Anoosh Dini

TL;DR: This paper presents the coordinated energy hubs energy management in different networks based on the cooperation of hubs in day-ahead (DA) markets, formulated as a scenario-based stochastic model using Monte Carlo simulation (MCS) for scenario generating and the fast backward/forward scenario reduction method for scenario reducing.

TL;DR: A hybrid teaching-learning-based optimization (TLBO) and crow search algorithm (CSA) is used to obtain a reliable optimal solution with a low standard deviation for flexible EH in the presence of renewable energy sources and active loads.

TL;DR: A hybrid stochastic/robust coordinated power management strategy (CPMS) to simultaneously improve the flexibility, reliability and security indices of MG in the presence of electric vehicles (EVs), energy storage system (ESS), distributed generation (DG) and demand response programming (DRP).

TL;DR: The proposed SCGTEP is tested on the 6-bus and 118-bus IEEE networks in the GAMS software and can be simultaneously improved operation and security indices about 34.5% and 100%, respectively, compared to the power flow analysis based on the optimal location of generation units and transmission lines.

TL;DR: A hybrid robust-stochastic method in which the load uncertainty, temperature and wind speed, the amount of solar radiation and the cost of purchasing energy are considered in the proposed model to solve the problem of large consumers' uncertainty.