CN103853042B - A kind of decomposition optimization of Multi-terminal Unified Power Flow Controller - Google Patents

Abstract

A kind of DECOMPOSED OPTIMIZATION computational methods of Multi-terminal Unified Power Flow Controller, are characterized in comprising the following steps：1. obtain steady-state operation parameter needed for electric power system tide calculating；2. determine the installation site and control parameter scope of Multi-terminal Unified Power Flow Controller；3. being based on Equivalent Network, Multi-terminal Unified Power Flow Controller branch road is equivalent to include multiple PQ nodes of control targe；4. using TABU search, optimal load flow calculating is repeatedly carried out, to determine the real power control target of Multi-terminal Unified Power Flow Controller；5. according to the control targe of Multi-terminal Unified Power Flow Controller and the running status of system has been obtained, its control parameter is asked for.Optimal Power Flow Problems computational problem containing Multi-terminal Unified Power Flow Controller is decomposed into a bilevel optimization problem by the present invention by Equivalent Network, it can more effectively and reliably carry out the Optimal Power Flow Problems containing Multi-terminal Unified Power Flow Controller to calculate, there is engineering use value.

Description

A Decomposition Optimization Method for Multi-terminal Unified Power Flow Controller

technical field

The invention relates to a power system calculation method, in particular to a power system decomposition and optimization method including a multi-terminal unified power flow controller, which belongs to the technical field of power system power transmission and operation.

Background technique

Since the concept of Flexible AC Transmission Systems (FACTS) was put forward, more and more FACTS components are applied to the power transmission system to ensure the safe operation of the power grid. Among them, the unified power flow controller has attracted extensive attention of domestic and foreign scholars because of its powerful control function. With the further development of FACTS technology, a FACTS component derived from the unified power flow controller but more powerful than the unified power flow controller - multi-terminal unified power flow controller (M-UPFC for short) began to entered people's sight. The multi-terminal unified power flow controller can not only control the node voltage but also control the power flow of multiple lines or a certain sub-network in the system at the same time, which shows a stronger control ability than the unified power flow controller that can only control the power flow of a single line, and It is more economical than multiple single-ended unified power flow controllers. At the same time, the multi-terminal unified power flow controller has strong adaptability to the power system and does not need to change the hardware structure of the power system. It is an effective technology to control the power flow of the power system, enhance the transmission power limit of the power system, and increase the stability of the power system. Therefore, it is of great practical significance to study the optimization calculation problem of power system with multi-terminal unified power flow controller.

At present, there are few literatures on the optimal power flow calculation method for power systems with multi-terminal unified power flow controllers, and few literatures conduct in-depth research on it. The optimal power flow problem is a complex nonlinear mathematical problem. With the continuous development of modern numerical optimization theory and power system optimal power flow calculation technology, various numerical optimization methods have been applied to power system optimal power flow calculations, such as linear Planning methods, quadratic programming methods, and nonlinear programming methods, etc., among which the interior point optimal power flow calculation based on the Newton class solution method has become the mainstream of modern optimal power flow calculation methods. In some literatures, the optimal power flow solution of multi-terminal unified power flow controller is based on the interior point method, and some changes are added on this basis, such as the interior point method based on the trust region. However, there are three main problems in this type of method. First, the control equation of the multi-terminal unified power flow controller is introduced, and the original equation of the power system is optimized and solved together, which increases the nonlinearity of the solution problem, so the convergence and reliability of the system Second, after adding new control equations, the original algorithms and programs need to be greatly modified; third, the existing optimization power flow algorithms and programs are not fully utilized. Based on the above reasons, such methods are difficult to apply in engineering.

Contents of the invention

The purpose of the present invention is to provide a reliable calculation method for the optimal power flow of a power system containing a multi-terminal unified power flow controller. The method adopted by Fang Ming decomposes the optimal power flow calculation problem of power system with multi-terminal unified power flow controller into a two-layer optimization problem through network equivalent: the outer layer is based on tabu search, and the multi-terminal optimization problem is realized by calling the inner layer optimization calculation. The optimization of the active power control power of the unified power flow controller; the inner optimization calculation is to perform the traditional optimal power flow calculation under the condition of the determined active power control power control value of the multi-terminal unified power flow controller. The method adopted in the invention can more effectively and reliably calculate the optimal power flow of the power system containing the multi-terminal unified power flow controller, and has engineering use value.

The fundamental difference between the characteristics of the present invention and the above-mentioned method in the prior art is: (1) based on the network equivalence, the branch of the multi-terminal unified power flow controller is equivalent to a plurality of PQ nodes containing control targets (2) using tabu search, only Optimize an equivalent control variable of the multi-terminal unified power flow controller, that is, the active power control target of the multi-terminal unified power flow controller, thereby reducing the amount of calculation and simplifying the optimization calculation; (3) The optimization process is completed through a two-layer optimization strategy , the outer layer uses tabu search to optimize the control objectives of the multi-terminal unified power flow controller, the inner layer adopts the traditional optimal power flow calculation method to optimize the operating state of the system, and the outer layer optimization calls the inner layer optimization; the above method improves the multi-terminal unified power flow controller Efficiency and reliability of controllers for power system optimal power flow calculations.

In order to achieve the above object, the technical solution adopted by the present invention is: this power system decomposition and optimization method comprising a multi-terminal unified power flow controller is characterized in that it is carried out in the following steps:

Step 1) Obtain the steady-state operating parameters required for the optimal power flow calculation of the power system;

Step 2) Determine the control parameters, control objectives and control range of the multi-terminal unified power flow controller;

Step 3) Based on the network equivalent, the multi-terminal unified power flow controller branches are equivalent to multiple PQ nodes containing control targets;

Step 4) Use tabu search to calculate the optimal power flow multiple times to determine the active power control target of the multi-terminal unified power flow controller:

① Coding the active power control target variable set of the multi-terminal unified power flow controller;

② Generate an initial solution;

③The single movement and exchange movement are respectively applied to the initial solution to obtain a set of feasible experimental solutions;

④ Optimal power flow calculation is performed on the above feasible test solutions, and the objective function value of optimal power flow calculation is used as the evaluation function of tabu search;

⑤ Update taboo search table;

⑥ Update the initial solution;

⑦ Judging the termination condition: If the objective function value of several consecutive iterations is not improved or reaches the maximum allowable number of iterations, stop the calculation and output the result;

⑧If the termination condition is not met, repeat step ③;

Step 5) Calculate its control parameters according to the obtained control objectives of the multi-terminal unified power flow controller and the operating state of the system.

The steady-state operating parameters required for obtaining the optimal power flow calculation of the power system refer to: the topology structure of the AC system network, the parameters of the transmission network, the system power generation and load parameters, and other parameters necessary for the calculation of the optimal power flow of the AC system.

The described determination of the control parameters, control objectives and control range of the multi-terminal unified power flow controller includes:

a. The control parameters of the multi-terminal unified power flow controller refer to the equivalent control parameters of the multi-terminal unified power flow controller in power system power flow analysis. In the present invention, the multi-terminal unified power flow controller is expressed as n+1( n≥2) controllable voltage sources, one connected in parallel to the access bus of the multi-terminal unified power flow controller, and n connected in series on the branch road where the multi-terminal unified power flow controller is installed. Therefore, the control parameters of the multi-terminal unified power flow controller are Amplitude and phase of series and parallel controllable voltage sources.

b. The control target of the multi-terminal unified power flow controller refers to the active power and reactive power injected into the bus by the parallel part of the multi-terminal unified power flow controller; the active and reactive power of the lines controlled by the series part; and the active power injected into the bus by the parallel part The sum of the active power of the line controlled by the series part is equal in value, and the control range of these steady-state control targets can be given during engineering design, and more accurate information can also be obtained through multiple power flow calculations.

Based on network equivalence, the multi-terminal unified power flow controller branches are equivalent to multiple PQ nodes containing control targets. The control effect of the inverter on the power system is represented by the equivalent injected power, and these equivalent injected powers act on n+1 equivalent nodes connected to the multi-terminal unified power flow controller. Considering the multi-terminal unified power flow controller In the calculation of optimal power flow, these n+1 equivalent nodes are treated as PQ nodes.

The encoding of the active power control target variable set of the multi-terminal unified power flow controller includes:

a. For a multi-terminal unified power flow controller active power control target variable, according to the adjustable range, the interval of the parameter is discretized to form a set to be selected for the parameter;

b. Binary code each element in the parameter set to be selected; if the decimal number corresponding to the binary code of a certain parameter T is d, then:

In the formula: T _max and T _min are the maximum and minimum values of this parameter; n is the number of bits of binary code;

c. Perform the above coding work on the active control target variables of all multi-terminal unified power flow controllers in the system;

d. Concatenate the binary codes of all parameter sets to form a (0-1) code string.

The described generation initial solution includes:

a. Assign initial values to the set of active power control variables of the multi-terminal unified power flow controller;

b. Under the condition of the initial value of the parameter, the traditional optimal power flow calculation of the inner layer is performed to obtain the initial value of the evaluation function;

c. Write the initial value vector of the parameter as a binary code.

The described single movement and exchange movement act on the initial solution respectively, including:

a. Single movement: Randomly select a certain bit of the code string for inversion operation;

b. Swap movement: Randomly select a certain bit of the code string for inversion operation;

c. Apply the two kinds of movement to the current solution respectively, so as to obtain a set of experimental solutions for the control target vector of the multi-terminal unified power flow controller.

The feasible experimental solutions include:

a. The test solution is not in the contraindication search list;

b. Although the test solution is in the taboo list, it has met the release criteria.

The optimal power flow calculation is performed on the above feasible experimental solutions, and the objective function value of the optimal power flow calculation is used as the evaluation function of the tabu search, including:

a. Take a feasible experimental solution, and calculate the parameter value through its binary code;

b. Use this parameter value as the active power control target value of the multi-terminal unified power flow controller;

c. Taking the equivalent network of the multi-terminal unified power flow controller as the calculation object, the traditional optimal power flow calculation is performed. Among them, the active injection power of the equivalent PQ node is a fixed value, and the reactive injection power is used as a variable for system optimization;

d. If the calculation is convergent, set the optimization target value of the optimal power flow calculation as the evaluation function value of the tabu search; if the calculation does not converge, set the evaluation function value of the tabu search to infinity.

e. Calculate the control parameters of the multi-terminal unified power flow controller according to the system operating state obtained from the optimal power flow results and the optimal control target value of the multi-terminal unified power flow controller. If the parameter is not within the reasonable range, it means that the control state does not exist, and the evaluation function value of the tabu search is set to infinity.

f. Compared with the original evaluation function value, keep the one with the smallest function value and the corresponding parameter value;

g. Repeat to a until all experimental solutions have been calculated.

The updating of the tabu search table is to record the movement in the opposite direction of the realized movement into the tabu table.

The method adopted by the invention can more effectively and reliably calculate the optimal power flow of the power system containing a multi-terminal unified power flow controller, and has engineering practical value.

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

1. This method has excellent computing performance. First of all, the inner layer optimization of this method is realized through the traditional optimal power flow calculation that does not include the multi-terminal unified power flow controller, which does not increase the difficulty of solving the system; at the same time, the outer layer is only for one active control target variable of the multi-terminal unified power flow controller. optimized to simplify calculations. Therefore, the overall computational performance of this method is better.

2. Suitable for complex system calculation conditions. This method can judge the feasibility of the current system operation state according to whether the optimal power flow converges or not and whether the obtained multi-terminal unified power flow controller control parameters are feasible or not. Therefore, when some limiting conditions are not accurate enough (such as the active power control interval of the multi-terminal unified power flow controller), this method can still give reasonable results.

3. The method is convenient for practical and commercial development. Since this method is mainly implemented by invoking the traditional optimal power flow calculation that does not include a multi-terminal unified power flow controller in the inner layer, these characteristics make this method easy to be practical and commercially developed.

Description of drawings

Fig. 1 is the overall flowchart of the decomposition and optimization method of the multi-terminal unified power flow controller;

Fig. 2 is the equivalent schematic diagram of the multi-terminal unified power flow controller;

Fig. 3 is a flow chart of parameter optimization using tabu search;

Figure 4 is a network topology diagram of the IEEE30 node system example.

detailed description

The features, advantages and implementation modes of the present invention will be described in further detail below in conjunction with the accompanying drawings and calculation examples.

As shown in Figure 1, Figure 2, Figure 3, and Figure 4, a decomposition and optimization method for a multi-terminal unified power flow controller includes the following steps:

Step 1) Obtain the steady-state operating parameters required for the optimal power flow calculation of the power system;

Step 2) Determine the control parameters, control objectives and control range of the multi-terminal unified power flow controller

Step 3) Based on network equivalence, the branches of the multi-terminal unified power flow controller are equivalent to multiple PQ nodes containing control targets

Step 4) Using tabu search, the optimal power flow calculation is performed multiple times to determine the active power control target of the multi-terminal unified power flow controller;

Step 1: Coding the active power control target variable set of the multi-terminal unified power flow controller;

The second step: generate the initial solution;

The third step: apply the single movement and the exchange movement to the initial solution respectively, and obtain a set of feasible experimental solutions;

Step 4: Perform optimal power flow calculation on the above feasible test solutions, and use the objective function value of optimal power flow calculation as the evaluation function of tabu search;

Step 5: Update taboo search table;

Step 6: Update the initial solution;

Step 7: Judging the termination condition: If the objective function value does not improve for several consecutive iterations or reaches the maximum allowable number of iterations, stop the calculation and output the result;

Step 8: If the termination condition is not met, repeat the third step;

Step 5) Obtaining its control parameters according to the obtained control target of the multi-terminal unified power flow controller and the operating state of the system;

The steady-state operating parameters required for obtaining the optimal power flow calculation of the power system refer to: the topology structure of the AC system network, the parameters of the transmission network, the system power generation and load parameters, and other parameters necessary for the calculation of the optimal power flow of the AC system.

The described determination of the control parameters, control objectives and control range of the multi-terminal unified power flow controller includes:

a. The control parameters of the multi-terminal unified power flow controller refer to the equivalent control parameters of the multi-terminal unified power flow controller in power system power flow analysis. In the present invention, the multi-terminal unified power flow controller is expressed as n+1(n in system analysis ≥2) Controllable voltage sources, one connected in parallel to the access bus of the multi-terminal unified power flow controller, and n connected in series on the branch circuit installed by the multi-terminal unified power flow controller. Therefore, the control parameters of the multi-terminal unified power flow controller are the amplitude and phase of the series and parallel controllable voltage sources.

b. The control target of the multi-terminal unified power flow controller refers to the active power and reactive power injected into the bus by the parallel part of the multi-terminal unified power flow controller; the active and reactive power of the lines controlled by the series part; and the active power injected into the bus by the parallel part The sum of the active powers of the lines controlled by the series part is numerically equal. The control range of these steady-state control objectives can be given during engineering design, and more accurate information can also be obtained through multiple power flow calculations.

Based on network equivalence, the multi-terminal unified power flow controller branches are equivalent to multiple PQ nodes containing control targets. The control effect of the inverter on the power system is represented by the equivalent injected power, and these equivalent injected powers act on n+1 equivalent nodes connected to the multi-terminal unified power flow controller. Considering the multi-terminal unified power flow controller In the calculation of optimal power flow, these n+1 equivalent nodes are treated as PQ nodes.

The encoding of the active power control target variable set of the multi-terminal unified power flow controller includes:

a. For a multi-terminal unified power flow controller active power control target variable, according to the adjustable range, the interval of the parameter is discretized to form the sum of the parameter to be selected;

b. Binary code each element in the parameter set to be selected; if the decimal number corresponding to the binary code of a certain parameter T is d, then:

In the formula: T _max and T _min are the maximum and minimum values of this parameter; n is the number of bits of binary code;

c. Perform the above coding work on the active control target variables of all multi-terminal unified power flow controllers in the system;

d. Concatenate the binary codes of all parameter sets to form a (0-1) code string.

The described generation initial solution includes:

a. Assign initial values to the set of active power control variables of the multi-terminal unified power flow controller;

b. Under the condition of the initial value of the parameter, the traditional optimal power flow calculation of the inner layer is performed to obtain the initial value of the evaluation function;

c. Write the initial value vector of the parameter as a binary code.

The described single movement and exchange movement act on the initial solution respectively, including:

a. Single movement: Randomly select a certain bit of the code string for inversion operation;

b. Swap movement: Randomly select a certain bit of the code string for inversion operation;

c. Apply the two kinds of movement to the current solution respectively, so as to obtain a set of experimental solutions for the control target vector of the multi-terminal unified power flow controller.

The feasible test solutions described include:

a. The test solution is not in the contraindication search list;

b. Although the test solution is in the taboo list, it has met the release criteria.

The optimal power flow calculation is performed on the above feasible experimental solutions, and the objective function value of the optimal power flow calculation is used as the evaluation function of the tabu search, including:

a. Take a feasible experimental solution, and calculate the parameter value through its binary code;

b. Use this parameter value as the active power control target value of the multi-terminal unified power flow controller;

c. Taking the equivalent network of the multi-terminal unified power flow controller as the calculation object, the traditional optimal power flow calculation is performed. Among them, the active injection power of the equivalent PQ node is a fixed value, and the reactive injection power is used as a variable for system optimization;

d. If the calculation is convergent, set the optimization target value of the optimal power flow calculation as the evaluation function value of the tabu search; if the calculation does not converge, set the evaluation function value of the tabu search to infinity.

e. Calculate the control parameters of the multi-terminal unified power flow controller according to the system operating state obtained from the optimal power flow results and the optimal control target value of the multi-terminal unified power flow controller. If the parameter is not within the reasonable range, it means that the control state does not exist, and the evaluation function value of the tabu search is set to infinity.

f. Compared with the original evaluation function value, keep the one with the smallest function value and the corresponding parameter value;

g. Repeat to a until all experimental solutions have been calculated.

The updated taboo search list, including:

a. Record the movement in the opposite direction of the achieved movement in the taboo table;

b. The taboo table adopts the first-in first-out management method.

Fig. 1 is an overall flowchart of the decomposition and optimization method of the multi-terminal unified power flow controller. The flowchart is consistent with the basic steps of the embodiments of the present invention. It should be noted that the active power control target of the multi-terminal unified power flow controller optimized by tabu search is realized by calling the traditional optimal power flow calculation multiple times, and it returns the result of the optimal power flow calculation as the evaluation function value of the tabu search. The optimal power flow problem mentioned in the present invention is specifically explained below in combination with the optimal power flow call in the flow chart:

The optimal power flow of the power system is a typical nonlinear programming problem, and the power system optimization equation can generally be expressed by the following mathematical model:

min f(z)

In the formula

z∈R ⁿ ; z is a vector composed of all variables considered in the optimization problem, including the control variables and state variables of the system; n is the dimension of the variable space. In the optimal power flow problem described in the present invention, the control variables include active power and reactive power of power generation nodes, reactive power of reactive power compensation nodes, and reactive power of multi-terminal unified power flow controller equivalent PQ nodes; state variables are the reactive power of each node of the system Voltage magnitude and phase. The impedance parameters of the electrical network components and the active power of the equivalent PQ nodes of the multi-terminal unified power flow controller are all constant.

f: R ^z → R characterizes the objective function of the optimization operation of the system. It is a function of the system variable vector, and in the optimal power flow problem described in the present invention, it can be the system's power generation cost, power purchase cost, and the like.

g: R ^z → R ^ng characterizes the equality constraint function vector, and ng is the number of system power flow active and reactive power equations. In the optimal power flow problem described in the present invention, the equality constraint refers to the system power flow equation constraint after the equivalent PQ node of the multi-terminal unified power flow controller.

h: R ^z → R ^nh characterizes the inequality constraint function vector, and nh is the number of inequality constraints. In the optimal power flow problem described in this paper, the operating constraints of the system may include node voltage constraints, transmission line transmission capacity constraints, transmission section capacity constraints, active and reactive power constraints of generation capacity, system reactive power compensation node reactive power compensation Capacity constraints, reactive power compensation capacity constraints of multi-terminal unified power flow controller equivalent PQ nodes, etc.

Fig. 2 is an equivalent schematic diagram of the multi-terminal unified power flow controller.

Fig. 3 is a flow chart of parameter optimization using tabu search. The present invention adopts the tabu search technology to adjust the parameters appropriately, so as to achieve the purpose of correcting the frequency emulation track. Tabu search, also known as TS method, is a heuristic search method for expanding neighborhoods. It was first proposed by Fred Glover in 1977 as an optimal tool to solve nonlinear coverage problems. It uses a special form of flexible memory to obtain knowledge during the search process to avoid the search from falling into local optimum. It has been successfully applied to solve large-scale combinatorial optimization problems. The basic principle of the TS method is: start searching from the initial solution X (which is an n-dimensional vector). By adopting a group of operators "moving" to operate on the current solution, a group of neighborhood N(X) experimental solutions X ₁ , X ₂ , ..., X _K of the current solution are randomly generated. Among the neighborhood test solutions generated, select the solution X* that can improve the evaluation function the most as the current local optimal solution, that is, let X=X*, repeat iterations until all the 'movements' cannot improve the evaluation function, Indicates that the current solution is a local optimal solution. In order to avoid falling into the local optimal solution, a flexible "memory technique" is adopted in the TS method. In addition, in order not to miss the "movement" that produces the optimal solution as much as possible, the TS method also adopts the "release criterion" strategy.

The general steps for calculation with tabu search are as follows:

(1) Read in the original variable set for encoding.

(2) Generate an initial solution: randomly generate an initial solution X within the constraints of the control variables, obtain the objective function value f(X), and set the best solution vector X _opt = f(X)

(3) Generate a set of experimental solutions: apply single movement and exchange movement to X respectively, obtain a set of feasible experimental solutions X ₁ , X ₂ ,...,X _K , and obtain the corresponding f(X ₁ ), f (X ₂ ),…,f(X _K ).

(4) Neighborhood search: Optimizing from the above test solutions to get the best test solution X*, if X* is not in the taboo list, or if it is in the tabu list but meets the release criteria, then use X* to update X, that is, let X=X*; if the solution is in the tabu list, and the release criterion is not met, then find the next best solution, and repeat this process.

(5) Update the initial solution, and use the best experimental solution to update the initial solution.

(6) Updating the taboo list: record the movement in the opposite direction of the realized move into the tabu list, if the tabu list is full, first exclude the first recorded move.

(7) Update X _opt : if f(X*)<f(X _opt ), update X _opt with X*, otherwise X _opt remains unchanged.

(8) Judging the termination condition: if the objective function value does not improve for several consecutive iterations or reaches the maximum allowable number of iterations, then stop the optimization and output the result; otherwise, go to step (3) to continue iteration.

Compared with other search algorithms, the tabu search method has a strong ability to jump out of local optimal solutions, so it has good convergence characteristics and high-quality solutions, and has been successfully applied to large-scale power system parameter optimization or adjustment problems. The invention adopts the taboo search technology to optimize the active power control target variable of the multi-terminal unified power flow controller.

Figure 4 is a network topology diagram of the IEEE30 node system example. The method proposed by the invention is verified by calculation in a 30-node network, which illustrates its feasibility. For the convenience of analysis and calculation, the multi-terminal unified power flow controller with n=2 in Fig. 2 is taken as the calculation object, also called two-terminal unified power flow controller. Set the transmission capacity of Line 2-4, Line 21-22 and Line 27-28 to 18MW, 20MW and 15MW respectively, and set the transmission capacity of other lines to 30MW. The two-terminal unified power flow controller is installed on Line 6-9 and on lines 6-10. The maximum control amplitude of the two-terminal unified power flow controller series equivalent voltage source is 0.1pu, and the maximum control amplitude of the parallel equivalent voltage source is 1.0pu. The reactive power control range of the equivalent PQ node of the two-terminal unified power flow controller is taken as 20MW and -20MW. The range of active power regulation is taken as ±50% of the power flow value when the line is in normal operation. The value of the power purchase function is as follows:

After 142 calculations of the tabu search, the variation of the evaluation function value begins to decrease gradually and tends to be stable. After 90 searches, the optimized results are as follows: the parallel control parameters of the two-terminal unified power flow controller are: 0.98pu, 0.03 degrees; the control parameters of the series controllable voltage source 1: 0.16pu, 94.1 degrees; the series controllable voltage source 2 The control parameters: 0.05pu, 93.7 degrees, at this time, the power generation cost is 588.43 US dollars per hour. It can be seen that using the method proposed by the present invention to calculate the optimal power flow of a power system with a multi-terminal unified power flow controller can reliably and effectively optimize the control of the operating state of the power system.

Claims (10)

1. a kind of decomposition optimization of Multi-terminal Unified Power Flow Controller, refers to the electric power containing Multi-terminal Unified Power Flow Controller System optimal Load flow calculation problem is decomposed into a bilevel optimization problem by Equivalent Network：Outer layer is based on TABU search, passes through Internal layer optimization is called to calculate, to realize the optimization to Multi-terminal Unified Power Flow Controller real power control power；Internal layer optimizes calculating It is determined that Multi-terminal Unified Power Flow Controller real power control power control value under conditions of, carry out traditional optimal load flow and calculate, It is characterized in that carry out according to the following steps：

Step 1) obtains steady-state operation parameter needed for Optimal Power Flow Problems calculating；

Step 2) determines the control parameter and control targe and modification scope of Multi-terminal Unified Power Flow Controller；

Step 3) is based on Equivalent Network, and Multi-terminal Unified Power Flow Controller branch road, which is equivalent to multiple PQ comprising control targe, to be saved Point；

Step 4) uses TABU search, repeatedly carries out optimal load flow calculating, has power control determine Multi-terminal Unified Power Flow Controller Target processed；

1. Multi-terminal Unified Power Flow Controller real power control target variable set is encoded；

2. produce initial solution；

3. single movement and exchange movement are respectively acting on into initial solution, one group of feasible experiment solution is obtained；

4. carrying out optimal load flow calculating to above-mentioned feasible experiment solution, the target function value that optimal load flow is calculated is searched as taboo The evaluation function of rope；

5. update TABU search table；

6. update initial solution；

7. judge end condition:If continuously iterative target functional value does not improve or reached maximum allowable iterations several times, Stop calculating, output result；

If 8. being not reaching to end condition, 3. repetition walks；

Step 5) asks for its control according to the obtained control targe of Multi-terminal Unified Power Flow Controller and the running status of system Parameter.

A kind of 2. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：It is described Acquisition Optimal Power Flow Problems calculate needed for steady-state operation parameter, refer to：Topological structure, the power transmission network of AC system network Network parameter, system generates electricity and load parameter carries out parameter necessary to AC system optimal load flow calculating.

A kind of 3. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：It is described Determination Multi-terminal Unified Power Flow Controller control parameter and control targe and modification scope, including：

A. the control parameter of Multi-terminal Unified Power Flow Controller refers to the Multi-terminal Unified Power Flow Controller in electric power system tide is analyzed Equivalent control parameter, Multi-terminal Unified Power Flow Controller is the controllable voltage source of n+1 and n >=2, and one to be connected in parallel on multiterminal unified On the access bus of flow controller, n are connected on the branch road of Multi-terminal Unified Power Flow Controller installation, and therefore, multiterminal are unified The control parameter of flow controller is the amplitude and phase of series connection and controllable voltage source in parallel；

B. Multi-terminal Unified Power Flow Controller control targe refers to that Multi-terminal Unified Power Flow Controller parallel connection part has to what bus injected Work(power and reactive power；The active and reactive power of the circuit of part in series control；Wherein parallel connection part injects to bus Active power and the active power sum numerically equal of the circuit of part in series control.

A kind of 4. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：It is described Based on Equivalent Network, Multi-terminal Unified Power Flow Controller branch road is equivalent to multiple PQ nodes comprising control targe and referred to：Press According to the equivalent Substitution Theoren of electric network, in steady-state analysis, the control action Multi-terminal Unified Power Flow Controller to power system Characterized with equivalent injecting power, these equivalent injecting powers are respectively acting on what is be connected with Multi-terminal Unified Power Flow Controller On n+1 equivalent node, in the calculating of optimal load flow of THE UPFC is considered, this n+1 equivalent node conducts PQ nodes are handled.

A kind of 5. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：It is described Multi-terminal Unified Power Flow Controller real power control target variable set is encoded, including：

A. to a certain Multi-terminal Unified Power Flow Controller real power control target variable, according to adjustable extent, the parameter space is entered Row discretization, form the set to be selected of the parameter；

B. each element of the selected works with is treated to the parameter, carries out binary coding；If corresponding to certain parameter T binary coding Decimal number is d, then has：

In formula：T_maxAnd T_minFor the minimum and maximum value of the parameter；N is binary coding digit；

C. above-mentioned coding work is carried out to the real power control target variable of all Multi-terminal Unified Power Flow Controllers in system；

D. the binary coding of all parameter sets is connected, forms 0-1 sequence.

A kind of 6. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：It is described Generation initial solution, including：

A. to Multi-terminal Unified Power Flow Controller real power control variables collection, initial value is assigned；

B. under the conditions of the initial parameter values, the traditional optimal load flow for carrying out internal layer calculates, and obtains the initial value of evaluation function；

C. the initial vector of parameter is write as binary coding.

A kind of 7. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：It is described By single movement and exchange movement be respectively acting on initial solution, including：

A. single movement：The a certain position for randomly selecting sequence carries out inversion operation；

B. movement is exchanged：Randomly select certain two progress inversion operations of sequence；

C. two kinds of movements are respectively acting on current solution, so as to obtain one group of Multi-terminal Unified Power Flow Controller control targe vector Experiment solution.

A kind of 8. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：It is described Feasible experiment solution, including：

A. the experiment solution is not in TABU search table；

Although b. the experiment solution is in taboo list, meet to discharge criterion.

A kind of 9. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：To upper State feasible experiment solution and carry out optimal load flow calculating, the evaluation letter using the target function value that optimal load flow calculates as TABU search Number, including：

A. some feasible experiment solution is taken, passes through its binary coding, calculating parameter numerical value；

B. the real power control desired value the parameter value as Multi-terminal Unified Power Flow Controller；

C. using the network after Multi-terminal Unified Power Flow Controller equivalence as object is calculated, carry out traditional optimal load flow and calculate, wherein The active injection power of equivalent PQ nodes is definite value, variable of the idle injecting power as system optimization；

If d. calculating convergence, the evaluation function value using the optimization target values that optimal load flow calculates as TABU search；If calculate not Convergence, the evaluation function value for putting TABU search are infinity；

E. the system running state and the optimal control target value of Multi-terminal Unified Power Flow Controller tried to achieve according to optimal load flow result, Calculate the control parameter of Multi-terminal Unified Power Flow Controller；If parameter not in reasonable interval, illustrates that this state of a control is not present, put The evaluation function value of TABU search is infinity；

F. made comparisons with original evaluation function value, retain functional value reckling and corresponding parameter value；

G. repeat to a, finished until all experiment solutions all calculate.

A kind of 10. decomposition optimization of Multi-terminal Unified Power Flow Controller according to claim 1, it is characterised in that：Institute The renewal TABU search table stated is the opposite direction moving recording for the movement that will be realized into taboo list.