CLOVER: A modelling framework for sustainable community-scale energy systems

Abstract

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.

How reliability and carbon prices impact pathways to universal electricity access in Africa

“…Off-grid energy system modelling We used the CLOVER open-source energy system model 46 to estimate the cost and emissions of delivering electricity via different off-grid systems. The CLOVER model runs simulations of energy systems within specifications predetermined by the user.…”

Opportunities for decentralised solar power to improve reliability, reduce emissions and avoid stranded assets

“…We use the open-source energy-system modelling framework CLOVER 48,49 to simulate the performance of systems capable of providing electricity to a rural community in Uttar Pradesh, India. We use CLOVER to investigate systems consisting of a combination of solar PV collectors, battery storage and a national grid connection.…”

“…The open-source modelling framework, CLOVER 48,49 , provides metrics for assessing the performance of a system. We use the notion of "blackouts", where a blackout is an hour during which any amount of electricity demand went unmet (i.e., any shortfall of energy results in the hour being classified as a blackout).…”

“…We employ an open-source modelling framework 48,49 to assess the potential for national grid-connected solar PV mini-grids to improve hours of electricity supply service for consumers (Figure 1). We consider how integrating mini-grid infrastructure at different levels of reliability may impact the risk of stranded assets and the potential loss of asset value under various scenarios.…”

“…Previous studies have used a single reliability level for the national grid network [44][45][46][47] . However, it is important to explore the impacts at different national grid reliability levels given that it may differ from what is anticipated, or change over time.We employ an open-source modelling framework 48,49 to assess the potential for national grid-connected solar PV mini-grids to improve hours of electricity supply service for consumers (Figure 1). We consider how integrating mini-grid infrastructure at different levels of reliability may impact the risk of stranded assets and the potential loss of asset value under various scenarios.…”