Information gap decision theory-based risk-constrained scheduling of smart home energy consumption in the presence of solar thermal storage system

In domestic sector, robust scheduling of energy usage under various uncertainties is an important factor for any smart home energy management systems (EMS). In this paper, information gap decision theory (IGDT) is proposed for robust scheduling of apartment smart building (ASB) in the presence of price uncertainty and solar thermal storage system (STS). The proposed sample ASB contains combined heat and power (CHP) generator, boiler, battery storage system (BSS), STS system and smart appliances. IGDT approach doesn't depend on the size of the model. So, the EMS of ASB which is known as small scale loads can use IGDT to make more informed decisions against the price uncertainty. IGDT contains two functions namely robustness and opportunity functions. Risk-averse perspective of optimal scheduling of ASB is modeled by robustness function and opportunity function is used to model risk-taker perspective of optimal scheduling of ASB. Also, to assess the effect of STS system on proposed problem, two case studies are studied, and significant results were obtained, which indicate the validity of proposed model.