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During the last decade, the application of pretreatment has been investigated to enhance methane production from lignocellulosic biomass such as wheat straw (WS). Nonetheless, most of these studies were conducted in laboratory batch tests, potentially hiding instability problems or inhibition, which may fail in truly predicting full-scale reactor performance. For this purpose, the effect of an alkaline pretreatment on process performance and methane yields from WS (0.10 g NaOH g−1 WS at 90 °C for 1 h) co-digested with fresh wastewater sludge was evaluated in a pilot-scale reactor (20 L). Results showed that alkaline pretreatment resulted in better delignification (44%) and hemicellulose solubilization (62%) compared to untreated WS. Pilot-scale study showed that the alkaline pretreatment improved the methane production (261 ± 3 Nm3 CH4 t−1 VS) compared to untreated WS (201 ± 6 Nm3 CH4 t−1 VS). Stable process without any inhibition was observed and a high alkalinity was maintained in the reactor due to the NaOH used for pretreatment. The study thus confirms that alkaline pretreatment is a promising technology for full-scale application and could improve the overall economic benefits for biogas plant at 24 EUR t−1 VS treated, improve the energy recovery per unit organic matter, reduce the digestate volume and its disposal costs.

The growing integration of renewable energy sources, especially offshore wind (OSW), is introducing frequency stability challenges to electric power grids. This paper presents a novel hybrid deloading control strategy that enables modular multilevel converter (MMC)-based wind energy conversion systems (WECSs) to actively contribute to grid frequency regulation. This research investigates a permanent-magnet synchronous generator (PMSG)-based direct-drive configuration, sourced from the International Energy Agency’s (IEA’s) 15 MW reference turbine model. Specifically, phase-locked loop (PLL)-free grid-forming (GFM) control is employed via the grid-side converter (GSC), and DC-link voltage control is realized through the machine-side converter (MSC), both of which boost the energy support for the integrated AC grid’s frequency stability. This control strategy combines the benefits of over-speeding and pitch control modes, facilitating smooth transitions between different modes based on real-time wind speed measurements. In addition, the practical challenges of MMCs, such as circulating currents and capacitor voltage imbalances, are addressed. Numerical simulations under varying wind speeds and loading conditions validate the enhanced frequency regulation capability of the proposed approach.

Based on current trends and policies aimed at decarbonizing energy systems, the conversion of biomass to bioenergy has the potential to grow rapidly, but such growth depends on the development of efficient, sustainable, and competitive biomass supply chains. As a result, the biomass supply chain has stimulated the interest of a diverse group of researchers across academia, government, and industry, and there is a need to synthesize and categorize the rapidly expanding literature in this field. We conducted a literature review using advanced bibliometric analysis and visualization of 1711 peer-reviewed articles published from January 1992 to August 2022 with the aim of promoting impactful research in both growing and neglected areas of investigation. The results show that there are potential research gaps and opportunities in six critical areas: globalization of supply chain research; incorporation of uncertainty, stochasticity, and risk into supply chain models; investigation of multi-feedstock supply systems; strengthening supply chain resilience; application of inventory control methods; and broader use of machine learning and artificial intelligence in this field. By providing a holistic examination of how biomass-to-bioenergy supply chain research has grown and evolved over this period, our results and subsequent framework and recommendations can aid researchers in developing future studies and can guide stakeholder strategies to identify, diagnose, and address modern challenges that face the bioenergy industry.

Vanadium pentoxide (V2O5)-anchored single-walled carbon nanotube (SWCNT) composites have been developed through a simple sol–gel process, followed by hydrothermal treatment. The resulting material is suitable for use in flexible ultra-high capacity electrode applications for lithium-ion batteries. The unique combination of V2O5 with 0.2 wt.% of SWCNT offers a highly conductive three-dimensional network. This ultimately alleviates the low lithium-ion intercalation seen in V2O5 itself and facilitates vanadium redox reactions. The integration of SWCNTs into the layered structure of V2O5 leads to a high specific capacity of 390 mAhg−1 at 0.1 C between 1.8 to 3.8 V, which is close to the theoretical capacity of V2O5 (443 mAhg−1). In recent research, most of the V2O5 with carbonaceous materials shows higher specific capacity but limited cyclability and poor rate capability. In this work, good cyclability with only 0.3% per cycle degradation during 200 cycles and enhanced rate capability of 178 mAhg−1 at 10 C have been achieved. The excellent electrochemical kinetics during lithiation/delithiation is attributed to the chemical interaction of SWCNTs entrapped between layers of the V2O5 nanostructured network. Proper dispersion of SWCNTs into the V2O5 structure, and its resulting effects, have been validated by SEM, TEM, XPS, XRD, and electrical resistivity measurements. This innovative hybrid material offers a new direction for the large-scale production of high-performance cathode materials for advanced flexible and structural battery applications.

This paper introduces a modified consensus-based real-time optimization framework for utility-connected and islanded microgrids scheduling in normal conditions and under cyberattacks. The exchange of power with the utility is modeled, and the operation of the microgrid energy resources is optimized to minimize the total energy cost. This framework tracks both generation and load variations to decide optimal power generations and the exchange of power with the utility. A linear cost function is defined for the utility where the rates are updated at every time interval. In addition, a realistic approach is taken to limit the power generation from renewable energy sources, including photovoltaics (PVs), wind turbines (WTs), and dispatchable distributed generators (DDGs). The maximum output power of DDGs is limited to their ramp rates. Besides this, a specific cloud-fog architecture is suggested to make the real-time operation and monitoring of the proposed method feasible for utility-connected and islanded microgrids. The cloud-fog-based framework is flexible in applying demand response (DR) programs for more efficiency of the power operation. The algorithm’s performance is examined on the 14 bus IEEE network and is compared with optimal results. Three operating scenarios are considered to model the load as light and heavy, and after denial of service (DoS) attack to indicate the algorithm’s feasibility, robustness, and proficiency. In addition, the uncertainty of the system is analyzed using the unscented transformation (UT) method. The simulation results demonstrate a robust, rapid converging rate and the capability to track the load variations due to the probable responsive loads (considering DR programs) or natural alters of load demand.

When the transmission capacity of an electrical system is insufficient to adequately serve customer demand, the transmission system is said to be experiencing congestion. More transmission lines can be built to increase capacity. However, transmission congestion typically only occurs during periods of peak demand, which occur just a few times per year; capitol-intensive investments in new transmission capacity address problems that occur infrequently. Alternative solutions to alleviated transmission congestion have been devised, including generation curtailment, demand response programs, and various remedial action schema. Though not currently a common solution, battery energy storage systems can also provide transmission congestion relief. Technological and market trends indicate the growing production capacity of battery energy storage systems and decreasing prices, which indicate the technology may soon become a viable option for providing congestion relief. Batteries can provide multiple ancillary services, and so can concurrently provide value through multiple revenue streams. In this manuscript, the authors present a systematic review of literature, technology, regulations, and projects related to the use of battery energy storage systems to provide transmission congestion relief.

Prognostics and remaining useful life (RUL) estimation for lithium-ion batteries play an important role in intelligent battery management systems (BMS). The capacity is often used as the fade indicator for estimating the remaining cycle life of a lithium-ion battery. For spacecraft requiring high reliability and long lifetime, in-orbit RUL estimation and reliability verification on ground should be carefully addressed. However, it is quite challenging to monitor and estimate the capacity of a lithium-ion battery on-line in satellite applications. In this work, a novel health indicator (HI) is extracted from the operating parameters of a lithium-ion battery to quantify battery degradation. Moreover, the Grey Correlation Analysis (GCA) is utilized to evaluate the similarities between the extracted HI and the battery’s capacity. The result illustrates the effectiveness of using this new HI for fading indication. Furthermore, we propose an optimized ensemble monotonic echo state networks (En_MONESN) algorithm, in which the monotonic constraint is introduced to improve the adaptivity of degradation trend estimation, and ensemble learning is integrated to achieve high stability and precision of RUL prediction. Experiments with actual testing data show the efficiency of our proposed method in RUL estimation and degradation modeling for the satellite lithium-ion battery application.