Actual Measurement and Evaluation of the Balance between Electricity Supply and Demand in Waste-Treatment Facilities and Development of Adjustment Methods  
[PERSON]  
1 Graduate School of Environment and Energy Engineering, Waseda University, 509, 513 Wasedatsurumakicho, Shinjuku-ku, Tokyo 162-0041, Japan; [EMAIL_ADDRESS] (D.Y.) [EMAIL_ADDRESS] (Y.O.) [PERSON]  
2 Daiei Environmental Research Institute Co., Ltd., 1 Chome-4-1 Nihonbashi, Chuo City, Tokyo 103-0022, Japan; kikuchi@[EMAIL_ADDRESS]  
[PERSON]  
1 Graduate School of Environment and Energy Engineering, Waseda University, 509, 513 Wasedatsurumakicho, Shinjuku-ku, Tokyo 162-0041, Japan; [EMAIL_ADDRESS] (D.Y.) [EMAIL_ADDRESS] (Y.O.) [PERSON]  
3 Environment Research Institute, Waseda University, 509, 513, Wasedatsurumakicho, Shinjuku-ku, Tokyo 162-0042, Japan; [EMAIL_ADDRESS]  
[PERSON]  
Correspondence: [EMAIL_ADDRESS]; Tel. : +81-3-6457-3972  
power generation efficiency due to a low combustion temperature, and difficulty in power adjustment. In addition, decarbonization in the supply chain under the greenhouse gas (GHG) protocol has been hindered by the increased CO2 emissions due to intermediate treatment facilities, such as incinerators [8; 9]. Furthermore, when electricity is purchased from a grid power company in Japan, it is calculated using a constant annual value factor of CO2 emission. However, the CO2 emission factor is not constant because the power supply composition fluctuates depending on the weather and time as the number of unstable power supplies increases [10]. In Japan, the increasing number of unstable power supplies necessitates adjusting the operation of solar power generation during the daytime on holidays. Moreover, the utilization of unstable power supplies is challenging [11; 12; 13]. In this study, to establish a plan to minimize CO2 emissions, large-scale waste treatment/disposal plants (hereafter abbreviated as RC) located in Iga City, Mie Prefecture, and solar power generation equipment (hereafter abbreviated as PV) located in Izumi City, Osaka Prefecture and owned by the same group corporation are taken as case study facilities. The RC plants were considered as one block (RC block). The internal processing equipment represented the consumer, and the three incineration facilities and PV in the RC block were the power supply source. Here, the present study established a method to predict power load and power generation patterns by acquiring and analyzing power demand and supply data at each facility. In Japan, methods for predicting energy demand in specific city blocks and the amount of electricity generated by specific facilities have been established [14; 15]. However, these methods are designed to be used in business models based on the viewpoint of power generators and retailers who supply electricity, and few studies capture the matching of supply and demand from both directions. One approach similar to this study is peak shifting, but the peak shifting plans that have been popularized mainly by retail electric utilities mostly only change the electricity price depending on the season and do not change the demand-side energy use plan following the demand-side energy use plan with the real-time power supply composition. Similarly, changing the demand-side energy use plan is impossible to comply with the real-time power supply configuration [16]. In a demand response approach, where consumer electricity consumption is reduced by fluctuating electricity prices when electricity load is tight, using simulation models in residential areas is effective. However, only a few industrial companies have taken this approach, and its actual status and effectiveness are unclear [17; 18]. The novelty of this research lies in the fact that, based on this background, this study has designed a model that makes it possible to construct electricity procurement and usage plans that minimize CO2 emissions based on measured data from actual operating facilities in the industrial sector and the demand and generation characteristics of each facility.