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The paper represents the analysis, which has helped to establish the usage of gas hydrate technologies in the methane conversion. This gas could be obtained in different ways. Possibilities and sources for the gas obtaining have been demonstrated. Use of other environmentally friendly sources to support operation in such systems in terms of joint energy complex has been considered. The necessary kinetic connections to provide operational sustainability of all the constituents have been given. The approach helps evaluate quantitatively the priority of its physicochemical transformations to obtain gas hydrates artificially. It is possible to transport methane at considerable distances when it is solidified. Actually, in this case there is no necessity to build costly compressor stations and pipelines for its transportation to consumers. The approach is extremely important for mining regions as it helps prolong the operating period and working out of the abandoned and off-balance coal reserves. In this case, it is proposed to apply special gasification technologies tending to maximum methane recovery. The proposed solutions give the possibility to define the trends of our further research. They will be highlighted in the following authors’ studies.

Introduction: During the COVID-19 lockdown significant improvements in urban air quality were detected due to the absence of motorized vehicles. It is crucial to perpetuate such improvements to maintain and improve public health simultaneously. Therefore, this exploratory study approached bicycle infrastructure in the case of Munich (Germany) to find out which specific bicycle lanes meet the demands of its users, how such infrastructure looks like, and which characteristics are potentially important. Methods: To identify patterns of bicycle infrastructure in Munich exploratory data is collected over the timespan of three consecutive weeks in August by a bicycle rider at different times of the day. We measure position, time, velocity, pulse, level of sound, temperature and humidity. In the next step, we qualitatively identified different segments and applied a cluster analysis to quantitatively describe those segments regarding the measured factors. The data allows us to identify which bicycle lanes have a particular set of measurements, indicating a favorable construction for bike riders. Results: In the exploratory dataset, five relevant segment clusters are identified: viscous, slow, inconsistent, accelerating, and best-performance. The segments that are identified as best-performance enable bicycle riders to travel efficiently and safely at amenable distances in urban areas. They are characterized by their width, little to no interaction with motorized traffic as well as pedestrians, and effective traffic light control. Discussion: We propose two levels of discussion: (1) revolves around what kind of bicycles lanes from the case study can help to increase bicycle usage in urban areas, while simultaneously improving public health and mitigating climate change challenges and (2) discussing the possibilities, limitations and necessary improvements of this kind of exploratory methodology.

In this paper, the allocation of charging station (CS) is optimized to alleviate the “range anxiety” of electric vehicle (EV) drivers by reducing the time of medium-to-long distance travel, which is raised due to the potential en-route charging. The problem is defined to explicitly consider the spatial differences in urban land price. Although many works take spatial land price into consideration, few of them notice what the gap of spatial land price bring to the charging system. Our objective function is the expected traveling time under an optimized distribution of urban EV flows, and models of spatial network and CSs allocation are then established. Based on Tabu Search algorithm (TSA), a fixed budget charging resources planning algorithm (FBCRPA) is proposed. The proposed method is compared with methods based on betweeness centrality, and results show that our method can find more effective allocation strategy. It is found that users’ traveling time would decrease with increase in difference in land price. Meanwhile, budget would transfer from central region to other regions and carrying capacity of charging system would improve in the above situation. This paper also finds that increase in budget is beneficial to a reduction in drivers’ time, but the improvement is limited.

Attributing to the irreplaceable quality of nil carbon footprints, the power system considering the integration of electric vehicles and renewable energy resources are appealing growing attention in the recent time, but the reliability of their associated components, is a main matter of concern nowadays. Therefore, in this paper, a novel incentive based fuzzy fault tree analysis (NIBFFTA) approach for restructured power system considering the influence of integrating Electric vehicles and Renewable energy resources-based hybrid wind-solar energy is presented. The approach combines the impacts of different components failure rate and the incentive Gaussian distribution effects under the inducement fuzzy fault tree atmosphere for the grid integrated Renewable energy resources and Electric vehicles configurations. In the basic fault tree analysis, the vague and inaccurate events such as system switches and low power component failures could not be identified competently. Moreover, the probability values of fault occurrences in the complete power system are not considered into account. Additionally, it is quite hard to have a precise assessment of the grid-connected wind energy power systems and EV configuration failure chances or the possibility of occurrence of undesired actions in the complete system because of data deficiency. To overwhelm these demerits, a novel incentive based fuzzy fault tree analysis based on the Gaussian distribution and fuzzy set model is recommended and used for the restructured power system considering the impact of integrating Electric vehicles and Renewable energy resources. Besides, the probability analysis of fault occurrence is also proposed to determine the impact of each basic event of the proposed system on the top event. Furthermore, the prediction analysis of fault occurrence is also done to know the effect of every basic action of the system on the top action. Whereas, prediction analysis factors for the different basic events of the proposed systems are evaluated and these can be used to obtain the real consequence of basic events on the proposed system. It is found that a novel incentive based fuzzy fault tree analysis approach is more significant and efficient than the conventional fault tree method for risk assessment of restructured power system with integrating the electric vehicles and renewable energy resources.

The consumer adoption of electric vehicles (EVs) has become most popular. Numerous studies are being carried out on the usage of EVs, the challenges of EVs, and their benefits. Based on these studies, factors such as battery charging time, charging infrastructure, battery cost, distance per charge, and the capital cost are considered factors in the adoption of electric vehicles and their interconnection with the grid. The large-scale development of electric vehicles has laid the path to Photovoltaic (PV) power for charging and grid support, as the PV panels can be placed at the top of the smart charging stations connected to a grid. By proper scheduling of PV and grid systems, the V2G connections can be made simple. For reliable operation of the grid, the ramifications associated with the PV interconnection must be properly addressed without any violations. To overcome the above issues, certain standards can be imposed on these systems. This paper mainly focuses on the various standards for EV, PV systems and their interconnection with grid-connected systems.

ABSTRACTWith a focus on sustainable development, industries around the world have been encouraging Circular Economy to decouple economic activities from consumption of resources. This has motivated existing materials and products to be shared, leased, reused, repaired, refurbished, and even recycled with an interest of using them for as long as possible. While this concept has taken root in most industries, it is still in the nascent stages in the maritime industry. Since the maritime industry is the backbone of the existing infrastructure of world trade, it has become imperative for the maritime industry to adopt the concept of Circular Economy to ensure their growth in a sustainable manner.Accordingly, the maritime industry has adopted some aspects of Circular Economy such as shipbreaking for recycling, emission control through decarbonisation, and reuse of material. With these notwithstanding, the industry has found it difficult to indoctrinate the true principles of Circular Economy due to issues such as disparity of information amongst suppliers and plurality of designs for ship components, to name a few.The paper thus aims to discuss the existing limits and challenges and the possible methods of promoting the principles of Circular Economy in the shipping industry for achieving sustainable growth.

Renewable energy systems (RESs) and electric vehicles (EVs) have become global necessities to meet the sustainable development goals (SDGs). Because they are intermittent and stochastic, these two technologies have caused power grid operation and regulation challenges despite their environmental benefits. A new combined dynamic optimal network reconfiguration (DONR) and capacitor bank switching (CBS) optimization technique reduces solar and multi-type load effects on the distribution network performance. Considering substantial EV load penetrations, ONR and CBS should coordinate to reduce energy loss, improve the voltage profile, and save money during 24 h operation. The artificial hummingbird algorithm (AHA) solves this difficult optimization problem for the first time. An enhanced IEEE 33-bus benchmark test system was used to simulate various instances to evaluate the computational characteristics of the AHA and compare it with other similar algorithms. The obtained results demonstrate the superiority of the combined DONR and CBS for real-time scenarios over any individual approach.

Renewable energy based power generation has proven to be a viable standalone option in areas where extending the grid is challenging. This study addresses this issue by assessing the possibility of an integrated renewable energy system (IRES) to electrify twelve villages in the Uttarakhand state of India. Four battery energy storage (BES) devices, namely Lead-Acid (LA), Sodium-Sulfur (NAS), Lithium-Ion (Li-Ion), and Nickel-Iron (Ni-Fe) are considered for storage in this study. Using the Chimp optimization algorithm (ChOA) on the MATLAB© platform, eight different configurations consisting of solar photovoltaic (SPV) array, a micro-hydropower (MHP) plant, and a biogas generator (BGG) are modeled and optimized. The study reveals that the optimal IRES configuration with the lowest cost and highest performance comprises 676 SPV panels (260 kWp), one MHP plant (25 kW), one BGG (40 kW), and 648 NAS batteries (778 kWh). This configuration has a total system life cycle cost (LCC) of INR 68.77 million and cost of energy (COE) of 16.77 INR/kWh at 0 % loss of power supply probability. The optimization problem was run 1–50 times and found that the proposed ChOA algorithm is more robust compared to others, displaying the lowest Best, Worst, and Mean values of LCC (across all eight configurations), convergence rapidity (26th iteration), and least computational time (3481 sec). However, GWO (seven configurations), MFO (34th iteration), and GA (4154 sec) stand very close to ChOA performance in terms of providing minimum LCCs, convergence rapidity, and computational time, respectively. Furthermore, surplus energy (SE) is effectively utilized by incorporating electric vehicles (EVs) as dump load in the system. The proposed integrated charging (IC) strategy outperforms other charging strategies by energizing 134 EVs, utilizing 99.59 % of SE, and reducing the total COE to 10.57 INR/kWh. Finally, the proposed IC strategy results in a net saving of 94,479.39 tons of greenhouse gas emissions. These findings support the feasibility of implementing a standalone IRES to electrify the study area and provide electricity to EVs.