The Uses of Renewable Energy in Buildings

Author(s):  
Paul C. Okonkwo ◽  
El Manaa Barhoumib ◽  
Wesam H. Beitelmal ◽  
Israr I. U. Hassan ◽  
Michael Nnamdi Azubuike ◽  
...  

Only 5% of Australia's energy utilization comes from renewables, while 86.3% of the electricity is produced from fossil fuels. Nonetheless, this pattern has been disturbed by the ongoing decommissioning and closure of old coal power plants, alongside the Australian policy to reduce fossil fuel emissions. Presently, Australia is at a pivotal phase of its change to renewable energy power generation and utilization specifically in residential and commercial buildings. Sustainability in renewable energy utilization is being achieved through guided government policies, reasonable energy costs, and improved energy technology transfer approaches. To give a refreshed delineation of renewable energy, related government policy, and the route ahead in the Australian setting, this chapter presents a deliberate Australia update with renewable energy generation and utilization in Australian buildings.

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2456
Author(s):  
Noman Khan ◽  
Fath U Min Ullah ◽  
Ijaz Ul Haq ◽  
Samee Ullah Khan ◽  
Mi Young Lee ◽  
...  

Renewable energy (RE) power plants are deployed globally because the renewable energy sources (RESs) are sustainable, clean, and environmentally friendly. However, the demand for power increases on a daily basis due to population growth, technology, marketing, and the number of installed industries. This challenge has raised a critical issue of how to intelligently match the power generation with the consumption for efficient energy management. To handle this issue, we propose a novel architecture called ‘AB-Net’: a one-step forecast of RE generation for short-term horizons by incorporating an autoencoder (AE) with bidirectional long short-term memory (BiLSTM). Firstly, the data acquisition step is applied, where the data are acquired from various RESs such as wind and solar. The second step performs deep preprocessing of the acquired data via several de-noising and cleansing filters to clean the data and normalize them prior to actual processing. Thirdly, an AE is employed to extract the discriminative features from the cleaned data sequence through its encoder part. BiLSTM is used to learn these features to provide a final forecast of power generation. The proposed AB-Net was evaluated using two publicly available benchmark datasets where the proposed method obtains state-of-the-art results in terms of the error metrics.


2021 ◽  
Vol 23 (06) ◽  
pp. 1128-1140
Author(s):  
Zahira Tabassum ◽  
◽  
Dr.Chandrashekhar Shastry ◽  

Excessive use of traditional energy sources such as fossil fuels has resulted in significant environmental deterioration. India is one of the world’s fastest-growing energy consumers, and it is making continual efforts to increase renewable energy generation. The use of renewable energy sources to generate electricity is expanding every day. Renewable energy integration with existing power systems is a difficult endeavor that necessitates strategy and development. Climate-friendly energy systems will result from the use of renewable energy sources in power generation, as they lower CO2 emissions caused by fossil fuels used in conventional power generation. This research looks at a renewable energy scenario using Gujarat as a case study, which is a leader in renewable energy generation. The policies taken by the Gujarat government to increase renewable energy’s participation in the energy mix, as well as the challenges and potential solutions for boosting the deployment of renewable energy sources across Gujarat, are discussed. This study can be used as a guide for policymakers and researchers in other states and around the world who want to boost renewable energy share.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiaojuan Lu ◽  
Leilei Cheng

With the advent of the new types of electrical systems that attach more importance to the renewability of the energy resource, issues arising out of the randomness and volatility of the renewable energy resource, such as the safety, reliability, and economic operation of the underlying power generation system, are expected to be challenging. Generally speaking, the power generation company can do a reasonable dispatch of each unit according to weather forecast and load demand information. Focusing on concentrating solar power (CSP) plants (wind power, photovoltaic, battery energy storage, and thermal power plants), this paper proposes a day-ahead scheduling model for renewable energy generation systems. The model also considers demand response and related generator set constraints. The problem is described as a mixed-integer nonlinear programming (MINLP) problem, which can be solved by the CPLEX solver to obtain an optimal solution. At the same time, the paper compares and analyzes the impact of concentrating solar power plants on other renewable energy generation and thermal power operation systems. The results show that the renewable energy generation system can lower power generation costs, reduce load fluctuation, and enhance the energy storage rate.


2012 ◽  
Author(s):  
Mark Woods ◽  
Michael Matuszewski ◽  
Robert Brasington

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