Submit to Inventions Review for Inventions Propose a Special Issue

Journal Menu

Journal Browser

Data Analytics in the Energy Sector

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Inventions (ISSN 2411-5134). This special issue belongs to the section "Inventions and Innovation in Electrical Engineering/Energy/Communications".

Deadline for manuscript submissions: closed (20 January 2023) | Viewed by 21515

Share This Special Issue

Special Issue Editor

Prof. Dr. Amjad Anvari-Moghaddam

E-Mail Website
Guest Editor

Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
Interests: power system operation and planning; microgrids and active energy networks; energy markets and analytics; operations research and its applications to energy systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Existing energy solutions have longstanding challenges in achieving optimal operational planning goals. On the operational side, existing energy networks are mainly controlled by local controllers with no/limited communications with other units, while being optimized only for specific local operation goals. Moreover, although real-time operation data may be available, a highly efficient system-level data analysis and decision-making process is severely missing current energy systems research, so existing decision-making energy management systems have very limited adaptivity to dynamic operation conditions. Likewise, at the planning level, decisions related to the purchase, placement, and sizing of energy-related devices are largely made within each sector “silo”, disregarding the huge potential of optimal interaction between different energy vectors. The traditional approach makes it almost impossible to achieve cost-effective, flexible and robust energy planning, and prevents the efficient use of infrastructures and research solutions.

This Special Issue will cover promising and dynamic areas of research and development in data analytics methods for the energy sector and will allow us to gather contributions to developing and applying such methods in different domains, ranging from energy generation, trading, and transmission to energy distribution, and consumption. This Special Issue also seeks papers to report advances in any aspect of these developments. The manuscripts should be unpublished and report significant advancements.

Prof. Dr. Amjad Anvari-Moghaddam
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. Inventions 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 1800 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

Data analytics for energy system planning and portfolio investment
Data analytics for enhanced monitoring
Machine learning applications in energy systems
Cognitive sector coupling
Data analytics for energy system operation and control
Data classification and clustering
Distributed data mining
Data-driven uncertainty characterization of stochastic renewable energy resources
Energy forecasting and management
Data collection and processing
Operation and control of energy systems
Fault detection and diagnosis for energy systems
Energy conversion, conservation and management
Artificial intelligence for smart energy
Data analytics for multi-energy integration
Data analytics for energy market and energy trading
Data detection, fusion, processing, storage and information management in energy system
Sectors data and regional data on energy, water, climate change and sustainability
Data mining and big data fusion technology
Data and the applications on low-carbon development pathways
Data and the applications on technology improvement and optimization
Scalable data analytics
Micro- and nano-energy systems and technologies

Published Papers (12 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

32 pages, 6606 KiB

Open AccessArticle

Designing Robust Forecasting Ensembles of Data-Driven Models with a Multi-Objective Formulation: An Application to Home Energy Management Systems

by Antonio Ruano and Maria da Graça Ruano

Inventions 2023, 8(4), 96; https://doi.org/10.3390/inventions8040096 - 25 Jul 2023

Cited by 2 | Viewed by 978

Abstract

This work proposes a procedure for the multi-objective design of a robust forecasting ensemble of data-driven models. Starting with a data-selection algorithm, a multi-objective genetic algorithm is then executed, performing topology and feature selection, as well as parameter estimation. From the set of non-dominated or preferential models, a smaller sub-set is chosen to form the ensemble. Prediction intervals for the ensemble are obtained using the covariance method. This procedure is illustrated in the design of four different models, required for energy management systems. Excellent results were obtained by this methodology, superseding the existing alternatives. Further research will incorporate a robustness criterion in MOGA, and will incorporate the prediction intervals in predictive control techniques. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

16 pages, 7298 KiB

Open AccessArticle

Methodology for Evaluating the Performance Data of Practical Honeycomb Fairing

by Valeriy V. Bodryshev, Artem A. Larin and Lev N. Rabinskiy

Inventions 2023, 8(1), 42; https://doi.org/10.3390/inventions8010042 - 03 Feb 2023

Cited by 5 | Viewed by 1256

Abstract

The quality criteria for fairing used to protect antenna devices (AD) of radar stations (RS) from environmental influences are the requirements for ensuring and maintaining strength and protective properties with minimal insertion loss of the transmitted electromagnetic wave (EMW). It is important to assess the influence of manufacturing technology on these parameters, identifying narrow critical zones on the product with minimum strength characteristics and maximum EMW insertion loss. Calculation models of the stress state in a three-layer sandwich are presented with the identification of critical places from a given type of loading. A method for flaw detection of fairings is presented, taking into account the influence of the dynamics of changes in the maximum allowable threshold of EMW losses, which is extremely necessary for analyzing the technological process and correcting strength calculations. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

10 pages, 2823 KiB

Open AccessArticle

Reduction in the Computational Complexity of Calculating Losses on Eddy Currents in a Hydrogen Fuel Cell Using the Finite Element Analysis

by Artem Khoroshev, Ivan Vasyukov, Alexander Pavlenko and Denis Batishchev

Inventions 2023, 8(1), 38; https://doi.org/10.3390/inventions8010038 - 01 Feb 2023

Viewed by 1177

Abstract

This paper considers the issues of the reduction in the computational complexity of the numerical problem and the requirements of the computer memory size when calculating the power of the eddy currents in a hydrogen fuel cell based on a proton exchange membrane. The study was performed on a model problem based on a geometric pattern of a hydrogen fuel cell of typical dimensions and characteristics operating at a nominal load in steady-state conditions. The power of the eddy currents was calculated using a numerical model based on a tetrahedral finite element mesh and a mathematical model of a quasi-stationary electromagnetic field in the classical formulation through the vector magnetic potential. The requirements for the minimum degree of the geometric model approximation by a finite element mesh to achieve mesh stability of the computational problem results were defined. The paper considers issues of finite element order selection, the method of ordering, and the solution of the systems of linear algebraic equations (SLAEs). It shows the techniques for determining the accuracy of the calculated SLAE solution obtained by the direct method, as well as the effectiveness of the low-rank approximation of the SLAE to reduce the computational complexity of the computational problem solution and reduce the requirements for the amount of computer memory needed, considering the reduced accuracy of the SLAE solutions. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

16 pages, 1226 KiB

Open AccessArticle

Analysis of Mathematical Methods of Integral Expert Evaluation for Predictive Diagnostics of Technical Systems Based on the Kemeny Median

by Vadim Manusov, Aysulu Kalanakova, Javod Ahyoev, Inga Zicmane, Seepana Praveenkumar and Murodbek Safaraliev

Inventions 2023, 8(1), 28; https://doi.org/10.3390/inventions8010028 - 19 Jan 2023

Cited by 2 | Viewed by 1763

Abstract

At present, diagnostics of the current technical condition of high-voltage power equipment in power systems have become more important. This allows the estimation of the real technical condition of power equipment more accurately with its removal into repair based on the results of the diagnostics. This paper presents the comparative analysis of expert evaluations with the use of the arithmetical mean and median values of expert evaluations. In this case, individual expert opinions, influenced by a level of competence, correspond to each other in a different manner, depending on the applied approach. As the comparison of the consistency of expert opinions is the basis for decision-making, it is recommended to make a decision on the technical condition using median estimations because these estimations are less subjected to distortions from single outliers of judgments. This provides more reliable information for making key decisions. Three approaches are considered in this paper: the method of arithmetical mean estimations, the method of median estimations based on the Kemeny median method, and the analytic hierarchy process of Saaty. The considered methods allow decisions on power equipment operation to be made very quickly; namely, if the power equipment is in an operable state and may remain operated, or it has considerable defects and should be removed from operation for routine maintenance, or it has reached the final technical state and needs to be removed from operation. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

18 pages, 3408 KiB

Open AccessArticle

A Cloud-Edge-Based Framework for Electric Vehicle Emergency Energy Trading

by Seyede Zahra Tajalli and Mohammad-Hassan Khooban

Inventions 2023, 8(1), 27; https://doi.org/10.3390/inventions8010027 - 19 Jan 2023

Viewed by 1261

Abstract

The number of electric vehicles (EVs) is increasingly growing day by day and the charging infrastructure for covering this growing number of EVs should be developed. The construction of charging stations is one of the main solutions for supporting EVs while it costs huge investments for installation. Thus, this is not financially logical to invest in charging stations in remote areas with lower demands. An alternative way of constructing charging stations is to provide a peer-to-peer (P2P) energy exchange system in order to support out-of-charge EVs. In this paper, a private cloud-edge emergency energy trading framework is proposed to facilitate energy exchange among consumers and providers. Furthermore, a bidding system is suggested to encourage EVs with extra charges to exchange their energy. Moreover, a matching strategy for pairing consumers and providers is suggested in this paper that considers the benefit of both consumers and providers. In the proposed matching system, a measurement strategy is also suggested for considering the effect of the reliability and punctuality of the providers. To develop the accuracy and efficiency of the proposed framework, employing deep learning methods is also suggested in different layers of the framework. The performance of the proposed framework is evaluated on several case studies in the presence of EVs with realistic features to prove its efficiency, feasibility, and scalability. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

16 pages, 835 KiB

Open AccessArticle

Mathematical Modelling of Rotary Drum Dryers for Alfalfa Drying Process Control

by Dario Friso

Inventions 2023, 8(1), 11; https://doi.org/10.3390/inventions8010011 - 06 Jan 2023

Cited by 1 | Viewed by 2882

Abstract

Rotary drum dryers operating in co-current mode are commonly used for drying food and feed in leaf form, reducing the damage caused by the high air temperatures typical of these dryers, as well as providing advantages including reduced drying times and increased energy efficiency. However, drying control to ensure a desirable product exit moisture content is strongly based on empirical practices, which are usually jealously guarded by producers and users, grounded in simplified mathematical modelling. To overcome these uncertainties, in this work, a more complete mathematical modelling approach, based on the solution of ordinary differential equations (ODEs), is developed. The ODEs describe the drying process in the drum dryer, where the air is continuously cooled and humidified as the product dries. The mathematical model developed was experimentally verified in a drum dryer by drying alfalfa, and the maximum relative error was found to be only 2.4%. Finally, a comparison between the complete model proposed here and a simplified model was conducted, using both for drying control to keep the product exit moisture content constant (i.e., at 0.111). The results indicated that the simplified model provided values of air inlet temperatures erroneously higher, up to +8.2%, with a consequent higher energy consumption, lower dried alfalfa quality, and a greater risk of fire, given that the product exit temperature was dangerously increased. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

12 pages, 3301 KiB

Open AccessArticle

Using XGBoost Regression to Analyze the Importance of Input Features Applied to an Artificial Intelligence Model for the Biomass Gasification System

by Hung-Ta Wen, Hom-Yu Wu and Kuo-Chien Liao

Inventions 2022, 7(4), 126; https://doi.org/10.3390/inventions7040126 - 13 Dec 2022

Cited by 5 | Viewed by 1984

Abstract

Recently, artificial intelligence models have been developed to simulate the biomass gasification systems. The extant research models use different input features, such as carbon, hydrogen, nitrogen, sulfur, oxygen, and moisture content, in addition to ash, reaction temperature, volatile matter (VM), a lower heating value (LHV), and equivalence ratio (ER). The importance of these input features applied to artificial intelligence models are analyzed in this study; further, the XGBoost regression model was used to simulate a biomass gasification system and investigate its performance. The top-four features, according to the results are ER, VM, LHV, and carbon content. The coefficient of determination (R²) was highest (0.96) when all eleven input features noted above were selected. Further, the model performance using the top-three features produced a R² value of 0.93. Thus, the XGBoost model performance was validated again and observed to outperform those of previous studies with a lower mean-squared error of 1.55. The comparison error for the hydrogen gas composition produced from the gasification at a temperature of 900 °C and ER = 0.4 was 0.07%. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

11 pages, 5076 KiB

Open AccessArticle

Development and Analysis of Solutions to Improve the Efficiency of Volute Inlet Pipes in Radial Turboexpanders

by Sergey Osipov, Nikolay Rogalev, Andrey Rogalev, Ivan Komarov and Dmitriy Lvov

Inventions 2022, 7(4), 124; https://doi.org/10.3390/inventions7040124 - 13 Dec 2022

Viewed by 1177

Abstract

The annual increase in demand for electrical power is accompanied by a significant combustion of hydrocarbon fuels and, accordingly, significant CO₂ emissions into the atmosphere, which, in turn, result in increasing the surface temperature of our planet. In addition, hydrocarbon fuel reserves are also depleted every year, which raises the question of the efficient use of fossil fuels. One of the promising solutions to this problem is introducing a technology that allows using the excess gas pressure at gas distribution points in order to generate additional electrical energy. As a rule, a radial turboexpander is used to convert the kinetic energy of natural gas at low power. In this paper, we study a method to reduce losses in a volute inlet of a radial expander. Based on our research, we could find that the use of two symmetrical fins in the volute inlet pipe makes it possible to decrease the turbulent kinetic energy by 1.29% and to reduce the energy losses in the inlet pipe by 2.18%. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

16 pages, 1508 KiB

Open AccessArticle

Evaluation of the Operating Modes of the Urban Electric Networks in Dushanbe City, Tajikistan

by Saidjon Shiralievich Tavarov, Inga Zicmane, Svetlana Beryozkina, Seepana Praveenkumar, Murodbek Safaraliev and Shahnoza Shonazarova

Inventions 2022, 7(4), 107; https://doi.org/10.3390/inventions7040107 - 18 Nov 2022

Cited by 15 | Viewed by 1700

Abstract

Currently, energy saving has become an acute problem all over the world. Due to the rapid development of both the energy and information technology sectors, as well as an increase in the electricity demand, the electric distribution system is facing problems caused by stricter requirements for electricity quality, reliability, efficiency, and sustainability. Therefore, the use of energy-saving technologies, both the improvement of existing ones and the application of new ones, is one of the main reserves for electricity saving in power supply systems. This study is devoted to the evaluation of the operating modes of transformer substations of the 6–10 kV electric distribution network in Dushanbe city, based on the results of control winter measurements and the dependence of the low coefficient of active power in transformer substations. It has been observed that, with a low coefficient of active power in transformer substations, when transmitting electricity from substation busbars to transformer substations of a final consumer via overhead transmission lines (an average length of 5 km), the voltage loss exceeds the maximum permissible values. When transmitting electricity via cable lines, the voltage losses are within the limit of 5%. However, a low active power factor may be the reason for an increase in capacitive currents, followed by the command of single-phase earth fault currents. Due to the low active power factor, the increase in voltage losses and useful power losses leads to the inefficient operating modes of the transformer substations. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

12 pages, 2734 KiB

Open AccessArticle

Influence of Kinematic Parameters of Carbon Dioxide Turbine on Its Coefficient of Efficiency and Dimensions

by Sergey Osipov, Olga Zlyvko, Igor Miliukov, Kirill Berdyugin and Dmitriy Lvov

Inventions 2022, 7(4), 105; https://doi.org/10.3390/inventions7040105 - 17 Nov 2022

Cited by 1 | Viewed by 1155

Abstract

To reduce carbon dioxide emissions into the environment, the energy sector develops oxygen-fuel energy cycles. One of the most promising cycles is the Allam cycle that features the highest efficiency of electricity generation among all others. One of the main elements of an oxy-fuel energy cycle is a high-temperature carbon dioxide turbine. The turbine’s working fluid and coolant consist predominantly of carbon dioxide at a supercritical pressure. Currently, there are no recommendations in the literature for the design of carbon dioxide turbines for an oxy-fuel energy system (OFES) operating according to the Allam cycle; therefore, there is a need to study the influence of parameters of the flow path of carbon dioxide turbines on its efficiency and overall performance. In this paper, we have presented the results of one-dimensional calculations of a flow path of the carbon dioxide turbine for the Allam cycle with a capacity of 300 MW, with an initial temperature and pressure of 1100 °C and 30 MPa, and an outlet pressure of 3 MPa. The study was carried out by varying the rotor speed, the reactivity level and the average diameter. Based on the results of one-dimensional calculations, we have found that the highest efficiency of the turbine flow path is achieved at a speed of 471 rad/s, a reactivity of 0.5, and an average diameter of 1.1 m for the first stage. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

12 pages, 1169 KiB

Open AccessArticle

The Optimal Operation and Dispatch of Commerce Air-Conditioning System by Considering Demand Response Strategies

by Ching-Jui Tien, Chung-Yuen Yang, Ming-Tang Tsai and Chin-Yang Chung

Inventions 2022, 7(3), 69; https://doi.org/10.3390/inventions7030069 - 18 Aug 2022

Cited by 3 | Viewed by 1683

Abstract

The purpose of this paper is to discuss an optimal operation and schedule of commerce air-conditioning system by considering the demand response in order to obtain the maximal benefit; this paper first collects the operating data of the chiller units in commercial users, calculates the cooling load of each unit, and derives the relationship between the cooling loads and power consumption of each unit. The weather information, such as temperature and humidity of inside/outside, are collected in the EXECL database, and the cooling load of the mall’s space is simulated by using the Least Square Support Vector Machine (LSSVM). Under the selected plan of power reduction, the requirement of space cooling loads, and the various operation constraints, the dispatch model of the commerce air-conditioning system with demand response strategies is formulated to minimize the total cost. A Modify Particle Swarm Optimization with Time-Varying Acceleration Coefficients (MPSO-TVAC) is proposed to solve the daily economic dispatch of the air-conditioning system. In the MPSO-TVAC procedure, the dynamic control parameters are embedded in the particle swarm of the PSO-TVAC in order to improve the behavior patterns of each particle swarm and increase its search efficiency in high dimensions. Different modifications in moving patterns of MPSO-TVAC are proposed to search the feasible space more effectively. By using MPSO-TVAC, it provides an optimal mechanism for variables regulated to increase the efficiency of the performing search and look for the probability of an optimal solution. Simulation results also provide an efficient method for commercial users to reduce their electricity bills and raise the ability of the market’s competition. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Figure 1

21 pages, 13730 KiB

Open AccessArticle

Carbon Emissions and Renewables’ Share in the Future Iberian Power System

by Gonçalo Marques Pereira, Rui Castro and Paulo Santos

Inventions 2022, 7(1), 4; https://doi.org/10.3390/inventions7010004 - 21 Dec 2021

Cited by 3 | Viewed by 2781

Abstract

The main objective of this study is to assess if the targets set by the European Commission (EC) relating to the share of renewables and CO₂ emissions by 2030 will be accomplished by the Iberian power system. In this regard, several projections for each generation technology’s installed capacity in the future power system are identified. These forecasts were issued by governmental and private Iberian organizations and by the European Association of Transmission System Operators (ENTSOE), the latter with three scenarios regarding the speed of the energy transition. The outputs of the study are extended to the 2040 horizon and include the energy generated by each technology, the CO₂ emissions, the costs involved in the decarbonization, and the storage capacity needed to compensate for the renewables’ variability. The conclusion is that the Iberia peninsular is on the right path to achieve a fully decarbonized power system by 2040, outperforming by far the EC’s targets in 2030 if the governmental projections are followed. A significant capacity of storage options is envisaged to compensate for the variability of generation from renewables and to replace the power regulation services provided by the fossil fuel plants that will be shut down. Full article

(This article belongs to the Special Issue Data Analytics in the Energy Sector)

► Show Figures

Journal Menu

Journal Browser

Data Analytics in the Energy Sector

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (12 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI