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Innovative information and communication technology (ICT) system for energy management of public utilities in a post-disaster region: Case study of a wastewater treatment plant in Fukushima

Maki, Seiya, Chandran, Remi, Fujii, Minoru, Fujita, Tsuyoshi, Shiraishi, Yasushi, Ashina, Shuichi, Yabe, Norio
Journal of cleaner production 2019 v.233 pp. 1425-1436
buildings, case studies, climate, communications technology, earthquakes, electric energy consumption, electricity, energy, governance, greenhouse gas emissions, greenhouse gases, households, issues and policy, models, monitoring, public utilities, wastewater treatment, Japan
On March 11, 2011, the Tohoku earthquake caused major damage to almost all public infrastructures including energy and water facilities in Fukushima Prefecture. Following the nuclear disaster, which lead to a shortage of energy, the government of Japan enacted new policy measures to redefine its energy-mix after its earlier commitment to the Copenhagen Climate Summit in 2009 to reduce greenhouse gas emission by 25% from 1990 levels by 2020. In 2015, Japan ratified the Paris Accord and set a national greenhouse gas reduction goal - 26% below 2013 levels by 2030. To meet this requirement, Japan needs to restructure its current electricity consumption by identifying the optimal demand of electricity by households, commercial buildings, and public utilities. This calls for public infrastructures to manage their electricity consumption efficiently by adopting appropriate electricity conservation methods using precision monitoring systems. To support the policy of the government of Japan toward conservation of energy, in this paper, we outline the energy demand of a public utility system, namely a wastewater treatment plant (WWTP), in Fukushima Prefecture, Japan, and based on the data obtained using an innovative information and communication technology (ICT) tool. Using the monitored data, we further predict the electricity demand for each process of the WWTP using a Markov switching model. These models have high repeatability of monitoring results for each process according to various indices. In our results, all R2 values were more than 0.8; mean absolute percentage error values were under 10% for total electricity consumption and the water treatment process, and the relative root mean square error rate of each process was under 20%. Based on the results, we developed a future electricity consumption prediction model for WWTP total electricity consumption and the consumption of each process. The study emphasizes the need for an innovative ICT and advanced analysis system for supporting the governance of public facilities.