2017 SICE Annual Conference Awardの贈呈
Mr. Keita MUTO
He received the B.E. degree in system design engineering from Keio University, Tokyo, Japan, in 2017. He is currently pursuing the M.E. degree at Keio University. His research interests include control systems, and real-time pricing in power network systems.
受賞論文「Optimal Pricing of Electricity by Aggregator for Demand Adjustment of Each Consumer Having Appliances」
This paper deals with demand adjustment problem of each consumer having appliances by an aggregator based on the optimal pricing problem in a day-ahead electricity market. In this paper, we design market model where the generators, the aggregator and the consumers exist. Especially, with regard to the consumer model, the utility of consumers obtained by electricity consumption is distinguished by appliances. Therefore, in this paper, we can consider the constraints on the consumption amount and the use time of each appliance, and derive optimal consumption of each appliance. And in this market model, we derived the problem of determining the supply and demand amount in consideration of acting so that market participants act to maximize their respective welfare. The dual decomposition is applied to this market problem to maximize the social welfare and the proposed algorithm decides electricity price based on the exchange of information among market participants to solve each distributed problem for improving convergence. In addition, the convergence of this proposed method is proven using Lyapunov stability theorem. Finally, by simulation, we confirmed that this proposed method can achieve optimal adjustment of demand for appliances and improvement of the price convergence speed.
Mr. Hyeonjun YUN
Hyeonjun Yun is a Ph.D. student in the Department of Electrical and Computer Engineering at Seoul National University, Korea. He received his B.S. degree in electrical engineering at Seoul National University in 2010. His research interest lies in control theory and control engineering, including nonlinear observers, model predictive control, disturbance observer technique, multi-agent systems, and distributed optimization.
受賞論文「Consensus-Based Distributed Coordination for Optimal Energy Generation of Hierarchical Systems」
This paper considers the optimal energy generation problem for hierarchical system, which consists of multi-cluster power system. In particular, consensus-based distributed hierarchical coordination algorithm is proposed to meet the power generation/demand balance. By using Lagrangian-based approach, we show that the optimization problem for the hierarchical system can be separated into each layer's consensus problem with communication between each layer's leader agent. The convergence is proved in the sense of global practical stability by the singular perturbation theory. Simulation result shows that the solution obtained by the proposed algorithm converges to the optimal solution.
○Young Author's Award
Mr. Kengo URATA (Student Member)
Kengo Urata was born in Miyagi, Japan, in 1992. He recieved the B.E. and M.E. degrees in applied physics and physico-informatics from Keio University, Kanagawa, Japan in 2015 and 2017, respectively. Since April 2017, he is currently working toward the Ph.D. degree in systems and control engineering from Tokyo institute of Technology and serving as a Research Fellow of the Japan Society for the Promotion of Science. His research interestes include the stability theory of dynamical systems and its application.
受賞論文「Performance Analysis in Iterative Feedback Connection of Passive Systems」
This paper addresses performance analysis and improvement of passive systems. We define a special passivity property that is characterized by two parameters. The paramters are also utilized for evaluting the L2-gain performance of passive systems. With the parameter-integrated passivity, the feedback system composed of passive systems preserves the passivity property as well as the passivity theorem. In addition, the quantitative analysis of the feedback system is provided as the parameter transition. It is further shown that the performance of the feedback system is strictly improved as compared to that of the disconnected systems. Subsequently, the performance analysis of the feedback system is extended to that of an iterative feedback system, which expresses a control system construcuted by the feedback connection of multiple controllers in a step by step manner. We show the gradual performance improvement with the controller connection. The analysis contributes a decentralized design problem of local controllers for large-scale systems, e.g., power systems with renewable energy resources.
○Poster Presentation Award
Dr. Xinmin ZHANG
He received the B.S. degree from Qingdao Agricultural University, Qingdao, China, in 2012 and the M.S. degree from Shenyang University of Chemical Technology, Shenyang, China, in 2015. He was an exchange student with the Department of Control Science and Engineering, Zhejiang University, China, from 2013 to 2014. He is currently pursuing the Ph.D. degree in System Science at Kyoto University, Kyoto, Japan. His research interests include fault detection and diagnosis, process data analysis, process control, and virtual sensing technology with application to industrial processes.
受賞ポスター「Soft-Sensor Reliability Evaluation and Y-Analyzer Fault Identification with Applications to Vinyl Acetate Monomer (VAM) Benchmark Process」
A great deal of research has been done to develop data-driven soft-sensors for quality estimation and control. However, a soft-sensor does not always function well. If estimates of the soft-sensor are blindly believed and used in a control system, the product quality and process performance will be deteriorated. To solve this issue, an on-line reliability evaluation method of soft-sensors using the k-nearest-neighbor rule (RE-kNN) was developed in this study. RE-kNN makes full use of the kNN rule to obtain local information, therefore it is suitable for nonlinear and multimodal cases. Since RE-kNN is a model-free approach, it can be applied to reliability evaluation of any inferential model. In addition, simple y-analyzer fault identification rules were also proposed by integrating RE-kNN with the 3-sigma method. The validity of the proposed methods was verified through numerical examples and a new, rigorous vinyl acetate monomer plant model. The application results demonstrate that the proposed methods are efficient to evaluate the reliability of soft-sensors and to detect y-analyzer faults.