Intelligent power grid distributed economic dispatching method based on event triggering

Abstract

The invention discloses a smart power grid distributed economic dispatching method based on event triggering, and belongs to the field of smart power grid energy-saving and environment-friendly economic dispatching. The method specifically comprises the steps that firstly, a distributed economic dispatching model of the smart power grid is constructed based on a precise penalty function method, then a distributed economic dispatching algorithm of the smart power grid is designed, and event triggering conditions are designed according to the algorithm; setting initial values of related parameters, and updating the output power of the generator by using a smart grid distributed economic dispatching algorithm and event triggering conditions; and finally, judging whether the auxiliary variables of the generators are consistent or not, and when the auxiliary variables of all the generators are consistent, ending the scheduling process and outputting related parameters. According to the method, rapid and economic dispatching of the intelligent power grid can be realized under the condition of supply and demand balance constraint conditions of the total output power of the generator and upper and lower limit constraint conditions of the output power of the generator, unnecessary communication is reduced, and network resources are saved.

Description

Technical Field

[0001] The present invention belongs to the field of energy - saving, environmental - protection and economic dispatching of smart grids, and in particular, to a distributed economic dispatching method for smart grids based on event - triggering. Background Art

[0003] In the practical industrial application of smart grids, the first thing to consider is stable and economic operation, which leads to a classic problem in the field of smart grids - the economic dispatching problem. A smart grid consists of a variety of different power generation devices, and the power generation characteristics and inherent parameters of different power generation devices are not the same. At the same time, the power generation process also needs to consider the cost factors of power generation resources in different regions. Therefore, the economic dispatching of a smart grid refers to minimizing the total power generation cost of the smart grid under the constraints of the supply - demand balance of the total output power of generators and the upper and lower limits of the output power of generators, thereby improving the economic benefits of the smart grid.

[0004] The economic dispatching of smart grids is crucial for ensuring the stable operation of power systems, improving power generation efficiency and reducing operating costs. With the popularization of distributed energy resources, traditional centralized dispatching methods gradually show limitations in dealing with complex dynamic environments and large - scale distributed units. Therefore, exploring more efficient, flexible and economic distributed economic dispatching algorithms has become the key to improving the performance of smart grids. Traditional consensus algorithms usually require continuous communication to maintain system synchronization and coordination, which not only increases the burden on the communication network, but also raises communication costs and reduces the economy of the system. Although theoretically, continuous periodic sampling has significant advantages, in actual operation, continuous sampling and communication will waste resources and increase the operating cost of the system. To solve this problem, the event - triggering mechanism has emerged. This mechanism changes traditional continuous - cycle sampling to aperiodic sampling, and only updates information and activates the controller when specific conditions (such as system state or output exceeding a preset threshold) occur. This method can greatly reduce unnecessary communication, save computing resources, and at the same time ensure that the system performance is not affected. The event - triggering mechanism not only reduces communication costs, but also improves the response speed and reliability of the system, making it more suitable for application in actual smart grid environments. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a distributed economic dispatching method for smart grids based on event - triggering in view of the defects of the above - mentioned existing technologies.

[0006] The present invention is implemented as follows: A distributed economic dispatching method for smart grids based on event - triggering includes the following steps:

[0007] Step S1: Construct a distributed economic dispatching model for smart grids based on the exact penalty function method;

[0008] Step S2: Design a distributed economic dispatch algorithm for the smart grid and design event trigger conditions accordingly;

[0009] Step S3: Set the initial output power of each generator and the initial values of the auxiliary variables of each generator in the distributed economic dispatch algorithm of the smart grid, and calculate the initial value of the total power generation cost of the smart grid;

[0010] Step S4: Use the distributed economic dispatch algorithm and event trigger conditions of the smart grid to update the output power of the generator, and calculate the total power generation cost of the smart grid according to the output power of the generator; Determine whether the auxiliary variables of the generator reach consistency. If they reach consistency, output the output power of each generator and the total power generation cost of the smart grid, otherwise continue to execute Step S4.

[0011] Furthermore, the specific steps of Step S1 include the following steps:

[0012] Construct a distributed economic dispatch model for the smart grid based on the exact penalty function method. The model includes: the economic dispatch objective function of the smart grid and the supply-demand balance constraint condition of the total output power of the generators, which are respectively:

[0013]

[0014] where i = 1, 2,..., n; n is the number of generators in the smart grid; is the exact penalty function of c i (p i (t)), and Δ > 0 is the penalty coefficient, c i (p i (t)) is the power generation cost function of the i-th generator, and p i (t) is the output power of the i-th generator at time t; α i > 0, β i > 0 and γ i > 0 are the power generation cost coefficients of the i-th generator, is the minimum output power of the i-th generator, is the maximum output power of the i-th generator; P D is the total power demand.

[0015] Furthermore, the specific steps of Step S2 include the following steps:

[0016] Step S21: Design a distributed economic dispatch algorithm for the smart grid, specifically:

[0017]

[0018] wherein, is the derivative of the output power of the i-th generator with respect to time t; a ij is an element of the adjacency matrix A=(a ij )∈R n×n ; z i (t) is the auxiliary variable of the i-th generator at time t, is the derivative of the auxiliary variable of the i-th generator with respect to time t; is the auxiliary variable of the i-th generator at time ; is the k-th trigger time for updating the auxiliary variable of the i-th generator, is the (k + 1)-th trigger time for updating the auxiliary variable of the i-th generator; is the measurement error of the auxiliary variable of the i-th generator; b 1 and b 2 are positive constants; is the generalized gradient of the exact penalty function , which is defined as follows:

[0019]

[0020] wherein, is the gradient of the power generation cost function c i (p i (t)) of the i-th generator at p i (t);

[0021] Step S22: Design an event trigger condition according to the distributed economic dispatch algorithm of the smart grid, specifically:

[0022]

[0023] wherein, the trigger function d 1 and d 2 are positive constants; σ>0 is the event trigger threshold; inf is the lower bound; when f i (t) of the i-th generator > σ, the event trigger condition is satisfied, and let when f i (t) of the i-th generator ≤ σ, the event trigger condition is not satisfied, and the auxiliary variable of the generator remains unchanged.

[0024] Furthermore, the specific steps of the said step S3 include the following steps:

[0025] The initial value of the output power of the i-th generator is set to p i (0), and it satisfies The initial value of the auxiliary variable of the i-th generator is set to z i (0);

[0026] The initial value of the total power generation cost of the smart grid is:

[0027]

[0028] Furthermore, the conditions for calculating the total power generation cost of the smart grid and determining whether the auxiliary variables of the generators reach consistency in step S4 are specifically as follows:

[0029] Calculating the total power generation cost of the smart grid according to the output power of the generator is specifically as follows:

[0030]

[0031] The conditions for determining whether the auxiliary variables of the generators reach consistency are specifically as follows:

[0032] max i,j；i≠j |z i (t) - z j (t)| ≤ θ

[0033] where θ > 0 is the convergence coefficient of the auxiliary variable.

[0034] The present invention provides an event-triggered distributed economic dispatch method for smart grids. Compared with the prior art, the beneficial effects of the present invention are as follows:

[0035] 1. The present invention constructs a distributed economic dispatch model by introducing the exact penalty function method, and combines the distributed economic dispatch algorithm and event-trigger mechanism of the smart grid to achieve efficient dispatch under the constraints of the supply-demand balance of the total output power of the generators and the upper and lower limits of the output power of the generators. This method not only ensures the stability of the system operation, but also accelerates the convergence speed in the dispatch process, making the power distribution more rapid and accurate, and helping to improve the response efficiency and service quality of the entire smart grid.

[0036] 2. The event-trigger mechanism adopted by the present invention only updates the output power of the generator when necessary, reducing unnecessary communication times. This not only reduces the demand for network bandwidth, saves valuable network resources, but also indirectly reduces the operating cost and improves the energy efficiency ratio of the system, which is particularly important for large-scale smart grids.

[0037] 3. The present invention particularly emphasizes considering energy conservation and environmental protection factors while meeting power demands. By optimizing the output power configuration of the generating units, it is possible to minimize energy consumption on the premise of ensuring the reliability of power supply. This economic dispatch strategy is of positive significance for promoting the application of renewable energy and reducing dependence on traditional fossil fuels, and is in line with the current global trend of green energy development. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a flowchart of the event-triggered intelligent grid distributed economic dispatch method of the present invention;

[0039] Figure 2 is the IEEE 24-node standard power network of the present invention;

[0040] Figure 3 is the communication topology diagram of each generator of the present invention;

[0041] Figure 4 is the graph of the output power p i (t) of each generator of the present invention changing with time;

[0042] Figure 5 is the total output power of the generators of the present invention changing with time;

[0043] Figure 6 is the total power generation cost of the present invention changing with time;

[0044] Figure 7 is the graph of the auxiliary variable z i (t) of each generator of the present invention changing with time;

[0045] Figure 8 is the graph of the event trigger moments of each generator of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0047] Example 1:

[0048] The flow of the event-triggered intelligent grid distributed economic dispatch method provided in this example is as Figure 1 shown and specifically includes the following steps:

[0049] Step S1: Construct a distributed economic dispatch model for the smart grid based on the exact penalty function method;

[0050] Step S2: Design a distributed economic dispatch algorithm for the smart grid and design an event trigger condition accordingly;

[0051] Step S3: Set the initial output power of each generator and the initial values of the auxiliary variables of each generator in the distributed economic dispatch algorithm of the smart grid, and calculate the initial value of the total power generation cost of the smart grid;

[0052] Step S4: Use the distributed economic dispatch algorithm and event trigger condition of the smart grid to update the output power of the generator, and calculate the total power generation cost of the smart grid according to the output power of the generator; Determine whether the auxiliary variables of the generator reach consistency. If they reach consistency, output the output power of each generator and the total power generation cost of the smart grid, otherwise continue to execute Step S4.

[0053] In this embodiment, the Step S1 constructs a distributed economic dispatch model for the smart grid based on the exact penalty function method, specifically:

[0054] Construct a distributed economic dispatch model for the smart grid based on the exact penalty function method. The model includes: the economic dispatch objective function of the smart grid and the supply-demand balance constraint condition of the total output power of the generators, which are respectively:

[0055]

[0056] where i = 1, 2,..., n; n is the number of generators in the smart grid; is the exact penalty function of c i (p i (t)), and Δ > 0 is the penalty coefficient, c i (p i (t)) is the power generation cost function of the i-th generator, and p i (t) is the output power of the i-th generator at time t; α i > 0, β i > 0 and γ i > 0 are the power generation cost coefficients of the i-th generator, is the minimum output power of the i-th generator, is the maximum output power of the i-th generator; P D is the total power demand.

[0057] In this embodiment, the Step S2 designs a distributed economic dispatch algorithm for the smart grid and designs an event trigger condition accordingly, specifically including the following steps:

[0058] Step S21: Design a distributed economic dispatch algorithm for the smart grid, specifically as follows:

[0059]

[0060] where, is the derivative of the output power of the i-th generator with respect to time t; a ij is an element of the adjacency matrix A = (a ij ) ∈ R n×n of the generator communication topology; z i (t) is the auxiliary variable of the i-th generator at time t, is the derivative of the auxiliary variable of the i-th generator with respect to time t; is the auxiliary variable of the i-th generator at time , is the k-th trigger time for the i-th generator to update the auxiliary variable, is the (k + 1)-th trigger time for the i-th generator to update the auxiliary variable; is the measurement error of the auxiliary variable of the i-th generator; b 1 and b 2 are positive constants; is the generalized gradient of the exact penalty function , defined as follows:

[0061]

[0062] where, is the gradient of the power generation cost function c i (p i (t)) of the i-th generator at p i (t);

[0063] The communication topology graph of the smart grid with n generators can be represented by a graph G = {V, ε, A}, where V = {1, 2,..., n}, ε ∈ V × V, and represent the node set, edge set, and adjacency matrix of the graph, respectively; e ij = (i, j) indicates that i and j are adjacent nodes and they can exchange information with each other; if (i, j) ∈ ε, then a ij = 1, otherwise a ij = 0;

[0064] Step S22: Design an event trigger condition according to the distributed economic dispatch algorithm of the smart grid, specifically as follows:

[0065]

[0066] where the trigger function d1 and d 2 are normal constants; σ > 0 is the event-triggering threshold; inf is the lower bound; when the f of the i-th generator i (t) > σ, the event-triggering condition is satisfied, and let when the f of the i-th generator i (t) ≤ σ, the event-triggering condition is not satisfied, and the auxiliary variable of the generator remains unchanged.

[0067] In this embodiment, the step S3 specifically includes the following steps:

[0068] The initial value of the output power of the i-th generator is set to p i (0), and it satisfies The initial value of the auxiliary variable of the i-th generator is set to z i (0);

[0069] The initial value of the total power generation cost of the smart grid is:

[0070]

[0071] In this embodiment, the step S4 uses the smart grid distributed economic dispatch algorithm and the event-triggering condition to update the output power of the generator, and calculates the total power generation cost of the smart grid according to the output power of the generator; determines whether the auxiliary variables of the generators reach consistency. If they reach consistency, the output power of each generator and the total power generation cost of the smart grid are output. Otherwise, step S4 is continued; the conditions for calculating the total power generation cost of the smart grid and determining whether the auxiliary variables of the generators reach consistency in S4 are specifically:

[0072] Calculating the total power generation cost of the smart grid according to the output power of the generator is specifically:

[0073]

[0074] The condition for determining whether the auxiliary variables of the generators reach consistency is specifically:

[0075] max i,j；i≠j |z i (t) - z j (t)| ≤ θ

[0076] where θ > 0 is the convergence coefficient of the auxiliary variable.

[0077] Embodiment 2:

[0078] Embodiment 2 uses the proposed event-triggered smart grid distributed economic dispatch method to perform numerical simulation on the IEEE 24-node standard power network. There are 10 generators in total, Figure 2It is the IEEE 24-node standard power network, and its communication topology of each generator is as Figure 3 shown.

[0079] Set the initial values of the output powers of each generator and the initial values of the auxiliary variables of each generator in the distributed economic dispatch algorithm of the smart grid, and calculate the initial value of the total power generation cost of the smart grid;

[0080] The power generation cost functions of the generators in the smart grid are all c i (p i (t)) = α i p i 2 + β i p i + γ i . Table 1 shows the values of the power generation cost coefficients α i , β i , γ i and the upper and lower limits of the generator output powers; the initial values of the output powers of each generator are set to p 1 (0) = 700 MW, p 2 (0) = 150 MW, p 3 (0) = 200 MW, p 4 (0) = 400 MW, p 5 (0) = 450 MW, p 6 (0) = 200 MW, p 7 (0) = 300 MW, p 8 (0) = 350 MW, p 9 (0) = 450 MW and p 10 (0) = 100 MW. The initial values of the auxiliary variables of each generator in the distributed economic dispatch algorithm of the smart grid are set to z 1 (0) = z 2 (0) = z 3 (0) = z 4 (0) = z 5 (0) = z 6 (0) = z 7 (0) = z 8 (0) = z 9 (0) = z 10 (0) = 0. The total power demand P D = 3300 MW. Calculate the initial value of the total power generation cost of the smart grid by the formula to be The penalty coefficient is set to Δ = 0.5, and the system parameters are set to b 1 = 0.5, b 2 = 0.5, d 1 = 0.005, d 2= 0.001, the event trigger threshold is set to σ = 0.003, and the convergence coefficient of the auxiliary variable is set to θ = 0.001; according to the communication topology, the adjacency matrix A is obtained as follows:

[0081]

[0082] Table 1

[0083]

[0084] When the f i (t) of the i-th generator > σ, the event trigger condition is satisfied, and let When the f i (t) of the i-th generator ≤ σ, the event trigger condition is not satisfied, and the auxiliary variable of the generator remains unchanged; the total power generation cost of the smart grid is calculated according to the output power of the generator as Judge whether the auxiliary variables of the generators reach consistency. If they reach consistency, output the output power of each generator, the total power generation power of the smart grid, and the incremental cost of each generator. Otherwise, continue to execute step S4. The condition for the auxiliary variables of the generators to reach consistency is: max i,j；i≠j |z i (t) - z j (t)| ≤ θ.

[0085] Finally, based on the given data, the effectiveness of the present invention is verified through numerical simulation. Figure 4 For the output power p i (t) of each generator of the present invention versus time graph, from Figure 4 it can be seen that at the convergence time t = 24.8 s, the optimal values of the generator output powers are respectively p 1 (t) = 257.41 MW, p 2 (t) = 284.16 MW, p 3 (t) = 352.02 MW, p 4 (t) = 302.81 MW, p 5 (t) = 336.09 MW, p 6 (t) = 257.45 MW, p 7 (t) = 352.00 MW, p 8 (t) = 351.28 MW, p 9 (t) = 283.74 MW and p 10 (t) = 523.02 MW, satisfying the upper and lower limit constraint conditions of the generator output power; Figure 5 For the total output power of the generator of the present invention versus time graph, from Figure 5It can be seen that the total output power of the generator does not change with time and meets the supply-demand balance constraint condition of the total output power of the generator; Figure 6 is the total power generation cost of the present invention The graph of the change with time, from Figure 6 it can be seen that the total power generation cost gradually decreases from the initial 105453$ to 76706$, achieving the goal of minimizing the total power generation cost of the smart grid; Figure 7 is the graph of the change with time of the auxiliary variable z i (t) of each generator of the present invention. From Figure 7 it can be seen that at the convergence time t = 24.8s, the values of the auxiliary variables of each generator converge to -86.58; Figure 8 is the graph of the event trigger moment of each generator of the present invention.

[0086] It should be noted that the above are only the preferred examples of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A distributed economic dispatching method for smart grid based on event triggering, characterized in that: The following steps are involved: Step S1: construct a distributed economic dispatch model for smart grid based on the exact penalty function method; Step S2: Design a distributed economic dispatch algorithm for smart grid and design event triggering conditions accordingly; Step S3: setting the initial value of the output power of each generator and the initial value of the auxiliary variable of each generator in the distributed economic dispatch algorithm of the smart grid, and calculating the initial value of the total power generation cost of the smart grid; Step S4: Use the smart grid distributed economic dispatch algorithm and event triggering conditions to update the output power of the generator, and calculate the total power generation cost of the smart grid based on the output power of the generator; determine whether the auxiliary variables of the generator are consistent, if they are consistent, output the output power of each generator and the total power generation cost of the smart grid, otherwise continue to execute step S4.

2. The event-triggered distributed economic dispatching method for smart grid according to claim 1, characterized in that: The step S1 specifically includes the following steps: Based on the exact penalty function method, a distributed economic dispatch model of smart grid is constructed. The model includes: the economic dispatch objective function of the smart grid and the supply and demand balance constraints of the total output power of the generator, which are: Where, i = 1, 2, ..., n; n is the number of generators in the smart grid; c i (p i (t)), and Δ>0 is the penalty coefficient, c i (p i (t)) is the power generation cost function of the i-th generator, and p i (t) is the output power of the i-th generator at time t; α i >0, β i >0 and γ i >0 is the power generation cost coefficient of the i-th generator, is the minimum output power of the i-th generator, is the maximum output power of the i-th generator; P D is the total power demand.

3. The event-triggered distributed economic dispatching method for smart grid according to claim 2, characterized in that: The step S2 specifically includes the following steps: Step S21: Design a distributed economic dispatch algorithm for smart grid, specifically: in, is the derivative of the output power of the i-th generator with respect to time t; a ij is the adjacency matrix A of the generator communication topology = (a ij )∈R n×n The element of i (t) is the auxiliary variable of the i-th generator at time t, is the derivative of the auxiliary variable of the i-th generator with respect to time t; is the i-th generator at time Auxiliary variables, Update the kth triggering time of the auxiliary variable for the i-th generator, Update the k+1th triggering time of the auxiliary variable for the i-th generator; is the measurement error of the auxiliary variable of the i-th generator; b1 and b2 are positive constants; is the exact penalty function The generalized gradient of is defined as follows: in, is the power generation cost function c of the i-th generator i (p i (t)) in p i The gradient at (t); Step S22: Design event triggering conditions according to the smart grid distributed economic dispatch algorithm, specifically: Among them, the trigger function d1 and d2 are positive constants; σ>0 is the event triggering threshold; inf is the lower bound; when the f of the i-th generator i When (t)>σ, the event triggering condition is met, let When the f of the i-th generator i When (t)≤σ, the event triggering condition is not met and the auxiliary variables of the generator remain unchanged.

4. The event-triggered distributed economic dispatching method for smart grid according to claim 3 is characterized in that: The step S3 specifically comprises the following steps: The initial value of the output power of the i-th generator is set to p i (0), and satisfies The initial value of the auxiliary variable of the i-th generator is set to z i (0); The initial value of the total power generation cost of the smart grid is:

5. The event-triggered distributed economic dispatching method for smart grid according to claim 4, characterized in that: In step S4, the conditions for calculating the total power generation cost of the smart grid according to the output power of the generator and judging whether the auxiliary variables of the generator have reached consistency are specifically: The total power generation cost of the smart grid is calculated based on the output power of the generator, which is: The conditions for judging whether the auxiliary variables of the generator have reached consistency are as follows: max i,j；i≠j |z i (t)-z j (t)|≤θ Among them, θ>0 is the auxiliary variable convergence coefficient.

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