An Optimal Installation Strategy for Allocating Energy Storage Systems and Probabilistic-Based Distributed Generation in Active Distribution Networks

An Optimal Installation Strategy for Allocating Energy Storage Systems and Probabilistic-Based Distributed Generation in Active Distribution Networks

Recently, owing to increased interest in low-carbon energy supplies, renewable energy sources such as photovoltaics andwind turbines in distribution networks have received considerable attention for generating clean and unlimited energy. The presence of energy storage systems (ESSs) in the promising field of active distribution networks (ADNs) would havedirect impact on power system problems such as encountered in probabilistic distributed generation (DG) model studies. Hence, the optimal procedure is offered herein, in which the simultaneous placement of an ESS, photovoltaic-based DG, andwind turbine-based DG in an ADN is taken into account. The main goal of this paper is to maximize the net present valueof the loss reduction benefit by considering the price of electricity for each load state. The proposed framework consists ofa scenario tree method for covering the existing uncertainties in the distribution network’s load demand as well as DG. Thecollected results verify the considerable effect of concurrent installation of probabilistic DG models and an ESS in definingthe optimum site of DG and the ESS and they demonstrate that the optimum operation of an ESS in the ADN is consequentlyrelated to the highest value of the loss reduction benefit in long-term planning as well. The results obtained are encouraging.

Recently, owing to increased interest in low-carbon energy supplies, renewable energy sources such as photovoltaics andwind turbines in distribution networks have received considerable attention for generating clean and unlimited energy. The presence of energy storage systems (ESSs) in the promising field of active distribution networks (ADNs) would havedirect impact on power system problems such as encountered in probabilistic distributed generation (DG) model studies. Hence, the optimal procedure is offered herein, in which the simultaneous placement of an ESS, photovoltaic-based DG, andwind turbine-based DG in an ADN is taken into account. The main goal of this paper is to maximize the net present valueof the loss reduction benefit by considering the price of electricity for each load state. The proposed framework consists ofa scenario tree method for covering the existing uncertainties in the distribution network’s load demand as well as DG. Thecollected results verify the considerable effect of concurrent installation of probabilistic DG models and an ESS in definingthe optimum site of DG and the ESS and they demonstrate that the optimum operation of an ESS in the ADN is consequentlyrelated to the highest value of the loss reduction benefit in long-term planning as well. The results obtained are encouraging.