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Mr Gregorio Higuera-Gutierrez

Research Postgraduate – Electrical Power Node

Research Postgraduate – Electrical Power Node in the Department of Engineering


Gregorio Higuera is a second-year Electrical Engineering PhD student focused on Active Network Management of Future Distribution Systems.
He holds a BEng in Mechatronics Engineering specialised in Power Electronics Systems from Instituto Tecnologico de Sonora (ITSON) in Ciudad Obregon, Sonora, Mexico. He got his engineering degree developing the thesis project “Grid-Connected Photovoltaic System with Maximum Point Tracking (MPPT) Algorithms” which focused mainly on the integration of photovoltaic systems into the electrical grid. Also, he received his BEng degree with two honorific mentions: For academic performance and thesis developed work.
Currently, his PhD work is related to Distribution Systems with high integration of renewable energy sources within an Active Network Management framework. He is exploring stochastic methods to optimise the operation of said systems. Moreover, while working on the PhD, he has done a 2-month summer internship in 2021 with the Durham Energy Institute (DEI) which consisted in understanding the energy consumption on the Durham University Science Site and making recommendations for improvements based on the findings without compromising teaching and research. Also, Gregorio recently has finished a Centre Doctoral Training (CDT) mini-project which consisted of establishing a carbon footprint benchmark for the Lumiere Festival 2021 held in County Durham.
Gregorio’s doctoral studies in Durham University are being funded by the Consejo Nacional de Ciencia y Tecnologia (CONACyT) of Mexico.

Research Project

The increasing number of Distributed Generation (DG) and stakeholders within the Distributed Networks (DNs) have introduced challenges, especially considering uncertainties and variability of DG outputs and demand. It is in this context that new control strategies such as Active Network Management (ANM) frameworks based on stochastic Optimal Power Flow (OPF) formulations should be adopted for day-ahead operation planning. Furthermore, there are also opportunities for energy market regulation and energy trading as the number of stakeholders that can sell and buy energy increases in future energy networks. Hence, a control mechanism for energy transactions should be considered for the future DN such as a Transactive Energy (TE) Framework to consider energy pricing for the stakeholders' energy exchange.
Gregorio’s work is proposing the development of a novel ANM framework for stochastic day-ahead operation planning under a TE Framework aiming to tackle challenges of uncertainty in DG outputs and demand. Also, it will address optimising the energy trading among the different stakeholders in future DNs.

Research interests

  • Electrical Machines
  • Energy Transition
  • Future Distribution Networks
  • Optimisation
  • Power Electronics
  • Smart Grids