Hiroto Iguchi

A novel charging-time control method for numerous EVs based on a period weighted prescheduling for power supply and demand balancing

To establish a sustainable energy supply system, renewable energy sources and low-carbon vehicles will have to become more widespread. However, it is often pointed out that the dissemination of these technologies will cause difficulties in balancing supply and demand in a power system, due to the fluctuation in the amounts of renewable energy generated and the fluctuation in the power demanded for numerous electric vehicles (EVs). The numerous EVs charging control seems to be difficult due to the difficulties in predicting EV trip behaviors, which vary depending on individual EV users. However, if we can control the total demand of numerous EVs, we can not only level their total load shape but also improve the supply-demand balancing capability of a power system to create new ancillary service businesses in the power market. This paper proposes a novel centralized EV-charging-control method to modify the total demand of EV charging by scheduling EV charging times. The proposed method is expected to be a powerful tool for a power aggregator (PAG), which will supply EV charging services to EV users and load leveling services to transmission system operators (TSOs) without inconveniencing EV users. The simulation showed that under the assumed EV trip patterns, the total charging demand of numerous EVs was successfully shaped so that the differences between watt-hours of the requirement and those of the controlled results were less than 4%.

Balancing power supply-demand by controlled charging of numerous electric vehicles

High penetration of variable renewable energy generation such as photovoltaics and wind power generation will cause a supply-demand imbalance in the entire system. The mass deployment of electric vehicles (EVs) and plug-in hybrid vehicles (PHVs) will also cause significant changes in electricity demand. Therefore, controlling and managing the charging time of EVs/PHVs are imperative for power system operation. We assumed trip patterns of 10 million EVs in the Tokyo power system and analyzed the power system loads, including the charging load of EVs, in some scenarios. We verified quantitatively that charging-time controls are absolutely necessary because the fuel costs for generating power by thermal power plants increase without charging-time controls. Further, we found that load leveling is more effective for multi-car charging management than for single-car charging management.

Consumer Phase Shift Simulation Based on Social Psychology and Complex Networks

We have developed the methods for estimating how a new product or a new service will be accepted in contemporary society, considering the effects of word-of-mouth recommendations. These methods are based on a consumer phase shift modeling framework that consists of a consumer agent model and a social network model. Consumer agents, which are classified into four types and six phases, exchange information with each other on a social network. Model parameters were acquired by surveys regarding several new services. These surveys were designed using the snowball sampling technique. We also developed a network generation procedure, applying the idea of complex networks. The multi-agent simulation results proved the feasibility of this framework.

Consumer Behavior Modeling Based on Social Psychology and Complex Networks

Service innovation necessitates the acceptance by customers. The evaluation of the acceptance is problematic as word-of-mouth type of advertising becomes popular. We developed a consumer behavior modeling framework that consists of consumer agents and consumer network, using snowball sampling technique. The differentiating technologies are social psychology and complex networks. Our data analysis and multi-agent simulations proved the feasibility of this framework.

Extraction of important keywords in free text of questionnaire data and visualization of relationship among sentences

Recently, companies often carry out questionnaire(s) and develop marketing strategies. There are usually two types of forms for the answer of a questionnaire. One is the form to select prepared answers and the other is free text form. The true message might be in the text form rather than the numerical part, then the analysis of free text form is needed. The amount of text in a questionnaire is, however, usually large and difficult to read whole text data for analysis. This study tries to develop a free text analysis support system which visualizes relationships among respondents based on their texts and shows their opinions using graph structure of keywords. First, this paper proposes the extraction method of important keywords in their opinions based on the modification relationships. Next, it clusters the respondents interactively on visible space using MDS. Finally, it shows their opinions using HK Graph which can visualize the relationship among words with hierarchical network structure based on the co-occurrence information for the keyword graph.

Impacts of ubiquitous society on the global warming problem in 2010

The authors used a macroeconomic modeling framework called a computable general equilibrium model to estimate the potential impact of the progress of ubiquitous networking technologies on CO/sub 2/ emissions in Japan. Four scenarios of the effects of ubiquitous networking technologies were made in Japan in 2010. The four scenarios correspond to four different levels of the progress of a ubiquitous networking society. In each scenario, the electricity consumed by electronics products, effects of ubiquitous applications on energy use, and the market size of ubiquitous application services were estimated. The results indicate that advanced ubiquitous networking technologies could potentially reduce the CO/sub 2/ emissions produced by the Japanese economy by approximately 3%.