Details of a Researcher - Namerikawa, Toru

Papers - Namerikawa, Toru

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Optimal Power Demand Management among Consumers with Aggregator considering State and Control Constraints

Yoshihiro Okawa, Toru Namerikawa

2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC) (IEEE) 801 - 806 2016.12

Research paper (international conference proceedings), Accepted, ISSN 0743-1546

This paper presents a novel optimal power demand management method for power consumers with an aggregator considering state and control constraints. The aggregator is an organization who manages some consumers to achieve demand response efficiently. This paper proposes a power demand adjustment method for the aggregator to allocate power reduction among consumers in a distributed manner. Specifically, this method simultaneously derives the optimal power reduction of each consumer using a gradient method and determines the control inputs by solving a quadratic programming problem with state and input constraint conditions. This paper also shows the convergence of the proposed algorithm, and finally, numerical simulation results illustrate the effectiveness of the proposed method.

Multi-Period Regional Energy Management Based on Dynamic Pricing with Non-Deficit Real-Time Market Trading

Yoshihiro OKAWA,NAMERIKAWA Toru

SICE Journal of Control, Measurement, and System Integration (The Society of Instrument and Control Engineers) 9 ( 5 ) 207 - 215 2016.09

Research paper (scientific journal), Joint Work, Accepted

This paper deals with a regional demand response method based on dynamic electricity pricing in a multi-period energy market. In the proposed method, first, the power supply and demand in each area are determined considering power flow using the retail and wholesale electricity prices in a day-ahead market. Next, in a real-time market, the proposed method adjusts to power deviations caused by errors in power generation with power demand reduction by consumers and increased power supply from balancing generators. In addition, in order to guarantee the non-deficiency in the real-time market trading, the incentive and penalty price design methods are discussed in this paper. This paper also shows a distributed algorithm for obtaining the optimal values of each market player in both the day-ahead and real-time markets, and finally, numerical simulation results demonstrate the effectiveness of the proposed method.

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Dynamic Pricing Using H∞ Control with Uncertain Behavior in Electricity Market Trading

Yoshihiro OKAWA, NAMERIKAWA Toru

SICE Journal of Control, Measurement, and System Integration (The Society of Instrument and Control Engineers) 9 ( 5 ) 192 - 200 2016.09

Research paper (scientific journal), Joint Work, Accepted

This paper deals with a dynamic pricing using the H∞ control with uncertain behavior in electricity market trading. The dynamic pricing is a decision procedure of an electricity price based on power supply and demand balance in power grids. However, in a future deregulated electricity market, both power consumers and generators determine their own power demand and supply selfishly according to the price information. Moreover, uncertainties are also included in their behavior. For this problem, we propose a novel price decision method using the locational price-updating H∞ controllers. This paper shows a design process of this price-updating H∞ controller to evaluate the following performance to reduce supply-demand imbalances in power grids and the robustness against uncertainties in electricity market participants' behavior, respectively. In addition, this paper also shows the effectiveness of our proposed price decision method using the designed H∞ controller through numerical simulation results.

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A Comparative Study of Extended Kalman Filter and H-infinity Filtering For State Estimation of Stewart Platform Manipulator

Shady A. Maged, A. A. Abouelsoud, Ahmed M. R. Fath El Bab, Toru Namerikawa

2016 55TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE) (IEEE) 1727 - 1732 2016.09

Research paper (international conference proceedings), Accepted

This paper presents the estimation of both position and velocity of Stewart Manipulator by means of limbs potentiometer measurements and MEMS inertial sensors. The estimation used the Extended Kalman Filter (EKF) and H-infinity optimal filtering technique based on the combination of these sensors. The two types of filters are used as nonlinear state estimators to the Stewart platform which is modeled as a stochastic differential equations due to measurement noise in case of EKF and as a continuous time system model in case of H-infinity filtering technique. The results of the both filters are compared with each other on the Stewart platform DELTALAB EX800 using MATLAB SimMechanics toolbox. The simulation results show that Kalman filters are not the best choice for parallel manipulator state estimation as they bear from the hypothesis of statistical noise with zero mean as well as known noise covariance, which may reduce its performance. For these reasons, H-infinity filter may be the alternative of Kalman filter.

Robust-Formation Control of Multi-Autonomous Underwater Vehicles based on Consensus Algorithm

Vina Putranti, Zool H. Ismail, Toru Namerikawa

2016 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA) (IEEE) 2016.09

Research paper (international conference proceedings), Accepted, ISSN 1085-1992

This paper discusses a robust formation control for multi-Autonomous Underwater Vehicles (AUVs). The AUVs are disturbed by exogenous perturbation during the mission, thus, the Robust Integral Sign of Error (RISE) is adopted. For a formation control, a leader-follower structure based on consensus algorithm is adopted and the use of graph theorem named connected graph is useful to exchange the required information. An AUV called leader is determined to bring a group of information, while the others called followers, receive the information from a leader. Lyapunov analysis proves the stability as well as the error convergence of proposed controller, whilst some simulations are performed to compare between the proposed controller, RISE with consensus, and the existing robust controller, Sliding Mode Controller (SMC) which is combined with consensus algorithm. As a result, the proposed controller works better and produces smaller error.

On the Fault Tolerant Control of a Quadrotor Manipulation System via MPC and DOb Approaches

Ahmed Khalifa, Mohamed Fanni, Toru Namerikawa

2016 55TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE) (IEEE) 700 - 705 2016.09

Research paper (international conference proceedings), Accepted

Recently, the Aerial Manipulation System becomes very attractive for a wide range of applications due to its unique features. However, control of such system is quite challenging. One of the critical challenge is that this system is very susceptible to actuators' faults. In this paper, a Passive Fault Tolerant Control System is proposed to address this issue with robust and optimal performance. The robustness is achieved using a linear Disturbance Observer (DOb) loop. Based on the linearization capability of DOb, a standard Model Predictive Control (MPC) is then used and the resulting control scheme is characterized by both a low computational load and optimal actuators' efforts with respect to conventional nonlinear robust solutions. This controller is tested to achieve the tracking of a point-to-point task space references under the effect of actuators' faults, picking/releasing a payload, changing the operating region, and measurement noise. Efficacy of the proposed technique is verified via numerical simulations.

Formation control considering disconnection of network links for a Multi-UAV system

Mori Shouhei, Namerikawa Toru

Journal of Robotics and Mechatronics (Fuji Technology Press) 28 ( 3 ) 343 - 350 2016.06

Research paper (scientific journal), Joint Work, Accepted, ISSN 0915-3942

The formation control algorithm we propose for a multi-UAV uses LMI conditions. Starting with a linearized model of UAVs such as a quadrotor, we introduce a formation control algorithm based on a consensus algorithm, a leader-follower structure, graph theory and the Lyapunov stability theorem for a liner system. We propose the control algorithm using the Lyapunov theorem and LMI conditions for intermittent communication. We demonstrate the proposed control algorithm’s stability even when network links are disconnected. Numerical simulation and experimental validation show the proposed control’s effectiveness.

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Distributed Power Supply-demand Management Based on Negawatt Trading with Energy Storage System

Yoshihiro Okawa, Toru Namerikawa

2016 EUROPEAN CONTROL CONFERENCE (ECC) (IEEE) 1812 - 1817 2016.06

Research paper (international conference proceedings), Accepted

This paper presents a distributed power supply demand management method based on negawatt trading including charge or discharge power from energy storage systems. In the negawatt trading, power consumers reduce their own power demand and receive monetary reward from the market operator. In order to derive appropriate electricity incentive prices for consumers and to use energy storage systems in power grids efficiently, we deal with a power adjustment problem using some future power supply information in this paper. We then show a novel market algorithm to solve this problem in a distributed manner through market trading among the market operator and consumers. Finally, we verify the effectiveness of our proposed method with numerical simulation results.

Fuel Consumption Optimization for a Power-Split HEV via Gain-Scheduled Model Predictive Control

Hitoshi Iyama, Takatoshi Suda, Masaaki Nishito, Hiroki Seto, Masakazu Mukai and Toru NAMERIKAWA

Transactions of the Society of Instrument and Control Engineers (IEEE) 52 ( 1 ) 1 - 10 2016.01

Research paper (scientific journal), Joint Work, Accepted, ISSN 0453-4654

In this paper, we propose a fuel consumption optimization technique for a power-split HEV via gain-scheduled model predictive control. The control algorithms for the powertrain choose the power split between engine and electric motor in order to minimize the fuel consumption. Operating conditions of the HEV change during driving in real time by road conditions and driver demand. Therefore, it is necessary to have optimal control in real time and to consider the time-varying motor condition. We model the HEV and propose a gain-scheduled model predictive control. Using the proposed technique, we succeeded in optimizing fuel consumption for a power-split HEV. Finally, the proposed approach was validated by numerical simulations.

Optimal energy management for smart grid system considering battery characteristics

Mukai Tatsuya, Igari Shunsuke, Namerikawa Toru

Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi) (WILEY-BLACKWELL) 194 ( 1 ) 18 - 26 2016.01

Research paper (scientific journal), Joint Work, ISSN 0424-7760

This paper discusses optimal energy management considering battery characteristics for smart grid and microgrid systems. Energy storage systems are very important for energy peak shifting and peak load cutting in microgrid and smart grid systems, but optimal battery formulation and energy management in the use of expensive energy storage system and methods of taking account of battery characteristics are still in the developmental stage. First, the optimal battery placement for a smart grid system with lithium-ion batteries is considered as a means of lifetime extension. The battery choice index for this optimal battery utilization problem of optimal energy management is discussed. Second, a smart grid system with a distributed battery system for grid frequency control with consideration of distributed control and battery characteristics is discussed. Optimal controllers for distributed battery systems to reduce the battery load and to expend the battery lifetime are designed. Simulations are used to demonstrate the effectiveness of the proposed method in comparison with conventional methods.

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Detection of Replay Attack on Smart Grid with Output Including Code Signal

Takashi Irita and Toru Namerikawa

T. SICE 51 ( 12 ) 822 - 828 2015.12

Research paper (scientific journal), Joint Work, Accepted, ISSN 0453-4654

Ensuring cyber security of smart grid based on supervisory control and data acquisition using information and communications technology has been becoming a major challenge. Especially, a replay attack is a dangerous cyber attack affecting integrity and authorization. The goal of this paper is to detect replay attack that is one of cyber attacks on the sensors of a control system. We propose a detecting method adding intentional noise to sensors as code signal playing a time-stamping part. Replay attack can immediately be reflected by using fault diagnosis matrices that are composed of the estimator and observed values. Finally, we show simulation results to analyze effectiveness of the proposed method.

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Regional Demand-Supply Management based on Dynamic Pricing in Multi-period Energy Market

Yoshihiro Okawa, Toru Namerikawa

2015 54TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) (IEEE) 7201 - 7206 2015.12

Research paper (international conference proceedings), Joint Work, Accepted

This paper deals with a regional demand response method based on dynamic electricity pricing in a multi-period energy market. In the proposed method, first, the power demand and supply in each area are determined considering power flow using the retail and wholesale electricity prices in a day-ahead market. Next, to adjust for power deviations caused by errors in power generation, our proposed method solves the problem of optimal allocation between power demand reduction by consumers and increased power supply from balancing generators in a real-time market. This paper also shows a distributed algorithm for obtaining the optimal values of each market player in both the day-ahead and real-time markets, and finally, numerical simulation results demonstrate the effectiveness of the proposed method.

Load Frequency Control of a Microgrid Based on H∞ Control Considering Response Speed of Generators

Kenji Masui, Shun Takamura and Toru Namerikawa

T. SICE 51 ( 8 ) 570 - 578 2015.08

Research paper (scientific journal), Joint Work, Accepted, ISSN 0453-4654

In this paper, load frequency control problem of a microgrid is discussed. The control is conducted to retain power demand supply balance by controling output of generators in power system. However, it becomes harder to retain the balance because of large-volume injection of renewable energy. For the problem, two approaches are considered in this research field. One is to use dispersion type power sources like batteries, and the other is to apply new control theories. Therefore, we focus on a microgrid which holds a wind turbine generator, a diesel generator and a battery, and propose a technique based a static H_∞ control. In the beginning, we design the generalized plant considering the difference of the response speed of a diesel generator and a battery. Then, static H_∞ control is applied to the generalized plant. Moreover, an LMI condition to avoid control gains to cause too big control input are combined with static H_∞ control. In numerical simulation, we validate that the controller can suppress frequency deviation and deviation of residual capacity of the battery. Futhermore, we show that the approach can design controllers with lower dimensions, and avoid undesirable control gains. In experiment with a generator and a variable resistance, the effectiveness of the controller is also confirmed.

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Real-Time Pricing Mechanism for Electricity Market With Built-In Incentive for Participation

Namerikawa Toru, Okubo Norio, Sato Ryutaro, Okawa Yoshihiro, Ono Masahiro

IEEE Transactions on Smart Grid (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC) 6 ( 6 ) 2714 - 2724 2015.07

Research paper (scientific journal), Joint Work, Accepted, ISSN 1949-3053

This paper proposes a game-theoretic approach to design a distributed real-time electricity pricing mechanism. Our approach is novel in that it guarantees individual rationality, meaning that it provides suppliers and consumers with a guaranteed incentive to participate in the real-time pricing market. Such an incentive is devised by offering a time-varying, situation-dependent subsidy that guarantees that a supplier/consumer profits by switching from a fixed-price contract to the real-time pricing contract. Although we assume that suppliers and consumers decide supply and demand quantities in a fully distributed manner to maximize their own profit, the proposed mechanism guarantees under moderate conditions that the market converges through an iterative process to a Nash equilibrium that maximizes social welfare. Furthermore, in order to guarantee safe operation of an electrical grid, our pricing mechanism increases stability of load frequency control, and at the same time, achieves supply-demand equilibrium by explicitly taking into account an equality constraint through dual decomposition method. We empirically demonstrate by simulations the individual rationality of the proposed mechanism as well as the convergence to supply-demand equilibrium.

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Formation Control with Collision Avoidance for a Multi-UAV System Using Decentralized MPC and Consensus-Based Control

Yasuhiro KURIKI and Toru NAMERIKAWA

SICE Journal of Control, Measurement, and System Integration, (IEEE) 8 ( 4 ) 285 - 294 2015.07

Research paper (scientific journal), Joint Work, Accepted, ISSN 1882-4889

In this paper, the authors propose a cooperative formation control strategy with collision-avoidance capability
for a multi-unmanned aerial vehicle (UAV) system using decentralized model predictive control (MPC) and consensus-
based control. Consensus-based control algorithms are applied for formation flying in three-dimensional space. However,
UAVs where these formation control algorithms are applied have not the ability to avoid collisions. Decentralized model
predictive control (MPC) is applied to generate control inputs for formation flying with collision-avoidance capability.
Using decentralized MPC, each UAV plans only its own action to track the trajectory specified by the formation control
algorithm within the feasible regions satisfying collision-avoidance. The authors show how the optimization problems
with coupled constraints such as collision-avoidance can be solved by each decoupled UAV in parallel with the other
UAVs so that the decisions independently taken by each UAV can ensure consistency in coupled constraints of collision-
avoidance. The computation time is also taken into account because it is a crucial factor to apply MPC to actual UAVs.
Finally, the proposed approach is validated by some simulations.

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Decentralized Fault Detection of Multiple Cyber Attacks in Power Network via Kalman Filter

Takashi Irita, Toru Namerikawa

2015 EUROPEAN CONTROL CONFERENCE (ECC) (IEEE) 3180 - 3185 2015.07

Research paper (international conference proceedings), Last author, Accepted

This paper discusses faults diagnosis method of multiple cyber attacks in networked electrical power systems. We deal with a power network of a centralized system, and then, some parameters are estimated by Kalman filter. Using a sensor network system, each of sensor nodes can exchange information by wireless communication. A fault diagnosis method is proposed by using both fault detection diagnosis matrix and fault distinction matrix. The former is composed of estimated values and observed values. On the other hand, the latter is composed of observed values and calculated values via the senor network. Finally, the effectiveness of the proposed approach is validated by a simulation experiment.

Power System Stabilization by Direct Load Control Based on Strategy-Proofness and Individual Rationality

Ryutaro Sato, Toru Namerikawa

2015 AMERICAN CONTROL CONFERENCE (ACC) (IEEE) 5913 - 5918 2015.07

Research paper (international conference proceedings), Joint Work, Last author, Accepted, ISSN 0743-1619

This paper proposes a novel direct load control method to stabilize the system frequency. The proposed method utilizes the consumers' controllable loads for load frequency control. By solving an optimization problem to maximize the social welfare function, the input required for the frequency control is allocated among the controllable loads and the load frequency control generator in an economically rational manner. To introduce the direct control program for smooth operation of the power system, preventing consumers from cheating and guaranteeing their benefits are required. Thus, strategy-proofness and individual rationality based on the Groves and Clarke mechanism were used to design the electricity charge. Each consumer bids on the utility functions truthfully to the independent system operator and gains from participating in the proposed direct load control program. The effectiveness of the proposed method was demonstrated through numerical simulations.

Dynamic Electricity Pricing via the H-infinity Control Considering Uncertainties in Market Participants' Behavior

Yoshihiro Okawa, Toru Namerikawa

2015 EUROPEAN CONTROL CONFERENCE (ECC) (IEEE) 1064 - 1069 2015.07

Research paper (international conference proceedings), Last author, Accepted

This paper deals with a dynamic pricing via the H-infinity control considering uncertainties in market participants' behavior. The dynamic pricing is a decision procedure of an electricity price based on power demand and supply information from selfish power consumers and generators. However, since market participants have uncertainties in their behavior, the price decision procedure is required to have robustness against these uncertainties for stable operation of power systems. Then, in this paper, we propose a novel price decision procedure via the H-infinity control and also show the effectiveness of our proposed price decision method in simulation results.

Distributed Dynamic Pricing with Alternating Decision Making of Market Players

Yoshihiro Okawa, Toru Namerikawa

2015 54TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE) (IEEE) 888 - 893 2015.07

Research paper (international conference proceedings), Last author, Accepted

This paper deals with a distributed decision procedure for determining the electricity price for a future smart grid. In order to derive the optimal regional prices and improve the convergence speed of the algorithm without private information of market players, we propose a price decision algorithm with an alternating decision making of market players. In this paper, we show that the optimal regional prices derived by using our proposed algorithm maximize the social welfare of power networks which includes profits of power consumers and power suppliers with renewable energy generators. Also, we discuss the convergence property of the proposed price decision algorithm. Finally, the feasibility of our proposed dynamic pricing methodology is shown with numerical simulation results.

Distributed dynamic pricing based on demand-supply balance and voltage phase difference in power grid

Okawa Yoshihiro, Namerikawa Toru

Control Theory and Technology (South China University of Technology) 13 ( 2 ) 90 - 100 2015.05

Research paper (scientific journal), Accepted, ISSN 2095-6983

This paper discusses a distributed decision procedure for determining the electricity price for a real-time electricity marketin an energy management system. The price decision algorithm proposed in this paper derives the optimal electricity pricewhile considering the constraints of a linearized AC power grid model. The algorithm is based on the power demand-supplybalance and voltage phase differences in a power grid. In order to determine the optimal price that maximizes the social welfare distributively and to improve the convergence speed of the algorithm, the proposed algorithm updates the price through the alternating decision making of market participants. In this paper, we show the convergence of the price derived from our proposed algorithm. Furthermore, numerical simulation results show that the proposed dynamic pricing methodology is effective and that there is an improvement in the convergence speed, as compared with the conventional method.

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