Designing a Data-Driven Electricity Tariff Optimisation Model for Nigerian DisCos

Electricity tariff design in Nigeria requires balancing cost recovery for distribution companies against affordability for consumers, and data analytics can provide the evidence base for more equitable and financially sustainable tariff structures. This study designed a data-driven tariff optimisation model for three Nigerian Electricity Distribution Companies covering the South West, North Central, and South East zones. A professional model design methodology was employed with structured consultations with 15 NERC tariff analysts and DisCo chief commercial officers, review of MYTO tariff methodology, and benchmarking against tariff optimisation frameworks used by ESKOM, Kenya Power, and Senelec. The model designed incorporates a demand elasticity estimation module, a cost allocation model separating network and energy components, a cross-subsidy simulation engine for residential, commercial, and industrial segments, and a revenue sufficiency dashboard. Affordability constraints based on willingness-to-pay survey data from 2,400 consumers across the three zones are embedded as optimisation constraints. Sensitivity analysis for exchange rate and gas price shocks is included. Expert review by ten electricity sector economics and data science specialists confirmed the model's regulatory soundness. The study recommends NERC adopt the model as a supplementary tool in MYTO review cycles, incorporate demand-side data from smart metering programmes into annual model calibration, and publish tariff optimisation assumptions transparently to improve stakeholder trust in the regulatory process.

Keywords: electricity tariff optimisation, DisCo, NERC, Nigeria, demand elasticity