• Energy Research
• Closed Access close
• Restricted close
• Open Source close
• AU close
• BE close

In this chapter, turbulent flow of water-based optimization (TFWO) inspired based on whirlpools created in turbulent flow of water is used to solve the maximum power point tracking (MPPT) of photovoltaic systems in partial shading conditions. The TFWO is used to determine the optimal duty cycle of the DC/DC converter with the objective of maximizing the extracted power of the photovoltaic system. The capability of proposed method is evaluated in different patterns of partial shading to achieve global optimal power. The simulation results showed that TFWO is able to track the global maximum power point (GMPP), successfully in PSC and also fast climate changing. The TFWO has a better tracking capability with faster tracking speed and accuracy than particle swarm optimization (PSO) in obtaining the GMPP. Moreover, the results indicate that the use of buck–boost converter led to faster and more accurate access to the global optimal point than the system equipped with boost converter. The results showed that photovoltaic system with boost converter cannot obtain global maximum power in climate changing condition and limited the efficiency of the MPPT algorithm, while the photovoltaic system with buck–boost converter could be tracked GMPP due to its wider operating area.

Abstract There are instances in remote areas where heat is being wasted, e.g., in internal combustion, engines, etc. Some of this heat can be recovered to produce distilled water in solar stills. The solar still replaces the cooling tower, ponds, or radiators normally used to control the engine temperature. The diesel cooling water in such a system remains separate from the saline water in the solar still. The advantages of using such a system compared with a conventional solar still are: 1. (a) water costs are very much reduced 2. (b) the area occupied is much less, i.e., about 1 5 th 3. (c) production has much less seasonal variation 4. (d) the efficiency of the solar still is improved due to the higher operating temperatures. From experiments conducted at Highett using a Mk VI solar still fitted with a simple heat exchanger and a separate electrically-heated source of hot water to simulate the waste heat, design data are not available for application to working systems. The information required to match a solar still to a diesel's cooling requirement is: 1. (a) engine efficiency 2. (b) hourly fuel consumption 3. (c) hourly solar radiation 4. (d) hourly ambient temperatures. A by-product of this work has been the production of a “solar water heater” which costs less than that of the cheapest conventional system. This “solar” hot water system uses a heat exchanger similar to what is used to transfer the waste heat to the saline water. It is envisaged to have hot water productions approximately the same as the distilled water productions. The influence of hot water production on the output of the waste heat solar still is discussed.

Abstract This paper discusses the minimization of the fuel consumption of a gasoline engine through dynamic optimization. The minimization uses a mean value model of the powertrain and vehicle. This model has two state variables: the pressure in the engine intake manifold and the engine speed. The control input is the throttle valve angle. The model is identified on a universal engine dynamometer. Optimal state and control trajectories are calculated using Bock’s direct multiple shooting method, implemented in the software MUSCOD-II. The developed approach is illustrated both in simulation and experimentally for a generic test case where a vehicle accelerates from 1100 rpm to 3700 rpm in 30 s . The optimized trajectories yield minimal fuel consumption. The experiments show that a linear engine speed trajectory yields an extra fuel consumption of 13 % when compared to the optimal trajectory. It is shown that, with a simple model, a significant amount of fuel can be saved without loss of the fun-to-drive.

AbstractThe paper describes some of the simulations of measurements taken using EMTDC to estimate power system load models. It shows how different load structure and non‐ideal conditions in power systems influence results of the measurements. On the basis of simulations performed different load models are proposed for various classes of load compositions. An example of load parameter estimation from measured results is given.

A detailed pollen record from the Ocean Drilling Program Site 820 core, located on the upper part of the continental slope off the coast of northeast Queensland, was constructed to compare with the existing pollen record from Lynch's Crater on the adjacent Atherton Tableland and allow the production of a regional picture of vegetation and environmental change through the last glacial cycle. Some broad similarities in patterns of vegetation change are revealed, despite the differences between sites and their pollen catchments, which can be related largely to global climate and sea-level changes. The original estimated time scale of the Lynch's Crater record is largely confirmed from comparison with the more thoroughly dated ODP record. Conversely, the Lynch's Crater pollen record has assisted in dating problematic parts of the ODP record. In contrast to Lynch's Crater, which reveals a sharp and sustained reduction in drier araucarian forest around 38,000 yrs BP, considered to have been the result of burning by Aboriginal people, the ODP record indicates, most likely, a stepwise reduction, dating from 140,000 yrs BP or beyond. The earliest reduction shows lack of a clear connection between Araucaria decline and increased burning and suggests that people may not have been involved at this stage. However, a further decline in araucarian forest, possibly around 45,000 yrs BP, which has a more substantial environmental impact and is not related to a time of major climate change, is likely, at least partially, the result of human burning. The suggestion, from the ODP core oxygen isotope record, of a regional sea-surface temperature increase of around 4 degrees C between about 400,000 and 250,000 yrs BP, may have had some influence on the overall decline in Araucaria and its replacement by sclerophyll vegetation. (C) 2000 Elsevier Science B.V. All rights reserved.

Nanotechnology, and particularly nanoparticles (NPs), command significant attention across diverse fields such as medicine, chemistry, and engineering. NPs are integrated into a base material through various techniques, such as dispersion, coating, and encapsulation. This review intends to offer an evaluation of the implementation of NPs in nuclear energy and radiation protection. Particular focus is given to nanofluids - suspensions of NPs in a base fluid - and their impact on the thermal–hydraulic and neutronic attributes of nuclear reactor cores. Discussion centers on how substituting water with nanofluids as a coolant can modify these characteristics. Computational modeling and experimental methods of nanofluids are examined, highlighting an enhanced heat transfer capacity under both regular and emergency reactor conditions. The influence of nanofluids on neutronic parameters, aiming for optimized operation and safety of nuclear reactors, is also explored. Furthermore, the potential of NPs for radiation shielding is considered, underlining their capability to attenuate radiation effects. Examples are drawn from the addition of NPs to containment structures in nuclear facilities and their use in radiotherapy, as well as enhancing radiation shielding in imaging techniques. Finally, the review encompasses the effects of nanofluids on surface oxidation and corrosion. The importance of these factors lies in their substantial impact on heat transport properties and potential for corrosive damage.

Risk preference is an important factor in electricity market strategy analysis and decision-making. The existing methods of risk preference analysis need to design and execute questionnaires or experiments on the subjects, and hence are costly and time-consuming for bidding in electricity markets. This article proposes a new method of data-driven risk preference analysis for power generation plants based on historical data and inverse reinforcement learning. Historical data are transformed to the transition function model according to the specific market mechanism. An adjusted inverse reinforcement learning model is thereafter proposed along with the optimization objective and technical constraints. The proposed method is tested in a simulated electricity market environment using the Australian Energy Market Operator (AEMO) day-ahead bidding data. Simulation results show that 1) thermal power plants prefer to adjust risk preferences within the day; 2) apart from the thermal power plants, the rest types of power plants are risk-neutral; 3) the daily risk preference trend of the thermal power plants varies in different seasons and is closely related to the load level.

Controlling the morphological structure of titanium dioxide (TiO2) is crucial for obtaining superior power conversion efficiency for dye‐sensitized solar cells. Although the sol–gel‐based process has been developed for this purpose, there has been limited success in resisting the aggregation of nanostructured TiO2, which could act as an obstacle for mass production. Herein, we report a simple approach to improve the efficiency of dye‐sensitized solar cells (DSSC) by controlling the degree of aggregation and particle surface charge through zeta potential analysis. We found that different aqueous colloidal conditions, i.e., potential of hydrogen (pH), water/titanium alkoxide (titanium isopropoxide) ratio, and surface charge, obviously led to different particle sizes in the range of 10–500 nm. We have also shown that particles prepared under acidic conditions are more effective for DSSC application regarding the modification of surface charges to improve dye loading and electron injection rate properties. Power conversion efficiency of 6.54%, open‐circuit voltage of 0.73 V, short‐circuit current density of 15.32 mA/cm2, and fill factor of 0.73 were obtained using anatase TiO2 optimized to 10–20 nm in size, as well as by the use of a compact TiO2 blocking layer.