New Results on Mathematical Methods–Models and Their Applications to Energy Systems

Topic Information

Dear Colleagues,

Energy systems have different areas of interdisciplinary research, bringing together mathematicians, physicists, and engineers. In energy systems, precise mathematical models and algorithms are needed for a good match between reality and theory. The aim of this Special Issue is to consider and publish original research articles covering the new results and developments in mathematical methods (such as optimization, control systems, model theory, analysis, computational techniques, fuzzy logic, representation theory, linear problems, ordinary and partial differential equations, etc.) applied to energy systems. Using these models and methods, energy systems are analyzed–designed to be reliable, efficient, flexible, and sustainable for real-life industry and science. Furthermore, the use of optimization algorithms in finding the optimal performance of energy systems is an interesting topic of discussion for researchers in the field of energy systems. This Special Issue will focus on various problems in these fields for mathematicians, engineers, physicians, and so on through comprehensive considerations. The topics of this Special Issue on applied sciences include but are not limited to the following:

• Linear and nonlinear dynamics
• Algorithms
• Markov decision process and Monte Carlo theory
• Optimization and control theory
• Game theory
• Econometric analysis
• Statistics
• Functional analysis and its applications
• Mathematical biology
• Mathematical physics
• Engineering applications of mathematics
• Industrial applications of mathematical models 
• Energy systems modeling
• Fractional calculus and its applications
• Numerical analysis
• Simulation
• Neural network
• Artificial intelligence in energy systems
• Mathematical biology
• Stability analysis of systems

Dr. Mohammad Hossein Ahmadi
Dr. Ozen Ozer
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Entropy entropy	2.7	4.7	1999	20.8 Days	CHF 2600
Mathematics mathematics	2.4	3.5	2013	16.9 Days	CHF 2600
Processes processes	3.5	4.7	2013	13.7 Days	CHF 2400
Sustainability sustainability	3.9	5.8	2009	18.8 Days	CHF 2400

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Published Papers (5 papers)

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All Entropy Mathematics Processes Sustainability

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19 pages, 17411 KiB  

Open AccessArticle

Multi-Time-Scale Optimal Scheduling Strategy for Marine Renewable Energy Based on Deep Reinforcement Learning Algorithm

by Ren Xu, Fei Lin, Wenyi Shao, Haoran Wang, Fanping Meng and Jun Li

Entropy 2024, 26(4), 331; https://doi.org/10.3390/e26040331 - 14 Apr 2024

Viewed by 365

Abstract

Surrounded by the Shandong Peninsula, the Bohai Sea and Yellow Sea possess vast marine energy resources. An analysis of actual meteorological data from these regions indicates significant seasonality and intra-day uncertainty in wind and photovoltaic power generation. The challenge of scheduling to leverage [...] Read more.

Surrounded by the Shandong Peninsula, the Bohai Sea and Yellow Sea possess vast marine energy resources. An analysis of actual meteorological data from these regions indicates significant seasonality and intra-day uncertainty in wind and photovoltaic power generation. The challenge of scheduling to leverage the complementary characteristics of various renewable energy sources for maintaining grid stability is substantial. In response, we have integrated wave energy with offshore photovoltaic and wind power generation and propose a day-ahead and intra-day multi-time-scale rolling optimization scheduling strategy for the complementary dispatch of these three energy sources. Using real meteorological data from this maritime area, we employed a CNN-LSTM neural network to predict the power generation and load demand of the area on both day-ahead 24 h and intra-day 1 h time scales, with the DDPG algorithm applied for refined electricity management through rolling optimization scheduling of the forecast data. Simulation results demonstrate that the proposed strategy effectively meets load demands through complementary scheduling of wave power, wind power, and photovoltaic power generation based on the climatic characteristics of the Bohai and Yellow Sea regions, reducing the negative impacts of the seasonality and intra-day uncertainty of these three energy sources on the grid. Additionally, compared to the day-ahead scheduling strategy alone, the day-ahead and intra-day rolling optimization scheduling strategy achieved a reduction in system costs by 16.1% and 22% for a typical winter day and a typical summer day, respectively. Full article

(This article belongs to the Topic New Results on Mathematical Methods–Models and Their Applications to Energy Systems)

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19 pages, 284 KiB  

Open AccessArticle

Exploring Thermoelastic Effects in Damped Bresse Systems with Distributed Delay

by Abdelbaki Choucha, Djamel Ouchenane, Safa M. Mirgani, Eltigan I. Hassan, A. H. A. Alfedeel and Khaled Zennir

Mathematics 2024, 12(6), 857; https://doi.org/10.3390/math12060857 - 14 Mar 2024

Viewed by 473

Abstract

In this work, we consider the one-dimensional thermoelastic Bresse system by addressing the aspects of nonlinear damping and distributed delay term acting on the first and the second equations. We prove a stability result without the common assumption regarding wave speeds under Neumann [...] Read more.

In this work, we consider the one-dimensional thermoelastic Bresse system by addressing the aspects of nonlinear damping and distributed delay term acting on the first and the second equations. We prove a stability result without the common assumption regarding wave speeds under Neumann boundary conditions. We discover a new relationship between the decay rate of the solution and the growth of $\varpi$ at infinity. Our results were achieved using the multiplier method and the perturbed modified energy, named Lyapunov functions together with some properties of convex functions. Full article

(This article belongs to the Topic New Results on Mathematical Methods–Models and Their Applications to Energy Systems)

22 pages, 9073 KiB  

Open AccessArticle

Ultra-Short-Term Load Forecasting for Customer-Level Integrated Energy Systems Based on Composite VTDS Models

by Tong Lu, Sizu Hou and Yan Xu

Processes 2023, 11(8), 2461; https://doi.org/10.3390/pr11082461 - 16 Aug 2023

Viewed by 871

Abstract

A method is proposed to address the challenging issue of load prediction in user-level integrated energy systems (IESs) using a composite VTDS model. Firstly, an IES multi-dimensional load time series is decomposed into multiple intrinsic mode functions (IMFs) using variational mode decomposition (VMD). [...] Read more.

A method is proposed to address the challenging issue of load prediction in user-level integrated energy systems (IESs) using a composite VTDS model. Firstly, an IES multi-dimensional load time series is decomposed into multiple intrinsic mode functions (IMFs) using variational mode decomposition (VMD). Then, each IMF, along with other influential features, is subjected to data dimensionality reduction and clustering denoising using t-distributed stochastic neighbor embedding (t-SNE) and fast density-based spatial clustering of applications with noise (FDBSCAN) to perform major feature selection. Subsequently, the reduced and denoised data are reconstructed, and a time-aware long short-term memory (T-LSTM) artificial neural network is employed to fill in missing data by incorporating time interval information. Finally, the selected multi-factor load time series is used as input into a support vector regression (SVR) model optimized using the quantum particle swarm optimization (QPSO) algorithm for load prediction. Using measured load data from a specific user-level IES at the Tempe campus of Arizona State University, USA, as a case study, a comparative analysis between the VTDS method and other approaches is conducted. The results demonstrate that the method proposed in this study achieved higher accuracy in short-term forecasting of the IES’s multiple loads. Full article

(This article belongs to the Topic New Results on Mathematical Methods–Models and Their Applications to Energy Systems)

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14 pages, 4462 KiB  

Open AccessArticle

Investigation of Mass-Transfer Performance for Biodiesel Reaction in Microchannel Reactor using Volume-of-Fluid with Species-Transport Model

by Afiq Mohd Laziz, Chong Yang Chuah, Jens Denecke, Muhammad Roil Bilad and Ku Zilati Ku Shaari

Sustainability 2023, 15(7), 6148; https://doi.org/10.3390/su15076148 - 03 Apr 2023

Viewed by 1850

Abstract

A microchannel reactor improves the overall mass and heat transfer as compared with a conventional reactor. This is attributed to the creation of a high area-to-volume ratio and enhanced mixing due to the presence of the vortices inside the slug. In this paper, [...] Read more.

A microchannel reactor improves the overall mass and heat transfer as compared with a conventional reactor. This is attributed to the creation of a high area-to-volume ratio and enhanced mixing due to the presence of the vortices inside the slug. In this paper, the mass-transfer performance was studied using a cross-junction microchannel. Subsequently, the computational fluid dynamic (CFD) method was used to observe the oil concentration contour inside a slug using volume-of-fluid (VOF) with the species-transport model. Based on the simulation results, the oil concentration was accumulated in both the slug’s rear and front regions. Hence, the creation of four vortices resulted in the creation of dead zones at the low-oil-concentration region. Furthermore, it has been observed that an optimum flow rate in a microchannel reactor is required to achieve a high mass transfer. A higher oil concentration was measured during the slug formation at a low flow regime due to the long residence time. In contrast, a high mass transfer has been reported during the slug-moving stage due to the higher vortices velocity, resulting in enhanced mixing and mass transfer. Hence, slug forming and the moving stage substantially influenced mass transfer at low and high flow rates, respectively. Full article

(This article belongs to the Topic New Results on Mathematical Methods–Models and Their Applications to Energy Systems)

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21 pages, 4031 KiB  

Open AccessArticle

Time-Transient Optimization of Electricity and Fresh Water Cogeneration Cycle Using Gas Fuel and Solar Energy

by Khosrow Hemmatpour, Ramin Ghasemiasl, Mehrdad Malekzadeh dirin and Mohammad Amin Javadi

Mathematics 2023, 11(3), 571; https://doi.org/10.3390/math11030571 - 21 Jan 2023

Cited by 1 | Viewed by 1140

Abstract

In this study, a cogeneration cycle in a time-transient state is investigated and optimized. A quasi-equilibrium state is assumed because of the small time increments. Air temperature and solar power are calculated hourly. The cycle is considered in terms of energy, exergy, and [...] Read more.

In this study, a cogeneration cycle in a time-transient state is investigated and optimized. A quasi-equilibrium state is assumed because of the small time increments. Air temperature and solar power are calculated hourly. The cycle is considered in terms of energy, exergy, and economic and environmental analyses. Increasing the net present value (the difference between the present value of the cash inflows and outflows over a period of time) and reducing exergy destruction are selected as two optimization objective functions. The net present value is calculated for the period of 20 years of operation according to the operation parameters. The optimization variables are selected in such a way that one important variable is selected from each system. To optimize the cycle, the particle swarm optimization method is used. The number of particles used in this method is calculated using the trial-and-error method. This cycle is optimized using 13 particles and 42 iterations. After optimization, the energy efficiency increased by 0.5%, the exergy efficiency increased by 0.25%, and the exergy destruction decreased by 1% compared to the cycle with existing parameters. Full article

(This article belongs to the Topic New Results on Mathematical Methods–Models and Their Applications to Energy Systems)

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