This work focuses on the development of optimization-based scheduling strategies for the coordination of microgrids. The main novelty of this work is the simultaneous management of energy production and energy demand within a reactive scheduling approach to deal with the presence of uncertainty associated to production and consumption. Delays in the nominal energy demands are allowed under associated penalty costs to tackle flexible and fluctuating demand profiles. In this study, the basic microgrid structure consists of renewable energy systems (photovoltaic panels, wind turbines) and energy storage units. Consequently, a Mixed Integer Linear Programming (MILP) formulation is presented and used within a rolling horizon scheme that periodically updates input data information.Peer ReviewedPostprint (author's final draft

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The concept of the circular economy has gained wide interest in industry as a powerful strategy to reduce impacts while remaining economically competitive. Here we explore the benefits of this approach in the chemical industry, quantifying explicitly the economic and environmental benefits of ethylene recovery from polyethylene plastics using process modeling coupled with Life Cycle Assessment (LCA). Our results show that the recovered ethylene represents a win-win alternative, offering a highly competitive cost of 0.386 €/kg vs 0.835 €/ kg with the standard naphtha-based route. Furthermore, substantial reductions of as much as 87%, 89% and 164% could also be attained (compared to the naphtha-based ethylene) in impacts on human health, ecosystem quality and resources scarcity, respectively.Overall, this work aims to promote the adoption of circular economy strategies in the chemical sector, while highlighting the role of process modeling, LCA and systems thinking in quantifying the associated benefits to build strong cases for policymaking.

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Nowadays market competition is essentially associated to supply chain (SC) improvement. Therefore, the locus of value creation has shifted to the chain network. The strategic decision of determining the optimal SC network structure plays a vital role in the later optimization of SC operations. This work focuses on the design and retrofit of SCs. Traditional approaches available in literature addressing this problem usually utilize as departing point a rigid predefined network structure which may restrict the opportunities of adding business value. Instead, a novel flexible formulation approach which translates a recipe representation to the SC environment is proposed to solve the challenging design-planning problem of SC networks. The resulting mixed integer linear programming model is aimed to achieve the best NPV as key performance metric. The potential of the presented approach is highlighted through illustrative examples of increasing complexity, where results of traditional rigid approaches and those offered by the flexible framework are compared. The implications of exploiting this potential flexibility to improve the SC performance are highlighted and are the subject of our further research work. V V C 2009 American Institute of Chemical Engineers AIChE J, 55: 1736AIChE J, 55: -1753AIChE J, 55: , 2009 Keywords: supply chain management, network design, flexibility, MILP Introduction A SC may be defined as a collaborative network wherein a number of various business entities work together in an effort to: (1) acquire raw materials, (2) convert these raw materials into specified final products, and (3) deliver these final products to retailers. This chain is traditionally characterized by a forward flow of materials and a backward flow of information.1 Usually in SC literature, business entities are classified by echelon type (e.g., suppliers, manufacturers, distributors, retailers).Subsequently, supply chain management (SCM) can be defined as the management of material, information, and financial flows through a SC that aims at producing and delivering products or services to consumers. 2 The main objectives usually are to achieve desired consumer satisfaction levels and/or satisfactory financial returns by synchronizing and coordinating the SC members activities. The need for such coordination grows out of several trends in the marketplace, such as the globalization of market economies. Business global perspective has led to the availability of a vast set of alternative sources of materials and other inputs as well as a wider array of potential customers. Customers' changing expectations regarding value of goods and services, combined with advances in technology and the availability of information, have driven the formation of interorganizational networks. 3 The SC modeling problem is very complex. In practice, it is usually helpful to use the time dimension to establish a hierarchical order so as to facilitate SC coordination. At the top level, long-term or strategic planning affects the achievement of g...