KBC, a Yokogawa Company, announced the release of a new high-fidelity analytics technology, VM-MPO 6 at the ARC Industry Forum held in Orlando, Florida. It will allow scheduling engineers and operators to incorporate more precise forecasts into the decision-making process, over various time horizons when dealing with multiple time-dependent constraints, resulting in increased optimization benefits of their energy systems.
Changes in electricity price contracts (e.g. real-time pricing, time of use pricing, critical peak pricing), variability of natural gas prices, and the capability of process plants to become electricity providers to the grid while managing a wide variety of energy sources (fossil fuels, renewables, etc.), impose unprecedented challenges to scheduling engineers that aim to deliver the most economic dispatch of energy to meet demand.
With this release, KBC’s first-to-market integrated optimal scheduling and real-time optimization offering for energy systems now has seamless integration with analytics platforms and external data analytics services to better predict unmodelled variables. The improved forecasts generated by these new capabilities result in users now being able to trigger more aggressive optimal actions, realizing additional benefits available in the system.
VM-MPO 6 brings together data analytics, first principles and multi-period constraints in a purpose-built mixed integer optimization to continually ensure that the right decisions are made about which generation assets to start up, shut down and where to deploy energy at lowest economic cost. Case studies have demonstrated this new release’s ability to improve optimization benefits by 5 per cent.
VM-MPO 6 constitutes a major upgrade of already proven technology that enhances the real-time optimization technology, Visual MESA Energy Real-Time Optimizer (VM-ERTO), by adding an upper decision layer where the time-sensitive variables are optimally defined. VM-MPO benefits from enhanced connectivity between data sources, forecasting methods, model structure and multi-period constraint capabilities for solving at speed. This technology further extends Yokogawa’s end-to-end portfolio of energy optimization solutions.