In this study, we utilize the cross and partial correlation analyses in order to investigate the dependence of power energy consumption on the temperature. To this end, we use a time series data that consists of three attributes : an hourly measured electric power consumption, temperature, and humidity. We, in particular, divide the yearly data into monthly base, and estimate the cross correlation coefficients between all possible pairs of attributes for each monthly based data. We found that temperature and power consumption are negatively correlated in the winter; positively correlated in the summer. A similar trend was found between humid and power consumption. This implies that when temperature or humidity is relatively high or low, the power consumption increases due to the cooling and heating system at work. In contrast, the correlation between temperature and humid behaves differently from those between temperature and power consumption. These results can be used to effectively manage the power system.

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon’s sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

In this paper, we investigate how the power consumption of a heat pump dryer depends on various factors in the drying process by analyzing variables that affect the power consumption. Since there are in general many variables that affect the power consumption, for a feasible analysis, we utilize the principal component analysis to reduce the number of variables (or dimensionality) to two or three. We find that the first component is correlated positively to the entrance temperature of various devices such as compressor, expander, evaporator, and the second, negatively to condenser. We then model the power consumption as a multiple regression with two and/or three transformed variables of the selected principal components. We find that fitted value from the multiple regression explains 80~90% of the observed value of the power consumption. This results can be applied to a more elaborate control of the power consumption in the heat pump dryer.

데이터 센터의 전력 소모가 크고, 그 중에 컴퓨터 서버의 전력 소모 비중이 높기 때문에, 최근 서버의 전력 절약을 위한 연구가 다양한 방향에서 진행되고 있다. 서버 컴퓨터의 구성 유닛들 중에서 특히 CPU는 주된 전력 소모 원인이다. 본 논문에서는 게임 서버 클러스터 환경에서 서버 CPU의 전력 소모를 최소화하기 위한 신규 클라이언트들을 서버에 배정하는 방법을 제안한다. 우리는 클라이언트-서버 배정 문제를 최적화 문제로 모델링하고, 시뮬레이티드 어닐링 기반 방법으로 그 해를 구한다. 우리의 방법의 특징들 중 하나는 CPU의 동작 주파수를 부하에 따라 적절히 선택하는 것으로서, 저 부하시에는 낮은 주파수를 선택해 전력 소모를 줄이게 된다. 우리의 조사에 따르면, 온라인 게임 서버의 전력 소모를 고려한 클라이언트-서버 배정에 관한 연구는 거의 없었다.

모바일 기기에 대한 다양한 멀티미디어 기능의 요구로 입체감을 제공하는 3차원 그래픽 가속기의 구현이 절실한 상황이다. 하지만 다양한 멀티미디어 기능을 가져야 하는 최근의 휴대폰의 경향과 상대적으로 발전이 더딘 배터리의 문제를 생각할 때 3차원 그래픽 가속기의 저전력화는 필수적이라고 할 수 있다. 이에 본 논문에서는 내장형 3차원 그래픽 가속기 각 내부모듈별 전력소비를 측정하고 이를 내부 그래픽 처리과정과 함께 분석하였다.