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Sustainable Development Goal 7 aims to provide sustainable, affordable, reliable and modern energy access to all by 2030 (United Nations, 2015). In order for this goal to be achieved, sustainable energy interventions in developing countries must be supported with design tools which can evaluate the technical performance of energy systems as well as their economic and climate impacts. CLOVER (Continuous Lifetime Optimisation of Variable Electricity Resources) is a software tool for simulating and optimising community-scale energy systems, typically minigrids, to support energy access in developing countries (Winchester et al., 2022). CLOVER can be used to model electricity demand and supply at an hourly resolution, for example allowing users to investigate how an electricity system might perform at a given location. CLOVER can also identify an optimally-sized energy system to meet the needs of the community under specified constraints. For example, a user could define an optimum system as one which provides a desired level of reliability at the lowest cost of electricity. CLOVER can provide an insight into the technical performance, costs, and climate change impact of a system, and allow the user to evaluate many different scenarios to decide on the best way to provide sustainable, affordable and reliable electricity to a community. CLOVER can be used on both personal computers and high-performance computing facilities. Its design separates its general framework (code, contained in a source src directory) from user inputs (data, contained in a directory entitled locations) which are specific to their investigations. The user inputs these data via a combination of .csv and .yaml files. CLOVER's straightforward command-line interface provides simple operation for both experienced Python users and those with little prior exposure to coding. An installable package, clover-energy, is available for users to download without needing to become familiar with GitHub's interface. Information about CLOVER and how to use it is available on the CLOVER wiki pages.

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Off-grid PV systems have been proposed as a panacea for economies with poor electricity access, offering a lower-cost “leapfrog” over grid infrastructure used in higher-income economies. However, reliability and carbon pricing impacts have been omitted from work that examines pathways to electricity access, underplaying the potential of off-grid PV. We perform high-resolution geospatial analysis on universal household electricity access in Sub-Saharan Africa that includes these aspects via least-cost pathways at different electricity demand levels. Under our "Tier 3" demand reference scenario, 24% of our study’s 470 million people obtaining electricity access by 2030 do so via off-grid PV. A penalty for unmet demand (0.50 $/kWh) increases this share to 41% and applying a carbon price (around $80/tonne CO2-eq) increases it to 38%. We identify thresholds for policy effectiveness in different regions and highlight the high degree of spatial heterogeneity and the areas where policy intervention may be most effective.