SDN-based energy management scheme for sustainability of data centers: An analysis on renewable energy sources and electric vehicles participation

2018 ◽  
Vol 117 ◽  
pp. 228-245 ◽  
Author(s):  
Gagangeet Singh Aujla ◽  
Neeraj Kumar
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Electric Vehicles ◽  
Data Centers ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Management Scheme

scholarly journals Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4240 ◽  
Author(s):  
Khairy Sayed ◽  
Ahmed G. Abo-Khalil ◽  
Ali S. Alghamdi
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Solar Pv ◽  
Dc Microgrid ◽  
Charging Station ◽  
And Control ◽  
Ev Charging

This paper introduces an energy management and control method for DC microgrid supplying electric vehicles (EV) charging station. An Energy Management System (EMS) is developed to manage and control power flow from renewable energy sources to EVs through DC microgrid. An integrated approach for controlling DC microgrid based charging station powered by intermittent renewable energies. A wind turbine (WT) and solar photovoltaic (PV) arrays are integrated into the studied DC microgrid to replace energy from fossil fuel and decrease pollution from carbon emissions. Due to the intermittency of solar and wind generation, the output powers of PV and WT are not guaranteed. For this reason, the capacities of WT, solar PV panels, and the battery system are considered decision parameters to be optimized. The optimized design of the renewable energy system is done to ensure sufficient electricity supply to the EV charging station. Moreover, various renewable energy technologies for supplying EV charging stations to improve their performance are investigated. To evaluate the performance of the used control strategies, simulation is carried out in MATLAB/SIMULINK.

Energy Management of Microgrid Considering Renewable Energy Sources and Electric Vehicles Using the Backtracking Search Optimization Algorithm

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Yong Li ◽  
Salim Qadir Mohammed ◽  
Goran Saman Nariman ◽  
Nahla Aljojo ◽  
Alireza Rezvani ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Energy Sources ◽  
Management Problem ◽  
Backtracking Search ◽  
Search Optimization ◽  
The Impact

Abstract Different distributed generation (DG) technologies, active loads, and storage devices create an independent microgrid (MG). Scheduling of an MG is an important issue in renewable energy sources (RESs) based systems. In this paper, MGs include RESs, plug-in hybrid electric vehicles (PHEVs), and electrical energy storage systems. The proposed scheduling framework utilizes the Monte Carlo simulation (MCS) to characterize the uncertain parameters of PHEVs and RESs. Three different charging strategies are investigated for modeling the impact of different behaviors of PHEVs in MGs. These schemes are smart, controlled, and uncontrolled charging. Due to the nonlinear feature of the suggested optimization problem, it needs an efficient optimization tool to tackle the problem appropriately. So, this paper uses the backtracking search optimization (BSO) algorithm for the short-term scheduling of an MG. The proper performance of the offered scheme is investigated in two scenarios with different time horizons. The BSO algorithm and other optimization algorithms are used for comparing the results to verify the presented method in solving the energy management problem of the MGs.

scholarly journals The Energy System of an Ecovillage: Barriers and Enablers

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 682
Author(s):  
Zita Szabó ◽  
Viola Prohászka ◽  
Ágnes Sallay
Keyword(s):  
Renewable Energy ◽  
Spatial Structure ◽  
Energy Management ◽  
Energy Production ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Energy Sources ◽  
Energy Management System ◽  
Production And Consumption ◽  
Ecologically Sustainable

Nowadays, in the context of climate change, efficient energy management and increasing the share of renewable energy sources in the energy mix are helping to reduce greenhouse gases. In this research, we present the energy system and its management and the possibilities of its development through the example of an ecovillage. The basic goal of such a community is to be economically, socially, and ecologically sustainable, so the study of energy system of an ecovillage is especially justified. As the goal of this community is sustainability, potential technological and efficiency barriers to the use of renewable energy sources will also become visible. Our sample area is Visnyeszéplak ecovillage, where we examined the energy production and consumption habits and possibilities of the community with the help of interviews, literature, and map databases. By examining the spatial structure of the settlement, we examined the spatial structure of energy management. We formulated development proposals that can make the community’s energy management system more efficient.

Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohamad Nassereddine
Keyword(s):  
Machine Learning ◽  
Renewable Energy ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Power Network ◽  
Network Stability ◽  
Fast Charging ◽  
Electrical Loads ◽  
Charging Stations

AbstractRenewable energy sources are widely installed across countries. In recent years, the capacity of the installed renewable network supports large percentage of the required electrical loads. The relying on renewable energy sources to support the required electrical loads could have a catastrophic impact on the network stability under sudden change in weather conditions. Also, the recent deployment of fast charging stations for electric vehicles adds additional load burden on the electrical work. The fast charging stations require large amount of power for short period. This major increase in power load with the presence of renewable energy generation, increases the risk of power failure/outage due to overload scenarios. To mitigate the issue, the paper introduces the machine learning roles to ensure network stability and reliability always maintained. The paper contains valuable information on the data collection devises within the power network, how these data can be used to ensure system stability. The paper introduces the architect for the machine learning algorithm to monitor and manage the installed renewable energy sources and fast charging stations for optimum power grid network stability. Case study is included.

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