A multi-objective optimisation strategy exploring the energy routing capability of a smart transformer while integrating hybrid energy hub into a distribution network

This study proposes an optimal planning approach for exploiting the energy routing capabilities of a smart transformer (ST) while integrating a hybrid energy hub (HEH) comprised of a wind turbine generator (WTG) and a battery storage system (BSS) into a distribution network (DN). An efficient energy management strategy (EMS) regulates energy exchanges within the HEH unit and with the utility grid. The work presents a mixed-integer nonlinear programming (MINLP) problem for optimising the HEH planning parameters with the purpose of minimising network performance costs such as line loading, real and reactive power losses, voltage profile, and asset management costs. Two approaches are used to achieve the goals, with the first strategy focused on network performance costs, while the second combines the network performance and the asset management expenses. The proposed methodology was tested using the 33-bus radial distribution network (RDN) alongwith a real-life 108bus Indian RDN, and the results of various case studies are reported. The MATLAB R2020a programming platform has been used to solve the MINLP problem using the posteriori approach based paretosearch algorithm (PSA). The outcomes of the evaluation show an apparent energy loss reduction of 58.44%, a line loading improvement of 36.24%, and a voltage deviation improvement of 68.24%. (c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

This study proposes an optimal planning approach for integrating a hybrid energy hub with a smart transformer in a distribution network, using an efficient energy management strategy. The proposed methodology optimizes the planning parameters of the hybrid energy hub to minimize network performance costs.