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Direct Numerical Simulations (DNS) have been conducted to study the response of initially laminar spherical premixed methane–air flame kernels to successively higher turbulence intensities at five different equivalence ratios. The numerical experiments include a 16-species/25-step skeletal mechanism for methane oxidation and a multicomponent molecular transport model. Highly turbulent conditions (with integral Reynolds numbers up to 4513) have been accessed. The effect of turbulence on the physical properties of the flame, in particular its consumption speed Sc, which is an interesting measure of the turbulent flame speed ST has been investigated. Local quenching events are increasingly observed for highly turbulent conditions, particularly for lean mixtures. The obtained results qualitatively confirm the expected trend regarding correlations between u′/SL and the consumption speed: Sc first increases, roughly linearly, with u′/SL (low turbulence zone), then levels off (bending zone) before decreasing again (quenching limit) for too intense turbulence. For a fixed value of u′/SL, Sc/SL varies with the mixture equivalence ratio, showing that additional parameters should probably enter phenomenological expressions relating these two quantities.

The impact of Type 4 wind turbine generator (WTG)-based 10 million megawatt clusters (TMMC) on small-signal dynamics of power systems was investigated using the second-generation generic models (GM) of Western Electricity Coordinating Council (WECC). A WTG participation index (WTG PI) was defined to investigate the impact of Type 4 WTGs on the traditional interarea electromechanical modes. To identify the new electromechanical modes dominated by Type 4 WTGs, an identification factor (IF) was also defined using participation factors. Given the increasing penetration of Type 4 WTGs replacing synchronous generators, the changed law of damping and frequencies of the traditional interarea modes was also investigated using the WTG PI. One new type of electromechanical mode dominated by Type 4 WTGs was identified by using the defined IF. These new modes can be divided into two categories: strong-interaction modes and weak-interaction modes, depending on the number of participating WTGs. The strong-interaction modes dominated by Type 4 WTGs can result in widely spread power oscillations in power systems. The results of small-signal analysis were validated by time domain simulation and mode detection.

Suvilahti, a suburb of the city of Vaasa in western Finland, was the first area to use seabed sediment heat as the main source of heating for a high number of houses. Moreover, in the same area, a unique land uplift effect is ongoing. The aim of this paper is to solve the challenges and find opportunities caused by global warming by utilizing seabed sediment energy as a renewable heat source. Measurement data of water and air temperature were analyzed, and correlations were established for the sediment temperature data using Statistical Analysis System (SAS) Enterprise Guide 7.1. software. The analysis and provisional forecast based on the autoregression integrated moving average (ARIMA) model revealed that air and water temperatures show incremental increases through time, and that sediment temperature has positive correlations with water temperature with a 2-month lag. Therefore, sediment heat energy is also expected to increase in the future. Factor analysis validations show that the data have a normal cluster and no particular outliers. This study concludes that sediment heat energy can be considered in prominent renewable production, transforming climate change into a useful solution, at least in summertime.

There are many real-world applications that require high-performance mobile computing systems for onboard, real-time processing of gathered data due to latency, reliability, security, or other application constraints. Unfortunately, most existing high-performance mobile computing systems require a prohibitively high power consumption in the face of the limited power available from the batteries typically used in these applications. For high-performance mobile computing to be practical, alternative hardware designs are needed to increase the computing performance while minimizing the required power consumption. This article surveys the state-of-the-art in high-efficiency, high-performance onboard mobile computing, focusing on the latest developments. It was found that more research is needed to design high-performance mobile computing systems while minimizing the required power consumption to meet the needs of these applications.

Electricity imbalance pricing provides the ultimate incentive for generators and suppliers to contract with one another ahead of time and deliver against their obligations. As delivery time approaches, traders must judge whether to trade-out a position or settle it in the balancing market at the as-yet-unknown imbalance price. Forecasting the imbalance price (and related volumes) is therefore a necessity in short-term markets. However, this topic has received surprisingly little attention in the academic literature despite clear need by practitioners. Furthermore, the emergence of algorithmic trading demands automated forecasting and decision-making, with those best able to extract predictive information from available data gaining a competitive advantage. Here we present the case for developing imbalance price forecasting methods and provide motivating examples from the Great Britain’s balancing market, demonstrating forecast skill and value.

Fracture conductivity decline is a concern in the Tuscaloosa Marine Shale (TMS) wells due to the high content of clay in the shale. An analytical well productivity model was developed in this study considering the pressure-dependent conductivity of hydraulic fractures. The log-log diagnostic approach was used to identify the boundary-dominated flow regime rather than the linear flow regime. Case studies of seven TMS wells indicated that the proposed model allows approximation of the field data with good accuracy. Production data analyses with the model revealed that the pressure-dependent fracture conductivity in the TMS in the Mississippi section declines following a logarithmic mode, with dimensionless coefficient χ varying between 0.116 and 0.130. The pressure-dependent decline of fracture conductivity in the transient flow period is more significant than that in the boundary-dominated flow period.

In China, the power sector is currently the largest carbon emitter and the transportation sector is the fastest-growing carbon emitter. This paper proposes a model of solar-powered charging stations for electric vehicles to mitigate problems encountered in China’s renewable energy utilization processes and to cope with the increasing power demand by electric vehicles for the near future. This study applies the proposed model to Shenzhen City to verify its technical and economic feasibility. Modeling results showed that the total net present value of a photovoltaic power charging station that meets the daily electricity demand of 4500 kWh is $3,579,236 and that the cost of energy of the combined energy system is $0.098/kWh. In addition, the photovoltaic powered electric vehicle model has pollutant reduction potentials of 99.8%, 99.7% and 100% for carbon dioxide, sulfur dioxide, and nitrogen oxides, respectively, compared with a traditional gasoline-fueled car. Sensitivity analysis results indicated that interest rate has a relatively strong influence on COE (Cost of Energy). An increase in the interest rate from 0% to 6% increases COE from $0.027/kWh to $0.097/kWh. This analysis also suggests that carbon pricing promotes renewable energy only when the price of carbon is above $20/t.