Proposal of Linear Approximation of Household Fuel Cells and Small-Scale Community Energy Management System

2015 ◽  
Author(s):  
Takaaki Ushioda ◽  
Motomu Toyokawa ◽  
Shigeo Kaneda
Keyword(s):  
Fuel Cells ◽  
Energy Management ◽  
Linear Approximation ◽  
Management System ◽  
Small Scale ◽  
Energy Management System

scholarly journals Secure Communication Modeling for Microgrid Energy Management System: Development and Application

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 68 ◽  
Author(s):  
Taha Selim Ustun ◽  
S. M. Suhail Hussain
Keyword(s):  
Energy Management ◽  
Management System ◽  
Secure Communication ◽  
Storage System ◽  
Distribution Networks ◽  
Cyber Attacks ◽  
Small Scale ◽  
Energy Management System ◽  
Sensitive Information ◽  
Active Components

As the number of active components increase, distribution networks become harder to control. Microgrids are proposed to divide large networks into smaller, more manageable portions. The benefits of using microgrids are multiple; the cost of installation is significantly smaller and renewable energy-based generators can be utilized at a small scale. Due to the intermittent and time dependent nature of renewables, to ensure reliable and continuous supply of energy, it is imperative to create a system that has several generators and storage systems. The way to achieve this is through an energy management system (EMS) that can coordinate all these generators with a storage system. Prior to on-site installation, validation studies should be performed on such controllers. This work presents a standardized communication modeling based on IEC 61850 that is developed for a commercial microgrid controller. Using commercial software, different terminals are set up as intelligent electronic devices (IEDs) and the operation of the EMS is emulated with proper message exchanges. Considering that these messages transmit sensitive information, such as financial transactions or dispatch instructions, securing them against cyber-attacks is very important. Therefore; message integrity, node authentication, and confidentiality features are also implemented according to IEC 62351 guidelines. Real-message exchanges are captured with and without these security features to validate secure operation of standard communication solution.

scholarly journals Microgrid Energy Management System for Residential Microgrid Using an Ensemble Forecasting Strategy and Grey Wolf Optimization

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8489
Author(s):  
Usman Bashir Tayab ◽  
Junwei Lu ◽  
Seyedfoad Taghizadeh ◽  
Ahmed Sayed M. Metwally ◽  
Muhammad Kashif
Keyword(s):  
Energy Management ◽  
Management System ◽  
Ensemble Forecasting ◽  
Small Scale ◽  
Energy Management System ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Scheduling Strategy ◽  
Load Demand ◽  
Microgrid Energy Management

Microgrid (MG) is a small-scale grid that consists of multiple distributed energy resources and load demand. The microgrid energy management system (M-EMS) is the decision-making centre of the MG. An M-EMS is composed of four modules which are known as forecasting, scheduling, data acquisition, and human-machine interface. However, the forecasting and scheduling modules are considered the major modules from among the four of them. Therefore, this paper proposed an advanced microgrid energy management system (M-EMS) for grid-connected residential microgrid (MG) based on an ensemble forecasting strategy and grey wolf optimization (GWO) based scheduling strategy. In the forecasting module of M-EMS, the ensemble forecasting strategy is proposed to perform the short-term forecasting of PV power and load demand. The GWO based scheduling strategy has been proposed in scheduling module of M-EMS to minimize the operating cost of grid-connected residential MG. A small-scale experiment is conducted using Raspberry Pi 3 B+ via the python programming language to validate the effectiveness of the proposed M-EMS and real-time historical data of PV power, load demand, and weather is adopted as inputs. The performance of the proposed forecasting strategy is compared with ensemble forecasting strategy-1, particle swarm optimization based artificial neural network, and back-propagation neural network. The experimental results highlight that the proposed forecasting strategy outperforms the other strategies and achieved the lowest average value of normalized root mean square error of day-ahead prediction of PV power and load demand for the chosen day. Similarly, the performance of GWO based scheduling strategy of M-EMS is analyzed and compared for three different scenarios. Finally, the experimental results prove the outstanding performance of the proposed scheduling strategy.

scholarly journals Energy Management System for Small Scale Hybrid Wind Solar Battery Based Microgrid

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 8336-8345 ◽  
Author(s):  
P. Satish Kumar ◽  
R. P. S. Chandrasena ◽  
V. Ramu ◽  
G. N. Srinivas ◽  
K. Victor Sam Moses Babu
Keyword(s):  
Energy Management ◽  
Management System ◽  
Small Scale ◽  
Energy Management System ◽  
Solar Battery

scholarly journals Smart Microgrid Management: A Hybrid Optimisation Approach

2020 ◽  
Author(s):  
amoura yahia ◽  
Ana Isabel Pereira ◽  
José Lima ◽  
Angela Ferreira ◽  
Fouad Boukli-Hacene ◽  
...  
Keyword(s):  
Energy Management ◽  
Smart City ◽  
Management System ◽  
Renewable Energy Sources ◽  
Market Price ◽  
Inverse Correlation ◽  
Optimization Method ◽  
Electrical Network ◽  
Small Scale ◽  
Energy Management System

Abstract Background: The association of distributed generators, energy storage systems and controllable loads close to the energy consumers gave place to a small-scale electrical network called microgrid. The stochastic behavior of renewable energy sources, as well as the demand variation, can lead in some cases to problems related to the reliability of the microgrid system. On the other hand, the market price of electricity from mainly non-renewable sources becomes a concern for a simple consumer due to its high costs.Method: In this work, an energy management system was developed based on an innovative optimization method, combining linear programming, based on the simplex method, with particle swarm optimisation algorithm. Two scenarios have been proposed to characterise the relation price versus gas emissions for optimal energy management. The objective of this study is to nd the optimal setpoints of generators in a smart city supplied by a microgrid in order to ensure consumer comfort, minimising the emission of greenhouse gases and ensure an appropriate operating price for all smart city consumers. Results: The simulation results have demonstrated the reliability of the optimisation approach on the energy management system in the optimal scheduling of the microgrid generators power ows, having achieved a better energy price compared to a previous study with the same data. Conclusion: The energy management system based on the proposedoptimisation approach gave an inverse correlation between economic and environmental aspects, in fact, a multi-objective optimisation approach is performed as a continuation of the work proposed in this paper.

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