Fig. 3
From: Predicting key features of a substation without monitoring
The genetic algorithm assigns Smart Meter profiles randomly to households on a substation. This is done several times to create several ‘populations’. Each population is assessed according to a fitness function. Pairs of populations ‘crossover’ according to fitness (the two most fit, followed by the next fittest pair and so on). The ‘crossover’ means that from the two Smart Meter profiles assigned to a single house from the two populations, one profile is chosen at random. Applying this process for each household on a substation gives a new population. To avoid converging to a local optimum, each household has a small probability of being replaced with any of the Smart Meter profiles available. The new populations are assessed according the fitness function, and the process is iterated