An optimization method for parallel operation of transformer substations

Abstract

The present invention provides a method for optimizing the parallel operation of substations. The parallel operation of substations is achieved through DC interconnection. The hardware device includes an intelligent distribution transformer terminal, an energy management system, a flexible inverter converter (FIC), and an energy storage system. The intelligent distribution transformer terminal collects the power of the distribution transformer. The energy management system controls the power of the flexible inverter converter (FIC) and the energy storage system. The substation parallel optimization operation algorithm is deployed in the energy management system. The application of this technical solution can achieve the minimum loss operation of the substation parallel operation system.

Description

Technical Field

[0001] The present invention relates to the technical field of low-voltage intelligent power distribution, and particularly to an optimization method for parallel operation of distribution areas. Background Art

[0002] The access of large-scale distributed photovoltaic power, charging piles, energy storage and other new devices to the low-voltage distribution network puts forward higher requirements for the carrying capacity of the low-voltage distribution network. According to the load characteristics of the low-voltage distribution area, connecting two or more distribution areas with complementary load characteristics through a DC interconnection device can significantly improve the power supply capacity of the distribution area. Considering that the operating efficiency of the distribution transformer has a non-linear relationship with the load rate of the distribution area, the advantages of the current parallel operation of the distribution areas cannot be fully utilized, and the system operating efficiency is low. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide an optimization method for parallel operation of distribution areas to fully utilize the advantages of parallel operation of distribution areas and improve the system operating efficiency.

[0004] To achieve the above purpose, the present invention adopts the following technical scheme: An optimization method for parallel operation of distribution areas realizes the parallel operation of distribution areas through DC interconnection. The hardware devices include an intelligent distribution transformer terminal, an energy management system, a flexible inverter converter FIC and an energy storage system; the intelligent distribution transformer terminal collects the power of the distribution transformer, the energy management system controls the power of the flexible inverter converter FIC and the energy storage system, and the parallel operation optimization algorithm of the distribution area is deployed in the energy management system.

[0005] In a preferred embodiment, the particle swarm algorithm is used to optimize the power P of the distribution transformer of different distribution areas Ti , where i is the number of distribution areas in parallel operation, and the power of the flexible inverter converter FIC and the energy storage system during the working period, so as to minimize the parallel operation loss of the distribution areas, including the following steps:

[0006] Step S1: Select the power P of the distribution transformer of the distribution area Ti during the working period, set the power P of the flexible inverter converter FIC FICi and the power P of the energy storage system FS as particles, and initialize the particle positions and velocities;

[0007] Step S2: Calculate the fitness of the particles with the goal of minimizing the overall system operation loss;

[0008] Step S3: Obtain the individual optimal value of the particles and the global optimal value of the population;

[0009] Step S4: Update the particle velocities and positions;

[0010] Step S5: Determine whether the maximum number of iterations has been reached;

[0011] Step S6: Screen the operating mode with smaller system losses and record the optimal power outputs of the flexible converter FIC and the energy storage system;

[0012] Step S7: Determine whether the calculation of the optimal power outputs of the flexible converter FIC and the energy storage system for all the distribution transformers' power P Ti during the working period is completed. Otherwise, repeat steps S1 - S6.

[0013] In a preferred embodiment, the objective function for the parallel operation optimization of the substation areas is:

[0014] minF = W T (t) + W line (t) + W ec (t) + W ex (t) (1);

[0015] where W T (t) is the power loss of the distribution transformer; W line (t) is the line loss; W ec (t) is the power conversion loss, including the power conversion losses of the flexible converter FIC and the energy storage system; W ex (t) is the additional loss caused by the operation of the system auxiliary equipment; t is the system operation time.

[0016] In a preferred embodiment, the calculation method of the power loss of the distribution transformer is as follows:

[0017]

[0018] where P T_n is the power of the distribution transformer in substation area n; η T_n is the operation loss rate of the distribution transformer in substation area n; N is the number of substation areas in parallel operation.

[0019] In a preferred embodiment, the calculation method of the line loss is as follows:

[0020]

[0021] where P ACline_n is the AC line power between the FIC and substation area n, η ACline_n is the AC line loss rate between the FIC and substation area n; P DCline_n is the DC line power between the FICs, η DCline_n is the DC line loss rate between the FICs.

[0022] In a preferred embodiment, the calculation method of the power conversion loss is as follows:

[0023]

[0024] Among them, P FIC_n is the FIC power, and η FIC_n is the FIC loss rate; P ES is the energy storage system power, and η ES is the energy storage system loss rate.

[0025] In a preferred embodiment, the calculation method of the additional power consumption caused by the operation of the system auxiliary equipment is as follows:

[0026]

[0027] Among them, P FIC_loss_n is the power consumed by the FIC auxiliary equipment; P ES_loss is the power consumed by the energy storage system auxiliary equipment.

[0028] In a preferred embodiment, the constraint conditions for parallel operation of the transformer substation area include:

[0029] (1) DC side power constraint:

[0030]

[0031] Among them, P ES_loss is the power consumed by the energy storage system auxiliary equipment;

[0032] (2) FIC power constraint:

[0033] |P FIC_n (t)| ≤ P FIC_max (7)

[0034] Among them, P FIC_max is the maximum operating power of the FIC;

[0035] (3) Energy storage system power constraint:

[0036]

[0037] Among them, P ES_chr_lim 、P ES_dis_lim are the charging and discharging power limits obtained from the energy storage battery management system respectively;

[0038] (4) Energy storage battery state of charge SOC constraint:

[0039] SOC min ≤ SOC(t) ≤ SOC max (9)

[0040] Among them, SOC min 、SOC max are the minimum and maximum limits of the energy storage battery respectively.

[0041] Compared with the prior art, the present invention has the following beneficial effects: 1) A method for optimizing the parallel operation of a distribution area is proposed. According to different working periods of distribution transformers in the distribution area, considering the losses of distribution transformers, AC lines, DC lines, auxiliary equipment, etc., the power outputs of flexible converters and energy storage systems are optimized based on the particle swarm algorithm to minimize the losses in the parallel operation of the distribution area, which has obvious executability and economic benefits. 2) Improve the parallel operation efficiency of the distribution area. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 Schematic diagram of a typical configuration of a distribution area applicable to the method proposed in the preferred embodiment of the present invention;

[0043] Figure 2 Schematic diagram of the optimization operation algorithm flow for the parallel operation of a distribution area in the preferred embodiment of the present invention.

[0044] Figure 3 Comparison of power curves before and after optimization of Distribution Area 1 in the preferred embodiment of the present invention;

[0045] Figure 4 Comparison of power curves before and after optimization of Distribution Area 2 in the preferred embodiment of the present invention;

[0046] Figure 5 Comparison of power curves before and after optimization of Distribution Area 3 in the preferred embodiment of the present invention;

[0047] Figure 6 Comparison of losses of parallel distribution areas before and after optimization in the preferred embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0048] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0049] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0050] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application; as used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0051] A method for optimizing the parallel operation of a distribution area, as Figure 1As shown in the figure, it is a typical configuration diagram of two adjacent substations operating in parallel for the method proposed in the embodiment of the present invention, including intelligent distribution transformer terminals, energy management systems, flexible inverters FIC, energy storage systems, etc. The intelligent distribution transformer terminal collects the power of the distribution transformer, and the energy management system controls the power of the flexible inverter FIC and the energy storage system. The parallel optimization operation algorithm of the substation is deployed in the energy management system.

[0052] Figure 2 It is an optimization operation algorithm for the parallel operation of a substation in the present invention. The algorithm steps include

[0053] Step S1: Select the power P of the distribution transformer of the substation Ti During the working period, set the power P of the FIC FICi and the power P of the energy storage system ES as particles, and initialize the particle positions and velocities;

[0054] Step S2: Calculate the fitness of the particles with the goal of minimizing the operation loss of the entire system;

[0055] Step S3: Obtain the individual optimal value of the particles and the global optimal value of the population;

[0056] Step S4: Update the particle velocities and positions;

[0057] Step S5: Determine whether the maximum number of iterations has been reached;

[0058] Step S6: Screen the operation mode with smaller system loss, and record the optimal power output of the FIC and the energy storage system.

[0059] Step S7: Determine whether the calculation of the optimal power output of the FIC and the energy storage system for all working periods of the power P of the distribution transformer of the substation has been completed. Otherwise, repeat steps S1 to S6. Ti

[0060] The objective function of the parallel operation optimization of the substation proposed in the present invention is:

[0061] minF = W T (t) + W line (t) + W ec (t) + W ex (t) (1);

[0062] Among them, W T (t) is the loss power of the distribution transformer; W 1ine (t) is the line loss power; W ec (t) is the power conversion loss power, including the power conversion loss power of the FIC and the energy storage system; W ex (t) is the additional loss power caused by the operation of the system auxiliary equipment; t is the system operation time.

[0063] The calculation method of the power loss of the distribution transformer is as follows:

[0064]

[0065] Among them, P T_n is the power of the distribution transformer in substation area n; η T_n is the operating loss rate of the distribution transformer in substation area n.

[0066] The calculation method of the line loss power is as follows:

[0067]

[0068] Among them, P ACline_n is the AC line power between the FIC and substation area n, and η ACline_n is the AC line loss rate between the FIC and substation area n; P DCline_n is the DC line power between the FICs, and η DCline_n is the DC line loss rate between the FICs.

[0069] The calculation method of the power loss of the power conversion is as follows:

[0070]

[0071] Among them, P FIC_n is the FIC power, and η FIC_n is the FIC loss rate; P ES is the power of the energy storage system, and η ES is the loss rate of the energy storage system.

[0072] The calculation method of the additional power loss caused by the operation of the system auxiliary equipment is as follows:

[0073]

[0074] Among them, P FIC_loss_n is the power consumed by the FIC auxiliary equipment; P ES_loss is the power consumed by the energy storage system auxiliary equipment.

[0075] The constraint conditions for the parallel operation of the substations include:

[0076] (1) DC side power constraint:

[0077]

[0078] Among them, P ES_loss is the power consumed by the energy storage system auxiliary equipment.

[0079] (2) FIC power constraint:

[0080] |P FIC_n (t)| ≤ PFIC_max (7)

[0081] Among them, P FIC_max is the maximum operating power of FIC.

[0082] (3) Energy storage system power constraint:

[0083]

[0084] Among them, P ES_chr_lim , P ES_chr_lim are the charging and discharging power limits obtained from the energy storage battery management system respectively.

[0085] (4) Energy storage battery state of charge (SOC) constraint:

[0086] SOC min ≤SOC(t)≤SOC ma (9)

[0087] Among them, SOC min , SOC max are the minimum and maximum limits of the energy storage battery respectively.

[0088] Figures 3 - 6 This is the optimized operation result of the parallel operation of the power distribution area in the embodiment of the present invention. After the optimized operation algorithm proposed by the present invention, compared with before optimization, the loss of the parallel operation of the power distribution area is reduced by 6.2%.

[0089] The above is the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications are also regarded as the protection scope of the present invention.

[0090] This patent is not limited to the above best embodiment. Anyone can obtain other various forms of voltage adjustment methods for the photovoltaic connection point in the power distribution area under the inspiration of this patent. All equal changes and modifications made according to the scope of the patent application of the present invention shall fall within the scope covered by this patent.

Claims

1. An optimization method for parallel operation of a transformer substation area, characterized in that, The parallel operation of transformer areas is achieved through DC interconnection. The hardware device includes an intelligent distribution transformer terminal, an energy management system, a flexible inverter converter FIC, and an energy storage system. The intelligent distribution transformer terminal collects the power of the distribution transformer, and the energy management system controls the power of the flexible inverter converter FIC and the energy storage system. The parallel operation optimization algorithm of the transformer area is deployed in the energy management system; Use the particle swarm optimization algorithm to optimize the power P of distribution transformers in different substations Ti , the power of the flexible converter FIC and the energy storage system during the working period, where i is the number of substations operating in parallel, to minimize the parallel operation loss of the substations, including the following steps: Step S1: Select the power P of the distribution transformer in the substation area Ti During the working period, set the power P of the flexible current converter FIC FICi and the power P of the energy storage system ES as particles, and initialize the particle positions and velocities; Step S2: Calculate the fitness of the particle with the goal of minimizing the operation loss of the entire system; Step S3: Obtain the individual optimal value of the particle and the global optimal value of the population; Step S4: Update the particle velocity and position; Step S5: Determine whether the maximum number of iterations is reached; Step S6: Screen the operation mode with smaller system loss and record the optimal power output of the flexible inverter converter FIC and the energy storage system; Step S7: Determine whether the optimal power output calculations of the flexible converter FIC and the energy storage system for all substation distribution transformers during the Ti working period have been completed. If not, repeat steps S1 to S6; The objective function for the parallel operation optimization of the transformer area is as follows: min F=W T (t)+W line (t)+W ec (t)+W ex (t) (1); Among them, W T (t) is the loss power of the distribution transformer; W line (t) is the line loss power; W ec (t) is the power conversion loss power, including the power conversion loss power of the flexible converter FIC and the energy storage system; W ex (t) is the additional loss power caused by the operation of the system auxiliary equipment; t is the system operation time; The calculation method of the power loss of the distribution transformer is as follows: Among them, P T_n is the power of the distribution transformer in substation area n; η T_n is the operating loss rate of the distribution transformer in substation area n; N is the number of substation areas operating in parallel; The calculation method of the line loss power is as follows: Among them, P ACline_n is the AC line power between the FIC and the nth transformer substation area, and η ACline_n is the AC line loss rate between the FIC and the nth transformer substation area; P DCline_n is the DC line power between the FICs, and η DCline_n is the DC line loss rate between the FICs; The calculation method of the power loss of the power conversion is as follows: Among them, P FIC_n is the FIC power, η FIC_n is the FIC loss rate; PES is the energy storage system power, and ηES is the energy storage system loss rate.

2. The optimized method for parallel operation of a transformer substation area according to claim 1, wherein The calculation method of the additional power loss caused by the operation of the system auxiliary equipment is as follows: Among them, P FIC_loss_n is the power consumption of the FIC auxiliary equipment; PES_loss is the power consumption of the energy storage system auxiliary equipment.

3. The optimization method for parallel operation of a transformer substation area according to claim 1, characterized in that The constraint conditions for the parallel operation of the transformer area include: (1) DC side power constraint: Among them, PFIC_loss_n is the power consumed by the FIC auxiliary equipment; PES_loss is the power consumed by the energy storage system auxiliary equipment; (2) FIC power constraint: |P FIC_n (t)|≤P FIC_max (7) Among them, P FIC_max is the maximum operating power of FIC; (3) Energy storage system power constraint: Among them, P ES_chr_lim is the charging power limit obtained from the energy storage battery management system, and P ES_dis_lim is the discharging power limit obtained from the energy storage battery management system; (4) State of charge SOC constraint of the energy storage battery: SOC min ≤SOC(t)≤SOC max (9) Among them, SOC min is the minimum limit value of the energy storage battery, and SOC max is the maximum limit value of the energy storage battery.

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