We are part of a collaborative UK project known as OPTEMIN which is taking a whole systems approach to the optimisation of energy management in industry, with a view to meeting long-term targets for reducing greenhouse gas emissions and global warming.
  • DatesDecember 2016 start (three years).
  • SponsorEngineering and Physical Sciences Research Council (EPSRC)
  • Funded£450,000 Cranfield’s income (£1.6 million total project).
  • PartnersBrunel University (lead) and Queen’s University Belfast.

The UK Government, the European Union and the international community in general have ambitious targets for reduction of greenhouse gas (GHG) emissions and global warming. Even though the UK is likely to meet its 2020 emission reduction targets, longer-term targets to 2050 and 2100 are unlikely to be met without substantial changes to policy and technological approaches in the generation, distribution and utilisation of energy.

We are part of a collaborative project known as OPTEMIN which is aiming to address these challenges by working closely with some key industrial collaborators. Its objective is to demonstrate, through the research programme and case studies supported by comprehensive data sets, the potential to achieve energy demand and carbon emission reductions of more than 15%.

We aim to understand the major technical, operational and economic issues associated with the acquisition and analysis of large energy data; use this data to gain insights into the complex energy networks, their interactions and impacts in large industrial manufacturing facilities; evaluate the performance of new innovative energy demand reduction and energy conversion technologies using data from demonstration installations; investigate drivers and business models that can facilitate their full development and commercialisation; as well as develop methodologies and tools to optimise individual process design, whole site energy integration and management and evaluate their decarbonisation potential within the context of Government policies and decarbonisation roadmaps to 2050.

Associated Publications

Model-based multi-objective optimisation of reheating furnace operations using genetic algorithm

Nonlinear dynamic simulation and control of large-scale reheating furnace operations using a zone method based model

System dynamics of oxyfuel power plants with liquid oxygen energy storage

Fuzzy Nonlinear Dynamic Evaporator Model in Supercritical Organic Rankine Cycle Waste Heat Recovery SystemsLink