Robust Integrated Energy Management of a Smart Home Considering Discomfort Degree-Day

Abstract

This article implements an integrated electrical and thermal energy management of a smart home in real time, taking into account the residents' comfort conditions. The smart home can benefit from a multi-carrier energy system. The energy resources include electrical network, photovoltaic generating unit and storage unit, as well as a hybrid water heating system supplied from solar irradiation and natural gas network. Additionally, electrical and thermal loads are categorized into three types: i)time flexible, ii) power flexible and iii) fixed loads. Taking advantage of smart grid technology, an energy management system receives required economic, technical, and climatic information in real-time, and decides the energy schedules time by time. The integrated energy management problem is formulated to optimize economic and discomfort metrics. A novel metric of discomfort degree-day is proposed to measure the residents' dissatisfaction with the indoor temperature, which considers both magnitude and duration of deviation from a desired temperature in a day. Additionally, the uncertainties in solar irradiation and outdoor temperature are presented by uncertainty sets, and handled through a robust optimization model. The out-of-sample results through a realistic case study indicate that a more robust schedule of energy resources and loads (e.g., ranging from 20% to 100% robustness) is obtained with negligible change (e.g., < 1%) in the operation cost, but at the expense of 48.82% and 58.97% increment of dissatisfaction under the uncertainty sets with the confidence levels of 0.6 and 0.8, respectively.