Browse
Submit Data
Databases
API
Help

Dataset Information

31 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A-RESS new dynamic and smart system for renewable energy sharing problem.

ABSTRACT: Energy is at the basis of any social or economic development. The fossil energy is the most used energy source in the world due to the cheap building cost of the power plants. In 2017, fossil fuels generated 64.5% of the world electricity. Since, on the one hand, these plants produce large amount of carbon dioxide which drives climate change, and on the other hand, the storage of existing world fossil resources is in continuous decrease, safer and highly available energy sources should be considered. Hence, for human well-being, and for a green environment, these fossil plants should be switched to cleaner ones. Renewable energy resources have begun to be used as alternatives. These resources have many advantages such as sustainability and environmental protection. Nevertheless, they require higher investment costs. In addition, the reliability of many planted systems is poor. In most cases these systems are not sufficient to ensure a continuous demand of energy for all in needy regions because most of their resources are climate dependent. The main contributions of this research are (i) to propose a natural formalisation of the renewable energy distribution problem, based on COP (Constraint Optimisation Problem), that takes into consideration all the constraints related to this problem; (ii) to propose a novel multi-agent dynamic (A-RESS for Agent based Renewable Energy Sharing System) to solve this problem. The proposed system was implemented and the obtained results show its efficiency and performance in terms of produced, consumed and lost energy.

SUBMITTER: Toumia I

PROVIDER: S-EPMC8279134 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Renewable energy production and demand dataset for the energy system of Colombia.

Project description:During the last decades, an increasing number of studies have focused their attention on the development of energy system models in order to facilitate sustainable energy planning strategies and understand the technical challenges associated with the integration of renewable energy sources. However, these models usually require detailed and large amount of data as inputs. The data presented in this article provides key inputs and modelling assumptions adopted in the research paper titled "Large scale integration of renewable energy sources (RES) in the future Colombian energy system" [1]. These datasets can be used by researchers and policymakers in order to analyse different pathways oriented to the development of low carbon strategies for Colombia and countries with similar energy systems.

| S-EPMC6956762 | biostudies-literature

Sensor Buoy System for Monitoring Renewable Marine Energy Resources.

Project description:In this paper we present a multi-sensor floating system designed to monitor marine energy parameters, in order to sample wind, wave, and marine current energy resources. For this purpose, a set of dedicated sensors to measure the height and period of the waves, wind, and marine current intensity and direction have been selected and installed in the system. The floating device incorporates wind and marine current turbines for renewable energy self-consumption and to carry out complementary studies on the stability of such a system. The feasibility, safety, sensor communications, and buoy stability of the floating device have been successfully checked in real operating conditions.

| S-EPMC5948478 | biostudies-literature

Least cost energy system pathways towards 100% renewable energy in Ireland by 2050.

Project description:Studies focusing on 100% renewable energy systems have emerged in recent years; however, existing studies tend to focus only on the power sector using exploratory approaches. This paper therefore undertakes a whole-system approach and explores optimal pathways towards 100% renewable energy by 2050. The analysis is carried out for Ireland, which currently has the highest share of variable renewable electricity on a synchronous power system. Large numbers of scenarios are developed using the Irish TIMES model to address uncertainties. Results show that compared to decarbonization targets, focusing on renewable penetration without considering carbon capture options is significantly less cost effective in carbon mitigation. Alternative assumptions on bioenergy imports and maximum variability in power generation lead to very different energy mixes in bioenergy and electrification levels. All pathways suggest that indigenous bioenergy needs to be fully exploited and the current annual deployment rate of renewable electricity needs a boost. Pathways relying on international bioenergy imports are slightly cheaper and faces less economic and technical challenges. However, given the large future uncertainties, it is recommended that further policy considerations be given to pathways with high electrification levels as they are more robust towards uncertainties.

| S-EPMC7338272 | biostudies-literature

Triple-renewable energy system for electricity production and water desalination.

Project description:This work presents a novel triple-renewable energy system (TRES) that is based on integrating the photovoltaic panels (PVPs), conventional solar chimney (CSC), and cooling tower (CT) in one structure. The ultimate objective of the proposed TRES system is to produce electrical power (Pelc), desalinated water (Dw), and if required cooling utilities. The components of the system include a chimney tower, collector, base, PVPs, water pool, bi-directional turbine, and water sprinklers. The TRES system can be operated as CSC during the daytime and CT at night providing 24-h operation. The PVPs were integrated within the structure to increase the Pelc production and enhance the process performance by heating the air inside the system. The TRES structure increased the efficiency to 0.860% in comparison with the CSC (0.313%). The annual Pelc production from the TRES system was found to be 792 MWh compared with only 380 MWh generated by the CSC achieving 2.1 folds overall improvement. The CSC-PV and CT contributed to 47% (494 MWh) and 24% (253 MWh) of the Pelc production, respectively. The annual Dw production was found to be 1.2-fold higher (163,142 tons) higher than the CSC (139,443 tons). The newly developed TRES system offers a great potential to produce Pelc and Dw and save fossil fuel consumption while reducing the emissions of greenhouse gasses (GHGs) to the atmosphere.

| S-EPMC10533634 | biostudies-literature

Electricity system based on 100% renewable energy for India and SAARC.

Project description:The developing region of SAARC (South Asian Association for Regional Cooperation) is home to a large number of people living below the poverty line. In future, providing affordable, universally accessible, reliable, low to zero carbon electricity in this region will be the main aim. A cost optimal 100% renewable energy system is simulated for SAARC for the year 2030 on an hourly resolved basis. The region was divided into 16 sub-regions and three different scenarios were set up based on the level of high voltage direct current (HVDC) grid connections. The results obtained for a total system levelised cost of electricity (LCOE) showed a decrease from 71.6 €/MWh in a decentralized to 67.2 €/MWh for a centralized grid connected scenario. An additional scenario was simulated to show the benefits of integrating industrial gas production and seawater reverse osmosis desalination demand, and showed the system cost decreased by 5% and total electricity generation decreased by 1%. The results show that a 100% renewable energy system could be a reality in the SAARC region with the cost assumptions used in this research and it may be more cost competitive than nuclear and fossil carbon capture and storage (CCS) alternatives. One of the limitations of this study is the cost of land for installation of renewables which is not included in the LCOE calculations, but regarded as a minor contribution.

| S-EPMC5516989 | biostudies-literature

A Smart System for the Contactless Measurement of Energy Expenditure.

Project description:Energy Expenditure (EE) (kcal/day), a key element to guide obesity treatment, is measured from CO2 production, VCO2 (mL/min), and/or O2 consumption, VO2 (mL/min). Current technologies are limited due to the requirement of wearable facial accessories. A novel system, the Smart Pad, which measures EE via VCO2 from a room's ambient CO2 concentration transients was evaluated. Resting EE (REE) and exercise VCO2 measurements were recorded using Smart Pad and a reference instrument to study measurement duration's influence on accuracy. The Smart Pad displayed 90% accuracy (±1 SD) for 14-19 min of REE measurement and for 4.8-7.0 min of exercise, using known room's air exchange rate. Additionally, the Smart Pad was validated measuring subjects with a wide range of body mass indexes (BMI = 18.8 to 31.4 kg/m2), successfully validating the system accuracy across REE's measures of ~1200 to ~3000 kcal/day. Furthermore, high correlation between subjects' VCO2 and λ for CO2 accumulation was observed (p < 0.00001, R = 0.785) in a 14.0 m3 sized room. This finding led to development of a new model for REE measurement from ambient CO2 without λ calibration using a reference instrument. The model correlated in nearly 100% agreement with reference instrument measures (y = 1.06x, R = 0.937) using an independent dataset (N = 56).

| S-EPMC8963031 | biostudies-literature

Smart grid energy scheduling based on improved dynamic programming algorithm and LSTM.

Project description:The optimal scheduling of energy in a smart grid is crucial to the energy consumption of the entire grid. In fact, for larger grids, intelligent scheduling may result in substantial energy savings. Herein, we introduce an enhanced dynamic programming algorithm (DPA) that utilizes two state variables to derive the optimal power supply schedule. The algorithm accounts for the dynamic states of both batteries and supercapacitors in the power supply system to augment the performance of the dynamic programming model. Additionally, this study incorporates a long short-term memory (LSTM) deep learning model, which integrates various environmental factors such as temperature, humidity, wind, and precipitation to predict grid power consumption. This serves as a mid-point pre-processing step for smart grid energy consumption scheduling. Our simulation experiments confirm that the proposed method significantly reduces energy consumption, surpassing similar grid energy consumption scheduling algorithms. This is critical for the establishment of smart grids and the reduction of energy consumption and emissions.

| S-EPMC10403179 | biostudies-literature

A near-zero energy system based on a kinetic energy harvester for smart ranch.

Project description:Smart ranch relying on sensor systems to realize monitoring of animals and the environment has emerged with the promotion of the Internet of Things (IoT). This paper proposes a near-zero energy system (NZES) based on a kinetic energy harvester (KEH) for smart ranch. The KEH is based on motion enhancement mechanism (MEM) for kinetic energy recovery from animal movement to realize self-powered applications of smart ranch. The MEM realizes the input and enhancement of weak kinetic energy based on bistable inertial swing. The KEH is analyzed theoretically and experimentally based on cattle leg movement. Under weak excitation (low-frequency and amplitude swing), the maximum voltage growth rate of the KEH based on the MEM reaches 103.7% compared with the linear KEH. The results of application feasibility tests, dressing field experiments, and application outlook show that the KEH has the potential to realize self-powered applications in the NZES of smart ranch.

| S-EPMC9801248 | biostudies-literature

Great Britain's power system with a high penetration of renewable energy: Dataset supporting future scenarios.

Project description:The share of variable renewable energy (VRE) is forecasted to increase in the energy sector to meet decarbonization targets and/or reduce their dependence on fossil fuels. The modeling of future power system scenarios is crucial to assess the role of different flexibility options, including low-carbon technologies. The data presented here support the research article "The role of energy storage in Great Britain's future power system: focus on hydrogen and biomass". These data include updated parameters, inputs, equations, biomass resource potential and biomass demand to balance bio-power and bio-hydrogen requirements. The Future Renewable Energy Performance into the Power System Model (FEPPS), a rule-based model that includes flexibility and stability constraints, has been used, and the hourly results of future scenarios by 2030 and 2040 are provided. Researchers, policymakers, and investors could use this paper as these data provide insights into the role of different technologies (including hydrogen and biomass) in power generation, system flexibility, decarbonization and costs.

| S-EPMC10859255 | biostudies-literature

Dynamic linkages between renewable energy, carbon emissions and economic growth through nonlinear ARDL approach: Evidence from Iran.

Project description:This study examines the relationship between economic growth, renewable energy consumption, and carbon emissions in Iran between 1975-2017, and the bounds testing approach to cointegration and the asymmetric method was used in this study. The results reveal that in the long run increase in renewable energy consumption and CO2 emissions causes an increase in real GDP per capita. Meanwhile, the decrease in renewable energy has the same effect, but GDP per capita reacts more strongly to the rise in renewable energy than the decline. Besides, in the long run, a reduction of CO2 emissions has an insignificant impact on GDP per capita. Furthermore, the results from asymmetric tests suggest that reducing CO2 emissions and renewable energy consumption do not have an essential role in decreasing growth in the short run. In contrast, an increase in renewable energy consumption and CO2 emissions do contribute to boosting the growth. These results may be attributable to the less renewable energy in the energy portfolio of Iran. Additionally, the coefficients on capital and labor are statistically significant, and we discuss the economic implications of the results and propose specific policy recommendations.

| S-EPMC8289101 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data