• Energy Research
• 2025-2025close
• Restricted close
• Open Source close
• Embargo close
• other engineering and technologies close

The conventional approach for controlling the supply temperature in collective space heating networks relies on a predefined heating curve determined by outdoor temperature and heat emitter type. This prioritises thermal comfort but lacks energetic and financial optimisation. This research proposes an adaptive supply temperature control in well-insulated dwellings, responsive to diverse environmental parameters. The approach considers variable electricity prices and accommodates different indoor temperature set points in dwellings. The study evaluates the effectiveness of two Deep Reinforcement Learning (DRL) algorithms, i.e., Proximal Policy Optimisation (PPO) and Deep Q-Network (DQN), across various scenarios. Results reveal that DQN excels in collective space heating systems with underfloor heating in each dwelling, while PPO proves superior for radiator-based systems. Both outperform the traditional heating curve, achieving up to 13.77% (DQN) and 16.15% (PPO) cost reduction while guaranteeing thermal comfort. Additionally, the research highlights the capability of DRL-based methods to dynamically set the supply temperature based on a cloud of set points, showcasing adaptability to diverse environmental factors and addressing the growing significance of indoor heat gains in well-insulated dwellings. This innovative approach holds promise for more efficient and environmentally conscious heating strategies within collective space heating networks.

The methane released from the coal combines with the air to form a very dangerous explosive mixture, which will be aggravated by the combustible gases of CO and H2 produced from the coal smoldering in coal mine. In this work, the effect of binary CO-H2 mixtures on methane explosion limits is investigated, and the inhibitory effect of N2 dilution on mixed combustible gases is analyzed via experiments and simulations subsequently. The methane explosion limits under different operating conditions are studied using a standard 20-L spherical chamber. The addition of the binary gas of CO-H2 mixtures exhibit a reduction for LEL and UEL of methane explosions, and remarkably enhance methane explosion risk. Moreover, the addition of binary gas mixture leads to a larger expansion range of the explosion triangle, compared to single CO conditions. In the simulations, the sensitivity of dominant elementary reactions on the H, O, and OH free radicals are analyzed based on the GRI mech 3.0 mechanisms. The inerting effect of N2 in CH4/CO/H2 component system is manifested in the combustion reaction kinetics of R53, R98, and R158, showing a significant inhibitory effect on the generation of these radicals during explosive process. The research results are helpful to understand the hazards of methane explosion in the coal fire area, and have certain guidance for the treatment of methane explosion in coal mine.

With the recent announcement of a joint goal among federal agencies to deploy 30 GW of offshore wind capacity by 2030 and the target for the Bureau of Ocean Energy Management (BOEM) to approve the Construction and Operations Plans of at least 16 offshore wind farms by 2025, the US offshore wind industry appears to be on the cusp of a major expansion. However, a literature review of the history and current state of the US offshore wind industry indicates that resource constraints within the BOEM and obstacles posed by the complex regulatory process could prevent the industry from reaching its full potential. A critical analysis was conducted on information and data collected from primary and secondary sources to propose strategies for mitigating and avoiding this regulatory turbulence. This paper concludes that BOEM must increase its bandwidth and accelerate the rate of offshore wind project review and approval by pursuing resource augmentation measures and opportunities to introduce efficiencies into its regulatory approach.