battery system using HOMER: A case study Sabah, Malaysia

Energy Conversion and Management 144 (2017) 322–339

Contents lists available at ScienceDirect

Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman

Performance analysis of hybrid PV/diesel/battery system using HOMER: A case study Sabah, Malaysia Laith M. Halabi a,⇑, Saad Mekhilef a,⇑, Lanre Olatomiwa b, James Hazelton c a Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia b Department of Electrical & Electronic Engineering, Federal University of Technology, PMB 65, Minna, Nigeria c School of Photovoltaics and Renewable Energy Engineering, University of New South Wales, Sydney, NSW 2052, Australia

a r t i c l e

i n f o

a b s t r a c t

Article history: Received 9 November 2016 Received in revised form 4 April 2017 Accepted 22 April 2017

This study considered two decentralized power stations in Sabah, Malaysia; each contains different combination of photovoltaic (PV), diesel generators, system converters, and storage batteries. The work was built upon previous related site surveys and data collections from each site. Verification of the site data sets, simulation of different operational scenarios, and a comparison with the optimum design were all considered in the work. This includes all possible standalone diesel generators, hybrid PV/diesel/battery, and 100% PV/battery scenarios for the proposed stations. HOMER software has been used in the modeling entire systems. The operational behaviors of different PV penetration levels were analyzed to accurately quantify the impact of PV integration. The performance of these stations was analyzed based on technical, economic and environmental constraints, besides, placing emphasis on comparative cost analysis between different operational scenarios. The results satisfied the load demand with the minimum total net present cost (NPC) and levelized cost of energy (LCOE). Moreover, sensitivity analysis was carried out to represents the effects of changing main parameters, such as; fuel, PV, battery prices, and load demand (load growth) on the system performance. Comparison of all operational behaviors scenarios was carried out to elucidate the advantages/disadvantages of utilizing each scenario. The impact of different PV penetration levels on the system performance and the generation of harmful emissions is also investigated. The results show more trends towards using renewable energy (RE) sources in energy generation and less dependence on standalone diesel generators. Hybrid PV/Diesel/Battery system is seen to be the best technical performance compared to all other scenarios, while also reporting good economic and environmental performance, which result in increased system sustainability. The 100% RE system showed the best environmental characteristics with the highest costs. This study has demonstrated that the presence of RE sources improves the performance of standalone systems and reduces energy storage requirements. Ó 2017 Elsevier Ltd. All rights reserved.

Keywords: Hybrid system Rural electrification Fuel saving HOMER Malaysia

1. Introduction Out of all renewable energy (RE) technologies that can be used in decentralized applications, solar energy has the widest applications in electricity generation. It provides reliable and low cost of energy when employed in remote areas [1]. It also enhances local development by creating new jobs and training opportunities. Furthermore, its environmental friendliness enhanced it is applicability [2]. This technology offers greater potential for developing countries, where a significant percentage of the population lives ⇑ Corresponding authors. E-mail addresses: (S. Mekhilef).

[email protected]

(L.M.

http://dx.doi.org/10.1016/j.enconman.2017.04.070 0196-8904/Ó 2017 Elsevier Ltd. All rights reserved.

Halabi),

[email protected]

in various regions that have limited or no electricity access. In such places, RE sources are considered a suitable solution for rural electrification. This type of energy generation could play an important role in energy provision. Where the presence of electrical energy access positively influences the human development index (HDI) [3], a strong relation links the national energy consumptions and the gross national product (GDP) because electricity is a key requirement for societies’ development over economic, education, and health sectors [4]. For example, in Malaysia, a certain portion of the population lives below the poverty line, this is mostly found in remote places of Sabah and Sarawak, with poverty levels 67.05% and 66.91%, respectively [5]. Malaysia has a good potential of solar energy, due to the abundance of solar radiation averaging 4.8–6.1 kW h/m2/day. Based on this, solar energy has always been

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

considered as a sensible approach to sustainable green energy in Malaysia [6,7]. Malaysia has lots of remote areas that are located away from the main grid and, surrounded by rugged terrains and dense jungles. Grid extension through these remote locations is not considered feasible or economical at present. Standalone diesel generators are commonly used to provide electricity for these areas [8,9]. Meanwhile, in a study carried out to investigate the potential of hybrid RE systems in various rural areas in Malaysia, indicated high potential of RE (solar and micro-hydropower resources) in electricity generation [10]. The Malaysian government adopted the National Energy Policy in 1979 to achieve three primary objectives; adequacy of supply, efficient utilization, and mitigating environmental effects. In 1981, the fossil fuel diversification strategy was introduced to reduce over dependence on oil, mainly in the power generation sector. This policy was aimed to provide a mix supply of natural gas, hydropower, oil, and coal. It has drastically minimized oil dependence from almost 90% in 1980, to less than 15% in 2000 [11]. RE in Malaysia was introduced in 8th Malaysia Plan (8MP; 2001–2005), where it expanded the Malaysian strategy towards considering RE as the fifth source of power generation. The 8MP was originally intended to yield 5% (600 MW) of the country’s electricity demand with RE by 2005, but only two plants with total capacities of 12 MW were subsequently commissioned. Later, the 9th Malaysia Plan (9MP; 2006–2010) was intended to produce 300 MW in Peninsular Malaysia and 50 MW in Sabah by 2010, while energy efficiency was the focus of the 10th Malaysia Plan (10MP; 2011–2015) [12]. Malaysia aims to attain 2000 MW of RE production by 2020. The Malaysian Government is endorsing RE usage, especially in power generation throughout its comprehensive policies and wide social support. This comes about as the country plans to be one of the leading RE producing countries in the world by 2020 [12,13]. Meanwhile, according to recent study [14], oil and natural gas are the most used sources for generating electrical energy with 87.4% from the total production. On the other hand, renewable energy penetrates only 9.4% from the total production, despite the high availability of renewable energy resources in Malaysia. Whereas, hydropower shares 8.7% versus all other renewable energy sources (such as solar and wind resources) as shown in Fig. 1. Currently, total replacement of conventional diesel generators by RE sources in rural/remote communities is unfeasible due to unstable nature of RE resources [15,16]. Renewable and conventional hybrid energy systems could be a suitable solution to provide the best in each system [16]. However, in designing of hybrid RE system several factors such as social, institutional, and technical need to be consider in order to obtain the desired results otherwise, the system would be unreliable and inefficient [17].

Fig. 1. Electricity generation share from several sources in Malaysia [14]

323

Several literature have reported optimum systems of different hybrid combinations such as PV/Wind/Diesel/Battery systems [18–21]. Meanwhile, PV systems had showed lower cost, and is more applicable compared to wind turbines [22]. Hybrid PV/Diesel systems for rural electrification was recommended in most studies [7,8,16–18,23]. Some studies have discussed the optimized designing methods of hybrid systems using different optimization software such as HOMER and several other optimization algorithms including artificial neural networks (ANN), differential evolution (DE), and particle swarm optimization (PSO) for assessments of suitable sizing and appropriate operating strategies for different configuration [24–30]. Rehman and Al-Hadhrami [31] presented a study on PV/diesel hybrid power system with battery backup for a village in Saudi Arabia. The proposed hybrid system seems to be more favorable, especially when there is an increase in fuel price. In [32], a study conducted in Palestine indicated that utilizing PV/diesel hybrid system in remote locations is more economically feasible than standalone diesel generators or grid extension. Some studies have also evaluated the techno-economic feasibility and potential of utilization different hybrid system configurations in remote places [33–37]. Based on this fact, hybrid RE systems was considered a promising technology and has the tendency to reduce environmental pollution, and improve system stability while simultaneously reducing the overall system cost. Up to date, many studies were performed to find the optimum solution for proposed projects based on different methods. A study was carried out to find the cost benefits of standalone solar/battery/diesel in different part of the world using Geographic Information System (GIS) software [38]. The result finds hybrid PV/battery/diesel reduced the levelized cost of energy (LCOE) than standalone diesel generators in many regions. Another study analyzed the potential of hybrid solar and wind energy system in Saudi Arabia using HOMER and MATLAB software [39]. The results have found PV system generate more and cheaper energy compared to wind turbine of the same size. Besides, indicating the need for more reliable system would result in increasing the overall system cost. Moreover, a study was performed in Egypt to examine the feasibility of introducing Fuel Cell (FC) in energy system along with PV, wind turbines, and battery banks. Six different combinations where employed and tested using HOMER software and were compared to gird extension solution. The results have found that hybrid system of PV/FC offers the best LCOE and Net Present Cost (NPC) over all possible solutions including grid extension and wind/battery systems. Different surveys of about 800 samples were reported to measure the user’s willingness to pay in residential and commercial sectors as shown in [40–42]. Among all of the scenarios, higher willingness to pay was found toward RE sources, particularly when it can displace the need of diesel gensets completely in both sectors. Generally, users show greater satisfaction for better energy services (such as fewer blackouts) and are found to be more willing to pay for reliable RE sources [22]. Based on the above literature, it can be seen that most studies in this field have been established to find the optimal deign, examine the potential or investigate the techno-economic feasibility based on different factors and comparison analysis for typical hybrid systems. Generally, these studies have shown hybrid systems offering higher level of reliability as well as lower LCOE compared to single source energy. However, analyzing the operational behavior of hybrid systems once it is built and commissioned has not been taken into consideration in previous studies, despite the high importance associated with such practical evaluation. Therefore, this research study and analyze the performance metrics of PV/ Diesel/Battery hybrid system in two locations; Pulau Banggi Island and Tanjung Labian, Sabah, Malaysia. System evaluation is carried out based on technical, economical and environmental factors as

324

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

well as modeling of all possible scenarios that contain different combinations. Within the study, a comparative analysis with the optimum design was performed to clarify whether the size of the PV systems was optimally selected prior installations in both locations. In addition to this, an examined hypothetical scenario using 100% RE generation were investigated. The results obtained were compared to standalone diesel generator and existing hybrid PV/ diesel/battery systems to accurately quantify the impact of PV injection into the mini-grid in the considered communities. Finally, a conclusion on the findings and a summary of advantages and disadvantages of each system is presented. This study is expected to be very useful in decision making in any area with similar conditions. All technical works in this study were accomplished using HOMER software. 2. Methodology In RE projects, successful evaluation requires appropriate criteria to be applied on site data in order to correctly analyze the operational behavior of all possible scenarios. The following analysis framework were employed in this study: I. Site specification. II. Derivation and verification of modeled data sets. a. Solar energy b. Temperature c. Load demand III. System analysis and operational performance impact. The collected data from each site was illustrated and investigated under these criteria. Each were discussed and analyzed to describe the entire system. 2.1. Site specifications Sabah, the second largest state in Malaysia, has an area that spans of about 72,500 km2. Sabah is located in the eastern part of Malaysia, and is generally made up of mountainous hills with dense jungles, hosting a diverse array of plant and animals, coupled with an extensive network of river valleys. This study considered two stations in specific locations in Sabah named Pulau Banggi Island and Tanjung Labian. The general description for both locations have been showed in a previous study [43]. The first location, Pulau Banggi is the third largest island in Malaysia, located on the northern coast of Sabah at a latitude 7.25°N/117.16667°E. Its main sources of income are agriculture, fishery, and tourism. Tanjung Labian on the other hand is a small area located on the eastern side of Sabah, at a latitude 5.10°N/119.13°E, where major sources of income are timber, tourism, and seafood exports. 2.2. Derivation and verification of modeled data sets Site’s surveys described in [43] were carried out on both locations to collect the required measured data for each site. It includes solar radiation, ambient temperature, and load profile data. In order to assess system performance, real-time measurements of solar irradiation and ambient temperature data is needed. Unfortunately, the measured data was limited due to faulty sensors and measuring tools. To overcome these challenges, data obtained from National Aeronautics and Space Administration (NASA) [44] was used as shown in the following sections. 2.2.1. Solar resource Solar radiation data obtained from NASA’s website [44] is shown in Fig. 2. Based on literature, satellite-based data such as

obtained (NASA) could be employed in the event of unavailability of sufficient measured data in the desired locations [45]. Monthly solar radiation data for both locations is generally in the range of 4.41–6.65 kW h/m2/day, with an annual average of 5.43 and 5.57 kW h/m2/day for Pulau Banggi and Tanjung Labian, respectively. 2.2.2. Temperature The NASA temperature data was also used in this work as shown in Fig. 3. The obtained data for both locations is generally in the range of (25.64–27.38) °C with an annual average of 26.8 °C and 26.3 °C in Pulau Banggi and Tanjung Labian respectively. However, it can be seen in some literature that the used of artificial intelligence to predict ambient temperature by using the direct relation between solar irradiation and temperature is possible and could be employed as a proper solution for future works [46–48]. 2.2.3. Load demand In rural areas, the majority of residents spend most of their time outside their homes for work purposes. At noon, increase in loads can be observed, as some family members usually come home for lunch and other activities. However, maximum demand takes place at night, when the entire family is at home. Demand profiles were constructed using 2014 load data sets collected during the site visits described in [43]. It was found that due to communication errors in measuring equipment, service interruptions and continuing load growth in these new energy access sites is prevalent. Therefore, the datasets had to be modified to give a more accurate representation of community demand for the modeled period. Firstly, erroneous data points were identified – these could be as a result of communications and computation errors in the SCADA system or incorrect equipment calibration. Filters were used to eliminate values seems unreasonable (less than 10 kW and more than 900 kW) before establishing the average profiles as shown in Fig. 4. To derive the demand input datasets in the models, the measured data also needed to be used to estimates data in months with no available data. This presented some challenges. Firstly, as different seasons will affect demand, there are some difficulties in approximating a full year based on size, therefore, monthly data would have to be done for Pulau Banggi site. Secondly, the sites were experiencing significant monthly load growth as new customers receive access via expanding distribution lines. To account for these, a temperature dependent regression model was used to take into account of the seasonal variation. From the measured datasets, the relationship between daily peak load and daily peak temperature were correlated. Temperature variations for the remaining months were taken from Section 2.2.2 and the average load scaled accordingly. Load growth was considered by taking the most recent month as a baseline, then scaling this based on sensitivity analysis in HOMER. The reduced loads at weekends were accounted for by using the measured data sets and comparing peak and average load values. The resulting baseline cases for weekdays and weekends are shown in Fig. 5. Once average load datasets were inputted into the model, variability must be introduced using HOMER’s time step variability and day to day variability functions. Appropriate values of these were determined to be 10.88% and 7.48%, respectively, in Pulau Banggi and 14.22% and 16.26%, respectively, in Tanjung Labian. 2.3. System components Both stations were implemented in two phases and each consists of several components (PV arrays, batteries, converters and diesel generation system) [43]. Pulau Banggi Island was commis-

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

325

Fig. 2. Solar irradiation comparison: (a) Pulau Banggi. (b) Tanjung Labian.

sioned in February 2014 and expected to serve about 1200 houses. On the other hand, Tanjung Labian was commissioned in November 2012 and expected to serve about 800 houses. Table 1 summarizes all components of each system in both locations. A brief description of the system parameters and components used in each location are presented as follows.

2.3.1. Diesel generators Diesel generators are usually employed to meet the peak demand, mainly when there is no output from the PV panels [49]. Capital and replacement costs in this study were regarded to be 220 $/kW and 200 $/kW respectively, where the maintenance cost was 0.030 $/h [50] all specifications are shown in Table 2. The price of diesel depends on the location of each site, 2.9 RM/L in Tanjung Labian and 3.3 RM/L in Pulau Banggi. In such rural areas, fuel price could be more than 1.5 times the normal price because of the high cost of fuel transportation and storage problems [51]. However, the fuel prices in both locations are equal to 0.7 $/L and 0.8 $/L, respectively (according to an exchange rate of $1 = RM4.08).

2.3.2. PV module PV system is employed to supply electrical power during the day from 7 am to 7 pm ± 20 min, when there is sunshine, otherwise, the diesel generators or battery banks take the role to supply the load. In this study, all specifications are shown in Table 2, where the capital cost and replacement costs of the PV, in addition to a small maintenance cost of 10 $/year was considered to be 2000 $/kWp [50]. 2.3.3. Converter Converters’ size is compatible with the PV arrays size to ensure full supply of PV power. Capital and replacement cost of the converter are 890 $/kW and 800 $/kW, respectively, while 10 $/year is marked for maintenance. The operational lifetime was considered to be 15 years [50]. 2.3.4. Battery energy storage Fiamm type batteries is employed in both sites (Pulau Banggi and Tanjung Labian). Each cell is made up of 2 V, and connected as follows:

326

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

Fig. 3. Measured and NASA temperature comparison (a) Pulau Banggi. (b) Tanjung Labian.

I. In Pulau Banggi: Four strings, each string with a capacity of 1500 A h and contains 240 units. II. In Tanjung Labian: Six strings, each string with a capacity of 1500 A h and contains 240 units. The battery’s prices were taken according to the local market of 1200 $/unit for capital cost and 1170 $/unit for replacement, where all specifications are shown in Table 2. 3. Operating strategies There are two main operating strategies employed in the hybrid RE systems, namely Load Following (LF) and Cycle Charging (CC) dispatch strategies. In LF strategy, diesel generators are configured to supply the loads only in the event of unavailability of PV power output, while the PV arrays supply the load and charges the batteries in the event of excess electricity. On the other hand, diesel generators are used to meet loads demand and simultaneously charge

the batteries in the CC strategy. LF strategy seems to be the optimal strategy, as it helps to reduce excess energy and the total NPC [52], hence it is considered in this analysis. However, the flowchart shown in Fig. 6 illustrates the system operational behavior in various cases of supplying the loads by the PV, diesel generators, and batteries, in addition to the batteries charging cycles. According to Fig. 6, an overall energy management system is needed to control the flow of energy, where the system operates in different modes according to the surrounding atmospheric conditions. At normal operating conditions, where the sun is available, the control system gives the PV arrays the highest priority to supply the loads. Meanwhile, in the case of excess energy the system will charge the battery, until it is fully charged (100% SOC), where any further excess energy can be used by dumped loads. In case of insufficient energy from the PV system, the battery will supply the loads until the minimum state of charge (40% SOC) is reached, then the conventional diesel generators will supply the loads. The decision of

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

327

Fig. 4. Measured average load profiles (a) Pulau Banggi. (b) Tanjung Labian.

the control system to operate any of the energy sources and charging/ discharging the battery takes place every hour based on the energy balance computation. The operating reserve is described by HOMER as the reliable amount of power that should supply if the RE supply suddenly decreased or the load demand suddenly increased. In this study, the operating reserve values were set to 10% of hourly loads and 25% of solar output, while, the renewable fraction represents the fraction of the energy delivered to the load which produced from renewable power sources. HOMER calculates the renewable fraction as:

  Enon-ren þ Hnon-ren  100% RF ¼ 1  Eserv ed þ Hserv ed

hypothetical standalone RE scenario (100% PV/Battery) systems were presented and discussed. Also included is the result of the sensitivity study applied to examine the effects of changes in fuel cost, PV cost, battery prices and demand growth over the years. Hybrid optimization model for electric renewable (HOMER) software were used in the simulation [53]. This entails establishing a reference case as the first step, followed by the determination of operational behaviors of existing and hypothetical systems based on economical, technical, and environmental constraints. Fig. 7 shows the existing system in both stations implemented by HOMER. The results for each station analysis is presented separately in Sections 4.1 and 4.2.

ð1Þ

where Enon-ren , Hnon-ren are respectively the electrical and thermal energy produced by non-renewable energy sources (kW h/yr), while Eserv ed , Hserv ed are the total served electrical and thermal loads (kW h/yr), respectively. Meanwhile, the renewable energy production represents the total amount of electrical energy produced annually by the renewable energy components of the power system. 4. Results In this section, the results of technical, economical and environmental analysis for different system configurations including standalone diesel generators, existing hybrid PV/Diesel/Battery and

4.1. Pulau Banggi Island 4.1.1. Standalone diesel system (Baseline model) This scenario was simulated based on the existing PV/Diesel/ Battery hybrid model using the available data. This is needed to accurately quantify the impact of injecting PV on NPC, LCOE, fuel consumption, running hours and other characteristics. Both electrical penetration and diesel generator operation seems to be directly influenced using PV and batteries. In this site, the system depended on the largest generators (both 400 kW) to deliver over 95% of the total energy production, as shown in Table 3. The LCOE is 0.276 $/kW h and NPC is $8,545,703 which is the lowest cost of energy compared to all

328

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

Fig. 5. Average load profiles (a) Weekdays. (b) Weekend.

Table 1 Summary of installed equipment. PV hybrid station

No. of connected houses

Solar photovoltaic

Diesel genset

kWp

Brand

kW

Brand

kW h

Battery bank Brand

Pulau Banggi Phase 1 Pulau Banggi Phase 2

1200

200 1000

Mitsubishi Mitsubishi

2  200, 1  250 2  400

Cummins Caterpillar

720 2160

Fiamm Fiamm

Tanjung Labian phase 1 Tanjung Labian phase 2

800

700 500

Mitsubishi Mitsubishi

2  500, 1  350 –

Cummins –

4320 –

Fiamm –

Table 2 Technical parameters for system components. Equipment

Factor

Value

Equipment

Factor

Value

PV

Rated power (kWp) Temperature co-efficient (°C) Derating factor (%) Operation temperature (°C) Lifetime (Years) Efficiency (%) Nominal capacity (A h/Cell) Nominal capacity (kW h/Cell) Nominal voltage (V/Cell) Lifetime per battery (Years) Round trip efficiency (%)

1200 0.5 80 47 25 13 1500 3 2 7 80

Converter

Rated power (kW) Lifetime (Years) Rectifier efficiency (%) Inverter efficiency (%) Rated power (kW) Load minimum ratio (%) Minimum running hours (h)

1200 15 85 90 350, 400 & 500 30 30,000

Rated power (kW)

200 & 250

Minimum running hours (h)

15,000

Battery

other scenarios using similar operating conditions of fuel and component prices. The systems’ capital, replacement, operation and maintenance, fuel, operational and salvage costs over the project

Diesel generators

period are $319,000, $239,453, $1,428,387, $6,595,138, $643,548 and $36,270 respectively, with 0% renewable penetration and excess energy.

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

329

Fig. 6. Flowchart of system operation in various scenarios.

4.1.2. Existing hybrid PV/diesel with batteries This scenario represents the existing system in both locations. It shows the advantages of including PV arrays in improving the system performance in both sites. This scenario does not provide the best economical system in HOMER, but performed better in terms of technical and environmentally aspects, as well as lowest operating cost. This system demonstrates the need of including storage system (batteries) to store excess energy from the PV. This scenario shows the effects of using PV/batteries in power generation. The main operational characteristics is shown in Table 3. In this case, the system mainly depends on PV to produce 59.21% of the total production, while the largest generators (400 kW) produce around 37%, while all other smaller generators provide only 3.54%. The LCOE is 0.366 $/kW h and NPC is $11,326,602, which is around 1.5 times larger than the previous system. The systems’ capital, replacement, operation and maintenance, fuel, operational and salvage costs were $4,939,000, $2,054,044, $1,179,342, $3,366,568,

$499,681 and $212,349 respectively, over the project period and 50.4% renewable fraction was found with 9.3% of excess energy. 4.1.3. Optimized hybrid PV/diesel/batteries This scenario was performed to examine whether the existing hybrid PV/diesel/batteries scenario were optimally selected in both locations prior to installation or not. The results of the optimized system in this location are shown in Table 3. The results showed the optimal selection for the PV, diesel generators, and battery banks. The LCOE is 0.302 $/kW h and NPC is $ 9, 345,510, which are lower than the existing system by 0.064 $/kW h and $1,981,092 respectively with two strings of 1440 kW h batteries. However, the systems’ capital, replacement, operation and maintenance, fuel, operational and salvage costs over the project period are $2,492,600, $1,098,347, $1,059,902, $4,772,016, $536,081 and $77,351 respectively, with 34.8% renewable fraction and 6.2% of excess energy. As a consequence, it is clear that the optimum solu-

330

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

Fig. 7. Existing hybrid system in both location implemented in HOMER (a) Pulau Banggi. (b) Tanjung Labian.

Table 3 System operational behavior (Pulau Banggi). Component

Rated capacity (kW)

Production (%)

Running hours (h/yr)

Fuel consumption (L/yr)

Standalone diesel generator G1 G2 G3 G4 G5 Total

400 400 250 200 200 1450

48.75 48.44 2.04 0.4 0.39 100

4,314 4,344 672 240 227 9797

309,142 307,430 19,715 4406 4201 644,894

Hybrid PV/Diesel/Batteries PV G1 G2 G3 G4 G5 Total

1200 400 400 250 200 200 2650

59.21 18.65 18.60 1.39 1.13 1.02 100

– 1950 1976 672 575 509 5682

– 143,342 143,137 171,86 134,26 121,04 329,195

Optimized Hybrid PV/Diesel/Batteries PV 800 G1 200 G2 200 G3 100 G4 80 G5 50 Total 1430

42.38 16.53 18.38 13.15 4.11 5.45 100

– 2367 2756 5339 5314 5736 21,512

– 115,769 129,098 122,562 46,275 52,920 466,624

tion system trends to depend more on the diesel generators compared to the existing hybrid system, which results in a higher fuel consumption and operational cost.

price is dut to the high battery replacement costs. Meanwhile, the excess energy is 29.2% of the total production, with no capacity shortage found.

4.1.4. 100% PV and batteries (hypothetical model) Initiating this scenario required dramatic increment over the rated values of PV and the batteries. As the existing rated capacity of the PV arrays in this site is 1200 kW and 4 strings batteries, which consist of 960 battery cells and provides 2880 kW h. However, the optimum 100% renewable fraction system comes with 3000 kWp PV arrays and 50 strings batteries, which consist of 12,000 battery cells and provide 36,000 kW h. The LCOE is 1.36 $/kW h and NPC is $42,140,180 which is four times larger than standalone diesel generators system and two times more than existing hybrid PV/diesel/battery system. The systems’ capital, replacement, operation and maintenance, operational and salvage costs over the project period are $21,468,000, $20,077,838, $, $2,070,905, $1,617,117 and $1,476,548 respectively. This high

4.2. Tanjung Labian 4.2.1. Standalone diesel system (baseline model) The main operational characteristics of this scenario are shown in Table 4. The system depends on the largest generators (both 500 kW) to produce 78.55% of total energy production. The other generator acts as backup generator and works normally in the low loads period. The LCOE is 0. 3303 $/kW h and NPC is $5,902,414 which is the lowest cost compared to all other scenarios based on similar operating conditions. The systems’ capital, replacement, operation and maintenance, Fuel, operational and salvage costs over the project lifetime (25 years) are $297,000, $309,371, $1,518,548, $3,806,995, $438,493 and $29,498 respectively, with 0% renewable penetration but a small amount of excess

331

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339 Table 4 System operational behavior (Tanjung Labian). Component

Rated capacity (kW)

Production (%)

Running hours (h/yr)

Fuel consumption (L/yr)

Standalone diesel generator G1 G2 G3 Total

500 500 350 1350

38.55 40.00 21.45 100

2938 3020 2802 8760

152,634 158,178 114,628 425,440

Hybrid PV/Diesel/Batteries PV G1 G2 G3 Total

1200 500 500 350 2550

86.90 4.66 4.76 3.68 100

– 511 516 878 1905

– 26,849 27,368 30,249 84,466

Optimized Hybrid PV/Diesel/Batteries PV 400 G1 250 G2 250 G3 200 Total 1100

39.89 27.23 27.52 5.36 100

– 2510 2480 1877 6867

– 107,062 108,007 33,238 248,307

energy was observed, representing 1% of the total energy production. 4.2.2. Existing hybrid PV/diesel with batteries The main characteristics is shown in Table 4. In this case, PV arrays produce 86.90% of the total energy production, where the largest generators (500 kW) produced only 9.42% and the smaller generators provide only 3.68%. The LCOE is 0.5352 $/kW h and NPC is $9,563,989 which is about two times more than standalone diesel generator system. The systems’ capital, replacement, operation and maintenance, fuel, operational and salvage costs over the project period are $5,493,000, $2,787,715, $805,659, $755,828, $318,460 and $278,210 respectively. The PV arrays provide 80.7% of the renewable fraction while 17.4% of excess energy was observed in this scenario. 4.2.3. Optimized hybrid PV/diesel/batteries The results of the optimized system in this location are shown in Table 4. The optimal selection of PV, diesel generators and battery banks are found in lower rated values, where the LCOE was 0.3118 $/kW h and NPC is $ 5, 571,168, which are lower than the existing system by 0.2234 $/kW h and $3,992,821 respectively, with two strings of 1440 kW h batteries. However, the systems’ capital, replacement, operation and maintenance, fuel, operational and salvage costs over the project period are $1,708,000, $978,872, $760,444, $2,221,939, $302,203 and $98,085 respectively with 35.7% renewable fraction and 0.3% excess energy. It is clear that the optimum system shows a distinguished difference in the overall costs compared to the existing hybrid system, this occurred due to lower batteries, PV and diesel generators sizes. 4.2.4. 100% PV and batteries (hypothetical model) This scenario has been developed to examine the advantages/ disadvantages of considering 100% RE system with different RE fractions in both locations based on the available data. The existing rated capacity of PV arrays in this site is 1200 kW and 6 strings batteries, which consist of 1440 battery cells and provide 4320 kW h. However, HOMER found the optimum 100% renewable fraction system required an increment of the rated PV values and associated batteries to be 1800 kW PV and 24 strings batteries, which consist of 5760 battery cells and provide 17,280 kW h. The LCOE is 1.22 $/kW h, and NPC is $21,797,966 making this system four times larger than standalone diesel generator system and around two times more than the existing hybrid PV/battery system. The systems’ capital, replacement, operation and maintenance, opera-

tional and salvage costs over the project period are $11,580,000, $9,845,661, $1,119,823, $799,318 and $747,514 respectively, with 33.2% excess energy. 4.3. Sensitivity analysis Sensitivity analysis was performed to investigate the effects the changes in some factors such as; fuel price, PV cost, battery costs and load demand growth will have on the system performance. In this study, the fuel price increased in a range from the current price (0.7 $/L) until 3.3 $/L. The load demand growth was considered 5% per year, while the cost of the PV and batteries opposed to cost variation as a portion of the total initial cost in a range starting from the current price to 60%. Diesel prices are expected to increase and the current technological development would lead to decrease PV and battery prices, as well as more utilization of new electrical devices would increase the future loads. The results of the sensitivity analysis in both sites are presented Figs. 8–11. 4.3.1. Pulau Banggi Island In this location, it is seen from the comparison of Fig. 8 and Fig. 9 that the effects of increasing the load demand and fuel price would result in more dependence on the hybrid PV/diesel/battery system. Decreasing PV and battery prices have the highest impact on reducing the dependence on the standalone diesel generator systems and depending more on hybrid RE systems (PV has more impact due to higher capital cost). 4.3.2. Tanjung Labian Figs. 10 and 11 show the effects of increasing the load demand and fuel price on the operational behavior. This increment leads to more dependence on the hybrid system. In the same manner, decreasing PV and battery prices reduce the dependence on the standalone diesel generators as well. 4.4. Storage system – batteries Battery roles in hybrid renewable energy system needs to the highlighted, as it is usually charged at daytime and discharges at the beginning of the night, where the loads dramatically increased. The appearance of the batteries enhanced the system performance in both locations. The battery state of charge (SOC) procedure in Pulau Banggi and Tanjung Labian are shown in Fig. 12. The lifetime of each battery is considered to be 7 years and the battery’s SOC should be at least 40%, according to manufacturer specifications.

332

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

Fig. 8. Pulau Banggi sensitivity with fixed PV and Battery prices.

Fig. 9. Pulau Banggi sensitivity with varied PV and Battery prices.

However, the maximum loads occur between May and August. During this period, the batteries would have the minimum charging and maximum discharging limits. The storage system is a very important towards ensuring system stability, without which leads to large amount of excess energy. This energy is often regarded as losses, which could affect the operational behavior of the system. However, in both locations, the amount of excess energy was determined to be 9.3% in Pulau Banggi and 17.4% in Tanjung Labian. 0% excess energy can only be achieved by feeding the generated power to national grid in a grid-connected system. On the other hand, in the 100% PV/ battery, the system totally relies on the battery banks to provide energy when PV is unavailable. The SOC performance showed a higher range of charging cycles as shown in Fig. 13.

4.5. Estimating reduction in fuel consumption and generators running hours The analyzed data provide a clear idea about fuel consumption and its related costs. Utilization of the hybrid system resulted in almost 49% and 80% fuel saving in Pulau Banggi and Tanjung Labian respectively. While, the utilization of 100% PV/battery system resulted in 100% fuel saving in both locations. However, from the sensitivity analysis, the system seems to relied more on the hybrid scenario when fuel price and load growth is increased and components prices decrease as shown in Fig. 8 and 10 for both locations. This led to the fact that a 100% PV/Battery system would be more feasible in the future in the case of increasing fuel prices, load demand, and reducing in both PV and battery costs.

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

333

Fig. 10. Tanjung Labian sensitivity with fixed PV and Battery cost.

Fig. 11. Tanjung Labian sensitivity with varied PV and Battery cost.

Furthermore, the simulation has shown that decreasing the running hours of the generators could lead to minimizing the dependence on the larger generators, thereby reducing the wear/ tear, and leading to overall efficiency improvement. In Pulau Banggi, Fig. 14 shows the reduction in the running hours of all generators. G1 and G2 were reduced by 54% and 54%, respectively. G3 reports similar running hours and G4 and G5 running hours increased by 58% and 55%. This results in maximized lifetime of the system component i.e. no need for component replacement at early stages of the project lifetime. Lower loading on the generator is generally regarded to be good for fuel consumption and reducing wear/tears, but within a limit specified by the manufacturer, otherwise, the system would be inefficient. Most generator’s

manufacturers recommended that their product to work at least 30–40% of the rated power. In the same manner, Tanjung Labian generators’ running was greatly reduced. G1, G2, and G3 were reduced by 83%, 83%, and 67%, respectively, as seen in Fig. 14. In summary, it should be pointed out that the generators are not only working less, but also running at lower loads. 4.6. Economic analysis Table 5 summarizes the NPC, operating and LCOE costs of all scenarios. As seen from this table, standalone diesel generators provide the lowest NPC and LCOE, followed by the optimized and existing hybrid then 100% RE system. The 100% PV/battery system

334

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

Fig. 12. Batteries SOC performance in (a) Pulau Banggi. (b) Tanjung Labian.

has the highest operating cost due to high battery replacement costs. It was assumed to be replaced every 7 years (battery lifetime). No fuel is required by this system (100% RE). Meanwhile, the optimized and existing hybrid systems report lower operating cost compared to standalone diesel generator, as less usage of the diesel generators is required, yet reported higher LCOE than standalone diesel generator system. From the sensitivity analysis in Section 4.4, it is clear that when the loads and fuel price increased, the system tends to depend more on the hybrid system, which provides a good indicator of the availability towards using such system in future projects. Furthermore, referring to current technologies, it is expected to see decreasing in PV and battery’s

prices in the future, which endorses the idea of implementing totally RE projects. 4.7. Reduction of pollutant emissions The addition of PV in the standalone power systems would significantly reduce harmful carbon emission. This reduction justifies eliminating the inefficient use of diesel generators, based on the results reported in Table 6. The utilization of PV and battery banks in the system enhanced the reduction of carbon emissions by 49% in Pulau Banggi, and 80% in Tanjung Labian. This shows that upgrading standalone diesel generation systems in mini-grids with PV and

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

335

Fig. 13. Batteries 100% PV operational behavior in (a) Pulau Banggi. (b) Tanjung Labian.

batteries reduced harmful emissions, as well as fuel consumption. However, 100% PV/Battery system offer zero emissions, and is considered as the best system from an environmental perspective, while the standalone diesel generators system is regarded as the worst, as it generates the highest amount of the harmful emissions. In this study, no penalties over CO2 emissions was considered.

5. Discussion on the operational analysis in both locations In this section, the main findings of Section 4 are discussed and explained. The results are connected together to show the relation between different system components and the effects of changes in the main system parameter on the system performance. In addi-

336

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

Fig. 14. Pulau Banggi and Tanjung Labian generators running hours before and after adding PV/Batteries.

Table 5 Economic summary of existing and hypothetical scenarios. Site

System description

NPC ($)

Operational cost ($)

LCOE ($/kW h)

Pulau Banggi

Standalone diesel (0% RE) Hybrid PV/DG/Battery (59.21% RE) Optimized Hybrid PV/DG/Battery (42.38% RE) PV/Battery (100% RE)

8,545,703 11,326,602 9,345,510 42,140,180

643,458 499,681 536,081 1,617,117

0.2761 0.366 0.302 1.36

Tanjung Labian

Standalone diesel (0% RE) Hybrid PV/DG/Battery (86.90% RE) Optimized Hybrid PV/DG/Battery (39.89% RE) PV/Battery (100% RE)

5,902,414 9,563,989 5,571,168 21,797,966

438,493 318,460 302,203 799,318

0.3303 0.5352 0.3118 1.22

tion, this study place emphasis on comparative cost and environmental analysis of each scenario. Four different scenarios were analyzed in Sections 4.1 and 4.2. These include the standalone diesel generators, existing hybrid PV/diesel/battery, 100% PV/battery, and the optimum solution scenarios. The effects of changing major parameters, such as fuel price and load growth on the system operation were investigated throughout the sensitivity analysis (Section 4.3). Each scenario shows and quantifies the impact of injecting PV on NPC, LCOE, power penetration, excess energy, fuel consumption, running hours and other characteristics. 5.1. Techno-economic impact The results obtained showed that standalone diesel system offers the best economic properties over the project period, in con-

trast to the 100% PV/Battery system that reports the highest cost. However, hybrid PV/diesel/battery system shows the best technical and a very good economic characteristics based on the overall system cost. The hybrid PV/diesel/battery system is costlier than the standalone diesel system over capital, replacement, operation and maintenance, fuel, operational and salvage costs. Where, hybrid PV/diesel/battery system shows lower costs compared to 100% PV/battery system as shown in Fig. 15(a) and (b). The results of both locations indicate that using 100% PV/battery would involve high cost due to high capital and battery replacement costs. But, if a price reduction is found for these component, it would be a feasible solution. A comparison with the optimized scenarios shows that both existing PV systems are not optimally selected prior to installation for the same load profiles, solar irradiation, and temperature data. Due to the extreme remote location of both areas, the designers of

Table 6 System pollutant harmful emissions. Site

Pulau Banggi

Tanjung Labian

Description

Emissions (kg/yr) Carbone dioxide

Carbone monoxide

Unburned hydrocarbons

Particular matters

Sulfur dioxide

Nitrogen oxide

Standalone diesel (0% RE) Existing hybrid PV/DG/Battery (59.21% RE) PV/Battery (100% RE)

1,705,774 870,387

289.04 326.41

23.66 32.27

18.75 23.19

3486.60 1776.30

3762.70 3462.5

Standalone diesel (0% RE) Existing hybrid PV/DG/Battery (86.90% RE) PV/Battery (100% RE)

1,124,134 223,090

797 205.85

84.18 22.07

58.62 15.25

2288.3 453.38

7717.10 1940.90

No Emissions

No Emissions

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

337

Fig. 15. Cost analysis over all combinations: (a) Pulau Banggi. (b) Tanjung Labian.

these projects prefer to depend more on the PV and batteries than the diesel generators for the existing systems. Thus, the optimal systems show lower PV penetration levels, where the RE share is 42.38% in Pulau Banggi and 39.89% in Tanjung Labian from the total production. Furthermore, the batteries strings are reduced to two strings in both locations. This is compared to 59.21% of RE sharing with four strings and 86.9% of RE sharing with six strings in the existing hybrid systems of Pulau Banggi and Tanjung Labian, respectively. The sensitivity analysis examined the effect of changes in major parameters, such as fuel price, load growth, PV, and battery banks prices on the overall system performance. The results show more trend towards using hybrid systems that include PV, battery, and

diesel generator particularly when the fuel prices and loads increase. Furthermore, reducing PV and battery banks costs would enhance the use of PV arrays and battery as lower NPC and LCOE would associate with such system. The storage battery system is crucial towards the stability of the of the system. The battery system offers a sufficient technique to minimize excess energy. Thus, the utmost usage of this energy to the current design is found. Meanwhile, the SOC of the battery system reports high charging cycles for both systems, but higher cycles are found in the 100% PV/battery system, where the system depends mainly on the batteries to provide adequate energy to loads when the PV is unavailable. Furthermore, the hybrid system is compared to the standalone diesel generators to quantify the

338

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339

Fig. 16. PV penetration level VS CO2 emissions in both locations.

effects of using such systems on fuel consumption, diesel generators running hours, harmful emission and economic aspects. The results indicate that hybrid systems would reduce the fuel consumption and generate less harmful emission to the surrounding environment. Diesel generators’ running hours would also reduce, as the system depends more on smaller generator units to supply the loads at different times during the day. The generators are working less at lower loads, which results in decreasing the replacement, maintenance, operational, fuel costs and the overall wear/tear of the system, hence leading to reduction in total NPC and LCOE. 5.2. Environmental impact The results showed that standalone diesel system offers the highest rate of harmful emissions into the surrounding environment, in contrast to the 100% PV/Battery system that reports the best environmental properties with no harmful emissions to the environment. However, hybrid PV/diesel/battery system shows a very good economical and environmental characteristic. The relation between the PV penetration and CO2 emissions is shown in Fig. 16 for both locations. As seen in Fig. 16 that increasing the energy produced by RE sources would result in reducing the harmful emissions generated by the system. It is also clear that the reduction of harmful emission depends on the system configuration and the amount of the generated energy.

6. Conclusion This study investigates the performance matrices of the current and proposed scenarios of two power stations located in Pulau Banggi and Tanjung Labian, Sabah, Malaysia. It showed the impact of injection of PV into mini-grids based on important operational procedures over different RE penetration levels (0%, 39.89%, 42.38%, 59.21%, 86.90% and 100%). The existing systems in both locations were compared to the optimum sizing of the PV system in order to examine whether the systems are optimally selected prior the installation for the same load profiles, solar radiation and temperature data sets. The effects of changing RE penetration levels on NPC, LCOE and associated technical properties, the influence of different PV penetration levels on the harmful emissions generation were also shown and discussed. In addition, the study

put emphasis on all costs associated with the systems through comparative cost analysis between different configurations. The comparison with the optimal system indicates that the existing systems were not optimally selected prior to installation. Hybrid PV/Diesel/Battery system shows the best performance compared to all other scenarios in terms of the technical aspects as well as supporting 24-h energy access. Meanwhile, the standalone diesel generator system shows the best economical scenario. However, 100% RE scenario is regarded as the best system for the provision of clean energy with no emissions. The results of sensitivity analysis carried out based on variation on some parameters including fuel, PV, battery prices and load demand (load growth), shows trends towards using RE sources in energy generation and less dependence on standalone diesel generators. The inclusion of RE resources in power generation has resulted in improving the system performance and minimizing the dependence on fossil fuel and harmful emissions as well. It also resulted in increasing system sustainability. This study has demonstrated the importance of including storage system (batteries) to store excess energy and reducing losses. Furthermore, it shows the benefits of RE projects in local communities in enhancing the socioeconomic developments by creating new job opportunities for the local residents. On the other hand, 100% RE system seems to be uneconomically feasible, due to the high PV and battery capital and replacement costs. However, with further research in PV and battery production technologies, projected decrease of the costs are expected to make this approach feasible in the near future.

Acknowledgement The authors would like to acknowledge the financial support from the University of Malaya, Malaysia, through the Postgraduate Research Grant (PPP) PG338-2016A and PG192-2016A.

References [1] Zhou W, Lou C, Li Z, Lu L, Yang H. Current status of research on optimum sizing of stand-alone hybrid solar–wind power generation systems. Appl Energy 2010;87:380–9. [2] Lovins AB. Small is profitable: the hidden economic benefits of distributed generation (and other distributed resources). In: Australian eco generation conference; 2002. [3] Kanagawa M, Nakata T. Assessment of access to electricity and the socioeconomic impacts in rural areas of developing countries. Energy Policy 2008;36:2016–29.

L.M. Halabi et al. / Energy Conversion and Management 144 (2017) 322–339 [4] Doll CN, Pachauri S. Estimating rural populations without access to electricity in developing countries through night-time light satellite imagery. Energy Policy 2010;38:5661–70. [5] Borhanazad H, Mekhilef S, Saidur R, Boroumandjazi G. Potential application of renewable energy for rural electrification in Malaysia. Renew Energy 2013;59 (November):210–9. [6] Lau KY, Yousof MFM, Arshad SNM, Anwari M, Yatim AHM. Performance analysis of hybrid photovoltaic/diesel energy system under Malaysian conditions. Energy 2010;35(August):3245–55. [7] Wong SY, Chai A. An off-grid solar system for rural village in Malaysia. In: 2012 Asia-Pacific power and energy engineering conference (Appeec); 2012. [8] Ajan CW, Ahmed SS, Ahmad HB, Taha F, Zin AABM. On the policy of photovoltaic and diesel generation mix for an off-grid site: East Malaysian perspectives. Sol Energy 2003;74:453–67. [9] Nandi SK, Ghosh HR. Prospect of wind–PV-battery hybrid power system as an alternative to grid extension in Bangladesh. Energy 2010;35:3040–7. [10] Izadyar N, Ong HC, Chong WT, Mojumder JC, Leong K. Investigation of potential hybrid renewable energy at various rural areas in Malaysia. J Clean Prod 2016;139:61–73. [11] Mustapa SI, Peng LY, Hashim AH. Issues and challenges of renewable energy development: a Malaysian experience. Proceedings of the international conference on energy and sustainable development: issues and strategies (ESD) 2010;2010:1–6. [12] Mekhilef S, Safari A, Mustaffa W, Saidur R, Omar R, Younis M. Solar energy in Malaysia: current state and prospects. Renew Sustain Energy Rev 2012;16:386–96. [13] Ahmad S, Ab Kadir MZA, Shafie S. Current perspective of the renewable energy development in Malaysia. Renew Sustain Energy Rev 2011;15:897–904. [14] NEB. Suruhanjaya Tenaga (Energy Commission), National Energy Balance. Available: ; 2013. [15] Phuangpornpitak N, Kumar S. PV hybrid systems for rural electrification in Thailand. Renew Sustain Energy Rev 2007;11(September):1530–43. [16] Olatomiwa L, Mekhilef S, Huda A, Sanusi K. Techno-economic analysis of hybrid PV–diesel–battery and PV–wind–diesel–battery power systems for mobile BTS: the way forward for rural development. Energy Sci Eng; 2015. [17] Lena G. Rural electrification with PV hybrid systems. St. Ursen: International Energy Agency Photovoltaic Power Systems Programme; 2013. [18] Khatib T, Mohamed A, Sopian K, Mahmoud M. Optimal sizing of building integrated hybrid PV/diesel generator system for zero load rejection for Malaysia. Energy Build 2011;43(December):3430–5. [19] Olatomiwa L, Mekhilef S, Huda A, Ohunakin OS. Economic evaluation of hybrid energy systems for rural electrification in six geo-political zones of Nigeria. Renew Energy 2015;83:435–46. [20] Olatomiwa L, Mekhilef S, Huda A. Optimal sizing of hybrid energy system for a remote telecom tower: a case study in Nigeria. In: IEEE conference on energy conversion (CENCON), 2014; 2014. p. 243–47. [21] Olatomiwa L. Optimal configuration assessments of hybrid renewable power supply for rural healthcare facilities. Energy Rep 2016;2:141–6. [22] Hazelton J, Bruce A, MacGill I. A review of the potential benefits and risks of photovoltaic hybrid mini-grid systems. Renew Energy 2014;67:222–9. [23] Neves D, Silva CA, Connors S. Design and implementation of hybrid renewable energy systems on micro-communities: a review on case studies. Renew Sustain Energy Rev 2014;31(March):935–46. [24] Olatomiwa L, Mekhilef S, Ohunakin OS. Hybrid renewable power supply for rural health clinics (RHC) in six geo-political zones of Nigeria. Sustain Energy Technol Assess 2016;13:1–12. [25] Banos R, Manzano-Agugliaro F, Montoya F, Gil C, Alcayde A, Gómez J. Optimization methods applied to renewable and sustainable energy: a review. Renew Sustain Energy Rev 2011;15:1753–66. [26] Belfkira R, Zhang L, Barakat G. Optimal sizing study of hybrid wind/PV/diesel power generation unit. Sol Energy 2011;85:100–10. [27] Erdinc O, Uzunoglu M. Optimum design of hybrid renewable energy systems: overview of different approaches. Renew Sustain Energy Rev 2012;16:1412–25. [28] Haidar AM, John PN, Shawal M. Optimal configuration assessment of renewable energy in Malaysia. Renew Energy 2011;36:881–8. [29] Zahboune H, Zouggar S, Krajacic G, Varbanov PS, Elhafyani M, Ziani E. Optimal hybrid renewable energy design in autonomous system using Modified Electric System Cascade Analysis and Homer software. Energy Convers Manage 2016;126:909–22.

339

[30] Olatomiwa L, Mekhilef S, Ismail M, Moghavvemi M. Energy management strategies in hybrid renewable energy systems: a review. Renew Sustain Energy Rev 2016;62:821–35. [31] Rehman S, Al-Hadhrami LM. Study of a solar PV-diesel-battery hybrid power system for a remotely located population near Rafha, Saudi Arabia. Energy Dec 2010;35:4986–95. [32] Mahmoud MM, Ibrik IH. Techno-economic feasibility of energy supply of remote villages in Palestine by PV-systems, diesel generators and electric grid. Renew Sustain Energy Rev Apr 2006;10:128–38. [33] Karakoulidis K, Mavridis K, Bandekas D, Adoniadis P, Potolias C, Vordos N. Techno-economic analysis of a stand-alone hybrid photovoltaic-diesel– battery-fuel cell power system. Renew Energy 2011;36:2238–44. [34] Rajkumar R, Ramachandaramurthy V, Yong B, Chia D. Techno-economical optimization of hybrid pv/wind/battery system using Neuro-Fuzzy. Energy 2011;36:5148–53. [35] Saheb-Koussa D, Haddadi M, Belhamel M. Economic and technical study of a hybrid system (wind–photovoltaic–diesel) for rural electrification in Algeria. Appl Energy 2009;86:1024–30. [36] Ohijeagbon O, Ajayi OO. Solar regime and LVOE of PV embedded generation systems in Nigeria. Renew Energy 2015;78:226–35. [37] Baneshi M, Hadianfard F. Techno-economic feasibility of hybrid diesel/PV/ wind/battery electricity generation systems for non-residential large electricity consumers under southern Iran climate conditions. Energy Convers Manage 2016;127:233–44. [38] Cader C, Bertheau P, Blechinger P, Huyskens H, Breyer C. Global cost advantages of autonomous solar–battery–diesel systems compared to dieselonly systems. Energy Sustain Develop 2016;31:14–23. [39] Ramli MA, Hiendro A, Al-Turki YA. Techno-economic energy analysis of wind/solar hybrid system: case study for western coastal area of Saudi Arabia. Renew Energy 2016;91:374–85. [40] Dagher L, Harajli H. Willingness to pay for green power in an unreliable electricity sector: Part 1. The case of the Lebanese residential sector. Renew Sustain Energy Rev 2015. [41] Harajli H, Gordon F. Willingness to pay for green power in an unreliable electricity sector: Part 2. The case of the Lebanese commercial sector. Renew Sustain Energy Rev 2015;50:1643–9. [42] Mahmud AM. Evaluation of the solar hybrid system for rural schools in Sabah, Malaysia. In: IEEE international conference on power and energy (PECon), 2010; 2010. p. 628–33. [43] Hazelton J, Bruce A, MacGill I. Improving risk management for utility PVbattery-diesel mini-grid projects in Sabah, Malaysia; 2015. [44] NASA. Surface meteorology and solar energy. Available: . [45] Sinha S, Chandel S. Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems. Renew Sustain Energy Rev 2015;50:755–69. [46] Olatomiwa L, Mekhilef S, Shamshirband S. Global solar radiation forecasting based on SVM-wavelet transform algorithm. Int J Intell Syst Appl (IJISA) 2016;8: 19. [47] Shamshirband S, Mohammadi K, Chen H-L, Samy GN, Petkovic´ D, Ma C. Daily global solar radiation prediction from air temperatures using kernel extreme learning machine: a case study for Iran. J Atmos Solar Terr Phys 2015;134:109–17. [48] Mohammadi K, Shamshirband S, Danesh AS, Abdullah MS, Zamani M. Temperature-based estimation of global solar radiation using soft computing methodologies. Theor Appl Climatol; 2015: 1–12. [49] Nfah E, Ngundam J. Modelling of wind/Diesel/battery hybrid power systems for far North Cameroon. Energy Convers Manage 2008;49:1295–301. [50] Hossain M, Mekhilef S, Olatimiwa L. Performance evaluation of a stand-alone PV-wind-diesel-battery hybrid system feasible for a large resort center in South China Sea, Malaysia. Sustain Cities Soc 2016. [51] Anwari M, Rashid M, Muhyiddin H, Ali A. An evaluation of hybrid wind/diesel energy potential in Pemanggil Island Malaysia. In: International conference on power engineering and renewable energy (ICPERE), 2012; 2012. p. 1–5. [52] Ngan MS, Tan CW. Assessment of economic viability for PV/wind/diesel hybrid energy system in southern Peninsular Malaysia. Renew Sustain Energy Rev 2012;16:634–47. [53] Lambert T, Gilman P, Lilienthal P. Micropower system modeling with HOMER. Integr Altern Sources Energy 2006;1:379–418.