BD. Soon & CL. Wooi /Future Sustainability                                                                      November 2023| Volume 01 | Issue 01 | Pages 
32-38 

32 

 

 

 

Article 

Design and analyzing a hybrid hydro and solar 

photovoltaic system for rural areas in Malaysia 
Brian Dean Soon1*, Chin-Leong Wooi2 

1Faculty of Engineering, Computing, and Science Swinburne University of Technology Sarawak Campus Kuching, Malaysia 
2Centre of Excellence for Renewable Energy (CERE), School of Electrical System Engineering, Pauh Putra Main Campus 

Universiti Malaysia Perlis, 02600, Arau, Perlis, Malaysia 

               A R T I C L E   I N F O 
 

Article history: 
Received 02 September 2023  
Received in revised form 
03 October 2023 
Accepted 10 October 2023 
 
Keywords:  
Renewable energy, Hybrid renewable energy 
systems (HRES), Microgrid, Hydropower,  
Solar photovoltaic (PV) 
 
*Corresponding author 
Email address: 
101211463@students.swinburne.edu.my 
 
 
DOI: 10.55670/fpll.fusus.1.1.4 
 

A B S T R A C T 
 

Some rural areas worldwide, including Malaysia, are not electrified due to 
geographical constraints, less infrastructure development, and isolation from 
the main power grid. In addition, renewable energy (RE) sources are 
considered alternatives to replace conventional (non-RE) sources that cause 
pollution. However, RE sources have limitations, such as the dependency of 
weather and geological conditions. To address this issue, a hybrid renewable 
energy system (HRES) is introduced by connecting one RE and non-RE source 
or more than one RE with or without non-RE sources. In this study, a stand-
alone hybrid hydro and solar photovoltaic (PV) HRES was designed for Rumah 
Bada in Nanga Talong, Ulu Engkari. As the site has limited information on load 
consumption and geographical data, estimations were done based on similar 
studies. The available solar PV and hydro system at the site was identified with 
the respective parameters. The proposed system was based on the hybrid AC-
DC microgrid, along with two alternatives based on the AC and DC microgrid, 
respectively. Technical analysis was done to find out the capability of the system 
by calculating the power generated during different periods and performing the 
load flow analysis using the PowerWorld Simulator. Apart from that, economic 
analysis was done to find out the most cost-efficient system by calculating the 
net present cost (NPC) and cost of energy (COE) using HOMER Pro.   

 

1. Introduction 

Renewable energy (RE) sources such as solar, wind, and 
hydro are considered alternatives for power generation. 
However, RE in stand-alone has limitations, such as the 
dependency on weather and geological conditions. Hence, a 
Hybrid RE System (HRES) is developed for a more reliable 
and sustainable energy supply with RE by combining one RE 
and one non-RE, or more than one RE (with or without non-
RE) together as one system [1]. In Malaysia, efforts to use RE 
for power generation have been made in the past few years. 
As of December 2020, the total installed capacity of RE in 
Malaysia was 8,450 MW, which accounts for 23% of the total 
installed capacity [2]. The most installed capacity of RE is 
large hydro, followed by solar photovoltaic (PV), small hydro, 
biomass, and biogas. However, most of these RE sources are 
installed as individual power stations. The coverage of rural 
electricity supply is increased to 98% in the 11th Malaysia 
Plan [3] and will continue to achieve 99% in 2025 in the 12th 
Malaysia Plan [4]. Other efforts, such as the Sarawak 
Alternative Rural Electrification Scheme (SARES) and Sabah 
Renewable Energy Rural Electrification (RE2) Roadmap, are 
done to accelerate rural electrification in East Malaysia, which 

has some remote villages isolated by the terrain. Hence, this 
project aims to design and optimize a hybrid hydro and solar 
PV system for a selected rural area in Malaysia. 

2. Literature review  

There are numerous configurations for hybrid hydro and 
solar PV systems in Malaysia and other countries. These 
models are dependent on the RE resources available and the 
price of components for the system. In short, the 
configurations of HRES can be classified into two categories: 
stand-alone (off-grid) and grid-connected (on-grid). Off-grid 
HRES is a system that generates power and supplies the loads 
connected without relying on the grid. As the primary energy 
source (which is RE) is stochastic in nature, energy storage 
technologies (for example, battery energy storage systems 
(BESS), supercapacitors, and flywheels) are normally 
connected to the system to store energy during the absence of 
RE [5]. In on-grid HRES, the system is connected to the grid, 
which enables the buying and selling of power from the grid 
to compensate for the variability of RE systems [5, 6]. A 
feasibility study of a stand-alone hybrid PV-hydrokinetic 
turbine (HKT) system was conducted for a rural village, 

Future Sustainability 

Open Access Journal 

https://doi.org/10.55670/fpll.fusus.1.1.4 

 

 

 

 

 

 

 

 

 

 

November 2023| Volume 01 | Issue 01 | Pages 32-38 

Journal homepage: https://fupubco.com/fusus 

 
ISSN 2995-0473 

mailto:101211463@students.swinburne.edu.my
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BD. Soon & CL. Wooi /Future Sustainability                                                                      November 2023| Volume 01 | Issue 01 | Pages 32-38 

33 

 

Kampung Git, in Sarawak, Malaysia [7], which was compared 
with a PV-battery system and diesel generator (DG) system. It 
was found that the proposed system had the lowest levelized 
cost of energy (LCOE) and net present cost (NPC) of 
RM1.21/kWh and RM1,431,000, respectively. Based on the 
renewable energy fraction (RF), PV contributes 66% of 
energy due to the larger size of 89.9 kW, as compared to the 7 
kW HKT system at the remaining 34%. Another study 
conducted for Mboke, Ihiagwa, Nigeria [8] proposed a stand-
alone PV-hydro-DG battery system due to the unstable grid 
supply. The system was compared with PV-hydro-battery, 
PV-DG-battery, and PV-DG system and was found to be the 
most optimized system with NPC of US$963,431 and COE of 
US$0.112/kWh. Although the PV-hydro-battery system is 
more environmentally friendly, it is not economically friendly 
as the NPC and COE are 125% and 127% more than that of the 
optimized system. Grid-connected hybrid hydro and solar PV 
systems were studied in ref [9] and ref [10]. Sabudin et al. [9] 
designed and simulated a grid-connected PV-hydro-battery 
system for Kampung Lepok, Kuala Selangor, Malaysia. The 
system was compared with PV-hydro (without battery) and 
hydro-battery systems, both grid-connected. The feasibility is 
based on RF and NPC, and it was concluded that the PV-hydro 
fulfilled the criteria with 9.12% RF and NPC of RM4.83 
million. By comparing the battery-hydro-grid and PV-battery-
hydro-grid systems, it was found that the largest RE 
contributor is hydro at 7.7%, followed by PV at 1.5%. The 
main supply of the system relies on the grid at 90.8%. 
Syahputra, and Soesanti [10] investigated the potential of a 
grid-connected PV-hydro-battery system in Banjarharjo 
Village, Yogyakarta, Indonesia. The comparison was made 
between similar systems with different capacities of solar PV 
from 0 to 40 kW, and the system with 0 kW solar PV (without 
PV) is the most optimal system due to the cost saved from not 
using a PV system, and the 622 kW micro-hydro system being 
sustainable, thanks to the strong flow rate of 6,500 L/s. To 
simulate and analyze the HRES design, several software has 
been used in various studies. One of the software is HOMER. 
Developed for both on-grid and off-grid systems by the 
National Renewable Energy Laboratory (NREL) in 1993 [11], 
HOMER is commonly used for the design and techno-
economic analysis of HRES. Another software is the 
PowerWorld Simulator, commonly used for power system 
applications. It is more popular than other simulation tools as 
it can display power flow, voltage, and other parameters in 
real-time animation, which helps users visualize the situation 
in a complex power system [12]. HRES functions in the form 
of a microgrid, which is defined as a self-sufficient energy 
system formed with local power generating units along with 
energy storage devices and controllable consumer load 
within clearly considered electrical borders [13]. Generally, 
HRES microgrids are classified into three types: AC 
(alternating current), DC (direct current), and hybrid AC-DC 
microgrids. AC microgrids can be further classified as 
centralized and decentralized AC microgrids. These 
configurations are different in terms of the bus involved and 
the number of components used. 

3. Methodology  

The research was done in several stages. Initially, the site 
was decided, and the geographical data (solar irradiance and 
flow rate) was obtained based on databases and similar 
studies. Next, the load demand of the site was estimated, and 
the specifications were identified. After that, the calculation of 
power generated by the different stand-alone systems at the 
site was done with the geographical data. Finally, 

optimization and simulation of the HRES design were done in 
PowerWorld Simulator and HOMER Pro, followed by techno-
economic analysis and comparison with alternative systems. 

3.1 Location details 
The proposed site for this project is Rumah Bada, which 

is located in Nanga Talong, Ulu Engkari (coordinates: 
1°23'22.69"N, 111°59'6.63"E). The nearest towns are Sri 
Aman and Lubok Antu. Figure 1 shows the aerial view of 
Rumah Bada. It is an Iban settlement with 30 households. The 
daily activities of the community are fishing, farming, and 
being a part-time National Park ranger. 

 
Figure 1. Aerial view of Rumah Bada 

 
3.2 Geographical data 
3.2.1 Solar-related data 

The monthly average solar global horizontal 
irradiance (GHI) is obtained from NREL and is shown in 
Figure 2. The daily radiation and clearness index was the 
lowest in January, with 4.552 kWh/m2/day and 0.459, 
respectively. The two values have a peak at different months, 
at 4.934 kWh/m2/day in March and 0.492 in August. The 
average values are 4.767 kWh/m2/day and 0.4765, 
respectively. 

 
Figure 2. Monthly average solar global horizontal irradiance (GHI) 

 
3.2.2 Hydro-related data 

The river near Rumah Bada is the Engkari River, which 
is one of the tributaries of Batang Lupar, a downstream river 
of Batang Ai dam. Due to the remoteness of the area, it is not 
possible to obtain direct data on the Engkari River. Hence, the 
hydro data of the river is reasonably estimated based on a 



BD. Soon & CL. Wooi /Future Sustainability                                                                      November 2023| Volume 01 | Issue 01 | Pages 32-38 

34 

 

case study analysing the potential of rural sustainable energy 
supply in the Baram River Basin, Sarawak [14]. Based on 
Figure 3, the monthly average flow rate has a maximum of 23 
L/s in April and a minimum of 11 L/s in July and October. The 
annual average flow rate is 17 L/s. 

 
Figure 3. Assumed monthly flow rate 

 

3.3 Load demand 
Due to the unavailability of site data related to the load 

demand in Rumah Bada, estimations will be done based on a 
study on the electricity consumption of rural villages that 
benefit from SARES [15]. Since all 30 households live in the 
same longhouse, it is expected that each household uses the 
same electrical appliances with a similar pattern of load 
demand. It is also assumed that the room for each household 
has one living room, two bedrooms, one kitchen, and one 
toilet. The load demand estimation is done for a typical day, 
and all appliances are assumed to be used. Table 1 shows the 
load estimation of one household in Rumah Bada. The daily 
load demand per household is estimated to be 2915 Wh 
(2.915 kWh). Based on this value, the daily load demand of 
Rumah Bada is 87.450 kWh. The load profile for the entire 
longhouse is illustrated in Figure 4. 

Table 1. Load estimation of one household in Rumah Bada 

Appliance 
Power 
Rating 
(W) 

Quantity 
Duration 
(hour) 

Load 
(W) 

Energy 
(Wh) 

Lamp 10 5 4 50 200 

TV 60 1 2 60 120 

Radio 20 1 1 20 20 

Table Fan 35 3 5 105 525 

Refrigerator 75 1 24 75 1800 

Rice Cooker  500 1 0.5 500 250 

Total 810 2915 

 

3.4 Components of hybrid hydro and solar PV system 
The proposed HRES for Rumah Bada is a stand-alone PV-

hydro-battery system. This is because the site has an 
independent PV system and hydro system under the initiative 
of SARES. It is worth noting that the capital cost, replacement 
cost, and operational and maintenance (O&M) cost are based 
on reasonable estimations from other studies due to the 
customization nature. The entire project is projected to have 
a lifetime of 25 years.  

3.4.1 Solar PV system 
The existing solar PV system in Rumah Bada was 

launched for operation in June 2019. The system consists of 

270 Wp polycrystalline PV panels connected in 6 strings with 
20 panels each in series. With a peak power of 32.4 kW, it is 
the main electricity source for the local community. The 
system has a capital cost of RM5015/kW; the same goes for 
the replacement cost. O&M cost is negligible, as minimal 
maintenance is required besides cleaning and dusting. The 
efficiency is estimated to be around 15% to 22%, and the 
lifetime of this system is 25 years. 

Figure 4. Load demand of a typical day for all households in Rumah 
Bada 

3.4.2 Hydro system 
The existing hydro system in Rumah Bada is a pico-

hydro system and was launched for operation in May 2018. 
The pico-hydro system acts as a supporting system and has a 
power capacity of 10 kW. The system is commonly used for 
lighting purposes whenever necessary. Both the capital cost 
and replacement cost are RM5000/kW. The O&M cost is 
RM250, mainly used for the maintenance of moving parts in 
the hydro turbine. The designed flow rate for the pico-hydro 
system is 25 L/s. The efficiency is 80%, and the lifetime is 25 
years. 

3.4.3 Battery 
For the PV system in Rumah Bada, a lithium-ion (Li-

ion) battery system with a capacity of 165 kWh is used. The 
capital cost is RM555/kWh, and the same goes for the 
replacement cost. Similar to solar PV systems, the O&M cost 
is negligible as the battery will be replaced immediately once 
it malfunctions. Depth of discharge (DoD) is 85%, and the 
lifetime is five years. 

3.4.4 Inverter 
In Rumah Bada, the PowerCube 5000 MicroGrid 

Inverter by Huawei Corporation is used to convert the DC 
power of solar PV systems and batteries into AC power for 
distribution. The specifications of the components in the 
system are given in Table 2. 

Table 2. Specifications of components in the system 

Parameter PV Hydro Battery Inverter 

Capital Cost 
RM5015
/kWp 

RM5000
/kW 

RM555/kW
h 

RM1635
/kW 

Replacement 
Cost 

RM5015
/kWp 

RM5000
/kW 

RM555/kW
h 

RM1635
/kW 

O&M Cost - RM250 - RM50 

Lifetime 25 years 25 years Five years 15 years 

Efficiency 
15 – 
22% 

80% - 96% 

Power 
Capacity 

32.4 
kWp 

10 kW 165 kWh 33 kW 



BD. Soon & CL. Wooi /Future Sustainability                                                                      November 2023| Volume 01 | Issue 01 | Pages 32-38 

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The system has six strings, with five batteries in each string. 
Both the capital cost and replacement cost are RM1635/kW. 
The O&M cost is RM50. The inverter has an efficiency of 96% 
and a lifetime of 15 years. 

3.5 Relevant equations 
In HRES design, technical and economic calculations are 

done to ensure the system will be able to fulfill the load 
demand and benefit the community economically.  

3.5.1 Technical calculations 
The generated solar PV power, PPV, can be obtained 

with Equation 1 [5]. 

𝑃𝑃𝑉 =
1

1000
∑ 𝐺𝐻𝐼(𝑡)24

𝑡=1 × 𝐴𝑃𝑉 × 𝑁𝑃𝑉 × ηPV (𝑘𝑊)           (1) 

Where GHI is the global horizontal irradiance (in 
kWh/m2/day), APV  is the surface area of solar PV panels (in 
m2), NPV is the number of solar PV panels, hPV is the solar PV 
panel efficiency (in %) (generally between 15% and 22%), 
and t is time of the day (in hours). 
By assuming the daily energy produced is constant 
throughout the year, the annual hourly energy generation, 
AEPPV can be obtained with Equation 2Error! Reference s
ource not found.. 

𝐴𝐸𝑃𝑃𝑉 = 𝑃𝑃𝑉 × 8760 (𝑘𝑊ℎ)                                                         (2) 

The power from falling water, PHY,avg can be obtained with 
Equation 3 [5].  

𝑃𝐻𝑌,𝑎𝑣𝑔 =
𝑚×𝑔×ℎ𝑛×𝜂

1000
 (𝑘𝑊)                             (3) 

Where m is the mass flow rate (in L/s), g is the gravity 
acceleration (= 9.81 m/s2), hn is the net head (in m) and h is 
the efficiency (generally between 75% and 95%). 
From here, with the power available for one year (365 days in 
hours), the annual energy produced from the hydro turbine, 
AEPHY is obtained with Equation 4. 

𝐴𝐸𝑃𝐻𝑌 = 𝐶𝐹 × ∑ 𝑃𝐻𝑌,𝑎𝑣𝑔,𝑑
365
𝑑=1  (𝑘𝑊ℎ)                                         (4) 

Where CF represents the capacity factor, which is the ratio of 
the annual energy produced by a hydro system to the 
theoretical maximum if the system operates 24/7 at 
maximum output power. 
The required battery size, Creq in ampere-hour (Ah), is 
computed with Equation 5 [16]. 

𝐶𝑟𝑒𝑞 =

𝑊𝑑𝑒𝑚𝑎𝑛𝑑(𝐷𝐶)

𝑉𝐷𝐶
×𝑁𝑠𝑡𝑜𝑟𝑎𝑔𝑒

𝐷𝑂𝐷×𝐷𝐹𝑏𝑎𝑡𝑡
(𝐴ℎ)                                                       (5) 

Where Wdemand(DC) is the average daily DC load demand during 
critical months, VDC is the system bus DC voltage, Nstorage is the 
design autonomy period (in days),  DOD is the depth of 
discharge, and DFbatt is the derating factor (including 
temperature and wiring losses). 
The battery capacity in kWh is expressed in Equation 6. 

𝐶𝑟𝑒𝑞 =
𝑊𝑑𝑒𝑚𝑎𝑛𝑑(𝐷𝐶)×𝑁𝑠𝑡𝑜𝑟𝑎𝑔𝑒

𝐷𝑂𝐷×𝐷𝐹𝑏𝑎𝑡𝑡
(𝑘𝑊ℎ)                                                (6) 

Load flow analysis is important in the power system study 
and is calculated by equation 7 & 8. The analysis is aimed to 
calculate and evaluate the important parameters of a test 
system, which are the sinusoidal steady state of system 
voltage, generated (P) and reactive (Q) power, and 
transmission losses. Single-line diagrams and per-unit 
systems are commonly used in this analysis [17]. Based on 
Kirchhoff's current law, the current at ith bus is: 

𝐼𝑖 = 𝑦𝑖0𝑉𝑖 + 𝑦𝑖1(𝑉𝑖 − 𝑉1) + 𝑦𝑖2(𝑉𝑖 − 𝑉2) + ⋯ + 𝑦𝑖𝑛(𝑉𝑖 − 𝑉𝑛) =
(𝑦𝑖0 + 𝑦𝑖1 + ⋯ + 𝑦𝑖𝑛)𝑉𝑖 − 𝑦𝑖1𝑉1 − 𝑦𝑖2𝑉2 − ⋯ − 𝑦𝑖𝑛𝑉𝑛                 
            (7) 

𝐼𝑖 = 𝑉𝑖 ∑ 𝑦𝑖𝑗
𝑛
𝑗=0 − ∑ 𝑦𝑖𝑗

𝑛
𝑗=0 𝑉𝑗        (𝑗 ≠ 𝑖)                               (8) 

The complex power at ith bus is calculated based on the 
equation 9 & 10: 

𝑆𝑖 = 𝑃𝑖 + 𝑗𝑄𝑖 = 𝑉𝑖𝐼𝑖
∗                                                                            (9)  

𝐼𝑖 =
𝑃𝑖−𝑗𝑄𝑖

𝑉𝑖
∗                                                                                          (10) 

From Equations 8 and 10, 

𝐼𝑖 =
𝑃𝑖−𝑗𝑄𝑖

𝑉𝑖
∗ = 𝑉𝑖 ∑ 𝑦𝑖𝑗

𝑛
𝑗=0 − ∑ 𝑦𝑖𝑗

𝑛
𝑗=0 𝑉𝑗     (𝑗 ≠ 𝑖)                       (11)  

3.5.2 Operational and economical calculations 
LCOE is a standardized method used for the evaluation 

of the cost of an energy source to produce a unit of energy 
(RM/kWh) across the lifespan of the project. This approach 
helps to determine the most suitable energy source at a 
specific location in the economic comparative analysis [5]. In 
HOMER, COE is formulated as such in Equation 12. 

𝐶𝑂𝐸 =
𝐶𝑎𝑛𝑛,𝑡𝑜𝑡−𝑐𝑏𝑜𝑖𝑙𝑒𝑟𝐻𝑠𝑒𝑟𝑣𝑒𝑑

𝐸𝑠𝑒𝑟𝑣𝑒𝑑
 (𝑅𝑀/𝑘𝑊ℎ)                                (12) 

Where Cann,tot is the total annualized cost of HRES, cboiler is the 
marginal cost of the boiler, while Hserved and Eserved represent 
the total thermal and electrical load served, respectively. 
Since there is no boiler in the system, COE is formulated as 
such in Equation 12 and expressed in Equation 13. 

𝐶𝑂𝐸 =
𝐶𝑎𝑛𝑛,𝑡𝑜𝑡

𝐸𝑠𝑒𝑟𝑣𝑒𝑑
 (𝑅𝑀/𝑘𝑊ℎ)                                       (13)  

In general, NPC is the total cost throughout the project 
lifespan, which includes installation, replacement, and O&M 
costs. When the total project cost is analyzed, the difference 
between the present revenue generated and the cost spent 
during the project lifetime is calculated. NPC is formulated as 
such in Equation 14 [7]. 

𝑁𝑃𝐶 =
𝐶𝑎𝑛𝑛,𝑡𝑜𝑡

𝐶𝑅𝐹
× 𝐼 × 𝑅                                                                    (14)  

Where CRF is the capital recovery factor, I is the annual 
interest rate, and R is the project lifetime. 

4. Results and discussion 

The proposed design of the system will be based on the 
hybrid AC-DC HRES microgrid. In this configuration, the pico-
hydro system is connected to the AC bus, while the solar PV 
and battery systems are connected to the DC bus. As the HRES 
provides electricity to an AC load, the DC bus is connected to 
the AC bus via the Huawei PowerCube 5000 Microgrid 
Inverter. Figure 5 shows a schematic of the proposed design. 
For comparison purposes, two alternative designs are 
proposed based on the centralized AC and DC HRES 
microgrid, respectively. In short, the components will be 
collected to a common bus, and the component that operates 
differently from the bus will be connected to a power 
converter. After performing the necessary calculations and 
simulation, the results and techno-economic analysis are 
presented in this section. 

4.1 Technical analysis 
The technical analysis is done by calculating the power 
generated by each component during different periods and 
performing the load flow analysis for the proposed and 
alternative configurations. 



BD. Soon & CL. Wooi /Future Sustainability                                                                      November 2023| Volume 01 | Issue 01 | Pages 32-38 

36 

 

 
Figure 5. Simple schematic of the proposed design 

 

4.1.1 Power calculation during different periods 
The average daily radiation of 4.767 kWh/m2/day is 

used for the calculation of power generated by solar PV 
systems. The efficiency of the solar PV panels is assumed to 
be 20%. The power and energy generated by the system are 
computed by using Equation 1 and multiplying the equation 
together with 12 hours, respectively. Table 3 represents the 
calculation of the average daily power and energy generated 
by solar PV systems. 

Table 3. Calculated average daily power and energy generated by a 
solar PV system 

Daily radiation (kWh/m2/day) 4.767 

Average daily power generated 
(kW) 

22.4716 

Average daily energy generated 
(kWh) 

269.6592 

 
The power supplied by the pico hydro system is assumed for 
two scenarios: low and high flow rates. The average low and 
high flow rates are taken as 14 L/s and 21 L/s, respectively. 
CF is taken as 0.771. The power and energy generated by the 
system are computed by using Equation 1 and Equation 2 
divided by 365 days. Table 4 shows the calculations of the 
average daily power and energy generated by the Pico hydro 
system. 

Table 4. Calculated average daily power and energy generated by the 
pico hydro system  

 Average low Average High 

Flow rate (L/s) 14 21 

Average daily power 
generated (kW) 4.9442 7.4164 

Average daily 
energy generated 
(kWh) 

91.4875 137.2331 

 

4.1.2 Load flow analysis 
The load flow analysis is done for the proposed and 

alternative configurations on the PowerWorld Simulator and 
is shown in Figure 6. The respective circuits are constructed, 
followed by the input of power capacity for each component. 
Due to the varying nature of output power during charging 
and discharging, the battery is set as the slack bus for each 
system. The simulation results for the three systems are 
obtained and summarised in Table 5. 

 
Figure 6. Load flow simulation for hybrid AC-DC microgrid 

 
Table 5. power of each component in different HRES design 

 

It was found that the solar PV and pico hydro systems are 
able to generate the specified real power (32 kW and 10 kW, 
respectively). In terms of reactive power, the two systems in 
the hybrid AC-DC microgrid have zero reactive power. In 
comparison, the reactive powers of the AC and DC microgrid 
are 32 kVAR and ten kVAR, respectively, which is contributed 
by the power converter connected to the components. Table 
5 shows the power values of each component in different 
HRES designs. The battery in each configuration is charged 
with different amounts of power. The battery is charged the 
most in the DC microgrid with 48 kW and the lowest in the AC 
microgrid with 17 kW. Nonetheless, no reactive power is 
supplied to the battery for each case. Also, the load demand of 
25 kW can be fulfilled by each configuration without reactive 
power. Another simulation shown in Figure 7 is done on the 
proposed design to identify the capability to supply power at 
night or when the solar PV system is unable to fulfil the load 
demand.  

 

 

 

 

 

 

Figure 7. Load flow simulation for hybrid AC-DC microgrid (without 
solar PV) 

This simulation is done by setting the solar PV power to 0 kW 
while maintaining the parameters of other components. 

4.2 Economic analysis 
The economic analysis is done by inserting the necessary 

inputs of each component for the proposed and alternative 

Design 
Hybrid AC-
DC 

AC DC 

Solar PV 
Real (kW) 32 32 32 
Reactive 
(kVAR) 

0 32 10 

Pico 
Hydro 

Real (kW) 10 10 10 
Reactive 
(kVAR) 

0 32 10 

Battery 
Real (kW) -42 -17 -48 
Reactive 
(kVAR) 

0 0 0 

Load 
Real (kW) 25 25 25 
Reactive 
(kVAR) 

0 0 0 

 



BD. Soon & CL. Wooi /Future Sustainability                                                                      November 2023| Volume 01 | Issue 01 | Pages 32-38 

37 

 

configurations and performing the simulation using HOMER 
(Table 6). 

Table 6. Economical results for the different HRES designs 

Design Hybrid AC-DC AC DC 

NPC (RM) 568,887 618,156 629,484 

COE (RM/kWh) 1.38 1.50 1.53 

Operating Cost 
(RM/yr) 

16,313 16,256 17,094 

Initial Capital (RM) 358,000 408,000 408,500 

Replacement (RM) 211,321.21 
209,624.1
1 

222,564.4
7 

O&M Cost (RM) 3,878.25 4,524.63 4,847.82 

Salvage (RM) -4,312.04 -3,992.63 -6,428.14 

 
The main economic parameters used to compare the 

different HRES designs are the NPC and COE. Based on Table 
6, the most economical HRES design is the proposed hybrid 
AC-DC microgrid with an NPC of RM568,887 and a COE of 
RM1.38/kWh. In comparison, the AC and DC microgrids have 
slightly higher NPC and COE, at about 110% of the proposed 
design. From Figure 8, the initial capital contributes the most 
to the NPC due to the budget spent on installation. However, 
the capital cost is not a major concern, as most components 
are installed beforehand. The replacement cost also 
contributes significantly to the NPC, as the batteries are 
replaced once every five years. It is worth noting that the RE 
sources are only replaced after the project lifetime, thus not 
contributing to the replacement cost. The O&M cost takes up 
a small portion of NPC, as it only comprises the maintenance 
for the pico hydro turbine and converter. 

 
Figure 8. NPC summary for hybrid AC-DC microgrid 

 

4.3 Discussion 
From the power calculation for HRES components at 

different periods, the solar PV and pico hydro systems are 
unable to reach the maximum power capacity with the 
geographical data. However, the generated power is sufficient 
to fulfill the load demand of Rumah Bada. From a technical 
perspective, the optimal system should have minimal reactive 
power in each component, as reactive power causes 
additional load, overheating, and power loss on the cables and 
system equipment. Based on the technical analysis, the 
proposed system is the most feasible system with the least 
reactive power. In terms of battery charging, the DC microgrid 
is more favorable as the system provides the most power to 
charge the battery. Despite that, the battery in the proposed 

system only requires to supply 15 kW when the solar PV 
system is unable to supply to Rumah Bada. From an economic 
perspective, the proposed hybrid AC-DC microgrid is also 
proven to be the most feasible system with the lowest COE 
and NPC. Although the proposed system will require a 
complex control system to facilitate the power flow, the 
proper utilization of components helps to reduce the overall 
cost. In comparison, the alternative systems have a simpler 
control system but will require more converters and power 
correction equipment, which contributes to the higher overall 
cost. 

5. Conclusion 

In conclusion, an HRES is proposed and designed for 
Rumah Bada, a longhouse located in Nanga Talong, Ulu 
Engkari. Due to the remoteness of the location, the 
geographical data was obtained based on databases and 
relevant studies. The load demand of Rumah Bada was 
estimated with an average consumption pattern based on 
relevant studies. The specifications of HRES components 
were identified. With that, the HRES design is proposed based 
on a hybrid AC-DC microgrid, along with alternatives based 
on AC and DC microgrids. Technical analysis was done by 
performing calculations on the power generated by the HRES 
components during different periods. It was found that the 
generated power is sufficient for the load demand in Rumah 
Bada despite not achieving the intended power capacity. 
Besides that, load flow analysis was done for the proposed 
and alternative designs using the PowerWorld Simulator. 
From the analysis, all three systems were able to supply 
sufficient power to the load in Rumah Bada. However, the AC 
and DC microgrids produce reactive power of 32 kVAR and 
ten kVAR, respectively, which would result in drawbacks such 
as additional load, overheating, and power loss on the cables 
and equipment of the system. From there, the proposed 
hybrid AC-DC microgrid is preferred as the system produces 
zero reactive power. Economic analysis was done with 
HOMER, and the proposed system is the most feasible system 
with the lowest COE of RM1.38/kWh and NPC of RM568,887. 
Overall, the proposed hybrid AC-DC microgrid system is the 
most optimal system. Further investigations can be done on 
the microgrid control system design to facilitate power flow 
and investigation on the transmission system. Thus, it is 
hoped that this project will contribute to the research on 
implementing HRES in Malaysia. 

Ethical issue 
The authors are aware of and comply with best practices in 
publication ethics, specifically with regard to authorship 
(avoidance of guest authorship), dual submission, 
manipulation of figures, competing interests, and compliance 
with policies on research ethics. The authors adhere to 
publication requirements that the submitted work is original 
and has not been published elsewhere. 

Data availability statement 
Data sharing is not applicable to this article as no datasets 

were generated or analyzed during the current study. 

Conflict of interest 

The authors declare no potential conflict of interest. 

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