Modeling and simulation of distributed generation system
711 Final Project
1. Analysis Of Implementation Of Micro-Grid Using
Renewable Resources In Rural Areas of Liberia
Vijit Dubey
Electrical and Computer Engineering
Texas A&M University
College Station, Texas, USA
vijit4072@tamu.edu
Lance Alpuerto
Electrical and Computer Engineering
Texas A&M University
College Station, Texas, USA
lanceg90@tamu.edu
Abstract— Liberia is one of the poorest countries in the world.
Poverty can be linked to lack of access to energy to the general
population. Liberia has only 4.1% of the population with access
to electricity. This paper investigates feasibility of seting up a
micro-grid with decenctralized generation using high content of
renewable energy by reviewing previous literature on micro-grid
components. The potential of wind, solar and biomass energy
have been examined in Sanniquellie. It has been concluded that
Solar and Biomass potential of the region is excellent. The
results found in the paper have have been used to choose a best
possible microgrid for the location.
Index Terms—Rural electrification in Senegal, Micro-grids,
Decentralized generation, solar PV energy, load estimation.
I. INTRODUCTION
Liberia is a war-torn and one of the poorest countries in the
world. This economic stability can be associated to the lack of
access to energy to the population. On an average, North
American countries consume 12 to 30 times more energy than
African countries [1], [2]. Poverty and lack of access to
electricity. In rural regions, significant effects of poverty and
lack of access to electricity can be seen. Liberia has just 4.1%
of population with access to electricity, which is one of the
lowest in the world [3]. State government-owned Liberia
Electricity Corporation provides electricity in the capital
Monrovia. A In 2013 the total installed capacity in Liberia
was 20MW [5]. A hydro project has been proposed to increase
the capacity to 100 MW. 70% of the population lives in the
rural areas which is quite far from the capital. Building a
transmission and distribution line from the main grid to the
rural areas would be expensive. However, electricity can be
provided by isolated systems supporting local demands in
rural areas. Renewable sources such as solar, wind or biomass
could be used to harness electricity. In 1999, Sanniquellie had
decent access to electricity, but all the electricity generation
and distribution system was destroyed during the civil war [6].
Access to electricity in Sanniquellie can only be received
through privately owned diesel generators. Many small
companies provide energy using privately owned generators at
a tariff rate of $0.54 per KWh [5].
Africa Energy Unit acknowledges in their published plans
the dire need to run parallel to central grids. Also, the Rural
Renewable Energy Agency (RREA) has established projects
to undertake projects for electrification of rural areas using
renewable energy in their National Rural Electrification
Master Plan (REMP) [4, 14]. This paper investigates available
resources to set up a micro-grid in Sanniquellie, a district
located 302 kilometers away from the capital Monrovia. The
renewable energy potential from different fuels is estimated,
and an analysis of a decentralised micro-grid is done. For a
comparison, energy derived from diesel fuel generators which
are the current source of electricity has been discussed. On
economic analysis, overnight capital costs and Levelized cost
of electricity (LCOE) have been considered. These costs are
compared to the wilingness and ability to pay of the rural
population of Sanniquellie.
II. RENEWABLE ENERGIES POTENTIAL
Decentralized generation (DG) is a more economical solution
than grid expansion for Liberia due to lack of existing
infrastructure. DG has prooved to be more economical in
regions with low electricity demand, low population density
and lack of generation infrastructure [1, 2, 11, 12]. There are
plenty of renewable energy options to generate electricity in
rural areas of sub-Saharan countries. Electricity can be
generated using biomass, wind or solar energy.
A. Biomass Energy
Liberia’s biomass potential has been presented in the report
published by National Rural Energy Laboratory [18].
Sanniquellie has electricity potential via municipal solid waste
generation potential of 432 MWh/yr. Table 1 discusses the
parameters for cost and levelized price of electricity
calculations for different sources of energy [13]. However,
producing energy from biomass creates air pollution by
producing carbon monoxide, nitrogen oxides and other volatile
gases [32]. Black carbon created during combustion of biomass
is one of the largest contributors to global warming [32].
B. Wind Energy
Wind energy has been developed significantly over the last
two decades [7]. It has proved to be very effective in windy
sites. Some global but not precise studies are conducted in
Sanniquellie. The average wind speed in Sanniquellie is
between 4 to 7 m/s [8]. However, most of the time wind speed
is more than 5 m/s (Fig. 1). The speed at which the wind
2. turbine will produce usable power is called the cut-in speed.
The cut-in speed is usually 7-9 m/s. The turbine needs higher
wind speeds to generate designated rated power for the system.
Rated power from most of the machines range from 11 to 15
m/s [10]. For higher power such as a 10 KW generator may not
generate power until 11 m/s wind speed. Hence, harnessing
power from wind energy does not appear feasible.
C. Solar Energy
Due to the geographical location of Liberia in Sub-Saharan
Africa, it has a huge solar energy potential. On average
Sanniquellie receives an average 2601 hours of sunshine a year
[9]. This corresponds to an average overall energy potential of
5.03 KWh/m^2/day [10]. Figure 2 shows the monthly average
irradiation throughout the year. Solar energy potential is
maximum during March, at 5.94 KWh/m^2/day and minimum
during July, at 4.17 KWh/m^2/day. Higher the irradiance,
higher will be the output power from photovoltaics. Irradiance
is maximum during February and March and minimum during
July and August. However, the average is irradiance is high
enough to harness energy throughout the year.
Sanniquellie’s potential for solar energy can be used to
generate electricity using photovoltaic panels. Even though the
technology is expensive, it would quite appropriate for this
region since there is no main grid nearby. Over the years more
efficient photovoltaics has been made. Also, over the years the
prices of photovoltaics have been decreasing. Cell temperature
also plays an important role in power output from
photovoltaics. At higher temperatures, the efficiency tends to
decrease. The efficiency generally drops off at 30 °C. Hence,
efficiency is higher during mornings when it is cooler and less
during the afternoon when it is hotter. The temperature in
Sanniquellie is usually constant throughout the year with
25.4°C [11, 12]. Maximum high average temperature is
experienced during March to May, 27°C with daily maximum
of 32°C. Minimum low temperature is experienced in August,
23°C with daily minimum of 21°C.
0
2
4
6
8
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Monthly average windspeed (m/s)
Minimum average windspeed required (m/s)
Fig. 1. Wind speed assessment in Sanniquellie
0
5
10
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Months
Solar irradiance KWh/m2/day
Fig. 2. Solar potential assessment in Sanniquellie
0
10
20
30
40
Average Temperature (°C) High Temperature (°C)
Low Temperature(°C)
Fig. 3. Average temperature trend in Sanniquellie
Fig. 4. Satellite view of Sanniquellie, Liberia
III. LOAD DEMAND ESTIMATION
Electricity is a novel technology for Liberia. A 4.1% per
capita access to electricity supports that. Generally, the energy
demand forecast is done using previous years data. However,
due to disruption of infrastructure due to the civil war it would
be difficult to estimate trends. In this paper, residential is
estimated using population growth, an annual increase of the
load of people with access to electricity and an annual increase
of connections [11]. It is based on estimation done by World
Bank in urban residential areas of Liberia. Currently, there is
no electricity available in Sanniquellie. The local hospital is fed
through diesel generators. Since Liberia has almost no oil
reserves, it imports oil from other countries. Diesel capital cost
3. has been quoted at 720 $/KW after a review from HOMER
Micropower Optimization community website [24].
Figure 4 shows the satellite view of the Sanniquellie. As
per 2008 census the population of the district is 11,415 [26]. As
per a report from Liberia Institute of Statistics and geo-
information services (LISGIS) the average household size in
Nimba county is 5.6 [27]. As per surveys the inhabitants rural
households allow the estimation of total connected load in the
district [28]. Table 2 shows hypotheses for subscribed power
once the micro-grid is built [28]. The average consumption per
household is calculated to be 5.22 Wh/d. Estimate of the
possible consumption of the district is calculated in Table 3
[13]. A load demand of 11.704 KWh/day from the micro-grid
has been calculated.
TABLE 1.
PARAMETERS FOR COST AND LEVELIZED PRICE OF ELECTRICITY
CALCULATIONS
Upper
Limit
Average Lower
Limit
Sources
11.68 3400 2700 [20]
14.02 11.68 9.34 [20]
247.5 209.95 173.75 [10]
4100 3350 2600 [10]
77.34 64.45 51.6 [10]
3 2 1 [19]
90 80 70 [21]
19 17.5 16 [22], [23]
720 600 480 [30]
0.024 0.02 0.016 HOMER
Micropower
optimization
community website
[31]
0.143 0.119 0.095 [30]
4.8 4 3.2 [30]
90 80 70 Author's
observation in [13]
Fossil capital cost ($/KW)
Fossil O&M ($/kWh)
Fossil fuel consumption
(gal/kWh)Fossil fuel costs ($/gal)
Fossil duty factor(%)
Biomass capital Costs
($/kWp)Biomass O&M ($/kWp)
Biomass fuel costs (W/m2)
Biomass duty factor (%)
Biomass heat rate
Small Diesel
Parameter
Solar PV
Solar capital Costs ($/kWp)
Solar O&M ($/kWp)
Insolation (W/m2)
Small biomass
TABLE 2.
AVERAGE LOAD ESTIMATION OF ENERGY CONSUMER PER HOUSEHOLD
Parameter Number Power (W) Operation
time (h/d)
Daily
consumption
(Wh/d)
Monthly
Consumption
(Wh/d)
Economic lamps 3 11 3 99 2.97
Radio 1 15 5 75 2.25
Total 4 26 8 174 5.22
TABLE 3.
DAILY CONSUMPTION OF SANNIQUELLIE
Parameter Value Sources
Population 11415 Liberia Census
Yearly population
increase
2% United Nations
2011
Daily consumption in
one house (Wh/d)
5.22
Daily consumption of
district (Wh/d)
11704.452
IV. ESTIMATING CAPITAL COSTS AND PRICING
Overnight capital costs do not include the time of
constructing a project and costs are placed in present time. The
costs are calculated using the average cost of technologies
across the world. However, data collected from local biomass
projects align in line with the world averages [4, 29, 30]. PV in
liberia have been estimated to be 60% higher than world
averages [13]. However, this paper assumes the PV project of
large scale public or private investment to be in line with the
world averages. Transmission and distribution are also
expected to be similar for all power source technologies. The
capital, Operation and maintenance, fuel costs in Solar,
biomass and Diesel plants have been discussed in Table 1 [13].
A servey was conducted by Winrock International among a
sample of people of Liberia. The servey results showed huge
determination in people to get electricity and showed
wilingness to pay the bill. However, the servey was conducted
in Bong county which is near a Hydro power plant which was
destroyed during the war. The locals were willing to pay upto
$10 per month electricity bill per household. Areas of Liberia
with access to electricity spend an average of $13 per month of
the electricity bill. This load is mostly lighting. Currently
household spend on expensive energy solutions such as
kerosene lamps ($1.53/KWh), diesel generators ($3.96/KWh)
and candles ($8.27/KWh) to meet their demands [7]. Using the
parameters mentioned in Table 1 and Table 2 the monthly bill
per household is calculated using solar and biomass energy.
The load factor for PV is assumed to be 0.25 and 0.55 load
factor is taken for biomass plant [10]. A discount factor of 3%
gives us a capital recovery factor of 1.5 [13].Hence, the
average monthly bill of one household calculated is shown in
Table 4 [13]. Monthly average bill estimation is $7.17 per
month from PV based power source and $7.57 per month from
biomass based power source.
Hence, Liberia has a decent renewable enrgy potential.
Seting a micro-grid with a renewable source will provide a
cheap and reliable uninterrupted power supply. When
compared to equavalent prices charged by privately own
generators which charge tarrif rate of $0.54/KWh, amounts to a
monthly bill of $84.56. This supply is also ureliable and subject
to interruption [5].
4. TABLE 4.
AVERAGE MONTHLY HOUSEHOLD BILL CALCULATION FROM SOLAR AND
BIOMASS ENERGY
Parameter solar biomass Diesel Units
Capital Recovery Factor 1.500001611 1.5000016
Price ofelectricity 45.81459093 48.396845 0.54 $/KWh
Monthly bill ofone household 7.17456494 7.5789459 84.564 $
load factor 0.25 0.55
V. MICROGRIDS
Renewable energy implementation in recent years
have increased substantially around the world [33]. Although,
the cost of making use of these resources in populated areas
does not compare to the price of electricity from the main grid
that use energy dense materials, considering the losses and
extension costs [34]. Shifting focus away from highly
electrified areas, renewables have assumed a significant role
for underdeveloped areas [35, 37-39]. Microgrids(MG) have
become the leading venture for implementing electrical
systems to previously unreachable areas. A MG is a system of
connected loads in a local area usually disassociated from a
main utility grid [36]. The benefits to the environment and
people are significant, but all issues must be mitigated for
appropriate use. The purpose here is to review the analysis and
impacts of MGs in order to form an outline best suited for
Sanniquellie.
A. Social Impact
Poverty and under education has been linked to the
availability of electricity of which a MG could alleviate
[40,42]. Microgrid Electrification of these rural areas would
also reduce the trend of urbanization of overpopulated areas
[41], making it beneficial for health and main grid stability.
The difficulty of attaining diesel due to poor or lack of
infrastructure would be mitigated, and even lead to a more
stable economy [33, 43]. For areas like Sanniquellie the
electric resource would benefit the community significantly
B. Environmental Impact
Effect on the environment is an important issue to raise
when planning any type of development. Reducing the effect
of climate change is commonly coupled with renewables.
Ultimately leading to a reduced dependency on limited
resources [44]. MG placement on degraded land can also
provide indirect conditioning to help reestablish soil stability
[50]. Although predominantly thought of as only beneficial to
the environment, tradeoffs to be aware of do arise [33].
Renewable energy setups can disturb movement of species
[45], soil deposition [46], disturb organic C dynamics [47,48],
as well as disrupting the albedo balance and surface roughness
[49].
C. System Variations
Many MG systems have been analyzed and have been
implemented in remote locations. MG systems can range from
stand-alone PV systems to hybrid renewable energy systems
(HRES).
The stand-alone systems have been found to be suitable
solutions to remote low load areas. These systems provide
simple local energy with equivocal cost. Stocastic optimal
planning can maximize the collection of this method [58].The
main issue with a singular source is lack of reliability due to
irregularity of renewable energy.
HRES have multiple power sources integrate into one MG
system in order to achieve reliability and cost effective output
[37]. Multiple resource harnessing leads to stable
electrification. PV-wind hybrid system introduced in Kuala
Terengganu, Malaysia, examined a single optimizatioin point
based on system cost and total load losses [51]. In HOMER,
PV-wind hybrid coupled with hydrogen reserve gave insight
to western coast Moroccan implementation [53]. Many
systems involve the use of battery storage systems. A MG
using wind-solar and lead-acid battery storage has been used
in a small village in South Africa [52]. A techno-economic
idea using wind-solar hybrid has shown to be beneficial in
urban high-rise application in Malaysia, featuring collection of
clean rainwater [54]. If available, hydro can be incorporated
into a MG design for low-cost electricity as shown in Ikaria,
Greece [55]. Wind-PV-biomass and hydro hybrid has been
studied to meet the load demand of Jaunpur of Uttaranchal
state, India as shown in figure 5 [56]. Analysis of a fuel cell
MG with a small-scale wind turbine generator attacked the
supply-and-demand error to determine ways to increase
generation efficiency.
Diesel integrated, albeit not renewable, provides
reliability and durability to the isolated system. In one study
wind-diesel generator-battery, wind-PV-diesel generator-
battery, PV-diesel generator-battery, and diesel generator
HREV systems were assessed, concluding a 38% decrease in
CO2 emissions and significant performance after pairing [57].
A rural hybrid diesel-solar-hydro-fuel cell system designed for
ICT Telecenter in the Kelabit highland of Sarawak, Bario
village, simulated an efficiency range between 15-75%
compared to Stand alone achieving only 10% , using HOMER
[59].
Fig. 4. PV-Wind-Diesel-Battery set up [37]
5. D. Storage
Deciding on battery type is a significant part of planning a
MG due to uncertain energy availability. Lead acid batteries
are popular in MG settings due to availability as well as cost
[41]. Sizing of batteries analyzed with the improved Bat
Algorithm suggested optimal size considering battery energy
storage, minimization of cost per day, and minimize
charging/discharging of battery energy storage [60]. A study
shows useful charging methods in MG PV systems results in
reducing charge time and adjusts according to solar radiation
by way of the state of charge [61]. Battery cycle life is also
studied for the reliability and capacity when introduced to
irregular insolation from a PV system [62].
E. Control
Control strategies are vital to the implementation of a MG.
A strategy for integration of PV and energy storage provides
maximum utilization of power and smooth transfer of grid
connections with inherent variations in load and solar radiation
[63]. For an AC/DC bussed system, a study has discussed a
robust multi-objective control using voltage source control
based DC-voltage power port in a HRES. This control includes
disturbance rejection, eliminates feed forward control, stable
DC adjustments, and a linear control structure [64].
F. Protection
Protection schemes for MG systems tend to vary due to
many types of hybrid systems being developed. Several issues
are faced regarding each type of protection. Some issues
relating to protection schemes are cost of communication,
knowledge of specifics of every operation mode, admittance on
short lines, and misoperation due to irregularity of voltage [65].
VI. CONCLUSION
The information collected on the natural resources in the
region of Sanniquellie, Liberia in combination with the
reviewed literature about MG systems a general outline can be
made. Since there is significant solar insolation and abundant
resources to utilize biomass, PV-biomass HRES would be best
suited for the selected location. Also, a diesel backup generator
should be considered after determining the reliability of the
system. Considering the load of simple lights and radios the
HRES along with the multi-connection control system could
establish a viable power control option for the smoothing and
storage of energy allocation. This process in addition to the
stability will allow for future expansion to the system. The
batteries for storage would be the easily accessible and low
cost lead acid battery, optimized by the additional control of
battery charging cycle life, could last several years. Lastly,
protection of the MG will be a persistent issue. The system
would have to be implemented to develop a specific protection
unique to the MG. The next step for this project would be to
develop a cost analysis of the specific HRES needed,
considering the cost of materials, maintenance, and
government subsidies.
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