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Wind And Solar Power Systems: Design, Analysis,...

This book provides technological and socio-economic coverage of renewable energy. It discusses wind power technologies, solar photovoltaic technologies, large-scale energy storage technologies, and ancillary power systems. In this new edition, the book addresses advancements that have been made in renewable energy: grid-connected power plants, power electronics converters, and multi-phase conversion systems.

Wind and solar power systems: design, analysis,...

The text has been revised to include up-to-date material, statistics, and current technology trends. Three new chapters have been added to cover turbine generators, AC and DC wind systems, and recent advances solar power conversion.

It offers students, practicing engineers, and researchers a comprehensive look at wind and solar power technologies. It is designed as a reference and can serve as a textbook for senior undergraduates in a one-semester course on renewable power or energy systems.

The search for clean, renewable energy sources has yielded enormous growth and new developments in these technologies in a few short years, driving down costs and encouraging utilities in many nations, both developed and developing, to add and expand wind and solar power capacity. The first, best-selling edition of Wind and Solar Power Systems prov

B EE 457 Electrical/Power Electronic Systems in Renewable Energy (5)Provides a quantitative and practical introduction to renewable energy electrical/power electronic systems. Emphasis on the fastest growing solar and wind technologies. Electrical/electronic architectures of other technologies such as hydroelectric power and electric vehicles are introduced. Energy storage technologies, such as battery technologies and their associated power electronics are discussed. Prerequisite: a minimum grade of 1.7 in either B EE 331 or E E 331; recommended: B EE 215 and B EE 233. View course details in MyPlan: B EE 457

B EE 557 Electrical/Power Electronic Systems in Renewable Energy (5)The course provides in-depth coverage of the power electronics of a range of renewable technologies including solar, wind and hydroelectric. The power electronics for energy storage technologies utilized in renewable systems and for electric transportation systems are addressed. The course covers recent advances of control and management architectures and discusses them in the context of current renewable energy technologies. Recommended: degree in Electrical Engineering or equivalent.View course details in MyPlan: B EE 557

B EE 572 Power System Operations (5)Topics include: electric power grid and its operation in the United States; characteristics of generating units; power/load flow analysis; economic dispatch; unit commitment; optimal power flow; and introduction of renewable energy generation such as wind and solar energy and their integration into the grid. Prerequisite: a minimum grade of 2.5 in B EE 571.View course details in MyPlan: B EE 572

There are a number of steps to follow when planning to power your home with solar energy. After choosing which option is best for you to use solar (see step 3), follow the steps afterward that apply to you. Your solar energy installer and local utility company can provide more information on the exact steps you will need to take to power your home with solar energy.

Before starting the process of powering your home with solar energy, homeowners should investigate their energy use and consider potential efficiency upgrades. Homeowners should be well aware of their total electricity usage, and consider low-cost and easy-to-implement efficiency measures before choosing solar.

One of the most efficient ways for communities to go solar is through a Solarize program. Solarize programs allow a locally organized group of homeowners and businesses to pool their purchasing power to competitively select an installer and negotiate reduced rates. This bulk purchase enables more people to go solar because the group model makes the process easier, increases demand for solar, and also lowers installation costs.

HAP provides a graphical approach to creating building models for peak load and energy modeling projects. First import, scale, and orient architectural floor plan images. Then define multiple building levels (floors). Use the powerful new sketch-over to define the boundaries of spaces within the floor plans. The software will automatically calculate room dimensions and surface areas of floors, walls, ceilings, and roofs. Drag and drop window, door, and skylight rough openings. Configure sloped roofs, if necessary. From this data HAP extrudes the 2D floor plans into 3 dimensions, and renders the building for visualization and checking.

Solar energy was present ever since the beginning of time and the form of energy that it was in is only the same. The only thing that changes over time is our understanding of how to harvest such abundance of energy efficiently with minimal wastage. PV harvesting in small scales have dated back since the 1950s and possibly earlier times within the nineteenth and twentieth century (Silvi 2008). The harvesting of solar energy was not done in large scale and not connected in a primary power grid until the 2009, where the first large-scale PV harvesting installation was installed. The 230 kV utility scale PV system plant by Desoto Solar Energy Centre was established. Being the early plant to generate power for utility provision, the plant faces problems especially when compared to other types of renewable energy sources. One main problem for large-scale PV power storage and harvester is the uncontrollable amount of power generation and demand [shah2015]. It was from this root of problem that has led to many other researchers conduct plant feasibility and evaluations before considering establishment and integration of large-scale PV power plants.

There are various system storage designs that are being tested for its feasibility in implementation as well as power generations. One of the energy storage design was developed by Babacan et al. (2017). This storage system design implements a (CO)-based charge/discharge algorithm scheduling with convex optimization. The algorithm is located in close vicinity with solar PV systems and minimizes the electricity expense of anyone who also owns an ESS. It takes into consideration the usage time volumetric tariff and charge demand tariff for minimizing the electricity expenses. Babacan et al. (2017) mentions that other typical scheduling algorithms do not incorporate the charge demand tariff and volumetric tariff for customers, which have led to development of the algorithm in question. Customers who exceed their load requirements can be provided a supply charge to help in sustaining their energy generation at reasonable cost.

Another system design was implemented within multiple different modes of renewable energy harvesting systems. In managing energy generations from a micro-grid comprising PV, wind and biomass harvesters require complex systems especially the energy storage systems. This is due to the irregular nature and power generations of each different type of energy harvesters requiring power backup from non-renewable energy sources such as diesel generators. Singh and Singh (2016) have proposed an algorithm for automation of PV, wind and biomass energy harvesting to store energy within a battery. This algorithm was designed in mind that the energy harvester operates and supply electricity in an off-grid location. From these energy storage systems design mentioned, it is essential for an algorithm for energy storage to take serious accounts of the various parameters in each mode of energy harvesting that is included in a system. When observing these mentioned works, it can be concluded that systems design should be carefully implemented based on what model is used for what configuration of harvester systems. A poor and oversimplified algorithm utilized on a sophisticated renewable energy harvesting system could end up as a liability for consumers demoting the practicality of renewable energy harvesting plants.

The increasing importance of renewable energy deployment, notably solar energy, has urged researchers to examine the economic aspect of solar energy projects. Some of them assessed PV projects economically, but the scale of the projects, the location and the grid connection were different from a study to another. Other studies focused on the cost of electricity from solar power plants, proposing new calculation methods. Furthermore, some researchers examined the financial feasibility of LSS projects, as well as the environmental outcome of such projects.

Pillai and Naser (2018) carried out the economic assessment of a 1-MW grid-connected PV system optimized for matching the daily peak load by analyzing the LCOE, NPV, PBP and EBPT. PVSyst software was used for design and optimization of the PV system. The annual degradation rate of 0.5% and lifetime of 30 years was assumed. The results show a positive indication for investment in the project as the LCOE was found to be 43% less than the present cost of kWh generation. It was also suggested by the author that with implementation of a cooling system will allow LCOE to experience positive values. However, for the LCOE to become enhanced, the maintenance cost of such system must be equal to per unit of energy generated. This may not be plausible in real situation, since the maintenance cost will always be more due to accounts have to be taken in also cleaning of the solar PV cooling system and their sister components. Solar PV projects can be further supported by favorable policies and subsidies to diversify the generation mix of Bahrain and to be more financially viable at the same time. The study thus provides data on the simulated large-scale solar PV project built in Bahrain to satisfy the growing demand of electricity power in the city. However, some assumptions may need further study in order to fully justify the requirements for constructing large-scale PV stations. 041b061a72

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