Climate change poses an urgent challenge to Canada’s sustainable development. The country experiences increasing extreme weather events, rising temperatures, and pressures on energy systems—particularly in remote northern regions. In Newfoundland and Labrador, isolated communities are vulnerable because reliance on diesel-based electricity increases greenhouse gas emissions, energy costs, and environmental risks, highlighting the need for resilient energy solutions. This study uses a systematic methodology combining literature review, local energy demand data, and site-specific wind resources to design and optimize hybrid renewable energy systems (HRESs) for Makkovik. It employs HOMER Pro and the Monte Carlo method to evaluate uncertainties in cost, fuel consumption, and renewable fraction. The objectives are to quantify how renewable integration can reduce emissions, improve energy reliability, and support sustainable development in remote communities. The novelty lies in combining location-specific modeling with probabilistic Monte Carlo analysis and providing robust, system-level insights into environmental and economic outcomes while guiding climate-resilient energy planning. The proposed HRES significantly mitigates climate change impacts, reducing annual CO2 emissions from 72, 500 kg/year to 15, 190 kg/year. Monte Carlo analysis indicates economic feasibility with a net present cost of 14. 5 million, a levelized cost of electricity of 0. 256 /kWh, and diesel consumption reduced from 29, 970 L/year to 5854 L/year. Wind energy provides 99. 6% of total annual electricity, ensuring a high renewable fraction and reliable power, enhancing energy resilience and adaptation potential. This study demonstrates that a well-designed hybrid renewable energy system can deliver measurable emission reductions, economic feasibility, and enhanced energy resilience. It supports sustainable development and climate change mitigation in remote Canadian communities.
Salari et al. (Sun,) studied this question.