In this paper, we focus on the voltage management problem in a distribution network in which a large amount of photovoltaic generations (PV) are penetrated. The proposed system employs a novel voltage control system utilizing controllable loads of consumers which are controlled based on an index to quantify a fairness between consumers. The main contributions of the paper are that (i) the index to quantify the fairness between consumers is firstly introduced, (ii) a novel voltage control system with low-cost communication infrastructure is proposed, and (iii) a mathematical model which efficiently optimizes a large amount of controllable loads by a commercial solver is proposed in the context of a implementation of the proposed method into a real world system. We verified the effectiveness of the proposed method by a computational experiment in which there are many consumers, low-cost communication network, and low-cost optimization manager.
The purpose of this paper is to propose the stochastic infectious model with time delay and to study the stability of the disease-free steady state. In the realistic spread of the infectious disease, environmental change and individual difference cause some kinds of random fluctuations in the model parameters. Moreover, in the vector-borne diseases such as malaria and dengue fever, there exists time delay caused by an incubation period in the virus development in the vectors (mosquitoes) on the transmission of disease. Taking these facts into consideration, we propose a stochastic SIR(susceptible-infected-recovered) model with time delay. We analyze stability of the disease-free steady state, and study the influence of time delay and the random noise on the stability by numerical simulations.
This paper proposes a novel transmission power-control method for power-saving in consensus problem. Focused consensus problem is an average-consensus where all agents try to assemble in the same position. Thus, in the process of consensus, the distance among agents becomes closer. Consequently, there is the gap between the maximum communication coverage and the distance to the farthest neighbor agent, which results in the waste of transmission power. This paper focuses on this fact and proposes the power-control method based on the position of neighbors. To keep the quality of control, we further propose the transmission power-control. The computer simulations showed that the proposed power saving can save the power consumption up to 1/5 but keep almost the same control quality as the system without power-saving.
For plants with sensor failures, this paper presents a new design method for a self-repairing control system (SRCS) with the FitzHugh-Nagumo (FHN) model. The FHN equation is well-known as the mathematical model which represents various electrical behaviors in membrane excitation. The proposed SRCS exploits this model as a fault detection filter. By monitoring a spike caused by an abnormal signal from the sensor, the faulty sensor can be detected and replaced with the healthy backup so as to maintain the stability of the control system. Furthermore, to confirm the effectiveness of the proposed SRCS, several numerical simulations are explored.
This paper presents performance analysis of fixed-gain moving object tracking filters for sensing systems based on fusion of range/acceleration sensors (e.g., radars and accelerometers). We propose a new position(range)-acceleration-measured tracking filter whose number of fixed gains is six, and derive its performance indices. The effectiveness of the proposed filter is verified based on the analytical performance comparison with conventional α-β-γfilters whose number of gains is three. In addition, numerical simulations assuming a realistic 2-dimensional sensing situation show the accurate tracking by use of the proposed filter and the validity of the analysis results.
Surplus power generated by large number of photovoltaics (PV) systems which are penetrating to general households is concerned as great impact to grid systems. This paper proposes a home energy management system (HEMS) which simultaneously controls charge/discharge of an in-vehicle battery of electric vehicle (EV) and operates heat pump water heating (HPWH). The proposed control is model predictive control manner in which the profiles of in-vehicle battery charge/discharge and HPWH operation are calculated iteratively in each step, minimizing the electricity bill with considering both the reverse surplus power as penalty and the vehicle usage as constraint. Especially,a piece-wise linear model of HPWH is introduced into the optimization problem in order to realize realistic computational time. As the result, both suppressing the surplus power reversing to the grid and decreasing electricity bill of the residents are realized. The effectivity of proposed system is verified by a simulation utilizing real data of a household.