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Variable renewable energy-based power is expected to increase toward a sustainable society, although the power cannot be dispatched effectively due to its intermittent nature. To accelerate renewable energy implementation, we simulated energy flows of paper mills installing wind energy and evaluated their potentials to function as energy hubs for appropriate early-stage design. We targeted 39 Japanese paper mills assumed to have thermal energy storage, wind–thermal energy converters and regional woody biomass installed, and analyzed the amount of power and heat selling and life cycle greenhouse gas emissions. The results for the paper mills were compared with conventional mills to examine effective conditions for greenhouse gas reduction. The amount of power or heat selling depended on the capacity of the paper mill and the installed equipment. Most paper mills could reduce greenhouse gas using thermal energy storage, wind energy, and woody biomass. The paper mill with the highest life cycle greenhouse gas reduction, compared with conventional mills, could achieve a 190% reduction. To function as a cogeneration energy hub, the equipment installed in paper mills should be designed according to the conditions of the paper mills and their regions. • Paper mills have potential as energy hubs by integrating variable renewable energy. • Thermal energy storage and wind–thermal energy converters were studied. • Energy flows and greenhouse gas emissions of paper mills were simulated. • Most mills could provide stable power and/or heat supplies and reduce emissions. [ABSTRACT FROM AUTHOR]

Wind and photovoltaic (PV) power forecasting are crucial for improving the operational efficiency of power systems and building smart power systems. However, the uncertainty and instability of factors affecting renewable power generation pose challenges to power system operations. To address this, this paper proposes a digital twin-based method for predicting wind and PV power. By utilizing digital twin technology, this approach provides a highly realistic simulation environment that enables accurate monitoring, optimal control, and decision support for power system operations. Furthermore, a digital twin platform for the AI (Artificial Intelligence) Grid is established, allowing real-time monitoring, and ensuring the safe, reliable, and stable operation of the grid. Additionally, a deep learning-based model WPNet is developed to predict wind and PV power at specific future time points. Four datasets are constructed based on weather conditions and historical wind and PV power data from the Flanders and Wallonia regions. The prediction models presented in this paper demonstrate excellent performance on these datasets, achieving mean square error (MSE) values of 0.001399, 0.001833, 0.000704, and 0.002708; mean absolute error (MAE) values of 0.025164, 0.027854, 0.018592, and 0.033501; and root mean square error (RMSE) values of 0.037409, 0.042808, 0.026541, and 0.052042, respectively. [ABSTRACT FROM AUTHOR]

Gassing problems and premature insulation failures in wind turbine transformers indicate reliability concerns about the insulation of such components. This fact necessitates investigating degradation of transformer insulation systems under high-dV/dt pulse voltages that exist in today's wind energy plants. For this purpose, PD activity, generally assumed to be the main long-term cause of insulation deterioration, needs to be analyzed. This work evaluates the effects of impulse voltage parameters such as rate of rise and repetition frequency on inception voltage and intensity of PD activities. PD parameter measurement under high-dV/dt voltages is challenging due to interferences from fast oscillations, and difficulties of PD energy measurements. To avoid such issues, which are related to electromagnetic detection methods under pulse energization, this work uses a chemical approach to compare PD activities, based on the rate of hydrogen generation in a controlled test chamber with oil/paper samples. Gas monitoring of the oil containing impregnated paper samples reveals that a faster rate of rise increases PD energy as well as inception voltage. Results based on experiments conducted in small oil chambers show good correlation between the amount of hydrogen detected and PD energy level; hence it can be used as a benchmark for comparing PD energy levels under various impulse waveforms. [ABSTRACT FROM AUTHOR]

Chile has a very ambitious energy transition agenda and massive challenges ahead to accomplish it. To integrate the high solar energy potential in the north an the high wind power potential of the south of the country, considerable investments in the electrical grid and new balancing mechanism and storage capacities are necessary. This study addresses the potential of individual industries, particularly the paper industry, to provide flexibility to the electrical system on-site. To achieve this, an optimization model that minimizes energy provision costs is proposed. The model considers the demand of a company including its demand side management potential, combined heat and power generation capacities, as well as on-site renewable energy generation location potential from photovoltaics and wind power. The model is computed under multiple parametrization scenarios to estimate under which conditions it would be advantageous for the company to use renewable electricity. This allows to evaluate how much of the renewable electricity produced in high peaks can be used by the company, and in how far, demand side management and combined heat and power can compensate low generation periods of renewable electricity. The model is feeded with typical hourly electricity and heat demand profiles of a prototypic paper producing company, which were statistically derived from one and a half years of measurements. Moreover, electricity generation time series from photovoltaics and wind power are derived from physical models that rely on ERA5 reanalysis data. The latter data set allows to compute the model in locations all around Chilean territory in a 30 km x 30 km spatial grid. Results are presented in the form of maps of the shares of renewables that would be enabled at avery location by industries of the same characteristics. [ABSTRACT FROM AUTHOR]

In recent years, the global installed capacity of wind power has grown rapidly. Wind power forecasting, as a key technology in wind turbine systems, has received widespread attention and extensive research. However, existing studies typically focus on the power prediction of individual devices. In the context of multi-turbine scenarios, employing individual models for each device may introduce challenges, encompassing data dilution and a substantial number of model parameters in power generation forecasting tasks. In this paper, a single-model method suitable for multi- device wind power forecasting is proposed. Firstly, this method allocates multidimensional random vectors to each device. Then, it utilizes space embedding techniques to iteratively evolve the random vectors into representative vectors corresponding to each device. Finally, the temporal features are concatenated with the corresponding representative vectors and inputted into the model, enabling the single model to accomplish multi-device wind power forecasting task based on device discrimination. Experimental results demonstrate that our method not only solves the data dilution issue and significantly reduces the number of model parameters but also maintains better predictive performance. Future research could focus on using more interpretable space embedding techniques to observe representation vectors of wind turbine equipment and further explore their semantic features. [ABSTRACT FROM AUTHOR]

Power generation by variable renewable energy (VRE) is expected to expand for decarbonization, although it is difficult to ensure stabilization of the energy demand due to fluctuations in the power output from VRE. To accelerate VRE implementation, wind-powered thermal energy systems (WT th -ES), which can provide dispatchable power using wind–thermal energy converter (WEC th) and thermal energy storage (TES), have been proposed. In this study, we are tackling the installation of VRE, i.e., wind energy, by TES with WEC th compared with wind turbine (WT p) in paper mills to demonstrate the applicability of TES in an industrial sector. Conventional and alternative energy systems in paper mills with TES were mathematically modeled and simulated to analyze the transmittable power output and the greenhouse gas (GHG) emissions by life cycle assessment. With the installation of TES and wind energy, transmittable power could be increased with GHG emissions reduction. However, their excess installation or unbalanced combination resulted in an increase in GHG emissions and a decrease in transmittable power. By comparing the cases, the combination of paper mill, TES, and WEC th could convert thermal energy efficiently and mitigate fossil fuel consumption for multiple production of paper and power from the paper mill. • A wind-thermal energy converter (WEC th) and a wind turbine (WT p) were compared. • Energy flows and GHG emissions of paper mills with TES and wind were simulated. • Paper mills reduced GHG of power generation less than fossil fuel-fired power plants. • Excess TES reduces dispatchable power generation and increases GHG emissions. • Paper mills with WEC th s and TES have the potential to be regional energy suppliers. [ABSTRACT FROM AUTHOR]

‘Landscape’ is relatively underexplored in legal scholarship, notwithstanding its occasional centrality to legal analysis, and the ways in which law contributes to the shaping of landscape.Wind energy is an especially rich area for the exploration of landscape; not only do wind farms consistently raise concerns about landscape, but the existence of climate change complicates the response to local concern. Most of the legal literature on ‘knowledge’ focuses on the ways in which different ‘expert’ knowledges find their way into, and then shape, legal processes and decisions. This article is more concerned with the ways in which the planning system receives different knowledge claims, and validates some of them. The discussion turns around four tentative categories of knowledge claim: expert or technical knowledge claims; lay (or sometimes local) knowledge claims; prior institutional knowledge claims; and professional planning knowledge claims. Knowledge of the complex, dynamic and plural idea of landscape in any particular case is constructed in the process of decision making and reason giving through a careful layering of these different sorts of knowledge claim. [ABSTRACT FROM AUTHOR]

This article will explore the need for archiving the rapidly expanding global wind energy sector. This task has not yet been undertaken systematically and is urgent as many of the pioneering actors are no longer active. An important initial task involves mapping, appraisal and surveying. The development of the global wind energy sector has massively expanded in scale and geographical reach over the last 40 years. This period closely coincides with the global shift from paper to digital records. The global wind energy sector is set to be an important industrial part of the transition away from fossil fuels, essential in addressing climate change. This transition process will still take many years to develop, and is likely to be very difficult, with many advances and setbacks occurring at different times and in different places. To evaluate progress along the way, it will be essential to preserve, access and interpret the historical records of the sector. It will be vital that historical records exist in the future in order to understand this transition. This co-authored article will draw on initial discussions between the three authors about how to understand this challenge and possible interventions. The article will draw on the co-authors' combined experience in both the archival and records management sectors, the global wind energy sector specifically, the global energy sector more generally, and the archiving of the uses of wind energy for milling and pumping, with some material on wind-generated electricity. [ABSTRACT FROM AUTHOR]

This paper presents a detailed model of low-frequency oscillations and their damping within the Electric Power System (EPS) of Bosnia and Herzegovina (B&H). The system is modeled using MATLAB software, analysing the steady state and dynamic responses. This research highlights the challenges and impacts of integrating renewable energy sources, such as wind farms, on grid stability and oscillation damping. The paper utilizes eigenvalue analysis to investigate the dynamic characteristics of the system, emphasizing the need for efficient damping strategies to maintain system stability. The methodology includes a comprehensive review of existing literature, the creation of a detailed EPS model of B&H, and the application of eigenvalue and oscillation amplitude analysis to determine damping ratios. The dynamic responses of hydro power plants, HPP Mostar and HPP Jablanica, to transient disturbances are analysed to validate the model and refine damping strategies. The results indicate that the B&H EPS is well-damped, with all eigenvalues possessing negative real parts, and demonstrate the system's resilience to small disturbances. The results are compared with the technical report on the integration of the wind power plant WPP Podveležje. This comparative analysis shows consistent patterns between the modeled calculations and empirical data, confirming the robustness of the EPS model. This alignment underscores the effectiveness of current damping mechanisms and provides a foundational strategy for enhancing system stability with increasing renewable energy penetration. The findings highlight the importance of developing advanced control strategies to sustain system stability as the integration of variable renewable energy sources continues to grow. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal power flow model that takes into account the uncertainty in the probability distribution of wind power. The model can schedule controllable generators under any possible distribution of wind power to ensure the safe and economic operation of the system. Firstly, considering the incompleteness of historical wind power data, the paper models the uncertainty of wind power using second-order moments of probability distribution and their fluctuation intervals. Subsequently, a robust optimal power flow model based on probability distribution model and joint chance constraints is established. The Lagrangian duality theorem is then employed to eliminate random variables from the optimization model, transforming the uncertainty model into a deterministic linear matrix inequality problem. Finally, a convex optimization algorithm is used to solve the deterministic problem, and the results are compared with traditional chance-constrained optimal power flow model. The feasibility and effectiveness of the proposed method are validated through case study simulations. [ABSTRACT FROM AUTHOR]

When employing stepwise inertial control (SIC), wind power generation can offer significant frequency support to the power system, concurrently mitigating energy shortages and suppressing secondary frequency drop. Nonetheless, further investigation is imperative for implementing stepped inertia control due to variations in frequency regulation capabilities and operational safety among diverse wind farm groups. Consequently, this paper advocates a multi-wind farm ladder timing SIC method designed to alleviate secondary drops in system frequency. Initially, the paper introduces the fundamental principles of stepped inertia control for a doubly-fed induction generator (DFIG) and deduces the relationship between support energy, wind power deficit at the exit, and SIC’s inertia power and support duration. Subsequently, the wind farm group is categorized into three groups using the classic wind speed zoning method, and the additional power reference for SIC is computed based on rotor safety requirements. A ladder time for the wind farm groups is introduced to address the potential exacerbation of secondary frequency drop issues resulting from the simultaneous activation of stepwise inertia control across all wind farms. The relationship between the initial kinetic energy loss of the wind farm group, the power deficit upon the exit of stepwise inertia control, and the ladder time is deduced. The NSGA-II multi-objective optimization algorithm is then employed to adjust the ladder time among multiple wind farm groups in the system. Finally, a modified IEEE-9 test system comprising three wind fields is constructed in MATLAB/Simulink to validate the proposed method. The results demonstrate the efficacy of the ladder time SIC coordinated strategy in providing robust frequency support, suppressing secondary frequency drops, streamlining control tasks, and enhancing the safety of wind power frequency regulation. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) calculation methods are important for the power system operation and mainly focus on the deterministic power flow calculation, neglecting the impact of demand response on online security calculation of power systems with renewable energy sources. Therefore, this paper proposes an OPF calculation method that considers the uncertainties of wind power, photovoltaic (PV) power generation and demand-side response. Firstly, the research focuses on the renewable energy grid, considering the uncertainties of wind power and PV power generation, and establishes uncertainty models for wind power and PV output. Secondly, based on cloud model theory, an uncertainty model for demand response is established. According to the established models, an efficient OPF model is constructed with a linearized submodels considering multiple uncertainties. By testing on the IEEE 30-bus system as a typical example, we found the effectiveness and superiority of the proposed OPF calculation method can benefit the power system economic operation and demand side resource utilization. [ABSTRACT FROM AUTHOR]

Changes in weather conditions directly impact the output of wind power, photovoltaic systems, and other forms of uncontrollable power generation. During extreme weather events, the output from wind and photovoltaic sources is typically reduced. In light of this, this paper proposes a two-stage operational strategy for energy storage, under scenarios of extreme-heat-with-low-wind-speed, in power systems. Firstly, historical data on wind and solar power, along with weather characteristics, are collected to analyze the power output during multi-day periods of extreme heat and low wind speed. Then, Monte Carlo simulations are employed to generate multi-day load curves with inherent uncertainties, based on regional load characteristics of the power system. Finally, a two-stage operation strategy for energy storage charging and discharging is established. In the first stage, normal operations are conducted to identify periods of power shortage across various types of loads. In the second stage, based on the identified moments of power shortage from the first stage, charging and discharging constraints are applied to the energy storage systems. The feasibility and effectiveness of this two-stage operational strategy are then validated through simulations, using historical data to generate scenarios of multi-day extreme-heat-and-low-wind-speed conditions. [ABSTRACT FROM AUTHOR]

Renewable energy is becoming more attractive as traditional fossil fuels are rapidly depleted and expensive, and their use would release pollutants. Power systems that use both wind and solar energy are more reliable and efficient than those that utilize only one energy. Hybrid renewable energy systems (HRES) are viable for remote areas operating in standalone mode. This paper aims to present the state-of-the-art research on off-grid solar-wind hybrid energy systems over the last two decades. More than 1500 published articles extracted from the Web of Science are analyzed by bibliometric methods and processed by CiteSpace to present the results with figures and tables. Productive countries and highly cited authors are identified, and hot topics with hotspot articles are shown in landscape and timeline views. Emerging trends and new developments related to techno-economic analysis and microgrids, as well as the application of HOMER software, are predicted based on the analysis of citation bursts. Furthermore, the opportunities of hybrid energy systems for sustainable development are discussed, and challenges and possible solutions are proposed. The study of this paper provides researchers with a comprehensive understanding and intuitive representation of standalone solar-wind hybrid energy systems. [ABSTRACT FROM AUTHOR]

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The reliability of wind turbine power converters is crucial for analyzing wind energy project costs, and for estimating maintenance and downtime. The published literature in this field relies on evaluating the reliability effect of wind speed to estimate the converter lifetime. However, this paper demonstrates that wind turbulence intensity, which has not been widely considered in similar reliability analyses, shows a significant impact on converter lifetime. This paper uses 821 10‐min wind speed time series sampled at 1 Hz on the two most commonly deployed wind turbine converter topologies: the two‐level voltage source and the three‐level neutral point clamped. Electromechanical and thermal modelling, combined with statistical analysis shows that mean wind speed and turbulence intensity both impact the lifetime of both converter topologies. However, the paper estimates that the three‐level converter can operate 2.4 to 4.0 times longer than the two‐level converter depending on the operating wind speed and turbulence intensity. [ABSTRACT FROM AUTHOR]

10.3390/en13143519 15 Yang R., Yuan Y., Ying R., Shen B., Long T. A novel energy management strategy for a ship's hybrid solar energy generation system using a particle swarm optimization algorithm. Unfortunately, the paper does not take into account the fragility of the European Energy System with respect to the Energy suppliers. Moreover, the Energy Plant is strongly constrained by the primary energy providers and the energy distribution system must provide the difficult tasks related to implement dispatching and energy saving systems. 10.3390/en13040894 10 Nikolaou T., Stavrakakis G.S., Tsamoudalis K. Modeling and optimal dimensioning of a pumped hydro energy storage system for the exploitation of the rejected wind energy in the non-interconnected electrical power system of the Crete island, Greece. [Extracted from the article]

The accumulation of wind power prediction deviations will make it difficult to maintain the long-term stable operation of energy storage. To solve this problem, this paper proposes a hybrid energy storage system configuration method containing second-use batteries. This paper establishes a three-battery hybrid energy storage operation strategy that considers the accumulation of prediction deviation and prevents the accumulation of prediction deviation by changing the energy storage used at the end of the dispatch cycle. It also establishes an optimal allocation model for energy storage capacity, which takes into account the performance parameters and life loss of the second-use batteries and the new power battery. Finally, Gurobi is used to simulate the field data of a wind farm. The simulation results show that this method is effective in preventing the accumulation of prediction deviation while reducing wind power grid deviation and improving the level of energy storage utilization. It can play a certain reference role in the configuration of energy storage for wind farms. [ABSTRACT FROM AUTHOR]

Aiming at the "net-zero carbon" target, a higher proportion of variable renewable energies (VREs) has been integrated into power grids, and pumped storage plants (PSPs) are crucial for guaranteeing the safe and stable operation of hybrid energy systems. As secondary frequency regulation (SFR) is related to the economic operation and the quality of auxiliary services provided by PSPs, it is critical to clarify its performance and compensation. Therefore, the corresponding quantitative evaluations of the SFR of pumped storage units (PSUs) are carried out in this paper. First, the performance of SFR is quantified based on the fuzzy analytic hierarchy process (FAHP). Considering the current situation in China's electricity market, the average compensation of the PSP with each MW is determined to be 9.336 CNY per day, and a method for calculating the compensation of SFR is constructed. Then, taking a real Chinese PSP as an example, based on different wind power deviation signals, the quantitative evaluation of the compensation of SFR is conducted in accordance with the fixed-speed pumped storage units (FSPSUs) and the variable-speed pumped storage units (VSPSUs) in power priority and speed priority modes. The results show that the compensation of FSPSUs and VSPSUs (power priority mode and speed priority mode) is 10,900 CNY per day; 54,400 CNY per day; and 17,300 CNY per day. This paper could contribute to clarifying the compensation of SFR and providing technical support for the development of the auxiliary service market. [ABSTRACT FROM AUTHOR]

With the development of renewable energy technologies such as photovoltaics and wind power, it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment of energy storage. To solve the problem of the interests of different subjects in the operation of the energy storage power stations (ESS) and the integrated energy multi-microgrid alliance (IEMA), this paper proposes the optimization operation method of the energy storage power station and the IEMA based on the Stackelberg game. In the upper layer, ESS optimizes charging and discharging decisions through a dynamic pricing mechanism. In the lower layer, IEMA optimizes the output of various energy conversion coupled devices within the IEMA, as well as energy interaction and demand response (DR), based on the energy interaction prices provided by ESS. The results demonstrate that the optimization strategy proposed in this paper not only effectively balances the benefits of the IEMA and ESS but also enhances energy consumption rates and reduces IEMA energy costs. [ABSTRACT FROM AUTHOR]