Abstract
Ghana's electricity sector faces dual challenges of rising demand and its ambitious 2030 target of 10 % renewable energy integration. This study analyzes urban consumption patterns in Accra and Kumasi through an 8760-h dataset to evaluate grid stabilization strategies. Our regression model (R2 = 0.793) identifies baseline demand as the primary driver of consumption, accounting for 79.3 % of the variation (coefficient = 2.141 kWh), underscoring the critical need for energy efficiency measures. Demand response (DR) programs yield mixed outcomes: while effective interventions reduce usage by 0.406 kWh (p < 0.001), current designs paradoxically associate participation with an increase of 0.501 kWh (p = 0.002). Renewable energy (0.141 kWh) and storage discharge (0.115 kWh) exhibit modest impacts, with weak correlations (r = 0.07 and 0.05, respectively), indicating operational mismatches. The study highlights the need for three key policy interventions: (1) restructuring DR programs to prioritize verified load reductions over enrollment metrics, (2) enhancing real-time data infrastructure to align renewable generation with demand patterns, and (3) integrating climate resilience into grid planning. Limitations include sensor-derived occupancy data with a 7.2 % interpolation error, omitted variables (e.g., temperature, pricing), and unmodeled climate risks that affect hydropower reliability. These findings establish a framework for IoT-enhanced energy analysis, providing actionable pathways for Ghana to achieve its renewable energy targets without compromising grid stability. The insights offer particular value for developing nations undergoing similar energy transitions, emphasizing the importance of addressing current implementation gaps in DR programs and renewable-storage coordination to meet sustainable energy goals.
