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44 pages, 2847 KB

Open AccessArticle

Advances in Optimal Reactive Power Dispatch: Formulations, Solution Approaches, and Future Directions

by Edgar E. Tibaduiza-Rincón, Walter M. Villa-Acevedo and Jesús M. López-Lezama

Processes 2026, 14(8), 1229; https://doi.org/10.3390/pr14081229 (registering DOI) - 11 Apr 2026

This paper provides a comprehensive analysis of the Optimal Reactive Power Dispatch (ORPD) problem, focusing on its mathematical formulations and the methodologies employed to solve it. This paper systematically categorizes the problem into single-objective and multi-objective formulations, as well as single-period and multi-period [...] Read more.

This paper provides a comprehensive analysis of the Optimal Reactive Power Dispatch (ORPD) problem, focusing on its mathematical formulations and the methodologies employed to solve it. This paper systematically categorizes the problem into single-objective and multi-objective formulations, as well as single-period and multi-period models, and addresses both single-area and multi-area operational frameworks. It explores a broad range of optimization techniques used to tackle the ORPD problem, including classical optimization methods, metaheuristic algorithms, and hybrid approaches. Additionally, this paper discusses the incorporation of uncertainty in ORPD models, highlighting methods to account for the stochastic nature of power systems. A critical assessment of the current literature identifies existing knowledge gaps and outlines promising future research directions. This paper aims to provide researchers with a thorough understanding of the ORPD problem, offering insights into emerging trends and areas for further exploration. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

28 pages, 6309 KB

Open AccessArticle

Rational Design and CFD Modeling of Innovative Jet Nozzles with a Streamlined Body

by Ivan Pavlenko, Vadym Baha, Marek Ochowiak, Magdalena Matuszak and Oleh Chekh

Processes 2026, 14(8), 1193; https://doi.org/10.3390/pr14081193 - 8 Apr 2026

Viewed by 82

Abstract

The use of confuser–diffuser nozzles in power machines enables efficient conversion of gas energy into mechanical work. However, traditional Laval, Venturi, and Vitoszynski nozzles are associated with shock wave formation, causing energy losses, noise, and structural loading. This study proposes innovative jet nozzles [...] Read more.

The use of confuser–diffuser nozzles in power machines enables efficient conversion of gas energy into mechanical work. However, traditional Laval, Venturi, and Vitoszynski nozzles are associated with shock wave formation, causing energy losses, noise, and structural loading. This study proposes innovative jet nozzles with an internal streamlined body that forms annular flow rather than a classical diffusor. A rational computational design methodology based on the Venturi effect criterion and equality of cross-sectional area variation laws was developed. A couple of configurations with spindle-toroidal and ellipsoidal streamlined bodies were generated analytically, studied numerically, and confirmed experimentally. Based on the SST turbulence model, CFD simulations for a compressible flow (air) show that the proposed designs reduce the pressure jump from 60 kPa (traditional nozzle) to 20 kPa for the spindle-toroidal configuration and eliminate it for the ellipsoidal configuration. The Reynolds number in the throat decreases by a factor of 2.6, reducing turbulence. The outlet velocity increases by 3.0% for the spindle-toroidal design, while the ellipsoidal nozzle provides expansion with slightly lower velocity but a smoother velocity profile. Experimental thrust measurements agree with simulations within 2.6–6.7%. The proposed designs enhance energy efficiency, reduce erosion and vibration, and enable adaptive flow control via axial displacement of the streamlined body. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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42 pages, 8200 KB

Open AccessArticle

Techno-Economic and Environmental Assessment of a Hybrid Photovoltaic–Diesel–Grid System for University Facilities

by Daniel Alejandro Pérez Uc, Susana Estefany de León Aldaco and Jesús Aguayo Alquicira

Processes 2026, 14(7), 1185; https://doi.org/10.3390/pr14071185 - 7 Apr 2026

Viewed by 228

Abstract

This study presents a techno-economic and environmental assessment of a photovoltaic–diesel–grid hybrid renewable energy system (SHER) applied to a university campus, with the aim of reducing monetary costs by implementing a methodology to mitigate energy consumption during peak hours, controlling the output of [...] Read more.

This study presents a techno-economic and environmental assessment of a photovoltaic–diesel–grid hybrid renewable energy system (SHER) applied to a university campus, with the aim of reducing monetary costs by implementing a methodology to mitigate energy consumption during peak hours, controlling the output of the diesel generator, and determining greenhouse gas emissions. Hourly load profiles are incorporated using billing data, local solar resource data, and grid connection rate schedules. The HOMER Pro v3.14.2 software is used to simulate and identify an off-grid scenario during peak hours, sizing the photovoltaic system at 30%, 50%, 70%, and 100% to compare the investment cost of the SHER. System performance is evaluated using key indicators, including net present cost ($6.96 million), levelized cost of energy (LCOE, $0.707/kWh), and CO₂ emissions (101,311 kg/yr.), among others. The results indicate that photovoltaic generation can cover approximately 80% of annual electricity demand, while the diesel generator operates only during critical periods, contributing to reduced operating costs and emissions. The optimal configuration has a lower LCOE than conventional supply, a renewable fraction of close to 80%, and an investment payback period of approximately five years, demonstrating the technical, economic, and environmental viability of the proposed system. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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16 pages, 1419 KB

Open AccessArticle

Study on Risk Analysis of a Rotary Kiln-Based Activated Carbon Manufacturing Process Using Fuzzy-FMEA

by Jong Gu Kim and Byong Chol Bai

Processes 2026, 14(7), 1071; https://doi.org/10.3390/pr14071071 - 27 Mar 2026

Viewed by 252

Abstract

Rotary kiln-based activated carbon production combines high-temperature operation with flammable/reducing gases, carbonaceous dust, and downstream off-gas treatment and acid/base washing, creating complex escalation pathways. This study prioritizes safety improvements by applying classical failure modes and effects analysis (FMEA) and a transparent Fuzzy-FMEA framework [...] Read more.

Rotary kiln-based activated carbon production combines high-temperature operation with flammable/reducing gases, carbonaceous dust, and downstream off-gas treatment and acid/base washing, creating complex escalation pathways. This study prioritizes safety improvements by applying classical failure modes and effects analysis (FMEA) and a transparent Fuzzy-FMEA framework to 18 representative failure modes (six each for kiln/activation, acid/base handling, and atmosphere/control). Five experts evaluated Severity, Occurrence, and Detection on a 10-point scale. The fuzzy model used triangular membership functions (L/M/H), a monotonic 27-rule base, Mamdani max–min inference, and centroid defuzzification to compute a continuous fuzzy risk priority number (FRPN, 0–10). Classical FMEA identified dust explosion (RPN = 405), temperature control failure (RPN = 378), and off-gas leakage (RPN = 324) as the highest-ranked risks. Fuzzy-FMEA preserved the top-risk group while more strongly highlighting barrier-related risks, placing off-gas leakage, instrumentation/interlock failure, and electrostatic ignition control alongside dust explosion (FRPN 9.221–9.332). The rankings were strongly correlated (Spearman ρ = 0.871; Kendall τ = 0.752), yet mid-risk items were rearranged (mean |Δrank| = 2.06; max = 5), improving discrimination within tied RPN clusters. The five highest-priority scenarios were reconstructed into actionable engineering packages, including dust and ignition control, off-gas integrity linked to shutdown logic, interlock proof testing and bypass management, and independent protection layers for kiln temperature control. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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19 pages, 3985 KB

Open AccessFeature PaperArticle

Optimization of Particle Size Blending and Binder Content in Coconut Shell-Based Activated Carbon Monoliths for Methane Adsorption

by Jun Hyung Jho, Hyun Ku Lee, Min Seong Han and Byong Chol Bai

Processes 2026, 14(7), 1029; https://doi.org/10.3390/pr14071029 - 24 Mar 2026

Viewed by 255

Abstract

This study examined the effects of particle size blending and hybrid binder content on the structural properties and methane adsorption behavior of coconut shell-based activated carbon monoliths. Monoliths were prepared using activated carbon particles with two size ranges (212–250 µm and 26–53 µm), [...] Read more.

This study examined the effects of particle size blending and hybrid binder content on the structural properties and methane adsorption behavior of coconut shell-based activated carbon monoliths. Monoliths were prepared using activated carbon particles with two size ranges (212–250 µm and 26–53 µm), blending ratios of 1:9, 3:7, 5:5, and 7:3, and a hybrid binder containing styrene–butyl acrylate (SBA) and carboxymethylcellulose (CMC). Morphology and elemental composition were analyzed by SEM-EDS, specific surface area and pore structure were evaluated by BET analysis, and surface properties were examined by XPS. Structural density and compressive strength were also measured. Among the tested samples, M50ML showed the highest structural density (0.544 g/cm³), compressive strength (27.5 MPa), and methane uptake (3.06 mg/g). This result was related to improved packing by particle size blending while maintaining microporosity. These results indicate that particle size blending and binder content significantly affected the structural properties and methane adsorption behavior of the prepared monoliths. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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30 pages, 2176 KB

Open AccessArticle

Clarke-Domain Dyadic Wavelet Denoising for Three-Phase Induction Motor Current Signals

by Edgardo de Jesús Carrera Avendaño, Iván Antonio Juarez Trujillo, Monica Borunda, Carlos Daniel García Beltrán, J. Guadalupe Velásquez Aguilar, Abisai Acevedo Quiroz and Susana Estefany De León Aldaco

Processes 2026, 14(6), 950; https://doi.org/10.3390/pr14060950 - 16 Mar 2026

Viewed by 689

Abstract

Noise elimination in current signals of three-phase induction motors, considered as energy systems for electromechanical conversion, is a critical preprocessing step for reliable condition monitoring and fault diagnosis. However, conventional wavelet-based denoising approaches often treat noise suppression as a generic filtering task, which [...] Read more.

Noise elimination in current signals of three-phase induction motors, considered as energy systems for electromechanical conversion, is a critical preprocessing step for reliable condition monitoring and fault diagnosis. However, conventional wavelet-based denoising approaches often treat noise suppression as a generic filtering task, which may distort diagnostically relevant spectral components and inter-phase relationships. To address this limitation, this paper presents a physically constrained denoising framework that integrates the Clarke transformation with dyadic wavelet analysis to enable diagnostic-safe noise attenuation. The proposed method explicitly preserves frequency bands associated with supply harmonics, mechanical phenomena, and fault-related sidebands, while enforcing inter-phase coherence and zero-sequence stability in the Clarke domain. Wavelet parameters are selected through a diagnostic-oriented multi-criteria framework that jointly balances disturbance attenuation, harmonic fidelity, coherence retention, zero-sequence stability, and time-domain waveform integrity. Experimental validation using real three-phase induction motor current measurements under steady-state conditions shows that the proposed framework achieves noise reduction ratios of approximately 8–10 dB, while preserving the amplitudes of the main harmonic components with deviations below

10^{- 3}

dB. These results demonstrate that the proposed method provides a robust and physically consistent preprocessing stage for current-based monitoring of three-phase AC machines. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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30 pages, 2209 KB

Open AccessArticle

Multi-Objective Optimization and K-Means Clustering Analysis of Green Hydrogen Production Routes via Biomass Gasification and Water Electrolysis

by Carlos Antonio Padilla-Esquivel, Thelma Posadas-Paredes, Heriberto Alcocer-García, César Ramírez-Márquez and José María Ponce-Ortega

Processes 2026, 14(6), 946; https://doi.org/10.3390/pr14060946 - 16 Mar 2026

Viewed by 729

Abstract

Green hydrogen is a key energy carrier for industrial decarbonization; however, its large-scale deployment requires the optimization of production routes from both energetic and economic perspectives. In this study, green hydrogen production via biomass gasification and water electrolysis is comparatively evaluated using a [...] Read more.

Green hydrogen is a key energy carrier for industrial decarbonization; however, its large-scale deployment requires the optimization of production routes from both energetic and economic perspectives. In this study, green hydrogen production via biomass gasification and water electrolysis is comparatively evaluated using a multi-objective optimization framework based on the Differential Evolution Tabu List (DETL) algorithm. The optimization simultaneously maximizes hydrogen production while minimizing specific energy consumption and total annualized cost, explicitly capturing the trade-offs between competing technologies. Results indicate that biomass gasification outperforms water electrolysis in both energetic and economic terms. The optimal gasification configuration achieves 3625.95 kg/h of H₂ with a specific energy consumption of 39.63 kWh/kg H₂ and a total annualized cost of 2.45 MUSD/yr, whereas water electrolysis reaches 3156.78 kg/h of H₂ with 68.7 kWh/kg H₂ and a cost of 3.72 MUSD/yr. To support the interpretation of results, K-means clustering is integrated into the methodological framework, enabling the identification of representative regions within the Pareto fronts. Overall, biomass gasification provides more balanced and flexible solutions, highlighting its potential as a competitive route for sustainable hydrogen production. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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17 pages, 1159 KB

Open AccessArticle

A Multi-Objective Dispatch Model for Polygeneration Systems with BESS and Industrial Demand Profiles

by Jhonatan Chicacausa-Niño, Ricardo Isaza-Ruget and Javier Rosero-García

Processes 2026, 14(6), 891; https://doi.org/10.3390/pr14060891 - 10 Mar 2026

Viewed by 264

Abstract

The transition towards sustainable energy systems requires a paradigm shift from purely economic optimization to a holistic framework that internalizes environmental and social externalities. This article integrates social and environmental aspects into the multi-objective dispatch model based on mixed-integer linear programming (MILP) for [...] Read more.

The transition towards sustainable energy systems requires a paradigm shift from purely economic optimization to a holistic framework that internalizes environmental and social externalities. This article integrates social and environmental aspects into the multi-objective dispatch model based on mixed-integer linear programming (MILP) for the economic, environmental, and social dispatch (EEDS) of a polygeneration microgrid. Unlike traditional approaches that treat social impact as a static planning constraint, this study introduces a quantified “Social Shadow Price” into the operational objective function, aiming to operationalize the concept of energy justice. The model is applied to a case study featuring a high-load factor industrial demand profile, integrated with thermal generation, solar PV, wind power, and BESS storage. Results demonstrate that internalizing environmental and social costs significantly alters the merit order dispatch, reducing the utilization of socially contentious technologies while leveraging storage arbitrage to mitigate intermittency. Furthermore, a sensitivity analysis is conducted to determine the optimal capacity of renewable energy sources, revealing that a balanced mix of solar and wind minimizes the composite sustainability index. The findings suggest that this EEDS framework provides a viable pathway for policymakers to achieve a socially equitable energy transition in industrial sectors. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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21 pages, 1139 KB

Open AccessArticle

Comparative Assessment of Energy and Emission Costs for Geothermal Heat Pumps and Fossil-Fuel Heating Systems Across U.S. Climatic Zones

by Md Shahin Alam, Shima Afshar, Seyed Ali Arefifar and Mohammad Haq

Processes 2026, 14(5), 876; https://doi.org/10.3390/pr14050876 - 9 Mar 2026

Viewed by 512

Abstract

In response to growing concerns over global warming and energy sustainability, transitioning from fossil-fuel-based heating systems to renewable alternatives is essential. This study evaluates the economic and environmental performance of geothermal heat pumps for building heating and compares it with conventional coal-fired boilers, [...] Read more.

In response to growing concerns over global warming and energy sustainability, transitioning from fossil-fuel-based heating systems to renewable alternatives is essential. This study evaluates the economic and environmental performance of geothermal heat pumps for building heating and compares it with conventional coal-fired boilers, natural-gas boilers, and diesel furnaces. Using the heating degree-day (HDD) method, heating energy demand was analyzed for four U.S. cities—Anchorage (AK), San Francisco (CA), Salt Lake City (UT), and Las Vegas (NV)—representing diverse climatic zones. The analysis integrates thermodynamic and economic parameters, including the coefficient of performance (COP = 2–5) and annual fuel-utilization efficiency (AFUE = 80–97%), to evaluate heating-system performance and operational cost across different climatic regions. Sensitivity analysis with ±10% variations in fuel and electricity prices and system efficiencies demonstrates that geothermal heating remains the most stable and emission-efficient option under all scenarios. Results indicate that geothermal systems, despite higher reported initial investment, achieve lower operational and emissions-related costs and offer a robust and sustainable solution for decarbonizing building-heating systems. For example, the estimated seasonal geothermal heating cost is $370.59 in Anchorage compared with $646.48 for coal heating and $3375.65 for diesel systems. Furthermore, policy evaluation indicates that federal and state incentives, such as investment tax credit under the Inflation Reduction Act and rebate programs, can reduce installation costs by 25–40%, improving economic feasibility, particularly in colder regions. The analysis focuses exclusively on energy and emissions-related costs and does not explicitly model capital investment or levelized cost metrics. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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29 pages, 7458 KB

Open AccessArticle

Characterization of Regulated Electricity Consumption Flexibility Using Variability, Entropy, and Latent Profiling

by Jesús Osorio-Lázaro and Javier Rosero-García

Processes 2026, 14(4), 712; https://doi.org/10.3390/pr14040712 - 21 Feb 2026

Cited by 1 | Viewed by 272

Abstract

Energy flexibility in regulated users is examined as a structural property of demand, assessed through variability and disorder metrics derived from smart metering data. Using the coefficient of variation and normalized entropy, the analysis reveals stable routines during weekdays and greater heterogeneity in [...] Read more.

Energy flexibility in regulated users is examined as a structural property of demand, assessed through variability and disorder metrics derived from smart metering data. Using the coefficient of variation and normalized entropy, the analysis reveals stable routines during weekdays and greater heterogeneity in transitional periods such as evenings and weekends. Non-negative matrix factorization (NMF) is applied to extract latent user pro-files, which are subsequently clustered to uncover representative trajectories of consumption. Groups with bimodal or extended load distributions emerge as the most adaptable, highlighting the role of latent profiling in identifying flexibility potential. Simulations of partial load redistribution demonstrate that, while individual savings remain modest, aggregated benefits and improvements in reliability indicators (SAIDI, SAIFI, ENS) are significant. These findings confirm that flexibility is unevenly distributed across users and time, and that its quantification provides a strategic foundation for differentiated demand response schemes and the design of resilient, user-oriented energy systems. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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56 pages, 2399 KB

Open AccessArticle

Real-Time Energy System Optimization and Resilience Analysis in Low-Voltage Networks Using Intelligent Edge Computing

by Dan Cristian Lazar, Dan Codrut Petrilean, Teodora Lazar, Florin Gabriel Popescu, Daria Ionescu, Adina Milena Tatar, Georgeta Buica and Dragos Pasculescu

Processes 2026, 14(4), 660; https://doi.org/10.3390/pr14040660 - 14 Feb 2026

Cited by 1 | Viewed by 428

Abstract

The transition toward active distribution networks requires advanced control solutions capable of handling the rapid dynamics of distributed energy resources. This paper proposes a low-cost, intelligent IoT architecture designed for the real-time optimization and analysis of energy systems within low-voltage networks. Unlike centralized [...] Read more.

The transition toward active distribution networks requires advanced control solutions capable of handling the rapid dynamics of distributed energy resources. This paper proposes a low-cost, intelligent IoT architecture designed for the real-time optimization and analysis of energy systems within low-voltage networks. Unlike centralized monitoring approaches constrained by communication latency, the proposed solution leverages Intelligent Edge Processing (IEP) implemented on ESP32 embedded nodes to optimize data flow and decision-making. This architecture executes stability assessments directly at the network edge, calculating critical analysis indicators such as the Voltage Deviation Index (VDI) and Rate of Change of Frequency (RoCoF). The system was validated on the CIGRE European LV benchmark under severe stress scenarios, including rapid solar transients and voltage sags. The results demonstrate that the proposed architecture effectively coordinates storage interventions, ensuring voltage recovery within 300 ms and maintaining power quality within EN 50160 limits even during severe voltage sags. The study validates the feasibility of using industrial IoT edge computing as a resilient, non-wire alternative for modernizing complex energy systems. Full article

(This article belongs to the Special Issue Optimization and Analysis of Energy System)

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