The strategic role of design in supporting knowledge exchange

Within the last decade design has had a strategic role in tackling escalating environmental, social and economic problems. Through design thinking, creative methods have been applied to problem solving in a process of collaboration and designers working in new territories and knowledge domains. As the designer has moved further afield the method of Knowledge Exchange (KE) has become more recognised as a democratic approach to collaboration with the ethos that everyone has something creative and productive to offer. This paper provides reflections on early stage findings from a strategic design innovation process in which collaborative partnerships between academics, SMEs and designers emerged through KE and suggests that there is value to be had from using design strategically for not only those from a business or academic background but also for those from the design community and points to a need for more training for designers from all disciplines in how to use design strategically

A genetic algorithm based economic dispatch (GAED) with environmental constraint optimisation

The role of renewable energy in power systems is becoming more significant due to the increasing cost of fossil fuels and climate change concerns. However, the inclusion of Renewable Energy Generators (REG), such as wind power, has created additional problems for power system operators due to the variability and lower predictability of output of most REGs, with the Economic Dispatch (ED) problem being particularly difficult to resolve. In previous papers we had reported on the inclusion of wind power in the ED calculations. The simulation had been performed using a system model with wind power as an intermittent source, and the results of the simulation have been compared to that of the Direct Search Method (DSM) for similar cases. In this paper we report on our continuing investigations into using Genetic Algorithms (GA) for ED for an independent power system with a significant amount of wind energy in its generator portfolio. The results demonstrate, in line with previous reports in the literature, the effectiveness of GA when measured against a benchmark technique such as DSM.