An efficient short-term energy management system for a microgrid with renewable power generation and electric vehicles

According to statistical reports, thermal power plants have long played a critical role in supplying electricity using fossil fuels. However, due to the high investment and operation costs of these power plants and their destructive effects on the environment, renewable energy sources (RESs) in power networks have been considered an effective alternative to traditional power plants. Optimal scheduling of microgrid in smart grids has a significant impact on reducing energy consumption, environmental pollutants and end-user's energy prices. In this paper, the influence of plug-in hybrid electric vehicles (PHEVs) charging on microgrids' optimal operation is evaluated. To assess the behaviour of PHEVs, three various charging patterns consisting of uncontrolled, controlled and smart charging methods are considered. Uncertainties due to forecast error in the PHEVs, loads, prices and renewable source output power are also considered in microgrid modelling energy management. To deal with the optimisation scheduling of microgrid considering uncertainty, a modified harmony search (MHS) algorithm is used. The suggested scheme is validated using simulations and without the PHEV charging effects compared with the conventional methods.

Automated summary

According to statistical reports, thermal power plants have long played a critical role in supplying electricity using fossil fuels. However, due to high investment and operation costs and their destructive effects on the environment, renewable energy sources (RESs) are considered an effective alternative. This paper evaluates the impact of plug-in hybrid electric vehicles (PHEVs) charging on optimal microgrid operation, considering different charging patterns and uncertainties in energy management. The study uses a modified harmony search algorithm to deal with uncertainty in microgrid optimization scheduling.