Optimal configuration method and device of distributed power supply, storage medium and electronic equipment

Abstract

The invention discloses an optimal configuration method and device of a distributed power supply, a storage medium and electronic equipment, and belongs to the technical field of power systems, the method comprises the steps that an optimal configuration model of the distributed power supply connected to a power grid is established, and an objective function of the optimal configuration model comprises a plurality of weighted items, the weighting items comprise a reliability factor item, an economical efficiency factor item and an environmental protection factor item, the reliability factor item is related to the voltage of nodes in the power grid, and the economical efficiency factor item is related to the active power loss of the power grid and the installation and maintenance cost of the distributed power supply; the environmental protection factor item is related to pollution gas discharged by the distributed power supply in the manufacturing and operating process; determining constraint conditions of the optimal configuration model; and based on constraint conditions, solving the optimal configuration model through a single-target optimization method to obtain an optimal configuration scheme of the distributed power supply, thereby realizing reasonable configuration of the distributed power supply based on economy, reliability and environmental protection, and improving the optimal configuration effect of the distributed power supply.

Description

Technical Field

[0001] The present application belongs to the technical field of power systems, and in particular, relates to a method, device, storage medium and electronic device for optimizing configuration of distributed power sources. Background Art

[0002] With the country's emphasis on new energy, distributed generation (DG) has achieved rapid development in my country. Distributed generation uses distributed power sources, which are flexible and dispersed, and are well adapted to decentralized power demand and resource distribution. At the same time, it serves as a backup for the large power grid, which also improves power supply reliability. In addition, distributed generation has many advantages such as less pollution, high reliability, high energy efficiency, and small and flexible installation area. It can effectively solve many potential problems of large centralized power grids, so it has been effectively used in recent years.

[0003] Smart grid requires that the grid can freely accept distributed power sources. However, due to the randomness, dispersion, unstable output, and complex control of distributed power sources, when they are connected to the grid, they will have positive and negative effects on the grid, such as voltage improvement, power loss, power quality, distribution network automation, short-circuit current, and safe and reliable operation. These effects depend on the configuration of distributed power sources, including type, installation location, and capacity. Therefore, the reasonable configuration of distributed power sources is extremely important and is the primary issue to be solved in DG planning. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a method, device, storage medium, electronic device and computer program product for optimizing the configuration of distributed power sources, which can realize the reasonable configuration of distributed power sources based on economy, reliability and environmental protection, and improve the optimization configuration effect.

[0005] In a first aspect, the present application provides a method for optimizing configuration of a distributed power source, comprising:

[0006] Establishing an optimal configuration model for accessing a distributed power source to a power grid, wherein the objective function of the optimal configuration model includes a plurality of weighted items, wherein the weighted items include a reliability factor item, an economic factor item, and an environmental factor item, wherein the reliability factor item is related to the voltage of a node in the power grid, the economic factor item is related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental factor item is related to the pollutant gas emitted by the distributed power source during the manufacturing and operation process;

[0007] Determining constraints of the optimization configuration model;

[0008] Based on the constraint conditions, the optimization configuration model is solved by a single-objective optimization method to obtain an optimization configuration scheme for the distributed power source.

[0009] In some embodiments, the objective function is:

[0010] f = λ1R + λ2T + λ2S;

[0011] Among them, λ1, λ2 and λ3 are weight coefficients, R is the reliability factor term, T is the economic factor term, and S is the environmental factor term.

[0012] In some embodiments, the reliability factor term R is expressed as:

[0013]

[0014] Where N is the total number of nodes in the power grid, i≤N, V imax is the voltage upper limit of the ith node in the power grid, V imin The voltage lower limit value of the ith node in the power grid, V i is the voltage value of the ith node in the power grid after the distributed power source is connected,

[0015] In some embodiments, the economic factor term T is expressed as:

[0016] T = ω1·η1+ω2·η2;

[0017] Among them, η1 is the network loss improvement rate, P DG(loss) is the active network loss of the power grid when the distributed generation is installed, P (loss) is the active network loss of the power grid when the distributed power source is not installed; η2 is the cost saving rate, c is the installation and maintenance cost of distributed power generation, C is the maximum allowable value of the installation and maintenance cost of distributed power generation; η1≤1, η2≤1, ω1 and ω2 are weight coefficients, and ω1+ω2=1.

[0018] In some embodiments, the environmental factor term S is expressed as:

[0019]

[0020] Where n is the number of pollutant gas types, j≤n, W j is the maximum allowable emission of the j-th pollutant gas, and wj is the actual emission of the j-th pollutant gas.

[0021] In some embodiments, the constraint condition includes a power balance constraint condition, and the power balance constraint condition is expressed as:

[0022] f(P,Q,V)=0;

[0023] Among them, P is the output power of each branch of the power grid, Q is the input power of each branch of the power grid, and V is the voltage of the distributed power source connected to the power grid.

[0024] In some embodiments, the constraint condition includes a transmission capacity constraint condition, and the transmission capacity constraint condition is that the transmission power of the power grid at any time cannot exceed the maximum capacity allowed to be transmitted by the power grid.

[0025] In a second aspect, the present application provides a distributed power supply optimization configuration device, comprising:

[0026] An establishing unit is used to establish an optimal configuration model for connecting a distributed power source to a power grid, wherein the objective function of the optimal configuration model includes a plurality of weighted items, wherein the weighted items include a reliability factor item, an economic factor item, and an environmental factor item, wherein the reliability factor item is related to the voltage of a node in the power grid, the economic factor item is related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental factor item is related to the pollutant gas emitted by the distributed power source during the manufacturing and operation process;

[0027] A determination unit, used to determine the constraint conditions of the optimization configuration model;

[0028] The model solving unit is used to solve the optimization configuration model based on the constraint conditions by a single-objective optimization method to obtain an optimization configuration scheme for the distributed power source.

[0029] In some embodiments, the objective function is:

[0030] f = λ1R + λ2T + λ3S;

[0031] Among them, λ1, λ2 and λ3 are weight coefficients, R is the reliability factor term, T is the economic factor term, and S is the environmental factor term.

[0032] In some embodiments, the reliability factor term R is expressed as:

[0033]

[0034] Where N is the total number of nodes in the power grid, i≤N, V imax is the voltage upper limit of the ith node in the power grid, V imin The voltage lower limit value of the ith node in the power grid, V i is the voltage value of the ith node in the power grid after the distributed power source is connected,

[0035] In some embodiments, the economic factor term T is expressed as:

[0036] T = ω1·η1+ω2·η2;

[0037] Among them, η1 is the network loss improvement rate, P DG(loss) is the active network loss of the power grid when the distributed generation is installed, P (loss) is the active network loss of the power grid when the distributed power source is not installed, η2 is the cost saving rate, c is the installation and maintenance cost of distributed power generation, C is the maximum allowable value of the installation and maintenance cost of distributed power generation, η1≤1, η2≤1, ω1 and ω2 are weight coefficients, and ω1+ω2=1.

[0038] In some embodiments, the environmental factor term S is expressed as:

[0039]

[0040] Where n is the number of pollutant gas types, j≤n, W j is the maximum allowable emission of the j-th pollutant gas, and wj is the actual emission of the j-th pollutant gas.

[0041] In some embodiments, the constraint condition includes a power balance constraint condition, and the power balance constraint condition is expressed as:

[0042] f(P,Q,V)=0;

[0043] Among them, P is the output power of each branch of the power grid, Q is the input power of each branch of the power grid, and V is the voltage of the distributed power source connected to the power grid.

[0044] In some embodiments, the constraint condition includes a transmission capacity constraint condition, and the transmission capacity constraint condition is that the transmission power of the power grid at any time cannot exceed the maximum capacity allowed to be transmitted by the power grid.

[0045] In a third aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements any of the above-mentioned methods for optimizing configuration of distributed power sources.

[0046] In a fourth 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 method for optimizing the configuration of a distributed power source as described in any one of the above items is implemented.

[0047] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned methods for optimizing the configuration of distributed power sources.

[0048] The embodiments of the present application provide a distributed power supply optimization configuration method, device, storage medium, electronic device and computer program product. By establishing an optimization configuration model for distributed power supply access to a power grid, the objective function of the optimization configuration model includes multiple weighted items, the weighted items include reliability factor items, economic factor items and environmental factor items, the reliability factor items are related to the voltage of the nodes in the power grid, the economic factor items are related to the active network loss of the power grid and the installation and maintenance costs of the distributed power supply, and the environmental factor items are related to the pollutant gases emitted by the distributed power supply during the manufacturing and operation process; determine the constraints of the optimization configuration model; based on the constraints, solve the optimization configuration model through a single-objective optimization method to obtain an optimization configuration plan for the distributed power supply, so that the distributed power supply can be reasonably configured based on economy, reliability and environmental protection, and multiple goals such as small network loss, low cost, good environmental benefits and high reliability can be achieved, thereby improving the optimization configuration effect of the distributed power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0050] Figure 1 It is a flow chart of a method for optimizing configuration of a distributed power source provided in an embodiment of the present application;

[0051] Figure 2 It is a structural schematic diagram of a distributed power supply optimization configuration device provided in an embodiment of the present application;

[0052] Figure 3 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0053] Figure 4 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0054] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0055] Explanation of common terms in this application:

[0056] Distributed Generation (DG): A more decentralized power generation method, which refers to the technology and system that uses a variety of small, grid-connected devices to generate electricity and store energy. Compared with centralized power generation, distributed generation is modular and flexible. It is usually located close to the load it serves and has a small power generation capacity, generally 10 megawatts (MW) or less.

[0057] Distributed power source: The power source used in distributed power generation is distributed at the user end, connected to the power grid with a voltage level of 35kV and below, and is mainly consumed locally, including solar energy, natural gas, biomass energy, wind energy, hydropower, hydrogen energy, geothermal energy, ocean energy, comprehensive resource utilization power generation (including coal mine gas power generation) and energy storage.

[0058] Embodiments of the present application provide a method, device, storage medium, electronic device, and computer program product for optimizing configuration of a distributed power source.

[0059] See also Figure 1 , Figure 1 1 is a flow chart of a method for optimizing configuration of a distributed power source provided in an embodiment of the present application. The method for optimizing configuration of a distributed power source is applied to an electronic device, and the electronic device can be implemented as a server or a terminal device. Specifically, the method for optimizing configuration of a distributed power source can include the following steps 101-103, wherein:

[0060] 101. Establish an optimal configuration model for the access of distributed power sources to the power grid. The objective function of the optimal configuration model includes multiple weighted items, including a reliability factor item, an economic factor item, and an environmental factor item. The reliability factor item is related to the voltage of the node in the power grid, the economic factor item is related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental factor item is related to the pollutant gas emitted by the distributed power source during the manufacturing and operation process;

[0061] 102. Determine the constraints of the optimization configuration model;

[0062] 103. Based on the constraint condition, the optimization configuration model is solved by a single-objective optimization method to obtain the optimal configuration scheme of the distributed power source.

[0063] The method for optimizing the configuration of distributed power sources provided in the embodiment of the present application makes the objective function of the optimization configuration model include a reliability factor term, an economic factor term and an environmental factor term. The reliability factor term is related to the voltage of the node in the power grid, the economic factor term is related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental factor term is related to the pollutant gas emitted by the distributed power source during the manufacturing and operation process. The optimization configuration model is solved by a single-objective optimization method, so that the reasonable configuration of the distributed power source can be achieved based on economy, reliability and environmental protection, so as to achieve multiple goals such as small network loss, low cost, good environmental benefit and high reliability, thereby improving the optimization configuration effect of the distributed power source.

[0064] The above steps 101-103 will be described in detail below.

[0065] 101. Establish an optimal configuration model for the access of distributed power sources to the power grid. The objective function of the optimal configuration model includes multiple weighted items, including reliability factor items, economic factor items and environmental factor items. The reliability factor item is related to the voltage of the nodes in the power grid, the economic factor item is related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental factor item is related to the pollutant gases emitted by the distributed power source during the manufacturing and operation process.

[0066] Among them, after research, it was found that when distributed power sources are connected to the power grid, different access locations, power capacity and power types have different impacts on the power grid. Regarding the problem of distributed power sources connected to the power grid, all optimization goals can be roughly summarized into three aspects: economy, reliability and environmental protection. The optimization goals belonging to economy mainly include: reducing network losses, improving DG operation efficiency and reducing DG installation and maintenance costs. The optimization goals belonging to reliability mainly include: ensuring that the load node voltage is within the specified value, ensuring the power quality of DG itself, and ensuring power flow balance. The optimization goals belonging to environmental protection mainly include: ensuring that the DG pollution discharge level meets the emission indicators.

[0067] Furthermore, the objective function is:

[0068] f = λ1R + λ2T + λ3S;

[0069] Among them, λ1, λ2 and λ3 are weight coefficients, R is the reliability factor term, T is the economic factor term, and S is the environmental factor term.

[0070] In some embodiments, the reliability factor term R is expressed as:

[0071]

[0072] Where N is the total number of nodes in the power grid, i≤N, V imaxis the voltage upper limit of the ith node in the power grid, V imin The voltage lower limit of the ith node in the power grid, V i is the voltage value of the i-th node in the power grid after the distributed power source is connected,

[0073] The main impacts of DG access on grid reliability are: node voltage, power flow balance and DG power quality issues. The calculation of the reliability factor R is based on the node voltage meeting the grid requirements. Preferably, the value range of the reliability factor R is between 0-0.5, and the smaller the value, the higher the reliability.

[0074] In some embodiments, the economic efficiency is mainly determined by the active network loss and the installation and maintenance costs. The economic efficiency factor T is expressed as:

[0075] T = ω1·η1+ω2·η2;

[0076] Among them, η1 is the network loss improvement rate, P DG(loss) is the active network loss of the power grid when the distributed power source is installed, P (loss) is the active network loss of the power grid when distributed power generation is not installed; η2 is the cost saving rate, c is the installation and maintenance cost of distributed power generation, C is the maximum allowable value of the installation and maintenance cost of distributed power generation; η1≤1, η2≤1, ω1 and ω2 are weight coefficients, and ω1+ω2=1.

[0077] ω1 represents the degree of dependence of the system project on the system loss, and ω2 represents the degree of dependence of the system project on the investment cost. Since the system loss and installation and maintenance costs have different dimensions, they cannot be directly weighted or compared in other ways in many cases. In this way, they can be grouped together using the weight coefficient after using their respective proportional scores as comparison coefficients. The smaller the value of the economic factor item T, the better the economy.

[0078] In some embodiments, the environmental factor term S is expressed as:

[0079]

[0080] Where n is the number of pollutant gas types, j≤n, W j is the maximum allowable emission of the j-th pollutant gas, and wj is the actual emission of the j-th pollutant gas.

[0081] First, identify several polluting gases that affect the environment and set appropriate indicators W for each gas. jAmong them, wind power generation, photovoltaic power generation and other renewable energy sources have no or almost no polluting gas emissions during power generation, but there are harmful gas emissions in the manufacturing of distributed power supply equipment. Furthermore, distributed power sources with adjustable capacity such as micro-gas turbines are indispensable in distributed power generation systems, so when calculating polluting gas emissions, these factors should be considered according to actual requirements. Next, when optimizing the configuration of distributed power sources, for all j, if w j / W j If w is less than 1, the actual value of the environmental factor S is calculated. The smaller S is, the better the environmental performance is. j / W j If it is greater than 1, then this configuration is unqualified.

[0082] After obtaining the above various weighted items, the weighted coefficients are determined according to actual needs, and the above objective function f is obtained according to the weighted coefficients and weighted items. Among them, the objective function can be simply adjusted according to the actual situation. For example, in actual situations, if only distributed power generation itself is considered, there is no need to consider the environmental pollution caused by distributed power generation, that is, the value of λ3 is 0, but if the distributed power generation construction process is considered, the environmental pollution caused by it is indispensable. In addition, in practical applications, if other factors such as increasing the DG installation capacity are also considered, the relevant factors can also be added to the objective function in the form of a reasonable "quotient" in the same way. This method combines various optimization objectives, truly and comprehensively reflects the impact of distributed power generation on the power grid and the requirements of the power grid, avoids the uncertainty and convergence characteristics of the mathematical optimization method, and because it uses ratio parameters to define each weighted item, it does not need to consider the different dimensions of the optimization objectives, and can combine more optimization objectives together, and can also make the optimization objectives simple and reduce constraints.

[0083] 102. Determine the constraints of the optimization configuration model.

[0084] In some embodiments, the constraint includes a power balance constraint, which is expressed as:

[0085] f(P,Q,V)=0;

[0086] Among them, P is the output power of each branch of the power grid, Q is the input power of each branch of the power grid, and V is the voltage of the distributed power source connected to the power grid.

[0087] After DG is connected to the distribution network, the system power must be balanced. Most of the time, the balance of power input and power output on the branch is taken as a constraint, which includes the power consumption of the distributed generation itself.

[0088] In some embodiments, the constraint condition includes a transmission capacity constraint condition, and the transmission capacity constraint condition is that the transmission power of the power grid cannot exceed the maximum capacity allowed to be transmitted by the power grid at any time.

[0089] In addition, the calculation constraints for the objective function in the optimization configuration model are:

[0090]

[0091] 103. Based on the constraint condition, the optimization configuration model is solved by a single-objective optimization method to obtain the optimal configuration scheme of the distributed power source.

[0092] Among them, since the optimization configuration model mainly makes appropriate adjustments at the objective function to make the calculation flexible and reliable, the calculation algorithm to solve the model only needs to use a simple optimization algorithm, that is, a simple genetic algorithm, and the calculation is simpler. The content of the optimization configuration plan includes the access location, capacity and type of each distributed power source. In the process of solving the model, under the constraints, it is necessary to repeatedly adjust the access location, capacity and type of each distributed power source in the power grid, and finally obtain the optimal solution of the objective function, that is, the optimal configuration plan of the distributed power source.

[0093] It should be pointed out that the objective function in the embodiment of the present application not only involves the system active network loss and voltage stability reliability, but also effectively combines the economy and reliability of DG configuration, and can also consider the environmental pollution caused by distributed power construction or some distributed power generation processes. It can be said that it truly and comprehensively reflects the impact of DG on the power grid and the requirements of the power grid. At the same time, users can determine the number of objective function items or weights according to the actual project situation, so the model has good versatility and flexibility, and can provide decision makers with more flexible DG configuration solutions according to their requirements.

[0094] From the above, it can be seen that the method for optimizing the configuration of distributed power sources provided in the embodiment of the present application establishes an optimization configuration model for the access of distributed power sources to the power grid, and the objective function of the optimization configuration model includes multiple weighted items, the weighted items include reliability factor items, economic factor items and environmental protection factor items, the reliability factor items are related to the voltage of the nodes in the power grid, the economic factor items are related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental protection factor items are related to the pollutant gases emitted by the distributed power source during the manufacturing and operation process; determine the constraints of the optimization configuration model; based on the constraints, solve the optimization configuration model through a single-objective optimization method to obtain an optimized configuration plan for the distributed power source, so that the reasonable configuration of the distributed power source can be achieved based on economy, reliability and environmental protection, so as to achieve multiple goals such as small network loss, low cost, good environmental benefits and high reliability, and improve the optimization configuration effect of the distributed power source.

[0095] According to the method described in the above embodiment, the present application also provides a distributed power supply optimization configuration device, which is used to execute the steps in the above distributed power supply optimization configuration method. Figure 2 , Figure 2 1 is a schematic diagram of the structure of the distributed power supply optimization configuration device provided in an embodiment of the present application. The distributed power supply optimization configuration device 200 is applied to an electronic device, and the electronic device can be implemented as a user terminal or a server. Specifically, the distributed power supply optimization configuration device 200 includes an establishment unit 201, a determination unit 202 and a model solving unit 203, wherein:

[0096] Establishing unit 201, used to establish an optimal configuration model for distributed power sources to access the power grid, the objective function of the optimal configuration model includes multiple weighted items, the weighted items include a reliability factor item, an economic factor item and an environmental factor item, the reliability factor item is related to the voltage of the node in the power grid, the economic factor item is related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental factor item is related to the pollutant gas emitted by the distributed power source during the manufacturing and operation process;

[0097] A determination unit 202, used to determine the constraint conditions of the optimization configuration model;

[0098] The model solving unit 203 is used to solve the optimization configuration model based on the constraint condition by a single-objective optimization method to obtain an optimization configuration solution for the distributed power source.

[0099] In some embodiments, the objective function is:

[0100] f = λ1R + λ2T + λ3S;

[0101] Among them, λ1, λ2 and λ3 are weight coefficients, R is the reliability factor term, T is the economic factor term, and S is the environmental factor term.

[0102] In some embodiments, the reliability factor term R is expressed as:

[0103]

[0104] Where N is the total number of nodes in the power grid, i≤N, V imax is the voltage upper limit of the ith node in the power grid, V imin The voltage lower limit of the ith node in the power grid, V i is the voltage value of the i-th node in the power grid after the distributed power source is connected,

[0105] In some embodiments, the economic factor term T is expressed as:

[0106] T = ω1·η1+ω2·η2;

[0107] Among them, η1 is the network loss improvement rate, P DG(loss) is the active network loss of the power grid when the distributed power source is installed, P (loss) is the active network loss of the power grid when distributed power generation is not installed, η2 is the cost saving rate, c is the installation and maintenance cost of distributed power generation, C is the maximum allowable value of the installation and maintenance cost of distributed power generation, η1≤1, η2≤1, ω1 and ω2 are weight coefficients, and ω1+ω2=1.

[0108] In some embodiments, the environmental factor term S is expressed as:

[0109]

[0110] Where n is the number of pollutant gas types, j≤n, W j is the maximum allowable emission of the j-th pollutant gas, and wj is the actual emission of the j-th pollutant gas.

[0111] In some embodiments, the constraint includes a power balance constraint, which is expressed as:

[0112] f(P,Q,V)=0;

[0113] Among them, P is the output power of each branch of the power grid, Q is the input power of each branch of the power grid, and V is the voltage of the distributed power source connected to the power grid.

[0114] In some embodiments, the constraint condition includes a transmission capacity constraint condition, and the transmission capacity constraint condition is that the transmission power of the power grid cannot exceed the maximum capacity allowed to be transmitted by the power grid at any time.

[0115] It should be noted that the specific details of each module unit in the above-mentioned distributed power supply optimization configuration device 200 have been described in detail in the embodiment of the above-mentioned distributed power supply optimization configuration method, and will not be repeated here.

[0116] In some embodiments, the optimization configuration device of the distributed power supply in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal device. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), etc., which is not specifically limited in the embodiment of the present application.

[0117] In some embodiments, Figure 3 As shown, an embodiment of the present application also provides an electronic device 300, including a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the program is executed by the processor 301, each process of the above-mentioned distributed power source optimization configuration method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0118] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0119] Figure 4 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of the present application.

[0120] The electronic device 400 includes but is not limited to: a radio frequency unit 401, a network module 402, an audio output unit 403, an input unit 404, a sensor 405, a display unit 406, a user input unit 407, an interface unit 408, a memory 409, a processor 410 and other components.

[0121] Those skilled in the art will appreciate that the electronic device 400 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 410 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 4The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0122] It should be understood that in the embodiment of the present application, the input unit 404 may include a graphics processor (Graphics Processing Unit, GPU) 4041 and a microphone 4042, and the graphics processor 4041 processes the image data of the static picture or video obtained by the image capture device (such as a camera) in the video capture mode or the image capture mode. The display unit 406 may include a display panel 4061, and the display panel 4061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 407 includes a touch panel 4071 and at least one of other input devices 4072. The touch panel 4071 is also called a touch screen. The touch panel 4071 may include two parts: a touch detection device and a touch controller. Other input devices 4072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0123] The memory 409 can be used to store software programs and various data. The memory 409 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, an image playback function, etc.), etc. In addition, the memory 409 may include a volatile memory or a non-volatile memory, or the memory 409 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory 409 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0124] The processor 410 may include one or more processing units; the processor 410 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the modem processor may not be integrated into the processor 410.

[0125] An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned distributed power supply optimization configuration method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0126] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0127] An embodiment of the present application also provides a computer program product, including a computer program, which implements the above-mentioned distributed power supply optimization configuration method when executed by a processor.

[0128] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0129] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0130] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0131] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0132] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0133] In the description of the present application, “plurality” means two or more.

[0134] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0135] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for optimizing the configuration of distributed power sources, characterized in that: include: Establishing an optimal configuration model for accessing a distributed power source to a power grid, wherein the objective function of the optimal configuration model includes a plurality of weighted items, wherein the weighted items include a reliability factor item, an economic factor item, and an environmental factor item, wherein the reliability factor item is related to the voltage of a node in the power grid, the economic factor item is related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental factor item is related to the pollutant gas emitted by the distributed power source during the manufacturing and operation process; Determining constraints of the optimization configuration model; Based on the constraint conditions, the optimization configuration model is solved by a single-objective optimization method to obtain an optimization configuration scheme for the distributed power source.

2. The method for optimizing the configuration of distributed power sources according to claim 1, characterized in that: The objective function is: f = λ1R + λ2T + λ3S; Among them, λ1, λ2 and λ3 are weight coefficients, R is the reliability factor term, T is the economic factor term, and S is the environmental factor term.

3. The method for optimizing the configuration of distributed power sources according to claim 2, characterized in that: The reliability factor term R is expressed as: Where N is the total number of nodes in the power grid, i≤N, V imax is the voltage upper limit of the ith node in the power grid, V imin The voltage lower limit value of the ith node in the power grid, V i is the voltage value of the i-th node in the power grid after the distributed power source is connected, 4. The method for optimizing the configuration of distributed power sources according to claim 2, characterized in that: The economic factor term T is expressed as: T = ω1·η1+ω2·η2; Among them, η1 is the network loss improvement rate, P DG(loss) is the active network loss of the power grid when the distributed generation is installed, P (loss) is the active network loss of the power grid when the distributed power source is not installed; η2 is the cost saving rate, c is the installation and maintenance cost of distributed power generation, C is the maximum allowable value of the installation and maintenance cost of distributed power generation; η1≤1, η2≤1, ω1 and ω2 are weight coefficients, and ω1+ω2=1.

5. The method for optimizing the configuration of distributed power sources according to claim 2, characterized in that: The environmental factor term S is expressed as: Where n is the number of pollutant gas types, j≤n, W j is the maximum allowable emission of the j-th pollutant gas, and wj is the actual emission of the j-th pollutant gas.

6. The method for optimizing the configuration of distributed power sources according to claim 1, characterized in that: The constraint condition includes a power balance constraint condition, and the power balance constraint condition is expressed as: f(P,Q,V)=0; Among them, P is the output power of each branch of the power grid, Q is the input power of each branch of the power grid, and V is the voltage of the distributed power source connected to the power grid.

7. A distributed power supply optimization configuration device, characterized in that: include: An establishing unit is used to establish an optimal configuration model for connecting a distributed power source to a power grid, wherein the objective function of the optimal configuration model includes a plurality of weighted items, wherein the weighted items include a reliability factor item, an economic factor item, and an environmental factor item, wherein the reliability factor item is related to the voltage of a node in the power grid, the economic factor item is related to the active network loss of the power grid and the installation and maintenance cost of the distributed power source, and the environmental factor item is related to the pollutant gas emitted by the distributed power source during the manufacturing and operation process; A determination unit, used to determine the constraint conditions of the optimization configuration model; The model solving unit is used to solve the optimization configuration model based on the constraint conditions by a single-objective optimization method to obtain an optimization configuration scheme for the distributed power source.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for optimizing configuration of a distributed power source according to any one of claims 1 to 6 is implemented.

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 distributed power source optimization configuration method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for optimizing configuration of a distributed power source according to any one of claims 1 to 6 is implemented.

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