NL2024943B1 - A Distributed Cooperative Control Method for Optimizing a DC Power Grid - Google Patents

A Distributed Cooperative Control Method for Optimizing a DC Power Grid Download PDF

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NL2024943B1
NL2024943B1 NL2024943A NL2024943A NL2024943B1 NL 2024943 B1 NL2024943 B1 NL 2024943B1 NL 2024943 A NL2024943 A NL 2024943A NL 2024943 A NL2024943 A NL 2024943A NL 2024943 B1 NL2024943 B1 NL 2024943B1
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power
node
power supply
load
voltage
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Liu Zhangjie
Liu Ruisong
Feng Wendong
Su Mei
Han Hua
Wang Hui
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Univ Central South
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J1/00—Circuit arrangements for DC mains or DC distribution networks
    • H02J1/10—Parallel operation of DC sources
    • H02J1/106—Parallel operation of DC sources for load balancing, symmetrisation, or sharing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/36—Circuit design at the analogue level
    • G06F30/367—Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/36—Circuit design at the analogue level
    • G06F30/373—Design optimisation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J1/00—Circuit arrangements for DC mains or DC distribution networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/06—Power analysis or power optimisation
    • H02J2101/00—
    • H02J2105/10—

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  • Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Power Engineering (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The present invention discloses a distributed cooperating control method for optimizing a DC power grid, in particular a distributed algorithm based on coordination descent, which can perform multiple—objective optimization, i.e., energy loss reduction and voltage adjustment. The method includes establishing a multi—objective optimization mathematical model for the DC power grid to prove that the multi—objective optimization problem is a convex optimization problem, and a distributed algorithm based on coordinate descent is designed to solve the problem. According to the method, it is unnecessary to use the line impedance during finding the optimization results, so that deviation to the optimization results caused by fluctuation of network parameters can be avoided, and the optimal economical operation point of the system can be automatically found.

Description

Ref.: P126385NL00 A Distributed Cooperative Control Method for Optimizing a DC Power Grid
Technical Field The present invention relates to the technical field of DC power system, in particular to power flow optimization and voltage adjustment of a grand power grid, and more particularly, to a distributed cooperative control method for optimizing a DC power grid.
Technical Background With the rapid development of power electronics technology, the DC power system including power electronic equipment acting as a core role has regained people's attention.
Compared with the AC power grid, the DC power grid has the following advantages.
In the aspect of distributed power generation, there is no need for redundant power conversion, thus enjoying less energy loss and simple control.
In the aspect of power transmission, there is no constraint for power angle stability, thus significantly reducing both of line cost and line loss.
In the aspect of power distribution, there is no need for phase frequency control, thus improving the ability of accommodating distributed sources and effectively coordinating the conflicts between renewable energy sources and the grand power grid.
In the aspect of power consumption, it is flexible in control, rapid in response, and able to supply high quality of energy and meet increasingly diverse load requirements.
Therefore, the DC power system has been more and more widely used.
Power flow optimization and voltage regulation are hot issues in power system research.
Specifically, due to the existence of the transmission line impedance, the 21 power loss will seriously affect the economical operation of the system. At the same time, the voltage deterioration caused by the line impedance may cause abnormal operation of the load, thus threatening safety and applicability of the equipment. In order to solve these problems, many studies have been conducted.
Most existing control methods adopt a centralized manner, which relies on computers of high band width communication and high performance. This will lead to high communication cost, single point of failure, and further limit the plug-and-play function of the system. In contrast, the distributed algorithm can achieve global information transmission through low band width communication, thus reducing communication cost. However, the distributed control method currently used needs to obtain information such as line impedance, which is difficult to measure. In addition, the impedance value is easily changed due to the operation state and weather conditions, so that the system operation will operate under a condition which is deviated from the optimal point.
Summary of the Invention In order to solve the above-mentioned problem, the present invention aims to provide a distributed cooperative control method for optimizing a DC power grid, so as to solve the problems of network loss and voltage adjustment In the DC power grid. According to the present method, each time the voltage of only one power supply node is adjusted, thus avoiding failure caused by regulating multiple power supplies at the same time. Moreover, computation of the present method is less complex, thus reducing the requirement on computer performance.
The present invention proposes a distributed cooperative control method for optimizing a DC power grid. Specifically, this method is a distributed cooperative control method for network loss reduction and voltage adjustment. The control method includes: a) enabling a topology of a mesh-like DC power system, which contains #2 power 222 supply nodes and m load nodes, to be equivalent to a graph based on graph theory, to obtain a corresponding admittance matrix of a power transmission network as follows: Y= Yo , Ys Yi and obtain, according Ohm’s Law, current {/, LY flowing to the power transmission network from each node, wherein gis output current from a power supply node, and I; is current flowing to the power transmission network from a load node; b) setting a performance index J; on line loss optimization and a performance index J, on voltage adjustment, and establishing a multiple-objective optimal problem, wherein J=ULI +UTT,, =U, UL; J=atJ + BJ, wherein a+B=1, 020, B>0, in which Us is output voltage from the power supply node, U, is voltage flowing to the power transmission network from a load node, and Uy is rated load voltage; and c) solving said optimal problem through an improved distributed algorithm based on coordination descent, wherein the distributed algorithm includes steps of: step 1: setting current step size d=do, output voltage U =U\, number of iterations i=0, and power supply node number p=1, wherein dois an initial step size, U{ is an mitial voltage value, and adjusting a power of a first power supply; step 2: collecting load power, power node power, and load voltage for feedback control, but not measuring a line impedance that is difficult to determine, and setting izi+l; step 3: calculating aJ;+ 27, which is recorded as P „n(i-1); step 4: adding a voltage step disturbance into a current power supply node voltage Vis Le, Vy Vp! +d, and keeping other node voltages unchanged; step 5: recalculating a/,+ 87, which is recorded as P ‚4 (7); step 6: comparing P (i) with P „n(i-1); step 7: changing, when |P _,,(i)-P ,5(i-1)i<e, the initial value of the current power supply, i=0, d=d;, Vip =V selecting p+1,and going to step 2; step 8: otherwise, determining whether P ,;,(i)-P ,,(i-1) is true; if yes, setting d =
1.1d and then going to step 2; if not, performing step 9; and step 9: setting d=-dh, and going to step 2.
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In an embodiment, the performance index J is specifically indicated as the follows: Jy =Ug Fg +Y A+ AY + AY AU wherein A = —(¥,; +[¥,,,, 1)" Yys, in which Yioag is admittance of the load, and Yss, Ys, Yrs and Yr, are elements in the admittance matrix Y, respectively. In an embodiment, the performance index Js is specifically indicated as the follows: J, =U{ATAU =2U {AU +U LU, In an embodiment, since the global information is necessary in the iteration procedure, the distributed control algorithm is used instead of centralized communication. According to follow-lead algorithm of the distributed control algorithm, the power supply nodes are divided as master nodes and slave nodes, each master nodes collecting information of adjacent loads and then transmitting it to slave nodes, k , Vr => a Vi Vi), Vie N-9Q 1=1 k PY => a,(P)~P), VieN-Q
IE k PY => a;(P{)-P{)), Vie N-Q I=1 wherein: Q is a collection of master nodes; N is a total number of power supply nodes; Vu Pri, and Pg; are load node voltage information, load node power information, and power supply node power information received from a node, respectively; Vr, Pr, and Py are load node voltage information, load node power information, and power supply node power information of a neighbor node, respectively: and a; is a weighting coefficient of a communication network, in which a;=1 when an i" power supply is in data communication with a i power supply, otherwise ag;=0. In this manner, global information sharing can be achieved. The distributed cooperating control method according to the present invention 4 proposes a distributed algorithm based on coordination descent, which can perform multiple-objective optimization, 1.e., energy loss reduction and voltage adjustment.
In particular, the distributed algorithm includes establishing a multi-objective optimization mathematical model for the DC power grid to prove that the multi-objective optimization problem is a convex optimization problem.
Therefore, based on the features of the convex optimization model, a distributed algorithm based on coordinate descent is designed to solve the problem.
According to the present method, it is unnecessary to use the line impedance during finding the optimization results, so that deviation to the optimization results caused by fluctuation of network parameters can be avoided, and the optimal economical operation point of the system can be automatically found.
According to the present method, in practical applications, each time the voltage of only one single power supply node is adjusted, thus achieving the cooperating control of the distributed control.
This can avoid failures caused by simultaneous adjustment of multiple power supplies, reduce the complex of computation and requirements on computer performance.
Brief Description of the Drawings Fig. 1 is an equivalent topology diagram of a DC power grid according to the present invention; Fig. 2 is a flow chart of iterative procedure of a distributed algorithm according to the present invention; Fig. 3 shows a simulation diagram of Example 1; Fig. 4 shows a simulation diagram of Example 2; Fig. 5 shows a simulation diagram of Example 3; and
Fig. 6 shows a simulation diagram of Example 4. Detailed Description of the Invention B.
The present invention will be described in further detail with reference to preferred embodiments in combination with the accompanying drawings. The following embodiments are merely used for illustration, but not for limiting the scope of the present invention.
To maintain the system operating in the optimal point, the present invention proposes a multi-objective optimal solution with respect to the line loss and voltage adjustment, and thus provides a distributed algorithm based on coordinate descent. The distributed cooperative control method for the DC power grid optimization according to the present invention includes the following steps.
Considering a mesh-like DC power distribution system containing " power supply nodes (e.g., transformers) and m load nodes, the topology of the DC distribution system can be equivalent to a graph by using graph theory. Therefore, a corresponding admittance matrix of a power transmission network is obtained as follows: y= 6 Yo | Ys Vu) According to Ohm’s law, current [/s, Li" flowing to the transmission network from each node is obtained, wherein /s is output current of a power supply node, and I; is current flowing to the transmission network from a load node. The line loss can be calculated through the following equation: L=USIg+UL, (1) The index on the load voltage is defined as follows: 4 =| Uyl 2) The multi-objective optimal problem is defined as follows: J=oJ;+ BJ 3) The relation between the voltage and the current of a node is as follows: I= YU 4) .6-
This can be represented in form of a matrix as follow: lH Ie 5) 1 Yio Yu |V, ’ The relation between the power and the voltage is represented as follows: Po =IUs WgsUs HU Ws, U, > p =U Wiss HU IY, U, © In resistance load characteristic, assuming the load impedance Raa to be 7 Ry pi [RR R | , the following can be obtained according to Ohm’s law: Fy = AU MY a U, (7)
wherein, Yad 1s admittance of the load, Ys, Ys, Yis and Yi; are elements in the admittance matrix Y respectively, and Uy is rated load voltage {which is set as 300V in the following). Considering equations (6) and (7), the load voltage can be represented as follows:
U =O roa D7 YoU (8)
Defining A = —(Y,; +{Y ond Fis, and combining equations (6) and (8) into equation (1), the following equation can be obtained: J =Ug (Yo +Y A+ AY, + ATY,, AU (9)
Combining equation (8) into equation (2), the following equation can be obtained: J, =U{A" AUG =U AU +ULU, (10) Combining equation (9) and (10) into equation (3), the following equation can be obtained:
J=UlaYy +aYgA+ad’Y, +aA’Y, A (11 + BAT A -2BULAU + BULU Based on non-negative of the performance index and the characteristic of _7-
quadratic, it can be readily concluded that J is a convex problem.
Therefore, the multi-objective optimization problem to be solved can be described as follows: s min J (Uy) (12) Js The global optimal solution for equation (12) is as follows: Us = Bos +00 A+GA'Y, +AAY, A+ BA" A) AU, (13) In order to solve equation (12), the following distributed algorithm based on coordination descent is presented, mainly including two parts.
A. the distributed algorithm based on improved coordination descent The optimization method based on coordinate descent is a cost-effective method.
In each iteration, the voltages of other power supplies remain unchanged, thus avoiding the risk of grid voltage collapse caused by simultaneous regulation of multiple power supplies.
Therefore, the multiple-variable optimization problem is transformed into a one-variable optimization problem.
The specific procedure thereof is shown in Fig. 2. specifically, the distributed algorithm employed in Fig. 2 includes the following steps: step 1: setting current step size d=do, output voltage U,=U{, number of iterations i=0, and power supply node number p=l, wherein dp is an initial step size, US is an initial voltage value, and adjusting a power of a first power supply: step 2: collecting load power, power node power, and load voltage for feedback control, but not measuring a line impedance, and setting i=i+1; step 3: calculating aJ;+ 8}, which is recorded as P „n(i-1); step 4: adding a voltage step disturbance into a current power supply node voltage Vis Le, Vy Vp! +d, and keeping other node voltages unchanged; step 5: recalculating a+ BJ», which is recorded as P «4 (i); -8-
step 6: comparing P (i) with P „a(i-1); step 7: changing, when |P ,,(i)-P op{i-l)l<e, the initial value of the current power supply, i=0, d=d, Vi '=V, selecting p+1,and going to step 2; step 8: otherwise, determining whether P p()-P_op(i-1) is true; if yes, setting d =
1.14 and then going to step 2; if not, performing step 9; and step 9: setting d=-dp, and going to step 2. In the entire optimization procedure, it is unnecessary to know the information about the line impedance. No matter how the line impedance or the load changes, it can be ensured that the power system can always operate under the optimal operation point. B. the distributed algorithm on global information estimation In order to better implement the algorithm based on coordinate descent, each power agent needs to collect the voltage and power of the load node, and the output power of other power nodes. Since the information is obtained by a local sensor installed at each node, the easiest way for information transmission is to broadcast it to all other agents. However, this will lead to an increase in communication cost, and is undesirable for the scalability of a large-scale distributed system. Therefore, in the present invention a distributed algorithm is adopted for global information transmission. In fact, the information about the voltage and power of each load node only needs to be transmitted to at least one agent adjacent to said power node. The agent is called master agent, and a collection of all master agents is expressed as Q. In order to broadcast this information to all other agents, the master agent repairs the information, and the slave agent should update its value as: k Vi =D a; Vi) =v). Vie N-Q BY => a; (Pp -Pj), Vie N-Q | = pl = >a, Py ~ Py, Vie N=O I=1 wherein: N is a total number of power supply nodes; Vii, Pr, and Pg are voltage information of load node, power information of load node, and power information of
9.
the power supply node received from a node, respectively; Vy, Pp, and Py are voltage information of the load node, power information of load node, and power information of power supply node of a neighbor node, respectively; and a; is a weighting coefficient of a communication network, in which a;=1 when an i™ power supply is in data communication with a /* power supply, otherwise a;=0. In this way, sharing global information is achieved.
Finally, in order to illustrate the practical effect of the above control method, the present invention provides a DC power distribution system, which comprises 6 power supply nodes and 14 load nodes, as shown in Fig. 1. In this figure, black nodes represent power supply nodes, dark gray nodes represent load nodes, light gray nodes represent intelligent nodes, and numbers represent line labels. The load impedance values are: R,, =[R,..R,..R;,1" ={10, 15, 20, 20, 20, 10, 30, 40, 10, 13, 13, 20, 20]Q, and the line impedance values are: R,,, = [Ryzer Reis Rina 1 =10.3, 0.1, 0.2, 0.1, 0.3,
0.3,0.1,0.2,0.2,03,04,0.3,05,0.3,04, 0.2, 04, 0.1, 0.1]Q. The rated load voltage is 300V, and the initial value of the power supply voltage is 302V.
Example 1: the weighing coefficient a=0.1 and B=0.9, and the initial optimized step size dy=0.1V.
Example 2: the weighing coefficient a=0.1 and B=0.9, and the impedance values of load nodes 2, 4, 9 and 13 are changed to 7.5Q, 10Q, 20Q and 100 from 159, 209, 40Q and 200, respectively, after t=100s.
Example 3: the weighing coefficient a=0.15 and B=0.85, and the line impedances Riines, Rîines, Riner7 are changed to 0.150, 0.20, and 0.29 from 0.30, 0.39, and 0,490, respectively, after t=70s.
Example 4: the weighing coefficient a=0.15 and B=0.85. The power supply node 7 is operated independent of the system at the beginning. After t=80s, the power supply node 7 is connected to the load node 11, and the connecting line impedance is
0.3Q. After t=160s, the load node is separated from the system and operated independently.
-10-
Figs. 3-6 show the simulation results of Example 1 to Example 4, which respectively include the simulation curves of target value, power supply voltage and load voltage.
The result of Example 1 is shown in Fig. 3. The target value curve a-1 of Fig. 3 indicates that the control method can converge to the optimal target value. The power supply voltage curve a-2 of Fig. 3 indicates that the power nodes change their output voltages in turn, in order to reduce the target value. The load voltage curve a-3 of Fig. 3 indicates that all voltages at the load nodes are close to 300V. Since the remote load nodes are not directly connected to the power supply nodes, there is a voltage drop on the transmission line between the load nodes, so that it is impossible for all load nodes to reach 300V.
Similarly, the result of Example 2 is shown in Fig. 4. After t=100s, when the load changes, the proposed control method can automatically detect the change of the load, so as to find the optimal solution of the system under the new state.
The result of Example 3 is shown in Fig. 5. Without measuring the line impedance, the system can automatically operate under a new optimal point according to the proposed control method.
The result of Example 4 is shown in Figure 6. When a new power supply node is connected to the system, the realization of plug-and-play capability is especially important in a large DC power system. In this case, the present invention verifies the plug-and-play performance of the method. The power node 7 operates independently of other nodes before t=80s. When t=80s, the node 7 is connected to the load node 11, with a line impedance of 0.3. At the same time, the node 7 is in data communication with the power supply nodes 5 and 6. When t=160s, the load node 11 is disconnected from the entire system. As can be seen from Fig. 1, during the insertion and removal of the power supply node 7 and of the load node 11, the voltage of the power supply node is continuously adjusted, indicating that the control method has good plug-and-play performance.
It should be pointed out that the above-mentioned multi-objective optimization -11-
problem of network loss reduction and voltage adjustment and the distributed algorithm based on coordinate descent include establishing a multi-objective optimization mathematical model of a DC power grid to prove that the multi-objective optimization problem is a convex optimization problem. On this basis, a distributed algorithm based on coordinate descent is designed to solve the problem. The control method does not need to know the information about the line impedance during the optimization process, so that the deviation to the optimal solution caused by the fluctuation of the network parameters can be avoided, and the optimal economic operation point of the system can be automatically found. In practical applications, the control method only adjusts the voltage of one single power supply node at a time, thus avoiding the adjustment failure caused by simultaneous adjustment of multiple power supplies. The method has low computational complexity and puts low requirements on computer performance.
The above description of specific embodiments of the present invention has been described with reference to the accompanying drawings, but is not intended to limit the scope of the invention. Other different forms of modifications or variations may be made by those skilled in the art in light of the above description. There is no need and no way to exhaust all of the implementation modes. On the basis of the technical solutions of the present invention, various modifications or variations that can be made by those skilled in the art without any creative effort are still within the scope of the present invention.
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Claims (4)

ConclusiesConclusions 1. Een gedistribueerde coöperatieve regelmethode voor het optimaliseren van een DC vermogensnetwerk, omvattende stappen van: a) het in staat stellen van een topologie van een netwerkachtig DC vermogenssysteem dat n vermogenstoevoerknooppunten en m belastingsknooppunten omvat, dat equivalent is aan een graaf voor het verkrijgen van een corresponderende admittantiematrix van een vermogensoverdrachtnetwerk als volgt: Yoo Y,A distributed cooperative control method for optimizing a DC power network, comprising steps of: a) enabling a network-like DC power system topology comprising n power supply nodes and m load nodes, which is equivalent to a graph for obtaining a corresponding admittance matrix of a power transfer network as follows: Yoo Y, SO en het verkrijgen van stroom [/s, ;]* dat door het vermogenstransmissienetwerk vloeit vanuit elk knooppunt, waarbij /s uitvoerstroom is van een vermogenstoevoerknooppunt en /; de stroom is die vloeit naar het vermogenstransmissienetwerk van een belastingsknooppunt; b) het opzetten van een prestatie-index J; van lijnverliesoptimalisatie en een prestatie-index J> van spanningsaanpassing, en het verkrijgen van een meervoudig doel optimaliseringsprobleem, waarbij J,=Ull +UlL, Is =o, =U; J=oJ + BJ, wherein a+p=1, 020, B>0, en waarbij Us een uitvoerspanning is van een vermogenstoevoerknooppunt Ur de spanning is die naar het vermogenstransmissienetwerk van een laadknooppunt wordt getransporteerd en Uy een geschat belastingsvoltage; en c) het oplossen van het optimaliseringsprobleem door een gedistribueerd algoritme op basis van een coördinatieafname, waarbij het gedistribueerde algoritme de stappen omvat van:SO and obtaining power [/ s,;] * flowing through the power transmission network from each node, where / s is output current from a power supply node and /; is the current flowing to the power transmission network of a load node; b) setting up a performance index J; of line loss optimization and a performance index J> of voltage adjustment, and obtaining a multiple target optimization problem, where J i = Ull + UlL, Is = 0, = U; J = oJ + BJ, wherein a + p = 1.020, B> 0, and where Us is an output voltage from a power supply node, Ur is the voltage transported to the power transmission network of a load node and Uy is an estimated load voltage; and c) solving the optimization problem by a distributed algorithm based on a coordination decrease, the distributed algorithm comprising the steps of: stap 1: het instellen van een stroomstap d=d,, wtvoerspanning U,=u?, het aantal iteraties i=0, en een vermogenstoevoer knooppuntnummer p=1, waarbij dy een initiële stapgrootte is U; een initiële voltagewaarde en het aanpassen van een vermogen van het eerste vermogenstoevoer; stap 2: het verzamelen van belastingsvermogen, vermogensknooppunt vermogen en belastingsvoltage voor feedbackregeling, maar niet meten van een lijn impedantie en het instellen van i=i+1; stap 3: het berekenen van a/;+ f/; dat wordt opgeslagen als P „(i-1); stap 4: het toevoegen van een spanningsstap verstoring in een huidig vermogenstoevoerknooppuntvoltage Vans ie., Vip! Vp +d, en het ongewijzigd laten van de andere knooppuntvoltages; stap 5: het opnieuw berekenen van a/,+ J, dat wordt opgeslagen als P (i); stap 6: het vergelijken van P ‚(ù) met P_,p(i-1); stap 7: het wijzigen wanneer IP „(i)-P ,(i-1)i<e, van de initiële waarde van de huidige vermogenstoevoer i=0, d=d, Von =Vop het selecteren van p+1, en het gaan naar stap 2; stap 8: anders het bepalen of P „()-P ‚{i-1) waar is, indien ja, het instellen van d = 1.1d en dan het gaan naar stap 2, en indien niet, het uitvoeren van stap 9; en stap 9: het instellen van d=-d, en het gaan naar stap 2.step 1: setting a current step d = d, wt input voltage U i = u ?, the number of iterations i = 0, and a power supply node number p = 1, where dy is an initial step size U; an initial voltage value and adjusting a power of the first power supply; step 2: collecting load power, power node power and load voltage for feedback control, but not measuring a line impedance and setting i = i + 1; step 3: calculating a / i + f /; which is stored as P '(i-1); step 4: adding a voltage step disturbance in a current power supply node voltage Vans ie., Vip! Vp + d, leaving the other node voltages unchanged; step 5: recalculate a /, + J, which is stored as P (i); step 6: comparing P 1 (4) with P 1, p (i-1); step 7: changing when IP „(i) -P, (i-1) i <e, of the initial value of the current power supply i = 0, d = d, Von = V upon selecting p + 1, and going to step 2; step 8: otherwise determining whether P1 () -P (i-1) is true, if yes, setting d = 1.1d and then going to step 2, and if not, performing step 9; and step 9: setting d = -d, and going to step 2. 2. De gedistribueerde coöperatieve regelmethode volgens conclusie 1 met het kenmerk dat de prestatie-index J; specifiek wordt geïndiceerd als volgt: J =U (Vy +V A+ ATY, (+ ATY,, AU, waarbij A=, +[¥,,.,D Ys, en waarbij ¥;.. de admittantie is van de belasting en Ys, Ysz, Ys and Yi: elementen zijn in de admittantiematrix Y,The distributed cooperative control method according to claim 1, characterized in that the performance index J; is specifically indicated as follows: J = U (Vy + V A + ATY, (+ ATY ,, AU, where A =, + [¥ ,,., D Ys, and where ¥; .. is the admittance of the load and Ys, Ysz, Ys and Yi: elements are in the admittance matrix Y, respectievelijk.respectively. 3. De gedistribueerde coöperatieve regelmethode volgens conclusie 2, met het kenmerk dat de prestatie-index J; specifiek wordt geïndiceerd als volgt: J =U{A"AU;-2UJAU;+ULU,The distributed cooperative control method according to claim 2, characterized in that the performance index J; is specifically indicated as follows: J = U {A "AU; -2UJAU; + ULU, 4. De gedistribueerde coöperatieve regelmethode volgens conclusie 1, met het kenmerk dat de vermogenstoevoer knooppunten zijn verdeeld als masterknooppunten en slaafknooppunten, waarbij elk masterknooppunt informatie verzamelt van aanliggende belastingen en deze overbrengt naar de slaafknooppunten, k Vi) => a, Vi), Vie N-QThe distributed cooperative control method according to claim 1, characterized in that the power supply nodes are divided as master nodes and slave nodes, each master node collecting information from adjacent loads and transferring it to the slave nodes, k Vi) => a, Vi), Vie NQ N PY => a,(P)~P)), VieN-QN PY => a, (P) ~ P)), VieN-Q BR PV => a, (PP), VieN-Q = waarbij Q een collectie is van master knooppunten, N een totaal aantal is van vermogenstoevoerknooppunten, Vi, Pri, en Py. belastingsknooppuntvoltage informatie zijn, respectievelijk belastingsknooppuntvermogensinformatie, en vermogenstoevoerknooppunt vermogensinformatie die worden ontvangen van een knooppunt, waarbij Vu, Pu, en Py respectievelijk belastingsknooppuntvoltage informatie, belastingsknooppunt vermogensinformatie en vermogenstoevoerknooppunt vermogensinformatie van een naburig knooppunt zijn en a; een gewichtscoëfficient is van een communicatienetwerk waarbij a;=l wanneer een i vermogenstoevoer in datacommunicatie is met th een j vermogenstoevoer, en anders a;=0.BR PV => a, (PP), VieN-Q = where Q is a collection of master nodes, N is a total number of power supply nodes, Vi, Pri, and Py. load node voltage information are load node power information, and power supply node power information, respectively, received from a node, where Vu, Pu, and Py are load node voltage information, load node power information and power supply node power information of a neighboring node, respectively, and a; is a weight coefficient of a communication network where a i = 1 when a i power supply in data communication is with th a j power supply, and a i = 0 otherwise.
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