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Optimal Control of Waste Recovery Process
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  • Othman Cherkaoui-Dekkaki,
  • Walid Djema,
  • Nadia Raissi,
  • Jean Luc Gouzé,
  • Noha El Khattabi
Othman Cherkaoui-Dekkaki
Universite Mohammed V de Rabat Faculte des Sciences

Corresponding Author:[email protected]

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Walid Djema
Centre Inria d'Université Côte d'Azur, France.
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Nadia Raissi
Universite Mohammed V de Rabat Faculte des Sciences
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Jean Luc Gouzé
Centre Inria d'Université Côte d'Azur, France.
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Noha El Khattabi
Universite Mohammed V de Rabat Faculte des Sciences
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Abstract

As society transitions away from fossil fuels towards renewable energy sources, finding alternatives that are reliable becomes imperative. Waste-to-energy bioprocesses are promising options due to their ability to operate independently of weather conditions or time of day, making them sustainable and potentially lucrative solutions. This paper proposes an updated bioeconomic model, based on previous research [12, 13], to analyze investment in waste-to-energy technology and its associated valorization of waste treatment. This conceptual model represents a generic framework for studying waste-to-energy processes. By taking technological constraints into account, the updated model aims to optimize energy production processes and establish a sustainable business model. Indeed, using dynamic modeling, investment and valorization strategies will be evaluated through a maximization criterion over a finite time horizon, which is stated as an optimal control problem. The effective control strategies are then determined using the Pontryagin’s Maximum Principle. Furthermore, direct optimization methods are applied to derive and validate the effectiveness of the obtained optimal strategy. This approach allows for a thorough evaluation of the economic and environmental impacts in waste-to-energy technologies, identifying optimal investment and valorization strategies to promote sustainable waste management practices. In addition, a sensitivity analysis is conducted to evaluate the robustness of the studied model, and provide insights into biotechnological limitations. Finally, an extensive numerical exploration of the turnpike-like features that characterize the optimal long-term behavior of the investment problem is widely discussed.