CINELDI recruits masters, PhDs and Post doctors in the following disciplines:

Electric power engineering  -  Communication technology  -  Information technology  -  Automation/cybernetics  -  Socio-economics  -  Social science aspects of smart grids


Romina Muka, PhD in CINELDI, explaining what she is working on in her PhD

PhD and PostDoc

PhD's in CINELDI and associated PhD's:

PostDoc's in CINELDI and associated PostDoc's:

Master theses

Master theses NTNU 2020:

  • Ringheim, Liv: Grid Impact from Increased Prosumer Penetration in the Norwegian Distribution Grid
  • Osnes, Mari Myrvold: Analyse av lastendringer på nettstasjonsnivå som følge av solkraftproduksjon på privathus og næringsbygg
  • Refvik, Håvard: Exploitation of big data and machine learning in the distribution grid operation
  • Deraas, Bendik Balstad: Analysis of interdependencies between power systems and other critical infrastructures
  • Rogne, Erik Log: Analysis and visualization of reinvestment scenarios for distribution networks
  • Veie, Bjørnar: Balancing power production and consumption in nano grids
  • Molvik, Øystein: Sensor for real time measurement of potential for electric power production from solar panels
  • Farooq, Mohamed: Benefits of TSO-DSO coordination for voltage control: Simulation study and use case development
  • Gunabala, Sarminal; Eriksen, Sara: Nettselskapers involvering av underleverandører i hendelseshåndtering ved cyberangrep
  • Gjørven, Bjørn O; Bakken, Alexander Hansen: Design and Implementation of a Novel Architecture for Virtual Smart Grid Cyber Ranges
  • Gudmestad, Racin: Delayed Integrity Check for IEC 61850 Communication
  • Rønningen, Fabian Skarboe: Adaptive Control of Distributed Generation Inverter Based on Impedance Estimation
  • Lillefosse, Eirik Haugan: Development of a computational tool for assessing uninterrupted microgrid operation
  • Steig, Rune: Model-based control of plug-and-play grid-connected inverters
  • Magnussen, Hannah: Model predictive controller for charging of grid-connected battery
  • Formo, Markus: Cont Power Flow as a tool for sequential simulation
  • Ellingsen, Matias Lunde: Security-Constrained Optimal Power Flow
  • Westad, Erlend: Harmonics Management through Data Analysis, Identification and Control
  • Narayan, Erik-Anant: Dynamic simulation of power systems based on a second-order predictor-corrector scheme
  • Sælen, Åsmund: Toolbox for specialized power system analysis
  • Bravo, Manuel Perez: Electric Vehicles Integration – Charging Infrastructure
  • Træland, Christian Fredrik Marquez: Grid Tariffs for Fast Charging Infrastructure in the Norwegian Distribution Grid
  • Ivarsøy, Eirik: Load profiles of electric vehicles for fast charging stations
  • Aarnes, Tormod Habbestad: High-power electric charging in the Norwegian distribution grid
  • Haugen, Eirik: Optimization of battery energy storage system: A case study for an electric vehicle fast-charging station
  • Brubæk, Maren Refsnes: Battery storage as alternative to grid reinforcement in the low-voltage network
  • Dynge, Marthe Fogstad: Local Energy Market Potential between Positive Energy Blocks in Trondheim
  • Holte, Jon Hvideberg: Analysis of seasonal variations for a multimarket energy storage system including uncertainty
  • Espevik, Linnea: Techno-economic optimization of energy storage for increased wind farm integration
  • Skonnord, Olav Henrik: Grid implications of local markets and peer-to-peer trading in Norwegian distribution grids
  • Abraham, Doney: Application of Machine Learning in IoT enabled Smart Grids for Attack Detection

Master theses NTNU 2019:

  • Lunden, Tonje L.: Analyse av forbruksmålinger fra smarte nettstasjoner for planlegging og drift av distribusjonsnett
  • Slinde, Torbjørn: Prosesstøtte og visualisering i neste generasjons asset management
  • Skyttermoen, Natalie: A Method for Planning a Fast Charging Station
  • Brurås, Marte: Impact of Fast Charging Stations on the Reliability of Electricity Supply in Distribution Networks
  • Heistad, Fredrik; Kristensen, William A.: Prediksjon av feil i det norske strømnettet
  • Lervik, Marius: System for acquisition and analyzing of data from smart meters
  • Damslora, Bernt J.: Data collection in a cellular sensor network with nRF9160
  • Skaftun, Ingvild: Effektforbruk ved svømmeanlegg (Pirbadet)
  • Karlsen, Mats K.: Energioptimalisering og mikrogrid, Granåsen skisenter
  • Runestad, Kjersti L.: Adaptive Protection of an Inverter- Dominated Microgrid and Testing at the Smart Grid Laboratory at NTNU
  • Baksvær, Martine J.N.: EMD and Online EMD for Harmonic Detection in Power Systems
  • Riseth, Jonas; Myhre, Stine F.: Interaction Strategies for an Optimal Grid Integration of Microgrids
  • Eidsvik, Håkon: Dynamic simulation of power systems based on a second-order predictor-corrector scheme
  • Kvandal, Hege B.: Toolbox for specialized power system analysis
  • Hjelme, Oda: Optimal PV Inverter Active and Reactive Power Control in Distribution Grids With High Amounts of Solar PV
  • Nyegaard, Line: Multi-Period AC Optimal Power Flow for Distribution Systems with Energy Storage
  • Bjerland, Siri F.; Grøttum, Hanne H.: Modelling coordination schemes for the transmission and distribution system operators in the power system
  • Sæther, Guro: Peer-to-Peer Energy Trading in Combination with Local Flexibility Resources in a Norwegian Industrial Site
  • Melby, Mathias: Comparison of virtual oscillator control and droop control in an inverter-based stand-alone microgrid
  • Halsne, Steinar: Stabilitetsvurdering ved Nettimpedansmetoden og Adaptiv Kontroll
  • Almenning, Ola M.: Reducing Neighborhood Peak Load with a Peer-to-Peer Approach under Subscribed Capacity Tariffs
  • Revenga, Rodrigo V.: A Shorterm assessment of flexibility analyzing different levels of VRES deployment in a Unit Commitment model
  • Mathisen, Andreas R.: Continuous-Time Unit Commitment using spline interpolation

Master theses NTNU 2018:

  • Harbo, Sondre: Tackling Variability in Renewable Energy Production and Electric Vehicle Consumption with Stochastic Optimization - The Benefits of Using the Stochastic Quasi-Gradient Method compared with Exact Methods and Machine Learning
  • Blom, Fredrik: A Feasibility Study of Blockchain Technology As Local Energy Market Infrastructure
  • Føyen, Sjur; Kvammen, Mads-Emil: A signal analysis toolbox for power system identification in Smart Grids
  • Hanssen, Håkon E.: Data acquisition and analysis of acquired data from geographically distributed sensors connected by 2G / 4G technology
  • Grande, Erlend: Data gathering and -assembling from several smart meter HAN ports
  • Øverlie, Thea: Forbrukerfleksibilitet som en ressurs i fremtidens kraftsystem
  • Buchmann, Ruben: Harmonic Sharing in Microgrid Applications - Modeling, Developing and Evaluating a Microgrid Control System With Harmonic Sharing Capability
  • Lillebo, Martin: Impact of EV Integration and Fast Chargers in a Norwegian LV Grid - An analysis based on data from a residential grid in Steinkjer
  • Hole, Jarand: Integrasjon av distribuert fornybar energi i Trøndelag
  • Gjørven, Signe: Integrasjon av sol i det norske kraftsystemet
  • Tveita, Elise: Methods for Cost Allocation Among Prosumers and Consumers Using Cooperative Game Theory
  • Thorvaldsen, Kasper: Multi-Market Optimization of Energy Storage Taking Into Account Uncertainty
  • Rognan, Lene M.: Photovoltaic Power Prediction and Control Strategies of the Local Storage Unit at Campus Evenstad
  • Willett, Henrik: Security evaluation of communication interfaces on smart meters
  • Avevor, Edem: Smart Grid security in the IoT world
  • Andersen, Ingrid: Stochastic Optimization of Zero Emission Buildings
  • Tundal, Marit: Utilizing Blockchain Technology for Settlement in a Microgrid
  • Holvik, Anders: Virtual Impedance Techniques for Power Sharing Control in AC Islanded Microgrids