• Energy Research
• 2021-2025close
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The path congestion and communication risks of electric power communication network have emerged as the carried businesses are becoming more and more heavy. In this paper, a multi-objective optimization method for power communication network routing considering the importance of the carried businesses is proposed to reduce load imbalance and transmission risk. Firstly, information entropy is introduced as the objective of communication network load balancing optimization. And a risk assessment model for power communication network nodes and links is established. Then fuzzy membership functions are adopted to singularize the two objectives to jointly optimize path congestion and communication risks. The device nodes are dynamically divided according to the carried businesses to pursue the global optimization of the power communication network in which the Yen's algorithm is adopted. Finally, this paper uses the IEEE 30-bus communication network to carry out case simulations and analyzes the proposed method to verify the effectiveness and feasibility.

AbstractRevolutionary changes in energy storage technology have put forward higher requirements on next‐generation anode materials for lithium‐ion battery. Recently, a new class of materials with complex stoichiometric ratios, high‐entropy oxide (HEO), has gradually emerging into sight and embracing the prosperity. The ideal elemental adjustability and attractive synergistic effect make HEO promising to break through the integrated performance bottleneck of conventional anodes and provide new impetus for the design and development of electrochemical energy storage materials. Here, the research progress of HEO anodes is comprehensively reviewed. The driving force behind phase stability, the role of individual cations, potential mechanisms for controlling properties, as well as state‐of‐the‐art synthetic strategies and modification approaches are critically evaluated. Finally, we envision the future prospects and related challenges in this field, which will bring some enlightening guidance and criteria for researchers to further unlock the mysteries of HEO anodes.image

AbstractShipbuilding is an energy-intensive industrial sector that produces a significant amount of waste, pollution and air emissions. However, the International Maritime Organization concentrates only on reducing emissions during the operational phase. In order to completely phase out emissions from the shipping industry, a life-cycle approach must be taken. The study implemented the proposed transdisciplinary energy management framework in a Bangladeshi shipyard. The framework aims to support shipyard decision makers in making rational and optimized decisions to make shipyards sustainable, while maintaining good product quality and reducing relative cost. This is achieved by applying the Fuzzy Analytical Hierarchy Process and Fuzzy Order of Preference by Similarity to Ideal Solution methods to identify optimal solutions. In addition to making shipyards more sustainable, the framework can enhance both the business and socio-economic prospects of the shipyard and promote the reputation of the shipyard and improve its competitiveness and, in line with this, lead to the promotion of nationally determined contributions under the Paris Agreement for States. The implementation of the framework shows that the political and legal discipline, the social criteria and the implementation of ISO 14001 and cyber security were the most important criteria and options for the yard's decision makers.

UV/visible light is a promising radiation source for biomass pretreatment, but very little knowledge is available on the effect of UV on the thermal behavior of lignocellulose in comparison with more classical, physical pretreatment methods. In this paper, we investigate the effects of ball-milling and UV irradiation on two species of softwood and two species of hardwood, using X-ray diffractometry (XRD), evolved gas analysis-mass spectrometry (EGA-MS), and pyrolysis-gas chromatography coupled to mass spectrometry (Py-GC/MS). The XRD data showed that the crystalline fraction of cellulose was destroyed by milling, but not by irradiation. The EGA-MS data and isoconversional kinetic analysis showed that both milling and irradiation can reduce the thermal stability of wood up to a limit value. The Py-GC/MS data showed that irradiation caused the most significant changes in the pyrolytic behavior of the wood species, increasing the ratio of holocellulose to lignin pyrolysis products and the reactivity of cellulose toward the derivatizing agent. Softwoods were more affected by irradiation than hardwoods. This paper shows that UV irradiation can decrease the recalcitrance of biomass toward pyrolysis, but its efficiency is highly dependent on the type of lignocellulosic substrate.

The wind power forecasting error restricts the benefit of the wind farm in the electricity market. Considering the cooperation of wind power bidding and energy storage system (ESS) operation with uncertainty, this paper proposes a coordinated bidding/operation model for the wind farm to improve its benefits in the electricity market. The maximum entropy based deep reinforcement learning (RL) algorithm, Soft Actor-Critic (SAC) is used to construct the model. The maximum entropy framework enables the designed agent to explore various optimal possibilities, which means the learned coordinated bidding/operation strategy is more stable considering the forecasting error. Particularly, penalty terms are introduced into the benefit function to relax the constraints and improve the convergency. The case study illustrates that the learned policy can effectively improve the wind farm benefit while ensuring robustness.

With the 2015 Paris Agreement pursuing efforts to limit global temperature increase to below 2°C above pre-industrial levels and the “energy trilemma” goals of energy security, energy equity and environmental sustainability, decarbonisation remains a priority across all of the United Kingdom (United Kingdom) energy system, not just electricity. Electricity and thermal energy storage technologies can offer a host of benefits across the energy value chain through the abilityS to capture, store and then release electricity or thermal energy over a period of time. These benefits include helping capture the full potential of renewable generation and providing services such as frequency response and reserve to Great Britain’s (GB) electricity system. In addition, with the aforementioned climate targets in mind, energy storage can also play a role in facilitating the decarbonisation of other activities and sectors. Here we delve deeper into how energy storage technologies can contribute to both energy sector transformation and more broadly, decarbonisation. Furthermore, we discuss the importance of ensuring a technology-agnostic approach to the development of policy and regulation with relevance to energy storage. This ensures that storage technologies with significant potential to contribute to the ‘energy trilemma’ goals are not precluded from entering the market due to unfavourable policy and regulatory frameworks.

Research on corona discharge, shared by physics, chemistry and electrical engineering, has not arrested yet. As a dissipative process, the development of corona increases the resistive losses of transmission lines and enhances the line capacitance locally. Introducing additional losses and propagation delay, along the line, non-linearity and non-uniformity of the line parameters; therefore, corona should not be neglected. The present work is meant to provide the reader with comprehensive information on the corona macroscopic phenomenology and development, referring to the most relevant contributions in the literature on this subject. The models proposed in the literature for the simulation of the corona development are reviewed in detail, and sensitivity curves are provided to highlight their dependence on the input parameters.