Optimal design and operation of multi-energy systems involving seasonal energy storage are often hindered by the complexity of the optimization problem. Indeed, the description of seasonal cycles requires a year-long time horizon, while the system operation calls for an hour resolution; this turns into a large number of decision variables, especially binaries. This work presents a novel mixed integer linear program methodology that allows considering a year time horizon with hour resolution whilst significantly reducing the complexity of the optimization problem. The validity of the proposed technique is tested by considering a simple system that can be solved in a reasonable computational time without resorting to design days. Findings show that the proposed approach provides results in good agreement with the full-size optimization, allowing to correctly size the energy storage and operate the system with a long-term policy, while significantly simplifying the optimization problem.

A MILP model for the design of multi-energy systems with long-term energy storage

Martelli, Emanuele;
2017-01-01

Abstract

Optimal design and operation of multi-energy systems involving seasonal energy storage are often hindered by the complexity of the optimization problem. Indeed, the description of seasonal cycles requires a year-long time horizon, while the system operation calls for an hour resolution; this turns into a large number of decision variables, especially binaries. This work presents a novel mixed integer linear program methodology that allows considering a year time horizon with hour resolution whilst significantly reducing the complexity of the optimization problem. The validity of the proposed technique is tested by considering a simple system that can be solved in a reasonable computational time without resorting to design days. Findings show that the proposed approach provides results in good agreement with the full-size optimization, allowing to correctly size the energy storage and operate the system with a long-term policy, while significantly simplifying the optimization problem.
2017
27TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PT C
9780444639653
MILP; Multi-energy systems; Optimal design; Seasonal storage; Chemical Engineering (all); Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1045966
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