Allocation of optimal energy from storage systems using solar energy

In order to reduce carbon emissions, a growing reliance on renewable energy sources such as solar energy is required. As a result of their ability to store excess solar electricity that may be used at a later time to reduce waste and increase utility profits, battery energy storage systems (BESSs) have emerged as a factor for power systems that integrates solar power system. BESSs are traditionally put on buses in solar farms, allowing extra electricity via solar to be stored instantaneously and transmission line losses to be kept to an absolute minimum. According to this placement strategy, BESS is exclusively built in the proximity of solar power plants. In this way, deployment of BESS without network topology consideration, and collaboration among BESSs is limited with capacity pooling to store excess electricity from photo voltaic (PV) panels. In this paper, we develop an optimal deployment of BESSs and it is associated with the estimation of the capacity using a multi-objective constraint modelling. The soft margin classifier minimize the curtailment associated with solar energy that considers both the power flow constraint and network topology. The results of entire model shows that the proposed soft margin classifier is efficient in storing the surplus power in the batter devices than other methods. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

To reduce carbon emissions, a greater reliance on renewable energy sources such as solar power is necessary. Battery energy storage systems (BESSs) have emerged as a solution for integrating solar power systems and storing excess electricity. However, the current deployment of BESSs has limitations that need to be addressed, such as network topology and capacity pooling considerations.