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Abstract This paper presented a novel method of dissipating solar photovoltaic heat based on the technology of micro-heat-pipe array and the utilization of photovoltaic-cell waste heat. This novel technology solved the problems of low PV electrical efficiency and thermal failure caused by high cell temperature, greatly increased the comprehensive utilization efficiency of solar energy, and extended the service life of photovoltaic modules. One-year experiments were conducted to investigate the electrical and thermal performance of a forced-circulation, household-type photovoltaic/thermal system based on micro-heat-pipe array in Beijing, China. Test results showed that on the four typical days in different seasons, the average electrical efficiencies were 13.76%, 11.92%, 13.71%, and 14.65%; the average thermal efficiencies were 31.62%, 33.07%, 24.99%, and 17.24%; and the average total efficiencies were 45.38%, 44.99%, 38.70%, 31.89%, respectively. The system met the demand of power supply on sunny days and the demand of hot water between March and November, except in cloudy days. These experimental results can provide basis and reference for practical applications of the system.

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 Global hydropower growth continues to accelerate with 25% of total capacity installed in just the last 10 years. This accelerating expansion and the important storage facility hydropower means it is increasingly important to understand the reasons for operational failures. This is a challenge because the major reason for failures involves the complex interaction of hydraulic, mechanical and electric subsystems. Historically, reliability modelling has been split in two directions, focusing on different sub-systems, and has not yet been unified. Here these approaches are unified with a novel expression of unbalanced forces. This model with operational data are validated and the important modes of oscillation in the shaft are identified. Finally, the mechanism of the first-order oscillation mode exciting a second-order mode is presented. This integrated and accurate mathematical model is a major advance in the diagnosis and prediction of failures in hydropower operation.

Abstract Castor seed is an important oil seed crop of dryland agriculture. To estimate the energy needs of this crop, two experiments were conducted with three tillage treatments under two farming systems, namely bullock and tractor farming. Under all the selected tillage treatments both for tractor and bullock farming systems, it was found that threshing, harvesting, manual weeding and seed bed preparation were the energy intensive operations. No-tillage treatments was found not only the least energy consuming package of practices but also resulted i n a comparatively high output-input energy ratio despite higher weed intensity. Further, tractor cultivation consumed a higher amount of energy as compared to bullock cultivation but did not result in higher production. The farmer may, therefore, continue with bullock cultivation unless he were to cover larger areas which cannot be commanded by the bullock power resources available to him.

Abstract Biodiesel has gained the forefront of our focus on renewable transportation fuels. This article provides a comprehensive review on the sources used as feedstock and their classification based on generation or type (edible, non-edible, waste resources and animal fats) along with a variety of classical and modern oil extraction techniques. The technical aspects of the various biodiesel production methods currently implemented to the best of our knowledge are discussed here, which include in-situ biodiesel production, both catalysed (homogeneous and heterogeneous systems) and uncatalysed classical production approaches, with emphasis on how each of these approaches are affected by their reaction parameters. The review also highlights the observed drawbacks of each process with a view to assessing the implementation of supercritical and superheated technologies as an alternative, economically feasible advancement. Supercritical process (SCP) has shown great prospect in the obtainment of high quality biodiesel from a wide range of high to low grade feedstock with minimal impacts on the presence of water or FFAs (free fatty acids). From available literature it is shown that these do not affect the process significantly, and various other supercritical fluids such as methyl acetate, tert-butyl methyl ether (MTBE) and dimethyl carbonate can also be used to avoid glycerol formation. The process however, suffers from high initial implementation cost being the most prominent drawback, among others like thermal degradation of the fuel. Another promising technique, the superheated vapour technology (SHV) has emerged as an alternative, with limited literature proving the superiority of either of these processes to be inconclusive. In future works, researchers need to look into various aspects such as developing a spiral reactor for heat recovery, using software based optimization for eliminating redundant experiments analysing production cost for industrial scale-up and improving the fuel’s oxidative stability by adding antioxidants for convenient long-term storage and use.

This paper presents a robust model predictive control strategy for improving the supply air temperature control of air-handling units by dealing with the associated uncertainties and constraints directly. This strategy uses a first-order plus time-delay model with uncertain time-delay and system gain to describe air-conditioning process of an air-handling unit usually operating at various weather conditions. The uncertainties of the time-delay and system gain, which imply the nonlinearities and the variable dynamic characteristics, are formulated using an uncertainty polytope. Based on this uncertainty formulation, an offline LMI-based robust model predictive control algorithm is employed to design a robust controller for air-handling units which can guarantee a good robustness subject to uncertainties and constraints. The proposed robust strategy is evaluated in a dynamic simulation environment of a variable air volume air-conditioning system in various operation conditions by comparing with a conventional PI control strategy. The robustness analysis of both strategies under different weather conditions is also presented.

Abstract In this work, the combustion and emission fundamentals of high n-butanol/diesel ratio blend with 40% butanol (i.e., Bu40) in a heavy-duty diesel engine were investigated by experiment and simulation at constant engine speed of 1400 rpm and an IMEP of 1.0 MPa. Additionally, the impact of EGR was evaluated experimentally and compared with neat diesel fuel (i.e., Bu00). The results show that Bu40 has higher cylinder pressure, longer ignition delay, and faster burning rate than Bu00. Compared with Bu00, moreover, Bu40 has higher NOx due to wider combustion high-temperature region, lower soot due to local lower equivalence ratio distribution, and higher CO due to lower gas temperature in the late expansion process. For Bu40, EGR reduces NOx emissions dramatically with no obvious influence on soot. Meanwhile, there is no significant change in HC and CO emissions and indicated thermal efficiency (ITE) with EGR until EGR threshold is reached. When EGR rate exceeds the threshold level, HC and CO emissions increase dramatically, and ITE decreases markedly. Compared with Bu00, the threshold of Bu40 appears at lower EGR rate. Consequently, combining high butanol/diesel ratio blend with medium EGR has the potential to achieve ultra-low NOx and soot emissions simultaneously while maintaining high thermal efficiency level.