CN118054427B - Operation control method of unified power quality regulator - Google Patents
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Abstract
The invention provides an operation control method of a unified power quality regulator, which comprises the following steps: establishing an electrical value vector diagram of a topological system; establishing a multi-objective optimization problem of a topological system based on the electrical value vector diagram, and converting the multi-objective optimization problem into a comprehensive single-objective optimization problem according to a preset constraint condition; determining a plurality of groups of weight combinations, and acquiring a solution of the comprehensive single-objective optimization problem according to the plurality of groups of weight combinations; determining an adaptability function, selecting an optimal solution under the comprehensive single-objective optimization problem according to the adaptability function, and determining an optimal weight coefficient under the current training working condition according to the optimal solution; and (3) selecting a plurality of training working conditions as input, and taking a corresponding optimal weight coefficient as output, repeating the steps to train to obtain a target agent model, and controlling the operation of the topology system in real time through the target agent model. The operation control method of the unified power quality regulator provided by the invention has high stability and flexibility of system operation.
Description
Technical Field
The invention relates to the technical field of power grid data processing, in particular to an operation control method of a unified power quality regulator.
Background
With the development of a distributed renewable energy system, the phenomena of grid connection, nonlinear load switching and the like of power electronic equipment are generated, the problem of power quality becomes more and more complex, and the problem of power quality related to voltage and current due to capacity limitation is not well restrained. The unified power quality conditioner (Unified Power Quality Conditioner, UPQC) is a power electronic compensation device which is universal and has great potential due to the perfect power quality compensation performance and the compact topology structure.
In order to further improve the application range of the UPQC, some students currently propose to coordinate the distribution of active power and reactive power output by the series-side converter and the parallel-side converter by controlling the phase angle between the load voltage and the voltage of the coupling point, so as to reduce the total apparent power of the UPQC, however, the capacity, the voltage and the current constraint of the series-side converter and the parallel-side converter are not considered through the distribution of the active power and the reactive power, so that the fluctuation of the voltage and the current is easily caused, and the use is influenced. Still scholars have proposed a layered optimization method based on the lagrangian multiplier method to achieve the goal of minimizing load voltage deviation, reactive power generated by the power grid, and total apparent power, however, the layered optimization method based on the lagrangian multiplier method has poor convergence and long operation time.
Disclosure of Invention
Based on this, the present invention aims to provide an operation control method for a unified power quality conditioner, so as to solve the technical problems existing in the prior art.
The invention provides an operation control method of a unified power quality regulator, which is applied to a topology system of an integrated unified power quality regulator, wherein the topology system at least comprises a series converter, a parallel converter, a direct current capacitor, a photovoltaic array and an energy storage battery, one end of the series converter is connected with a power grid through a series power frequency transformer, the other end of the series converter is connected with one end of the parallel converter through the direct current capacitor, the other end of the parallel converter is connected with a load, and the photovoltaic array and the energy storage battery are connected with a direct current end of the integrated unified power quality regulator;
The operation control method comprises the following steps:
Step one, an electrical value vector diagram of the topological system is established, and load voltage, power factor at the power grid side, UPQC total apparent power and system utilization rate are calculated according to the electrical value vector diagram;
Step two, based on the load voltage, the power factor at the power grid side, the UPQC total apparent power and the system utilization rate, establishing a multi-objective optimization problem of the topological system, and converting the multi-objective optimization problem into a comprehensive single-objective optimization problem according to preset constraint conditions, wherein the comprehensive single-objective optimization problem comprises optimization problems of maximizing photovoltaic power generation active power, minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing system utilization rate;
Step three, determining a plurality of groups of weight combinations, and acquiring solutions of the comprehensive single-objective optimization problem according to the plurality of groups of weight combinations;
Determining a fitness function according to the characteristics of each optimization target, selecting an optimal solution of the comprehensive single-target optimization problem under a plurality of groups of weight combinations according to the fitness function, and determining an optimal weight coefficient under the current training working condition according to the optimal solution;
and fifthly, selecting a plurality of training working conditions as input, and selecting a corresponding optimal weight coefficient as output, repeating the first step to the fourth step for training to obtain a target agent model, and controlling the operation of the topological system in real time through the target agent model.
Preferably, the load voltage satisfies the following expression:
In the method, in the process of the invention, For the load voltage, V Gd and V Gq represent the d-axis and q-axis components of the grid voltage, respectively, I Sd and I Sq represent the d-axis and q-axis components of the grid current, respectively, V srd and V srq represent the d-axis and q-axis components of the series converter injection voltage, respectively, R is the impedance,/>Is angular frequency,/>Is the inductance value;
The grid-side power factor satisfies the following expression:
In the method, in the process of the invention, V Ld、VLq、Vsrd、Vsrq is the d-axis component and q-axis component of the load side voltage and the series injection voltage respectively, and I S is the grid current;
the UPQC total apparent power satisfies the following expression:
In the method, in the process of the invention, For UPQC total apparent power,/>Is the apparent power of the series converter,/>For the total apparent power generated by the parallel converters, P pv is the active power generated by the photovoltaic array,/>Active power generated for the energy storage battery;
The system utilization satisfies the following expression:
In the method, in the process of the invention, For the system utilization rate, P pv、Pba is the active power sent by the photovoltaic array and the energy storage battery respectively, k is the relation coefficient reflecting the actual voltage and the nominal voltage of the power grid, λ=v L/VS0,VS0 is the rated voltage of the power grid side, P S、QS is the active power and the reactive power sent by the power grid respectively, S L is the complex power generated by the load,/>、/>The superscript "×" indicates the nominal value of the corresponding variable, respectively the power factor angle of the load and the phase angle of the load voltage and the grid voltage.
Preferably, in the second step, the preset constraint condition at least includes: the method comprises the steps of restraining charge and discharge power of an energy storage battery, restraining charge state of the energy storage battery, restraining charge and discharge power of the energy storage battery, restraining volt-ampere capacity of a series-parallel side converter and restraining voltage and current.
Preferably, the expression of the preset constraint condition satisfies:
Wherein P pv,max is the maximum active power which can be emitted by the photovoltaic array, SOC (t) is the real-time capacity of the energy storage battery at the moment t, SOC min is the minimum electric energy storage capacity of the energy storage battery, SOC max is the maximum electric energy storage capacity of the energy storage battery, P ch (t) is the real-time charging power of the energy storage battery, P dis (t) is the real-time discharging power of the energy storage battery, P ch,max、Pdis,max is the maximum charging power and the maximum discharging power of the energy storage battery respectively, V sr is the voltage injected by the series converter, I sh is the current injected by the parallel converter, S sr is the capacity of the series converter, and S sh is the capacity of the parallel converter.
Preferably, the multi-objective optimization problem satisfies the following expression:
Wherein Min represents minimum value operation, P pv is active power generated by the photovoltaic array, P pv,max is maximum active power which can be generated by the photovoltaic array, V S0 is the rated voltage at the grid side, PF is the power factor at the grid side,/>The system utilization rate is the system utilization rate;
the expression of the solution of the comprehensive single-objective optimization problem satisfies the following conditions:
In the method, in the process of the invention, For solving the comprehensive single-objective optimization problem, the weight coefficient for maximizing the photovoltaic power generation active power is recorded as 1,/>、/>、/>The method comprises the steps of respectively minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing weight coefficient of system utilization.
Preferably, the expression of the fitness function satisfies:
In the method, in the process of the invention, 、/>、/>、/>The system is an optimal solution set capable of meeting the multi-objective optimization problem, the coefficient for maximizing the active power of the photovoltaic power generation is recorded as1, and w 1、w2、w3 is a self-adaptive degree function coefficient for minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing system utilization rate respectively; p pv,min is the minimum active power which can be sent out by the photovoltaic array, P pv,max is the maximum active power which can be sent out by the photovoltaic array, deltaV min is the minimum voltage deviation value which can be accepted by the system, deltaV max is the maximum voltage deviation value which can be accepted by the system, PF min is the minimum power factor at the power grid side, PF max is the maximum power factor at the power grid side, eta min is the minimum utilization rate of the system, and eta max is the maximum utilization rate of the system.
Preferably, in the third step, a PSO algorithm is adopted to obtain a solution of the comprehensive single-objective optimization problem according to a plurality of groups of weight combinations.
Preferably, in the fifth step, an extreme learning machine algorithm is adopted to train to obtain a target agent model based on the extreme learning machine.
Compared with the prior art, the application has the beneficial effects that: the operation control method of the unified power quality conditioner provided by the application comprises the steps of firstly establishing an electrical value vector diagram of a topological system, establishing a multi-objective optimization problem based on the electrical value vector diagram, converting the multi-objective optimization problem into a comprehensive single-objective optimization problem according to a preset constraint condition, and solving a solution of the comprehensive single-objective optimization problem under a plurality of groups of weight combinations by using a PSO algorithm; formulating a reasonable fitness function, utilizing the established fitness function to establish an optimal solution set of the comprehensive single-objective optimization problem under a plurality of groups of weight combinations, and determining an optimal weight coefficient under the working condition; then obtaining the optimal weight coefficient combination of the comprehensive single-objective optimization problem under the fitness function; based on an extreme learning machine algorithm, taking all working conditions of a source-network-load-storage system integrated with UPQC as input and taking a weight coefficient as output, training a proxy model based on the extreme learning machine, and applying the obtained target proxy model to the system so as to control the operation of the system in real time; compared with the traditional source-network-charge-storage system, the system considers the capacity, voltage and current constraints of the series-side converter and the parallel-side converter, can provide reactive compensation, and has better capability of suppressing voltage sag and harmonic waves; the photovoltaic array is connected into a power grid through the serial/parallel side converter, and the battery is connected into the power grid through the direct-current link, so that the permeability of the photovoltaic system can be improved; the access of the energy storage battery provides more sufficient margin for the optimized operation of the system, and the flexibility of the system is enhanced; the photovoltaic array and the battery can transmit energy to the load and the power grid through the serial/parallel converter, so that the reactive power and the voltage compensation range can be conveniently improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
FIG. 1 is a block diagram of a source-net-load-store topology system of a unified power quality conditioner according to an embodiment of the present invention;
Fig. 2 is a flowchart of an operation control method of a unified power quality conditioner according to an embodiment of the present invention.
The invention will be further described in the following detailed description in conjunction with the above-described figures.
Detailed Description
In order that the invention may be readily understood, a more complete description of the invention will be rendered by reference to the appended drawings. Several embodiments of the invention are presented in the figures. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The embodiment of the invention provides an operation control method of a unified power quality conditioner, which is applied to a source-network-load-storage topological system integrating the unified power quality conditioner.
Referring to fig. 1, the "source-grid-load-storage" topology system of the integrated unified power quality regulator at least comprises a series converter, a parallel converter, a dc capacitor, a photovoltaic array and an energy storage battery, wherein one end of the series converter is connected with a power grid through a series power frequency transformer, the other end of the series converter is connected with one end of the parallel converter through the dc capacitor, the other end of the parallel converter is connected with a load, and the photovoltaic array and the energy storage battery are connected with a dc end of the integrated unified power quality regulator.
In the figure, A, B and C respectively represent three-phase transmission lines of a power system A, B and C, and N represents a neutral line; v Ga,vGb,vGc represents A, B, C phase grid voltage values respectively; v Sa,vSb,vSc represents A, B, C phase pcc voltage values, respectively; v sra,vsrb,vsrc represents A, B, C phase series injection voltage values, respectively; v La,vLb,vLc represents A, B, C phase load voltage values, respectively; i Sa,iSb,iSc represents A, B, C phase grid current values respectively; i La,iLb,iLc represents A, B, C phase load current values, respectively; c sra,Csrb,Csrc represents A, B, C phase series filter capacitance values respectively; c d represents the capacitance value of the middle direct current bus; v d represents an intermediate dc bus voltage value; AC stands for alternating current; DC stands for direct current.
The series-side converter may be a three-phase series-side converter for improving voltage quality (harmonics, amplitudes, transients, etc.) and isolating the mutual transfer of the load-carrying harmful currents. The parallel-side converter may be a three-phase parallel-side converter for outputting current to compensate for load current quality (harmonics, reactive, unbalance, etc.). Compared with the traditional source-network-load-storage system, the system not only can provide reactive compensation, but also has better capability of suppressing voltage sag and harmonic waves; the photovoltaic array is connected into a power grid through the serial/parallel side converter, and the battery is connected into the power grid through the direct-current link, so that the permeability of the photovoltaic system can be improved; the access of the energy storage battery provides more sufficient margin for the optimized operation of the system, and the flexibility of the system is enhanced; the photovoltaic array and the battery can transmit energy to the load and the power grid through the serial/parallel converter, so that the reactive power and the voltage compensation range can be conveniently improved.
Referring to fig. 2, the operation control method includes steps one to five.
Step one, an electrical value vector diagram of the topological system is established, and load voltage, power factor at the power grid side, UPQC total apparent power and system utilization rate are calculated according to the electrical value vector diagram;
In particular implementations, it is assumed that the grid voltage and grid current phasors are represented as ，/>And/>Is the series injection voltage phasor and the parallel injection current phasor,/>And/>The load voltage and current phasors, respectively, where/>、/>The power factor angle of the load and the phase angle of the load voltage and the grid voltage are respectively,/>、/>Respectively, power grid voltage and power grid current,/>、/>Voltage and phase angle injected for series converters respectively,/>For the load voltage,/>For load current,/>Is the phase angle of the load current.
In an active power distribution network, a transformer substation supplies power to all end users, and the relation between a power grid voltage V G and a public connection point voltage is as follows:
considering the equivalent line impedance as r+ jwL, the voltage drop in the line impedance is expressed as:
in combination with the above two equations, consider a v G phase angle of 0 and a point of common coupling voltage of:
Wherein, I Sd and I Sq are d-axis component and q-axis component of the grid current respectively, V Gd and V Gq are d-axis component and q-axis component of the grid voltage respectively, V srd and V srq are d-axis component and q-axis component of the series converter injection voltage respectively, Δv d、△Vq is d-axis component and q-axis component of the voltage drop respectively, V S is kV S0,VS0 as the grid side rated voltage, k is a relation coefficient reflecting the actual voltage and the nominal voltage of the grid, and λ=v L/VS0.
The load voltage is mainly affected by the line impedance and the grid current. When the distributed photovoltaic array transmits energy to the power grid, the current I Sd is negative, and the voltage V S is always larger than the power grid voltage V G. The grid voltage is determined mainly by the values of the grid currents I Sd and I Sq and the equivalent resistance.
The load voltage satisfies the following expression:
In the method, in the process of the invention, For the load voltage, V Gd and V Gq represent the d-axis and q-axis components of the grid voltage, respectively, I Sd and I Sq represent the d-axis and q-axis components of the grid current, respectively, V srd and V srq represent the d-axis and q-axis components of the series converter injection voltage, respectively, R is the impedance,/>Is angular frequency,/>Is the inductance value;
the series converter side injection voltage is:
Wherein k is a relation coefficient reflecting the actual voltage and the nominal voltage of the power grid;
the complex power generated by the power grid is as follows:
P S and Q S are active power and reactive power respectively emitted by the power grid, the load active power P L will be completely provided by the power grid, the photovoltaic array and the energy storage battery, the load reactive power Q L is provided by the UPQC and the power grid together, then:
In the method, in the process of the invention, P pv is active power generated by a photovoltaic array, P ba is active power generated by an energy storage battery, and Q UPQC is reactive power generated by UPQC.
The grid-side power factor satisfies the following expression:
In the method, in the process of the invention, V Ld、VLq、Vsrd、Vsrq is the d-axis component and q-axis component of the load side voltage and the series injection voltage respectively, and I S is the grid current;
the complex power generated by the series converter is:
The apparent power of the series converter is calculated as:
the complex power produced by the parallel converter is expressed as:
the total apparent power produced by the parallel converter is expressed as:
The total apparent power of a "source-net-load-store" system integrating UPQC can be expressed as:
In the method, in the process of the invention, For UPQC total apparent power,/>Is the apparent power of the series converter,/>For the total apparent power generated by the parallel converters, P pv is the active power generated by the photovoltaic array,/>Active power generated for the energy storage battery;
The system utilization satisfies the following expression:
In the method, in the process of the invention, For the system utilization rate, P pv、Pba is the active power sent by the photovoltaic array and the energy storage battery respectively, k is the relation coefficient reflecting the actual voltage and the nominal voltage of the power grid, λ=v L/VS0,VS0 is the rated voltage of the power grid side, P S、QS is the active power and the reactive power sent by the power grid respectively, S L is the complex power generated by the load,/>、/>The superscript "×" indicates the nominal value of the corresponding variable, respectively the power factor angle of the load and the phase angle of the load voltage and the grid voltage.
Step two, based on the load voltage, the power factor at the power grid side, the UPQC total apparent power and the system utilization rate, establishing a multi-objective optimization problem of the topological system, and converting the multi-objective optimization problem into a comprehensive single-objective optimization problem according to preset constraint conditions, wherein the comprehensive single-objective optimization problem comprises optimization problems of maximizing photovoltaic power generation active power, minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing system utilization rate;
Optionally, in a specific implementation, the preset constraint condition at least includes: the energy storage battery charging and discharging power constraint, the volt-ampere capacity of the series-parallel side converter and the voltage-current constraint, and the expression of the preset constraint condition meets the following conditions:
Wherein P pv,max is the maximum active power which can be emitted by the photovoltaic array, SOC (t) is the real-time capacity of the energy storage battery at the moment t, SOC min is the minimum electric energy storage capacity of the energy storage battery, SOC max is the maximum electric energy storage capacity of the energy storage battery, P ch (t) is the real-time charging power of the energy storage battery, P dis (t) is the real-time discharging power of the energy storage battery, P ch,max、Pdis,max is the maximum charging power and the maximum discharging power of the energy storage battery respectively, V sr is the voltage injected by the series converter, I sh is the current injected by the parallel converter, S sr is the capacity of the series converter, and S sh is the capacity of the parallel converter.
The multi-objective optimization problem satisfies the following expression:
Wherein Min represents minimum value operation, P pv is active power generated by the photovoltaic array, P pv,max is maximum active power which can be generated by the photovoltaic array, V S0 is the rated voltage at the grid side, PF is the power factor at the grid side,/>The system utilization rate is the system utilization rate;
the expression of the solution of the comprehensive single-objective optimization problem satisfies the following conditions:
In the method, in the process of the invention, For solving the comprehensive single-objective optimization problem, the weight coefficient for maximizing the photovoltaic power generation active power is recorded as 1,/>、/>、/>The method comprises the steps of respectively minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing weight coefficient of system utilization.
Step three, determining a plurality of groups of weight combinations, and acquiring solutions of the comprehensive single-objective optimization problem according to the plurality of groups of weight combinations;
optionally, in a specific implementation, a PSO algorithm may be used to obtain a solution of the comprehensive single-objective optimization problem according to a number of sets of the weight combinations.
Determining a fitness function according to the characteristics of each optimization target, selecting an optimal solution of the comprehensive single-target optimization problem under a plurality of groups of weight combinations according to the fitness function, and determining an optimal weight coefficient under the current training working condition according to the optimal solution;
Optionally, the weight combinations of the groups can be freely selected according to actual working conditions.
The expression of the fitness function satisfies:
In the method, in the process of the invention, 、/>、/>、/>The system is an optimal solution set capable of meeting the multi-objective optimization problem, the coefficient for maximizing the active power of the photovoltaic power generation is recorded as1, and w 1、w2、w3 is a self-adaptive degree function coefficient for minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing system utilization rate respectively; p pv,min is the minimum active power which can be sent out by the photovoltaic array, P pv,max is the maximum active power which can be sent out by the photovoltaic array, deltaV min is the minimum voltage deviation value which can be accepted by the system, deltaV max is the maximum voltage deviation value which can be accepted by the system, PF min is the minimum power factor at the power grid side, PF max is the maximum power factor at the power grid side, eta min is the minimum utilization rate of the system, and eta max is the maximum utilization rate of the system.
And fifthly, selecting a plurality of training working conditions as input, and selecting a corresponding optimal weight coefficient as output, repeating the first step to the fourth step for training to obtain a target agent model, and controlling the operation of the topological system in real time through the target agent model.
Optionally, in the specific implementation, based on an extreme learning machine algorithm, a plurality of preset training conditions are taken as input, corresponding optimal weight coefficients are taken as output, the steps one to four are repeated for training to obtain a target agent model based on the extreme learning machine, and after the training of the extreme learning machine model is completed, accurate output estimation of optimal operation of a source-network-load-storage system integrated with UPQC can be realized for any given weight input combination, so that real-time control of operation of the system is realized.
It will be appreciated that the proxy model training requires training data, which includes input data operating parameters (k, P L、QL、Ppv,max and P ba,max) and output weight coefficients (w 1、w2、w3); after the target training model is obtained, when the actual working condition parameters (k, P L、QL、Ppv, max、Pba,max) are given, an output solution set (w 1、w2、w3) can be obtained, and 20 values can be selected for each input variable in order to extract data with high fidelity.
The extreme learning machine algorithm has the advantages of extremely high training speed, good generalization, good convergence, general approximation and the like. The extreme learning machine is unique in that the weights and biases of the hidden nodes are randomly selected, and thus the output weights are easy to calculate.
In summary, the operation control method of the unified power quality conditioner provided by the application comprises the steps of firstly establishing an electrical value vector diagram of a topological system, converting a multi-objective optimization problem into a comprehensive single-objective optimization problem based on a multi-objective optimization problem of the topological system of the electrical value vector diagram according to preset constraint conditions, wherein the multi-objective optimization problem comprises a multi-optimization problem of maximizing active power of photovoltaic power generation, minimizing load voltage deviation, maximizing power factor of a power grid side and maximizing utilization rate of the system, and obtaining solutions of the comprehensive single-objective optimization problem under a plurality of groups of weight combinations by using a PSO algorithm; formulating a reasonable fitness function, utilizing the established fitness function to establish an optimal solution set of the comprehensive single-objective optimization problem under a plurality of groups of weight combinations, and determining an optimal weight coefficient under the working condition; then obtaining the optimal weight coefficient combination of the comprehensive single-objective optimization problem under the fitness function; based on an extreme learning machine algorithm, taking all working conditions of a source-network-load-storage system integrated with UPQC as input and taking a weight coefficient as output, training a proxy model based on the extreme learning machine, and applying the obtained target proxy model to the system so as to control the operation of the system in real time; compared with the traditional source-network-charge-storage system, the operation control method of the unified power quality regulator provided by the application considers the capacity, voltage and current constraints of the series-side converter and the parallel-side converter, can provide reactive compensation, and has better capacity of inhibiting voltage sag and harmonic waves; the photovoltaic array is connected into a power grid through the serial/parallel side converter, and the battery is connected into the power grid through the direct-current link, so that the permeability of the photovoltaic system can be improved; the access of the energy storage battery provides more sufficient margin for the optimized operation of the system, and the flexibility of the system is enhanced; the photovoltaic array and the battery can transmit energy to the load and the power grid through the serial/parallel converter, so that the reactive power and the voltage compensation range can be conveniently improved.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
Claims (7)
1. The operation control method of the unified power quality conditioner is characterized by being applied to a topology system of the integrated unified power quality conditioner, wherein the topology system at least comprises a series converter, a parallel converter, a direct current capacitor, a photovoltaic array and an energy storage battery, one end of the series converter is connected with a power grid through a series power frequency transformer, the other end of the series converter is connected with one end of the parallel converter through the direct current capacitor, the other end of the parallel converter is connected with a load, and the photovoltaic array and the energy storage battery are connected with a direct current end of the integrated unified power quality conditioner;
The operation control method comprises the following steps:
Step one, an electrical value vector diagram of the topological system is established, and load voltage, power factor at the power grid side, UPQC total apparent power and system utilization rate are calculated according to the electrical value vector diagram;
Step two, based on the load voltage, the power factor at the power grid side, the UPQC total apparent power and the system utilization rate, establishing a multi-objective optimization problem of the topological system, and converting the multi-objective optimization problem into a comprehensive single-objective optimization problem according to preset constraint conditions, wherein the comprehensive single-objective optimization problem comprises optimization problems of maximizing photovoltaic power generation active power, minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing system utilization rate;
Step three, determining a plurality of groups of weight combinations, and acquiring solutions of the comprehensive single-objective optimization problem according to the plurality of groups of weight combinations;
Determining a fitness function according to the characteristics of each optimization target, selecting an optimal solution of the comprehensive single-target optimization problem under a plurality of groups of weight combinations according to the fitness function, and determining an optimal weight coefficient under the current training working condition according to the optimal solution;
Fifthly, selecting a plurality of training working conditions as input, and selecting a corresponding optimal weight coefficient as output, repeating the first step to the fourth step for training to obtain a target agent model, and controlling the operation of the topology system in real time through the target agent model; the load voltage satisfies the following expression:
In the method, in the process of the invention, For the load voltage, V Gd and V Gq represent the d-axis and q-axis components of the grid voltage, respectively, I Sd and I Sq represent the d-axis and q-axis components of the grid current, respectively, V srd and V srq represent the d-axis and q-axis components of the series converter injection voltage, respectively, R is the impedance,/>Is angular frequency,/>Is the inductance value;
The grid-side power factor satisfies the following expression:
In the method, in the process of the invention, V Ld、VLq、Vsrd、Vsrq is the d-axis component and q-axis component of the load side voltage and the series injection voltage respectively, and I S is the grid current;
the UPQC total apparent power satisfies the following expression:
In the method, in the process of the invention, For UPQC total apparent power,/>Is the apparent power of the series converter,/>For the total apparent power generated by the parallel converters, P pv is the active power generated by the photovoltaic array,/>Active power generated for the energy storage battery;
The system utilization satisfies the following expression:
In the method, in the process of the invention, For the system utilization rate, P pv、Pba is the active power sent by the photovoltaic array and the energy storage battery respectively, k is the relation coefficient reflecting the actual voltage and the nominal voltage of the power grid, λ=v L/VS0,VS0 is the rated voltage of the power grid side, P S、QS is the active power and the reactive power sent by the power grid respectively, S L is the complex power generated by the load,/>、/>The superscript "×" indicates the nominal value of the corresponding variable, respectively the power factor angle of the load and the phase angle of the load voltage and the grid voltage.
2. The method of claim 1, wherein in the second step, the preset constraint at least includes: the method comprises the steps of restraining charge and discharge power of an energy storage battery, restraining charge state of the energy storage battery, restraining charge and discharge power of the energy storage battery, restraining volt-ampere capacity of a series-parallel side converter and restraining voltage and current.
3. The method of operation control of a unified power quality conditioner according to claim 2 wherein the expression of the preset constraint satisfies:
Wherein P pv,max is the maximum active power which can be emitted by the photovoltaic array, SOC (t) is the real-time capacity of the energy storage battery at the moment t, SOC min is the minimum electric energy storage capacity of the energy storage battery, SOC max is the maximum electric energy storage capacity of the energy storage battery, P ch (t) is the real-time charging power of the energy storage battery, P dis (t) is the real-time discharging power of the energy storage battery, P ch,max、Pdis,max is the maximum charging power and the maximum discharging power of the energy storage battery respectively, V sr is the voltage injected by the series converter, I sh is the current injected by the parallel converter, S sr is the capacity of the series converter, and S sh is the capacity of the parallel converter.
4. A method of controlling operation of a unified power quality conditioner according to claim 3 wherein the multi-objective optimization problem satisfies the following expression:
Wherein Min represents minimum value operation, P pv is active power generated by the photovoltaic array, P pv,max is maximum active power which can be generated by the photovoltaic array, V S0 is the rated voltage at the grid side, PF is the power factor at the grid side,/>The system utilization rate is the system utilization rate;
the expression of the solution of the comprehensive single-objective optimization problem satisfies the following conditions:
In the method, in the process of the invention, For solving the comprehensive single-objective optimization problem, the weight coefficient for maximizing the photovoltaic power generation active power is recorded as 1,/>、/>、/>The method comprises the steps of respectively minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing weight coefficient of system utilization.
5. The method of operation control of a unified power quality conditioner according to claim 4 wherein the expression of the fitness function satisfies:
In the method, in the process of the invention, 、/>、/>、/>The system is an optimal solution set capable of meeting the multi-objective optimization problem, the coefficient for maximizing the active power of the photovoltaic power generation is recorded as1, and w 1、w 2、w 3 is a self-adaptive degree function coefficient for minimizing load voltage deviation, maximizing power factor at the power grid side and maximizing system utilization rate respectively; p pv,min is the minimum active power which can be sent out by the photovoltaic array, P pv,max is the maximum active power which can be sent out by the photovoltaic array, deltaV min is the minimum voltage deviation value which can be accepted by the system, deltaV max is the maximum voltage deviation value which can be accepted by the system, PF min is the minimum power factor at the power grid side, PF max is the maximum power factor at the power grid side, eta min is the minimum utilization rate of the system, and eta max is the maximum utilization rate of the system.
6. The method of claim 1, wherein in step three, a PSO algorithm is used to obtain solutions to the comprehensive single-objective optimization problem based on a combination of several sets of the weights.
7. The method of claim 1, wherein in step five, an extreme learning machine algorithm is used to train the target agent model based on the extreme learning machine.
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