A Backcasting Analysis toward a 100% Renewable Energy Transition by 2040 for Off-Grid Islands

Abstract

The rapid increase in energy consumption results from population growth and technological advancement, while economic growth also relies heavily on the availability of energy. As fossil fuels become scarcer and greenhouse gas emissions increase, renewable energy sources are regarded as practical solutions to meet increasing energy demands. This study aims to develop a sustainable energy transition pathway for off-grid island communities in the Philippines. It adopts the concept of backcasting analysis, focusing on the demand and supply side of the energy transition. The transition considers three milestones: business as usual (BAU), minimal transition scenario (MTS), and absolute transition scenario (ATS). The techno-enviro-economic analysis is performed for each milestone to determine the optimal energy resource mix while addressing the three dimensions of the Energy Trilemma: energy security, energy equity, and environmental sustainability. The approach is implemented in three off-grid island municipalities in Palawan, Philippines: Araceli, Balabac, and Cuyo. The results suggest that the optimal electrification configuration for each island at the MTS is a hybrid system consisting of a diesel generator and solar photovoltaics with batteries, while at the ATS, it is a hybrid system of solar photovoltaics and wind with batteries. In addition, greenhouse gas emissions are reduced by 79.7% in Araceli, 78.7% in Balabac, and 41.2% in Cuyo from the BAU scenario to MTS. The actors involved in said transition are identified. A transitional pathway can be seen as a strategic plan to achieve the desired goal: to have a sustainable energy transition.

1. Introduction

The continuous population growth and technological advancement have led to a rapid increase in energy consumption worldwide. The global energy demand increased an estimated 4.6% in 2021, more than offsetting the 4% contraction in 2020 [1], and fossil fuel is still the primary energy source at 84.3% [2]. However, burning fossil fuels for electricity generation contributes to environmental and social problems such as global warming, acid rain, and health-related issues for human beings [3]. The precipitous depletion of fossil deposits, coupled with climate change issues, has spurred countries worldwide to find solutions to transform the global electrification landscape and shift the dependence from conventional fossil fuels to renewable energy resources [4,5]. This has prompted various energy stakeholders around the world to look for potential and affordable energy resources to replace conventional fossil fuels that can help ensure energy security and, at the same time, reduce the emissions of greenhouse gases [6,7,8,9,10].

The Philippines, deeply affected by the detriments of climate change, has pledged support to reduce carbon emissions in support of the Paris Agreement and COP26 [11,12,13]. As an archipelagic country with 7641 islands, the country is frequently hit by typhoons and has been severely exposed to the impacts of climate change, such as sea-level rise, threats to biodiversity and food security, and the compromise of vulnerable groups [14]. As the country moves toward achieving 100% household electrification by 2022, the need to espouse a paradigm shift in terms of power generation becomes forthcoming to ensure that cleaner and more sustainable energy sources are used and to support climate change actions in the country [15]. The Philippine government created a renewables readiness assessment (RRA) with the International Renewable Energy Agency (IRENA), which identifies the barriers and proposes key actions to strengthen the policy, regulatory, and institutional framework for accelerating renewable energy deployment [16]. To improve the country’s problem with electricity generation, the following actions are proposed: (1) raise awareness to ensure sustained political commitment; (2) assess the country’s grid infrastructure; (3) evaluate the renewable energy sector’s institutional capacity; and (4) study the potential for renewable electrification through mini- and micro-grids [17].

The country has three primary power grids: the Luzon, Visayas, and Mindanao grids owned by the National Transmission Corporation (TRANSCO). The National Grid Corporation of the Philippines (NGCP) serves as the operator of the system and operates, develops, and monitors the grid. The Luzon and Visayas grids are linked by a high-voltage direct-current (HVDC) transmission line and submarine cable of 440 MW transfer capacity between Naga and Ormoc. The Visayas grid has five different sub-grids: Panay, Negros, Cebu, Bohol, and Leyte-Samar. These are connected with submarine cables, arranged in a radial configuration, to protect and isolate it if a fault occurs to one sub-grid. A proposal for the interconnection of the Mindanao grid to the other two is underway, and just recently, NGCP filed an application to the Energy Regulatory Commission (ERC) for the Mindoro-Palawan power interconnection. It is pursuant to the government’s directive to connect off-grid areas to the primary grid [18]. Electricity in the Philippines is produced from various sources: coal, oil-based, natural gas, and renewables. Fossil fuels (coal, natural gas, and oil-based) contribute the highest percentage to electricity generation. They are the primary source of power generation at 71%, while the remaining 29% are from renewable energy sources (geothermal, hydro, biomass, solar, and wind) [19]. However, the Philippine government is seriously considering the shift to renewable energy sources because of the global concern on rising fuel prices, fast depletion of fuel deposits, and the environmental challenges associated with greenhouse gas emissions [14]. According to the Philippine Energy Plan 2020–2040, the Philippine Department of Energy (DOE) targets to achieve energy access for all Filipinos by 2022 and off-grid island electrification by 2040 [20]. However, as of December 2020, over 1.2 million households in off-grid areas are still without electricity, mostly on islands in the southern part of the country that are unserved or underserved [15].

This paper aims to develop a sustainable energy transition pathway for off-grid island communities. It adopts a backcasting analysis by performing a techno-enviro-economic analysis of three different transition targets that will help reach the goal of 100% renewable energy power generation for off-grid island communities in the Philippines. It involves simulation and optimization of a hybrid renewable energy power system to determine the optimal sizing configurations, financial feasibility, electrical components data, and pollutant gas emissions. The analysis will serve as a basis for developing future ideal scenarios, identifying interventions, and creating a transitional pathway to help achieve the desired goal. The following is the structure of this paper: Section 1 discusses the literature reviews on hybrid renewable energy systems (HRES) and the techno-economic analysis carried out in optimization studies, and details backcasting analysis. Section 2 illustrates the research framework and methodologies, Section 3 presents the results, and Section 4 presents the conclusions of this study.

1.1. Hybrid Renewable Energy System (HRES)

The use of renewable energy sources (i.e., solar, wind, biomass, geothermal, hydro) has been considered a practical solution to environmental problems and a sustainable solution in the energy industry for rural electrification [21]. Usually, solar PV and wind are the most common renewable energy sources used by most developing countries to meet the rapidly growing energy demand and substantially contribute to global climate protection efforts [22]. However, reliability, stability, and power quality are the main issues for these sources due to the unpredictable, seasonal, and time-dependent natures [23], resulting in intermittent power delivery [24]. To address the intermittency, hybridized systems with more than one renewable energy source, which can be combined with other conventional energy sources, are employed, either as stand-alone or grid-connected systems [25]. The main benefit of having hybrid systems is that when a variety of energy productions are mixed together, the system’s reliability improves [26]. It is also seen to reduce cost, enhance efficiency, and reduce air pollutant emissions [27]. The type of HRES in a particular location varies mainly on the available renewable energy sources [28].

In recent years, numerous studies have been conducted on the design, simulation, and optimization of HRES for off-grid locations, typically combining renewable energy with existing diesel generators that are already used in these locations as backup power. A techno-economic study performed on Kutubdia Island, Bangladesh, assessed the solar and wind resources of the island with the analysis showing that the wind–diesel system is the better option than wind-alone, PV-alone, and wind–PV hybrid systems [29]. Mamaghani et al. tried to model and optimize different PV, wind turbine, and diesel generator combinations to determine the most energy-efficient and cost-effective configuration for Colombia’s three (3) off-grid villages. The solar–diesel system led to the most economically convenient design for two villages among those combinations. The combination of diesel–solar PV–wind turbines was optimal in one village [30].

One of the setbacks of using RE systems is their intermittent nature. Many studies have been conducted to provide a solution using energy storage. It is an essential element to maintain the continuity of the supply and stabilize the power fluctuations during transmission [31]. Most optimization results showed that combining renewable energy systems with batteries is practical, economical, and ecological [32]. In a study of optimal sizing of a hybrid PV–diesel–battery storage system at Sebira Island, Jakarta province, it was concluded that the hybrid system with a renewable fraction of 70% has a better levelized cost of energy (LCOE) compared to a 100% diesel generator system [33]. It was also an ultimate solution to the power crisis in St. Martin Island, Bangladesh. They used a solar PV–wind–diesel–biomass–battery hybrid configuration to supply electricity to 1400 families, 150 shops, 100 hotels, and various organizations [34].

In hybrid system modeling, typical approaches use programmable algorithms and built-in software tools for designing off-grid or on-grid systems [35]. Among various design optimization tools, HOMER is the most extensively used by researchers worldwide [36]. Developed by the National Renewable Energy Laboratory (NREL) in the USA, this software application is used for techno-economic evaluation of various off-grid and on-grid power systems for remote, stand-alone, and distributed generation applications [37]. Some studies using HOMER involve the optimization of hybridized systems, usually incorporating renewable energy, battery energy storage systems, and/or conventional fossil fuels for residential consumption [38,39], electrification of remote communities [31,40,41,42], and energy access in off-grid island communities [43,44].

1.2. Backcasting Analysis

The term “soft energy path” was first coined in 1977 to describe an alternative future in which energy efficiency and suitable renewable energy sources will eventually replace the current fossil-based energy systems [45]. The method to achieve this was initially termed “backward-looking analysis” and is now known as “energy backcasting.” The fundamental concept of backcasting is to conceptualize desirable futures, extrapolate backward from the future to the present, and analyze various alternative options that can be used to make these envisioned futures a reality [46,47]. Vallabhaneni (2018) reviewed five backcasting approaches that were used in various literary sources: (1) the Robinson approach; (2) The Natural Step approach (TNS); (3) the Sustainable Technology Development approach (STD); (4) Quist approach; and (5) Sushouse approach [48,49,50]. The Robinson approach is the most famous method and can be applied in various scenarios. It can be used in crafting policy analysis in transport infrastructure projects [51,52,53,54], low-carbon electricity generation, CO₂ mitigation [55,56,57,58,59], and creating system design for the transition to renewable energy [60,61,62,63,64].

Quist classified backcasting processes as follows: target-oriented, process-oriented, action-oriented, and participation-oriented backcasting [65]. Target-oriented backcasting involves developing and analyzing future scenarios, which are usually expressed in quantitative terms. Process-oriented backcasting emphasizes the changes rather than the end goal and usually includes policy recommendations to influence change. The action-oriented process focuses more on the actors and stakeholders who can effect change. The ultimate goal of this would be to establish an action agenda or plan for different stakeholders [66]. The last backcasting process is participation-oriented backcasting, where stakeholder participation is of higher priority. It is used as a creative workshop tool to engage the stakeholders [48]. Various policymakers and researchers have used backcasting analysis extensively, and it is proven to help create roadmaps and pathways for achieving the desired targets.

1.3. Scenario Typology

Backcasting analysis works through envisioning and analyzing sustainable futures. It is considered a sustainable alternative to traditional planning as it develops agendas, strategies, and pathways in most sustainability studies [67,68]. Its application in various disciplines to target a common goal involves creating different scenarios for sustainable futures [46]. It is said that the scenario is defined as a depiction of the future and the series of events that may lead to that future based on assumptions about the present [48,69].

Borjeson et al. (2005) summarized the scenario typology into three categories and six types (Figure 1) [48,70,71]. It was based on the key questions: (1) What will happen? (2) What can happen? (3) How can a specific target be reached? The first question can be answered by using predictive scenarios. Predictive scenarios aim to paint a picture of what the future will look like and devise a strategy for adapting to the most probable outcome of the scenario. Forecasts and what-if scenarios are two types of predictive scenarios that may be used to anticipate the future. Forecasts are often conducted to predict what will happen if the most probable development is predicted. Trend extrapolation and quantitative data are used [50]. What-if scenarios are used to study what would happen in the case of certain circumstances occurring in the future.

The explorative scenarios respond to the second question and are used to study the possibilities that a different situation or development may occur in the future. A typical scenario has several situations that might occur, each designed from a different perspective. It resembles what-if scenarios but differs in the initial point from which they are developed as explorative scenarios are elaborated with a long time horizon to explicitly allow more structural, profound changes. Moreover, explorative scenarios take the starting point in the future, while what-if scenarios are usually developed from the present situation. The application of this scenario is helpful in cases in which the user has a clear idea of the current situation but is interested in learning more about the implications of alternative developments [72].

It has two types of scenarios, external and strategic. External scenarios can be applied within a specific company or organization. It can open up the possibility of finding flexible and adaptive solutions, thus creating resilient business strategies in the face of a variety of probable future developments. Strategic scenarios encompass policy actions that are placed in the hands of the intended scenario user to deal with the problem at hand. Its purpose is to depict possible consequences that might result from strategic decisions. It is primarily concerned with internal factors while also considering external ones.

The last question, “How can a specific target be reached?” is the issue that normative scenarios must address. Most often, it is used to achieve desired outcomes in the future. The two different types are preserving and transforming scenarios. Preserving scenarios answer the question, “How can the target be reached by adjusting to the present situation?”, while transforming scenarios respond to the question, “How can the target be accomplished while the existing structure prevents necessary changes from happening?”.

To put it more simply, preserving scenarios are employed to determine how a specific target can be efficiently achieved, usually performed by model optimization while considering environmental, social, economic, and cultural factors. It is to find the most efficient and viable path to reach a specific goal. In transforming scenarios, such as backcasting, the starting point is a high-priority goal that seems unattainable if the development keeps getting in the way. A clear and detailed image of the future is needed to discuss what changes are necessary to reach them, and this is where the backcasting study provides a solution [73,74]. Its purpose is to search for alternative pathways and recommend specific policy implementations for the development while trying to avoid or prevent more negative effects of the changes [75].

2. Materials and Methods

2.1. Study Area

The study is performed in three island municipalities in Palawan, Philippines: Araceli, Balabac, and Cuyo. In Araceli, the power generation is a diesel generator that supplies electricity to only two of thirteen barangays: Poblacion and Tinintinan. The municipality of Balabac has 20 barangays, but only six are also electrified by a diesel generator, which is unreliable due to constant brownouts. Cuyo Island has 24 h of electricity supplied to all barangays, although the electricity tariff is PhP 9.62 or USD 0.18 per kilowatt-hour (kWh), which is considered too expensive. Each of these island communities has its geographical characteristics with the potential of having a hybrid renewable energy system.

2.2. Research Framework

The transition to renewable energy is one solution to address climate change and is the future vision of this study. Backcasting analysis is employed to reach the target vision (Figure 2). Different milestones are analyzed considering the technical, environmental, and economic dimensions to determine the islands’ most feasible renewable energy configurations. With energy access projects, especially those that are implemented in energy-poor communities, the fundamental balance of the Energy Trilemma elements is crucial, considering that the Energy Trilemma is regarded as a grounding framework in energy access projects and its elements of energy security, energy equity, and environmental sustainability are key indicators for the sustainability of such projects [76,77,78]. Thus, the results of the techno-enviro-economic analysis are further interpreted considering the dimensions of the Energy Trilemma [79].

2.3. Development of Target Milestones

The approach to use is target-oriented, where the end goal is the transition to a sustainable renewable energy power system by 2040. There are three target milestones based on the government’s projection of expanded electrification and increasing the country’s renewable energy mix to 35% by 2030 and 50% by 2040 [15]. The first milestone is called the Business-as-usual (BAU) scenario, in which the current electrification landscape will be laid out. In BAU, the energy generation uses fossil-fired fuels, and to gradually replace that, the second milestone is the Minimal Transition Scenario (MTS). There will be a 50% reduction in the conventional energy supply, which will be replaced by renewable energy by 2030. The last milestone is the Absolute Transition Scenario (ATS), in which the diesel power plants will be completely phased-out, and energy generation will use 100% renewable energy by 2040.

2.4. Techno-Enviro-Economic Analysis

The input data for the HOMER simulation and analysis are the hourly load data, renewable resource data performed by [80], technical, and the cost parameter of HRES components. The software optimizes the most feasible configuration to satisfy the load demand.

2.4.1. Input Data

• Site description and electric load profile.

The study considers the three study areas (Figure 3), namely: Araceli (10.558889° N and 119.994444° E), Balabac (7.983333° N and 117.05° E), and Cuyo (10.85° N and 121.016667° E), which all exhibit the following attributes: (1) off-grid island; (2) difficulty in the transportation of fossil fuel that leads to expensive energy costs; (3) limited energy access; (4) poor energy reliability; and (5) renewable resource availability and quality. The electricity supply of these islands is from the local distribution utility, self-owned generators, barangay-owned island generators, or self-owned solar PV. Most parts of the island do not have energy access, and those who have one use it for 4–5 h daily. For this study, the electric hourly load profile is obtained from the local distribution utility for 2021.

Table 1. Electric load profile of the study areas.

Island	Current Installed Rated Capacity (MW)	Load Demand (kWh/day)	Peak Demand (kW)	Load Factor
Araceli	1.386	3728.78	238	0.65
Balabac	1.086	2693.04	190	0.59
Cuyo	3.2	22,065.09	1467	0.63

shows the load demand in kWh/day, peak load in kW, and load factors.

• Resource data.

Table 2. Monthly average solar GHI and clearness index.

	GHI (kWh/m2/day)	Clearness Index	GHI (kWh/m2/day)	Clearness Index	GHI (kWh/m2/day)	Clearness Index
	Araceli		Balabac		Cuyo
January	4.513	0.512	4.932	0.539	4.758	0.543
February	4.942	0.520	5.495	0.563	5.454	0.575
March	5.547	0.544	6.234	0.605	6.246	0.613
April	5.604	0.532	6.174	0.589	6.208	0.589
May	5.022	0.480	5.313	0.516	5.406	0.516
June	4.669	0.452	5.075	0.503	4.753	0.459
July	4.763	0.460	5.122	0.505	4.886	0.471
August	4.884	0.468	5.224	0.505	4.977	0.477
September	4.942	0.482	5.224	0.507	5.016	0.489
October	4.732	0.489	5.155	0.522	4.847	0.503
November	4.530	0.507	4.653	0.503	4.600	0.517
December	4.720	0.552	4.885	0.548	4.712	0.554

presents the monthly average solar global horizontal irradiance (GHI) for the three case islands [81]. The months of March and April show that it has the highest solar irradiance and clearness index for the entire year.

For the wind resource data, the annual average wind speed required for off-grid islands at 50 m hub height is 5.5 m/s [82]. Araceli has a yearly average of 6.24 m/s, Balabac has 5.39 m/s, and Cuyo has 5.91 m/s [83]. Hence, Balabac is not a feasible area for installing wind farms.

• Technical and Economic data.

The technical and economic data pertain to the technical specifications and cost of the components to design the hybrid system, as shown in

Table 3. Technical specifications and cost of the components for the proposed hybrid system [84].

Description	Generator	PV Modules	Wind Turbine	Battery	Converter
Material	-	Monocrystalline	GFK/epoxy	Lithium-ion	-
Fuel	Diesel
Fuel cost	USD 1/L
Nominal efficiency	-	13%	-	-	-
Nominal capacity	-	-	-	300 Ah	-
Nominal voltage	-	45.3 V	-	220 V	-
Nominal energy capacity	-	-	-	14.4 kWh	-
Operating temperature	-	44.3 °C	-	-	-
Cut-in wind speed	-	-	4 m/s	-	-
Cut-out wind speed	-	-	25 m/s	-	-
Hub height	-	-	50 m	-	-
Capital cost	$500/kW	$1000/kW	$973/kW	$900	$140/kW
Replacement cost	$400/kW	$1000/kW	$873/kW	$900	$140/kW
O & M	$0.02/op.h	$10/kW	$5/kW	$90	$14/kW
Lifetime	15,000 h	25 years	20 years	10 years	15 years
Inverter efficiency	-	-	-	-	97.5%
Rectifier efficiency	-	-	-	-	100%

.

2.4.2. Optimization Analysis and Control Strategy

An optimization analysis aims to determine the most feasible hybrid power system configuration based on the specified constraints with the lowest total net present cost [40]. The flowcharts below show the optimization analysis and simple control strategies for the MTS (Figure 4) and ATS (Figure 5) [28,85,86].

This paper has several configurations of the techno-enviro-economical simulation and analysis. The first configuration is adding any renewable energy sources to the current diesel generator, either solar PV modules or wind turbines, or both battery storage and a converter. The other configuration where RETs will fully replace the conventional sources is a hybrid solar PV and/or wind with battery storage and a converter. The schematic diagrams of the two proposed configurations are shown in Figure 6. HOMER software is utilized for this purpose. The software simulates the process and determines the system’s feasibility in component size, electrical output, and battery performance. It considers the power system viable to meet the load demand utilizing the proposed hybrid power system while considering different constraints.

2.4.3. Optimization Result Outputs

The technical operation of the hybrid system is essential, as well as the consideration of economic and environmental assessment. It is to identify if the optimized system design is a power-generating asset or opt for an alternative if it does not. It is be based on calculating the net present cost (NPC), the Levelized cost of energy (LCOE), and the payback period [87]. These parameters are explained below [88,89,90]:

• Net Present Cost (NPC)

The present value of all the costs incurred during the installation and operation of the system throughout the component lifetime, minus the current value of all revenues earned over the component lifetime [91], or the total annual installation and operation costs over the capital recovery factor,

$$\mathrm{NPC}=\frac{\mathrm{total} \mathrm{annual} \cos \mathrm{t} \left(\mathrm{CTA}\right)}{\mathrm{capital} \mathrm{recovery} \mathrm{factor} \left(\mathrm{CRF}\right)}$$

(1)

where the total annual cost (CTA) is the sum of the annual capital cost of the system components (CC), the annual cost for the replacements of the system components (CR), the fuel costs (CF), and the annual operating and maintenance cost (COM) given by,

$$\mathrm{CTA}=\mathrm{CC}+\mathrm{CR}+\mathrm{CF}+\mathrm{COM}$$

(2)

The capital recovery factor (CRF) converts the initial investment cost to annual capital cost, where r is the interest rate (%) and n is the component lifetime in years.

$$\mathrm{CRF} \left(\mathrm{r}, \mathrm{n}\right)=\frac{{\mathrm{r} (1+\mathrm{r})}^{\mathrm{n}}}{{(1+\mathrm{r})}^{\mathrm{n}}-1}$$

(3)

2.

Levelized Cost of Energy (LCOE)

It is the cost of the generated electrical energy from the hybrid system in USD/kWh and is given by the equation:

$$\mathrm{LCOE}=\frac{\mathrm{CTA}}{{{\displaystyle \sum }}_{\mathrm{h}=1}^{\mathrm{h}=8760}\mathrm{Pload}}$$

(4)

or,

$$\mathrm{LCOE}=\frac{\mathrm{NPC}}{{{\displaystyle \sum }}_{\mathrm{h}=1}^{\mathrm{h}=8760}\mathrm{Pload}}\times \mathrm{CRF}$$

(5)

where P_load is the value of hourly load demand.

3.

Energy Payback Period

The energy payback period is significant in power system generation. The number of years that the proposed hybrid system takes to recover its initial investment cost by earnings after interests and taxes [92].

4.

Greenhouse Gas Emissions

The transition to renewable energy is one way to reduce the emissions of carbon dioxide (CO₂), sulfur dioxide (SO₂), nitrogen oxide (NO_x), and other toxic pollutants into the atmosphere.

3. Results and Discussion

3.1. Techno-Enviro-Economic Analysis

The current energy landscape of the three islands is supplied by conventional coal-fired power plants and is not connected to the primary grid of Palawan. Among the three islands, only Cuyo island has a 24 h electricity supply. In Araceli, 2 out of 13 barangays, and in Balabac, only 6 out of 10 barangays have benefited from the 24 h energy supply. Others opt to buy their own solar PV and generators, while some receive their power supply from the village generator that operates 4–5 h daily from 6:00 p.m. to 10:00 p.m. This has opted for the national government to craft policy regulations on the deployment of RETs in off-grid islands that is impossible for the primary grid to reach.

The gradual shift from fossil-fueled power plants to renewables by 2030 is considered in the Minimal Transition Scenario (MTS) target, where diesel generators will be cut to half capacity and serve as backup for the renewables baseload. The projections of the load demand are extrapolated by applying the annual energy demand growth rate from the last five years [93]. Optimization analysis is performed using the hourly load data, solar GHI and wind resource data, and technical and cost parameters of diesel generators, solar PV modules, wind turbines, batteries, and converters to the HOMER software. The summary of the simulation results in

Table 4. Simulation results of the HOMER analysis in different configurations for MTS and ATS.

Target	System Configurations					Component Size					Electrical Production (kWh/yr)	Load Demand (kWh/yr)	Excess Energy (kWh/yr)	Peak Load (kWp)
Araceli
MTS	●	●		●	●	363 kW	1000 kW	-	269 strings	282 kW	1,687,668	1,551,561	92,933	269
ATS		●	●	●	●	-	1000 kW	200 kW	228 strings	341 kW	2,369,402	1,985,998	383,404	344
Balabac
MTS	●	●		●	●	323 kW	700 kW	-	182 strings	213 kW	1,260,985	1,163,432	64,823	221
ATS	●	●		●	●	-	1000 kW	-	237 strings	274 kW	1,503,765	1,489,193	14,572	283
Cuyo
MTS	●	●		●	●	1700 kW	3200 kW	-	695 strings	1497 kW	9,447,998	9,250,446	53,693	1681
ATS		●	●	●	●	-	3200 kW	3000 kW	988 strings	1883 kW	12,996,864	11,841,436	1,155,428	2152

presents the most optimal configuration of the hybrid system and the comparison when the MTS and ATS are applied.

One possible configuration is chosen for the three islands, the hybrid diesel–solar PV–battery for the MTS. These are the most optimal configuration for Araceli, Balabac, and Cuyo with an electrical production of 1,687,668 kWh/yr, 1,260,985 kWh/yr, and 9,447,998 kWh/yr and a spinning reserve of 92,933 kWh/yr, 64,823 kWh/yr, and 53,693 kWh/yr, respectively. It satisfies the required load demand of 1,551,560 kWh/yr, 1,163,434 kWh/yr, and 9,250,447 kWh/yr, and the daily peak load of 269 kWp, 221 kWp, and 1681 kWp, respectively.

The transition to a 100% sustainable renewable energy system is the overarching goal of the third milestone (ATS). The use of fossil-fired generators is phased out, and renewable energy resources are promoted in electricity production. Two configurations are simulated, the hybrid solar PV–wind for Araceli and Cuyo, while Balabac will have a solar PV–battery system configuration. The reason is based on the previous study that the Balabac island is not feasible to have wind farms [79]. The load demand from 2030 to 2040 increases by 28%, as extrapolated using the average annual energy growth of 2.5%. The energy generation supply meets the conservative values of load demand during the transition with a spinning reserve of 383,404 kWh/yr, 14,572 kWh/yr, and 1,155,428 kWh/yr for the islands of the Araceli, Balabac, and Cuyo, respectively.

Aside from the technical parameters of the hybrid system, the component economic cost of the most optimal hybrid system configurations is also assessed (

Table 5. The component economic cost of the most optimal configurations for MTS and ATS.

Target	Capital Cost (USD)	NPC (USD)	LCOE (USD/kWh)	Payback Period (Year)
Araceli
Minimal Transition Scenario (MTS)	1,463,074.17	3,352,228.00	0.167	2.99
Absolute Transition Scenario (ATS)	1,447,583.75	2,645,441.00	0.103	2.93
Balabac
Minimal Transition Scenario (MTS)	1,055,091.57	2,448,940.00	0.163	2.92
Absolute Transition Scenario (ATS)	1,251,727.08	2,652,098.00	0.138	3.70
Cuyo
Minimal Transition Scenario (MTS)	4,885,141.25	27,775,330.00	0.232	2.66
Absolute Transition Scenario (ATS)	7,271,820.00	19,478,720.00	0.127	2.87

). For the MTS, the capital cost of the hybrid diesel–solar PV–battery ranges from USD 1,055,091.57 to USD 4,885,141.25 with a payback period of 2.66–2.99 years. During the ATS, solar PVs will be the baseload, and wind turbines will serve as the peak load power provider. In terms of capital expenditures, the increase in supply has a payback period of 2.87–2.93 years and an initial cost ranging from USD 1,447,583.75 to USD 7,271,820.00. The cost of the generated electrical energy from the hybrid system (LCOE) in Araceli is USD 0.167/kWh (MTS) and USD 0.103/kWh (ATS), USD 0.163/kWh (MTS) and USD 0.138/kWh (ATS) in Balabac, and USD 0.232/kWh (MTS) and USD 0.127/kWh (ATS) in Cuyo.

It is necessary to generate electricity if that electricity should be made available to the consumers. As of now, the distribution network of Araceli and Balabac is 6% and 10% completed, respectively. In expanding energy access to those far-flung areas, Araceli needs roughly USD 1.24 M and Balabac needs USD 1.18 M for the service provider to complete the construction of the distribution network. In Cuyo, where the distribution network is almost finished, it still needs USD 0.19 M. According to the local distribution utility, the expansion of the distribution lines is currently underway. If it is constructed by 2030, then, by the time of the MTS, the delivery of energy to the consumers will have better accessibility. An additional cost of expanding the distribution network can be added to the capital cost if necessary. With that, the service provider will be able to provide a resilient, efficient, and stable electric system, and everyone can have access to energy, along with low-cost energy tariffs to provide more socio-economic benefits to the local community.

The transition to renewable energy is a viable approach for reducing the quantity of carbon dioxide (CO₂), sulfur dioxide (SO₂), nitrogen oxide (NO_x), and other hazardous pollutants released into the environment that causes global warming. In the Minimal Transition Scenario (MTS), 79.7% of CO₂, CO, SO₂, NO_x, unburned hydrocarbons, and particulate matters can be reduced when half of the existing diesel generators are cut off for the island of Araceli, 78.7% in Balabac, and 41.2% in Cuyo. On the other hand, the Absolute Transition Scenario (ATS) presents that there will be zero emissions of these gases, and they will not reach the atmosphere.

Table 6. Pollutant emissions of the optimal configurations for MTS and ATS.

Pollutant	Araceli			Balabac			Cuyo
	Value (kg/yr)			Value (kg/yr)			Value (kg/yr)
	BAU	MTS	ATS	BAU	MTS	ATS	BAU	MTS	ATS
Carbon Dioxide (CO2)	1,040,115	210,672	0	752,771	160,419	0	6,048,500	3,558,629	0
Carbon Monoxide (CO)	7076	1433	0	5121	1091	0	41,148	24,210	0
Unburned Hydrocarbons	286	58.0	0	207	44.2	0	1665	980	0
Particulate Matter	28.3	5.73	0	20.5	4.37	0	165	96.9	0
Sulfur Dioxide (SO2)	2549	516	0	1845	393	0	14,823	8721	0
Nitrogen Oxide (NOx)	566	115	0	410	87.3	0	3292	1937	0

indicates how much of these gases may be prevented from contributing harmful effects on humans and the environment.

3.2. Assessment of Targets

The backcasting approach used is the What-How-Who analysis, which identifies the actors and barriers that may influence the energy transition. The standard backcasting methodology examines the desirable future scenario in several aspects: economic, political, social, technological/technical, legal, and environmental. However, in this study, the measurement used is based on the dimensions of the energy trilemma index: energy security, energy equity, and environmental sustainability.

3.2.1. Energy Security

The continual increase in fuel prices in the world energy market impacts those countries that heavily rely on fossil fuels for energy generation. It has become a concern to increase further the electricity price, which will affect the people living in an island community who do not have large incomes. The transition scenarios where renewable energy technologies replace fossil-fired power plants may become a solution to this.

However, a feasibility assessment is needed to plan a more detailed design of the renewable energy systems. Based on the optimization analysis performed, following the most optimal configurations, and installing the component sizes mentioned, the three islands will have enough energy to consume. They will also have an adequate amount of surplus energy to say they are energy-secure.

For this to occur, the national government is in charge of crafting policies regarding the electricity tariffs that may be favorable for both the supplier and the end-use consumers. That may become a good reason for private energy companies to capitalize on the installation of RETs. The department of energy is responsible for attracting private energy companies interested in putting up these projects and overseeing how these projects are being implemented. Lastly, the consumers should be responsive to the energy transition, for they are the ones who will benefit most in this endeavor.

3.2.2. Energy Equity

Far-flung islands are often the ones to suffer a lack of access to electricity. Or if there is any, there is not enough for everyone to use. That situation impedes the economic development and quality of life for a community.

The utilization of local renewable resources can be a viable solution to this. However, it is not enough if the people are not aware of how these sources may help them, so educating them is more important. They must first appreciate that clean and affordable energy access may help increase their standard of living. If they are all well-informed during the MTS, the energy company’s return of investment (ROI) can be met and may be good enough for another expansion before the ATS in 2040.

A collaborative effort of various stakeholders is needed to meet universal energy access. Investments may come from public and private sources—the national government and private entities. The national government must create strong governance and regulatory frameworks to draw potential investors’ attention to the energy access sector.

3.2.3. Environmental Sustainability

The shift from conventional energy sources to renewable energy technologies helps reduce pollutant gas emissions into the atmosphere. In the BAU scenario (Table 6), where generators are the primary source of electricity, a significant amount of gases are produced. From the BAU scenario to the MTS, the island of Araceli may reduce 79.7% of CO₂, CO, SO₂, NO_x, unburned hydrocarbons, and particulate matters, 78.7% in Balabac, and 41.2% in Cuyo. Meanwhile, from the MTS to ATS, zero emissions can be expected by 2040. According to Climate Action Tracker, they expect that the country will have a conditional target of 70% below the business as usual (BAU) level “2 °C-compatible,” where it falls short of “1.5 °C Paris Agreement-compatible” [94]. However, if the MTS is realized by 2030, it will significantly contribute to the Philippines’ emission pathway.

4. Conclusions

This paper aimed to develop a sustainable energy transition pathway for off-grid island communities. The backcasting analysis adopted in this study focused on the demand and supply side of the energy transition, considering the techno-enviro-economic dimensions grounded on the Energy Trilemma framework. It answered the What-How-Who questions when it comes to the desired future scenario of the energy system: (1) what will the transition to 100% renewable energy systems look like, and what technologies will likely help the said transition; (2) how is the present energy landscape of the three islands and how will the transition be attained; and (3) who are the drivers that will plan, monitor, and execute the said transition for it to succeed?

Three different target milestones were modeled and assessed by employing techno-enviro-economic analysis. A hybrid renewable energy power system was simulated and optimized to find the most optimal sizing configurations, financial feasibility, electrical components data, and pollutant gas emissions. The integration of renewable energy technologies was proven to be beneficial in resolving the issues of energy security, affordable energy cost, and greenhouse gas emissions. A transition pathway was developed based on the hypothetical energy system scenarios defined by energy sustainability. However, the analysis results may change depending on what will occur in the future as some uncontrollable circumstances are beyond control. The methodology used in this study proved to help assess different milestones toward achieving 100% Energy Transition considering energy demand and supply. It can be replicated on any other island with no or limited energy access. The backcasting analysis can also explore several factors: political, economic, social, technological, legal, and environmental.

The government policy, regulations, and initiatives on energy transition can be reviewed using the same analysis. The transformation to a low-carbon economy will create new industries, new investments, new jobs, new skills, and an opportunity to create a more equal and resilient economy. Still, it is not that easy [95]. Many workers will be affected by the transition from conventional sources, so employment rates, economic growth, and the like should be looked into. The legal component might be considered, including labor laws, health and safety regulations, and consumer protection regulations. Island communities have different social structures, so studying the trend in the consumers’ energy demand (heating and nonheating appliances, etc.) can be considered. The technological advancement through the years requires more energy demand, and electric vehicle (EV) technology and the transport sector can also be included in the future study. Environmental policies need to be considered as well.