Long-term Power Research Articles

Конкуренция и монополия в цифровую эпоху

Patterns for competitive and monopoly behaviour, market power configurations and instruments of interfirm relationships are under radical transformation in a digital era. There arise new forms of monopolistic strategies that aim at establishing, strengthening and withstanding long-term market power in various industries. Analysis of Russian and foreign economic research that was done in the article promoted a conceptual theoretical approach to monopoly and competition under digitalization.

Approximate Dynamic Programming of Long Term Power Generation Schedule

With respect to the features in optimal scheduling of long-term power generation such as long cycle, large scale and strong randomness, the paper proposed a multi-stage optimized decision model based on approximate dynamic programming. In this model, the influence of random variables including load, fuel price, and water was tested by means of stochastic simulations. Staged solution was used to reduce the size and difficulty of solving the problem. The proposed value function approximation strategy of pondage and coal inventory solved the "curse of dimensionality" in staged recursion and maintained the overall optimization characteristics after staged decomposition. Through the iterative update between the decision and the approximation function, the approximate optimal decision sequence was solved to obtain the optimization scheme of power generation scheduling. The calculation and analysis results in a real system in some province showed that the modeling by approximate dynamic programming is an effective way to solve such large-scale optimization and has a promising future by virtue of its conciseness, effectiveness, convenience in dealing with random factors, high calculation accuracy and rapidity of solution.

Influence of the POuN4-u structural units on the formation energies and transport properties of lithium phosphorus oxynitride: a DFT study.

The potential of mobile applications for digital networking is constantly increasing. A key challenge is to ensure a reliable and long-term power supply. One possible solution is the use of all-solid-state thin-film lithium batteries which use amorphous lithium phosphorus oxynitride (LIPON) as solid electrolyte. It is well known that the electrochemical properties of this material are related to the amorphous state, which correlates with the nitrogen content. Due to the difficulty of calculating amorphous structures using first principles methods, three different LIPON structure models are considered in this study and the influence of the anion POuN4-u sublattice on the Li vacancy and Li interstitial formation as well as on the lithium ion transport is highlighted. While for all three model systems the migration energies of the energetically preferred Li vacancies increase with increasing complexity of the anion POuN4-u sublattice only slightly from 0.38 eV to 0.55 eV, the migration energies for the energetically preferred Li interstitials decrease with increasing complexity of the anion POuN4-u sublattice from 0.68 eV to 0.38 eV. Thus, it was found that the energetically preferred lithium ion (Li vacancy and Li interstitial ion) transport mechanism in LIPON can be explained on the basis of the present POuN4-u structural units. In the presence of isolated PON3x- tetrahedra or periodic PO2N2 chains, the lithium vacancy diffusion dominates, whereas in the presence of periodic POuN4-u planes, the lithium interstitial diffusion becomes dominant.

Questionnaire Survey Concerning the Insulin Storage Status During Long-term Power Outages on Hot Summer Days Following Typhoon Faxai (Typhoon 1915)

Questionnaire Survey Concerning the Insulin Storage Status During Long-term Power Outages on Hot Summer Days Following Typhoon Faxai (Typhoon 1915)

N-type core-shell heterostructured Bi2S3@Bi nanorods/polyaniline hybrids for stretchable thermoelectric generator

With the growing need on distributed power supply for portable electronics, energy harvesting from environment becomes a promising solution. Organic thermoelectric (TE) materials have advantages in intrinsic flexibility and low thermal conductivity, thus hold great prospect in applications as a flexible power generator from dissipated heat. Nevertheless, the weak electrical transport behaviors of organic TE materials have severely impeded their development. Moreover, compared with p-type organic TE materials, stable and high-performance n-type counterparts are more difficult to obtain. Here, we developed a n-type polyaniline-based hybrid with core-shell heterostructured Bi2S3@Bi nanorods as fillers, showing a Seebeck coefficient –159.4 μV/K at room temperature. Further, a couple of n/p legs from the PANI-based hybrids were integrated into an elastomer substrate forming a stretchable thermoelectric generator (TEG), whose function to output stable voltages responding to temperature differences has been demonstrated. The in situ output performance of the TEG under stretching could withstand up to 75% elongation, and stability test showed little degradation over a one-month period in the air. This study provides a promising strategy to develop stable and high thermopower organic TEGs harvesting heat from environment as long-term power supply.

Optimization Method and Reduced-Order Steady-State Model for Variable-Speed Pump-Turbine Unit

Increased attention has been paid to the high-capacity variable-speed pumped storage to stabilize the large-scale renewable energy. Nevertheless, the optimum reference values of variable-speed units (i.e., the optimum speed and optimum gate opening) come from the actual operating data from power plants or the model pump-turbine test from manufacturers. It is generally a commercial secret, and no historical data is available for a new power plant. For general researchers, it is not easy to obtain relevant data. Therefore, this paper proposes an optimization method for the variable-speed unit and establishes a simplified steady-state model that can be used for medium and long-term power system research. First, based on the pump-turbine’s performance curves, this paper presents an optimization method for the variable-speed unit in turbine and pump mode without additional tests, aiming to optimize the turbine’s efficiency and track the input power of the pump. Second, the concept of “steady operation area in non-optimum condition” is proposed based on the non-linear characteristics of the optimum operating condition curve. Finally, simplified steady-state models of the variable-speed unit are established, and the model validation has been tested in typical scenario analysis. The results show that the variable-speed unit’s steady-state operating characteristic can be described by this simplified linear model, based on the power, the head, and the optimum speed (or the gate opening). This simplified model’s percentage error is less than 5%, which meets engineering accuracy requirements. The error mainly comes from the linear correlation coefficient of the optimum operating condition curve and the operating head’s deviation from the design head. This model is available for power system planning and dispatch.

A HYBRID MONTE-CARLO-DETERMINISTIC METHOD FOR AP1000 EX-CORE DETECTOR RESPONSE SIMULATION

The ex-core detector-response calculation is a typical deep-penetration problem, which is challenging for the Monte Carlo method. The response of the ex-core detector is an important parameter for the safe operation of the nuclear power plants. Meanwhile, evaluation of the ex-core detector response during each step of fuel-loading is used to guide the fuel-loading sequence. The response can also be used to reconstruct core-power distribution for online monitoring of long-term power. The detector used for the ex-core response is the source-range detector which is sensitive to thermal neutrons. For a Monte Carlo shielding calculation of the above detector response, the thermal flux under 0.625eV is needed, which is too small to be tallied by traditional Monte Carlo simulations. In practice, the tally results are close to zero in the detector region under direct Monte Carlo calculation. Even if the number of particles is increased to a significant amount, the statistical variance is still very large. The high variance along with a significant calculation time leads to a small Figure Of Merit (FOM). In order to solve this problem and to improve the tally efficiency of the ex-core detector response, a hybrid Monte-Carlo-deterministic method is employed in this study, and an in-house hybrid Monte-Carlo-deterministic particle transport code, NECP-MCX, is developed in this paper. The method takes the space-energy-dependent adjoint fluxes to generate importance parameters for the mesh-based weight window in the Monte Carlo calculation. Simultaneously, the mesh-based source biasing is performed with the consistent importance parameters to make the starting weight of neutrons matching with the survival weight of the weight windows. As the mesh used in the hybrid Monte-Carlo-deterministic method is superimposed, the mesh of the weight window will not be affected by the complex geometry model. The adjoint flux is obtained by the efficient SN method with the multi-group cross-section data. The whole toolset is convenient to use with single set of the modelling data for both Monte Carlo and deterministic simulations. Compared with the direct Monte Carlo simulation, the hybrid Monte-Carlo-deterministic method has a higher efficiency for a typical deep-penetration problem such as the AP1000 ex-core detector-response simulation.

Long-term load combination forecasting method considering the periodicity and trend of data

In order to solve the problems of insufficient accuracy of long-term power load forecasting and poor applicability of the model, this paper considers the coupling of a number of macro indicators, such as regional economic development and social development indicators, with the time series data of regional power load. BP neural network and Autoregressive integrated moving average model (ARIMA) are used to integrate and improve the forecasting model, so as to improve the trend forecasting ability of annual load forecasting model. The non parametric function method is used to forecast the periodic load data in the monthly load data, the annual load forecast is combined with the monthly load forecast to improve the overall forecasting accuracy of the model. Finally, through the comparison of grey prediction and other models and the verification of MAPE error analysis method, the prediction accuracy of the model method considering the combination of data periodicity and trend is significantly improved, which is suitable for the long-term prediction of regional power load.

A Calculation Method of Available Transmission Capacity for Medium and Long-term Electricity Trading

In view of the fact that China’s power dispatching agencies and trading centers are relatively independent, but the medium and long-term power transactions need physical execution, which leads to higher requirements for transaction security boundary, this paper proposes a calculation method of available transmission capacity for medium and long-term power transactions, which calculates the available transmission capacity of transmission channels through probabilistic method to improve the enforceability of transaction results. Numerical simulation results also verify the effectiveness of the algorithm.

Medium- And Long-term Power Curve Division Mechanism Based on Energy Block Segmentation

With the development of electric power system reform, it is very important to design the medium- and long-term curve division mechanism for electric power in China. The essence of power supply is "continuous" energy block supply. The two sides of supply and demand take the power block as the interactive unit agreement to deal with electricity. The model of medium- and long-term curve division based on energy block can reflect the abundance of electric power, be beneficial to the stable and reliable supply of electric power and effectively reduce the loss of auxiliary service. Based on the development of new power systems at home and abroad, this paper designs the power curve division mechanism based on energy blocks, and takes Qinghai Province as an example to study its medium - and long-term power curve division mechanism with high proportion of renewable energy.

Quantifying Power System Operational and Infrastructural Resilience Under Extreme Conditions Within a Water-Energy Nexus Framework

This work presents definitions and metrics developed for quantifying the resilience of the electric power system (EPS) while considering its interdependent operation with the water distribution system (WDS). These metrics are used within a novel formulation in order to determine EPS resilience during the coordinated real-time operation of the two systems where both the operational state and infrastructural configuration of the EPS is taken into account. Coordinated operation of the two systems involves simulations that account for the main dependencies of each system on the other (cooling water for thermoelectric generation and electric power for WDS pumps). The results for several test cases are used within this work to demonstrate how system resilience in the EPS is captured for simulations that emulate the critical conditions of long-term power outages (in the EPS) and severe drought (in the WDS).

A New Medium and Long-Term Power Load Forecasting Method Considering Policy Factors

At present, China’s power load development is facing a new situation in which policies such as the new economic norm, industrial structure adjustment, energy conservation and emission reduction, etc. are being deeply promoted, load growth in some areas begin to ease, and volatility of load gradually become prominent, which increases the difficulty of medium and long-term load forecasting. In this context, in view of multi-correlation, uncertainty of influence of policy factors on power load, in order to improve the accuracy of load forecasting under the influence of policy factors, and solve the problem that policy factors are ambiguous, difficult to be quantified, and difficult to be integrated into load forecasting model, a medium and long-term load forecasting model considering policy factors is proposed. First, by analyzing the influence of various policies on power load, a hierarchical policy influencing factor index system that combines macro and micro levels is constructed to systematically reflect the influence of economy and policies on load under the new situation. Then, in view of the traditional grey relational analysis model’s insufficient consideration of the difference of historical data and future power development situation, by respectively weighting historical periods and factor indexes, a quantification analysis model of power load influencing factors based on two-way weighted grey relational analysis is proposed to quantify the influence of various policy factors on power load, achieve the combination of subjective weighting and objective weighting,and obtain quantification weights. Finally, the weighted fuzzy cluster analysis method combined with weights is used to predict load under the influence of policy factors. The proposed model can better solve the difficulty of medium and long-term load forecasting caused by the volatility of load under the influence of policy factors, and is suitable for medium and long-term load forecasting under the background of policy changes. The analysis of calculation examples shows that compared with traditional grey relational analysis model, the quantification results of proposed methods are more realistic, compared with traditional prediction methods such as time series extrapolation and elasticity coefficient, proposed method has better prediction accuracy and engineering application value.

Inter-comparison of long-term wave power potential in the Black Sea based on the SWAN wave model forced with two different wind fields

In this study, a long-term comparative assessment of the potential of wave power in the Black Sea was conducted using the calibrated and validated SWAN (Simulating WAves Nearshore) model forced by two well-known wind fields. The European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and National Centers for Environmental Prediction/Climate Forecast System Reanalysis (NCEP/CFSR) wind fields were used, covering data from 1979 to 2018. In general, the wave power potential based on the results of the CFSR wind field was found to be slightly higher than that obtained with the ERA-Interim wind field. The greatest discrepancy between the results of the ERA-Interim and CFSR wind fields was observed in the northeastern Black Sea. The spatial distributions of the wave power were also evaluated on a seasonal scale using wave parameters obtained from the calibrated SWAN model. The wave climate obtained from both long-term and seasonal assessments indicates that the western Black Sea, especially the southwestern Black Sea, is characterized by higher wave power potential and lower variability, while the eastern Black Sea has lower wave power potential and higher variability. Stable and powerful long-term wave conditions in the southwestern Black Sea can indicate that this region is a suitable location for wave farms. In contrast, the effect of the long-term variability on wave power is greatest in the eastern Black Sea owing to the highly variable wave conditions in this region.

Determinations of Annual Investments of DisCo and Private Sector in Expansion Planning of Distribution Network

Ever-increasing load-demand, threaten the continuity of power supply and diminishes power quality causing serious technical challenges in distribution networks. In this regards, commonly used cheaper practices like capacitor allocation and network configuration, can enhance operational parameters of the network. On the other hand, supplying the future loaddemand, requires installing new substations or distributed generations (DGs). Because of DGs inherent technical and economic advantages, Distribution Company (DisCo), encourage private investment to install DGs, by signing long-term Power Purchase Agreement (PPA) with DG owners (DGO). In such a situation created, DG allocation and simultaneously capacitor allocation and network configuration can be economical for both DisCo and DGO and also can enhance the reliability and power quality. So, this paper is aimed to find the annual instants for network configuration; timing, sizing and sitting of capacitors and DGs, and PPA rates using Multi-Objective Particle Swarm Optimization (MOPSO). Also, the uncertainties of load-demand and electricity-price, voltage-sensitive loads and load priority in power supply are applied into the planning problem. Voltage deviation and voltage stability are considered as constraints which must be better in optimum solution. The effectiveness of the proposed scheme, is validated by computer simulation done on a 33-Bus IEEE distribution network and the outcomes are discussed.

Analysis of Meteorological Factor Multivariate Models for Medium- and Long-Term Photovoltaic Solar Power Forecasting Using Long Short-Term Memory

Solar power generation is an increasingly popular renewable energy topic. Photovoltaic (PV) systems are installed on buildings to efficiently manage energy production and consumption. Because of its physical properties, electrical energy is produced and consumed simultaneously; therefore solar energy must be predicted accurately to maintain a stable power supply. To develop an efficient energy management system (EMS), 22 multivariate numerical models were constructed by combining solar radiation, sunlight, humidity, temperature, cloud cover, and wind speed. The performance of the models was compared by applying a modified version of the traditional long short-term memory (LSTM) approach. The experimental results showed that the six meteorological factors influence the solar power forecast regardless of the season. These are, from most to least important: solar radiation, sunlight, wind speed, temperature, cloud cover, and humidity. The models are rated for suitability to provide medium- and long-term solar power forecasts, and the modified LSTM demonstrates better performance than the traditional LSTM.

An Overview and Prospect of Nuclear Battery

The nuclear battery has many advantages, including high energy density, stable performance, no manual intervention etc., which can be widely utilized in cases requiring long-term reliable power supply. Among them, the Radioisotope Thermoelectric Generators (RTG) is the earliest used and the most technically matured one, while betavoltaic battery is now commercialized. However, there are still some problems including self-absorption effect, low energy conversion efficiency and severe radiation damage which restrict the application of betavoltaic batteries. Additionally, for an actual nuclear battery, it should be noticed that the component and density of the source will be changed because the radiation source decays continually, which leads to the electrical performance decline. In this review, the major events in nuclear battery development are listed on a timeline, and the principles and applications of different types of nuclear batteries are also introduced. For betavoltaic battery, the existence of self-absorption effect is pointed out as an important scientific problem, and for batteries with 63Ni and TiT2 source, the time-related electrical properties are also obtained. This paper also pointed out that, fine and precise calculations are very crucial in the optimized designing processes for a particular structure of the practical nuclear battery. Finally, researching assumptions including combining the source and the energy converting material and the use of energy converting structures with heavier isotopes are presented, which are benefit to solve the self-absorption problem, rise the output power of the nuclear battery and reduce the influence of radiation damage.

Optimal valuation of wind energy projects co-located with battery storage

The electricity market in the UK has been reformed over recent years resulting in the introduction of ‘Contracts for Difference’ as an option for wind producers. They can use these contracts only if at the same time they enter into other market contracts, i.e., Power Purchase Agreements or participation in the wholesale market. Most wind producers prefer the option of holding a long-term Power Purchase Agreement with another party. However, these agreements do not always offer the best terms for a wind producer due to them selling energy at lower electricity prices than those of the wholesale market spot prices. In addition, direct participation in the wholesale market can lead to high imbalance costs for the wind producers. In this paper, we propose an optimal dispatch model solved via dynamic programming optimisation to examine these two different business cases for wind operators alongside the existence (or not) of subsidised Contracts for Difference. A case study with an onshore UK wind farm and a lithium-based battery is provided. The proposed methodology was designed flexibly, so that it can be applied to different wind farm and battery configurations, as well as energy market structures. It is found that it is not always more profitable for the wind operator to hold a Power Purchase Agreement with another party than owning a battery storage unit and trading wind energy directly into the wholesale market. The discount rate of the Power Purchase Agreements, the capital cost of the wind farm and the strike price of the Contracts for Difference are critical factors affecting the profitability of both business cases. In addition, if subsidies are totally removed from both of them, then these are no longer economically justifiable, unless significant reductions are achieved in the capital costs of wind farms and battery storage units. Lastly, we show that considering only the calendar life of the battery (and not the cycle life) leads to significant underestimation of the investment costs.

Multi-Year and Typical Year Data for Solar Energy System in South Korea

Typical meteorological year (TMY) data has significant importance for solar resource assessment, as well as for building performance analysis. The necessity of high-accuracy TMY data has been well known for many years for the financial viability of solar long-term planing project as it represents long-term weather features. However, the TMY does not mean the use of real-time data; it is therefore important to determine the accuracy of the TMY dataset. In this study, the solar energy performance of TMY was evaluated quantitatively by comparing it to multi-year average weather data (2008-2017) based on the statistical analysis method. The PV power output were produced by using 100kW photovoltaic system based on PVsyst software at six sites. The results showed that the difference between the TMY-PV power output and long-term PV power output (measured with percentage error) are smaller than 9%, which means there is close-fit agreement between TMY and long-term averages PV power output. These findings suggests that TMY can provide reliable estimation of PV power in the feasibility study of PV project.

Strengthening Resilience of Lithuania in an Era of Great Power Competition: The Case for Total Defence

Abstract In response to the power redistribution in the international system, the United States prepares for long-term Great power competition. It is aiming at strengthening America's network of alliances and partnerships in order to counter a rising China and revisionist Russia. The other states react to greater or lesser extent to the changing constraints and opportunities in the international system. The article examines how Lithuania, being a small state that belongs to the North Atlantic Alliance, is adapting to these systemic pressures. Current NATO's deterrence posture in the Baltic region is something akin to deterrence by the assured response – NATO is sending a signal that if the Russians attacked, NATO would respond in the Baltics. Lithuania, as well as other Baltic countries, has undertaken many legal, procedural, financial and technical measures to boost resilience and deterrence. However, there are not enough national or NATO military forces that would be able to counter conventional Russian forces deployed in the region. There are challenges such as air defence and control of the Baltic Sea. Also land forces are not present in adequate quantities. As a result, Lithuania has to strengthen its own capabilities with the help of the allied countries. It argued in the article that building up a total defence system in Lithuania would be a right effort in this regard.

Personality Changes Predict Early Career Outcomes: Discovery and Replication in 12-Year Longitudinal Studies

In this research, we examined whether personality changes from adolescence to young adulthood predicted five early career outcomes: degree attainment, income, occupational prestige, career satisfaction, and job satisfaction. The study used two representative samples of Icelandic youth (Sample 1: n = 485, Sample 2: n = 1,290) and measured personality traits over 12 years (ages ~17 to 29 years). Results revealed that certain patterns of personality growth predicted career outcomes over and above adolescent trait levels and crystallized ability. Across both samples, the strongest effects were found for growth in emotional stability (income and career satisfaction), conscientiousness (career satisfaction), and extraversion (career satisfaction and job satisfaction). Initial trait levels also predicted career success, highlighting the long-term predictive power of personality. Overall, our findings show that personality has important effects on early career outcomes—both through stable trait levels and how people change over time. We discuss implications for public policy, for theoretical principles of personality development, and for young people making career decisions.