Dr. Taylor is currently collaborating with Dr. Liuchen Chang (UNB ECE
Department) in a project sponsored by the Atlantic Innovation
Fund to develop and commercialize a distributed power
generation system based on renewable energy resources. A
distributed power generation system may contain a combination of small
wind turbines, small hydro turbines, photovoltaic arrays, gas
microturbines and fuel cells that are connected to the power system
grid and are located in close proximity to electricity consumers.
Distributed power generation systems (DPG systems) offer secure and
diversified fuel options with low or zero greenhouse gas
emissions.
This project is vitally important because there are tremendous market
opportunities for distributed power generation systems, the result of
(i) deregulation of the power industry and (ii) mandates to reduce
greenhouse gases, such as the Kyoto Accord. The market opportunities are
long term and world wide. The project will help to create an expertise
in sustainable power research and development here in Atlantic
Canada.
His team will focus on the Energy Control Centre for a DPG
system. Specifically, the objective is to develop the energy
management and control strategy and system, customized to be highly
effective for distributed power generation networks (DPGNs). As such,
it will act to create a dispatchable DPGN system that can be controlled
as a single "virtual generator" by the utilities' Energy Control Centre
(ECC) for real power and reactive power dispatch based on the
utilities' requirements. The system will schedule, in an optimal
fashion, the DPGN generation sources for operation with high
reliability and economy. To do this, it will use 24-hour weather
forecast data from Environment Canada along with forecast error statistics
to perform a Monte Carlo study predicting the 24-hour-ahead means and error bands for
power available from wind and photovoltaic generators
truly optimal. In the end, the energy control centre subsystem will
consist of a software product that implements the energy management
policies defined for the DPGN, based on advanced intelligent control
methodologies.
A schematic for the Energy Control Centre's Forecasting Module is shown in Figure 1.
