Embedding energy storage for multi-energy microgrid optimal operation

2017 ◽  
Author(s):  
Benedetto Aluisio ◽  
Maria Dicorato ◽  
Giuseppe Forte ◽  
Michele Trovato
Keyword(s):  
Energy Storage ◽  
Optimal Operation ◽  
Embedding Energy

scholarly journals Dynamic Operation Management of a Renewable Microgrid including Battery Energy Storage

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Shaozhen Jin ◽  
Zhizhong Mao ◽  
Hongru Li ◽  
Wenhai Qi
Keyword(s):  
Dynamic Programming ◽  
Energy Storage ◽  
Renewable Energy Sources ◽  
Main Idea ◽  
Optimal Operation ◽  
Optimal Control Strategy ◽  
Programming Technique ◽  
Battery Energy Storage ◽  
Comparison Results ◽  
Battery Energy

In this paper, a novel dynamic programming technique is presented for optimal operation of a typical renewable microgrid including battery energy storage. The main idea is to use the scenarios analysis technique to proceed the uncertainties related to the available output power of wind and photovoltaic units and dynamic programming technique to obtain the optimal control strategy for a renewable microgrid system in a finite time period. First, to properly model the system, a mathematical model including power losses of the renewable microgrid is established, where the uncertainties due to the fluctuating generation from renewable energy sources are considered. Next, considering the dynamic power constraints of the battery, a new performance index function is established, where the Lagrange multipliers and interior point method will be presented for the equality and inequality operation constraints. Then, a feedback control scheme based on the dynamic programming is proposed to solve the model and obtain the optimal solution. Finally, simulation and comparison results are given to illustrate the performance of the presented method.

scholarly journals Optimal operation of a hybrid-energy microgrid with energy storage system

2019 ◽  
Vol 138 ◽  
pp. 01003 ◽  
Author(s):  
Mohamed Elgamal ◽  
Nikolay V. Korovkin ◽  
Ahmed Refaat ◽  
Akram Elmitwally
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Storage System ◽  
Bat Algorithm ◽  
Energy Storage System ◽  
Optimal Operation ◽  
Rule Base ◽  
Hybrid Energy ◽  
Management Scheme ◽  
Management Optimization

In this paper, a day-ahead profit-maximizing energy management scheme for a grid-tied microgrid operation is proposed. The microgrid contains various types of distributed energy resources (DERs) and an inverter-interfaced battery-bank storage system. The average of day-ahead hourly forecasted data for loads, wind speed, and solar radiation are inputted into the framework of energy management (EMF). To optimize the microgrid performance, EMF determines the hourly dispatch of reactive and active power for each DER. Also, it specifies the discharging and charging times of the energy storage system and the onload tap changer position setting of the transformer connected to the main grid. The main aim is to maximize the revenue of microgrid meeting all technical limitations. The main grid can sell/buy reactive and active powers to/from the microgrid with a variable daily energy price of the market. A collective rule base-BAT algorithm is implemented as a solver of the energy management optimization problem for a grid-tided microgrid. Furthermore, the ability of the suggested EMF is proved in comparison with recent approaches.

scholarly journals Enhanced Intelligent Energy Management System for a Renewable Energy-Based AC Microgrid

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3268
Author(s):  
Mehdi Dhifli ◽  
Abderezak Lashab ◽  
Josep M. Guerrero ◽  
Abdullah Abusorrah ◽  
Yusuf A. Al-Turki ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Energy Management ◽  
Management System ◽  
Optimal Operation ◽  
Green Energy ◽  
Energy Management System ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Ac Microgrid

This paper proposes an enhanced energy management system (EEMS) for a residential AC microgrid. The renewable energy-based AC microgrid with hybrid energy storage is broken down into three distinct parts: a photovoltaic (PV) array as a green energy source, a battery (BT) and a supercapacitor (SC) as a hybrid energy storage system (HESS), and apartments and electric vehicles, given that the system is for residential areas. The developed EEMS ensures the optimal use of the PV arrays’ production, aiming to decrease electricity bills while reducing fast power changes in the battery, which increases the reliability of the system, since the battery undergoes fewer charging/discharging cycles. The proposed EEMS is a hybrid control strategy, which is composed of two stages: a state machine (SM) control to ensure the optimal operation of the battery, and an operating mode (OM) for the best operation of the SC. The obtained results show that the EEMS successfully involves SC during fast load and PV generation changes by decreasing the number of BT charging/discharging cycles, which significantly increases the system’s life span. Moreover, power loss is decreased during passing clouds phases by decreasing the power error between the extracted power by the sources and the required equivalent; the improvement in efficiency reaches 9.5%.

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