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Fuzzy Decision Support Systems for Efficient Energy Management

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: 12 February 2025 | Viewed by 19517

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Special Issue Editors

Dr. Jelena Kilić Pamuković

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Guest Editor

Faculty of Civil Engineering, Architecture and Geodesy, University of Split, 21000 Split, Croatia
Interests: decision making; decision support system; artificial intelligence; expert systems; neural networks; fuzzy logic; sustainable management; energy management planning process
Special Issues, Collections and Topics in MDPI journals

Dr. Katarina Rogulj

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Guest Editor

Faculty of Civil Engineering, Architecture and Geodesy, University of Split, 21000 Split, Croatia
Interests: sustainable infrastructures; project management; operational research; decision support systems; expert systems; multi-criteria analysis; fuzzy set theory; neutrosophic set theory; bridge management system; historic bridge management system; urban heat islands; efficient energy management; e-mobility management; infrastructure management; system engineering; land management
Special Issues, Collections and Topics in MDPI journals

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Dear Colleagues,

One of the most essential resources, to gain continuous development and comfort in everyday life, is energy. Throughout the decades, demand for energy has been on the constant rise due to the amelioration of life standards, population and economic growth in the world. On the other hand, the reserves of fossil–fuels are steadily decreasing which progressively increases their cost. Now day’s decision-makers are dealing with great challenges in distributing energy resources within systems of efficient energy management. There are many parameters included in these systems which are mainly uncertain, complex and stochastically valued like technologies efficiencies, resources properties, location characteristics, etc. These parameters demand certain skills and experiences from decision-makers. For that reason, it is necessary to create effective and useful tools for managing efficient energy systems under multiple scales of socio-economic and ecologic environments. Decision Support Systems are well-known and often used as a tool for solving various problems that involve energy efficiency and energy management. Recently, decision support systems are frequently developed under the theory of fuzzy logic when dealing with complex, vague, uncertain, and multi-objective problems such as system management of efficient energy.

This Special Issue aims to present and disseminate the most recent advances related to the numerical modeling of efficient energy management using Fuzzy Decision Support Systems (FDSS). Topics of interest for publication include but are not limited to the development of FDSS to energy efficiency and energy management in construction, mobility, industrial processes, materials, manufacturing, environmental processes that include water, air and soil resources, exploration, exploitation, conversion, supply of energy resources, etc.

Dr. Jelena Kilić Pamuković
Dr. Katarina Rogulj
Guest Editors

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Keywords

fuzzy logic
decision support systems
energy efficiency
energy management
energy resources
sustainable energy strategy
renewable energy system
uncertainty in energy management
building energy management
urban heat island
decarbonization urban areas
sustainable energy
petroleum energy
solar energy and photovoltaic systems
energy economics and policy
electric vehicles
distributed energy system
bio-energy
power electronics
energy and buildings
smart grids and microgrids
smart cities and urban management
wind, wave and tidal energy
hydro power plant
plant & energy solutions

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Published Papers (9 papers)

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Research

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15 pages, 4066 KiB

Open AccessArticle

Fuzzy Decision-Making Valuation Model for Urban Green Infrastructure Implementation

by Samanta Bačić, Hrvoje Tomić, Katarina Rogulj and Goran Andlar

Energies 2024, 17(20), 5162; https://doi.org/10.3390/en17205162 - 17 Oct 2024

Viewed by 520

Abstract

Urban green infrastructure plays a significant role in sustainable development and requires proper land management during planning. This study develops a valuation model for urban green infrastructure in land management, focusing on Zagreb’s 17 city districts. The fuzzy AHP method was used to calculate the weighting coefficients for a suitable set of criteria, and the TOPSIS method was used to select the priority city districts for implementing green infrastructure. The research results are relevant to decision makers, who can utilize them to prioritize areas for the development and implementation of green infrastructure. The green infrastructure index calculated in this study can be compared with other spatial and land data for effective spatial planning. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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18 pages, 430 KiB

Open AccessArticle

A Novel Trigonometric Entropy Measure Based on the Complex Proportional Assessment Technique for Pythagorean Fuzzy Sets

by Sahil Kashyap, Bartosz Paradowski, Neeraj Gandotra, Namita Saini and Wojciech Sałabun

Energies 2024, 17(2), 431; https://doi.org/10.3390/en17020431 - 16 Jan 2024

Cited by 1 | Viewed by 1009

Abstract

The extension of intuitionistic fuzzy sets (IFS) to Pythagorean fuzzy sets (PFS) is a significant advancement, addressing the inherent limitations of IFS. This study introduces a novel entropy measure specifically designed for Pythagorean fuzzy sets, establishing its axiomatic definition and presenting key properties. Decision making guided by entropy is advantageous, as it effectively mitigates ambiguity with increasing entropy values. Furthermore, a numerical example is provided to facilitate a comparative assessment of our newly introduced entropy measure in contrast to existing PFS entropy measures. The validation of our findings is achieved through the application of the COPRAS method, which determines decision outcomes based on a multitude of influencing factors. Notably, the determination of weights in this method is underpinned by the utilization of our innovative entropy measure. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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13 pages, 910 KiB

Open AccessArticle

Empowering Sustainable Energy Solutions through Real-Time Data, Visualization, and Fuzzy Logic

by Adam Stecyk and Ireneusz Miciuła

Energies 2023, 16(21), 7451; https://doi.org/10.3390/en16217451 - 5 Nov 2023

Viewed by 4490

Abstract

This article shows the evaluation of the Integrated Real-time Energy Management Framework (IREMF), a cutting-edge system designed to develop energy management practices. The framework leverages real-time data collection, advanced visualization techniques, and fuzzy logic to optimize energy consumption patterns. To assess the performance and importance of each layer and main factor within IREMF, we employ a multi-step methodology. First, the Fuzzy Delphi Method is utilized to harness expert insights and collective intelligence, providing a holistic understanding of the framework’s functionality. Researchers used a fuzzy analytic hierarchy process (AHP) to determine the relative importance of each component of the energy system (first stage). This careful evaluation process helps ensure that resources are allocated effectively and that strategic decisions are made based on sound data. The findings of the study not only improve our understanding of the capabilities of the IREMF platform but also pave the way for future developments in energy system management. The study highlights the critical role of real-time data, visualization, fuzzy logic, and advanced decision-making methods in shaping a sustainable energy future. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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19 pages, 2005 KiB

Open AccessArticle

Fuzzy Decision-Making Model for Solar Photovoltaic Panel Evaluation

by Paweł Ziemba and Marta Szaja

Energies 2023, 16(13), 5161; https://doi.org/10.3390/en16135161 - 4 Jul 2023

Cited by 4 | Viewed by 1416

Abstract

The use of solar photovoltaic (PV) panels is one of the most promising ways to generate electricity. However, the complex technical parameters associated with them make the choice between different PV panels a complicated task. The aim of the article is the analysis and multi-criteria evaluation of PV panels available on the Polish market and to indicate the optimal solar PV panels according to the adopted technical criteria. The practical goal was achieved using a fuzzy approach, taking into account the uncertainty of operational parameters. Based on the applied approach and multi-criteria NEAT F-PROMETHEE method, a fuzzy decision model was built for the evaluation of PV panels. The results of this model were compared with the results of an analogous model that did not take into account the uncertainty of the data. As a result of the research, it was found that the results of the fuzzy model should be considered more reliable, because fuzzy numbers allow for capturing more data than real numbers, which translates into greater reliability of the results of the fuzzy model. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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18 pages, 4205 KiB

Open AccessArticle

Fuzzy Multi-Criteria Decision for Geoinformation System-Based Offshore Wind Farm Positioning in Croatia

by Ivana Racetin, Nives Ostojić Škomrlj, Marina Peko and Mladen Zrinjski

Energies 2023, 16(13), 4886; https://doi.org/10.3390/en16134886 - 22 Jun 2023

Cited by 2 | Viewed by 1954

Abstract

Renewable energy is one of the main components of a sustainable world and its future. The consumption of electricity from renewable sources in Croatia has an impressive rate of 53.5%, but offshore wind turbines (OWT) have not yet been installed in the Adriatic Sea. The aim of this study is to determine the possibilities for offshore wind farm (OWF) positioning in the Croatian part of the Adriatic Sea using marine spatial planning (MSP). Initial research to determine the points of interest was conducted based on wind speed. The authors established ten possible points for further research. Subsequently, different parameters were used as inputs for exclusion. The Fuzzy Analytic Hierarchy Process (AHP) method was used to calculate the weighting coefficients for a suitable set of criteria, exactly six of them. Using a combination of geoinformation system (GIS) analysis and weighting coefficients established through Fuzzy AHP, four points were established as suitable for OWF installation in Croatia. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used to select the best order for OWF positioning in the eastern part of the Adriatic Sea. To conclude, there are not many options for OWF positioning in Croatia. Furthermore, it is clear that they exist and should be explored further. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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24 pages, 2961 KiB

Open AccessArticle

Site Selection of Solar Power Plants Using Hybrid MCDM Models: A Case Study in Indonesia

by Chia-Nan Wang, Yu-Chi Chung, Fajar Dwi Wibowo, Thanh-Tuan Dang and Ngoc-Ai-Thy Nguyen

Energies 2023, 16(10), 4042; https://doi.org/10.3390/en16104042 - 11 May 2023

Cited by 11 | Viewed by 3320

Abstract

Among developing countries in Asia, Indonesia has realized the importance of transitioning from fossil fuels to renewable energy sources such as solar power. Careful consideration must be given to the strategic placement of solar power installations to fully leverage the benefits of solar energy. This study proposes a methodology to optimize the site selection of solar power plants in Indonesia by integrating Data Envelopment Analysis (DEA), Fuzzy Analytic Hierarchy Process (F-AHP), and Fuzzy Measurement of Alternatives and Ranking according to Compromise Solution (F-MARCOS) models. The proposed methodology considers quantitative and qualitative criteria to evaluate potential locations for solar power plants. In the first stage, DEA is used to identify the most efficient locations based on quantitative measures such as solar radiation, land availability, and grid connectivity. In the second stage, qualitative factors such as technological, economic, environmental, and socio-political aspects are evaluated using F-AHP to prioritize the most important criteria for site selection. Finally, F-MARCOS ranks potential locations based on the selected criteria. The methodology was tested using data from Indonesia as a case study. The results show that the proposed hybrid model optimizes Indonesia’s solar power plant site selection. The optimal locations can contribute to a cost-effective long-term renewable energy supply nationwide. The findings from this study are relevant to policymakers, industry stakeholders, and researchers interested in renewable energy development and site selection. However, to promote sustainable solar energy development, governments and local authorities must also enact supportive policies and mechanisms that encourage the adoption and growth of renewable energy technologies in Indonesia. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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18 pages, 5324 KiB

Open AccessArticle

Battery Energy Management System Using Edge-Driven Fuzzy Logic

by Mustapha Habib, Elmar Bollin and Qian Wang

Energies 2023, 16(8), 3539; https://doi.org/10.3390/en16083539 - 19 Apr 2023

Cited by 2 | Viewed by 1849

Abstract

Building energy management systems (BEMSs), dedicated to sustainable buildings, may have additional duties, such as hosting efficient energy management systems (EMSs) algorithms. This duty can become crucial when operating renewable energy sources (RES) and eventual electric energy storage systems (ESSs). Sophisticated EMS approaches that aim to manage RES and ESSs in real time may need high computing capabilities that BEMSs typically cannot provide. This article addresses and validates a fuzzy logic-based EMS for the optimal management of photovoltaic (PV) systems with lead-acid ESSs using an edge computing technology. The proposed method is tested on a real smart grid prototype in comparison with a classical rule-based EMS for different weather conditions. The goal is to investigate the efficacy of islanding the building local network as a control command, along with ESS power control. The results show the implementation feasibility and performance of the fuzzy algorithm in the optimal management of ESSs in both operation modes: grid-connected and islanded modes. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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22 pages, 1686 KiB

Open AccessArticle

Algorithm for Energy Resource Selection Using Priority Degree-Based Aggregation Operators with Generalized Orthopair Fuzzy Information and Aczel–Alsina Aggregation Operators

by Maria Akram, Kifayat Ullah, Goran Ćirović and Dragan Pamucar

Energies 2023, 16(6), 2816; https://doi.org/10.3390/en16062816 - 17 Mar 2023

Cited by 8 | Viewed by 1572

Abstract

Many aggregation operators are studied to deal with multi-criteria group decision-making problems. Whenever information has two aspects, intuitionistic fuzzy sets and Pythagorean fuzzy sets are employed to handle the information. However, q-rung orthopair fuzzy sets are more flexible and suitable because they cover information widely. The current paper primarily focuses on the multi-criteria group decision-making technique based on prioritization and two robust aggregation operators based on Aczel–Alsina t-norm and t-conorm. This paper suggests two new aggregation operators based on q-rung orthopair fuzzy information and Aczel–Alsina t-norm and t-conorm, respectively. Firstly, novel q-rung orthopair fuzzy prioritized Aczel–Alsina averaging and q-rung orthopair fuzzy prioritized Aczel–Alsina geometric operators are proposed, involving priority weights of the information. Several related results of the proposed aggregation operators are investigated to see their diversity. A multi-criteria group decision-making algorithm based on newly established aggregation operators is developed, and a comprehensive numerical example for the selection of the most suitable energy resource is carried out. The proposed aggregation operators are compared with other operators to see some advantages of the proposed work. The proposed aggregation operators have a wider range for handling information, with priority degrees, and are based on novel Aczel–Alsina t-norm and t-conorm. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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Review

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41 pages, 2589 KiB

Open AccessFeature PaperReview

A Systematic Review on Fuzzy Decision Support Systems and Multi-Criteria Analysis in Urban Heat Island Management

by Majda Ćesić, Katarina Rogulj, Jelena Kilić Pamuković and Andrija Krtalić

Energies 2024, 17(9), 2013; https://doi.org/10.3390/en17092013 - 24 Apr 2024

Viewed by 1138

Abstract

The phenomenon known as urban heat islands (UHIs) is becoming more common and widespread, especially in large cities and metropolises around the world. The main cause of these temperature variations between the city center and the suburbs is the replacement of large tracts of natural land with artificial (built-up) surfaces that absorb solar heat and radiate it back at night. UHIs have been the subject of numerous studies, most of which were about defining the main characteristics, factors, indexes, etc., of UHIs using remote sensing technologies or about determining mitigating activities. This paper provides a comprehensive overview of the literature, as well as a bibliometric analysis, to discover research trends related to the application of decision support systems and multi-criteria decision-making for UHI management, with a special emphasis on fuzzy theory. Data collection is conducted using the Scopus bibliographic database. Throughout the literature review, it was found that there were not many studies on multi-criteria analysis and decision support system applications regarding UHIs. The fuzzy theory application was also reviewed, resulting in only a few references. However, this topic is current, with an increase in published papers, and authors see this as an opportunity for improvement and further research. Full article

(This article belongs to the Special Issue Fuzzy Decision Support Systems for Efficient Energy Management)

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