Data‐driven mathematical modeling and global optimization framework for entire petrochemical planning operations

Computational Experience with Piecewise Linear Relaxations for Petroleum Refinery Planning

Refinery planning optimization is a challenging problem as regards handling the nonconvex bilinearity, mainly due to pooling operations in processes such as crude oil distillation and product blending. This work investigated the performance of several representative piecewise linear (or piecewise affine) relaxation schemes (referred to as McCormick, bm, nf5, and nf6t) and de (which is a new approach proposed based on eigenvector decomposition) that mainly give rise to mixed-integer optimization programs to convexify a bilinear term using predetermined univariate partitioning for instances of uniform and non-uniform partition sizes. The computational results showed that applying these schemes improves the relaxation tightness compared to only applying convex and concave envelopes as estimators. Uniform partition sizes typically perform better in terms of relaxation solution quality and convergence behavior. It was also seen that there is a limit on the number of partitions that contribute to relaxation tightness, which does not necessarily correspond to a larger number of partitions, while a direct relationship between relaxation size and tightness does not always hold for non-uniform partition sizes.

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.

An Investigation of the Techno-Economic and Environmental Aspects of Process Heat Source Change in a Refinery

This study of process heat source change in industrial conditions has been developed to aid engineers and energy managers with working towards sustainable production. It allows for an objective assessment from energetic, environmental, and economic points of view, thereby filling the gap in the systematic approach to this problem. This novel site-wide approach substantially broadens the traditional approach, which is based mostly on “cheaper” and “cleaner” process heat sources’ application and only takes into account local changes, while neglecting the synergic effect on the whole facility’s operations. The mathematical model employed assesses the performance change of all the affected refinery parts. The four proposed aromatic splitting process layouts, serving as a case study, indicate feasible heat and condensate conservation possibilities. Although the estimated investment needed for the most viable layout is over €4.5 million, its implementation could generate benefits of €0.5–1.5 million/year, depending on the fuel and energy prices as well as on the carbon dioxide emissions cost. Its economics is most sensitive to the steam to refinery fuel gas cost ratio, as a 10% change alters the resulting benefit by more than €0.5 million. The pollutant emissions generated in the external power production process contribute significantly to the total emissions balance.

Analysis of C3 fraction splitting system performance by mathematical modeling in MATLAB environment

Propane-propylene mixture splitting by industrial conventional rectification incorporating a heat pump for energy intensity decrease was modeled in the Matlab environment. The constructed model was verified by comparing its results with operational data of a real C3 fraction splitting unit. As documented, increased product quality can be obtained at zero additional costs due to specific features of the system design. Process capacity and product purity limitations have to be considered in future C3 fraction production increase plans. Further compressor and its driving unit design features have to be incorporated in the calculation model to reliably assess the C3 fraction processing costs and provide a reliable tool for process operation optimization.