Probability-Based Power Dispatch in Wind-Integrated Electrical Grid for Energy Storage Capacity Determination

2016 ◽  
Author(s):  
Tzu-Chieh Hung ◽  
Kuei-Yuan Chan
Keyword(s):  
Energy Storage ◽  
Wind Energy ◽  
Real Time ◽  
Current Trend ◽  
Electric Utility ◽  
Energy Access ◽  
Short Term ◽  
Power Dispatch ◽  
Time Operation

Implementing microgrids has become a current trend in the electric utility industry to either improve system reliability or energy access for energy sustainability. This study proposes a probability-based strategy for both long- and short-term power dispatch with wind and load uncertainty. The long-term power dispatch is used to determine a suitable capacity of energy storage, and the short-term power dispatch is used for real-time operation. For both short- and long-term power dispatch, the trends of wind energy and electricity demand are extracted using the wavelet packet analysis method and the moving average technique. The uncertainties from wind speed and power generation data are modeled with log-normal and extreme value distributions, respectively. From the obtained power dispatch and model forecasting, the capacity of energy storage is determined. To validate the proposed approach, a real-time operating simulation is used as a case study to observe the behavior of the wind-integrated electrical system. Results show that the proposed method can estimate the uncertainty variation range of wind energy and the state of charge of energy storage effectively.

scholarly journals Home Energy Management for Community Microgrids Using Optimal Power Sharing Algorithm

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1060
Author(s):  
Md Mamun Ur Rashid ◽  
Majed A. Alotaibi ◽  
Abdul Hasib Chowdhury ◽  
Muaz Rahman ◽  
Md. Shafiul Alam ◽  
...  
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Energy Management ◽  
Cost Minimization ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Power Sharing ◽  
Optimal Power ◽  
Time Operation ◽  
Home Energy Management

From a residential point of view, home energy management (HEM) is an essential requirement in order to diminish peak demand and utility tariffs. The integration of renewable energy sources (RESs) together with battery energy storage systems (BESSs) and central battery storage system (CBSS) may promote energy and cost minimization. However, proper home appliance scheduling along with energy storage options is essential to significantly decrease the energy consumption profile and overall expenditure in real-time operation. This paper proposes a cost-effective HEM scheme in the microgrid framework to promote curtailing of energy usage and relevant utility tariff considering both energy storage and renewable sources integration. Usually, the household appliances have different runtime preferences and duration of operation based on user demand. This work considers a simulator designed in the C++ platform to address the domestic customer’s HEM issue based on usages priorities. The positive aspects of merging RESs, BESSs, and CBSSs with the proposed optimal power sharing algorithm (OPSA) are evaluated by considering three distinct case scenarios. Comprehensive analysis of each scenario considering the real-time scheduling of home appliances is conducted to substantiate the efficacy of the outlined energy and cost mitigation schemes. The results obtained demonstrate the effectiveness of the proposed algorithm to enable energy and cost savings up to 37.5% and 45% in comparison to the prevailing methodology.

Optimal Energy Management of Hybrid Power System With Two-Scale Dynamic Programming

2011 ◽  
Author(s):  
Lei Zhang ◽  
Yaoyu Li
Keyword(s):  
Dynamic Programming ◽  
Wind Energy ◽  
Energy Management ◽  
Electricity Price ◽  
Short Term ◽  
Optimal Energy ◽  
Macro Scale ◽  
Optimal Energy Management ◽  
The Impact

Energy management is one of the main issues in operating the HPS, which needs to be optimized with respect to the current and future change in generation, demand, and market price, particularly for HPS with strong renewable penetration. Optimal energy management strategies such as dynamic programming (DP) may become significantly suboptimal under strong uncertainty in prediction of renewable generation and utility price. In order to reduce the impact of such uncertainties, a two-scale dynamic programming scheme is proposed in this study to optimize the operational benefit based on multi-scale prediction. First, a macro-scale dynamic programming (MASDP) is performed for the long term period, based on long term ahead prediction of hourly electricity price and wind energy (speed). The battery state-of-charge (SOC) is thus obtained as the macro-scale reference trajectory. The micro-scale dynamic programming (MISDP) is then applied with a short term interval, based on short term-hour ahead auto-regressive moving average (ARMA) prediction of hourly electricity price and wind energy. The nodal SOC values from the MASDP result are used as the terminal condition for the MISDP. The simulation results show that the proposed method can significantly decrease the operation cost, as compared with the single scale DP method.

scholarly journals Revised criteria system for a national assessment of threatened habitats in Germany

2020 ◽  
Vol 40 ◽  
pp. 39-64 ◽  
Author(s):  
Stefanie Heinze ◽  
Peter Finck ◽  
Ulrike Raths ◽  
Uwe Riecken ◽  
Axel Ssymank
Keyword(s):  
Current Trend ◽  
Reference Value ◽  
Red List ◽  
Habitat Types ◽  
Short Term ◽  
National Assessment ◽  
The Third ◽  
Threatened Habitats ◽  
Threatened Habitat

The Red List of threatened habitat types in Germany was first published in 1994 and it is updated approximately every ten years. In 2017 the third version was published by the German Federal Agency for Nature Conservation. In the course of the revision, the criteria system was also extended. In doing so, an attempt was made to find a compromise between the consideration of international developments that had taken place and existing national requirements. In particular, short-term developments should become visible through the German Red List status. In addition to ‘National long-term Threat’, the valuation now also includes ‘Current Trend’ and ‘Rarity’. Following the IUCN’s approach, the collapse risk is now represented on the basis of several criteria. However, in contrast to the IUCN procedure, where the worst evaluated criterion is determinative for Red List status, in our procedure all criteria are included in the evaluation. To counteract misleading signal-effects for management decisions, all significant criteria have an influence on the resulting German Red List status (RLG). They are combined in an assessment scheme. In order to map the overall risk of loss, both the long-term threat as a historical reference value and furthermore the current trend must have an influence on RLG. As a result, 65% of habitat types have differing risk of loss.

scholarly journals Near-Real-Time Surveillance of Illnesses Related to Shellfish Consumption in British Columbia: Analysis of Poison Center Data (Preprint)

2017 ◽  
Author(s):  
Victoria Wan ◽  
Lorraine McIntyre ◽  
Debra Kent ◽  
Dennis Leong ◽  
Sarah B Henderson
Keyword(s):  
Public Health ◽  
Real Time ◽  
Public Health Surveillance ◽  
Data File ◽  
Health Surveillance ◽  
Poison Control ◽  
Short Term ◽  
Control Data

BACKGROUND Data from poison centers have the potential to be valuable for public health surveillance of long-term trends, short-term aberrations from those trends, and poisonings occurring in near-real-time. This information can enable long-term prevention via programs and policies and short-term control via immediate public health response. Over the past decade, there has been an increasing use of poison control data for surveillance in the United States, Europe, and New Zealand, but this resource still remains widely underused. OBJECTIVE The British Columbia (BC) Drug and Poison Information Centre (DPIC) is one of five such services in Canada, and it is the only one nested within a public health agency. This study aimed to demonstrate how DPIC data are used for routine public health surveillance in near-real-time using the case study of its alerting system for illness related to consumption of shellfish (ASIRCS). METHODS Every hour, a connection is opened between the WBM software Visual Dotlab Enterprise, which holds the DPIC database, and the R statistical computing environment. This platform is used to extract, clean, and merge all necessary raw data tables into a single data file. ASIRCS automatically and retrospectively scans a 24-hour window within the data file for new cases related to illnesses from shellfish consumption. Detected cases are queried using a list of attributes: the caller location, exposure type, reasons for the exposure, and a list of keywords searched in the clinical notes. The alert generates a report that is tailored to the needs of food safety specialists, who then assess and respond to detected cases. RESULTS The ASIRCS system alerted on 79 cases between January 2015 and December 2016, and retrospective analysis found 11 cases that were missed. All cases were reviewed by food safety specialists, and 58% (46/79) were referred to designated regional health authority contacts for follow-up. Of the 42% (33/79) cases that were not referred to health authorities, some were missing follow-up information, some were triggered by allergies to shellfish, and some were triggered by shellfish-related keywords appearing in the case notes for nonshellfish-related cases. Improvements were made between 2015 and 2016 to reduce the number of cases with missing follow-up information. CONCLUSIONS The surveillance capacity is evident within poison control data as shown from the novel use of DPIC data for identifying illnesses related to shellfish consumption in BC. The further development of surveillance programs could improve and enhance response to public health emergencies related to acute illnesses, chronic diseases, and environmental exposures.

Short-term and long-term learners’ motivation modeling in Web-based educational systems

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shahzad Shabbir ◽  
Muhammad Adnan Ayub ◽  
Farman Ali Khan ◽  
Jeffrey Davis
Keyword(s):  
Real Time ◽  
Learning Process ◽  
Educational Systems ◽  
Short Term ◽  
Web Based ◽  
Learner Motivation ◽  
Content Type ◽  
Model Based ◽  
Motivation Model

Purpose Short-term motivation encompasses specific, challenging and attainable goals that develop in the limited timespan. On the other hand, long-term motivation indicates a sort of continuing commitment that is required to complete assigned task. As short-term motivational problems span for a limited period of time, such as a session, therefore, they need to be addressed in real time to keep the learner engaged in the learning process. Similarly, long-term learners’ motivation plays an equally important role to retain the learner in the long run and minimize the risk of dropout. Therefore, the purpose of this study is to incorporate a comprehensive learner motivation model that is based on short-term and long-term aspects of the learners' motivation. This approach enables Web-based educational systems to identify the real-time motivational state of the learner and provide personalized interventions to keep the learners engaged in learning process. Design/methodology/approach Recent research regarding personalized Web-based educational systems demonstrates learner’s motivation to be an essential component of the learning model. This is because of the fact that low motivation results in either students’ less engagement or complete drop out from the learning activities. A learner motivation model is considered to be a set of perceptions and beliefs that the system has developed about a learner. This includes both short-term and long-term motivations of leaners. Findings This study proposed a framework of a domain independent learners’ motivation model based on firm educational theories. The proposed framework consists of two modules. The primary module deals with real-time identification of motivation and logging off activities such as login, forum participation and adherence to assessment deadline. Secondary module maintains the profile of leaners associated with both short-term and long-term motivation. A study was conducted to verify the impact of learners’ motivation model and personalized interventional strategies based on proposed model, using Systematical Information Education Method assessment standards. The results show an increase in motivational index and the characteristics associated with motivation during the conducted study. Originality/value Motivational diagnosis is important for both traditional classrooms and Web-based education systems. It is one of the major elements that contribute in the success of the learning process. However, dropout rate among online students is very high, which leads to incorporate motivational elements in more personalized way because motivated students will retain the course until they successfully complete it. Hence, identifying learner’s motivation, updating learners’ motivation model based on this identification and providing personalized interventions are the key for the success of Web-based educational systems.

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