TY - JOUR AU - Bachankar, Shital AU - Malavekar, Dhanaji AU - Lokhande, Vaibhav AU - Ji, Taeksoo TI - Empowering supercapacitors: Strategic B-site modulations of transition metal atoms in perovskite oxide based electrodes JF - JOURNAL OF ALLOYS AND COMPOUNDS J2 - J ALLOY COMPD VL - 1003 PY - 2024 PG - 26 SN - 0925-8388 DO - 10.1016/j.jallcom.2024.175708 UR - https://m2.mtmt.hu/api/publication/35154535 ID - 35154535 LA - English DB - MTMT ER - TY - JOUR AU - Gao, Ding AU - Zhi, Yuan AU - Rong, Xing AU - Yang, Xudong TI - Mismatch analysis of rooftop photovoltaics supply and farmhouse load: Data dimensionality reduction and explicable load pattern mining via hybrid deep learning JF - APPLIED ENERGY J2 - APPL ENERG VL - 377 PY - 2024 PG - 19 SN - 0306-2619 DO - 10.1016/j.apenergy.2024.124520 UR - https://m2.mtmt.hu/api/publication/35586420 ID - 35586420 N1 - Funding Agency and Grant Number: Chinese Academy of Engineering [2023-XBZD-07]; Energy Foundation [G-2310-35184] Funding text: This study was supported by the Chinese Academy of Engineering (2023-XBZD-07) , and Energy Foundation (G-2310-35184). Part number: B AB - 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. LA - English DB - MTMT ER - TY - THES AU - Jonathan, Ullmark TI - Short- and long-term variability in future electricity systems PY - 2024 UR - https://m2.mtmt.hu/api/publication/35071337 ID - 35071337 LA - English DB - MTMT ER - TY - JOUR AU - Nica, Ionuț AU - Georgescu, Irina AU - Chiriță, Nora TI - Simulation and Modelling as Catalysts for Renewable Energy: A Bibliometric Analysis of Global Research Trends JF - ENERGIES J2 - ENERGIES VL - 17 PY - 2024 IS - 13 SN - 1996-1073 DO - 10.3390/en17133090 UR - https://m2.mtmt.hu/api/publication/35071476 ID - 35071476 AB - 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. LA - English DB - MTMT ER - TY - CHAP AU - Prasad, Dharmbir AU - Singh, Rudra Pratap AU - Rizwan, Ariba AU - Roy, Ranadip AU - Verma, Shubham ED - Naoui, Mohamed ED - Ben Khalifa, Romdhane ED - Sbita, Lassaad TI - Modelling of Grid Management Strategy for Handling Intermittent Renewable Energy Generation in Island Regions T2 - Modeling, Analysis, and Control of Smart Energy Systems PB - IGI Global SN - 9798369330005 T3 - Advances in Chemical and Materials Engineering, ISSN 2327-5448 PY - 2024 SP - 194 EP - 222 PG - 29 DO - 10.4018/979-8-3693-2999-3.ch011 UR - https://m2.mtmt.hu/api/publication/35166137 ID - 35166137 AB - 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. LA - English DB - MTMT ER - TY - JOUR AU - Shi, Xincong AU - Wang, Xinrui AU - Ji, Yuze AU - Liu, Zhiliang AU - Han, Weiheng TI - Distributionally Robust Demand Response for Heterogeneous Buildings with Rooftop Renewables under Cold Climates JF - BUILDINGS J2 - BUILDINGS-BASEL VL - 14 PY - 2024 IS - 6 PG - 20 SN - 2075-5309 DO - 10.3390/buildings14061530 UR - https://m2.mtmt.hu/api/publication/34885973 ID - 34885973 AB - 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. LA - English DB - MTMT ER -