Governmental support and renewable energy production: A cross-country review

Smirnova, Elena; Kot, Sebastian; Kolpak, Eugeny P.; Shestak, Viktor

doi:10.1016/j.energy.2021.120903

Cited by 93 publications

(29 citation statements)

References 53 publications

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“…Other forms of renewable energy include biomass energy harnessed from solid fuel from plant materials to generate electricity. Moreover, hydropower is one of the most commercialized forms of renewable energy harnessed from water reservoirs used to turn turbines that generate electricity [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Factors Influencing Consumer’s Adoption of Renewable Energy

et al. 2021

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The objective of this study was to investigate the factors that influence the consumer adoption of renewable energy in Thailand. The study adopted an extended theory of planned behavior (TPB) by including three additional variables. The study applied a quantitative study methodology, with primary data collected using a survey of consumers in five major cities in Thailand. The data were analyzed using structural equation modeling (SEM). The findings of the study indicated that perception of self-effectiveness, environmental concern, renewable energy awareness, and beliefs about renewable energy benefits have a significant and positive effect on consumers’ intention to adopt renewable energy. The cost of renewable was found to have a negative but non-significant influence on consumers’ adoption of renewable energy, while risk/trust perception was found to have a positive but non-significant influence on consumers’ adoption of renewable energy. The study concluded that stakeholders should take into account the aspects of perception of self-effectiveness, environmental concern, renewable energy awareness, and beliefs about renewable energy benefits when running campaigns to promote the consumer adoption of renewable energy in Thailand

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Section: Introductionmentioning

confidence: 99%

Factors Influencing Consumer’s Adoption of Renewable Energy

et al. 2021

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“…By defining the specific heath of the metals used (copper/ aluminium) it is possible to calculate in the same way the heating absorbed/ceded from the reticular structure by means of the Eqs. (3,4).…”

Section: Methodsmentioning

confidence: 99%

“…The increase in energy demand and environmental issues due to the widespread use of fossil fuels encouraged many countries to focus on sustainability, for this reason, renewable and sustainable energy sources are getting more and more important [1][2][3]. One of the most affordable and favourable sources of renewable green energy which is drawing particular attention is the solar one [4,5].…”

Section: Introductionmentioning

confidence: 99%

Design and analysis of compound structures integrated with bio-based phase change materials and lattices obtained through additive manufacturing

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et al. 2021

Int J Adv Manuf Technol

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Phase change materials (PCMs) are an interesting category of materials employed in latent heat thermal energy storage, such as ad hoc designed heat exchangers. Nowadays, there are several typologies of PCMs, which derive from the wastes of the agricultural industry, which could be used for this kind of design. Each material made of biological waste has a different melting/solidification point and latent heat of fusion/solidification, which means flexibility of design on the heat exchangers by considering the different thermal proprieties of the chosen material. Also, using recycled material from wastes can lead to an overall improvement of the resources and goes hand in hand with the need of today’s society to aim more and more at a Circular Economy. The industrial development of this kind of material is limited by its thermal properties, such as poor thermal conductivity both in liquid and solid phases, leading to low heat transfer effectiveness. To overcome these limitations, in this paper, the bio-based PCMs were integrated into a metallic reticular structure made of copper and aluminium and realised through Indirect-Additive Manufacturing, to improve the overall thermal conductivity of the system and increase the efficiency of the heat transfer. Four compound structures filled each time with four different PCMs were realised and tested, in order to thermally characterise each combination of materials used and choose which one has an overall better thermal behaviour. The results showed how the thermal storage/release was improved by 10% for the copper reticular structure, even if must be considered the tradeoff between better thermal management and the increase of the costs and the weight of the designed heat exchanger.

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“…Sustainable energy has become increasingly important due to the present-day shortage of and pollution from fossil fuels (Albuyeh, 2013;Menon, 2013;Bozchalui, 2015;Brahman and Jadid, 2015;Zhang et al, 2015;Güney, 2019;Hasan Mehrjerdi, 2021;Rajvikram Madurai Elavarasan et al, 2021;Thomas Sattich et al, 2021). Consequently, renewable power generation technologies such as wind, solar, hydro, and biomass are used widely (Rajkumar, 2011;Francesco Calise and Piacentino, 2014;Pazouki, 2014;Zhaoyang Dong and Wen, 2014;Pazouki, 2016;Elena Smirnova et al, 2021;Eric O Shaughnessy et al, 2021;Olusola Bamisile et al, 2021;Pradhan et al, 2021). Simultaneously, energy storage technologies such as fuel cells, hydrogen storage, supercapacitors, and pumped storage systems (PSSs) have attracted increasing attention (Yves Pannatier et al, 2010;Pazouki, 2014;Brahman and Jadid, 2015;Zhang et al, 2015;Pazouki, 2016;Li et al, 2017a;Schmidt et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning-Based Model Predictive Control Method for Pumped Storage Systems

et al. 2021

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Integrated systems required for renewable energy use are under development. These systems impose more stringent control requirements. It is quite challenging to control a pumped storage system (PSS), which is a key component of such power systems. Because of the S-characteristic area of the PSS pump turbine, traditional proportional-integral-derivative (PID) control induces considerable speed oscillation under medium and low water heads. PSSs are difficult to model because of their nonlinear characteristics. Therefore, we propose a machine learning (ML)-based model predictive control (MPC) method. The ML algorithm is based on Koopman theory and experimental data that includes PSS state variables, and is used to establish linear relationships between the variables in high-dimensional space. Subsequently, a simple, accurate mathematical PSS model is obtained. This mathematical model is used via the MPC method to obtain the predicted control quantity value quickly and accurately. The feasibility and effectiveness of this method are simulated and tested under various operating conditions. The results demonstrate that the proposed MPC method is feasible. The MPC method can reduce the speed oscillation amplitude and improve the system response speed more effectively than PID control.

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Governmental support and renewable energy production: A cross-country review

Cited by 93 publications

References 53 publications

Factors Influencing Consumer’s Adoption of Renewable Energy

Factors Influencing Consumer’s Adoption of Renewable Energy

Design and analysis of compound structures integrated with bio-based phase change materials and lattices obtained through additive manufacturing

A Machine Learning-Based Model Predictive Control Method for Pumped Storage Systems

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