power generation of the th unit in the total power generation of all thermal power units in the whole network, , , , are the actual NO emission, SO2, soot, and solid waste performance emission rates of the x th unit respectively.

[0083] (4)Low-carbon index

[0084] The low-carbon index is determined based on the carbon emission index and carbon emission reduction index of the power plant. Among them, the calculation method of each index is as follows: , , Among them, is the serial number of the thermal power unit, is the total number of thermal power units in the urban area, is the ratio of the power generation of the th unit to the total power generation of all thermal power units in the power grid, is the actual CO2 performance emission rate of the th unit, is the power generation carbon emission reduction of the th unit,

[0085] (5)Energy-saving index

[0086] The energy-saving index is determined based on the fossil energy consumption index , the auxiliary power consumption index and the water consumption index , where the calculation methods of the respective indexes are as follows: , among which, , , , where, is the serial number of the thermal power unit, is the total number of thermal power units in the urban area, is the ratio of the power generation of the th unit to the total power generation of all thermal power units in the power grid, is the standard coal consumption for power supply of the th unit at 80% load rate, is the corresponding auxiliary power consumption of the th unit, is the water consumption for power supply of the

[0087] Example 3 The electronic device of the present invention includes a central processing unit (CPU), which can execute various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or computer program instructions loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for device operation can also be stored. The CPU, ROM, and RAM are connected to each other through a bus. The input / output (I / O) interface is also connected to the bus.

[0088] Multiple components in the device are connected to the I / O interface, including: an input unit, such as a keyboard, a mouse, etc.; an output unit, such as various types of displays, speakers, etc.; a storage unit, such as a disk, an optical disc, etc.; and a communication unit, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit allows the device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0089] The processing unit executes the various methods and processes described above, such as methods S1 to S4. For example, in some embodiments, methods S1 to S4 can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device via the ROM and / or the communication unit. When the computer program is loaded into the RAM and executed by the CPU, one or more steps of methods S1 to S4 described above can be executed. Alternatively, in other embodiments, the CPU can be configured to execute methods S1 to S4 by any other suitable means (e.g., by means of firmware).

[0090] The functions described above herein can be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: Field Programmable Gate Arrays (FPGA), Application Specific Integrated Circuits (ASIC), Application Specific Standard Products (ASSP), System on Chip (SOC), Complex Programmable Logic Devices (CPLD), and so on.

[0091] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0092] In the context of the present invention, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium would include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0093] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A dispatching method based on the power harmony index of grid-connected main equipment, characterized in that: The method comprises the following steps: Establishing mathematical models of main grid-connected equipment and obtaining operation data respectively, wherein the main grid-connected equipment includes thermal power units, wind power units, photovoltaic systems and energy storage systems; Constructing an electric energy harmony index based on the mathematical model and the operating data, wherein the electric energy harmony index is a normalized weighted average of at least two of a network access safety coordination capability index, a network access safety coordination performance index, a green environmental protection index, a low carbon index, and an energy-saving index; Constructing a multi-objective optimization model, wherein the objective function of the multi-objective optimization model includes maximizing the system total power harmony index and minimizing the total operating cost; Solve the multi-objective optimization model to obtain the optimal scheduling solution for the main grid-connected equipment.

2. A dispatching method based on the power harmony index of grid-connected main equipment according to claim 1, characterized in that: The grid access safety coordination capability index is determined based on the primary frequency regulation capability, AGC capability, AVC capability, phase leading capability, phase lagging capability, black start capability, deep peak regulation capability, rapid load shedding capability and unit steady-state performance of the grid-connected entity, where: When the primary frequency regulation performance index of the grid-connected generator set meets the preset requirements, the corresponding primary frequency regulation capability index is 1; if it does not meet the requirements, the primary frequency regulation capability index is 0; When the AGC performance index of the grid-connected generator set meets the preset requirements, the corresponding AGC capability index is 1, and if it does not meet the requirements, the AGC capability index is 0; The calculation method of AVC capability index is: ,in, is the AVC capability indicator, is the AVC performance qualification factor, is the monthly commissioning rate of AVC. When AVC can be adjusted to the target range according to the instruction requirements within the preset time, The value is 1, otherwise it is 0; The calculation method of the phase-advancing capability index is: ， in, is the phase-advancing capability indicator, It is the actual phase advance depth of the unit under the condition of 100% rated power. is the rated power of the unit; The calculation method of the hysteresis capability index is: ， in, is the hysteresis capability index, is the actual lag degree of the unit under the condition of 100% rated power, is the rated active power of the unit; The black start capability is determined by whether the unit has the black start capability. If the unit has the black start capability, the black start capability index is 1, otherwise it is 0; When the minimum power generation capacity of the generator set is less than or equal to 30% The deep peak load regulation capability index is 1, which is greater than 30%. and less than or equal to 40% The deep peak load regulation capability index is 0.5, which is greater than 40%. and less than or equal to 50% The deep peak load regulation capability index is 0.2, which is greater than or equal to 50% The deep peak-shaving capability index is 0; The rapid load shedding capability is determined by whether the unit has the capability of rapid load shedding. If the unit has the capability of rapid load shedding, the rapid load shedding capability index is 1, otherwise it is 0. The calculation method of the unit steady-state performance index is: ， in, and They are the stable operation time of the unit and the total operation time of the unit respectively.

3. The dispatching method based on the power harmony index of the main grid-connected equipment according to claim 1 is characterized in that: The network access safety coordination performance index is determined based on the primary frequency regulation performance, AGC performance, AVC performance, low frequency regulation response performance, unit non-stop performance, and unit technical management performance, among which: Primary frequency modulation performance indicators The calculation method is: ， in, and They are the number of qualified actions for one frequency modulation and the number of assessments for one frequency modulation action respectively; AGC Performance Indicators The calculation method is: ， in, and They are the AGC performance qualified time and the total AGC operation time; AVC Performance Indicators The calculation method is: ， in, and They are AVC response qualified time and AVC total operation time; The calculation method of low-frequency regulation response performance index is as follows: the number of low-frequency regulation responses that the unit should participate in is calculated, and the number of low-frequency regulation responses that the unit participates in each adjustment is calculated as follows: , and are the actual action value and the theoretical action value respectively. If it is greater than 1, it is assigned a value of 1. , To evaluate the number of low-frequency regulation responses that the unit should participate in during the time period, It is a performance indicator for low frequency regulation response; The calculation method of the unit non-stop performance index is: ， in, and They are the maximum number of tripping times of the unit and the number of tripping times of all units in the whole network respectively; The unit technical management performance indicator is the technical supervision quality evaluation score of each unit.

4. The dispatching method based on the power harmony index of the main grid-connected equipment according to claim 1 is characterized in that: The green environmental index is based on NO X Emission indicators 、SO2 emission indicators , smoke emission indicators and solid waste emission indicators The calculation method of each indicator is as follows: ， ， ， ， in, is the serial number of the thermal power unit, is the total number of thermal power units in urban areas, For the The proportion of the power generation of the unit to the total power generation of the thermal power units in the whole network, , , , Respectively Actual NO of the unit x , SO2, smoke and solid waste performance emission rates.

5. The dispatching method based on the power harmony index of the main grid-connected equipment according to claim 1 is characterized in that: The low carbon index is based on the carbon emission indicators of power plants. and carbon reduction targets Determine, among which, the calculation method of each indicator is: ， ， in, is the serial number of the thermal power unit, is the total number of thermal power units in urban areas, For the The proportion of the power generation of the unit to the total power generation of the thermal power units in the whole network, For the The actual CO2 performance emission rate of each unit, For the Carbon emissions reduction of power generation units, is the total carbon emission reduction of regional power generation.

6. The dispatching method based on the power harmony index of the main grid-connected equipment according to claim 1 is characterized in that: The energy saving index is based on the fossil energy consumption index , Factory power consumption indicators and water consumption indicators Determine, among which, the calculation method of each indicator is: ， ， ， in, is the serial number of the thermal power unit, is the total number of thermal power units in urban areas, For the The proportion of the power generation of the unit to the total power generation of the thermal power units in the whole network, For the Coal consumption for power generation at 80% load rate of each unit, For the The power consumption of the plant corresponding to each unit is For the Power supply water consumption of each unit.

7. The dispatching method based on the power harmony index of the main grid-connected equipment according to claim 1 is characterized in that: The objective function of the multi-objective optimization model is expressed as: ， ， in, T is the total number of time periods in the scheduling cycle, N is the total number of grid-connected main equipment, For equipment i exist t The power harmony index of the time period, For equipment i exist t Output during the period, , , , are the operating costs of thermal power units, wind power units, photovoltaic systems and energy storage systems at time t respectively.

8. The dispatching method based on the power harmony index of the main grid-connected equipment according to claim 1 is characterized in that: The constraints of the multi-objective optimization model include power balance constraints, thermal power unit ramp constraints, energy storage SOC constraints and power grid security constraints.

9. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 8 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 method according to any one of claims 1 to 8 is implemented.

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