Power Industry


ISC has a long track record in developing high-fidelity models of nuclear power generating plant for use in simulations used to investigate design and operating changes. Dynamic models have also proven invaluable in our investigation of control problems at CCGT and CHP generating plant.

ISC also run an annual Process Control Academy training event.

Our clients include British Energy, Scottish Power, Scottish and Southern Energy.

  • ISC Capability Statements - Power Generation Industry (PDF Download).
Example Projects
  • Advanced Control for Wind Turbines - ISC have investigated advanced predictive control for variable-speed variable-pitch wind turbines, using both simplified physics-based models, linearised models from Bladed and full aero-elastic Bladed models. The objective was to increase the power output and reduce the fatigue loads of the turbines simultaneously. The full range of below- and above-rated wind speeds was covered by predictive control, including the important transition zone between the torque control and pitch control modes around rated wind speed.
  • Improving CHP Steam Pressure - A detailed dynamic model of a CHP plant was built and used to investigate how steam pressure could be improved though modified control strategies. The study showed improved stability and a potential increase in power output. (Download project presentation)
  • Nuclear Power Plant Modelling - To investigate the possibility of trips in the steam condensate plant a high fidelity dynamic model was developed and used to identify where additional sensing would be beneficial.
  • EU funded Project AEOLUS - ISC is a key partner in the project to research and develop new optimisation strategies for large offshore wind farms. The objectives of which are to increase the through life economic performance of the wind farm, carefully balancing power extraction and mechanical fatigue.
  • Powerstation Trips - The cause of a gas supply trip at a gas-fired combined cycle powerstation was investigated using dynamic models which allowed different solutions to be explored prior to commissioning.
  • EU funded PAM Project - Provided the technical input to industrialise new controller performance assessment algorithms for use on real world applications, including power stations and chemical plant.