CN103001225A - MAS-based (multi-agent system) multi-microgrid energy management system simulation method - Google Patents

Abstract

The invention relates to an MAS-based (multi-agent system) multi-microgrid energy management system simulation method. The method is characterized in that a multi-microgrid energy management system is divided into a local management layer, a microgrid management layer and a microgrid coordinated management layer in different levels; various energy management functions of the different layers are used to establish a multi-microgrid energy management system model by different types of agents, and agent communication protocol is designed for coordination and convention of the agents. The agents in different control layers of the local management layer, the microgrid management layer and the coordinated management layer are integrated by a client-server architecture, and accordingly an MAT-based (multi-agent technology-based) multi-microgrid energy management system simulation platform is formed. The method is provided to verify different microgrid control strategies and scheduling plans.

Description

Many microgrid energies management system emulation mode based on MAS

Technical field

The present invention relates to a kind of energy control and management system emulation mode that is applied in the micro-grid system.

Background technology

Little electrical network is usually by clean energy resource electricity generation systems such as the renewable energy systems such as wind energy, solar energy and biomass energy, fuel cell, miniature gas turbines, long-term and the energy storage device of short-term and various users' various electric loadings and the heat load composition such as storage battery and flywheel.The purpose of microgrid energy management system (EMS-MG) is under the prerequisite how user's electric loading and heat load require in satisfying little electrical network, keeps little power grid operation, improves the efficient of generating equipment using energy source in little electrical network; On this basis, by accurately weather forecasting data, improve wind energy, solar energy etc. in little electrical network and can in the utilance of giving birth to energy generating, reduce the pollution that utilizes traditional energy to generate electricity and bring to environment.In addition, also to guarantee the smooth conversion of little electrical network when different operational mode transition.With respect to large electrical network conventional energy management system (EMS), the microgrid energy management system is faced with many new challenges.This mainly is the following feature that comes from little electrical network:

1, the diversity of generator unit: because the load follow reaction speed difference of each generator unit is very large in little electrical network, from Millisecond (solar energy, fuel cell, electric energy storage device), second level (gas turbine, mechanical energy storage) to classification (wind power generation), and the correlation of the correlation of input energy sources (such as wind energy, solar energy), the output energy (power supply) more increased the complexity of little operation of power networks scheduling problem, so that energy control and the large increase of containing much information of management.

2, the fluctuation of primary energy: because the randomness of solar energy and wind energy, so that comprise the actual power ability of the micro-grid system of solar power generation and wind power generation unit be at random with the fluctuation, so that the system capacity scheduling is compared with electric power system, the demand that not only needs the Accurate Prediction load, also must Accurate Prediction solar energy and the generating capacity of wind power generation unit when long (in short-term), this will increase the complexity of system capacity control and scheduling decision greatly.

3, the polymorphism of system operation and control model: under the normal condition micro-grid system can with the electrical network parallel running; In case when electrical network broke down, micro-grid system then will initiatively withdraw from large electrical network, is transitioned into independent operation mode, keep the busbar voltage amplitude of little electrical network inside and stablizing of frequency.The polymorphism of this micro-grid system operation and control model is so that the no longer applicable micro-grid system of the energy of conventional energy resource control model needs the new overall intelligent energy of research to control model.

Above-mentioned feature so that the energy traffic control of micro-grid system and energy scheduling decision be multiple target, a multivariable, have probabilistic DYNAMIC COMPLEX process, must depend on new control method, computational methods and evaluation method, thereby support reliable, efficient, the flexibly operation of distributed energy micro-grid system.The checking of said method need to provide effective, economic means, but does not have so far the open report of correlation technique.

Summary of the invention

The present invention is for avoiding the existing weak point of above-mentioned prior art, a kind of many microgrid energies management system emulation mode based on MAS is provided, energy control and management system simulation problems for the multiple-energy-source micro-grid system, a kind of energy control and administrative model based on MAS is provided, realize the emulation of multiple-energy-source micro-grid system energy control and management system, for different little power grid control strategy and operation plan provide a kind of verification tool.

The present invention is that the technical solution problem adopts following technical scheme:

The characteristics that the present invention is based on many microgrid energies management system emulation mode of MAS are:

Many microgrid energies management system is divided into local management layer, three different levels of little administration of power networks layer and micro electric network coordination management level; Described local management layer makes it by existing plan normal operation for little power supply of managing little electrical network, satisfies in real time the equilibrium of supply and demand, and sustain pulse frequency is stable; Described little administration of power networks layer is by the coordination control of little power supply, reduce little line voltage and frequency departure amplitude during lonely network operation, reduce the exchange power of public electric wire net switching node and the deviation of planned value when being incorporated into the power networks, and the economic dispatch in the realization microgrid, improve regenerative resource in little electrical network proportion of utilization and take full advantage of the heat energy that produces in the generating; Described micro electric network coordination management level are by whole little power grid control, finish cooperation target between a plurality of little electrical networks or the control target of large electrical network, and switch little operation of power networks when little electric network fault, coordinate that each little power supply makes little electrical network transition steady in little electrical network;

The various energy management functionality that possess on described local management layer, little administration of power networks layer and three different levels of micro electric network coordination management level adopt dissimilar Agent to set up many microgrid energies management system simulation model, and role and the functional definition of the Agent on described local management layer, little administration of power networks layer and the micro electric network coordination management level are as follows:

1) local management layer, it is provided with model of element Agent, state Agent, local control agents and Communication Agent:

A), described model of element Agent, it is including but not limited to the energy computation model of following little power supply: the photovoltaic plant power output is calculated model, wind power generation is that the unit power output is calculated model, the fuel cell output power computation model, storage battery power output and state-of-charge computation model, the gas turbine power output is calculated model, bearing power computation model; Described energy computation model provides the Digital Simulation calculated data of little electrical network dynamic operation for the microgrid energy management system;

B), described state Agent, the state of its Real Time Monitoring local device, power output, output voltage and the output frequency that comprises little grid generation equipment is connected distributed power generation unit, energy-storage units or load unit and connected the information of electric current, voltage and the frequency of little electrical network bus, described state Agent shows these information on the one hand, on the other hand these information is passed to described local control agents;

C), described local control agents, the state of the local device that it provides according to decision instruction and the described state Agent of little administration of power networks layer, according to designed little power system controller algorithm, realization manages meritorious, the reactive power of distributed power generation unit, energy-storage units, load is realized the corresponding demand side management, and when circuit breaks down, local device is protected action; Described local device is little power supply, contactor, circuit breaker and the load cell that is connected to the different nodes of little electrical network electrical network; Described little power supply comprises photovoltaic generating system, wind generator system, fuel cell, miniature gas turbine and storage battery;

D), described Communication Agent, its be responsible for and the local management layer between each local Agent and the information exchange between the Agent of each local Agent and little administration of power networks layer;

2) little administration of power networks layer, it is provided with little electric network data and gathers SCADA Agent, coordination control agents, economic optimization scheduling Agent, tidal current analysis Agent, energy predicting Agent and historical failure analysis Agent:

A), described SCADA Agent, it collects state and the service data of equipment in little electrical network by remote data collecting unit (RTU), simultaneously issue setup control order from little electrical network central controller to low layer control unit orientation, the real-time running state of the equipment in little electrical network is monitored;

B), described coordination control agents, it is according to the generation schedule of local each equipment of little electrical network real-time running state data modification of SCADAAgent acquisition, but by power and the voltage-operated reference point of setting controlling equipment in little electrical network, make little mains frequency stable, power-balance is to reach the purpose of automatic generation coordination control in little electrical network, and realize that little electrical network overall efficiency is maximum, little administration of power networks target that little grid net loss is minimum;

C), described economic dispatch Agent, it is according to optimization and the economy principle of trend, bid information to generating equipment in the prediction of the ultra-short term of regenerative resource and the little electrical network, use contract net coordination, Market Bidding Mechanism and particle cluster algorithm on the multiple-factor evaluation method basis, formulate following 24 hours the harmonious economy operation plan of each generator unit in little electrical network, economy optimization is carried out in the operation of little electrical network;

D), described tidal current analysis Agent, data that it is collected according to SCADA Agent and to the analysis of network topology, trend in little electrical network is carried out computational analysis, and the trend in little electrical network is optimized, to reduce the loss on the circuit, in the stability that guarantees whole little electrical network, make its economy reach optimum;

E), described energy predicting Agent, its historical data and weather forecasting data according to generating are carried out ultra-short term prediction of energy to the power station of renewable energy power generation; And from real-time data base and historical data base, analyze data, and utilize the intensified learning algorithm, constantly the predicted value of oneself is optimized;

F), described historical failure analyzes Agent, it is analyzed the fault that occurs in whole little operation of power networks, avoids next time controller to take again identical order initiating failure;

3) micro electric network coordination management level, it is provided with static switch Agent and little operation of power networks Agent:

A), static switch Agent, it monitors the state of little electrical network and regional power grid contact interface, when regional power grid breaks down or recovers fault, switches the running status of little electrical network;

B), little operation of power networks Agent, its representative system firing floor coordinate between little electrical network or little electrical network and regional power grid between cooperate, with little electrical network as a unified individual electricity market scheduling of participating in regional power grid, and according to the overall strategy of the size of self generating ability and Regional Electric Market price decision next stage.

The characteristics that the present invention is based on many microgrid energies management system emulation mode of MAS also are:

The upper different interior Agent of key-course of described local management layer, little administration of power networks layer and coordinated management layer adopts client-server architecture integrated, forms the many microgrid energies management system emulation platform based on multi-agent technology; In described many microgrid energies management system emulation platform based on multi-agent technology, comprise a server end and a plurality of client; The Agent that little administration of power networks layer and micro electric network coordination management level comprise adopts the method for function and assembly to realize at server end, and each Agent provides service and by coordinating control little electrical network managed and moves to the Agent of other little electrical network local management layers; At described server end, definition management service Agent and directory service Agent, wherein: when the user generates, deletes, removes or move into an Agent at platform, described management service Agent records, and realization is to the registration management of Agent; Described directory service Agent records the COS of each Agent, finishes complicated microgrid energy managerial role for the common cooperation of the Agent with different COS;

Described many microgrid energies management system based on multi-agent technology comprises the Agent client of multiple different type, and the Agent client of described different type realizes the energy management of the local management layer in little electrical network; An Agent client is used for realizing the control of concrete local device, according to the difference of client institute management equipment, client is divided into generating Agent, loaded Ag ent and energy storage Agent; There are a plurality of Agent to cooperate to manage this equipment on the Agent client, wherein the most basic Agent comprises: control agents, state Agent and Communication Agent, described Communication Agent represent this client and cooperate with little administration of power networks layer or other clients.

The characteristics that the present invention is based on many microgrid energies management system emulation mode of MAS also are:

Described based on communication need between the client and server in many microgrid energies management system emulation platform of multi-agent technology, required communications protocol is set, and server end utilizes described communications protocol to monitor the request of client: the Agent that server end is in little administration of power networks layer utilizes described communications protocol to collect information or the issue an order of client; Thereby the little operation of power networks Agent that is in the micro electric network coordination management level connects long-range electricity market server by described communications protocol to be identified oneself with among the electricity market;

Described communications protocol is as the basis take ICP/IP protocol, the intrinsic level that shows in information exchanging process according to Agent is divided into transport layer, communication layers and alternation of bed, and lower floor provides service for the upper strata, described transport layer is in the bottom, be the computer protocol layer, by described transport layer the message of protocol layer passed on by computer network protocol; Described communication layers is in the second layer, and namely protocol layer defines information type sign, message length and the device status data structure corresponding with the information type sign in described protocol layer; Described alternation of bed is in the 3rd layer, it is the interaction protocol layer, described interaction protocol layer coordinates, consults by a series of realizations that protocol layer is given expression to or the language of cooperation makes up, finish under the guidance of the upper strata of interaction protocol layer strategy between each Agent cooperation and agreement.

Compared with the prior art, beneficial effect of the present invention is embodied in:

1, the present invention is based on many Agent Theory, set up the layering of many microgrid energies management system, distribution energy control model, thus the quick efficient coordinated management unified many microgrid energies management system model based on multi-agent technology mutually of control and global energy of the distribution that can realize little electrical network local management layer, little administration of power networks layer and micro electric network coordination management level;

2, the present invention is based on many microgrid energies management system model architecture of multi-agent technology, structure realizes simple, but expansion flexibly.Not only the various models of new equipment can be realized by adding different Agent, and the new function that needs in the energy management also can realize by the Agent that adds a kind of this function, thereby so that the change of microgrid energy control strategy and expansion have flexibility, opening and high degree of autonomy;

3, the present invention is based on many microgrid energies management system model architecture of multi-agent technology, not only can combine to realize with physical hardware the dynamic network environment of whole little electrical network, realize the totally digitilized emulation of micro-grid system operation, can also be by the flexible design of control strategy in the generating embedding of model and the control agents among little electrical network unit Agent, make real-time energy management and the control of the many micro-grid systems of its easier realization, convenience provides one can have both real time execution control and the mutually unified system of scientific research platform to the assessment of the effect of different-energy management strategy;

4, the MAS model is not only on whole little electrical network aspect among the present invention, and this locality control on the client also can on the basis of carrying out the overall goal that little administration of power networks layer sends, be carried out local optimum; And utilize the rapidly characteristics of communicating by letter between the client, adopt unified agreement just can make the cooperation that realizes some complexity between the Agent client, certain Agent client is initiation session initiatively, and cooperate between one or more Agent client, redistributing in carrying out among a small circle to current load is to reach the purpose of quick local optimum.

5, Client-Server multi-agent system framework among the present invention on the basis that client is expanded, can conveniently be realized the emulation of the EMS of many microgrids.

Description of drawings

Fig. 1 is the many microgrid energies management system agent functional schematic that the present invention is based on multi-agent technology;

Fig. 2 is the little topological structure of electric of embodiment of the invention emulation experiment;

Fig. 3 is the many microgrid energies management system structural representation that the present invention is based on multi-agent technology;

Fig. 4 is typical local Agent structural representation of the embodiment of the invention;

Characteristic of solar cell curve under Fig. 5 a different temperatures;

Characteristic of solar cell curve under Fig. 5 b different light;

Fig. 6 is the characteristic curve of embodiment of the invention blower fan model;

Fig. 7 is the single output characteristic of fuel cell curve of the embodiment of the invention;

Fig. 8 is the single electric power storage battery of embodiment of the invention output characteristic curve;

Fig. 9 is embodiment of the invention primary frequency modulation frequency-power static characteristic;

Figure 10 is embodiment of the invention SCADAAgent structure;

Figure 11 is that the embodiment of the invention is coordinated the control agents structural representation;

Figure 12 is embodiment of the invention MRE assigning process schematic diagram;

Figure 13 is embodiment of the invention economic dispatch algorithm flow;

Figure 14 is embodiment of the invention static switch Agent structural representation;

Figure 15 is the little operation of power networks Agent of embodiment of the invention structural representation.

Embodiment

For by photovoltaic generation, wind power generation, fuel cell, the micro-grid system (as shown in Figure 2) that the energy-storage units such as little power supply electricity generation system such as miniature gas turbine, lead acid accumulator and ultracapacitor and AC load and DC load form illustrates the specific embodiment of the present invention.Consider that the equipment configuration that little electrical network uses is as shown in table 1:

Table 1, little electrical network configuration parameter

To micro-grid system shown in Figure 1, design multi-Agent EMS model and analogue system, as shown in Figure 3, multi-Agent EMS model comprises the local management layer, little administration of power networks layer and micro electric network coordination management level.The design of each energy layer is as follows:

1, the Agent of local management layer design

At local control and management layer the local management module corresponding with corresponding distributed power generation unit, energy-storage units and load unit is set respectively: photovoltaic generation administration module, wind power generation administration module, fuel cell management module and miniature gas turbine administration module etc.Typical local energy Management Agent concrete structure as shown in Figure 4, comprise model of element Agent, state Agent, local control agents and Communication Agent, wherein the state of state Agent Real Time Monitoring local device model passes to control agents with these information simultaneously; Control agents is then controlled the output of model of element in real time according to these information; Communication Agent is responsible for the electric data of little power-supply device operation is passed to the SCADA Agent of little administration of power networks layer, and meritorious, the idle set point of accepting little power supply with satisfy little power supply Agent cooperation and little administration of power networks layer Agent Optimized Operation in the micro-grid system requirement.Model of element Agent, state Agent, local control agents and Communication Agent implementation are as follows:

1) design of model of element Agent

Model of element Agent comprises corresponding unit energy computation model, the model that different generator units is corresponding different, when this enforcement, comprise photovoltaic array model Agent, wind power generation model Agent, fuel cell mode Agent and battery model Agent in the row, wherein:

A), photovoltaic array model Agent, it has comprised photovoltaic solar energy content of battery computation model, the output current I of photovoltaic array _PVShown in (1):

$I_{\mathrm{PV}}=I_{\mathrm{sc}}(1-C_1(e^{\frac{V-\mathrm{DV}}{C_2{V}_{\mathrm{oc}}}}-1))+\mathrm{DI}---\left(1\right)$

Wherein:

${\mathrm{<figure-callout\; id="1"\; label="C"\; filenames="HDA00002403336000041.png,HDA00002403336000051.png"\; state="\{\{state\}\}">C</figure-callout>}}_1=(1-I_m/I_{\mathrm{sc}})e^{\frac{V-\mathrm{DV}}{C_2{V}_{\mathrm{oc}}}}$

C ₂=(V _m/V _oc-1)/ln(1-I _m/I _sc)

DI=α·R/R _ref·DT+(R/R _ref-1)I _sc

DV＝-β·DT-R _S·DI

DT＝T _c-T _ref

In the formula:

R is solar radiation intensity [kW/m ²]; α is current temperature variation coefficient under the reference case [A/ ℃];

I _ScBe short circuit current [A]; V _m, I _mBe maximum power point voltage under the reference case and electric current [V, A];

V _OcBe open circuit voltage size [V]; Rs is photovoltaic cell series connection resistance value [Ω];

T _cFor the solar cell plate temperature [℃]; β is voltage temperature variation coefficient under the reference case [V/ ℃];

R _RefBe the solar radiation intensity reference value; T _RefFor solar cell plate temperature under the reference case [℃].

Under given reference parameter, the solar power generation model is carried out emulation, can obtain P-V curve and I-V curve under different temperatures and the illumination condition, shown in Fig. 5 a and Fig. 5 b;

B), wind power generation model Agent, it has comprised wind power generation energy computation model; When emulation, do not need the dynamic characteristic of knowing that blower fan is concrete, only need to know that the electric energy relation that current wind speed and blower fan can send gets final product, so can be according to wind speed and the wind driven generator output power curve of wind generator tower eminence, the method of recycling linear difference, can obtain the power output at any wind speed apparatus for lower wind generator, as shown in Figure 6.Different blower fan separately different wind speed-output power curve can obtain by wind-driven generator production firm;

C), fuel cell mode Agent, it has comprised single fuel cell chemical model and a plurality of fuel cell energy computation model:

(1) single fuel cell chemical model

The terminal voltage V of single fuel cell _FCRepresent with formula (2):

$V_{\mathrm{FC}}=E-(J+J_{\mathrm{in}})r-X\ln \left(\frac{J+J_{\mathrm{in}}}{J_0}\right)+Y\ln (1-\frac{J+J_{\mathrm{in}}}{J_L})---\left(2\right)$

Wherein battery current density J is:

E is theoretical open circuit voltage [V]; A is fuel cell effective area [cm ²];

J is battery current density [mA/cm ²]; J _InBe internal current density [mA/cm ²];

J ₀Be exchange current density [mA/cm ²]; J _LBe limiting current density [mA/cm ²];

X is the Tafel slope of curve [V]; Y is concentration polarization formula constant [V].

(2) total terminal voltage U of a plurality of series connection fuel cells _FcWith gross power P _FcCalculate by formula (3)

U _fc=n _cell·V _fc

P _fc＝i _fc·U _fc （3）

n _CellBe the series connection number; i _FcOutput current for a plurality of series connection fuel cells.

Under given reference parameter, the simulation result of single PEMFC fuel cell mode as shown in Figure 7;

D), batteries model Agent, it has comprised batteries energy computation model.Batteries energy computation model is made of two parts: one is that the capacity model of storage battery is used for the size that calculating accumulator discharges and recharges rear dump energy; Another one is the voltage model of storage battery, is used for the dc terminal output voltage of calculating accumulator under different capabilities:

(1) capacity model

According to Kinetic Battery Model model, storage battery total capacity Q (Ah) be divided into two parts: existing energy (Available Energy) and fetter energy (Bound Energy).Existing energy refers to that storage battery can be converted into the energy of electric energy immediately, waits between when not required; On the contrary, the constraint energy then needs the elapsed time could transform electric energy, that is to say that the time that storage battery once discharges is longer, and total electric weight q that can emit is just larger.

q＝q ₁+q ₂ （4）

Wherein, q ₁Existing energy, q ₂It is the constraint energy.

After the every one-phase of simulation process finished, two-part calculation of capacity formula was:

${\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA00002403336000041.png,HDA00002403336000051.png"\; state="\{\{state\}\}">q</figure-callout>}}_1={\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA00002403336000041.png,HDA00002403336000051.png"\; state="\{\{state\}\}">q</figure-callout>}}_{\mathrm{1,0}}{e}^{-\mathrm{k\&Delta;t}}+\frac{({\mathrm{<figure-callout\; id="0"\; label="q"\; filenames="HDA00002403336000032.png,HDA00002403336000041.png"\; state="\{\{state\}\}">q</figure-callout>}}_0\mathrm{kc}-1)(1-e^{-\mathrm{k\&Delta;t}})}{k}-\frac{\mathrm{Ic}(\mathrm{k\&Delta;t}-1+e^{-\mathrm{k\&Delta;t}})}{k}$ （5）

${\mathrm{<figure-callout\; id="2"\; label="q"\; filenames="HDA00002403336000041.png,HDA00002403336000051.png"\; state="\{\{state\}\}">q</figure-callout>}}_2={\mathrm{<figure-callout\; id="2"\; label="q"\; filenames="HDA00002403336000041.png,HDA00002403336000051.png"\; state="\{\{state\}\}">q</figure-callout>}}_{2,0}{e}^{-\mathrm{k\&Delta;t}}+q_0(1-c)(1-e^{-\mathrm{k\&Delta;t}})-\frac{I(1-c)(\mathrm{k\&Delta;t}-1+e^{-\mathrm{k\&Delta;t}})}{k}$

Storage battery is at the maximum discharge capacity q of T in the time under the discharging current I _Max(I) computing formula is:

$q_{\max }\left(I\right)=\frac{q_{\max }\mathrm{kcT}}{1-e^{-\mathrm{kT}}+c(\mathrm{kT}-1+e^{-\mathrm{kT}})}---\left(6\right)$

Storage battery charge state SOC computing formula is:

$\mathrm{SOC}=\frac{q_{\max }-q_{\mathrm{out}}}{q}---\left(7\right)$

Wherein:

q _out=∫I _batdt=q _max-q=q _max-(q ₁+q ₂) （8）

q ₀Be the initial storage battery total capacity of emulation [Ah]; q _1,0Be emulation active volume [Ah] immediately when initial; q _2,0Be emulation capacity to be transformed [Ah] when initial; K is capacity to be transformed and active volume transformation constant immediately; q _MaxBe the storage battery maximum discharge capacity; C is active volume ratio immediately; Δ t is simulation step length time span [hrs]; E is natural constant; I be battery charge (just) or discharging current (bearing) (A); T is total charge or discharge time.

(2) voltage model

Storage battery is slow at discharge starting stage voltage-drop, but voltage can descend rapidly when approaching discharging.By voltage model this flash-over characteristic, wherein E are described ₀, A, C and D get different value in charge model and discharging model.

$V_{\mathrm{BB}}={\mathrm{<figure-callout\; id="0"\; label="E"\; filenames="HDA00002403336000032.png,HDA00002403336000041.png"\; state="\{\{state\}\}">E</figure-callout>}}_0+\mathrm{AX}+\frac{\mathrm{CX}}{D-X}---\left(9\right)$

$X=q_{\mathrm{out}}\&CenterDot;\frac{q_{\max }}{q_{\max }\left(I\right)}---\left(10\right)$

E ₀Battery open-circuit voltage during for full state; A is that discharge starting stage (SOC is high) voltage is with the SOC rate of change; X is the rear size of battery capacity under normal conditions of discharge; C is that discharge terminal stage (SOC is low) voltage is with the SOC rate of change; D be one with the relevant parameter of current state-of-charge SOC.

Under given reference parameter, the simulation result of accumulator cell charging and discharging model as shown in Figure 8;

2) design of state Agent

State Agent is responsible for the state of Real Time Monitoring local device model, such as power output, output voltage and the output frequency etc. of little grid generation equipment.State Agent shows the mode of these information with form or figure on the one hand, on the other hand these information is passed to described control agents, and control agents is then controlled local device in real time according to these information;

3) design of local control agents

Local control agents implements to comprise the normal operation of generating, energy storage, load equipment and the control of the switch that some are important; Differentiate, analyze correctness and reasonability that the instruction of sending is controlled on the upper strata; To the monitoring state of equipment little grid nodes of living in, and take into account influence each other and the self-ability range of condition under carry out the control of regulating and controlling voltage and power stage;

During normal operation, local control agents adopts the active power droop control automatically to regulate little power output, stable orphan little mains frequency off the net and the exchange power of little electrical network common node off the net (PCC) also.When little electrical network during with lonely network operation, local control agents adopts droop control to come the blanketing frequency fluctuation, as shown in Figure 9; Under the initial launch state, the power-frequency characteristic of load is L ₁(f), with little electrical network in little power supply equivalent power-frequency droop characteristic K _F-PIntersect at a point, this moment, little mains frequency was f ₀, little output power of power supply is P, when load has increased Δ P _l, the power-frequency characteristic of load becomes L ₂, the new frequency stabilization point of so little electrical network is by L ₂With K _F-PIntersection point c determine that namely little mains frequency of this moment is f ₁, little output power of power supply is P ₁

In the control method of local control agents, add primary frequency function and be used for suppressing little mains frequency fluctuation, this carries out in real time, work as storage battery, fuel cell, gas turbine detects Frequency generated when fluctuation of little electrical network at its state Agent, and local control agents few energy output that can automatic torque-increasing adds deduct suppresses this frequency fluctuation.Represented respectively little mains frequency of a upper time period and this time period with Fre1 and Fre2, then Fre2-Fre1 has just represented the variation of little mains frequency:

Fre2-Fre1＜0 o'clock, the expression frequency descends, the generator unit that then has regulatory function increases meritorious output-k (Fre2-Fre1), k〉0.Like this, the Δ P of whole little electrical network → 0, thereby the fluctuation of the frequency that Δ f → 0 suppresses;

Fre2-Fre1〉0 o'clock, the expression frequency rises, the generator unit that then has regulatory function reduces meritorious output-k (Fre2-Fre1), k〉0.Like this, the Δ P of whole little electrical network → 0, thereby the fluctuation of the frequency that Δ f → 0 suppresses;

4) design of Communication Agent

The prescriptive procedure of reference standard agreement has designed necessary communications protocol of some Agent present stages.Present embodiment has defined a communication class (TProtocal), has comprised the structure that is used for transmitting different Content of communciations in the class.The structure of dissimilar imformosomes is as follows:

Used imformosome in table 2 communications protocol

Communications protocol is not only according to Agent collaboration method definition Agent communication layers elemental motion agreement, also formulate the competitive bidding content of transmitting under the different collaboration methods according to the content of little electrical network Agent competitive bidding, namely finish following two tasks: (1) transmits the electric data of little power-supply device operation; (2) satisfy little power supply Agent cooperation and little administration of power networks layer Agent Optimized Operation in the micro-grid system requirement.Like this, designed communications protocol just realizes between the local control, the transmission of the information between local control and the center-control realizes knowledge exchange and distributed problem solving, has also namely realized the function that Agent interactive function in the Agent system and interoperability need;

Communication between service end and client or the client, undertaken by using TServer Socket and TClient Socket control among the C++Builder:

A), server and client communication

Use a TServer Socket and client to use a TClient Socket in service end.The agreement of communication has comprised the structure that is used for transmitting different Content of communciations by a self-defining communication class (TProtocal) in the class;

B), client and client communication

The a pair of TServer Socket of interpolation and TClient Socket control carry out communication each other on each client.The agreement that adopts also is contained among the communication class (TProtocal);

C), the agreement of communications protocol

Communications protocol is based upon on the ICP/IP protocol, adopts the formula of replying.For any command set timer, overtimely think communication failure.The form of communications protocol is as follows:

The first field	The second field	The 3rd field
			Type of message	Message length	Message information content information body

Wherein, the structure of the message information content information body of the 3rd field is as shown in table 2.

2, little administration of power networks layer Agent design

Little administration of power networks layer is optimized management from little electrical network overall situation to microgrid energy.Little administration of power networks layer Agent comprises SCADA Agent in the present embodiment, coordinated scheduling Agent and economic dispatch Agent:

1) design of SCADA Agent

Such as Figure 10, SCADA Agent has comprised communication module, protocol analysis module and monitoring module, and wherein communication module is responsible for collecting the communication data that comprises each Agent operation information of these management level that local management layer Communication Agent sends; The protocol analysis module therefrom analyze local control agents in little electrical network and with state and the service data of the corresponding equipment of each local management module, and it is stored to database; Monitoring module is responsible for the state of Real Time Monitoring local device, such as power output, output voltage and the output frequency etc. of little grid generation equipment, will pass to SCADA Agent from the generation schedule of coordinating control agents or economic dispatch Agent acceptance simultaneously;

2) design of coordination control agents

Coordination control is divided into local primary frequency modulation and two steps of frequency modulation frequency modulation of little administration of power networks layer are carried out, primary frequency modulation is responsible for stoping frequency fluctuation, and frequency modulation frequency modulation is used for frequency is adjusted to 50Hz(because may not be 50Hz through the stationary value behind the primary frequency modulation).The local control agents of local management layer is responsible for primary frequency modulation, little administration of power networks layer is coordinated control agents and is responsible for frequency modulation frequency modulation, such as Figure 11, at first, in real time the little mains frequency and each generating set power that gather are monitored according to communication module, the automatic generation module calculates the difference of sending power and bearing power in little electrical network, again according to the relation of power fluctuation and frequency fluctuation, the frequency fluctuation in current little electrical network can be estimated, the size of the current frequency values of little electrical network can be obtained.Frequency fluctuation is shown with following formula table:

$\mathrm{\&Delta;P}=\mathrm{\&Sigma;}{P}_i^{\mathrm{gen}}-\mathrm{\&Sigma;}{P}_j^{\mathrm{load}}---\left(11\right)$

Δ P is the power fluctuation value in the formula,

The power that i platform generating equipment is sent, The power of j platform load.

$\mathrm{\&Delta;f}=\frac{\mathrm{\&Delta;P}}{k}---\left(12\right)$

K is power in the system-frequency relation constant.

In central platform, at first defining current little grid generation amount is MRE (Microgrid Regulation Error) with reaching the difference of controlling the energy output that requires:

MRE=ΔP ^pcc+k·Δf （13）

Δ P wherein ^PccFor in the trend of the common node that is connected with electrical network and the deviation of planned value.Δ f is the deviation of little mains frequency and 50Hz.

Automatic generation module rated output vacancy value MRE also sends it to vacancy planned assignment module.In little electrical network cooperation control procedure, the automatic generation control frequency modulation frequency modulation function of little electrical network need to be kept the MRE value and fluctuate in a less scope, when exceeding this scope, automatic generation control can be distributed to little interior frequency modulation unit with crossing vacancy planned assignment module and communication module with MRE, thereby makes little mains frequency and the requirement of exchange power load.As shown in figure 12.

Coordinate contract net of control agents initiation in per 15 minutes original generation schedule is adjusted, concrete steps are:

A), mounting phase

When MRE surpasses little electrical network preset value, coordinate control agents and initiate contract net;

B), the competitive bidding stage

SCADA Agent will be at first has the ability to participate in this stratum Agent of frequency modulation frequency modulation in the reporting system, Agent competitive bidding information that will participate in frequency modulation frequency modulation control in these this stratum is submitted to the coordination control agents afterwards, wherein, the competitive bidding that can dispatch generating set thes contents are as follows: (machine set type, can dispatch the power bound, price curve is estimated the factor);

C), competitive bidding the processing stage

Coordinating control agents distributes task according to bid information, power shortage and certain rule: when little grid power vacancy value is on the occasion of (load is greater than generating merit power), and the target of coordinating control agents is when recovering power shortage as early as possible, coordinate control agents and will at first select in the competitive bidding the fastest little power supply Agent start-up time, and make it adjust to the power stage maximum, if still can't satisfy power shortage this moment, coordinate control agents remaining task is distributed to the start-up time second of little power supply Agent fast, by that analogy.When little grid power vacancy value when negative, coordinate control agents and call the power stage that energy storage Agent in little electrical network absorbs unnecessary electric energy or reduces some unit;

At last, coordinating control agents notifies all competitive biddings little power supply Agent the task allocation result of contract net.Little power supply Agent revises corresponding generation schedule table immediately after receiving the competitive bidding result;

3) design of economic dispatch Agent

Three frequency modulation control refer to carry and formulate following 24 hours generation schedule of little electrical network according to load and power prediction information the previous day in little electrical network.In little electrical network, economic dispatch Agent adds up in little electrical network the need for electricity of all load Agent, represents that all consumers send the electricity consumption request in little electrical network.When economic dispatch Agent initiates to submit a tender to all this stratum Agent, all little power supply Agent will participate in the market, propose electric energy and the requirement that oneself can provide, to increase the income of oneself.Dissimilar Agent competitive bidding protocol contents are as follows:

A) non-scheduling regenerative resource: (machine set type, prediction generating curve is estimated the factor)

B) can dispatch generating set: (price curve is estimated the factor for machine set type, power bound)

C) batteries: (the machine set type, total capacity, current SOC, the power bound is estimated the factor)

D) load: (machine set type, the prediction load curve is estimated the factor)

Economic dispatch Agent then application market mechanism processes to realize economic dispatch control to the competitive bidding of this stratum Agent in little electrical network.In the contract net of three frequency modulation of little electrical network is realized, each the generating Agent that participates in competitive bidding has three factors: reliability factor a, Price factor b and environmental impact c estimate, and economic dispatch Agent at first considers three factors by weight:

y=αa+βb+γc；(α+β+γ=1) （14）

Then according to the value of y corresponding Agent is selected.Can find out that this moment, can change the operation strategy of little electrical network: when α was larger, little electrical network tended to select the Agent that generates electricity comparatively reliably in little electrical network, and the reliability of whole so little electrical network also is guaranteed by the adjustment of weight; When γ is larger in the three, in little electrical network environmental impact less Agent can be paid the utmost attention to;

The overall merit factor of last each this stratum Agent according to obtaining is selected and following 24 hours generation schedule of the little electrical network of formulation place detailed algorithm flow process such as Figure 13 to each Agent.

4) design of tidal current analysis Agent

Data that tidal current analysis Agent collects according to SCADAAgent and to the analysis of network topology, trend in little electrical network is carried out computational analysis, and the trend in little electrical network is optimized, to reduce the loss on the circuit, in the stability that guarantees whole little electrical network, make its economy reach optimum;

5) design of energy predicting Agent

Energy predicting Agent carries out the ultra-short term prediction of energy according to historical data and the weather forecasting data of generating to the power station of renewable energy power generation; And from real-time data base and historical data base, analyze data, and utilize the intensified learning algorithm, constantly the predicted value of oneself is optimized;

6) historical failure is analyzed the design of Agent

Historical failure is analyzed Agent the fault that occurs in whole little operation of power networks is analyzed, and avoids next time controller to take again identical order initiating failure;

3, the design of micro electric network coordination management level

The micro electric network coordination management level comprise that little electrical network participates in the selection of large grid power market and little operation of power networks pattern.Originally be that the micro electric network coordination management level comprise static switch Agent among the embodiment:

The static switch that the little electrical network of the special control of static switch Agent is connected with the upper strata electrical network.The state of static switch Agent Real-Time Monitoring public electric wire net side when little electrical network detects large electrical network and breaks down, disconnects static switch immediately, and sends emergency alert signals for the Agent of little administration of power networks layer, and little electrical network switches to the islet operation pattern; After fault recovery, little electrical network again with large electrical network parallel running;

Static switch Agent structural representation as shown in figure 14.Wherein, the state information of the large electrical network of power network monitoring module Real Time Monitoring, block of state is the state information of Real Time Monitoring static switch then, each Agent that the static switch state information that communication module is responsible for being provided by block of state sends to little administration of power networks layer accepts the instruction that it sends simultaneously, the static switch that control module provides according to block of state and power network monitoring module and the information of public electric wire net are sent the break-make of control signal control static switch.

Each little electrical network has expense and the profit target of oneself under open distribution electricity consumption Power Market, little operation of power networks Aget represents the electricity market in little electrical network participation regional power grid, in electricity market, play the part of the electric power buyer, the electric power seller, the various roles such as electric power auctioner and bidder, and the buyer and the seller's role may transform when electricity needs changes, by determining the exchange power of little electrical network and large electrical network, and response or initiate to cooperate with other little electrical networks, jointly finish the task in the regional power grid, electrical network is played the regulating action of peak load shifting, and make quick response user for the change of power business demand, diversity with power mode is provided, is beneficial to the user and obtains most economical power supply service;

Little operation of power networks Agent structural representation as shown in figure 15.Wherein, block of state is the state information of other little electrical networks of Real Time Monitoring then, each Agent that each little electric network state information that communication module is responsible for being provided by block of state sends to little administration of power networks layer accepts the instruction that it sends simultaneously, each little electrical network that control module provides according to block of state and communication module and the information of public electric wire net are sent the exchange power that control signal is controlled little electrical network and large electrical network.

4, simulation process

Act on behalf of energy management model according to above-mentioned little electrical network more, can realize little electrical network and comprise energy control and management simulation run platform under the different target condition of distribution system of little electrical network.Little electrical network brings into operation under the pattern of being incorporated into the power networks, and from the electrical network input power, frequency is the stable 50Hz that remains on always.After discovery was broken down in public electric wire net, little electrical network and grid disconnection also entered independent operation mode.When little electrical network detect frequency descend can initiatively excise a part in little electrical network when larger normal load with stabilized frequency, and the power output output that will increase sharply after detecting frequency and falling of the batteries in little electrical network is used for stablizing little mains frequency.But because battery group capacity is limited, over time, coordination control agents in little electrical network will order other generators in little electrical network (for example miniature gas turbine) to start, and correspondingly recover common load cut in little electrical network this moment, and little electrical network enters independent operation mode.

Per half a minute of primary frequency modulation on this stratum equipment carries out once, and the frequency modulation frequency modulation system of little administration of power networks layer carried out once every 15 minutes.When 8:00, give little electrical network a distribution network failure signal;

After little electrical network behind the 8:00 entered lonely network operation pattern, frequency was fallen to some extent.After this illustrated lonely network operation, before each generating equipment power generation dispatching plan was also in time adjusted, the original plan of each hour beginning each generating equipment of period when being incorporated into the power networks caused active power not enough, so that little mains frequency descends.But because the primary frequency function of batteries Agent client terminal local control has in time increased power stage, stoped little electrical network frequency continue fall.But because that frequency still fluctuates is larger, central authorities coordinate control agents order normal load 2 and constantly disconnect with little electrical network with 10:00 and being connected, and frequency has been recovered to stablize after an of short duration fluctuation;

From the 12:00 point, coordinating control agents order gas turbine Agent has increased the 6kw power stage, has remedied electrical network and has disconnected the input power that loses.Simultaneously order has recovered the power supply of normal load 2, and makes generating and load balance in little electrical network.The situation of specifically exerting oneself of each equipment is as shown in table 3:

Table 3 micro-grid system distributed power source generated output and bearing power table (unit: kW)

When the different factor that stresses, the share that each equipment that advantage is different on each factor obtains in generation schedule is different.For example in the larger situation of Price factor weight, the relative FC of MT that has more advantage on the price just obtains more generation schedule.

Claims (3)

1. based on many microgrid energies management system emulation mode of MAS, it is characterized in that:

Many microgrid energies management system is divided into local management layer, three different levels of little administration of power networks layer and micro electric network coordination management level; Described local management layer makes it by existing plan normal operation for little power supply of managing little electrical network, satisfies in real time the equilibrium of supply and demand, and sustain pulse frequency is stable; Described little administration of power networks layer is by the coordination control of little power supply, reduce little line voltage and frequency departure amplitude during lonely network operation, reduce the exchange power of public electric wire net switching node and the deviation of planned value when being incorporated into the power networks, and the economic dispatch in the realization microgrid, improve regenerative resource in little electrical network proportion of utilization and take full advantage of the heat energy that produces in the generating; Described micro electric network coordination management level are by whole little power grid control, finish cooperation target between a plurality of little electrical networks or the control target of large electrical network, and switch little operation of power networks when little electric network fault, coordinate that each little power supply makes little electrical network transition steady in little electrical network;

The various energy management functionality that possess on described local management layer, little administration of power networks layer and three different levels of micro electric network coordination management level adopt dissimilar Agent to set up many microgrid energies management system simulation model, and role and the functional definition of the Agent on described local management layer, little administration of power networks layer and the micro electric network coordination management level are as follows:

1) local management layer, it is provided with model of element Agent, state Agent, local control agents and Communication Agent:

A), described model of element Agent, it is including but not limited to the energy computation model of following little power supply: the photovoltaic plant power output is calculated model, wind power generation is that the unit power output is calculated model, the fuel cell output power computation model, storage battery power output and state-of-charge computation model, the gas turbine power output is calculated model, bearing power computation model; Described energy computation model provides the Digital Simulation calculated data of little electrical network dynamic operation for the microgrid energy management system;

B), described state Agent, the state of its Real Time Monitoring local device, power output, output voltage and the output frequency that comprises little grid generation equipment is connected distributed power generation unit, energy-storage units or load unit and connected the information of electric current, voltage and the frequency of little electrical network bus, described state Agent shows these information on the one hand, on the other hand these information is passed to described local control agents;

C), described local control agents, the state of the local device that it provides according to decision instruction and the described state Agent of little administration of power networks layer, according to designed little power system controller algorithm, realization manages meritorious, the reactive power of distributed power generation unit, energy-storage units, load is realized the corresponding demand side management, and when circuit breaks down, local device is protected action; Described local device is little power supply, contactor, circuit breaker and the load cell that is connected to the different nodes of little electrical network electrical network; Described little power supply comprises photovoltaic generating system, wind generator system, fuel cell, miniature gas turbine and storage battery;

D), described Communication Agent, its be responsible for and the local management layer between each local Agent and the information exchange between the Agent of each local Agent and little administration of power networks layer;

2) little administration of power networks layer, it is provided with little electric network data and gathers SCADA Agent, coordination control agents, economic optimization scheduling Agent, tidal current analysis Agent, energy predicting Agent and historical failure analysis Agent:

A), described SCADA Agent, it collects state and the service data of equipment in little electrical network by remote data collecting unit (RTU), simultaneously issue setup control order from little electrical network central controller to low layer control unit orientation, the real-time running state of the equipment in little electrical network is monitored;

B), described coordination control agents, it is according to the generation schedule of local each equipment of little electrical network real-time running state data modification of SCADA Agent acquisition, but by power and the voltage-operated reference point of setting controlling equipment in little electrical network, make little mains frequency stable, power-balance is to reach the purpose of automatic generation coordination control in little electrical network, and realize that little electrical network overall efficiency is maximum, little administration of power networks target that little grid net loss is minimum;

C), described economic dispatch Agent, it is according to optimization and the economy principle of trend, bid information to generating equipment in the prediction of the ultra-short term of regenerative resource and the little electrical network, use contract net coordination, Market Bidding Mechanism and particle cluster algorithm on the multiple-factor evaluation method basis, formulate following 24 hours the harmonious economy operation plan of each generator unit in little electrical network, economy optimization is carried out in the operation of little electrical network;

D), described tidal current analysis Agent, data that it is collected according to SCADA Agent and to the analysis of network topology, trend in little electrical network is carried out computational analysis, and the trend in little electrical network is optimized, to reduce the loss on the circuit, in the stability that guarantees whole little electrical network, make its economy reach optimum;

E), described energy predicting Agent, its historical data and weather forecasting data according to generating are carried out ultra-short term prediction of energy to the power station of renewable energy power generation; And from real-time data base and historical data base, analyze data, and utilize the intensified learning algorithm, constantly the predicted value of oneself is optimized;

F), described historical failure analyzes Agent, it is analyzed the fault that occurs in whole little operation of power networks, avoids next time controller to take again identical order initiating failure;

3) micro electric network coordination management level, it is provided with static switch Agent and little operation of power networks Agent:

A), static switch Agent, it monitors the state of little electrical network and regional power grid contact interface, when regional power grid breaks down or recovers fault, switches the running status of little electrical network;

B), little operation of power networks Agent, its representative system firing floor coordinate between little electrical network or little electrical network and regional power grid between cooperate, with little electrical network as a unified individual electricity market scheduling of participating in regional power grid, and according to the overall strategy of the size of self generating ability and Regional Electric Market price decision next stage.

2. the many microgrid energies management system emulation mode based on MAS according to claim 1 is characterized in that:

The upper different interior Agent of key-course of described local management layer, little administration of power networks layer and coordinated management layer adopts client-server architecture integrated, forms the many microgrid energies management system emulation platform based on multi-agent technology; In described many microgrid energies management system emulation platform based on multi-agent technology, comprise a server end and a plurality of client; The Agent that little administration of power networks layer and micro electric network coordination management level comprise adopts the method for function and assembly to realize at server end, and each Agent provides service and by coordinating control little electrical network managed and moves to the Agent of other little electrical network local management layers; At described server end, definition management service Agent and directory service Agent, wherein: when the user generates, deletes, removes or move into an Agent at platform, described management service Agent records, and realization is to the registration management of Agent; Described directory service Agent records the COS of each Agent, finishes complicated microgrid energy managerial role for the common cooperation of the Agent with different COS;

Described many microgrid energies management system based on multi-agent technology comprises the Agent client of multiple different type, and the Agent client of described different type realizes the energy management of the local management layer in little electrical network; An Agent client is used for realizing the control of concrete local device, according to the difference of client institute management equipment, client is divided into generating Agent, loaded Ag ent and energy storage Agent; There are a plurality of Agent to cooperate to manage this equipment on the Agent client, wherein the most basic Agent comprises: control agents, state Agent and Communication Agent, described Communication Agent represent this client and cooperate with little administration of power networks layer or other clients.

3. the many microgrid energies management system emulation mode based on MAS according to claim 1 is characterized in that:

Described based on communication need between the client and server in many microgrid energies management system emulation platform of multi-agent technology, required communications protocol is set, and server end utilizes described communications protocol to monitor the request of client: the Agent that server end is in little administration of power networks layer utilizes described communications protocol to collect information or the issue an order of client; Thereby the little operation of power networks Agent that is in the micro electric network coordination management level connects long-range electricity market server by described communications protocol to be identified oneself with among the electricity market;

Described communications protocol is as the basis take ICP/IP protocol, the intrinsic level that shows in information exchanging process according to Agent is divided into transport layer, communication layers and alternation of bed, and lower floor provides service for the upper strata, described transport layer is in the bottom, be the computer protocol layer, by described transport layer the message of protocol layer passed on by computer network protocol; Described communication layers is in the second layer, and namely protocol layer defines information type sign, message length and the device status data structure corresponding with the information type sign in described protocol layer; Described alternation of bed is in the 3rd layer, it is the interaction protocol layer, described interaction protocol layer coordinates, consults by a series of realizations that protocol layer is given expression to or the language of cooperation makes up, finish under the guidance of the upper strata of interaction protocol layer strategy between each Agent cooperation and agreement.

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