ALBERT

Description: Stand-alone hybrid energy systems are an enticing option for electrification in remote areas in several aspects such as grid extension difficulty, economic feasibility and reliability. The use of existing micro-hydropower (MHP) with other renewable resources in rural areas has not been well studied. Moreover, it is challenging to use mathematical optimization algorithms for these kinds of real-world problems, so the derivative-free algorithm is highly sought. In this paper, a methodology has been proposed to perform the optimal sizing, financial and generation uncertainty analysis of solar photovoltaic (SPV) based on an MHP that is proposed to handle the intermittent power output of the SPV. The analysis is performed in two cases: using storage and without storage. The optimal sizing is performed using the least present value cost and reliability constraint using different derivative-free algorithms. The storage-based hybrid system has been found to generate reliable electricity at minimal cost than without a storage-based one. This study would be helpful to propose electrification and existing micro-hydro reinforcement policies to provide reliable electricity in rural areas.

Description: In city gas pressure reducing stations, in order not to hydrate natural gas after a sudden drop in pressure, the gas temperature is raised by a heater. The increase in temperature is such that after the pressure drop, the gas inside the pipes does not freeze. These heaters are gas burning and very high consumption, and because they use fossil fuels, produce environmental pollution. Accordingly, in this research, solar energy will be used to preheat the gas, which will be used for the most accurate analysis of TRNSYS software. In this regard, the amount of utilization of the sun and the amount of energy required for preheating will be obtained. After the implementation of the TRNSYS program, the highest amount of energy supply by the sun is related to spring, which on this day provides 55% of the thermal energy required by the load by solar energy.

Description: In order to reduce the carbon emission and improve the de-carbonization in distribution of vehicle routing problem with simultaneous delivery and pickup (VRPSDP), a two-stage disruption management method based on the changes of customer demand is proposed in this paper. Firstly, a mathematics model of VRPSDP is established to optimize the parameters and the distribution carbon emission cost and time window deviation. Next, several carbon emission equations in VRPSDP are inducted and designed. Considering the strong global searching ability of quantum particle swarm optimization (QPSO) and combing the advantages of superposition and parallelism of quantum computing, a multi-phase QPSO (MQPSO) is proposed to enhance global searching ability. At last, on the basis of Solomon examples, the validity of the proposed model and MQPSO is tested and compared with the classical algorithms at present. The simulation results show that the proposed method can not only achieve the goal of performance but also meet the practical requirements of reducing carbon emissions in VRPSDP.

Description: Renewable energy sources cannot guarantee long-term and stable output supply when they are given energy consumption at the load end. At the same time, traditional solar and utility power supply systems cannot guarantee the priority of using solar energy to generate electricity, which has certain limitations. In this regard, an energy control strategy for achieving smooth and no backflow switching and prioritizing the use of clean energy solar energy under a joint power supply system of a solar power grid and a municipal power grid is proposed, which is used for a conventional combined power supply system of a contactor switching circuit. A topology of low voltage power grid is proposed, which effectively reduces the impact on the solar power grid and the municipal power grid during the system switching process combined control mode for controlling the current phase and repetitive control at the output end of the solar power grid in the combined power supply mode, and adding a feedforward control method for the grid voltage is adopted to ensure that the solar grid and the municipal power prioritize the use of clean energy solar energy and, at the same time, ensure the maximum utilization of solar energy. This paper chose the combined power supply system with the solar power grid and the municipal power grid as the object of this research. The topology structure and controlling strategy of the power supply system were comprehensively and deeply researched, and on this basis, the combined power supply system prototype was designed on the foundation of DSP28335 and CPLD. Moreover, hardware parameters are designed in the system, and an energy management optimization algorithm based on the system is developed on the corresponding experimental platform. The experimental results show that the proposed energy control strategy can effectively reduce the impact on the solar power grid and the municipal power grid during the system switching process, ensure that the solar power grid and the municipal power grid have no backflow combined power supply and give priority to the use of clean energy solar energy.

Description: To reveal the flame propagation and CO/CO2 generation characteristics of coal dust explosion, lignite dust cloud is studied through experiment and numerical simulation in a horizontal pipeline apparatus. The result indicated that within 0.5 s after explosion, the flame propagation distance rapidly increases until the explosion reaction is sufficient. FLUENT is used to simulate the flame propagation and CO/CO2 generation characteristics. It is found that the simulation error is acceptable and the simulation result is consistent with the experimental result. The explosion space is divided into five zones by simulating the flame temperature. It also revealed that z = 0.3 ~ 0.6 m in the pipeline generates more CO because it is closed to the ignition zone. As the explosion spreads through the pipeline, the generated CO accumulates to the bottom of the pipeline, and the generated CO2 accumulates more in the upper part of the pipeline.

Description: Nowadays, the global energy and environmental problems are becoming more and more serious, which promotes the development and utilization of renewable and clean energy in various countries. Intelligent car involves many subjects such as electronic technology, artificial intelligence, automatic control technology, sensor technology and computer technology and has become an important part of the application of artificial intelligence. Solar cell is a necessary part of the normal operation of the solar intelligent car, which can provide clean energy for the intelligent car. In this paper, the image recognition technology is used to design the intelligent vehicle control system. According to the intelligent vehicle path recognition, the scale invariant feature transform (SIFT) algorithm is improved to improve the accuracy of intelligent vehicle recognition. Data fusion is used to process the data detected by multi-sensor, and the running state of intelligent vehicle is studied. An evaluation method of intelligent vehicle navigation parameters based on association rules and belief network is proposed. The maximum power point tracking control is realized by using the interference observation method to ensure that the intelligent vehicle can track the maximum power point of the solar cell.

Description: Accurate prediction of electricity sale has a positive effect on power companies in rationally arranging power supply plans, scientifically optimizing power resource allocation, improving power management efficiency, saving energy and reducing consumption. Predicting future electricity sale based on historical electricity sale data can essentially be summarized as a time series forecasting problem. This paper proposes a fast and memory-efficient method, which adopts the expressive power of deep neural networks and the time characteristics of sequence-to-sequence structure (parallel convolution and recurrent neural network) for long range forecasting in electricity sale. Through a large number of experiments and evaluation of real-world datasets, the effectiveness of the proposed method is proved and verified in terms of prediction accuracy, time consuming and training speed.

Description: The production of liquefied natural gas (LNG) is a high energy-consuming process. The study of ways to reduce energy consumption and consequently to reduce operational costs is imperative. Toward this purpose, this study proposes a hybrid system adopting a mixed refrigerant for the liquefaction of natural gas that is precooled with an ammonia/water absorption refrigeration (AR) cycle utilizing the exhaust heat of a molten carbonate fuel cell, 700°C and 2.74 bar, coupled with a gas turbine and a bottoming Brayton super-critical carbon dioxide cycle. The inauguration of the ammonia/water AR cycle to the LNG process increases the cooling load of the cycle by 10%, providing a 28.3-MW cooling load duty while having a 0.45 coefficient of performance. Employing the hybrid system reduces energy consumption, attaining 85% overall thermal efficiency, 53% electrical efficiency and 35% fuel cell efficiency. The hybrid system produces 6300 kg.mol.h−1 of LNG and 146.55 MW of electrical power. Thereafter, exergy and sensitivity analyses are implemented and, accordingly, the fuel cell had an 83% share of the exergy destruction and the whole system obtained a 95% exergy efficiency.

Description: The skylight on the roof of an atrium can be popular for commercial malls to illuminate the core area of the building. However, the solar radiation and its heat can get into the building together with the daylight, causing excessive cooling load. This paper studies the daylighting and energy performances of skylight coverage area for the air-conditioned atriums in the hot and humid regions. The energy performance with different atrium heights, glass types and the coverage ratios of the skylight are studied. The daylight performance was simulated by the ray-tracing Radiance and was transferred into EnergyPlus for energy evaluations. The finding suggested that, for hot and humid climates, the skylight coverage ratio should be controlled carefully to prevent the excessive solar heat gain. When the on/off lighting control is applied, the total energy consumption of the single-floor cases (or of the top floor for the multi-floor cases) leveled off when the coverage ratio of the skylight reached 9%. Thus, the skylight is favorable to the energy saving of the low-rise or single-floor commercial buildings only under the current assumptions, as the ground of the atrium cannot be well illuminated while the excessive solar radiation gets into the building. The skylight should be shaded in cooling seasons to prevent the excessive solar heat gains.

Description: Lithium-ion batteries retired from electric vehicles can provide considerable economic benefits when they are retired for secondary use. However, retired batteries after screening and restructuring still face the problem of inaccurate battery pack state-of-charge (SOC) estimation due to the existence of extreme inconsistency. To solve this problem, an adaptive fading unscented Kalman filtering (AFUKF) algorithm based on the cell difference model (CDM) is proposed in this paper for improving the accuracy of SOC estimation of retired lithium-ion battery packs. Firstly, an improved CDM based on a hypothetical Rint model is developed based on a second-order resistor/capacitor equivalent circuit model. Secondly, an AFUKF algorithm is developed to improve the adaptability and robustness of local state estimation against process modelling errors. Finally, characteristic data are obtained by conducting discharge tests on the screened retired lithium-ion batteries under specific operating conditions. The proposed method can improve the accuracy of SOC estimation of retired lithium-ion battery packs and provide a new idea for SOC estimation of retired lithium-ion battery packs, as shown by the simulated real experimental data.