dr. Y. (Yashar) Ghiassi-Farrokhfal

Rotterdam School of Management (RSM)
Erasmus University Rotterdam
Associate Member ERIM
Field: Logistics & Information Systems
Affiliated since 2015

Energy systems, electricity markets, storage systems, market design and analysis, city-wide energy planning (FlexSUS)

 

 

 

 

Publications

  • Academic (1)
    • Ansarin, M., Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2018). Cross-subsidies in Energy Co-operative Tariff Designs.

  • Academic (15)
    • Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2021). Making Green Power Purchase Agreements More Predictable and Reliable for Companies. Decision Support Systems, 144, [113514]. https://doi.org/10.1016/j.dss.2021.113514

    • Esmat, A., De Vos, M., Ghiassi-Farrokhfal, Y., Palensky, P., & Epema, D. (2020). A Novel Decentralized Platform for Peer-to-Peer Energy Trading Market with Blockchain Technology. Applied Energy, 282, [11623]. https://doi.org/10.1016/j.apenergy.2020.116123

    • Ansarin, M., Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2020). Cross-subsidies among residential electricity prosumers from tariff design and metering infrastructure. Energy Policy, 145. https://doi.org/10.1016/j.enpol.2020.111736

    • Pevec, D., Babic, J., Carvalho, A., Ghiassi-Farrokhfal, Y., Ketter, W., & Podobnik, V. (2020). A Survey-Based Assessment of How Existing and Potential Electric Vehicle Owners Perceive Range Anxiety. Journal of Cleaner Production, 276, [122779]. https://doi.org/10.1016/j.jclepro.2020.122779

    • Ansarin, M., Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2020). The Economic Consequences of Electricity Tariff Design in a Renewable Energy Era. Applied Energy, 275, [115317]. https://doi.org/10.1016/j.apenergy.2020.115317

    • Kazhamiaka, F., Ghiassi-Farrokhfal, Y., Keshav, S., & Rosenberg, C. (2019). Comparison of Different Approaches for Solar PV and Storage Sizing. IEEE Transactions on Sustainable Computing. https://doi.org/10.1109/TSUSC.2019.2946246

    • Basmadjian, R., Ghiassi-Farrokhfal, Y., & Vishwanath, A. (2018). Hidden Storage in Data Centers: Gaining Flexibility Trough Cooling Systems. Lecture Notes in Computer Science, 10740, 68-82. https://doi.org/10.1007/978-3-319-74947-1_5

    • Pevec, D., Babic, J., Kayser, MA. M., Carvalho, A., Ghiassi-Farrokhfal, Y., & Podobnik, V. (2018). A Data-Driven Statistical Approach for Extending Electric Vehicle Charging Infrastructure. International Journal of Energy Research, 42(9), 3102-3120. https://doi.org/10.1002/er.3978

    • Ghiassi-Farrokhfal, Y., Rosenberg, C., Keshav, S., & Adjaho, M-B. (2016). Joint Optimal Design and Operation of Hybrid Energy Storage Systems. IEEE Journal on Selected Areas in Communications, 34(3), 639-650. https://doi.org/10.1109/JSAC.2016.2525599

    • Ghiassi-Farrokhfal, Y., Keshav, S., Rosenberg, C., & Ciucu, F. (2015). Solar Power Modelling: An Analytical Approach. IEEE Transactions on Sustainable Energy, 6(1), 162-170. https://doi.org/10.1109/TSTE.2014.2359795

    • Ghiassi-Farrokhfal, Y., Keshav, S., & Rosenberg, C. (2015). Towards a Realistic Storage Modelling and Performance Analysis in Smart Grids. IEEE Transactions on Smart Grid. https://doi.org/10.1109/TSG.2014.2330832

    • Ghiassi-Farrokhfal, Y., Kazhamiaka, F., Rosenberg, C., & Keshav, S. (2015). Optimal Design of Solar PV Farms With Storage. IEEE Transactions on Sustainable Energy, 6(4), 1586-1593. https://doi.org/10.1109/TSTE.2015.2456752

    • Liebeherr, J., & Ghiassi-Farrokhfal, Y. (2015). On the Output Rate of Overloaded Link Schedulers. IEEE Communications Letters, 19(4), 573-576. https://doi.org/10.1109/LCOMM.2015.2401569

    • Singla, S., & Ghiassi-Farrokhfal, Y. (2014). Using Storage to Minimize Carbon Footprint of Diesel Generators for Unreliable Grids. IEEE Transactions on Sustainable Energy, 5(4), 1270-1277. http://hdl.handle.net/1765/79420

    • Liebeherr, J., Ghiassi-Farrokhfal, Y., & Burchard, A. (2011). On the impact of link scheduling on end-to-end delays in large networks. IEEE Journal on Selected Areas in Communications, 29(5), 1009-1020. https://doi.org/10.1109/JSAC.2011.110511

  • Academic (3)
    • Ghiassi-Farrokhfal, Y., & Pakravan, M. R. (2005). Cross-layer flooding for sensor networks without location information. IEEE MASS.

    • Mansouri, V. S., Mohammadnia-Awal, M., Ghiassi-Farrokhfal, Y., & Khalaj, B. H. (2005). Dynamic scheduling MAC protocol for large scale sensor networks. IEEE MASS.

    • Mansouri, V. S., Ghiassi-Farrokhfal, Y., Mohammadnia-Awal, M., & Khalaj, B. H. (2005). Using a diversity scheme to reduce energy consumption in wireless sensor networks. BroadNets.

  • Academic (26)
    • Ansarin, M. M., Ghiassi-Farrokhfal, Y. Y., Ketter, W. W., & Collins, J. (2020). Economic Inefficiencies of Distributed Generation under Novel Tariff Designs. In International Conference on Applied Energy

    • Naseri, N., Ghiassi-Farokhfal, Y., & Collins, J. (2019). A trade-off analysis between the spot and real-time electricity markets for batteries. In 40th International Conference on Information Systems, ICIS 2019 [2267] Association for Information Systems. 40th International Conference on Information Systems, ICIS 2019 https://aisel.aisnet.org/icis2019/sustainable_is/sustainable_is/8/

    • Pevec, D., Babic, J., Carvalho, A., Ghiassi-Farrokhfal, Y., Ketter, W., & Podobnik, V. (2019). Electric Vehicle Range Anxiety: An Obstacle for the Personal Transportation (R) evolution? In 4th International Conference on Smart and Sustainable Technologies (SpliTech) IEEE. https://doi.org/10.23919/SpliTech.2019.8783178

    • Ansarin, M., Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. J. M. . (2019). Increasing Renewables In Energy Cooperatives Leads To Higher Cross-Subsidies, Depending On Tariff. In 42nd IAEE Conference (International Association for Energy Economics)

    • Naseri, N., Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2019). Battery with Market Power in Electricity Markets. In Workshop on Information Technologies and Systems (WITS)

    • Ghiassi-Farrokhfal, Y., Nasiri, N., Ketter, W., & Collins, J. J. M. . (2019). The Role of Batteries with Market Power in Electricity Markets. In Workshop on Information Technologies and Systems (WITS)

    • Nasiri, N., Ghiassi-Farrokhfal, Y., & Ketter, W. (2019). Batteries With Market Power In Electricty Markets. In 42nd IAEE Conference (International Association for Energy Economics)

    • Ghiassi-Farrokhfal, Y., & van Lunteren, B. (2019). Designing an Inter-Sectoral Energy Storage System. In 42nd IAEE Conference (International Association for Energy Economics)

    • Kazhamiaka, F., Ghiassi-Farrokhfal, Y., Keshav, S., & Rosenberg, C. (2018). Robust and Practical Approaches for Solar PV and Storage Sizing. In e-Energy '18 Proceedings of the Ninth International Conference on Future Energy Systems https://doi.org/10.1145/3208903.3208935

    • Ansarin, M., Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2017). Cross-subsidies in Energy Cooperative Tariff Designs. In Workshop on Information Technology & Systems (WITS)

    • Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2017). Designing a Battery-Friendly Electricity Market. In International Conference on Information Systems (ICIS-17)

    • Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2016). Analyzing Market Pricing Schemes To Integrate Renewable Sources. In Workshop on Information Technology & Systems (WITS)

    • Ansarin, M., Ghiassi-Farrokhfal, Y., Ketter, W., & Collins, J. (2016). A cooperative aggregation model for pricing residential energy users with renewable energy sources. In Workshop on Information Technology and Systems

    • Ansarin, M., Ghiassi-Farrokhfal, Y., Collins, J., & Ketter, W. (2016). A Demand Response Model for Residential Energy Cooperatives with Distributed Generation. In Workshop on Information Technology and Systems (WITS)

    • van Gelder, C., & Ghiassi-Farrokhfal, Y. (2016). On The Reliability Gain of Neighborhood Coalitions: A Data-Driven Study. In IEEE SmartGridComm.

    • Ghiassi-Farrokhfal, Y., Keshav, S., & Rosenberg, C. (2014). An EROI Analysis of Renewable Energy Farms with Storage. In e-Energy '14: Proceedings of the 5th international conference on Future energy systems https://doi.org/10.1145/2602044.2602064

    • Singla, S., Ghiassi-Farrokhfal, Y., & Keshav, S. (2014). Battery Provisioning and Scheduling for a Hybrid Battery-Diesel Generator System. In ACM SIGMETRICS Performance Evaluation Review (Vol. 41, pp. 71-76). 3 https://doi.org/10.1145/2567529.2567552

    • Ghiassi-Farrokhfal, Y., & Liebeherr, J. (2013). Capacity Provisioning for Schedulers with Tiny Buffers. In 2013 Proceedings IEEE INFOCOM (pp. 2445-2453) https://doi.org/10.1109/INFCOM.2013.6567050

    • Singla, S., Ghiassi-Farrokhfal, Y., & Keshav, S. (2013). Near-Optimal Scheduling for a Hybrid Battery-Diesel Generator for Offline-Grid Locations. In Proceedings of ACM Sigmetrics http://hdl.handle.net/1765/79425

    • Ghiassi-Farrokhfal, Y., & Ciucu, F. (2012). On the Impact of Finite Buffers on Per-Flow Delays in FIFO Queues. In Proceedings of International Teletraffic Congress (ITC) http://hdl.handle.net/1765/79428

    • Ghiassi-Farrokhfal, Y., Liebeherr, J., & Burchard, A. (2011). The impact of link scheduling on long paths: statistical analysis and optimal bounds. In 2011 Proceedings IEEE INFOCOM https://doi.org/10.1109/INFCOM.2011.5934905

    • Liebeherr, J., & Ghiassi-Farrokhfal, Y. (2010). Does link scheduling matter on long paths? In Proceedings of ICDCS http://hdl.handle.net/1765/79430

    • Ghiassi-Farrokhfal, Y., & Liebeherr, J. (2009). Output characterization of constant bit rate traffic in FIFO schedulers. In IEEE Communications Letters (Vol. 13, pp. 618-620). 8 https://doi.org/10.1109/LCOMM.2009.090979

    • Ghiassi-Farrokhfal, Y., Arbab, V. R., & Pakravan, M. R. (2006). A near optimum RREQ flooding algorithm in sensor networks. In -

    • Ghiassi-Farrokhfal, Y., Arbab, V. R., & Pakravan, M. R. (2006). Estimation error minimization in sensor networks with mobile agents. In -

    • Ghiassi-Farrokhfal, Y., Shah-Mansouri, V., & Pakravan, M. R. (2005). A novel joint routing and power management algorithm for energy-constraint ad-hoc sensor network. In -

  • External (1)
  • Academic (1)
  • Role: Daily Supervisor
  • PhD Candidate: Mohammad Ansarin
  • Time frame: 2015 -
  • Role: Member Doctoral Committee
  • PhD Candidate: Derck Koolen
  • Time frame: 2014 - 2019
  • Role: Member Doctoral Committee
  • PhD Candidate: Cristian Stet
  • Time frame: 2017 -

The MAGPIE consortium, consisting of 4 ports (Lighthouse port Rotterdam, Fellow Ports DeltaPort (inland), Sines and HAROPA), 9 research institutes and universities, 32 private companies and 4 other institutes, forms a unique collaboration addressing the missing link between green energy supply and green energy use in port-related transport and the implementation of digitalisation, automation, and autonomy to increase transport efficiency. This project accelerates the introduction of green energy carriers combined with realisation of and logistic optimisation in ports through automation and autonomous operations. A living lab approach is applied in which technological and nontechnological innovations are developed or demonstrated. All results feed into the Master Plan for the future European green port, aiming at full decarbonisation by 2050 by providing solutions that can be implemented immediately to make significant steps in decarbonisation already by 2030.

We are seeking highly motivated students with demonstrated academic ability, those who possess a commitment to interdisciplinary research on significant information technology and management issues, and those who desire to pursue an academic research career in this field. You will be part of the Business Information Management (BIM) section within the Department of Technology & Operations Management at the Rotterdam School of Management, Erasmus University.

Applicants must have strong quantitative training, with preference given to candidates who have earned an MSc, MPhil or Research Master in economics, computer science, engineering, econometrics, statistics, or a related field. Successful candidates have proficiency with C++, Java, Python, or other programming languages.

As a Ph.D. student, you will gain the training and experience necessary to conduct independent research through course work in information systems, economics, econometrics, machine learning, optimization, and large-scale data analytics. You will work closely with the advisors to define, develop, and execute your own research. The Ph.D. dissertation will be defined by the student with inputs from the advisors, and thus requires creativity, self-direction, and a passion for scientific inquiry.

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2015
February
18

Address

Visiting address

Office: Mandeville Building T09-11
Burgemeester Oudlaan 50
3062 PA Rotterdam

Postal address

Postbus 1738
3000 DR Rotterdam
Netherlands