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Green Energy and Consumer Preferences: Sustainability and Society

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 19081

Special Issue Editor


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Guest Editor
Albers School of Business and Economics, Seattle University, Seattle, WA 98122, USA
Interests: development economics; environmental policies; Indian economy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Despite the disruptions caused by COVID-19, the global demand for renewables remains intact and resilient. Recognizing that renewables can help to meet climate targets, spur economic growth, and create jobs, many nations are centering their recovery policies around green energy. Ample scholarship is available from a supply side (producer’s) perspective, such as green energy firms (Ng and Zheng 2018) and the green energy sector (Conte and Jacobsen 2016), but the consumer perspective has not received commensurate attention in academic research. In industrialized countries such as the United States, the UK, France, Finland, Australia, and Germany, many green energy programs have been implemented to support the providers of clean electricity from renewable sources including solar, wind, hydro, biomass, or ocean. However, many of these programs have been unsuccessful due to low consumer participation. Although people state that they are pro-green energy, they do not actually participate in green energy programs (Zhang and Wu, 2012; Kaenzig et al., 2013; Rowlands et al., 2002; Stigka et al., 2014). There could be various explanations for the discrepancies between consumers’ stated preference on green electricity and actual behaviors: The higher production costs associated with renewable energy as compared to fossil fuel energy may result in some of these costs being passed onto consumers, for example. Thus, there is a need to understand how consumers react to the development of clean energy and how they makes choices about green energy products not just in industrialized nations but also in developing economies.  

Identifying the consumer’s perspective is a crucial first step in formulating energy and environmental policies. The success of green energy schemes depends crucially on the support of consumers in addition to the private sector and the government. Therefore, the purpose of this Special Issue is to showcase research on consumers’ WTP for renewable energy sources in electricity production. Authors may submit theoretical papers or local country/area studies that explore the possible determinants which may affect consumers’ WTP for renewable energy.

This Special Issue welcomes a diversity of submissions and research methods that deliver practical policy knowledge because the transition to sustainable societies requires a set of applicable polices.

Prof. Dr. Meenakshi Rishi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

22 pages, 1983 KiB  
Article
A Method for Stakeholder Mapping in Connection with the Implementation of a Development Project
by Katarzyna Styk and Paweł Bogacz
Energies 2022, 15(4), 1592; https://doi.org/10.3390/en15041592 - 21 Feb 2022
Cited by 3 | Viewed by 3568
Abstract
In the case of the energy sector (including mining companies) and the implementation of their development projects, it is necessary to obtain a social license to operate for a given project, which is associated with the involvement of various groups of stakeholders in [...] Read more.
In the case of the energy sector (including mining companies) and the implementation of their development projects, it is necessary to obtain a social license to operate for a given project, which is associated with the involvement of various groups of stakeholders in the project and should be consistent with the company’s strategy. The basis for obtaining permission to operate is to conduct a stakeholder mapping process. Such an analysis will aid effective dialogue with all stakeholders and guide appropriate relationship building. The aim of this paper is to present the authors’ method of stakeholder mapping, which is an independent methodical idea that can be implemented in any enterprise. This paper comprehensively presents this algorithm, starting with the identification of stakeholder groups, through the determination of their level of interest and influence, ending with the construction of a matrix indicating the necessity of undertaking specific communication activities. Finally, the implementation of the created method in the form of a real business project is presented, the advantages are pointed out, and the possibilities and determinants of further development of this algorithm are presented. This method is proposed to companies from the energy sector, including those mining energy resources, as companies that have a significant impact on their social and environmental environment. Full article
(This article belongs to the Special Issue Green Energy and Consumer Preferences: Sustainability and Society)
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22 pages, 4528 KiB  
Article
The Probabilistic Optimal Integration of Renewable Distributed Generators Considering the Time-Varying Load Based on an Artificial Gorilla Troops Optimizer
by Ashraf Ramadan, Mohamed Ebeed, Salah Kamel, Ahmed M. Agwa and Marcos Tostado-Véliz
Energies 2022, 15(4), 1302; https://doi.org/10.3390/en15041302 - 11 Feb 2022
Cited by 21 | Viewed by 1691
Abstract
Renewable distributed generators (RDGs) are widely embedded in electrical distribution networks due to their economic, technological, and environmental benefits. However, the main problem with RDGs, photovoltaic generators, and wind turbines, in particular, is that their output powers are constantly changing due to variations [...] Read more.
Renewable distributed generators (RDGs) are widely embedded in electrical distribution networks due to their economic, technological, and environmental benefits. However, the main problem with RDGs, photovoltaic generators, and wind turbines, in particular, is that their output powers are constantly changing due to variations in sun irradiation and wind speed, leading to power system uncertainty. Such uncertainties should be taken into account when selecting the optimal allocation of RDGs. The main innovation of this paper is a proposed efficient metaheuristic optimization technique for the sizing and placement of RDGs in radial distribution systems considering the uncertainties of the loading and RDG output power. A Monte Carlo simulation method, along with the backward reduction algorithm, is utilized to create a set of scenarios to model these uncertainties. To find the positions and ratings of the RDGs, the artificial gorilla troops optimizer (GTO), a new efficient strategy that minimizes the total cost, is used to optimize a multiobjective function, total emissions, and total voltage deviations, as well as the total voltage stability boosting. The proposed technique is tested on an IEEE 69-bus network and a real Egyptian distribution grid (East Delta Network (EDN) 30-bus network). The results indicate that the proposed GTO can optimally assign the positions and ratings of RDGs. Moreover, the integration of RDGs into an IEEE 69-bus system can reduce the expected costs, emissions, and voltage deviations by 28.3%, 52.34%, and 66.95%, respectively, and improve voltage stability by 5.6%; in the EDN 30-bus system, these values are enhanced by 25.97%, 51.1%, 67.25%, and 7.7%, respectively. Full article
(This article belongs to the Special Issue Green Energy and Consumer Preferences: Sustainability and Society)
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16 pages, 726 KiB  
Article
CBLSTM-AE: A Hybrid Deep Learning Framework for Predicting Energy Consumption
by Olamide Jogunola, Bamidele Adebisi, Khoa Van Hoang, Yakubu Tsado, Segun I. Popoola, Mohammad Hammoudeh and Raheel Nawaz
Energies 2022, 15(3), 810; https://doi.org/10.3390/en15030810 - 23 Jan 2022
Cited by 27 | Viewed by 3257
Abstract
Multisource energy data, including from distributed energy resources and its multivariate nature, necessitate the integration of robust data predictive frameworks to minimise prediction error. This work presents a hybrid deep learning framework to accurately predict the energy consumption of different building types, both [...] Read more.
Multisource energy data, including from distributed energy resources and its multivariate nature, necessitate the integration of robust data predictive frameworks to minimise prediction error. This work presents a hybrid deep learning framework to accurately predict the energy consumption of different building types, both commercial and domestic, spanning different countries, including Canada and the UK. Specifically, we propose architectures comprising convolutional neural network (CNN), an autoencoder (AE) with bidirectional long short-term memory (LSTM), and bidirectional LSTM BLSTM). The CNN layer extracts important features from the dataset and the AE-BLSTM and LSTM layers are used for prediction. We use the individual household electric power consumption dataset from the University of California, Irvine to compare the skillfulness of the proposed framework to the state-of-the-art frameworks. Results show performance improvement in computation time of 56% and 75.2%, and mean squared error (MSE) of 80% and 98.7% in comparison with a CNN BLSTM-based framework (EECP-CBL) and vanilla LSTM, respectively. In addition, we use various datasets from Canada and the UK to further validate the generalisation ability of the proposed framework to underfitting and overfitting, which was tested on real consumers’ smart boxes. The results show that the framework generalises well to varying data and constraints, giving an average MSE of ∼0.09 across all datasets, demonstrating its robustness to different building types, locations, weather, and load distributions. Full article
(This article belongs to the Special Issue Green Energy and Consumer Preferences: Sustainability and Society)
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18 pages, 958 KiB  
Article
Sustainability and Society: Do Environmental, Social, and Governance Factors Matter for Foreign Direct Investment?
by Niranjan Chipalkatti, Quan Vu Le and Meenakshi Rishi
Energies 2021, 14(19), 6039; https://doi.org/10.3390/en14196039 - 23 Sep 2021
Cited by 23 | Viewed by 5714
Abstract
Sustainable investing allocates investments based on environmental, social and governance factors (ESG). The societal value of sustainable investment is becoming progressively relevant as investors are increasingly recognizing the importance of investing in companies that seek to combat climate change, environmental destruction, while promoting [...] Read more.
Sustainable investing allocates investments based on environmental, social and governance factors (ESG). The societal value of sustainable investment is becoming progressively relevant as investors are increasingly recognizing the importance of investing in companies that seek to combat climate change, environmental destruction, while promoting corporate responsibility. Environmental policy and sustainable growth initiatives at a country-level are also being influenced by the UN’s Sustainable Development Goals (SDGs). Situated within the current trend of declining foreign direct investment flows (FDI), our study examines the role of ESG factors in attracting FDI and enabling progress toward SDGs. We econometrically examine the linkages between ESG and FDI inflows for a sample of 161 counties. We also focus on low- and middle-income emerging economies and low- and middle-income commodity exporters as these countries face unique challenges of mobilizing financing to achieve SDGs and generating sustainable economic growth. Results suggest that FDI inflows to the full sample of countries are positively attracted by good governance in a destination country. We observe that good scores on HDI deters FDI, that higher FDI flows are associated with higher levels of carbon emissions in the case of emerging markets. Sustainability reporting attracts FDI to commodity exporting countries. The study provides possibilities for future research in a post-pandemic future. Full article
(This article belongs to the Special Issue Green Energy and Consumer Preferences: Sustainability and Society)
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17 pages, 3396 KiB  
Article
Willingness to Pay for Renewable Energy in Myanmar: Energy Source Preference
by Masako Numata, Masahiro Sugiyama, Wunna Swe and Daniel del Barrio Alvarez
Energies 2021, 14(5), 1505; https://doi.org/10.3390/en14051505 - 09 Mar 2021
Cited by 9 | Viewed by 3484
Abstract
The increased use of renewable energy is imperative as a countermeasure to climate change. As with conventional electricity generation technologies, public acceptance of renewables is an important issue, and willingness to pay (WTP) is a widely used indicator to assess such public attitudes. [...] Read more.
The increased use of renewable energy is imperative as a countermeasure to climate change. As with conventional electricity generation technologies, public acceptance of renewables is an important issue, and willingness to pay (WTP) is a widely used indicator to assess such public attitudes. Unfortunately, the literature to date mostly covers developed countries, with few WTP surveys in developing countries. Tackling climate change is an urgent issue for these developing countries; therefore, understanding of public attitudes toward renewables in developing countries is crucial. This study conducted the first survey on WTP for introducing renewable energy in Myanmar. Although Myanmar boasts abundant renewable energy resources, including solar power and biomass in addition to large-scale hydro plants, its resources are not being properly utilized to generate electricity. This study surveyed WTP for power generation by solar photovoltaics, small hydropower, and biomass facilities. The results showed the highest WTP for solar power (USD 1.92) with 10% share in the energy mix, and lower WTP for biomass and small hydropower electricity generations (USD 1.13 and USD 1.17, respectively). Careful public communication is thus crucial for expanding biomass and small-scale hydro power plants. Full article
(This article belongs to the Special Issue Green Energy and Consumer Preferences: Sustainability and Society)
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