Battery switch station as storage system in an autonomous power system: Optimization issue

Due to the high volatility of the oil price, cars producers have been motivated to find new solutions for reducing or eliminating the use of fossil fuel. In the last few years, hybrid vehicles (combustion engine combined with an electric motor) and full electric vehicles (EVs) have been designed and commercialized with relatively good success. Both technologies use batteries to drive an electric motor. Nowadays there are two main options for charging the batteries: · Through the direct connection of the vehicles to the grid, so called V2G · Through a battery switch station (BSS), where the empty batteries are replaced with charged batteries. Both the V2Gs and the battery switch stations can operate either as an energy source, when the batteries are fully charged or as an electrical load, when the batteries need to be charged. The use of EVs, whose batteries are recharged by using renewable energy, can mitigate the bottleneck operative situations, which generally appear in power systems with a high penetration of generators based on renewable energy sources. Nowadays, such a problem is handled using the Net Security Management System (NSM) which limits the production of the generators based on renewable sources. Although such a device works well, it has the disadvantage of wasting "green energy". The aim of this work it to analyse the behaviour of an Autonomous Power System (APS) with a high penetration of generators based on renewable energy sources where BSS are used both for charging the EVs and for energy management purposes. Moreover, the operation of an Intelligent Management Energy System (IEMS), which optimizes the power flow depending on the power demand, will be described. If there is an electrical surplus, the IEMS directs the power flow to the battery switch station, while if there is an electrical deficit the IEMS collects electricity from it. The benefits (economical and environmental) which the BSS gives to the APS will be evaluated. Th- - e optimal storage capacity of the BSS will be estimated.