A Production Scheduling Method Supporting Peak Shaving Power Demand Response
A technology for power demand response and production scheduling, applied in data processing applications, instruments, calculations, etc., can solve problems such as poor convergence ability of the solution algorithm, great difficulty in solving, weak optimization ability, etc., and achieve the effect of good convergence ability
Active Publication Date: 2022-04-19
GUANGDONG UNIV OF TECH
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Problems solved by technology
Theoretically, this problem is a complex combinatorial optimization problem, which is difficult to solve, and commonly used solving algorithms generally have the disadvantages of poor convergence ability and weak optimization ability
Method used
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Embodiment 1
[0075] Such as figure 1 As shown, the present invention provides a production scheduling method that supports peak-shaving power demand response, including the following steps:
[0076] S1: Establish a production scheduling mathematical model that supports peak-shaving power demand response;
[0077] In step S1, the established mathematical model is:
[0078]
[0079]
[0080]
[0081]
[0082] e ij =s ij +t ij ,i=1,2,...,n,j=1,2,...,S (5)
[0083] e ij +t b ≤s i(j+1) ,i=1,2,...,n,j=1,2,...,S-1 (6)
[0084]
[0085]
[0086]
[0087] Such as Figure 4 Shown, where n represents the number of workpieces; such as Figure 5 Shown, J i Indicates the workpiece number, i=1,2,...,n; S is the number of processes of the workpiece; for J i The processing load of the jth process at time t; s ij for J i The start processing time of the jth process; e ij for workpiece J i The processing completion time of the jth process; T s is the start time of dema...
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The invention relates to the field of production scheduling, and more specifically, to a production scheduling method supporting peak-shaving power demand response. Establish a mathematical model of production scheduling that supports peak-shaving power demand response; initialize parameters, and randomly generate N initial gray wolf populations to obtain a set N(t); calculate the fitness value of each gray wolf in N(t); The first three gray wolves with the best fitness are recorded as α, β, δ, and the other gray wolves are recorded as ω; use α, β, and δ wolves to collaboratively update the positions of other ω wolves to obtain the set U(t); global particle information Update the wolf group N(t) to get the set V(t); use the best gray wolf, the worst gray wolf and a random gray wolf in the set {N(t)∪U(t)∪V(t)} The mutation search strategy obtains the set W(t); calculates the global optimal gray wolf position X b and the optimal fitness value f b ; Determine whether the end condition is met. The production scheduling method proposed by the invention has good convergence ability, global optimization ability and practicability, and can effectively support the implementation of power demand response projects.
Description
technical field [0001] The invention relates to the field of production scheduling, and more specifically, to a production scheduling method supporting peak-shaving power demand response. Background technique [0002] With the development of smart grid, power demand response has become the core technology to maintain the balance between supply and demand of power grid. Power demand response refers to the behavior of power users in the power market to change their normal power consumption patterns by responding to time-varying prices or incentive rewards. Industrial users have the advantages of large power consumption, strong stability, and high intelligence, and are very important demand response resources. Peak-shaving power demand response is a demand response method commonly used by industrial users. During the peak period of the power grid, industrial users can reduce the production load during the peak period by reducing production tasks, thereby supporting the implem...
Claims
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IPC IPC(8): G06Q10/06G06Q50/06
CPCG06Q10/0631G06Q50/06
Inventor 蔡延光黄何列蔡颢
Owner GUANGDONG UNIV OF TECH