Multi objective receding horizon optimization for optimal scheduling of hybrid renewable energy system

In this paper, a methodology for energy management system (EMS) based on the multi-objective receding horizon optimization (MO-RHO) is presented to find the optimal scheduling of hybrid renewable energy system (HRES). The proposed HRES which is experimentally installed in educational building comprising the PV panels, wind turbine, battery bank and diesel generator as the backup system. The data acquisition system provides input profiles for receding horizon optimizer. A mixed-integer convex programing technique is used to achieve the optimal operation regarding to two conflicting operation objectives including diesel fuel cost and battery wear cost. The Pareto frontiers are presented to show the trade-offs between two operation objective functions. Analysis of obtained results demonstrates that the system economic and technical performance are improved using longer prediction horizon. The results show that using longer time view (from 6 h to 24 h) the total share of renewable energy in supplying weekly demand can be improved up to 18.7%. Therefore, the proposed methodology can manage system to make a better use of resources resulting in a better system scheduling. The sensitivity analysis also demonstrates the effectiveness of seasonal variations of available renewable resources on the optimal operation scheduling.