Publications featuring data by OPSD

This site displays all publications featuring data from the OPSD project sorted by year.

2019

Keliris, Anastasis; Konstantinou, Charalambos; Sazos, Marios; Maniatakos, Michail (2019): Open Source Intelligence for Energy Sector Cyberattacks. In: Dimitris Gritzalis, Marianthi Theocharidou und George Stergiopoulos (Hg.): Critical infrastructure security and resilience. Theories, methods, tools and technologies, Bd. 26. Cham, Switzerland: Springer Nature (Advanced Sciences and Technologies for Security Applications), S. 261–281.

Lombardi, Francesco; Rocco, Matteo Vincenzo; Colombo, Emanuela (2019): A multi-layer energy modelling methodology to assess the impact of heat-electricity integration strategies: The case of the residential cooking sector in Italy. In: Energy 170, S. 1249–1260. DOI: 10.1016/j.energy.2019.01.004.

Wiese, Frauke; Schlecht, Ingmar; Bunke, Wolf-Dieter; Gerbaulet, Clemens; Hirth, Lion; Jahn, Martin et al. (2019): Open Power System Data – Frictionless data for electricity system modelling (free version on arXiv). In Applied Energy 236, pp. 401–409.

2018

Amme, Jonathan; Pleßmann, Guido; Bühler, Jochen; Hülk, Ludwig; Kötter, Editha; Schwaegerl, Peter (2018): The eGo grid model: An open-source and open-data based synthetic medium-voltage grid model for distribution power supply systems. An open-source and open-data based synthetic medium-voltage grid model for distribution power supply systems. In J. Phys.: Conf. Ser. 977, p. 12007.

Brown, T.; Schlachtberger, D.; Kies, A.; Schramm, S.; Greiner, M. (2018): Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system. In: Energy 160, S. 720–739. DOI: 10.1016/j.energy.2018.06.222.

Chen, Bei; Eck, Bradley; Fusco, Francesco; Gormally, Robert; Purcell, Mark; Sinn, Mathieu; Tirupathi, Seshu: Castor: Contextual IoT Time Series Data and Model Management at Scale. Available online at https://arxiv.org/pdf/1811.08566.pdf.

Deschatre, Thomas; Veraart, Almut E. D. (2018): A Joint Model for Electricity Spot Prices and Wind Penetration with Dependence in the Extremes. In: Philippe Drobinski, Mathilde Mougeot, Dominique Picard, Riwal Plougonven und Peter Tankov (Hg.): Renewable Energy: Forecasting and Risk Management. Paris, France, June 7-9, 2017, Bd. 254. Cham: Springer International Publishing (Springer Proceedings in Mathematics & Statistics, 254), S. 185–207.

Ding, Wenxiu; Jing, Xuyang; Yan, Zheng; Yang, Laurence T. (2018): A Survey on Data Fusion in Internet of Things: Towards Secure and Privacy-Preserving Fusion. In Information Fusion. DOI: 10.1016/j.inffus.2018.12.001.

El-Amary, Noha H.; Balbaa, Alsnosy; Swief, R.; Abdel-Salam, T. (2018): A Reconfigured Whale Optimization Technique (RWOT) for Renewable Electrical Energy Optimal Scheduling Impact on Sustainable Development Applied to Damietta Seaport, Egypt. In Energies 11 (3), p. 535.

Gambardella, Christian; Pahle, Michael (2018): Time-varying electricity pricing and consumer heterogeneity: Welfare and distributional effects with variable renewable supply. In: Energy Economics 76, S. 257–273.

Gardumi, Francesco; Shivakumar, Abhishek; Morrison, Robbie; Taliotis, Constantinos; Broad, Oliver; Beltramo, Agnese et al. (2018): From the development of an open-source energy modelling tool to its application and the creation of communities of practice: The example of OSeMOSYS. In Energy Strategy Reviews 20, pp. 209–228.

Gotzens, Fabian; Heinrichs, Heidi; Hake, Jürgen-Friedrich; Allelein, Hans-Josef (2018): The influence of continued reductions in renewable energy cost on the European electricity system. In Energy Strategy Reviews 21, pp. 71–81.

Hirth, Lion; Mühlenpfordt, Jonathan; Bulkeley, Marisa (2018): The ENTSO-E Transparency Platform – A review of Europe’s most ambitious electricity data platform. In: Applied Energy 225, S. 1054–1067. DOI: 10.1016/j.apenergy.2018.04.048.

Lee, Esther H. Park; Lukszo, Zofia; Herder, Paulien (2018): Aggregated fuel cell vehicles in electricity markets with high wind penetration. In: ICNSC 2018. The 15th IEEE International Conference on Networking, Sensing and Control : March 27-29, 2018, Zhuhai, China. 2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC). Zhuhai, 3/27/2018 – 3/29/2018. [Piscataway, New Jersey]: IEEE, S. 1–6.

Masum, Shamsul; Liu, Ying; Chiverton, John (2018): Multi-step Time Series Forecasting of Electric Load Using Machine Learning Models. In: Leszek Rutkowski, Rafał Scherer, Marcin Korytkowski, Witold Pedrycz, Ryszard Tadeusiewicz und Jacek M. Zurada (Hg.): Artificial Intelligence and Soft Computing, Bd. 10841. Cham: Springer International Publishing (Lecture Notes in Computer Science), S. 148–159.

Müller, Ulf Philipp; Wienholt, Lukas; Kleinhans, David; Cussmann, Ilka; Bunke, Wolf-Dieter; Pleßmann, Guido; Wendiggensen, Jochen (2018): The eGo grid model. An open source approach towards a model of German high and extra-high voltage power grids. In J. Phys.: Conf. Ser. 977, p. 12003.

Olauson, Jon (2018): ERA5: The new champion of wind power modelling? In Renewable Energy 126, pp. 322–331.

Osegi, E. N. (2018): Using the Hierarchical Temporal Memory Spatial Pooler for short-term forecasting of electrical load time series. In: Applied Computing and Informatics. DOI: 10.1016/j.aci.2018.09.002.

Pfenninger, Stefan; Hirth, Lion; Schlecht, Ingmar; Schmid, Eva; Wiese, Frauke; Brown, Tom et al. (2018): Opening the black box of energy modelling. Strategies and lessons learned. In Energy Strategy Reviews 19, pp. 63–71.

Riepin, Iegor; Mobius, Thomas; Musgens, Felix (2018 – 2018): Integrated Electricity and Gas Market Modeling – Effects of Gas Demand Uncertainty. In: 2018 15th International Conference on the European Energy Market (EEM). 2018 15th International Conference on the European Energy Market (EEM). Lodz, 6/27/2018 – 6/29/2018: IEEE, S. 1–5.

Robinius, Martin; Linßen, Jochen; Grube, Thomas; Reuß, Markus; Stenzel, Peter; Syranidis, Konstantinos et al. (2018): Comparative Analysis of Infrastructures: Hydrogen Fueling and Electric Charging of Vehicles. Jülich: Schriften des Forschungszentrums Jülich (Energy & Environment, 408).

Sharma, Ekanki (2018): Energy forecasting based on predictive data mining techniques in smart energy grids. In: Energy Inform 1 (S1), S. 982. DOI: 10.1186/s42162-018-0048-9.

Victoria, Marta; Andresen, Gorm B. (2018): Using validated reanalysis data to investigate the impact of the PV system configurations at high penetration levels in European countries. Available online at http://arxiv.org/pdf/1807.10044v1.

Weber, Juliane; Heinrichs, Heidi Ursula; Gillessen, Bastian; Schumann, Diana; Hörsch, Jonas; Brown, Tom; Witthaut, Dirk (2018): Counter-intuitive behaviour of energy system models under CO2 caps and prices. Available online at http://arxiv.org/pdf/1809.03157v1.

Wehrle, Sebastian; Schmidt, Johannes (2018): District heating systems under high CO2 emission prices: the role of the pass-through from emission cost to electricity prices. Available online at https://arxiv.org/pdf/1810.02109v1.

Zerrahn, Alexander; Schill, Wolf-Peter; Kemfert, Claudia (2018): On the economics of electrical storage for variable renewable energy sources. 19/2/2018. Available online at http://arxiv.org/pdf/1802.07885.

Zhu, K.; Victoria, M.; Brown, T.; Andresen, G. B.; Greiner, M. (2018): Impact of CO2 prices on the design of a highly decarbonised coupled electricity and heating system in Europe. Available online at http://arxiv.org/pdf/1809.10369v1.

 

2017

Fusco, Francesco; Tirupathi, Seshu; Gormally, Robert (2017): Power Systems Data Fusion based on Belief Propagation. In : 7th IEEE International Conference on Innovative Smart Grid Technologies (ISGT). 7th IEEE International Conference on Innovative Smart Grid Technologies. IEEE.

González Ordiano, Jorge Á.; Waczowicz, Simon; Hagenmeyer, Veit; Mikut, Ralf (2017): Energy forecasting tools and services. In WIREs Data Mining Knowl Discov 14, e1235.

Kendziorski, Mario; Setje-Eilers, Mona; Kunz, Friedrich (2017): Generation expansion planning under uncertainty: An application of stochastic methods to the German electricity system. In : 2017 14th International Conference on the European Energy Market (EEM). 2017 14th International Conference on the European Energy Market (EEM). Dresden, Germany, 6/6/2017 – 9/6/2017: IEEE, pp. 1–7.

Klein, Martin; Deissenroth, Marc (2017): When do households invest in solar photovoltaics? An application of prospect theory. In Energy Policy 109, pp. 270–278.

Müller, Ulf Philipp; Cussmann, Ilka; Wingenbach, Clemens; Wendiggensen, Jochen (2017): AC Power Flow Simulations within an Open Data Model of a High Voltage Grid. In Volker Wohlgemuth, Frank Fuchs-Kittowski, Jochen Wittmann (Eds.): Advances and new trends in environmental informatics. Stability, continuity, innovation, vol. 8. New York, NY: Springer Berlin Heidelberg (Progress in IS), pp. 181–193.

Nacken, Lukas; Mobius, Thomas (2017): The effects of harmonized European climate policy targets in comparison to national targets utilizing a European electricity market model. In : 2017 14th International Conference on the European Energy Market (EEM). 2017 14th International Conference on the European Energy Market (EEM). Dresden, Germany, 6/6/2017 – 9/6/2017: IEEE, pp. 1–5.

Portela, Jose; Munoz, Antonio; Alonso, Estrella (2017): Forecasting functional time series with a new Hilbertian ARMAX model. Application to electricity price forecasting. In IEEE Trans. Power Syst., p. 1.

Schill, Wolf-Peter; Pahle, Michael; Gambardella, Christian (2017): Start-up costs of thermal power plants in markets with increasing shares of variable renewable generation. In Nat. Energy 2 (6), p. 17050.

Schill, Wolf-Peter; Zerrahn, Alexander; Kunz, Friedrich (2017): Prosumage of Solar Electricity. Pros, Cons, and the System Perspective. In SSRN Journal.

Tafarte, Philip; Buck, Patrick (2017): Integration of wind power — Challenges and options for market integration and its impact on future cross-sectorial use. In : 2017 14th International Conference on the European Energy Market (EEM). 2017 14th International Conference on the European Energy Market (EEM). Dresden, Germany, 6/6/2017 – 9/6/2017: IEEE, pp. 1–5.

Yaslan, Yusuf; Bican, Bahadır (2017): Empirical mode decomposition based denoising method with support vector regression for time series prediction. A case study for electricity load forecasting. In Measurement 103, pp. 52–61.

Zaidi, Bizzat Hussain; Hong, Seung Ho (2017): Combinatorial double auctions for multiple microgrid trading. In Electr Eng 62 (4), p. 2551.