CN112465187A - Power grid planning design method based on multi-objective optimization - Google Patents
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Abstract
The invention relates to the technical field of power systems, and discloses a power grid planning design method based on multi-objective optimization, which comprises the following steps: 1. c, power grid current situation investigation; 2. predicting the power load; calculating the development cost of the power grid, the economic loss of wind and light abandonment and the discharge capacity of the power grid; 3. solving an optimal solution set of power grid constraint conditions according to the multi-target power grid planning model, and planning a transformer substation; 4. a planning scheme is specified; 5. evaluating the technology and the economy; 6. an optimal solution is determined. According to the power grid planning design method based on multi-objective optimization, economy and reliability can be considered during planning, and the economy and reliability of a planning scheme can be flexibly evaluated.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a power grid planning design method based on multi-objective optimization.
Background
The power supply reliability refers to the capability of a power supply system for continuously supplying power to users, is an important index for evaluating the power quality of the power supply system, reflects the satisfaction degree of the power industry on national economic power requirements, and becomes one of the standards for measuring the developed degree of national economy; in an electric power system, a power grid plays an important role in distributing electric energy and is a bridge between a power supply enterprise and a user.
On the one hand, the power supply reliability and the power supply capacity are improved through a new round of power grid optimization and transformation, the requirements of load increase and urban development are met, on the other hand, the urban electric quantity is slowly increased, and the investment economic benefits of the power grid cannot be reflected. Under the background of high power supply reliability and gradual increase of electric quantity in cities, the influence of factors such as a power grid network frame, equipment configuration, an intelligent level and an operation and maintenance management level on the investment economy of a power grid needs to be considered in power grid planning construction, and more refined and systematic analysis needs to be carried out on the coordination of the power grid power supply reliability and the investment economy.
Disclosure of Invention
The invention aims to provide a power grid planning design method based on multi-objective optimization, which can give consideration to economy and reliability during planning and flexibly evaluate the economy and the reliability of a planning scheme.
The technical scheme provided by the invention is as follows:
a power grid planning design method based on multi-objective optimization comprises the following steps:
1) analyzing the existing power grid state and historical data of the planning area through three dimensions of technical reasonability, safety and power grid conversion rate, and investigating and evaluating the existing power grid of the planning area;
2) forecasting the power load by combining the local economy, population, policy and regional development planning data of the planning region to obtain the total power load;
3) calculating the development cost of the power grid, the economic loss of wind and light abandonment and the discharge capacity of the power grid;
4) analyzing the electric power and the electric quantity of the planning area by combining the total electric power load obtained by prediction, determining a voltage grade sequence, a power grid structural form and an equipment selection principle in the planning area on the basis of adapting to a local power grid planning principle, dividing the planning area into mutually independent and multi-level power supply areas according to land functions, geographic environments and administrative division factors, establishing a coordinate system in the planning area, and determining the coordinates of each load center;
5) optimizing and selecting the site of the transformer substation based on an equal load principle, an initial investment minimum principle, a load distance minimum principle and a network operation cost minimum principle;
6) solving an optimal solution set of power grid constraint conditions according to the multi-target power grid planning model;
7) and (4) making a planning scheme, carrying out economic and technical evaluation on the planning scheme, and determining the optimal scheme.
Further, the power grid development cost is as follows: CD ═ AI+BOM+CNL+DGWhere CD represents the grid development cost, AIRepresents the total investment cost of the power grid,BOMmaintenance cost of electric meter grid operation, CNLRepresents the loss cost of the network, DGRepresents the cost of the power generation of the power grid,
Wherein x ismRepresenting the commissioning status of the mth thermal power unit to be added, ynRepresenting the operational status of the nth wind farm grid-connected line to be added, zoThe method comprises the steps that the operation state of the grid-connected line of the photovoltaic power station to be increased is shown, m is 1,2, …, i, i represents the total number of thermal power generating units to be increased, n is 1,2, …, j, j represents the total number of the grid-connected line of the wind power station to be increased, and o is 1,2, …, k, k represents the total number of the grid-connected line of the photovoltaic power station to be increased; a. theIG,mRepresenting the annual value of the investment cost and the like of the mth thermal power generating unit to be increased,IIG,mrepresenting the investment cost of the mth thermal power generating unit to be increased, q representing the annual discount rate of the investment, and N G representing the service life of the thermal power generating unit; a. theIWTG,nRepresents the annual value of the investment cost of the nth wind power plant grid-connected line to be increased, andIIWTG,nthe method comprises the steps that initial investment cost of an nth thermal power generating unit to be increased is shown, and N WTG shows the economic life of a grid-connected line of a wind power plant; a. theIPVG,oRepresents the annual value of the investment cost of the grid-connected line of the photovoltaic power station to be increased in the No. o, andIIPVG,orepresents the initial investment cost, N, of the photovoltaic power plant grid-connected line to be added in the o-th itemPVGRepresenting the economic life of a grid-connected line of the photovoltaic power station; alpha represents an operation cost proportionality coefficient; Δ T represents a period variation amount, T represents a total number of the year-round period; delta represents the unit grid power loss price, and the unit is ten thousand yuan/(kWh & h); l represents the total number of the original transmission lines; i isu,tRepresents the current flowing on the u-th transmission line in the time period tn,tRepresents the current I flowing on the nth grid-connected line of the wind power plant to be increased in the time period to,tRepresenting the electricity flowing on the photovoltaic power station grid-connected line to be increased in the period tth; ruRepresenting the resistance, R, of the original u-th transmission linenRepresenting the resistance, R, of the nth wind farm grid-connection line to be addedoRepresenting the resistance of the photovoltaic power station grid-connected line to be increased;
ρGrepresents the unit power generation cost, rho, of the thermal power generating unitWTGRepresents the unit generation cost, rho, of the wind turbinePVGRepresenting the unit power generation cost of the photovoltaic unit;the active power output of the thermal power generating unit is shown in a time period t,the active power output of the wind turbine is shown in the time period t,and representing the active power output of the photovoltaic unit in a time period t.
Further, the wind curtailment economic loss is as follows:
wherein f is2Representing economic loss of wind and light abandoning, cWTGRepresents the economic loss caused by unit air loss, cPVGRepresenting the economic loss due to unit light rejection,representing the planned active power output of the wind generating set in the grid-connected line of the nth wind power plant in the time period t,representing the actual active power output of the wind turbine in the grid-connected line of the wind power plant to be increased at the nth time interval,representing the planned active power output of the photovoltaic unit in the grid-connected line of the photovoltaic power station to be increased at the No. o time of the time period t,the actual active power output of the photovoltaic unit in the grid-connected line of the photovoltaic power station to be increased in the period tth is shown,andrespectively as follows:
wherein v, vi、vr、voRespectively representing the actual wind speed, the cut-in wind speed, the rated wind speed and the cut-out wind speed; wherein E represents the actual illumination intensity, EKExpressing the rated illumination intensity, A expressing the area of the photovoltaic array, eta expressing the light spot conversion efficiency of the photovoltaic array, etainvRepresenting the efficiency of the photovoltaic inverter.
Further, the grid sewage discharge capacity is as follows:
wherein N isERepresenting the number of contaminant species, betao、β1、β2Mu and epsilon represent the pollution discharge coefficient of the thermal power generating unit.
Furthermore, a multi-target power grid planning model with the following formula is constructed by taking the minimum development cost of the power grid, the economic loss of the wind and light abandoning and the minimum discharge capacity of the power grid as the targets,
further, the grid constraint conditions comprise equality constraints and inequality constraints; the equality constraint comprises a power balance constraint; the inequality constraints comprise load node new energy power generation penetrating power constraints, branch flow constraints, thermal power generating unit output upper and lower limit constraints, wind turbine generator set operation condition constraints and photovoltaic generator set operation condition constraints;
further, the solving of the optimal solution set meeting the power grid constraint condition according to the multi-target power grid planning model includes: solving a multi-target power grid planning model by adopting an NSGA-II algorithm, and outputting an optimal solution set meeting power grid constraint conditions;
further, the economic and technical evaluation comprises a network system platform, and a data acquisition unit, a data monitoring unit, a data analysis unit and a statistical form query unit which are established on the platform; the network system platform comprises a network basic frame, a data exchange system and a general report system; the network basic frame comprises a plurality of layers of databases, constructs a data storage layer and provides a general data storage service; the data exchange system provides standards-based universal data exchange; the universal report system provides the functions of drawing and generating the network system platform report;
furthermore, the data acquisition unit comprises a plurality of communication channels aiming at different detection points, is wirelessly interconnected with each detection terminal, inputs and processes the acquired data, and stores the acquired data in the multilayer database in a centralized manner, wherein each detection terminal comprises each electric energy detection meter positioned on a power grid transformer and a power transmission and transformation line;
furthermore, the data monitoring unit comprises an independent GIS platform and a monitoring module based on the GIS platform, the data monitoring unit is used for constructing a power grid geographic information network diagram, and the monitoring module comprises a processor, a data memory and an alarm unit.
The beneficial effects brought by one aspect of the invention are as follows: the invention aims to provide a power grid planning design method based on multi-objective optimization, which can give consideration to economy and reliability during planning and flexibly evaluate the economy and the reliability of a planning scheme.
Drawings
FIG. 1 is a flow chart of steps of a power grid planning and designing method based on multi-objective optimization.
Detailed Description
In order to make the technical problems solved, technical solutions adopted and technical effects achieved by the present invention clearer, the technical solutions of the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, those skilled in the art can obtain the embodiments without creative efforts, and the embodiments belong to the protection scope of the present invention.
Example 1
The purpose of this embodiment is to further illustrate the implementation and attention points of the above technical solution, as shown in fig. 1, specifically as follows:
a power grid planning design method based on multi-objective optimization comprises the following steps:
1) analyzing the existing power grid state and historical data of the planning area through three dimensions of technical reasonability, safety and power grid conversion rate, and investigating and evaluating the existing power grid of the planning area;
2) forecasting the power load by combining the local economy, population, policy and regional development planning data of the planning region to obtain the total power load;
3) calculating the development cost of the power grid, the economic loss of wind and light abandonment and the discharge capacity of the power grid;
4) analyzing the electric power and the electric quantity of the planning area by combining the total electric power load obtained by prediction, determining a voltage grade sequence, a power grid structural form and an equipment selection principle in the planning area on the basis of adapting to a local power grid planning principle, dividing the planning area into mutually independent and multi-level power supply areas according to land functions, geographic environments and administrative division factors, establishing a coordinate system in the planning area, and determining the coordinates of each load center;
5) optimizing and selecting the site of the transformer substation based on an equal load principle, an initial investment minimum principle, a load distance minimum principle and a network operation cost minimum principle;
6) solving an optimal solution set of power grid constraint conditions according to the multi-target power grid planning model;
7) and (4) making a planning scheme, carrying out economic and technical evaluation on the planning scheme, and determining the optimal scheme.
The power grid development cost is as follows: CD ═ AI+BOM+CNL+DGWhere CD represents the grid development cost, AIRepresents the total investment cost of the power grid, BOMMaintenance cost of electric meter grid operation, CNLRepresents the loss cost of the network, DGRepresents the cost of the power generation of the power grid,
Wherein x ismRepresenting the commissioning status of the mth thermal power unit to be added, ynRepresenting the operational status of the nth wind farm grid-connected line to be added, zoThe method comprises the steps that the operation state of the grid-connected line of the photovoltaic power station to be increased is shown, m is 1,2, …, i, i represents the total number of thermal power generating units to be increased, n is 1,2, …, j, j represents the total number of the grid-connected line of the wind power station to be increased, and o is 1,2, …, k, k represents the total number of the grid-connected line of the photovoltaic power station to be increased; a. theIG,mRepresenting the annual value of the investment cost and the like of the mth thermal power generating unit to be increased,IIG,mrepresenting the investment cost of the mth thermal power generating unit to be increased, q representing the annual discount rate of the investment, and N G representing the service life of the thermal power generating unit; a. theIWTG,nRepresents the annual value of the investment cost of the nth wind power plant grid-connected line to be increased, andIIWTG,nrepresenting the initial investment cost, N, of the nth thermal power unit to be addedWTGRepresenting the economic life of a grid-connected line of the wind power plant; a. theIPVG,oRepresents the annual value of the investment cost of the grid-connected line of the photovoltaic power station to be increased in the No. o, andIIPVG,orepresents the initial investment cost, N, of the photovoltaic power plant grid-connected line to be added in the o-th itemPVGRepresenting the economic life of a grid-connected line of the photovoltaic power station; alpha represents an operation cost proportionality coefficient; Δ T represents a period variation amount, T represents a total number of the year-round period; delta represents the unit grid power loss price, and the unit is ten thousand yuan/(kWh & h); l represents the total number of the original transmission lines; i isu,tRepresents the current flowing on the u-th transmission line in the time period tn,tRepresents the current I flowing on the nth grid-connected line of the wind power plant to be increased in the time period to,tRepresenting the electricity flowing on the photovoltaic power station grid-connected line to be increased in the period tth; ruRepresenting the resistance, R, of the original u-th transmission linenRepresenting the resistance, R, of the nth wind farm grid-connection line to be addedoLight to be added at bar oResistance of the grid-connected line of the photovoltaic power station;
ρGrepresents the unit power generation cost, rho, of the thermal power generating unitWTGRepresents the unit generation cost, rho, of the wind turbinePVGRepresenting the unit power generation cost of the photovoltaic unit;the active power output of the thermal power generating unit is shown in a time period t,the active power output of the wind turbine is shown in the time period t,and representing the active power output of the photovoltaic unit in a time period t.
The economic loss of the wind abandon light is as follows:
wherein f is2Representing economic loss of wind and light abandoning, cWTGRepresents the economic loss caused by unit air loss, cPVGRepresenting the economic loss due to unit light rejection,representing the planned active power output of the wind generating set in the grid-connected line of the nth wind power plant in the time period t,representing the actual active power output of the wind turbine in the grid-connected line of the wind power plant to be increased at the nth time interval,representing the planned active power output of the photovoltaic unit in the grid-connected line of the photovoltaic power station to be increased at the No. o time of the time period t,denotes the period tth oThe actual active power output of the photovoltaic unit in the grid-connected line of the photovoltaic power station is simulated to be increased,andrespectively as follows:
wherein v, vi、vr、voRespectively representing the actual wind speed, the cut-in wind speed, the rated wind speed and the cut-out wind speed; wherein E represents the actual illumination intensity, EKExpressing the rated illumination intensity, A expressing the area of the photovoltaic array, eta expressing the light spot conversion efficiency of the photovoltaic array, etainvRepresenting the efficiency of the photovoltaic inverter.
The sewage discharge capacity of the power grid is as follows:
wherein N isERepresenting the number of contaminant species, betao、β1、β2Mu and epsilon represent the pollution discharge coefficient of the thermal power generating unit.
The multi-target power grid planning model with the following formula is constructed by taking the minimum development cost of a power grid, the economic loss of wind and light abandoning and the minimum discharge capacity of the power grid as the targets,
the power grid constraint conditions comprise equality constraints and inequality constraints; the equality constraint comprises a power balance constraint; the inequality constraints comprise load node new energy power generation penetrating power constraints, branch flow constraints, thermal power generating unit output upper and lower limit constraints, wind turbine generator set operation condition constraints and photovoltaic generator set operation condition constraints;
the solving of the optimal solution set meeting the power grid constraint condition according to the multi-target power grid planning model comprises the following steps: solving a multi-target power grid planning model by adopting an NSGA-II algorithm, and outputting an optimal solution set meeting power grid constraint conditions;
the economic and technical evaluation comprises a network system platform, and a data acquisition unit, a data monitoring unit, a data analysis unit and a statistical form query unit which are established on the platform; the network system platform comprises a network basic frame, a data exchange system and a general report system; the network basic frame comprises a plurality of layers of databases, constructs a data storage layer and provides a general data storage service; the data exchange system provides standards-based universal data exchange; the universal report system provides the functions of drawing and generating the network system platform report;
the data acquisition unit comprises a plurality of communication channels aiming at different detection points, is wirelessly interconnected with each detection terminal, performs input processing on the acquired data, and stores the acquired data in the multilayer database in a centralized manner, wherein each detection terminal comprises each electric energy detection meter positioned on a power grid transformer and a power transmission and transformation line;
the data monitoring unit comprises an independent GIS platform and a monitoring module based on the GIS platform, the data monitoring unit is used for constructing a power grid geographic information network diagram, and the monitoring module comprises a processor, a data memory and an alarm unit.
Example 2
On the basis of the embodiment 1, a power grid planning and designing method based on multi-objective optimization is further extended and explained, and the specific process is as follows:
a power grid planning design method based on multi-objective optimization comprises the following steps:
1) analyzing the existing power grid state and historical data of the planning area through three dimensions of technical reasonability, safety and power grid conversion rate, and investigating and evaluating the existing power grid of the planning area;
2) forecasting the power load by combining the local economy, population, policy and regional development planning data of the planning region to obtain the total power load;
3) calculating the development cost of the power grid, the economic loss of wind and light abandonment and the discharge capacity of the power grid;
4) analyzing the electric power and the electric quantity of the planning area by combining the total electric power load obtained by prediction, determining a voltage grade sequence, a power grid structural form and an equipment selection principle in the planning area on the basis of adapting to a local power grid planning principle, dividing the planning area into mutually independent and multi-level power supply areas according to land functions, geographic environments and administrative division factors, establishing a coordinate system in the planning area, and determining the coordinates of each load center;
5) optimizing and selecting the site of the transformer substation based on an equal load principle, an initial investment minimum principle, a load distance minimum principle and a network operation cost minimum principle;
6) solving an optimal solution set of power grid constraint conditions according to the multi-target power grid planning model;
7) and (4) making a planning scheme, carrying out economic and technical evaluation on the planning scheme, and determining the optimal scheme.
Further, the power grid development cost is as follows: CD ═ AI+BOM+CNL+DGWhere CD represents the grid development cost, AIRepresents the total investment cost of the power grid, BOMMaintenance cost of electric meter grid operation, CNLRepresents the loss cost of the network, DGRepresents the cost of the power generation of the power grid,
Wherein x ismRepresenting the commissioning status of the mth thermal power unit to be added, ynRepresenting the operational status of the nth wind farm grid-connected line to be added, zoThe method comprises the steps that the operation state of the grid-connected line of the photovoltaic power station to be increased is shown, m is 1,2, …, i, i represents the total number of thermal power generating units to be increased, n is 1,2, …, j, j represents the total number of the grid-connected line of the wind power station to be increased, and o is 1,2, …, k, k represents the total number of the grid-connected line of the photovoltaic power station to be increased; a. theIG,mRepresenting the annual value of the investment cost and the like of the mth thermal power generating unit to be increased,IIG,mrepresenting the investment cost of the mth thermal power generating unit to be increased, q representing the annual discount rate of the investment, and N G representing the service life of the thermal power generating unit; a. theIWTG,nRepresents the annual value of the investment cost of the nth wind power plant grid-connected line to be increased, andIIWTG,nthe method comprises the steps that initial investment cost of an nth thermal power generating unit to be increased is shown, and N WTG shows the economic life of a grid-connected line of a wind power plant; a. theIPVG,oRepresents the annual value of the investment cost of the grid-connected line of the photovoltaic power station to be increased in the No. o, andIIPVG,orepresents the initial investment cost, N, of the photovoltaic power plant grid-connected line to be added in the o-th itemPVGRepresenting the economic life of a grid-connected line of the photovoltaic power station; alpha represents an operation cost proportionality coefficient; Δ T represents a period variation amount, T represents a total number of the year-round period; delta represents the unit grid power loss price, and the unit is ten thousand yuan/(kWh & h); l represents the total number of the original transmission lines; i isu,tRepresents the current flowing on the u-th transmission line in the time period tn,tRepresents the current I flowing on the nth grid-connected line of the wind power plant to be increased in the time period to,tPhotovoltaic power station grid-connected line upstream representing time t to be increasedElectricity that has passed; ruRepresenting the resistance, R, of the original u-th transmission linenRepresenting the resistance, R, of the nth wind farm grid-connection line to be addedoRepresenting the resistance of the photovoltaic power station grid-connected line to be increased;
ρGrepresents the unit power generation cost, rho, of the thermal power generating unitWTGRepresents the unit generation cost, rho, of the wind turbinePVGRepresenting the unit power generation cost of the photovoltaic unit;the active power output of the thermal power generating unit is shown in a time period t,the active power output of the wind turbine is shown in the time period t,and representing the active power output of the photovoltaic unit in a time period t.
The economic loss of the wind abandon light is as follows:
wherein f is2Representing economic loss of wind and light abandoning, cWTGRepresents the economic loss caused by unit air loss, cPVGRepresenting the economic loss due to unit light rejection,representing the planned active power output of the wind generating set in the grid-connected line of the nth wind power plant in the time period t,representing the actual active power output of the wind turbine in the grid-connected line of the wind power plant to be increased at the nth time interval,photovoltaic power station grid-connected line light to be increased in expression time t (to the o) th stripThe planned active power output of the photovoltaic unit,the actual active power output of the photovoltaic unit in the grid-connected line of the photovoltaic power station to be increased in the period tth is shown,andrespectively as follows:
wherein v, vi、vr、voRespectively representing the actual wind speed, the cut-in wind speed, the rated wind speed and the cut-out wind speed; wherein E represents the actual illumination intensity, EKExpressing the rated illumination intensity, A expressing the area of the photovoltaic array, eta expressing the light spot conversion efficiency of the photovoltaic array, etainvRepresenting the efficiency of the photovoltaic inverter.
The sewage discharge capacity of the power grid is as follows:
wherein N isERepresenting the number of contaminant species, betao、β1、β2Mu and epsilon represent the pollution discharge coefficient of the thermal power generating unit.
The multi-target power grid planning model with the following formula is constructed by taking the minimum development cost of a power grid, the economic loss of wind and light abandoning and the minimum discharge capacity of the power grid as the targets,
the power grid constraint conditions comprise equality constraints and inequality constraints; the equality constraint comprises a power balance constraint; the inequality constraints comprise load node new energy power generation penetrating power constraints, branch flow constraints, thermal power generating unit output upper and lower limit constraints, wind turbine generator set operation condition constraints and photovoltaic generator set operation condition constraints;
the solving of the optimal solution set meeting the power grid constraint condition according to the multi-target power grid planning model comprises the following steps: solving a multi-target power grid planning model by adopting an NSGA-II algorithm, and outputting an optimal solution set meeting power grid constraint conditions;
the economic and technical evaluation comprises a network system platform, and a data acquisition unit, a data monitoring unit, a data analysis unit and a statistical form query unit which are established on the platform; the network system platform comprises a network basic frame, a data exchange system and a general report system; the network basic frame comprises a plurality of layers of databases, constructs a data storage layer and provides a general data storage service; the data exchange system provides standards-based universal data exchange; the universal report system provides the functions of drawing and generating the network system platform report;
the data acquisition unit comprises a plurality of communication channels aiming at different detection points, is wirelessly interconnected with each detection terminal, performs input processing on the acquired data, and stores the acquired data in the multilayer database in a centralized manner, wherein each detection terminal comprises each electric energy detection meter positioned on a power grid transformer and a power transmission and transformation line;
the data monitoring unit comprises an independent GIS platform and a monitoring module based on the GIS platform, the data monitoring unit is used for constructing a power grid geographic information network diagram, and the monitoring module comprises a processor, a data memory and an alarm unit.
The grid constraint condition may include an equality constraint and an inequality constraint; wherein the equality constraints comprise power balance constraints; the inequality constraints comprise load node new energy power generation penetrating power constraints, branch flow constraints, thermal power generating unit output upper and lower limit constraints, wind turbine generator set operation condition constraints and photovoltaic generator set operation condition constraints.
The power balance constraint is as follows:
wherein, PtNode injected power vector, B, representing time period ttThe node admittance matrix, θ, representing the time period ttA node voltage phase angle vector representing time period t,representing the active power of the load for time period tsupport.
In the inequality constraint, the load node new energy power generation penetration power constraint, the branch flow constraint, the thermal power generator set output upper and lower limit constraint, the wind turbine set operating condition constraint and the photovoltaic set operating condition constraint are respectively as follows:
the new energy power generation penetration power constraint of the load node is as follows:
wherein the content of the first and second substances,
representing the maximum output power of the wind turbine in the nth wind power plant grid-connected line to be increased, NWTG representing the wind turbine set,
representing the maximum output power of the photovoltaic units in the photovoltaic power station grid-connected circuit to be increased, NPVG representing the photovoltaic unit set,
the branch flow constraint is as follows:
wherein the content of the first and second substances,
the upper and lower output limits of the thermal power generating set are constrained as follows:
wherein the content of the first and second substances,respectively representing the lower limit and the upper limit of the active power output of the thermal power generating unit;
the operating condition constraint of the wind turbine generator is as follows:
wherein the content of the first and second substances,representing the maximum output of the wind turbine;
wherein the content of the first and second substances,and representing the maximum output of the photovoltaic unit.
The NSGA-II algorithm accelerates the speed of the algorithm, the elite retention strategy avoids the loss of the optimal solution, the distribution range of the optimal solution set is expanded, and the diversity of the population is ensured.
The optimal solution set meeting the constraint conditions comprises minimizing the development cost of the power grid, minimizing the economic loss of wind curtailment and minimizing the pollution discharge capacity of the power grid. In the multi-target power grid planning model, a feasible solution with a plurality of targets well coordinated exists, and a final planning scheme can be determined according to the degree of emphasis on each target function.
Claims (10)
1. A power grid planning design method based on multi-objective optimization is characterized by comprising the following steps:
1) analyzing the existing power grid state and historical data of the planning area through three dimensions of technical reasonability, safety and power grid conversion rate, and investigating and evaluating the existing power grid of the planning area; 2) forecasting the power load by combining the local economy, population, policy and regional development planning data of the planning region to obtain the total power load; 3) calculating the development cost of the power grid, the economic loss of wind and light abandonment and the discharge capacity of the power grid; 4) analyzing the electric power and the electric quantity of the planning area, determining a voltage grade sequence, a power grid structure form and an equipment selection principle in the planning area, dividing the planning area into mutually independent power supply areas, and determining the coordinates of each load center; 5) optimizing and selecting the site of the transformer substation based on an equal load principle, an initial investment minimum principle, a load distance minimum principle and a network operation cost minimum principle; 6) solving an optimal solution set of power grid constraint conditions according to the multi-target power grid planning model; 7) and (4) making a planning scheme, carrying out economic and technical evaluation on the planning scheme, and determining the optimal scheme.
2. The multi-objective optimization-based power grid planning and design method according to claim 1, wherein the method comprises the following steps: the power grid development cost is as follows: CD ═ AI+BOM+CNL+DGWhere CD represents the grid development cost, AIRepresents the total investment cost of the power grid, BOMMaintenance cost of electric meter grid operation, CNLRepresents the loss cost of the network, DGRepresents the cost of power generation of the grid, and
wherein x ismRepresenting the commissioning status of the mth thermal power unit to be added, ynRepresenting the operational status of the nth wind farm grid-connected line to be added, zoThe method comprises the steps that the operation state of the grid-connected line of the photovoltaic power station to be increased is shown, m is 1,2, …, i, i represents the total number of thermal power generating units to be increased, n is 1,2, …, j, j represents the total number of the grid-connected line of the wind power station to be increased, and o is 1,2, …, k, k represents the total number of the grid-connected line of the photovoltaic power station to be increased; a. theIG,mRepresenting the annual value of the investment cost and the like of the mth thermal power generating unit to be increased,IIG,mrepresenting the investment cost of the mth thermal power generating unit to be increased, q representing the annual discount rate of the investment, and N G representing the service life of the thermal power generating unit; a. theIWTG,nRepresents the annual value of the investment cost of the nth wind power plant grid-connected line to be increased, andIIWTG,nrepresenting the initial investment cost of the nth thermal power unit to be added, and N WTG representing windEconomic life of the electric field grid-connected line; a. theIPVG,oRepresents the annual value of the investment cost of the grid-connected line of the photovoltaic power station to be increased in the No. o, andIIPVG,orepresents the initial investment cost, N, of the photovoltaic power plant grid-connected line to be added in the o-th itemPVGRepresenting the economic life of a grid-connected line of the photovoltaic power station;
alpha represents an operation cost proportionality coefficient;
Δ T represents a period variation amount, T represents a total number of the year-round period; delta represents the unit grid power loss price, and the unit is ten thousand yuan/(kWh & h); l represents the total number of the original transmission lines; i isu,tRepresents the current flowing on the u-th transmission line in the time period tn,tRepresents the current I flowing on the nth grid-connected line of the wind power plant to be increased in the time period to,tRepresenting the electricity flowing on the photovoltaic power station grid-connected line to be increased in the period tth; ruRepresenting the resistance, R, of the original u-th transmission linenRepresenting the resistance, R, of the nth wind farm grid-connection line to be addedoRepresenting the resistance of the photovoltaic power station grid-connected line to be increased;
ρGrepresents the unit power generation cost, rho, of the thermal power generating unitWTGRepresents the unit generation cost, rho, of the wind turbinePVGRepresenting the unit power generation cost of the photovoltaic unit;the active power output of the thermal power generating unit is shown in a time period t,the active power output of the wind turbine is shown in the time period t,and representing the active power output of the photovoltaic unit in a time period t.
3. The multi-objective optimization-based power grid planning and design method according to claim 1, wherein the method comprises the following steps: the economic loss of the wind abandon light is as follows:
wherein f is2Representing economic loss of wind and light abandoning, cWTGRepresents the economic loss caused by unit air loss, cPVGRepresenting the economic loss due to unit light rejection,
representing the planned active power output of the wind generating set in the grid-connected line of the nth wind power plant in the time period t,
representing the actual active power output of the wind turbine in the grid-connected line of the wind power plant to be increased at the nth time interval,
representing the planned active power output of a photovoltaic unit in the grid-connected line of the photovoltaic power station to be increased at the No. o time of the time t;
representing the actual active power output of a photovoltaic unit in the photovoltaic power station grid-connected line to be increased at the No. o time of the time period t;
wherein v, vi、vr、voRespectively representing the actual wind speed, the cut-in wind speed, the rated wind speed and the cut-out wind speed; wherein E represents the actual illumination intensity, EKExpressing the rated illumination intensity, A expressing the area of the photovoltaic array, eta expressing the light spot conversion efficiency of the photovoltaic array, etainvRepresenting the efficiency of the photovoltaic inverter.
4. The multi-objective optimization-based power grid planning and design method according to claim 1, wherein the method comprises the following steps: the sewage discharge capacity of the power grid is as follows:
wherein N isERepresenting the number of contaminant species, betao、β1、β2Mu and epsilon represent the pollution discharge coefficient of the thermal power generating unit.
5. The multi-objective optimization-based power grid planning and design method according to claim 1, wherein the method comprises the following steps: the multi-target power grid planning model with the following formula is constructed by taking the minimum development cost of a power grid, the economic loss of wind and light abandoning and the minimum discharge capacity of the power grid as the targets,
6. the multi-objective optimization-based power grid planning and design method according to claim 5, wherein the method comprises the following steps: the power grid constraint conditions comprise equality constraints and inequality constraints; the equality constraint comprises a power balance constraint; the inequality constraints comprise load node new energy power generation penetrating power constraints, branch flow constraints, thermal power generating unit output upper and lower limit constraints, wind turbine generator set operation condition constraints and photovoltaic generator set operation condition constraints.
7. The multi-objective optimization-based power grid planning and design method according to claim 5, wherein the method comprises the following steps: the solving of the optimal solution set meeting the power grid constraint condition according to the multi-target power grid planning model comprises the following steps:
and solving the multi-target power grid planning model by adopting an NSGA-II algorithm, and outputting an optimal solution set meeting power grid constraint conditions.
8. The multi-objective optimization-based power grid planning and design method according to claim 1, wherein the method comprises the following steps: the economic and technical evaluation comprises a network system platform, and a data acquisition unit, a data monitoring unit, a data analysis unit and a statistical form query unit which are established on the platform; the network system platform comprises a network basic frame, a data exchange system and a general report system; the network basic frame comprises a plurality of layers of databases, constructs a data storage layer and provides a general data storage service; the data exchange system provides standards-based universal data exchange; the universal report system provides the functions of drawing and generating the network system platform report.
9. The multi-objective optimization-based power grid planning and design method according to claim 8, wherein the method comprises the following steps: the data acquisition unit comprises a plurality of communication channels aiming at different detection points, is wirelessly interconnected with each detection terminal, carries out input processing on the acquired data, and stores the acquired data in the multilayer database in a centralized manner, wherein each detection terminal comprises each electric energy detection meter positioned on a power grid transformer and a power transmission and transformation line.
10. The multi-objective optimization-based power grid planning and design method according to claim 9, wherein: the data monitoring unit comprises an independent GIS platform and a monitoring module based on the GIS platform, the data monitoring unit is used for constructing a power grid geographic information network diagram, and the monitoring module comprises a processor, a data memory and an alarm unit.
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Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103049799A (en) * | 2012-12-10 | 2013-04-17 | 河海大学 | Multi-objective-optimization-based power grid planning and designing method |
CN104299051A (en) * | 2014-10-10 | 2015-01-21 | 国家电网公司 | Network system used for technical and economic analysis and comment of power grid project |
CN107681654A (en) * | 2017-09-06 | 2018-02-09 | 国网福建省电力有限公司经济技术研究院 | Consider the Multi-Objective Electric Power Network Planning method and apparatus of new energy consumption and environmental benefit |
-
2020
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Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103049799A (en) * | 2012-12-10 | 2013-04-17 | 河海大学 | Multi-objective-optimization-based power grid planning and designing method |
CN104299051A (en) * | 2014-10-10 | 2015-01-21 | 国家电网公司 | Network system used for technical and economic analysis and comment of power grid project |
CN107681654A (en) * | 2017-09-06 | 2018-02-09 | 国网福建省电力有限公司经济技术研究院 | Consider the Multi-Objective Electric Power Network Planning method and apparatus of new energy consumption and environmental benefit |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117764258A (en) * | 2024-02-22 | 2024-03-26 | 广东电网有限责任公司广州供电局 | Power supply path optimization method and device |
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