Industrial & Engineering Chemistry Research
Industrial & Engineering Chemistry Research
5 years ago

Multiobjective Integrated Planning and Scheduling of the Energy Infrastructure of the Oil Sands Industry Incorporating Intermittent Renewable Energy

Multiobjective Integrated Planning and Scheduling of the Energy Infrastructure of the Oil Sands Industry Incorporating Intermittent Renewable Energy
Ali Elkamel, Mohamed Elsholkami
The energy infrastructure for oil sands operations can be classified as a decentralized energy system, in which energy requirements (i.e., power, heat and hydrogen) are generated near the end-users, and can operate with interactions with the local Alberta grid, in which it feeds surplus power generated to it. In this study, a mathematical optimization model is developed for the integrated planning and scheduling of the energy infrastructure of the oil sands industry. The contributions of various energy sources including conventional, renewables, and nuclear are investigated. Power-to-gas for energy storage is incorporated to manage surplus power generated from intermittent renewable energy sources, particularly wind. The wind-electrolysis system included incorporates two hydrogen recovery pathways, which are power-to-gas and power-to-gas-to-power using natural gas generators. The problem is modeled as a multiobjective and multiperiod mixed integer linear programming model that minimizes the system cost (energy production and storage), grid cost, and total greenhouse gas emissions. In addition to including the grid cost and emissions in the objective function, grid-interaction is incorporated in the optimization model through the unit commitment operations of the existing power generation units of the grid. The proposed model is designed to evaluate the optimal operation and sizing of the energy producers and the energy storage system as well as the interactions between them. The epsilon constraint method is used to solve the multiobjective aspect of the proposed model. To illustrate its applicability, the model is applied to a case study based on the oil sands industry in Alberta for the integrated planning and scheduling of its energy infrastructure for the year 2017.

Publisher URL: http://dx.doi.org/10.1021/acs.iecr.7b04800

DOI: 10.1021/acs.iecr.7b04800

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