Study on energy conservation in experimental facilities by changing users’ behavior

In 2021, Japan announced its aim to reduce greenhouse gas emissions by 46% in FY2030 than in FY2013, and universities were expected to contribute to the conservation of energy. The current study focused on ventilation systems in laboratories, which are among the most energy-intensive areas in universities, with the aim of reducing overall electricity consumption. The amount of electricity consumed by the draft chamber in a laboratory was determined based on the chamber opening. Result confirmed that the amount of electricity consumed by the 12 draft chambers to be 63,263 kWh/year. Using the relationship between chamber opening degree and power consumption by air conditioners and exhaust fans, we implemented a method to induce users of the draft chamber to take action toward controlling the chamber opening degree, using real-time information on chamber opening degree. A screen was set up to provide information to draft-chamber users in the laboratory using real-time monitors, and the induction of behavior was investigated over a 5-week period. Results confirmed that information displayed on the tablet device indeed reduced the chamber opening, the reduction rate being 21–48% compared to that before the information was displayed

Same-day correction of baselines for demand response using long short-term memory

In incentive-based the Demand Response, the amount of electricity demand reduction is calculated by subtracting actual electricity demand from the baseline (BL). The BL is the estimated electricity demand of households when no electricity demand suppression is performed. In Japan, the high 4 of 5 method is used to forecast the BL by averaging the actual demand of the day. In this study, we refer to the high 4 of 5 method as BL1. BL2 is the BL to which the value of the same-day adjustment is added based on the actual demand of the day. BL3 is BL1 plus the value of the same-day adjustment predicted using Long Short-Term Memory (LSTM). The average MAE values for BL2 and BL3, calculated using actual electricity demand data from October 15, 2021, to December 24, 2021, were 11.2 kW and 8.1 kW, respectively, with BL3 being 3.1 kW smaller than BL2. To estimate the confidence intervals for BL2 and BL3, we calculated the error by subtracting each BL from the actual value and calculated the ±3σ equivalent for the distribution of the error. The confidence interval calculated for BL3 was found to be ±9.2 kW lower than that for BL2. The F-test for the distribution of the errors for BL2 and BL3 yielded a P-value of 4.05 × 10-50, indicating that the variances of the two distributions were not equally distributed

Same-day correction of baselines for demand response using long short-term memory

In incentive-based the Demand Response, the amount of electricity demand reduction is calculated by subtracting actual electricity demand from the baseline (BL). The BL is the estimated electricity demand of households when no electricity demand suppression is performed. In Japan, the high 4 of 5 method is used to forecast the BL by averaging the actual demand of the day. In this study, we refer to the high 4 of 5 method as BL1. BL2 is the BL to which the value of the same-day adjustment is added based on the actual demand of the day. BL3 is BL1 plus the value of the same-day adjustment predicted using Long Short-Term Memory (LSTM). The average MAE values for BL2 and BL3, calculated using actual electricity demand data from October 15, 2021, to December 24, 2021, were 11.2 kW and 8.1 kW, respectively, with BL3 being 3.1 kW smaller than BL2. To estimate the confidence intervals for BL2 and BL3, we calculated the error by subtracting each BL from the actual value and calculated the ±3σ equivalent for the distribution of the error. The confidence interval calculated for BL3 was found to be ±9.2 kW lower than that for BL2. The F-test for the distribution of the errors for BL2 and BL3 yielded a P-value of 4.05 × 10-50, indicating that the variances of the two distributions were not equally distributed

Study on energy conservation in experimental facilities by changing users’ behavior

In 2021, Japan announced its aim to reduce greenhouse gas emissions by 46% in FY2030 than in FY2013, and universities were expected to contribute to the conservation of energy. The current study focused on ventilation systems in laboratories, which are among the most energy-intensive areas in universities, with the aim of reducing overall electricity consumption. The amount of electricity consumed by the draft chamber in a laboratory was determined based on the chamber opening. Result confirmed that the amount of electricity consumed by the 12 draft chambers to be 63,263 kWh/year. Using the relationship between chamber opening degree and power consumption by air conditioners and exhaust fans, we implemented a method to induce users of the draft chamber to take action toward controlling the chamber opening degree, using real-time information on chamber opening degree. A screen was set up to provide information to draft-chamber users in the laboratory using real-time monitors, and the induction of behavior was investigated over a 5-week period. Results confirmed that information displayed on the tablet device indeed reduced the chamber opening, the reduction rate being 21–48% compared to that before the information was displayed