ANALYTICAL HIERARCHY PROCESS (AHP) MODEL FEEDSTOCK SELECTION ON PRODUCING THE SUSTAINABLE AVIATION FUEL

ABSTRACT


INTRODUCTION
Indonesia's commitment to the Paris Agreement has shown significant forward steps with the recent developments in the adoption of sustainable aviation fuels. As a part of its Nationally Determined Contribution (NDC), Indonesia had pledged to reduce greenhouse gas emissions by 29% on its own or up to 41% with international assistance by 2030, in alignment with the Paris Agreement's global objectives (Suroso et al., 2022;Wijaya et al., 2017). This is further represented in the National General Energy Roadmap (Rencana Umum Energi Nasional/RUEN) which details the energy source mix including from new and renewables (Hartono et al., 2023;Maulidia et al., 2019).
The aviation sector, representing a significant contributor to global emissions, emerged as a focal point for Indonesia's green transition strategy (Arens et al., 2021;Fragkos et al., 2021). With over 17,000 islands and a rapidly expanding middle class that increasingly travels by air, the nation's aviation sector plays a pivotal role in its carbon footprint. Thus, the Ministry of Energy & Mineral Resources mandated the periodic increasing mixture of bio-based aviation fuel mixture in the Jet Fuel through Regulation No.12/2015: 2% (2016, 3% (2020) and 5% (2025). Considering In accordance with International Civil Aviation Organization (ICAO) programe named Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA), utilization of drop-in fuel produced from bio-based feedstock which is later known as Sustainable Aviation Fuel (SAF) is the current best option for reducing emissions from aviation industry while minimizing investment on changing the current airplane, pilot training, or other related investment (Bauen et al., 2020;Prussi et al., 2019). From this program, ICAO is targeting 50% emission reduction from aviation industries by 2050 (ICAO, Annex 16 -Environmental Protection, Volume IV, 2018). To achieve this target, ICAO created the criteria for eligibility of SAF production feedstock which should reduce at least 10% of the conventional fossil-based jet fuel (ICAO, 2021). This includes several bio-based feedstock which are abundance in Indonesia such as Crude Palm Oil (CPO), Refined Bleached Deodorized Palm Kernel Oil (RBDPKO), and Used Cooking Oil (UCO).
Despite of the establishment of government regulation and large potential of bio-based feedstock mentioned above, currently there is no production of SAF in Indonesia. This is due to the high price of SAF compared to conventional Jet Fuel and lack of restrictive domestic policy to drive airlines to adopt SAF thus they are still utilizing conventional Jet Fuel (IATA, 2022). On the other hand, a very restrictive regulation had been made by several countries such as Renewable Energy Directive II (RED II) by European Union (EU) which restricts usage of palm oil derivative in the renewable fuels, including SAF (Makahekum & Arfani, 2021). Hence, fuel producer shall consider these factors when determining the strategy for investing in SAF production facilities. One of the key factor of the strategy is determining the bio-based feedstock to be used in the SAF production (Briassoulis & Giannoulis, 2018;Hildebrandt et al., 2021;Koutra et al., 2018). Therefore, the research analyzed the business aspect of SAF product development, especially biofeedstock selection. Analytical Hierarchy Process (AHP) method with 5 selection criteria: feedstock availability, feedstock price, required capital expenditure (CAPEX), profitability and SAF marketability to analyze 3 possible feedstock: RBDPKO, CPO and UCO. This research did not include detailed technological aspects of SAF production including the technological advancement of various SAF production methods. The researchers hoped to give more insight into SAF business implementation and contribute to the company on developing strategic plan for SAF production in Indonesia.

METHOD Scenario Planning Development
Through research and development (R&D), a Scenario Planning approach is utilized rather than simple Forecast Planning method. The Scenario Planning method allows to evaluate all the factors that influence the goal comprehensively compared to simple Forecast Planning which can only determine several deviations from the goal.

Figure 1. Forecast Planning vs Scenario Planning
Several steps with each conceptual framework are required to construct the Scenario Planning including the determination of driving forces and critical uncertainties, developing the scenario planning framework, and select several scenarios to be rigorously analyzed. The overview of Scenario Planning flow is depicted below.

Figure 2. Scenario Planning Flow
To develop the contextual analysis and strategic issues, an Outside-In Approach framework will be used. This approach results in two critical uncertainties which lead to the primary driving forces which affect the future reality scenarios. A scenario development framework is then developed to analyze four possible scenarios and their respective mitigation strategy options. Input from internal and external data is also utilized to further refine the applicable mitigation strategies. An AHP methodology is then implemented to construct, select, and evaluate the best strategy from the options identified. Finally, implementation steps required to bring the best strategy into reality are then listed as the guidance to the company to execute the chosen strategy.

Analytic Hierarchy Process (AHP) Framework
From the Scenario Development process, several strategies are developed. The options of feedstock selection are then listed and compared to each other by implementing the AHP Framework to determine the best feedstock for SAF development. The AHP Framework is depicted below:  Finally, selected scenario will be evaluated economically through analysing its NPV and IRR. The Investment Cost for the project is based on AACE Class V methodology on determining capital cost investment. Revenues and costs are calculated based on experience on previous projects, market intelegence, and stadard practices.

RESULT AND DISCUSSION Driving Forces and Critical Uncertainties Analysis
An outside-in analysis to determine the driving forces of SAF production from available biobased feedstock in Indonesia is done by viewing internal and external force.s to fuel producing company. This includes gathering data from interview with Government Bodies, Airlines, Fuel Producers, Feedstock Producers, Consultancy bodies, and Experts. The driving forces are mapped as follows:

Figure 5. Outside-in Approach in Determining the Driving Forces
A list of driving forces ranged from internal organization issues to contextual global regulation are listed and grouped with Outside-in Approach framework. From the listed forces, we acknowledge that the contextual forces, namely Global & Government Regulation and Customer Behavior are two factors that have the highest uncertainty since they are beyond company's control while in the same time having the most impact towards company's strategy in developing SAF production. From these two factors, several elements which represent scenarios are listed below:   Option.
Identify Early Warning Signal. Use as a Base.
The following analysis done for the Business Solution and Implementation Plan are based on the highly regulated and fast adaptation scenario depicted above.
By considering 2 (two) uncertainties factors, one of key success factors of developing SAF product is feedstock selection so that: 1) the feedstock characteristic satisfies the implied regulation thus the SAF product will be acceptable by most of the customers from various countries while 2) the feedstock is sufficiently available to fulfill the growing demand due to the fast adaptation behavior by customer. In this essence, RBDPKO, CPO and UCO are further considered by using AHP method with following parameters: From the availability standpoint, CPO is widely available and accessible compared to other feedstocks, hence Fuel Producer can purchase CPO by open tender easily. UCO collection is still a challenge, especially to collect vast amounts of volume to fulfill the Green Refinery production capacity.
Due to its challenging collection process and high demand from foreign countries, UCO price is considerably higher than the others. Due to its high acidity nature, processing UCO needs more pre-treatment than the other feedstocks, hence the higher CAPEX requirements are expected. Due to its popularity in EU countries, SAF produced from UCO has considerably higher price than SAF produced from other feedstocks resulting a higher profitability. UCO-based SAF will definitely be accepted by all airlines while RBDPKO and CPO-based SAF might be subject to anti-dumping policy or even embargo.
The AHP method is then implemented and checked for consistency. All parameters are considered consistent with CR < 0,100. The resulting AHP method is as follows: From the analysis above, the best strategy option for SAF development is by selecting UCO as the bio-feedstock. The development project essential profile is as follows: From the two critical uncertainties above, a base scenario of "highly regulated and fastly adopted SAF" is selected as the reference of developing the strategy. This scenario is indicated by early warning signs such as: establishment of GHG emission reduction framework, establishment of incentives framework and high SAF demand from airlines.
From the study presented in this paper, the writer recommends to accelerate the SAF development by installing a New Green Refinery with the capability of utilizing Used Coking Oil as a feedstock. Coordinate with Government to develop a robust regulatory framework mandated by the government to support the SAF adoption ranging from the technical specification requirement, trading regulations, up to incentives and/or subsidies essential to help the people afford the increasing fuel price.