Research areas

1. Environmental management and assessment
2. State of environmental evaluation methodology development
3. Environmental management systems; capacity building and auditing
4. Sustainable energetics, energy partnerships, development of complex smart energy grid solutions on renewable energies
5. Environmental-performance-evaluation
6. Noise mapping
7. Modeling of air-pollution of transportation/city traffic
8. Improvement of regional waste management/treatment and reutilization
9. Optimization of building’s energy-utilization
10. ESG (Environmental - Social - Governance)
11. Life Cycle Assessment of Hydrogen value chain (production, storage, stationery and mobility usage, network infrastructure)
12. Design and development of a smart grid test ecosystem for renewable energy integration, optimization through different objective functions
13. Integration of complex energy communities
14. Impact of high penetration of photovoltaic systems on grid stability
15. Socio-economic and environmental benefits of distributed energy resources
16. Using Artificial Intelligence for setting up a company-wide environmental indicator system with predictive modeling opportunities
17. Quantitative and qualitative distribution of micro- and nano-plastics in the Danube River, based on measurements
18. Analyzing energy-poverty situation in Hungary and EU member states
19. Hydrogen policy uptake in EU member states

Life Cycle Assessment of Hydrogen value chain (production, storage, stationery and mobility usage, network infrastructure):

• • We aim to comprehensively evaluate the environmental impact of the entire hydrogen value chain, including production methods, storage options, its usage in stationery and mobile applications, and the associated network infrastructure, providing insights into the most sustainable pathways for hydrogen utilization.

Design and development of a smart grid test ecosystem for renewable energy integration, optimization through different objective functions:

• We focus on creating a simulated smart grid environment (so called virtual test-ecosystem) to assess the seamless integration of renewable energy sources. By employing various objective functions, it seeks to optimize energy flow, storage, and distribution in the grid, ultimately contributing to the efficient and reliable integration of renewables. The main focus here is to understand the causal connections and interactions between the system elements to develop an optimization method for the whole system.

Integration of complex energy communities:

• Investigating the integration of diverse energy communities, we examine the interactions between consumers, prosumers, and various energy resources. It explores the technical, economic, and social aspects of such integrated systems, aiming to design models that promote better energy management and sustainability. The research focus is not only the use of electricity but also other types of energy with a special focus on utilization of heat losses in an energy community.

Impact of high penetration of photovoltaic systems on grid stability:

• We analyze the potential effects of a significant increase in photovoltaic systems' adoption on grid stability. We assess issues such as voltage fluctuations, power quality, and grid resilience, providing valuable insights for policymakers and grid operators to maintain stability in the face of rising solar energy installations.

Socio-economic and environmental benefits of distributed energy resources:

• Examining the positive effects of distributed energy resources, exploring how decentralized power generation, storage, and consumption can lead to socio-economic advantages, such as increased energy access and job opportunities, while also reducing greenhouse gas emissions and promoting environmental sustainability.

Using Artificial Intelligence for setting up a company-wide environmental indicator system with predictive modeling opportunities:

• We focus on leveraging Artificial Intelligence to develop an environmental indicator system for companies. The planned method incorporates not only the analysis of big data, but also by using predictive modeling, the system can forecast potential environmental impacts, enabling proactive measures to reduce ecological footprints and improve sustainability performance.

Quantitative and qualitative distribution of micro- and nano-plastics in the Danube River, based on measurements:

• We involve extensive measurements to assess the presence and distribution of micro- and nano-plastics in the Danube River. By providing both quantitative and qualitative data, it sheds light on the extent of plastic pollution in the ecosystem and its potential impact on aquatic life and human health. Also, the effect of large cities (such like Győr) on river microplastic pollutions will be investigated during the research.

Analyzing energy-poverty situation in Hungary and EU member states:

• Quantifying the energy poverty in Hungary and investigating the causes and consequences of energy poverty on vulnerable communities. It aims to identify potential policy interventions and energy assistance programs to alleviate energy poverty and promote social equity.

Hydrogen policy uptake in EU member states:

• We examine the adoption and implementation of hydrogen policies across various EU member states. By comparing policy frameworks, incentives, and investments, it provides an understanding of the factors influencing hydrogen uptake and its role in achieving the EU's energy and climate targets.