Dai Murayama

Power output smoothing for hybrid wind-solar thermal plant using chance-constrained model predictive control

Fluctuating wind power must be smoothed before supplied to a power grid in order to prevent potential damages of sensitive electrical devices connected to the grid. This paper considers a hybrid wind-solar thermal plant, where the output from the wind turbine is smoothed by bypassing through the thermal plant. We propose a chance-constrained MPC-based control method that optimally decides the ratio of the wind output that is bypassed through the thermal plant so that the rapid fluctuation of output is suppressed while the direct power output is maximized. The controllers parameters are designed in a way that result in a Pareto-optimal performance. We demonstrate the performance of the proposed method through simulations using real data.

Smart grid ready BEMS adopting model-based HVAC control for energy saving

The newly developed building energy management system (BEMS) is presented. The main feature of the BEMS is the following 2 technologies. (1) The new air-conditioning control technology for the energy saving of buildings. The method is mainly focused on the compatibility of energy savings and comfort. The energy saving is achieved through the twin coil air handling unit that controls room humidity and temperature independently without energy loss and by the optimal operation of HVAC (Heating, Ventilating and air-conditioning) system, manipulating the supplying airflow temperature to the rooms, room temperature and the humidity. The comfort is kept by the index (PMV: Predicted Mean Vote) that is calculated with room temperature, humidity, radiation temperature, wind velocity and so on. In order to avoid large-scale nonlinear programming for optimal conditions, the driving function is introduced. The effectiveness of the HVAC control technology is proved through a building HVAC data and the simulations using the data. (2) Automated demand responding mechanism. The mechanism has function that predicts how much electricity demand is trimmed for a given reward. It also has ability to communicate with community energy management server for finding appropriate balances between electricity demand and generations.

A new control strategy for coal fired thermal power plants

This paper presents a coordinated controller parameter adjusting method for boilers. The method includes constructing a simplified engineering boiler model and adjusting controller parameters with nonlinear constrained optimization. Because many control loops in the generation plants interfere with each other, the improvement in the control ability by the method is remarkable. Simulation results are shown in the paper

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

Proceedings of the IEEE Conference on Decision and Control

Fluctuating wind power must be smoothed before supplied to a power grid in order to prevent potential damages of sensitive electrical devices connected to the grid. This paper considers a hybrid wind-solar thermal plant, where the output from the wind turbine is smoothed by bypassing through the thermal plant. We propose a chance-constrained MPC-based control method that optimally decides the ratio of the wind output that is bypassed through the thermal plant so that the rapid fluctuation of output is suppressed while the direct power output is maximized. The controllers parameters are designed in a way that result in a Pareto-optimal performance. We demonstrate the performance of the proposed method through simulations using real data.

An Intelligent Control System for Distributed Mini Grids

A new power system that consists of loosely coupled mini grids is providing a number of challenging problems for many power system experts. In the new development, the power system is said to change from nowadays closely coupled and fully coordinated system that mainly consists of the large power stations, to the mixture of the large power stations and loosely coupled mini grids. The paper focused on the features of the mini grid control system, in particular, its robust generator controller and optimal management schemes.

The power system of the loosely coupled distributed mini grids

A new power system that consists of loosely coupled mini grids is introduced. In the future, the power system is said to change from nowadays closely coupled full coordinated system that mainly consists of the large power stations, to the mixture of the large power stations and loosely coupled mini grids. The paper mainly mentions about the features of the mini grid control system.