Abstract
Renewable energy sources are an environmentally attractive idea, but they require a proper control scheme to guarantee optimal operation. In this work, we tune different controllers for an Interleaved Boost Converter (IBC) powered by a photovoltaic array using three metaheuristics: Genetic Algorithm, Particle Swarm Optimization, and Gray Wolf Optimization. We also develop several controllers for a second simulated scenario where the IBC is plugged into an existing microgrid (MG) as this can provide relevant data for real-life applications. In both cases, we consider hybrid controllers based on a Linear Quadratic Regulator (LQR). However, we hybridize it with an Integral action (I-LQR) in the first scenario to compare our data against previously published controllers. In the second one, we add a Proportional-Integral technique (PI-LQR) as we do not have previous data to compare against to provide a more robust controller than I-LQR. To validate our approach, we run extensive simulations with each metaheuristic and compare the resulting data. We focus on two fronts: the performance of the controllers and the computing cost of the solvers when facing practical issues. Our results demonstrate that the approach proposed for tuning controllers is a feasible strategy. The controllers tuned with the metaheuristics outperformed previously proposed strategies, yielding solutions thrice faster with virtually no overshoot and a voltage ripple seven times smaller. Not only this, but our controllers could correct some issues liaised to the IBC when it is plugged into an MG. We are confident that these insights can help migrate this approach to a more diverse set of MGs with different renewable sources and escalate it to real-life experiments.
Highlights
Recent studies have corroborated that the excessive exploitation of fossil fuels as a primary energy source has caused negative impacts on our environment
We contrasted our data against previously published controllers for Interleaved Boost Converter (IBC) in terms of three performance metrics: the maximum overshoot, the response time when faced with perturbations, and the output voltage ripple
We analyzed these metaheuristics when tuning controllers for a system comprised of the IBC and a microgrid (MG) under different testing conditions
Summary
Recent studies have corroborated that the excessive exploitation of fossil fuels as a primary energy source has caused negative impacts on our environment. The chief goal is to update the current electrical system by incorporating renewable energies so that fossil fuel consumption can be gradually decreased to 20% by 2050 [1]. This objective has created several research opportunities in the Distributed Energy Resources (DERs) field. The DERs appear as an innovative solution that benefits customers at a lower energetic cost while preserving a high power quality and energy independence [2].
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