Short-term and probability scenario-oriented energy management of integrated energy distribution systems with considering energy market interactions and end-user participation

In this research, a scenario-oriented operational framework and an optimal tri-level energy management system within the energy hub (EH) architecture are introduced, considering the uncertainties associated with renewable energy resources and stochastic demand, particularly from electric vehicles, utilizing both central and local controller platforms. The devised model incorporates the variability of pricing for both electric and thermal energy carriers, informed by indicators from wholesale and retail markets. The scenario-oriented model for optimal power management and operation employs the K-means clustering technique alongside the development of probabilistic scenarios, which is subsequently addressed through the particle swarm optimization method. The K-means clustering technique is articulated to ascertain the array of multidimensional correlation scenarios that encompass power generation sources and varieties of consumption loads, temporal sequences, auto-correlation, and cross-correlation. To enhance the subscriber engagement, diminish operational expenditures, and also augment profitability as a consequence of subscriber involvement, the integrated demand response (IDR) program has been developed within the framework of the EH. The findings indicate a 24 % decrement in overall operation cost, a 24 % reduction in energy supply expenditures, and a 23.4 % increase in profitability attributable to the IDR programs execution and the engagement of energy storage units in the power supply chain.