Long-term Power Research Articles

Physical security systems in today's conditions play a key role in maintaining nuclear security and ensuring the normal functioning of facilities in the nuclear power industry. Given the possible lack of electrical power caused by missile strikes in wartime, the enemy or criminals can take advantage of the vulnerability of the physical protection system, the means of which will be de-energized, which can lead to unacceptable radiation consequences [1] as a result of successfully executed illegal actions (sabotage, theft, etc.) ). Therefore, in accordance with the legislation, a number of requirements are put forward to the power supplies of the complex of engineering and technical means of the physical security system, the fulfillment of which in the process of designing, construction or operation of the physical security system is aimed at preventing the failure of power supplies or minimizing the probability of failures in the reliable power supply of the equipment of the physical security n system protection An important stage of ensuring the uninterrupted functioning of the physical security system in conditions of long-term emergency power outages is the selection of a generator set. In this work, the object of research is the security of critical infrastructure objects in conditions of long-term power outages, and the subject of research is the power supply system of the complex of engineering and technical means of the physical security system. The paper analyzes the existing regulatory and legal documentation regarding physical security and provides the method of selecting a generator set, as well as the option of integrating the set into the scheme of power supplies of the complex of engineering and technical means. The main method of the process of selecting the specified equipment is the comparison and analysis of the parameters specified by the manufacturer with the parameters and characteristics that will meet the requirements of the current regulatory and legal documentation and the needs of the training center in supplying electricity to this or that equipment. The method presented in the paper is universal in application and can be scaled to other critical infrastructure facilities, where it is necessary to provide power supplies with a power reserve in conditions of long-term emergency shutdowns of industrial power sources.

In the context of China’s electricity market reform, green certificate trading and carbon trading, as important policy tools to promote the development of renewable energy and energy conservation and emission reduction in the power industry, will inevitably be coupled with the electricity market. In order to study whether the coupled market can successfully achieve the goals of power supply structure adjustment and carbon emission reduction, this paper establishes a system dynamics (SD) model, analyzes the correlation and coordination mechanism among the green certificate market (TGC), carbon market (ET) and electricity market, including generation right trading, and simulates the changes of market price and power supply structure. The results show that (1) the power price under the coupling of three markets includes the TGC price and the ET price, so it is influenced by the ratio of renewable portfolio standards (RPS) and carbon reduction policy; (2) the combination of the TGC mechanism and the ET mechanism will be conducive to the optimization of long-term market power supply structure, so as to promote the realization of emission reduction targets; and (3) power generation rights trading, as a carbon reduction policy, will reduce the power generation of fossil energy in the short-term market, but in the long run, it will lead to the loss of momentum for the development of renewable energy. Therefore, regulators need to reasonably adjust different policies in order to give full play to the comprehensive regulatory role and help the energy and power industry and the low-carbon transformation of society.

This paper presents the details predicting wind energy output with machine learning models. Accurate forecasts of wind power's future are essential to the feasibility of major renewable energy projects. Making precise forecasts of wind power generation requires accounting for changes in weather patterns over time. This is also essential for issuing early warnings and implementing risk-reduction measures. In this study, prediction models for wind energy are developed using wind data collected at coastal regions in Kerala. Accurate forecasting of wind power generation is necessary to balance supply and demand in the smart grid. In the present investigation, an extensive analysis of long-term wind power forecasting was undertaken utilizing daily wind speed data, employing five distinct machine learning algorithms like XG Boost, LASSO, Gradient Boosting, Random Forest, and Bayesian Ridge Regression.

In contrast to the more conventional gas-filled post-compression technique, solid-state-based multi-pass cells and multiple plates allow for the robust and efficient generation of intense few-cycle pulses from ytterbium (Yb) lasers with moderate energies. In this Letter, 180-fs 200-μJ pulses at 50 kHz were efficiently compressed down to 6.9 fs 144 μJ, enhancing the peak power from 1.1 GW to 12.5 GW with a long-term power stability of 0.1%. Moreover, we generated over-1.5-octave-spanning white light (500 nm-1420 nm) by using an enhanced self-steepening effect, supporting a Fourier transform limit (FTL) pulse of 2.7 fs (0.8-cycle).

Abstract Environmental impact assessment (EIA), life cycle analysis (LCA), and cost benefit analysis (CBA) embed crucial but subjective judgments over the extent of system boundaries and the range of impacts to consider as causally connected to an intervention, decision, or technology of interest. EIA is increasingly the site of legal, political, and social challenges to renewable energy projects proposed by utilities, developers, and governments, which, cumulatively, are slowing decarbonization. Environmental advocates in the United States have claimed that new electrical interties with Canada increase development of Canadian hydroelectric resources, leading to environmental and health impacts associated with new reservoirs. Assertions of such second-order impacts of two recently proposed 9.5 TWh yr−1 transborder transmission projects played a role in their cancellation. We recast these debates as conflicting mental models of decarbonization, in which values, beliefs, and interests lead different parties to hypothesize causal connections between interrelated processes (in this case, generation, transmission, and associated impacts). We demonstrate via Bayesian network modeling that development of Canadian hydroelectric resources is stimulated by price signals and domestic demand rather than increased export capacity per se. However, hydropower exports are increasingly arranged via long-term power purchase agreements that may promote new generation in a way that is not easily modeled with publicly available data. We demonstrate the utility of causal inference for structured analysis of sociotechnical systems featuring phenomena that are not easily modeled mechanistically. In the setting of decarbonization, such analysis can fill a gap in available energy systems models that focus on long-term optimum portfolios and do not generally represent questions of incremental causality of interest to stakeholders at the local level. More broadly, these tools can increase the evidentiary support required for consequentialist (as opposed to attributional) LCA and CBA, for example, in calculating indirect emissions of renewable energy projects.

Yarn-shaped energy-storage devices (YSEs), including supercapacitors and batteries, are becoming promising energy-supply units with decent mechanical flexibility to be integrated into e-textiles, in various shapes and locations with the possibility of hiding among regular textile yarns without being noticed or detected. However, a robust YSE configuration, which can provide long-term and reliable power output after rigorous weaving/knitting processes and upon all kinds of end-use scenarios, is yet to be established. Most YSEs today still suffer from performance decay and short-circuiting risks, primarily due to structural failures of active materials involved. Moreover, a prominent length-dependent output has been observed in many YSE samples, which exhibit a plateaued capacitance/capacity at extended yarn lengths. In this talk, we will give an overview of existing issues of the state-of-the-art YSEs, and their possible solutions or mitigation strategies. In detail, we will discuss the incorporation of separator threads in a twisted YSE, to withstand repetitive mechanical deformations. A detailed mathematical model for YSEs will also be discussed to clarify the length dependence of their performances. REFERENCES He, X. Zhang, J. Song, F. Zhao, W. Gao*, Modeling of yarn-shaped supercapacitors – Unraveling its length dependent output, Journal of Power Sources, 2024, 595, 234067He, J. Song, J. Liao, F. Zhao, W. Gao*, Separator Threads in Yarn-Shaped Supercapacitors to Avoid Short-Circuiting Upon Length, npj Flexible Electronics , 2022, 6, article number 19.He, N.; King, C.; Xie, Q.; Zhao, F.; Gao, W.* A Multidirectional Forearm Electromagnetic Generator Designed via Numerical Simulations. Actuators,2023, 12 (6), 225.Wang, Y.; Shim, E.; He, N.; Pourdeyhimi, B.; Gao, W.* Modeling the Triboelectric Behaviors of Elastomeric Nonwoven Fabrics. Adv. Mater. 2022, 34 (2), 2106429.Subjalearndee, N. He, H. Cheng, P. Teastchabut, P. Eiamlamai, P. Limthongkul, V. Instasanta, W. Gao*, X. Zhang*, Gamma (ɣ)-MnO2/rGO Fibered Cathode Fabrication from Wet Spinning and Dip Coating Techniques for Cable-Shaped Zn-Ion Batteries, Adv. Fiber. Mater. , 2022, 1-18.Mainka, W. Gao, N. He, J. Dillet, O. Lottin, A General Equipvalent Electrical Cuicuit Model for the Characterization of MXene/graphene oxide hybrid-fiber supercapacitors by electrochemical impedance spectroscopy-Impace of fiber length, Electrochimica Acta , 2022, 404, 139740N. He, J. Liao, F. Zhao, W. Gao*, Dual-Core Supercapacitor Yarns: An Enhanced Performance Consistency and Linear Power Density, ACS Appl. Mater. Interfaces , 2020, 12, 15211-25219. ACKNOWLEDGMENT This work has been financially supported by 1) United States Army Research Office under the contract number W911NF19C0074 and W911NF18C0086; 2) Intelligence Advanced Research Projects Activity (IARPA) under the SMART ePANTS program. Figure 1

Offshore wind power resources in the Red Sea waters of Saudi Arabia are yet to be explored. The objective of the present study is to assess offshore wind power resources at 49 locations in the Saudi waters of the Red Sea and prioritize the sites based on wind characteristics. To accomplish the set objective, long-term hourly mean wind speed (WS) and wind direction (WD) at 100 m above mean sea level, temperature, and pressure data near the surface were used at sites L1-L49 over 43 years from 1979 to 2021. The long-term mean WS and wind power density (WPD) varied between 3.83 m/s and 66.6 W/m2, and 6.39 m/s and 280.9 W/m2 corresponding to sites L44 and L8. However, higher magnitudes of WS >5 m/s were observed at 34 sites and WPD of > 200 W/m2 at 21 sites. In general, WS, WPD, annual energy yield, mean windy site identifier, plant capacity factor, etc. were found to be increasing from east to west and from south to north. Similarly, the mean wind variability index and cost of energy were observed to be decreasing as one moves from east to west and south to north in the Saudi waters of the Red Sea.

This study evaluates and compares the power consumption and resource utilization of open-source and proprietary media players during the playback of a large raw video file. Using real-time monitoring tools like HWiNFO, key metrics such as GPU power consumption, CPU power consumption, memory usage, and CPU usage percentage were collected and analyzed. The experiment was conducted on a system powered by a 12th Gen Intel(R) Core(TM) i7-12700H processor, and the media players were tested with a 2-minute, 14-second raw video file in .MOV format. A statistical analysis using t-tests was performed to assess the significance of the differences between the two categories. The results indicated that open-source media players generally exhibit lower GPU and CPU power consumption, with a potential for saving energy. Long-term power consumption analysis further demonstrated that users could achieve significant energy savings by opting for open-source media players, making them more suitable for energy-conscious environments. These findings highlight the trade-offs between power efficiency and performance while playing raw videos.

Maintaining the operability of a hydroelectric power station at a scale originally designed is being compromised by continuous reservoir sedimentation. The underlying factors include a complex mix of landscape alterations owing to natural and anthropogenic activities around dam areas, such as gully erosion, landslides, floods triggered by heavy rainfall, climate change, and construction activities. The hydropower projects in the low-to-mid mountain regions of Nepal are witnessing a combination of these phenomena, affecting their optimal performance in meeting long-term sustainable power supply targets. This paper presents a combination of geo-spatial analysis and field evaluations to identify the trends from Kulekhani-I, one of the oldest storage-type hydropower projects in Nepal, using long-term time series remote sensing satellite imagery from 1988 to 2020. Our analysis shows an expansion of the surface water content area over time, attributed mainly to high sedimentation deposition owing to multiple factors. This study has identified an urgent need for addressing the following two key contributory factors through an effective control mechanism to avoid rapid sedimentation in the reservoirs: natural—landslides and floods leading to mainly silt deposition during heavy rainfalls; and anthropogenic—road construction materials dumped directly in the reservoir. Effective implementation of a remote sensing monitoring scheme can safeguard future damages to dam environments of more recently built storage-type hydropower projects.

Abstract The configuration of adjustable capacity transformers will be affected by photovoltaic (PV) penetration. In this paper, we propose a method for optimizing the configuration of adjustable capacity transformers by analyzing the parameters and topology of the low-voltage distribution network, which considers both the operational safety of the grid and economic objectives under optimal power flow (OPF) distribution. We construct the objectives and constraints of the OPF-solving model in different PV penetration scenarios for two types of node topologies and utilize second-order cone (SOC) relaxation to solve the results of OPF distribution. In order to calculate the long-term power loss and comprehensively assess the transformer replacement cost, we analyze the low-voltage side load curves of the adjustable capacity transformers based on the OPF solutions. We design an optimization scheme for the capacity configuration of transformers under different PV penetration rates. Simulation results show that the proposed scheme can effectively reduce power loss and transformer operating costs.

Integrating photovoltaic power stations into large-capacity hydropower stations is an efficient and promising method for regulating large-scale photovoltaic power generation. However, constrained by the time step length, traditional long-term scheduling of hydro-PV hybrid systems does not adequately consider short-term operational performance indicators, resulting in sub-optimal scheduling plans that fail to coordinate the consumption of photovoltaic power and the utilization of water resources in the basin. To address this, this study established a long-term optimal scheduling model for hydro-PV hybrid systems. This model overcomes the limitation of the time step length in long-term scheduling by incorporating long-term power generation goals and short-term operation performance targets into the long-term optimal scheduling process based on scheduling auxiliary functions. In case studies, the optimised model balanced the long-term power-generation goals and short-term operational performance targets by redistributing energy across different periods. Compared to optimization models that did not consider short-term operation performance, in a typical normal year, the model effectively reduced the electricity curtailment volume (28.54%) and power shortage volume (10.91%) of the hybrid system while increasing on-grid electricity (0.03%). Similar improvements were observed in wet and dry years. These findings provide decision support for hydropower scheduling in the context of large-scale photovoltaic power integration.

A high-performance all-day vertical thermoelectric generator based on a double-sided reflective structure

Flexibility potential quantification of electric vehicle charging clusters

In order to consider the impact of source-load uncertainty on traditional power system planning methods, a medium- and long-term optimization planning method based on source-load uncertainty modeling and time-series production simulation is proposed. First, a new energy output probability model is developed using non-parametric kernel density estimation, and the spatial correlation of the new energy output is described using pair-copula theory to model the uncertainty analysis of the new energy output. Secondly, a large number of source-load scenarios are generated using the Markov chain Monte Carlo simulation method, and the optimal selection method for discrete state numbers is provided, and then the scenario reduction is carried out using the fast forward elimination technology. Finally, the typical time-series curves of the source-load uncertainty characteristics obtained are incorporated into the optimization planning method together with various flexible resources, such as the demand-side response and energy storage, and the rationality of the planning scheme is judged and optimized based on key indicators such as the cost, wind–light abandonment rate, and loss-of-load rate. Based on the above methods, this paper offers an example of the power supply planning scheme for a certain region in the next 30 years, providing effective guidance for the development of new energy in the region.

Distributed photovoltaic power stations have advantages such as local direct power supply and reduced transmission energy consumption, and whose demands are constantly being developed. Conducting research on medium- and long-term distributed photovoltaic prediction will have significant value for applications such as the electricity trade market, power grid operation, and the planning of new power stations. Due to characteristics such as long time dependence, disperse power stations, and strong randomness, making accurate and stable predictions becomes very difficult. In this research, we propose a multiple time series feature and multiple-model fusion-based ensemble learning model for medium- and long-term distributed photovoltaic power prediction (M2E-DPV). Considering the wave influence and the differences in distributions in different areas of photovoltaic power, multiple feature combinations are designed to increase feature expression ability and adaptability. Based on the boost ensemble learning model, trained on a single model of different time scale features, the optimal scoring strategy is used for multiple model fusion in the rolling prediction process, and finally, time-segmented probabilistic correction is performed. The experiment results show the effectiveness of the M2E-DPV under multiple feature combinations and multi-model fusion strategies. The average MAPE, R2, and ACC indicators are 0.15, 0.96, and 0.91, respectively. Compared with other methods, there is a significant improvement, indicating that the prediction ability of the model framework proposed in this paper is advanced and robust.

Abstract Owing to the high stored energy of ITER plasmas, the heat pulses due to uncontrolled Type I edge localized modes (ELMs) can be sufficient to melt the top surface of several poloidal rows of tungsten monoblocks in the divertor strike point regions. Coupled with the melt motion associated with tungsten in the strong tokamak magnetic fields, the resulting surface damage after even a comparatively small number of such repetitive transients may have a significant impact on long-term stationary power handling capability. The permissible numbers set important boundaries on operation and on the performance required from the plasma control system. Modelling is carried out with the recently updated MEMENTO melt dynamics code, which is tailored to tackle melt motion problems characterized by a vast spatio-temporal scale separation. The crucial role of coupling between surface deformation and shallow angle heat loading in aggravating melt damage is highlighted. As a consequence, the allowable operational space in terms of ELM-induced transient heat loads is history-dependent and once deformation has occurred, weaker heat loads, incapable of melting a pristine surface, can further extend the damage.

The article analyzes the main risks faced by business entities in Ukraine with a full-scale Russian invasion of Ukraine in 2022. The modern dynamics of registration of new business entities since the beginning of the full-scale war for March - August 2022 were analyzed. The main problems that made it difficult to do business in Ukraine since the beginning of the full-scale invasion were identified, namely consumer insolvency, a drop in demand for the products of enterprises, and a lack of funding. , destruction of supply chains, long-term power outages due to military attacks on energy facilities, rising costs of raw materials, materials and energy resources, and a shortage of skilled workers. The article also analyzed the rating of doing business in strategic cities of Ukraine, namely Lviv, Odesa, Kharkiv and Dnipro. Preventive measures were also proposed to reduce business risks in Ukraine under martial law.Among the main recommendations: analysis of the insurance policy and the possibility of asset protection; development of crisis management and evacuation plans; strengthening relations with other companies and authorities to provide support in crisis; analysis of risks in the market and adaptation of production in accordance with changes in demand; development of different planning and budgeting scenarios for different market conditions; diversification of supply chains and search for alternative sources of raw materials; monitoring of financial markets and timely response to changes; development of a strategy to reduce currency risks and other financial losses; development of alternative sources of financing and investments; developing an emergency plan and having alternative suppliers of raw materials; ensuring the stability of infrastructure and transport links; monitoring of global events and geopolitical risks to predict possible supply interruptions; development of emergency power plans and backup solutions - to ensure power supply in case of energy shortage; reducing dependence on centralized energy sources and developing alternative energy sources, etc.

A long-term power system state calculation method using sequential power and holomorphic embedding

Abstract In the context of virtual power plants gradually joining the medium-and long-term power market transactions, the decision-making problem of this new subject in the transaction process has attracted wide attention. Since virtual power plants possess distributed power sources on the supply side, as well as variable loads, energy storage, and other resources on the customer side, they are able to participate in both the sale and purchase of electricity in the medium-and long-term electricity market at the same time, which leads to the need for the relevant analysis to be divided into the two cases of sale and purchase of electricity. At the same time, due to the wide application of the CFD mechanism, power transactions should also take into account the compensation adjustment brought by this mechanism in addition to the market price. To sum up, this paper constructs a static game model for the virtual power plant’s power sales and purchasing strategies in the medium-and long-term power market under the premise of the CFD mechanism. The analysis shows that the optimal trading volume is related to the CFD volume, the total volume of power supplied by the bidding, the market price, etc. The relevant conclusions will help market managers to grasp the market price. The conclusions of the analysis help market managers grasp the key transaction information and assist virtual power plants to participate in medium-and long-term power transactions in an orderly manner.

High-efficiency Yb:YAG thin-disk chirped pulse amplifier delivering 884-femtosecond laser with tunable repetition rates and high stability