Cost Sensitivity of Electricity Systems to the Shape of Electricity Demand Curve: A Sub-Saharan Africa Example

Abstract:

Sub-Saharan Africa’s underdeveloped power sector has an electrification rate of approximately 45% and experiences frequent power outages. The United Nations has set a 100% electrification goal for the region by 2030. To help meet this target, wind and solar power installations are expected to increase substantially in the coming years. As such, energy systems planning – relying on accurate data – has become increasingly important. In part, because hourly electricity demand data for Sub-Saharan Africa is scarce, current and future electricity demand largely unknown.

In this study, we aim to quantify the impacts that an uncertain demand curve can have on energy systems and their costs. We study three types of energy systems: wind and solar generation; wind, solar, and diesel generation; and wind and solar generation with battery energy storage. We conduct a sensitivity analysis of a synthetic one-year demand curve and alter the phase and amplitude to create 144 unique demand profiles. We use a least-cost capacity and dispatch power system model to simulate the different electricity system configurations resulting from the different demand profiles. Results indicate that the sensitivity of system cost to demand pattern fluctuations is strongly influenced by the system configuration. For wind and solar based systems, cost per delivered kWh can vary by up to 30% with changing demand profiles; for systems with additional storage or diesel generator capacity, cost varies by about 7% across demand profiles.

This suggests that assumptions about demand in electricity modeling can substantially impact the results of proposed system architectures. For new electricity systems, costs could potentially be reduced through investigations of how demand profiles and electricity systems could be jointly shaped to facilitate reliable low-cost electricity systems.