@article{MTMT:35154535,
	title = {Empowering supercapacitors: Strategic B-site modulations of transition metal atoms in perovskite oxide based electrodes},
	url = {https://m2.mtmt.hu/api/publication/35154535},
	author = {Bachankar, Shital and Malavekar, Dhanaji and Lokhande, Vaibhav and Ji, Taeksoo},
	doi = {10.1016/j.jallcom.2024.175708},
	journal-iso = {J ALLOY COMPD},
	journal = {JOURNAL OF ALLOYS AND COMPOUNDS},
	volume = {1003},
	unique-id = {35154535},
	issn = {0925-8388},
	year = {2024},
	eissn = {1873-4669}
}

@article{MTMT:35586420,
	title = {Mismatch analysis of rooftop photovoltaics supply and farmhouse load: Data dimensionality reduction and explicable load pattern mining via hybrid deep learning},
	url = {https://m2.mtmt.hu/api/publication/35586420},
	author = {Gao, Ding and Zhi, Yuan and Rong, Xing and Yang, Xudong},
	doi = {10.1016/j.apenergy.2024.124520},
	journal-iso = {APPL ENERG},
	journal = {APPLIED ENERGY},
	volume = {377},
	unique-id = {35586420},
	issn = {0306-2619},
	abstract = {Establishing a new type of electricity system based on rooftop photovoltaics (PV) can facilitate the energy transition in rural China. Research on the mismatch between the PV supply and rural household demand is vital to the widespread adoption of PV microgrid systems. Currently, typical load patterns (TLPs) in rural areas lack accurate characterization and mismatch assessment methods disregard PV curtailment. Therefore, this study proposes a hybrid deep learning-based analytical framework to quantify short-term mismatches between PV power generation and TLPs throughout the day and applies it to a real rural dataset. This study employs the variational autoencoder (VAE) model for dimensionality reduction and feature extraction of high-resolution load data and compares it with traditional methods. In addition, we employed the k-medoids method to uncover TLPs and utilized decision trees to enhance interpretability. The results show that (1) The VAE model exhibits superior dimensionality reduction and feature extraction capabilities on both public and measured datasets and compared to other models, it can reconstruct peak loads more effectively. (2) Three types of TLPs were identified within the rural dataset, with the outdoor average daily wet-bulb temperature being the major influencing factor. (3) Significant differences existed in the mismatch levels between the three types of TLPs and PV power generation. The Lorenz curves and Gini coefficients can effectively quantify the mismatch between PV power generation and TLPs. The proposed framework provides theoretical support for optimizing PV microgrid systems design in rural areas and developing demand-side response strategies.},
	keywords = {SYSTEM; PROFILES; STRATEGY; Deep learning; Energy & Fuels; Supply-demand mismatch; Typical load patterns; Photovoltaic microgrid system},
	year = {2024},
	eissn = {1872-9118}
}

@mastersthesis{MTMT:35071337,
	title = {Short- and long-term variability in future electricity systems},
	url = {https://m2.mtmt.hu/api/publication/35071337},
	author = {Jonathan, Ullmark},
	unique-id = {35071337},
	year = {2024}
}

@article{MTMT:35071476,
	title = {Simulation and Modelling as Catalysts for Renewable Energy: A Bibliometric Analysis of Global Research Trends},
	url = {https://m2.mtmt.hu/api/publication/35071476},
	author = {Nica, Ionuț and Georgescu, Irina and Chiriță, Nora},
	doi = {10.3390/en17133090},
	journal-iso = {ENERGIES},
	journal = {ENERGIES},
	volume = {17},
	unique-id = {35071476},
	issn = {1996-1073},
	abstract = {This study investigates the application of advanced simulation and modeling technologies to optimize the performance and reliability of renewable energy systems. Given the urgent need to combat climate change and reduce greenhouse gas emissions, integrating renewable energy sources into existing infrastructure is essential. Using bibliometric methods, our research spans from 1979 to 2023, identifying key publications, institutions, and trends. The analysis revealed a significant annual growth rate of 16.78% in interest in simulation and modeling, with a notable surge in published articles, reaching 921 in 2023. This indicates heightened research activity and interest. Our findings highlight that optimization, policy frameworks, and energy management are central themes. Leading journals like Energies, Energy, and Applied Energy play significant roles in disseminating research. Key findings also emphasize the importance of international collaboration, with countries like China, the USA, and European nations playing significant roles. The three-field plot analysis demonstrated interconnections between keywords, revealing that terms like “renewable energy sources”, “optimization”, and “simulation” are central to the research discourse. Core funding agencies, such as the National Natural Science Foundation of China (NSFC) and the European Union, heavily support this research. This study underscores the importance of policies and sustainability indicators in promoting renewable energy technologies. These insights emphasize the need for ongoing innovation and interdisciplinary collaboration to achieve a sustainable energy future.},
	year = {2024},
	eissn = {1996-1073},
	orcid-numbers = {Nica, Ionuț/0000-0003-2118-3654; Georgescu, Irina/0000-0002-8536-5636; Chiriță, Nora/0009-0005-6633-9466}
}

@{MTMT:35166137,
	title = {Modelling of Grid Management Strategy for Handling Intermittent Renewable Energy Generation in Island Regions},
	url = {https://m2.mtmt.hu/api/publication/35166137},
	author = {Prasad, Dharmbir and Singh, Rudra Pratap and Rizwan, Ariba and Roy, Ranadip and Verma, Shubham},
	booktitle = {Modeling, Analysis, and Control of Smart Energy Systems},
	doi = {10.4018/979-8-3693-2999-3.ch011},
	unique-id = {35166137},
	abstract = {The integration of solar and wind power into standard grid systems has increased the usage of renewable energy; however, the operational challenges presented by these sources' fundamental intermittency remain. This research analyses grid management approaches designed to decrease intermittency concerns related to solar and wind energy. Resource utilization and grid balancing are made feasible by precise short- and long-term forecasting models for solar irradiance and wind patterns, which allow generators to plan for changes. The planned location, Sagar Island, requires 9.5 MW of electricity. The suggested mix of solar, wind, and grid generate 16.5MW. The PV module generates 8,339 kWh, the wind turbine creates 7,532 kWh, the grid purchased 674 kWh, and the grid sold 12,454. The CO2 emission of the system is 33.7 kg/year. The economics metrics ROI 4.5%, IRR 6.6%, and simple payback is 11.34 year.},
	year = {2024},
	pages = {194-222},
	orcid-numbers = {Prasad, Dharmbir/0000-0002-9010-9717; Singh, Rudra Pratap/0000-0001-7352-855X; Roy, Ranadip/0000-0003-2111-2581}
}

@article{MTMT:34885973,
	title = {Distributionally Robust Demand Response for Heterogeneous Buildings with Rooftop Renewables under Cold Climates},
	url = {https://m2.mtmt.hu/api/publication/34885973},
	author = {Shi, Xincong and Wang, Xinrui and Ji, Yuze and Liu, Zhiliang and Han, Weiheng},
	doi = {10.3390/buildings14061530},
	journal-iso = {BUILDINGS-BASEL},
	journal = {BUILDINGS},
	volume = {14},
	unique-id = {34885973},
	abstract = {A considerable penetration of rooftop PV generation and increasing demand for heating loads will enlarge the peak-to-valley difference, imposing a great challenge to the reliable operation of distribution systems under cold climates. The objective of this paper is to establish a distributionally robust demand response (DR) model for building energy systems for suppressing peak-to-valley load ratios by exploiting cooperative complementarity and flexible transformation characteris-tics of various household appliances. The thermodynamic effect of buildings is modeled for harvesting intermittent renewable energy sources (RESs) on the building roof in the form of thermal energy storages to reduce RES curtailments and eliminate thermal comfort violations in cold weather. Furthermore, the Wasserstein metric is adopted to develop the ambiguity set of the uncertainty probability distributions (PDs) of RESs, and thus, only historical data of RES output is needed rather than prior knowledge about the actual PDs. Finally, a computationally tractable mixed-integer linear programming reformulation is derived for the original distributionally robust optimization (DRO) model. The proposed DRO-based DR strategy was performed on multiple buildings over a 24 h scheduling horizon, and comparative studies have validated the effectiveness of the proposed strategy for building energy systems in reducing the peak/valley ratio and decreasing operation costs.},
	year = {2024},
	eissn = {2075-5309}
}