Generator Set Load Balancing Control Using the Knapsack Algorithm

Abstract

The factory test and maintenance of the generator set are essential for ensuring that the generator runs smoothly. A generator test is frequently required to determine the generator set's rated capacity. A range of test loads must be varied to fulfil the test criteria during the test. Traditional load switching systems are inefficient, simple to misuse, and use load resources imbalanced. Because of these issues, this study provides a solution for load matching and balancing control of generator unit tests based on the knapsack algorithm. Combining the knapsack problem model with multiple combinatorial optimization algorithms allows for simulated comparison and analysis. In the actual test, the optimal control technique obtained is compared to the traditional approach. The results reveal that the knapsack algorithm, which is based on a combination of the knapsack problem model and the discrete binary particle swarm algorithm, can more accurately match and apply the test load, successfully overcoming the old technique's issues causes. Simultaneously, test efficiency is enhanced, and the whole test load's service life is extended.