Abstract

This study developed a star-shaped 3,6-Bis(5-(4,4′- bis(3-azidopropyl)-[1,1′:3′,1′-terphenyl]-5′-yl)- thien-2-yl)-2,5-bis(2-ethylhexyl)pyrrolo[3,4-c]pyrrole1,4(2H,5H)-dione (DPPTPTA) additive in combination with electrospun carbon nano fibers integrated bimetallic copper-cobalt phosphide (DPPTPTA/CuCoP/CNF) as an interface layer for dyesensitized solar cells (DSSCs). This interface layer is different from conventional blend films. As a multifunctional additive, DPPTPTA provides ladder-like energy levels for efficient charge separation, changing the morphology of the interface layer and improving performance. The CuCoP/CNF has high electrocatalytic activity and enhanced ionic conductivity. The interface layer ensures efficient charge transfer at the electrode/electrolyte interface with lower electron recombination rate in the DSSC, and it is expected that the photoelectric conversion efficiency (η) of the DSSC can be greatly improved under the condition of 1 sun (AM 1.5G, 100 mW cm-2 ), and the local boundary is constructed through the interface layer. It ensures longterm thermal stability; and it is expected to have higher η under indoor light condition test, which is one of the most promising devices for renewable energy generation.

Abstract

The energy consumption of cities is an important carbon emission source, so it is significant to develop a high efficiency energy system for the whole city. This study proposes an optimization process of planning and operation for low-carbon city energy system. The process is divided into four steps：estimation of city energy demand, optimization of energy technology selection and operation, minimum energy station number optimization, and site and network optimization. Based on these, most parts of the flow are tested by the data from a local government, showing its practicability.

Abstract

The holistic optimization of district cooling systems is a computationally intensive undertaking, owing to the sheer number of conflicting decision variables and nonconvex nature of the problem. This is the primary reason which inhibits the real-time deployment of optimization algorithms for the operations of district cooling systems. To overcome this challenge, we adopt a model-based, decomposed approach involving the concurrent use of reinforcement learning and mixed integer linear program to holistically optimize the thermal and physical interactions while still capturing the tight coupling between the components of the system. Resolution speed and solution accuracy are paramount for a realtime optimization algorithm thus, the critical advantage of the proposed approach is two-fold – the mixed integer linear program drastically reduces the action space of the reinforcement learning problem, promoting accuracy and when trained, the agent neural network can then rapidly determine the optimal values of the remaining actions, improving resolution speed. The current work makes the two ensuing vital contributions: (1) we introduced a decomposed optimization approach with resolution speeds which are compatible with real-time deployment, (2) through the application on a real test-case, we compare both the resolution time and solution quality against an approach used in our previous work, which deployed the genetic algorithm instead of a reinforcement learner. Results indicate that the impact on solution quality is below 7.52%, thereby, validating the feasibility of the proposed approach.

Abstract

The double transmission double expansion approach (DTDE) of Compressed Air System (CAS) is expanded in the work. The influence of such technology on the performance characteristics of a pneumatic machine is presented. Examples of recoverable air capacity are shown.

Abstract

Due to the strengthening of the coupling between the power system and the natural gas system, this paper aims to study the impact of natural gas system infrastructure failure on the power supply of the power system. A quasi-dynamic model adapted to the different time scales of the coupled natural gas and electricity system is established. The effectiveness of the calculation method is demonstrated by comparison with the simulation results of SYNERGI software. The case study shows that if the power system can know the failure in the natural gas system in advance, there is some buffer time to take control measures.

Abstract

This paper focuses on a small-scale solar-driven system for power generation in remote, off-grid, rural areas. In particular, the research investigates a smallscale thermal Brayton system suitable for power output < 10 kW. The study addressed the need of thermal energy storage integration into the main process to extend operability and electricity generation when solar irradiance is lower than the design value or insufficient to drive the process. The work combines both experimental and numerical methods to investigate integration of TES and four different types of TES materials.

Abstract

Building & transportation have been the major sectors for the energy consumption of modern city. The recent development of distributed energy resources is attracting extensive attention from city designers, primarily driven by the transition need towards a future smart city. Key challenges exist from planning, design, construction, build, operation and service due to the barrier in regulation and engineering practice between building, transportation and energy industry as well information technology & recent rising industry of the Internet of things (IoT). This paper proposed a novel energy system infrastructure to create a synergy to accommodate the diverse temporal and spatial features cross building, transportation, energy and information domain. In addition, this concept is carrying out in an official area for 2022 Beijing Winter Olympic game and is also discussing for the implement in NEOM, Saudi Arabia. This paper mainly discusses the latest progress of the demonstration for the 2022 Winter Olympic.

Abstract

A 2D filter is proposed for battery incremental capacity curve filtering in a cyclic aging test. The filter works in two directions, namely, from time to time and from batch (cycle) to batch. In details, a simple low-pass filter is applied in the batch direction, and a bias-corrected Gaussian filter is applied in the time direction. Experimental results show that the root-meansquare-error of the proposed method is 20% lower than the neural-network-based benchmarking algorithm. Over-fitting and under-fitting could also be resolved.

Abstract

Iron and steel industry (ISI) is an important pollutant emission source in China. This research estimated the energy consumption, CO2, air pollutants and heavy metal emissions from ISI in different regions of China based on the different resource endowments and development strategies. AIM/Enduse model was applied to analyze the application ratio of 16 advanced technologies in 9 scenarios. Different EAF ratio and emission factor of electricity were estimated in different scenarios. Results show that although the crude steel demand will decrease in the future, the application ratio of advanced technologies will be increases of varying degrees. EAF will keep increasing to the maximum limitation in CM2 and CM4 scenario. Correspondingly, electricity consumption will increase 9.7% and 34.1% in these two scenarios comparing with BaU in 2050, while, coal used for coking will decrease. Higher EAF ratio and low electricity emission factor will decrease CO2 and air pollutants emission. However, more Hg, Cd and Cr will be emitted with the increasing EAF ratio.

Abstract

For a wider utilization of model-based control e.g. for energy management systems, their installation and maintenance costs must be reduced. A possible solution is the automated identification of the different asset model parameters. However, robust model validation methods are necessary in order to guarantee an adequate performance in practice without additional manual review. This paper presents a model validation method for energy conversion units based on an uncertainty and consistency analysis of the extrapolated energy efficiency ratio (EER). First, the approach is described in detail. Afterwards, the advantages of the concept over validation methods based on model accuracy are illustrated with a case study of a compression chiller. Only the presented approach ensured a robust validation of the chiller models.