Optimal energy management in the smart microgrid considering the electrical energy storage system and the demand-side energy efficiency program

Dorahaki, Sobhan; Dashti, Rahman; Shaker, Hamid Reza

doi:10.1016/j.est.2020.101229

Cited by 51 publications

(28 citation statements)

References 26 publications

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“…Energy storage also emerges as a critical resource for microgrid (MG) energy management [2] offering services such as increased self-consumption of RES-based generation and energy arbitrage [3], which benefit the MG owners. Following a decrease in the battery cost [4], the installation of behindthe-meter battery energy storages (BESs) has increased [3], signifying their value in reducing the building electricity cost.…”

Section: A Background and Motivationmentioning

confidence: 99%

Market-Based Energy Management Model of a Building Microgrid Considering Battery Degradation

Antoniadou-Plytaria

Steen

Tuấn

et al. 2021

IEEE Trans. Smart Grid

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Section: A Background and Motivationmentioning

confidence: 99%

Market-Based Energy Management Model of a Building Microgrid Considering Battery Degradation

Antoniadou-Plytaria

Steen

Tuấn

et al. 2021

IEEE Trans. Smart Grid

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“…At present, the short-term scheduling methods that consider the distribution of renewable energy output forecast errors mainly include the random planning method based on chance constraints, the scene reduction method based on sampling technology, and the point estimation method. Among them, the scene reduction method uses the scene reduction technology to transform large number of scenarios to perform scheduling analysis for countable typical static scenarios; point estimation law analyzes by calculating probability statistics of random function values composed of multiple random variables [79,80].…”

Section: Optimization Of Tes Microgrid Energy Managementmentioning

confidence: 99%

A Review on Thermal Energy Modelling for Optimal Microgrids Management

Yan

Wang

Lai

et al. 2021

Thermo

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Microgrids have become increasingly popular in recent years due to technological improvements, growing recognition of their benefits, and diminishing costs. By clustering distributed energy resources, microgrids can effectively integrate renewable energy resources in distribution networks and satisfy end-user demands, thus playing a critical role in transforming the existing power grid to a future smart grid. There are many existing research and review works on microgrids. However, the thermal energy modelling in optimal microgrid management is seldom discussed in the current literature. To address this research gap, this paper presents a detailed review on the thermal energy modelling application on the optimal energy management for microgrids. This review firstly presents microgrid characteristics. Afterwards, the existing thermal energy modeling utilized in microgrids will be discussed, including the application of a combined cooling, heating and power (CCHP) and thermal comfort model to form virtual energy storage systems. Current trial programs of thermal energy modelling for microgrid energy management are analyzed and some challenges and future research directions are discussed at the end. This paper serves as a comprehensive review to the most up-to-date thermal energy modelling applications on microgrid energy management.

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“…A smart power distribution system consists of different units such as a smart protection unit [5], a smart energy management unit [6], a demand response aggregator unit [7] and a smart outage management unit [8]. The smart outage management unit is one of the important units in the smart power distribution system.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Equation (6) shows that the sum of the DG output power and transmission power should be equal to the demand in each time interval. The capacity of the distribution lines is limited to P max Line .…”

Section: The Second Stagementioning

confidence: 99%

Optimal Outage Management Model Considering Emergency Demand Response Programs for a Smart Distribution System

2020

Self Cite

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In this paper, a novel smart outage management system considering Emergency Demand Response Programs (EDRPs) and Distributed Generations (DGs) denoted as SOMSDGsEDRPs is proposed. The EDRPs are provided to decrease the cost of load shading in a time of emergency. The objective function of the problem is proposed to minimize the load shading cost, the DG dispatch cost, the demand response cost and the repair dispatch time for crews. The SOMSDGsDERPs solves an optimization problem that is formulated as Mixed Integer Linear Programming (MILP) taking into account the grid topology constraints, EDRP constraints, DG constraints and crew constraints. The MILP formulation was demonstrated in the GAMS software and solved with the CPLEX solver. The proposed method was tested on the IEEE 34 bus test system as well as an actual Iranian 66 bus power distribution feeder. The results show that the EDRPs and DGs can be effective in decreasing the outage cost and increasing the served load of the distribution power system in a crisis time.

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Optimal energy management in the smart microgrid considering the electrical energy storage system and the demand-side energy efficiency program

Cited by 51 publications

References 26 publications

Market-Based Energy Management Model of a Building Microgrid Considering Battery Degradation

Market-Based Energy Management Model of a Building Microgrid Considering Battery Degradation

A Review on Thermal Energy Modelling for Optimal Microgrids Management

Optimal Outage Management Model Considering Emergency Demand Response Programs for a Smart Distribution System

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