LAUSR

Abstract Combined heat power dispatch with improved operation remains a popular preference in microgrid having uncertain and non-convex nature of the system. This research work deploys an efficient energy management system driven by a novel stochastic transitions tuned unscented Gaussian distribution (ST-UnGD) for optimal energy transaction. The proposed scheme has been introduced with uncertainty modeling of available generations and load using probabilistic transition-based timed petri net. Echo algorithm has been used to influence prioritized transition for appropriate number of token distribution. The control over the process during transition has been supervised with UnGD. A uniform probability density function has been created using Gaussian distribution to characterize random variables for effective time series scenario generation. The mean and variance which helps in sorting ten competent scenarios from one thousand scenarios, has been computed with the proposed strategy and compared with other methods. The improvement has been noticed with standard deviation of 0.0162% after 40 trials run with average operational cost of 254.211€ when token distribution was updated by 100, 200, 300, 400, and 500 firings. A statistical analysis by parametric and non-parametric test confirmed the effectiveness of the proposed algorithm showing appropriate confidence level in the mentioned case study.