A Multi-Objective Design Optimization Approach to PV and Battery Storage for Sector-Integrated Energy Systems at Logistics Facilities - Under Consideration for the Integration of Temperature-Controlled Transport

Abstract

This work outlines an approach to the optimal design optimization of a photovoltaic (PV) and battery storage system and its integration into the sector-integrated energy system of a logistics company’s facilities. Another major objective is the optimized integration of refrigerated trailers (reefers) into the energy system with the goal of minimizing both costs and CO2 emissions, as demonstrated in a case study. For this purpose, an existing energy system model utilizing reefers was optimized for computing time and the energy system was extended through the use of a facility’s cooling utility. Multi-criteria design optimization was performed using a multi-objective evolutionary algorithm based on decomposition approach. For this, three key performance indicators (KPIs) were used: the annuity, CO2-emissions, and own-consumption rate. The results of the multi-criteria design optimization were then analyzed using Pareto fronts. Stakeholders are thus able to find their individual techno-economic/ecological optimum and so plan the transformation to an decentralized, renewable, distributed energy supply accordingly. Three selected Pareto optimal results were selected to evaluate the effect of PV and battery storage on the optimal operation of the sector-integrated energy system and reefer integration.