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KBC Introduces New High-Fidelity Analytics Technology for Optimal Operation of Energy

| Editor: Ahlam Rais

The improved forecasts generated by these new capabilities result in users now being able to trigger more aggressive optimal actions, realising additional benefits available in the system.
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The improved forecasts generated by these new capabilities result in users now being able to trigger more aggressive optimal actions, realising additional benefits available in the system. (Source: Deposit Photos)

The newly launched technology by KBC will reduce costly uncertainty in planning, scheduling and trading of energy over multiple time periods across portfolios of generation assets and different asset classes.

Texas/USA – KBC has recently announced the release of a new high-fidelity analytics technology, Visual Mesa Multi-Period Optimizer 6 (VM-MPO 6). 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 optimisation 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, the company’s first-to-market integrated optimal scheduling and real-time optimisation 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, realising additional benefits available in the system.

This technology brings together data analytics, first principles and multi-period constraints in a purpose-built mixed integer optimisation 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 optimisation benefits by 5 per cent.

The Technology constitutes a major upgrade of already proven technology that enhances the industry’s leading real-time optimisation technology, Visual Mesa Energy Real-Time Optimizer (VM-ERTO) by adding an upper decision layer where the time-sensitive variables are optimally defined. This technology 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 optimisation solutions.

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