The University of Tokyo · Engineering
Professor Ziyang Wang's research lab specializes in energy efficiency and sustainable building systems, with a focus on real-time thermal comfort modeling, intelligent HVAC control, and energy optimization in residential and commercial buildings. The lab also investigates vehicle energy consumption and CO2 emissions prediction, particularly through advanced driving behavior analysis, and develops innovative machine learning models—such as CNN-LSTM—for day-ahead electricity price forecasting in renewable energy-integrated power systems. A key research direction involves improving energy conservation through dynamic assessment of thermal sensation trends and adaptive ventilation strategies in indoor environments.
Figures are computed from collected data and may differ slightly.
Real-time thermal comfort evaluation is not only essential in constructing the control module of Heating, Ventilation and Air Conditioning (HVAC) systems in residential buildings but also rather critical in energy conservation. In the transient thermal environment, current thermal comfort is not stable and varies from time to time. Therefore, if we only evaluate the current thermal sensation that will cause prediction error. Existing thermal comfort models mainly focus on the evaluation of curre
Fossil fuel vehicles significantly contribute to CO2 emissions due to their high consumption of fossil fuels. Accurate estimation of vehicular fuel consumption and the associated CO2 emissions is crucial for mitigating these emissions. Although driving behavior is a vital factor influencing fuel consumption and CO2 emissions, it remains largely unaddressed in current CO2 emission estimation models. This study incorporates novel driving behavior data, specifically counts of occurrences of dangero
Day-ahead electricity price forecasting (DAEPF) holds critical significance for stakeholders in energy markets, particularly in areas with large amounts of renewable energy sources (RES) integration. In Japan, the proliferation of RES has led to instances wherein day-ahead electricity prices drop to nearly zero JPY/kWh during peak RES production periods, substantially affecting transactions between electricity retailers and consumers. This paper introduces an innovative DAEPF framework employing
Day-ahead electricity price forecasting (DAEPF) is vital for participants in energy markets, particularly in regions with high integration of renewable energy sources (RESs), where price volatility poses significant challenges. The accurate forecasting of high and low electricity prices is particularly essential, as market participants seek to optimize their strategies by selling electricity when prices are high and purchasing when prices are low to maximize profits and minimize costs. In Japan,
Buildings consume a huge amount of energy and mainly utilize it for occupants' thermal comfort satisfaction. Real-time thermal comfort assessment can enormously contribute to thermal comfort optimization and energy conservation in buildings. Existing thermal comfort models mainly focus on the real-time assessment of occupants' current thermal comfort. However, in the transient thermal environment, occupants' thermal comfort is unsteady and varies from time to time. Therefore, if we only assess o
The paper introduces the basic principle of the inducement type ventilation in the province of aerodynamics: disturbed characteristic of high-speed cascade can effectively leads quiescent air around it and drive air flow, compares and analyzes the traditional ventilation type and inducement ventilation type applied in underground garage in the facets of airflow organization, practicability and economy, coming to the conclusion that the inducement type ventilation is applied to the underground ga
Wearable thermoelectric coolers (TECs), applicable in both indoor and outdoor environments, directly cool the human body surface and are considered to have much higher energy efficiency compared to compressor-based air-conditioners.However, the low coefficient of performance (COP) of TECs continues to be a significant burden on lithium-ion batteries, limiting the widespread use of TEC-based wearable coolers.In this study, we propose a novel water-electricity hybrid energy system by utilizing the
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