VIMSEN — New energy management tool for RES aggregators

2016 ◽  
Author(s):  
Ganesh Sauba ◽  
Jos van der Burgt ◽  
Manos Varvarigos ◽  
Prodromos Makris ◽  
Ioannis Mamounakis ◽  
...  
Keyword(s):  
Energy Management ◽  
Management Tool ◽  
New Energy

scholarly journals MODELO DE GESTIÓN DE ENERGÍA ELÉCTRICA DOMICILIARIA: PROPUESTA PRELIMINAR

2015 ◽  
Vol 6 (1) ◽  
pp. 95 ◽  
Author(s):  
Adriana Marcela Vega ◽  
Francisco Santamaria Piedrahita ◽  
Edwin Rivas Trujillo
Keyword(s):  
Energy Efficiency ◽  
Energy Management ◽  
Communication Protocols ◽  
Management Tool ◽  
Management Model ◽  
Conceptual Approach ◽  
Home Management ◽  
Home Energy Management ◽  
Toma De Decisiones ◽  
Monitoring Protocols

Se propone una aproximación conceptual de un modelo de gestión de energía en el hogar, denominado GEDE (Gestión de Energía Eléctrica Domiciliaria), el cual tiene como fin principal contribuir con la eficiencia energética domiciliaria; el modelo involucra protocolos de comunicación, infraestructura y software como herramienta de gestión para la toma de decisiones energéticas, relacionadas con el consumo y/o generación de energía eléctrica por parte del usuario final residencial.Home energy management model: preliminary proposalAbstract A conceptual approach of a home energy management model called GEDE (acronym in Spanish), which mainly aims at contributing to the domiciliary energy efficiency is proposed; The model involves communication protocols, infrastructure and software as a management tool for making energy decisions related to consumption and / or generation of electricity from the residential end user.Keywords: domotic, monitoring, protocols, home management, software.

Smart Software Applications for a Low Carbon Economy

2011 ◽  
pp. 506-512
Author(s):  
Aditya Bates
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Energy Management ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Software Applications ◽  
World Energy ◽  
New Energy ◽  
User Groups ◽  
Carbon Economy

There are changes underway in the world energy and power systems because of climate change, which will result in smart and intelligent infrastructure for the new energy management and power system. Smart grid software will play an important part in making this new infrastructure intelligent. This chapter investigates software applications that have a potential to be developed for a new low carbon economy. In addition, this paper explains what the standard bodies and user groups driving the development of these new smart software applications. The chapter will also discuss the control points where software can be added to smart grid infrastructure for a low carbon economy.

Development of new energy management strategy for a household fuel cell/battery hybrid system

2019 ◽  
Vol 43 (9) ◽  
pp. 4686-4700 ◽  
Author(s):  
Kai Ou ◽  
Wei‐Wei Yuan ◽  
Mihwa Choi ◽  
Jungsuk Kim ◽  
Young‐Bae Kim
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Hybrid System ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
New Energy

scholarly journals A Novel Energy Management Strategy for a Ship’s Hybrid Solar Energy Generation System Using a Particle Swarm Optimization Algorithm

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1380 ◽  
Author(s):  
Rui Yang ◽  
Yupeng Yuan ◽  
Rushun Ying ◽  
Boyang Shen ◽  
Teng Long
Keyword(s):  
Solar Energy ◽  
Energy Management ◽  
Optimization Algorithm ◽  
Management Strategy ◽  
Energy System ◽  
Generation System ◽  
Energy Management Strategy ◽  
Swarm Optimization ◽  
Multi Objective ◽  
New Energy

Due to the pressures caused by the energy crisis, environmental pollution, and international regulations, the largest ship-producing nations are exploring renewable resources, such as wind power, solar energy, and fuel cells to save energy and develop more environmentally-friendly ships. Solar energy has recently attracted a great deal of attention from both academics and practitioners; furthermore, the optimization of energy management has become a research topic of great interest. This paper takes a solar-diesel hybrid ship with 5000 car spaces as its research object. Then, following testing on this ship, experimental data were obtained, a multi-objective optimization model related to the ship’s fuel economy and diesel generator’s efficiency was established, and a partial swarm optimization algorithm was used to solve a multi-objective problem. The results show that the optimized energy management strategy for a hybrid energy system should be tested under different electrical loads. Moreover, the hybrid system’s economy should be taken into account when the ship’s power load is high, and the output power from the new energy generation system should be increased as much as possible. Finally, the diesel generators’ efficiency should be taken into consideration when the ship’s electrical load is low, and the injection power of the new energy system should be reduced appropriately.

scholarly journals A New Energy Management Technique for PV/Wind/Grid Renewable Energy System

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Onur Ozdal Mengi ◽  
Ismail Hakki Altas
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Management System ◽  
Energy System ◽  
Management Technique ◽  
Solar Panels ◽  
Power Requirement ◽  
Power Sources ◽  
Power Bus ◽  
New Energy

An intelligent energy management system (IEMS) for maintaining the energy sustainability in renewable energy systems (RES) is introduced here. It consists of wind and photovoltaic (PV) solar panels are established and used to test the proposed IEMS. Since the wind and solar sources are not reliable in terms of sustainability and power quality, a management system is required for supplying the load power demand. The power generated by RES is collected on a common DC bus as a renewable green power pool to be used for supplying power to loads. The renewable DC power bus is operated in a way that there is always a base power available for permanent loads. Then the additional power requirement is supplied from either wind or PV or both depending upon the availability of these power sources. The decision about operating these systems is given by an IEMS with fuzzy logic decision maker proposed in this study. Using the generated and required power information from the wind/PV and load sides, the fuzzy reasoning based IEMS determines the amount of power to be supplied from each or both sources. Besides, the IEMS tracks the maximum power operating point of the wind energy system.

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