CN107832873B - Comprehensive energy system optimization planning method and device based on double-layer bus type structure - Google Patents

Comprehensive energy system optimization planning method and device based on double-layer bus type structure Download PDF

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CN107832873B
CN107832873B CN201710986210.6A CN201710986210A CN107832873B CN 107832873 B CN107832873 B CN 107832873B CN 201710986210 A CN201710986210 A CN 201710986210A CN 107832873 B CN107832873 B CN 107832873B
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洪博文
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Abstract

The invention provides a comprehensive energy system optimization planning method and device based on a double-layer bus type structure. The method is based on a double-layer bus type structure, adopts a simulation evaluation-intelligent optimization double-module structure to construct a main frame of an optimization planning model of the comprehensive energy system, further expands on the basis of a single-bus type structure, adds a detailed inner-layer topological structure for each bus, and carries out independent simulation modeling according to the self characteristic of each bus so as to ensure the precision requirement of each system; the invention not only considers the energy flow relation among different energy forms in the comprehensive energy system, but also considers the network structure and the transmission characteristic in the same energy form, carries out layered modeling and iterative optimization, and can effectively reflect the difference of heat and electricity transmission characteristics, effectively reduce the dimension and complexity of system simulation and facilitate the combined optimization of the comprehensive energy system through a thermoelectric decoupling mode.

Description

Comprehensive energy system optimization planning method and device based on double-layer bus type structure
Technical Field
The invention belongs to the technical field of electric power system analysis, and particularly relates to a comprehensive energy system optimization planning method and device based on a double-layer bus type structure.
Background
With the development of economy, environmental and energy problems are becoming more severe, and people are continuously looking for more effective methods to improve energy application efficiency. The comprehensive energy system is used as a comprehensive energy body which takes electric power as a center, is coupled by multiple energy sources and is communicated by multiple networks, forms transverse coupling of various forms of energy sources such as cold, heat, electricity and gas and longitudinal communication of multiple links such as energy production, conversion, transmission and consumption, breaks through the existing independent energy supply mode of electricity, heat and gas, and is a novel energy development and utilization mode for improving the comprehensive energy efficiency.
The comprehensive energy system not only comprises various devices such as a distributed power supply, a heat source, an electric energy storage device and a refrigerating machine, but also comprises multiple loads such as cold load, heat load, electricity load, hot water load, steam load and the like under an integrated scene of production and consumption of a user, even comprises multiple pipe networks such as a power grid, an air grid and a heat grid under a regional comprehensive energy supply scene, and the energy flow relation of the comprehensive energy system is extremely complex, so that higher requirements are provided for an optimization planning process.
Some optimization devices and methods for integrated energy systems are disclosed in the prior art. The devices and methods do not usually distinguish the difference of the characteristics of the thermal system and the electrical system, and adopt a unified modeling method; or the network relationship is not considered, the simplification processing is carried out according to the energy flow relationship, the difference of the transmission characteristics of electricity and heat and the network loss can not be effectively reflected, and the precision requirement of the model is difficult to meet for the comprehensive energy system comprising the complex network.
Disclosure of Invention
In order to solve the technical problem, the invention provides a comprehensive energy system optimization planning method based on a double-layer bus type structure, which specifically comprises the following steps:
1) inputting the composition equipment and structure parameters, equipment model parameters and genetic algorithm parameters of the comprehensive energy system;
2) the intelligent optimization module generates an initial population according to a genetic algorithm and transmits system variables corresponding to initial population individuals to the simulation evaluation module;
3) the simulation evaluation module performs decoupling and iteration operation to obtain a simulation result, calculates corresponding evaluation indexes and transmits the evaluation indexes to the intelligent optimization module;
4) the intelligent optimization module determines the numerical value of the individual fitness of the population according to each evaluation index;
5) the intelligent optimization module performs tournament selection, single-point crossing and uniform variation operation according to the individual fitness to obtain a filial generation population, and transmits system variables corresponding to the filial generation population individuals to the simulation evaluation module;
6) the simulation evaluation module performs decoupling and iteration operation to obtain a simulation result, calculates corresponding evaluation indexes and transmits the evaluation indexes to the intelligent optimization module;
7) the intelligent optimization module determines the value of the individual fitness of the offspring population according to each evaluation index;
8) the intelligent optimization module screens and sorts the parent population and the offspring population as a whole to obtain new population individuals;
9) the intelligent optimization module judges whether the filial generation population is the maximum genetic algebra, and if not, the steps 4-8) are repeated; if yes, the intelligent optimization module terminates the optimization program and outputs a final optimization planning result.
Further, the specific contents of the decoupling and the iterative operation performed by the simulation evaluation module include:
firstly, a simulation evaluation module respectively establishes a balance equation of each bus in an outer-layer bus structure according to a double-layer bus structure, the balance equation of each bus consists of the power of each device in the bus, the transmission loss of the bus and the transmission power between the bus and other buses, and the initial value of the transmission loss of each bus is set to be 0; inputting basic data;
calculating the power of each device and the transmission power among the buses by combining an outer bus balance equation and the selected scheduling strategy;
respectively inputting the power of each device in each bus into a simulation calculation model of the internal network of the bus, and performing simulation calculation on each bus according to the selected time scale to calculate the internal network loss value of the bus;
judging whether the changes of the internal network loss values of the buses before and after the simulation calculation are smaller than the allowable error range, if so, turning to the fifth step; if not, outputting the internal network loss value as the transmission loss of each bus, and turning to the second step;
stopping iteration and outputting the system state quantity as a simulation result.
Further, the system state quantity comprises power of each device in each bus, transmission loss of each bus and transmission power between buses.
The invention also provides a comprehensive energy system optimization planning device based on the double-layer bus type structure, which comprises an intelligent optimization module and a simulation evaluation module;
the intelligent optimization module comprises:
a first input unit: the interface is used for providing an input genetic algorithm parameter and transmitting the input data to the initial population generating unit;
an initial population generation unit: the system comprises a simulation evaluation module, a data processing module and a data processing module, wherein the simulation evaluation module is used for generating an initial population according to a genetic algorithm and transmitting system variables corresponding to individuals of the initial population to the simulation evaluation module;
an individual fitness calculation unit: a value for determining the fitness of individual population;
a child population generation unit: the system comprises a simulation evaluation module, a match selection module, a single-point crossing module and a single-point crossing module, wherein the simulation evaluation module is used for performing match selection, single-point crossing and uniform variation operation according to individual fitness to obtain an offspring population and transmitting system variables corresponding to the offspring population individuals to the simulation evaluation module;
screening unit: the system is used for screening and sequencing the parent population and the offspring population as a whole according to the individual fitness of the parent population and the offspring population to obtain new population individuals;
a judging unit: used for judging whether the offspring population is the maximum genetic algebra; if not, the new population individuals are transmitted to the individual fitness calculation unit; if yes, the optimization program is terminated, and termination information is sent to the output unit;
an output unit: the optimization planning method comprises the steps of outputting a final optimization planning result after receiving termination information;
the simulation evaluation module is used for decoupling and iterative operation to obtain a simulation result, simultaneously calculating corresponding evaluation indexes and transmitting the evaluation indexes to the individual fitness calculation unit.
Further, the simulation evaluation module includes:
a second input unit: the interface is used for providing an interface for inputting the composition equipment, the structure parameters and the equipment model parameters of the comprehensive energy system and transmitting the input data to the balance equation unit;
balance equation unit: the balance equation is used for establishing each bus;
a power calculation unit: the system comprises a simulation calculation unit, a balance equation calculation unit, a power calculation unit and a power calculation unit, wherein the simulation calculation unit is used for calculating the power of each device in each bus according to the balance equation of each bus and transmitting the power to the simulation calculation unit;
a simulation calculation unit: the system is used for carrying out simulation calculation on each bus according to the selected time scale and calculating the internal network loss value of each bus;
an alignment unit: the system is used for judging whether the internal network loss value changes of the buses before and after simulation calculation are smaller than an allowable error range, and if not, outputting the internal network loss value as the transmission loss of each bus and transmitting the transmission loss to the power calculation unit; if so, stopping iteration and sending stopping information to the simulation result unit;
a simulation result unit: and the system state quantity is used as a simulation result after the stop information is received, and meanwhile, each corresponding evaluation index is calculated and transmitted to the individual fitness calculation unit.
Further, the system state quantity comprises power of each device in each bus, transmission loss of each bus and transmission power between buses.
Compared with the prior art, the invention has the beneficial effects that:
the method is based on a double-layer bus type structure, adopts a simulation evaluation-intelligent optimization double-module structure to construct a main frame of an optimization planning model of the comprehensive energy system, further expands on the basis of a single-bus type structure, adds a detailed inner-layer topological structure for each bus, and carries out independent simulation modeling according to the self characteristic of each bus so as to ensure the precision requirement of each system; the invention not only considers the energy flow relation among different energy forms in the comprehensive energy system, but also considers the network structure and the transmission characteristic in the same energy form, carries out layered modeling and iterative optimization, and can effectively reflect the difference of heat and electricity transmission characteristics, effectively reduce the dimension and complexity of system simulation and facilitate the combined optimization of the comprehensive energy system through a thermoelectric decoupling mode.
Drawings
FIG. 1 is a block diagram of an outer bus of a typical integrated energy system;
FIG. 2 is a diagram of the internal topology of the electrical bus of FIG. 1;
FIG. 3 is a diagram of a simulation evaluation-intelligent optimization dual module relationship;
FIG. 4 is a flow chart of the method for optimizing and planning the integrated energy system based on the double-bus type structure according to the present invention;
FIG. 5 is a flow chart of the decoupling and iteration operations performed by the simulation evaluation module of the present invention;
fig. 6 is a schematic structural diagram of the comprehensive energy system optimization planning device based on the double-bus type structure.
Detailed Description
The invention provides an optimized planning method of an integrated energy system based on a double-layer bus type structure, which is characterized in that a main frame of an optimized planning model of the integrated energy system is constructed by adopting a simulation evaluation-intelligent optimization double-module structure based on the double-layer bus type structure.
The outer layer of the double-layer bus type structure adopts a single bus type structure to describe the composition structure of the comprehensive energy system. For example, the outer layer structure of a typical integrated energy system shown in fig. 1 includes three buses, namely, an electric bus, a hot bus and a cold bus, various devices are connected to the three buses, and energy conversion between different media is realized through an energy conversion device between the three buses. The single bus type structure of the outer layer can independently model different power supplies, heat sources, energy storage devices and cold/heat/electricity conversion devices, and under the condition of not considering energy transmission characteristics, balance equations written in rows and columns of all buses can be simplified, but the difference of the transmission characteristics of electricity and heat and the loss of a transmission network cannot be effectively reflected, and the precision requirement of the model cannot be met for a comprehensive energy system comprising a complex network.
In order to avoid the problems of the single bus type structure, the structure is further expanded on the basis of the outer single bus type structure, a detailed inner layer topological structure is added for each bus, the function of thermoelectric decoupling in the optimization planning of the comprehensive energy system is emphasized, and the electric heating system is conveniently subjected to separate modeling and combined optimization. Fig. 2 is an inner layer electric network structure topology obtained by network expansion of the electric bus in fig. 1, and the actual topology structure of electric power transmission and the loss of intermediate transmission and conversion links are fully considered. Similarly, both the hot bus and the cold bus in fig. 1 can be expanded to more complex topologies and network relationships, fully reflecting the operating characteristics of the system in which electricity, heat, and cold are decoupleable.
In the simulation evaluation-intelligent optimization dual-module structure, as shown in fig. 3, a simulation evaluation module mainly simulates the technical characteristics of a system through a mathematical simulation model and evaluates the technical, economic, environmental and other comprehensive indexes of a comprehensive energy system planning scheme; and the intelligent optimization module synthesizes index evaluation results of different schemes and obtains an optimized comprehensive energy system planning scheme through a genetic algorithm.
The invention provides a comprehensive energy system optimization planning method based on a double-layer bus-type structure, which comprises the following specific steps as shown in figure 4:
1) inputting genetic algorithm parameters to an intelligent optimization module, and inputting composition equipment, structure parameters and equipment model parameters of the comprehensive energy system to a simulation evaluation module;
the optimization process of the intelligent optimization module adopts a genetic algorithm; the genetic algorithm parameters comprise parameters required in the genetic algorithm, such as population number, individual number, and parameters of main links such as heredity, crossing, variation and the like;
the structural parameters of the comprehensive energy system comprise equipment connection relation, topological structures of an electric bus, a hot bus and a cold bus and the like;
the equipment model parameters comprise relevant parameters of equipment and network connection lines;
2) the intelligent optimization module generates an initial population according to a genetic algorithm and transmits system variables corresponding to initial population individuals to the simulation evaluation module;
the initial population generated by the intelligent optimization module is a first parent population;
each individual in the initial population corresponds to a planning scheme, and each scheme covers data information such as types and capacities of all devices in the comprehensive energy system;
3) the simulation evaluation module performs decoupling and iteration operation to obtain a simulation result, calculates corresponding evaluation indexes and transmits the evaluation indexes to the intelligent optimization module;
4) the intelligent optimization module receives each evaluation index and determines the numerical value of individual fitness of the population according to the evaluation indexes of the genetic algorithm;
5) the intelligent optimization module performs tournament selection, single-point crossing and uniform variation operation according to the individual fitness to obtain a filial generation population, and transmits system variables corresponding to the filial generation population individuals to the simulation evaluation module;
6) the simulation evaluation module performs decoupling and iteration operation to obtain a simulation result, calculates corresponding evaluation indexes and transmits the evaluation indexes to the intelligent optimization module;
7) the intelligent optimization module receives each evaluation index and determines the value of the individual fitness of the offspring population according to the evaluation indexes of the genetic algorithm;
8) the intelligent optimization module screens and sorts the parent population and the offspring population as a whole to obtain new population individuals;
9) the intelligent optimization module judges whether the offspring population is the maximum genetic algebra or not, and the maximum genetic algebra can be set in advance by the intelligent optimization module; if not, substituting the new population individuals obtained in the step 8) as new parent population into the steps 4) to 8); if so, the intelligent optimization module terminates the optimization program and outputs a final optimization planning result, and the final optimization planning result output by the intelligent optimization module is the configuration of each device in the comprehensive energy system, including the information of the type, the installation capacity and the like of each device.
In the invention, the simulation evaluation module mainly evaluates the economy of the scheme of the comprehensive energy system, namely, on the basis of the obtained simulation result, various evaluation indexes (namely, the running cost in the project period of the system) are calculated according to the equipment configuration scheme and the scheduling strategy of the comprehensive energy system; for the comprehensive energy system, the evaluation indexes mainly include investment cost, electricity purchasing cost and system operation and maintenance cost of a project construction period (usually 20 years), and if the system is allowed to sell electricity to the power grid, the evaluation indexes further include power grid electricity purchasing income and the like, and the specific steps are as follows:
(1) net present value
When a project is invested, the net present value is generally adopted to measure the investment benefit, and the smaller the net present value of the total cost of an investment scheme in the life cycle of the project is, the better the scheme is; the net present value of the total cost is calculated as follows:
Figure BDA0001440565580000091
wherein，CNPVNet present value of total cost of project, Cann,tIs the annual average cash flow, KCRF(r,Tpro) For the project cycle capital recovery factor, used to calculate the present value of the annual average cash flow, the calculation formula is as follows:
Figure BDA0001440565580000092
wherein r is the interest rate, TproIs a project period;
(2) cost benefit model
For the comprehensive energy system, the main purpose is to reduce the electricity purchasing cost, the total cost is greater than the total income, the total net present value input is selected for analysis, and the specific calculation formula is as follows:
Cann,t＝Cann,cap+Cann,rep+Cann,om+Cann,ele+Cann,bas-Bsel-Bsub
wherein, Cann,capFor annual cost, Cann,repFor annual replacement costs, Cann,omFor annual maintenance cost, Cann,eleAnnual electricity charge cost, Cann,basFor annual basic electricity charge cost, BselFor annual electric sales income, BsubEarning for subsidy; among the above, annual operation and maintenance cost Cann,omAnnual electricity charge cost Cann,eleAnnual electricity sales income BselAnd subsidy income BsubRelated to system operation, calculation needs to be carried out by combining a simulation result of 8760 hours;
annual capital cost Cann,capThe calculation formula is as follows:
Cann,cap＝Ccap.KCRF(r,Tpro)
wherein, CcapInitial capital costs for all equipment (including photovoltaic modules, energy storage cells, inverters, etc.);
year of project replacement cost Cann,repSubtracting the residual value at the end of the project from the replacement cost of each element of the system in the whole period of the project, and calculating the formula as follows:
Figure BDA0001440565580000101
wherein, CrepFor a single replacement cost, TcomThe life cycle of the elements, T, varies with the particular operating conditions of the stored energysurFor the remaining life of the element at the end of the project, KSF(r,Tcom) Paying fund factor, K, for a component cycleSF(r,Tpro) Paying fund factor for project period, frepCorrecting factors for capital recovery coefficients, which are used for dividing different capital recovery stages generated by element replacement in the whole project period;
annual electricity charge cost Cann,eleThe method is used for representing the electricity consumption cost of the integrated energy system for actually purchasing electricity from the power grid, and the calculation formula is as follows:
Figure BDA0001440565580000102
wherein, Wpur,iThe amount of electricity purchased to the grid for the ith hour, cpur,iElectricity prices are purchased for the ith hour, different electricity prices exist in different periods of electricity consumption peak, flat section and low valley of provinces in China, and electricity charges of 8760 hours of electricity in the whole year need to be added according to the operation condition of the system;
annual basic electricity charge cost Cann,basThe method is used for representing the basic capacity electric charge paid when the large industrial comprehensive energy system in China adopts two electric prices, and is calculated according to the maximum load demand standard in the month:
Figure BDA0001440565580000111
wherein, Pmax,jAverage maximum load capacity of 15 minutes for peak power consumption in the month of jbasBasic electricity fee price collected monthly from the two electricity prices;
annual electricity sales income BselIs used for showing whenThe comprehensive energy system obtains the income of selling the surplus electric quantity to the power grid on line, and the calculation formula is as follows:
Figure BDA0001440565580000112
wherein, Wsel,iThe amount of electricity sold to the grid for the ith hour, cselBuybacking the electricity price for the power grid;
subsidy income BsubThe method mainly adopts the generated energy subsidy of the distributed power supply, and does not consider investment subsidy or electric quantity subsidy which is possibly adopted for energy storage application in the future.
In the present invention, as shown in fig. 5, the specific contents of the decoupling and iteration operations performed by the simulation evaluation module include:
A. the simulation evaluation module respectively establishes a balance equation of each bus in the outer-layer bus structure according to the double-layer bus structure, the balance equation of each bus consists of the power of each device in the bus, the transmission loss of the bus and the transmission power between the bus and other buses, and the initial values of the internal network loss values of the buses are set to be 0; inputting basic data such as illumination, load and the like, and calculating the initial power of each device in each bus;
in the invention, the initial power of the photovoltaic power generation equipment and the wind power generation equipment is calculated according to resource data, the initial power of the gas generator, the energy storage and the like is obtained according to a scheduling strategy, and the scheduling strategy can select a fixed strategy or an optimization strategy;
the external bus bar type structure diagram of the typical integrated energy system shown in fig. 1, wherein the balance equation of the electric bus bar is:
Pgrid+PPV+PWT+Ppgu+LE+PES+PEC+Ploss＝0
wherein, PgridRepresenting the grid exchange power, PPVRepresenting the photovoltaic power generation power, PWTRepresenting the power generated by the fan, PpguRepresents the output power of the cogeneration unit, LERepresenting the electrical load, PESRepresenting stored energy exchange power, PECIndicating the refrigerator power, PlossRepresenting transmission losses, P, of the electrical busbarlossIs 0; in the balance equation of the electric bus, the power flow direction to the electric bus is positive, and the flow direction to the electric bus is negative; the transmission power between the electric bus and the thermal bus is PEC；
The equilibrium equation for the cold bus is:
QPGUηabsorber+COPECPEC+Lcooling+QES,cooling+Qloss,cooling＝0
wherein Q isPGUWaste heat quantity of the cogeneration unit etaabsorberFor absorption chiller efficiency, COPECIs the coefficient of performance (COP), P, of an electric refrigeratorECFor electric refrigerator power, LcoolingFor cold load, QES,coolingFor storing the power of the apparatus, Qloss,coolingIs the cold bus transmission loss;
the equilibrium equation for the thermal busbar is:
QPGUηWH+Qboiler+Lheat+QES,heat+Qloss,heat＝0
wherein Q isPGUWaste heat quantity of the cogeneration unit etaWHFor waste heat recovery efficiency, QboilerFor heat supply to gas-fired boilers, LheatFor thermal load, QES,heatFor the power of the heat storage device, Qloss,heatIs the thermal bus transmission loss;
B. respectively inputting the initial power of each device in each bus into a simulation calculation model of the internal network of the bus, and performing simulation calculation on each bus according to the selected time scale to calculate the internal network loss value of the bus;
in the present invention, the calculation model of the internal network of each bus is selected according to the characteristics of each bus, for example, the calculation model of the internal network of the electrical bus selects a power system load flow calculation model, and the initial power of each device in the electrical bus is input into the calculation model for simulation calculation, and the power system load flow calculation model is as follows:
f(x,u,D,p,A)＝0
umin≤u≤umax
hmin≤h(x,u,D,p,A)≤hmax
wherein x, u, D, p, A are a dependent variable (dependent variable), a control variable (independent variable), an interference variable (disturbance variable), a network element parameter and an incidence matrix representing a structural variable in sequence; the compliance variables x comprise voltage amplitude phase angles of a bus and a motor, input power of each point, load flow of a line and the like, namely main system state quantities to be calculated by a load flow algorithm are influenced by a network structure A, network element parameters p, load change D and adjustment u of a power grid together, and aiming at different load flow problems, various variables have different contents and characteristics;
C. judging whether the changes of the internal network loss values of the buses before and after the simulation calculation are smaller than an allowable error range, wherein the allowable error range is artificially set, preferably set to 0.000001, and if so, turning to the step F; if not, go to step D;
D. returning the internal network loss value of each bus to the outer-layer bus structure, substituting the internal network loss value serving as the transmission loss of each bus into a balance equation of each bus, and recalculating the power of each device in each bus;
in the invention, the calculation of the power of each device in the integrated energy system is determined by a specific scheduling strategy; generally, a fixed strategy or an optimization strategy can be selected, wherein the optimization strategy can be divided into static optimization and dynamic optimization; the fixed strategy makes an operation rule according to the priority of equipment drawn up in advance, and the priority does not change along with the operation environment of the system; the static optimization determines the priority and the operation mode of each device according to the operation cost of each device under the operation environment of the system at the current time or time period; the dynamic optimization considers the operation cost in a scheduling cycle (comprising a plurality of time intervals), and optimizes the system operation by taking the highest total income or the lowest total cost in the scheduling cycle as a target; because the dynamic optimization considers the coordination and cooperation among the multi-period equipment operation, a more ideal optimization effect can be obtained for a comprehensive energy system which usually contains time coupling characteristic elements such as an energy storage element, a generator and the like; because the planning model is focused on, the internal scheduling strategy can be selected according to needs, and the fixed strategy or the optimization strategy can be used for calculating and determining the power of each device, so that the application of the method is not influenced;
E. d, respectively inputting the power of each device in each bus calculated in the step D into a simulation calculation model of the internal network of the bus, recalculating the internal network loss value of the bus, and returning to the step C;
F. stopping iteration, and outputting the system state quantity as a simulation result; the system state quantity comprises power of each device in each bus, transmission loss of each bus and transmission power among the buses, and the simulation evaluation module can calculate each corresponding evaluation index through the system state quantity.
The invention also provides a comprehensive energy system optimization planning device based on the double-layer bus type structure, which comprises an intelligent optimization module and a simulation evaluation module as shown in fig. 6;
the intelligent optimization module comprises:
a first input unit: the interface is used for providing an input genetic algorithm parameter and transmitting the input data to the initial population generating unit;
an initial population generation unit: the system comprises a simulation evaluation module, a data processing module and a data processing module, wherein the simulation evaluation module is used for generating an initial population according to a genetic algorithm and transmitting system variables corresponding to individuals of the initial population to the simulation evaluation module;
an individual fitness calculation unit: a value for determining the fitness of individual population;
a child population generation unit: the system comprises a simulation evaluation module, a match selection module, a single-point crossing module and a single-point crossing module, wherein the simulation evaluation module is used for performing match selection, single-point crossing and uniform variation operation according to individual fitness to obtain an offspring population and transmitting system variables corresponding to the offspring population individuals to the simulation evaluation module;
screening unit: the system is used for screening and sequencing the parent population and the offspring population as a whole according to the individual fitness of the parent population and the offspring population to obtain new population individuals;
a judging unit: used for judging whether the offspring population is the maximum genetic algebra; if not, the new population individuals are transmitted to the individual fitness calculation unit; if yes, the optimization program is terminated, and termination information is sent to the output unit;
an output unit: and the optimization planning module is used for outputting a final optimization planning result after receiving the termination information.
The simulation evaluation module is used for decoupling and iterative operation to obtain a simulation result, simultaneously calculating corresponding evaluation indexes and transmitting the evaluation indexes to the individual fitness calculation unit.
When the device provided by the invention is adopted to carry out optimization planning on the comprehensive energy system based on the double-layer bus type structure, firstly, genetic algorithm parameters are input through the first input unit; the first input unit transmits the data to an initial population generation module; an initial population generating unit generates an initial population P according to a genetic algorithm based on the data0And the initial population P is added0The system variables corresponding to the individuals are transmitted to a simulation evaluation module; the simulation evaluation module obtains a simulation result through decoupling and iterative operation, calculates corresponding evaluation indexes through the simulation result and transmits the evaluation indexes to the individual fitness calculation unit; the individual fitness calculation unit determines an initial population P through the evaluation index0The value of the individual fitness degree transmits the calculation result to the offspring population generation unit; the child population generating unit generates a child population according to the initial population P0The individual fitness is subjected to championship selection, single-point crossing and uniform variation operation to obtain an initial population P0Progeny population Q of0Initial population P0For its offspring population Q0And the offspring population Q0The system variables corresponding to the individuals are transmitted to a simulation evaluation module; the simulation evaluation module obtains a simulation result again through decoupling and iteration operation, calculates corresponding evaluation indexes through the simulation result and transmits the evaluation indexes to the individual fitness calculation unit; the individual fitness calculation unit determines the filial generation population Q through the evaluation index0A value of individual fitness; the screening unit is based on the initial population P0And its progeny population Q0To the initial population P0And its progeny population Q0Screening and sequencing the whole to obtain a new population P1(ii) an individual; at this time, the judging unit judges the filial generation population Q0Whether the number of the generations is the preset maximum genetic algebra or not; if yes, the judging unit terminates the optimization program and sends termination information to the output unit; the output unit outputs a final optimization planning result after receiving the termination information; if not, the population P is divided into1As a new parent population, determining a parent population P sequentially through an individual fitness calculating unit1Value of individual fitness, generation of parent population P by child population generation unit1Progeny population Q of1The simulation evaluation module is used for evaluating the filial generation population Q1Performing simulation evaluation, and determining offspring population Q by an individual fitness calculation unit1Value of individual fitness, screening unit to initial population P1And its progeny population Q1Screening and sorting the whole to obtain a new population P2Individuals and the like, the judging unit judges the filial generation population Q again1Whether the number of the generations is the preset maximum genetic algebra or not; repeating the optimization process until the filial generation population QnThe loop process can be ended for the preset maximum genetic algebra, and the optimization result is output.
In the device provided by the present invention, the simulation evaluation module performs index evaluation on the system design scheme, and then transmits the evaluation result to the intelligent optimization module, as shown in fig. 6, specifically including:
a second input unit: the interface is used for providing an interface for inputting the composition equipment, the structure parameters and the equipment model parameters of the comprehensive energy system and transmitting the input data to the balance equation unit;
balance equation unit: the balance equation is used for establishing each bus;
a power calculation unit: the system comprises a simulation calculation unit, a balance equation calculation unit, a power calculation unit and a power calculation unit, wherein the simulation calculation unit is used for calculating the power of each device in each bus according to the balance equation of each bus and transmitting the power to the simulation calculation unit;
a simulation calculation unit: the system is used for carrying out simulation calculation on each bus according to the selected time scale and calculating the internal network loss value of each bus;
an alignment unit: the system is used for judging whether the internal network loss value changes of the buses before and after simulation calculation are smaller than an allowable error range, and if not, outputting the internal network loss value as the transmission loss of each bus and transmitting the transmission loss to the power calculation unit; if so, stopping iteration and sending stopping information to the simulation result unit;
a simulation result unit: the system state quantity is used as a simulation result after the stop information is received, corresponding evaluation indexes are calculated at the same time, and the evaluation indexes are transmitted to the individual fitness calculation unit; the system state quantity comprises power of each device in each bus, transmission loss of each bus and transmission power between buses.
In the present invention, the decoupling and iteration operations of the simulation evaluation module specifically include: firstly, a balance equation unit establishes a balance equation of each bus according to data input by a second input unit; then the power calculation unit calls a balance equation unit, determines the initial power of each device in the balance equation of each bus according to the resource data or the selected scheduling strategy and transmits the initial power to the simulation calculation unit; the simulation calculation unit carries out simulation and calculates the internal network loss value t of each bus1(ii) a The comparison unit judges whether the absolute values of the difference between two continuous internal network loss values of each bus are less than 0.000001 or not, because the initial value t of the internal network loss value of each bus0Are all set to 0, t1-t0＝t1Therefore, at this time, the comparison unit directly judges the internal network loss value t of each bus1If the absolute values of the bus parameters are less than 0.000001, sending stop information to a simulation result unit, taking the initial power of each device in each bus and the initial transmission power between each bus as a simulation result after the simulation result unit receives the stop information, simultaneously calculating each corresponding evaluation index, and transmitting each evaluation index to an individual fitness calculation unit; if not, the simulation calculation unit compares the internal network loss value t of each bus1Transmitting the power to a power calculation unit; the power calculation unit calls a balance equation unit to calculate the internal network loss value t of each bus1Substituting the transmission loss into a balance equation of each bus, and calculating the power of each device in each bus according to the selected scheduling strategy;and the simulation calculation unit carries out simulation and calculates the internal network loss value t of each bus2(ii) a The comparison unit judges the difference t between two continuous internal network loss values of each bus2-t1Whether the absolute values of the parameters are all less than 0.000001 or not, if so, sending stopping information to a simulation result unit, and after receiving the stopping information, the simulation result unit takes the system state quantity as a simulation result, simultaneously calculates corresponding evaluation indexes and transmits the evaluation indexes to an individual fitness calculation unit; if not, the power calculation unit calls the balance equation unit again to calculate the internal network loss value t of each bus2Substituting the transmission loss into a balance equation of each bus, and recalculating the power of each device in each bus; and the simulation calculation unit carries out simulation and calculates the internal network loss value t of each bus3(ii) a The comparison unit judges t of each bus3-t2Whether or not the absolute values of (a) are all less than 0.000001; repeatedly circulating the iteration process until the comparison unit judges tn-tn-1If the absolute value of the first and second values is less than 0.000001, the iteration is ended, and stop information is sent to the simulation result unit.
Finally, it should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered by the claims of the present invention.

Claims (4)

1. The comprehensive energy system optimization planning method based on the double-layer bus type structure is characterized by comprising the following steps:
1) inputting the composition equipment and structure parameters, equipment model parameters and genetic algorithm parameters of the comprehensive energy system;
2) the intelligent optimization module generates an initial population according to a genetic algorithm and transmits system variables corresponding to initial population individuals to the simulation evaluation module;
3) the simulation evaluation module performs decoupling and iteration operation to obtain a simulation result, calculates corresponding evaluation indexes and transmits the evaluation indexes to the intelligent optimization module;
the specific contents of the decoupling and iteration operations performed by the simulation evaluation module comprise:
firstly, a simulation evaluation module respectively establishes a balance equation of each bus in an outer-layer bus structure according to a double-layer bus structure, the balance equation of each bus consists of the power of each device in the bus, the transmission loss of the bus and the transmission power between the bus and other buses, and the initial value of the transmission loss of each bus is set to be 0; inputting basic data;
calculating the power of each device and the transmission power among the buses by combining an outer bus balance equation and the selected scheduling strategy;
respectively inputting the power of each device in each bus into a simulation calculation model of the internal network of the bus, and performing simulation calculation on each bus according to the selected time scale to calculate the internal network loss value of the bus;
judging whether the changes of the internal network loss values of the buses before and after the simulation calculation are smaller than the allowable error range, if so, turning to the fifth step; if not, outputting the internal network loss value as the transmission loss of each bus, and turning to the second step;
stopping iteration, and outputting the system state quantity as a simulation result;
4) the intelligent optimization module determines the numerical value of the individual fitness of the population according to each evaluation index;
5) the intelligent optimization module performs tournament selection, single-point crossing and uniform variation operation according to the individual fitness to obtain a filial generation population, and transmits system variables corresponding to the filial generation population individuals to the simulation evaluation module;
6) the simulation evaluation module performs decoupling and iteration operation to obtain a simulation result, calculates corresponding evaluation indexes and transmits the evaluation indexes to the intelligent optimization module;
7) the intelligent optimization module determines the value of the individual fitness of the offspring population according to each evaluation index;
8) the intelligent optimization module screens and sorts the parent population and the offspring population as a whole to obtain new population individuals;
9) the intelligent optimization module judges whether the filial generation population is the maximum genetic algebra, and if not, the steps 4-8) are repeated; if yes, the intelligent optimization module terminates the optimization program and outputs a final optimization planning result.
2. The method of claim 1, wherein the system state quantities include power of individual devices in each bus, transmission losses of each bus, and transmission power between buses.
3. The comprehensive energy system optimization planning device based on the double-layer bus type structure is characterized by comprising an intelligent optimization module and a simulation evaluation module;
the intelligent optimization module comprises:
a first input unit: the interface is used for providing an input genetic algorithm parameter and transmitting the input data to the initial population generating unit;
an initial population generation unit: the system comprises a simulation evaluation module, a data processing module and a data processing module, wherein the simulation evaluation module is used for generating an initial population according to a genetic algorithm and transmitting system variables corresponding to individuals of the initial population to the simulation evaluation module;
an individual fitness calculation unit: a value for determining the fitness of individual population;
a child population generation unit: the system comprises a simulation evaluation module, a match selection module, a single-point crossing module and a single-point crossing module, wherein the simulation evaluation module is used for performing match selection, single-point crossing and uniform variation operation according to individual fitness to obtain an offspring population and transmitting system variables corresponding to the offspring population individuals to the simulation evaluation module;
screening unit: the system is used for screening and sequencing the parent population and the offspring population as a whole according to the individual fitness of the parent population and the offspring population to obtain new population individuals;
a judging unit: used for judging whether the offspring population is the maximum genetic algebra; if not, the new population individuals are transmitted to the individual fitness calculation unit; if yes, the optimization program is terminated, and termination information is sent to the output unit;
an output unit: the optimization planning method comprises the steps of outputting a final optimization planning result after receiving termination information;
the simulation evaluation module is used for performing decoupling and iterative operation to obtain a simulation result, calculating corresponding evaluation indexes at the same time, and transmitting the evaluation indexes to the individual fitness calculation unit;
the simulation evaluation module comprises:
a second input unit: the interface is used for providing an interface for inputting the composition equipment, the structure parameters and the equipment model parameters of the comprehensive energy system and transmitting the input data to the balance equation unit;
balance equation unit: the balance equation is used for establishing each bus;
a power calculation unit: the system comprises a simulation calculation unit, a balance equation calculation unit, a power calculation unit and a power calculation unit, wherein the simulation calculation unit is used for calculating the power of each device in each bus according to the balance equation of each bus and transmitting the power to the simulation calculation unit;
a simulation calculation unit: the system is used for carrying out simulation calculation on each bus according to the selected time scale and calculating the internal network loss value of each bus;
an alignment unit: the system is used for judging whether the internal network loss value changes of the buses before and after simulation calculation are smaller than an allowable error range, and if not, outputting the internal network loss value as the transmission loss of each bus and transmitting the transmission loss to the power calculation unit; if so, stopping iteration and sending stopping information to the simulation result unit;
a simulation result unit: and the system state quantity is used as a simulation result after the stop information is received, and meanwhile, each corresponding evaluation index is calculated and transmitted to the individual fitness calculation unit.
4. The apparatus of claim 3, wherein the system state quantities include power of individual devices in each bus, transmission loss of each bus, and transmission power between buses.
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