Optimal design of off-grid power systems operated by a rolling-horizon strategy: a method to reduce computational requirements

Optimal Design of Isolated Mini-Grids with Deterministic Methods: Matching Predictive Operating Strategies with Low Computational Requirements

“…The operating costs are evaluated based on the simulation of the typical year at an hourly resolution, which is a good compromise between problem tractability and optimality of results. This formulation is based on the one described in [39].…”

“…This activity is an advancement of other works published by the same authors [35,39] and this paper aims at establishing a solid baseline for researchers and developers to tackle the microgrid sizing, combined with advanced operating strategies.…”

“…Heuristic methodologies rely on an iterative process, where a given number of different sizing cases is drawn, then their yearly operation is simulated; the target function to be minimized is evaluated for all cases, selecting the cheapest ones, which are then considered in the next round of sizing cases generated, until the termination criteria are met [17,18,23,25,37,38]. As an example of heuristic methodology, Particle Swarm Optimization (PSO) has been used in the field of mini-grids for rural electrification [35,39]. In [39], the authors proposed two interesting approaches to reduce computational requirements in heuristic approaches for a hybrid system, also including the simulation of the fuel logistics.…”

“…As an example of heuristic methodology, Particle Swarm Optimization (PSO) has been used in the field of mini-grids for rural electrification [35,39]. In [39], the authors proposed two interesting approaches to reduce computational requirements in heuristic approaches for a hybrid system, also including the simulation of the fuel logistics. The paper [35] proposed an interesting comparison between different sizing methodologies, including MILP and heuristic approaches; however, we believe that the comparison could be improved, also including the methodologies developed in [39].…”

“…In [39], the authors proposed two interesting approaches to reduce computational requirements in heuristic approaches for a hybrid system, also including the simulation of the fuel logistics. The paper [35] proposed an interesting comparison between different sizing methodologies, including MILP and heuristic approaches; however, we believe that the comparison could be improved, also including the methodologies developed in [39]. The benefits of predictive approaches is showcased also by authors in [40], which obtained, with respect to LFS and CCS strategies, notable savings in the annualized costs.…”