scholarly journals Aerostatic Way of Harvesting High Altitude Wind Energy

2019 ◽  
Vol 8 (4) ◽  
pp. 7840-7844

Renewable energy system in electrical power generation is one of important field of electrical engineering due to its source is natural, reusable and environmental pollution free and cost free. There are renewable energies such as wind, solar and so on. The wind is a free, clean, and inexhaustible energy source. It has served mankind well for many centuries by propelling ships and driving wind turbines to pump water. It has become one of the most attractive energy system in several decades due to rich availability. The important proposed contribution in this work is to enhance the efficiency of renewable energy using AEROSTATIC WAY OF HARVESTING WIND ENERGY that allows turbines to capture as much as possible wind by increase in the altitude at which is the turbine is placed. Which is done by attaching the turbine to aerostat and the aim of the study is to extract maximum energy of the turbine and transmit it to grid, storage device with suitable converters and controllers.

Author(s):  
Dilara Gulcin Caglayan ◽  
Heidi Ursula Heinrichs ◽  
Detlef Stolten ◽  
Martin Robinius

The transition towards a renewable energy system is essential in order to reduce greenhouse gas emissions. The increase in the share of variable renewable energy sources (VRES), which mainly comprise wind and solar energy, necessitates storage technologies by which the intermittency of VRES can be compensated for. Although hydrogen has been envisioned to play a significant role as a promising alternative energy carrier in a future European VRES-based energy concept, the optimal design of this system remains uncertain. In this analysis, a hydrogen infrastructure is posited that would meet the electricity and hydrogen demand for a 100% renewable energy-based European energy system in the context of 2050. The overall system design is optimized by minimizing the total annual cost. Onshore and offshore wind energy, open-field photovoltaics (PV), rooftop PV and hydro energy, as well as biomass, are the technologies employed for electricity generation. The electricity generated is then either transmitted through the electrical grid or converted into hydrogen by means of electrolyzers and then distributed through hydrogen pipelines. Battery, hydrogen vessels and salt caverns are considered as potential storage technologies. In the case of a lull, stored hydrogen can be re-electrified to generate electricity to meet demand during that time period. For each location, eligible technologies are introduced, as well as their maximum capacity and hourly demand profiles, in order to build the optimization model. In addition, a generation time series for VRES has been exogenously derived for the model. The generation profiles of wind energy have been investigated in detail by considering future turbine designs with high spatial resolution. In terms of salt cavern storage, the technical potential for hydrogen storage is defined in the system as the maximum allowable capacity per region. Whether or not a technology is installed in a region, the hourly operation of these technologies, as well as the cost of each technology, are obtained within the optimization results. It is revealed that a 100 percent renewable energy system is feasible and would meet both electricity demand and hydrogen demand in Europe.


Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1269
Author(s):  
Yongzhen Wang ◽  
Congchuan Hu ◽  
Boyuan Wu ◽  
Jing Zhang ◽  
Zhenning Zi ◽  
...  

Considering the huge power consumption, rapid response and the short-term heat reserving capacity of the air conditioning load in the building’s energy system, the air conditioning load and its system can be equivalent to the virtual energy storage device for the power grid. Therefore, to obtain a high matching building renewable energy system, a virtual energy storage system of the air conditioning load, accompanied by a storage battery, was built in the paper. Then, operating strategies for the virtual energy storage of the air conditioning load and storage battery were designed. Further, to quantize the contribution of the virtual energy storage to the improvement of matching characteristics, two indicators of the demand side and supply side in the energy system were adopted, including on-site energy fraction (OEFr) and on-site energy matching (OEMr). Lastly, matching characteristic research of the building’s renewable energy system based on virtual energy storage of the air conditioning load was established and analyzed by TRNSYS and MATLAB in Tianjin, China. The results revealed that a better matching characteristic performance of the building’s renewable energy systems driven by virtual energy storage was obtained. In the condition set out in the paper, compared with that without virtual energy storage, the average values of OEFr and OEMr after virtual energy storage were 0.66 and 0.77, which increased by 8.19% and 8.45% respectively. Simultaneously, the battery operation performance in the building renewable system was improved when the virtual energy storage was working. The times of charge and discharge cycles decreased after virtual energy storage, and the depth of discharge of the battery reduced by 23.37% on a specific day.


Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7084
Author(s):  
Fadi Kahwash ◽  
Basel Barakat ◽  
Ahmad Taha ◽  
Qammer H. Abbasi ◽  
Muhammad Ali Imran

This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simulations were carried out using the actual and forecasted parameters to improve decision making. The results show that incorporating forecasted parameters into the optimisation allows to identify the subset of optimal solutions that will become sub-optimal in the future and, therefore, should be avoided. Finally, a framework for choosing the most suitable subset of optimal solutions was presented.


Sign in / Sign up

Export Citation Format

Share Document