The decarbonization of the electricity system coupled with the electrification of transport, heat, and industry represents a practical and cost-effective approach to deep decarbonization. A key question is as follows: where to build new solar and wind farms? This study presents a cost-based approach to evaluate land parcels for solar and wind farm suitability using colour-coded heatmaps that visually depict favourable locations. An indicative cost of electricity is calculated and classified for each pixel by focusing on key factors including the resource availability, proximity to transmission infrastructure and load centres, and exclusion of sensitive areas. The proposed approach mitigates the subjectivity associated with traditional multi-criteria decision-making methods, in which both the selection of siting factors and the assignment of their associated weightings rely highly on the subjective judgements of experts. The methodology is applied to Australia, South Korea, and Indonesia, and the results show that proximity to high-voltage transmission and load centres is a key factor affecting site selection in Australia and Indonesia, while connection costs are less critical in South Korea due to its smaller land area and extensive infrastructure. The outcomes of this study, including heatmaps and detailed statistics, are made publicly available to provide both qualitative and quantitative information that allows comparisons between regions and within a region. This study aims to empower policymakers, developers, communities, and individual landholders to make informed decisions and, ultimately, to facilitate strategic renewable energy deployment and contribute to global decarbonization.

Achieving net zero relies on siting large-scale solar and wind where they are cheapest and most socially acceptable. We present a transferable, evidence-based siting framework and apply it to Australia. The landscape is divided into millions of 250 m pixels, each assigned an indicative cost based on resource quality, distance-weighted connection costs, and land use exclusions. Two bounding generation mix scenarios (high solar vs. high wind) stack the cheapest pixels until a fully electrified demand of 20 MWh per capita per year is met. Results are aggregated to all 547 Local Government Areas (LGAs) and 150 federal electorates and expressed as capital inflow, construction job-years, long-term jobs, and land-lease income. We find Class A solar (<50 AUD/MWh) is abundant nationwide except in Tasmania, while high-quality wind is concentrated in Victoria, Tasmania, and coastal Western Australia. Just 15% of LGAs, mainly within 100 km of the existing 275–500 kV transmission backbone, can host over half of least-cost capacity. A single top-ranked LGA such as Toowoomba (Queensland) could attract around AUD 33 billion in investment and sustain over 50,000 construction job-years. Mapping ten candidate high-voltage transmission corridors shows how new lines shift opportunities to under-served councils. The results bridge the gap between state-level renewable energy zones and fine-scale site suitability maps, with policy recommendations proposed. Because the workflow relies mainly on globally available datasets, it can be replicated in other countries to raise public awareness, align policy with community support, and accelerate clean-energy buildouts while maximising regional benefit.

Decarbonization of the electricity system coupled with electrification of transport, heat and industry represents a practical and cost-effective approach to deep decarbonization. A key question is: where to build new solar and wind farms? This study presents a cost-based approach to evaluate land parcels for solar and wind farm suitability using colour-coded heatmaps that visually depict favourable locations. An indicative cost of electricity is calculated for each pixel by focusing on key factors including resource availability, proximity to transmission infrastructure or load centres, and exclusion of sensitive areas. The proposed approach mitigates the subjectivity associated with traditional multi-criteria decision-making methods, in which both the selection of siting factors and the assignment of their associated weightings rely highly on the subjective judgments of experts. The methodology is applied to Australia, South Korea, and Indonesia, and the results are made publicly available to provide both qualitative and quantitative information that allows comparisons between regions and within a region. The study aims to empower policymakers, developers, communities and individual landholders to make informed decisions, and ultimately, facilitate strategic renewable energy deployment and contribute to global decarbonization.