Dušan Bajatović

ORCID: 0000-0003-1604-0317
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About
Contact & Profiles
Research Areas
  • Reservoir Engineering and Simulation Methods
  • Market Dynamics and Volatility
  • Monetary Policy and Economic Impact
  • Energy Load and Power Forecasting
  • Global Energy and Sustainability Research
  • Building Energy and Comfort Optimization
  • Global Energy Security and Policy
  • Integrated Energy Systems Optimization
  • Water resources management and optimization
  • Energy Efficiency and Management
  • Grey System Theory Applications

University of Novi Sad
2020-2024

Nowadays, in terms of trading on the world scale, to foresee a natural gas consumption represents an essential activity.In first part, paper examines current state Serbian sector and methodology applied for prediction capacity planning.In addition, study intends give comprehensive assessment predictive algorithms needs involved last decade with projections suggestions future applications.The primary task is evaluate used models emphasis accuracy predictions obtained.Additionally, will...

10.17559/tv-20191119153507 article EN cc-by Tehnicki vjesnik - Technical Gazette 2020-04-01

This paper studies the forecast accuracy and explainability of a battery dayahead (Henry Hub Title Transfer Facility (TTF)) natural gas price volatility models. The results demonstrate dominance non-linear, non-parametric models with deep structure relative to various competing model specifications. By employing explainable artificial intelligence (XAI) approach, we document that is formed strategically based on crude oil electricity prices. While conditional returns driven by long-memory...

10.1177/01956574241277302 article EN The Energy Journal 2024-07-01

An accelerated rise in energy consumption associated with industry development, urbanization and more comfortable life of people worldwide, caused environmental issues to grow into a serious problem calling for an urgent global action. The case study presented discussed this paper analyses key influential parameters the city-scale moderate natural gas profiles. On one side, information herein can be beneficial companies operating on market build their own predictive models appropriate...

10.23919/splitech49282.2020.9243816 article EN 2022 7th International Conference on Smart and Sustainable Technologies (SpliTech) 2020-09-23

This paper studies the forecast accuracy and explainability of a battery dayahead (Henry Hub Title Transfer Facility (TTF)) natural gas price volatility models. The results demonstrate dominance non-linear, non-parametric models with deep structure relative to various competing model specifications. By employing explainable artificial intelligence (XAI) approach, we document that is formed strategically based on crude oil electricity prices. While conditional returns driven by long-memory...

10.5547/01956574.45.4.dbaj article EN The Energy Journal 2023-10-25
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