Energies

68 pages, 24222 KB

Open AccessArticle

Collaborative Optimization of Numerical Empowerment-Driven Campus IES Public Services Considering Elderly-Oriented Renovation

by Xiao-Jing Zhao, Xiao Du, Rui-Nan Zha, Ze-Qi Li and Zhi-Feng Liu

Energies 2026, 19(16), 3941; https://doi.org/10.3390/en19163941 - 21 Aug 2026

Viewed by 254

Abstract

With the continued advancement of low-carbon campus transformation and the increasing penetration of renewable energy, campus integrated energy systems have become key infrastructure for green campus development. However, the highly random nature of student behavior causes dynamic fluctuations in electricity, heating, and cooling [...] Read more.

With the continued advancement of low-carbon campus transformation and the increasing penetration of renewable energy, campus integrated energy systems have become key infrastructure for green campus development. However, the highly random nature of student behavior causes dynamic fluctuations in electricity, heating, and cooling loads, creating major challenges for real-time supply-demand balance and economic system scheduling. To address this problem, this paper takes student behavior uncertainty as the core disturbance factor and proposes a flexible architecture-driven autonomous adaptation and multi-energy complementary optimization strategy. A closed-loop operation paradigm of signal–response–complementarity–regulation is established, in which dynamic electricity price signals, comfort-oriented guidance, and campus functional energy-zone division are combined to form a multi-level autonomous response chain. To improve solution efficiency, the electromagnetic wave propagation algorithm is further enhanced, and a Multi-Objective Electromagnetic Wave Propagation Algorithm (MEMWPA) is developed. Wave-impedance matching and energy-flux-density feedback mechanisms are introduced to strengthen convergence performance in complex multi-objective optimization problems. Comparative case studies show that the proposed strategy can effectively smooth the net load curve, reduce the campus peak load by 26.73%, and increase the load factor by 14.533 percentage points, thereby improving both operational flexibility and energy efficiency. Full article

(This article belongs to the Special Issue Next-Generation Smart Energy Systems for Sustainable and Decarbonized Energy Infrastructures)

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35 pages, 4418 KB

Open AccessArticle

A Modified 2-DoF Wave Buoy with an Embedded Tunable Magnetic-Spring Electromagnetic Energy Harvester: Concept, Dynamic Modeling and Numerical Analysis

by Joanna Bijak and Tomasz Trawiński

Energies 2026, 19(16), 3940; https://doi.org/10.3390/en19163940 - 21 Aug 2026

Viewed by 209

Abstract

This paper presents a modified two-degree-of-freedom wave buoy with an embedded tunable magnetic-spring electromagnetic energy harvester. The proposed device is modeled as a branched kinematic chain composed of a rotational–rotational buoy mechanism and a rotational–prismatic harvester branch sharing the first revolute joint. Two [...] Read more.

This paper presents a modified two-degree-of-freedom wave buoy with an embedded tunable magnetic-spring electromagnetic energy harvester. The proposed device is modeled as a branched kinematic chain composed of a rotational–rotational buoy mechanism and a rotational–prismatic harvester branch sharing the first revolute joint. Two harvester orientations are considered and compared. The mathematical model is formulated using homogeneous transformations, velocity Jacobians and Lagrange equations. Particular attention is paid to the structure of the inertia matrix and to the way in which its inverse transmits generalized forces between the rotational coordinates and the translational motion of the moving magnet. The model is implemented in MATLAB/Simulink R2024b and evaluated under free-response, regular-wave, and bidirectional frequency-sweep excitation scenarios. Under regular-wave excitation, Config. 1 produces approximately 19.3 and 2.98 times greater average load power than Config. 2 for moving-assembly masses of 5 g and 268 g, respectively. The frequency-sweep results show that the preferred harvester orientation depends on the excitation frequency and moving-assembly mass. No resolved sweep-direction dependence is observed for 5 g, whereas for 268 g the identified hysteresis intervals are approximately 0.53 rad/s for Config. 2 and 0.64 rad/s for Config. 1. These results provide design guidelines for selecting the harvester orientation and moving mass in compact wave-excited buoy systems. Full article

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24 pages, 7033 KB

Open AccessArticle

An Enhanced Lightweight YOLOv11 Algorithm for Real-Time Detection of High-Voltage Line Insulators

by Abdil Karakan

Energies 2026, 19(16), 3939; https://doi.org/10.3390/en19163939 - 21 Aug 2026

Viewed by 206

Abstract

UAV-based insulator detection is challenging because insulators often occupy small regions of aerial images and appear against complex backgrounds, while subtle local features may be lost during feature extraction and down-sampling. Moreover, practical UAV and edge-device applications require efficient models with limited computational [...] Read more.

UAV-based insulator detection is challenging because insulators often occupy small regions of aerial images and appear against complex backgrounds, while subtle local features may be lost during feature extraction and down-sampling. Moreover, practical UAV and edge-device applications require efficient models with limited computational and memory demands. This study proposes an optimized lightweight YOLOv11n model for high-voltage transmission-line insulator detection. The architecture integrates C3k2MBNV2 to reduce model complexity, SCDown to preserve spatial information during down-sampling, and C3k2WTDC to enhance multi-frequency feature representation. A diverse dataset containing 5750 insulator images acquired under different environmental conditions, viewing angles, and backgrounds was used for evaluation. Experimental results show that the proposed model reduces the parameter count from 6.20 M to 3.26 M and computational complexity from 20.5 to 12.7 GFLOPs, corresponding to reductions of 47.4% and 38.0%, respectively. Meanwhile, precision increases from 91.3% to 93.8%, recall from 73.4% to 75.2%, mAP50 from 71.2% to 73.9%, and mAP50–95 from 65.6% to 67.3%. These results demonstrate an improved accuracy–efficiency trade-off, supporting real-time insulator detection in resource-constrained UAV and edge-device applications. Full article

(This article belongs to the Section F1: Electrical Power System)

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37 pages, 2536 KB

Open AccessArticle

Power and Fatigue–Load Assessment of Static Wake Steering in a Floating Wind Farm with 15 MW Turbines

by Majid Ebrahimi, Federico Bellini, Alessandro Fontanella, Sara Muggiasca and Marco Belloli

Energies 2026, 19(16), 3938; https://doi.org/10.3390/en19163938 - 21 Aug 2026

Viewed by 323

Abstract

Static wake steering can increase wind-farm power production, but its application to floating offshore wind farms requires assessment of the coupled wake, platform, structural, and station-keeping response. This study evaluates whether power-maximizing static yaw setpoints identified using the steady, control-oriented FLORIS model retain [...] Read more.

Static wake steering can increase wind-farm power production, but its application to floating offshore wind farms requires assessment of the coupled wake, platform, structural, and station-keeping response. This study evaluates whether power-maximizing static yaw setpoints identified using the steady, control-oriented FLORIS model retain their benefit when transferred without re-optimization to a coupled FAST.Farm floating wind-farm model. The reference farm comprises four IEA Wind 15 MW turbines mounted on VolturnUS-S semi-submersible platforms. Greedy and static wake-steering operations are compared at three below-rated wind speeds, three sea states, and five matched turbulent-inflow realizations, resulting in 90 farm-level FAST.Farm simulations. Wake behavior is characterized through wake-center deflection, meandering, and velocity-deficit profiles, while turbine and mooring fatigue responses are evaluated using paired damage-equivalent-load statistics. Static wake steering increases mean farm power under all nine investigated wind–wave conditions. The gains are approximately 5.1–

5.2 %

at

7 m s^{- 1}

,

5.0

–

5.1 %

at

8 m s^{- 1}

, and

4.0

–

4.2 %

at

9 m s^{- 1}

, with all paired

95 %

confidence intervals remaining above zero. The gain results from a power redistribution in which the intentionally yawed upstream turbine incurs a local loss that is exceeded by the combined recovery of the downstream turbines. The fatigue response is strongly component- and turbine-dependent. The paired farm-mean blade-root DEL decreases by

0.82

–

2.24 %

, whereas the tower-base DEL increases by

0.76

–

2.78 %

, and the FairTen1 response generally increases by

0.88

–

2.92 %

. The farm-mean yaw-bearing response is mixed, ranging from a

1.15 %

reduction to a

4.32 %

increase. Turbine-level analysis reveals larger localized penalties, reaching approximately

10.4 %

for the yaw-bearing DEL and

12.8 %

for FairTen1. Spectral analysis associates the yaw-bearing response with yaw-induced aerodynamic and structural excitation, while the tower-base response is strongly influenced by low-frequency wave–platform dynamics. A complementary FLORIS sensitivity analysis demonstrates that the optimized aerodynamic benefit depends strongly on wind direction, spacing, wind speed, and turbulence intensity. For a Tampen-derived 11-turbine layout, resource weighting over the modeled 4–

13 m s^{- 1}

interval produces an annual energy-contribution increase of

3.653 GWh {year}^{- 1}

, or

0.921 %

. These results provide numerical evidence that static wake steering can retain a positive power benefit in a coupled floating wind-farm environment, but controller assessment must include turbine- and component-specific dynamic loads rather than farm power alone. Full article

(This article belongs to the Special Issue Latest Challenges in Modelling and Control of Wind Turbines: Aerodynamics, Structural Dynamics, Hydrodynamics and Inflow Effects)

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30 pages, 15338 KB

Open AccessArticle

Segmented Finite Line Source Analysis of Mid-Deep UBHE with Geothermal Gradient and Stratification

by Zhigang Shi, Zheng Xu, Lin Zhang, Shiwei Xia, Chaozheng Wang, Jin Tu and Peng He

Energies 2026, 19(16), 3937; https://doi.org/10.3390/en19163937 - 21 Aug 2026

Viewed by 317

Abstract

This study develops an analytical model for a mid-deep U-shaped borehole heat exchanger (UBHE) based on the segmented finite line source method, integrating geothermal gradient, five-layer geological stratification, and groundwater seepage within a unified framework. The injection, horizontal, and extraction sections are represented [...] Read more.

This study develops an analytical model for a mid-deep U-shaped borehole heat exchanger (UBHE) based on the segmented finite line source method, integrating geothermal gradient, five-layer geological stratification, and groundwater seepage within a unified framework. The injection, horizontal, and extraction sections are represented by independent local coordinates and coupled through the position- and time-dependent unit-length heat-transfer rate

q_{l} (s_{n}, t)

. Validation against the benchmark results of Bao et al. yields a mean absolute error of 0.87 °C and a mean relative error of 1.6%. Numerical-independence tests identify a 1 h time step and 100/50 m vertical/horizontal segment lengths as the adopted settings, and the iterative residual reaches 10⁻⁴ °C within eight iterations for the representative case. In a homogeneous, no-seepage limiting case, the model agrees with the classical finite line-source solution with an MAE of 0.012 °C and a maximum relative-error magnitude of 0.41%. The extraction-well fluid-temperature peak occurs at 600–800 m depth, whereas the local heat-transfer direction changes near 1600 m. For the investigated 2500–650–2500 m geometry, the highest cycle-averaged outlet temperature is obtained at an insulation length of 1600 m. Sensitivity analyses further quantify the effects of seepage velocity, equivalent thermal conductivity, geothermal gradient, and the validation insulation-length assumption. Full article

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50 pages, 5585 KB

Open AccessArticle

An Integrated Stochastic Decision-Support Framework: Hybrid Commercialization of Marginal Dry Gas Wells

by Juan Rogelio Rodríguez-Velázquez, Omar Gustavo Alvarado-Mancilla, Eduardo Morales-Sánchez, Jonás Velasco-Álvarez, Rubén Vázquez-Medina and Daniel Aguilar-Torres

Energies 2026, 19(16), 3936; https://doi.org/10.3390/en19163936 - 21 Aug 2026

Viewed by 518

Abstract

Natural gas production from mature fields is progressively shifting toward low-rate wells operating near their economic limit, creating challenges for long-term asset management. This study proposes an integrated stochastic decision-support framework combining Arps decline curve analysis, a calibrated Schwartz Type-I mean-reverting jump-diffusion model, [...] Read more.

Natural gas production from mature fields is progressively shifting toward low-rate wells operating near their economic limit, creating challenges for long-term asset management. This study proposes an integrated stochastic decision-support framework combining Arps decline curve analysis, a calibrated Schwartz Type-I mean-reverting jump-diffusion model, Monte Carlo simulation, and Bellman dynamic programming to optimize marginal dry gas well management. The framework evaluates pipeline commercialization and a hybrid strategy integrating on-site electricity generation, while incorporating monetized environmental externalities associated with CO₂ emissions from gas combustion and potential post-abandonment CH₄ emissions. Application to the Mareógrafo 100 well in Mexico shows that the environmentally adjusted Bellman policy yields a mean NPV of USD 34.84 thousand, exceeding the comparable pipeline-only and hybrid strategies. Internalizing environmental costs reduces the mean optimal NPV by 46.6% relative to the economic-only formulation, while the mean abandonment time is approximately 200 days. Sensitivity analysis identifies electricity price, natural gas price, and pipeline distance as the dominant profitability drivers. The proposed framework provides a transferable methodology for jointly evaluating commercialization, environmental externalities, and abandonment decisions in mature dry gas fields under uncertainty. Full article

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27 pages, 7511 KB

Open AccessArticle

From Prediction to Decision: A Unified Dual-Stage LLM-Driven Framework for Intelligent Energy Management with Unstructured Information

by Yong Chen, Guo Chen and Fang Yao

Energies 2026, 19(16), 3935; https://doi.org/10.3390/en19163935 - 21 Aug 2026

Viewed by 217

Abstract

Modern energy systems, including those supporting transportation electrification, are increasingly exposed to volatile market conditions and external events. Effective decision-making therefore requires the integration of structured operational data with unstructured contextual information. Existing studies on Large Language Model (LLM)-assisted energy systems have mainly [...] Read more.

Modern energy systems, including those supporting transportation electrification, are increasingly exposed to volatile market conditions and external events. Effective decision-making therefore requires the integration of structured operational data with unstructured contextual information. Existing studies on Large Language Model (LLM)-assisted energy systems have mainly applied LLMs to individual tasks such as forecasting, scheduling, or decision support, while forecasting and control are typically treated separately. As a result, semantic information extracted from external events is not consistently propagated from market prediction to operational decision-making. This paper proposes a unified dual-stage framework in which the LLM functions as a shared semantic information processor, converting raw event data into structured representations used by both forecasting and control modules. In the forecasting stage, these representations improve price prediction under non-stationary conditions. In the control stage, the same information provides an event-aware contextual action prior for reinforcement learning-based energy management. This design allows external event information to inform both future-state estimation and subsequent control decisions, establishing a consistent connection between prediction and decision-making. The framework is evaluated using real-world electricity market data and a battery energy management environment. The results show that the proposed framework achieves the highest average cumulative reward among the evaluated methods while maintaining greater robustness than the forecasting-only LLM configuration. Overall, this work demonstrates the benefit of consistently propagating structured semantic information across forecasting and control and provides a viable approach to event-aware intelligent energy management, with potential extensions to multi-energy transportation systems and electrified mobility applications. Full article

(This article belongs to the Topic Intelligent Modeling, Predictive Control, and Decision-Making for Multi-Energy Transportation Systems)

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23 pages, 2825 KB

Open AccessArticle

Hierarchical Distributed Optimal Scheduling of Integrated Electricity–Gas–Heat Systems: An ATC–ADMM Approach

by Zekai Zong and Bin Song

Energies 2026, 19(16), 3934; https://doi.org/10.3390/en19163934 - 21 Aug 2026

Viewed by 293

Abstract

Integrated electricity–gas–heat systems require coordinated scheduling while limiting data sharing and representing network constraints. This paper develops a day-ahead model incorporating reactive power, voltage magnitudes, network losses, demand response, and CHP/P2G coupling. Piecewise linearization and second-order cone relaxation reformulate the model as a [...] Read more.

Integrated electricity–gas–heat systems require coordinated scheduling while limiting data sharing and representing network constraints. This paper develops a day-ahead model incorporating reactive power, voltage magnitudes, network losses, demand response, and CHP/P2G coupling. Piecewise linearization and second-order cone relaxation reformulate the model as a mixed-integer second-order cone program, while a hierarchical ATC–ADMM method coordinates the electricity–heat and natural gas subsystems by exchanging coupling variables. Residual checks verify approximation accuracy and original equation feasibility. In the test system, ATC–ADMM reached consensus within five iterations, with a total-cost deviation of 0.0075% from centralized optimization, whereas ATC did not converge within 500 iterations. Coordinated operation reduced the total cost by 1.13%, and Shapley allocation benefited both subsystems. Increasing demand-side flexibility from 5% to 9% reduced the total cost by 0.88% and wind curtailment from 6.02% to 4.86%; increasing reactive compensation from 40% to 60% reduced the total cost by 0.41% and wind curtailment to 5.70%. The results reveal non-monotonic penalty-update effects and diminishing marginal benefits of flexibility resources, providing guidance for parameter selection and capacity allocation. Full article

(This article belongs to the Section F: Electrical Engineering)

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32 pages, 14184 KB

Open AccessArticle

Surface Hydraulic Fracturing with L-Shaped Wells for Rock Burst Prevention in Hard Roof Key Strata of Deep Coal Mines

by Weixin Zhang, Hailong Xiangli, Hongli Song, Jianxi Ren, Jingkun Li and Yongtao Zhang

Energies 2026, 19(16), 3933; https://doi.org/10.3390/en19163933 - 21 Aug 2026

Viewed by 277

Abstract

Targeting the rock burst hazard induced by the hard roof key stratum during deep mining at the Mengcun Coal Mine in the Binchang mining area, this study takes the No. 403109 working face as the engineering background and systematically investigates the rockburst prevention [...] Read more.

Targeting the rock burst hazard induced by the hard roof key stratum during deep mining at the Mengcun Coal Mine in the Binchang mining area, this study takes the No. 403109 working face as the engineering background and systematically investigates the rockburst prevention mechanism and effectiveness of ground hydraulic fracturing through theoretical analysis, UDEC numerical simulation, and surface microseismic monitoring. The results indicate that fracturing pre-weakens the overlying key stratum, transforming its load-bearing mode from a long-beam rigid support to a segmented flexible support. This significantly reduces the cantilever length, lowers the accumulation of elastic strain energy, and enables flexible load transfer and stress redistribution in the overburden. Numerical simulations reveal that after fracturing, the breakage timing of the key stratum advances, the fragmentation size decreases, and the over-burden movement shifts from stepwise fracturing to sequential caving, with the stress concentration zone substantially narrowed. In the field, a total of 44 fracturing stages were implemented in wells MC-05L and MC-06L, creating a fracture network with an average fracture length of 317 m and an average fracture height of 55 m, achieving an effective stimulated volume ratio of 86.7%. During the mining period, microseismic events exhibited a median energy of only 868.14 J, characterized by high frequency and low energy. The average weighting interval was 13.69 m, the peak coal stress was controlled within 5.0–6.7 MPa, and the loads on roadway bolts and cables remained within safe limits. This study validates the source-control effect of ground hydraulic fracturing on working faces with strong rock burst risks in deep mining, providing a theoretical basis and engineering reference for mines with analogous conditions. Full article

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21 pages, 1461 KB

Open AccessArticle

Basin-Scale Screening of Spillway-Related Total Dissolved Gas Generation Potential Under Intermittent Hydropower Operation in the Brazilian Amazon and Tocantins–Araguaia Basins

by Guilherme Martinez Figueiredo Ferraz, Dieimys Santos Ribeiro, Guilherme Sousa Bastos, Walker Matheus Ferreira da Silva, Andrey Leonardo Fagundes de Castro, Lorena Bettinelli Nogueira, Juliano Mafra Neves, Liandro Rosa, Bruno Correia Macedo, Ramon Rodrigues Vieira de Carvalho and Carlos Barreira Martinez

Energies 2026, 19(16), 3932; https://doi.org/10.3390/en19163932 - 21 Aug 2026

Viewed by 313

Abstract

As variable renewable generation grows, intermittent dispatch of run-of-river hydropower plants may transfer required environmental-flow releases from turbines to spillways, creating conditions that favor total dissolved gas (TDG) supersaturation and may constrain hydropower flexibility. This study presents a reproducible basin-scale screening assessment for [...] Read more.

As variable renewable generation grows, intermittent dispatch of run-of-river hydropower plants may transfer required environmental-flow releases from turbines to spillways, creating conditions that favor total dissolved gas (TDG) supersaturation and may constrain hydropower flexibility. This study presents a reproducible basin-scale screening assessment for 24 selected hydropower plants in the Brazilian Amazon and Tocantins–Araguaia basins. The analysis combines a plant inventory, spillway typology, standardized environmental-flow scenarios, and two configuration-specific linear relationships between unit discharge and the increase in TDG saturation (ΔTDG), derived from digitized Pubugou and Gongzui observations. Two release configurations were examined: flow distributed among all available bays and flow concentrated in a single bay as a theoretical hydraulic bounding case. The Pubugou-based relationship was applied only to broadly comparable ski-jump configurations within 9.1 ≤ UD ≤ 72.3 m³ m⁻¹ s⁻¹, whereas the Gongzui-based relationship was provisionally assigned, as an inventory-level first-order analog, to controlled spillways discharging into stilling basins within 34.6 ≤ UD ≤ 234.6 m³ m⁻¹ s⁻¹. Hydraulically dissimilar cases were classified as NE-H, and cases outside the applicable empirical domain as NE-UD. Digitization sensitivity, regression uncertainty, and model-form selection were explicitly evaluated and documented. None of the distributed-flow scenarios produced a numerical estimate: cases assigned to the Pubugou- or Gongzui-based relationships were classified as NE-UD, whereas hydraulically dissimilar free-surface cases were classified as NE-H. Four single-bay scenarios produced configuration-specific

Δ T D G

increments: 22.5–33.4 percentage points for three Gongzui-based cases and 13.6 percentage points for one Pubugou-based case. Upstream TDG was not added, and no plant-specific final concentration or universal ranking was reported. Sinop and Colíder observations were retained as qualitative contextual evidence of limited transferability and the importance of site-specific hydraulics. The outputs support conditional monitoring prioritization under standardized assumptions, not compliance prediction, ecological-risk assessment, or gate-operation recommendations. Synchronized monitoring and plant-specific rating curves are required before TDG-related variables can be incorporated into operational planning. Full article

(This article belongs to the Special Issue Flexibility Regulation and Operational Optimization of New-Type Power Systems)

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31 pages, 73006 KB

Open AccessArticle

Numerical Study on the Energy-Harvesting Performance of a Flapping Foil Under Vortical-Gust Encounters

by Shihui Wu, Xiaoyang Wang, Hua Qiang, Zhixu Zhou, Shaofeng Wu, Shuangbao Luo and Li Wang

Energies 2026, 19(16), 3931; https://doi.org/10.3390/en19163931 - 21 Aug 2026

Viewed by 305

Abstract

Coherent vortices alter flapping-foil energy harvesting, but wake-generated vortex properties and timing are coupled to upstream-body kinematics. We use two-dimensional immersed boundary–lattice Boltzmann simulations of a prescribed heaving–pitching NACA0015 foil at

R e = 1100

. An independently prescribed Taylor vortex allows nominal [...] Read more.

Coherent vortices alter flapping-foil energy harvesting, but wake-generated vortex properties and timing are coupled to upstream-body kinematics. We use two-dimensional immersed boundary–lattice Boltzmann simulations of a prescribed heaving–pitching NACA0015 foil at

R e = 1100

. An independently prescribed Taylor vortex allows nominal encounter phase, body-fixed offset, diameter, and intensity to be varied at fixed kinematics. Production-grid

{\bar{C}}_{P}

is within

0.10 %

of the fine-grid result; the fine-grid diffusion test gives a maximum full-field velocity

L_{2}

error of

0.0690 %

against the analytical solution over

0 \leq t^{*} \leq 4

. For the reference vortex with a pivot-centered nominal target (

D / c = v_{θ m} / U_{\infty} = 1

), nominal-encounter-aligned mean power coefficients of

0.747

,

0.862

, and

0.987

occur at

ψ_{e} = 0.10

,

0.40

, and

0.60

, respectively, compared with

0.832

without gusts. These define the power-reducing (PR), near-baseline (NB), and power-enhancing (PE) cases. Within the sampled ranges, diameter is associated mainly with disturbance reach and duration, intensity with loading magnitude, and offset with spatial overlap and interaction timing. Power variations are consistent with the timing of vortex-modified loading relative to prescribed foil motion. In three same-sign, once-per-cycle sequences, the PR–NB–PE ordering persists despite residual-wake interactions, with sustained mean power coefficients of

0.763

,

0.916

, and

0.965

, respectively. Nominal encounter phase and foil placement should be considered jointly for repeatable or predictable vortex passages. Full article

(This article belongs to the Special Issue Development of Energy Harvesting Systems and Methods from Uncommon Sources: 2nd Edition)

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23 pages, 4277 KB

Open AccessArticle

A Numerical–Textual Dual-Channel Forecasting Framework for Short-Term Load Forecasting

by Xiaohu Xin, Jing Xu, Xin Wang, Weili Xu, Yang Yue, Chengshuai Wang, Junwei Yang and Bing Sun

Energies 2026, 19(16), 3930; https://doi.org/10.3390/en19163930 - 21 Aug 2026

Viewed by 360

Abstract

Short-term load forecasting underpins power-system dispatching, yet classical models degrade when historical samples are scarce. This paper proposes NTSForecast, a numerical–textual dual-channel framework: a trainable multi-layer perceptron encodes the numerical input, a frozen large language model (LLM) embeds the task instruction and the [...] Read more.

Short-term load forecasting underpins power-system dispatching, yet classical models degrade when historical samples are scarce. This paper proposes NTSForecast, a numerical–textual dual-channel framework: a trainable multi-layer perceptron encodes the numerical input, a frozen large language model (LLM) embeds the task instruction and the field labels, and a small head returns the load from the frozen decoder output. No backbone parameter is updated at any point. At each of six rolling origins training sees only a seven-day record of 94 samples, while the non-overlapping test windows supply 7824 held-out hourly points across four seasons, five seeds each. NTSForecast attains the lowest MAE, RMSE and MAPE of the methods compared (5.66 ± 0.04% against 5.68% for the strongest baseline), but that margin is small and sensitive to how serial dependence is handled; under scarce history the framework is competitive with that baseline, not superior to it. What the evidence does establish is the contribution of the frozen backbone. With architecture, trainable-parameter count, hyperparameters and data held identical, removing it costs 1.38 percentage points of MAPE. Backbone scale runs against a capacity argument; on a 0.5B-to-8B ladder the smallest pretrained backbone is the most accurate and becomes the reference configuration (1445 MB peak memory). Removing the textual channel costs 1.17 percentage points. Full article

(This article belongs to the Topic Advanced Forecasting Methods for Sustainable Power Systems)

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21 pages, 3528 KB

Open AccessArticle

Comparison Between Transportation and Disjunctive DC Models in the Transmission Expansion Planning

by Mateus de Oliveira Vaz, Murilo E. C. Bento and Gustavo da Silva Viana

Energies 2026, 19(16), 3929; https://doi.org/10.3390/en19163929 - 21 Aug 2026

Viewed by 249

Abstract

This paper presents a comparative analysis of two models for direct current (DC) networks used in transmission expansion planning (TEP) problems. These models incorporate distinct sets of constraints and have different levels of detail: the transportation model incorporates only Kirchhoff’s First Law, while [...] Read more.

This paper presents a comparative analysis of two models for direct current (DC) networks used in transmission expansion planning (TEP) problems. These models incorporate distinct sets of constraints and have different levels of detail: the transportation model incorporates only Kirchhoff’s First Law, while disjunctive model represents both Kirchhoff’s Laws. The choice of an appropriate modeling approach is a critical decision for planners, as it directly impacts the accuracy and feasibility of expansion plans. This study examines the impact of these different DC system representations, particularly in multi-terminal configurations with closed meshed topologies, on power flow calculations and system expansion investments. Although these models are well established for alternating current (AC) networks, their application to the DC portion of power systems is still under development regarding more complex grids. The results, obtained through modified IEEE test cases incorporating DC meshes along with a simplified example case, show superior results of the disjunctive DC formulation in comparison to the transportation model. Full article

(This article belongs to the Section F1: Electrical Power System)

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32 pages, 11501 KB

Open AccessArticle

Experimental Evaluation of Synthetic n-Propanol in a Dual-Fuel Engine and Modeling of Its Renewable Electrochemical Production from CO₂

by Janusz Kotowicz, Kamil Niesporek and Wojciech Tutak

Energies 2026, 19(16), 3928; https://doi.org/10.3390/en19163928 - 21 Aug 2026

Viewed by 283

Abstract

The use of synthetic fuels produced from CO₂ requires efficient production technologies and evaluation of their application in energy systems. This study combines experimental tests of a dual-fuel engine powered by n-propanol and diesel fuel with modeling of electrochemical n-propanol synthesis from [...] Read more.

The use of synthetic fuels produced from CO₂ requires efficient production technologies and evaluation of their application in energy systems. This study combines experimental tests of a dual-fuel engine powered by n-propanol and diesel fuel with modeling of electrochemical n-propanol synthesis from CO₂. The aim was to determine the optimal n-propanol share and investigate the performance of a tandem electrochemical reactor. Increasing the energy share of n-propanol reduced CO and CO₂ emissions. The highest engine efficiency of 33.94% was achieved at a 50% energy share of n-propanol, representing an increase of 1.5% compared with diesel-only operation. At this operating point, CO and CO₂ emissions were reduced by 87.7% and 18.5%, respectively, compared with diesel-only operations. This point was selected for further analysis. A mathematical model of a tandem electrochemical reactor was developed. The system included CO₂-to-CO conversion followed by n-propanol synthesis. The energy efficiencies of the CO generation and n-propanol synthesis reactors were 47.77% and 23.07%, respectively. Faradaic efficiency and cell voltage were the main factors affecting reactor performance. The overall tandem reactor efficiency ranged from 12% to 22%. The results confirm the potential of n-propanol as a dual-fuel engine fuel and identify key directions for improving electrochemical CO₂ conversion. Full article

(This article belongs to the Special Issue Renewable Energy-Driven Production of Synthetic Fuels: Technologies, Systems and Sustainability)

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4 pages, 145 KB

Open AccessEditorial

Editorial: Special Issue “From Waste to Energy: Towards Resource Recovery Optimization from Waste”

by Christian Aragón-Briceño, Panagiotis Boutikos and Musa Manga

Energies 2026, 19(16), 3927; https://doi.org/10.3390/en19163927 - 21 Aug 2026

Viewed by 305

Abstract

One of society’s most pressing goals is the transition toward a circular economy, in which governments and industries alike are prioritizing the minimization of waste through the maximization of resource use [...] Full article

(This article belongs to the Special Issue From Waste to Energy: Towards Resource Recovery Optimization from Waste)

23 pages, 8025 KB

Open AccessArticle

Environmental Impact Assessment of Photovoltaic Parks Through a RIAM-Based Environmental Indicator Matrix

by Despoina Konstantinou and Dimitra G. Vagiona

Energies 2026, 19(16), 3926; https://doi.org/10.3390/en19163926 - 21 Aug 2026

Viewed by 331

Abstract

Photovoltaic parks support climate change mitigation by generating low-emission electricity. However, their environmental impacts strongly depend on site features and proximity to environmentally sensitive areas. The aim of the present paper is to develop and apply an innovative methodological framework that integrates an [...] Read more.

Photovoltaic parks support climate change mitigation by generating low-emission electricity. However, their environmental impacts strongly depend on site features and proximity to environmentally sensitive areas. The aim of the present paper is to develop and apply an innovative methodological framework that integrates an environment-based Rapid Impact Assessment Matrix with selected indicators. Six environmental components are linked to ten measurable indicators. Each indicator is documented through an inventory sheet and evaluated using adapted RIAM criteria. The proposed methodology is applied to the existing photovoltaic farm installations located in the Regional Unit of Messinia, Greece. The results show that most indicators produced positive Environmental Scores across the examined installations. The negative impacts are mainly associated with the proximity of the projects to wildlife refuges. The largest variations were associated with distance from wildlife refuges and forested areas, with standard deviations of 67.9 and 58.4, respectively. PV7 received major negative Environmental Scores of −96 and −72 because it is located within a wildlife refuge and forested land, while PV8 received a score of −72 due to its overlap with sclerophyllous vegetation. On the other hand, the positive impacts are mainly reflected in CO₂ reduction across all photovoltaic parks in the study area. These findings confirm that appropriate site selection of photovoltaic parks is a decisive factor in either reducing or eliminating environmental impacts. The proposed methodology can be applied to any photovoltaic farm and study area, enabling quantification of environmental impacts and facilitating comparative assessment of these projects. Full article

(This article belongs to the Section B: Energy and Environment)

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21 pages, 4815 KB

Open AccessArticle

Probabilistic Prediction of Ice-Shedding Jump Height of Overhead Transmission Lines Using a Dimensionless-Group-Guided Bayesian Neural Network

by Bing Li, Shuaiqi Zhu, Mengqi Zhang, Yuan Yao, Deshui Yu, Zichao Zhang and Yizhao Li

Energies 2026, 19(16), 3925; https://doi.org/10.3390/en19163925 - 21 Aug 2026

Viewed by 281

Abstract

The jump height of overhead transmission lines after ice shedding is closely related to electrical clearance, and structural safety. For different conductor parameters, span lengths, horizontal stress, and icing conditions, transient finite-element analysis can provide detailed dynamic responses, but repeated simulations are not [...] Read more.

The jump height of overhead transmission lines after ice shedding is closely related to electrical clearance, and structural safety. For different conductor parameters, span lengths, horizontal stress, and icing conditions, transient finite-element analysis can provide detailed dynamic responses, but repeated simulations are not convenient for fast engineering assessment. In addition, a deterministic prediction model only gives a single jump-height value, and the reliability of this value is difficult to judge when the input condition is close to the boundary of the sampled range. In this study, a Dimensionless-Group-Guided Bayesian Neural Network (DG-BNN) is developed to predict the ice-shedding jump height and estimate the associated uncertainty. The original physical variables are first transformed into seven dimensionless Pi-groups according to Buckingham Pi dimensional analysis. These variables describe the main effects of geometry, mass distribution, stress state, and ice shedding in a compact form. The network is trained through a two-stage procedure. A heteroscedastic regression model is first obtained with a trend-regularization term based on a fixed second-order polynomial, and then the deterministic layers are converted into Bayesian layers for probabilistic inference. Monte Carlo sampling is used to calculate the predictive mean, epistemic uncertainty, and aleatoric uncertainty. Temperature scaling is further introduced to adjust the prediction intervals on the validation set. The comparison with several regression models shows that DG-BNN can maintain accurate jump-height prediction while giving calibrated uncertainty information. On the FEM-generated test set, DG-BNN achieved an R² of 0.986, an RMSE of 0.958 m, and an MAE of 0.649 m. After temperature calibration, the coverage probability of the 90% prediction interval reached 89.96%. The model can therefore serve as a fast surrogate tool for ice-shedding response assessment, especially when the reliability of the predicted result needs to be considered. Full article

(This article belongs to the Section F: Electrical Engineering)

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18 pages, 444 KB

Open AccessArticle

Foreign Direct Investment and Energy Infrastructure in Sub-Saharan Africa: Does Energy Infrastructure Condition the Sustainable Development Effects of FDI?

by Patricia Lindelwa Makoni and Jude Igyo Ali

Energies 2026, 19(16), 3924; https://doi.org/10.3390/en19163924 - 20 Aug 2026

Viewed by 322

Abstract

Despite rising foreign direct investment (FDI), Sub-Saharan Africa continues to experience inadequate energy infrastructure and weak sustainable development outcomes, suggesting that investment alone is insufficient to generate long-term development gains. This study investigates whether energy infrastructure conditions the relationship between FDI and sustainable [...] Read more.

Despite rising foreign direct investment (FDI), Sub-Saharan Africa continues to experience inadequate energy infrastructure and weak sustainable development outcomes, suggesting that investment alone is insufficient to generate long-term development gains. This study investigates whether energy infrastructure conditions the relationship between FDI and sustainable development in 35 Sub-Saharan African countries over the period 2000–2024. Sustainable development is measured using adjusted net savings, while energy infrastructure is proxied by the Energy Infrastructure Composite Index. The analysis employs complementary second-generation panel estimators, including fixed effects with Driscoll–Kraay standard errors, common correlated effects mean group, Augmented Mean Group, System Generalized Method of Moments, and panel quantile regression to address cross-sectional dependence, slope heterogeneity, endogeneity, dynamic persistence, and distributional heterogeneity. The results demonstrate that FDI exerts adverse effects on sustainable development where energy infrastructure is weak but generates significant positive outcomes as infrastructure improves. Institutional quality consistently emerges as the most robust determinant across all estimators and quantiles, while the positive interaction between FDI and energy infrastructure confirms that stronger energy systems enhance countries’ absorptive capacity. The findings underscore the need for coordinated investments in energy infrastructure and institutional reforms to maximize the sustainable development benefits of foreign investment in Sub-Saharan Africa. Full article

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22 pages, 4965 KB

Open AccessArticle

Wave Energy Converter Feasibility in Türkiye’s Surrounding Waters: A Twenty-Year, Four-Basin Assessment

by Ahmet Durap

Energies 2026, 19(16), 3923; https://doi.org/10.3390/en19163923 - 20 Aug 2026

Viewed by 477

Abstract

Wave energy in short-fetch, semi-enclosed seas depends on how closely the response of a converter matches locally generated, short-period waves. This study makes that match explicit for the Black Sea, the Sea of Marmara, the Aegean, and the Eastern Mediterranean, the four seas [...] Read more.

Wave energy in short-fetch, semi-enclosed seas depends on how closely the response of a converter matches locally generated, short-period waves. This study makes that match explicit for the Black Sea, the Sea of Marmara, the Aegean, and the Eastern Mediterranean, the four seas around Türkiye, as four distinct regions within a single study area. Twenty years (May 2006 to March 2026) of three-hourly significant wave height and energy period from the Copernicus Marine global wave reanalysis (0.2°) were combined with GEBCO 2026 bathymetry to map the wave power flux, to screen cells inside a first-order 25–100 m deployment-depth band, and to rank three candidate sites in each region. Specific power matrices were applied to three full-scale reference converters (Pelamis P-750, AquaBuOY and Wave Dragon) and to two shallow-water archetypes, the Oyster surge flap and the Wavestar multi-float machine, standing for contemporary shallow-water design classes, at full scale and under Froude similitude. The best deployable sites of the Black Sea and the Aegean carry mean fluxes of 3.1–3.6 kW m⁻¹, and the Marmara sites define the low-resource end member at 0.2–0.8 kW m⁻¹; mean energy periods at the twelve sites range from 2.7 to 5.4 s. At their original scale the three reference converters reach capacity factors of up to 3.4%, because their specific power matrix response bands fall largely outside the regional sea-state distribution. Scaling changes that. Froude scaling to 0.20–0.25 of the original linear dimensions moves the response into the dominant 4–5 s band and raises the capacity factor to 30–47% at the seven sites where the mean flux exceeds 2.5 kW m⁻¹, at scaled rated powers of about 2–25 kW; the two archetypes reach 7–19% at full scale and 49–59% once scaled at the same sites. Both the preferred scale and the achievable capacity factor are near-uniform along the Black Sea rim, the Aegean archipelago, and the Levantine shore, so the analysis yields a single regional design specification, as follows: a small, short-period converter deployed in modular arrays. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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29 pages, 1248 KB

Open AccessArticle

Novel Performance of T-S Fuzzy Power System Based on a New Slack Lemma and an Optimization Algorithm

by Ziqiao Tang, Zhixiang Li, Yu Hu, Can Zhao, Won-Ho Kim, Haiyin Qing and Tao Liu

Energies 2026, 19(16), 3922; https://doi.org/10.3390/en19163922 - 20 Aug 2026

Viewed by 241

Abstract

This paper studies performance analysis and load frequency control (LFC) for a Takagi–Sugeno (T-S) fuzzy power system equipped with an energy storage unit. A corresponding T-S fuzzy representation of the system is constructed. Subsequently, a new lemma of slack Lyapunov function is constructed, [...] Read more.

This paper studies performance analysis and load frequency control (LFC) for a Takagi–Sugeno (T-S) fuzzy power system equipped with an energy storage unit. A corresponding T-S fuzzy representation of the system is constructed. Subsequently, a new lemma of slack Lyapunov function is constructed, which relaxes the conventional positive-definiteness requirement on the quadratic form, provides additional flexibility in the LMI formulation, and yields less conservative stability conditions. In addition, a genetic-algorithm-based outer search is employed to optimize the scalar parameter

ϱ

, while the associated LMIs are solved using the LMI solver, thereby reducing the conservatism of the stability conditions and enlarging the maximum allowable delay bound. Simulation cases are finally presented to confirm the feasibility and effectiveness of the proposed methods. The proposed method increases the maximum allowable delay bound by

2.6920 %

,

4.0220 %

and

4.0528 %

compared with the reference method for the tested controller parameters. Full article

(This article belongs to the Section F1: Electrical Power System)

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24 pages, 3191 KB

Open AccessArticle

Enhancement of Renewable Power System Protection Reliability Using a Superconducting Fault Current Limiting Circuit Breaker (SFCL-CB)

by Sangjae Choi and Sung-Hun Lim

Energies 2026, 19(16), 3921; https://doi.org/10.3390/en19163921 - 20 Aug 2026

Viewed by 234

Abstract

The proliferation of inverter-based resources (IBRs) and energy storage systems in power grids has led to a decline in the short-circuit ratio (SCR) and reduced fault current magnitudes, compromising the reliability of conventional overcurrent relays (OCRs) and creating protection blind zones. To resolve [...] Read more.

The proliferation of inverter-based resources (IBRs) and energy storage systems in power grids has led to a decline in the short-circuit ratio (SCR) and reduced fault current magnitudes, compromising the reliability of conventional overcurrent relays (OCRs) and creating protection blind zones. To resolve these vulnerabilities, this paper proposes an electromagnetic repulsion-based Superconducting Fault Current-Limiting Circuit Breaker (SFCL-CB) utilizing a flux-lock type mechanism. Unlike protection schemes that rely on secondary accessories such as current and potential transformers which introduce computational delays, the proposed SFCL-CB utilizes a driving force that scales with the square of the current gradient ((di/dt)²). This characteristic allows the device to distinguish low-magnitude fault currents from transient load growths. Through duality-based modeling and parametric simulations in PSCAD/EMTDC, the structural and electrical design configurations—including the coil turns (N₁, N₂) and the superconducting quench resistance (R_SC)—were optimized. The simulation results verify that the proposed SFCL-CB substantially reduces the OCR blind zone, securing fault clearance within a maximum of 0.131 s in the regions cleared under low SCR and high-fault-resistance conditions, while achieving mechanical separation in 0.0048 s under robust power system. This SFCL-CB offers an alternative to enhance the protection reliability and operational stability of distribution power system. Full article

(This article belongs to the Special Issue Application of the Superconducting Technology in Energy System)

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27 pages, 22895 KB

Open AccessArticle

Multi-Year Assessment of the Real-World Performance of Residential Photovoltaic Microinstallations in the Sandomierz Basin, Southeastern Poland

by Bogdan Saletnik, Katarzyna Kamińska and Czesław Puchalski

Energies 2026, 19(16), 3920; https://doi.org/10.3390/en19163920 - 20 Aug 2026

Viewed by 250

Abstract

The rapid expansion of residential photovoltaics (PV) increases the need for long-term evidence on system performance under real operating conditions. This study compared four grid-connected rooftop PV microinstallations (4.69–5.04 kWp) located in the Sandomierz Basin, southeastern Poland, over 2022–2025. Monthly alternating-current production from [...] Read more.

The rapid expansion of residential photovoltaics (PV) increases the need for long-term evidence on system performance under real operating conditions. This study compared four grid-connected rooftop PV microinstallations (4.69–5.04 kWp) located in the Sandomierz Basin, southeastern Poland, over 2022–2025. Monthly alternating-current production from SolarEdge monitoring was combined with regional sunshine duration and mean air temperature from the IMGW Sandomierz station, providing 192 installation–month observations. Specific yield, capacity factor, a model-based estimate of the performance ratio (PR_AP), Pearson correlations, ordinary least-squares regression, and sensitivity analysis of a documented failure were applied. Mean annual specific yields were 1077.7, 1061.7, 908.6, and 779.6 kWh/kWp for PV-I–PV-IV, respectively, while mean PR_AP estimates were 82.2%, 82.5%, 70.6%, and 65.5%. Sunshine duration was strongly correlated with monthly specific yield (r = 0.830–0.983; p < 0.001), and the combined model explained 88.8% of its variability. Excluding the zero-output failure month of PV-IV increased R² for the sunshine–yield relationship from 0.689 to 0.812 and improved the combined-model fit from 0.888 to 0.921. Greater nominal capacity did not guarantee higher normalized productivity. Regional solar-resource information should therefore be complemented by monitored operational data to support design, benchmarking, fault detection, and local distributed-energy planning. The findings also support SDG 7 by providing evidence for more reliable, locally adapted planning and operation of household photovoltaic systems. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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20 pages, 12170 KB

Open AccessArticle

Geometrical Effects of Flow Reversers on the Thermo-Hydraulic Performance of a Rotating Horizontal Spiral Heat Exchanger

by Mohammad Mobin Bakhshi, Faezeh Ahangar, Mohammadreza Abbaspour, Huixuan Wu, Akshay Anand and Ganesh Desai Ramakrishna

Energies 2026, 19(16), 3919; https://doi.org/10.3390/en19163919 - 20 Aug 2026

Viewed by 265

Abstract

This research numerically evaluates the effects of various geometric parameters on the optimization of flow reversers on a rotating spiral heat exchanger utilizing computational fluid dynamics. There were three important geometric parameters investigated to find their impact on thermo-hydraulic characteristics: (i) distribution frequency [...] Read more.

This research numerically evaluates the effects of various geometric parameters on the optimization of flow reversers on a rotating spiral heat exchanger utilizing computational fluid dynamics. There were three important geometric parameters investigated to find their impact on thermo-hydraulic characteristics: (i) distribution frequency of reversers along the spiral channel, (ii) reverser turn diameter, and (iii) reverser tube diameter. Thermo-hydraulic characteristics of the proposed designs were studied according to the velocity and temperature distributions, average Nusselt number, pressure drop, and performance evaluation criterion. From all the evaluated designs, the reduction in reverser tube diameter resulted in the most desirable performance as the average Nusselt number increased about 44.6% while the pressure drop increased merely by 10% compared to the base design. Thus, the obtained design gave the best performance evaluation criterion of around 1.77. Decrease in reverser turn diameter led to an increase in Nusselt number about 6.3%, although with 40% increase in pressure drop, resulting in the worst performance evaluation criterion of approximately 1.20. Overall, the results show that proper geometric optimization of flow reversers is able to noticeably enhance the thermo-hydraulic performance of the heat exchangers. Full article

(This article belongs to the Section J: Thermal Management)

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17 pages, 2601 KB

Open AccessArticle

High-Precision Insulation Monitoring-Driven Intelligent Fault Line Selection Method for Photovoltaic DC Grounding Faults

by Binyao Lu and Xiangning Lin

Energies 2026, 19(16), 3918; https://doi.org/10.3390/en19163918 - 20 Aug 2026

Viewed by 235

Abstract

Currently, insulation faults in the DC system of photovoltaic (PV) power stations are handled by a full shutdown strategy of inverters, and fault branch localization relies on manual inspection, resulting in low efficiency and poor accuracy, leading to prolonged unplanned outages and substantial [...] Read more.

Currently, insulation faults in the DC system of photovoltaic (PV) power stations are handled by a full shutdown strategy of inverters, and fault branch localization relies on manual inspection, resulting in low efficiency and poor accuracy, leading to prolonged unplanned outages and substantial power generation losses. This paper proposes an integrated solution combining high-precision insulation monitoring and intelligent fault line selection, which ensures the reliability of line selection criteria through improved measurement accuracy and achieves automatic fault isolation via optimized line selection strategies. The paper analyzes the mathematical essence of the ill-conditioned measurement equations of the traditional bridge method under severe single-pole grounding faults, establishes a dual-channel heteroscedastic noise model, and utilizes the inherent physical constraint that the sum of the positive and negative pole-to-ground voltages always equals the bus voltage to transform the ill-posed inverse problem into an equality-constrained optimal estimation problem, deriving an analytical solution in the sense of constrained least squares. A collaborative monitoring strategy of “balanced bridge monitoring first, unbalanced bridge precision measurement afterward” is proposed. An automatic fault line selection and isolation algorithm based on sequential branch switching is designed, which leverages the operational characteristic that PV systems allow short-term branch interruption, enabling automatic identification and isolation of faulty branches and automatic restoration of non-faulty branches without installing any leakage current sensors. Experimental results show that under severe fault conditions with a single-pole insulation resistance as low as 22 kΩ, the proposed method limits the error to within 5%; the proposed line selection strategy can complete identification and isolation of all faulty branches within at most two rounds of switching. Full article

(This article belongs to the Section F1: Electrical Power System)

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22 pages, 1308 KB

Open AccessArticle

Phase-Adaptive Constrained Active Sampling for Simulation-Verified Planning of Renewable Energy Bases

by Jishuo Qin, Yahan Dong, Fan Li, Jian Meng, Jingyan Liu and Taikun Tao

Energies 2026, 19(16), 3917; https://doi.org/10.3390/en19163917 - 20 Aug 2026

Viewed by 262

Abstract

Planning renewable energy bases with chronological source-grid-storage simulation makes exhaustive capacity screening impractical. This study develops a phase-adaptive constrained active-sampling framework whose core mechanism is a simulator-verified phase switch: a probability-of-feasibility-weighted lower confidence bound (PoF-LCB) directs the search until the first verified feasible [...] Read more.

Planning renewable energy bases with chronological source-grid-storage simulation makes exhaustive capacity screening impractical. This study develops a phase-adaptive constrained active-sampling framework whose core mechanism is a simulator-verified phase switch: a probability-of-feasibility-weighted lower confidence bound (PoF-LCB) directs the search until the first verified feasible plan is found, after which constrained expected improvement (CEI) directs economic refinement, supplemented by bounded optimal-neighborhood and constraint-boundary ranking refinements. Gaussian-process surrogates decide only the evaluation order; the reported objective and all four engineering constraints—photovoltaic curtailment, loss-of-load energy, capacity credit, and flexibility scarcity—are verified exclusively by the original 8760 h simulator. In a paired 2 × 2 factorial experiment over 30 common initial designs on a 125-candidate pool, the phase switch raised exact-optimum recovery from 24/30 to 30/30 (exact McNemar p = 0.03125), and the full rule maintained 30/30 under two unseen profile seeds where CEI achieved 24/30 and 22/30. The full rule further recovered the exact optimum of a 1224-candidate pool in 30/30 runs within 20 evaluations and of a six-variable 729-point grid within 75 evaluations, using roughly 2–10% of the exhaustive simulation budget. Constraint-slack and guard-band reporting, candidate-domain audits, and repeated wall-clock measurements turn the recommendation into auditable planning decisions, with all evidence drawn from a reproducible synthetic benchmark. Full article

(This article belongs to the Section F1: Electrical Power System)

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32 pages, 19296 KB

Open AccessArticle

Expert Systems in Energy Transition as a Tool for Intelligent Support of Decarbonization and Sustainable Development

by Dariusz Sala, Alla Polyanska and Vladyslaw Psyuk

Energies 2026, 19(16), 3916; https://doi.org/10.3390/en19163916 - 20 Aug 2026

Viewed by 305

Abstract

The article explores the evolution of energy transition research through a bibliometric co-occurrence analysis of author keywords extracted from 146 scientific publications. The analysis reveals a shift from the technical aspects of energy systems and traditional decision-support approaches (2014–2018) towards climate change, decarbonization, [...] Read more.

The article explores the evolution of energy transition research through a bibliometric co-occurrence analysis of author keywords extracted from 146 scientific publications. The analysis reveals a shift from the technical aspects of energy systems and traditional decision-support approaches (2014–2018) towards climate change, decarbonization, renewable energy, investments, and energy policy (2018–2021). Recent studies (2022–2024) increasingly emphasize renewable energy, sustainable development, and intelligent decision-support systems, reflecting the growing digitalization of energy systems and the transition towards intelligent energy management. Based on these findings, the study develops a Digital-Twin-Oriented Techno-Economic Decision-Support Framework (DTOTEDSF) for optimizing and managing carbon-reduction strategies under dynamic energy transition conditions. Rather than representing a fully implemented digital twin (DT), the proposed framework constitutes the analytical foundation for its future development. It integrates techno-economic modeling, optimization, scenario analysis, and sensitivity assessment into a unified decision-support methodology. To demonstrate its practical applicability, the framework was applied to four industrial CCS case studies in the cement sector using publicly available technical and economic data. Its analytical core combines technical, economic, and optimization models to evaluate CCS performance under alternative operating conditions. Consequently, the proposed framework provides a methodological basis for the future implementation of fully operational DTs and contributes to the development of intelligent decision-support tools for industrial decarbonization and the sustainable energy transition. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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18 pages, 2482 KB

Open AccessArticle

Optimal Scheduling of a Photovoltaic–Storage–Charging System Considering Charging Services, Ancillary Service Markets, and Spot Markets

by Zhichao Lin, Busheng Luo, Zhenkun Qiu, Xiangyang Su, Yuting Huang and Xuebo Qiao

Energies 2026, 19(16), 3915; https://doi.org/10.3390/en19163915 - 20 Aug 2026

Viewed by 322

Abstract

Current research on photovoltaic–storage–charging (PSC) systems operating in market-oriented environments mainly focuses on individual service types, such as charging services or ancillary services, without fully considering the interactions among multiple market mechanisms. In particular, the competition and coordination of shared flexible resources across [...] Read more.

Current research on photovoltaic–storage–charging (PSC) systems operating in market-oriented environments mainly focuses on individual service types, such as charging services or ancillary services, without fully considering the interactions among multiple market mechanisms. In particular, the competition and coordination of shared flexible resources across different markets are seldom explicitly modelled, while the economic opportunities associated with spot market participation are often overlooked. These limitations may lead to an incomplete assessment of the operational flexibility and economic value of PSC systems. To overcome these shortcomings, this paper develops a coordinated scheduling approach for PSC systems participating in multiple markets under market-rule constraints. A unified modelling framework is established to describe the allocation of shared resources among charging services, ancillary service provision, and spot market trading activities. Based on this framework, the scheduling problem is formulated with the objective of maximizing the total economic return of the system. Using charging services and peak-shaving services as representative applications, the proposed method determines both the optimal deployment of flexible regulation resources and the corresponding electricity trading decisions. Numerical results under the representative case study demonstrate that the coordinated utilisation of resources across multiple markets can improve the economic performance of the PSC system compared with single-market participation. The findings further demonstrate the effectiveness of the proposed framework in unlocking and quantifying the flexibility value of PSC systems. Full article

(This article belongs to the Special Issue Application of Swarm Intelligence for Multi-Energy Virtual Power Plants—2nd Edition)

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37 pages, 1365 KB

Open AccessArticle

Toward Secure and Privacy-Preserving Distributed Scheduling in Data-Center-Integrated Microgrids via Blockchain

by Yuan Liu, Guilan Dai, Lili Yao, Kai Yang and Peng Wang

Energies 2026, 19(16), 3914; https://doi.org/10.3390/en19163914 - 20 Aug 2026

Viewed by 249

Abstract

As data centers become major and schedulable loads of the new power system, connecting them to multiple microgrids offers a promising route to absorb local renewable energy through cross-domain coordination. However, when the microgrids belong to competing operators, coordinated scheduling forces each party [...] Read more.

As data centers become major and schedulable loads of the new power system, connecting them to multiple microgrids offers a promising route to absorb local renewable energy through cross-domain coordination. However, when the microgrids belong to competing operators, coordinated scheduling forces each party to disclose its data-center load curve, storage state, and pricing strategy, which constitutes a core operational secret that no microgrid is willing to reveal. This paper develops a secure and privacy-preserving distributed scheduling scheme for data-center-integrated microgrids built on blockchain. A “data-stays-local, energy-crosses-centers” model is established that elevates privacy from an add-on feature to a first-order architectural constraint, defining a “three-no” principle and a two-layer architecture in which each microgrid optimizes its interior in plaintext and exposes only encrypted matchable factors. On this basis, a decentralized ciphertext scheduling-negotiation algorithm is designed on blockchain smart contracts, performing cross-microgrid matching under secure multi-party computation entirely in the encrypted domain, committing auditable encrypted digests on-chain, and dynamically allocating scheduling priority through an on-chain reputation mechanism. Case studies on a cluster of interconnected microgrids show that the proposed scheme attains cost and renewable accommodation within about three-tenths of a percent of the centralized optimum while reducing operational data-leakage risk from 96.7 percent to 3.8 percent, at the manageable expense of a few seconds of negotiation latency. Benchmarking against an exact mixed-integer solver on small-scale systems bounds the mean optimality gap of the decomposed scheme at 0.74 percent, with a worst case of 2.54 percent over sixty instances. Full article

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20 pages, 7918 KB

Open AccessArticle

An Innovative Method for Modeling Inertia in Wind Turbine Emulators: Concept, Implementation, and Laboratory Testing

by Robert Rink and Robert Małkowski

Energies 2026, 19(16), 3913; https://doi.org/10.3390/en19163913 - 20 Aug 2026

Viewed by 280

Abstract

This monograph synthesizes the current state of knowledge on mathematical models and wind turbine (WT) modeling methods, in particular in the field of implementation of wind turbine emulators (WTE). The areas covered include the methods used to create a physical and simulation model [...] Read more.

This monograph synthesizes the current state of knowledge on mathematical models and wind turbine (WT) modeling methods, in particular in the field of implementation of wind turbine emulators (WTE). The areas covered include the methods used to create a physical and simulation model of a WT and its individual components, as well as an analysis of published results of research conducted using WTEs. The analysis of wind turbine generator inertia modeling and its impact on accurate simulation of WT operation in dynamic states is given special attention in this publication. This publication provides in-depth analysis of the dynamic properties of WTEs. The analysis identifies the shortcomings and limitations of existing models. As a result of the research, an original and effective method was proposed for creating an emulator of a real WT with a doubly fed induction machine. Achieving significantly better simulation accuracy in dynamic states than in models found in scientific publications. The tests results presented in the paper proved that the dynamic properties of the emulator developed by the authors allow its use in research and development work in a laboratory on a real turbine. The proposed solution was used to develop a scalable emulator of a real WT utilizing the physical properties of a doubly fed machine which is an element of the emulator. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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18 pages, 2066 KB

Open AccessArticle

Thermodynamic Sustainability Analysis of Sweet Sorghum Production with Renewable Energy Integration

by Müjdat Öztürk and Arman Ameen

Energies 2026, 19(16), 3912; https://doi.org/10.3390/en19163912 - 20 Aug 2026

Viewed by 267

Abstract

In response to rising global energy demand and sustainability targets, assessing the energy-related efficiency of agricultural products has become a critical issue. Sweet sorghum is widely recognized as a promising energy crop for sustainable biofuel production, thanks to its low water requirements and [...] Read more.

In response to rising global energy demand and sustainability targets, assessing the energy-related efficiency of agricultural products has become a critical issue. Sweet sorghum is widely recognized as a promising energy crop for sustainable biofuel production, thanks to its low water requirements and high biomass productivity. To the best of the authors’ knowledge, this study provides the first comprehensive cumulative exergy-based evaluation of sweet sorghum production by simultaneously assessing its energy, exergy, and environmental performance using five key indicators: Cumulative Energy Consumption (CEnC, 718.48 MJ/ton), Cumulative Exergy Consumption (CExC, 2031.42 MJ/ton), Cumulative CO₂ Emission (CCO₂E, 124.01 kg CO₂/ton), Cumulative Degree of Perfection (CDP, 2.8) and Renewability Index (RI, 0.64), based on field level data for the production of one ton of sweet sorghum. Input-based analysis revealed that electricity consumption accounted for the largest share of both energy and exergy use, amounting to 334.85 MJ/ton and 1396.32 MJ/ton, respectively. At the same time, irrigation water was identified as a major contributor to carbon emissions. The integration of renewable electricity sources substantially improved system performance, increasing the CDP to 6.32 and the RI to 0.84, corresponding to more than a twofold increase in exergy efficiency and a shift toward a predominantly renewable production system. Overall, the findings highlight the strong potential of sweet sorghum as a sustainable biofuel feedstock and underline the importance of integrated policy and management approaches that simultaneously address energy quality, exergy losses, and carbon emissions in agricultural energy systems. Full article

(This article belongs to the Special Issue Renewable Energy Integration into Agricultural and Food Engineering)

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