Abstract

The present study focuses on the heat integration of process streams for a methanol-reforming proton exchange membrane fuel cell (PEMFC). A Big-M method-based heat integration-PEMFC-heat exchanger network (HEN) synthesis model is established in the GAMS environment. The optimal operating condition and heat exchange topology structure of the PEMFC system integrated with methanol-reforming are obtained through the developed optimization method. Comparative analysis on two different energy utilization configurations is conducted. The PEMFC system with heat integration performs the reduction of 42.62% in operating cost.

Abstract

Ceria has absorbed extensive interests in mediating low-temperature (LT) selective catalytic reduction (SCR) of NOx due to its abundance of surface oxygen species and consequential salient redox property. The mechanistic interpretations of how such redox property contributes to its LT-SCR activity, however, still remain debated. Here, we use a model WO3-promoted CeO2 catalyst (WO3/CeO2), known as preeminent in LT-SCR reactions, and combine kinetic, characteristic and in situ spectroscopic experiments with theoretical treatments to reveal the mechanistic connections between NO oxidative activation and LT-SCR turnovers. We show that NO oxidation to NO2 is both kinetically (reaction rates: 8~40-fold lower than LT-SCR at 423~523 K) and thermodynamically (reaction free energy at 473 K: ~20 kJ mol-1 higher than NO to nitrites) less favorable than NO activation to nitrite intermediates, thus suggesting a relevance of the latter route, rather than NO oxidation to NO2 and subsequent occurrence of fast SCR, to WO3/CeO2-catalyzed LT-SCR reaction cascade.

Abstract

Flue gas released by the traditional coal-fired power plant can be converted into electricity by means of thermoelectric generation system (TGS). The self-supply power system (SSPS) utilizes this electric power to safeguard the power plant and, meanwhile, increase the energy efficiency. An inverter interfaces TGS and working loads to provide a stable regulation of frequency and voltage based on virtual synchronous generator (VSG). The characteristics of the synchronous generators is emulated by the power controllers. Currently, transient stability of the power loop control is still a critical issue in the condition of remarkable changes of the power angle and the grid voltage. In this paper, the frontend power control is enhanced for the frequency regulation with variable moment of inertia and damping coefficient. The simulation and experiment results verify that the proposed method produces enhanced dynamic performance.

Abstract

This paper mainly investigates the effect of the premixing of hydrogen and gasoline (PHG) on the flow and combustion characteristics of the X-type rotary engine (XRE). The three-dimensional numerical simulation model is firstly established based on CFD software. Then, the flow fields and combustion performances of XRE under 1%, 3% and 5% energy fractions of hydrogen-blended (EFHB) are compared and analyzed. The results show that the in-cylinder mean turbulent kinetic energy (TKE) and vorticity present three peaks at the beginning, middle and end stage of the intake process, respectively. Meanwhile, the peak in the middle stage is the largest and steepest, indicating that the in-cylinder flow field is fully mixing air and fuel at this stage. The PHG can produce more OH, O and H radicals, and accelerate the combustion process. Furthermore, the PHG can increase the combustion temperature. In particular, the peak of the in-cylinder mean temperature is increased by 6.4% when the EFHB is 5%. The hydrogen can broaden the combustion area to both sides of the combustion chamber, and help to solve the problem of incomplete combustion in the slit of the combustion chamber of XRE.

Abstract

This paper contains a holistic approach to carbon
reduction within the household, assessing multiple areas
of consumption to identify sectors critical to lowering
emissions and solutions that are more effective when
combined. It finds that emissions from food and
transportation overshadow results from heat and
electricity and that lowering emissions through lifestyle
changes can be as effective as existing engineering
solutions.

Abstract

Agricultural trade works as an important node in transnational trade. As various resources and emissions inextricably interrelate and interact with each other, exploring the flow becomes rather complicated. This article integrates multi-regional input-output (MRIO) and the nexus intensity to investigate the energy-water-carbon nexus correlated with agricultural products at the transnational level through the entire supply and demand chain. The combination is aimed at bettering bilateral policy formulation and optimal resource allocation in the context of ambiguity in the flow of resources and emissions correlated with agriculture. Consequently, this article takes RCEP as a case study and the results show that:(1) China is consistently the largest producer and demander of energy-water-carbon flows correlated with agricultural products. (2) When it comes to the external dependence on resources correlated with agriculture, the majority of countries in RCEP rely on a higher degree of energy and carbon than water. On average, Singapore shows the highest external dependence while Indonesia displays the lowest. (3) The self-sufficiency, production, and consumption of agricultural trade-related resources and emissions among RCEP countries present different nexus intensities due to discrepant policies and natural endowments.

Abstract

The focus on the reduction of emissions and the transition away from fossil fuels has been growing, especially in recent years. This is of the utmost importance on islands where the impacts of climate change are most threatening and where the main source of energy has been found to come from the burning of fossil fuels. Thus, the feasibility of implementing a distributed renewable energy system has been investigated for a set of islands off the coast of the UK. Three systems and their technical and economic feasibility were analysed using a software designed in Excel with one system having net zero emissions.

Abstract

The rapidly increasing penetration of distributed generation (DG) such as photovoltaic (PV) has brought various impacts on distribution network (DN), such as voltage rise and power decline. Considering that, the hosting capacity evaluation of PV in DN is essential to provide useful references for PV development. Meanwhile, the mobile energy storage system (MESS) has proven to have the potential of improving the HC for its ability to provide various grid support services. This paper proposes a multi-scenario-based model to evaluate the hosting capacity of distribuited considering the impacts of MESS. In the proposed model, the transit features of MESS are considered. Besides, the scenarios are generated according to the uncertainties associated with solar irradiance and load demand. The effectiveness of the proposed method is demonstrated using a modified IEEE 33-bus distribution system.

Abstract

This paper presents a pipeline for creating digital twins of building energy systems, which is shared as an open test-environment for controller benchmarking. The digital twin is calibrated based on an extensive dataset including a wide variety of data with fine temporal resolutions. The comprehensive list of controllable variables, the temporal resolution of measurements, and the real-time capabilities of the digital twin distinguish this work from the existing test environments. A case study is also provided to exemplify the use of this open environment for benchmarking the performance of building automation and control systems.

Abstract

Clean energy production is often accompanied by battery storage systems that undergo complex degradation processes. Incremental capacity and differential voltage peaks are traditionally used for degradation analysis, but are sensitive to current rate, deep degradation, and battery chemistry. To enhance the robustness of degradation feature tracking, this study proposes a conditional temporal convolutional autoencoder. The unsupervised nature of the proposed method enables the extraction of degradation related features from data that have no peak features. Results show that the proposed method can extract features and reconstruct battery cycling curves with high fidelity. Furthermore, the extracted features are highly correlated with peak locations of incremental capacity and differential voltage curves. The extracted features also have less noise and no missing values compared to the peak locations. Prediction of peak locations from single encoding achieves mean absolute errors of 0.019 V and 2.4% state-of-charge. The proposed method is therefore potentially useful for battery degradation analysis and health assessment.