Grid–variable renewable energy supply optimization for sustainable tourism in developing countries: A case of small-sized hotels in low-wind regions

Abstract

This study assesses the techno-economic viability of grid-connected variable renewable energy (VRE) systems for small-sized hotels in low-wind areas of developing tropical countries where the sustainable tourism infrastructure is subjected to unique resource constraints. This paper compares three optimization methods-linear programming (LP), simulated annealing (SA), and the genetic algorithm (GA)-to determine the optimal levelized cost of energy (LCOE), component sizing, and generation mixes across four regulatory scenarios, using the hourly load and resource profiles of a planned hotel on Nusa Penida Island, Bali, Indonesia. Methodological comparison of these techniques unveils distinct computational trade-offs, with LP providing the fastest optimization (54.35 to 162.16 s), drastically outperforming iterative metaheuristics such as GA, which required up to 772.18 s. Regarding energy performance, all photovoltaic (PV)-integrated configurations outperform the grid-only benchmark of $0.0824/kWh. The PV–grid system yields the lowest LCOE ($0.0637 to $0.0714/kWh), reducing costs by 3.2% to 15% compared with the grid. Notably, hybrid wind–PV–grid configurations are economically feasible ($0.0662 to $0.0798/kWh), successfully meeting demands even under a stringent 25% obligatory renewable fraction. Without sellback incentives, the VRE mix ranges from 30.1% to 38.2% for PV–grid systems and reaches up to 49% for wind–solar–grid setups, whereas elevated sellback rates strongly boost VRE adoption. This study has practical implications for policymakers and hospitality investors by showing that while solar PV remains the most cost-effective asset, small wind turbines can synergistically complement grid–VRE systems in low-wind tropical environments when supported by strategic market mechanisms.

Keywords

grid-connected variable renewable energy / sustainable tourism infrastructure / low-wind regions of developing tropical countries / linear programming / simulated annealing / genetic algorithm / techno-economic / hourly load and resources profiles

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