Voltage control of active MV networks integrating RES and storage units: Advanced algorithm and lab tests

2014 ◽  
Author(s):  
Diana Moneta ◽  
Claudio Carlini ◽  
Giacomo Vigano ◽  
Daniele Stein ◽  
Lilia Consiglio
Keyword(s):  
Voltage Control ◽  
Advanced Algorithm ◽  
And Storage ◽  
Storage Units

scholarly journals Estimation of Energy Activity and Flexibility Range in Smart Active Residential Building

Smart Cities ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 471-495
Author(s):  
Viktor Stepaniuk ◽  
Jayakrishnan Pillai ◽  
Birgitte Bak-Jensen ◽  
Sanjeevikumar Padmanaban
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Storage Tank ◽  
Residential Buildings ◽  
Renewable Energy Sources ◽  
Hot Water ◽  
Active Management ◽  
Worst Case ◽  
And Storage ◽  
Storage Units

The smart active residential buildings play a vital role to realize intelligent energy systems by harnessing energy flexibility from loads and storage units. This is imperative to integrate higher proportions of variable renewable energy generation and implement economically attractive demand-side participation schemes. The purpose of this paper is to develop an energy management scheme for smart sustainable buildings and analyze its efficacy when subjected to variable generation, energy storage management, and flexible demand control. This work estimate the flexibility range that can be reached utilizing deferrable/controllable energy system units such as heat pump (HP) in combination with on-site renewable energy sources (RESs), namely photovoltaic (PV) panels and wind turbine (WT), and in-house thermal and electric energy storages, namely hot water storage tank (HWST) and electric battery as back up units. A detailed HP model in combination with the storage tank is developed that accounts for thermal comforts and requirements, and defrost mode. Data analytics is applied to generate demand and generation profiles, and a hybrid energy management and a HP control algorithm is developed in this work. This is to integrate all active components of a building within a single complex-set of energy management solution to be able to apply demand response (DR) signals, as well as to execute all necessary computation and evaluation. Different capacity scenarios of the HWST and battery are used to prioritize the maximum use of renewable energy and consumer comfort preferences. A flexibility range of 22.3% is achieved for the scenario with the largest HWST considered without a battery, while 10.1% in the worst-case scenario with the smallest HWST considered and the largest battery. The results show that the active management and scheduling scheme developed to combine and prioritize thermal, electrical and storage units in buildings is essential to be studied to demonstrate the adequacy of sustainable energy buildings.

scholarly journals Assessing the efficiency of different CSO positions based on network graph characteristics

2013 ◽  
Vol 67 (7) ◽  
pp. 1574-1580 ◽  
Author(s):  
R. Sitzenfrei ◽  
C. Urich ◽  
M. Möderl ◽  
W. Rauch
Keyword(s):  
Treatment Plant ◽  
Spatial Layout ◽  
Construction Costs ◽  
Sewer Systems ◽  
Significant Difference ◽  
Combined Sewer ◽  
The Impact ◽  
And Storage ◽  
Storage Units ◽  
Sewer Networks

The technical design of urban drainage systems comprises two major aspects: first, the spatial layout of the sewer system and second, the pipe-sizing process. Usually, engineers determine the spatial layout of the sewer network manually, taking into account physical features and future planning scenarios. Before the pipe-sizing process starts, it is important to determine locations of possible weirs and combined sewer overflows (CSOs) based on, e.g. distance to receiving water bodies or to a wastewater treatment plant and available space for storage units. However, positions of CSOs are also determined by topological characteristics of the sewer networks. In order to better understand the impact of placement choices for CSOs and storage units in new systems, this work aims to determine case unspecific, general rules. Therefore, based on numerous, stochastically generated virtual alpine sewer systems of different sizes it is investigated how choices for placement of CSOs and storage units have an impact on the pipe-sizing process (hence, also on investment costs) and on technical performance (CSO efficiency and flooding). To describe the impact of the topological positions of these elements in the sewer networks, graph characteristics are used. With an evaluation of 2,000 different alpine combined sewer systems, it was found that, as expected, with CSOs at more downstream positions in the network, greater construction costs and better performance regarding CSO efficiency result. At a specific point (i.e. topological network position), no significant difference (further increase) in construction costs can be identified. Contrarily, the flooding efficiency increases with more upstream positions of the CSOs. Therefore, CSO and flooding efficiency are in a trade-off conflict and a compromise is required.

scholarly journals Framework for efficient transformation for complex medical data for improving analytical capability

2020 ◽  
Vol 10 (5) ◽  
pp. 4853
Author(s):  
Chandru A. S. ◽  
Seetharam K.
Keyword(s):  
Cloud Storage ◽  
Medical Data ◽  
Structured Data ◽  
Healthcare Sector ◽  
Technological Advancement ◽  
Processing And Storage ◽  
Conventional Manner ◽  
And Storage ◽  
Analytical Operation ◽  
Storage Units

The adoption of various technological advancement has been already adopted in the area of healthcare sector. This adoption facilitates involuntary generation of medical data that can be autonomously programmed to be forwarded to a destined hub in the form of cloud storage units. However, owing to such technologies there is massive formation of complex medical data that significantly acts as an overhead towards performing analytical operation as well as unwanted storage utilization. Therefore, the proposed system implements a novel transformation technique that is capable of using a template based stucture over cloud for generating structured data from highly unstructured data in a non-conventional manner. The contribution of the propsoed methodology is that it offers faster processing and storage optimization. The study outcome also proves this fact to show propsoed scheme excels better in performance in contrast to existing data transformation scheme.

scholarly journals Accelerated Thermal Aging of Bio-Based Composite Wood Panels

Fibers ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 32
Author(s):  
Brent Tisserat ◽  
Nicholas Montesdeoca ◽  
Veera M. Boddu
Keyword(s):  
Thermal Aging ◽  
Extreme Temperatures ◽  
Soybean Flour ◽  
Wood Panels ◽  
Wood Particles ◽  
Composite Wood ◽  
And Storage ◽  
Storage Units ◽  
Accelerated Thermal Aging

Bio-based adhesives and resins are sought as alternatives to synthetics in order to fabricate all-biobased composite wood panels (CWPs), which provide environmentally friendly building products for indoor use. Very little information exists as to how these bio-based CWPs would perform long-term in non-temperature controlled structures such as warehouses and storage units where extreme temperatures occur depending on the season. In this study, novel all-bio-based CWPs were fabricated using a matrix of 50% distiller’s dried grains with solubles (DDGS) and 50% soybean flour ProsanteTM (PRO) mixed with wood particles. Bio-based CWPs were subjected to accelerated thermal aging for a 10-year period resembling outdoor temperatures in Peoria, IL USA. Four seasonal periods (Winter, Spring, Summer, and Fall) were simulated varying from −26–40 °C and 36–76% relative humidity (RH). The bio-based adhesive employed consisted of 50% distiller’s dried grains with solubles (DDGS) and 50% soybean flour ProsanteTM (PRO). CWPs consisted of 15 or 50% DDGS/PRO with 85% or 50% pine wood. CWPs were evaluated for 5, 7.5, and 10-years for their physical, flexural, dimensional stability, surface roughness, FTIR, TGA, and spectral properties. The changes in the CWP properties were notable during the initial 5 years, and later aged samples showed less change.

Distributed Data Mining

2009 ◽  
pp. 157-164 ◽  
Author(s):  
Grigorios Tsoumakas ◽  
Ioannis Vlahavas
Keyword(s):  
Distributed Data Mining ◽  
The Internet ◽  
Distributed Data ◽  
Distributed Environment ◽  
Earth Observing System ◽  
Information And Communication ◽  
Computing Environments ◽  
And Storage ◽  
Different Sources ◽  
Storage Units

The continuous developments in information and communication technology have recently led to the appearance of distributed computing environments, which comprise several, and different sources of large volumes of data and several computing units. The most prominent example of a distributed environment is the Internet, where increasingly more databases and data streams appear that deal with several areas, such as meteorology, oceanography, economy and others. In addition the Internet constitutes the communication medium for geographicallydistributed information systems, as for example the earth observing system of NASA (eos.gsfc.nasa.gov). Other examples of distributed environments that have been developed in the last few years are sensor networks for process monitoring and grids where a large number of computing and storage units are interconnected over a highspeed network.

scholarly journals Concurrent Voltage Control and Dispatch of Active Distribution Networks by Means of Smart Transformer and Storage

2018 ◽  
Vol 65 (8) ◽  
pp. 6657-6666 ◽  
Author(s):  
Xiang Gao ◽  
Fabrizio Sossan ◽  
Konstantina Christakou ◽  
Mario Paolone ◽  
Marco Liserre
Keyword(s):  
Voltage Control ◽  
Distribution Networks ◽  
And Storage ◽  
Active Distribution Networks
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