Distributed renewable generation and storage systems sizing in deregulated energy markets

Abstract

As the needs for distributed renewable generation (DRG) increase driven by the accelerated growth of electric demand in order to deter greenhouse emissions and create a more economic and efficient power supply environment, this papers pays attention to the potential contribution of independent owners (IOs) of DRG operating within the microgrid (MG). In order to assess such role, an optimization scheme is introduced to allocate and size the stochastic DRG with a distributed energy storage system (DESS) based on a novel energy management system (EMS) that accounts for power distribution loss, dynamic pricing environment, demand response, stochastic generation, etc. The proposed EMS utilizes an iterative Newton-Raphson linear programming algorithm that gradually schedule the resources maximizing the objective function and coping with the complicated nonlinear nature of the problem and enabling of efficiently carrying long-term assessments. The EMS is used to evaluate candidate solutions that are generated by a genetic algorithm (GA) working on evolutionary basis to determine the optimal combination of DRG and DESS. A case study for IEEE 34-bus distribution MG in Okinawa, Japan is used for testing the algorithm and analyzing the potential of IO investments and their strategies.