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Optimal control of energy hub systems by use of SQP algorithm and energy prediction
Kampouropoulos, Konstantinos; Sala Cardoso, Enric; Andrade, Fabio; Romeral Martínez, José Luis
Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica; Universitat Politècnica de Catalunya. MCIA - Centre MCIA Innovation Electronics
This paper presents an energy optimization methodology applied on industrial plants with multiple energy carriers. The methodology combines an adaptive neuro-fuzzy inference system to calculate the short-term load forecasting of a plant, and the sequential quadratic programming algorithm to optimize its energy flow. Furthermore, the mathematical models of the plant's equipment are considered into the optimization process, in order to calculate the dynamic system response and the equipment's inertias. The final algorithm optimizes the operation of the plant in order to satisfy the energy demand, minimizing several optimization criteria. The methodology has been tested and evaluated in an automotive factory plant using real production and consumption data.
Àrees temàtiques de la UPC::Enginyeria electrònica
Àrees temàtiques de la UPC::Energies
Electric engineering
adaptive neuro-fuzzy inference system
energy hub
energy optimization
energy prediction
sequential quadratic programming algorithm
Enginyeria electrònica
Enginyeria elèctrica

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