• Energy Research

Abstract The Economic Order Quantity, EOQ, model has been popular among academicians and practitioners for decades. Despite the many variants of the EOQ that have appeared in the literature to fine-tune it to reality, it still has limitations. A major one is that it does not take into account the hidden costs inherent in inventory systems. Some of these costs relate to sustainability issues including environmental, social labor, and economic effects. This paper considers some of these costs, referred to as the exergetic costs, and estimates them using the Extended Exergy Accounting, EEA, approach. Extended Exergy Accounting assigns equivalent exergetic values to capital, labor and environmental remediation costs of a system. The analysis combines the classical exergy analysis with the sustainability factors, which are the labor, capital and environment. The paper uses an exergetic model to determine the EOQ inventory policies for three firms operating in the USA, Germany and China. The results show that the EOQ is different for the three firms because the equivalent exergy of capital, labor and environment remediation costs is different in each country.

Abstract Industrial symbiosis is a cost-effective and environmentally-friendly solution for industries. It reduces the consumption of energy and virgin material by extracting value from waste, lost heat and by-products. Energy symbiosis could fulfill a portion of industrial and non-industrial energy needs. This study discusses the opportunities and challenges of energy symbioses for non-industrial purposes, and develops a multi-objective mixed integer linear programming model for that purpose. The model minimizes the total cost and the environmental impact among energy suppliers and users. It includes the costs of implementing and operating an energy sharing network. The model is used to determine the optimal energy partners in an industrial area and residential neighborhoods in a western European industrial park. The proposed model also helps in studying the effects of uncertainties that may arise when establishing the energy network. The contribution of this paper is twofold. First, it proposes using industrial symbioses to identify the challenges and to find solutions to meet the increasing demand for energy in urban and rural areas. Second, it develops a method to access affordable sources of energy for non-industrial purposes under uncertainties. The results show that involving residential customers in the symbioses would increase the environmental and economic benefits for all stakeholders in an eco-industrial park. The paper also shows that industries can play a key role in reducing the environmental impact in residential neighborhoods.

Abstract Industrial symbiosis can play a prominent role in greening existing industrial networks by reducing the costs of raw material and energy exchanges, as well as decreasing the environmental impact of businesses. Energy symbiosis, a key component of industrial symbiosis, could reduce the need for fossil fuels and contribute to the circular economy by recovering waste energy throughout production processes. There are currently gaps in the literature regarding the social aspects of industrial symbiosis, including in the selection of energy partners. This paper presents a novel mixed-integer linear programming (MILP) model incorporating the key sustainability pillars in the optimal design of an energy symbiosis network, which also accounts for the fluctuation of energy demand in different seasons. It also shows, using a case study, that the model applies to a real-life situation and could be a useful decision-making tool to firms interested in promoting energy symbiosis. The results show that the economic and environmental objectives promote a similar energy exchange network. Social value preference, however, could encourage more symbiotic connections, which, as the results suggest, does not decrease the economic and environmental effect of the symbiotic network. The research provides a new perspective on the role of social objectives individually or combined with other sustainability pillars in designing optimal energy symbiosis networks.