CN103490444B - Method for photovoltaic grid connected coordination control based on MAGA - Google Patents
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Abstract
The invention relates to a method for photovoltaic grid connected coordination control based on the MAGA. The method for photovoltaic grid connected coordination control based on the MAGA is characterized by comprising the following steps that large-scale photovoltaic grid connected coordination control architecture composed according to the MA technology is established; parameters of each Agent are collected and each Agent is controlled; information is transmitted and fed back; photovoltaic grid connected coordination control is achieved through the MAGA; the information is fed back and further optimization is achieved. According to the method for photovoltaic grid connected coordination control based on the MAGA, a micro-grid system composed of a large-scale photovoltaic power generation system, a fuel cell, a storage battery and the like is controlled through the MAGA technology according to the characteristic that the photovoltaic power generation system has access to a power distribution network, the maximum-efficiency output of the photovoltaic power generation system is achieved, the power supply reliability of the system is improved, and the efficient use of energy is achieved.
Description
Technical field
The invention belongs to technical field of power generation, especially a kind of grid-connected control method for coordinating based on MAGA.
Background technology
Due to the exhaustion day by day of petroleum-based energy, the extensive utilization of new forms of energy is the trend of following power network development.Along with distributed energy generating and the fast development of interconnection technology and extensive use, the interconnection technology of photovoltaic generating system will be the emphasis of power network development from now on.Due to large-scale photovoltaic generating be connected to the grid after, after distribution system there occurs larger change, cooperation control is carried out to distributed power source, finally realize clean energy resource and utilize maximization, and when extreme accident is occurred to power distribution network, to positive, the effective supporting role of power distribution network, ensure power distribution network safety, reliably and efficiently run, therefore, the control method for coordinating of large-scale photovoltaic electricity generation grid-connecting is needed to realize carrying out cooperation control to photovoltaic generating system is grid-connected, but, also there is no the effective coordination control method that large-scale photovoltaic electricity generation system is grid-connected at present.Due to large-scale photovoltaic electricity generation system grid-connected after, its power supply relation is comparatively complicated, and therefore, the control method for coordinating of conventional energy resource generating can not be suitable for the cooperation control of large-scale photovoltaic electricity generation grid-connecting, can not give full play to the advantage of photovoltaic generating system.
In the prior art, about Agent(intelligent body) technology is for the correlative study analysis in microgrid laboratory, and the research adopting Agent technology to carry out cooperation control grid-connected specially still belongs to blank; Simultaneously, use genetic algorithm can analyze the developing relevant issues of intelligent grid, but, traditional genetic algorithm, in analytic process, if there is fitness Selecting parameter improperly in situation, likely converges on local optimum, and global optimum can not be reached, and for high-dimension function, convergence rate is very slow, even can not restrain.Therefore, how to give full play to the advantage of photovoltaic generating system, realizing effective is problem in the urgent need to address at present to grid-connected cooperation control.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, a kind of grid-connected control method for coordinating based on MAGA is provided, it is according to the feature of photovoltaic system access distribution, utilize the communication mechanism of multi-Agent, set up corresponding control strategy, and pass through information transmission and the feedback mechanism of this system, next step control strategy is constantly optimized, to guarantee the optimal control exporting system power and utilize.
The present invention solves existing technical problem and takes following technical scheme to realize:
Based on a grid-connected control method for coordinating of MAGA, comprise the following steps:
Step 1: set up and adopt the large-scale photovoltaic grid-connected coordination of MA technological maheup to control framework;
Step 2: gather the parameter in each Agent, and provide certain control to Agent;
Step 3: information transmission and feedback: among the information transmission in each Agent to the Agent of circuit, meanwhile, among the information feed back in circuit to initial Agent, and arranges the running status of himself;
Step 4: adopt MAGA algorithm realization grid-connected cooperation control: circuit Agent is supplied to photovoltaic main website Agent administrative circuit and unit Agent operation conditions, while photovoltaic main website Agent provide control strategy according to MAGA algorithm to circuit Agent and transfer to circuit Agent to change the running status of each unit according to circuit operating condition;
Step 5: information feed back and further optimization: managed subordinate's situation is shared with upper level power supply Agent by each photovoltaic main website Agent, circulates a notice of to superior instructions in conjunction with own situation, waits for that higher level issues an order; The assessment integrative feedback of transmission link to Agent is assessed, if when system changes, upper level power supply Agent can carry out next step adjustment and optimization according to operational factor.
And, described large-scale photovoltaic grid-connected coordination controls framework and comprises level power supply Agent and micro-grid system, photovoltaic main website Agent and each photovoltaic subsystem Agent, photovoltaic main website Agent is connected with upper level power supply Agent and each photovoltaic subsystem Agent, and the coordination control strategy of each Agent is the control mode under same institutional framework.
And, described photovoltaic main website Agent realizes the aggregation of data process of photovoltaic system, solution formulation, order are issued and function grid-connected with major network, by the distribution of the task division between each Agent of communication-cooperation and shared resource between this photovoltaic main website Agent and upper level power supply Agent, described upper level power supply Agent is responsible for the coordinated scheduling between electricity market and each Agent, and comprehensive photovoltaic main website Agent information makes very important decision.
And described photovoltaic subsystem Agent has the following two kinds operational mode: MPPT maximum power point tracking pattern and voltage limiting mode, when this photovoltaic subsystem Agent is operated under MPPT pattern, once battery tension reaches voltage limit, VL pattern will be transferred to; Photovoltaic subsystem Agent is under above-mentioned two kinds of patterns, if battery charging current exceedes the safe operation limit, so load will be disconnected.
And parameter and the control procedure thereof of described step 2 collection are as follows:
The parameter gathering photovoltaic substation Agent comprises: the power output of photovoltaic generating system and node voltage; Its control mode is: the power stage being controlled photovoltaic system by maximal power tracing; Typical PID is used to control management node voltage, to realize the normal operation of system and grid-connected smoothly;
The parameter gathering fuel cell Agent comprises: cell output, output current and node voltage; Its control mode is: the pwm signal utilizing PWM generator to produce, as control signal source, adopts classical PID to control, controls the electric current of fuel cell, thus control the discharge and recharge of storage battery;
The parameter gathering storage battery Agent comprises: charging voltage, charging current and charge power; Its control mode is: V/F controls.
And, adopt interactive type communication mode to carry out information transfer and feedback in described step 3 between each Agent, and realize multi-Agent Communication in point-to-point request-acknowledge communication mode.
And, when described MAGA algorithm controls, each individuality is considered as an Agent, all Agent all live in Agent grid environment, each Agent is a feasible solution in solution space, and adopts following four genetic operators: neighborhood competition operator, neighborhood orthogonal crossover operator, mutation operator and self-learning operator four operators; Described neighborhood competition operator achieves the contention operation between each Agent; Neighborhood orthogonal crossover operator achieves the cooperative behaviors between each Agent; Mutation operator and self-learning operator achieve the behavior that Agent utilizes its knowledge
And the concrete control flow of described MAGA algorithm comprises initialization network step, searching optimization individual step, self study treatment step, neighborhood competition process step, neighborhood orthogonal crossover treatment step and variation treatment step.
Advantage of the present invention and good effect are:
The present invention is according to the feature of photovoltaic generating system access power distribution network, utilizing MAGA(Multi-Agent GeneticAlgorithm multi-Agent Genetic Algorithm) control strategy of technology controls the micro-grid system that large-scale photovoltaic electricity generation system, fuel cell, storage battery etc. are formed, under the prerequisite ensureing large-scale photovoltaic grid-connected system Power supply, economy, power supply reliability and safe and stable operation, the maximal efficiency achieving photovoltaic generating system exports.The present invention can control the maximum power output of parallel networking type photovoltaic electricity generation system and the cost of electricity-generating of distribution, and increases the power supply reliability of system and the efficiency utilization of energy.
Accompanying drawing explanation
Fig. 1 is large-scale photovoltaic grid-connected coordination control framework figure;
Fig. 2 is PV system control strategy figure;
Fig. 3 is fuel cell boost converter inner-current control loop:
Fig. 4 is fuel cell boost converter external voltage control loop;
Fig. 5 is Agent system request-acknowledge communication mode;
Fig. 6 is MAGA algorithm control flow.
Embodiment
Below in conjunction with accompanying drawing, the embodiment of the present invention is further described.
A kind of grid-connected control method for coordinating based on MAGA adopts MAGA(Multi-AgentGenetic Algorithm, multi-Agent Genetic Algorithm) cooperation control that photovoltaic generating system is incorporated into the power networks, by setting up knowledge base and control strategy, and mutual study between each Agent and coordination optimization control, can ensure that system optimal controls.This method divides the economic performance considering whole system, under the prerequisite ensureing large-scale photovoltaic grid-connected system economy, power supply reliability and safe and stable operation, with the optimal utilization of luminous energy for cooperation control target, the related key technical of combined with intelligent electrical network and intelligent computation, ensures that the maximal efficiency of photovoltaic generating system exports.
The MAGA that the present invention adopts refers to multi-Agent Genetic Algorithm, be MA (Multi-Agent, multiple agent) and GA(GeneticAlgorithm, genetic algorithm) a kind of hybrid algorithm of combining of technology.Agent acts on behalf of, and also claims intelligent body, originates from distributed artificial intelligence, is a kind ofly have perception, problem solving ability and the entity with extraneous communication capacity.MA refers to that the comparatively loose multi-Agent of of being made up of multiple Agent is combined, between these Agent mutually collaborative, mutually serve, jointly complete a task.How interaction in the activity of main research whole system between each Agent produces, the existence of other Agent in the reasoning of each Agent and behaviour decision making how consideration system, the division of collision detection possible between the target of Agent and behavior and coordination and task and resource, distribution and management etc.MAGA as a kind of Hybrid GA of improvement on convergence time, optimum results often more traditional GA have very large lifting, particularly when processing ultra-large, higher-dimension, complexity, optimization problems, MAGA algorithm also exists obvious advantage, this algorithm between individuals mutual, cooperation and self study on, algorithm is more in the past very different.
A kind of grid-connected control method for coordinating based on MAGA is used in the photovoltaic parallel in system of large-scale photovoltaic generating access, energy storage, fuel cell, load composition, comprise the pattern that light+storage (fuel cell)+bulk power grid is powered to system loading, this photovoltaic parallel in system known terms is light conditions, energy storage device parameters and load parameter etc.Specifically comprise the following steps:
Step 1: set up and adopt the large-scale photovoltaic grid-connected coordination of MA technological maheup to control framework
As shown in Figure 1, this cooperation control framework comprises level power supply Agent and micro-grid system, photovoltaic main website Agent, each photovoltaic subsystem Agent, photovoltaic main website Agent is connected with upper level power supply Agent and each photovoltaic subsystem Agent, and the coordination control strategy of each Agent is the control mode under same institutional framework.Below the various piece function in control cage structure is described respectively:
Photovoltaic main website Agent has the aggregation of data process of photovoltaic system, solution formulation, order are issued and function grid-connected with major network, by the distribution of the task division between each Agent of communication-cooperation and shared resource between this photovoltaic main website Agent and upper level power supply Agent.Upper level power supply Agent is responsible for the coordinated scheduling between electricity market and each Agent, and comprehensive photovoltaic main website Agent information makes very important decision.
Photovoltaic subsystem Agent has MPPT maximum power point tracking (MPPT) function, cell panel monitoring and defencive function, inversion grid connection function, to ensure that photovoltaic cell can reliably, safely run.The power that the power that not only can produce from photovoltaic panel due to the charge power of storage battery obtain but also can produce from fuel cell obtain, when therefore designing photovoltaic generation subsystem, need the safety margins considering charge in batteries, the voltage of storage battery should be remained in a safe range, can not safety margins be exceeded.Photovoltaic subsystem Agent has two kinds of operational modes: one is MPPT pattern; One is voltage restriction (VL) pattern, the control strategy of photovoltaic subsystem Agent as shown in Figure 2, in figure, arrow represents from a control model and turns to another control model, MPPT represents MPPT maximum power point tracking pattern, VL representative voltage unrestricted model, DISC and load disconnect, switch condition: 1(MPPT to VL pattern): Vb>Vref, 2(VL to MPPT pattern): Vb<Vref, 3,4(MPPT to DISC, VL to DISC): │ Ib │ >Idisc.Under first photovoltaic subsystem Agent is operated in MPPT pattern, once battery tension reaches voltage limit, VL pattern will be transferred to.Under both modes, if battery charging current exceedes the safe operation limit, so load will be disconnected (the rated charge streams of such as four times).The target of MPPT maximum power point tracking is continuous Modulating Power converter, makes photovoltaic panel all send maximum power under the situation of any weather and load.When PV system cloud gray model is under VL pattern, control management node voltage with a typical PID.
Fuel cell Agent has water treatment, fuel treatment and air supply, the monitoring of hydrogen-oxygen content and fuel and injects control, heat treatment, power adjustments and the function such as grid-connected.Because fuel cell needs to provide fuel and air by pump, valve and compressor to it, therefore, it is compared with the time constant of electric power system, and it has a relatively large time constant, fuel cell system can not be made the increase of load power demand and decline and react quickly and accurately.Fuel cell system in hybrid power system works close under Stable State Environment at one usually.Consider above factor, fuel cell system is used for compensating the remaining part of average power requirement, charges a battery simultaneously.
Fuel cell Agent manages output current and the adjustment node voltage of fuel cell by boost converter.As shown in Figure 3, fuel cell Agent adopts a typical PID controller and PWM generator to coordinate and controls fuel cell current, the input of this inner-current control loop is a reference signal Ifc_ref, and this signal is produced by an external voltage loop.As shown in Figure 4, voltage circuit includes a P controller, it creates baseline fuel cell electric current, and by this algorithm, when battery tension is lower, fuel cell current raises; When storage battery is filled electricity, fuel cell current declines.This control strategy, can regulating cell voltage just as photovoltaic control system.When battery is full of electricity, fuel cell system is closed, and at this moment only has photovoltaic panel and battery to provide power to load.This strategy has individual advantage to be exactly can fuel saving resource.
Storage battery Agent has the monitoring function to battery tension, electric current, energy storage, also has charging/discharging function and start and stop attributive function.The power that the power that the charge power of storage battery not only can produce from photovoltaic panel obtain but also can produce from fuel cell obtain.The voltage of storage battery should remain in a safe range, can not exceed safety margins.When the demand of load peak exceedes photovoltaic panel and fuel cell providing capability, power supply is responsible for by storage battery.
Step 2: gather the parameter in each Agent, and provide certain control to Agent.
Parameter and the control procedure thereof of the collection of this step are as follows:
The parameter gathering photovoltaic substation Agent comprises: the power output of photovoltaic generating system and node voltage; Its control mode is: the power stage being controlled photovoltaic system by maximal power tracing; Typical PID is used to control management node voltage, to realize the normal operation of system and grid-connected smoothly;
The parameter gathering fuel cell Agent comprises: cell output, output current and node voltage; Its control mode is: the pwm signal utilizing PWM generator to produce, as control signal source, adopts classical PID to control, controls the electric current of fuel cell, thus control the discharge and recharge of storage battery;
The parameter gathering storage battery Agent comprises: charging voltage, charging current and charge power; Its control mode is: V/F controls.
Step 3: information transmission and feedback, among the information transmission in each Agent to the Agent of circuit, meanwhile, among the information feed back in circuit to initial Agent, and arranges the running status of himself.
In this step, interactive type communication mode is adopted to carry out information transfer and feedback between each Agent.In Agent system, need collaborative work to come a job and Solve problems between each unit, this has advance and superiority than traditional control system.The each member of Agent need to adopt message communicating mode realize mutually between communication, and set up a kind of mechanism.The present invention adopts point-to-point request-acknowledge communication mode to realize multi-Agent Communication function.As shown in Figure 5, known quantity is recipient and the person of sending of message, when needing other Agent to cooperate jointly to finish the work when an Agent job, request can be sent to other Agent, when not clashing with the task of self, can not exceed it when namely performing this request task and run restriction, this Agent will perform and complete this request task; Send successful execution information to requesting party, if do not return this information, then task requests failure, this point-to-point mode effectively can reduce the delay of information simultaneously.
Step 4: adopt MAGA algorithm realization grid-connected cooperation control: circuit Agent is supplied to photovoltaic main website Agent administrative circuit and unit Agent operation conditions, while photovoltaic main website Agent provide control strategy according to MAGA algorithm to circuit Agent and transfer to circuit Agent to change the running status of each unit according to circuit operating condition.
This step is set out according to the angle of grid-connected each Agent functions of modules of large-scale photovoltaic and related control strategies, each Agent is as having local sensing, competing the individuality of cooperation and self-learning capability in GA, MAGA reaches the object of global optimization by the interaction between Agent and environment and Agent.Each individuality is considered as an Agent by MAGA algorithm, all Agent all live in Agent grid environment, each Agent is a feasible solution in solution space, when adopting MAGA algorithm to control, adopt following four genetic operators: neighborhood competition operator, neighborhood orthogonal crossover operator, mutation operator and self-learning operator four operators.Wherein neighborhood competition operator achieves the contention operation between each Agent; Neighborhood orthogonal crossover operator achieves the cooperative behaviors between each Agent; Mutation operator and self-learning operator achieve the behavior that Agent utilizes its knowledge.The concrete control flow of MAGA algorithm as shown in Figure 6, comprise initialization network step, searching optimization individual step, self study treatment step, neighborhood competition process step, neighborhood orthogonal crossover treatment step and variation treatment step, thus realize grid-connected coordinated control function.
Step 5: information feed back and further optimization: managed subordinate's situation is shared with upper level power supply Agent by each photovoltaic main website Agent, circulates a notice of to superior instructions in conjunction with own situation, waits for that higher level issues an order; The assessment integrative feedback of transmission link to Agent is assessed, if when system changes, upper level power supply Agent can carry out next step adjustment and optimization according to operational factor.Thus, ensure that electrical network can be in safety economy and reliably run.
It is emphasized that; embodiment of the present invention is illustrative; instead of it is determinate; therefore the present invention includes the embodiment be not limited to described in embodiment; every other execution modes drawn by those skilled in the art's technical scheme according to the present invention, belong to the scope of protection of the invention equally.
Claims (8)
1., based on a grid-connected control method for coordinating of MAGA, it is characterized in that: comprise the following steps:
Step 1: set up the large-scale photovoltaic grid-connected coordination adopting multi-agent Technology to form and control framework;
Step 2: gather the parameter in each intelligent body, and provide certain control to intelligent body;
Step 3: information transmission and feedback: among the information transmission in each intelligent body to the intelligent body of circuit, meanwhile, among the information feed back in circuit to initial intelligent body, and arranges the running status of himself;
Step 4: adopt MAGA algorithm realization grid-connected cooperation control: circuit intelligent body is supplied to photovoltaic main website intelligent body administrative circuit and unit intelligent body operation conditions, while photovoltaic main website intelligent body provide control strategy according to MAGA algorithm to circuit intelligent body and transfer to circuit intelligent body to change the running status of each unit according to circuit operating condition;
Step 5: information feed back and further optimization: managed subordinate's situation is shared with higher level's power supply smart body by each photovoltaic main website intelligent body, circulates a notice of to superior instructions in conjunction with own situation, waits for that higher level issues an order; The assessment integrative feedback of transmission link to intelligent body is assessed, if when system changes, higher level's power supply smart knows from experience adjustment and optimization that to carry out next step according to operational factor.
2. a kind of grid-connected control method for coordinating based on MAGA according to claim 1, it is characterized in that: described large-scale photovoltaic grid-connected coordination controls framework and comprises higher level's power supply smart body and micro-grid system, photovoltaic main website intelligent body and each photovoltaic subsystem intelligent body, photovoltaic main website intelligent body is connected with higher level's power supply smart body and each photovoltaic subsystem intelligent body, and the coordination control strategy of each intelligent body is the control mode under same institutional framework.
3. a kind of grid-connected control method for coordinating based on MAGA according to claim 2, it is characterized in that: described photovoltaic main website intelligent body realizes the aggregation of data process of photovoltaic system, solution formulation, order are issued and function grid-connected with major network, by the distribution of the task division between each intelligent body of communication-cooperation and shared resource between this photovoltaic main website intelligent body and higher level's power supply smart body, described higher level's power supply smart body is responsible for the coordinated scheduling between electricity market and each intelligent body, and comprehensive photovoltaic main website intelligent body information makes very important decision.
4. a kind of grid-connected control method for coordinating based on MAGA according to claim 2, it is characterized in that: described photovoltaic subsystem intelligent body has the following two kinds operational mode: MPPT maximum power point tracking pattern and voltage limiting mode, when this photovoltaic subsystem intelligent body is operated under MPPT maximum power point tracking pattern, once battery tension reaches voltage limit to, voltage limiting mode will be transferred; Photovoltaic subsystem intelligent body is under above-mentioned two kinds of patterns, if battery charging current exceedes the safe operation limit, so load will be disconnected.
5. a kind of grid-connected control method for coordinating based on MAGA according to claim 1, is characterized in that: the parameter that described step 2 gathers and control procedure as follows:
The parameter gathering photovoltaic substation intelligent body comprises: the power output of photovoltaic generating system and node voltage; Its control mode is: the power stage being controlled photovoltaic system by maximal power tracing; Typical PID is used to control management node voltage, to realize the normal operation of system and grid-connected smoothly;
The parameter gathering fuel cell intelligent body comprises: cell output, output current and node voltage; Its control mode is: the pwm signal utilizing PWM generator to produce, as control signal source, adopts classical PID to control, controls the electric current of fuel cell, thus control the discharge and recharge of storage battery;
The parameter gathering intelligent accummulator body comprises: charging voltage, charging current and charge power; Its control mode is: V/F controls.
6. a kind of grid-connected control method for coordinating based on MAGA according to claim 1, it is characterized in that: adopt interactive type communication mode to carry out information transfer and feedback in described step 3 between each intelligent body, and realize agents and communications in point-to-point request-acknowledge communication mode.
7. a kind of grid-connected control method for coordinating based on MAGA according to claim 1, it is characterized in that: when described MAGA algorithm controls, each individuality is considered as an intelligent body, all intelligent bodies are all lived in Agent Grid environment, each intelligent body is a feasible solution in solution space, and adopts following four genetic operators: neighborhood competition operator, neighborhood orthogonal crossover operator, mutation operator and self-learning operator four operators; Described neighborhood competition operator achieves the contention operation between each intelligent body; Neighborhood orthogonal crossover operator achieves the cooperative behaviors between each intelligent body; Mutation operator and self-learning operator achieve the behavior that intelligent body utilizes its knowledge.
8. a kind of grid-connected control method for coordinating based on MAGA according to claim 1, is characterized in that: the concrete control flow of described MAGA algorithm comprises initialization network step, finds optimization individual step, self study treatment step, neighborhood competition process step, neighborhood orthogonal crossover treatment step and variation treatment step.
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| CN101777769A (en) * | 2010-03-24 | 2010-07-14 | 上海交通大学 | Multi-agent optimized coordination control method of electric network |
| CN102496937A (en) * | 2011-11-28 | 2012-06-13 | 山东工商学院 | Fault recovery method applied to intelligent distribution network and based on load balance |
| CN102801790A (en) * | 2012-07-19 | 2012-11-28 | 江苏省电力设计院 | Microgrid energy management system based on IEC (International Electrotechnical Commission) 61850 and multi-agent method |
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