CN101777769A - Multi-agent optimized coordination control method of electric network - Google Patents
Multi-agent optimized coordination control method of electric network Download PDFInfo
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Abstract
The invention relates to a multi-agent optimized coordination control method of an electric network in the technical field of electric networks, which comprises the following steps of: collecting local electric information, transmitting the local electric information to a central agent of a microgrid and issuing a control command by a local electric network to the central agent of the microgrid simultaneously; computing by a grid technology; issuing a new control command by the central agent of the microgrid and transmitting the information to a regulation agent of the local electric network by a network line simultaneously; receiving a dispatching instruction of the central agent of the microgrid by the agent of each element and carrying out logical judgment on a result executing these dispatching commands according to the collected local electric information; and meanwhile, optimizing the electric network within a control range by the regulation agent of the local electric network and controlling a computer to carry out parallel computation by the grid technology. The invention is suitable for carrying out optimal dispatching on a distributed energy resource of an intelligent electric network, can control each power supply by an optimization scheme, also enhances the operational processing time greatly and ensures that the intelligent electric network runs safely, stably and economically.
Description
Technical field
What the present invention relates to is the control method in a kind of electric power network technique field, particularly a kind of multi-agent optimized coordination control method of the electrical network based on grid.
Background technology
In the intelligent grid in future, electric energy not only flows to power transmission network, power distribution network until the user from centralized power plant, also spread all over various forms of new forms of energy and clean energy resource in the electrical network simultaneously, comprise: solar energy, wind energy, fuel cell, electric automobile or the like just are called as distributed energy when these energy are installed in user side.Yet after incorporating a large amount of distributed energies in the electrical network, the complexity of the structure of electrical network, form of energy, flow of power, information exchange and control mode will increase greatly.Therefore, how various distributed energies being carried out intelligent management is one of key technology that realizes intelligent grid.The problem of bringing at distributed energy, proposing at present and studying maximum solutions is exactly little electrical network (Micro Grid) technology, promptly for transmission of electricity cost height, to the demanding concentrated power consumer of quality of power supply district, distributed energy is inserted big electrical network with the form of little electrical network.Little electrical network can effectively utilize distributed energy on the one hand, and high-quality power supply service is provided, and can avoid the impact of distributed energy to big electrical network on the other hand again, therefore becomes to solve the effective means that distributed energy inserts problem on a large scale.
Meanwhile, how to solve the safe and reliable stable operation of the electric power system that comprises a large amount of distributed energies, the safety and stability that is related to a society will be carried out the normal operation and the economical operation of safety analysis, assurance electric power system to electrical network, and we must carry out a large amount of digital operations.And because the restriction of existing computer technology, the method for the main employing in electric power system is rule of thumb existing network to be carried out equivalence simplification at present, carries out calculated off-line again or in line computation. this just can not guarantee real-time and the accuracy calculated.Simultaneously, control of the optimization of electric power system and dynamic real-time safety analysis have also proposed very high requirement to computational speed.Because present unit computational speed can not satisfy the real-time calculation requirement of large-scale electrical power system far away.In order to improve computing capability, main method is parallel computation in electric power system tide calculating, transient stability analysis now, but its calculating speed-up ratio and efficient are not high, and computing capability does not catch up with the growth of practical problem computation requirement all the time.And the required hardware cost of parallel computation is too high, the software programming difficulty, and many unfavorable factors such as user's working service technical sophistication are calculated to be pressing for for power system development thereby cause studying grid.
Yet, comprise the intelligent grid of a large amount of distributed power sources, owing to there is a large amount of information datas,, be difficult to effectively realization to effective control of each power supply and load if adopt traditional centralized dispatching control mode.And the multi-agent system that reaches its maturity provides effective solution for the distributed control of electric power system.And in view of a plurality of advantages such as intelligent body independence and reactivities, it can fully realize functional management and unmanned scheduling to electric power system.
Find by prior art documents, Chinese patent application numbers 200710152493.0, denomination of invention: the system and method for controlling little electrical network, publication number: CN101207284, this patent has realized control and the management of large-scale power grid to little electrical network preferably by being communicated with lane controller, however this method: and (1) this control method lacks the optimization analysis of the whole network operation and quick account form; (2) control method does not have the error correction of consideration to false command, causes the possibility of system's unstability, and this connection lane controller is difficult for reaching electrical network economy and aim of stable operation because network delay or obstruction are difficult to realize real-time control.
In view of above analysis, provide the optimized dispatching scheme in order to give the intelligent grid comprise a large amount of distributed energies, at the management of wherein distributed power source, this project has proposed the intelligent grid multi-agent optimized coordination control method based on grid especially.
Summary of the invention
The objective of the invention is to solve the optimum management and the control of a large amount of distributed power sources of intelligent grid, and coordinate whole electrical network and reach safety, stable, economic, operation reliably, a kind of intelligent grid multi-agent optimized coordination control method based on grid is provided.This control method is carried out hierarchical control by multi-agent system to intelligent grid, and utilizes grid to carry out parallel computation, guarantees the intelligentized safe and stable operation of following electrical network.
It is as follows to the present invention includes step:
The first step: gather local electric information by sampling apparatus by each the element Agent that is in the control structure bottom, as information such as frequency, voltage, electric currents, and pass to little electrical network maincenter Agent by netting twine, regional power grid is transferred stable principle and the economic principle of Agent according to regional power grid simultaneously, can assign control command information and give little electrical network maincenter Agent.
Second step: little electrical network maincenter Agent carries out total activation to little electrical network of its administration, receive electric information, and carry out the computation optimization of electrical network in the control range, carry out security and stability analysis and economic operation analysis, promptly pass through grid, the mathematics target function is sent to many computers carry out parallel computation simultaneously, calculate by the unit serial computing by described grid and change parallel computation into, utilize MPICH to realize by many computers of grid.Can improve computing time greatly like this.
The 3rd step: little electrical network maincenter Agent is according to computation optimization result and predefined coordination control strategy in second step
The 3rd goes on foot: little electrical network maincenter Agent assigns new control command according to computation optimization result in second step and preestablishing to bottom component Agent of coordination control, and simultaneously information is passed to regional power grid accent Agent by netting twine.
The 4th step: each element Agent accepts the dispatch command of little electrical network maincenter Agent, and according to the local electric information of being gathered, as voltage, frequency, electric current, the result who carries out these dispatching commands is carried out logic determines according to the program of prior setting, if carrying out these instructions can not damage the stability of electrical network, then carry out the related electric element for example power supply and load operate, otherwise refusal is carried out and is newly instructed and inquire little electrical network maincenter Agent.Simultaneously, the computation optimization of electrical network in the control range is carried out in information that little electrical network maincenter Agent uploaded during regional power grid accent Agent went on foot according to the 3rd and the instruction of always transferring Agent to assign, promptly carry out security and stability analysis and economic operation analysis, calculate to adopt grid, be about to target function and send to many computers by netting twine and carry out parallel computation simultaneously.
The 5th step: regional power grid transfers Agent to assign new control command for little electrical network maincenter Agent according to the computation optimization result, and simultaneously information is passed to total accent Agent by netting twine.
The 6th step: little electrical network maincenter Agent transfers the local electric information of new control command of Agent and collection to carry out second step the operation described according to the 5th step regional power grid.Total computation optimization of transferring Agent to carry out electrical network in the control range, promptly carry out security and stability analysis and economic operation analysis, calculate and adopt grid, be about to target function and send to many computers by netting twine and carry out parallel computation simultaneously, and transfer Agent to assign new control command to regional power grid by netting twine according to the computation optimization result.
The 7th step: regional power grid accent Agent carries out the operation described in the 4th step according to the information that the 6th step always transferred little electrical network maincenter Agent of new control command of Agent and description in the 3rd step to upload.
In electric power system, electrical network is formed little electrical network by some single electric component, again by certain electrical network compositing area electrical network slightly, all at last regional power grids are formed the whole network, the present invention utilizes the control structure of multiple agent, element Agent from bottom to top, little electrical network maincenter Agent, regional power grid is transferred Agent, total Agent that transfers, each layer Agent is one or more CPU that ability to communicate is arranged, wherein element Agent mainly is responsible for the control of electric components such as power supply and load and gathers this ground voltage, electric current, electric informations such as frequency, little electrical network maincenter Agent replaces the artificial management of being responsible in certain little electrical network scope, regional power grid transfers Agent to replace the artificial management of being responsible in certain regional power grid scope, total Agent of accent replaces the artificial management of being responsible in the network-wide basis, their management method is to be optimized calculating according to various electric informations, and the following one deck Agent issue control command in its compass of competency.By grid, target function is sent to many computers carry out parallel computation simultaneously, intelligent grid the whole network is optimized coordinates control, promptly carry out security and stability analysis and economic operation analysis, realize economy, the security dispatching of the whole network automatically.
Intelligent grid multi-agent optimized coordination control method based on grid of the present invention, its maximum characteristics are to have adopted the thought of MAS control system hierarchical control and utilized grid, the optimized dispatching of realization the whole network that can automated intelligent has solved the problem that the intelligent grid distributed power source is many, management is difficult; Realized the unmanned scheduling of intelligence of intelligent grid; The computing and the analysis of control system have been accelerated; Guarantee the operation of electricity net safety stable when rational dispatching by power grids can be guaranteed.
Description of drawings
Fig. 1, be the intelligent grid of distributed energy management means with little electrical network;
The multiple agent structural system schematic diagram of Fig. 2, intelligent grid;
Fig. 3, quiescent voltage analysis process figure;
The MPI parallel computation flow chart that Fig. 4, quiescent voltage are analyzed;
Fig. 5, based on the central controlled distributed power source overall coordination of microgrid strategic process figure;
Fig. 6, accumulator element Agent functional schematic;
Fig. 7, fuel cell and gas turbine Agent control strategy flow chart;
Fig. 8, photovoltaic Agent and wind-powered electricity generation Agent control strategy flow chart;
Fig. 9, load Agent control strategy flow chart;
Figure 10, photovoltaic generation MPPT and load curve;
Figure 11, simulation result figure;
Figure 12, photovoltaic, wind-powered electricity generation MPPT compare with actual output;
Figure 13, the whole network node voltage curve chart;
Figure 14, batteries to store energy and charge power.
Embodiment
Below in conjunction with accompanying drawing embodiments of the invention are elaborated: following examples have provided detailed execution mode and process being to implement under the prerequisite with the technical solution of the present invention, but protection scope of the present invention is not limited to following embodiment.
Embodiment
Present embodiment is coordinated in the control based on the optimization that grid is applied to intelligent grid.This intelligent grid utilizes little grid mode unification to manage distributed power source as shown in Figure 1, inserts distribution network system again, and then connects into an integral body with traditional electrical network.This management mode can effectively be utilized distributed energy on the one hand, and high-quality power supply service is provided, and can avoid the impact of distributed energy to big electrical network on the other hand again.Be described in detail as follows:
The first step: gather local related electric information by sampling apparatus by each bottom component Agent, as information such as frequency, voltage, electric currents, and passing to little electrical network maincenter Agent by netting twine, regional power grid is transferred Agent can assign control command information and is given little electrical network maincenter Agent simultaneously.
The multi-agent system hierarchy that present embodiment adopts is divided into four layers as shown in Figure 2: element Agent, little electrical network maincenter Agent, regional power grid transfer Agent, regional power grid to transfer Agent.Each layer Agent can be regarded as one or more CPU that ability to communicate is arranged, and each bottom component (comprising generator, load etc.) is all as independently Agent operation; Little electrical network maincenter Agent coordinates and manages bottom component Agent in this little electrical network according to bottom Agent information and last layer Agent instruction; Regional power grid transfers Agent to can be understood as traditional power distribution network dispatching patcher, and it coordinates to solve task division and the shared resource allocation between each little electrical network maincenter Agent in the compass of competency by communication, and the generating of management legacy and converting equipment; Net transfers Agent to can be understood as the power transmission network dispatching patcher, and it coordinates to solve task division and the shared resource allocation between each regional power grid accent Agent in the compass of competency by communication.Different Agent also keeps the reasonability of a certain amount of data communication with better each self-decision of assurance.
Second step: little electrical network maincenter Agent is by the information described in the netting twine reception first step, and carry out the computation optimization of electrical network in the control range, promptly carry out security and stability analysis and economic operation analysis, calculate and adopt grid, be about to target function and send to many computers and carry out parallel computation simultaneously, can improve computing time greatly like this.
The optimization essence of each layer of present embodiment Agent is security and stability analysis and economic analysis, it also is the basis of this project control method, any control command all will be referred from these result of calculations, in order in time the whole network to be controlled fast, realize that fast these mass computings just seem most important, and traditional serial computing mode can be improved to the parallel computation mode based on the multimachine parallel computation mode of grid, this mode has significantly reduced computing time.This project adopts message TRANSFER MODEL MPI (Message Passing Interfae) to realize parallel computation, it has higher communication performance, characteristics such as program portability and strong functions preferably, so it becomes the most general multiple programming mode at present.Present embodiment is analyzed quiescent voltage safety, and continuous tide algorithm and corresponding gridding parallel computation flow chart are as shown in Figure 3 and as shown in Figure 4.With the IEEE162 node is that example is analyzed, if the unit serial computing, consuming running time is 5.0105s, and adopt 2 machine parallel computations, operation time, consumption was 4.65503, this shows, if it is many more to participate in the number of computers of parallel computation on the grid, will faster operation time so.
The 3rd step: little electrical network maincenter Agent assigns new control command by netting twine for bottom component Agent according to computation optimization result in second step and predefined coordination control strategy, and simultaneously information is passed to regional power grid accent Agent.
The main target of present embodiment is to realize most economical operation under the condition that guarantees network-wide security stable operation, be noted that, the safety and stability emphasis of this paper research is from the stable angle of voltage, because in little electrical network of distributed power source by the inverter access, there is not synchronous type distributed power source, angle stability is not a subject matter just also, and the surplus of active power or not enough will directly cause the rising or the decline of busbar voltage; Most economical operation then is to make regenerative resource (photovoltaic, wind-powered electricity generation) be operated in the MPPT pattern as far as possible, because their generatings do not need to spend this cost such as fuel-cell fuel.Be that the controlled target function is:
F＝{maxP
G，i|V
min≤V(t)
i≤V
max} (1)
In the formula: P
G, iBe i renewable energy power generation element of electrical network energy output, V (t)
iBe i bus nodes voltage of t little electrical network of the moment, V
Max, V
MinBe respectively 1.05,0.95.
Corresponding constraint constrains condition is as follows:
1) power-balance
∑P
G，i＝P
D+P
L (2)
In the formula, P
D, P
LBe respectively workload demand and via net loss.
2) batteries to store energy restriction
0.2≤S
s(t)≤S
s，max (3)
In the formula, S
s(t) be t battery stores amount constantly, S
S, max=2.5.For storage battery, generally can not allow it put electricity fully, so this paper is lower than after 0.2 being connected of automatic disconnection storage battery and electrical network in energy storage, and the put electric state of the state of energy storage capacity 0.2 for hereinafter being mentioned.
3) accumulator cell charging and discharging Power Limitation
P
s(t)≤P
max (4)
In the formula, P
s(t) be t accumulator cell charging and discharging power constantly, P
Max=1.25.
4) storage battery trouble free service voltage limit
V
safe_min＜V
s(t)＜V
safe_max (5)
In the formula, V
s(t) be storage battery t operating voltage constantly, V
Safe_min=0.9, V
Safe_max=1.1 are respectively the minimum and the peak of storage battery trouble free service voltage.
5) photovoltaic, wind-powered electricity generation generating restriction
P
PV(t)≤P
PV_mppt (6)
P
wind(t)≤P
wind_mppt (7)
In the formula, P
PV(t), P
Wind(t) be t photovoltaic and wind-powered electricity generation generated output constantly, P
PV_mppt, P
PV_winddGenerated output during for MPPT.(all parameters all are per unit value)
According to controlled target and each constraints of formula (1), little electrical network maincenter Agent designs as shown in Figure 5 for the coordination control strategy of microgrid.Little electrical network maincenter Agent will transfer the information of Agent that bottom Agent is carried out event-driven control according to bottom component Agent and regional power grid, in case new environmental change is arranged in little electrical network, the running status of each Agent will be adjusted.
The 4th step: each bottom component Agent accepts the dispatch command of little electrical network maincenter Agent, and according to the local electric information of being gathered, as voltage, frequency, electric current, the result who carries out these dispatching commands is carried out carrying out logic determines according to the program of setting in advance, if judge that carrying out these instructions can not damage the stability of electrical network, then carry out the related electric element for example power supply and load operate, otherwise refusal is carried out and is newly instructed and inquire little electrical network maincenter Agent.Simultaneously, regional power grid is transferred the information that Agent uploads according to little electrical network maincenter Agent in the 3rd step and is always transferred Agent to carry out the computation optimization of electrical network in the control range, promptly carry out security and stability analysis and economic operation analysis, calculate to adopt grid, be about to target function and send to many computers and carry out parallel computation simultaneously.
Each the bottom component Agent that describes for the 4th step is according to the operation of setting program in advance or being embodied as of inquiry higher level Agent: according to the storage battery Agent control flow of formula (3), (4), (5) design as shown in Figure 6; According to the control flow of the fuel cell of Fig. 5 design and miniature gas turbine Agent as shown in Figure 7; According to the blower fan of formula (6), (7) design, photovoltaic Agent control flow as shown in Figure 8; According to the control flow of the load Agent of Fig. 5 design as shown in Figure 9.
Regional power grid transfers Agent to adopt the optimized Algorithm of grid to describe as second step, and just the more little electrical network maincenter of compass of competency Agent is bigger.
The 5th step: regional power grid transfers Agent to assign new control command for little electrical network maincenter Agent according to the computation optimization result, and simultaneously information is passed to total accent Agent.
The 6th step: little electrical network maincenter Agent transfers the local electric information of new control command of Agent and collection to carry out second step the operation described according to the 5th step regional power grid.Total computation optimization of transferring Agent to carry out electrical network in the control range, promptly carry out security and stability analysis and economic operation analysis, calculate and adopt grid, be about to target function and send to many computers and carry out parallel computation simultaneously, and transfer Agent to assign new control command to regional power grid according to the computation optimization result.
Total Agent of accent adopts the optimized Algorithm of grid to describe as second step, and just compass of competency transfers Agent bigger than regional power grid.
The 7th step: regional power grid accent Agent carries out the operation described in the 4th step according to the information that the 6th step always transferred little electrical network maincenter Agent of new control command of Agent and description in the 3rd step to upload.
Present embodiment emulation desired parameters figure as shown in figure 10.It has described 12 load variations in 8 of mornings to evening, photovoltaic MPPT curve and wind-powered electricity generation MPPT curve.Wherein, the primary fault that takes place suddenly of 12:35 make load lose near half.The installed capacity that it should be noted that wind-powered electricity generation and photovoltaic might be greater than the demand of microgrid internal loading, and still under the situation of being incorporated into the power networks, unnecessary energy output will be transferred to major network.The data of this emulation all are perunit values, and the line voltage reference value is 400V, and the power reference value is 500kVA.Provided under the coordination control of MAS, this actual power of netting each element is exported situation as shown in figure 11, and among the figure, except load curve, power is for just representing the injecting power to system.The difference of photovoltaic, the actual output of wind-powered electricity generation and MPPT as shown in figure 12.Under the control method for coordinating control action that this project proposes, different little line voltage situations constantly as shown in figure 13, as can be seen, under the coordination control of MAS, each node voltage of little electrical network is all the time all in safe range, even if etching system catastrophic failure during 12:35 also because of the fast reaction of Agent, has guaranteed the stable of the whole network voltage.The charging of storage battery and energy storage situation as shown in figure 14 because unit all is perunit value, so can be illustrated in both among 1 figure.As can be seen from the figure, storage battery has carried out power adjustments by discharging and recharging effectively to electrical network, and because storage battery Agent controls for the strictness that discharges and recharges power, storage battery can always work in safe condition.Present embodiment is applicable to the intelligent grid distributed energy is carried out optimal scheduling that it can control each power supply with optimized scheme, improves greatly the calculation process time simultaneously, guarantees intelligent grid safety, stable, operation economically.
Claims (5)
1. the multi-agent optimized coordination control method of an electrical network is characterized in that, comprises that step is as follows:
The first step: gather local electric information by each the element Agent that is in the control structure bottom by sampling apparatus, and pass to little electrical network maincenter Agent by netting twine, regional power grid is assigned control command and is given little electrical network maincenter Agent simultaneously;
Second step: little electrical network maincenter Agent carries out total activation to little electrical network of its administration, and by grid, the control computer carries out parallel computation simultaneously;
The 3rd goes on foot: little electrical network maincenter Agent assigns new control command according to computation optimization result in second step and preestablishing to bottom component Agent of coordination control, and simultaneously information is passed to regional power grid accent Agent by netting twine;
The 4th step: each element Agent accepts the dispatch command of little electrical network maincenter Agent, and according to the local electric information of being gathered, the result who carries out these dispatching commands is carried out logic determines:
Can the stability of electrical network not damaged if carry out these instructions, then carry out power supply and the load electric component is operated, otherwise refusal is carried out and newly to be instructed and inquire little electrical network maincenter Agent;
Simultaneously, the optimization of electrical network in the control range is carried out in information that little electrical network maincenter Agent uploaded during regional power grid accent Agent went on foot according to the 3rd and the instruction of always transferring Agent to assign, and by grid, the control computer carries out parallel computation simultaneously;
The 5th step: regional power grid transfers Agent to assign new control command for little electrical network maincenter Agent according to the computation optimization result, and simultaneously information is passed to total accent Agent by netting twine;
The 6th step: little electrical network maincenter Agent transfers the local electric information of new control command of Agent and collection to carry out for second step according to the 5th step zone: always transfer Agent to carry out the optimization of electrical network in the control range, pass through grid, the control computer carries out parallel computation simultaneously, and transfers Agent to assign new control command by netting twine according to the computation optimization result to regional power grid;
The 7th step: regional power grid accent Agent carries out the operation described in the 4th step according to the information that the 6th step always transferred little electrical network maincenter Agent of new control command of Agent and description in the 3rd step to upload.
2. the multi-agent optimized coordination control method of electrical network according to claim 1 is characterized in that, described electric information is frequency, voltage, current information.
3. the multi-agent optimized coordination control method of electrical network according to claim 1, it is characterized in that the described control command of assigning is meant that regional power grid accent Agent assigns control command information to little electrical network maincenter Agent according to the stable principle and the economic principle of regional power grid.
4. the multi-agent optimized coordination control method of electrical network according to claim 1, it is characterized in that, the described grid that passes through, be that little electrical network maincenter Agent receives electric information, and carry out the computation optimization of electrical network in the control range, carry out security and stability analysis and economic operation analysis to stablizing principle and economic principle, target function is sent to many computers carry out parallel computation simultaneously, improve computing time.
5. the multi-agent optimized coordination control method of electrical network according to claim 1 is characterized in that, calculates by described grid, is meant: change parallel computation by many computers of grid into by the unit serial computing, utilize MPICH to realize.
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