Risk management of smart grids based on managed charging of PHEVs and vehicle-to-grid strategy using Monte Carlo simulation

• Actual distribution system is used to analyze the proposed methodology.
• A novel charging management method for PHEVs has been introduced.
• The well-being criteria have been provided in addition to reliability indices.
• The uncertainty of results is analyzed in addition to expected average results.
• System effects due to charging and penetration level of PHEVs are analyzed.

The unmanaged charging of plug-in-hybrid-electric vehicles (PHEVs) may adversely affect electric grid reliability because a large amount of additional electrical energy is required to charge the PHEVs. In this paper, a comprehensive method to evaluate the system reliability concerning the stochastic modeling of PHEVs, renewable resources, availability of devices, etc. is proposed. In addition, a novel risk management method in order to reduce the negative PHEVs effects is introduced. This method, which consists of managed charging and vehicle-to-grid (V2G) scenarios, can be practically implemented in smart grids because the bidirectional-power-conversion technologies and two-way of both the power and data are applicable. The introduced method was applied to a real 20 kV network of the Hormozgan Regional Electric Company (HREC) of Iran which is considered as a pilot system for upgrading to smart distribution grid. The results showed that the smart grid’s adequacy was jeopardized by using the PHEVs without any managed charging schedule. The sensitivity analyses results illustrated that by using the risk management scenarios, not only did the PHEVs not compromise the system reliability, but also in the V2G scenario acted as storage systems and improved the well-being criteria and adequacy indices. The comparison between the results based on the proposed method and the other conventional approaches in addition to study of various parameters uncertainty emphasized the advantages of the proposed method.