Estimating the hourly electricity profile of Japanese households – Coupling of engineering and statistical methods

AbstractUnderstanding the hourly electricity profile and the electricity consumption by each appliance is essential for encouraging energy-saving measures in the household sector. There are two methods for identifying energy consumption for households in existing studies: the engineering and the statistical methods. Both methods have strengths and limitations. In this study, we developed a hybrid method based on the statistical method by combining following three steps using knowledge of the engineering method; externalizing the electricity consumption for the refrigerator, adding the number of at-home-and-awake members as explanatory variables, and restricting appliance usage hours. The proposed hybrid method could adequately reproduce the total hourly electricity consumption and seasonal variation compared to the engineering method, and could decompose major appliances, some of which that were not disaggregated by the statistical method. For the quantitative analysis of the model improvement, we calculated Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) for each method with direct metering data. For most of appliances, RMSE and MAE of hybrid model were improved from 11% to 71% compared to the existing methods. The collection of more samples to increase the accuracy of the estimation and application to areas of low statistical data availability are future steps

CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies

This paper explores a multi-model scenario ensemble to assess the impacts of idealized and non-idealized climate change stabilization policies on fossil fuel markets. Under idealized conditions climate policies significantly reduce coal use in the short- and long-term. Reductions in oil and gas use are much smaller, particularly until 2030, but revenues decrease much more because oil and gas prices are higher than coal prices. A first deviation from optimal transition pathways is delayed action that relaxes global emission targets until 2030 in accordance with the Copenhagen pledges. Fossil fuel markets revert back to the no-policy case: though coal use increases strongest, revenue gains are higher for oil and gas. To balance the carbon budget over the 21st century, the long-term reallocation of fossil fuels is significantly larger—twice and more—than the short-term distortion. This amplifying effect results from coal lock-in and inter-fuel substitution effects to balance the full-century carbon budget. The second deviation from the optimal transition pathway relaxes the global participation assumption. The result here is less clear-cut across models, as we find carbon leakage effects ranging from positive to negative because trade and substitution patterns of coal, oil, and gas differ across models. In summary, distortions of fossil fuel markets resulting from relaxed short-term global emission targets are more important and less uncertain than the issue of carbon leakage from early mover action

Quantitative analysis of energy-efficiency strategy on CO2 emissions in the residential sector in Japan - Case study of Iwate prefecture

This study examines the economics of energy-efficiency strategies for reducing CO2 emissions in the residential sector in Japan from the perspective of regional characteristics. For this study, the residential sector in Iwate prefecture was selected as representative of rural areas in Japan. In order to promote purchases of energy-efficient consumer appliances, the prefectural government is presumed to reimburse purchasers a part of the cost difference between energy efficient and conventional appliances. This paper begins with a discussion of the prefecture's financial support for purchasers of energy efficient appliances and assumes that the payments come from prefectural government funds. This paper then looks at the effect of a carbon-tax refund on the reduction of CO2 emissions. The results show that, if half of the households use energy-efficient appliances, then CO2 emissions in the residential sector in the year 2020 will decreases from the BAU scenario, 0.726 Mt-C to 0.674 Mt-C. However, the Iwate prefectural government expends $105 million annually, which is 1.5$20/tC carbon tax, proposed by the Ministry of the Environment, the carbon-tax refund leads to a reduction in residential CO2 emissions from 0.726 Mt-C to 0.712 Mt-C.Energy efficiency Rural energy policy Residential sector

Energy-efficiency strategy for CO2 emissions in a residential sector in Japan

This study examines the economics of energy-efficiency strategies, for reducing CO2 emissions in a residential sector in Japan, from the perspective of regional characteristics. For this study, the residential sector in the Iwate prefecture was selected as representative of rural areas in Japan. In order to promote the purchases of energy-efficient consumer appliances, the prefectural government is presumed to reimburse purchasers a part of the cost difference between energy-efficient and conventional appliances. This paper begins with a discussion of the prefecture's financial support for purchasers of energy-efficient appliances and assumes that the payments come from prefectural government funds. This paper then looks at the effect of a carbon-tax refund on the reduction of CO2 emissions. The results show that, if half of the households use energy-efficient appliances, then CO2 emissions in the residential sector in the year 2020 will decreases from the BAU scenario of 0.726 Mt-C to 0.674 Mt-C. However, the Iwate prefectural government expends $105 million annually, which is 1.5$20/tC carbon-tax, proposed by the Ministry of the Environment, the carbon-tax refund leads to a reduction in residential CO2 emissions from 0.726 Mt-C to 0.712 Mt-C.Energy efficiency Rural energy-policy Residential sector

Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect

<div><p>After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan’s NDC (nationally determined contribution) assumes the reduction of CO₂ emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO₂ emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers’ electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%–6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO₂–2.26 MtCO₂ (−4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan’s electricity demand and CO₂ emissions after the earthquake.</p></div

CO₂ emissions from power plants, January 1988–March 2016.

<p>CO₂ emissions from power plants, January 1988–March 2016.</p

Model variables and data sources.

<p>Model variables and data sources.</p

Autocorrelation functions of standardized prediction errors derived from the seasonal and non-seasonal models.

<p>The gray regions indicate the 95% confidence intervals.</p

Result of model selection (i): Relationships between the base temperatures of the degree-day indices and AIC of the electricity demand models.

<p>Result of model selection (i): Relationships between the base temperatures of the degree-day indices and AIC of the electricity demand models.</p

Japan’s electric power generation by energy source, January 1988–March 2016.

<p>Source: EDMC Databank [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196331#pone.0196331.ref011" target="_blank">11</a>].</p