What is ©E-OPT

The novelty of the ©E-OPT concept is related to the capability of dealing with huge amount of variables, characterized by non-linear correlations and with multi-objective optimization problem. Through an innovative algorithm based on:

  • Hybrid heuristic-deterministic solver
  • Integration of commercially available component database
  • Artificial Intelligence and Machine Learning
  • Adoption of Normalized cost functions based on existing components and wide database

The ©E-OPT allows for solving in a single step, with significant saving in time and computational resource, the Master Planning and Optimal Dispatch problems. The ©E-OPT indeed is able today, and will be perform better in the future, to solve:

  • Highly non-linear problems, characterized by a significant amount of variables
  • High Accuracy and Customization in comparison with existing software
  • Multi-Objective Optimization, based on Cost, Environmental constraints and technological limitations

Related to the two main categories of problems the end-users/customer will need to solve, according to the above bullet points, the ©E-OPT allows for solving:

  • Master planning, design of Greenfield projects and retrofitting of Brownfield projects characterized by highly integrated energy-mix (renewable energy, cogeneration technologies, storage, etc) for different end-user demands (e.g. Commercial, residential, office). The tool shall make available:
    • Selection of real existing components, available in the market (©E-OPT component Data Base)
    • Data Base is easy to update (automatic) and option for components to be filled by the end-user
    • Integration of the code of practice for the geographical location for complying with the regulations.
    • Multi-Objective function formulations based on searching the best for NPV, ROI, IR, CAPEX, OPEX, CO2
  • Optimal Dispatch problem solving for new projects as well as for existing plant layout:
    • Dispatching Profile optimized on the financial/objective required by the customer
    • Establishing the component part-load operations and optimal set-point values for safe and reliable operations strategy
    • Defining and suggesting the optimal maintenance scheduling.