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The current critical global concerns regarding fossil fuel exhaustion and environmental pollution have been driving advancements in transportation electrification and related battery technologies. In turn, the resultant growing popularity of electric vehicles (EVs) calls for the development of a well-designed charging infrastructure. However, an inappropriate placement of charging stations might hamper smooth operation of the power grid and be inconvenient to EV drivers. Thus, the present work proposes a novel two-stage planning model for charging station placement. The candidate locations for the placement of charging stations are first determined by fuzzy inference considering distance, road traffic, and grid stability. The randomness in road traffic is modelled by applying a Bayesian network (BN). Then, the charging station placement problem is represented in a multi-objective framework with cost, voltage stability reliability power loss (VRP) index, accessibility index, and waiting time as objective functions. A hybrid algorithm combining chicken swarm optimization and the teaching-learning-based optimization (CSO TLBO) algorithm is used to obtain the Pareto front. Further, fuzzy decision making is used to compare the Pareto optimal solutions. The proposed planning model is validated on a superimposed IEEE 33-bus and 25-node test network and on a practical network in Tianjin, China. Simulation results validate the efficacy of the proposed model.

The exhaustive nature of fossil fuels and environmental concerns associated with greenhouse gases are the major causes of the paradigm shift from conventional vehicles to electric vehicles (EVs). The electrification of the transportation sector and the increasing popularity of the EVs have driven scientists and researchers to delve into charging stations. Underdeveloped charging infrastructure, optimal placement of charging stations, and charge scheduling in the charging stations are the major concerns for the large-scale deployment of EVs. Even few questions related to EVs, such as the vehicle price and driving range, can be partially solved with a well-developed charging infrastructure. Existing old infrastructure may bring severe limitations in the realization of the optimal placement of charging stations as EVs have not existed when the road and grid infrastructure have been developed. For the past few years, the studies associated with the optimal placement and sizing of EV charging stations have drawn the consideration of the researchers. The researchers have used different approaches, objective functions, and applied different optimization algorithms while dealing with the problem of charging station placement. The complex and dynamic nature of the problem has led researchers to apply different optimization algorithms for the solution of the problem. In this particular review study, the research works bearing on the charging infrastructure planning for the EVs are considered. Thus, this review work will endow the research community with the latest developments and research findings in the paradigm of charging infrastructure planning for EVs. This article is categorized under: Energy Infrastructure > Systems and Infrastructure Energy and Urban Design > Systems and Infrastructure Energy and Transport > Science and Materials Energy Systems Analysis > Science and Materials

Pressurised circulating fluidised bed (CFB) technology is a potentially promising development for clean coal technologies. The current work explores the hydrodynamics of a small-scale circulating fluidised bed at elevated operating pressures ranging from 0.10 to 0.25 MPa. The initial experiments were performed at atmospheric pressure with air and O2/CO2 environments as the fluidisation gas to simulate the hydrodynamics in a CFB. A comparison between the effects of air and O2/CO2 mixtures on the hydrodynamics was outlined in this paper for particles of 160 μm diameter. A small but distinct effect on axial voidage was observed due to the change in gas density in the dense zone of the bed at lower gas velocity, while only minimal differences were noticed at higher gas velocities. The hydrodynamic parameters such as pressure drop and axial voidage profile along the height were reported at two different bed inventories (0.5 and 0.75 kg) for three mean particle sizes of 160, 302 and 427 μm and three superficial gas velocities. It was observed that the operating pressure had a significant effect on the hydrodynamic parameters of bed pressure drop and axial bed voidage profiles. The effect of solids loading resulted in an exponential change in pressure drop profile at atmospheric pressure as well as at elevated pressure. The experimental results on hydrodynamic parameters are in reasonable agreement with published observations in the literature.

Combustion of fossil fuels is one of the major sources of greenhouse gas (GHG) CO2, it is therefore necessary to develop technologies that will allow us to utilize the fossil fuels while reducing the emissions of GHG. Removal of CO2 from flue gasses has become an effective way to mitigate the GHG and adsorption is considered to be one of the methods. Adsorption of CO2 on zeolite 13X, zeolite 4A and activated carbon (AC) have been investigated at a temperature ranging from 25 to 60 °C and pressure up to 1 bar. The experimental data were fitted with isotherm models like Langmuir and Freunlich isotherm model. The Langmuir model fit well with the two zeolites and Freunlich model fit well with AC. The thermodynamics parameters were calculated and found to be exothermic in natures for all three adsorbents. Moreover, regeneration studies have been conducted in order to verify the possibility of activated carbon reutilization, to determine its CO2 adsorption capacity within consecutive cycles of adsorption–desorption. Temperature swing adsorption was employed as the regeneration method through heating up to a temperature of approximately 100 °C. There is no full reversibility for zeolites while AC can achieve complete regenerations.

The Indian Government's National Biogas and Manure Management Programme (NBMMP) seeks to deliver renewable energy services to households across the country by facilitating the deployment of family-sized ( 3 ) anaerobic (biogas) digesters. NBMMP policy is implemented at three levels, from government and state nodal agency, via private contractors to households, creating multiple institutional arrangements. We analysed the scheme in Assam, north-east India, focusing on how policy was implemented across two districts and interviewing stakeholders in rural households, state and non-state institutions. The top-down, supply-side approach to policy enables government to set targets and require individual states to deploy the scheme, which benefits households who can afford to participate. NBMMP delivered improved energy service outcomes to a majority of households, although the level of knowledge and understanding of the technology amongst users was limited. Training and education of householders, and particularly women, is needed in relation to the maintenance of digesters, feedstock suitability and the environmental and potential livelihood benefits of digestate. A revised bottom-up approach to policy, which highlights the contextual and demand-side issues around adopting the technology, may deliver monetary benefits from market competition and enable development of community-focused microfinance schemes to improve the affordability of biogas systems.