Robust multi-objective optimal design of islanded hybrid system with renewable and diesel sources/stationary and mobile energy storage systems

TLDR: Capacity of the method in extracting a robust IHS for sources and ESSs are validated depending on optimal economic and environmental conditions, and the scheme obtains a robust structure for the IHS.

Abstract: Planning of an islanded hybrid system (IHS) with different sources and storages to supply clean, flexible, and highly reliable energy at consumption sites is of high importance. To this end, this paper presents the design of an IHS with a wind turbine, photovoltaic, diesel generator, and stationary (battery) and mobile (electrical vehicles) energy storage systems (ESS). The proposed method includes a multi-objective optimization to minimize the total cost of construction, maintenance, and operation of sources and ESSs within the IHS and the emission level of the system using two separate objective functions. The problem is subject to operational and planning constraints of sources and ESSs and power. Employing the Pareto optimization technique based on the e-constraint method forms a single-objective optimization problem for the proposed design. The problem involves uncertainties of load, renewable energy, and energy demand of mobile ESSs and has a nonlinear form. Adaptive robust optimization based on a hybrid meta-heuristic algorithm that utilizes a combination of the sine-cosine algorithm (SCA) and crow search algorithm (CSA) is proposed to achieve an optimal robust structure for the suggested scheme. In this scheme, operation model of the mobile storage systems in the IHS considering the uncertainties prediction errors and its model using HMA-based ARO besides adopting the HMA to achieve a unique optimal solution are among the novelties of this research. Eventually, considering the climate data and energy consumption of a region in Rafsanjan, Iran, capabilities of the method in extracting a robust IHS for sources and ESSs are validated depending on optimal economic and environmental conditions. The HMA succeeds to reach an optimal solution with an SD of 0.92% in the final response and this underlines its capability in achieving approximate conditions of unique responsiveness. The proposed scheme with proper planning and operation of sources and storages in the form of a HIS finds optimal values for economic and environmental conditions so that the difference between pollution and cost values from its minimum values at the compromise point is roughly 22%. For 17% uncertainty parameters prediction errors, the scheme obtains a robust structure for the IHS.