Optimal control of energy hub systems by use of SQP algorithm and energy prediction
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...
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| creator | Kampouropoulos, Konstantinos Andrade, Fabio Sala, Enric Romeral, Luis |
| description | 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. |
| doi_str_mv | 10.1109/IECON.2014.7048503 |
| format | Conference Proceeding |
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| ispartof | IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, 2014, p.221-227 |
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| language | eng |
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| source | Recercat |
| subjects | adaptive neuro-fuzzy inference system Cooling Electric engineering Energies energy hub energy optimization energy prediction Enginyeria electrònica Enginyeria elèctrica Heating Heuristic algorithms Inference algorithms Mathematical model Optimization Production sequential quadratic programming algorithm Àrees temàtiques de la UPC |
| title | Optimal control of energy hub systems by use of SQP algorithm and energy prediction |
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