Chien-fei Chen

A Smart Home Test Bed for Undergraduate Education to Bridge the Curriculum Gap From Traditional Power Systems to Modernized Smart Grids

There is a worldwide trend to modernize old power grid infrastructures to form future smart grids, which will achieve efficient, flexible energy consumption by using the latest technologies in communication, computing, and control. Smart grid initiatives are moving power systems curricula toward smart grids. Although the components of smart grids fall within the broader discipline of electrical and computer engineering, undergraduate students are rarely assigned single design projects that require classic power systems knowledge combined with communication, computing, and control. Therefore, as a significant step toward potential curriculum changes, this paper presents such a project, a smart home test bed based on the pedagogical model of project-based learning (PBL) for undergraduate education. The proposed test bed allows undergraduates to gain key knowledge in smart grid topics, such as flattening demand peaks, real-time price response, wireless sensor networks, machine learning, pattern recognition, embedded system programming, user interface design, circuit design, and databases. This is well aligned with smart grid initiatives and provides a platform for students to develop their creativity in engineering design. It also offers real-life examples to be used for raising general public awareness of energy conservation.

Residential customers elasticity estimation and clustering based on their contribution at incentive based demand response

Incentive-based demand response (IBDR) is an important category of demand response (DR) programs with large untapped potential, especially in the residential sector. Understanding customers elasticity is key to effective design of incentives. However due to limited information, price-based elasticity is needed in IBDR modeling as well. In this work, customer elasticity for an IBDR program is calculated using data from two national surveys and integrated with a detailed residential load model. There are three important aspects about elasticity estimation in this work. First, the elasticity is specific to the structure of the incentives. Second, an elasticity at the individual appliance level in residential sector is more effective for designing incentives than one for aggregate load of the feeder. Third, if elasticity can be classified based on customers contribution and incentive expectations, then targeted incentives can be developed. All of these factors are novel idea for elasticity estimation. Main motivation behind this study is to show necessity of accurate customer modeling for IBDR programs. Distinction between elasticity of each appliance as well as each customer group could lead to huge difference in results of IBDR programs.

Behavior Propagation in Cognitive Radio Networks: A Social Network Approach

A key feature of cognitive radio network is the intelligence of secondary users who can collaborate to improve the system performance. The collaboration in terms of channel recommendation is studied in this paper. The recommendation mechanism results in dynamics of the channel preferences of secondary users, thus causing a behavior propagation in a social network. For cognitive radio networks having a grid topology, the ergodicity of the dynamics is studied using the model of interacting particles in nonequilibrium statistical mechanics. For networks having a grid topology or being randomly deployed, mean field descriptions using ordinary differential equation are used to explicitly describe the dynamics of behavior propagation. The analytic results are demonstrated by numerical simulations.

Propagation of Spectrum Preference in Cognitive Radio Networks: A Social Network Approach

The social behavior in cognitive radio networks is studied using analysis tools in social networks. A recommendation system is proposed for cognitive radio, thus incurring the channel preference propagation in the corresponding random geometric network. A mean field based ordinary differential equation is used to describe the dynamics of the channel preference propagation in cognitive radio networks. The conditional distribution of random geometric graph is studied. The convergence and the steady state of the mean field equation are discussed. Numerical simulations are used to demonstrate the properties uncovered by the analysis.

Analysis of societal event impacts on the power system frequency using FNET measurements

Nation-wide, or largely synchronous activities, such as the World Cup or Super Bowl, have impacts on the power grid frequency response. This paper examines the influence of these sporting events on power system dynamics using data collected from the Frequency Monitoring Network (FNET). The frequency data of the German power grid during the 2010 World Cup semifinal game and the U.S. power system during three consecutive Super Bowls are investigated as examples of societal event impacts on power frequency. The frequency observations and analyses demonstrate such significant effects on the power system. Additionally, featured characteristics are drawn from the frequency data and several special events during the Super Bowl are examined.

Metanorm expectations: Determining what to sanction

Instrumental approaches to norms treat their enforcement as problematic and suggest that self-interested actors are unlikely to sanction. We suggest an alternative conceptualization of the norm enforcement problem. Research shows that social rewards can offset sanctioning costs, thereby encouraging enforcement. The issue then becomes how individuals determine what to sanction. We suggest that the typicality of behavior may provide a clue. We identify conditions under which atypical behavior may be punished. Consistent with existing instrumental approaches, we find that atypical behavior is sanctioned if it detracts from group welfare. We also find evidence pointing to the importance of a non-instrumental factor – perceptions of a behaviors social desirability.