scholarly journals Smart energy management systems: a literature review

2018 ◽  
Vol 225 ◽  
pp. 01016 ◽  
Author(s):  
N. Loganathan ◽  
P.S. Mayurappriyan ◽  
K. Lakshmi
Keyword(s):  
Literature Review ◽  
Energy Management ◽  
Management Systems ◽  
Technical Approach ◽  
Peak Shaving ◽  
Energy Management Systems ◽  
Smart Energy Management

Recently smart energy management systems (SEMS) have been developed extremely fast. The significant methods facilitate SEMS to sustain system scheming via demand responses, possibly together with peak shaving and load changing as well as a few additional services. This paper reviews the thought of SEMS and looks into its environment. It highlights the SEMS most important apparatus and moderately analyzes a different technical approach. In adding together discuss a number of the concern and challenge as well as suggests a framework for prospect systems.

Role of Cyber-Security in Smart Energy Management Systems

2021 ◽  
pp. 1-18
Author(s):  
Sudhakar Ranjan ◽  
Sarim Moin ◽  
Parikshit Vashist ◽  
Abdus Samad Moin Uddin
Keyword(s):  
Energy Management ◽  
Cyber Security ◽  
Management Systems ◽  
Energy Management Systems ◽  
Smart Energy Management

scholarly journals Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges

2020 ◽  
Vol 12 (20) ◽  
pp. 8495
Author(s):  
Tri-Hai Nguyen ◽  
Luong Vuong Nguyen ◽  
Jason J. Jung ◽  
Israel Edem Agbehadji ◽  
Samuel Ofori Frimpong ◽  
...  
Keyword(s):  
Energy Management ◽  
Smart Grids ◽  
Optimization Problems ◽  
State Of The Art ◽  
Biological Evolution ◽  
Optimization Methods ◽  
Management Systems ◽  
Collective Behaviors ◽  
Energy Management Systems ◽  
Smart Energy Management

Sustainable energy development consists of design, planning, and control optimization problems that are typically complex and computationally challenging for traditional optimization approaches. However, with developments in artificial intelligence, bio-inspired algorithms mimicking the concepts of biological evolution in nature and collective behaviors in societies of agents have recently become popular and shown potential success for these issues. Therefore, we investigate the latest research on bio-inspired approaches for smart energy management systems in smart homes, smart buildings, and smart grids in this paper. In particular, we give an overview of the well-known and emerging bio-inspired algorithms, including evolutionary-based and swarm-based optimization methods. Then, state-of-the-art studies using bio-inspired techniques for smart energy management systems are presented. Lastly, open challenges and future directions are also addressed to improve research in this field.

scholarly journals Analyzing the Improvements of Energy Management Systems for Hybrid Electric Vehicles Using a Systematic Literature Review: How Far Are These Controls from Rule-Based Controls Used in Commercial Vehicles?

2020 ◽  
Vol 10 (23) ◽  
pp. 8744
Author(s):  
Juan P. Torreglosa ◽  
Pablo Garcia-Triviño ◽  
David Vera ◽  
Diego A. López-García
Keyword(s):  
Literature Review ◽  
Energy Management ◽  
Electric Vehicles ◽  
Systematic Literature Review ◽  
Power Flow ◽  
Hybrid Electric Vehicles ◽  
Management Systems ◽  
Rule Based ◽  
Energy Management Systems ◽  
Hybrid Electric

The hybridization of vehicles is a viable step toward overcoming the challenge of the reduction of emissions related to road transport all over the world. To take advantage of the emission reduction potential of hybrid electric vehicles (HEVs), the appropriate design of their energy management systems (EMSs) to control the power flow between the engine and the battery is essential. This work presents a systematic literature review (SLR) of the more recent works that developed EMSs for HEVs. The review is carried out subject to the following idea: although the development of novel EMSs that seek the optimum performance of HEVs is booming, in the real world, HEVs continue to rely on well-known rule-based (RB) strategies. The contribution of this work is to present a quantitative comparison of the works selected. Since several studies do not provide results of their models against commercial RB strategies, it is proposed, as another contribution, to complete their results using simulations. From these results, it is concluded that the improvement of the analyzed EMSs ranges roughly between 5% and 10% with regard to commercial RB EMSs; in comparison to the optimum, the analyzed EMSs are nearer to the optimum than commercial RB EMSs.

Sign in / Sign up

Export Citation Format

Share Document