Optimization of hybrid renewable energy systems for remote communities in northern Canada

Abstract

Electricity is currently provided in remote communities in Nunavut, Canada, using diesel generators. This study aims to identify the most cost-effective hybrid renewable energy systems by integrating photovoltaic panels and wind turbines to reduce carbon emissions and fuel costs associated with diesel generation. Two system configurations are considered: fully renewable energy systems and hybrid systems incorporating diesel generators. A genetic algorithm-based optimization approach is used to determine the optimal wind farm layout while considering wake effects. The hybrid system achieved levelized costs of electricity (LCOEs) of 0.30 $/kWh in Arviat, 0.35 $/kWh in Rankin Inlet, 0.29 $/kWh in Baker Lake, and 0.37 $/kWh in Sanikiluaq, significantly reducing energy costs compared to diesel-only systems. Additionally, the optimized hybrid configurations led to over 55 % reduction in greenhouse gas (GHG) emissions, while improving annual energy production by 20 % in Arviat and up to 15 % in Sanikiluaq. The study demonstrates that integrating wind and solar energy with existing diesel infrastructure provides a financially viable and environmentally sustainable pathway for energy transition in remote off-grid communities. These findings contribute to ongoing research on optimizing hybrid renewable energy systems for cold-climate regions, ensuring affordability, reliability, and emissions reduction.