Energy Management

GenScada is an advanced web scada application enabling a secure supervision and advanced control of your Genport’s Hybrid Power Source (G300/1000/5000HPS) and Battery Energy Storage System (GENIOL 6200) installed in different remote locations.

GenScada embeds a sophisticated diagnostics and predictive control algorithm, dispatching efficiently the energy among storage, generation units and the loads.

An HMI downloaded into your smartphone enables to achieve a great and easy visibility of all the key process variables and performance.

We offer an advanced and highly precise real time estimator of state of charge (SOC) and state of health (SOH) for lithium ion batteries.
The algorithms are based on an accurate electro-chemical model of the lithium ion cell.
It can be integrated in the micro-controller of existing BMS or as a higher level separate micro-controller that communicates with the BMS via CAN. 

GenSOH is an advanced and highly precise real time estimator of state of charge (SOC) and state of health (SOH) for lithium ion batteries. The algorithms are based on an accurate electro-chemical model of the lithium ion cell. It can be integrated in the micro-controller of existing BMS or as a higher level separate micro-controller that communicates with the BMS via CAN. 

GENMPC is a model predictive  closed-loop control strategy.  The problem solved by GENMPC in real time is to minimize a target (i.e., RUL) or a combination of different internal battery states  (i.e., RUL with SOP). In the latter case the GENMPC finds the best trade-off among the different objectives. The objective function consists of a set of electro-chemical models of the lithium-ion cell ageing subjected to a set of  physical and operational constraints.  GENMPC searches the best-fit charge/discharge profile to optimize the battery operations, e.g., maximizing the battery life extension.  

GenOPT is a novel computer-based tool suitable for optimizing the design and operation of multiple interconnected microgrid incorporating heating and electrical distributed energy resources. GenOPT enables the search of the best location in gridded area of small energy system connected with macrogrids.This optimizator is based on a combination of a multi-objective evolutionary algorithm with sequential least squares linear programming method. The tool aims to support policy maker, engineers during the design phase of complex combined heat and power microgrids.