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The adoption of power supply systems powered by renewable energy sources is growing
these days as a result of the problems associated with economic, environmental and
depletion of conventional energy sources. The main issue with the renewable energy
power supply system is to determine the optimal, reliable, and feasible configuration
and the corresponding components of the system. Even though Ethiopia is endowed
with abundant renewable energy resources, the electrification rate of the country is very
low, and there is no general framework that is used for the development of a renewablebased
off-grid power supply system for rural electrification. Therefore, the main aim of
this study is to develop a general framework for the optimal size of a renewable-based
off-grid power supply system for rural communities.
The power generated from the photovoltaic module is directly related to the magnitude
of total incident solar radiation on the surface of the solar module. In this dissertation,
generic models were developed that determine the seasonal and annual optimal tilt angle
of the Photovoltaic module at any location in Ethiopia without using meteorological
data. Both isotropic and anisotropic diffused solar radiation models were used to estimate
monthly, seasonal, and annual optimal tilt angles. The monthly average daily
global horizontal solar radiation for a total of 44 cities -32 for developing the models
and 12 for testing were obtained from the National Aeronautical and Space Administration
database, and algorithms were developed and implemented using MATLAB and R
programming software to obtain optimum tilt angle and regression models. The study
showed that the developed model accurately estimates the optimal tilt angle with the
minimum statistical validation errors. It is also found that 5.1% to 6.3% (isotropic) and
5.7% to 6.3% (anisotropic models) solar radiation energy is lost when using the yearly
average fixed optimal tilt angle as compared with the monthly optimal tilt angle. The
developed optimal tilt angle models were validated by comparing them with previously
published works, PVGIS, and PVWatt online software.
The electricity demand is highly stochastic and unpredictable. A good load model is
one of the main inputs for the design of an economical and reliable renewable-based
rural electrification system for rural communities and demand management systems.
This study presents a generic methodology for determining a rural community’s energy
consumption load profile, which is used to determine the most cost-effective size
of the renewable-based off-grid power supply system for rural electrification purposes.
To determine the load profile parameters, such as the types of appliances used, their
functioning times, functioning windows, and expected minimum and maximum cycle
time, a field survey was conducted in four rural electrified Ethiopian villages. Since the
survey findings will not fully explain the stochastic nature of the load profile, the load
parameters are randomly generated, and a bottom-up approach is used to estimate the
rural community’s energy usage. A MATLAB program is developed and implemented
to obtain the load profiles of different customer groups. The results of this study are
assessed per the multi-tier criterion and verified using the use of the well-known software
HOMER Pro and LoadProGen.
The zebra optimization algorithm (ZOA), a recently developed meta-heuristic optimization
algorithm, has been used to perform the techno-economic performance analysis and
optimal sizing of the renewable-based off-grid power supply system for rural Ethiopian
villages. The optimal sizing of the off-grid power supply system is performed to supply
synthetically developed load demand that comprises 1243 households, various commercial
loads, public institutions, and small industrial loads on Dek Island, which is one of
the largest islands in Ethiopia, on Lake Tana. Using the proposed optimal tilt angle
model, the maximum solar radiation on the PV module’s surface is determined, leading
to the determination of the PV output power. All the off-grid power supply system
components are modeled, the objective function is formulated, and the optimization
and techno-economic analysis are performed based on the minimum total annual cost
of the off-grid system. Three off-grid power supply systems, such as PV-BAT, PV-WTBAT,
and WT-BAT, are proposed to evaluate the optimal configuration for the study
site at various losses of power supply probabilities (LPSP). The study’s findings showed
that the photovoltaic-battery (PV-BAT) system, with an optimal size of 3483.161 kW
of PV, 3668 units of storage batteries (11,444.160 kWh), and 2082 kW of converter
at 0.044030% LPSP, is the best configuration for electrifying the rural communities of
the study site with the minimum annual total cost of 621,736.056 USD and 0.227063
$/kWh COE. It results in a 3.3% annual total cost reduction and a 1.3% unmet load
(kWh/year) improvement as compared to the PV-WT-BAT system. The performance
of the proposed ZOA in obtaining the optimal size of the renewable-based power supply
system for rural communities is evaluated by comparing it with a well-known gray wolf
optimization (GWO) and HOMER Pro software, and it was found that the proposed
algorithm is relatively best in finding the optimal size of the power supply system at the
minimum cost. The standard deviation for ZOA and GWO, respectively, in determining
the optimal configuration value for 25 runs is 14.295 and 36.360 for the PV-BAT configuration,
indicating that ZOA is more reliable than GWO in determining the optimal
size. Furthermore, ZOA yields a 16.76% reduction in the total net present cost when
compared to the HOMER software results. |
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