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Determining the impact of future load compositions on cost-reflective tariffs and monthly electricity bills in a rural solar PV mini-grid

2026Open accessWollo University

Abstract

Renewables-based mini-grids can significantly increase electricity access in rural, non-electrified areas. Despite their potential, mini-grid deployment has been slower than expected due to low profitability in areas with initially low demand. Tariff settings that would improve profitability are challenging due to uncertainty of future demand. While previous studies have explored how tariff settings affect demand and how productive use increases profitability, the impact of load compositions on cost-reflective tariffs and users' bills remains unexplored. This study determines the impact of future load compositions on cost-reflective tariffs and monthly electricity bills in a rural solar PV mini-grid. By combining a case with an already installed solar PV-based mini-grid with spare capacity for future demand evolution and three future load composition scenarios, the study calculates cost-reflective tariffs under five different tariff structures (fixed energy, fixed and variable, time-of-use, power, and hybrid) and users monthly bills using the calculated cost-reflective tariffs. The results show that future load compositions significantly impact cost-reflective tariffs and monthly bills, with the effect depending on the tariff structure. Power-based tariffs show a higher reduction compared to energy-based tariffs for load compositions dominated by daily productive uses. The impact on bills for lower-usage households is significant. • Load composition impacts cost-reflective tariffs and monthly bills in mini-grids. • Load composition's impact on tariffs depends on the tariff structure used. • Load and tariff combinations can significantly affect low-income household bills. • Distinguishing daily vs. non-daily productive use is vital for mini-grid viability.

Research topics

  • Smart Grid Energy Management
  • Integrated Energy Systems Optimization
  • Power System Reliability and Maintenance

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DOI: 10.1016/j.enpol.2025.115058

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