scholarly journals Semiactive Hybrid Energy Management System: A Solution for Electric Wheelchairs

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 345 ◽  
Author(s):  
Sadam Hussain ◽  
Muhammad Umair Ali ◽  
Sarvar Hussain Nengroo ◽  
Imran Khan ◽  
Muhammad Ishfaq ◽  
...  
Keyword(s):  
Energy Management ◽  
High Power ◽  
Management System ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Energy Management System ◽  
Power Demand ◽  
Normal Medium ◽  
Hybrid Energy

Many disabled people use electric wheelchairs (EWs) in their daily lives. EWs take a considerable amount of time to charge and are less efficient in high-power-demand situations. This paper addresses these two problems using a semiactive hybrid energy storage system (SA-HESS) with a smart energy management system (SEMS). The SA-HESS contained a lithium-ion battery (LIB) and supercapacitor (SC) connected to a DC bus via a bidirectional DC–DC converter. The first task of the proposed SEMS was to charge the SA-HESS rapidly using a fuzzy-logic-controlled charging system. The second task was to reduce the stress of the LIB. The proposed SEMS divided the discharging operation into starting-, normal-, medium-, and high-power currents. The LIB was used in normal conditions, while the SC was mostly utilized during medium-power conditions, such as starting and uphill climbing of the EW. The conjunction of LIB and SC was employed to meet the high-power demand for smooth and reliable operation. A prototype was designed to validate the proposed methodology, and a comparison of the passive hybrid energy management system (P-HESS) and SA-HESS was performed under different driving tracks and loading conditions. The experimental results showed that the proposed system required less charging time and effectively utilized the power of the SC compared with P-HESS.

scholarly journals A Rule Based Energy Management System of Experimental Battery/Supercapacitor Hybrid Energy Storage System for Electric Vehicles

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Qiao Zhang ◽  
Weiwen Deng ◽  
Sumin Zhang ◽  
Jian Wu
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management System ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management System ◽  
Rule Based ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Hybrid Energy Storage System

In this paper, a simple and efficient rule based energy management system for battery and supercapacitor hybrid energy storage system (HESS) used in electric vehicles is presented. The objective of the proposed energy management system is to focus on exploiting the supercapacitor characteristics and on increasing the battery lifetime and system efficiency. The role of the energy management system is to yield battery reference current, which is subsequently used by the controller of the DC/DC converter. First, a current controller is designed to realize load current distribution between battery and supercapacitor. Then a voltage controller is designed to ensure the supercapacitor SOC to fluctuate within a preset reasonable variation range. Finally, a commercial experimental platform is developed to verify the proposed control strategy. In addition, the energy efficiency and the cost analysis of the hybrid system are carried out based on the experimental results to explore the most cost-effective tradeoff.

scholarly journals A Multi-Criteria Computer Package-Based Energy Management System for a Grid-Connected AC Nanogrid

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 487
Author(s):  
Carlos Roncero-Clemente ◽  
Eugenio Roanes-Lozano ◽  
Fermín Barrero-González
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Management System ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management System ◽  
Energy Prices ◽  
Hybrid Energy ◽  
Electric System ◽  
Improved Performance

The electric system scenario has been changing during the last years moving to a distributed system with a high penetration of renewables. Due to the unpredictable behavior of some renewables sources, the development of the energy management system is considered crucial to guarantee the reliability and stability of the system. At the same time, increasing the lifespan of the energy storage system is one of the most important points to take into account. In this sense, a software package implemented in the computer algebra system Maple is proposed in this work to control a grid-connected nanogrid with hybrid energy storage system (composed by batteries and supercapacitors). The energy management system considers several rules as the state of charge of the energy storage system, the photovoltaic power generation and the load profile, the nanogrid power trend and the energy prices. The improved performance of the nanogrid is proven by simulations in MATLAB/Simulink.

scholarly journals A Stochastic MPC Based Energy Management System for Simultaneous Participation in Continuous and Discrete Prosumer-to-Prosumer Energy Markets

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3751
Author(s):  
Pablo Baez-Gonzalez ◽  
Felix Garcia-Torres ◽  
Miguel A. Ridao ◽  
Carlos Bordons
Keyword(s):  
Energy Management ◽  
Management System ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management System ◽  
Bidding Strategies ◽  
Production And Consumption ◽  
Optimal Bidding ◽  
Continuous Trading ◽  
Stochastic Model Predictive Control

This article studies the exchange of self-produced renewable energy between prosumers (and with pure end consumers), through the discrete trading of energy packages and proposes a framework for optimizing this exchange. In order to mitigate the imbalances derived from discrepancies between production and consumption and their respective forecasts, the simultaneous continuous trading of instantaneous power quotas is proposed, giving rise to a time-ahead market running in parallel with a real-time one. An energy management system (EMS) based on stochastic model predictive control (SMPC) simultaneously determines the optimal bidding strategies for both markets, as well as the optimal utilisation of any energy storage system (ESS). Simulations carried out for a heterogeneous group of agents show that those with SMPC-EMS achieve savings of between 3% and 15% in their energy operation economic result. The proposed structures allows the peer-to-peer (P2P) energy trading between end users without ESS and constitute a viable alternative to avoid deviation penalties in secondary regulation markets.

scholarly journals Multi-Objective Fuzzy Logic-Based Energy Management System for Microgrids with Battery and Hydrogen Energy Storage System

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1074 ◽  
Author(s):  
Francisco José Vivas ◽  
Francisca Segura ◽  
José Manuel Andújar ◽  
Adriana Palacio ◽  
Jaime Luis Saenz ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Energy Storage ◽  
Energy Management ◽  
Management System ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management System ◽  
Hydrogen Energy ◽  
Economic Point ◽  
Load Demand

This paper proposes a fuzzy logic-based energy management system (EMS) for microgrids with a combined battery and hydrogen energy storage system (ESS), which ensures the power balance according to the load demand at the time that it takes into account the improvement of the microgrid performance from a technical and economic point of view. As is known, renewable energy-based microgrids are receiving increasing interest in the research community, since they play a key role in the challenge of designing the next energy transition model. The integration of ESSs allows the absorption of the energy surplus in the microgrid to ensure power supply if the renewable resource is insufficient and the microgrid is isolated. If the microgrid can be connected to the main power grid, the freedom degrees increase and this allows, among other things, diminishment of the ESS size. Planning the operation of renewable sources-based microgrids requires both an efficient dispatching management between the available and the demanded energy and a reliable forecasting tool. The developed EMS is based on a fuzzy logic controller (FLC), which presents different advantages regarding other controllers: It is not necessary to know the model of the plant, and the linguistic rules that make up its inference engine are easily interpretable. These rules can incorporate expert knowledge, which simplifies the microgrid management, generally complex. The developed EMS has been subjected to a stress test that has demonstrated its excellent behavior. For that, a residential-type profile in an actual microgrid has been used. The developed fuzzy logic-based EMS, in addition to responding to the required load demand, can meet both technical (to prolong the devices’ lifespan) and economic (seeking the highest profitability and efficiency) established criteria, which can be introduced by the expert depending on the microgrid characteristic and profile demand to accomplish.

scholarly journals Reinforcement Learning Based Energy Management Algorithm for Smart Energy Buildings

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2010 ◽  
Author(s):  
Sunyong Kim ◽  
Hyuk Lim
Keyword(s):  
Reinforcement Learning ◽  
Smart Grid ◽  
Energy Management ◽  
Management System ◽  
Transition Probability ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Costs ◽  
Energy Management System ◽  
Management Algorithm

A smart grid facilitates more effective energy management of an electrical grid system. Because both energy consumption and associated building operation costs are increasing rapidly around the world, the need for flexible and cost-effective management of the energy used by buildings in a smart grid environment is increasing. In this paper, we consider an energy management system for a smart energy building connected to an external grid (utility) as well as distributed energy resources including a renewable energy source, energy storage system, and vehicle-to-grid station. First, the energy management system is modeled using a Markov decision process that completely describes the state, action, transition probability, and rewards of the system. Subsequently, a reinforcement-learning-based energy management algorithm is proposed to reduce the operation energy costs of the target smart energy building under unknown future information. The results of numerical simulation based on the data measured in real environments show that the proposed energy management algorithm gradually reduces energy costs via learning processes compared to other random and non-learning-based algorithms.

Energy management system for stand-alone diesel-wind-biomass microgrid with energy storage system

Energy ◽  
2016 ◽  
Vol 97 ◽  
pp. 90-104 ◽  
Author(s):  
Chengshan Wang ◽  
Yixin Liu ◽  
Xialin Li ◽  
Li Guo ◽  
Lei Qiao ◽  
...  
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Management System ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management System
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