Microgrid economic dispatch method based on Lambert W function distributed consensus algorithm

Abstract

The present invention belongs to the field of renewable energy power generation, and specifically relates to a microgrid economic dispatch method based on the Lambert W function distributed consistency algorithm. The method realizes communication and coordination between generator nodes in a microgrid through distributed computing technology, while taking into account pollutant gas emissions, thereby improving the practicality of the economic dispatch method. The present invention can monitor the mismatch between power demand and generator power output in real time, and update the output power of the generator in real time. In addition, the present invention has plug-and-play capabilities, effectively optimizes the operating cost and reliability of the microgrid, and improves the management and operation efficiency of the microgrid.

Description

Technical Field

[0001] The present invention belongs to the field of renewable energy power generation, and in particular to a microgrid economic dispatching method based on a Lambert W function distributed consistency algorithm. Background Art

[0002] In modern power systems, economic dispatch is an important research direction, which aims to meet power demand at the lowest cost by optimizing the operation strategy of generator sets. Traditional economic dispatch methods mainly rely on centralized control systems. Although these methods are effective, they have high computing and communication costs, as well as the risk of single point failure. These shortcomings become more obvious when facing large-scale distributed power generation systems.

[0003] To solve the economic dispatch problem, centralized economic dispatch algorithms were initially used, such as genetic algorithms, particle swarm optimization, evolutionary programming, differential evolution, and simulated annealing. These centralized economic dispatch algorithms rely on a powerful central controller to collect global information in order to process large amounts of data, and require large amounts of storage capacity and fast operating rates. However, this results in centralized economic dispatch algorithms being costly and prone to single point failures. In addition, they lack robustness, and when generators and loads need to be added or removed from the microgrid, the entire system needs to be rebuilt.

[0004] With the development of microgrid technology, distributed power generation systems have gradually become an important way of power supply. Microgrids use advanced information and communication technologies, as well as intelligent control methods, to achieve real-time monitoring, precise control, and intelligent scheduling of power systems. Distributed power generation systems have higher robustness and scalability, and can better adapt to dynamically changing power demands.

[0005] However, existing distributed economic dispatch methods still face many challenges in practical applications. Traditional methods usually assume that global information can be obtained, which is difficult to achieve in actual operation, especially when the generator sets and loads change dynamically. In addition, pollutant gas emissions are also an important factor affecting economic dispatch optimization. How to consider pollutant gas emissions in a distributed environment to achieve optimal dispatch is a key issue. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a microgrid economic dispatching method based on the Lambert W function distributed consensus algorithm in view of the defects of the above-mentioned prior art.

[0007] The present invention adopts the following scheme to implement a microgrid economic dispatch method based on the Lambert W function distributed consensus algorithm, including the following steps:

[0008] Step 1: Construct a microgrid economic dispatch problem model based on pollutant gas emissions. The model includes: the type of generators in the microgrid and their output power costs; the objective function of the economic dispatch problem; the supply and demand balance constraints of the generator output power and the limit constraints of the generator output power;

[0009] Step 2: Determine the matrix θ using the Metropolis method based on the communication topology of the microgrid;

[0010] Step 3: Initialize the relevant parameters required by the algorithm;

[0011] Step 4: The distributed algorithm for economic dispatch problem based on Lambert W function dynamically calculates the incremental cost of each generator, the output power of each generator and the output power mismatch of each generator;

[0012] Step 5: Check the output power of all generators. If the output power of any generator does not meet the predetermined output power constraint condition, process its output power;

[0013] Step 6: Determine whether the supply and demand balance constraint of the generator output power is met; if so, output the optimal incremental cost and the optimal generator output power; if not, return to step 4.

[0014] Furthermore, the step 1 is specifically as follows:

[0015] The types of generators in microgrids include fuel energy generators and renewable energy generators;

[0016] The output power cost of the generator in the microgrid is:

[0017]

[0018] Where i = 1, 2, ..., n; n is the number of generators in the microgrid; k is the number of iterations; is the output power cost of the kth iteration generator under the condition of considering the emission of polluting gases; p i(k) is the output power of the i-th generator at the k-th iteration; α i , β i , γ i , l i and δ i K is the cost coefficient of the i-th generator based on the emission of polluting gases; i is the penalty parameter of the i-th generator;

[0019] The objective function of the economic dispatch problem, the supply and demand balance constraints of the generator output power, and the limit constraints of the generator output power are:

[0020]

[0021] p i_min ≤p i(k) ≤p i_max

[0022] in, is the objective function of the economic dispatch problem; is the supply and demand balance constraint of the generator output power; p i_min ≤p i(k) ≤p i_max is the constraint condition for the generator output power; p d is the total required power; p i_min is the minimum output power of the i-th generator; p i_max is the maximum output power of the i-th generator.

[0023] Furthermore, the method for determining the matrix θ using the Metropolis method in step 2 is specifically:

[0024]

[0025] Among them, θ ij Represented as the i-th row and j-th column element of matrix θ; n i and n j Respectively represent the number of generators connected to the i-th generator and the j-th generator, j∈N i , j = 1, 2, ..., n, N i represents the set of generators that communicate with the i-th generator.

[0026] Furthermore, the step three is specifically as follows:

[0027] Set the initial output power of the i-th generator to p i(0) ; The initial value of the output power mismatch of the i-th generator is D pi(0) ; The initial incremental cost of the i-th generator is At the same time, the initial value is required to meet the following requirements:

[0028]

[0029] Furthermore, the step 4 is specifically as follows:

[0030] The distributed algorithm for economic dispatch problem based on Lambert W function dynamically calculates the incremental cost of each generator, the output power of each generator and the output power mismatch of each generator; the specific calculation method is:

[0031]

[0032] in, and p i(k+1) represents the incremental cost and output power of the i-th generator at the k+1th iteration; ε is the convergence coefficient, which determines the rate at which the incremental cost converges to consistency; D pi(k) represents the output power mismatch of the i-th generator at the k-th iteration; Y i(k+1) is an auxiliary variable; W0(·) is the Lambert W function.

[0033] Furthermore, the step five is specifically as follows:

[0034] Check the output power of all generators. If the output power of any generator does not meet the preset output power constraint condition, process its output power:

[0035]

[0036] The present invention provides a microgrid economic dispatch method based on the Lambert W function distributed consensus algorithm. Compared with the prior art, the present invention has the following beneficial effects:

[0037] 1. The present invention adopts a distributed algorithm for economic dispatch problems based on the Lambert W function and distributed computing technology to avoid the risk of single point failure, improve the operating stability and reliability of the microgrid, and ensure the continuous and efficient operation of the system.

[0038] 2. The present invention comprehensively considers the emission cost of pollutant gases during the scheduling process, reduces the emission of pollutants by optimizing the output power of the generator, promotes the realization of environmental protection and energy-saving goals, and contributes to environmental protection.

[0039] 3. Since the method of the present invention does not rely on a central controller, the microgrid can also achieve the optimal solution to the economic dispatch problem when expanding new generators or adjusting the existing structure. This means that the microgrid can seamlessly connect to new generators at any time without large-scale modifications to the existing dispatch strategy, making the expansion of the microgrid easier. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flow chart of a microgrid economic dispatch method based on the Lambert W function distributed consensus algorithm of the present invention;

[0041] Figure 2 It is an IEEE 30-node standard power network;

[0042] Figure 3 A communication topology diagram of the microgrid of the present invention;

[0043] Figure 4 This is the incremental cost change diagram of the present invention without adding a generator;

[0044] Figure 5 This is a diagram showing the variation of the output power of a generator without adding a generator in the middle of the present invention;

[0045] Figure 6 This is a mismatch variation diagram without adding a generator in the middle of the present invention;

[0046] Figure 7 This is a graph showing the incremental cost change after adding a generator midway in the present invention;

[0047] Figure 8 This is a diagram showing the change in generator output power after a generator is added midway in the present invention;

[0048] Fig. 9 This is a diagram showing the mismatch change after a generator is added midway in the present invention. DETAILED DESCRIPTION

[0049] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0050] Embodiment 1:

[0051] The process of the microgrid economic dispatch method based on the Lambert W function distributed consensus algorithm provided in this embodiment is as follows: Figure 1 As shown, the following steps are included:

[0052] Step 1: Construct a microgrid economic dispatch problem model based on pollutant gas emissions. The model includes: the type of generators in the microgrid and their output power costs; the objective function of the economic dispatch problem; the supply and demand balance constraints of the generator output power and the limit constraints of the generator output power;

[0053] Step 2: Determine the matrix θ using the Metropolis method based on the communication topology of the microgrid;

[0054] Step 3: Initialize the relevant parameters required by the algorithm;

[0055] Step 4: The distributed algorithm for economic dispatch problem based on Lambert W function dynamically calculates the incremental cost of each generator, the output power of each generator and the output power mismatch of each generator;

[0056] Step 5: Check the output power of all generators. If the output power of any generator does not meet the predetermined output power constraint condition, process its output power;

[0057] Step 6: Determine whether the supply and demand balance constraint of the generator output power is met; if so, output the optimal incremental cost and the optimal generator output power; if not, return to step 4.

[0058] In this embodiment, the step 1 is specifically as follows:

[0059] The types of generators in microgrids include fuel energy generators and renewable energy generators;

[0060] The output power cost of the generator in the microgrid is:

[0061]

[0062] Where i = 1, 2, ..., n; n is the number of generators in the microgrid; k is the number of iterations; is the output power cost of the kth iteration generator under the condition of considering the emission of polluting gases; p i(k) is the output power of the i-th generator at the k-th iteration; α i , β i , γ i , l i and δ i K is the cost coefficient of the i-th generator based on the emission of polluting gases; i is the penalty parameter of the i-th generator;

[0063] The objective function of the economic dispatch problem, the supply and demand balance constraints of the generator output power, and the limit constraints of the generator output power are:

[0064]

[0065] p i_min ≤p i(k) ≤p i_max

[0066] in, is the objective function of the economic dispatch problem; is the supply and demand balance constraint of the generator output power; p i_min ≤p i(k) ≤p i_max is the constraint condition for the generator output power; p d is the total required power; p i_min is the minimum output power of the i-th generator; p i_max is the maximum output power of the i-th generator.

[0067] In this embodiment, the method for determining the matrix θ using the Metropolis method in step 2 is specifically:

[0068]

[0069] Among them, θ ij Represented as the i-th row and j-th column element of matrix θ; n i and n j Respectively represent the number of generators connected to the i-th generator and the j-th generator, j∈N i , j = 1, 2, ..., n, N i represents the set of generators that communicate with the i-th generator.

[0070] In this embodiment, the step three is specifically as follows:

[0071] Set the initial output power of the i-th generator to p i(0) ; The initial value of the output power mismatch of the i-th generator is D pi(0) ; The initial incremental cost of the i-th generator is At the same time, the initial value is required to meet the following requirements:

[0072]

[0073] In this embodiment, the step 4 is specifically as follows:

[0074] The distributed algorithm for economic dispatch problem based on Lambert W function dynamically calculates the incremental cost of each generator, the output power of each generator and the output power mismatch of each generator; the specific calculation method is:

[0075]

[0076] in, and p i(k+1) represents the incremental cost and output power of the i-th generator at the k+1th iteration; ε is the convergence coefficient, which determines the rate at which the incremental cost converges to consistency; D pi(k) represents the output power mismatch of the i-th generator at the k-th iteration; Y i(k+1) is an auxiliary variable; W0(·) is the Lambert W function.

[0077] In this embodiment, the step five is specifically as follows:

[0078] Check the output power of all generators. If the output power of any generator does not meet the preset output power constraint condition, process its output power:

[0079]

[0080] Embodiment 2:

[0081] Example 2 uses the proposed microgrid economic dispatch method based on the Lambert W function distributed consensus algorithm to perform numerical simulation on the IEEE 30-node standard power network, with a total of 6 generators. Figure 2 It is an IEEE 30-node standard power network; Figure 3 This is the communication topology diagram of the microgrid.

[0082] The specific process is described as follows:

[0083] The types of generators in microgrids include fuel energy generators and renewable energy generators;

[0084] The output power cost of the generator in the microgrid is:

[0085]

[0086] Where i = 1, 2, ..., n; n is the number of generators in the microgrid; k is the number of iterations; is the output power cost of the kth iteration generator under the condition of considering the emission of polluting gases; p i(k) is the output power of the i-th generator at the k-th iteration; α i , β i , γ i , l i and δ i K is the cost coefficient of the i-th generator based on the emission of polluting gases; i is the penalty parameter of the i-th generator;

[0087] The objective function of the economic dispatch problem, the supply and demand balance constraints of the generator output power, and the limit constraints of the generator output power are:

[0088]

[0089] p i_min ≤p i(k) ≤p i_max (2c)

[0090] Among them, (2a) is the objective function of the economic dispatch problem; (2b) is the supply and demand balance constraint of the generator output power; (2c) is the limit constraint of the generator output power; p d is the total required power; p i_min is the minimum output power of the i-th generator; p i_max is the maximum output power of the i-th generator.

[0091] According to the communication topology of the microgrid, the matrix θ is determined using the Metropolis method. The specific method for determining the matrix θ using the Metropolis method is:

[0092]

[0093] Among them, θ ij Represented as the i-th row and j-th column element of matrix θ; n i and n j Respectively represent the number of generators connected to the i-th generator and the j-th generator, j∈N i , j = 1, 2, ..., n, N i represents the set of generators that communicate with the i-th generator.

[0094] Set the initial output power of the i-th generator to p i(0) ; The initial value of the output power mismatch of the i-th generator is D pi(0) ; The initial incremental cost of the i-th generator is At the same time, the initial value is required to meet the following requirements:

[0095]

[0096] The distributed algorithm for economic dispatch problem based on Lambert W function dynamically calculates the incremental cost of each generator, the output power of each generator and the output power mismatch of each generator; the specific calculation method is:

[0097]

[0098] in, and p i(k+1) represents the incremental cost and output power of the i-th generator at the k+1th iteration; ε is the convergence coefficient, which determines the rate at which the incremental cost converges to consistency; D pi(k) represents the output power mismatch of the i-th generator at the k-th iteration; Y i(k+1) is an auxiliary variable; W0(·) is the Lambert W function.

[0099] Check the output power of all generators. If the output power of any generator does not meet the preset output power constraint condition, process its output power:

[0100]

[0101] Determine whether the supply and demand balance constraint conditions of the generator output power are met; if so, output the optimal incremental cost and the optimal generator output power; if not, return to step 4.

[0102] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0103] The relevant parameters of the generator are shown in Table 1:

[0104] Table 1

[0105]

[0106] Set the initial output power of the i-th generator to be p 1(0) =120MW, p 2(0) =130MW, p 3(0) =50MW, p 4(0) =60MW, p 5(0) =40MW, p 6(0) =100MW; the initial values ​​of the output power mismatch of the i-th generator are D p1(0) =0MW, D p2(0) =0MW, D p3(0) =0MW, D p4(0) =0MW, D p5(0) =0MW and D p6(0) =0MW; According to the communication topology of the microgrid, the matrix θ is determined using the Metropolis method as shown in formula (7). Based on the given data, this numerical simulation shows that the optimal incremental cost of all generators converges to the same value of 817.35$ / MW. In the transient response, it is noted that after generator 5 reaches the upper limit of the predetermined output power constraint at the 5th iteration, the maximum output power of the generator is maintained at 84MW and no longer increases. According to the results, the final output power of the generator is 63.38MW, 72.95MW, 82.99MW, 121.42MW, 82.99MW and 76.29MW, and the output power of all generators is within the range of the generator constraints.

[0107]

[0108] In order to verify the plug-and-play characteristics of the algorithm in the economic dispatch of microgrids, a new generator was added to the microgrid at the 70th iteration. The simulation verified that the microgrid can effectively maintain the supply and demand balance of the generator output power.

[0109] The simulation of the present invention adopts MATLAB2022a, and the computer configuration is COREi7, 2.80GHz; Figure 4 This is the incremental cost change diagram of the present invention without adding a generator; Figure 5 This is a diagram showing the variation of the output power of a generator without adding a generator in the middle of the present invention; Figure 6 This is a mismatch variation diagram without adding a generator in the middle of the present invention; Figure 7 This is a graph showing the incremental cost change after adding a generator midway in the present invention; Figure 8 This is a diagram showing the change in generator output power after a generator is added midway in the present invention; Fig. 9 This is a diagram showing the mismatch change after a generator is added midway in the present invention.

[0110] Finally, it should be noted that the above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A microgrid economic dispatch method based on Lambert W function distributed consensus algorithm, characterized in that: The following steps are involved: Step 1: Construct a microgrid economic dispatch problem model based on pollutant gas emissions. The model includes: the type of generators in the microgrid and their output power costs; the objective function of the economic dispatch problem; the supply and demand balance constraints of the generator output power and the limit constraints of the generator output power; Step 2: Determine the matrix θ using the Metropolis method based on the communication topology of the microgrid; Step 3: Initialize the relevant parameters required by the algorithm; Step 4: The distributed algorithm for economic dispatch problem based on Lambert W function dynamically calculates the incremental cost of each generator, the output power of each generator and the output power mismatch of each generator; Step 5: Check the output power of all generators. If the output power of any generator does not meet the predetermined output power constraint condition, process its output power; Step 6: Determine whether the supply and demand balance constraint condition of the generator output power is met; if so, output the optimal incremental cost and the optimal generator output power; if not, return to step 4; The step 1 is specifically as follows: The types of generators in microgrids include fuel energy generators and renewable energy generators; The output power cost of the generator in the microgrid is: Where i = 1, 2, ..., n; n is the number of generators in the microgrid; k is the number of iterations; is the output power cost of the kth iteration generator under the condition of considering the emission of polluting gases; p i(k) is the output power of the i-th generator at the k-th iteration; α i , β i , γ i , l i and δ i K is the cost coefficient of the i-th generator based on the emission of polluting gases; i is the penalty parameter of the i-th generator; The objective function of the economic dispatch problem, the supply and demand balance constraints of the generator output power, and the limit constraints of the generator output power are: p i_min ≤p i(k) ≤p i_max in, is the objective function of the economic dispatch problem; is the supply and demand balance constraint of the generator output power; p i_min ≤p i(k) ≤p i_max is the constraint condition for the generator output power; p d is the total required power; p i_min is the minimum output power of the i-th generator; p i_max is the maximum output power of the i-th generator; The method for determining the matrix θ using the Metropolis method in step 2 is specifically: Among them, θ ij Represented as the i-th row and j-th column element of matrix θ; n i and n j Respectively represent the number of generators connected to the i-th generator and the j-th generator, j∈N i , j = 1, 2, ..., n, N i represents the set of generators communicating with the i-th generator; The step three is specifically as follows: Set the initial output power of the i-th generator to p i(0) ; The initial value of the output power mismatch of the i-th generator is D pi(0) ; The initial incremental cost of the i-th generator is At the same time, the initial value is required to meet the following requirements: The step 4 is specifically as follows: The distributed algorithm for economic dispatch problem based on Lambert W function dynamically calculates the incremental cost of each generator, the output power of each generator and the output power mismatch of each generator; the specific calculation method is: in, and p i(k+1) represents the incremental cost and output power of the i-th generator at the k+1th iteration; ε is the convergence coefficient, which determines the rate at which the incremental cost converges to consistency; D pi(k) represents the output power mismatch of the i-th generator at the k-th iteration; Y i(k+1) is an auxiliary variable; W0(·) is the Lambert W function; The step five is specifically as follows: Check the output power of all generators. If the output power of any generator does not meet the preset output power constraint condition, process its output power:

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