Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies

• Published in: Applied energy Vol. 261; p. 114393
• Main Authors: Heidari, A., Mortazavi, S.S., Bansal, R.C.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2020
• Subjects: case studies; cold storage; cooling; Demand response; energy conversion; Energy hub; heat; Ice storage; operating costs; Renewable energies; renewable energy sources; solar collectors; Stochastic programming; wind turbines; Energy hub; Demand response; Renewable energies; Ice storage; Stochastic programming
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2019.114393

•A model is presented for an ice storage performance inside an energy hub.•Energy hub uses stochastic programming for optimal operation.•There are renewable energies including wind turbines and solar panels.•There are uncertainties in scheduling of energy hub.•The proposed solution is based on scenario generation and scenario reduction. The energy hub as a new concept has attracted much attention in modern power systems. One of the aspects of an energy hub deals with its optimal operation. Energy hub scheduling for a day-ahead time horizon including demand response program, different kinds of energy storage, and renewable energy resources, are focused on this current study. In particular, the effects of ice storage, as a novel and developing storage device and yet researchable subject, on the performance and efficiency of the energy hub operation cost are investigated. The stochastic behavior of ice storage is also considered to be compared with deterministic conditions. The studied energy hub is composed of energy converters, including combined cooling, heating, and power (CCHP), to deliver energy to its electrical, heating, and cooling loads. It uses clean, green and, renewable energies as wind turbines and solar panels. The method applied is that the studied energy hub minimizes its operation costs while satisfying demand response constraints in an uncertain environment. The proposed methodology has been evaluated in comparative case studies, and the obtained results show the requirement of including uncertain mode of ice storage in the energy hub.