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Simulation Modelling and Analysis of a Renewable Energy System — 3rd Edition

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "K: State-of-the-Art Energy Related Technologies".

Deadline for manuscript submissions: 15 December 2026 | Viewed by 1861

Special Issue Editors

Department of Environmental Horticulture & Landscape Architecture, College of Life Science & Biotechnology, Dankook University, Yongin, Republic of Korea
Interests: renewable energy; energy crops; agrophotovoltaic systems; simulation
Special Issues, Collections and Topics in MDPI journals
Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, Republic of Korea
Interests: renewable energy; photovoltaics; simulation; optimization; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

For decades, environmental pollution has threatened the whole of civilization, and energy use generated by fossil fuel use is one of the major sources of pollution. To mitigate environmental pollution, the identification of renewable energy has received global attention. Currently, multiple renewable energy sources such as biofuel, solar and wind power, and geothermal energy are available. However, it is challenging to implement these renewable energy systems in real-world applications due to heavy implementation costs. Thus, it is crucial to utilize modelling techniques which enable us to predict the performance of renewable energy systems in terms of practicality, energy generation capacity, and monetary benefit. This Special Issue thus aims to identify multiple techniques of simulation modelling and analysis for renewable energy management.

We are pleased to invite you to submit original research papers and critical review papers to a Special Issue of Energies entitled “Simulation Modelling and Analysis of a Renewable Energy System”. Any simulation modelling techniques (e.g., discrete event simulation, system dynamics, agent-based simulation, artificial intelligence) used for better renewable energy management will be considered in this Special Issue.

Dr. Sumin Kim
Dr. Sojung Kim
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 250 words) can be sent to the Editorial Office for assessment.

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.

Keywords

  • environmental pollution
  • renewable energy
  • simulation modelling
  • energy management
  • artificial intelligence

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Related Special Issue

Published Papers (2 papers)

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Research

24 pages, 3810 KB  
Article
Designing a Rice Straw-Based Biofuel Supply Chain Using Mixed-Integer Programming in South Korea
by Seongeun Song, Junyoung Seo, Youngjin Kim, Sumin Kim and Sojung Kim
Energies 2026, 19(5), 1338; https://doi.org/10.3390/en19051338 - 6 Mar 2026
Viewed by 463
Abstract
To achieve the goal of the 2015 Paris Agreement to limit global warming to 2 °C compared to pre-industrial levels, South Korea is implementing a policy to use bioethanol as a transportation fuel based on the Renewable Fuel Standard (RFS). This study proposes [...] Read more.
To achieve the goal of the 2015 Paris Agreement to limit global warming to 2 °C compared to pre-industrial levels, South Korea is implementing a policy to use bioethanol as a transportation fuel based on the Renewable Fuel Standard (RFS). This study proposes a mixed-integer linear programming (MILP) model to design an optimal bioethanol supply chain utilizing rice straw, a readily available resource in South Korea. To minimize the total cost of bioethanol production, the proposed model considers optimal facility locations, i.e., those of feedstock collection (farm), refining (refinery), and consumption (market), and transportation volumes. This experiment is conducted to evaluate the blending ratios of bioethanol in gasoline (3%, 6%, and 9%) specified by the Renewable Fuel Standard (RFS) policy, based on actual gasoline consumption data in South Korea. In the RFS 3% scenario, operating a single large-scale refinery was the most economical option, but in the RFS 6% and RFS 9% scenarios, multiple refineries must be utilized to ensure supply chain economics. In conclusion, the proposed MILP model shows the practicality of gradually increasing the number of refineries and selecting the optimal location for each region as future bioethanol demand increases. Full article
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17 pages, 2707 KB  
Article
Impact Analysis of Energy and Emissions in Lane-Closure-Free Road Inspections
by Junseo Lee, Junhwi Cho, Shanelle Aira Rodrigazo, Kyung-Sun Lee and Jaeheum Yeon
Energies 2025, 18(21), 5848; https://doi.org/10.3390/en18215848 - 6 Nov 2025
Cited by 1 | Viewed by 741
Abstract
Road damage threatens driving safety, making timely maintenance essential. However, conventional repairs require on-site personnel, necessitating traffic control and lane closures. These restrictions cause traffic congestion, leading to unnecessary idling and repeated acceleration and deceleration of vehicles, reducing fuel efficiency and increasing energy [...] Read more.
Road damage threatens driving safety, making timely maintenance essential. However, conventional repairs require on-site personnel, necessitating traffic control and lane closures. These restrictions cause traffic congestion, leading to unnecessary idling and repeated acceleration and deceleration of vehicles, reducing fuel efficiency and increasing energy consumption. To overcome these limitations, this study proposes a method for performing inspections without lane closures, utilizing machine vision and AI-based damage detection technology. Furthermore, to quantitatively verify the effectiveness of the proposed method, an energy consumption analysis is conducted using the traffic simulator simulation of urban mobility (SUMO) and the vehicle energy simulator future automotive systems technology simulator (FASTSim). Results show lane closures reduced average speed by 25% and increased driving time by over 40%, adding 5044.73 L of fuel for gasoline vehicles and 3208.63 L for diesel vehicles, with CO2 emissions rising by 11.86 and 8.60 t, respectively. In contrast, the proposed method had minimal traffic impact, with less than 0.1% increases in fuel use and emissions. This approach enables simultaneous multi-lane inspection, improving maintenance efficiency and reducing social costs and energy waste caused by traffic control. Full article
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