Joint optimal allocation methodology for renewable distributed generation and energy storage for economic benefits

Nowadays renewable distributed generation (RDG) is observed as an option to the conventional distributed generation due to increased demand for electric energy and green energy concerns. Despite sustainable energy choice, RDGs are also becoming more cost effective. This study presents a joint optimal allocation methodology of RDG and energy storage (ES) to achieve economic benefits. The proposed method minimises costs of distribution company (DISCOM) while assuring the benefits of RDG owner (RDGO). The main novelty of this study is that the contract price of renewable energy between RDGO and DISCOM is obtained along with the allocation of RDG and ES to achieve cost-benefits, and the ES contributes the peak shaving. This study also includes the formulation of generation models for solar power and wind power from the seasonal probabilistic generation models and integration of this renewable generation and load model with an ES model to achieve economic benefits. Moreover, the generation model, storage model, and load model are combined into an optimal power flow model to obtain energy loss minimisation. This constrained non-linear problem is solved using a highly competitive algorithm called grey wolf optimiser in MATLAB (R). Three case studies are presented on the 34-bus test system.