Despite substantial progress in recent years, the global community is projected to fall short in its goal to achieve universal electricity access by 2030. State-of-the-art electrification planning models enable planners to outline pathways towards improving the economic feasibility of extending access. The studies presented in this paper employ the Reference Electrification Model (REM) to investigate the value of accurately modeling detailed demand characteristics for electrification planning endeavors. Additionally, the benefits of demand stimulation are explored. REM uses information about consumer demand, existing grid topology, network and generation components, and other features to produce detailed engineering designs of recommended systems for every consumer in an area of interest. These designs may comprise different supply technologies including grid extension, mini-grid, and stand-alone systems. In our case study, the model determines the cost-optimal technology mix to provide full electrification for a 10,914 square kilometer area of Uganda with 366,946 individual consumers. These consumers are categorized into 20 consumer types. The studies presented are unique from those previously reported due to the high (consumer-level) spatial granularity, technical detail in system designs, and large areal extent of analysis. A number of contributions are made. First, the criticality of adequately estimating demand and its evolution is demonstrated for large-scale planning; notable cost and supply technology sensitivities are observed as a function of anticipated demand levels. Second, the importance of representing demand heterogeneity is elucidated via modeling a diversity of consumer types. In the “central demand case” presented, modeling demand heterogeneity results in least-cost plans that are 9% less costly than modeling assuming one single customer type. Modeling heterogeneity also decreases prescribed grid extension shares from 89% to 77%, increasing the prevalence of mini-grid and stand-alone systems. Lastly, the potential economic benefits of demand stimulation are characterized. We show how stimulating demand can lead to positive feedback loops: increasing electricity demand can lower electricity unit-costs through the realization of economies of scale and improved network utilization, which can improve the viability of additional electric loads, continuing the cycle. Specific studies comparing the economics of clean cooking via electric and liquefied petroleum gas (LPG) cookstoves show how these feedback loops can jointly benefit progress towards universal access to clean cooking and electricity. The demand assumptions modeled show that coordinated planning can reduce electricity costs by 34% and increase electric cookstove viabilities from 42% to 82%.
demand characterization, demand stimulation, demand forecasting, productive use of energy, energy for growth, electrification planning, clean cooking, electric cooking, universal energy access, reference electrification model