The LIVA Hybrid Energy Storage System (Hybrid ESS) for industrial applications helps companies to improve their energy and power management and thus reduce energy costs and CO2 emissions. Hybrid ESS have a storage capacity of 3.45 MWh up to more than 100 MWh.
Our LIVA Hybrid ESS in fully automated operation at AMG Graphite in Hauzenberg, Germany.
We design and build customized LIVA Hybrid ESSs that efficiently combine four core components:
The LIVA software ecosystem simulates and operates various energy storage assets like lithium-ion and Vanadium Redox Flow batteries as well as Gas-To-Power facilities with artificial intelligence routines and self-learning algorithms. Besides maximizing the efficiency, safety and lifetime of the batteries, the software enables the economic integration of sector coupling strategies with renewable energies and green hydrogen.
p7.analytic analyses a demand power curve and finds an optimal solution to the given problem or setup. Our solution to this problem can then be used for the design and layout of a IPS or even for steering and operation.
The simulation of a smoothed curve is also the baseline for p7.control, which shares the optimisation algorithm.
p7.control is using the optimised curve of p7.analytic to steer the IPS for a more efficient power consumption.
As an operating system (OS) it controls the charging and discharging of the primary Li-Ion battery, secondary batteries as well as the control of generators, fuel cells, power-to-gas or power-to-heat plants.
Data of p7.control is fed back for further forecasting and optimisation by the use of self-learning adjustments.
p7.grid is combining p7.control entities for a microgrid of exchanged power supply and production.
The automated trading systems shifts energy capacities matching every users interest, while maintaining grid stability.
p7.analytic takes into account all relevant technical and electrochemical properties of a storage technology. These include e.g. the rapid charging and discharging ability (C-rate), life-time (cycle stability and calendar life-time) and energy charging efficiency of a specific battery technology. All of these factors are in complex dependencies to other factors (depth of discharge/DoD, state of charge/SoC, state of health/SoH, temperature range) and also linked to each other.
Depending on the individual power curve and further specific assumptions from the customer p7.analytic finds a real custom tailors system design with the best fit technologies. With an economic framework the software calculates and maximises the reliability and the economic benefit of the power management system.