Optimal scheduling of PHEVs and D‐BESSs in the presence of DGs in a distribution system

Abstract

Optimisation of cost and load flattening for a distribution network is attempted in this work. The objective function is described in terms of energy cost, C O 2 emissions, real power losses, and load flattening. The solution is envisaged in terms of hourly scheduling of distributed generations (DGs), distributed battery energy storage systems (D-BESSs), and plug-in hybrid electric vehicles (PHEVs). An investigation in the reformulation of the cost of energy is carried out to eliminate the solutions involving excessive charging and discharging of BESSs/D-BESSs and PHEVs. It is demonstrated that simultaneous optimisation of cost, C O 2 emissions, real power losses, and load flattening cannot be effectively solved as a weighted sum objective function. An e -constraint method is applied to obtain the optimal scheduling to achieve cost optimisation, load flattening, and minimisation of C O 2 emissions from the utility point of view. A case of decentralised multi-agent optimisation problem is also formulated and compared. It is observed that the combination of the scheduling of DGs, BESSs/D-BESSs, grid-to-vehicle/vehicle-to-grid can successfully be used to significantly reduce the system peak demand along with system cost, losses and C O 2 emissions.