May 16, 2024
Sayyad Nojavan

Sayyad Nojavan

Academic rank: Associate professor
Address:
Education: Ph.D in ٍElectrical Power Engineering
Phone: 09148903379
Faculty: Faculty of Engineering
Department: Electrical Engineering

Research

Title
Risk assessment of residential home in the presence of electrical, thermal and water storage systems via downside risk constraint method
Type Article
Keywords
Energy storage Smart appliances Rainwater collection and greywater recycling Downside risk constraint method Risk-neutral Risk-averse
Researchers Shuo Liu، Chen Liu، Qun Guo، Kamran Taghizad-Tavana، Sayyad Nojavan

Abstract

Today, water and power are the essential items that influence people's lives regarding water demand and energy supply. In this regard, due to the impacts of residential homes on energy consumption in energy distributions, the integrated systems could be applied for smart homes' optimization, including water and electricity consumption. In this study, the related standards of the smart home, smart appliances, technologies for storing energy, rainwater harvesting (RWH) and greywater recycling system, renewable energy storage, and ground source heat pump (GSHP) are established in the building to maximize the system's profit. Integration of various technologies and energy types leads to huge problems in optimal scheduling, especially under the uncertain environment that needs to be investigated. Investigating the impacts of uncertainty in the optimal operation of integrated energy homes could be carried by risk assessment under various scenarios in uncertain parameters. In this concern, the downside risk constraint (DRC) method is applied to assess the system performance under wind speed and solar radiation uncertainty in 10 scenarios with different uncertainty conditions. It should also be mentioned that the results are represented in the risk-averse and risk-neutral strategies. Compared to the risk-neutral model, almost 14 % of the system profit is reduced in the risk-averse model, in which the level of risk reduces from $0.2 to zero. In addition to that, in the risk-averse model, approximately 8 % of the electricity consumption is shifted from peak hours to off-peak hours in the building.