scholarly journals PRICE FORECASTING MECHANISMS OF MODERN ENERGY MARKETS

2020 ◽  
Author(s):  
Vasyl Gorbachuk ◽  
◽  
Andrij Syrku ◽  
Seit-Bekir Suleimanov ◽  
◽  
...  
Keyword(s):  
Energy Storage ◽  
Supply Chains ◽  
Power Plants ◽  
Energy Markets ◽  
Power Grids ◽  
Price Forecasting ◽  
Medium Term ◽  
Short Term ◽  
Power Sources

The trends of European energy markets depend on the forecasting of fundamental price based on the modeling approaches for short-term physical electricity markets, including day-ahead trade markets for energy power, intra-day trade markets for energy power, trade for balancing or reserving energy capacity. The typical hierarchy of modeling on modern market consists of the fundamental model of long-term planning to years ahead (where stochastic aggregation or disaggregation for price forecasting takes place), the model of medium-term planning to months ahead (where the stochastic modeling of semi aggregated hydro energy with generation of cuts, at prices given, takes place), and the model of short-term planning to weeks ahead (where the deterministic modeling of disaggregated hydro energy, at prices given, takes place). The model of long-term planning is a fundamental one in the sense of a detailed and adequate description of market, supply, demand, and network topology. The models of medium-term and short-term planning are typical ones for regional markets. Energy storage technologies have changed modern energy markets. If the traditional power grids have worked like ultimate just-in-time supply chains without stocks and with almost immediate delivery of good (electricity), then modernized power grids will create new opportunities for their optimization and operation. The new power grids will resemble common supply chains with stocks (in the form of large-scale batteries and other energy storage devices), supply uncertainty (from variable power sources such as wind and solar power plants), high customer service requirements (under deregulating of the electricity market and entering of new competitors to the market), the newest pricing schemes (due to the new communication infrastructure allowing information transmission for real time pricing). An energy storage system can be viewed as a system of stocks, where the product stored is the energy instead of a traditional good. Then a series of models of energy storage management is based on the fundamental theory of inventory optimization. On the other hand, energy storage systems usually have more room for decision: in addition to the decision to purchase a product (as in classic inventory models), there may be decisions about the quantity and the price of product sales.

scholarly journals Long-Term Data Traffic Forecasting for Network Dimensioning in LTE with Short Time Series

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1151
Author(s):  
Carolina Gijón ◽  
Matías Toril ◽  
Salvador Luna-Ramírez ◽  
María Luisa Marí-Altozano ◽  
José María Ruiz-Avilés
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Analysis ◽  
Data Traffic ◽  
Medium Term ◽  
Short Term ◽  
Traffic Forecasting ◽  
Series Analysis ◽  
Radio Planning

Network dimensioning is a critical task in current mobile networks, as any failure in this process leads to degraded user experience or unnecessary upgrades of network resources. For this purpose, radio planning tools often predict monthly busy-hour data traffic to detect capacity bottlenecks in advance. Supervised Learning (SL) arises as a promising solution to improve predictions obtained with legacy approaches. Previous works have shown that deep learning outperforms classical time series analysis when predicting data traffic in cellular networks in the short term (seconds/minutes) and medium term (hours/days) from long historical data series. However, long-term forecasting (several months horizon) performed in radio planning tools relies on short and noisy time series, thus requiring a separate analysis. In this work, we present the first study comparing SL and time series analysis approaches to predict monthly busy-hour data traffic on a cell basis in a live LTE network. To this end, an extensive dataset is collected, comprising data traffic per cell for a whole country during 30 months. The considered methods include Random Forest, different Neural Networks, Support Vector Regression, Seasonal Auto Regressive Integrated Moving Average and Additive Holt–Winters. Results show that SL models outperform time series approaches, while reducing data storage capacity requirements. More importantly, unlike in short-term and medium-term traffic forecasting, non-deep SL approaches are competitive with deep learning while being more computationally efficient.

Sampling estuarine copepods at different scales and resolutions: a study in Rio de la Plata

2018 ◽  
Vol 99 (5) ◽  
pp. 1059-1064 ◽  
Author(s):  
Sourav Paul ◽  
Danilo Calliari
Keyword(s):  
Sampling Effort ◽  
Rio De La Plata ◽  
Population Densities ◽  
Medium Term ◽  
Short Term ◽  
Río De La Plata ◽  
La Plata ◽  
Resource Limitations ◽  
Paracalanus Parvus

AbstractIn the Rio de la Plata salinity, temperature, chlorophyll a (chl a), and densities (ind. m−3) of the copepods Acartia tonsa and Paracalanus parvus were measured from January to November in 2003 by following a nested weekly and monthly design. Such sampling yielded two separate datasets: (i) Yearly Dataset (YD) which consists of data of one sampling effort per month for 11 consecutive months, and (ii) Seasonal Weekly Datasets (SWD) which consists of data of one sampling effort per week of any four consecutive weeks within each season. YD was assumed as a medium-term low-resolution (MTLR) dataset, and SWD as a short-term high-resolution (STHR) dataset. The hypothesis was, the SWD would always capture (shorter scales generally captures more noise in data) more detail variability of copepod populations (quantified through the regression relationships between temporal changes of salinity, temperature, chl a and copepod densities) than the YD. Analysis of both YD and SWD found that A. tonsa density was neither affected by seasonal cycles, nor temporal variability of salinity, temperature and chl a. Thus, compared to STHR sampling, MTLR sampling did not yield any further information of the variability of population densities of the perennial copepod A. tonsa. Analysis of SWD found that during summer and autumn the population densities of P. parvus had a significant positive relationship to salinity but their density was limited by higher chl a concentration; analysis of YD could not yield such detailed ecological information. That hints the effectiveness of STHR sampling over MTLR sampling in capturing details of the variability of population densities of a seasonal copepod species. Considering the institutional resource limitations (e.g. lack of long-term funding, manpower and infrastructure) and the present hypothesis under consideration, the authors suggest that a STHR sampling may provide useful complementary information to interpret results of longer-term natural changes occurring in estuaries.

scholarly journals Towards the best future for humankind: ZIPAR whitepaper.

2018 ◽  
Author(s):  
Marko Kovic ◽  
Christian Caspar ◽  
Adrian Rauchfleisch
Keyword(s):  
Medium Term ◽  
Short Term ◽  
Profound Impact ◽  
Future Challenges ◽  
The Way

Humankind is facing major challenges in the short-term, medium-term, and long-term future. Those challenges will have a profound impact on humankind’s future progress and wellbeing. In this whitepaper, we outline our understanding of humankind’s future challenges, and we describe the way in which we work towards identifying as well as managing them. In doing so, we pursue the overall goal of ZIPAR: We want to make the best future for humankind (ever so slightly) more probable.

scholarly journals Intralymphatic immunotherapy for allergic rhinoconjunctivitis: a systematic review and meta-analysis

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
M.P. Hoang ◽  
K. Seresirikachorn ◽  
W. Chitsuthipakorn ◽  
K. Snidvongs
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Specific Ige ◽  
Allergic Rhinoconjunctivitis ◽  
Medium Term ◽  
Short Term ◽  
Intralymphatic Immunotherapy ◽  
Specific Igg4 ◽  
Igg4 Level

BACKGROUND: Intralymphatic immunotherapy (ILIT) is a new route of allergen-specific immunotherapy. Data confirming its effect is restricted to a small number of studies. METHODOLOGY: A systematic review with meta-analysis was conducted. The short-term (less than 24 weeks), medium-term (24-52 weeks), and long-term (more than 52 weeks) effects of ILIT in patients with allergic rhinoconjunctivitis (ARC) were assessed. The outcomes were combined symptom and medication scores (CSMS), symptoms visual analog scale (VAS), disease-specific quality of life (QOL), specific IgG4 level, specific IgE level, and adverse events. RESULTS: Eleven randomized controlled trials and 2 cohorts (483 participants) were included. Compared with placebo, short term benefits of ILIT for seasonal ARC improved CSMS, improved VAS and increased specific IgG4 level but did not change QOL or specific IgE level. Medium-term effect improved VAS. Data on the long-term benefit of ILIT remain unavailable and require longer term follow-up studies. There were no clinical benefits of ILIT for perennial ARC. ILIT was safe and well-tolerated. CONCLUSION: ILIT showed short-term benefits for seasonal ARC. The sustained effects of ILIT were inconclusive. It was well tolerated.

scholarly journals A Study of Multi-Scale Relationship Between Investor Sentiment and Stock Index Fluctuation Based on the Analysis of BEMD Spillover Index

2021 ◽  
Vol 9 (4) ◽  
pp. 399-420
Author(s):  
Weiguo Chen ◽  
Shufen Zhou ◽  
Yin Zhang ◽  
Yi Sun
Keyword(s):  
Stock Price ◽  
Composite Index ◽  
Investor Sentiment ◽  
Stock Index ◽  
Financial Industry ◽  
Medium Term ◽  
Short Term ◽  
Frequency Components ◽  
Original Scale

Abstract According to behavioral finance theory, investor sentiment generally exists in investors’ trading activities and influences financial market. In order to investigate the interaction between investor sentiment and stock market as well as financial industry, this study decomposed investor sentiment, stock price index and SWS index of financial industry into IMF components at different scales by using BEMD algorithm. Moreover, the fluctuation characteristics of time series at different time scales were extracted, and the IMF components were reconstructed into short-term high-frequency components, medium-term important event low-frequency components and long-term trend components. The short-term interaction between investor sentiment and Shanghai Composite Index, Shenzhen Component Index and financial industries represented by SWS index was investigated based on the spillover index. The time difference correlation coefficient was employed to determine the medium-term and long-term correlation among variables. Results demonstrate that investor sentiment has a strong correlation with Shanghai Composite Index, Shenzhen Component Index and different financial industries represented by SWS index at the original scale, and the change of investor sentiment is mainly influenced by external market information. The interaction between most markets at the short-term scale is weaker than that at the original scale. Investor sentiment is more significantly correlated with SWS Bond, SWS Diversified Finance and Shanghai Composite Index at the long-term scale than that at the medium-term scale.

scholarly journals Design Considerations for the Liquid Air Energy Storage System Integrated to Nuclear Steam Cycle

2021 ◽  
Vol 11 (18) ◽  
pp. 8484
Author(s):  
Seok-Ho Song ◽  
Jin-Young Heo ◽  
Jeong-Ik Lee
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Power Sources

A nuclear power plant is one of the power sources that shares a large portion of base-load. However, as the proportion of renewable energy increases, nuclear power plants will be required to generate power more flexibly due to the intermittency of the renewable energy sources. This paper reviews a layout thermally integrating the liquid air energy storage system with a nuclear power plant. To evaluate the performance realistically while optimizing the layout, operating nuclear power plant conditions are used. After revisiting the analysis, the optimized performance of the proposed system is predicted to achieve 59.96% of the round-trip efficiency. However, it is further shown that external environmental conditions could deteriorate the performance. For the design of liquid air energy storage-nuclear power plant integrated systems, both the steam properties of the linked plants and external factors should be considered.

The Temporal-Spatial Evolution of the Southern Corridor of West-to-East Power Transmission Project in China

2014 ◽  
Vol 521 ◽  
pp. 485-489
Author(s):  
Hong Hao Fu ◽  
Guo Tian Cai ◽  
Dai Qing Zhao
Keyword(s):  
Power Supply ◽  
Power Plants ◽  
Power Transmission ◽  
Market Mechanism ◽  
Power Grids ◽  
Total Power ◽  
Spatial Process ◽  
Market Situation ◽  
Increasing Demand

This paper analyzes temporal and spatial process, and problems based on data between 1986 and 2010. Conclusions are as follows. Power supply of Guangdong relied more on distant outer-province power grids over time, not inner-province ones, close ones or independent power plants. This accelerating enlargement of power supply range could well satisfy its increasing power consumption. However, power production of western provinces couldnt simultaneously meet their own increasing demand and demand by Guangdong. Furthermore, total power transmission and electricity tariff were fixed by long-term framework agreements signed among governments, in which the transmission amount was too much while the tariff was too low, forcing the western provinces limiting their domestic demand without proper compensation. So the current enlarging trend of power supply range of Guangdong is unsustainable and its necessary to introduce power market mechanism through adjusting short-term total power transmission and power tariff according to the market situation.

Retrofitting Offshore Drilling Rigs with Islanded DC Grids and Energy Storage

2021 ◽  
Author(s):  
Stig Settemsdal ◽  
Saverio Ventrelli
Keyword(s):  
Energy Storage ◽  
Power Plant ◽  
Power Plants ◽  
Oil And Gas ◽  
Dynamic Performance ◽  
Wind Farms ◽  
Power Grids ◽  
Offshore Drilling ◽  
Drilling Rig ◽  
Drilling Rigs

Abstract The paper presents a novel approach for modernizing/retrofitting offshore drilling rig power plants with islanded direct current (DC) power grids and energy storage. The concept has been successfully applied on several offshore rigs which are in operation today and is applicable to jack-ups, semi-submersibles, drill ships, as well as other types of marine support vessels for oil and gas platforms and wind farms. The approach aims to enhance the feasibility of leveraging energy storage solutions on offshore drilling rigs and marine vessels by making use of the existing power plant footprint. Unique measures have also been incorporated into the electrical system architecture to ensure that the reliability and safety of the existing alternating current (AC)-based system are not compromised. This enables operators to capitalize on the numerous benefits of energy storage (e.g., reduced emissions, enhanced dynamic performance for drilling and dynamic positioning, etc.) without having to perform a "rip and replace" of the entire power plant and electrical infrastructure.

Evolutionary Stable Strategies for Supply Chains: Selfishness, Fairness, and Altruism

2018 ◽  
Vol 6 (6) ◽  
pp. 532-551 ◽  
Author(s):  
Caichun Chai ◽  
Hailong Zhu ◽  
Zhangwei Feng
Keyword(s):  
Supply Chains ◽  
Evolutionary Dynamics ◽  
Replicator Dynamics ◽  
Management Strategies ◽  
Individual Preference ◽  
Short Term ◽  
Evolutionary Stable Strategies ◽  
Pure Strategies ◽  
The Stability

Abstract The management strategies of a firm are inevitable affected by individual behavior preferences. The effect of individual preference on the evolutionary dynamics for supply chains is studied by employing replicator dynamics. Each firm has three behavior preferences: selfishness, fairness, and altruism. Firstly, the case that the strategy set of manufacturers and retailers including two pure strategies is considered and the effect of preference parameter on the equilibrium outcome in the short-term interaction is discussed. Secondly, the equilibrium state in the short-term is always disturbed because the change of the environment, firm’s structure, and so forth. Using the replicator dynamics, the evolutionary stable strategies of manufacturers and retailers in the long-term interaction are analyzed. Finally, the extend case that the strategy set of manufacturers and retailers include three pure strategies is investigated. These results are found that the strategy profile in which both manufacturer and retailer choose fairness or altruism, or one player chooses fair or altruistic strategy and the other player chooses selfish strategy may be evolutionary stable, the stability of these equilibria depends on the the preference parameters.

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