Energy management with control of thermal loads considering renewable energy resources

نوع: Type: thesis

مقطع: Segment: PHD

عنوان: Title: Energy management with control of thermal loads considering renewable energy resources

ارائه دهنده: Provider: Ashkan Talebi

اساتید راهنما: Supervisors: Dr. Alireza Hatami

اساتید مشاور: Advisory Professors: Dr. Raad. Z. Homod

اساتید ممتحن یا داور: Examining professors or referees: Dr. Mohammad Hasan Moradi, Dr. Abbas Fattahi, Dr. Kazem Zare

زمان و تاریخ ارائه: Time and date of presentation: February 16, 14 PM

مکان ارائه: Place of presentation: Bu Ali Sina University virtual room

چکیده: Abstract: Recently, electricity consumption has increased significantly. The construction of new power plants requires considerable time and money. To balance supply and consumption, demand response programs have been developed in recent years. HVAC systems consume more than 50% of the building energy consumption. Two unique features of HVACs, namely, long hours of use per day and high energy consumption, place their energy loads among the important in the demand response field. In this research, the optimal day-ahead scheduling of HVAC systems is studied to minimize the user's electricity cost in a smart building equipped with renewable energy resources. At the beginning of each day, nondeterministic parameters, including electricity price, ambient temperature, solar radiation, and wind speed are forecasted. Based on these forecasts, a risk-based stochastic optimization model using Chimp Optimization Algorithm (ChOA) has been employed to specify the optimal indoor setpoints of the HVAC. To manage the risk of the uncertainties involved in the forecasts, a Glue-VaR risk measure is adopted. Glue-VaR constitutes new risk measures free of the limitations and drawbacks of those proposed earlier. The results demonstrate that the scheduling could reduce users' costs and improve the utilization of renewable energy resources. Moreover, users with different attitudes toward risk are studied, and it is demonstrated that risk-averse users usually pay for more costs than risk-taking users, who will incur more losses, of course, in case the worst possible scenario occurs. The main decision parameter in the objective function is the 24 hours set-point. Also, using dead-band width and the effect of asymmetric dead-band are analyzed. The results show that the proposed method could reduce the user's cost by 33% and the HVAC's energy consumption by 12%. The HVAC system uses 20% less energy during the peak hours. Also, the user purchases 14% less energy from the main grid. Buying less energy from the main grid and selling the extra energy of renewable energy resources to grid not only reduces the user's costs, but also supports the main grid. In this research, the effect of HVAC set-point increment is analyzed and it has been shown that by decreasing the set-point by 1°C, the cost and the energy consumption would be reduced by 5%. Also, it has been shown that by decreasing the dead-band width by 0.8°C, the cost and the energy consumption would be reduced about 1%. In addition, the rebound phenomenon has been analyzed and it has been shown that by using the optimal scheduling method, no rebound phenomenon is observable

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