Integrated Power System Research Articles

Management of Hybrid Hydropower and Floating Solar Systems at Num Ngum 1 in Lao PDR

The integration of a hybrid hydro-floating solar power (HPP-FPV) system is covered in this study with the goal of improving energy management and producing more electricity. The production capacity of the hybrid system is almost twice as high as that of the original HPP system, demonstrating its potential for higher energy generation. Because it forecasts weather and modifies electricity generation accordingly. The analysis highlights how crucial it is to make sure that the hybrid system's electricity generation doesn’t go beyond the current power grid's maximum transmission capacity. This is essential to preserving the consistency and caliber of the power that is provided. The research's overall goal of increasing the output of renewable energy through creative system integration and practical management techniques is captured in the abstract.

Moisture dynamics during high‐load fluctuations in transformers: Localised accumulation and interfacial transfer within oil/pressboard insulation

AbstractPower systems grapple with the challenges of high load rates and intermittent new energy sources integration. Transformers, as vital equipment, employ oil/pressboard (oil/PB) insulation. Uneven moisture distribution in this insulation can jeopardise safety thresholds, necessitating precise moisture assessment for grid stability. A novel mathematical model, adsorption–desorption and porous media moisture transfer (ADP‐MoT), is presented. This model incorporates adsorption and desorption processes within the porous pressboard, enabling a description of the dynamic moisture transfer between the oil and pressboard. Using this mathematical model, simulations for moisture dynamics were performed on a 750‐kV transformer across four typical days. The results indicate that temperature fluctuations are the primary driving factor for moisture migration at the oil/PB interface. Convection and diffusion contribute to moisture movement towards cooler regions. Fluid properties and structural characteristics induce a distinctive streamline‐shaped moisture flow within horizontal oil channels, with localised moisture accumulation in specific areas. Moreover, the analysis of 96 transient results uncovers potential free‐state moisture formation during severe conditions, underscoring the importance of monitoring the pressboard at winding bases during high load fluctuations. In conclusion, this study significantly contributes to scientifically identifying and addressing risks tied to new energy sources integration in power systems.

Dynamic control of grid-following inverters using DC bus controller and power-sharing participating factors for improved stability

Integrating Grid-Following Inverters (GFLs) into power systems presents significant stability challenges, particularly in systems with reduced strength and high renewable energy penetration. This study delves into the dynamic interactions between parallel synchronous generators (SGs) and GFLs, highlighting the impact of reduced system inertia and transient stability margins. A novel DC bus controller is proposed to enhance the inertia and stability of GFLs during grid disturbances by dynamically adjusting power references based on load demand. Through mathematical modelling, small signal analysis, and MATLAB simulations, the study evaluates the effects of inverter-based resources (IBRs) on power system stability. The proposed GFL configuration demonstrates improved stability control, achieving an 80 % increase in stability under weak grid conditions. This paper provides insights into optimized control strategies, emphasizing the importance of power-sharing participation factors (PSPF) for effective GFL integration in modern power systems with high renewable energy penetration.

Modeling Nuclear-Centric Scenarios for Ukraine’s Low-Carbon Energy Transition Using Diffusion and Regression Techniques

This study presents a mathematical model for forecasting the development of Ukraine’s Integrated Power System (IPS) until 2040, with a specific focus on the expansion of nuclear energy as a cornerstone of the nation’s low-carbon transition. The model is an extension of Frank Bass’s mixed influence diffusion model, incorporating both economic and technological factors. These factors are treated as stochastic variables essential for accurately predicting the evolution of an integrated energy system, particularly in the context of rapid renewable energy sources (RES) growth. The model employs regression techniques using generalized logistic curves, improving forecasting efficiency by aligning modeling parameters with experimental data. The study’s results indicate the potential for optimizing IPS components, including nuclear and thermal power generation, through the model’s application. The model is distinguished by its inclusion of economic and technological impacts, such as state matrices, control actions, and external influence matrices, which enhance the accuracy of simulations and predictions. The validation of the model, based on scenarios of electricity consumption and generation, shows significant alignment with observed trends, confirming the model’s reliability. The findings suggest that this model is an effective tool for developing and refining energy system scenarios, with nuclear energy playing a pivotal role in Ukraine’s sustainable energy future.

Synergistic Control of Active Filter and Grid Forming Inverter for Power Quality Improvement

This paper addresses the challenges and opportunities associated with integrating grid-forming inverters (GFMs) into modern power systems, particularly in the presence of nonlinear loads. Nonlinear loads introduce significant harmonic distortions in the source voltage and current, leading to reduced power factor, increased losses, and an overall reduction in system performance. To mitigate these adverse effects, active filters are employed. The objective of this study is to investigate a synergistic approach to modeling and control in integrated power systems with GFMs, focusing on enhancing power quality and grid stability by reducing harmonic distortions through the use of voltage-source active filters. This research contributes to sustainability by supporting the reliable and efficient integration of renewable energy sources, thereby reducing dependency on fossil fuels and minimizing greenhouse gas emissions. Additionally, improving power quality and system efficiency helps reduce energy waste, which is crucial for achieving sustainable energy goals. Simulations are conducted on a 1000 kW GFM connected to a grid with a nonlinear variable load, demonstrating the system’s effectiveness in adapting to dynamic conditions, reducing harmonics, and promoting a stable, resilient, and sustainable power grid.

Probabilistic Tide Calculation for Multi-Wind Farm Distribution Network Based on CATTSTS Model

Traditional probabilistic tide calculation methods often fall short in capturing the dynamic nature of these systems, leading to discrepancies between calculated and actual data. To address this, a dynamic probabilistic tide calculation model is proposed in this study, incorporating a wind farm probabilistic model enhanced by the CATTSTS model. This integration aims to optimize prediction accuracy by improving feature focusing and data fitting, thereby reducing prediction errors and providing more reliable data for power system adjustments and optimizations. Experimental results demonstrate that the model's predictions for wind speed series in multi-wind farm distribution networks closely match actual conditions, underscoring its practical applicability and reliability in real-world settings. Furthermore, the study highlights the impact of spatial and temporal correlations on model performance. This research contributes to advancing the management of renewable energy integration in power systems, offering insights for more informed decision-making and operational efficiency.

Power Quality Disturbance Monitoring in PV Integrated Power System with Mode Decomposition and Ensemble Extreme Learning Machine

Power quality disturbance (PQD) monitoring has become an important issue in modern power system due to integration of several renewable energy sources such as photovoltaic (PV), wind energy system (WES), Fuel cells etc. This research presents a mode decomposed based ensemble extreme learning machine (EELM) to recognise and classify the PQD events with higher accuracy in terms of rapid learning speed and smaller computational burden in a complete PV based power system, The PQD signals are decomposed using a variational mode decomposition (VMD) to obtain effective band limited intrinsic mode functions (BIIMF) which leads to compute robust features and improves classification accuracy. For Power Quality Disturbances detection and classification, an ensemble extreme learning machine is suggested since an ensemble outperforms any single contributing model in terms of performance and prediction. The proposed VMD-EELM approach is validated in a modified IEEE 13 Bus system integrating PV with eleven types of PQDs. The proposed research having 100% classification accuracy for no noise and 99.88%, 99.94% 99.94% for 20dB, 30dB and 40dB noises respectively. It is being demonstrated that the suggested method can reliably identify and track PQD occurrences both with and without noise.

Aperiodic Coordination Scheduling of Multiple PPLs in Shipboard Integrated Power Systems

Aperiodic Coordination Scheduling of Multiple PPLs in Shipboard Integrated Power Systems

Application of cascaded neural network for prediction of voltage stability margin in a solar and wind integrated power system

Voltage stability is a paramount concern in the management of renewable-rich power systems. As the diffusion of renewable energy sources continues to increase, accurately estimating voltage stability margins becomes essential. This paper addresses the critical need for effective voltage stability margin estimation and presents a novel approach to predict the same on the solar and wind integrated power system. A new machine learning methodology is developed based on the cascaded neural network (CNN). The proposed CNN methodology effectively estimates the loadability margin in a renewable-rich power system under normal operating conditions, varied loading directions, and various contingency situations. The results of CNN are compared with different machine learning techniques and tested in the IEEE 30 bus system and IEEE 118 bus system under various operational circumstances. The results illustrate the efficiency of the suggested method for online assessment of a power system's Voltage Stability Margin. The proposed approach gives real-time insights into voltage stability margins by leveraging the power of data and powerful algorithms, allowing grid operators to proactively manage and optimize renewable energy integration while ensuring grid dependability and stability.

First-Principles Investigation on Ru-Doped Janus WSSe Monolayer for Adsorption of Dissolved Gases in Transformer Oil: A Novel Sensing Candidate Exploration.

Using first-principles theory, this work purposes Ru-doped Janus WSSe (Ru-WSSe) monolayer as a potential gas sensor for detection of three typical gas species (CO, C2H2, and C2H4), in order to evaluate the operation status of the oil-immersed transformers. The Ru-doping behavior on the WSSe surface is analyzed, giving rise to the preferred doping site by the replacement of a Se atom with the formation energy of 0.01 eV. The gas adsorption of three gas species onto the Ru-WSSe monolayer is conducted, and chemisorption is identified for all three gas systems with the adsorption energy following the order: CO (-2.22 eV) > C2H2 (-2.01 eV) > C2H4 (-1.70 eV). Also, the modulated electronic properties and the frontier molecular orbital are investigated to uncover the sensing mechanism of Ru-WSSe monolayer upon three typical gases. Results reveal that the sensing responses of the Ru-WSSe monolayer, based on the variation of energy gap, to CO, C2H2, and C2H4 molecules are calculated to be 1.67 × 106, 2.10 × 105, and 9.61 × 103, respectively. Finally, the impact of the existence of O2 molecule for gas adsorption and sensing is also analyzed to uncover the potential of Ru-WSSe monolayer for practical application in the air atmosphere. The obtained high electrical responses manifest strong potential as a resistive sensor for detection of three gases. The findings hold practical implications for the development of novel gas sensing materials based on Janus WSSe monolayer. We anticipate that our results will inspire further research in this domain, particularly for applications in electrical engineering where the reliable detection of fault gases is paramount for maintaining the integrity and safety of power systems.

Optimizing Microgrid Planning for Renewable Integration in Power Systems: A Comprehensive Review

Optimizing Microgrid Planning for Renewable Integration in Power Systems: A Comprehensive Review

Leveraging the Performance of Integrated Power Systems with Wind Uncertainty Using Fractional Computing-Based Hybrid Method

Leveraging the Performance of Integrated Power Systems with Wind Uncertainty Using Fractional Computing-Based Hybrid Method

Performance and optimization evaluation for integration of sCO2 power system into the aircraft propulsion system

The aviation industry accounts for part of the CO2 emissions contributing to climate change. The industry has established a target to reduce 2050 net aviation carbon emissions by 50 % relative to 2005 levels. With this in mind, waste heat recovery is a key pathway to achieve reduced emissions and improve system efficiency. The waste heat may potentially be converted to electric power using a supercritical CO2 Brayton power cycle. The sCO2 power system offers the advantage of compactness owing to the high working fluid density, which is an important consideration for aircraft performance. The present work focuses on the integration of the sCO2 power system into the aircraft propulsion system and evaluation of its performance. Detailed optimization of the sCO2 waste heat system will be evaluated with a focus on cycle efficiency and net power under different operating conditions, including ground, takeoff, climb, cruise, and landing operations. The study is divided into two parts with two different turbofan engines, one with a nominal thrust of 30 kN and the other with a nominal thrust of 9 kN. The first part shows the effect and operation of the waste heat recovery unit under the different operating conditions. The second part is focused on cycle optimization and performance evaluation. The results demonstrate the potential of waste heat recovery during a range of operational conditions. The sCO2 cycle efficiency can reach between 25 and 39 % (depending on aircraft engine) with net power output in the range of 100 to 260 kW.

Optimal allocation of wind-based distributed generators and STATCOMs using a hierarchical stochastic programming approach

Allocating static synchronous compensators (STATCOMs) to regulate given allotted wind-based distributed generators (W-DGs) during planning stages can provide high investment returns by maximizing the installed W-DGs. Amidst rising global warming concerns, commitments to adopt renewable energy gain international momentum to curb greenhouse emissions and meet environmental targets, reducing reliance on fossil-based resources. Renewable energy's intermittency complicates distribution planning, stressing voltage devices and increasing network losses. This paper presents a new hierarchical stochastic planning model that addresses uncertainties related to W-DGs and generic loads. The model optimizes allocation with voltage constraints and reactive power while incorporating a two-stage mixed-integer nonlinear program (MINLP), maximizing net profit, and adding an economic dimension to promote renewable energy investments. Improved wind power modeling with historical data and collective evaluation metrics for selecting the best-fitted probability distribution function (PDF) enhances the accuracy of wind power integration assessment. The hierarchical approach considers relaxed voltage constraints in Stage I to allow maximum allotment of W-DGs while introducing STATCOMs and DGs' reactive power in Stage II to address voltage violations. Verification on the Canadian 41-bus network demonstrates the advantage of the hierarchical approach in allocating more W-DGs and achieving higher profits than the simultaneous planning approach. These advances significantly enhance renewable energy integration in power systems.

Economic analysis of hydrogen energy systems: A global perspective

In the realm of renewable energy, the integration of wind power and hydrogen energy systems represents a promising avenue towards environmental sustainability. However, the development of cost-effective hydrogen energy storage solutions is crucial to fully realize the potential of hydrogen as a renewable energy source. By combining wind power generation with hydrogen storage, a comprehensive hydrogen energy system can be established. This study aims to devise a physiologically inspired optimization approach for designing a standalone wind power producer that incorporates a hydrogen energy system on a global scale. The optimization process considers both total cost and capacity loss to determine the optimal configuration for the system. The optimal setup for an off-grid solution involves the utilization of eight distinct types of compact horizontal-axis wind turbines. Additionally, a sensitivity analysis is conducted by varying component capital costs to assess their impact on overall cost and load loss. Simulation results indicate that at a 15 % loss, the cost of energy (COE) is $1.3772, while at 0 % loss, it stands at $1.6908. Capital expenses associated with wind turbines and hydrogen storage systems significantly contribute to the overall cost. Consequently, the wind turbine-hydrogen storage system emerges as the most cost-effective and reliable option due to its low cost of energy.

Deep Entropy-Learning based virtual inertia control for VRFB regulation considering Phase-Locked loop dynamics

The virtual inertia control (VIC) technique is often adopted as a prominent mechanism to address the inertia deficiency of modern integrated power systems with high penetration of sustainable energy units. In such control mechanisms, a phase-locked loop (PLL) is required to estimate the grid frequency. However, utilization of such frequency measurement platforms is accompanied by large frequency fluctuations due to its inherent dynamics. In particular, this paper proposes an adaptive integral recursive backstepping (I-RBSC) based on virtual inertia for the regulation of vanadium redox flow battery (VRFB) in stand-alone Micro-Grids (SMGs). Unlike previous works that neglected the effect of frequency measurement devices, this work investigates the effect of PLL dynamics in virtual inertia control. The I-RBSC controller is designed by an entropy-driven actor-critic neural networks (NNs) to adaptively adjust the tunable coefficients during its interaction with the SMG. By training the ability of deep NNs, the entropy is maximized to regulate the system output. The VRFB unit can be discharged up to 90% which can quickly respond to the randomness of loads and sustainable energy units. The transient outcomes of SMG reveal the feasibility of I-RBSC (designed by entropy learning) to address the challenges of low inertia and PLL dynamics. The real-data of wind turbine and solar radiation are utilized to simulate the SMG in a more realistic framework from a systematic point of view. The comprehensive analysis under typical scenarios confirms the supremacy of the suggested VIC controller over prevalent state-of-the-art virtual inertia controllers including conventional VIC, fuzzy logic, backstepping, and model-predictive control (MPC).

Development of low-carbon technologies in China's integrated hydrogen supply and power system

Hydrogen and electricity are crucial and interdependent energy carriers in China's pursuit of carbon neutrality, suggesting the necessity of utilizing cost-effective low-carbon technologies that facilitate their integrated development. The cost-optimal, provincial level, deployment of low-carbon technologies under this long-term goal remains to be determined. This study employs the REPO model to identify the cost-optimal, low-carbon hydrogen production mixes and the evolution of the integrated power system of China from 2020 to 2050. The integrated planning and operation of hydrogen supply and power systems are explored at the provincial level. The role of high-temperature gas-cooled reactors in this integrated energy system is also analyzed. The results reveal that electrolytic hydrogen would dominate China's hydrogen supply after 2040, with alkaline, proton exchange membrane, and solid oxide electrolyzers produce over 1 Mt of hydrogen in the short term, by 2035, and in 2050. Leveraging the low-carbon heat production of high-temperature gas-cooled reactors in addition to its electricity generation to meet the thermal requirements of solid oxide electrolyzers could boost the output to 4.2 Mt in 2050 and reducing the total system CO2 emissions and costs by 2.28% and 0.05%, respectively. By 2050, the integration of hydrogen supply and power systems also generates up to 2194 TW h of flexible electricity demand by electrolyzers, which raised the renewable energy penetration by 4 percentage points while decreasing the need of flexible natural gas power generations and energy storages. This study is valuable for proposing the analytical framework and performing the provincial-level study of decarbonization of China's integrated hydrogen supply and power system.

Coordinated energy storage and network expansion planning considering the trustworthiness of demand-side response

The enhancement of economic sustainability and the reduction of greenhouse gas (GHG) emissions are becoming more relevant in power system planning. Thus, renewable energy sources (RESs) have been widely used as clean energy for their lower generation costs and environmentally friendly characteristics. However, the strong random uncertainties from both the demand and generation sides make planning an economic, reliable, and ecological power system more complicated. Thus, this paper considers a variety of resources and technologies and presents a coordinated planning model including energy storage systems (ESSs) and grid network expansion, considering the trustworthiness of demand-side response (DR). First, the size of a single ESS was considered as its size has a close effect on maintenance costs and ultimately affects the total operating cost of the system. Second, it evaluates the influence of the trustworthiness of DR. Third, multiple resources and technologies were included in this high-penetration renewable energy integrated power system, such as ESSs, networks, DR technology, and GHG reduction technology. Finally, this model optimizes the decision variables such as the single size and location of ESSs and the operation parameters such as thermal generation costs, loss load costs, renewable energy curtailment costs, and GHG emission costs. Since the problem scale is very large not only due to the presence of various devices but also both binary and continuous variables considered simultaneously, we reformulate this model by decomposition. Then, we transform it into a master problem (MP) and a dual sub-problem (SP). Finally, the proposed method is applied to a modified IEEE 24-bus test system. The results show computational effectiveness and provide a helpful method in planning low-carbon electricity power systems.

Optimal transient power sharing method for shipboard MVDC System based on segmented variable step dynamic programming

Supplying power for large pulsed power load with shipboard medium voltage direct current integrated power system has continued to be a challenge. The energy storage device configured in the system can effectively mitigate the power impact on grid and gas turbine gensets, but it also complicates the system operation, requiring advanced power sharing and control strategies for support. In this paper, the control framework of system configured with hybrid energy storage is presented, the objective function to quantify transient power disturbance on gas turbine genset is established, and the segmented variable step dynamic programming method for system transient power sharing is innovatively proposed and employed to derive the optimal transient power-sharing scheme for the rectangular and triangular large pulsed power load conditions. Compared with the conventional approach through MATLAB/Simulink simulation, the scheme derived from segmented variable step dynamic programming demonstrates enhanced utilization of the transient power compensation capability of hybrid energy storage, and leads to a reduction in the power regulation pressure on gas turbine gensets. In the assumption of two typical operating processes, as the results of the power impacts，the transient regulation rate of the genset rotor is reduced from 10.4 % to 9.9 % and from 13.7 % to 8.6 %, respectively, the fatigue damage of shaft system is decreased by 53 % and 94.4 %, respectively, and the maximum inlet relative temperature of gas generator turbine is reduced by 0.015 and 0.139, respectively.

Effects of adverse sea conditions on the dynamic performance of a cruise ship integrated power system

In adverse sea conditions, changes in the propeller emergence depth can cause propulsion load fluctuations, resulting in significant variations in ship-integrated power systems (IPS). These fluctuations can severely affect the power quality of ships and the operational efficiency of electrical devices. To develop appropriate mitigation measures against the impact of wind and waves on IPS, a comprehensive model that can simulate the response characteristics of the hull and IPS for different heading angles in different sea conditions is necessary. This paper presents an integrated multi-system dynamic model capable of simulating the response characteristics of a ship's hull and its IPS under the wind and waves interference. A novel method is proposed to estimate propeller thrust and torque loss directly from the ship's pitch and roll angles. Utilizing this dynamic model, the responses characteristics of the hull and IPS in varying sea conditions have been investigated. The findings demonstrate that the model accurately captures variations in ship motions, as well as IPS voltage and frequency, under wind and waves interference. Additionally, this study explores the application of a hybrid energy storage system (HESS) to enhance the IPS power quality in the context of Sea State (SS) 7. Results indicate that the HESS has good potential to compensate for propulsion load fluctuations, thereby mitigating the negative impacts on the ship's IPS.