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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.

This study presents a comprehensive three-dimensional Computational Fluid Dynamics (CFD) analysis of the pre-cooling process of a Type B LNG tank using various refrigerants, including liquid nitrogen (LN), nitrogen gas (NG), liquefied natural gas (LNG), boil-off gas (BOG), and their combinations. The simulation model accounts for phase change (through the mixture multiphase model), convective heat transfer, and conjugate heat exchange between the fluid and the tank structure. The results indicate that liquid nitrogen is the most efficient refrigerant, achieving the highest cooling rate through both latent and sensible heat. LNG also demonstrated a relatively high cooling rate, 79% of that of liquid nitrogen. Gas-only pre-cooling schemes relying solely on sensible heat exhibited slower cooling rates, with BOG achieved 79.4% of the cooling rate of NG. Mixed refrigerants such as NG + LN and BOG + LNG can achieve comparable, while slightly slower, cooling than the pure liquid refrigerants, outperforming gas-only strategies. A further assessment of the heat transfer coefficient suggests the mixed cooling schemes have almost identical heat transfer coefficient on the inner tank surface to the liquid cooling scheme, over 5% higher than the gas refrigerants. The study also highlighted the uneven temperature distribution within the tank due to the bulkhead’s blockage effect, which can induce significant thermal stress and potentially compromise structural integrity. Mixed schemes exhibit thermal gradients higher than those of gas schemes but lower than those of liquid schemes, while achieving cooling speeds comparable to liquid schemes if the inlet velocity of the refrigerants is properly configured. These findings offer valuable insights for developing safer and more efficient pre-cooling procedures for Type B LNG tanks and similar cryogenic storage tanks.

The two-stroke engine is a common power source for small and medium-sized unmanned aerial vehicles (UAV), which has wide civil and military applications. To improve the engine performance, we chose a prototype two-stroke small areoengine, and optimized the geometric parameters of the scavenging ports by performing one-dimensional (1D) and three-dimensional (3D) computational fluid dynamics (CFD) coupling simulations. The prototype engine is tested on a dynamometer to measure in-cylinder pressure curves, as a reference for subsequent simulations. A GT Power simulation model is established and validated against experimental data to provide initial conditions and boundary conditions for the subsequent AVL FIRE simulations. Four parameters are considered as optimal design factors in this research: Tilt angle of the central scavenging port, tilt angle of lateral scavenging ports, slip angle of lateral scavenging ports, and width ratio of the central scavenging port. An evaluation objective function based on the Benson/Bradham model is selected as the optimization goal. Two different operating conditions, including the take-off and cruise of the UAV are considered. The results include: (1) Orthogonal experiments are analyzed, and the significance of parameters are discussed; (2) the best factors combination is concluded, followed by simulation verification; (3) results before and after optimization are compared in details, including specific scavenging indexes (delivery ratio, trapping efficiency, scavenging efficiency, etc.), conventional performance indicators, and the sectional views of gas composition distribution inside the cylinder.

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.

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.

Small-scale bio-energy projects have been launched in rural areas of China and are considered as alternatives to fossil-fuel energy. However, energetic and environmental evaluation of these projects has rarely been carried out, though it is necessary for their long-term development. A village-level biomass gasification project provides an example. A hybrid life-cycle assessment (LCA) of its total nonrenewable energy (NE) cost and associated greenhouse gas (GHG) emissions is presented in this paper. The results show that the total energy cost for one joule of biomass gas output from the project is 2.93 J, of which 0.89 J is from nonrenewable energy, and the related GHG emission cost is 1.17 × 10−4 g CO2-eq over its designed life cycle of 20 years. To provide equivalent effective calorific value for cooking work, the utilization of one joule of biomass gas will lead to more life cycle NE cost by 0.07 J and more GHG emissions by 8.92 × 10−5 g CO2-eq compared to natural gas taking into consideration of the difference in combustion efficiency and calorific value. The small-scale bio-energy project has fallen into dilemma, i.e., struggling for survival, and for a more successful future development of village-level gasification projects, much effort is needed to tide over the plight of its development, such as high cost and low efficiency caused by decentralized construction, technical shortcomings and low utilization rate of by-products.