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• Agent-Based Model to emulate real-world performance of microgrid with P2P trading. • Holistic simulation of economic, technical, and ecological metrics. • Validation of Model with urban area of medium-sized German city. • Comparison of microgrid metrics before and during the European energy crisis. • Conclusions for research, practice, and energy policy. The shift towards renewable energy sources (RES) in energy systems is becoming increasingly important. Residential energy generation and storage assets, smart home energy management systems, and peer-to-peer (P2P) electricity trading in microgrids can help integrate and balance decentralized renewable electricity supply with an increasingly electrified power, heat, and transport demand, reducing costs and CO 2 emissions. However, these microgrids are difficult to model because they consist of autonomous and interacting entities, leading to emergent phenomena and a high degree of complexity. Agent-based modeling is an established technique to simulate the complexity of microgrids. However, the existing literature still lacks real-world implementation studies and, as a first step, models capable of validating the existing results with real-world data. To this end, we present an agent-based model and analyze the corresponding microgrid performance with real-world data. The model quantifies economic, technical, and environmental metrics to simulate microgrid performance holistically and, in line with state-of-the-art research, consists of self-interested, autonomous agents with specific load profiles, RES generation, and demand-response potential. The model can simulate a P2P marketplace where electricity is traded between agents. In the second part of the paper, we validate the model with data from a medium-sized German city. In this case study, we also compare microgrid performance in 2022, during the energy market crisis in Europe, with historical data from 2019 to assess the effects of energy market shocks. Our results show how microgrids with P2P trading can reduce electricity costs and CO 2 emissions. However, our trading mechanism illustrates that the benefits of energy-community trading are almost exclusively shared among prosumers, highlighting the need to consider distributional issues when implementing P2P trading. [ABSTRACT FROM AUTHOR]

This paper examines the risk transmissions across the green economy indices of three major regions which include US, Europe and Asia. The econometric analyses are conducted using DCC-GARCH and TVP-VAR connectedness approach to evaluate potential spillover effects within the context of oil and gold. Results indicate that green economy indices of US-Europe exhibit the greatest time-varying correlations among the three pairs during much of 2010–2022 consistent with that of the general equity market. However, co-movements during the COVID-19 pandemic period seem to display a change in pattern for green economy indices. The strength of the co-movements between the US and Europe displayed a declining trend, while that between US and Asia was strengthened, suggesting greater interdependence between these two markets. TVP-VAR connectedness analysis revealed that US and Europe dominate the transmission of the shocks across the years in the green economy, similar to that of the equity markets. However, during the pandemic a pronounced shift occurred in green economies when considering the risk transmissions within the context of commodities: oil and gold. While Asian green economy index was persistently a receiver of risk transmission from oil unlike the other two regions, since pandemic, oil displayed an asymmetric effect and has become the net transmitter of risk in negative returns of the green economies of US and Europe. This may reflect the diversion in environmental policies of the two regions in the recent past, and point to the dominance of energy sector in the green economy. These findings have substantial implications for the development of green economy policies and from an investment perspective. [ABSTRACT FROM AUTHOR]

This paper examines the risk transmissions across the green economy indices of three major regions which include US, Europe and Asia. The econometric analyses are conducted using DCC-GARCH and TVP-VAR connectedness approach to evaluate potential spillover effects within the context of oil and gold. Results indicate that green economy indices of US-Europe exhibit the greatest time-varying correlations among the three pairs during much of 2010–2022 consistent with that of the general equity market. However, co-movements during the COVID-19 pandemic period seem to display a change in pattern for green economy indices. The strength of the co-movements between the US and Europe displayed a declining trend, while that between US and Asia was strengthened, suggesting greater interdependence between these two markets. TVP-VAR connectedness analysis revealed that US and Europe dominate the transmission of the shocks across the years in the green economy, similar to that of the equity markets. However, during the pandemic a pronounced shift occurred in green economies when considering the risk transmissions within the context of commodities: oil and gold. While Asian green economy index was persistently a receiver of risk transmission from oil unlike the other two regions, since pandemic, oil displayed an asymmetric effect and has become the net transmitter of risk in negative returns of the green economies of US and Europe. This may reflect the diversion in environmental policies of the two regions in the recent past, and point to the dominance of energy sector in the green economy. These findings have substantial implications for the development of green economy policies and from an investment perspective. [ABSTRACT FROM AUTHOR]