HELM: Holomorphic Embedding Load Flow Method


Grids are one of the most critical infrastructures in any country. Electric corporations need to guarantee power supply to users and take preventive measures in case of blackouts caused by network voltage collapse or failures of power transmissions.


HELM is an algorithm created, designed and developed by Grupo AIA, called this way for its acronyms in English Holomorphic Embedding Load Flow Method. It´s a power load flow computing method, not iterative which means it´s a constructive deterministic method (non-iterative), direct and completely reliable and which guarantees finding the correct operational solution. (power flow is a multivalued problem), Signals the condition of voltage collapse when there is no solution (infeasible power flow).

HELM is an innovative method to tackle power load flow problem and state estimator for AC terrestrial networks that has been successfully tested for over 15 years in Grupo AIA´s application developed for power grids.


Since 2014, through its affiliate companies EleQuant Inc. and EQ-KIDS, AIA has participated in NASA´s SBIR and STTR projects in SMEs innovation program. HELM has been applied on software developments for autonomous functioning of power systems functioning and management.


Moreover, in Grupo AIA the HELM method has been used to solve non-linear problems in DC micro networks for NASA. This means Grupo AIA has developed autonomous and intelligent systems capable of solving spacecrafts power systems (manned or unmanned) without human intervention on in space missions to Mars and beyond.


The HELM algorithm was invented by Dr. Antonio Trias and patented in the U.S.A. The method is based on it is based on advanced concepts and results from Complex Analysis, such as holomorphism, the theory of algebraic curves, and analytic continuation. However, its numerical implementation is direct as it uses linear algebra standard and Padé approximation.

For more information about the HELM method, its publications, patents, and features compared with iterative traditional methods, visit EleQuant Inc. website

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