Optimal design of multi-energy systems with seasonal storage. (1st June 2018)

• Record Type: Journal Article
• Authors: Gabrielli, Paolo; Gazzani, Matteo; Martelli, Emanuele; Mazzotti, Marco
• Is Part Of: Applied energy. Volume 219(2018)
• Page Start: 408
• Page End: 424
• Publication Date: 2018-06-01
• Subjects: Multi-energy systems -- Microgrids -- Seasonal storage -- Investment planning -- Yearly scheduling -- MILP -- Power-to-gas; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2017.07.142
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Novel MILP approaches to enable design of MES including seasonal energy storage. Good accuracy and much lower computational complexity compared to current approaches. Realistic Swiss case-study evaluated in terms of total annual cost and emissions. Extensive sensitivity analysis defining design guidelines for seasonal energy storage. 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 hourly resolution; this turns into a large number of decision variables, including binary variables, when large systems are analyzed. This work presents novel mixed integer linear program methodologies that allow considering a year time horizon with hour resolution while significantly reducing the complexity of the optimization problem. First, the validity of the proposed techniques 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 results of the proposed approaches are in good agreement with the full-scale optimization, thus allowing to correctly size the energy storage and to operate the system with a long-term policy, while significantly simplifying the optimization problem. Furthermore, the developed methodology is adopted to design a multi-energy system based on a neighborhood in Zurich, Switzerland, which is optimized in terms of total annual costs and carbon dioxide emissions. Finally the system behavior is revealed by performing a sensitivity analysis on different features of the energy system and by looking at the topology of the energy hub along the Pareto sets.