An IPFC Planning and Configuration Method Considering the Adjustment Capabilities of Multiple Flexible Devices

Abstract

The present invention discloses an IPFC planning and configuration method considering the regulation capabilities of multiple flexible devices. This method fully takes into account the regulation capabilities of multiple flexible devices, takes the minimum IPFC investment and the maximum available transfer capability of the system as the optimization objectives, and constructs a multi-objective optimization model for IPFC planning and configuration. Based on a multi-objective algorithm nested with a multi-objective particle swarm algorithm and the interior point method, the solution of the proposed multi-objective optimization model is realized. The interior point method is used in the inner layer of the algorithm to solve the available transfer capability of the system with IPFC, and the multi-objective particle swarm algorithm is used in the outer layer to calculate the Pareto solution set of IPFC planning and configuration. The proposed model can fully consider the mutual support effect of the existing flexible devices in the system, and the corresponding solution algorithm can accurately and efficiently complete the optimization calculation, having great practical value, and can provide theoretical and technical support for the planning and configuration and demonstration application of IPFC.

Description

Technical Field

[0001] The present invention relates to a method for planning and configuring an IPFC considering the regulation capabilities of multiple flexible devices, belonging to the technical field of power system planning. Background Art

[0002] However, with the continuous growth of load, the increasingly complex grid structure, and the large-scale access of new energy, the uneven power flow distribution has become an important factor restricting the power transmission capacity of the power grid.

[0003] IPFC is a large-scale FACTS device with more powerful functions for controlling the power flow of multiple lines, and has a very broad application prospect for solving the transmission bottleneck problem of load-intensive power grids.

[0004] Existing IPFC planning methods are prone to result in an overly large planned capacity of IPFC, causing many problems such as waste of resources and poor practicability. Summary of the Invention

[0005] In order to solve the problems existing in the prior art, the present invention provides a method for planning and configuring an IPFC considering the regulation capabilities of multiple flexible devices, which can fully consider the mutual support effect of the existing flexible devices in the system, has great practical value, and can provide theoretical and technical support for the planning, configuration and demonstration application of IPFC.

[0006] In order to achieve the above object, the technical solution proposed by the present invention is: a method for planning and configuring an IPFC considering the regulation capabilities of multiple flexible devices, characterized in that:

[0007] Taking the maximum available transfer capability in the power system and the minimum IPFC investment as the optimization objectives, and taking the operation constraints of flexible power electronic devices and the operation constraints of the AC side of the power system as the constraint conditions, a multi-objective optimization model for IPFC planning and configuration is constructed;

[0008] A multi-objective algorithm based on the nested MOPSO algorithm and IPM is used to solve the multi-objective optimization model, and the solution process is as follows:

[0009] Step 1: Set the particle swarm and the maximum number of iterations of the outer-layer MOPSO algorithm, and set the initial calculation value and the maximum number of iterations of the inner-layer IPM;

[0010] Step 2: The inner-layer IPM calculates the available transfer capability index under each particle, and for the particles that do not meet the constraint conditions, a penalty term is added;

[0011] Step 3: Calculate the IPFC investment index of each particle;

[0012] Step 4: According to the Pareto dominance criterion, perform non-dominated sorting of the particles based on the available transfer capability and the IPFC investment index, and store the non-dominated solutions in the Pareto solutions;

[0013] Step 5: Update the particles within the constraints;

[0014] Step 6: Determine whether the maximum number of iterations is reached. If so, output the Pareto solution; otherwise, go to Step 2.

[0015] A further design of the above technical solution is that the available transfer capability F of the power system in the objective function of the proposed optimization model ATC is:

[0016]

[0017] where N PQ is the number of PQ nodes in the power system, λ Li is the growth ratio of the i-th load, P Li is the load of the power system's power receiving area, and P 0 is the total active load of the base-state power flow.

[0018] The IPFC investment index Fv in the objective function of the proposed optimization model is:

[0019]

[0020] where Smax is the maximum capacity required for the converter valve.

[0021] The flexible power electronic device includes UPFC and VSC-HVDC.

[0022] The operating constraints of the flexible power electronic device include:

[0023] a. IPFC operating constraints:

[0024] P inl + P inm + P inn = 0

[0025] where P inl is the active power injection power of the IPFC common node, P inm is the active power injection power of the additional node m of the main control line, and P inn is the active power injection power of the additional node n of the auxiliary control line;

[0026] b. UPFC operating constraints:

[0027] P ins + P inp + P inq = 0

[0028] where P ins is the active power injection power of the shunt converter to the UPFC common node pins , P inp is the active power injection P of the series converter to the common node p of the UPFC inp , P inq is the active power injection at the additional node q of the UPFC;

[0029]

[0030] In the formula, V se max and V sh max are respectively the maximum values of the output voltages of the series and shunt converters; S se max and S sh max are respectively the maximum values of the capacities of the series and shunt converters; V p min and V p max are respectively the minimum and maximum values of the voltage of the common node of the UPFC;

[0031] c. VSC-HVDC operation constraints:

[0032]

[0033] In the formula, G and B are respectively the conductance and susceptance between the AC side and the DC side; P d , Q d are respectively the active and reactive power injections of the AC network into the DC converter; V a , θ a are the voltage amplitude and phase angle of the AC side of the VSC-HVDC; V d , θ d are the voltage amplitude and phase angle of the DC side converter of the VSC-HVDC; θ ad is respectively the node voltage phase angle difference between the AC side and the DC side; P DC_loss is the sum of the active power losses in the DC network; P ai represents the active power at node i on the AC side; Y DCij represents the admittance between nodes i and j in the DC network; V DCi and V DCj respectively represent the voltages of nodes i and j in the DC network;

[0034]

[0035] In the formula, S s max is the maximum value of the complex power injected into the AC side, P s is the active power injected into the AC side, Q s is the reactive power injected into the AC side.

[0036] The AC - side operation constraints of the power system are as follows:

[0037]

[0038] In the formula, N is the number of system nodes; V i and V j are the voltage amplitudes of nodes i and j respectively; θ ij is the phase - angle difference between the voltages of the two ends of line ij; G ij , B ij are the elements in the i - th row and j - th column of the node conductance and susceptance matrices respectively, P ini , Q ini are the active and reactive injection powers of the flexible power electronic device;

[0039]

[0040] In the formula, V i min and V i max are the minimum and maximum values of the voltage of node i respectively; P Gi min and P Gi max are the minimum and maximum values of the active power output of generator i respectively; Q Gi min and Q Gi max are the minimum and maximum values of the reactive power output of generator i respectively; S ij and S ij max are the transmission power and maximum capacity of line ij respectively.

[0041] The beneficial effects of the present invention are as follows:

[0042] An IPFC planning and configuration method considering the regulation capabilities of multiple flexible devices proposed by the present invention fully takes into account the influence of the flexible control characteristics of multiple high - power flexible power electronic devices in the power grid, quantifies the mutual support effect when the power electronic devices jointly regulate, effectively avoids the problem of excessive IPFC planning capacity and poor practicability, provides a new idea for increasing the utilization rate of power grid transmission channels, improving the operation efficiency of the power grid, and optimizing the power system resource allocation, and also provides key technical support for the demonstration application of IPFC in the power grid. Brief Description of the Drawings

[0043] Figure 1 is the flow chart of the IPFC planning and configuration algorithm;

[0044] Figure 2 is the equivalent model diagram of IPFC;

[0045] Figure 3 It is the equivalent model diagram of UPFC;

[0046] Figure 4 It is the equivalent model diagram of VSC-HVDC. Specific implementation manners

[0047] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0048] Embodiment

[0049] A method for planning and configuring an IPFC considering the regulation capabilities of multiple flexible devices in this embodiment aims at the drawback that the existing configuration method of an interline power flow controller (IPFC) fails to fully utilize the mutual support effect of the flexible power electronic devices existing in the system. With the minimum investment of the IPFC and the maximum available transfer capability (ATC) of the power system as the optimization objectives, a multi-objective optimization model for IPFC planning and configuration is constructed. The objective functions are as follows:

[0050] When the load P Li , Q Li in the power receiving area and the generator output P Gi , Q Gi in the power generation area increase synchronously in the power system, the available transfer capability F ATC of the system can be described as:

[0051]

[0052] In the formula, N PQ is the number of PQ nodes in the system, λ Li is the growth ratio of the i-th load, and P 0 is the total active load of the base-state power flow.

[0053] The investment index (practicality index) F v of the IPFC device and the maximum capacity S max required for the converter valve are related as:

[0054]

[0055] The constraints of the above multi-objective optimization model are divided into two parts, namely the operation constraints of flexible power electronic devices and the operation constraints of the AC side of the power system.

[0056] (1) Operation constraints of flexible power electronic devices

[0057] In the above optimization model, the flexible power electronic devices considered include the unified power flow controller (UPFC) and the voltage source converter based high voltage direct current transmission (VSC-HVDC). Considering their supporting roles when jointly regulating with the IPFC, the corresponding constraints are as follows:

[0058] a) IPFC operation constraints

[0059] Based on the IPFC model, according to the objects of action of the converters, as Figure 2 shown, the active and reactive injection powers P inl , Q inl at the common node of the IPFC, the active and reactive injection powers P inm , Q inm at the additional node m of the main control line, and the active and reactive injection powers P inn , Q inn at the additional node n of the auxiliary control line are respectively:

[0060]

[0061]

[0062] In the formula, V se1 ∠θ se1 , V se2 ∠θ se2 are the output voltages of the main control and auxiliary control converters respectively; X se1 , X se2 are the reactances of the coupling transformers of the main control line and the auxiliary control line respectively; V l , θ l are the voltage amplitude and phase angle of the common node of the IPFC; V m , θ m are the voltage amplitude and phase angle of the additional node of the main control line of the IPFC; V n , θ n are the voltage amplitude and phase angle of the additional node of the auxiliary control line of the IPFC.

[0063] To ensure the stability of the DC side voltage, the IPFC follows the active power conservation constraint as follows:

[0064] P inl +P inm +P inn =0 (6)

[0065] b) UPFC operation constraints

[0066] Based on the UPFC model, according to the objects affected by the converters, such as Figure 3 shown, the active and reactive power injection powers P ins , Q ins of the shunt converter to the common node p, and the active and reactive power injection powers P inp , Q inp of the series converter to the UPFC common node p, and the active and reactive power injection powers P inq , Q inq of the UPFC additional node q are respectively:

[0067]

[0068] In the formula, V se ∠θ se , V sh ∠θ sh are the output voltages of the series and shunt converters respectively; X se , X sh are the reactances of the series and shunt coupling transformers respectively; V p , θ p are the voltage amplitude and phase angle of the UPFC common node; V q , θ q are the voltage amplitude and phase angle of the UPFC main control line additional node.

[0069] To ensure the stability of the DC-side voltage, the UPFC follows the active power conservation constraint as follows:

[0070] P ins +P inp +P inq = 0 (10)

[0071] For the UPFC already installed in the power system, the following inequality constraints need to be satisfied:

[0072]

[0073] In the formula, V se max and V sh max are the maximum values of the output voltages of the series and shunt converters respectively; S se max and S sh max are the maximum values of the capacities of the series and shunt converters respectively; V p min and V p max are the minimum and maximum values of the voltage of the UPFC common node respectively.

[0074] c) VSC-HVDC Operating Constraints

[0075] Based on the two-terminal VSC-HVDC model, as Figure 4 shown, the DC network satisfies the following equality constraints:

[0076]

[0077] where G and B are the conductance and susceptance between the AC side and the DC side respectively; P d , Q d are the active and reactive injection powers injected from the AC network into the DC converter respectively; V a , θ a are the voltage amplitude and phase angle of the AC side of the VSC-HVDC; V d , θ d are the voltage amplitude and phase angle of the DC side converter of the VSC-HVDC; θ ad is the phase angle difference of the node voltages between the AC side and the DC side respectively; P DC_loss is the sum of the active power losses in the DC network, mainly including the losses of converter stations, reactors and DC lines in the DC network; P ai represents the active power at node i on the AC side; Y DCij represents the admittance between nodes i and j in the DC network; V DCi and V DCj represent the voltages of nodes i and j in the DC network respectively.

[0078] The DC network also needs to satisfy the following inequality constraints:

[0079]

[0080] where S s max are the maximum values of the complex power injected from the AC side respectively.

[0081] (2) Operating Constraints of the AC Side of the Power System

[0082] Introducing the injection powers P ini , Q ini of the flexible devices, the node power balance equation is:

[0083]

[0084] where N is the number of system nodes; V i and V j are the voltage amplitudes of nodes i and j respectively; θ ij is the phase angle difference of the node voltages at both ends of line ij respectively; G ij , B ij are the elements in the i-th row and j-th column of the node conductance and susceptance matrices respectively.

[0085] The system inequality constraints are as follows:

[0086]

[0087] wherein, V i min and V i max are respectively the minimum value and the maximum value of the voltage of node i; P i min and P i max are respectively the minimum value and the maximum value of the active power output of generator i; Q i min and Q i max are respectively the minimum value and the maximum value of the reactive power output of generator i; S ij and S ij max are respectively the transmission power and the maximum capacity of line ij.

[0088] After determining the optimization model of the IPFC planning configuration, it is necessary to further study the solution algorithm of the optimization model. The proposed model is a multi-objective optimization model, and the calculation of some optimization objective values is relatively complex. Therefore, a multi-objective algorithm nested with the multi-objective particle swarm optimization (MOPSO) algorithm and the interior point method (IPM) is proposed to solve the proposed multi-objective optimization model. The interior point method is used in the inner layer of the algorithm to solve the ATC index introduced into the IPFC system, and the MOPSO algorithm is used in the outer layer to calculate the Pareto solution set of the IPFC planning configuration.

[0089] For the IPM for solving ATC in the inner layer, the optimization variables are the generator output and load in the system, the adjustable variables of the IPFC, the adjustable variables of the UPFC, and the adjustable variables of the VSC-HVDC; for the MOPSO algorithm in the outer layer, the optimization variables are the installation location variables of the IPFC and the converter valve capacity. The installation location of the IPFC in the power system should follow the following principles:

[0090] 1) The two selected branches should have a common node;

[0091] 2) The IPFC does not need to be installed on the transformer branch;

[0092] 3) The IPFC does not need to be installed on the branch with generators at both ends.

[0093] Considering that there may be contradictions between optimization objectives and the multi-objective optimization solution is not unique, the excellent position of the particle is updated according to the dominance relationship of Pareto. If the current position value of the particle dominates the individual optimal value P of the particle b , then the individual optimal value P b is updated to the current position value of the particle; if the current position value of the particle is dominated by P b , then P b remains unchanged; if there is no dominance relationship between the two, one of them is selected with equal probability.

[0094] The calculation process of the IPFC planning and configuration algorithm is as Figure 1 shown, and the specific steps are as follows:

[0095] Step 1: Set the particle swarm and the maximum number of iterations of the outer layer MOPSO algorithm, and set the initial calculation value and the maximum number of iterations of the inner layer IPM;

[0096] Step 2: The inner layer IPM calculates the available transmission capacity index for each particle. For particles that do not meet the constraint conditions, a penalty term is added, and each particle is output after reaching the maximum number of iterations;

[0097] Step 3: Calculate the IPFC investment index for each particle;

[0098] Step 4: According to the Pareto dominance criterion, perform non-dominated sorting of the particles based on the available transmission capacity and the IPFC investment index, and delete the solutions that do not meet the constraint conditions. Store the non-dominated solutions in the Pareto solutions; after non-dominated sorting, in the given set of alternative solutions, no solution can be found to improve each index, which is the non-dominated solution.

[0099] Step 5: Update the particles within the constraint range; obtain a set of corrected particles (solutions). After correction, gradually approach the obtained set of non-dominated solutions;

[0100] Step 6: Determine whether the maximum number of iterations has been reached. If so, output the Pareto solutions. The Pareto solutions are the solutions in the given set of alternative solutions where no solution can be found to improve each index, which is the optimal solution; otherwise, go to Step 2.

[0101] The technical solution of the present invention is not limited to the above embodiments, and all technical solutions obtained by equivalent replacement fall within the scope of protection required by the present invention.

Claims

1. An IPFC planning and configuration method considering the adjustment capabilities of multiple flexible devices, Characterized in that: Taking the maximum available transfer capability in the power system and the minimum IPFC investment as the optimization objectives, and taking the operating constraints of flexible power electronic devices and the operating constraints of the AC side of the power system as the constraint conditions, a multi-objective optimization model for IPFC planning and configuration is constructed; A multi-objective algorithm based on the MOPSO algorithm and IPM nesting is used to solve the multi-objective optimization model, and the solution process is as follows: Step 1: Set the particle swarm and the maximum number of iterations of the outer-layer MOPSO algorithm, and set the initial calculation value and the maximum number of iterations of the inner-layer IPM; Step 2: The inner-layer IPM calculates the available transfer capability index under each particle, and adds a penalty term to the particles that do not meet the constraint conditions; Step 3: Calculate the IPFC investment index of each particle; Step 4: According to the Pareto dominance criterion, perform non-dominated sorting of the particles based on the available transfer capability and the IPFC investment index, and store the non-dominated solutions in the Pareto solutions; Step 5: Update the particles within the constraint range; Step 6: Determine whether the maximum number of iterations has been reached. If so, output the Pareto solutions; Otherwise, go to Step 2; The available transfer capability F of the power system in the objective function of the proposed optimization model ATC is as follows: where N PQ is the number of PQ nodes in the power system, λ Li is the growth ratio of the i-th load, P Li is the load in the power receiving area of the power system, P 0 is the total active power load of the base-state power flow; The IPFC investment index Fv in the objective function of the proposed optimization model is: where S max is the maximum capacity required for the commutation valve; The flexible power electronic devices include UPFC and VSC-HVDC; The operating constraints of the flexible power electronic devices include: a. IPFC operating constraints: P inl +P inm +P inn = 0 where P inl is the active power injection of the IPFC common node, P inm is the active power injection of the additional node m of the main control line, and P inn is the active power injection of the additional node n of the auxiliary control line; b. UPFC operating constraints: P ins +P inp +P inq = 0 Wherein, P ins is the active power injection of the shunt converter into the UPFC common node p, P ins , P inp is the active power injection of the series converter into the UPFC common node p, P inp , P inq is the active power injection of the UPFC additional node q; Wherein, and are respectively the maximum values of the output voltages of the series and parallel converters; and are respectively the maximum values of the capacities of the series and parallel converters; and are respectively the minimum and maximum values of the voltage at the common node of the UPFC; c. VSC-HVDC operating constraints: where G and B are the conductance and susceptance between the AC side and the DC side respectively; P d , Q d are the active and reactive injection powers injected from the AC network into the DC converter respectively; V a is the voltage amplitude of the AC side of the VSC-HVDC; V d is the voltage amplitude of the converter on the DC side of the VSC-HVDC; θ ad is the phase angle difference of the nodal voltage between the AC side and the DC side; P DC_loss is the sum of the active power losses in the DC network; P ai represents the active power at node i on the AC side; Y DCij represents the admittance between nodes i and j in the DC network; V DCi and V DCj represent the voltages of nodes i and j in the DC network respectively; where S s max is the maximum complex power injected into the AC side, P s is the active power injected into the AC side, Q s is the reactive power injected into the AC side; The operating constraints of the AC side of the power system are: Where N is the number of system nodes; V i and V j are the voltage magnitudes of nodes i and j, respectively; θ ij is the phase angle difference of the node voltages at both ends of line ij; G ij , B ij are respectively the elements in the i-th row and j-th column of the nodal conductance and susceptance matrices, P ini , Q ini are the active and reactive injection powers of the flexible power electronic device; wherein, and are the minimum and maximum values of the voltage of node i, respectively; and are the minimum and maximum values of the active power output of generator i, respectively; and are the minimum and maximum values of the reactive power output of generator i, respectively; S ij and are the transmission power and the maximum capacity of line ij, respectively.

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