Geometrical investigation of microchannel with two trapezoidal blocks subjected to laminar convective flows with and without boiling

Microchannels are important devices to improve the heat exchange in several engineering applications as heat, ventilation and air conditioning, microelectronic cooling, power generation systems and others. The present work performs a numerical study of a microchannel with two trapezoidal blocks subjected to laminar flows, aiming to analyze the influence of the boiling process on the geometric configuration of the microchannel. Constructal Design and Exhaustive Search are used for the geometrical evaluation of the blocks. The Mixture multi-phase model and the Lee phase change model were both employed for the numerical simulation of the boiling process. In this study, the influence of the height and higher width of the first block (H11/L11) over the heat transfer rate and pressure drop for different magnitudes of the ratio between the lower width and higher width (L12/L11) was investigated. It is considered water in monophase cases and water/vapor mixture for multiphase flow. Two different Reynolds numbers (ReH = 0.1 and 10.0) were investigated. Results indicated that, for the present thermal conditions, the consideration of boiling flows were not significant for prediction of optimal configurations. Results also showed that in the cases where the boiling process was enabled, the multi-objective performance was higher than in the cases without boiling, especially for ReH = 0.1.

Knowledge Based Engineering for Hydrogen Gas Turbines and Burners Design: a review

Hydrogen gas turbines and burners need high attention and their appropriate realization, yet during their design, can lead important benefits for the whole sector. Realizing the best design, the first time, reduces reworks and requests of design changes from the manufacturing departments. In this field, Knowledge Based Engineering is a good strategy for embedding, in an automatic way, experts’ knowledge into CAD models during the design of a component. It enables a reduction of human errors and costs in several design tasks and improving the final quality of a component model. With these premises, the aim to the study is to lead improvements and appropriate actions in the design and re-configuration of hydrogen power generation systems (i.e. gas turbines and burners) by means of KBE, leading improvements yet in this early phase of the global race for hydrogen. A systematic literature review is carried out to explore the current state of art for the application of KBE for the design of turbines and burners in different industrial sectors. Evidences from the practice are collected in a structured classification and elaborated and summarized for application in the design of gas turbines and burners for the hydrogen production.

A Review of the Optimization Design and Control for Ocean Wave Power Generation Systems

Ocean wave power generation techniques (converting wave energy into electrical energy) have been in use for many years. The objective of this paper is to review the design, control, efficiency, and safety of ocean wave power generation systems. Several topics are discussed: the current situation of ocean wave power generation system tests in real ocean waves; the optimization design of linear generator for converting ocean wave energy into electrical energy; some optimization control methods to improve the operational efficiency of ocean wave power generation systems; and the current policy and financial support of ocean wave power generation in some countries. Due to the harsh ocean environment, safety is another factor that ocean wave power generation systems will face. Therefore, before the conclusion of this review, a damping coefficient optimization control method based on the domain partition is proposed to improve the efficiency and safety of ocean wave power generation systems.

Climate and Environmental Benefit Study of PV Resource Development: Case Study of Angola

Vigorously promoting the development of photovoltaic (PV) resources is a positive measure taken by humanity in response to the changes in global climate and environment. At the same time, combining photovoltaic power generation systems with traditional power generation systems, using the advantages of different power generation systems to achieve real-time scheduling optimization has become an urgent problem to be solved in engineering applications. This paper attempts to study the climate and environmental benefits of the development of photovoltaic resource in Africa by taking Angola as an example based on actual project data. According to the characteristics, load requirements, seasonal characteristics and actual engineering background of Tombwa in Angola, a baseline Scenario and four comparative Scenarios were established, and the operating costs of the five Scenarios in local rainy season and dry season were obtained respectively. The cost of electricity for the five Scenarios calculated subsequently. Through real-time scheduling and optimization of the software, the emission characteristics of CO2, NOx and CO under five Scenarios are obtained, and the climate benefits and environmental benefits of the five scenarios are further analyzed and compared. The results show that the development of photovoltaic resources in Angola has good climate and environmental benefits. In addition, the combine application of diesel, PV and battery power system will be the most effective of the five Scenarios to reduce the CO2 emissions with the lowest levelized cost of electricity (LCOE) of 0.38 yuan/kwh, as a cost-effective solution in remote areas of Angola, Africa.

Optimal Sizing and Placement of Distributed Generation (DG) Using Particle Swarm Optimization

Continuous urban development and sustainable development goals to develop cities and transform them into smart cities faces many challenges that appear in the transfer of electricity to this place or the difficulty and high price of building a station in this place. And power loss and voltage instability are major problems in distribution systems. However, these problems are typically mitigated by efficient network reconfiguration. Distributed generation (DG) can be used in the distribution systems to fight the increase of the load demand and it improve power generation systems and improvement the system efficiency. But it is very strange that if the generators are placed in an ill-considered size and in an inappropriate location, this causes the system to weaken, which has a bad effect on use, and this is not desirable. Not only that, but with the increase in the demand for power to cope with the increasing loads, stages of loss of power appear when it enters the distribution stage through transmission lines to loads. Therefore, the process of selecting the appropriate size and location with the general cost and taking into account environmental factors is a very important process to ensure the stability and reliability of the system .In the event that the generators are placed in an inappropriate size and in an inappropriate location, this leads to many problems in voltage, power and distribution, which causes severe weakness of the system, which causes an increase in the chance that electricity is not connected to the loads. So the appropriate way to choose the right placement and size is very important. In this study, we study the best place in which distribution generators can be added and the best size for them using PSO and its implementation on IEEE14 standard systems

A Survey on Electric Power Demand Forecasting

Recently there has been tremendous change in use of the forecasting techniques due to the increase in availability of the power generation systems and the consumption of the electricity by different utilities. In the field of power generation and consumption it is important to have the accurate forecasting model to avoid the different losses. With the current development in the era of smart grids, it integrates electric power generation, demand and the storage, which requires more accurate and precise demand and generation forecasting techniques. This paper relates the most relevant studies on electric power demand forecasting, and presents the different models. This paper proposes a novel approach using machine learning for electric power demand forecasting.