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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.

Abstract Breastshot water wheels are gravity hydraulic machines employed in low head sites. The scope of this work is to test the performance of a breastshot water wheel with two geometric inflow configurations: a sluice gate at different openings and two vertical overflow weirs. With the sluice gate, the maximum efficiency of the plant is 75%, constant over a wide range of flow rates, while the efficiency with the weir is increasing in the same flow rate range. Therefore, the wheel with the weir can exploit higher water volumes, and also it performs better at high power input. In practical applications, the inflow configuration can be effectively controlled to optimize the operative working conditions of breastshot water wheels, depending on the external hydraulic ones. The experimental results are also discussed in dimensionless terms, in order to support engineers in the design of similar breastshot water wheels.

Seagrass systems of the Western Pacific region are biodiverse habitats, providing vital services to ecosystems and humans over a vast geographic range. SeagrassNet is a worldwide monitoring program that collects data on seagrass habitats, including the ten locations across the Western Pacific reported here where change at various scales was rapidly detected. Three sites remote from human influence were stable. Seagrasses declined largely due to increased nutrient loading (4 sites) and increased sedimentation (3 sites), the two most common stressors of seagrass worldwide. Two sites experienced near-total loss from of excess sedimentation, followed by partial recovery once sedimentation was reduced. Species shifts were observed at every site with recovering sites colonized by pioneer species. Regulation of watersheds is essential if marine protected areas are to preserve seagrass meadows. Seagrasses in the Western Pacific experience stress due to human impacts despite the vastness of the ocean area and low development pressures.

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

The crucial role evaluation can play in the co-development of project design and its implementation will be addressed through the analysis of a case study, the Green Communities (GC) project, funded by the Italian Ministry of Environment within the EU Interregional Operational Program (2007-2013) "Renewable Energy and Energy Efficiency". The project's broader goals included an attempt to trigger a change in Italian local development strategies, especially for mountain and inland areas, which would be tailored to the real needs of communities, and based on a sustainable exploitation and management of the territorial assets. The goal was not achieved, and this paper addresses the issues of how GC could have been more effective in fostering a vision of change, and which design adaptations and evaluation procedures would have allowed the project to better cope with the unexpected consequences and resistances it encountered. The conclusions drawn are that projects should be conceived, designed and carried out as dynamic systems, inclusive of a dynamic and engaged evaluation enabling the generation of feedbacks loops, iteratively interpreting the narratives and dynamics unfolding within the project, and actively monitoring the potential of various relationships among project participants for generating positive social change.

Previous work carried out for the last eight years resulted in the proposal of a complete system of dimensionless groups in order to represent the performance of different kinematic Stirling engine configurations. When looking for experimental support for the proposed model, some differences between the performances of several prototypes were observed. In this paper an equation is introduced to be applied to all known kinematic engines and to their whole range of performance. The coefficients appearing in this equation can be computed from temperature and geometrical dimensionless ratios and from experimental measurements at the maximum indicated power operating point. The meaning of those coefficients is interpreted and their usefulness to provide an engine performance overview is shown. The quasi-static simulation and the characteristic Mach number at the maximum indicated power operating point appear to be interesting criteria in order to evaluate the performance of prototypes.

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

Abstract Economically harvesting energy from a microbial fuel cell (MFC), increasing its electrical power production, and developing its role as a practical energy supply, needs a low-cost and high-performance design of the MFC compartments. According to this strategy, a novel monolithic membrane electrode assembly (MEA) was fabricated and evaluated as an air–cathode in a single-chamber MFC (SCMFC). The MEA was made of bacterial cellulose (BC), conductive multi-walled carbon nanotubes (CNT), and nano-zycosil (NZ). BC, as a nano-celluloses with oxygen barrier property, can maintain anaerobic conditions for the anode compartment. Binder-less CNT coating on BC avoids costly binders such as poly-tetra fluoro ethylene (PTFE) and Nafion and decreases the MEA charge transfer resistance. NZ, as a very cheap modifier, not only prevents the anolyte leakage but also provides more MEA’s active sites for the oxygen reduction reaction (ORR). The electrochemical performance of the MEA was compared to a PTFE- based gas diffusion electrode (GDE) in the SCMFC. The MEA cell provided a pulse power density of 1790 mW/m2, roughly twice as high as the pulse power density of GDE (920 mW/m2). SCMFC’s internal resistance decreased from 1.84 KΩ (with GDE) to 0.8 KΩ (with MEA). Also, the cell’s columbic efficiency increased from 4.2% (with GDE) to11.7% (with MEA). Additionally, the capacitance of the MEA (65 mF) was much higher than the value for GDE (0.73 mF). Thus, the MEA compared to the GDE showed higher performance in the SCMFC for electricity generation and wastewater treatment at a lower cost.

Artículos en revistas It is shown how a standard nonlinear programming approach can be applied to solve a sophisticated version of the static optimal mix problem in generation planning. The model presented includes technical minima of thermal capacity, detailed operating models of storage-hydro and pumped-hydro units, a realistic model of capital costs for hydro plants, operating reserve and minimum demand constraints, and capacity already in existence. The model formulation is in a format that can be directly handled by the well-known MINOS code and can be efficiently solved. The use of a general-purpose nonlinear optimization program results in a great flexibility, making it possible to modify the model formulation easily or to adapt it to the characteristics of a particular electric system. A realistic application to the Spanish generation system is presented info:eu-repo/semantics/publishedVersion