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Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

Microgrids are increasingly being used as a platform to integrate distributed generation such as renewable energy sources and (RESs) conventional sources in both grid-connected and isolated power systems. Due to the inherent intermittent nature of RESs, energy storage systems (ESSs) that can absorb fluctuations have become inevitable. Nevertheless, large capacities of ESSs increase the initial cost while small capacities lead to instabilities and increase in the cost of conventional fuels. Therefore, finding the optimal size of the ESS for a given application is essential for the reliable, efficient and economical operation of a microgrid. Once the battery size is decided, maintaining its energy at appropriate levels is essential to ensure stable and safe operation of the microgrid. This paper presents a novel expert fuzzy system - grey wolf optimization (FL-GWO) based intelligent meta-heuristic method for battery sizing and energy management. The proposed energy management operation is carried out by a Grey Wolf Optimiser (GWO) that is helped to set the membership functions and rules of the fuzzy logic expert system. The unit commitment (UC) issue, which is essential for the proper operation of the isolated microgrid, has been additionally considered in this paper. To verify the performance of the proposed method, results are compared with the rules-based method and traditional GWO algorithm. It has been proven from the results that the FL-GWO has a significant convergence property and capability to minimize the Levelized Cost Of Electricity (LCOE) by 14.13% and 24.15% compared with conventional GWO algorithm and rules-based method, respectively. The weather conditions for different climates is used to verify the performance of the intelligent energy management method under different operating scenarios. The results show that the intelligent online multi-objective energy management strategy is capable of managing a smooth power flow with the same optimal configuration in the isolated microgrid, minimising the fossil fuel utilisation and reducing the CO2 emission level.

Mixed transition metal oxides with high theoretical capacity show great potential to replace carbonaceous anode materials in lithium-ion batteries.

The catalytic active sites of NiFe and NiFeCr (oxy)hydroxides are revealed byoperandospectroscopic techonologies for alkaline water oxidation.

Abstractπ‐Conjugated polyelectrolytes (CPEs) have been studied as interlayers on top of a separate hole transport layer (HTL) to improve the wetting, interfacial defect passivation, and crystal growth of perovskites. However, very few CPE‐based HTLs have been reported without rational molecular design as ideal HTLs for perovskite solar cells (PeSCs). In this study, the authors synthesize a triphenylamine‐based anionic CPE (TPAFS‐TMA) as an HTL for p‐i‐n‐type PeSCs. TPAFS‐TMA has appropriate frontier molecular orbital (FMO) levels similar to those of the commonly used poly(bis(4‐phenyl)‐2,4,6‐trimethylphenylamine) (PTAA) HTL. The ionic and semiconducting TPAFS‐TMA shows high compatibility, high transmittance, appropriate FMO energy levels for hole extraction and electron blocking, as well as defect passivating properties, which are confirmed using various optical and electrical analyses. Thus, the PeSC with the TPAFS‐TMA HTL exhibits the best power conversion efficiency (PCE) of 20.86%, which is better than that of the PTAA‐based device (PCE of 19.97%). In addition, it exhibits negligible device‐to‐device variations in its photovoltaic performance, contrary to the device with PTAA. Finally, a large‐area PeSC (1 cm2) and mini‐module (3 cm2), showing PCEs of 19.46% and 18.41%, respectively, are successfully fabricated. The newly synthesized TPAFS‐TMA may suggest its great potential as an HTL for large‐area PeSCs.

Abstract Background Parabolic Trough Solar Collector (PTSC) is one of the most popular and an effective device that converts solar radiation into a heat or useful energy. However, it suffers from high temperature gradient and low thermal efficiency. The solution for this problem is to use new advanced coolants (hybrid nanofluids) in order to enhance PTSC's thermal efficiency. Methods A numerical analysis on the thermo-hydraulic performance of a PTSC receiver's tube equipped with conical turbulators is presented. The Navier-Stokes equations are solved using Finite Volume Method (FVM) coupled with Monte Carlo Ray Tracing (MCRT) method. The flow and thermal characteristics as well as entropy generation of the PTSC's receiver tube are investigated for three hybrid nanofluids (Ag-SWCNT, Ag-MWCNT, and Ag-MgO) having a mixing ratio of (50:50) dispersed in Syltherm oil 800, Reynolds number (5000 to 100,000) and fluid inlet temperatures (400 to 650 K). Significant findings The conical turbulators effectively augmented the thermal performance by 233.4% utilising Ag-SWCNT/Syltherm oil instead of pure Syltherm oil. The performance evaluation criterion is found to be in the range of 0.9–1.82. The thermal and exergetic efficiencies increased by 11.5% and 18.2%, respectively. The maximum decrement in the entropy generation rate and entropy generation ratio are 42.7% and 33.7%.

Sugarcane biorefineries, despite their contribution to sustainable transportation fuels and mitigation of carbon emissions in the mobility sector, produce a large amount of carbon dioxide in their conversion processes. According to the Paris climate agreement, a carbon neutral energy system has to be launched in the years to come, and in this scenario, greenhouse gases emission free industrial processes and alternative carbon sources will be needed. Therefore, this paper presents the evaluation of carbon mass balance of a typical Brazilian ethanol mill to better understand its potential for energy and carbon yield improvement. Due to the fact that Brazilian sugarcane mills are evolving from first generation to integrated first and second generation plant, four different scenarios were analysed. For a first generation plant without (S-I) and with conversion of straw to electricity (S-II) and for the integrated plant (S-III), results of carbon mass balance showed that the harvested sugarcane carbon was mainly converted into CO2 and in a smaller proportion into ethanol. In the modelled cases S-I to S-III the conversion of sugarcane carbon into CO2 and ethanol ranged from 41% to 53% and 17%-22%, respectively. Because this carbon amount in the CO2 flows provides an interesting platform to both increase the bioenergy produced and the harvested carbon-to-fuels ratio, a fourth scenario (S-IV) that studies the integration of power-to-gas (PtG) technologies into the mill was also considered. PtG can increase the sugarcane fuels energy content from 9.3 kW/ha to 33.6 kW/ha using 1361.3 MWe of electricity, increasing the amount of sugarcane carbon transformed into sugarcane based fuels to 54% and converting CO2 into a high value added product.

Highly efficient nanocatalysts which can selectively decompose hydrous hydrazine for hydrogen production are introduced.

PurposeThe purpose of this paper is to outline a comprehensive picture of the coverage of various certification schemes and sustainability principles relating to the entire value‐added chain of biomass and bioenergy and comparing them accordingly.Design/methodology/approachA tri‐dimensional approach (sustainability issues; technical biomass conversion routes; physical trade flows) was developed for testing the coverage of various sustainability dimensions in different phases of the value‐added chain with the chosen certification schemes and sustainability principles.FindingsUsing the tri‐dimensional approach, a comparison of the chosen schemes and principles demonstrated that the application of existing schemes and the development of new ones have placed a major emphasis on the primary production of biomass. Economic and social dimensions related to biofuels and bioenergy processing and trade were either emphasised less or they were covered inadequately. In view of this, the schemes sometimes seem to ignore that the utilisation of renewable energy as such guarantee no positive or neutral climate impact and may not be economically sustainable, especially when bioenergy can often be more expensive than energy generated from fossil energy sources.Originality/valueThe analysis showed that the tri‐dimensional model is an applicable framework that could facilitate policy makers to formulate policies that comprehensively take into consideration the various sustainability dimensions throughout the entire value‐added chain, now and in the future. It can be applied to the future outlining and completion of certification schemes and sustainability principles for biomass and bioenergy, as well as in the testing of their applicability in the implementation.