Optimal home energy management including batteries and heterogenous uncertainties. (April 2023)

• Record Type: Journal Article
• Authors: Tostado-Véliz, Marcos; Hasanien, Hany M.; Turky, Rania A.; Assolami, Yasser O.; Vera, David; Jurado, Francisco
• Is Part Of: Journal of energy storage. Volume 60(2023)
• Publication Date: 2023-04
• Subjects: Battery energy storage -- Home energy management -- Renewable energy -- Robust optimization -- Uncertainty; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2023.106646
• Languages: English
• ISSNs: 2352-152X

Abstract

Abstract: Energy storage will play a vital role in the decarbonization of the electricity sector, especially in domestic installations. In such kind of systems, home energy management applications are becoming essential. These kinds of tools enable active control of domestic appliances and storage systems to pursue a more efficient use of energy in household installations. However, the emergence of renewable generators and electric vehicles makes the operation of residential assets more difficult, as multiple uncertainties should be managed on a whole. These unknowns have a different character, in fact, some of them can be easily predicted while others are subject to a high level of randomness. This paper addresses this issue by developing a novel home energy management tool that accounts for the different levels of the randomness of the uncertainties involved in home operation. To this end, a novel Lexicographic-Interval formulation of the home energy management problem is presented, by which the uncertainties can be easily modelled using interval notation. Unlike conventional tools, the new proposal sorts the uncertainties according to their level of randomness. Then, the energy management mechanism performs the scheduling plan according to the predefined classification so that the more random parameters rule the impact of others, thus giving more importance to those uncertainties that are hardly predictable. A benchmark case study is performed to validate the new proposal and illustrate its capabilities. Different tariffs are compared, showing that the Time-of-Use mechanism is normally more expensive than Real-Time-Pricing tariffs, increasing the electricity bill by 12 % in some cases. However, the level of robustness achieved with Time-of-Use tariffs seems higher, allowing to assume an abruptly unexpected reduction of photovoltaic generation. Highlights: A novel HEM system including batteries and heterogeneous uncertainties is developed. The different uncertainties are sorted according their level of randomness. The developed method is based on a novel Lexicographic-Interval scheme. A case study accounting for weather, demand and EV uncertainties is studied. Results reveal the effectiveness and usefulness of the new methodology.