Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Menu

Journal Browser

Energy and Environment Management through Data-Driven Modelling, Optimization and Forecasting

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (10 April 2023) | Viewed by 18341

Share This Special Issue

Special Issue Editors

Prof. Dr. Farshid Keynia

E-Mail Website
Guest Editor

Department of Energy Management and Optimization, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, 7631818356 Kerman, Iran
Interests: energy management; load forecasting; smart grid; power market; optimization; renewable energy

Dr. Azim Heydari

E-Mail Website
Guest Editor

Department of Astronautics, Electrical and Energetic Engineering (DIAEE) Sapienza University, 00184 Rome, Italy
Interests: renewable energy management; renewable-based microgrid planning; machine learning; optimization; forecasting; air pollution assessment

Special Issue Information

Dear colleagues,

Energy currently plays a crucial role in human life and economic development, and its consumption is growing rapidly, mainly because of the fast increase in the human population, technological development, and the electrification of energy consumption mainly related to sustainable mobility and new heating/cooling systems. Consequently, the prediction of electricity consumption in the near future will be crucial to better manage energy needs and production from variable renewable energies. Accurate load forecasts are essential for resource planning, rate structure design, rate analysis, and related financial planning. Both in developed and developing countries, forecasting long-term energy consumption is a key preliminary step for the planning of further installation of power and grid improvements.

CO₂ emission is directly related to economic growth, which is a key factor in the world economy both for production and for consumption. Furthermore, most CO₂ emissions are caused by gaseous/liquid/solid fuel consumption, an essential source of internal combustion engine vehicles and industries that are closely linked to economic development and economic growth. Consequently, the intimate association between CO₂ emissions and economic growth plays a key role in economic and environmental policy.

This Special Issue seeks contributions from researchers, industry experts, and academia to the topics addressed below. We therefore invite papers on methodologies, case studies, and reviews, contributing to the advancement of the quantification of energy and environment management, Renewable energy systems, energy planning, reduction emissions, etc. at different scales, i.e., urban, regional, national, and even continental, for renewable scenario planning and policy making are of interest.

For all the aforementioned reasons, we encourage researchers to share their original works in the field of energy and environment management through data-driven modeling, optimization, and forecasting.

Topics of primary interest include but are not limited to:

Optimization of energy management systems;
Renewable energy systems planning;
Renewable energies generation forecasting;
Electricity and load forecasting;
Air pollution analysis and forecasting;
Earth observation based on satellite imagery and decision tools;
Best practices and case studies.

Prof. Dr. Farshid Keynia
Dr. Azim Heydari
Guest Editors

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. Sustainability 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 2400 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.

Keywords

energy management
renewable energy generation and assessment
smart grid
environmental pollution
metaheuristic optimization models
neural networks
forecasting

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Jump to: Review

12 pages, 2359 KiB

Open AccessArticle

Short-Term Electricity Load Forecasting Using a New Intelligence-Based Application

by Salahuddin Khan

Sustainability 2023, 15(16), 12311; https://doi.org/10.3390/su151612311 - 12 Aug 2023

Cited by 3 | Viewed by 3263

Abstract

Electrical load forecasting plays a crucial role in planning and operating power plants for utility factories, as well as for policymakers seeking to devise reliable and efficient energy infrastructure. Load forecasting can be categorized into three types: long-term, mid-term, and short-term. Various models, including artificial intelligence and conventional and mixed models, can be used for short-term load forecasting. Electricity load forecasting is particularly important in countries with restructured electricity markets. The accuracy of short-term load forecasting is crucial for the efficient management of electric systems. Precise forecasting offers advantages for future projects and economic activities of power system operators. In this study, a novel integrated model for short-term load forecasting has been developed, which combines the wavelet transform decomposition (WTD) model, a radial basis function network, and the Thermal Exchange Optimization (TEO) algorithm. The performance of this model was evaluated in two diverse deregulated power markets: the Pennsylvania-New Jersey-Maryland electricity market and the Spanish electricity market. The obtained results are compared with various acceptable standard forecasting models. Full article

(This article belongs to the Special Issue Energy and Environment Management through Data-Driven Modelling, Optimization and Forecasting)

► Show Figures

Figure 1

26 pages, 4129 KiB

Open AccessArticle

Forecasting Renewable Energy Generation Based on a Novel Dynamic Accumulation Grey Seasonal Model

by Weijie Zhou, Huimin Jiang and Jiaxin Chang

Sustainability 2023, 15(16), 12188; https://doi.org/10.3390/su151612188 - 9 Aug 2023

Cited by 5 | Viewed by 1165

Abstract

With the increasing proportion of electricity in global end-energy consumption, it has become a global consensus that there is a need to develop more environmentally efficient renewable energy generation methods to gradually replace traditional high-pollution fossil energy power generation. Renewable energy generation has become an important method of supplying power across the world. Therefore, the accurate prediction of renewable energy generation plays a vital role in maintaining the security of electricity supply in all countries. Based on this, in our study, a novel dynamic accumulation grey seasonal model is constructed, abbreviated to DPDGSTM(1,1), which is suitable for forecasting mid- to long-term renewable energy generation. Specifically, to overcome the over-accumulation and old information disturbance caused by traditional global accumulation, a dynamic accumulation generation operator is introduced based on a data-driven model, which can adaptively select the optimal partial accumulation number according to the intrinsic characteristics of a sequence. Subsequently, dummy variables and a time trend item are integrated into the model structure, significantly enhancing the adaptability of the new model to the sample sequence with different fluctuation trends. Finally, a series of benchmark models are used to predict renewable energy generation in China, wind power generation in the United States, and hydropower generation in India. The empirical results show that the new model performs better than other benchmark models and is an effective tool for the mid- to long-term prediction of renewable energy generation. Full article

(This article belongs to the Special Issue Energy and Environment Management through Data-Driven Modelling, Optimization and Forecasting)

► Show Figures

Figure 1

33 pages, 3685 KiB

Open AccessArticle

The Effect of Market Isolation on Competitive Behavior in Retail Petrol Markets

by Arezoo Ghazanfari and Armin Razmjoo

Sustainability 2022, 14(13), 8102; https://doi.org/10.3390/su14138102 - 2 Jul 2022

Cited by 2 | Viewed by 2375

Abstract

Regarding the importance of energy for societies, this study examines the characteristics of the petrol price cycle in Perth, Australia. Given the micro-and macro-economic changes, the study’s purpose was to determine whether the Edgeworth features of the cycle are robust and resilient to market changes. The contribution is to extend previous studies, evaluate Edgeworth’s consistency, and capture several episodes of economic activity that have been unexplored. The findings showed a frequent and asymmetric weekly cycle that is characterized by decreasing prices over six consecutive days, followed by a large price jump in one day. The average price rise in the relenting phase for major stations was 14.10 cents per liter (CPL) and 13.14 CPL for independents. For the major and independents, the daily average price drops in the undercutting phase were 2.25 and 1.92 CPL, respectively. Despite the market changes, Edgeworth’s cycle characteristics, cycle duration, and the stations’ role have remained stable during the last 15 years, but peak and trough days have changed. The study is crucial as it provides insights into the robustness of price cycles and competition during significant downturns and prolonged periods of growth. This analysis is critical from a regulatory, policy, and consumer welfare perspective. Furthermore, this paper investigates future petrol consumption in light of renewable energy developments. Full article

(This article belongs to the Special Issue Energy and Environment Management through Data-Driven Modelling, Optimization and Forecasting)

► Show Figures

Figure 1

18 pages, 8591 KiB

Open AccessArticle

Characterizing the Theory of Energy Transition in Luxembourg, Part Two—On Energy Enthusiasts’ Viewpoints

by Ali Arababadi, Stephan Leyer, Joachim Hansen, Reza Arababadi and Gloria Pignatta

Sustainability 2021, 13(21), 12069; https://doi.org/10.3390/su132112069 - 1 Nov 2021

Cited by 3 | Viewed by 3517

Abstract

The energy transition is a certain phenomenon in the future of the world. However, exploring the existing literature suggests that public considerations have not been analyzed in Luxembourg yet. A widespread move from the conventional energy system based on fossil fuels into a new energy system with renewable energy could not occur successfully without the strong support of the public. Characterizing a theory of transition was intended to fill in the gap of knowledge of the field. To ground the built theory, it is necessary to collect as much empirical data as possible. The applied methodology to collect data was to run a survey. Public groups in a variety of job statuses were invited to take part in the survey. The employed method to analyze the data was a combination of qualitative analysis with the pragmatic theory of truth. Overall, the number of collected responses reached 96. Notably, people did not imagine the future differently. They showed a lack of optimism in the future. The findings confirm that the necessity of energy transition is fairly far from people’s considerations. It is a big concern that the authors would like to highlight. Full article

(This article belongs to the Special Issue Energy and Environment Management through Data-Driven Modelling, Optimization and Forecasting)

► Show Figures

Figure 1

15 pages, 2315 KiB

Open AccessArticle

Water Use Behavior in a Multicultural Urban Area in Sweden

by Atefeh Dadvar, Krushna Mahapatra and Jörgen Forss

Sustainability 2021, 13(15), 8603; https://doi.org/10.3390/su13158603 - 2 Aug 2021

Cited by 8 | Viewed by 2615

Abstract

The increasing world population and climate change are major concerns for the supply of water needs. Understanding user behavior facilitates the development of effective strategies of domestic water management. This research applied a questionnaire survey and data analysis methods to analyze the water consumption behavior of tenants in a multicultural urban area, dominated by immigrants of different ethnic origins, in the city of Växjö in Sweden. Results showed that the majority of the studied participants perceived themselves to be environmentally friendly. They reported to be engaged in water conservation activities quite often, but analysis showed that they did not have accurate perceptions of their water consumption. Positive attitudes towards water conservation and self-reported water conservation activities significantly but negatively influenced respondents’ actual water consumption, i.e., water consumption was higher. Subjective norms did not have a significant influence. The results also revealed that individual measurement and debit positively influenced, i.e., reduced, actual water consumption. Therefore, water management systems should include an individual measurement and debit system combined with a visualization system to enable tenants to monitor the quantity and cost of their water consumption. Full article

(This article belongs to the Special Issue Energy and Environment Management through Data-Driven Modelling, Optimization and Forecasting)

► Show Figures

Figure 1

Review

Jump to: Research

17 pages, 475 KiB

Open AccessReview

Development of Sustainable Energy Use with Attention to Fruitful Policy

by Armin Razmjoo, Mostafa Rezaei, Seyedali Mirjalili, Meysam Majidi Nezhad and Giuseppe Piras

Sustainability 2021, 13(24), 13840; https://doi.org/10.3390/su132413840 - 15 Dec 2021

Cited by 8 | Viewed by 3835

Abstract

There are different energy approaches around the world to the development of sustainable energy systems. In this regard, the role of governments, local governments, and people in the development and use of sustainable energy is remarkable. This research, concerning the present epistemic and normative differences, aims to investigate the societal debate on citizen inclusion, local and national attempts to develop clear procedures and guidelines in the transition to sustainable energy use in different countries. Existing theories, subjectivities, and policy implications for different countries are first carefully analyzed. Based on theories, evidence, and policy implications, the behavioural insights for sustainable energy use are then examined. The results show that national governments should never ignore the psychology and behaviour of people, especially in terms of economic behaviour, performance applicable and knowledge of local governments and people in sustainable energy development. Channels of communication between local, people, and national governments, can make a robust shared network and implement simple policies such as increasing their authority. They can also encourage and build capacity through the training, support, trust and knowledge capacity of local governments and people to move toward sustainable energy development. Therefore, focusing on government and maintaining national authority should be departed from any approaches that local government and the public should be constrained as minor actors in sustainable energy governance networks. This work demonstrates that local governments can develop sustainable energy. Moreover, national governments can overcome issues and further control sustainable energy public policy goals under difficult national political conditions. Full article

(This article belongs to the Special Issue Energy and Environment Management through Data-Driven Modelling, Optimization and Forecasting)

► Show Figures

Journal Menu

Journal Browser

Energy and Environment Management through Data-Driven Modelling, Optimization and Forecasting

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (6 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI