Nationwide energy supply chain analysis for hybrid feedstock processes with significant CO2 emissions reduction

Performance Measurement of the Sustainable Supply Chain During the COVID-19 Pandemic: A real-life case study

This paper aims to introduce a framework to measure the sustainable performance of the supply chain (SC) during the COVID-19 pandemic. The SC stakeholders in this investigation are Suppliers, Production / Remanufacturing / Refurbishing Centers (Factories), Collection / Distribution Centers, Recycling / Landfill Centers, and Customers. The suggested sustainable supply chain (SSC) performance measurement included three pillars with 23 indicators. To evaluate the overall sustainability of the SC understudy, a composite index has been developed that combines all the indicators to reflect the sustainability performance of the SC. Four steps are involved in creating a composite index:1) measuring the value of indicators, 2) weighing indicators, 3) Using the normalization technique, and 4) Evaluating the overall SSC indicator. The real case in Iran is selected as an illustrative case. Our research contributions are: We suggested a novelty indicator of SSC to better show the economic, environmental, and social tradeoffs during the COVID-19 pandemic and lockdowns. We have found and measured the negative and positive impacts of COVID-19 on aspects of sustainability in SC. Based on the achieved data of the real case study, a numerical example is represented to explain how to calculate the composite index. The main contribution of this paper is the development of SSC indicators during the COVID-19 epidemic.

A framework to predict the price of energy for the end-users with applications to monetary and energy policies

Energy affects every single individual and entity in the world. Therefore, it is crucial to precisely quantify the “price of energy” and study how it evolves through time, through major political and social events, and through changes in energy and monetary policies. Here, we develop a predictive framework, an index to calculate the average price of energy in the United States. The complex energy landscape is thoroughly analysed to accurately determine the two key factors of this framework: the total demand of the energy products directed to the end-use sectors, and the corresponding price of each product. A rolling horizon predictive methodology is introduced to estimate future energy demands, with excellent predictive capability, shown over a period of 174 months. The effectiveness of the framework is demonstrated by addressing two policy questions of significant public interest.

Global energy transformation requires quantifying the "price of energy" and studying its evolution. Here the authors present a predictive framework that calculates the average US price of energy, estimating future energy demands for up to four years with excellent accuracy, designing and optimizing energy and monetary policies.

Synthesis of European Union Biorefinery Supply Networks Considering Sustainability Objectives

Increasing the use of renewable energy sources is one of the most important goals of energy policies in several countries to build a sustainable energy future. This contribution proposes the synthesis of a biorefinery supply network for a case study of the European Union (EU-27) under several scenarios based on a mathematical programming approach. Several biomass and waste sources, such as grains, waste oils, and lignocellulosics, are proposed to be utilized, and various biofuels including first, second, and third generations are produced such as bioethanol, green gasoline, biodiesel, Fischer Tropsch (FT) diesel, and hydrogen. The aim of this study is to evaluate the capabilities of EU-27 countries to be able to meet the Renewable Energy Directive (RED II) target regarding the share of renewable energy in the transport sector by 2030 in each Member State while not compromising the current production of food. A generic mathematical model has been developed for the multi-period optimization of a biorefinery supply network with the objective of maximizing sustainability profit. The solutions obtained show that biomass and waste are promising raw materials to reach and go beyond the EU’s renewable energy target in the transport sector for the year 2030. However, some countries would need to provide additional subsidies for their companies to achieve at least a non-negative economic performance of biofuel production.

Modeling and Simulation of Energy Systems: A Review

Energy is a key driver of the modern economy, therefore modeling and simulation of energy systems has received significant research attention. We review the major developments in this area and propose two ways to categorize the diverse contributions. The first categorization is according to the modeling approach, namely into computational, mathematical, and physical models. With this categorization, we highlight certain novel hybrid approaches that combine aspects of the different groups proposed. The second categorization is according to field namely Process Systems Engineering (PSE) and Energy Economics (EE). We use the following criteria to illustrate the differences: the nature of variables, theoretical underpinnings, level of technological aggregation, spatial and temporal scales, and model purposes. Traditionally, the Process Systems Engineering approach models the technological characteristics of the energy system endogenously. However, the energy system is situated in a broader economic context that includes several stakeholders both within the energy sector and in other economic sectors. Complex relationships and feedback effects exist between these stakeholders, which may have a significant impact on strategic, tactical, and operational decision-making. Leveraging the expertise built in the Energy Economics field on modeling these complexities may be valuable to process systems engineers. With this categorization, we present the interactions between the two fields, and make the case for combining the two approaches. We point out three application areas: (1) optimal design and operation of flexible processes using demand and price forecasts, (2) sustainability analysis and process design using hybrid methods, and (3) accounting for the feedback effects of breakthrough technologies. These three examples highlight the value of combining Process Systems Engineering and Energy Economics models to get a holistic picture of the energy system in a wider economic and policy context.

Energy Supply Chain Optimization of Hybrid Feedstock Processes: A Review

The economic, environmental, and social performances of energy systems depend on their geographical locations and the surrounding market infrastructure for feedstocks and energy products. Strategic decisions to locate energy conversion facilities must take all upstream and downstream operations into account, prompting the development of supply chain modeling and optimization methods. This article reviews the contributions of energy supply chain studies that include heat, power, and liquid fuels production. Studies are categorized based on specific features of the mathematical model, highlighting those that address energy supply chain models with and without considerations of multiperiod decisions. Studies that incorporate uncertainties are discussed, and opportunities for future research developments are outlined.