Real-time pricing will be one of the demand response methods for the future smart grid. Assuming an advanced building energy management system for air-conditioning facilities in commercial buildings, a simulated annealing optimization that minimizes an evaluation function consisting of power cost and comfort degradation terms is studied.

SUMMARY In this paper, we have constructed an auto regressive and neural network combined type prediction model for responsive change in the room temperature trend due to the fast automated demand response (FastADR) power limitation of office building air‐conditioning facilities. We defined the average of differences between room temperature and set point of each indoor unit for the entire building as a FastADR side effect index for the building. Prediction experiments using an actual office building showed that the root mean square prediction error of our model was 0.23 °C for 5 min after the FastADR. This prediction ability is considered sufficient to estimate the side effect of FastADR power limitation.

No abstract

No abstract

This paper proposes a new CSMA/CD MAC protocol for air-conditioner control networks using only the UART built in a microcontroller as a collision detection mechanism. For performance evaluation of the proposed protocol, steady state throughput and average delay are calculated by analysis based on an imbedded Markov chain model. The analysis forecasts adequate throughput and delay for an example control network. The implementation of the proposed protocol to a very low-cost microcontroller that is installed in each air-conditioner consumed only about 1 kbytes of ROM and 20 bytes of RAM. The experiments on the performance confirmed the analysis results and obtained satisfactory throughput and average delay.