To deal with the rising demand of fossil fuels and their associated untoward environmental and economic effects, the feasibility of Indian government’s green move towards blending of 20% fuel grade ethanol with gasoline has been studied by performing techno-economic-environmental analysis of second generation lignocellulose biomass as feedstock. An optimized supply chain network (SCN) has been designed with four layers of structure starting from raw material suppliers to the retailers through the layers of the manufacturers and the distributors aiming at the net present value (NPV) maximization. The cost calculation includes operating expenditure (OPEX) and capital expenditure (CAPEX) components involving transport, storage, production and import decisions as linear variables and decisions on connections between two nodes between two consecutive layers as binary variables. The distribution layer of the mixed integer linear programming (MILP) model has been uniquely designed for the imported ethanol to serve the twin purposes of meeting the unmet demand as well as enhancing the bio-ethanol product quality in terms of research octane number. The revenue generation is calculated not only from selling the final product but also from the carbon credits calculated using greenhouse gas emission (GHGe) during project life cycle assessment. Further, sensitivity analysis has been performed to show the effect of various parameters such as modes of transport, transport distance limitation on feedstock and product, number of zones, international fuel price fluctuations, feedstock availability on NPV. With ∼80% increase in demand over the 9-year planning horizon, a dynamically changing supply chain (SC) structure shows a ∼36% increase in the newly added locations. Feed availability, critical for Indian scenario, to the tune of at least 40% of the capacity is needed to meet the projected demands.

Introduction

The reserve of fossil fuels that are being used as energy resource is depleting day by day (Razm et al., 2019). The rising pace of development across the globe has led to a great demandsupply imbalance for these conventional fuels, causing unexpected cost escalation and economic inflation (Dovì et al., 2009). Apart from this, they have vital role in environmental pollution (Liu et al., 2018). Thus, a need is felt to migrate from non-renewable to renewable resources of energy, providing immense opportunity to various untapped renewable resources namely, solar, wind, hydro, geothermal, tidal and bio energy (Sequeira and Santos, 2018). Fig 1 (Govt of India Minsitry of Power, 2018; Ministry of Natural Resources and Environment, 2018) shows the current usage of different sources of energy in India. Amidst these alternatives, bioenergy, more precisely bioethanol, generated from 2nd generation biomass (~ 13%, Fig 1b) is one of the sources of carbon neutral renewable energy that is gaining popularity in India. This is because the major part of economy and society in India depends on forest and agriculture and 70% of the its population represents rural India (Yong et al., 2016; Natarajan et al., 2015). As per the government regulation, it is mandatory to blend fuel grade ethanol with gasoline to reduce the burden of crude oil import and this blending percentage is increasing over years (Tables 1 and 2) (Ahmad, 2018; Aradhey, 2017). Moreover, this sector can provide jobs to local people and help boost the national gross domestic product. The low pollution greenhouse gas emission (GHGe) can help in getting revenue in the form of carbon credits for biofuels as per the Kyoto protocol (Grubb et al, 1997).

Bioenergy is considered a potential solution to reduce carbon footprint and fight against global warming. However, uncertainty in the harvest of biomass could lead to the instability of feedstock supply that has a significant impact on the sustainability of biomass supply chain. In this paper, we present a two-stage stochastic programming model dealing with supplier selection to stabilize feedstock supply of a biomass supply chain in uncertain environments. The model involves the first stage decisions for the supplier selection and the second-stage decisions for planning transportation, inventory and production operations. To reduce the computational burden for large instances, we propose an enhanced and regularized L-shaped decomposition algorithm to solve the model. The applicability of this model and the performance of the solution method are evaluated by numerical studies. Sensitivity analysis shows that the values of some parameters related to suppliers have significant impacts on the optimal expected cost and supplier selection.

Introduction

Nowadays, humanity is facing enormous challenges of global warming and the exhaustion of fossil resources according to Shafiee and Topal (2009). The use of fossil fuel is one of the major causes of global warming that affects severely human life and increases natural disaster in recent decades. Therefore, renewable energy will play a significant role in the energy transition and appears to be a very promising solution to sustainable development in the future. The various renewable resources require different technologies to capture energy such as solar, hydro-power, wind, geothermal, marine and biological resources. They are clean energy sources and do not contribute to global warming, greenhouse effect and air pollution. However, the exploitation of renewable energy sources requires much time, high costs of investment and incentive policies from the government. Bioenergy is generated from sources such as wood, agricultural products, animal and plant wastes. In contrast to wind and solar power, biomass can be stored in existing infrastructures in response to various demand according to Kaut et al. (2015). Nowadays, bioenergy industry has to deal with challenges related to low energy density, high harvest, and transportation costs of biomass to compete with fossil energy. The research in Eks¸ioglu et al. (2009) shows that an ˘ efficient supply chain design and management could reduce the biofuel price significantly.

During recent decades, energy issues turned worldwide into a fundamental component of the strategic discussions on sustainable development [1, 2]. The world energy demand increases faster than the global population [3]. With about 80 % of the energy obtained from fossil fuels [4], the effects on climate change threaten human security, e.g. by affecting the weather patterns and the economy [5–7]. Moreover, as fossil fuel reserves are limited, a transition towards a sustainable energy supply is mandatory. A core element of this transition is the use of biomass to generate renewable energy [8]. It is foreseen that renewable energy will play a major role in the rest of the twenty-first century [9] and will be very important to increase energy security [10]. Moreover, biomass based energy is environmentally viable and economically feasible [11] and biomass is the only renewable resource capable of substituting oil, both as fuel and in chemical applications [12, 13]. Currently, biomass covers about 9 % of the world’s primary energy demand [4], and there is potential to further increase the energy production from biomass [14]. However, some biofuels are produced from food crops, which may increase food prices and affect food security [15, 16]. Moreover, the increase of bioenergy crops demands more agricultural land, which is a further threat to the environment [17]. Life cycle analysis studies demonstrate that greenhouse gas emissions reduction realized by using biofuels are currently limited as a result of the high carbon intensity of growing crops and producing the fuel [18]. Although the use of biofuel can potentially reduce the emissions of greenhouse gases compared with fossil fuels [19], other studies point out that several biofuels even show higher environmental impacts than fossil fuels. To address the ‘‘food, energy and environment trilemma’’ [20], alternative biomass sources including crop residues, wood and forest residues, as well as municipal and industrial waste were suggested. These might meet a substantial share of the future energy demand [21]. The current energy consumption in Cuba shows an increasing trend and is expected to rise further in the future [22]. Moreover, the transition to a market economy will likely accelerate and intensify this trend. Historically, the Cuban energy supply strongly depended on imports from abroad [22]. More recently the ‘‘energetic revolution’’ made the country more efficient after implementation of energy management strategies and technological update of devices with small electricity consumption (light bulbs, domestic water pumps, etc.), mainly in residential areas, which account for 56 % of the electricity consumption of the country [22, 23]. Moreover, since it mainly focused on the residential sector, the energetic revolution resulted in a limited impact on the energy efficiency of industry, transport and agriculture [24].