CN103870649A - Active power distribution network autonomous simulation method based on distributive intelligent computing - Google Patents
Active power distribution network autonomous simulation method based on distributive intelligent computing Download PDFInfo
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Abstract
The invention relates to an artificial intelligence and electric power system simulation integrated technology, in particular to an active power distribution network autonomous simulation method based on the distributive intelligent computing. The method comprises the following steps of (1) establishing an autonomous simulation target ASOM model target collection based on a multi-agent system MAS according to the characteristics of a distributive power supply; (2) establishing an autonomous simulation target model central coordinator AJC based on the distributive agent architecture to integrally manage each real simulation area; (3) setting the task central coordinator AJC in multiple levels according to the ASOM model; establishing an interaction mechanism between each level central coordinator AJC and the ASOM model. By adopting the method, the simulation target of different types in the active power distribution network can be distributively simulated, a simulation task is distributed to a plurality of intelligent simulation targets to be autonomously actuated, and the combined optimization strategy of different distributive power supplies can be realized through the task coordinative management of the central coordinator AJC.
Description
Technical field
The present invention relates to artificial intelligence and electric system simulation interleaving techniques, be specifically related to a kind of active power distribution network autonomyization emulation mode of calculating based on distributed intelligence.
Background technology
Active power distribution network (Active Distribution Networks, ADN) is the multiple-energy-source combined operation system of a quasi-representative.Wherein combine take photovoltaic PV(solar-photovoltaic), wind-powered electricity generation WT(Wind Turbine) and energy-storage battery be main a large amount of burning natural gas distributed power apparatus.Mutual benefit and replacement mode can make the comprehensive energy utilization ratio of various energy resources symbiotic system inside get a promotion, also strengthened the internetwork coupled relation of different energy sources simultaneously, but complicated network annexation and steering logic make internal coordination difficulty all the more, data mode is difficult to supervision, and logic communication is difficult to control and coordinated management is difficult to carry out.
Distributed artificial intelligence (Distributed Artificial Intelligence, and artificial life (Artificial Life DAI), AL) the reach of science needs and the MAS(Multi-Agent System of generation, multi-agent system, multi-agent system) be the set of multiple Agent compositions.Agent runs on dynamic environment, have intelligence, perception environment, can be according to own resource, state, capacity, knowledge rule and the external environmental information obtaining, solve by planning, reasoning and decision-making problem of implementation, and make a response, the autonomous entity with high degree of autonomy ability that completes particular task and make it.MAS is exactly by mutually coordinating between so multiple Agent members, mutually serves, and jointly completes the system of a task.Its target be by large and complicated system Construction become multiple little, have intelligence, communicate by letter and coordinate each other, be easy to the system of management.
By the emulation to active power distribution network, optimize various energy resources associating, formulate relevant Optimal Control Strategy, safety in operation, reliability and system stability in analysis and assessment net between various energy resources situation, be one of emphasis realize target of active Distribution Network Practicalization construction.But at present owing to lacking technical research and the practical research of this respect, cause distributed power source access and the network operation in active distribution to be optimized the hysteresis of analytical work.Therefore, being badly in need of a kind of active power distribution network emulation practical application technology of research and development solves the problems referred to above, realizes above-mentioned target.
Summary of the invention
For the deficiencies in the prior art, the object of this invention is to provide a kind of active power distribution network autonomyization emulation mode of calculating based on distributed intelligence, the method can be supported dissimilar simulation object in distributed earth simulation active power distribution network, artificial tasks is distributed to be had intelligent multiple simulation object autonomyizatioies and carries out, and can realize by the management of central coordinator AJC task coordinate the combined optimization strategy of multiple distributed power source.
The object of the invention is to adopt following technical proposals to realize:
The invention provides a kind of active power distribution network autonomyization emulation mode of calculating based on distributed intelligence, its improvements are, described method comprises the steps:
(1) set up the autonomous simulation object ASOM model object collection based on multi-agent system MAS according to the feature of distributed power source;
(2) the autonomous simulation object model central coordinator AJC setting up based on distributed agent framework comes the each actual emulation of integrated management region;
(3) in conjunction with ASOM model, task central coordinator AJC is carried out to multistage setting; And set up the interaction mechanism of central coordinator AJC at different levels and ASOM model.
Further, in described step (1), autonomous simulation object model ASOM comprises computing unit, communication port and serve port, and described communication port and serve port carry out data interaction with computing unit respectively; The number of described communication port and serve port is 2;
Described computing unit comprises that argument sequence imports unit, sequence of events imports unit, overhead control logical block, operational parameter control unit, knowledge logic unit, context unit and object properties; Described argument sequence imports unit and sequence of events importing unit transmits data with overhead control logical block respectively; Described overhead control logical block is transmitted data with operational parameter control unit and knowledge logic unit respectively.
Further, described 2 communication port are respectively used to data input and output; Described 2 serve ports are respectively used to the request of subordinate's order and distributing of superior command;
Described overhead control logical block and operational parameter control unit are the core of central agency for the superior and the subordinate's management; Described central agency refers to central coordinator AJC;
Described argument sequence imports unit and sequence of events importing unit is respectively used to parameter and the event that buffer memory the superior and the subordinate transmit in time series emulation;
Relationship between superior and subordinate and object properties that described context unit and object properties specify respectively this unit to act on behalf of;
Described knowledge logic unit is the basis of event response, for explaining self rule of conduct of autonomous simulation object ASOM model and central coordinator AJC;
Wherein context unit comprises context source unit and context object element.
Further, in described step (2), by the autonomous operation of the autonomous simulation object model profile formula based on multi-agent system MAS, carry out synchronous and unified coordination of task by the autonomous simulation object model work telegon based on distributed agent framework;
The unified coordination of autonomous simulation object ASOM model based on multi-agent system MAS and central coordinator AJC comprises: A, distributed power source DER unit regulate, and vehicle economy R unit regulates; B, distributed energy storage DES and electric automobile EV model regulate; C, normal power supplies model regulate; D, initiatively power distribution network load model adjusting; E, intelligent power distribution substation model regulate.
Further, the DER unit of described A regulate will the value of exerting oneself curve as inputting data; According to the orderly access of DER unit and the global coordination target that initiatively power distribution network network fluctuates minimum, guarantee the access of DER unit; In the time not considering distributed power source random fluctuation, current self value of exerting oneself is is directly reported and submitted in each DER unit timing, in the time of the random fluctuation of consideration distributed power generation, according to normal distribution, the value of exerting oneself is carried out to random processing, worthwhile actual the exerting oneself of doing of then this being exerted oneself at random;
The operation constraint of DER unit is that the maximum of DER can be accepted access than DER_MAX, and in the time that distributed electrical source unit changes, central coordinator AJC, as central agency, carries out decision-making by central agency:
Step a.: when newly adding a DER or existing DER state to upgrade in simulation process, the DER that triggers a central agency coordinates event, and central agency is called DER coordination function;
Step b.: whether first central agency judges that the rear maximum of variation can be accepted access more out-of-limit than DER_MAX, if not, allows access and finish; If so, enter Step c;
Step c: more out-of-limit than DER_MAX if maximum can be accepted access, continue to judge whether to be newly to add power supply, if so, asked veto and finish; If not, enter DER grading subprocess, comprising:
-Substep is c.1: call Ranking () function to the sequence of all DER unit, generate the sequencing table DERSchedule of all DER;
-Substep is c.2: pointer K points to the first place of DER Schedule;
-Substep is c.3: the DER unit that central agency specifies pointer K to point to exits, and then judges that whether DER_MAX is still out-of-limit, if so, moves afterwards the pointer K address duplicate step of laying equal stress on, and if not, process finishes.
Further, the distributed energy storage DES of described B and electric automobile EV model are for the balance optimizing between auxiliary distributed generators and loads; In the time that distributed power source-balancing the load is carried out in electric system, the difference that power supply and load are coordinated for supplementing Power Systems.
Further, the normal power supplies model adjusting of described C comprises: initiatively the normal power supplies unit in power distribution network comprises two classes: the small power supply node in outer net or major network equivalence and net, for the parameter variation of tracing and monitoring external network equivalent and exerting oneself of adjusting small power supply node; Operation constraint condition is determined by electric system total load; When operation each load cell initiatively report and submit to central agency timing self load value, central agency need consider with current system in total load amount balance, in the time that system loading amount reduces, central agency initiation power supply coordination of tasks, first guarantees the access of DER unit; In the time that load increases, central agency priority access DER unit, then regulates normal power supplies unit, if still uneven, initiates Load Regulation.
Further, the active power distribution network load model of described D regulates and comprises:
Initiatively power distribution network load model comprises in business power load, commercial power load, residential electricity consumption load and active power distribution network in rushing distributed energy storage DES and the electric automobile EV of electric state;
Initiatively power distribution network load model comprises two input parameters: load curve and power purchase price target; The power purchase price target power purchase cost optimization that is used for loading; In the time not considering to load provisional random fluctuation, initiatively power distribution network load model carries out oneself state adjusting according to load curve, in the time experiencing external power source conveying deficiency, initiate Load Regulation request to central coordinator AJC, autonomous simulation object model work telegon based on distributed agent framework is received after request, initiate load model adjustment process, comprise the steps:
<1> is at load model universal time coordinated, for the priority access to distributed power source DER and power purchase cost optimization, priority access distributed power source DER, if exist DER for subsequent use to carry out DER adjustment process at once, if meet operation constraint, DER is normal to be started and system source lotus balance, and tuning algorithm finishes;
If <1> is invalid for <2> step, enter the normal power supplies model adjustment process described in C, iterate until electric system balance, coordination process finishes; If still invalid, enter step <3> and carry out load adjustment;
<3>, in the situation that all power adjustment are invalid, calls the load grading subprocess of central coordinator AJC, comprises the steps:
1. all load grading sequences, " charging electric vehicle state → distributed energy storage → tri-type load → bis-type load → mono-type load order is followed in grading; (three type loads are: 1. type load one type load is very important load, if power failure is occurred this type load to, will cause personal injury, device damage, and civil order confusion, so that cause great economic loss.2. two type load two type load interruption of power supply, will cause producing and stop work, product rejection, and traffic jam, so that cause larger economic loss.3. three type loads are every does not belong to a type load, two type load persons, is all under the jurisdiction of three type loads.）
2. generate temporary address pointer J and point to first of load sequencing table;
3. first central coordinator AJC notifies the load model that pointer J points to regulate execution shutoff operation, and wait for that accepting load model regulates and return and close successful message, then whether balance of cycle criterion system loading total amount sysload_quantum, if not, move afterwards the pointer J address duplicate step of laying equal stress on, if so, coordination process finishes.
Further, the intelligent power distribution substation model of described E regulates and comprises:
Unit, distribution substation, SUBST unit is determined according to the difference of its distribution substation cell type pointed, and distribution substation cell type comprises mode transmission, power-type or load type; In the time of needs intellectual power distributing station detailed model, SUBST unit is as the central agency of management distribution substation, the intelligent terminal of inside, unified management SUBST unit, protection, disconnector, bus, feeder line various kinds of equipment unit;
SUBST is as the internetwork intermediate node of the superior and the subordinate, for task distribution formula distribute and subnet between the function of delivery of electrical energy and coordination.
Further, following two aspects of the action of the autonomous simulation object model based on multi-agent system MAS foundation:
1) do not stop the variation that gets parms, according to the autonomous action of self rule and central coordinator AJC is circulated a notice of;
2), when needs are unified universal time coordinated, central coordinator AJC distributes to force the autonomous simulation object model based on multi-agent system MAS to move by organization task;
Central coordinator AJC is connected to obtain constraint condition and policing rule with unified knowledge engine, generates applicable coordination strategy under constraint condition; Unified knowledge engine is a data base administration engine based on knowledge rule.
Further, described step (3) comprising:
1> carries out multistage setting in conjunction with ASOM model to task central coordinator AJC: on the basis of step (2), active power distribution network is divided into multiple subnets multistage and that how to move according to electric pressure and Regional Distribution;
2> sets up the interaction mechanism of central coordinator AJC at different levels and ASOM model: integrating step (1) and step (2), set up the topological sum administrative model of multistage active power distribution network, realize trans-regional energy equilibrium by higher level's network that each bottom subnet is coordinated.
Further, initiatively the emulation of power distribution network autonomyization comprises energy coordinated management task, and energy coordinated management comprises the steps:
A, when certain industrial load ASOM model monitoring is when commercial power load increases in region, to this region central coordinator AJC transmitted power solicited message;
B, receive after the solicited message of industrial load control ASOM model as central coordinator AJC at the corresponding levels, simulation calculation is carried out in this region, if the scheme of being resolved, issue regulating command to power supply, electric automobile energy storage and the load ASOM model of its administration, if it is still excessive to load, continue superior request;
C, when higher level's central coordinator AJC receives after the solicited message of subordinate, the realistic model in this region is calculated, the region AJC of other subordinates administering to it issues regulating command, if power does not also reach balance, continues superior request.
Compared with the prior art, the invention has the beneficial effects as follows:
1, the active power distribution network autonomyization simulating analysis calculating based on distributed intelligence provided by the invention, can support dissimilar simulation object in distributed earth simulation active power distribution network, artificial tasks is distributed to be had intelligent multiple simulation object autonomyizatioies and carries out, and can realize by the management of central coordinator AJC task coordinate the combined optimization strategy of multiple distributed power source.
2, the active power distribution network autonomyization simulating analysis calculating based on distributed intelligence provided by the invention, can be by the active power distribution network artificial tasks containing a large amount of distributed power sources, resolve into the multi-level Sub-region and hierarchical of multizone and there is the computing module of independence, carry out Distributed Calculation, realize the initiatively emulation of power distribution network.
Accompanying drawing explanation
Fig. 1 is the ASOM generic structure diagram in the active power distribution network autonomyization simulating analysis calculating based on distributed intelligence provided by the invention;
Fig. 2 is a kind of active power distribution network entirety simulation framework figure calculating based on distributed intelligence provided by the invention;
Fig. 3 is that control flow chart is coordinated in the AJC emulation of distributed power source provided by the invention;
Fig. 4 is that control flow chart is coordinated in the AJC emulation about load provided by the invention;
Fig. 5 is unified the coordinate control flow chart of AJC provided by the invention in simulation process;
Fig. 6 is the active power distribution network power adjustments process flow diagram calculating based on distributed intelligence provided by the invention.
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail.
For the active power distribution network containing distributed power source is carried out to simulation analysis, the invention provides a kind of modeling simulation analysis method that combines distributed intelligence system (DIS), its process flow diagram as shown in Figure 6, comprises the steps:
(1) set up autonomous simulation object model (Autonomous Simulation Object Model, the ASOM) object set based on MAS according to the feature of distributed power source.The ASOM that wherein comprises multiple primary types such as wind-powered electricity generation WT, photovoltaic PV, normal power supplies GEN, energy storage DES, distribution substation SUBST and load Load, wherein WT and PV have similar characteristic and similar structure, maybe can merge into a class.
As shown in Figure 1, autonomous simulation object ASOM model comprises computing unit, communication port and serve port to ASOM universal architecture, and described communication port and serve port carry out data interaction with computing unit respectively; The number of described communication port and serve port is 2; Described computing unit comprises that argument sequence imports unit, sequence of events imports unit, overhead control logical block, operational parameter control unit, knowledge logic unit, context unit, object properties; Described argument sequence imports unit and sequence of events importing unit transmits data with overhead control logical block respectively; Described overhead control logical block is transmitted data with operational parameter control unit and knowledge logic unit respectively.
In 2 communication port, input for one for data, another is exported for data; A request for subordinate's order in 2 serve ports, another distributes for superior command;
Overhead control logical block and operational parameter control unit be central agency (refer to work coordination device AJC, what does object broker refer to so? the autonomous simulation object model whether referring to) for the core of the superior and the subordinate management;
Argument sequence imports unit and sequence of events imports parameter and the event of unit for transmitting in time series emulation buffer memory the superior and the subordinate;
Relationship between superior and subordinate and object properties that context unit and object properties specify this unit to act on behalf of;
Knowledge logic unit is the basis of event response, for explaining self rule of conduct of autonomous simulation object ASOM model and central coordinator AJC; Wherein context unit comprises context source unit and context object element.
Be more than the universal architecture of computing unit, in practice, object broker is with different with the knowledge logic structure of central agency, and the parameter of the object broker inside of different realistic models (load, power supply, equipment etc.) is different with " knowledge logic " content.
(2), on the basis of step (1), the ASOM work coordination device (Autonomous Job Coordinator, AJC) of setting up based on distributed agent framework comes the each actual emulation of integrated management region.AJC is equivalent to center-control agency, and it is mainly responsible for the core missions such as order issue in simulation flow and response, communication coordination, integrated optimization aim.
Fig. 2 has provided the general frame of the proposed by the invention active power distribution network simulation analysis algorithm calculating based on distributed intelligence.The unified coordination of autonomous simulation object ASOM model based on multi-agent system MAS and central coordinator AJC comprises: A, distributed power source DER unit regulate, and vehicle economy R unit regulates; B, distributed energy storage DES and electric automobile EV model regulate; C, normal power supplies model regulate; D, initiatively power distribution network load model adjusting; E, intelligent power distribution substation model regulate.
A. distributed electrical source unit regulates (Distributed Energy Resources, DER)
Distributed electrical source unit (Distributed Energy Resource Model, DER) (hereinafter to be referred as the DER unit) value of taking efforts curve is as input data.According to " the global coordination target " of " distributed power source is access and ADN network fluctuation minimum in order ", the access of DER unit needs preferential assurance.In the time not considering distributed power source random fluctuation (DER_forcast_wave=0), current self value of exerting oneself is is directly reported and submitted in each DER unit timing, in the time considering distributed power generation random fluctuation (appendix table 1.DER_forcast_wave=1), according to normal distribution, the value of exerting oneself is carried out to random processing, then this random value is regarded and truly exerted oneself.
The operation constraint of DER unit is that the maximum of DER can be accepted access and compares DER_MAX.As shown in Figure 3, in the time that DER unit changes, for guaranteeing security of system, carry out decision-making by central agency:
Step a.: when newly adding a DER or existing DER state to upgrade in simulation process, the DER that triggers a central agency coordinates event, and central agency is called DER coordination function;
Step b.: after first central agency judges variation, whether DER_MAX is out-of-limit, if not, allows access and finish.If so, enter Step c;
Step c: if DER_MAX is out-of-limit, continue to judge whether to be newly to add power supply, if so, asked veto and finish.If not, enter DER grading subprocess:
-Substep is c.1: call Ranking () function to the sequence of all DER unit, generate the sequencing table DERSchedule of all DER;
-Substep is c.2: pointer K points to the first place of DER Schedule;
-Substep is c.3: the DER unit that central agency specifies K to point to exits, and then judges that whether DER_MAX is still out-of-limit, if so, moves afterwards the K address duplicate step of laying equal stress on, and if not, algorithm finishes.
B. distributed energy storage DES and electric automobile EV model regulate:
Energy storage and electric automobile unit are for the balance optimizing between auxiliary DER and load.In the time that system is carried out power supply-balancing the load, the two is for the difference of replenishment system power coordination, for example, when after the photovoltaic cells of a 1～2MW of system access, in the time that fluctuation occurs between 1～2MW for it, energy-storage units does not independently stop switching and rushes/put state, optimizes exert oneself/balancing the load.In addition, electric automobile will be noted the impact of instantaneous power to ADN network.
C. normal power supplies model regulates (GEN ASOM):
Normal power supplies unit in ADN comprises two classes: the small power supply node in outer net or major network equivalence and net, it is mainly responsible for parameter variation of tracing and monitoring external network equivalent and regulates exerting oneself of small power supply node.Its operation constraint condition is determined by system total load.In the time of operation, each load cell can initiatively be reported and submitted self load value to central agency timing, central agency need consider with current system in total load amount (sysLoad_quantum) balance, in the time that system loading amount reduces, central agency is initiated power supply coordination of tasks, first guarantees the access of DER unit.In the time that load increases, central agency is paid the utmost attention to access DER unit equally, then regulates normal power supplies unit, if still uneven, initiates Load Regulation.
D.ADN load model regulates Load ASOM:
General Load ASOM comprises business power load, commercial power load, residential electricity consumption load etc., in addition in ADN, also there is energy storage DES and the EV(EVL in rushing electric state: Charging state) can be used as special Load ASOM and participate in Load Regulation, load model Load ASOM is mainly used in guaranteeing the normal power supply of system important load, and the coordination target of total system and AJC is all to maximize and meet workload demand under each operation constraint condition.
Load ASOM comprise two important enter ginseng: load curve and power purchase price target (electrovalence).The latter's power purchase cost optimization that is mainly used in loading.In the time not considering to load provisional random fluctuation, Load ASOM can carry out oneself state adjusting according to load curve, in the time experiencing external power source conveying deficiency, initiate Load Regulation request Load_requst (i) to AJC, AJC receives after request, initiate Load Regulation process AJC.Concerting (Load (i)), as shown in Figure 4:
<1> is at universal time coordinated, for the priority access to DER and power purchase cost electrovalence, pay the utmost attention to access DER, if exist DER for subsequent use to carry out DER adjustment process at once, if meet operation constraint, DER is normal to be started and system source lotus balance, and tuning algorithm finishes;
If <2> step a is invalid, enter the described GEN adjustment process of C. joint, iterate until system balancing, tuning algorithm finishes.If still invalid, enter Step c. and carry out load adjustment;
This step of <3> is to carry out in the situation that all power adjustment are invalid, similar with DER adjusting, calls the load grading subprocess of AJC:
1. all loads grading sequence, " EV → DES(Charging state) → tri-type load → bis-type load → mono-type loads " agreement is followed in grading;
2. generate temporary address pointer J and point to first of Load Schedule;
3. the Load ASOM that AJC head points to notice J carries out close () operation, and wait for that accepting Load (J) returns to successfully message of close (), then whether balance of cycle criterion sysload_quantum, if not, move afterwards the J address duplicate step of laying equal stress on, if so, tuning algorithm finishes.
E. intelligent power distribution substation model SUBST ASOM:
Unit, distribution substation (SUBST unit) is not the unit that certain class has exact function to point to, and (as mode transmission, power-type or load type) determined according to the difference of the particular type of its distribution substation unit pointed in SUBST unit.In the time of needs intellectual power distributing station detailed model, SUBST unit similarly is more the central agency of a small-sized management distribution substation, the various kinds of equipment unit such as its inner intelligent terminal of unified management, protection, disconnector, bus, feeder line.
In the ordinary course of things, SUBST unit is as the internetwork intermediate node of the superior and the subordinate more, play that task distribution formula distributes and subnet between the function of delivery of electrical energy and coordination.AJC central coordinator
When each ASOM model, related to some extent central coordinator AJC, the ASOM of each object is dispersed on the different simulation nodes of different sub-network and moves, but AJC need to operate in central simulation management node.All ASOM carry out information and data interaction by high speed data bus and AJC.For larger power distribution network, by subnet division and by the mode of electric pressure classification, set up multiple AJC and jointly carry out internetwork coordination.
AJC constantly updates current network trend, and by trend result to self Web broadcast, monitor to obtain the control to affiliated AOM by a series of ports.Action foundation two aspects of each ASOM:
1> does not stop to obtain changes in external parameters, according to the autonomous action of self rule and AJC is circulated a notice of;
2> is when unifying universal time coordinated, and AJC can distribute to force each ASOM to carry out relevant action by organization task;
AJC need to be connected to obtain corresponding constraint condition and policing rule with unified knowledge engine (KM Engine, a data base administration engine based on knowledge rule), generates current applicable coordination strategy under current constraint condition.The overall workflow of AJC as shown in Figure 5.
(3) on the basis of step (2), active power distribution network is divided into multiple subnets multistage and that how to move according to electric pressure and Regional Distribution, integrating step (1) and step (2), set up multistage ADN topological sum administrative model, realize trans-regional energy equilibrium by higher level's network that each bottom subnet is coordinated, wherein emphasis relates to and has solved the information synchronization mechanism problem in distributed parallel simulation calculation.In multistage network, high-rise AJC with the AJC of lower floor by communicating by letter to coordinate subordinate's subnet.
According to specific tasks, in conjunction with ASOM model, task AJC is carried out to multistage setting, as shown in Figure 3.AJC needs corresponding constraint condition and policing rule, generates current applicable coordination strategy under current constraint condition.When AJC generation strategy result does not restrain, show that present networks inside cannot self-coordinating, can superior application (in the time allowing).In like manner, the request that AJC reply undernet sends responds.
Set up the interaction mechanism of AJC at different levels and ASOM.Take energy coordinated management task as example, concrete interaction flow as shown in Figure 3,
A, in the time that certain industrial load ASOM monitors in region commercial power load and increases, to this region AJC transmitted power solicited message.
B, when receiving load, AJC at the corresponding levels controls after the solicited message of ASOM, simulation calculation is carried out in this region, if the scheme of being resolved issues regulating command to power supply, energy storage (electric automobile) and the load ASOM of its administration, if load or excessive, continues superior request.
C, when higher level AJC receives after the solicited message of subordinate, the realistic model in this region is calculated, the region AJC of other subordinates administering to it issues regulating command, if power does not also reach balance, continues superior request.
By above-mentioned implementation step, can be containing the active power distribution network artificial tasks of a large amount of distributed power sources, resolve into the multi-level Sub-region and hierarchical of multizone and there is the computing module of independence, carry out Distributed Calculation, realize the initiatively emulation of power distribution network.
Finally should be noted that: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit, although the present invention is had been described in detail with reference to above-described embodiment, those of ordinary skill in the field are to be understood that: still can modify or be equal to replacement the specific embodiment of the present invention, and do not depart from any modification of spirit and scope of the invention or be equal to replacement, it all should be encompassed in the middle of claim scope of the present invention.
Claims (12)
1. an active power distribution network autonomyization emulation mode of calculating based on distributed intelligence, is characterized in that, described method comprises the steps:
(1) set up the autonomous simulation object ASOM model object collection based on multi-agent system MAS according to the feature of distributed power source;
(2) the autonomous simulation object model central coordinator AJC setting up based on distributed agent framework comes the each actual emulation of integrated management region;
(3) in conjunction with ASOM model, task central coordinator AJC is carried out to multistage setting; And set up the interaction mechanism of central coordinator AJC at different levels and ASOM model.
2. active power distribution network autonomyization emulation mode as claimed in claim 1, it is characterized in that, in described step (1), autonomous simulation object model ASOM comprises computing unit, communication port and serve port, and described communication port and serve port carry out data interaction with computing unit respectively; The number of described communication port and serve port is 2;
Described computing unit comprises that argument sequence imports unit, sequence of events imports unit, overhead control logical block, operational parameter control unit, knowledge logic unit, context unit and object properties; Described argument sequence imports unit and sequence of events importing unit transmits data with overhead control logical block respectively; Described overhead control logical block is transmitted data with operational parameter control unit and knowledge logic unit respectively.
3. active power distribution network autonomyization emulation mode as claimed in claim 2, is characterized in that, described 2 communication port are respectively used to data input and output; Described 2 serve ports are respectively used to the request of subordinate's order and distributing of superior command;
Described overhead control logical block and operational parameter control unit are the core of central agency for the superior and the subordinate's management; Described central agency refers to central coordinator AJC;
Described argument sequence imports unit and sequence of events importing unit is respectively used to parameter and the event that buffer memory the superior and the subordinate transmit in time series emulation;
Relationship between superior and subordinate and object properties that described context unit and object properties specify respectively this unit to act on behalf of;
Described knowledge logic unit is the basis of event response, for explaining self rule of conduct of autonomous simulation object ASOM model and central coordinator AJC;
Wherein context unit comprises context source unit and context object element.
4. active power distribution network autonomyization emulation mode as claimed in claim 1, it is characterized in that, in described step (2), by the autonomous operation of the autonomous simulation object model profile formula based on multi-agent system MAS, carry out synchronous and unified coordination of task by the autonomous simulation object model work telegon based on distributed agent framework;
The unified coordination of autonomous simulation object ASOM model based on multi-agent system MAS and central coordinator AJC comprises: A, distributed power source DER unit regulate, and vehicle economy R unit regulates; B, distributed energy storage DES and electric automobile EV model regulate; C, normal power supplies model regulate; D, initiatively power distribution network load model adjusting; E, intelligent power distribution substation model regulate.
5. active power distribution network autonomyization emulation mode as claimed in claim 4, is characterized in that, the DER unit of described A regulate will the value of exerting oneself curve as inputting data; According to the orderly access of DER unit and the global coordination target that initiatively power distribution network network fluctuates minimum, guarantee the access of DER unit; In the time not considering distributed power source random fluctuation, current self value of exerting oneself is is directly reported and submitted in each DER unit timing, in the time of the random fluctuation of consideration distributed power generation, according to normal distribution, the value of exerting oneself is carried out to random processing, worthwhile actual the exerting oneself of doing of then this being exerted oneself at random;
The operation constraint of DER unit is that the maximum of DER can be accepted access than DER_MAX, and in the time that distributed electrical source unit changes, central coordinator AJC, as central agency, carries out decision-making by central agency:
Step a.: when newly adding a DER or existing DER state to upgrade in simulation process, the DER that triggers a central agency coordinates event, and central agency is called DER coordination function;
Step b.: whether first central agency judges that the rear maximum of variation can be accepted access more out-of-limit than DER_MAX, if not, allows access and finish; If so, enter Step c;
Step c: more out-of-limit than DER_MAX if maximum can be accepted access, continue to judge whether to be newly to add power supply, if so, asked veto and finish; If not, enter DER grading subprocess, comprising:
-Substep is c.1: call Ranking () function to the sequence of all DER unit, generate the sequencing table DERSchedule of all DER;
-Substep is c.2: pointer K points to the first place of DER Schedule;
-Substep is c.3: the DER unit that central agency specifies pointer K to point to exits, and then judges that whether DER_MAX is still out-of-limit, if so, moves afterwards the pointer K address duplicate step of laying equal stress on, and if not, process finishes.
6. active power distribution network autonomyization emulation mode as claimed in claim 4, is characterized in that, the distributed energy storage DES of described B and electric automobile EV model are for the balance optimizing between auxiliary distributed generators and loads; In the time that distributed power source-balancing the load is carried out in electric system, the difference that power supply and load are coordinated for supplementing Power Systems.
7. active power distribution network autonomyization emulation mode as claimed in claim 4, it is characterized in that, the normal power supplies model adjusting of described C comprises: initiatively the normal power supplies unit in power distribution network comprises two classes: the small power supply node in outer net or major network equivalence and net, for the parameter variation of tracing and monitoring external network equivalent and exerting oneself of adjusting small power supply node; Operation constraint condition is determined by electric system total load; When operation each load cell initiatively report and submit to central agency timing self load value, central agency need consider with current system in total load amount balance, in the time that system loading amount reduces, central agency initiation power supply coordination of tasks, first guarantees the access of DER unit; In the time that load increases, central agency priority access DER unit, then regulates normal power supplies unit, if still uneven, initiates Load Regulation.
8. active power distribution network autonomyization emulation mode as claimed in claim 4, is characterized in that, the active power distribution network load model of described D regulates and comprises:
Initiatively power distribution network load model comprises in business power load, commercial power load, residential electricity consumption load and active power distribution network in rushing distributed energy storage DES and the electric automobile EV of electric state;
Initiatively power distribution network load model comprises two input parameters: load curve and power purchase price target; The power purchase price target power purchase cost optimization that is used for loading; In the time not considering to load provisional random fluctuation, initiatively power distribution network load model carries out oneself state adjusting according to load curve, in the time experiencing external power source conveying deficiency, initiate Load Regulation request to central coordinator AJC, autonomous simulation object model work telegon based on distributed agent framework is received after request, initiate load model adjustment process, comprise the steps:
<1> is at load model universal time coordinated, for the priority access to distributed power source DER and power purchase cost optimization, priority access distributed power source DER, if exist DER for subsequent use to carry out DER adjustment process at once, if meet operation constraint, DER is normal to be started and system source lotus balance, and tuning algorithm finishes;
If <1> is invalid for <2> step, enter the normal power supplies model adjustment process described in C, iterate until electric system balance, coordination process finishes; If still invalid, enter step <3> and carry out load adjustment;
<3>, in the situation that all power adjustment are invalid, calls the load grading subprocess of central coordinator AJC, comprises the steps:
1. all load grading sequences, charging electric vehicle state → distributed energy storage → tri-type load → bis-type load → mono-type load order is followed in grading;
2. generate temporary address pointer J and point to first of load sequencing table;
3. first central coordinator AJC notifies the load model that pointer J points to regulate execution shutoff operation, and wait for that accepting load model regulates and return and close successful message, then whether balance of cycle criterion system loading total amount sysload_quantum, if not, move afterwards the pointer J address duplicate step of laying equal stress on, if so, coordination process finishes.
9. active power distribution network autonomyization emulation mode as claimed in claim 4, is characterized in that, the intelligent power distribution substation model of described E regulates and comprises:
Unit, distribution substation, SUBST unit is determined according to the difference of its distribution substation cell type pointed, and distribution substation cell type comprises mode transmission, power-type or load type; In the time of needs intellectual power distributing station detailed model, SUBST unit is as the central agency of management distribution substation, the intelligent terminal of inside, unified management SUBST unit, protection, disconnector, bus, feeder line various kinds of equipment unit;
SUBST is as the internetwork intermediate node of the superior and the subordinate, for task distribution formula distribute and subnet between the function of delivery of electrical energy and coordination.
10. active power distribution network autonomyization emulation mode as claimed in claim 4, is characterized in that, following two aspects of action foundation of the autonomous simulation object model based on multi-agent system MAS:
1) do not stop the variation that gets parms, according to the autonomous action of self rule and central coordinator AJC is circulated a notice of;
2), when needs are unified universal time coordinated, central coordinator AJC distributes to force the autonomous simulation object model based on multi-agent system MAS to move by organization task;
Central coordinator AJC is connected to obtain constraint condition and policing rule with unified knowledge engine, generates applicable coordination strategy under constraint condition; Unified knowledge engine is a data base administration engine based on knowledge rule.
11. active power distribution network autonomyization emulation modes as claimed in claim 1, is characterized in that, described step (3) comprising:
1> carries out multistage setting in conjunction with ASOM model to task central coordinator AJC: on the basis of step (2), active power distribution network is divided into multiple subnets multistage and that how to move according to electric pressure and Regional Distribution;
2> sets up the interaction mechanism of central coordinator AJC at different levels and ASOM model: integrating step (1) and step (2), set up the topological sum administrative model of multistage active power distribution network, realize trans-regional energy equilibrium by higher level's network that each bottom subnet is coordinated.
12. active power distribution network autonomyization emulation modes as claimed in claim 1, is characterized in that, initiatively the emulation of power distribution network autonomyization comprises energy coordinated management task, and energy coordinated management comprises the steps:
A, when certain industrial load ASOM model monitoring is when commercial power load increases in region, to this region central coordinator AJC transmitted power solicited message;
B, receive after the solicited message of industrial load control ASOM model as central coordinator AJC at the corresponding levels, simulation calculation is carried out in this region, if the scheme of being resolved, issue regulating command to power supply, electric automobile energy storage and the load ASOM model of its administration, if it is still excessive to load, continue superior request;
C, when higher level's central coordinator AJC receives after the solicited message of subordinate, the realistic model in this region is calculated, the region AJC of other subordinates administering to it issues regulating command, if power does not also reach balance, continues superior request.
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