Solid waste mixtures combustion in a circulating fluidized Bed: emission properties of NOx, Dioxin, and Heavy Metals

To efficiently and environment friendly combust the domestic garbage, sludge, and swill waste fuels, five different fuels are prepared by mixing the waste fuels together with coal, and grass biomass at different mixing ratios, and finally those fuels were combusted in a circulating fluidized bed (CFB) reactor. The emission performances of NOx, dioxin, and heavy metal during the combustion tests are studied. The results showed that a stable furnace temperature can be reached at approximately 850 °C when combusting all studied mixed fuels, benefiting the thermal processes of sludge and domestic garbage and thus realizing the purpose of waste-to-fuel. In addition, the dioxin emissions are much lower than the emission standards, and NOx emissions could be reduced significantly by adjusting the ratio of waste fuels. However, the emissions of mercury, lead, and the combinations of chromium, tin, antimony, cupper and manganese components all exceeded the pollution control standard for hazardous wastes incineration, a further technology is required for heavy metal reductions to achieve the emission standards

5G network deployment and the associated energy consumption in the UK: A complex systems’ exploration

Investing in the communication infrastructure transition requires significant scientific consideration of challenges, prioritisation, risks and uncertainties. To address these challenges, a bottom-up approach was used to demonstrate the future of wireless network transmission and deployment. This study developed an agent-based model to explore the future deployment of non-standalone 5G networks, synthesizing multi-dimensional data visualization. In particular, this research took the UK as an example to investigate the spatiotemporal dynamic characteristics of 5G evolution, and further analysed the energy consumption and carbon footprint of 5G networks, as well as the consequent change in the operating expenses pattern. The simulation results show that 700 MHz and 26 GHz will play an important role in 5G deployment in the UK, which allow base stations to meet short-term and long-term data traffic demands respectively. Furthermore, due to the geopolitical restrictions and embargos, telecommunications may face additional costs of £0.63bn to £1.19bn when deploying 5G radio access networks. Network densification may cause some environmental and economic problems. Take a medium demand scenario as an example, it is found that the electricity consumed by the 5G radio access network will account for more than 2.1% of the total electricity generation, and indirectly lead to 990,404 tonnes carbon emissions in 2030

Applications of Agent-Based Methods in Multi-Energy Systems—A Systematic Literature Review

The need for a greener and more sustainable energy system evokes a need for more extensive energy system transition research. The penetration of distributed energy resources and Internet of Things technologies facilitate energy system transition towards the next generation of energy system concepts. The next generation of energy system concepts include “integrated energy system”, “multi-energy system”, or “smart energy system”. These concepts reveal that future energy systems can integrate multiple energy carriers with autonomous intelligent decision making. There are noticeable trends in using the agent-based method in research of energy systems, including multi-energy system transition simulation with agent-based modeling (ABM) and multi-energy system management with multi-agent system (MAS) modeling. The need for a comprehensive review of the applications of the agent-based method motivates this review article. Thus, this article aims to systematically review the ABM and MAS applications in multi-energy systems with publications from 2007 to the end of 2021. The articles were sorted into MAS and ABM applications based on the details of agent implementations. MAS application papers in building energy systems, district energy systems, and regional energy systems are reviewed with regard to energy carriers, agent control architecture, optimization algorithms, and agent development environments. ABM application papers in behavior simulation and policy-making are reviewed with regard to the agent decision-making details and model objectives. In addition, the potential future research directions in reinforcement learning implementation and agent control synchronization are highlighted. The review shows that the agent-based method has great potential to contribute to energy transition studies with its plug-and-play ability and distributed decision-making process