Investigation of the Impacts of Demand-Side Factors on the Planning, Operation, and Tariff Design of Rural Mini-Grids
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Date
2025-05
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Publisher
Addis Ababa University
Abstract
Electricity is essential for socio-economic development, quality of life, and environmental
protection. Despite significant improvements in rural electrification, millions of people in
rural areas of developing countries, especially in sub-Saharan Africa, still lack access to
electricity. Off-grid mini-grid systems are a promising alternative to traditional grid
expansion, but ensuring their economic viability remains a significant challenge. To enhance
economic viability, most studies have focused on supply-side solutions; however, many minigrid
programs in developing countries are still failing for various reasons, including
inadequate integration of demand-side factors such as load estimation, demand development,
demand-side management, and load composition.
The thesis aims to address mini-grid economic viability challenges by examining how
demand-side factors impact the planning, operational and tariff design of mini-grids, focusing
on four key specific objectives. First, comparing interview- and measurement-based load
profile estimation methods, identifying load categories and specific appliances responsible
for significant differences. The impact of these differences between methods and the
difference in load profile resolution on mini-grid sizing and cost is also examined using the
PSO algorithm. The findings reveal that interview-based methods underestimate peak loads,
daily energy use, and system costs (by up to 52%). The underestimation is more pronounced
for household load categories, due to appliances with high power ratings and cyclic operation
(e.g. electric cooking appliances). Hourly electric load estimation methods also lead to (9%)
cost underestimation.
Second, exploring the advantages of a multi-year-adaptive design approach on cost-optimal
long-term mini-grid component sizing under different demand evolution scenarios. PSO
algorithm is used with measured loads to determine component sizes under three demand
evolution scenarios and various design approaches. The results show that the multi-yearadaptive
approach helps to manage demand evolution challenges. It leads to significant costsavings
in higher demand evolution scenarios compared to multi-year and single-year
approaches. These cost-savings increase with load flexibility (up to 4% with 10% flexibility),
higher discount rates (up to 9.4% with rates from 7% to 20 %), and component cost
reductions (up to 3.6% per 1% reduction). The study demonstrates how an adaptive
approach can be utilized to optimize mini-grid component sizing and enhance cost
efficiency.
Third, determining the impacts of demand-side management implementation and shifting
hours of electric cooking operation on the cost-efficient mini-grid sizing. To determine the impact of demand-side management and shifting hours on mini-grid sizing and cost, a shifting
strategy is applied based on classification into high- and low priority loads. The results indicate
that implementing demand-side management on different load categories leads to significant
variations in potential levelized cost of energy reductions. Household and productive use load
categories have the largest capacity to reduce the levelized cost of energy. Shifting hours of
electric cooking in the household impacts the size of the mini-grid component, resulting in a
system cost reduction.
Finally, the thesis examines the impact of load compositions on the economic viability of
rural mini-grids, addressing the challenges of revenue and tariff settings due to future demand
uncertainties in already installed mini-grids. Using normalized high-resolution measurements
of households and productive users load profiles, the study determines the optimal load
composition that maximizes mini-grid revenue. Results indicate that for a system with fixed
capacity, there is an optimal mix of household and productive users that leads to high
revenue. However, this composition changes with differentiated tariffs between households
and productive users. Additionally, analysis using a mini-grid with spare capacity and three
future load composition scenarios under five tariff structures (fixed energy, fixed and
variable, time-of-use, power, and hybrid) shows that future load compositions
significantly impact cost-reflective tariffs and users' monthly bills, with the impact varying
across the tariff structures
Description
Keywords
Mini-grid, load estimation method, multi-year-adaptive design approach, demand uncertainty, demand-side management, load categories, load composition, tariff structures