CN113872250B - Thermal power-based three-level control method for multi-energy complementary energy base - Google Patents
Thermal power-based three-level control method for multi-energy complementary energy base Download PDFInfo
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Abstract
The invention relates to a thermal power-based three-level control method of a multi-energy complementary energy base, wherein the multi-energy complementary energy base adopts a three-level control strategy, a regional level controller executes a first-level regional control, a base level controller executes a second-level base level control, and a power level controller executes a third-level power level control; the regional level controller is used for controlling a plurality of multi-energy complementary energy bases, and the multi-energy complementary energy bases are used as basic units for overall control; the base level controller is used for controlling various power supplies in the multi-energy complementary energy base, calculating control parameters based on the operation working conditions and actual control parameters of each unit, and issuing the control parameters to the power supply level for execution, so that accurate control is realized; the power stage controller is used for carrying out quick response regulation by itself according to regulation information from a base stage. The invention can improve the cooperative control capability of the multi-energy complementary energy base and promote the support and contribution of the multi-energy complementary energy base to the system power angle, voltage, frequency and dynamic stability.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a thermal power-based three-level control method for a multi-energy complementary energy base.
Background
The development and the consumption of non-fossil energy mainly based on new energy are increased, and the decisive force for improving the ratio of the non-fossil energy is provided. The clean energy resource is preferentially utilized, the water electricity and coal electricity regulation performance is fully exerted, the energy storage facilities are properly configured, the flexible response enthusiasm of the demand side is mobilized, the advantages of the new energy resource enrichment region are favorably exerted, the clean electric power is realized for large-scale absorption, the energy structure is optimized, the resource environment constraint is broken, the energy field and the ecological environment are promoted to coordinate and sustainable development, and ecological civilization construction is promoted. The energy pattern of rich coal, lean oil and less gas in China is provided with new energy (photovoltaic, wind power) around the existing thermal power unit, energy is stored, and the new energy is sent out by the original transmission line, so that a multi-energy complementary energy base is formed, and the energy pattern is the development direction of thermal power in the future.
The wind-light-water-fire-storage integrated power system realizes complementation, storage and conversion of various energy sources, can reduce the problems caused by intermittence and instability of wind-light resources, obtains a stable comprehensive output curve of various energy sources, and improves the stability and reliability of the power system. Through the on-site development and the consumption of new energy, the flexible adjustment resources of the power grid can be occupied as little as possible or even not occupied, the wind and light discarding phenomenon is reduced, and the dependence on the power grid is greatly reduced. Meanwhile, the equipment capacity of the energy storage device can be obviously reduced, so that the system cost tends to be reasonable. The control mode of the prior multi-energy complementary energy base is single, the control structure is single, and the cooperative control capability of the multi-energy complementary energy base is not fully exerted.
Disclosure of Invention
The invention aims to provide a thermal power-based three-level control method for a multi-energy complementary energy base, which improves the cooperative control capacity of the multi-energy complementary energy base and improves the support and contribution of the multi-energy complementary energy base to the system power angle, voltage, frequency and dynamic stability.
The invention provides a thermal power-based three-level control method of a multi-energy complementary energy base, wherein the multi-energy complementary energy base adopts a three-level control strategy, a regional level controller executes a first-level regional control, a base level controller executes a second-level base level control, and a power level controller executes a third-level power level control; the regional level controller is used for controlling a plurality of multi-energy complementary energy bases, and the multi-energy complementary energy bases are used as basic units for overall control; the base level controller is used for controlling various power supplies in the multi-energy complementary energy base, calculating control parameters based on the operation working conditions and actual control parameters of each unit, and issuing the control parameters to the power supply level for execution, so that accurate control is realized; the power level controller is used for carrying out self quick response adjustment according to adjustment information from a base level;
the specific steps of the three-level control strategy are as follows:
step 1, setting a regional level control station, incorporating all the multi-energy complementary energy bases in a region into a control system, and monitoring the voltage Ui of each node of the regional system and the frequency Fi of the regional system in the whole course through a regional level controller;
step 2, the regional level controller judges the system node voltage and the system frequency on the basis of the whole-process monitoring of the regional system voltage and the frequency, if the voltage or the frequency is within the allowable range, the step 1 is continued, and if the voltage or the frequency is beyond the allowable range, the step 3 is executed;
step 3, the regional level controller calculates the deviation of the current voltage or frequency, determines the voltage or frequency required adjustment quantity, and sets an adjustment dead zone, so that the regional level controller is prevented from always issuing an adjustment instruction;
step 4, the regional level controller takes the optimal economic cost as an objective function, the response sensitivity of the voltage or frequency of the system, the busbar voltage of the external transmission line of the base, the new energy consumption degree of the base and the base productivity condition as constraint conditions, and the base in the region is comprehensively ordered through an empire competition algorithm;
step 5, the regional level controller issues an adjusting instruction to the base level controller for the base which is ranked in front in the region;
step 6, after receiving the instruction issued by the regional level controller, the base level controller regards the economic cost as an objective function, uses the response sensitivity of each power supply in the base to the voltage or frequency, uses the bus voltage of the power supply to the external transmission line and uses the power supply output condition as constraint conditions, and comprehensively sorts the power supplies in the base through an empire competition algorithm;
step 7, the base level controller orders the power supplies in the base at the front, and sends power generation voltage or frequency adjustment instructions to the power level controller;
and 8, after receiving the base level controller adjusting instruction, the power level controller responds quickly.
Further, the empire competition algorithm in step 4 comprises the following steps:
setting model input parameters, and setting voltages S of various bases in the region to the system iv =dv/dt or frequency S if Response sensitivity of =df/dt, including upper and lower system voltage limits U min \U max Upper and lower system frequency limits f min \f max Bus voltage upper and lower limits U of base external conveying line dmin \U dmax Upper and lower limits ρ of new energy consumption of base min \ρ max Upper and lower limits of base output P imin \P imax ；
According to the number N of the multipotent complementary bases W And the base-to-system voltage S of the multi-energy complementary base iv Or frequency S if To the bus voltage U of the external transmission line d Base new energy consumption degree rho and base power P i Code formation [1× (4t+1)]The vector is initialized to form a population of N countries; initializing the value of each dimension of each country as a random number meeting the constraint condition; calculating the fitness function value, namely the total cost F, of all countries generated by initialization; selecting a plurality of countries as empiric according to the calculated fitness function values, and forming a plurality of empiric groups; setting the index of the current iteration times as g=0;
step 4.1, moving all colonial areas towards the empire inside the group according to the empire competition algorithm;
step 4.2, adopting constraint processing algorithm to make all countries; checking constraints to be within a feasible region;
step 4.3, for each empire group, checking whether one or more colonial areas are present therein with a smaller fitness function value than the empire; if yes, carrying out step 4.4; otherwise, jumping to the step 4.5;
step 4.4, exchanging the positions of colonial and empire with the smallest fitness function value in the group;
step 4.5, calculating the potential values of all empire groups;
step 4.6, selecting the weakest colonial area in the weakest empire as the colonial area with the largest fitness function value from the empire group with the largest fitness function value, and distributing the colonial area to the empire with the largest encroachment probability;
step 4.7, checking whether the empire has lost all colonial land; if yes, step 4.8 is carried out, otherwise step 4.9 is skipped;
step 4.8, eliminating empiric which has lost all colonial land;
step 4.9, checking whether only one empire group remains in the population and all countries in the group have the same fitness function value; if yes, jumping to the step 4.11, otherwise, performing the step 4.10;
step 4.10, checking whether the algorithm has reached the maximum iteration number; if yes, go to step 4.11; otherwise, setting g=g+1 and returning to the step 4.1;
and 4.11, outputting the country information with the lowest fitness function value in the population as an optimal decision variable, and taking the fitness function value as an optimal objective function value.
Further, the empire competition algorithm in step 6 comprises the following steps:
setting model input parameters including upper and lower limits f of base frequency zmin \f zmax Bus voltage upper and lower limits U of base external conveying line dmin \U dmax Bus voltage U of power supply to external transmission line amin /U amax Upper and lower power supply output limits P wmin \P wmax ；
According to the number N of power supplies in the multi-energy complementary base E And the base-to-system voltage S of the multi-energy complementary base WV Or frequency S WF Is sensitive to the bus voltage U of the external transmission line d Power supply output P w Code formation [1× (4t+1)]The vector is initialized to form a population of N countries; initializing the value of each dimension of each country as a random number meeting the constraint condition; calculating the fitness function value, namely the total cost F, of all countries generated by initialization; selecting a plurality of countries as empiric according to the calculated fitness function values, and forming a plurality of empiric groups; setting the index of the current iteration times as g=0;
step 6.1, moving all colonial areas towards the empire inside the group according to the empire competition algorithm;
6.2, adopting constraint processing algorithm to check constraint of all countries (empire and colonial land) to make them be in the feasible region;
step 6.3, for each empire group, checking whether one or more colonial areas are present therein with a smaller fitness function value than the empire; if yes, carrying out step 6.4; otherwise, jumping to the step 6.5;
step 6.4, exchanging the positions of colonial and empire with the smallest fitness function value in the group;
step 6.5, calculating the potential values of all empire groups;
step 6.6, selecting the weakest colonial area in the weakest empire as the colonial area with the largest fitness function value from the empire group with the largest fitness function value, and distributing the colonial area to the empire with the largest encroachment probability;
step 6.7, checking whether the empire has lost all colonial land; if yes, step 6.8 is carried out, otherwise step 6.9 is skipped;
step 6.8, eliminating empiric which has lost all colonial land;
step 6.9, checking whether only one empire group remains in the population and all countries in the group have the same fitness function value; if yes, jumping to the step 6.11, otherwise, performing the step 6.10;
step 6.10, checking whether the algorithm has reached the maximum iteration number; if yes, go to step 6.11; otherwise, setting g=g+1 and returning to the step 6.1;
and 6.11, outputting the country information with the lowest fitness function value in the population as an optimal decision variable, and taking the fitness function value as an optimal objective function value.
Further, the step 8 includes:
optimizing new energy control in power level control, controlling the new energy power supply in a new energy source synchronous mode, and enhancing autonomy of the new energy power supply; in the aspect of frequency modulation, energy is borrowed from the inertia of the wind wheel, the standby capacity is reserved by utilizing the characteristic that new energy is rapidly connected with the grid to achieve the frequency modulation effect, and the new energy unit is controlled by a new energy source synchronous control mode.
By means of the scheme, the cooperative control capacity of the multi-energy complementary energy base can be improved through the multi-energy complementary energy base three-level control method based on thermal power, and the support and contribution of the multi-energy complementary energy base to the system power angle, voltage, frequency and dynamic stability are improved.
The foregoing description is only an overview of the present invention, and is intended to provide a better understanding of the present invention, as it is embodied in the following description, with reference to the preferred embodiments of the present invention and the accompanying drawings.
Drawings
FIG. 1 is a three-stage control schematic of the present invention;
FIG. 2 is a flow chart of a three-stage control method of the present invention.
Detailed Description
The following describes in further detail the embodiments of the present invention with reference to the drawings and examples. The following examples are illustrative of the invention and are not intended to limit the scope of the invention.
Referring to fig. 1 and fig. 2, the present embodiment provides a thermal power-based three-level control method for a multi-energy complementary energy base, where the multi-energy complementary energy base adopts a three-level control strategy, a regional level controller performs a first-level regional control, a base level controller performs a second-level base level control, and a power level controller performs a third-level power level control; the regional level controller is used for controlling a plurality of multi-energy complementary energy bases, and takes the multi-energy complementary energy bases as basic units for overall control, so that the regional level controller has the whole-course detection, rapid identification and rapid calculation capability of a regional system; the base level controller is used for controlling various power supplies in the multi-energy complementary energy base, calculating control parameters based on the operation working conditions and actual control parameters of each unit, and issuing the control parameters to the power supply level for execution, so that accurate control is realized; the power level controller is used for carrying out self quick response adjustment according to adjustment information from a base level;
the specific steps of the three-level control strategy are as follows:
step 1: the method is characterized in that a regional control station is arranged to save one region, and all the multi-energy complementary energy bases in the region are brought into a control system. By means of stability of thermal power, comprehensive coordination control of the area is achieved by utilizing quick response capability and angle direct control capability of new energy grid-connected control, and voltage U of each node in the area is achieved i And frequency F of regional system i And (5) monitoring the whole process.
Step 2: the regional level control station judges the system node voltage and the system frequency on the basis of the whole-process monitoring of the regional system voltage and the frequency, and if the voltage or the frequency is within the allowable range, the regional level control station judges the system node voltage and the system frequency by the following steps: u (U) i ∈(U min ～U max) ，f i ∈(f min ～f max) The zone level controller will proceed to step 1 if the voltage or frequency is outside the allowed range, either:step 3 will be performed.
Step 3: zone level controller for current voltage U ace ＝min{U i -U min ,U i -U max Either frequency face=min { f i -f min ,fi-f max The deviation is calculated and the smallest adjustment is selected as the adjustment needed for the voltage or frequency. According to response time T of three-stage control system s And setting an adjusting dead zone, and avoiding the area control station from always issuing an adjusting instruction.
Step 4: the regional control station takes the economic cost as an optimal target function and uses the voltage S of each base station in the region to the system v =dv/dt or frequency S f Response sensitivity=df/dt, base-to-outside transmission line busbar voltage Ud, base new energy consumption degree ρ, base output P i And (3) taking the situation as a constraint condition, and comprehensively sequencing the power supplies in the base through an empire competition algorithm.
The empire competition algorithm comprises the following steps:
setting model input parameters, and setting voltages S of various bases in the region to the system iv =dv/dt or frequency S if Response sensitivity of =df/dt, including upper and lower system voltage limits U min \U max Upper and lower system frequency limits f min \f max Bus voltage upper and lower limits U of base external conveying line dmin \U dmax Upper and lower limits ρ of new energy consumption of base min \ρ max Upper and lower limits of base output P imin \P imax 。
According to the number N of the multipotent complementary bases W Multiple partsBase-to-system voltage S of complementary base iv Or frequency S if To the bus voltage U of the external transmission line d Base new energy consumption degree rho and base power P i Code formation [1× (4t+1)]The vector is initialized to form a population of N countries; initializing the value of each dimension of each country as a random number meeting the constraint condition; calculating the fitness function value, namely the total cost F, of all countries generated by initialization; selecting a plurality of countries as empiric according to the calculated fitness function values, and forming a plurality of empiric groups; setting the index of the current iteration times as g=0;
step 4.1, moving all colonial areas towards the empire inside the group according to the empire competition algorithm;
step 4.2, adopting constraint processing algorithm to check constraint of all countries (empire and colonial land) to make them be in the feasible region;
step 4.3, for each empire group, checking whether one or more colonial areas are present therein with a smaller fitness function value than the empire; if yes, carrying out step 4.4; otherwise, jumping to the step 4.5;
step 4.4, exchanging the positions of colonial and empire with the smallest fitness function value in the group;
step 4.5, calculating the potential values of all empire groups;
step 4.6, selecting the weakest colonial area in the weakest empire as the colonial area with the largest fitness function value from the empire group with the largest fitness function value, and distributing the colonial area to the empire with the largest encroachment probability;
step 4.7, checking whether the empire has lost all colonial land; if yes, step 4.8 is carried out, otherwise step 4.9 is skipped;
step 4.8, eliminating empiric which has lost all colonial land;
step 4.9, checking whether only one empire group remains in the population and all countries in the group have the same fitness function value; if yes, jumping to the step 4.11, otherwise, performing the step 4.10;
step 4.10, checking whether the algorithm has reached the maximum iteration number; if yes, go to step 4.11; otherwise, setting g=g+1 and returning to the step 4.1;
and 4.11, outputting the country information with the lowest fitness function value in the population as an optimal decision variable, and taking the fitness function value as an optimal objective function value.
Step 5: and issuing an adjusting instruction to a base level controller for the base which is ranked ahead in the area.
Step 6: the multi-energy complementary energy base is used as a control center, a base level control station is arranged, the upper receiving area level control station issues instructions, and the lower fine adjustment is carried out on each power supply in the base, so that the adjustment requirement of the area level control station is met. After receiving the instruction issued by the regional level controller, the base level controller controls the voltage S by each power supply in the base wv =dv/dt or frequency S wf Response sensitivity of =df/dt as an objective function, bus voltage U of power supply to external transmission line a Power supply output P w And (3) taking the situation as a constraint condition, and comprehensively sequencing the power supplies in the base through an empire competition algorithm.
Further, the step 6 empire competition algorithm comprises the following steps:
setting model input parameters including upper and lower limits f of base frequency zmin \f zmax Bus voltage upper and lower limits U of base external conveying line dmin \U dmax Bus voltage U of power supply to external transmission line amin /U amax Upper and lower power supply output limits P wmin \P wmax 。
According to the number N of power supplies in the multi-energy complementary base E And the base-to-system voltage S of the multi-energy complementary base WV Or frequency S WF Is sensitive to the bus voltage U of the external transmission line d Power supply output P w Code formation [1× (4t+1)]The vector is initialized to form a population of N countries; initializing the value of each dimension of each country as a random number meeting the constraint condition; calculating the fitness function value, namely the total cost F, of all countries generated by initialization;selecting a plurality of countries as empiric according to the calculated fitness function values, and forming a plurality of empiric groups; setting the index of the current iteration times as g=0;
step 6.1, moving all colonial areas towards the empire inside the group according to the empire competition algorithm;
6.2, adopting constraint processing algorithm to check constraint of all countries (empire and colonial land) to make them be in the feasible region;
step 6.3, for each empire group, checking whether one or more colonial areas are present therein with a smaller fitness function value than the empire; if yes, carrying out step 6.4; otherwise, jumping to the step 6.5;
step 6.4, exchanging the positions of colonial and empire with the smallest fitness function value in the group;
step 6.5, calculating the potential values of all empire groups;
step 6.6, selecting the weakest colonial area in the weakest empire as the colonial area with the largest fitness function value from the empire group with the largest fitness function value, and distributing the colonial area to the empire with the largest encroachment probability;
step 6.7, checking whether the empire has lost all colonial land; if yes, step 6.8 is carried out, otherwise step 6.9 is skipped;
step 6.8, eliminating empiric which has lost all colonial land;
step 6.9, checking whether only one empire group remains in the population and all countries in the group have the same fitness function value; if yes, jumping to the step 6.11, otherwise, performing the step 6.10;
step 6.10, checking whether the algorithm has reached the maximum iteration number; if yes, go to step 6.11; otherwise, setting g=g+1 and returning to the step 6.1;
and 6.11, outputting the country information with the lowest fitness function value in the population as an optimal decision variable, and taking the fitness function value as an optimal objective function value.
Step 7: and (3) sequencing the power supply at the front in the base, and sending a power generation voltage or frequency adjustment command to the power supply stage.
Step 8: and after receiving the base level controller adjusting instruction, the power level responds quickly.
In the power level control, new energy control is optimized, and a new energy source is controlled in a new energy source synchronization mode, so that autonomy of the new energy source is enhanced. In the aspect of frequency modulation, energy is borrowed from the inertia of the wind wheel, the standby capacity is reserved by utilizing the characteristic that new energy can be rapidly connected with the grid to achieve the frequency modulation effect, and the new energy is controlled by a synchronous control mode.
By the thermal power-based three-level control method for the multi-energy complementary energy base, the cooperative control capability of the multi-energy complementary energy base can be improved, and the support and contribution of the multi-energy complementary energy base to the system power angle, voltage, frequency and dynamic stability are improved.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, and it should be noted that it is possible for those skilled in the art to make several improvements and modifications without departing from the technical principle of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention.
Claims (4)
1. The thermal power-based three-level control method for the multi-energy complementary energy base is characterized in that the multi-energy complementary energy base adopts a three-level control strategy, a regional level controller executes first-level regional control, a base level controller executes second-level base level control, and a power level controller executes third-level power level control; the regional level controller is used for controlling a plurality of multi-energy complementary energy bases, and the multi-energy complementary energy bases are used as basic units for overall control; the base level controller is used for controlling various power supplies in the multi-energy complementary energy base, calculating control parameters based on the operation working conditions and actual control parameters of each unit, and issuing the control parameters to the power supply level for execution, so that accurate control is realized; the power level controller is used for carrying out self quick response adjustment according to adjustment information from a base level;
the specific steps of the three-level control strategy are as follows:
step 1, setting a regional level control station, incorporating all the multi-energy complementary energy bases in a region into a control system, and monitoring the voltage Ui of each node of the regional system and the frequency Fi of the regional system in the whole course through a regional level controller;
step 2, the regional level controller judges the system node voltage and the system frequency on the basis of the whole-process monitoring of the regional system voltage and the frequency, if the voltage or the frequency is within the allowable range, the step 1 is continued, and if the voltage or the frequency is beyond the allowable range, the step 3 is executed;
step 3, the regional level controller calculates the deviation of the current voltage or frequency, determines the voltage or frequency required adjustment quantity, and sets an adjustment dead zone, so that the regional level controller is prevented from always issuing an adjustment instruction;
step 4, the regional level controller takes the optimal economic cost as an objective function, the response sensitivity of the voltage or frequency of the system, the busbar voltage of the external transmission line of the base, the new energy consumption degree of the base and the base productivity condition as constraint conditions, and the base in the region is comprehensively ordered through an empire competition algorithm;
step 5, the regional level controller issues an adjusting instruction to the base level controller for the base which is ranked in front in the region;
step 6, after receiving the instruction issued by the regional level controller, the base level controller regards the economic cost as an objective function, uses the response sensitivity of each power supply in the base to the voltage or frequency, uses the bus voltage of the power supply to the external transmission line and uses the power supply output condition as constraint conditions, and comprehensively sorts the power supplies in the base through an empire competition algorithm;
step 7, the base level controller orders the power supplies in the base at the front, and sends power generation voltage or frequency adjustment instructions to the power level controller;
and 8, after receiving the base level controller adjusting instruction, the power level controller responds quickly.
2. The thermal power-based three-level control method of the multi-energy complementary energy base according to claim 1, wherein the empire competition algorithm in the step 4 comprises the following steps:
setting model input parameters, and setting voltages S of various bases in the region to the system iv =dv/dt or frequency S if Response sensitivity of =df/dt, including upper and lower system voltage limits U min U max Upper and lower system frequency limits f min f max Bus voltage upper and lower limits U of base external conveying line dmin U dmax Upper and lower limits ρ of new energy consumption of base min ρ max Upper and lower limits of base output P imin P imax ；
According to the number N of the multipotent complementary bases W And the base-to-system voltage S of the multi-energy complementary base iv Or frequency S if To the bus voltage U of the external transmission line d Base new energy consumption degree rho and base power P i Code formation [1× (4t+1)]The vector is initialized to form a population of N countries; initializing the value of each dimension of each country as a random number meeting the constraint condition; calculating the fitness function value, namely the total cost F, of all countries generated by initialization; selecting a plurality of countries as empiric according to the calculated fitness function values, and forming a plurality of empiric groups; setting the index of the current iteration times as g=0;
step 4.1, moving all colonial areas towards the empire inside the group according to the empire competition algorithm;
step 4.2, adopting constraint processing algorithm to make all countries; checking constraints to be within a feasible region;
step 4.3, for each empire group, checking whether one or more colonial areas are present therein with a smaller fitness function value than the empire; if yes, carrying out step 4.4; otherwise, jumping to the step 4.5;
step 4.4, exchanging the positions of colonial and empire with the smallest fitness function value in the group;
step 4.5, calculating the potential values of all empire groups;
step 4.6, selecting the weakest colonial area in the weakest empire as the colonial area with the largest fitness function value from the empire group with the largest fitness function value, and distributing the colonial area to the empire with the largest encroachment probability;
step 4.7, checking whether the empire has lost all colonial land; if yes, step 4.8 is carried out, otherwise step 4.9 is skipped;
step 4.8, eliminating empiric which has lost all colonial land;
step 4.9, checking whether only one empire group remains in the population and all countries in the group have the same fitness function value; if yes, jumping to the step 4.11, otherwise, performing the step 4.10;
step 4.10, checking whether the algorithm has reached the maximum iteration number; if yes, go to step 4.11; otherwise, setting g=g+1 and returning to the step 4.1;
and 4.11, outputting the country information with the lowest fitness function value in the population as an optimal decision variable, and taking the fitness function value as an optimal objective function value.
3. The thermal power-based three-level control method of the multi-energy complementary energy base according to claim 1, wherein the empire competition algorithm in the step 6 comprises the following steps:
setting model input parameters including upper and lower limits f of base frequency zmin f zmax Bus voltage upper and lower limits U of base external conveying line dmin U dmax Bus voltage U of power supply to external transmission line amin /U amax Upper and lower power supply output limits P wmin P wmax ；
According to the number N of power supplies in the multi-energy complementary base E And the base-to-system voltage S of the multi-energy complementary base WV Or frequency S WF Is sensitive to the bus voltage U of the external transmission line d Power supply output P w Code formation [1× (4t+1)]The vector is initialized to form a population of N countries; initializing the value of each dimension of each country as a random number meeting the constraint condition; for all countries generated by initialization, calculating the fitness function value, namely the assemblyThe F; selecting a plurality of countries as empiric according to the calculated fitness function values, and forming a plurality of empiric groups; setting the index of the current iteration times as g=0;
step 6.1, moving all colonial areas towards the empire inside the group according to the empire competition algorithm;
step 6.2, adopting constraint processing algorithm to check constraint on all countries, namely empire and colonial, so as to make the constraint be in a feasible domain;
step 6.3, for each empire group, checking whether one or more colonial areas are present therein with a smaller fitness function value than the empire; if yes, carrying out step 6.4; otherwise, jumping to the step 6.5;
step 6.4, exchanging the positions of colonial and empire with the smallest fitness function value in the group;
step 6.5, calculating the potential values of all empire groups;
step 6.6, selecting the weakest colonial area in the weakest empire as the colonial area with the largest fitness function value from the empire group with the largest fitness function value, and distributing the colonial area to the empire with the largest encroachment probability;
step 6.7, checking whether the empire has lost all colonial land; if yes, step 6.8 is carried out, otherwise step 6.9 is skipped;
step 6.8, eliminating empiric which has lost all colonial land;
step 6.9, checking whether only one empire group remains in the population and all countries in the group have the same fitness function value; if yes, jumping to the step 6.11, otherwise, performing the step 6.10;
step 6.10, checking whether the algorithm has reached the maximum iteration number; if yes, go to step 6.11; otherwise, setting g=g+1 and returning to the step 6.1;
and 6.11, outputting the country information with the lowest fitness function value in the population as an optimal decision variable, and taking the fitness function value as an optimal objective function value.
4. The thermal power-based three-level control method of a multi-energy complementary energy base according to claim 1, wherein the step 8 includes:
optimizing new energy control in power level control, controlling the new energy power supply in a new energy source synchronous mode, and enhancing autonomy of the new energy power supply; in the aspect of frequency modulation, energy is borrowed from the inertia of the wind wheel, the standby capacity is reserved by utilizing the characteristic that new energy is rapidly connected with the grid to achieve the frequency modulation effect, and the new energy unit is controlled by a new energy source synchronous control mode.
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