State of the Art in the Optimisation of Wind Turbine Performance Using CFD

Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained

Optimization of a PV-Wind Hybrid Power Supply Structure with Electrochemical Storage Intended for Supplying a Load with Known Characteristics

An important aspect of the off-grid utilization of hybrid generation systems is the integration of energy storage facilities into their structures, which allows for improved power supply reliability. However, this results in a significant increase in the cost of such systems. Therefore, it is justified to use optimization resulting in the minimization of the selected economic indicator taking into account the most important technical constraints. For this reason, this work proposes an algorithm to optimize the structure of a hybrid off-grid power distribution system (with electrochemical energy storage), designed to supply a load with known daily energy demand. The authors recommend genetic algorithm utilization as well as a modified criterion for evaluating the quality of solutions based on the Levelized Cost of Energy (LCOE) index. Several technical and economic analyses were presented, including unit costs, power distribution of the wind and solar sections, nominal battery capacity, SSSI index (System Self-Sufficiency Index), etc. The model of the system includes durability of the elements which have a significant impact on the periodic battery replacement. The tests were carried out for two types of loads and two types of electrochemical batteries (NMC-Lithium Nickel Manganese Cobalt Oxide; and PbO2-Lead-Acid Battery), taking into account the forecast of an increased lifetime of NMC type batteries and decreasing their price within five years. The proposed synthesis method of photovoltaic-wind (PV-wind) hybrid off-line systems leads to limiting the energy capacity of electrochemical storages. Based on the analyses, the authors proposed recommended methods to improve (reduce) the value of the criterion index (LCOE) for PV-wind off-grid systems while maintaining the assumed level of power supply reliability.Fil: Kasprzyk, Leszek. Poznań University of Technology; PoloniaFil: Tomczewski, Andrzej. Poznań University of Technology; PoloniaFil: Pietracho, Robert. Poznań University of Technology; PoloniaFil: Nadolny, Zbigniew. Poznań University of Technology; PoloniaFil: Mielcarek, Agata. Poznań University of Technology; PoloniaFil: Tomczewski, Krzysztof. Opole University of Technology; PoloniaFil: Trzmiel, Grzegorz. Poznań University of Technology; PoloniaFil: Alemany, Juan Manuel. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica. Instituto de Protecciones de Sistemas Eléctricos de Potencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentin

Research of interconnected wind turbines with intelligent control

Development of renewable energy sources in Kazakhstan, including wind energy, brings the needs to design and develop control and integration to a power system. The aim of the Project is to design a power converter supplied by intelligent controllers that provide a stable 3-phase output voltage in the presence of uncertain fluctuations of a wind speed

A review of net zero energy buildings in hot and humid climates: Experience learned from 34 case study buildings

Sustainable development in the building sector requires the integration of energy efficiency and renewable energy utilization in buildings. In recent years, the concept of net zero energy buildings (NZEBs) has become a potential plausible solution to improve efficiency and reduce energy consumption in buildings. To achieve an NZEB goal, building systems and design strategies must be integrated and optimized based on local climatic conditions. This paper provides a comprehensive review of NZEBs and their current development in hot and humid regions. Through investigating 34 NZEB cases around the world, this study summarized NZEB key design strategies, technology choices and energy performance. The study found that passive design and technologies such as daylighting and natural ventilation are often adopted for NZEBs in hot and humid climates, together with other energy efficient and renewable energy technologies. Most NZEB cases demonstrated site annual energy consumption intensity less than 100 kW-hours (kWh) per square meter of floor space, and some buildings even achieved “net-positive energy” (that is, they generate more energy locally than they consume). However, the analysis also shows that not all NZEBs are energy efficient buildings, and buildings with ample renewable energy adoption can still achieve NZEB status even with high energy use intensity. This paper provides in-depth case-study-driven analysis to evaluate NZEB energy performance and summarize best practices for high performance NZEBs. This review provides critical technical information as well as policy recommendations for net zero energy building development in hot and humid climates

Optimal Scheduled Power Flow for the Distributed Photovoltaic-Wind Turbine-Diesel Generator with Battery Storage System

Published ThesisThe high cost of the transportation of power from the grid to rural areas is a great concern for most of the countries in the world and the above results in many remote areas not being able to have electricity. To overcome the challenges of electrification of rural areas, some generate their own energy by continuous or prime power diesel generators (DGs) or by producing energy using different small-scale renewable energy sources (Photovoltaic, Wind, hydroelectric and others). Despite their advantages of being easy to transport, easy to install and of low initial cost, diesel generators present many disadvantages when they are used as continuous or prime power sources due to the high requirement of fuels and non-linearity of daily load demand profile. Beside the cost, diesel generators are detrimental to the environment and cause global warming. To overcome the issues of costs and global warming, diesel generators can be used in combination with renewable energy such as photovoltaic as a backup to form a hybrid power generation system. The stand-alone photovoltaic (PV) and wind turbine (WT) power generators have drawbacks as the power produced depends on the sun and wind, which means that if there is no sun or wind, no electricity can be produced. The non-linearity of solar and wind resources makes the stand-alone photovoltaic and wind operation non-reliable. The combination of photovoltaic-wind turbine–diesel-battery power generation ensures that the energy produced is reliable and efficient. The diesel generator is used as back up to the system and is used only when the renewable energy sources are insufficient and the battery banks are low. The PV-WT-Diesel-Battery hybrid power system reduces the consumption of fuel hence minimizes fuel costs. The system also presents the advantage of less pollution to the environment due to the short running time of the generator, a low generator maintenance requirement and long life expectancy of the generator. As indicated above, the hybrid systems have the advantage of saving costs compare to a standalone diesel generator operation, but the system requires proper control to minimize the operation costs while ensuring optimum power flow considering the intermittent solar and wind resources, the batteries state of charge and the fluctuating load demand. The aim of this research is to develop two different control strategies to minimize the daily operational cost of hybrid systems involving PV/WT/DG and batteries by finding the optimal schedules for running the diesel generator while in the meantime responding to the power required by the load. The two control strategies developed are “Continuous operational mode” and “ON/OFF” operational mode. The developed mathematical models of the two control strategies are simulated using MatLab functions, with “fmincon solver” for continuous operational mode and “Intlinprog solver” for ON/OFF operational mode

Computational intelligence techniques for HVAC systems: a review

Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO2 emissions. The drive to reduce energy use and associated greenhouse gas emissions from buildings has acted as a catalyst in the development of advanced computational methods for energy efficient design, management and control of buildings and systems. Heating, ventilation and air conditioning (HVAC) systems are the major source of energy consumption in buildings and an ideal candidate for substantial reductions in energy demand. Significant advances have been made in the past decades on the application of computational intelligence (CI) techniques for HVAC design, control, management, optimization, and fault detection and diagnosis. This article presents a comprehensive and critical review on the theory and applications of CI techniques for prediction, optimization, control and diagnosis of HVAC systems.The analysis of trends reveals the minimization of energy consumption was the key optimization objective in the reviewed research, closely followed by the optimization of thermal comfort, indoor air quality and occupant preferences. Hardcoded Matlab program was the most widely used simulation tool, followed by TRNSYS, EnergyPlus, DOE–2, HVACSim+ and ESP–r. Metaheuristic algorithms were the preferred CI method for solving HVAC related problems and in particular genetic algorithms were applied in most of the studies. Despite the low number of studies focussing on MAS, as compared to the other CI techniques, interest in the technique is increasing due to their ability of dividing and conquering an HVAC optimization problem with enhanced overall performance. The paper also identifies prospective future advancements and research directions

Research of interconnected wind turbines with intelligent control

Development of renewable energy sources in Kazakhstan, including wind energy, brings the needs to design and develop control and integration to a power system. The aim of the Project is to design a power converter supplied by intelligent controllers that provide a stable 3-phase output voltage in the presence of uncertain fluctuations of a wind speed