• Energy Research
• Closed Access close
• Restricted close
• Open Source close
• Energy Conversion and Management close

Abstract Limiting the increase of global temperature requires electrification of the railway transport, which is relatively a distinct mode of transport in terms of economy, business and socialization of a country. However, battery complemented railway transport systems such as fuel cell hybrid railway propulsion systems are constrained by the high cost of the battery, and suboptimal performance of the fuel cell under varying loads. Optimized selection of battery can reduce its costs associated with sizing, life and utilization. Similarly, managing the load distribution between the battery and fuel cell can reduce the load variations concern for fuel cell. In this study, model-based selective characterization of the battery and fuel cell is done to identify the optimal features and constraints. Following characterization, the load allocation to battery and fuel cell is determined with the targets of collaborative utilization of optimal features and mitigation of constraints. Subsequently, considering this load allocation and results of characterization, conditions are proposed for reliable sizing and optimized selection of battery. The significance of the proposed conditions in reliable sizing is explored. Based on these conditions, certain commercially developed batteries are evaluated for optimized selection of battery. The results signify this study as a foundation for research on the reliable sizing and optimized selection of battery in fuel cell hybrid railway propulsion systems.

Abstract In this paper, Linear Regression and M5’Rules models within Data Mining Process and Artificial Neural Network (ANN) model for thermodynamic evaluation of ammonia–water absorption refrigeration systems was carried out. A new formulation based on ANN model is presented for the analysis of ammonia–water absorption refrigeration systems (AWRS) because the optimal result was obtained by using ANN Model. Thermodynamic analysis of the AWRS is very complex because of analytic functions used for calculating the properties of fluid couples and simulation programs. Therefore, it is extremely difficult to perform analysis of this system. COP and f are estimated depending on the temperatures of system component and concentration values. Using the weights obtained from the trained network a new formulation is presented for the calculation of the COP and f; the use of ANN is proliferating with high speed in simulation. The R2-values obtained when unknown data were used to the networks was 0.9996 and 0.9873 for the circulation ratio and COP respectively which is very satisfactory. The use of this new formulation, which can be employed with any programming language or spreadsheet program for the estimation of the circulation ratio and COP of AWRS, as described in this paper, may make the use of dedicated ANN software unnecessary.

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.

The paper describes a two dimensional numerical model for analysis of the local and integral characteristics of linear electromagnetic pumps, such as magnetic field distribution, pressure developed, amplitude of pressure pulsation with double supply frequency and distribution of liquid metal velocity over the azimuth. Numerical results are compared with experimental ones.

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 Hybrid energy storage is a multi-modal approach to store and supply different forms of energy (electricity, heat, cold) simultaneously. This is an important sector coupling approach and enables large scale flexibility for a deep decarbonization of energy systems. Two different proposed energy storages – power-to-heat-to-X energy storage (PHXES) and pumped thermal energy storage (PTES) – are investigated in detail in this work towards their potential towards a hybrid deployment. The techno-economic analysis includes thermodynamic flowsheet simulations and unified cost estimations based on the used equipment. It is shown that the main input data set (e.g. working fluid selection, turbomachinery efficiency, pinch temperatures) has a strong influence on storage roundtrip efficiency in the thermodynamic simulations, but also on storage costs. Cost decrease and performance increase can be conflicting development targets, and it is not clear if future energy systems rather require technologies with the highest storage efficiencies or if low cost is an important prerequisite. PHXES and three variants of PTES are implemented into a simplified energy system model of the city of Hamburg that comprises the electric load and heat demand of the district heating system. Two scenarios (fossil benchmark and 80% decarbonization) are used to select the technologies and their capacities that allow the most cost-effective energy supply solution by a linear-programming optimization procedure. Large scale renewable power generation and hybrid energy storage play the major roles in the decarbonization scenario. PHXES with a storage capacity of 69 GWh, hot water storage (3.6 GWh) and a battery system (430 MWh) are part of the cost-optimal solution. A cost sensitivity analysis shows that a total cost reduction of 60–80% is required for PTES to become competitive in this model scenario.

We have studied the response of the efficiency and short-circuit current of an array of silicon solar cells to changes in intensity of solar radiation under tropical atmospheric conditions. The investigation was carried out simultaneously at two different geographical locations in Nigeria: Enugu (6.20°N, 7.30°E) and Port Harcourt (4.43°N, 7.10°E) (Port Harcourt is located very close to the sea, while Enugu is far away from the sea). Data collected from the two locations clearly reveal that the mean optimum efficiency is not constant, but decreases exponentially as the intensity of solar radiation increases. The short-circuit current, on the other hand, increases non-linearly with intensity of solar radiation and approaches some constant maximum value under very high insolation. The change in efficiency is above 70% as the intensity of solar radiation changes from 100 to 800 W m−2. An empirical equation, relating the mean optimum efficiency to intensity of solar radiation, and an empirical equation, relating the mean short-circuit current to intensity of solar radiation, have been proposed. No previous similar work is available for comparison, but our results are consistent with the well-established fact that under cloudy conditions (and thereafter low insolation), short-wavelength radiation becomes predominant.

Abstract A major component of solar thermal systems is the solar absorber, which converts light into heat. We report on achieving high absorptance, excellent adhesion, and high thermal stability of carbon nanotube-based black coatings by applying a layer of Boehmite (AlOOH) on top of the carbon nanotube (CNT) film by solution-processed spray deposition. The CNT layer made-up by spraying, functions as an absorbing layer and the AlOOH serves as an anti-reflecting and protecting film. The anti-reflecting property of AlOOH layer effectively increases the absorptance of CNT coating by decreasing the reflectance. The effect of the thickness of AlOOH layer on the absorptance, adhesion, and thermal stability of the resulting CNT/AlOOH coating was investigated. The CNT/AlOOH coating with optimized thickness of AlOOH layer shows very high absorptance ( α ) of 0.975. The adhesion of the coating is in the range of 95–100% with significant increase of thermal stability. This new approach is expected to open new possibilities for fabricating low-cost, highly efficient and thermally stable solar-thermal devices which are based on simple coating processes.