The Influence of Hydrogen on Vaporization, Mixture Formation and Combustion of Diesel Fuel at an Automotive Diesel Engine

Hydrogen can be a viable alternative fuel for modern diesel engines, offering benefits on efficiency and performance improvement. The paper analyses the results of a thermodynamic model developed by authors in order to study the influence of Hydrogen addition on a process like vaporization, mixture forming, and combustion at the level of diesel fuel droplets. The bi-zonal model is applied for a dual-fueled diesel engine K9K type designed by Renault for automotives. For the engine operating regime of 2000 rpm speed and 55% engine load, the diesel fuel is partially substituted by Hydrogen in energetic percents of 6.76%, 13.39%, and 20.97%, the engine power being maintained at the same level comparative to classic fueling. At Hydrogen addition, the diesel fuel jets atomization and diesel fuel droplets vaporization are accelerated, the speed of formation of the mixture being increased. Comparative to classic fueling, the use of Hydrogen leads to diesel droplets combustion intensification, with a shortened autoignition delay, reduction of combustion duration, and increase of flame radius.

Inverse modeling of zonal transmission network

Presently, many ideas have been proposed for constructing zonal models of the European transmission network. Most of them are based on transmission network reduction and bus clustering, which requires the ex-ante knowledge on the details (impedance, interconnections, etc.) of the network’s elements. Generally, the information is not publicly disclosed. This paper describes a method for serving the purpose, which only requires the ex-post (i.e., published) inter-zonal power flow data as input. It performs inverse modeling on the ex-post data to reveal the virtual reactance of the interconnectors in the zonal model. The reactance values are then used for computing the zonal Power Transfer Distribution Factors (PTDFs) of the model, which is the best representation of the loop flows. A large number of such zonal PTDFs could exist in one zonal model because of its dependency on the Generation Shift Keys (GSKs). Theoretically, the GSKs could exist as an infinite set of unique combinations but only a finite number of them applied in real system operations. As a solution, the authors propose a heuristic approach for grouping the ex-post power flow cases into clusters, and find the zonal PTDF for each of them; in order to effectively reduce the domain of the zonal PTDFs and enhance the tractability of the solution. The identified zonal PTDFs meaningfully represent the zonal model. Additionally, they can also be used for studying the best and worst case scenarios of cross-border security-constrained economic dispatch.

One-Dimensional Zonal Model for the Unsteady Heat Transfer Analysis in an Open Volumetric Air Receiver

The open volumetric air receiver (OVAR)-based central solar thermal systems provide air at a temperature > 1000 K. Such a receiver is comprised of porous absorbers, which are exposed to a high heat-flux > 800 Suns (1 Sun = 1 kW/m2). A reliable assessment of heat transfer in an OVAR is necessary to operate such a receiver under transient conditions. Based on a literature review, the need for developing a comprehensive, unsteady, heat transfer model is realized. In this paper, a seven-equations based, one-dimensional, zonal model is deduced. This includes heat transfer in porous absorber, primary-air, return-air, receiver casing, and their detailed interaction. The zonal model is validated with an inhouse experiment showing its predictive capability, for unsteady and steady conditions, within the reported uncertainty of ±7%. The validated model is used for investigating the effect of operating conditions and absorber geometry on the thermal performance of an absorber. Some of the salient observations are (a) the maximum absorber porosity of 70–90% may be preferred for non-volumetric and volumetric-heating conditions, (b) the minimum air-return ratio should be 0.7, and (c) the smallest gap to absorber-length ratio of 0.2 should suffice. Finally, suggestions are provided for extending the model.

A data-driven approach for constructing a zonal network model for long-term dispatch planning

The most important aspect of the planning of power generation dispatch is its complementary relationship with the power flows on the interconnectors of the transmission network. A plan could become invalid if the power flow created violates the transfer limit of any interconnectors. The long-term dispatch planning is more affected by this because of the relative difficulty in predicting the state of the transmission network in advance. It is generally planned in a trade-based manner, without a means to explicitly compute the power flows. Deviations in the plans are then corrected near the time of dispatch, in the expense of opportunity costs. In Europe, the flow-based market coupling is proposed in the Central Western Europe, which is an effective means for modeling the inter-zonal power flows and transfer capacity allocations. However, its usefulness for long-term planning is still limited. Especially, the Power Transfer Distribution Factors (PTDFs) of its model (key parameter for integrating power flow in dispatch planning) is stochastic and unpredictable. This paper introduces a data-driven approach to construct a zonal model for closing the gap between the long-term and the actual dispatch plan. It is able to reconstruct all zonal PTDFs existed in the system, by inverse modeling the ex-post power flow data. The paper as well presented the validity of decomposing a large zonal model into substantially smaller sub-problems, and the existence of clusters of ex-post power flow cases which share the same zonal PTDFs. These features have greatly simplified the implementation of the method.

ANTHROPOLOGY OF ZONALITY: NATURE AND CULTURE IN THE SPATIAL DIFFERENTIATION OF HUMAN ACTIVITY

The article is theoretical in nature and does not cover any particular region; however, the phenomenon of zonality is of particular relevance to the northern part of Siberia. The article draws a fundamental analogy be-tween the classical theoretical zonal model of Thünen and zoning models of various regions of the world (South-east Asia, Africa and the Khanty-Mansi Autonomous Okrug — Ugra in Russia). Zonality is usually perceived as a natural phenomenon — regularly and naturally alternating natural zones (tundras, taigas, steppes, etc.). Under the influence of changing natural conditions, human activity also changes to one degree or another. However, there are many cultural and human factors under whose influence a similar picture of regularly and naturally dif-ferentiated zones emerges. For example, it could be the centre and periphery, previously and newly developed zones, etc. These zones are differentiated not only from an economic point of view but also as complex phenom-ena including holistic, imperious, behavioural and other aspects. The article is aimed at expanding the standard use of the concept ‘zonality’, reconsider zoning as not only and not so much a natural phenomenon as a broad theoretical approach effective for comparative studies in anthropology, economic and social geography, history, economics, as well as other disciplines. The technique used in this study consists in the identification of similar features when modelling the geographical differentiation of processes of different nature. As a result, the author proposes a general conceptualisation framework for the concept ‘zonality’ as a universal phenomenon of spatially differentiated conditions for activities and the understanding of these conditions by people. The phenomenon of zonality can be observed when the geographical differentiation of any studied process is determined by a regular difference in a certain basic condition from place to place, which has a definitive effect on the development of the studied process. In the case of natural zonality, this is the distribution of solar radiation; in the case of economic zoning, cost of transportation often serves as the differentiating factor; in the case of areas of new development, the differentiating factor is the age of development.